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Open-science initiatives have gained substantial momentum in computer science, and particularly in software-engineering research. A critical aspect of open-science is the public availability of artifacts (e.g., tools), which facilitates the replication, reproduction, extension, and verification of results. While we experienced that many artifacts are not publicly available, we are not aware of empirical evidence supporting this subjective claim. In this article, we report an empirical study on software artifact papers (SAPs) published at the International Conference on Software Engineering (ICSE), in which we investigated whether and how researchers have published their software artifacts, and whether this had scientific impact. Our dataset comprises 789 ICSE research track papers, including 604 SAPs (76.6 %), from the years 2007 to 2017. While showing a positive trend towards artifact availability, our results are still sobering. Even in 2017, only 58.5 % of the papers that stated to have developed a software artifact made that artifact publicly available. As we did find a small, but statistically significant, positive correlation between linking to artifacts in a paper and its scientific impact in terms of citations, we hope to motivate the research community to share more artifacts. With our insights, we aim to support the advancement of open science by discussing our results in the context of existing initiatives and guidelines. In particular, our findings advocate the need for clearly communicating artifacts and the use of non-commercial, persistent archives to provide replication packages. [ABSTRACT FROM AUTHOR]

The research output of India in computer science during 1999-2008 is analyzed in this paper on several parameters including total research output, its growth, rank and global publication share, citation impact, share of international collaborative papers and major collaborative partner countries and patterns of research communication in most productive journals. It also analyses the characteristics of most productive institutions, authors and high-cited papers. The publications output and impact of India is also compared with China, South Korea, Taiwan and Brazil. [ABSTRACT FROM AUTHOR]

The paper examines quality and quantity of scientific research in India as reflected in publications output on grid computing on a series of bibliometric indicators. Data were extracted from Scopus database consisting of 1340 publications in grid computing research from India in 10 years during 2008-17 citation impact of 4.33 citations per paper and international collaborative publication share of 12.16%. The paper profiles global publication output and share of 10 most productive countries in grid computing research, 15 most productive Indian organizations and 15 most productive authors on a series of indicators including publications output, number of citations, the relative citation index, citations per paper, h-index and share of international collaborative papers during 2008-17. Computer science, among top 3 subjects, accounted for the largest publication share (90.15%), followed by engineering (26.79%) and mathematics (13.66%). The 15 most leading organizations and authors together contributed 31.57% and 14.25% as their share of Indian publication output and 44.93% and 16.17% as their share of Indian citation output respectively during 2008-17. The most productive Indian organizations were Anna University, Chennai (74 papers) and Thapar University, Patiala (48 papers) The most productive authors were I. Chana of Thapar University, Patiala (21 papers) and N. Mukherjee of Jadavpur University, Kolkata (18 papers). The 15 most productive journals contributed 43.92% share to the Indian journal publication output during 2008-17. The most productive journals were Applied Engineering Research (16 publications), Journal of Grid Computing (14 publications) and Future Generation Computer Systems (13 publications). [ABSTRACT FROM AUTHOR]

Aim of this study is to determine the preferences of Computer Information Systems students as regards to knowledge sharing technologies. In this paper, qualitative method is preferred in order to obtain detailed opinions of university students on knowledge sharing and its technologies in the Northern of Cyprus. The study group of the research consists of 69 students who studied at Computer Information Systems department in the fall semester of 2017-2018 academic year. It has been found out that Computer Information System department students generally use knowledge sharing technologies. Students prefer using the opportunities offered by the technology in knowledge sharing process. This finding contributes to future directions on developing strategies to improve knowledge sharing in the classroom by enhancing the classroom environment. This study also discusses the implications of knowledge sharing and web technologies for researchers and educators.

Continuous improvement in the clinical performance of neonatal intensive care units (NICU) depends on the use of locally relevant, reliable data. However, neonatal databases with these characteristics are typically unavailable in NICUs using paper-based records, while in those using electronic records, the inaccuracy of data and the inability to customize commercial data systems limit their usability for quality improvement or research purposes. We describe the characteristics and uses of a simple, neonatologist-centered data system that has been successfully maintained for 30 years, with minimal resources and serving multiple purposes, including quality improvement, administrative, research support and educational functions. Structurally, our system comprises customized paper and electronic components, while key functional aspects include the attending-based recording of diagnoses, integration into clinical workflows, multilevel data accuracy and validation checks, and periodic reporting on both data quality and NICU performance results. We provide examples of data validation methods and trends observed over three decades, and discuss essential elements for the successful implementation of this system. This database is reliable and easily maintained; it can be developed from simple paper-based forms or used to supplement the functionality and end-user customizability of existing electronic medical records. This system should be readily adaptable to NICUs in either high- or limited-resource environments. [ABSTRACT FROM AUTHOR]

This editorial introduces the special issue, Resources for Undergraduate Cryptology. We begin by describing possible roles for cryptology in the undergraduate mathematics curriculum together with a brief overview of the subject. We conclude with a brief preview of each paper included in this issue. [ABSTRACT FROM AUTHOR]

The goal of this paper is to estimate object's 6D pose based on the texture-less dataset. The pose of each projection view is obtained by rendering the 3D model of each object, and then the orientation feature of the object is implicitly represented by the latent space obtained from the RGB image. The 3D rotation of the object is estimated by establishing the codebook based on a template matching architecture. To build the latent space from the RGB images, this paper proposes a network based on a variant Adversarial Autoencoder (Makhzani et al. in Computer Science, 2015). To train the network, we use the dataset without pose annotation, and the encoder and decoder do not have a structural symmetry. The encoder is inspired by the existing model (Yang et al. in proceedings of IJCAI, 2018), (Yang et al. in proceedings 11 of CVPR, 2019) that incorporates the function of feature extraction from two different streams. Based on this network, the latent feature vector that implicitly represents the orientation of the object is obtained from the RGB image. Experimental results show that the method in this paper can realize the 6D pose estimation of the object and the result accuracy is better than the advanced method (Sundermeyer et al. in proceedings of ECCV, 2018). [ABSTRACT FROM AUTHOR]

Baba is You is a 2019 indie puzzle game whose levels are two-dimensional grids of objects. This paper demonstrates how a universal Turing machine could be created as a custom level in the game if a specific in-game limit were to be removed. A player could perform any computation by playing this level, allowing infinitely many new and meaningful puzzles to be created. Furthermore, the construction is such that the level is won if and only if the Turing machine halts, proving perfect play of the game to be unattainable by any computer. The machine is found to be exponentially time-complex, and the paper concludes with a discussion of the practical feasibility of in-game computation. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to commemorate the late scholar Loet Leydesdorff for his great academic contribution on the basis of data from Web of Science. In the span of more than 40 years, he had 526 publications, with the years 2004-2021 being the most productive (394 publications). His international collaborations spread widely across 36 countries, with Germany, the USA, the UK, China, Russia, and South Korea being the most significant. His most frequent collaboration partners included Lutz Bornmann (Germany), Staša Milojević (USA), Caroline Wagner (USA), Henry Etzkowitz (USA), Jonathan Adams (UK), Ronald Rousseau (Belgium), and Ping Zhou (China). With a broad and deep knowledge background, Leydesdorff's research extended across multiple disciplines and fields, but he was most active in library and information science and computer science. He made profound contributions to the study of bibliometrics, innovation systems (the Triple Helix model), and communications. Leydesdorff had a remarkable and extensive citation impact, with citations in 221 WoS subject categories from 120 countries. His publications in 1996, 1998, 2000, 2005, 2006, and 2012 are highly cited, and those on university-industry-government relations (the Triple Helix model) are the most cited. [ABSTRACT FROM AUTHOR]

In this paper we have examined the position and roles of Computer Science in curricula in the light of recent calls for curriculum change and we have proposed principles and issues to consider in curriculum design as well as identifying priority areas for further research. The paper is based on discussions within and beyond the International Federation of Information Processing (IFIP) Education Community since 2012 as well as an analysis of curriculum developments in five different countries. Emerging themes have been discussed with reference to important perspectives from curriculum theory including "powerful knowledge" as a key element of entitlement and management of the growth of expertise. Based on this analysis we have identified areas of consensus as well as constraints, risks and issues that are still subject to controversy. There is an emerging consensus of the importance of Computer Science and the nature of its "powerful knowledge". Furthermore current understanding of the opportunities and benefits for starting to learn Computer Science early in primary schools has identified this early start as an entitlement and equity issue. There is a strong consensus that teacher professional development in Computer Science Education is critical for supporting curriculum change and is currently a major challenge in many countries. Other key issues include understanding how the growth of expertise affects potential structure and sequencing in the curriculum and the balance of content. Further considerations include how new technological opportunities interact with pedagogical approaches and can provide new potential for the growth of expertise.

Computer science (CS) is becoming an increasingly diverse domain. This paper reports on an initiative designed to introduce underrepresented populations to computing using an eclectic, multifaceted approach. As part of a yearlong computing course, students engage in Maker activities, participatory simulations, and computing projects that foreground the social and collaborative aspects of CS. Collectively, these activities are designed to introduce learners to the growing diversity of what CS looks like in the 21st century. This paper lays out the practical and theoretical motivations for the Computational Thinking for Girls (CT4G) project, specifically highlighting the use of Making through physical and social computing as ways to engage students in CS. A snapshot of one activity from the program is provided--"Wearing the Web"--in which students use open-hardware programmable badges to explore the underlying structure and technology that enables the Internet. Data from the first year of the CT4G program are presented to show the positive effects that this diverse introduction to CS is having on the students with respect to their attitudes toward CS.

Purpose: The focus on innovation as a foundational element of enhanced organisational performance has led to the promoting and valuing of greater levels of employee participation in innovation processes. An emergent concept of employee-driven innovation could be argued to have hindered understandings of the creative and transformative nature of work and the kinds of work and learning practices that all workers engage in as part of their routine occupational practices. The purpose of this paper is to propose that a stronger focus on work-learning as workers' personal enactment of the collective activities that comprise their occupational practice and its circumstances can clarify the nature of innovation. Design/methodology/approach: The paper is based on an extended ethnographic study (18 months) of 12 employees from four different workplaces and who were engaged in a variety of different occupational practices. Findings: The argument is advanced through discussion of four kinds of innovation that were identified through examining the work-learning practices of restaurant, gymnasium, computing and fire service workers. They are personal heuristics, test benching, efficiencies and shared needs. Originality/value: These innovation forms illuminate personal work-learning practices and offer means of explaining innovation as a foundational factor of work, suggesting that work that supports these work-learning practices can enhance organisational innovation.

Bioinformatics--the so-called shotgun marriage between biology and computer science--is an interdiscipline. Despite interdisciplinarity being seen as a virtue, for having the capacity to solve complex problems and foster innovation, it has the potential to place projects and people in anomalous categories. For example, valorised "outputs" in academia are often defined and rewarded by discipline. Bioinformatics, as an interdisciplinary bricolage, incorporates experts from various disciplinary cultures with their own distinct ways of working. Perceived problems of interdisciplinarity include difficulties of making explicit knowledge that is practical, theoretical, or cognitive. But successful interdisciplinary research also depends on an understanding of disciplinary cultures and value systems, often only tacitly understood by members of the communities in question. In bioinformatics, the "parent" disciplines have different value systems; for example, what is considered worthwhile research by computer scientists can be thought of as trivial by biologists, and "vice versa." This paper concentrates on the problems of reward and recognition described by scientists working in academic bioinformatics in the United Kingdom. We highlight problems that are a consequence of its cross-cultural make-up, recognising that the mismatches in knowledge in this borderland take place not just at the level of the practical, theoretical, or epistemological, but also at the cultural level, too. The trend in big, interdisciplinary science is towards multiple authors on a single paper; in bioinformatics this has created "hybrid" or "fractional" scientists who find they are being positioned not just in-between established disciplines but also in-between as middle authors or, worse still, left off papers altogether.

The recent focus on computational thinking as a key 21st century skill for all students has led to a number of curriculum initiatives to embed it in K-12 classrooms. In this paper, we discuss the key computational thinking constructs, including algorithms, abstraction, and automation. We further discuss how these ideas are related to current educational reforms, such as Common Core and Next Generation Science Standards and provide specific means that would allow teachers to embed these ideas in their K-12 classrooms, including recommendations for instructional technologists and professional development experts for infusing computational thinking into other subjects. In conclusion, we suggest that computational thinking ideas outlined in this paper are key to moving students from merely being technology-literate to using computational tools to solve problems.

This paper attempts an analysis of some current trends and future developments in computer science, education, and educational technology. Based on these trends, two possible future predictions of AIED are presented in the form of a utopian vision and a dystopian vision. A comparison of these two visions leads to seven challenges that AIED might have to face in the future: intercultural and global dimensions, practical impact, privacy, interaction methods, collaboration at scale, effectiveness in multiple domains, and the role of AIED in educational technology. The paper discusses these challenges and the associated risks and opportunities.

The abstract should summarize the content of the paper. Try to keep the abstract below 200 words. Do not make references nor display equations in the abstract. The journal will be printed by photo-offset from the same-sized copy prepared by you. Your manuscript should be printed on A4 paper (21.0 cm x 29.7 cm). It is imperative that the margins and style described below be adhered to carefully. This will enable us to keep uniformity in the final printed copies of the Journal. Please keep in mind that the manuscript you prepare will be photographed and printed as it is received. Readability of copy is of paramount importance. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI), machine learning (ML) and deep learning (DL) techniques have made a breakthrough in many different research fields, such as computer vision, natural language processing, network management and mobile communication. One of the primary goals in 5G network pursues high efficiency, higher spectrum and energy efficiency, higher system capacity and data rates, and lower latency with cost reduction. The papers on the topic of "AI-enabled intelligent networks for 5G and beyond" contain novel network architectures and mechanisms by using AI/ML/DL approaches for 5G/B5G networks. [Extracted from the article]

Recently, computational thinking (CT) has attracted much research attention, especially within primary and secondary education settings. However, incorporating in mathematics or other disciplines is not a straightforward process and introduces many challenges concerning the way disciplines are organised and taught in school. The aim of this paper is to identify what characterises CT in mathematics education and which CT aspects can be addressed within mathematics education. First, we present a systematic literature review that identifies characteristics of CT that have been explored in mathematics education research. Second, we present the results of a Delphi study conducted to capture the collective opinion of 25 mathematics and computer science experts regarding the opportunities for addressing CT in mathematics education. The results of the Delphi study, which corroborate the findings of the literature review, highlight three important aspects of CT to be addressed in mathematics education: problem solving, cognitive processes, and transposition.

This paper describes an interdisciplinary effort involving faculty from five different disciplines who came together to develop an interdisciplinary, open, general education cybersecurity course. The course, Cybersecurity, Technology, and Society, brings together ideas from interdisciplinary studies, information technology, engineering, business, computer science, criminal justice, and philosophy to provide students an interdisciplinary introduction to cybersecurity. We provide an overview of the rationale for the course, the process the authors went through developing the course, a summary of the course modules, details about the open education resources used as readings, and the types of assignments included in the class. We conclude by offering recommendations for others developing similar courses.

Abstract: The Workshop for the Executable Paper Grand Challenge, taking place at the 2011 International Conference on Computational Science, is a platform for Grand Challenge contestants and finalists to present their concept of an Executable Paper, a method by which data intensive research is better represented in a scholarly journal article. The Executable Paper Grand Challenge is designed to enhance how scientific information is used and communicated in computer- and computational sciences. [Copyright &y& Elsevier]

Google Scholar has been a widely used platform for academic performance evaluation and citation analysis. The issue about the mis-configuration of author profiles may seriously damage the reliability of the data, and thus affect the accuracy of analysis. Therefore, it is important to detect the mis-configured author profiles. Dealing with this issue is challenging because the scale of the dataset is large and manual annotation is time-consuming and relatively subjective. In this paper, we first collect a dataset of Google Scholar's author profiles in the field of computer science and compare the mis-configured author profiles with the reliable ones. Then, we propose an integrated model that utilizes machine learning and node embedding to automatically detect mis-configured author profiles. Additionally, we conduct two application case studies based on the data of Google Scholar, i.e., outstanding scholar searching and university ranking, to demonstrate how the improved dataset after filtering out the mis-configured author profiles will change the results. The two case studies validate the importance and meaningfulness of the detection of mis-configured author profiles. [ABSTRACT FROM AUTHOR]

Reviewing is the most important step in the quality accreditation of scientific works, requires the professional expertise of the reviewer as well as there is no conflict of interest in the evaluation process. However, we also acknowledge that reviewers have limited knowledge, experience and opinions about the work of others, so they may misinterpret the author's point of view, leading to the rejection of excellent scientific work or a potentially successful project proposal. Manually selecting reviewers can lead to bias and time-consuming. To solve these problems, we have developed a support system for selecting a group of reviewers to evaluate a particular problem, such as a proposal or a research paper. Our support system consists of three main modules: data collection, reviewer identification and group prediction of reviewers. The Data Collection module collects data from a variety of sources to create the scientist profile database. The reviewer identification module recognizes reviewers on a specific topic. The reviewer prediction module provides a group of exp reviewers to evaluate a submitted paper or a proposal. Experiments on the DBLP computer science bibliography dataset showed that our system achieves better results in terms of accuracy in comparison to other methods. [ABSTRACT FROM AUTHOR]

What are the landmark papers in scientific disciplines? Which papers are indispensable for scientific progress? These are typical questions which are of interest not only for researchers (who frequently know the answers – or guess to know them) but also for the interested general public. Citation counts can be used to identify very useful papers since they reflect the wisdom of the crowd – in this case, the scientists using published results for their research. In this study, we identified with recently developed methods for the program CRExplorer landmark publications in nearly all Web of Science subject categories (WoS-SCs). These are publications which belong more frequently than other publications during the citing years to the top-1‰ in their subject area. As examples, we show the results of five subject categories: 'Information Science & Library Science', 'Computer Science, Information Systems', 'Computer Science, Software Engineering', 'Psychology, Social' and, 'Chemistry, Physical'. The results of the other WoS-SCs can be found online at http://crexplorer.net. An analyst of the results should keep in mind that the identification of landmark papers depends on the used methods and data. Small differences in methods and/or data may lead to other results. [ABSTRACT FROM AUTHOR]

Informatics education has been in a cul-de-sac for several years (not only in Hungary), being less and less able to meet the needs of the industry and higher education. In addition, the latest PISA survey shows that--to put it a little strongly--the majority of the x-, y- and z generations are digital illiterates. The aim of this paper to examine what could be done in order to improve the situation.

The abstract should summarize the content of the paper. Try to keep the abstract below 200 words. Do not make references nor display equations in the abstract. The journal will be printed by photo-offset from the same-sized copy prepared by you. Your manuscript should be printed on A4 paper (21.0 cm x 29.7 cm). It is imperative that the margins and style described below be adhered to carefully. This will enable us to keep uniformity in the final printed copies of the Journal. Please keep in mind that the manuscript you prepare will be photographed and printed as it is received. Readability of copy is of paramount importance. [ABSTRACT FROM AUTHOR]

Design as an academic endeavor has a rich history in the visual and performing arts as well as the "construction" arts: architectural, industrial, graphic, interior, fashion, and landscape design. Design in the natural and commercial sciences is largely peripheral. Although not ignored, design in the sciences predominates as a dialect of problem-solving rather than artifact creation. Information Systems (IS) as a fusion of computer science and business struggles with the identity and role of design as it leans heavily on its roots in mathematics and formal logic with the scattered influences of statistics (data analysis) as practiced in research among the social and behavioral sciences. Design as a practical skill is a critical ingredient in successful information systems. Yet, design as a distinctive element in programs and curricula of IS and computing is (at best) haphazardly diffused--if not completely omitted. This paper presents a special ontology of design to frame the opportunities and justification for conscious and deliberate design pedagogy in IS and computing education. It presents an example of integrating design pedagogy into existing object modeling and data management syllabi by tailoring design quality guidelines to the specific paradigm.

A new, interdisciplinary, team-taught course has been designed to educate students in Electrical and Computer Engineering (ECE) so that they can respond to global and urgent issues concerning computer control systems in nuclear power plants. This paper discusses our experience and assessment of the interdisciplinary computer and nuclear energy course, which was developed and offered primarily to ECE students at Howard University. A unique team-teaching model utilized with ECE professors and nuclear field experts was applied to teach the two diverse subjects: computer safety and nuclear energy. The survey result from the first offering of the course showed a very positive response from the majority of the students about the team-teaching method and the knowledge acquired on the two subjects.

Modern cloud services are monitored by numerous multidomain and multivendor monitoring tools, which generate massive numbers of alerts and events that are not actionable. These alerts usually carry isolated messages that are missing service contexts. Administrators become inundated with tickets caused by such alert events when they are routed directly to incident management systems. Noisy alerts increase the risk of crucial warnings going undetected and leading to service outages. One of the feasible ways to cope with the above problems involves revealing the correlations behind a large number of alerts and then aggregating the related alerts according to their correlations. Based on these guidelines, AlertInsight, a framework for alert event reduction, is proposed in this paper. In AlertInsight, the correlations among event sources are found by mining a sequence of historical events. Then, event correlation knowledge is employed to build an online detector targeting the correlated events that are hidden in the event stream. Finally, the correlated events are aggregated into a single high-level event for alert reduction. Because of theweaknesses of the commonly used pairwise correlation analysis methods in complex environments, an innovative approach for multiple correlation mining, which overcomes computational complexity challenges by scanning panoramic views of historical episodes from the perspective of holism, is proposed in this paper. In addition, a neural network-based correlated event detector that can learn the event correlation knowledge generated from correlation mining and then detect the correlated events in a sequence online is proposed. Experiments are conducted to test the effectiveness of AlertInsight. The experimental results (precision=0.92, recall=0.93, and F1-score=0.93) demonstrate the performance of AlertInsight for the recognition of multiple correlated alerts and its competence for alert reduction. [ABSTRACT FROM AUTHOR]

A number of bibliometric studies point out that the role of conference publications in computer science differs from that in other traditional fields. Thus, it is interesting to identify the relative status of journal and conference publications in different subfields of computer science based on the citation rates categorised by the China Computer Federation (CCF) classifications and venue types. In this research, we construct a dataset containing over 100,000 papers recommended by the CCF catalogue and their citation information. We also investigate some other factors that often influence a paper's citation rate. An experimental study shows that the relative status of journals and conferences varies greatly in different subfields of computer science, and the impact of different publication levels varies according to the citation rate. We also verify that the classification of a publication, number of authors, maximum h-index of all authors of a paper, and average number of papers published by a publication have different effects on the citation rate, although the citation rate may have a different degree of correlation with these factors. [ABSTRACT FROM AUTHOR]

The purpose of this article is to examine the level of emphasis placed on safety concepts and guidelines in "Standards for Technological and Engineering Literacy" ("STEL") (ITEEA, 2020) in comparison to other current science, technology, engineering, and math (STEM) content area standards and frameworks. The authors who conducted this analysis have served on the National Science Teaching Association's (NSTA) Safety Advisory Board (SAB) for a number of years, authored safety white papers and research studies for both NSTA and International Technology and Engineering Educators Association (ITEEA), served on a number of state and national standards-development committees, and have received extensive training in Occupational Safety and Health Administration (OSHA) regulations that pertain to general industry, including schools. The views and opinions expressed in this article are based on the authors' findings, academic preparation, and years of experience relative to STEM education safety and standards development. The overarching goal of this article is to raise awareness about the importance of incorporating safety in every STEM learning experience, which directly relates to explicitly embedding safety concepts and guidelines throughout standards and framework documents.

This study aimed to investigate the effects of gender pairings on collaborative problem-solving performance, processes, and attitudes in a social learning context. Three types of pairings (i.e., male-male, female-female, and mixed pairings) were considered in an empirical study with 222 tenth-grade students. The selection of three different schools facilitated discussions regarding which schools were more divergent and competitive in a social learning context. The students were asked to solve computer science problems on a social media platform. The results revealed that (1) the single-gender groups had more focused discussions than the mixed-gender groups. Specifically, the male-male groups tended to develop and test their solutions directly without spending significant time on problem identification. Consequently, the single-gender groups exhibited superior performance compared to the mixed-gender groups in terms of applying their knowledge to problem solving. In terms of attitudes toward social learning, the female-female groups were more attentive to the benefits of social learning than the male-male groups. (2) The mixed gender groups had more diverse and divergent discussions compared to the single-gender groups. The educational implications of these findings are also discussed in this paper.

Contributions: The underrepresentation of women in computer science (CS) majors has long been a focus of attention in many academic documents, the majority of them from the United States and Europe. There is, however, a lack of information about educational interventions (EIs) for women in computing in Latin America. The contribution of this article is to cover this gap and describe what researchers in Latin American countries have been publishing about the recruitment and retention of women in the CS field. Background: Many EIs targeting female students at different educational levels—K-12, undergraduate, and graduate—have been undertaken to increase the participation of women in computing in Latin America. However, descriptions of these activities rarely are included in international academic databases. Research Questions: This literature mapping addresses two main research questions (RQ) about the topic of women in computing in academic publications in Latin American countries: RQ1) what are the characteristics of the publications about women in computing in Latin America? and RQ2) what are the published interventions to recruit and retain women in computing in Latin America? To answer RQ1, six subquestions were created covering year, language, country of origin, document type, and professional track. Furthermore, for RQ2, two subquestions were created involving educational level and the use of software development with a female theme. Methodology: This investigation used the systematic literature mapping process. To achieve a broad coverage of papers, the following sources were included: Scopus, Web of Science, Google Scholar, EBSCO, the proceedings of the Latin American Women in Computing Conference (LAWCC), and those of the Women in Technology (WIT) workshop colocated with the annual conference of the Brazilian Computer Society (SBC). The included papers were published in the last decade (2010–2020) and written in English, Portuguese, or Spanish. Findings: The literature mapping encompasses 197 academic documents, 48.2% of which were written in Portuguese, 28.7% in English, and 23.1% in Spanish. The papers originated from 15 of the 20 Latin American countries. Brazil and Costa Rica have the highest number of publications overall. The documents describe initiatives to increase the participation of women in computing majors that cover the entire educational spectrum, from K-12 to graduate programs, but papers targeting populations in higher education have started to appear recently. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to examine important work on MOOCs by researchers in the form of major contributing universities, sources of funding, authors, journals, keywords, and citation data. Design/Methodology/Approach: In this study, the researchers assessed by conducting a systematic review of MOOC literature, as other researchers have rightly said that reviewing entails learning from experience. In this study, patterns of research publications within particular topics and historical periods were described using bibliometric analysis, quantitative analysis, and statistical analysis. Findings: The results of this study's cluster analysis revealed the areas where future academics might focus their efforts on MOOCs for future research. There were a total of 199 entries in the notifications, which were then sorted into seven clusters. Every cluster contains different numbers of items. According to the study's findings, education, e-learning, online learning, massive open online courses, and data mining are the most often used keywords. Mostly, Social sciences and computer sciences articles have the highest contribution to research. Research Limitation: The current study only makes use of the Scopus database. The study's focus was taken into consideration when selecting the keywords. Only three keywords were used in this study. The sole language employed in this study was English. Managerial Implications: Tthe paper would help the policymakers Future studies can analyse actual challenges faced by higher education institutions and suggest methods for incorporating MOOCs into the teaching environment to address them. In-depth reporting on real-world case studies can be helpful to academics as well as practitioners. Originality/Value: The evaluation of selected papers yielded a major contribution and food for thought for both scholars and policymakers. [ABSTRACT FROM AUTHOR]

Designing and deploying programming courses is undoubtedly a challenging task. In this paper, an attempt to analyze important aspects of a sequence of two courses on imperative-procedural and object-oriented programming in a non-CS majors Department is made. This analysis is based on a questionnaire filled in by fifty students in a voluntary basis. The issues of the programming courses that are investigated refer to: the "strategy" selected for the introduction to programming; the sequence of the "programming techniques and languages" taught and the transition from the one to the other; students' "difficulties" with programming in general and with imperative-procedural and object-oriented programming in specific; the "teaching" and "learning design" of both courses; and the "material" that students rely on for learning programming. Based on the analysis of students' replies on the questionnaire, related work and the instructor's experience on teaching the courses, conclusions are drawn regarding all the aforementioned aspects of designing and deploying programming courses. The main contribution of the paper is the fact that all the important and interrelated aspects of a sequence of two programming courses are investigated in conjunction, providing realistic implications and guidelines for improving the quality and effectiveness of existing programming courses and designing and deploying new courses. The main results refer to the usage of a pseudo-language for an introduction to programming, the transition from procedural to object-oriented programming, the intrinsic difficulties of learning programming, and practices for a more successful teaching and learning design of programming courses.

Computer science has been a discipline for some years, and its position in the school curriculum has been contested differently in several countries. This paper looks at its role in three countries to illustrate these differences. A reconsideration of computer science as a separate subject both in primary and secondary education is suggested. At EDUsummIT 2015 it was argued that the major rationales for including computer science as a subject in the K-12 curriculum are economic, social and cultural. The paper explores these three rationales and also a beneficence matrix to assist curriculum designers. It also argues computer science is rapidly becoming critical for generating new knowledge, and should be taught as a distinct subject or content area, especially in secondary schools. The paper concludes by looking at some of the key questions to be considered when implementing computer science in the school curriculum, and at ways its role might change in the future.

A drug molecule is a substance that changes an organism's mental or physical state. Every approved drug has an indication, which refers to the therapeutic use of that drug for treating a particular medical condition. While the Large Language Model (LLM), a generative Artificial Intelligence (AI) technique, has recently demonstrated effectiveness in translating between molecules and their textual descriptions, there remains a gap in research regarding their application in facilitating the translation between drug molecules and indications (which describes the disease, condition or symptoms for which the drug is used), or vice versa. Addressing this challenge could greatly benefit the drug discovery process. The capability of generating a drug from a given indication would allow for the discovery of drugs targeting specific diseases or targets and ultimately provide patients with better treatments. In this paper, we first propose a new task, the translation between drug molecules and corresponding indications, and then test existing LLMs on this new task. Specifically, we consider nine variations of the T5 LLM and evaluate them on two public datasets obtained from ChEMBL and DrugBank. Our experiments show the early results of using LLMs for this task and provide a perspective on the state-of-the-art. We also emphasize the current limitations and discuss future work that has the potential to improve the performance on this task. The creation of molecules from indications, or vice versa, will allow for more efficient targeting of diseases and significantly reduce the cost of drug discovery, with the potential to revolutionize the field of drug discovery in the era of generative AI. [ABSTRACT FROM AUTHOR]

This paper investigates the evolving landscape of blockchain technology in renewable energy. The study, based on a Scopus database search on 21 February 2024, reveals a growing trend in scholarly output, predominantly in engineering, energy, and computer science. The diverse range of source types and global contributions, led by China, reflects the interdisciplinary nature of this field. This comprehensive review delves into 33 research papers, examining the integration of blockchain in renewable energy systems, encompassing decentralized power dispatching, certificate trading, alternative energy selection, and management in applications like intelligent transportation systems and microgrids. The papers employ theoretical concepts such as decentralized power dispatching models and permissioned blockchains, utilizing methodologies involving advanced algorithms, consensus mechanisms, and smart contracts to enhance efficiency, security, and transparency. The findings suggest that blockchain integration can reduce costs, increase renewable source utilization, and optimize energy management. Despite these advantages, challenges including uncertainties, privacy concerns, scalability issues, and energy consumption are identified, alongside legal and regulatory compliance and market acceptance hurdles. Overcoming resistance to change and building trust in blockchain-based systems are crucial for successful adoption, emphasizing the need for collaborative efforts among industry stakeholders, regulators, and technology developers to unlock the full potential of blockchains in renewable energy integration. [ABSTRACT FROM AUTHOR]

The problem of finding a maximum size matching in a graph (known as the maximum matching problem) is one of the most classical problems in computer science. Despite a significant body of work dedicated to the study of this problem in the data stream model, the state-of-the-art single-pass semi-streaming algorithm for it is still a simple greedy algorithm that computes a maximal matching, and this way obtains 1 / 2 -approximation. Some previous works described two/three-pass algorithms that improve over this approximation ratio by using their second and third passes to improve the above mentioned maximal matching. One contribution of this paper continues this line of work by presenting new three-pass semi-streaming algorithms that work along these lines and obtain improved approximation ratios of 0.6111 and 0.5694 for triangle-free and general graphs, respectively. Unfortunately, a recent work Konrad and Naidu (Approximation, randomization, and combinatorial optimization. Algorithms and techniques, APPROX/RANDOM 2021, August 16–18, 2021. LIPIcs, vol 207, pp 19:1–19:18, 2021. https://doi.org/10.4230/LIPIcs.APPROX/RANDOM.2021.19) shows that the strategy of constructing a maximal matching in the first pass and then improving it in further passes has limitations. Additionally, this technique is unlikely to get us closer to single-pass semi-streaming algorithms obtaining a better than 1 / 2 -approximation. Therefore, it is interesting to come up with algorithms that do something else with their first pass (we term such algorithms non-maximal-matching-first algorithms). No such algorithms were previously known, and the main contribution of this paper is describing such algorithms that obtain approximation ratios of 0.5384 and 0.5555 in two and three passes, respectively, for general graphs. The main significance of our results is not in the numerical improvements, but in demonstrating the potential of non-maximal-matching-first algorithms. [ABSTRACT FROM AUTHOR]

Motivated by the fact that the fuzzy quasi-normed space provides a suitable framework for complexity analysis and has important roles in discussing some questions in theoretical computer science, this paper aims to study the nearest point problems in fuzzy quasi-normed spaces. First, by using the theory of dual space and the separation theorem of convex sets, the properties of the fuzzy distance from a point to a set in a fuzzy quasi-normed space are studied comprehensively. Second, more properties of the nearest point are given, and the existence, uniqueness, characterizations, and qualitative properties of the nearest points are obtained. The results obtained in this paper are of great significance for expanding the application fields of optimization theory. [ABSTRACT FROM AUTHOR]

Presents the special issue in the journal "Parallel Processing Letters," which contains the best papers from the Centre Interantional de Rencontres Mathématiques workshopin October 2001. "Scheduling Issues in Survivality Applications Using Hybrid Fault Models," by A. W. Krings, W. S. Harrison, A. Azadmanesh and M. McQueen"; "Parallel Tabu Search Approaches for Two-Dimensional Cutting," by J. Blazewicz, A. Moret-Salvador and R. Walkowiak"; "Strategies for Workload Balancing in Cluster-Based Image Databases," by F. Drews, K. Ecker, O. Kao and S. Schomann.

David A. Huffman (1925–1999) is best known in computer science for his work in information theory, particularly Huffman codes, and best known in origami as a pioneer of curved-crease folding. But during his early paper folding in the 1970s, he also designed and folded over a 100 different straight-crease origami tessellations. Unlike most origami tessellations designed in the past 20 years, Huffman's straight-crease tessellations are mostly three-dimensional, rigidly foldable, and have no locking mechanism. In collaboration with Huffman's family, our goal is to document all of his designs by reverse-engineering his models into the corresponding crease patterns, or in some cases, matching his models with his sketches of crease patterns. Here, we describe several of Huffman's origami tessellations that are most interesting historically, mathematically, and artistically. [ABSTRACT FROM AUTHOR]

This document is a special section of the SIAM Journal on Computing, focusing on the Fifty-Ninth Annual IEEE Symposium on Foundations of Computer Science (FOCS 2018). It includes ten fully refereed papers that were presented at the symposium in Paris in October 2018. The papers cover a wide range of topics, including complexity theory, graph algorithms, approximation algorithms, cryptography, quantum computing, pseudorandom generators, matrix multiplication, and graph sparsification. The papers underwent an extensive refereeing process, and the authors and anonymous referees are thanked for their efforts. The special section was prepared with the help of the guest editors and the SIAM Publications Manager. [Extracted from the article]

The opinions on MOOCs go to extremes, covering a wide variety of topics, affecting economy, pedagogy, and computer science which makes it hard to keep oversight. Despite the many excellent research reports and articles, an overview of the bigger picture, providing a holistic qualitative summary of the different opinions, is still very welcome. Special attention is given to the broader social, cultural, and technological context in which these developments come about. In this paper, it is discussed how the educational industry has received a "wake up call" provoking a global discussion on learning and teaching, accordingly disturbing established boundaries between formal and informal learning, public and for-profit education, teachers and learners and quite intriguingly, between software and teaching practices. Golden opportunities for Artificial Intelligence and Technology Enhanced Learning are unfolding, evidenced by the digitalization movement of education, gamification, and the stringent need for massively scalable (and therefore computerized) personal learning experiences.

While advances in game-based learning are already transforming educative practices globally, with tech giants like Microsoft, Apple and Google taking notice and investing in educational game initiatives, there is a concurrent and critically important development that focuses on "game construction" pedagogy as a vehicle for enhancing computational literacy in middle and high school students. Essentially, game construction-based curriculum takes the central question "do children learn from playing games" to the next stage by asking "(what) can children learn from constructing games?" Founded on Seymour Papert's constructionist learning model, and developed over nearly two decades, there is compelling evidence that game construction can increase student confidence and build their capacity towards ongoing computing science involvement and other STEM subjects. Our study adds to the growing body of literature on school-based game construction through comprehensive empirical methodology and evidence-based guidelines for curriculum design. There is still debate as to the utility of different software tools for game construction, models of scaffolding knowledge, and evaluation of learning outcomes and knowledge transfer. In this paper, we present a study we conducted in a classroom environment with three groups of grade 6 students (60+ students) using Game Maker to construct their own games. Based on a quantitative analysis and a qualitative discussion we organize results around several core themes that speak to the field of inquiry: levels of computational literacy based on pre- and post-tests; gender-based attitudes to computing science and programming based on a pre- and post-survey; and the relationship between existing media literacy and performance in programming as part of the game construction curriculum. Significant results include some gender differences in attitudes towards computers and programming with boys demonstrating slightly higher confidence and performance. We discuss the complex reasons potentially contributing to that, particularly against a diverse ecology of overall media use, gameplay experience, and access to technology at home. Finally, we theorize game construction as an educational tool that directly engages foundational literacy and numeracy, and connects to wider STEM-oriented learning objectives in ways that can benefit both boys and girls in the classroom.

Are computer science papers extended after they are published? We have surveyed 200 computer science publications, 100 journal articles, and 100 conference papers, using self-citations to identify potential and actual continuations. We are interested in determining the proportion of papers that do indeed continue, how and when the continuation takes place, and whether any distinctions are found between the journal and conference populations. Despite the implicit assumption of a research line behind each paper, manifest in the ubiquitous 'future research' notes that close many of them, we find that more than 70% of the papers are never continued. [ABSTRACT FROM AUTHOR]