DOI: 10.3897/jucs.164654

Authors: Wolfram Luther, A. J. Han Vinck

Abstract: This volume presents a conference paper selection from the 4th Workshop on Collaborative Technologies and Data Science in Smart City Applications (CODASSCA 2024): Data Science and Reliable Machine Learning, held in Yerevan, Armenia, October 3-6, 2024, https://codassca2024.aua.am/. The special issues guest editors invited five groups of authors from Armenia, Chile, Germany, the UK, and the USA to submit enlarged versions of their CODASSCA 2024 papers There was also a J.UCS open call so that any author could submit papers on the highlighted subjects. The invitation to review the 16 contributions received was accepted by 16 experts, and, after three rounds, seven articles were finally accepted for publication in the special issue.

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DOI: 10.3897/jucs.97822

Authors: Herminia Beatriz Parra de Gallo, Marcela Vegetti

Abstract: This paper shows the research conducted to respond to a continuous requirement of justice regarding the application of scientifically supported forensic tools. Considering ontological engineering as the appropriate framework to respond to this requirement, the article presents OntoFoCE (Spanish abbreviation for Ontology for Electronic Mail Forensics), a specific ontology for the forensic analysis of emails. The purpose of this ontology is to help the computer expert in the validation of an email presented as judicial evidence. OntoFoCE is the fundamental component of the ObE Forensics (Ontology-based Email Forensics) tool. Although there are numerous forensic tools to analyze emails, the originality of the one proposed here lies in the implementation of semantic technologies to represent the traceability of the email transmission process. From that point on, it is possible to provide answers to the items of digital evidence subject to the expert examination. These answers make it possible to support these evidence items in the forensic analysis of an email and to guarantee the gathering of scientifically and technically accepted results that are valid for justice. Thus, the research question that is tried to be answered is: Is it possible to apply ontological engineering as a scientific support to design and develop a forensic tool that allows automatic answers to the evidence items subject to the expert examination in the forensic analysis of emails?

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DOI: 10.3897/jucs.101550

Authors: Anita Herrera, Ángel Arroyo, Alfredo Jiménez, Álvaro Herrero

Abstract: The analysis of Artificial Intelligence techniques and models used in the tourism sector provides insightful information for the management and innovation of this industry. In this paper, we conduct a comprehensive review of the different techniques and models, in regards to Artificial Intelligence when applied to the tourism industry. Specifically, we present a categorization of Artificial Intelligence applications used in different areas of tourism. The results allow to recognize valid studies and useful tools for the activation and growth of the tourism sector, an industry that represents a significant increase in the Gross Domestic Product of various economies and supports the development of life conditions for their inhabitants. Artificial Intelligence applications generate more personalized travel experiences, improve the efficiency of tourism services and strengthen the tourism competitiveness of the destination.

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DOI: 10.3897/jucs.93533

Authors: Kashif Mehboob Khan, Warda Haider, Najeed Ahmed Khan, Darakhshan Saleem

Abstract: The amount of data is increasing rapidly as more and more devices are being linked to the Internet. Big data has a variety of uses and benefits, but it also has numerous challenges associated with it that are required to be resolved to raise the caliber of available services, including data integrity and security, analytics, acumen, and organization of Big data. While actively seeking the best way to manage, systemize, integrate, and affix Big data, we concluded that blockchain methodology contributes significantly. Its presented approaches for decentralized data management, digital property reconciliation, and internet of things data interchange have a massive impact on how Big data will advance. Unauthorized access to the data is very challenging due to the ciphered and decentralized data preservation in the blockchain network. This paper proposes insights related to specific Big data applications that can be analyzed by machine learning algorithms, driven by data provenance, and coupled with blockchain technology to increase data trustworthiness by giving interference-resistant information associated with the lineage and chronology of data records. The scenario of record tampering and big data provenance has been illustrated here using a diabetes prediction. The study carries out an empirical analysis on hundreds of patient records to perform the evaluation and to observe the impact of tampered records on big data analysis i.e diabetes model prediction. Through our experimentation, we may infer that under our blockchain-based system the unchangeable and tamper-proof metadata connected to the source and evolution of records produced verifiability to acquired data and thus high accuracy to our diabetes prediction model.

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DOI: 10.3897/jucs.86563

Authors: Uma Priya D, P. Santhi Thilagam

Abstract: In recent years, the increased use of smart devices and digital business opportunities has generated massive heterogeneous JSON data daily, making efficient data storage and management more difficult. Existing research uses different similarity metrics and clusters the documents to support the above tasks effectively. However, extant approaches have focused on either structural or semantic similarity of schemas. As JSON documents are application-specific, differently annotated JSON schemas are not only structurally heterogeneous but also differ by the context of the JSON attributes. Therefore, there is a need to consider the structural, semantic, and contextual properties of JSON schemas to perform meaningful clustering of JSON documents. This work proposes an approach to cluster heterogeneous JSON documents using the similarity fusion method. The similarity fusion matrix is constructed using structural, semantic, and contextual measures of JSON schemas. The experimental results demonstrate that the proposed approach outperforms the existing approaches significantly.

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DOI: 10.3897/jucs.67593

Authors: Florencia Vega, Guillermo Rodríguez, Fabio Rocha, Rodrigo Pereira dos Santos

Abstract: Agile Methods propose an approach for developing software based on an iterative and incremental life cycle model, in which needs and solutions evolve through collaboration between multi-functional and self-organized teams. As such, agile practices in work teams are gaining much momentum. To meet the demanding level of projects, agile software development also has to keep up with several challenges. In this context, software industry has chosen to use several tools to ease development and communication between different teams’ members. However, these tools generate overwhelming volumes of data that hamper decision-making by project managers. To address this issue, we present Scrum Watch, a tool-based approach that focuses on generating, through cloud-based technologies, graphic elements and reports that assist project managers with information to support decision making. Results obtained from an undergraduate Systems Engineering course through a capstone project confirm the feasibility of the proposed approach, which exploits the benefits of the availability and visualization of process and product metrics.

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DOI: 10.3897/jucs.71645

Authors: Roberto Cavicchioli, Riccardo Martoglia, Micaela Verucchi

Abstract: Exposing city information to dynamic, distributed, powerful, scalable, and user-friendly big data systems is expected to enable the implementation of a wide range of new opportunities; however, the size, heterogeneity and geographical dispersion of data often makes it difficult to combine, analyze and consume them in a single system. In the context of the H2020 CLASS project, we describe an innovative framework aiming to facilitate the design of advanced big-data analytics workflows. The proposal covers the whole compute continuum, from edge to cloud, and relies on a well-organized distributed infrastructure exploiting: a) edge solutions with advanced computer vision technologies enabling the real-time generation of “rich” data from a vast array of sensor types; b) cloud data management techniques offering efficient storage, real-time querying and updating of the high-frequency incoming data at different granularity levels. We specifically focus on obstacle detection and tracking for edge processing, and consider a traffic density monitoring application, with hierarchical data aggregation features for cloud processing; the discussed techniques will constitute the groundwork enabling many further services. The tests are performed on the real use-case of the Modena Automotive Smart Area (MASA).

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DOI: 10.3897/jucs.70326

Authors: Mathieu Briland, Fabrice Bouquet

Abstract: False data injection is an attack in which an attacker injects fabricated data into a system with the objective to change the behaviour and the decision-making of the system. Many industrial data-based devices are vulnerable to such attacks, this work presents an approach for testing False Data Injection Attack. This approach uses a Domain-Specific Language to generate altered data with two objectives, to provide sophisticated attacks scenarios to increase the resilience of vulnerable systems against False Data Injection Attack and to train detection tools.

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DOI: 10.3897/jucs.67046

Authors: Marcelo Aires Vieira, Elivaldo Lozer Fracalossi Ribeiro, Daniela Barreiro Claro, Babacar Mane

Abstract: With the growth of cloud services, many companies have begun to persist and make their data available through services such as Data as a Service (DaaS) and Database as a Service (DBaaS). The DaaS model provides on-demand data through an Application Programming Inter- face (API), while DBaaS model provides on-demand database management systems. Different data sources require efforts to integrate data from different models. These model types include unstructured, semi-structured, and structured data. Heterogeneity from DaaS and DBaaS makes it challenging to integrate data from different services. In response to this problem, we developed the Data Join (DJ) method to integrate heterogeneous DaaS and DBaaS sources. DJ was described through canonical models and incorporated into a middleware as a proof-of-concept. A test case and three experiments were performed to validate our DJ method: the first experiment tackles data from DaaS and DBaaS in isolation; the second experiment associates data from different DaaS and DBaaS through one join clause; and the third experiment integrates data from three sources (one DaaS and two DBaaS) based on different data type (relational, NoSQL, and NewSQL) through two join clauses. Our experiments evaluated the viability, functionality, integration, and performance of the DJ method. Results demonstrate that DJ method outperforms most of the related work on selecting and integrating data in a cloud environment.

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DOI: 10.3897/jucs.2020.078

Authors: Dawid Ewald, Hubert Zarzycki, Łukasz Apiecionek, Jacek Czerniak

Abstract: The paper presents an innovative OFNBee optimization method based on combining the swarm intelligence with the use of directed fuzzy numers OFN. In the introduction, the issues related to the subject of the study, including bee algorithms and OFN numbers, were reviewed. The innovative OFNBee algorithm was presented and verified against a set of known benchmarks functions such as Sphere, Rastrigin, Griewank, Rosenbrock, Schwefel and Ackley. These functions have been applied due to their reliability in the literature. In the further part of the study, the configuration of the algorithm parameters is carried out, including the launch of each mathematical function several dozen times for different data, such as different population sizes. The key part of the research and analysis was to compare OFNBee with six standard ABC, MBO, IMBO, TLBO, HBMO, BBMO bee algorithms. The article ends with a summary and an indication of the possible future works.

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DOI: 10.3897/jucs.2020.073

Authors: Izabela Rojek, Dariusz Mikołajewski, Piotr Kotlarz, Alžbeta Sapietová

Abstract: This article presents the evolution of databases from classical relational databases to distributed databases and data warehouses to fuzzy databases used in a production enterprise. This paper discusses characteristics of this kind of enterprise. The authors precisely define centralized and distributed databases, data warehouses and fuzzy databases. In the modern global world, many companies change their management strategy from the one based on a centralized database to an approach based on distributed database systems. Growing expectations regarding business intelligence encourage companies to deploy data warehouses. New solutions are sought as the demand for engineers' expertise continues to rise. The requested knowledge can be certain or uncertain. Certain knowledge does not any problems and is easy to obtain. However, uncertain knowledge requires new ways of obtaining, including the use of fuzzy logic. It is from where the fuzzy database approach takes its beginning. The above-mentioned strategies of a production enterprise were described herein as a case of special interest.

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DOI: 10.3897/jucs.2020.070

Authors: Jisha Maniamma, Hiroaki Wagatsuma

Abstract: Bongard Problems (BPs) are a set of 100 visual puzzles introduced by M. M. Bongard in the mid-1960s. BPs have been established as benchmark puzzles for understanding the human context-based learning abilities to solve ill- posed problems. The puzzle requires the logical explanation as the answer to distinct two classes of figures from redundant options, which can be obtained by a thinking process to alternatively change the target frame (hierarchical level of analogy) of thinking from a wide range concept networks as D. R. Hofstadter suggested. Some minor research results to solve a limited set of BPs have reported based a single architecture accompanied with probabilistic approaches; however the central problem on BP's difficulties is the requirement of flexible changes of the target frame, therefore non-hierarchical cluster analyses does not provide the essential solution and hierarchical probabilistic models needs to include unnecessary levels for learning from the beginning to prevent a prompt decision making. We hypothesized that logical reasoning process with limited numbers of meta-data descriptions realizes the sophisticated and prompt decision-making and the performance is validated by using BPs. In this study, a semantic web-based hierarchical model to solve BPs was proposed as the minimum and transparent system to mimic human-logical inference process in solving of BPs by using the Description Logic (DL) with assertions on concepts (TBox) and individuals (ABox). Our results demonstrated that the proposed model not only provided individual solutions as a BP solver, but also proved the correctness of Hofstadter's idea as the flexible frame with concept networks for BPs in our actual implementation, which no one has ever achieved. This fact will open the new horizon for theories for designing of logical reasoning systems especially for critical judgments and serious decision-making as expert humans do in a transparent and descriptive way of why they judged in that manner.

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DOI: 10.3897/jucs.2020.039

Authors: Mariusz Topolski

Abstract: The vast majority of medical problems are characterised by the relatively high spatial dimensionality of the task, which becomes problematic for many classic pattern recognition algorithms due to the well-known phenomenon of the curse of dimensionality. This creates the need to develop methods of space reduction, divided into strategies for the selection and extraction of features. The most commonly used tool of the second group is the PCA, which, unlike selection methods, does not select a subset of the original set of features and performs its mathematical transformation into a less dimensional form. However, natural downside of this algorithm is the fact that class context is not present in supervised learning tasks. This work proposes a feature extraction algorithm using the approach of the pca method, trying not only to reduce the feature space, but also trying to separate the class distributions in the available learning set. The problematic issue of the work was the creation of a method of feature extraction describing the prognosis for a chronic lymphocytic leukemia type B-CLL, which will be at least as good, or even better than when compared to other quality extractions. The purpose of the research was accomplished for binary and three-class cases in the event in which for verification of extraction quality, five algorithms of machine learning were applied. The obtained results were compared with the application of paired samples Wilcoxon test.

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DOI: 10.3897/jucs.2020.007

Authors: Anastasija Nikiforova, Janis Bicevskis, Zane Bicevska, Ivo Oditis

Abstract: The paper proposes a new data object-driven approach to data quality evaluation. It consists of three main components: (1) a data object, (2) data quality requirements, and (3) data quality evaluation process. As data quality is of relative nature, the data object and quality requirements are (a) use-case dependent and (b) defined by the user in accordance with his needs. All three components of the presented data quality model are described using graphical Domain Specific Languages (DSLs). In accordance with Model-Driven Architecture (MDA), the data quality model is built in two steps: (1) creating a platform-independent model (PIM), and (2) converting the created PIM into a platform-specific model (PSM). The PIM comprises informal specifications of data quality. The PSM describes the implementation of a data quality model, thus making it executable, enabling data object scanning and detecting data quality defects and anomalies. The proposed approach was applied to open data sets, analysing their quality. At least 3 advantages were highlighted: (1) a graphical data quality model allows the definition of data quality by non-IT and non-data quality experts as the presented diagrams are easy to read, create and modify, (2) the data quality model allows an analysis of "third-party" data without deeper knowledge on how the data were accrued and processed, (3) the quality of the data can be described at least at two levels of abstraction - informally using natural language or formally by including executable artefacts such as SQL statements.

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DOI: 10.3217/jucs-025-12-1531

Authors: Mahnane Lamia, Mohamed Hafidi, André Tricot, Ouissem Benmesbah

Abstract: While some studies indicate that flipped classrooms offer many positive educational outcomes, other studies draw attention to limitations associated with flipped classroom (students' limited preparation prior to class, students' need for guidance at home, students' inability to get immediate feedback while they study at home, and little research has focused on students' learning outcomes, such as: satisfaction and motivation). This paper attempts to address several of these limitations through exploratory studies conducted in an Algerian University. The approach proposed in this paper called Flipped classroom based on Context-Aware mobile learning system (FC-CAMLS) aims to provide learners with an adapted course content format based on their feedback and context. The latter has a significant influence on multimedia content in adaptive mobile learning. The system was implemented in an English Language course. It was expected that the FC-CAMLS increased the management of students' heterogeneity. A quantitative analysis by means of structural equation modeling was performed to analyze the caUnited States of Americal relationships between knowledge, skills, motivation and students' satisfaction. The results show that the system has positive effects on students' knowledge, skills, and motivation. Finally, our research provides useful results that the use of the context dimensions and learner's feedback in adaptive mobile learning is more beneficial for learners especially in the flipped classroom.

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DOI: 10.3217/jucs-025-09-1174

Authors: Ziad Al-Sharif, Mohammed Al-Saleh, Yaser Jararweh, Ahmed Shatnawi

Abstract: Identifying the software used in a cybercrime can play a key role in establishing the evidence against the perpetrator in the court of law. This can be achieved by various means, one of which is to utilize the RAM contents. RAM comprises vital information about the current state of a system, including its running processes. Accordingly, the memory footprint of a process can be used as evidence about its United States of Americage. However, this evidence can be influenced by several factors. This paper evaluates three of these factors. First, it evaluates how the used programming language affects the evidence. Second, it evaluates how the used platform affects the evidence. Finally, it evaluates how the search for this evidence is influenced by the implicitly used encoding scheme. Our results should assist the investigator in its quest to identify the best amount of evidences about the used software based on its execution logic, host platform, language used, and the encoding of its string values. Results show that the amount of digital evidence is highly affected by these factors. For instance, the memory footprint of a Java based software is often more traceable than the footprints of languages such as C++ and C#. Moreover, the memory footprint of a C# program is more visible on Linux than it is on Windows or Mac OS. Hence, often software related values are successfully identified in RAM memory dumps even after the program is stopped.

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DOI: 10.3217/jucs-025-04-0361

Authors: Asieh Ghanbarpour, Hassan Naderi

Abstract: Keyword search is known as an attractive alternative for structured query languages in querying over graph-structured data. A keyword query is expressed by a set of keywords and respond by a set of connected structures from the database, which totally or partially cover the queried keywords. These results show how the queried keywords are related in the database. Since there may be numerous results to a given query, a ranking function is essential to present top-k more relevant results to the user. The effectiveness of this function directly affected the effectiveness of the keyword search system. In this paper, we survey the proposed ranking functions in the context of keyword search. First, the proposed models for the results of a keyword query are discussed and a categorization of them is presented. Next, the effective factors in determining the relevance of results are examined. Then, various ranking functions for ordering the results of a query are described and categorized based on their main view in determining the semantic of the results. Finally, we present an analysis of these classes and discuss the evolution of new research strategies to resolve the issues associated with the ranking of results in the keyword search domain.

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DOI: 10.3217/jucs-025-03-0270

Authors: Xiuze Dong, Yunchuan Guo, Fenghua Li, Liju Dong, Arshad Khan

Abstract: Measuring security is a core step for guaranteeing security of network and information systems. Due to massiveness and heterogeneity of measurement data, it is difficult to classify and combine them on demand. In this paper, considering implication relationship of metrics, we propose a combination model and combination policy for security measurement. Several examples demonstrate the effectiveness of our model.

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DOI: 10.3217/jucs-024-11-1651

Authors: Yoan Gutiérrez, Elena Lloret, José Gómez

Abstract: Ontologies are appropriate structures for capturing and representing the knowledge about a domain or task. However, the design and further population of them are both di_cult tasks, normally addressed in a manual or in a semi-automatic manner. The goal of this article is to de_ne and extend a task-oriented ontology schema that semantically represents the information contained in texts. This information can be extracted using Human Language Technologies, and throughout this work, the whole process to design such ontology schema is described. Then, we also describe an algorithm to automatically populate ontologies based our Human Language Technology oriented schema, avoiding the unnecessary duplication of instances, and having as a result the required information in a more compact and useful format ready to exploit. Tangible results are provided, such as permanent online access points to the ontology schema, an example bucket (i.e. ontology instance repository) based on a real scenario, and a documentation Web page.

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DOI: 10.3217/jucs-023-09-0907

Authors: Mohsen Shahriari, Sabrina Haefele, Ralf Klamma

Abstract: Nowadays, people use online social networks almost every day. They activate either due to their interests, or to search or catch their desirable information. Users of online social networks generate structural and contextual traces that can be analyzed by, i.e., network science researchers. Researchers can describe networks fabricated out of online traces from different perspectives that one of them is communities. Overlapping communities are overlapped structures, in which nodes have denser connections with each other than the rest of the network. Different approaches have addressed this problem; however, few analyses and methods have focused on contextual traces generated by users. As such, in this paper, we propose an algorithm that uses actual content produced by users. This algorithm uses term frequency of words generated by users and combines them by an extended clustering technique. Our evaluation results compare the proposed content-based community detection with structural-based methods. We also reveal community properties as well as its relation to contextual information. Administrators can use these algorithms in question & answer forums where the explicit links among users are missing.

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DOI: 10.3217/jucs-023-07-0603

Authors: Chuandong Qin, Zhenxia Xue, Quanxi Feng, Xiaoyang Huang

Abstract: Taking full advantages of the L1-norm support vector machine and the L2-norm support vector machine, a new improved double regularization support vector machine is proposed to analyze the datasets with small samples, high dimensions and high correlations in the parts of the variables. A kind of smooth function is used to approximately overcome the disdifferentiability of the L1-norm and the steepest descent method is used to solve the model. But the parameters of this model bring some trouble about the accuracy of the experiments. By use of the characteristics of chaotic systems, we propose a chaotic particle swarm optimization to select the parameters in the model. Experiments show the improvement gains the better effects.

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DOI: 10.3217/jucs-022-03-0438

Authors: I-Hsien Ting

Abstract: Opinion mining has been a crucial research topic among recent studies, particularly concerning data from social media. However, a widely discussed communication concern called "the spiral of silence effect" has not been examined in opinion mining studies. In this paper, we propose an approach for detecting the spiral of silence effect in social media. We believe that the accuracy of opinion mining can be improved by considering the effect of the spiral of silence. The details and steps of the detection approach are discussed. We also collected data from two popular social networking websites, namely Facebook and Twitter, for performance measurement. Analysis findings show that the average accuracy of the proposed approach was higher than 0.85, indicating that the approach is highly effective.

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DOI: 10.3217/jucs-022-02-0228

Authors: Luca Carafoli, Federica Mandreoli, Riccardo Martoglia, Wilma Penzo

Abstract: A major societal challenge to be tackled in megacities is sustainable urban transportation. Intelligent Transportation Systems (ITSs) are actually data-centric applications that need to store and query real-time as well as historical/static data from various data sources and have to provide timely responses to users' transportation needs. In this paper we introduce a data management middleware that offers the robustness of a common framework to support the development of smart applications having the above needs. It supports the efficient storage and access to real-time and historical/static data and provides both one-time and continuous query capabilities. While the middleware has been designed to be general and versatile to support data management for any kind of application, in this paper we explore its suitability to ITS smart services also by means of an experimental evaluation conducted on a variety of traffic scenarios.

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DOI: 10.3217/jucs-022-01-0124

Authors: Dilek Karahoca, Adem Karahoca, Ayça Kurnaz

Abstract: This study aims to investigate certain communication dimensions to assess the impact of Computer Mediated Communication (CMC) tendencies of students on ubiquitous environments. Communication dimensions were determined as message content, message interaction, semantic of message, emotional situation, and security. Message content was used as a determiner indicator to measure the effectiveness of communication methods in ubiquitous environments. The effects on the inclination to communicate in ubiquitous learning environments are explained in detail with Partial Least Squares Structural Equation Modeling (PLS-SEM). Message interaction, semantic of message, and security all have a great impact on the adoption of message content; therefore, they promote students' engagement through ubiquitous learning. According to the correlation values, we observed that the user is prone to participate in CMC if the message is meaningful, replied to immediately, sent from someone that looks familiar and sent to the right person.

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DOI: 10.3217/jucs-021-11-1439

Authors: Mehedi Masud, M. Hossain, Atif Alamri, Ahmad Almogren, Mohammed Zakariah

Abstract: Data interoperability and synchronization among heterogeneous data providers in collaborative e-health systems are challenging research issues. Efficient data management techniques promote an efficient way of sharing data. This paper describes existing approaches to data interoperability (platform independency) for exchanging and synchronizing data between heterogeneous data sources or various platforms. We also illustrate an update query execution protocol, which can reduce query execution cost and query response time. We further perform different experiments to validate the effectiveness of the proposed approaches.

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DOI: 10.3217/jucs-021-06-0816

Authors: Zbyněk Falt, Martin Kruliš, David Bednárek, Jakub Yaghob, Filip Zavoral

Abstract: Parallel data processing and parallel streaming systems become quite popular. They are employed in various domains such as real-time signal processing, OLAP database systems, or high performance data extraction. One of the key components of these systems is the task scheduler which plans and executes tasks spawned by the application on available CPU cores. The multiprocessor systems and CPU architecture of the day become quite complex, which makes the task scheduling a challenging problem. In this paper, we propose a novel task scheduling strategy for parallel data stream systems, that reflects many technical issues of the current hardware. In addition, we have implemented a NUMA aware memory allocator that improves data locality in NUMA systems. The proposed task scheduler combined with the new memory allocator achieve up to 3* speed up on a NUMA system and up to 10% speed up on an older SMP system with respect to the unoptimized versions of the scheduler and allocator. Many of the ideas implemented in our parallel framework may be adopted for task scheduling in other domains that focus on different priorities or employ additional constraints.

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DOI: 10.3217/jucs-021-03-0473

Authors: Hongyu Liu, Leiting Chen, Zahra Davar, Mohammad Pour

Abstract: Cloud storage has a long string of merits but at the same time, poses many challenges on data integrity and privacy. A cloud data auditing protocol, which enables a cloud server to prove the integrity of stored files to a verifier, is a powerful tool for secure cloud storage. Wang et al. proposed a privacy-preserving public auditing protocol, however, Worku et al. found the protocol is seriously insecure and proposed an improvement to remedy the weakness. In this paper, unfortunately, we demonstrate that the new protocol due to Worku et al. fails to achieve soundness and obtains merely limited privacy. Specifically, we show even deleting all the files of a data owner, a malicious cloud server is able to generate a response to a challenge without being caught by TPA in their enhanced but unrealistic security model. Worse still, the protocol is insecure even in a correct security model. For privacy, a dishonest verifier can tell which file is stored on the cloud. Solutions to efficient public auditing mechanisms with perfect privacy protection are still worth exploring.

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DOI: 10.3217/jucs-021-03-0454

Authors: Zhusong Liu, Hongyang Yan, Zhiqiang Lin, Lingling Xu

Abstract: Cloud computing is an emerging computing paradigm that can provide storage resources and computing capacities services over the Internet. However, some new security issues arise when users' sensitive data are outsourced and shared in untrusted cloud. The traditional techniques to protect the confidentiality of sensitive data stored in cloud are encryption and related cryptographic tools. And the corresponding private keys to access and decrypt the files are disclosed to only authorized users. However, these traditional solutions are not scalable because the computational cost of encryption and other access control is heavy for devices with limited computation ability. In this paper, we present a new way to implement scalable and fine-grained access control systems, which can be applied for big data in untrusted cloud computing environment. The solution is based on symmetric, efficient broadcast encryption and fine-grained attribute-based encryption (ABE). In this access control system, users are able to join and revoked with broadcast encryption. An outsourced Hierarchical ABE scheme is first proposed in this paper to construct the access control system. The security analysis is also

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DOI: 10.3217/jucs-021-03-0406

Authors: Chien-Ming Chen, Tsu-Yang Wu, Raylin Tso, Masahiro Mambo, Mu-En Wu

Abstract: Mobile data traffic has been growing at an increasing rate with the popularity of smartphones, tablets, and other wireless devices. To reduce the load on the network, mobile network operators deploy femtocells to increase their coverage and performance and to eliminate wireless notspots. Femtocells are low-cost devices that connect a new femtocell network architecture to the core telecommunication network through a licensed spectrum and standardized interface protocols. In this paper, we first note that the user equipment registration procedure, which is defined in the 3GPP (Third Generation Partnership Project) standard, in a femtocellenabled network is vulnerable to denial-of-service attacks. We then propose a mechanism to defend against these attacks. For compatibility, the proposed mechanism makes use of the well-defined control message in the 3GPP standard and modifies the user equipment registration procedure as little as possible.

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DOI: 10.3217/jucs-021-02-0268

Authors: Mehri Rajaei, Mostafa Haghjoo, Eynollah Miyaneh

Abstract: A well-known privacy-preserving network data publication problem focuses on how to publish social network data while protecting privacy and permitting useful analysis. Designing algorithms that safely transform network data is an active area of research. The process of applying these transformations is called anonymization operation. The authors recently proposed the (?,?,?,?)-SNP (Social Network Privacy) model and its an anonymization technique. The present paper introduces a novel anonymization algorithm for the (?,?,?,?)-SNP model. The desirability metric between two individuals of social network is defined to show the desirability of locating them in one group keeping in mind privacy and data utility considerations. Next, individuals are grouped using a greedy algorithm based on the values of this metric. This algorithm tries to generate small-sized groups by maximizing the sum of desirability values between members of each group. The proposed algorithm was tested using two real datasets and one synthetic dataset. Experimental results show satisfactory data utility for topological, spectrum and aggregate queries on anonymized data. The results of the proposed algorithm were compared in the topological properties with results of two recently proposed anonymization schemes: Subgraph-wise Perturbation (SP) and Neighborhood Randomization (NR). The results show that the proposed method is better than or similar to SP and NR for preservation of all structural and spectrum properties, except for the clustering coefficient.

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DOI: 10.3217/jucs-021-01-0007

Authors: Maria del Puerto Paule-Ruiz, Moises Riestra-Gonzalez, Miguel Sánchez-Santillan, Juan Pérez-Pérez

Abstract: In general, research confirms that learning is more effective when students obtain feedback regarding their learning progress. Currently, new versions of e-learning platforms include indicators that provide some static feedback mechanisms and help both learners and educators in planning their learning strategies. This paper explains the usage of indicators in current e-learning systems, generates a taxonomy for their classification, and studies their influence on student performance. Also, it provides a study which is based on the combination of a user-based evaluation process that facilitates data collection and data mining algorithms to infer association rules between learning variables and performance. The results highlight how procrastination influences negative learning performance and how time-related indicators are tightly coupled with students' performance in e-learning platforms.

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DOI: 10.3217/jucs-020-15-2043

Authors: Pablo Orduña, Aitor Almeida, Salvador Ros, Diego López-De-Ipiña, Javier Garcia-Zubia

Abstract: When performing analytics on educational datasets, the best scenario is where the dataset was designed to be analyzed. However, this is often not the case and the data extraction becomes more complicated. This contribution is focused on extracting social networks from a dataset which was not adapted for this type of extraction and where there was no relation among students: a set of remote laboratories where students individually test their experiments by submitting their data to a real remote device. By checking which files are shared among students and submitted individually by them, it is possible to know who is sharing how many files with who, automatically extracting what students are bigger sources. While it is impossible to extract the full real social network of these students, all the edges found are clearly part of it. These relations can indeed be used as a new input for performing the analytics on the dataset.

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DOI: 10.3217/jucs-020-14-1876

Authors: Itziar Arrieta-Salinas, José Armendáriz-Iñigo, Joan Navarro

Abstract: Classic replication protocols running on traditional cluster-based databases are currently unable to meet the ever-growing scalability demands of many modern software applications. Recent cloud-based storage repositories overcome such limitations by fostering availability and scalability over data consistency and transactional support. However, many applications that cannot resign from their transactional nature are unable to benefit from the cloud paradigm. This paper presents Epidemia, a distributed storage architecture featuring a hybrid approach that combines classic database replication with a cloud-inspired infrastructure to provide transactional support and high availability. This architecture is able to offer different consistency levels according to the client demands, thanks to a replication strategy based on epidemic updates in which the replicas of each data partition are organized hierarchically. Additionally, the behavior of a prototype implementation under different workload scenarios is evaluated. Conducted experiments verify that (1) configuration parameters such as the partitioning scheme or the replication protocol play a crucial role on system's throughput, and (2) the existence of replica hierarchies that are asynchronously updated is able to alleviate the scalability limitations of traditional replicated databases by directing transactions that tolerate a certain staleness in the versions of retrieved data items to these replicas.

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DOI: 10.3217/jucs-020-10-1469

Authors: Hassan Abdalla, Ali Amer, Hassan Mathkour

Abstract: Modern database systems are commonly distributed, and data is kept at isolated locations (sites). The various sites are connected through communications links, which may be of low speed resulting in bottlenecks for data transfer between sites. Data replication is considered as one of the effective methods in dealing with such situations to achieve improved performance in distributed database systems (DDBSs). In this work, authors explore a new model for improving performance in distributed database environment by using a vertical fragmentation method along with a novel replication and allocation techniques. The solution procedure consists of a new vertical fragmentation model to fragment a relation and two phases of allocation of fragments to nodes. The paper discusses the tradeoffs between the different scenarios for finding an optimal way of deciding on attribute allocation to sites by evaluating performance based on the collected requirements. This model will significantly reduce communication cost and query response time in DDBSs.

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DOI: 10.3217/jucs-020-07-1026

Authors: Sergio Moya, Sergi Grau, Dani Tost

Abstract: 3D Virtual Environments (VE) are becoming popular as a tool for cognitive, functional and psychological assessment. Navigation in these environments is recognized as one of the most difficult activities in 3D Virtual Environments (VE). Users unfamiliar to 3D games, specially elder persons, get puzzled when they try to virtually move an avatar through these environments. Their inability to navigate prevents them from concentrating in the task and even to finish it. In this paper, we analyze the influence of different factors in locomotion control. We investigate the impact of having the cursor fixed at the camera center or leaving it free inside the current view. We also analyze the influence of the pitch angle on the camera control. In addition, we have designed an automatic locomotion system that we compare to user-controlled locomotion. We describe a virtual scenario and a test task that we have implemented to evaluate these different methods with users of diverse profiles.

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DOI: 10.3217/jucs-020-07-0944

Authors: Chiraz Hog, Raoudha Djemaa, Ikram Amous

Abstract: Web services are rapidly gaining acceptance as a fundamental technology in the web fields. They are becoming the cutting edge of communication between the different applications all over the web. Because of today's wide diversity of devices together with the variety of the user's preferences, context-aware web services are becoming a fundamental challenge that must be targeted. This issue is a part of the Human Computer Interaction (HCI) discipline and it aims at adapting the web service behavior according to the user's context such as his specific work environment, language, type of Internet connection, devices and preferences. Many solutions have been proposed in this area. Nevertheless, the adaptation was carried out only at the runtime and it partially covered the user's general context. In this paper, we introduce a new context-aware approach that provides adaptive web services. Our approach allows to express requirements by taking into account potential user's profile in addition to the functional one. While the latter ensures the description of the web service-functionalities, adaptation expresses the ability of a service to be self-adapted to runtime context changes. Our approach deals with adaptation from the very beginning of the modeling step of a web service. Furthermore, it upgrades description and publication usual methods in order to support profile specification.

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DOI: 10.3217/jucs-020-06-0826

Authors: Maral Mayeh, Thurasamy Ramayah, Simona Popa

Abstract: The purpose of this study is to model the relationship between absorptive capacity and intention to use in the Enterprise Resource Planning (ERP) environment in Iran. This research is a correlation study where a field survey was employed for data collection. The unit of analysis is Iranian individuals who are ERP user in organizations using ERP systems. The questionnaires were sent to the selected organizations. Using a structural equation modeling analysis we tested the hypothesized relationship using AMOS version 16.0. The results indicate that all three absorptive capacity measures to be good predictors of intention to use. Absorptive capacity for applying was the strongest predictor followed by absorptive capacity for understanding and absorptive capacity for assimilating. When implementing complex information systems, managers must also look at the absorptive capacity of the users in order to successful implementation of the system and to ensure continued usage. Previous researchers have not looked at the role of absorptive capacity in system usage at the same rate as those related to technology acceptance research which only focuses on the ease of use and usefulness. Thus this research adds on to the existing literature where future researchers may want to expand on the factors that may influence absorptive capacity for further policy implications.

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DOI: 10.3217/jucs-020-05-0797

Authors: Luiz Laerte Nunes Da Silva Junior, Alexandre Plastino, Leonardo Gresta Paulino Murta

Abstract: In the software development field, the amount of data related to documentation and to the source code itself is huge. Relevant knowledge can be extracted from these data, provided that the adequate tools are in place. In this context, data mining can be seen as an important tool. This paper presents a new approach for code completion based on sequential patterns mined from previous developed source code. According to what is being coded, suggestions of new code sequences are made based on the mined patterns. As a result, a plug-in for the Eclipse IDE, named Vertical Code Completion, was developed and applied over widely known Open Source systems, identifying that our approach could provide suggestions that would anticipate what a developer intends to code.

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DOI: 10.3217/jucs-020-03-0329

Authors: Jakub Malý, Martin Nečaský

Abstract: Complex applications can benefit greatly from using conceptual models and Model Driven Architecture during development, deployment and runtime. XML applications are not different. In this paper, we examine the possibility of using Object Constraint Language (OCL) for expressing constraints over a conceptual model for XML data. We go through the different classes of OCL expression and show how each class can be translated into XPath constructs. Subsequently we show how the constraints can be checked using Schematron. We introduce a function library OclX, which provides constructs necessary to translate those OCL constructs that have no counterpart in XPath. With our tool, it is possible to check validity of OCL constraints in XML data.

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DOI: 10.3217/jucs-020-03-0277

Authors: Jakub Klímek, Soběslav Benda, Martin Nečaský

Abstract: Today, XML (eXtensible Markup Language) is a standard for exchange inside and among IT infrastructures. For the exchange to work an XML format must be negotiated between the communicating parties. The format is often expressed as an XML schema. In our previous work, we introduced a conceptual model for XML, which utilizes modeling, evolution and maintenance of a set of XML schemas and allows schema designers to export modeled formats into grammar-based XML schema languages like DTD and XML Schema. However, there is another type of XML schema languages called rule-based languages with Schematron as their main representative. In our preceding conference paper [Benda et al.(2013)] we briefly introduced the process of translation from our conceptual model to Schematron. Expressing XML schemas in Schematron has advantages over grammar-based languages and in this paper, we describe the previously introduced translation in more detail with focus on structural constraints and how they are represented in Schematron. Also, we discuss the possibilities and limitations of translation from our grammar-based conceptual model to the rule-based Schematron.

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DOI: 10.3217/jucs-020-02-0169

Authors: Tomas Grigalis, Antanas Čenys

Abstract: This paper studies structured data extraction from template-generated Web pages. Such pages contain most of structured data on the Web. Extracted structured data can be later integrated and reused in very big range of applications, such as price comparison portals, business intelligence tools, various mashups and etc. It encourages industry and academics to seek automatic solutions. To tackle the problem of automatic structured Web data extraction we present a new approach - structured data extraction based on clustering visually similar Web page elements. Our method called ClustVX combines visual and pure HTML features of Web page to cluster visually similar Web page elements and then extract structured Web data. ClustVX can extract structured data from Web pages where more than one data record is present. With extensive experimental evaluation on three benchmark datasets we demonstrate that ClustVX achieves better results than other state-of-the-art automatic structured Web data extraction methods.

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DOI: 10.3217/jucs-020-02-0079

Authors: Carlos Blanco, Ignacio De Guzmán, Eduardo Fernández-Medina, Juan Trujillo

Abstract: Data Warehouses (DW) manage enterprise information that is queried for decision making purposes by using On-Line Analytical Processing (OLAP) tools. The establishment of security constraints in all development stages and operations of the DW is highly important since otherwise, unauthorized users may discover vital business information. The final users of OLAP tools access and analyze the information from the corporate DW by using specific views or cubes based on the multidimensional modelling containing the facts and dimensions (with the corresponding classification hierarchies) that a decision maker or group of decision makers are interested in. Thus, it is important that security constraints will be also established over this metadata layer that connects the DW's repository with the decision makers, that is, directly over the multidimensional structures that final users manage. In doing so, we will not have to define specific security constraints for every particular user, thereby reducing the developing time and costs for secure OLAP applications. In order to achieve this goal, a model driven architecture to automatically develop secure OLAP applications from models has been defined. This paper shows the benefits of this architecture by applying it to a case study in which an OLAP application for an airport DW is automatically developed from models. The architecture is composed of: (1) the secure conceptual modelling by using a UML profile; (2) the secure logical modelling for OLAP applications by using an extension of CWM; (3) the secure implementation into a specific OLAP tool, SQL Server Analysis Services (SSAS); and (4) the transformations needed to automatically generate logical models from conceptual models and the final secure implementation.

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DOI: 10.3217/jucs-019-12-1854

Authors: Leonardo Lezcano, Brigitte Jörg, Brian Lowe, Jon Corson-Rikert

Abstract: Institutional repositories (IR) and Current Research Information Systems (CRIS) store and manage information on the context in which research activity takes place. Several models, standards and ontologies have been proposed to date as solutions to provide coherent semantic descriptions of research information. These present a large degree of overlap but also present very different approaches to modelling. This paper introduces a contrast of two of the more widespread models, the VIVO ontology and the CERIF standards, and provides guidance for mapping them in a way that enables clients to integrate data coming from heterogeneous sources. The majority of mapping challenges have risen from the representation of VIVO sub-hierarchies in CERIF as well as from the representation of CERIF attributes in VIVO. In addition, the paper illustrates features for linking data across the Web, for querying of geographically distributed data stores and for aggregating data described using different data models in a common store. These features are supported by semantic web technologies including RDF, OWL and SWRL.

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DOI: 10.3217/jucs-019-10-1351

Authors: Jia Fan, Yuliang Zheng, Xiaohu Tang

Abstract: Signcryption is a public key cryptographic technique that is particularly suited for mobile communications thanks to its light computational and communication overhead. The wide spread use of signcryption in a mobile computing environment, however, is accompanied by an increased risk of private key exposure. This paper addresses the issue of key exposure by proposing a key-insulated signcryption technique. We define a security model for key-insulated signcryption and prove that the keyinsulated signcryption technique is provably secure in the security model.

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DOI: 10.3217/jucs-019-05-0619

Authors: Dilek Karahoca

Abstract: This paper presents a Meta-Cognitive Tool (MCT) development for history teaching. It was developed to support teaching history of civilization courses at the engineering faculty. It covers hierarchically arranged concept maps which are presented dynamically by using Extensible Markup Language (XML) files. MCTs are integrated in e-learning portals to support self-learning. MCTs were investigated in terms of the Human Computer Interaction (HCI) discipline to evaluate their usability in online courses. For this purpose, relationships between learners' cognitive abilities, individual differences, and usability of e-learning portal were considered in order to create a model between individual differences and software usability. The usability of MCT was evaluated by 116 (70 male, 46 female) subjects who were registered for the HUM1005 History of Civilization I, a general elective course at the faculty of engineering. They completed four different surveys: an IQ survey, a personality survey, a motivation survey, and a software usability measurement inventory (SUMI). This research compares intelligence, personal factors, and motivation factors with the personal software usability results in order to determine the correlations and associations between the usability of the software and learners’ individual differences. In the study, results show that the usability of any education tool has effect on achievement of the learner. Noteworthy, a correlation was found between Grade Point Average (GPA) and usability scores.

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DOI: 10.3217/jucs-019-04-0539

Authors: Bogdan Trawiński

Abstract: An approach to predict from a data stream of real estate sales transactions based on ensembles of genetic fuzzy systems was presented. The proposed method relies on incremental expanding an ensemble by models built over successive chunks of a data stream. The output of aged component models produced for current data is updated according to a trend function reflecting the changes of premises prices since the moment of individual model generation or the beginning of the data stream. The impact of different trend functions on the accuracy of single and ensemble fuzzy models was investigated in the paper. Intensive experiments were conducted to evaluate the proposed method using real-world data taken from a dynamically changing real estate market. The statistical analysis of experimental output was made employing the nonparametric methodology designed especially for multiple comparisons including Friedman tests followed by Nemenyi's, Holm's, Shaffer's, and Bergmann-Hommel's post-hoc procedures. The results proved the usefulness of ensemble approach incorporating the correction of individual component model output.

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DOI: 10.3217/jucs-019-04-0521

Authors: Chun-Wei Lin, Tzung-Pei Hong, Yi-Fan Chen, Tsung-Ching Lin, Shing-Tai Pan

Abstract: In the past, many algorithms have been proposed for mining association rules from binary databases. Transactions with quantitative values are, however, also commonly seen in real-world applications. Each transaction in a quantitative database consists of items with their purchased quantities. The multiple fuzzy frequent pattern tree (MFFP-tree) algorithm was thus designed to handle a quantitative database for efficiently mining complete fuzzy frequent itemsets. It however, only processes a database for mining the desired rules. In this paper, we propose an integrated MFFP (called iMFFP)-tree algorithm for merging several individual MFFP trees into an integrated one. The proposed iMFFP-tree algorithm firstly handles the fuzzy regions for providing linguistic knowledge for human beings. The integration mechanism of the proposed algorithm thus efficiently and completely moves a branch from one sub-tree to the integrated tree. The proposed approach can derive both global and local fuzzy rules from distributed databases, thus allowing managers to make more significant and flexible decisions. Experimental results also showed the performance of the proposed approach.

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DOI: 10.3217/jucs-019-04-0462

Authors: Piotr Sobolewski, Michal Woźniak

Abstract: The paper presents a concept drift detection method for unsupervised learning which takes into consideration the prior knowledge to select the most appropriate classification model. The prior knowledge carries information about the data distribution patterns that reflect different concepts, which may occur in the data stream. The presented method serves as a temporary solution for a classification system after a virtual concept drift and also provides additional information about the concept data distribution for adapting the classification model. Presented detector uses a developed method called simulated recurrence and detector ensembles based on statistical tests. Evaluation is performed on benchmark datasets.

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DOI: 10.3217/jucs-018-19-2686

Authors: Gislaine Camila Lapasini Leal, Ana Chaves, Elisa Hatsue Moriya Huzita, Marcio Delamaro

Abstract: The Distributed Software Development (DSD) is a development strategy that meets the globalization needs concerned with the increase productivity and cost reduction. However, the temporal distance, geographical dispersion and the socio-cultural di_erences, increased some challenges and, especially, added new requirements related with the communication, coordination and control of projects. Among these new demands there is the necessity of a software process that provides adequate support to the distributed software development. This paper presents an integrated approach of software development and test that considers distributed teams peculiarities. The approach purpose is to o_er support to DSD, providing a better project visibility, improving the communication between the development and test teams, minimizing the ambiguity and di_culty to understand the artifacts and activities. This integrated approach was conceived based on four pillars: (i) to identify the DSD peculiarities concerned with development and test processes, (ii) to de_ne the necessary elements to compose the integrated approach of development and test to support the distributed teams, (iii) to describe and specify the workows, artifacts, and roles of the approach, and (iv) to represent appropriately the approach to enable the e_ective communication and understanding of it.

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DOI: 10.3217/jucs-018-17-2452

Authors: Ajantha Dahanayake, Bernhard Thalheim

Abstract: Although services are developed, used, applied and intensively discussed in nowadays IT practice, the concept of an IT service has not yet been introduced. Services are IT artifacts that can be used by many users in different context at different points of time in different locations and serve a certain purpose. They provide the data and functionality at the best point of time, in the agreed format and quality for the right user with the right location and context. We generalize some of the introduced notions such as the REA framework (resource-event-agent) and introduce a framework for conceptual modeling of IT service systems that is based on the classical rhetorical frame introduced by Hermagoras of Temnos (Quis, quid, quando, ubi, cur, quem ad modum, quibus adminiculis (W7: Who, what, when, where, why, in what way, by what means)). Services are primarily characterized by W4: wherefore (end), whereof (source), wherewith (supporting means), and worthiness ((surplus) value). Additionally, the purpose can be characterized by answering the why, whereto, when, and for which reason W4 questions. The secondary characterization W14H is given by characterizing user or stakeholder (by whom, to whom, whichever), the application domain (wherein, where, for what, wherefrom, whence, what), the solution they are providing (how, why, whereto, when, for which reason), and the additional context (whereat, whereabout, whither, when).

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DOI: 10.3217/jucs-018-12-1662

Authors: Thijs Baars, Marco Spruit

Abstract: When IS/IT needs to be replaced, cloud systems might provide a feasible solution. However, the adoption process thus far has gone undocumented and enterprise architects are troubled with proper hands-on tools missing, until very recently. This single case study describes a large Dutch utility provider in their effort to understand the facets of the cloud and identifying the risks associated with it. In an action research setting, the SeCA model was used to analyse the cloud solutions and identify the risks with specific data classifications in mind. The results show how decision makers can use the SeCA model in various ways to identify the security risks associated with each cloud solution analysed. The analysis assumes that data classifications are in place. This research concludes that by using the SeCA model, a full understanding of the security risks can be gained on an objective and structural level; this is a further validation of prior empirical research that the SeCA model is a proper hands-on tool for cloud security analysis.

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DOI: 10.3217/jucs-018-04-0532

Authors: Joo Lee, Yue Duan, Jae Oh, Wenliang Du, Howard Blair, Lusha Wang, Xing Jin

Abstract: We develop two social network based algorithms that automatically compute author reputation from a collection of textual documents. We first extract keyword reference behaviors of the authors to construct a social network, which represents relationships among the authors in terms of information reference behavior. With this network, we apply the two algorithms: the first computes each author's reputation value considering only direct reference and the second utilizes indirect reference recursively. We compare the reputation values computed by the two algorithms and reputation ratings given by a human domain expert. We further evaluate the algorithms in email categorization tasks by comparing them with machine learning techniques. Finally, we analyse the social network through a community detection algorithm and other analysis techniques. We observed several interesting phenomena including the network being scale-free and having a negative assortativity.

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DOI: 10.3217/jucs-017-04-0618

Authors: Marta Poblet, Pompeu Casanovas, José-Manuel López-Cobo, Núria Casellas

Abstract: Online communities and institutions create new spaces for interaction, but also open new avenues for the emergence of grievances, claims, and disputes. Consequently, online dispute resolution (ODR) procedures are core to these new online worlds. But can ODR mechanisms provide sufficient levels of reputation, trust, and enforceability for it to become mainstream? This contribution introduces the new approaches to ODR and provides a description of the design and structure of Ontomedia, a web-based platform to facilitate online mediation in different domains.

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DOI: 10.3217/jucs-017-03-0498

Authors: Marta Poblet

Abstract: This paper offers an overview of the emerging domain of mobile governance as an offspring of the broader landscape of e-governance. Mobile governance initiatives have been deployed everywhere in parallel to the development of crowdsourced, open source software applications that facilitate the collection, aggregation, and dissemination of both information and data coming from different sources: citizens, organizations, public bodies, etc. Ultimately, mobile governance can be seen as a tool to promote the rule of law from a decentralized, distributed, and bottom-up perspective.

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DOI: 10.3217/jucs-016-21-3164

Authors: Raju Halder, Shantanu Pal, Agostino Cortesi

Abstract: Digital watermarking for relational databases emerged as a candidate solution to provide copyright protection, tamper detection, traitor tracing, maintaining integrity of relational data. Many watermarking techniques have been proposed in the literature to address these purposes. In this paper, we survey the current state-of-theart and we classify them according to their intent, the way they express the watermark, the cover type, the granularity level, and their verifiability.

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DOI: 10.3217/jucs-016-20-3102

Authors: Bernhard Thalheim

Abstract: Conceptual modelling is a widely applied practice and has led to a large body of knowledge on constructs that might be used for modelling and on methods that might be useful for modelling. It is commonly accepted that database application development is based on conceptual modelling. It is however surprising that only very few publications have been published on a theory of conceptual modelling. Modelling is typically supported by languages that are well-founded and easy to apply for the description of the application domain, the requirements and the system solution. It is thus based on a theory of modelling constructs. At the same time, modelling incorporates a description of the application domain and a prescription of requirements for supporting systems. It is thus based on methods of application domain gathering. Modelling is also an engineering activity with engineering steps and engineering results. It is thus engineering. The first facet of modelling has led to a huge body of knowledge. The second facet is considered from time to time in the scientific literature. The third facet is underexposed in the scientific literature. This paper aims in developing principles of conceptual modelling. They cover modelling constructs as well as modelling activities as well as modelling properties. We first clarify the notion of conceptual modelling. Principles of modelling may be applied and accepted or not by the modeler. Based on these principles we can derive a theory of conceptual modelling that combines foundations of modelling constructs, application capture and engineering. A general theory of conceptual modelling is far too comprehensive and far too complex. It is not yet visible how such a theory can be developed. This paper therefore aims in introducing a framework and an approach to a general theory of conceptual modelling. We are however in urgent need of such a theory. We are sure that this theory can be developed and use this paper for the introduction of the main ingredients of this theory.

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DOI: 10.3217/jucs-016-20-3073

Authors: James Terwilliger, Rafael Fernández-Moctezuma, Lois M. L. Delcambre, David Maier

Abstract: Unlike Database Management Systems (DBMSs), Data Stream Management Systems (DSMSs) do not evaluate queries over static data sets — rather, they continuously produce result streams to standing queries, and often operate in a context where any interruption can lead to data loss. Support for schema evolution in such an environment is currently unaddressed. In this work we address evolution in DSMSs by introducing a new element to streams, called an accent, that precedes and describes an evolution. We characterize how a subset of commonly used query operators in DSMS act on and propagate accents with respect to three evolution primitives: Add Attribute, Drop Attribute, and Alter Data.

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DOI: 10.3217/jucs-016-20-3043

Authors: Klaus-Dieter Schewe, Qing Wang

Abstract: Database transformations provide a unifying umbrella for queries and updates. In general, they can be characterised by five postulates, which constitute the database analogue of Gurevich's sequential ASM thesis. Among these postulates the background postulate supposedly captures the particularities of data models and schemata. For the characterisation of XML database transformations the natural first step is therefore to define the appropriate tree-based backgrounds, which draw on hereditarily finite trees, tree algebra operations, and extended document type definitions. This defines a computational model for XML database transformation using a variant of Abstract State Machines. Then the incorporation of weak monadic second-order logic provides an alternative computational model called XML machines. The main result is that these two computational models for XML database transformations are equivalent.

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DOI: 10.3217/jucs-016-20-2956

Authors: Stephen Hegner

Abstract: Although a database view embodies partial information about the state of the main schema, the state of the view schema is a quotient (and not a subset) of the state of the main schema. It is the information content of the view state, the set of sentences which are true for that state, and not the state itself which is a subset of the information content of the state of the main schema. There are thus two dual approaches to modelling this partiality, one based upon structures, with a consequent quotient relationship, and another based upon logical theories, with a consequent subset relationship. In this work, a representation for database views is developed which combines these two approaches. The state-based representation is expanded so that the information content embodied in a wide class of views, including those defined by SPJ queries, is fully representable, thus permitting the view state to be modelled internally as a subset of the main database state. The utility of this framework is demonstrated with a simple solution to the uniqueness problem for view updates via constant complement.

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DOI: 10.3217/jucs-016-20-2934

Authors: Flavio Ferrarotti, Alejandra Paoletti, José María Turull Torres

Abstract: We initiate in this work the study of a sort of redundancy problem revealed by what we call redundant relations. Roughly, we define a redundant relation in a database instance (dbi) as a k-ary relation R such that there is a first-order query which evaluated in the reduced dbi, (i.e., the dbi without the redundant relation R) gives us R. So, given that first-order types are isomorphism types on finite structures, we can eliminate that relation R as long as the equivalence classes of the relation of equality of the first-order types for all k-tuples in the dbi are not altered. It turns out that in a fixed dbi, the problem of deciding whether a given relation in the dbi is redundant is decidable, though intractable, as well as the problem of deciding whether there is any relation symbol in the schema which is a redundant relation in the given dbi. We then study redundant relations with a restricted notion of equivalence so that the problem becomes tractable.

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DOI: 10.3217/jucs-016-17-2293

Authors: Duc-Hanh Dang, Anh-Hoang Truong, Martin Gogolla

Abstract: Narrowing the wide conceptual gap between problem and implementation domains is considered a significant factor within software engineering. Currently, such a relation is often obtained using mappings between metamodels for a structural semantics. This paper proposes an approach based on the integration of Triple Graph Grammars (TGGs) and the Object Constraint Language (OCL) in order to explain a behavioral relation between models at different levels of abstraction. Triple rules incorporating OCL allow us to synchronize execution scenarios of a system at two levels. In this way we obtain an integrated operational semantics of the models as well as the possibility for conformance verification between them. We illustrate our approach with a case study for the relation between use case and design models.

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DOI: 10.3217/jucs-016-16-2179

Authors: Sandy Helou, Christophe Salzmann, Denis Gillet

Abstract: This paper discusses the 3A recommender system that targets CSCL (computer-supported collaborative learning) and CSCW (computer-supported collaborative work) environments. The proposed system models user interactions in a heterogeneous graph. Then, it applies a personalized, contextual, and multi-relational ranking algorithm to simultaneously rank actors, activity spaces, and assets. The results of an empirical evaluation carried out on an Epinions dataset indicate that the proposed recommendation approach exploiting the trust and authorship networks performs better than user-based collaborative filtering in terms of recall.

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DOI: 10.3217/jucs-016-06-0938

Authors: Gamgarn Somprasertsri, Pattarachai Lalitrojwong

Abstract: Online customer reviews is considered as a significant informative resource which is useful for both potential customers and product manufacturers. In web pages, the reviews are written in natural language and are unstructured-free-texts scheme. The task of manually scanning through large amounts of review one by one is computational burden and is not practically implemented with respect to businesses and customer perspectives. Therefore it is more efficient to automatically process the various reviews and provide the necessary information in a suitable form. The high-level problem of opinion summarization addresses how to determine the sentiment, attitude or opinion that an author expressed in natural language text with respect to a certain feature. In this paper, we dedicate our work to the main subtask of opinion summarization. The task of product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the performance of opinion orientation identification. It is important to properly identify the semantic relationships between product features and opinions. We proposed an approach for mining product feature and opinion based on the consideration of syntactic information and semantic information. By applying dependency relations and ontological knowledge with probabilistic based model, the result of our experiments shows that our approach is more flexible and effective.

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DOI: 10.3217/jucs-016-05-0729

Authors: Michael Johnson, Robert Rosebrugh, Richard Wood

Abstract: The classical (Bancilhon-Spyratos) correspondence between view update translations and views with a constant complement reappears more generally as the correspondence between update strategies and meet complements in the order based setting of S. Hegner. We show that these two theories of database view updatability are linked by the notion of "lens" which is an algebra for a monad. We generalize lenses from the category of sets to consider them in categories with finite products, in particular the category of ordered sets.

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DOI: 10.3217/jucs-016-01-0022

Authors: Alberto Salguero, Francisco Araque

Abstract: Information Systems usually rely on external and independent data sources. When integrating the data to build the integrated repository it is possible to make use of the temporal characteristics of the data sources to improve the whole integration process and the quality of the integrated data, which support the organization’s decision-making tasks. In this work the usage of an Ordered Weighted Averaging-based operator is presented as the best option when the data sources refer to similar facts but the data on each data source is expressed with different temporal characteristics. This is a common issue in Information Systems development.

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DOI: 10.3217/jucs-015-15-2999

Authors: William Claycomb, Dongwan Shin

Abstract: Enterprise directory services are commonly used in enterprise systems to store object information relating to employees, computers, contacts, etc. These stores can act as information providers or sources for authentication and access control decisions, and could potentially contain sensitive information. An insider attack, particularly if carried out using administrative privileges, could compromise large amounts of directory information. We present two solutions for protecting directory services information from insider attacks. The first is a centralized approach utilizing a customized virtual directory server. The second is a distributed approach using existing key management infrastructure and a new component called a Personal Virtual Directory Service. We explain how these solutions interact with existing directory services and client applications. We also show how impact to existing users, client applications, and directory services are minimized, and how we prevent insider attacks from revealing protected data. We compare and contrast both solutions, including potential tradeoffs, administrative overhead, and enterprise systems impact. Additionally, our solution is supported by implementation results showing the impact to client performance and directory storage capacity.

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DOI: 10.3217/jucs-015-14-2765

Authors: Leendert Botha, Lynette van Zijl, McElory Hoffmann

Abstract: We consider the realtime content-based image retrieval of LEGO bricks from a database of images of LEGO bricks. This seemingly simple problem contains a number of surprisingly the image signature, and corresponding feature set, and illustrate cellular automaton-based methods for the whole feature extraction phase.

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DOI: 10.3217/jucs-015-13-2622

Authors: Ngoc Nguyen

Abstract: Rough classification has been known as the concept of Pawlak within the Rough Set Theory. In this paper the novel rough classification approach and its applications in e-learning systems and user interface management for recommendation processes will be presented.

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DOI: 10.3217/jucs-015-13-2566

Authors: Tao Jiang, Yucai Feng, Bin Zhang

Abstract: Online detecting special patterns over financial data streams is an interesting and significant work. Existing many algorithms take it as a subsequence similarity matching problem. However, pattern detection on streaming time series is naturally expensive by this means. An efficient segmenting algorithm ONSP (ONline Segmenting and Pruning) is proposed, which is used to find the end points of special patterns. Moreover, a novel metric distance function is introduced which more agrees with human perceptions of pattern similarity. During the process, our system presents a pattern matching algorithm to efficiently match possible emerging patterns among data streams, and a probability prediction approach to predict the possible patterns which have not emerged in the system. Experimental results show that these approaches are effective and efficient for online pattern detecting and predicting over thousands of financial data streams.

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DOI: 10.3217/jucs-015-13-2463

Authors: Dong-Wook Seo, Hyun-Uk Chae, Byeong-Woo Kim, Won-Ho Choi, Kang-Hyun Jo

Abstract: We propose a method for detection and tracking for objects under multiple cameras system. To track objects, one need to establish correspondence objects among multiple views. We apply the principal axis of objects and the homography constraint to match objects across multiple cameras. The principal axis belongs to the silhouette of objects that is extracted by the background subtraction. We use the multiple background model to the background subtraction. In an image sequence, many changes happen with respect to pixel intensity. This cannot be characterized by the single background model so that is necessary to use the multiple background model. Also, we use the median background model reducing some noises. The silhouette is detected by difference with background models and current image which includes moving objects. For calculating homography, we use landmarks on the ground plane in 3D space. The homography means the relation between two correspondence between two coinciding points from different views. The intersection of principal axes and ground plane in 3D space are the same point shown in each view. The intersection occurs when a principal axis in an image crosses to the transformed ground plane from another image. We construct the correspondence which means the relationship between intersection in current image and transformed intersection from the other image by homography constraint. Those correspondences confirm within a short distance measuring in the top viewed plane. Thus, we track a person by these corresponding points on the ground plane.

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DOI: 10.3217/jucs-015-10-2058

Authors: Eric Pardede, J. Rahayu, Ramanpreet Aujla, David Taniar

Abstract: The increase utilization of XML structure for data representation, exchange, and integration has strengthened the need for an efficient storage and retrieval of XML data. Currently, there are two major streams of XML data repositories. The first stream is the Native XML database systems which are built solely to store and manipulate XML data, and equipped with the standard XML query language known as XPath and XQuery. The second stream is the XML-Enabled database systems which are generally existing traditional database systems enhanced with XML storage capabilities. The SQL/XML standard for XML querying is used in these enabled database systems stream. The main specific characteristic of this standard is the fact that XPath and XQuery are embedded within SQL statements. To date, most existing work in XML query analysis have been focussing on the first stream of Native XML database systems. The focus of this paper is to present a taxonomy of different hierarchical query patterns in XML-Enabled database environment, and to analyze the performance of the different query structures using the SQL/XML standard.

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DOI: 10.3217/jucs-015-10-2028

Authors: Klaus-Dieter Schewe, Bernhard Thalheim, Qing Wang

Abstract: The exact validation of streaming XML documents can be realised by using visibly push-down automata (VPA) that are defined by Extended Document Type Definitions (EDTD). It is straightforward to represent such an automaton as an Abstract State Machine (ASM). In doing so we enable computations on abstract states that are defined by a certain class of automata, in this case VPAs. In this paper we elaborate on this approach by taking also updates of XML documents into account. In this way the ASM-approach combines vertical refinements, which first make states explicit and then instantiate by a specific EDTD, with horizontal refinements, which replace streaming XML documents by stored ones and then add updates. Furthermore, as the EDTD appears as part of the abstract state, updating it is another natural extension by horizontal refinement. In this way we obtain consistently integrated updates and schema updates for XML documents, which can even be extended to become fault-tolerant by taking at most k errors in the document into consideration. It further provides an example of ASM-based computation with automata-defined states.

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DOI: 10.3217/jucs-015-09-1782

Authors: Lili Sun, Hua Wang, Jianming Yong

Abstract: Permission-role assignments (PRA) is one important process in Role-based access control (RBAC) which has been proven to be a flexible and useful access model for information sharing in distributed collaborative environments. However, problems may arise during the procedures of PRA. Conflicting permissions may assign to one role, and as a result, the role with the permissions can derive unexpected access capabilities. This paper aims to analyze the problems during the procedures of permission-role assignments in distributed collaborative environments and to develop authorization allocation algorithms to address the problems within permission-role assignments. The algorithms are extended to the case of PRA with the mobility of permission-role relationship. Finally, comparisons with other related work are discussed to demonstrate the effective work of the paper.

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DOI: 10.3217/jucs-015-01-0304

Authors: Attila Sali, Klaus-Dieter Schewe

Abstract: We investigate properties of coincidence ideals in subattribute lattices that occur in complex value datamodels, i.e. sets of subattributes, on which two complex values coincide. We let complex values be defined by constructors for records, sets, multisets, lists, disjoint union and optionality, i.e. the constructors cover the gist of all complex value data models. Such lattices carry the structure of a Brouwer algebra as long as the union-constructor is absent, and for this case sufficient and necessary conditions for coincidence ideals are already known. In this paper, we extend the characterisation of coincidence ideals to the most general case. The presence of the disjoint union constructor complicates all results and proofs significantly. The reason for this is that the union-constructor causes non-trivial restructuring rules to hold. The characterisation of coincidence ideal is of decisive importance for the axiomatisation of (weak) functional dependencies.

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DOI: 10.3217/jucs-015-01-0241

Authors: Scott Lee, Gillian Dobbie, Jing Sun, Lindsay Groves

Abstract: The rapid growth of the World Wide Web has resulted in a dramatic increase in semistructured data usage, creating a growing need for effective and efficient utilization of semistructured data. In order to verify the correctness of semistructured data design, precise descriptions of the schemas and transformations on the schemas must be established. One effective way to achieve this goal is through formal modeling and automated verification. This paper presents the first step towards this goal. In our approach, we have formally specified the semantics of the ORA-SS (Object-Relationship-Attribute data model for Semistructured data) data modeling language in PVS (Prototype Verification System) and provided automated verification support for both ORA-SS schemas and XML (Extensible Markup Language) data instances using the PVS theorem prover. This approach provides a solid basis for verifying algorithms that transform schemas for semistructured data.

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DOI: 10.3217/jucs-015-01-0195

Authors: Henning Köhler

Abstract: A common approach in designing relational databases is to start with a universal relation schema, which is then decomposed into multiple subschemas. A good choice of subschemas can be determined using integrity constraints defined on the schema, such as functional, multivalued or join dependencies. In this paper we propose and analyze a new normal form based on the idea of minimizing overall storage space and update costs, and as a consequence redundancy as well. This is in contrast to existing normal forms such as BCNF, 4NF or KCNF, which only characterize the absence of redundancy (and thus space and update time minimality) for a single schema. We show that our new normal form naturally extendexisting normal forms to multiple schemas, and provide an algorithm for computing decompositions.

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DOI: 10.3217/jucs-015-01-0157

Authors: Markus Kirchberg

Abstract: Transaction management is an essential component of database management systems. It enables multiple users to access the database concurrently while preserving transactional properties such as atomicity, consistency, isolation, and durability. In this paper, we propose a formal framework specification for transaction processing. Our work can be seen as an extension of previous work by Gurevich et al. who have presented a formalism for general database recovery processing. Based on this formalism, we incorporate additional mechanisms that remove several explicit constraints, support normal transaction processing, and, most importantly, apply the approach to more advanced recovery mechanisms.

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DOI: 10.3217/jucs-015-01-0112

Authors: Sven Hartmann, Sebastian Link

Abstract: We study inference systems of weak functional dependencies in relational and complex-value databases. Functional dependencies form a very common class of database constraints. Designers and administrators proficiently utilise them in everyday database practice. Functional dependencies correspond to the linear-time decidable fragment of Horn clauses in propositional logic. Weak functional dependencies take advantage of arbitrary clauses, and therefore represent full propositional reasoning about data in databases. Moreover, they can be specified in a way that is very similar to functional dependencies. In relational databases the class of weak functional dependencies is finitely axiomatisable and the associated implication problem is coNP-complete in general. Our first main result extends this axiomatisation to databases in which complex elements can be derived from atomic ones by finitely many nestings of record, list and disjoint union constructors. In particular, we construct two nested tuples that can serve as a counterexample relation for the implication of weak functional dependencies. We further apply this construction to show an equivalence to truth assignments that serve as counterexamples for the implication of propositional clauses. Hence, we characterise the implication of weak functional dependencies in complex-value databases in completely logical terms. Consequently, state-of-the-art SAT solvers can be applied to reason about weak functional dependencies in relational and complex-value databases.

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DOI: 10.3217/jucs-015-01-0033

Authors: Andrea Calì, Diego Calvanese, Davide Martinenghi

Abstract: Unlike relational tables in a database, data sources on the Web typically can only be accessed in limited ways. In particular, some of the source fields may be required as input and thus need to be mandatorily filled in order to access the source. Answering queries over sources with access limitations is a complex task that requires a possibly recursive evaluation even when the query is non-recursive. After reviewing the main techniques for query answering in this context, in this article we consider the impact of functional and inclusion dependencies on dynamic query optimization under access limitations. In particular, we address the implication problem for functional dependencies and simple full-width inclusion dependencies, and prove that it can be decided in polynomial time. Then we provide necessary and sufficient conditions, baseon the dependencies together with the data retrieved at a certain step of the query answering process, that allow avoiding unnecessary accesses to the sources.

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DOI: 10.3217/jucs-014-22-3658

Authors: Ismael Caballero, Angélica Caro, Coral Calero, Mario Piattini

Abstract: In order to enhance their global business performance, organizations must be careful with the quality of their information since it is one of their main assets. Analogies to quality management of classical products demonstrate that Information Quality is also preferably attainable through management by integrating some corresponding Information Quality management activities into the organizational processes. To achieve this goal we have developed an Information Quality Management Framework (IQMF). It is articulated on the concept of Information Management Process (IMP), based on the idea of Software Process. An IMP is a combination of two sub-processes: the first, a production process, aimed to manufacture information from raw data, and the second to adequately manage the required Information Quality level of the first. IQMF consists of two main components: an Information Quality Management Maturity Model (IQM3), and a Methodology for the Assessment and Improvement of Information Quality Management (MAIMIQ), which uses IQM3 as a reference model for the assessment and for the improvement goal of an IMP. Therefore, as a result of an assessment with MAIMIQ, an IMP can be said to have raised one of the maturity levels described in IQM3, and as improvement goal, it would be desirable to achieve a higher maturity level. Since an Information System can be seen as a set of several IMPs sharing several resources, it is possible to improve the Information Quality level of the entire Information System by improving the most critical IMPs. This paper is focused only on describing the foundations and structure of IQM3, which is based on staged CMMI.

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DOI: 10.3217/jucs-014-20-3333

Authors: António Leitão

Abstract: UCL-GLORP is a Common Lisp implementation and extension of GLORP (Generic Lightweight Object-Relational Persistence), an Object-Relational Mapper for the Smalltalk language. UCL-GLORP is now a mature framework that largely extends GLORP and that takes advantage of some of Common Lisp unique features. This paper illustrates UCL-GLORP and discusses some of the challenges that we faced in order to find suitable replacements, in Common Lisp, for some of the more esoteric features of Smalltalk that were explored by GLORP.

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DOI: 10.3217/jucs-014-18-2998

Authors: Boris Chidlovskii, Loïc Lecerf

Abstract: We address the problems of structuring and annotation of layout-oriented documents.We model the annotation problems as the collective classification on graph-like structures with typed instances and links that capture the domain-specific knowledge. We use the relational de-pendency networks (RDNs) for the collective inference on the multi-typed graphs. We then describe a variant of RDNs where a stacked approximation replaces the Gibbs sampling in orderto accelerate the inference. We report results of evaluation tests for both the Gibbs sampling and stacking inference on two document structuring examples.

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DOI: 10.3217/jucs-014-18-2982

Authors: Farshideh Einsele, Rolf Ingold, Jean Hennebert

Abstract: In this paper, we introduce and evaluate a system capable of recognizing words extracted from ultra low resolution images such as those frequently embedded on web pages. The design of the system has been driven by the following constraints. First, the system has to recognize small font sizes between 6-12 points where anti-aliasing and resampling filters are applied. Such procedures add noise between adjacent characters in the words and complicate any a priori segmentation of the characters. Second, the system has to be able to recognize any words in an open vocabulary setting, potentially mixing different languages in Latin alphabet. Finally, the training procedure must be automatic, i.e. without requesting to extract, segment and label manually a large set of data. These constraints led us to an architecture based on ergodic HMMs where states are associated to the characters. We also introduce several improvements of the performance increasing the order of the emission probability estimators, including minimum and maximum width constraints on the character models and a training set consisting all possible adjacency cases of Latin characters. The proposed system is evaluated on different font sizes and families, showing good robustness for sizes down to 6 points.

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DOI: 10.3217/jucs-014-17-2877

Authors: Craig Stewart

Abstract: The Cultural Artefacts in Education (CAE) questionnaire is used to determine the educational values of different cultures. In this paper I examine the results for ten countries, specifically focussing on their attitudes towards adaptive hypermedia in an educational setting. These results can inform the authoring process for adaptive systems & content, with Adaptive Hypermedia systems being able to employ stereotype adaptation to deliver content pre-adjusted to a learner’s cultural background.

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DOI: 10.3217/jucs-014-11-1838

Authors: Paula Montoto, Alberto Pan, Juan Raposo, Jose Losada, Fernando Bellas, Víctor Carneiro

Abstract: Most today’s web sources do not provide suitable interfaces for software programs to interact with them. Many researchers have proposed highly effective techniques to address this problem. Nevertheless, ad-hoc solutions are still frequent in real-world web automation applications. Arguably, one of the reasons for this situation is that most proposals have focused on query wrappers, which transform a web source into a special kind of database in which some queries can be executed using a query form and return resultsets that are composed of structured data records. Although the query wrapper model is often useful, it is not appropriate for applications that make decisions according to the data retrieved or processes that use forms that can be modelled as insert/update/delete operations. This article proposes a new language for defining web automation processes that is based on a wide range of real-world web automation tasks that are being used by corporations from different business areas.

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DOI: 10.3217/jucs-014-07-1048

Authors: Grażyna Brzykcy, Jerzy Bartoszek, Tadeusz Pankowski

Abstract: We propose specification of schema mappings and agents' actions in XML data integration task. We discuss the problem in a highly-dynamic environment consisting of a community of peer-to-peer cooperating partners (agents). Peers decide how to describe their local data, when to join and when to leave the system, how to communicate and share their information with partners. An agent responds to the query by asking its partners (friends), which are able to partly answer the query. All the answers are merged and final result is constructed. A peer propagates a query along semantic paths existing in the system. Semantic paths are determined by schema mappings defined between partners. We propose a method for specifying schema mappings and to translate them to XQuery expressions. Mappings are represented by means of logical formulas. We also propose a declarative specification of semantic-driven communication in the system. The specification is made in a peer-oriented extension of Prolog.

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DOI: 10.3217/jucs-013-12-1936

Authors: Domenico Beneventano, Sonia Bergamaschi, Francesco Guerra, Maurizio Vincini

Abstract: Integration of heterogeneous information in the context of Internet becomes a key activity to enable a more organized and semantically meaningful access to data sources. As Internet can be viewed as a data-sharing network where sites are data sources, the challenge is twofold. Firstly, sources present information according to their particular view of the matter, i.e. each of them assumes a specific ontology. Then, data sources are usually isolated, i.e. they do not share any topological information concerning the content or the structure of other sources. The classical approach to solve these issues is provided by mediator systems which aim at creating a unified virtual view of the underlying data sources in order to hide the heterogeneity of data and give users a transparent access to the integrated information. In this paper we propose to use a multi-agent architecture to build and manage a mediators network. While a single peer (i.e. a mediator agent) independently carries out data integration activities, it exchanges knowledge with other peers by means of specialized agents (i.e. brokers) which provide a coherent access plan to access information in the peer network. This defines two layers in the system: at local level, peers maintain an integrated view of local sources, while at network level agents maintain mappings among the different peers. The result is the definition of a new networked mediator system intended to operate in web economies, which we realized in the SEWASIE (SEmantic Webs and AgentS in Integrated Economies) project. SEWASIE is a RDT project supported by the 5th Framework IST program of the European Community successfully ended on September 2005.

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DOI: 10.3217/jucs-013-11-1767

Authors: Dan Simovici

Abstract: We introduce the notion of ∧- and ∨-pairs of functions on lattices as an abstraction of the notions of metric and its related entropy for probability distributions. This approach allows us to highlight the relationships that exist between various properties of metrics and entropies and opens the possibility of extending these concepts to other algebraic structures.

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DOI: 10.3217/jucs-013-10-1484

Authors: Tao Zeng, Changjie Tang, Yong Xiang, Peng Chen, Yintian Liu

Abstract: Rule mining is an important issue in data mining. To address it, a novel Immune Gene Expression Programming (IGEP) model was proposed. Concepts of rule, gene, immune cell, and antibody were formalized. The dynamic evolution models and the corresponding recursive equations of immune cell, self, immune-tolerance were built. The novel key techniques of IGEP were presented. Experiment results showed that the new method has good stability, scalability and flexibility. It can discover traditional association rule, non-traditional rule including connective "OR" or "NOT", and meta-rule of strong rule. Furthermore, it can perform well in constrained pattern mining.

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DOI: 10.3217/jucs-013-08-1110

Authors: Nuno Carvalho, Alfranio Jr., José Pereira, Luís Rodrigues, Rui Oliveira, Susana Guedes

Abstract: The Database Management System (DBMS) used to be a commodity software component, with well known standard interfaces and semantics. However, the performance and reliability expectations being placed on DBMSs have increased the demand for a variety add-ons, that augment the functionality of the database in a wide range of deployment scenarios, offering support for features such as clustering, replication, and self-management, among others. A well known software engineering approach to systems with such requirements is reflection. Unfortunately, standard reflective interfaces in DBMSs are very limited. Some of these limitations may be circumvented by implementing reflective features as a wrapper to the DBMS server. Unfortunately, these solutions comes at the expense of a large development effort and significant performance penalty. In this paper we propose a general purpose DBMS reflection architecture and interface, that supports multiple extensions while, at the same time, admitting efficient implementations. We illustrate the usefulness of our proposal with concrete examples, and evaluate its cost and performance under different implementation strategies.

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DOI: 10.3217/jucs-013-08-1094

Authors: P. Melliar-Smith, Louise Moser

Abstract: Web Services enable the creation of complex business activities through the cooperation of independently developed software programs. However, Web Services incur the risk of long delays and locked data when using the classical distributed transaction strategy, and the risk of inconsistency when using the compensating transactions strategy. If the benefits of Web Services are to be fully realized, a better strategy must be employed. In this paper we describe an extended transactions strategy that can be used in conjunction with existing Web Services infrastructures, and that is compatible with existing business practices. The strategy exploits local transactions and commutativity of local actions at each data item to achieve global atomicity for business activities.

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DOI: 10.3217/jucs-013-02-0329

Authors: Michal Zgrzywa

Abstract: In this paper the author considers some problems related to attribute dependencies in consensus determining. These problems concern the dependencies of attributes representing the content of conflicts, which cause that one may not treat the attributes independently in consensus determining. It is assumed that attribute values are represented by intervals. In the paper the author considers the choice of proper distance function. Next, the limitations guarantying determining a correct consensus despite treating the attributes independently are presented. Additionally, the algorithm of calculating the proper consensus in cases when these limitation are not met is introduced.

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DOI: 10.3217/jucs-013-02-0317

Authors: Marcin Hernes, Ngoc Nguyen

Abstract: A method for determining consensus of hierarchical incomplete ordered partitions and coverings of sets is presented in this chapter. Incomplete ordered partitions and coverings are often used in expert information analysis. These structures should be useful when an expert has to classify elements of a set into given classes, but referring to several elements he does not know to which classes they should belong. The hierarchical ordered partition is a more general structure than incomplete ordered partition. In this chapter we present definitions of the notion of hierarchical incomplete ordered partitions and coverings of sets. The distance functions between hierarchical incomplete ordered partitions and coverings are defined. We present also algorithms of consensus determining for a finite set of hierarchical incomplete ordered partitions and coverings.

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DOI: 10.3217/jucs-013-02-0287

Authors: Leszek Borzemski

Abstract: In this paper we propose an application of data mining methods in the prediction of the availability and performance of Internet paths. We deploy a general decision-making method for advising the users in further usage of Internet path at particular time and date. The method is based on the clustering and tree classification data mining techniques. The usefulness of our method for prediction the Internet path behavior has been confirmed in real-life experiment. The active Internet measurements were performed to gather the end-to-end latency and packet routing information. The knowledge gathered has been analyzed using a professional data mining package via neural clustering and decision tree algorithms. The results show that the data mining can be efficiently used for the purpose of the forecasting the network behavior. We propose to build a network performance monitoring and prediction service based on proposed data mining procedure. We address our approach especially to the non-networkers of such networking frameworks as Grid and overlay networks who want to schedule their network activity but who want to be left free from networking issues to concentrate on their work.

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DOI: 10.3217/jucs-013-02-0199

Authors: Jerzy Świątek

Abstract: In this paper the problem of parameter estimation of an input-output system is discussed. It is assumed that the system is described by the relation known with accuracy to some parameters. The possible noisy observations of system are described. The estimation algorithm based on maximum likelihood method is proposed. The presented approach is illustrated by analytical examples.

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DOI: 10.3217/jucs-012-11-1651

Authors: Jesús Almendros-Jiménez, Antonio Becerra-Terón, Francisco Enciso-Baños

Abstract: The eXtensible Markup Language (XML) is considered as the format of choice for the exchange of information among various applications on the Internet. Since XML is emerging as a standard for data exchange, it is natural that queries among applications should be expressed as queries against data in XML format. This use gives rise to a requirement for a query language expressly designed for XML resources. World Wide Web Consortium (W3C) convened to create the XQuery language, concretely, a typed functional language for querying XML documents. One key aspect of the XQuery language is the use of the XPath language as basis for handling the structure of an XML document. In this paper, we present a proposal for the representation of XML documents by means of a logic program. Rules and facts can be used for representing the document schema and the XML document itself. In addition, we study how to query by means of the XPath language against a logic program representing an XML document. It evolves the specialization of the logic program with regard to the XPath expression. This specialization technique is based on the well-known transformation technique called Magic Sets and studied for deductive databases. The bottom-up evaluation of the speciali

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DOI: 10.3217/jucs-012-09-1240

Authors: András Hajdu, János Kormos, Tamás Tóth, Krisztián Veréb

Abstract: In this paper we show how the distance functions generated by neighborhood sequences provides flexibility in image processing algorithms and image database retrieval. Accordingly, we present methods for indexing and segmenting color images, where we use digital distance functions generated by neighborhood sequences to measure distance between colors. Moreover, we explain the usability of neighborhood sequences within the field of image database retrieval, to find similar images from a database for a given query image. Our approach considers special distance functions to measure the distance between feature vectors extracted from the images, which allows more flexible queries for the users.

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DOI: 10.3217/jucs-012-09-1165

Authors: Antal Buza

Abstract: CQL, Continuous Query Language is suitable for data stream queries. Sometimes it is better if the queries operate on relational databases and data streams simultaneously. The execution of a CQL query takes a long time (several hours, days or even more). It is not clear what kind of semantics is suitable for the user when the database is updated during the execution of a CQL query. In this paper we give a short description of CQL, a characterization of update-problems, and we offer possible suggestions for the semantic extension of CQL. After the expansion, the CQL would be suitable for solving much more practical problems. The parallel usage of continuous data streams and updatable databases would be settled.

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DOI: 10.3217/jucs-012-07-0938

Authors: Rodrigo Machado, Álvaro Moreira, Renata Galante, Mirella Moro

Abstract: The concept of versioning was initially proposed for controlling design evolution on computer aided design and software engineering. On the context of database systems, versioning is applied for managing the evolution of different elements of the data. Modern database systems provide not only powerful data models but also complex query languages that have evolved to include several features from complex programming languages. While most related work focuses on different aspects of the concepts, designing models, and processing of versions efficiently, there is yet to be a formal definition of a query language for database systems with versions control. In this work we propose a query language, named Versioned Object Query Language (VOQL), that extends ODMG Object Query Language (OQL) with new features to recover object versions. We provide a precise definition of VOQL through a type system and we prove it safe in relation to a small-step operational semantics. Finally, we validate the proposed definition by implementing an interpreter for VOQL.

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DOI: 10.3217/jucs-012-02-0160

Authors: Ping-Yu Hsu, Ping-Ho Ting

Abstract: As enterprises worldwide race to improve real-time management to improve productivity, customer services and flexibility, huge resources have been invested into enterprise systems (ESs). All modern ESs adopt an n-tier client-server architecture, which includes several application servers to hold users and applications. As in any other multi-server environment, the load distributions, and user distributions in particular, become a critical issue in tuning system performance. In stateful ESs, a user who logs onto an application server and stays connected to the server for an entire working session, which can last for days, evokes each application. Therefore, admitting a user onto an application server affects not only current but also future performance of that server. Although the n-tier architecture may involve web servers, there is little in the literature in Distributed Web Server Architectures that considers the effects of distributing users instead of individual requests to servers. The algorithm proposed in this paper gives specific suggestions in user distributions and the minimal number of servers required based on the application reusability threshold. A heuristic version of the algorithm is also presented to improve the performance. The paper also discusses how to apply association rules to predict new user behavior when distributing users in the run-time. The distributions recommended by the algorithms are compared against the Round-Robin distributions on a set of real data derived from a mid size company. The result shows that the user distributions suggested have better performance than Round Robin distributions.

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