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Misinformation is a complex and urgent sociotechnical problem that requires meaningful governance, in addition to technical efforts aimed at detection or classification and intervention or literacy efforts aimed at promoting awareness and identification. This review draws on interdisciplinary literature—spanning information science, computer science, management, law, political science, public policy, journalism, communications, psychology, and sociology—to deliver an adaptable, descriptive governance model synthesized from past scholarship on the governance of misinformation. Crossing disciplines and contexts of study and cases, we characterize: the complexity and impact of misinformation as a governance challenge, what has been managed and governed relative to misinformation, the institutional structure of different governance parameters, and empirically identified sources of success and failure in different governance models. Our approach to support this review is based on systematic, structured literature review methods to synthesize and compare insights drawn from conceptual, qualitative, and quantitative empirical works published in or translated into English from 1991 to the present. This review contributes a model for misinformation governance research, an agenda for future research, and recommendations for contextually‐responsive and holistic governance. [ABSTRACT FROM AUTHOR]

Context: The retraction of research papers, for whatever reason, is a growing phenomenon. However, although retracted paper information is publicly available via publishers, it is somewhat distributed and inconsistent. Objective: The aim is to assess: (i) the extent and nature of retracted research in Computer Science (CS) (ii) the post-retraction citation behaviour of retracted works and (iii) the potential impact upon systematic reviews and mapping studies. Method: We analyse the Retraction Watch database and take citation information from the Web of Science and Google scholar. Results: We find that of the 33,955 entries in the Retraction watch database (16 May 2022), 2,816 are classified as CS, i.e., ≈ 8%. For CS, 56% of retracted papers provide little or no information as to the reasons. This contrasts with 26% for other disciplines. There is also some disparity between different publishers, a tendency for multiple versions of a retracted paper to be available beyond the Version of Record (VoR), and for new citations long after a paper is officially retracted (median = 3; maximum = 18). Systematic reviews are also impacted with ≈ 30% of the retracted papers having one or more citations from a review. Conclusions: Unfortunately, retraction seems to be a sufficiently common outcome for a scientific paper that we as a research community need to take it more seriously, e.g., standardising procedures and taxonomies across publishers and the provision of appropriate research tools. Finally, we recommend particular caution when undertaking secondary analyses and meta-analyses which are at risk of becoming contaminated by these problem primary studies. [ABSTRACT FROM AUTHOR]

The 33rd International Workshop On Combinatorial Algorithms (IWOCA 2022) was held at the University of Trier in Germany. This workshop covers a wide range of topics related to combinatorial algorithms. The special issue of the journal Algorithmica contains extended versions of selected papers from IWOCA 2022, which were nominated by the Program Committee and underwent a rigorous reviewing process. The special issue includes nine papers on various topics such as perfect matchings, algorithmic questions, and winner determination algorithms. One paper was chosen as the Best Paper of IWOCA 2022 and another as the Best Student Paper. The special issue is recommended for readers interested in exploring more papers from IWOCA 2022. [Extracted from the article]

Asking questions and making comments in conference Q&A sessions can be challenging for novice academics. Discussants not only try to seek answers or exchange ideas with the presenter but also endeavour to project a positive image of themselves by asking the 'right' questions in the 'right' way. However, many novice academics fear looking foolish because of unfocused and convoluted questions. Surprisingly, little guidance is available for how to formulate Q&A questions. This study attempts to address the gap by investigating the forms, functions and generic moves of 268 turns taken by discussants in 80 computer science conference Q&A sessions. Certain forms (i.e., question and comment) were found to be associated with certain pragmatic functions. This study reveals that different types of question/comment have major moves in common. The study also shows that the more evaluative and face-threatening the question is, the more important it is for the discussant to make the moves of building rapport with the presenter, and contextualising and justifying the main question/statement. The importance of justifying the main question/statement also resonates with the persuasive nature of scientific argumentative discourse. The findings can offer novice academics detailed explanations of the communicative purposes and strategies for this important conference interaction. • The two forms (question & comment) are associated with different functions. • All types of questions/comments were found to share the major generic moves. • Evaluative/critical questions entail building rapport as a move. • Evaluative/critical questions entail justifying the question as a move. • The importance of justification resonates with scientific argumentative discourse. [ABSTRACT FROM AUTHOR]

Purpose: The number of citations has been widely used to measure the significance of a paper. However, there is a need in introducing another index to determine superiority or inferiority of papers with the same number of citations. We determine superiority or inferiority of papers by using the ranking based on the number of citations and PageRank. Design/methodology/approach: We show the positive linear correlation between Citation Rank (the ranking of the number of citation) and PageRank. On this basis, we identify high-quality, prestige, emerging, and popular papers. Findings: We found that the high-quality papers belong to the subjects of biochemistry and molecular biology, chemistry, and multidisciplinary sciences. The prestige papers correspond to the subjects of computer science, engineering, and information science. The emerging papers are related to biochemistry and molecular biology, as well as those published in the journal "Cell." The popular papers belong to the subject of multidisciplinary sciences. Research limitations: We analyze the Science Citation Index Expanded (SCIE) from 1981 to 2015 to calculate Citation Rank and PageRank within a citation network consisting of 34,666,719 papers and 591,321,826 citations. Practical implications: Our method is applicable to forecast emerging fields of research subjects in science and helps policymakers to consider science policy. Originality/value: We calculated PageRank for a giant citation network which is extremely larger than the citation networks investigated by previous researchers. [ABSTRACT FROM AUTHOR]

The 26th International Conference on Developments in Language Theory (DLT 2022) took place in Tampa, Florida, USA in May 2022. The conference, organized by the Department of Mathematics and Statistics of the University of South Florida, focused on formal languages and automata. This special issue of Theory of Computing Systems contains extended versions of selected papers presented at DLT 2022, as well as papers based on invited talks. The papers cover a range of topics in the field of formal languages and automata, and underwent a rigorous review process. The preface expresses gratitude to the authors and reviewers involved in the publication. [Extracted from the article]

Purpose: The current article presents the results of a case study dealing with the historical roots of Eastern European researchers in computer science. Design/methodology/approach: The study is based on an analysis of cited references stemming from a collection of around 80,000 computer science papers by Eastern European researchers published from 1989 to 2014. By using a method called "reference publication year spectroscopy" (RPYS) for historical analyses based on bibliometric data, we analyze around 800,000 references cited in those papers. The study identifies the peak years, including most frequently cited publications (from 1952, 1965 and 1975), and focuses on these outstanding works for the field. The research shows how these influential papers were cited in Eastern Europe and in general, and on which scientific fields they have the most impact. Findings: A noteworthy publication that seems to have a tremendous effect on Eastern European computer science is Zadeh's "Fuzzy sets" article which appeared in Information and Control in 1965. The study demonstrates that computer scientists from Eastern Europe are more conservative in their citation behaviour and tend to refer to older and more established research than their counterparts from the West. Originality/value: Which are the historical roots of researchers working in a particular field or on a specific topic? Are there certain publications – landmark papers – which are important for their research? We guess that these are questions bothering researchers in many fields. [ABSTRACT FROM AUTHOR]

The present study aims to measure the contributions of Prof. Anurag Kumar, who served as the Director at the Indian Institute of Science (IISc) in Bengaluru between August 2014 to July 2020. He has contributed 181 publications during his 36 years of career. He has published his majority of publications 171 (94.48%) in collaboration; most active collaborators with Prof. Anurag Kumar are Altman E. with (17) publications, Kuri Joy (15), Anand (14), and Singh (12). His highest Collaboration Coefficient found is 0.73 in 2013, and the highest Modified Collaboration Coefficient is 1.33 in the year 2018. The highest degree of collaboration observed for Prof. Anurag Kumar was 1.00. The highest Collaborative Index of Prof. Anurag found is 4.75 in the year 2016. His publications received 2595 citations so far, with 14.3 citations for each publication and an average citation of 72.08 per year. He has produced most of his publications in the field of computer science (45.9%). He preferred conference papers as his communication channel, where he published 100 (55.24%) papers out of 181. Prof. Anurag Kumar has contributed the highest (62) publication between 2005-2010, and he has published his first publication at the age of 30. [ABSTRACT FROM AUTHOR]

Secondary school students (N = 269) participated in a daylong visual programming course held in a stimulating environment for start‐up enterprises. The tasks were application‐oriented and partly creative. For example, a wearable device with light‐emitting diodes, (ie, LEDs) could be applied to a T‐shirt and used for optical messages. Our research questions related to the control‐value model of achievement emotions. We measured experienced enjoyment four times and examined the dependence of enjoyment on the individual tasks. Experience of enjoyment was also tested for the prediction of students' self‐efficacy for programming. The results showed that momentary enjoyment was not significantly dependent on the task situation, but it was dependent on the general enjoyment of programming. However, students with lower enjoyment scores showed higher increases in enjoyment during the final tasks than those with higher initial scores. The emotion score of the girls increased more than those of the boys but the girls' overall enjoyment scores were lower than those of the boys. Students' self‐efficacy beliefs of both genders increased over the course, and some of the differences in beliefs can be explained by the enjoyment of the course. In conclusion, our teaching approach seemed beneficial for the motivation to learn programming, particularly among girls. Practitioner notes What is already known about this topic Lower secondary students often report a lack of self‐efficacy beliefs for visual programming, especially girls whose confidence in their abilities seems to be missing. Activities that show how programming can be used in everyday life or at work promote interest and enjoyment, especially among girls. What this paper adds Experiencing enjoyment did not depend on individual task types (more structured vs. more open), but proved to be stable across all tasks. The experience of positive emotions in our computer science course had an impact on the secondary school students' self‐efficacy beliefs. Implications for practice and/or policy The combination of smart textiles and programming was viewed as a motivating learning experience with the potential to foster secondary school students' confidence and problem‐solving skills in computer science. A guided sequence of learning to debug can provide a self‐enhancing foundation for the students' own activities with following tasks that are more open and creative approaches. What is already known about this topic Lower secondary students often report a lack of self‐efficacy beliefs for visual programming, especially girls whose confidence in their abilities seems to be missing. Activities that show how programming can be used in everyday life or at work promote interest and enjoyment, especially among girls. What this paper adds Experiencing enjoyment did not depend on individual task types (more structured vs. more open), but proved to be stable across all tasks. The experience of positive emotions in our computer science course had an impact on the secondary school students' self‐efficacy beliefs. Implications for practice and/or policy The combination of smart textiles and programming was viewed as a motivating learning experience with the potential to foster secondary school students' confidence and problem‐solving skills in computer science. A guided sequence of learning to debug can provide a self‐enhancing foundation for the students' own activities with following tasks that are more open and creative approaches. [ABSTRACT FROM AUTHOR]

Neutrosophic topological spaces (NTS) offer a novel framework for uncertainty modeling by incorporating degrees of truth, indeterminacy, and falsity. This paper investigates the potential applications of NTS in computer science. We provide background on neutrosophic sets and their extension to topological spaces. We then explore how NTS could be used for uncertainty modeling in data analysis (e.g., handling noisy data in sensor networks), pattern recognition (e.g., improving image classification with imprecise features), and information retrieval (e.g., enhancing search results by considering relevance uncertainty). We discuss the challenges associated with applying NTS and highlight promising areas for future research, such as developing efficient algorithms for NTS operations. Overall, this paper aims to stimulate further exploration of how neutrosophic topological spaces can contribute to advancements in various computer science domains. [ABSTRACT FROM AUTHOR]

This paper introduces a ranking and selection approach to psychoacoustic and psychophysical experimentation, with the aim of identifying top-ranking samples in listening experiments with minimal pairwise comparisons. We draw inspiration from sports tournament designs and propose to adopt modified knockout (KO) tournaments. Two variants of modified KO tournaments are described, which adapt the tree selection sorting algorithm and the replacement selection algorithm known from computer science. To validate the proposed method, a listening experiment is conducted, where binaural renderings of seven chamber music halls are compared regarding loudness and reverberance. The rankings obtained by the modified KO tournament method are compared to those obtained from a traditional round-robin (RR) design, where all possible pairs are compared. Moreover, the paper presents simulations to illustrate the method's robustness when choosing different parameters and assuming different underlying data distributions. The study's findings demonstrate that modified KO tournaments are more efficient than full RR designs in terms of the number of comparisons required for identifying the top ranking samples. Thus, they provide a promising alternative for this task. We offer an open-source implementation so that researchers can easily integrate KO designs into their studies. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the differences between conference papers and journal papers in the field of computer science based on Bayesian network. This paper investigated the differences between conference papers and journal papers in the field of computer science based on Bayesian network, a knowledge-representative framework that can model relationships among all variables in the network. We defined the variables required for Bayesian networks modeling, calculated the values of each variable based Aminer dataset (a literature data set in the field of computer science), learned the Bayesian network and derived some findings based on network inference. The study found that conferences are more attractive to senior scholars, the academic impact of conference papers is slightly higher than journal papers, and it is uncertain whether conference papers are more innovative than journal papers. The study was limited to the field of computer science and employed Aminer dataset as the sample. Further studies involving more diverse datasets and different fields could provide a more complete picture of the matter. By demonstrating that Bayesian networks can effectively analyze issues in Scientometrics, the study offers valuable insights that may enhance researchers' understanding of the differences between journal and conference in computer science. Academic conferences play a crucial role in facilitating scholarly exchange and knowledge dissemination within the field of computer science. Several studies have been conducted to examine the distinctions between conference papers and journal papers in terms of various factors, such as authors, citations, h-index and others. Those studies were carried out from different (independent) perspectives, lacking a systematic examination of the connections and interactions between multiple perspectives. This paper supplements this deficiency based on Bayesian network modeling. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to characterize library and information science (LIS) as fragmenting discipline both historically and by applying Whitley's (1984) theory about the organization of sciences and Fuchs' (1993) theory about scientific change. Design/methodology/approach: The study combines historical source analysis with conceptual and theoretical analysis for characterizing LIS. An attempt is made to empirically validate the distinction between LIS context, L&I services and information seeking as fragmented adhocracies and information retrieval and scientific communication (scientometrics) as technologically integrated bureaucracies. Findings: The origin of fragmentation in LIS due the contributions of other disciplines can be traced in the 1960s and 1970s for solving the problems produced by the growth of scientific literature. Computer science and business established academic programs and started research relevant to LIS community focusing on information retrieval and bibliometrics. This has led to differing research interests between LIS and other disciplines concerning research topics and methods. LIS has been characterized as fragmented adhocracy as a whole, but we make a distinction between research topics LIS context, L&I services and information seeking as fragmented adhocracies and information retrieval and scientific communication (scientometrics) as technologically integrated bureaucracies. Originality/value: The paper provides an elaborated historical perspective on the fragmentation of LIS in the pressure of other disciplines. It also characterizes LIS as discipline in a fresh way by applying Whitley's (1984) theory. [ABSTRACT FROM AUTHOR]

The action required to stem the environmental and social implications of climate change depends crucially on how humankind shapes technology, economy, lifestyle and policy. With transport CO2 emissions accounting for about a quarter of the total, we examine the contribution of CO2 output by scientific travel. Thankfully for the reputation of the scientific community, CO2 emissions associated with the trips required to present a paper at a scientific conference account for just 0.003% of the yearly total. However, with CO2 emissions for a single conference trip amounting to 7% of an average individual’s total CO2 emissions, scientists should lead by example by demonstrating leadership in addressing the issue. [ABSTRACT FROM AUTHOR]

Buildings are complex structures composed of heterogeneous elements; these require building management systems (BMSs) to dynamically adapt them to occupants' needs and leverage building resources. The fast growth of information and communication technologies (ICTs) has transformed the BMS field into a multidisciplinary one. Consequently, this has caused several research papers on data-driven solutions to require examination and classification. This paper provides a broad overview of BMS by conducting a systematic literature review (SLR) summarizing current trends in this field. Unlike similar reviews, this SLR provides a rigorous methodology to review current research from a computer science perspective. Therefore, our goal is four-fold: (i) Identify the main topics in the field of building; (ii) Identify the recent data-driven methods; (iii) Understand the BMS's underlying computing architecture (iv) Understand the features of BMS that contribute to the smartization of buildings. The result synthesizes our findings and provides research directions for further research. [ABSTRACT FROM AUTHOR]

Metaphors that compare the computer to a human brain are common in computer science and can be traced back to a fertile period of research that unfolded after the Second World War. To conceptualize the emerging "intelligent" properties of computing machines, researchers of the era created a series of virtual objects that served as interpretive devices for representing the immaterial functions of the computer. This paper analyses the use of the terms "artificial" and "virtual" in scientific papers, textbooks, and popular articles of the time, and examines how, together, they shaped models in computer science used to conceptualize computer processes. [ABSTRACT FROM AUTHOR]

In this paper we study the classical problem of throughput maximization. In this problem we have a collection J of n jobs, each having a release time r j , deadline d j , and processing time p j . They have to be scheduled non-preemptively on m identical parallel machines. The goal is to find a schedule which maximizes the number of jobs scheduled entirely in their [ r j , d j ] window. This problem has been studied extensively (even for the case of m = 1 ). Several special cases of the problem remain open. Bar-Noy et al. (Proceedings of the Thirty-First Annual ACM Symposium on Theory of Computing, May 1–4, 1999, Atlanta, Georgia, USA, pp. 622–631. ACM, 1999, https://doi.org/10.1145/301250.301420) presented an algorithm with ratio 1 - 1 / (1 + 1 / m) m for m machines, which approaches 1 - 1 / e as m increases. For m = 1 , Chuzhoy et al. (42nd Annual Symposium on Foundations of Computer Science (FOCS) 2001, 14–17 October 2001, Las Vegas, Nevada, USA, pp. 348–356. IEEE Computer Society, 2001) presented an algorithm with approximation with ratio 1 - 1 e - ε (for any ε > 0 ). Recently Im et al. (SIAM J Discrete Math 34(3):1649–1669, 2020) presented an algorithm with ratio 1 - 1 / e + ε 0 for some absolute constant ε 0 > 0 for any fixed m. They also presented an algorithm with ratio 1 - O (log m / m) - ε for general m which approaches 1 as m grows. The approximability of the problem for m = O (1) remains a major open question. Even for the case of m = 1 and c = O (1) distinct processing times the problem is open (Sgall in: Algorithms - ESA 2012 - 20th Annual European Symposium, Ljubljana, Slovenia, September 10–12, 2012. Proceedings, pp 2–11, 2012). In this paper we study the case of m = O (1) and show that if there are c distinct processing times, i.e. p j 's come from a set of size c, then there is a randomized (1 - ε) -approximation that runs in time O (n m c 7 ε - 6 log T) , where T is the largest deadline. Therefore, for constant m and constant c this yields a PTAS. Our algorithm is based on proving structural properties for a near optimum solution that allows one to use a dynamic programming with pruning. [ABSTRACT FROM AUTHOR]

The recognition that different aspects of the urban environment can affect individuals' mental health is growing, as they are responsible for facilitating or inhibiting behaviors and lifestyles that affect sentiment. The increasing availability of user-generated data on social media provides information about users and their surroundings, enabling sentiment analysis. This study investigates the global production of documents on sentiment analysis and the built environment, urban or city, published between 2009 and 2023. Bibliometric indicators on trends, most cited articles, authors, institutions, countries, funding agencies, and thematic research areas were analyzed. The bibliometrix library of R software was used for the performance analysis and the VOSviewer software for mapping scientific connections. A total of 728 eligible papers were identified from 2009 to June 2023. Most publications were computer science papers (n=487). This type of analysis provides researchers with guidance on the possible critical points that can be found in this field of research, as well as informs about the multiplicity of scientific research conducted globally so far by authors, countries, sources, allocated funding, and active institutions, allowing improving the production of documents on sentiment analysis concerning the urban environment. [ABSTRACT FROM AUTHOR]

This article examines the historical contribution of the German Informatics Society (GI) to the establishment of computer education in German schools. It highlights the role of societal interests, international developments, public and professional debates, and technological change in the GI’s educational policy recommendations. The historical source base consists of conference proceedings, position papers and other publications by key actors within and outside the GI. Methodologically, the article refers to the concept of strategic fields of action. The article shows how the GI’s understanding of computer science played an important role in its initial policy recommendations. With increasing computerisation and then the World Wide Web, the GI had to adapt its recommendations to the now more complex situation in Germany and the polyphonic debate. [ABSTRACT FROM AUTHOR]

One of the topics of distance in graphs is resolving set problem. This topic has many applications in science and technology namely navigation robots, chemistry structure, and computer sciences. Suppose the set W = { s 1 , s 2 , ... , s k } ⊂ V (G) , the vertex representations of x ∈ V (G) is r m (x | W) = { d (x , s 1) , d (x , s 2) , ... , d (x , s k) } , where d (x , s i) is the length of the shortest path of the vertex x and the vertex in W together with their multiplicity. The set W is called a local m -resolving set of graphs G if r m (v | W) ≠ r m (u | W) for u v ∈ E (G). The local m -resolving set having minimum cardinality is called the local multiset basis and its cardinality is called the local multiset dimension of G , denoted by m d l (G). In our paper, we determine the establish bounds of local multiset dimension of graph resulting corona product of tree graphs. [ABSTRACT FROM AUTHOR]

Iteration is one of the most important topics in computer science and attentions are paid to functional equations involving iterates, one of which is the linear combination of alternative iterates. Recently existence, uniqueness and dependence for increasing Lipschitzian solutions were obtained for linear combination of alternative iterates on $ [0, 1] $ [ 0 , 1 ] and $ \mathbb {R} $ R in the case that all given functions are strictly increasing. In this paper we work in various cases of monotonicity (increasing and decreasing) among given functions and the unknown function. [ABSTRACT FROM AUTHOR]

In this paper, we discuss a generalization of Vieta theorem (Vieta's formulas) to the case of Clifford geometric algebras. We compare the generalized Vieta formulas with the ordinary Vieta formulas for characteristic polynomial containing eigenvalues. We discuss Gelfand–Retakh noncommutative Vieta theorem and use it for the case of geometric algebras of small dimensions. We introduce the notion of a simple basis‐free formula for a determinant in geometric algebra and prove that a formula of this type exists in the case of arbitrary dimension. Using this notion, we present and prove generalized Vieta theorem in geometric algebra of arbitrary dimension. The results can be used in symbolic computation and various applications of geometric algebras in computer science, computer graphics, computer vision, physics, and engineering. [ABSTRACT FROM AUTHOR]

Data transparency plays a critical role in understanding IoT privacy practices and making informed decisions. To gain a comprehensive understanding of transparency in the IoT environment, a systematic literature review of 58 academic articles is conducted to investigate the progress and status of existing data transparency studies from a design perspective. Data transparency was identified as a signifier to bridge the connection between user behavior and privacy risks. The level of transparency achieved was shaped by users' privacy perceptions, which in turn influenced their privacy behavior. GUI-based transparency design has been widely used in IoT, but it is not sufficient to provide users with accessible, understandable, and unified transparency information. A conceptual transparency design is proposed based on the extracted design opportunities and practices. This paper provides an important resource on transparency issues in the IoT environment, and will benefit the design and computer science communities. [ABSTRACT FROM AUTHOR]

While there is a growing body of research that explores the integration of music and coding in learning environments, much of this work has either emphasised the technical aspects of computer language design or music as a motivational context within which to learn computer science concepts. In this paper, we report on a study in which five undergraduate students with experience in both music and coding completed two creative musical tasks: one using conventional instruments and tools and one using Python code in an online music + coding environment. Inspired by the work of Christopher Small (1998. Musicking: The Meanings of Performing and Listening. University Press of New England), we describe music + coding as a set of interlocking processes which we call computational musicking and explore how practices from both domains are reimagined in this new hybrid context. We introduce semiotic theories of translation and transcription to make sense of the computational musicking process and describe strategies that participants devised in their creative process. [ABSTRACT FROM AUTHOR]

AbstractWhile computer science is widely recognized as crucial for all U.S. high school students, challenges persist for teachers’ pedagogical, content, and culturally responsive-sustaining education. In this paper, we explore how a co-teaching model with an experienced CS instructor shaped three novice CS teachers’ knowledge while implementing Advanced Placement Computer Science Principles courses. Using a multi-case study methodology, we analyzed semi-structured interviews, content knowledge test, and teacher created artifacts from the three teachers to compare their knowledge and experiences. We found that the teachers perceived the co-teaching model as valuable professional development, used pedagogical strategies to fill in content knowledge gaps, and struggled with culturally responsive-sustaining education. We discuss the implications of these findings for supporting novice CS teachers. [ABSTRACT FROM AUTHOR]

AbstractMultilingual learners, also known as English learners (ELs), are underrepresented in K-12 computer science (CS) courses, where they often struggle. This paper demonstrates how a Computer Science for English Learners (CSforEL) professional development (PD) program supported Advanced Placement CS Principles (APCSP) teachers in attending to both content and language demands while teaching ELs. We highlight qualitative findings showcasing how CSforEL PD yielded (micro)shifts in teacher practice and EL Student-Content interactions. Specifically, we discuss how unique instructional scaffolds offered within the PD shifted teachers’ awareness regarding EL students’ needs, and helped them support their EL students more effectively. [ABSTRACT FROM AUTHOR]

The project We:Design delves into the digital inequalities affecting young people in Vienna during their transition from education to employment. It not only investigates the barriers faced by youth in the job market but also collaborates with them to create an accessible and open-source job application mobile app. Employing a mixed-method approach, the project is an equal-footed collaboration between computer science and social and cultural anthropology. This paper explores the notion of ‘drifting’ within participatory research and how seemingly irrelevant data can inform the design process. By examining the We:Design case study, we discuss the importance of embracing interdisciplinary tensions and the unexpected insights that research and design ‘byproducts’ can inspire, thus advocating for a more inclusive, flexible, and open-ended approach to participatory design. [ABSTRACT FROM AUTHOR]

Frequent gradual pattern extraction is an important problem in computer science widely studied by the data mining community. Such a pattern reflects a co-variation between attributes of a database. The applications of the extraction of the gradual patterns concern several fields, in particular, biology, finances, health and metrology. The algorithms for extracting these patterns are greedy in terms of memory and computational resources. This clearly poses the problem of improving their performance. This paper proposes a new approach for the extraction of gradual and frequent patterns based on the reduction of candidate generation and processing costs by exploiting frequent itemsets whose size is a power of two to generate all candidates. The analysis of the complexity, in terms of CPU time and memory usage, and the experiments show that the obtained algorithm outperforms the previous ones and confirms the interest of the proposed approach. It is sometimes at least 5 times faster than previous algorithms and requires at most half the memory. [ABSTRACT FROM AUTHOR]

The growing diffusion of perspectivism within the debate on information system ontologies [ISOs] does not correspond to a thorough analysis of what perspectivism specifically consists of. This paper aims to fill this void. First, I show what supporting perspectivism in information system ontologies [PISO] means in terms of (minimal) claims and implications; then I argue that the definitions of ISO implicitly assume PISO's (minimal) claims or, in other words, that ISOs presuppose and maintain PISO. Section 2 presents the main definitions of ISO. Section 3 specifies what claims are common to all perspectivists in ISO. Sects. 4–7 analyze the implications of those claims. Section 8 explores the chance of multiple perspectivisms within ISOs' domain. Finally, Sects. 9–10 assume that, if PISO's (minimal) claims and (their) implications can be inferred from ISO's definitions, then ISOs are perspectivist, or PISO's minimal claims are assumptions underlying ISOs. [ABSTRACT FROM AUTHOR]

Prior research has introduced the Single-Instruction-Multiple-Data paradigm for DNA computing (SIMD DNA). It offers the potential for storing information and performing in-memory computations on DNA, with massive parallelism. This paper introduces three new SIMD DNA operations: sorting, shifting, and searching. Each is a fundamental operation in computer science. Our implementations demonstrate the effectiveness of parallel pairwise operations with this new paradigm. [ABSTRACT FROM AUTHOR]

Teaching and learning methods that are related to student-generated content (SGC) seem a promising strategy for including sustainable development goals (SDGs) in education (established as a fundamental cornerstone in the achievement of these goals by the United Nations). This paper describes the inclusion of SDGs through the implementation of website learning projects, whose products are SGC where materials developed by students can be made available to other students (from the same or different courses) in Project Management subjects of the Degree in Computer Science. The method has trialled at two different universities working in a coordinated way. A total of 301 students developed these projects with which they completed the content of the subject, in addition to achieving learning with respect to the SDGs, increasing their understanding of the impact of information and communication technologies on the SDGs, and their awareness of the related problems. We also found that more learning is perceived with information search and content generation activities than with those that focus on the use of materials produced by peers. Finally, it is observed that the method has similar results in different contexts and with different groups of students. [ABSTRACT FROM AUTHOR]

Computer system resilience refers to the ability of a computer system to continue functioning even in the face of unexpected events or disruptions. These disruptions can be caused by a variety of factors, such as hardware failures, software glitches, cyber attacks, or even natural disasters. Modern computational environments need applications that can recover quickly from major disruptions while also being environmentally sustainable. Balancing system resilience with energy efficiency is challenging, as efforts to improve one can harm the other. This paper presents a method to enhance disaster survivability in microservice architectures, particularly those using Kubernetes in cloud-based environments, focusing on optimizing electrical energy use. Aiming to save energy, our work adopt the consolidation strategy that means grouping multiple microservices on a single host. Our aproach uses a widely adopted analytical model, the Generalized Stochastic Petri Net (GSPN). GSPN are a powerful modeling technique that is widely used in various fields, including engineering, computer science, and operations research. One of the primary advantages of GSPN is its ability to model complex systems with a high degree of accuracy. Additionally, GSPN allows for the modeling of both logical and stochastic behavior, making it ideal for systems that involve a combination of both. Our GSPN models compute a number of metrics such as: recovery time, system availability, reliability, Mean Time to Failure, and the configuration of cloud-based microservices. We compared our approach against others focusing on survivability or efficiency. Our approach aligns with Recovery Time Objectives during sudden disasters and offers the fastest recovery, requiring 9% less warning time to fully recover in cases of disaster with alert when compared to strategies with similar electrical consumption. It also saves about 27% energy compared to low consolidation strategies and 5% against high consolidation under static conditions. [ABSTRACT FROM AUTHOR]

Orthogonal array and a large set of orthogonal arrays are important research objects in combinatorial design theory, and they are widely applied to statistics, computer science, coding theory, and cryptography. In this paper, some new series of large sets of orthogonal arrays are given by direct construction, juxtaposition construction, Hadamard construction, finite field construction, and difference matrix construction. Subsequently, many new infinite classes of orthogonal arrays are obtained by using these large sets of orthogonal arrays and Kronecker product. [ABSTRACT FROM AUTHOR]

The sparse literature on the use of imperatives in research papers suggests that they are relatively common in a small number of disciplines, but rare, if used at all, in others. The present study addresses the use of imperatives in a corpus of upper-level A-graded student papers from 16 disciplines. A total of 822 papers collected within the past 5 years were analyzed for imperative use, with particular emphasis placed on the main text of papers from the five disciplines with the highest proportion of imperatives. In each of these disciplines, text-based interviews were conducted with faculty members to establish disciplinary contexts. Results show that imperatives are used frequently in physics, philosophy, economics, mechanical engineering, and linguistics, though in quite varying ways. The interview data suggest that successful and experienced student writers adopt the potentially 'high risk strategy' (Hyland 2012) of initiating a sentence with an imperative for various strategic purposes that are discipline-specific. Such insights have implications for writing instructors and materials designers in both L1 and L2 contexts. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has emerged as an innovative technology with the potential to revolutionize various industries including libraries and information science. Academic libraries are increasingly adopting artificial intelligence (AI) to enhance services, improve efficiency, and enhance user experience. This study utilizes a bibliometric approach to comprehensively analyze current research on AI in academic libraries (AI in ALs). This study employed bibliometric indicators to identify key trends, patterns, and research gaps in the existing literature. A comprehensive dataset of 373 research papers on AI in ALs published between 2002 and 2022 was collected and analyzed using the Scopus database. Various bibliometric tools, such as Biblioshiny, VOSviewer, and BibExcel, have enhanced this analysis. The findings of this study provide important insights. By 2022, there were 64 publications, constituting 17.16% of the total corpus, accompanied by 65 citations. In contrast, 2019 witnessed only 33 publications yet accumulated a substantial number of citations, amounting to 294, representing 8.85% of the overall citations. Conference papers exhibited the highest frequency among different publication types, with 165 publications, whereas journal articles had the highest citation count, accumulating 217 citations. Geographically, China emerged as the leading contributor with 119 publications, and Wuhan University stood out as the most prominent affiliation. Notably, the "Lecture Notes in Computer Science" series emerged as the most prolific source title, publishing 15 articles, of which eight were cited. The authors Wang J., Wang C., and Wang X. from China demonstrated significant contributions, consistently publishing four papers annually from 2010 to 2022. [ABSTRACT FROM AUTHOR]

ChatGPT, a recently developed product by openAI, is successfully leaving its mark as a multi-purpose natural language based chatbot. In this paper, we are more interested in analyzing its potential in the field of computational biology. A major share of work done by computational biologists these days involve coding up bioinformatics algorithms, analyzing data, creating pipelining scripts and even machine learning modeling and feature extraction. This paper focuses on the potential influence (both positive and negative) of ChatGPT in the mentioned aspects with illustrative examples from different perspectives. Compared to other fields of computer science, computational biology has (1) less coding resources, (2) more sensitivity and bias issues (deals with medical data), and (3) more necessity of coding assistance (people from diverse background come to this field). Keeping such issues in mind, we cover use cases such as code writing, reviewing, debugging, converting, refactoring, and pipelining using ChatGPT from the perspective of computational biologists in this paper. [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]

Deep neural networks are extensively used in text mining and Natural Language Processing is to enable computers to understand, analyze, and generate natural language data, such as text or speech, but semantic resources, such as taxonomies and ontologies, are not fully included in deep learning. In this paper, we use Deep Convolutional Neural Network (Deep CNN) to classify research papers using the Computer Science Ontology, an ontology of research areas in the field of computer science. It takes as input the abstract and keywords of a particular research paper and returns the relevant research topic. To evaluate our ontology, we used a gold standard dataset that includes research articles. To further improve text classification results, we propose to design a Deep CNN model. We then used ontology matching to reduce the classes and get better results. Experimental results show that the proposed approach outperforms the one with the highest precision, recall, and F1-score. [ABSTRACT FROM AUTHOR]

The approximate uniform sampling of graph realizations with a given degree sequence is an everyday task in several social science, computer science, engineering etc. projects. One approach is using Markov chains. The best available current result about the well-studied switch Markov chain is that it is rapidly mixing on P-stable degree sequences (see DOI:10.1016/j.ejc.2021.103421). The switch Markov chain does not change any degree sequence. However, there are cases where degree intervals are specified rather than a single degree sequence. (A natural scenario where this problem arises is in hypothesis testing on social networks that are only partially observed.) Rechner, Strowick, and Müller–Hannemann introduced in 2018 the notion of degree interval Markov chain which uses three (separately well studied) local operations (switch, hinge-flip and toggle), and employing on degree sequence realizations where any two sequences under scrutiny have very small coordinate-wise distance. Recently, Amanatidis and Kleer published a beautiful paper (DOI:10.4230/LIPIcs.STACS.2023.7), showing that the degree interval Markov chain is rapidly mixing if the sequences are coming from a system of very thin intervals which are centered not far from a regular degree sequence. In this paper, we substantially extend their result, showing that the degree interval Markov chain is rapidly mixing if the intervals are centered at P-stable degree sequences. [ABSTRACT FROM AUTHOR]

One of the most widely referenced Swarm Intelligence (SI) algorithms is the Grey Wolf Optimizer (GWO), which is based on the pack hunting and natural leadership organization of grey wolves. The GWO algorithm offers several significant benefits, including simple implementation, rapid convergence, and superior convergence outcomes, leading to its effective application in diverse fields for solving optimization issues. Consequently, the GWO has rapidly garnered substantial research interest and a broad audience across numerous areas. To better understand the literature on this algorithm, this review paper aims to consolidate and summarize research publications that utilized the GWO. The paper begins with a concise introduction to the GWO, providing insight into its natural establishment and conceptual framework for optimization. It then lays out the theoretical foundation and key procedures involved in the GWO, following which it comprehensively examines the most recent iterations of the algorithm and categorizes them into parallel, modified, and hybridized variations. Subsequently, the primary applications of the GWO are thoroughly explored, spanning various fields such as computer science, engineering, energy, physics and astronomy, materials science, environmental science, and chemical engineering, among others. This review paper concludes by summarizing the key arguments in favour of GWO and outlining potential lines of inquiry in the future research. [ABSTRACT FROM AUTHOR]

This document is an editorial summarizing the Applied Geometric Algebras in Computer Science and Engineering (AGACSE) conference held in Brno, Czech Republic in September 2021. The conference aimed to promote the use of geometric algebra in fields such as image processing, robotics, and quantum computing. The conference proceedings were published in the journal Mathematical Methods in the Applied Sciences. The editorial provides a list of accepted papers, covering topics such as applied geometry, technological applications, algebra, and quantum phenomena. One specific paper explores the use of geometric algebra in teaching rotations through neural networks. The document is a compilation of research papers showcasing the applications of geometric algebra in various fields, including robotics, control systems, image processing, cryptography, and physics. Each paper presents a specific problem or application and proposes a unique approach or solution using geometric algebra. The authors compare their methods with existing techniques and provide mathematical analysis to support their claims. Overall, the papers demonstrate the versatility and effectiveness of geometric algebra in different domains. [Extracted from the article]

Purpose – Informally computer scientists reported they could access free copies of research papers they needed via tools such as Google Scholar. To ascertain whether this perception came from widespread free access or from unnoticed employer-paid access, the purpose of this paper was to locate computer science papers and determine what proportion was freely available using Google Scholar. Design/methodology/approach – A sample of 1,967 conference papers and periodical papers from 2003 to 2010, indexed in the ACM Guide to Computing Literature, was searched for manually in Google Scholar, using the paper or article title and the first author's surname and supplementary searches as needed. Findings – Free full-text versions were found for 52 per cent of the conference papers and 55 per cent of the periodical papers. Documents with older publication dates were more likely to be freely accessible than newer documents, with free versions found for 71 per cent of items published in 2003 and 43 per cent of items published in 2010. Research limitations/implications – Results were limited to the retrieval of known computer science publications via Google Scholar. Future research could examine whether the decline found in this study is specific to Google Scholar or reflects a decrease in the free sharing of research by computer scientists. Originality/value – Previous research for computer science found lower levels of free access than this research determined, but the decline found in this study runs contrary to increases that have been found. This research confirms many computer science papers are available for free but also that subscription holdings are necessary for complete coverage of papers in the field. [ABSTRACT FROM AUTHOR]

Nowadays, there has been a rapidly increasing number of scientific submissions in multiple research domains. A large number of journals have various acceptance rates, impact factors, and rankings in different publishers. It becomes time-consuming for many researchers to select the most suitable journal to submit their work with the highest acceptance rate. A paper submission recommendation system is more critical for the research community and publishers as it gives scientists another support to complete their submission conveniently. This paper investigates the submission recommendation system for two main research topics: computer science and applied mathematics. Unlike the previous works (Wang et al., 2018; Son et al., 2020) that extract TF–IDF and statistical features as well as utilize numerous machine learning algorithms (logistics regression and multiple perceptrons) for building the recommendation engine, we present an efficient paper submission recommendation algorithm by using different bidirectional transformer encoders and the Mixture of Transformer Encoders technique. We compare the performance between our methodology and other approaches by one dataset from Wang et al. (2018) with 14012 papers in computer science and another dataset collected by us with 223,782 articles in 178 Springer applied mathematics journals in terms of top K accuracy (K = 1 , 3 , 5 , 10). The experimental results show that our proposed method extensively outperforms other state-of-the-art techniques with a significant margin in all top K accuracy for both two datasets. We publish all datasets collected and our implementation codes for further references. 1 1 https://github.com/BinhMisfit/PSRMTE. • Bidirectional transformer encoders can improve the performance of the paper submission recommendation system. • The Mixture of Transformer Encoders framework shows the efficiency in the paper submission recommendation problem. • Proposed techniques can surpass other recent techniques on two datasets related. [ABSTRACT FROM AUTHOR]