1,657 research outputs found

    Ontology-based context-sensitive software security knowledge management modeling

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    The disconcerting increase in the number of security attacks on software calls for an imminent need for including secure development practices within the software development life cycle. The software security management system has received considerable attention lately and various efforts have been made in this direction. However, security is usually only considered in the early stages of the development of software. Thus, this leads to stating other vulnerabilities from a security perspective. Moreover, despite the abundance of security knowledge available online and in books, the systems that are being developed are seldom sufficiently secure. In this paper, we have highlighted the need for including application context sensitive modeling within a case-based software security management system. Furthermore, we have taken the context-driven and ontology-based frameworks and prioritized their attributes according to their weights which were achieved by using the Fuzzy AHP methodology

    The Assessment of the Usability of Digital Educational Resources: An interdisciplinary analysis from two systematic reviews

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    Producción CientíficaInternational reports analyzing current and future educational trends with an emphasis on technologies applied to education declare the importance of the design and application of digital educational resources. Guaranteeing its usability allows obtaining an adequate resource with a high pedagogical and technological quality. The objective of this paper is to analyze the empirical researches to determine if exists convergence between educational and computational researches on the assessment of the usability of digital educational resources. To fulfill the objective, the PRISMA protocol was used to carry out two systematic reviews and answer the two scientific questions. The results show that in few cases an adequate integration is achieved between: (1) the criteria for assessing usability as established by Software Engineering; (2) the methods and computational models to assess usability and, (3) the criteria established in pedagogical usability. Due to these shortcomings, a model for evaluating the usability of digital educational resources is proposed as future work. It concludes with the importance of interdisciplinary integration to assess the usability of digital educational resources

    A systematic literature review on the semi-automatic configuration of extended product lines

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    Product line engineering has become essential in mass customisation given its ability to reduce production costs and time to market, and to improve product quality and customer satisfaction. In product line literature, mass customisation is known as product configuration. Currently, there are multiple heterogeneous contributions in the product line configuration domain. However, a secondary study that shows an overview of the progress, trends, and gaps faced by researchers in this domain is still missing. In this context, we provide a comprehensive systematic literature review to discover which approaches exist to support the configuration process of extended product lines and how these approaches perform in practice. Extend product lines consider non-functional properties in the product line modelling. We compare and classify a total of 66 primary studies from 2000 to 2016. Mainly, we give an in-depth view of techniques used by each work, how these techniques are evaluated and their main shortcomings. As main results, our review identified (i) the need to improve the quality of the evaluation of existing approaches, (ii) a lack of hybrid solutions to support multiple configuration constraints, and (iii) a need to improve scalability and performance conditions

    Strategies for the intelligent selection of components

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    It is becoming common to build applications as component-intensive systems - a mixture of fresh code and existing components. For application developers the selection of components to incorporate is key to overall system quality - so they want the `best\u27. For each selection task, the application developer will de ne requirements for the ideal component and use them to select the most suitable one. While many software selection processes exist there is a lack of repeatable, usable, exible, automated processes with tool support. This investigation has focussed on nding and implementing strategies to enhance the selection of software components. The study was built around four research elements, targeting characterisation, process, strategies and evaluation. A Post-positivist methodology was used with the Spiral Development Model structuring the investigation. Data for the study is generated using a range of qualitative and quantitative methods including a survey approach, a range of case studies and quasiexperiments to focus on the speci c tuning of tools and techniques. Evaluation and review are integral to the SDM: a Goal-Question-Metric (GQM)-based approach was applied to every Spiral

    VIKOR Technique:A Systematic Review of the State of the Art Literature on Methodologies and Applications

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    The main objective of this paper is to present a systematic review of the VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method in several application areas such as sustainability and renewable energy. This study reviewed a total of 176 papers, published in 2004 to 2015, from 83 high-ranking journals; most of which were related to Operational Research, Management Sciences, decision making, sustainability and renewable energy and were extracted from the “Web of Science and Scopus” databases. Papers were classified into 15 main application areas. Furthermore, papers were categorized based on the nationalities of authors, dates of publications, techniques and methods, type of studies, the names of the journals and studies purposes. The results of this study indicated that more papers on VIKOR technique were published in 2013 than in any other year. In addition, 13 papers were published about sustainability and renewable energy fields. Furthermore, VIKOR and fuzzy VIKOR methods, had the first rank in use. Additionally, the Journal of Expert Systems with Applications was the most significant journal in this study, with 27 publications on the topic. Finally, Taiwan had the first rank from 22 nationalities which used VIKOR technique

    INQUIRIES IN INTELLIGENT INFORMATION SYSTEMS: NEW TRAJECTORIES AND PARADIGMS

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    Rapid Digital transformation drives organizations to continually revitalize their business models so organizations can excel in such aggressive global competition. Intelligent Information Systems (IIS) have enabled organizations to achieve many strategic and market leverages. Despite the increasing intelligence competencies offered by IIS, they are still limited in many cognitive functions. Elevating the cognitive competencies offered by IIS would impact the organizational strategic positions. With the advent of Deep Learning (DL), IoT, and Edge Computing, IISs has witnessed a leap in their intelligence competencies. DL has been applied to many business areas and many industries such as real estate and manufacturing. Moreover, despite the complexity of DL models, many research dedicated efforts to apply DL to limited computational devices, such as IoTs. Applying deep learning for IoTs will turn everyday devices into intelligent interactive assistants. IISs suffer from many challenges that affect their service quality, process quality, and information quality. These challenges affected, in turn, user acceptance in terms of satisfaction, use, and trust. Moreover, Information Systems (IS) has conducted very little research on IIS development and the foreseeable contribution for the new paradigms to address IIS challenges. Therefore, this research aims to investigate how the employment of new AI paradigms would enhance the overall quality and consequently user acceptance of IIS. This research employs different AI paradigms to develop two different IIS. The first system uses deep learning, edge computing, and IoT to develop scene-aware ridesharing mentoring. The first developed system enhances the efficiency, privacy, and responsiveness of current ridesharing monitoring solutions. The second system aims to enhance the real estate searching process by formulating the search problem as a Multi-criteria decision. The system also allows users to filter properties based on their degree of damage, where a deep learning network allocates damages in 12 each real estate image. The system enhances real-estate website service quality by enhancing flexibility, relevancy, and efficiency. The research contributes to the Information Systems research by developing two Design Science artifacts. Both artifacts are adding to the IS knowledge base in terms of integrating different components, measurements, and techniques coherently and logically to effectively address important issues in IIS. The research also adds to the IS environment by addressing important business requirements that current methodologies and paradigms are not fulfilled. The research also highlights that most IIS overlook important design guidelines due to the lack of relevant evaluation metrics for different business problems
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