Association For Computing Machinery Research Articles

OpenRank – a novel approach to rank universities using objective and publicly verifiable data sources

PurposeAcademic rankings are facing various issues, including the use of data sources that are not publicly verifiable, subjective parameters, a narrow focus on research productivity and regional biases and so forth. This research work is intended to enhance creditability of the ranking process by using the objective indicators based on publicly verifiable data sources.Design/methodology/approachThe proposed ranking methodology – OpenRank – drives the objective indicators from two well-known publicly verifiable data repositories: the ArnetMiner and DBpedia.FindingsThe resultant academic ranking reflects common tendencies of the international academic rankings published by the Shanghai Ranking Consultancy (SRC), Quacquarelli Symonds (QS) and Times Higher Education (THE). Evaluation of the proposed methodology advocates its effectiveness and quick reproducibility with low cost of data collection.Research limitations/implicationsImplementation of the OpenRank methodology faced the issue of availability of the quality data. In future, accuracy of the academic rankings can be improved further by employing more relevant public data sources like the Microsoft Academic Graph, millions of graduate's profiles available in the LinkedIn repositories and the bibliographic data maintained by Association for Computing Machinery and Scopus and so forth.Practical implicationsThe suggested use of open data sources would offer new dimensions to evaluate academic performance of the higher education institutions (HEIs) and having comprehensive understanding of the catalyst factors in the higher education.Social implicationsThe research work highlighted the need of a purposely built, publicly verifiable electronic data source for performance evaluation of the global HEIs. Availability of such a global database would help in better academic planning, monitoring and analysis. Definitely, more transparent, reliable and less controversial academic rankings can be generated by employing the aspired data source.Originality/valueWe suggested a satisfying solution for improvement of the HEIs' ranking process by making the following contributions: (1) enhancing creditability of the ranking results by merely employing the objective performance indicators extracted from the publicly verifiable data sources, (2) developing an academic ranking methodology based on the objective indicators using two well-known data repositories, the DBpedia and ArnetMiner and (3) demonstrating effectiveness of the proposed ranking methodology on the real data sources.

An Overview of Social Media Apps and their Potential Role in Geospatial Research

Social media apps provide analysts with a wide range of data to study behavioral aspects of our everyday lives and to answer societal questions. Although social media data analysis is booming, only a handful of prominent social media apps, such as Twitter, Foursquare/Swarm, Facebook, or LinkedIn are typically used for this purpose. However, there is a large selection of less known social media apps that go unnoticed in the scientific community. This paper reviews 110 social media apps and assesses their potential usability in geospatial research through providing metrics on selected characteristics. About half of the apps (57 out of 110) offer an Application Programming Interface (API) for data access, where rate limits, fee models, and type of spatial data available for download vary strongly between the different apps. To determine the current role and relevance of social media platforms that offer an API in academic research, a search for scientific papers on Google Scholar, the Association for Computing Machinery (ACM) Digital Library, and the Science Core Collection of the Web of Science (WoS) is conducted. This search revealed that Google Scholar returns the highest number of documents (Mean = 183,512) compared to ACM (Mean = 1895) and WoS (Mean = 1495), and that data and usage patterns from prominent social media apps are more frequently analyzed in research studies than those of less known apps. The WoS citation database was also used to generate lists of themes covered in academic publications that analyze the 57 social media platforms that offer an API. Results show that among these 57 platforms, for 26 apps at least some papers evolve around a geospatial discipline, such as Geography, Remote Sensing, Transportation, or Urban Planning. This analysis, therefore, connects apps with commonly used research themes, and together with tabulated API characteristics can help researchers to identify potentially suitable social media apps for their research. Word clouds generated from titles and abstracts of papers associated with the 57 platforms, grouped into seven thematic categories, show further refinement of topics addressed in the analysis of social media platforms. Considering various evaluation criteria, such as provision of geospatial data or the number (i.e., absence) of currently published research papers in connection with a social media platform, the study concludes that among the numerous social media apps available today, 17 less known apps deserve closer examination since they might be used to investigate previously underexplored research topics. It is hoped that this study can serve as a reference for the analysis of the social media landscape in the future.

Augmented reality in patient education and health literacy: a scoping review protocol.

BackgroundHealth literacy enables the patients in understanding the basic healthcare information and taking informed health decisions; thus, it is a desirable goal of any healthcare system. It increases patients’ adherence to treatment, improves the quality of care and eases the overall burden on the healthcare system. In recent years, technological solutions are being increasingly used in educating patients and achieving better health literacy. Augmented reality (AR) provides powerful, contextual and situated learning experiences and supplements the real world with virtual objects. AR could potentially be an effective learning methodology for the patients, thus, warranting a comprehensive overview of the current state of AR in patient education and health literacy.MethodsThe proposed scoping review will be based on the framework developed by Arksey and O’Malley, including the refinements suggested by Levac et al. A systematic search for references in the published literature will be conducted in nine research databases—Institute of Electrical and Electronics Engineers (IEEE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), PubMed, PsycInfo, Embase, Web of Science, Scopus, Association for Computing Machinery (ACM) and Association for Information Systems eLibrary (AISeL). The unpublished studies from ProQuest Dissertations and Theses, Conference Proceedings Citation Index and grey literature references obtained from a web search will also be included. Databases will be searched from inception to 14 January 2020. Two independent reviewers will screen the studies from the search results in two successive stages of title/abstract screening followed by full-text screening. Data variables will be extracted from the selected studies to characterise study design, type of AR technology employed and the relational factors affecting patient education. Lastly, key stakeholders will be consulted to gather their insights about the study findings.Ethics and disseminationThe results will be disseminated through stakeholder meetings and conference presentations. The data used are from publicly available secondary sources, so this study does not require ethical review.

The Effects of Gamification on Computerized Cognitive Training: Systematic Review and Meta-Analysis.

BackgroundThere has been a growing interest in the application of gamification (ie, the use of game elements) to computerized cognitive training. The introduction of targeted gamification features to such tasks may increase motivation and engagement as well as improve intervention effects. However, it is possible that game elements can also have adverse effects on cognitive training (eg, be a distraction), which can outweigh their potential motivational benefits. So far, little is known about the effectiveness of such applications.ObjectiveThis study aims to conduct a systematic review and meta-analysis to investigate the effect of gamification on process outcomes (eg, motivation) and on changes in the training domain (eg, cognition), as well as to explore the role of potential moderators.MethodsWe searched PsycINFO, Cumulative Index to Nursing and Allied Health Literature, ProQuest Psychology, Web of Science, Scopus, PubMed, Science Direct, Excerpta Medica dataBASE, Institute of Electrical and Electronics Engineers Xplore, Association for Computing Machinery, and a range of gray-area literature databases. The searches included papers published between 2008 and 2018. Meta-analyses were performed using a random-effects model.ResultsThe systematic review identified 49 studies, of which 9 randomized controlled trials were included in the meta-analysis. The results of the review indicated that research in this context is still developing and lacks well-controlled empirical studies. Gamification in cognitive training is applied to a large range of age groups and audiences and is mostly delivered at a research site through computers. Rewards and feedback continue to dominate the gamification landscape, whereas social-oriented features (eg, competition) are underused. The meta-analyses showed that gamified training tasks were more motivating/engaging (Hedges g=0.72) and more demanding/difficult (Hedges g=–0.52) than non- or less-gamified tasks, whereas no effects on the training domain were found. Furthermore, no variables moderated the impact of gamified training tasks. However, meta-analytic findings were limited due to a small number of studies.ConclusionsOverall, this review provides an overview of the existing research in the domain and provides evidence for the effectiveness of gamification in improving motivation/engagement in the context of cognitive training. We discuss the shortcomings in the current literature and provide recommendations for future research.

Influences on the Uptake of and Engagement With Health and Well-Being Smartphone Apps: Systematic Review.

BackgroundThe public health impact of health and well-being digital interventions is dependent upon sufficient real-world uptake and engagement. Uptake is currently largely dependent on popularity indicators (eg, ranking and user ratings on app stores), which may not correspond with effectiveness, and rapid disengagement is common. Therefore, there is an urgent need to identify factors that influence uptake and engagement with health and well-being apps to inform new approaches that promote the effective use of such tools.ObjectiveThis review aimed to understand what is known about influences on the uptake of and engagement with health and well-being smartphone apps among adults.MethodsWe conducted a systematic review of quantitative, qualitative, and mixed methods studies. Studies conducted on adults were included if they focused on health and well-being smartphone apps reporting on uptake and engagement behavior. Studies identified through a systematic search in Medical Literature Analysis and Retrieval System Online, or MEDLARS Online (MEDLINE), EMBASE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsychINFO, Scopus, Cochrane library databases, DataBase systems and Logic Programming (DBLP), and Association for Computing Machinery (ACM) Digital library were screened, with a proportion screened independently by 2 authors. Data synthesis and interpretation were undertaken using a deductive iterative process. External validity checking was undertaken by an independent researcher. A narrative synthesis of the findings was structured around the components of the capability, opportunity, motivation, behavior change model and the theoretical domains framework (TDF).ResultsOf the 7640 identified studies, 41 were included in the review. Factors related to uptake (U), engagement (E), or both (B) were identified. Under capability, the main factors identified were app literacy skills (B), app awareness (U), available user guidance (B), health information (E), statistical information on progress (E), well-designed reminders (E), features to reduce cognitive load (E), and self-monitoring features (E). Availability at low cost (U), positive tone, and personalization (E) were identified as physical opportunity factors, whereas recommendations for health and well-being apps (U), embedded health professional support (E), and social networking (E) possibilities were social opportunity factors. Finally, the motivation factors included positive feedback (E), available rewards (E), goal setting (E), and the perceived utility of the app (E).ConclusionsAcross a wide range of populations and behaviors, 26 factors relating to capability, opportunity, and motivation appear to influence the uptake of and engagement with health and well-being smartphone apps. Our recommendations may help app developers, health app portal developers, and policy makers in the optimization of health and well-being apps.

Explainable artificial intelligence models using real-world electronic healthrecord data: a systematic scoping review.

To conduct a systematic scoping review of explainable artificial intelligence (XAI) models that use real-world electronic health record data, categorize these techniques according to different biomedical applications, identify gaps of current studies, and suggest future research directions. We searched MEDLINE, IEEE Xplore, and the Association for Computing Machinery (ACM) Digital Library to identify relevant papers published between January 1, 2009 and May 1, 2019. We summarized these studies based on the year of publication, prediction tasks, machine learning algorithm, dataset(s) used to build the models, the scope, category, and evaluation of the XAI methods. We further assessed the reproducibility of the studies in terms of the availability of data and code and discussed open issues and challenges. Forty-two articles were included in this review. We reported the research trend and most-studied diseases. We grouped XAI methods into 5 categories: knowledge distillation and rule extraction (N = 13), intrinsically interpretable models (N = 9), data dimensionality reduction (N = 8), attention mechanism (N = 7), and feature interaction and importance (N = 5). XAI evaluation is an open issue that requiresa deeper focus in the case of medical applications. We also discuss the importance of reproducibility of research work in this field, as well as the challenges and opportunities of XAI from 2 medical professionals' point of view. Based on our review, we found that XAI evaluation in medicine has not been adequately and formally practiced. Reproducibility remains a critical concern. Ample opportunities exist to advance XAI research in medicine.

Barriers and Facilitators That Influence Telemedicine-Based, Real-Time, Online Consultation at Patients' Homes: Systematic Literature Review.

BackgroundHealth care providers are adopting information and communication technologies (ICTs) to enhance their services. Telemedicine is one of the services that rely heavily on ICTs to enable remote patients to communicate with health care professionals; in this case, the patient communicates with the health care professional for a follow-up or for a consultation about his or her health condition. This communication process is referred to as an e-consultation. In this paper, telemedicine services refer to health care services that use ICTs, which enable patients to share, transfer, and communicate data or information in real time (ie, synchronous) from their home with a care provider—normally a physician—at a clinical site. However, the use of e-consultation services can be positively or negatively influenced by external or internal factors. External factors refer to the environment surrounding the system as well as the system itself, while internal factors refer to user behavior and motivation.ObjectiveThis review aims to investigate the barriers and the facilitators that influence the use of home consultation systems in the health care context. This review also aims to identify the effectiveness of Home Online Health Consultation (HOHC) systems in improving patients’ health as well as their satisfaction with the systems.MethodsWe conducted a systematic literature review to search for articles—empirical studies—about online health consultation in four digital libraries: Scopus, Association for Computing Machinery, PubMed, and Web of Science. The database search yielded 2518 articles; after applying the inclusion and exclusion criteria, the number of included articles for the final review was 45. A qualitative content analysis was performed to identify barriers and facilitators to HOHC systems, their effectiveness, and patients’ satisfaction with them.ResultsThe systematic literature review identified several external and internal facilitators and barriers to HOHC systems that were used in the creation of a HOHC framework. The framework consists of four requirements; the framework also consists of 17 facilitators and eight barriers, which were further categorized as internal and external influencers on HOHC.ConclusionsPatients from different age groups and with different health conditions benefited from remote health services. HOHC via video conferencing was effective in delivering online treatment and was well-accepted by patients, as it simulated in-person, face-to-face consultation. Acceptance by patients increased as a result of online consultation facilitators that promoted effective and convenient remote treatment. However, some patients preferred face-to-face consultation and showed resistance to online consultation. Resistance to online consultation was influenced by some of the identified barriers. Overall, the framework identified the facilitators and barriers that positively and negatively influenced the uptake of HOHC systems, respectively.

Utilization of Mobile Mental Health Services among Syrian Refugees and Other Vulnerable Arab Populations-A Systematic Review.

The global refugee crisis is at its most critical state in history; Syria alone has produced 12 million internally displaced persons, with another 5 million refugees seeking protection across the globe. Faced with the heavy burden of mental distress carried by a massive refugee influx, many host nations lack the service capacity to respond adequately. While mobile mental health (mMHealth) applications and platforms have the potential to augment screenings and interventions for vulnerable populations, an insufficient gender and cultural adaptation of technology may drastically hamper its uptake in Arab refugees. Reporting only papers originating from Middle Eastern and/or Arab nations or refugee host nations, this systematic review evaluates the available literature published between 2000 and 2019 on the usage acceptability of mMHealth in Syrian refugees and other vulnerable Arab populations. We conducted a systematic review in PubMed, PsychInfo, Association of Computing Machinery (ACM) and the Directory of Open Access Journals (DOAJ) using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to identify studies that addressed mMHealth implementation in these populations; of a total of 607 articles identified, only 10 (1.6%) available, unique articles met our search criteria. These studies discussed the feasibility and efficacy of mMHealth applications and the barriers to their uptake. The few existing studies show positive impacts of mMHealth on the access to services and on treatment outcomes but also reveal a paucity of literature on mMHealth for vulnerable Arab populations. These findings indicate a critical need for research on the barriers to mMHealth uptake, to bolster service capacity in the Arab Region and in the refugee diaspora of other, non-Arab host countries.

Analysis on the Possibility of RISC-V Adoption

Author(s): Scott, Ian | Abstract: As the interface between hardware and software, Instruction Set Architectures (ISAs) play a key role in the operation of computers. While both hardware and software have continued to evolve rapidly over time, ISAs have undergone minimal change. Since its release in 2010, RISC-V has begun to erode the industry aversion to ISA innovation. Established on the principals of the Reduced Instruction Set Computer (RISC), and as an open source ISA, RISC-V offers many benefits over popular ISAs like Intel’s x86 and Arm Holding’s Advanced RISC Machine (ARM). In this literature review I evaluate the literature discussing: What makes changing Instruction Set Architectures difficultWhy might the industry choose to implement RISC-V When researching this topic I visited the IEEE (Institute of Electrical and Electronics Engineers), INSPEC (Engineering Village), and ACM (Association for Computing Machinery) Digital Library databases. I used the search terms, “RISC-V”, “Instruction Set Architecture”, “RISC-V” AND “x86”, and “RISC-V” AND “Instruction Set Architecture”. This literature review evaluates 10 papers on implementation of RISC-V. As this paper was intended to cover recent developments in the field, publication dates were limited to from 2015 to present.

Klasifikasi Teks Berbasis Ontologi Untuk Dokumen Tugas Akhir Berbahasa Indonesia

In this research, the classification of the final project document in Informatics Engineering UMM. The problem faced is the difficulty of finding relevant information and the difficulty of categorizing the TA documents according to areas of interest if it should be done manually. The purpose of this research is to get information based on abstract TA according to the category and make it easier to classify the TA document according to the field of interest. The categories used are the areas of interest in the study program: RPL, Computer Networking, Intelligent Game and Data Science. The data used TA documents as many as 500 data. The stage is to build and model ontology rules according to the data obtained with reference data of UMM Informatics Engineering Curriculum 2017 sourced from the Association for Computing Machinery (ACM) of the IEEE Computer Society. Ontology aims to classify the objects that exist in the collection without requiring the data train. To support the classification process used dao method. The dao method is used to calculate the similarity between documents from an existing node on the ontology by looking at the closest distance. Stage testing system using accuracy obtained result of 87%. This shows that ontologists are able to classify documents without using train data.

Ekspansi Query Berbasis Semantik Pada Online Public Access Catalog (OPAC)

Digital library is an important system useful as the fulfillment of information needs library collection. The Online Public Access Catalog (OPAC) is a feature available in digital libraries that lets you browse library collections. In this research, semantic based query expansion system is developed. The goal is to improve search results to be more relevant. Domain used is information technology where book data obtained from online book site and book publishing sites as much as 500 data. The stage is to build ontology according to the data obtained. The formation of ontology refers to the data of UMM Informatics Engineering curriculum which refers to the Association for Computing Machinery (ACM) Ontology is applied to find the connection between a user entered keyword. To support the search results used cosine similarity method. Cosine similarity is a method to calculate the similarity between search results with user keywords so as to generate search results ranking. Stages of testing the system using precision obtained a value of 65.6. This indicates that the system is capable enough to provide search results that are relevant to a user's search keyword.

GeoAI at ACM SIGSPATIAL

Geospatial artificial intelligence (GeoAI) is an interdisciplinary field that has received tremendous attention from both academia and industry in recent years. This article reviews the series of GeoAI workshops held at the Association for Computing Machinery (ACM) International Conference on Advances in Geographic Information Systems (SIGSPATIAL) since 2017. These workshops have provided researchers a forum to present GeoAI advances covering a wide range of topics, such as geospatial image processing, transportation modeling, public health, and digital humanities. We provide a summary of these topics and the research articles presented at the 2017, 2018, and 2019 GeoAI workshops. We conclude with a list of open research directions for this rapidly advancing field.

A Systematic Mapping of Translation-Enabling Technologies for Sign Languages

Sign languages (SL) are the first language for most deaf people. Consequently, bidirectional communication among deaf and non-deaf people has always been a challenging issue. Sign language usage has increased due to inclusion policies and general public agreement, which must then become evident in information technologies, in the many facets that comprise sign language understanding and its computational treatment. In this study, we conduct a thorough systematic mapping of translation-enabling technologies for sign languages. This mapping has considered the most recommended guidelines for systematic reviews, i.e., those pertaining software engineering, since there is a need to account for interdisciplinary areas of accessibility, human computer interaction, natural language processing, and education, all of them part of ACM (Association for Computing Machinery) computing classification system directly related to software engineering. An ongoing development of a software tool called SYMPLE (SYstematic Mapping and Parallel Loading Engine) facilitated the querying and construction of a base set of candidate studies. A great diversity of topics has been studied over the last 25 years or so, but this systematic mapping allows for comfortable visualization of predominant areas, venues, top authors, and different measures of concentration and dispersion. The systematic review clearly shows a large number of classifications and subclassifications interspersed over time. This is an area of study in which there is much interest, with a basically steady level of scientific publications over the last decade, concentrated mainly in the European continent. The publications by country, nevertheless, usually favor their local sign language.

Mobile Self-Monitoring ECG Devices to Diagnose Arrhythmia that Coincide with Palpitations: A Scoping Review.

The use and deployment of mobile devices across society is phenomenal with an increasing number of individuals using mobile devices to track their everyday health. However, there is a paucity of academic material examining this recent trend. Specifically, little is known about the use and deployment of mobile heart monitoring devices for measuring palpitations and arrhythmia. In this scoping literature review, we identify the contemporary evidence that reports the use of mobile heart monitoring to assess palpitations and arrhythmia across populations. The review was conducted between February and March 2018. Five electronic databases were searched: Association for Computing Machinery (ACM), CINHAL, Google Scholar, PubMed, and Scopus. A total of 981 records were identified and, following the inclusion and exclusion criteria, nine papers formed the final stage of the review. The results identified a total of six primary themes: purpose, environment, population, wearable devices, assessment, and study design. A further 24 secondary themes were identified across the primary themes. These included detection, cost effectiveness, recruitment, type of setting, type of assessment, and commercial or purpose-built mobile device. This scoping review highlights that further work is required to understand the impact of mobile heart monitoring devices on how arrhythmias and palpitations are assessed and measured across all populations and ages of society. A positive trend revealed by this review demonstrates how mobile heart monitoring devices can support primary care providers to deliver high levels of care at a low cost to the service provider. This has several benefits: alleviation of patient anxiety, lowering the risk of morbidity and mortality, while progressively influencing national and international care pathway guidelines. Limitations of this work include the paucity of knowledge and insight from primary care providers and lack of qualitative material. We argue that future studies consider qualitative and mixed methods approaches to complement quantitative methodologies and to ensure all actors’ experiences are recorded.

Digital and online symptom checkers and assessment services for urgent care to inform a new digital platform: a systematic review

Background Digital and online symptom checkers and assessment services are used by patients seeking guidance about health problems. NHS England is planning to introduce a digital platform (NHS111 Online) to operate alongside the NHS111 urgent-care telephone service. This review focuses on digital and online symptom checkers for urgent health problems. Objectives This systematic review was commissioned to provide NHS England with an independent review of previous research in this area to inform strategic decision-making and service design. Data sources Focused searches of seven bibliographic databases were performed and supplemented by phrase searching for names of symptom checker systems and citation searches of key included studies. The bibliographic databases searched were MEDLINE, EMBASE, The Cochrane Library, CINAHL (Cumulative Index to Nursing and Allied Health Literature), HMIC (Health Management Information Consortium), Web of Science and the Association of Computing Machinery (ACM) Digital Library, from inception up to April 2018. Review methods Brief inclusion criteria were (1) population – general population seeking information online or digitally to address an urgent health problem; (2) intervention – any online or digital service designed to assess symptoms, provide health advice and direct patients to appropriate services; and (3) comparator – telephone or face-to-face assessment, comparative performance in tests or simulations (studies with no comparator were included if they reported relevant outcomes). Outcomes of interest included safety, clinical effectiveness, costs or cost-effectiveness, diagnostic and triage accuracy, use of and contacts with health services, compliance with advice received, patient/carer satisfaction, and equity and inclusion. Inclusion was not restricted by study design. Screening studies for inclusion, data extraction and quality assessment were carried out by one reviewer with a sample checked for accuracy and consistency. Final decisions on study inclusion were taken by consensus of the review team. A narrative synthesis of the included studies was performed and structured around the predefined research questions and key outcomes. The overall strength of evidence for each outcome was classified as ‘stronger’, ‘weaker’, ‘conflicting’ or ‘insufficient’, based on study numbers and design. Results In total, 29 publications describing 27 studies were included. Studies were diverse in their design and methodology. The overall strength of the evidence was weak because it was largely based on observational studies and with a substantial component of non-peer-reviewed grey literature. There was little evidence to suggest that symptom checkers are unsafe, but studies evaluating their safety were generally short term and small scale. Diagnostic accuracy was highly variable between different systems but was generally low. Algorithm-based triage tended to be more risk averse than that of health professionals. Inconsistent evidence was found on effects on service use. There was very limited evidence on patients’ reactions to online triage advice. The studies showed that younger and more highly educated people are more likely to use these services. Study participants generally expressed high levels of satisfaction with digital and online triage services, albeit in uncontrolled studies. Limitations Findings from symptom checker systems for specific conditions may not be applicable to more general systems and vice versa. Studies of symptom checkers as part of electronic consultation systems in general practice were also included, which is a slightly different setting from a general ‘digital 111’ service. Most studies were screened by one reviewer. Conclusions Major uncertainties surround the probable impact of digital 111 services on most outcomes. It will be important to monitor and evaluate the services using all available data sources and by commissioning high-quality research. Future work Priorities for research include comparisons of different systems, rigorous economic evaluations and investigations of patient pathways. Study registration The study is registered as PROSPERO CRD42018093564. Funding The National Institute for Health Research Health Services and Delivery Research programme.

The Deep Learning-Based Recommender System "Pubmender" for Choosing a Biomedical Publication Venue: Development and Validation Study.

BackgroundIt is of great importance for researchers to publish research results in high-quality journals. However, it is often challenging to choose the most suitable publication venue, given the exponential growth of journals and conferences. Although recommender systems have achieved success in promoting movies, music, and products, very few studies have explored recommendation of publication venues, especially for biomedical research. No recommender system exists that can specifically recommend journals in PubMed, the largest collection of biomedical literature.ObjectiveWe aimed to propose a publication recommender system, named Pubmender, to suggest suitable PubMed journals based on a paper’s abstract.MethodsIn Pubmender, pretrained word2vec was first used to construct the start-up feature space. Subsequently, a deep convolutional neural network was constructed to achieve a high-level representation of abstracts, and a fully connected softmax model was adopted to recommend the best journals.ResultsWe collected 880,165 papers from 1130 journals in PubMed Central and extracted abstracts from these papers as an empirical dataset. We compared different recommendation models such as Cavnar-Trenkle on the Microsoft Academic Search (MAS) engine, a collaborative filtering–based recommender system for the digital library of the Association for Computing Machinery (ACM) and CiteSeer. We found the accuracy of our system for the top 10 recommendations to be 87.0%, 22.9%, and 196.0% higher than that of MAS, ACM, and CiteSeer, respectively. In addition, we compared our system with Journal Finder and Journal Suggester, which are tools of Elsevier and Springer, respectively, that help authors find suitable journals in their series. The results revealed that the accuracy of our system was 329% higher than that of Journal Finder and 406% higher than that of Journal Suggester for the top 10 recommendations. Our web service is freely available at https://www.keaml.cn:8081/.ConclusionsOur deep learning–based recommender system can suggest an appropriate journal list to help biomedical scientists and clinicians choose suitable venues for their papers.

Analysis of ICT education in Azerbaijan: current state, foreign experience, problems and prospects

Purpose of the study. The aim of the study is to develop recommendations for improving educational curricula for ICT specialties taught to students in universities of the Azerbaijan Republic.The urgency of the problems outlined in this article is determined by the urgency of the transition to the modernization of the national education system and its integration into the global and world educational space, the requirements of creating an information society in Azerbaijan.Modern society needs qualified personnel who own new information technologies and are able to apply them in various fields of activity. Therefore, the process of modernization of the ICT education system is necessary; curricula should comply with international standards and specialization profile.Materials and research methods. The article provides a comparative analysis of higher professional ICT education in the developed countries of the world, shows the similarities and differences of the educational systems of the United States, European countries, Russia and Azerbaijan, analyzes the trends and features of the educational systems of developed countries, provides a list of IT specialties in demand today and in the near future. . The article also outlines the problems facing higher education institutions that train IT profile specialists.As research materials are used:policy documents of the governing bodies of the Republic of Azerbaijan in the field of higher vocational education;training programs of ICT specialties of universities of the Azerbaijan Republic;study programs of ICT specialties of leading foreign universities;scientific works of domestic and foreign authors in the field of ICT education;recommendations of international organizations ACM (The Association for Computing Machinery) and IEEE (The Institute of Electrical and Electronics Engineers) on the development of curricula for various areas of IT profile.Results. Taking into account the analysis of the curriculum of the IT profile of foreign universities, recommendations of international organizations of standardization, monitoring of the labor market, methodical recommendations were developed to improve ICT education in Azerbaijan. The necessity of modernization of the education system and bringing it into line with modern requirements is shown.Conclusion. In modern conditions of the formation of the information society in Azerbaijan, the educational program of the university should take into account the results of monitoring the labor market and the dynamics of macroeconomic changes, the disappearance of old and the emergence of new activities related to the use of ICT. Therefore, an important task is to prepare highly professional specialists in the country who are able to use and implement the advanced development of information technologies in practice.The recommendations outlined in the article can be used by university professors to improve the educational programs of ICT specialties in Azerbaijan.

Ethics Is a Software Design Concern

The IEEE and Association for Computing Machinery (ACM) joint report Software Engineering Code of Ethics summarizes the responsibilities of software engineers as the following: Software engineers shall commit themselves to making the analysis, specification, design, development, testing and maintenance of software beneficial and respected profession.

Reflecting on the Presence of Science Fiction Robots in Computing Literature

Depictions of robots and AIs in popular science fiction movies and shows have the potential to showcase visions of Human-Robot Interaction (HRI) to the general public and computer science researchers alike. In contrast, studies on the referral, usage, and appropriation of these portrayals by computer scientists in their research publications is an academic void at present. However, such investigations are critical to better understand the potential utility and latent shortcomings of science fiction robots for future HRI research, innovation, and education. To address this research gap, this study investigates the overall presence, nature, and frequency of referrals of 18 popular science fiction robots in the Association for Computing Machinery (ACM) Digital Library. These robots were either portrayed in various movies and subsequently inducted into the Robot Hall of Fame, created by Carnegie Mellon University in 2003, or were top-ranked in a user-curated Internet Movie Database (IMDB) list. To do so, we performed full-text search and retrieval queries of all 18 robots in the ACM Digital Library. In total, we identified 121 relevant mentions, across 102 individual publications, in a time span from 1973 to 2017. These 121 mentions were then qualitatively analysed to determine the nature of the robot mentions. Our results indicate that the robot attributes of voice or dialogue were emerging as a popularly mentioned element. In addition, we find that research papers of philosophical nature mention sci-fi robots more frequently than papers of technical or theoretical nature. We also observe that the dystopian element of science fiction is under-utilised, with the majority of robot mentions exhibiting neutral or utopian characteristics. In conclusion, we speculate on our results and present possible avenues of future HRI research on the topic.

INTEGRATING STANDARD SCRM KNOWLEDGE INTO CONVENTIONAL ACADEMIC CURRICULA AN EXAMINATION OF THE CURRENT STATE OF THINGS

ABSTRACTThe assurance of effective information and communication technology supply chain risk management is a national priority due to the potential impact of supply chain failures on our national infrastructure. Given education’s role in facilitating social change, it is imperative that information and communication technology (ICT-SCRM) supply chain risk management topics are embedded in our present computer curricula. The existence of a well-defined and standard body of knowledge for ICT supply chain risk management offers a validated point of departure for defining and then amalgamating supply chain risk management topics into conventional higher education teaching. This article presents an analysis that explores the specific ways that ICT-SCRM could be disseminated into various computer curricula based on the standards of the traditional societies for those areas (Association for Computing Machinery, Institute of Electrical and Electronics Engineers, Association for Information Systems). This analysis found that it was possible to incorporate secure acquisition and ICT–SCRM best practices into higher education teaching. This can be demonstrated down to the course level.