Search

We conducted a mapping study to investigate how the scientific community uses Ambient intelligence technologies to assist visually impaired people. Our initial search identified a total of 807 publications; after applying our selection criteria, we accepted 65 publications. We seek to show which technologies, methodologies, techniques, architectures, features, and evaluations are most used. Results indicated that only 15.53% have a specific focus on people who are visually impaired. Most of the results were published in 2015. Most authors used their own architectures. Many results used techniques such as Detection and recognition, Artificial Intelligence, Networking, and others.

Data visualization is an arrangement that presents data in manners that enable the utilization of human subjective and visual capacities. It is the method used to convert crude information into some visual structure. It uses designs and visuals to help with the psychological burden of comprehending big data. The burden put on general well-being because of the coronavirus is exacerbated by the ceaseless rise of new strains and unanswered inquiries concerning viral spread inside the host. Observations regarding the course of coronaviruses in people have been step by step expanded and extended to numerous regions worldwide. These observation programs have created an enormous amount of genomic information regarding coronaviruses, which encourages the investigation of the infection by computational strategies that are proficient and cost effective.

The year 2018 marked the tenth anniversary of the Symposium on Search Based Software Engineering (SSBSE). In order to better understand the characteristics and evolution of papers published in SSBSE, this work reports results from a mapping study targeting the ten proceedings of SSBSE. Our goal is to identify and to analyze authorship collaborations, the impact and relevance of SSBSE in terms of citations, the software engineering areas commonly studied as well as the new problems recently solved, the computational intelligence techniques preferred by authors and the rigour of experiments conducted in the papers. Besides this analysis, we list some recommendations to new authors who envisage to publish their work in SSBSE. Despite of existing mapping studies on SBSE, our contribution in this work is to provide information to researchers and practitioners willing to enter the SBSE field, being a source of information to strengthen the symposium, guide new studies, and motivate new collaboration among research groups.

The aim of this study is to perform a Systematic Literature Mapping (SLM) about methodologies, methods, techniques and tools used on the development of Systematic Literature Reviews (SLR). As a result, on the mapping, we expected to find and classify methodologies, methods, techniques and tools commonly used on SLR. In addition, we have considered other contexts such as, Medicine or Education with the purpose of getting multiple methodologies, methods, techniques and tools that allow performing SLR on efficient ways. It is mainly expected to identify techniques related to research questions formulation and the methods used for building search strings in order to get the higher number of studies associated to the research topic. In our study, we found multiple methodologies, methods, techniques and tools already implemented for performing SLRs On the mapping we describe some of them to highlight the most used and referenced studies.

Data mining techniques (DMT) provide powerful tools to extract knowledge from data helping in decision making. Medicine, like many other fields, is using DM in diabetes, cardiology, cancer and other diseases. In this paper, we investigate the use of DMT in diabetes, in particular in diabetes self-management (DSM). The purpose is to conduct a systematic mapping study to review primary studies investigating DMT in DSM. This mapping study aims to summarize and analyze knowledge on: (1) years and sources of DSM publications, (2) type of diabetes that took most attention, (3) DM tasks and techniques most frequently used, and (4) the considered functionalities. A total of 57 papers published between 2000 and April 2017 were selected and analyzed regarding four research questions. The study shows that prediction was largely the most used DM task and Neural Networks were the most frequently used technique. Moreover, T1DM is largely the type of diabetes that is most concerned by the studies so as the Prediction of blood glucose.

Usability evaluation is currently considered critical for the success of mobile interactive applications. This paper presents a Systematic Mapping Study (SMS) that has been conducted to investigate the literature related to the Mobile Usability Evaluation (MUE) techniques. This mapping study builds on the followings classification criteria for the selection of studies: research approaches, research types, research domains, Usability evaluation methods, data collection tools, types of questionnaires that have been used in the empirical evaluations of these studies, and software quality (SQ) models. Publication channels and trends were also identified and 81 papers of MUE were selected.

Context: In experimental software engineering (ESE), experimental replication is applied to validate results of an experiment. Much information and one version of the experimental materials are required for replication. Prior to the replication execution, all or part of the materials may require changes, producing new or modified versions of these, which should be incorporated into the material of the original experiment. There is a direct relationship between the increase in the number of replications with the increase of versions of the experimental material, which commonly causes confusion and disorder for experimental administrators. Objective: The aim of this paper is to conduct a mapping study to locate articles about the use of experimental material management tools in experimental replication in ESE. Method: We applied the mapping study to search, analyze and select published papers from reported replications. Results: We analyzed a total of 592 articles published from 1998 to 2014, 24 of them have been pre-selected and 4 have finally been selected. Conclusion: The results show the limited existence of articles on this subject. In addition, our analysis has allowed to identify that most of them suffer from problems in versions management for both replication and experimental material. These data provide information of interest to start a research about adoption of the paradigm of software configuration management inside the management of the experimental material in ESE.

Clinical databases often comprise noisy, inconsistent, missing, imbalanced and high dimensional data. These challenges may reduce the performance of DM techniques. Data preprocessing is, therefore, essential step in order to use DM algorithms on these medical datasets as regards making it appropriate and suitable for mining. The objective is to carry out a systematic mapping study in order to review the use of preprocessing techniques in clinical datasets. As results, 110 papers published between January 2000 and March 2017 were, selected, analyzed and classified according to publication years and channels, research type and the preprocessing tasks used. This study shows that researchers have paid a considerable amount of attention to preprocessing in medical DM in last decade and a significant number of the selected studies used data reduction and cleaning preprocessing tasks.

Context-of-use is a vital consideration when evaluating the usability of mobile applications. Thus, when defining sets of heuristics for the usability evaluation of mobile applications, a common practice has been to include one or more heuristics that consider context-of-use. Yet, most evaluations are conducted within usability labs. Consequently, the aim of this research is to question the utility of attempting to include inherently complex areas of context-of-use within limited sets of mobile application usability heuristics. To address this, a mapping study uncovered six sets of heuristics that can be applied to mobile application usability evaluations. A within-subjects empirical test with six Human-Computer Interaction practitioners evaluated a well-known travel mobile application using three sets of the mapped heuristics. The study found that the common practice of including context-of-use within mobile application usability heuristics is an ineffective approach.

This paper reports on a mapping study of dissertation supervision across distance Master’s Courses in the University of London. The study suggests that there is a wide diversity of ways of handling Master’s students at a distance due to the multiplicity of factors that impinge on distance supervision, and a range of requirements in terms of the dissertation outcomes or products. The findings also suggest that in terms of the dissertation process, the course or programme leader plays a key role in dissertation supervision at a distance. The distance element means that course leaders take a more highly structured and hands-on approach to provide support for students embarking on the dissertation. The paper suggests that rather than conceptualising the supervisory process on one axis (supervisor-supervisee), we need to understand it as a complex relationship involving multiple actors.

In this article, we report the findings of a systematic literature mapping study aimed at identifying contextual factors that should be described in case studies about teams in software engineering. As a result, we identified 26 factors, which we organized in five dimensions: characteristics of individuals, groups, team processes, projects and organizations. These dimensions and factors can guide future reports to present better descriptions of the context in which their software teams are studied.

Software ecosystems is one promising strategy for organizations to find new market segments, new innovative value propositions creating new value streams. However, understanding internal and external actors, resources and relationships that could be leveraged in a SECO is critical for their strategic decisions. The consequence of mistakes may be costly failures that can force an organization to move out of a market. This paper describes a systematic mapping study that targets description of software ecosystems. Our conjecture is that adequate description support leads to modeling, which will improve information and in turn strategic decisions. The survey searches existing literature for description techniques and their application for comprehensive description.

Part 13: Metrics, Standards and Regulation; International audience; PLM encompasses a wide array of expertise, from designing green products to digital factories, with perspectives ranging from an IT standpoint to business strategies, encompassing products, processes and services. Hence, identifying the contours of PLM as a science through the themes, trends and clusters of its scientific literature is very challenging. At the same time, being able to portray PLM will benefit the PLM community, including researchers and practitioners, and should help foresee its future. This work examines PLM research bibliometric trends over the last ten years. We review the scientific literature published in English from 2005 to 2014 in peer-reviewed journals and conferences. Paper keywords are analyzed so as to identify trends and reveal the clusters of related themes based on the occurrences of words and the frequency of associations between them. Amongst the findings we observe that PLM coverage is both very large (2847 keywords being used over a decade) and very thin (2134 of these keywords appear only once in the decade). We also observe that the keyword showing the highest increase is Building Information Modeling (BIM).

Part 6: Investigating Enterprise Models; International audience; Enterprises operate in dynamically changing environments that have an influence on both business and IT areas. Capabilities have been proposed as instruments to align business and IT in such environments. One aim of enterprise modelling is a better communication between the stakeholders of an enterprise at various levels. Thus, the alignment can be facilitated by the exploitation of enterprise models as an abstraction instrument. In this respective the paper analyses the methods for capability design and development from the enterprise modelling perspective by conducting a mapping study, i.e. the level of methodological support for capability modelling is investigated. For this purpose 112 journals and 24 conference proceedings were analysed. The most important findings are that the research in capability design (i) adopts empirical research, mostly in form of case studies and surveys (ii) is mainly motivated by Resource Based View (RBV) and changing environments (iii) proposes development approaches and frameworks as solution artefacts, (iv) lately receives attention in the Information Systems Development & Tools of MIS subject classification lately, (v) provides a scarce methodological support that is mostly represented as procedures and most importantly (vi) only to some extent exploit enterprise models that could enhance stakeholder communication at various abstraction levels.

Background – Startup companies are becoming important suppliers of innovative and software intensive products. The failure rate among startups is high due to lack of resources, immaturity, multiple influences and dynamic technologies. However, software product engineering is the core activity in startups, therefore inadequacies in applied engineering practices might be a significant contributing factor for high failure rates. Aim – This study identifies and categorizes software engineering knowledge areas utilized in startups to map out the state-of-art, identifying gaps for further research. Method – We perform a systematic literature mapping study, applying snowball sampling to identify relevant primary studies. Results – We have identified 54 practices from 14 studies. Although 11 of 15 main knowledge areas from SWEBOK are covered, a large part of categories is not. Conclusions – Existing research does not provide reliable support for software engineering in any phase of a startup life cycle. Transfer of results to other startups is difficult due to low rigor in current studies.

The mobile devices market has grown substantially, along with significant developments in mobile interactive technologies. Devices such as tablets, smartphones and others have increasingly become more popular and helped improve the way people interact and exchange information. The aim of this paper is to perform a systematic mapping of the literature regarding the use of heuristic evaluation methods applied on mobile applications. The aims of this research were twofold: analysing what are the most used sets of usability heuristics on usability evaluations of mobile devices, providing a common base to improve mobile design and usability evaluation; analysing details of how usability inspections of mobile applications have been conducted. The results show that different heuristics have been reported in research papers to evaluate usability of mobile devices. The study identified a total of 9 different heuristics sets means of the literature mapping. The traditional set of heuristics proposed by Nielsen and Molich was still the most used set of heuristics in heuristic usability evaluations of mobile devices, but the proposal of new specific heuristics for mobile interfaces has grown substantially.