Computer Science Disciplines Research Articles

TRAINING AND DEVELOPMENT OF DIGITAL SKILLS IN GENERAL EDUCATION

Based on the analysis of the curricula in computer science subjects in the countries with traditions in the field and the experience of the Republic of Moldova, it is argued the need to further promote the curricular reform in general education. It is proposed to re-conceptualize the current and summative assessment methods in computer science disciplines by basing them on the evaluation of digital products developed by students: documents and electronic presentations, Web documents, computer programs, simulation models. It is recommended that the assessment itself be conducted in a digital environment, giving students the opportunity to demonstrate their knowledge and skills directly on the computer.

A free application engineering economics developed in C++ to improve the teaching process in distance learning

The present work was developed in a high education institution of Brazil. Because to the difficulty of many students of the superior technology in Indus-trial Production Management in the study of the discipline of Computer Science where the main objective is to learn computer programming, we chose to work together with the discipline of Engineering Economics to motivate and help in understanding concepts related to the C++ language as well as to promote improvements in the programming steps. Each team of 4 or 5 students developed an application that has the main tools of Engineering Economics and, for social purposes, these students provided free share the respective applications and posted the link in social networks. It was observed that there was a 44.83% improvement in the performance of the students in the course evaluations after their participation in the project. It was also possible to observe the good acceptance on the part of the users regarding the applications developed and shared free.

Sampling a Near Neighbor in High Dimensions — Who is the Fairest of Them All?

Similarity search is a fundamental algorithmic primitive, widely used in many computer science disciplines. Given a set of points S and a radius parameter r > 0, the r-near neighbor ( r -NN) problem asks for a data structure that, given any query point q , returns a point p within distance at most r from q . In this paper, we study the r -NN problem in the light of individual fairness and providing equal opportunities: all points that are within distance r from the query should have the same probability to be returned. In the low-dimensional case, this problem was first studied by Hu, Qiao, and Tao (PODS 2014). Locality sensitive hashing (LSH) , the theoretically strongest approach to similarity search in high dimensions, does not provide such a fairness guarantee. In this work, we show that LSH based algorithms can be made fair, without a significant loss in efficiency. We propose several efficient data structures for the exact and approximate variants of the fair NN problem. Our approach works more generally for sampling uniformly from a sub-collection of sets of a given collection and can be used in a few other applications. We also develop a data structure for fair similarity search under inner product that requires nearly-linear space and exploits locality sensitive filters. The paper concludes with an experimental evaluation that highlights the unfairness of state-of-the-art NN data structures and shows the performance of our algorithms on real-world datasets.

Quantum computations for disambiguation and question answering

Automatic text processing is now a mature discipline in computer science, and so attempts at advancements using quantum computation have emerged as the new frontier, often under the term of quantum natural language processing. The main challenges consist in finding the most adequate ways of encoding words and their interactions on a quantum computer, considering hardware constraints, as well as building algorithms that take advantage of quantum architectures, so as to show improvement on the performance of natural language tasks. In this paper, we introduce a new framework that starts from a grammar that can be interpreted by means of tensor contraction, to build word representations as quantum states that serve as input to a quantum algorithm. We start by introducing an operator measurement to contract the representations of words, resulting in the representation of larger fragments of text. We then go on to develop pipelines for the tasks of sentence meaning disambiguation and question answering that take advantage of quantum features. For the first task, we show that our contraction scheme deals with syntactically ambiguous phrases storing the various different meanings in quantum superposition, a solution not available on a classical setting. For the second task, we obtain a question representation that contains all possible answers in equal quantum superposition, and we implement Grover’s quantum search algorithm to find the correct answer, agnostic to the specific question, an implementation with the potential of delivering a result with quadratic speedup.

What do faculty members know about universal design and digital accessibility? A qualitative study in computer science and engineering disciplines

Purpose Students in higher education are a diverse group comprising people with different backgrounds and abilities. Regulations require that digital learning materials and platforms employed in higher education accommodate this diversity. Furthermore, they require faculty members to have an understanding of universal design and digital accessibility, as well as practical knowledge of how to make learning materials and courses accessible for more students. The goal of this research is to gain insight into the status of such knowledge among faculty members. Methods The research presented in this paper involved a qualitative study. Semi-structured interviews were conducted with 35 faculty members employed in higher education institutions (HEIs) in Norway and Poland. The participants worked in the computer science and engineering disciplines. The data was analysed using thematic analysis, and two main themes and six sub-themes were identified. Results We found that most participants lack sufficient understanding of digital barriers and assistive technologies. Very few were aware of legislation and guidelines related to universal design. Most importantly, the majority lack practical knowledge on how to make digital learning materials and courses accessible. Furthermore, the solutions they propose for addressing the barriers are intuitive and only encompass barriers that are easy to recognise and identify. Conclusion The findings indicate that there is a gap between legislation and implementation in practice when it comes to making digital learning materials accessible in higher education. The lack of knowledge among faculty members shows that training is necessary to increase understanding and practical knowledge, and HEIs should prioritise this in strategies and action plans going forward.

(Almost) all of entity resolution.

Whether the goal is to estimate the number of people that live in a congressional district, to estimate the number of individuals that have died in an armed conflict, or to disambiguate individual authors using bibliographic data, all these applications have a common theme-integrating information from multiple sources. Before such questions can be answered, databases must be cleaned and integrated in a systematic and accurate way, commonly known as structured entity resolution (record linkage or deduplication). Here, we review motivational applications and seminal papers that have led to the growth of this area. We review modern probabilistic and Bayesian methods in statistics, computer science, machine learning, database management, economics, political science, and other disciplines that are used throughout industry and academia in applications such as human rights, official statistics, medicine, and citation networks, among others. Last, we discuss current research topics of practical importance.

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Editorial Policy

Gender Differences in Collaboration Patterns in Computer Science

The research discipline of computer science (CS) has a well-publicized gender disparity. Multiple studies estimate the ratio of women among publishing researchers to be around 15–30%. Many explanatory factors have been studied in association with this gender gap, including differences in collaboration patterns. Here, we extend this body of knowledge by looking at differences in collaboration patterns specific to various fields and subfields of CS. We curated a dataset of nearly 20,000 unique authors of some 7000 top conference papers from a single year. We manually assigned a field and subfield to each conference and a gender to most researchers. We then measured the gender gap in each subfield as well as five other collaboration metrics, which we compared to the gender gap. Our main findings are that the gender gap varies greatly by field, ranging from 6% female authors in theoretical CS to 42% in CS education; subfields with a higher gender gap also tend to exhibit lower female productivity, larger coauthor groups, and higher gender homophily. Although women published fewer single-author papers, we did not find an association between single-author papers and the ratio of female researchers in a subfield.

Deep learning does not replace Bayesian modeling: Comparing research use via citation counting

AbstractOne could be excused for assuming that deep learning had or will soon usurp all credible work in reasoning, artificial intelligence, and statistics, but like most “meme” class broad generalizations the concept does not hold up to scrutiny. Memes do not generally matter since the experts will always know better; but in the case of Bayesian software like Stan and PyMC3, even their developers and advocates bemoan the apparent dominance of deep learning as manifested in popular culture, breathtaking performance, and most problematically from funding agency peer review that impacts our ability to further advance the field. The facts, however, do not support the assumed dominance of deep learning in science upon closer examination. This letter simply makes the argument by the crudest of possible metrics, citation count, that once the discipline of Computer Science is subtracted, Bayesian software accounts for nearly a third of research citations. Stan and PyMC3 dominate some fields, PyTorch, Keras, and TensorFlow dominate others with lot of variations in between. Bayesian and deep‐learning approaches are related but very different technologies in goals, implementation, and applicability with little actual overlap‐‐so this is not a surprise. For example, deep learning cannot bring the explainability of applied math/statistics and Bayesian methods do not scale to deep‐learning data sets. While deep‐learning behemoths like Facebook and Google use and support Bayesian efforts, the Bayesian packages scientists actually use are academic/volunteer efforts punching far above their weight class, and they need financial support. It would behoove funders to fully understand the impact and role of Bayesian methods in resource allocation.

Development and Application of Artificial Intelligence Multimedia Technology Based on Big Data

Artificial intelligence is an innovative enterprise theme that combines computer science, physiology, science, and other disciplines, including expert programs, technical experiments, games, native language understanding, cognitive rehabilitation, robotics, engineering, recognition, and other fields. The breakthrough growth made the arrival of the era of big data have a fundamental impact on many traditional industries and has also promoted the transformation of teaching methods and methods in the field of education. In the traditional classroom, due to the limitations of teaching resources, teaching time, and location, students are basically passively accepted by the teacher, and the teaching form is single. This will improve in the age of big data with well-developed network message. Modern distance education uses advanced technology such as computer networks, multimedia, and artificial intelligence to build a virtual teaching environment based on the network. It breaks through the limitations of teachers, teaching materials, experimental equipment, and other resources that exist under the traditional teaching model. Using educational resources of the same scale can expand educational capabilities exponentially and at the same time overcomes the unified progress of traditional teaching methods, single teaching methods, and students’ dissatisfaction. The shortcomings of differences and personalities that are not reflected are conducive to the improvement of the quality of education. It is the original intention of education to offer students special study resources and to stimulate students’ enthusiasm for learning. To enhance the current learning environment, the article builds a personalized multimedia network teaching system based on big data and streaming media technology. By recording the teacher’s class process as a video and uploading it to the multimedia network teaching system, students can watch and download related videos online for learning and also communicate online. The system can also provide personalized and intelligent recommendations for students based on student learning habits. The system is developed based on intelligent multimedia method and has the characteristics of security and stability and has done some help for network teaching of educational institutions.

SPMM: A Model Taxonomy for Designing and Managing Quality System

Software engineering is a discipline of Computer Science in which the new sub-areas are constantly added, especially in the area of quality, data management, and architectural design. Nowadays software development languages and processes are rapidly changing to deliver high-quality software products, i.e., usable systems, hybrid, and fulfill users’ needs. This paper aims to identify and classify different process models proposed by the researchers based on characteristics of software quality, data management, and software integration and redesign. From a study of several models through a systematic mapping study, we identify different parameters and presented them in a traceability matrix. The parameters are classified into six areas. This paper provides an in-depth theoretical insight into the models and characteristics. A systematic mapping study was conducted through a literature review. The methodology used in this paper is both qualitative and quantitative. Initially, through a systematic mapping study, we study different models working on different parameters. And then proposed a model that can cover all the aspects of software implementation and management. We select ERP systems for it. Later we perform the GAP analysis and statistical evaluation of the model. It has been observed that all of the models are area specific either focused on quality parameters or management issues or architectural-based. The proposed model covers all aspects. The primary research shows that industrialists also need a better model for quality implementation. Our statistical analysis can serve as a decision-making tool for them to add to their decision-making processes. The other could use it to further enhance the framework for quality management. This model will enhance further in the future for better implementation.

Studies of Multilevel Networks via Fault-Tolerant Metric Dimensions

A subset <i>T</i> of the vertex set of a network <i>G</i> is called a resolving set for <i>G</i> if each pair of vertices of <i>G</i> have distinct representations with respect to <i>T</i>. A resolving set <i>B</i>&#x02B9; among all the resolving sets of a network <i>G</i> is called a fault-tolerant resolving set if <i>B</i>&#x02B9;&#x005C;&#x007B;<i>t</i>&#x007D; is as well a resolving set for each vertex <i>t</i> &#x03F5; <i>B</i>&#x02B9;. A fault-tolerant resolving set <i>B</i>&#x02B9; of a network <i>G</i> which contains minimum number of vertices is called a fault-tolerant metric basis. The cardinality of a fault-tolerant metric basis is called fault-tolerant metric dimension. This concept is widely used to find the integral solution of the problems existing in different disciplines of computer science and chemistry such as linear optimization problems, robot navigation, operation research problems, sensor networking, classification of chemical compounds, drug discoveries, source localization, embedding biological sequence data, detecting network motifs, comparing the interconnected networks and image processing. In this paper, we compute the fault-tolerant metric dimensions of three wheel related networks called by <i>r</i>-level anti-web wheel <i>AWW</i>(_<i>n,r</i>), <i>r</i>-level Helm <i>H</i>(_<i>n,r</i>) and <i>r</i>-level anti-web gear <i>AWJ</i>(_2<i>n,r</i>) networks in the form of different algebraic expressions consisting of the integral numbers <i>n</i> and <i>r</i>. At the end we discussed a simple method for finding the fault-tolerant metric dimensions and fault-tolerant resolving sets of a <i>r</i>-level wheel related network. We also discussed the importance of these networks in navigation.

Issues and Challenges Faced by Institutions Giving Management Education in India and Strategies to be Adopted for the Survival

Management education is considered as elitist, precious and professional course as it attracts young candidates who are very passionate and motivated by the positive consequences associated with management education to either become a successful manager or to set an example by becoming successful entrepreneur. Management education in India is predominately a derivative of western management thought and practice. Occasionally, management schools draw some inferences from Indian epics, shastras and practices. It may be worthwhile to notice that management itself as a discipline has evolved from fundamental disciplines of philosophy, psychology, economics, accounting, computer science, mathematics, statistics and industrial engineering. In this decade India has witnessed a drastic change in higher education. Especially management education is witnessing an exponential growth in terms of number of institutes imparting management education which are usually termed as Business Schools or Management Institutions. In this paper authors have tried to explore the present situation of management education in India. This paper also studies the trends prevailing in management education in India, and tries to find out how effectively the management education helps the industries as well as how does it help one to become successful entrepreneur. Further the paper explains the emerging issues of management education in India and also explores the strategies and policies to be implied to improve the quality of management education and survive in long run. This paper throws light on existing literatures in management education in India as well as discusses the challenges faced by management institutions.

SCIENTIFIC ARTICLE AS A DOCUMENT IN A PROFESSIONAL EDITION (ON THE MATERIAL OF THE SCIENTIFIC AND PRACTICAL JOURNAL “BULLETIN OF THE BOOK CHAMBER”)

The study of a document as the main research object by various sciences led to the formation of document science as a metascience for all sciences of the document and communication field: library science, bibliography, bibliology, archival science, computer science and other disciplines. The purpose of this research is a scientific article in a professional publication within the hierarchy of concepts: from a publication as a document (in a number of names: a publication (periodical, journal, professional); a scientific journal (printed, electronic)) to hypothesizing a scientific article as a document (primary and secondary) with functions, details, typical composition and language formulas of scientific style. A special place in documentary communication belongs to the following publications: books, magazines, newspapers, posters, maps, notes, divided by frequency, material structure, iconic nature of information, and purpose. In Ukraine a scientific professional publication is a periodical or ongoing publication (also electronic) included by the Attestation Board of the Ministry of Education and Science of Ukraine in the list of publications in which the results of dissertation research for obtaining the degree of doctor and candidate of science can be published. The interesting material for the study is provided by the scientific professional publication of Ukraine in the field of social communication “Bulletin of the Book Chamber” (the articles from all issues during 2020 were selected for the analysis). It promotes materials on publishing activities, legal support of book publishing and book distribution, analytical and statistical reviews of publications in Ukraine, problematic articles on the development of the media, bibliology and library science, reviews of new publications, and historical research. Within the framework of the article, the following concepts are considered: “primary document”, “secondary document”, “details”. The primary document is a text of the article, drawn up in accordance with the rules for submitting scientific articles. The secondary document includes the UDC index, DOI, abstracts, keywords, bibliography, and references. In any article certain details are singled out: 1) information about the author (authors); 2) title of the article – in Ukrainian and English; 3) text of the article with the necessary elements; 4) date (submission of the article to the editorial office). The resolution of the Presidium of the Higher Attestation Commission of Ukraine on January 15, 2003 No. 7–05/1, which is now known to any scientist, significantly unifies the scientific article. Paragraph 3 obliges the editorial boards of professional publications to accept publications according to previously known formal requirements: statement of the problem, analysis of recent studies and publications, formulation of goals, presentation of the main material of the study, and conclusions. Of course, it encourages authors to use well-established lexical and grammatical constructions that “serve” the aforementioned semantically completed compositional parts.

A conceptual framework for multidisciplinary design research with example application to agent-based modeling

The design community traditionally excels at multidisciplinary research efforts, integrating work from social science, engineering, computer science, and other disciplines. Simultaneously, design is also developing as a discipline in its own right. In order to balance a multidisciplinary 1 1 In this work we use multidisciplinary in the general sense, referring to a non-specific combination of disciplines. tradition against consolidation around a core set of disciplinary foundations, the design community must make intentional decisions about engaging in multidisciplinary research. Towards this end, we propose the Degrees of Disciplinarity Framework, a lingua franca for describing varying relationships between disciplines in a given research effort. We also introduce research archetypes in relation to this conceptual framework and provide examples of the framework using agent-based modeling research in design. Further, we discuss implications of this framework for the education of future design practitioners and researchers. • The design community must intentionally consider multidisciplinarity. • This work introduces the Degrees of Disciplinarity Framework. • The framework is demonstrated through examples to agent-based modeling.

Biological Transformation in Manufacturing: Overview and Fields of Application

Manufacturing system digitalization has recently surged due to Industry 4.0 developments. The interaction between manufacturing and computer science disciplines has driven a new generation of cyber-physical production systems. Smart factories can collect and process a large amounts of data, this data needs to be used meaningfully to raise manufacturing efficiency and sustainability. We posit that in the future improvements can be achieved through biointelligent manufacturing systems. These systems combine technological innovations, digitization, and artificial intelligence with principles derived from nature and biotechnology. Biological transformations of manufacturing systems hold many future possibilities. We provide a general overview of manufacturing system biological transformation and propose key areas for practical application in organizations.

Control of upper limb rehabilitation robot based on active disturbance rejection control

AbstractThe upper limb rehabilitation robot technology integrates rehabilitation medicine, human anatomy, mechanics, computer science, robotics, and many other disciplines. Its main function is to drive the affected limb to carry out rehabilitation training to restore the condition of patients with upper limb dyskinesia, which plays a great role in improving the quality of life. In this study, to resolve the problems of slow convergence speed and poor tracking accuracy due to the interference of patient spasms with the trajectory‐tracking control of the upper limb rehabilitation robot, a novel algorithm based on active disturbance rejection control (ADRC) is adopted, and the convergence of its main structure is proved by the time‐domain analysis method. First, this ADRC algorithm can obtain better trajectory‐tracking performance due to its non‐linear extended observer and non‐linear feedback mechanism, even if the model suffers a strong disturbance or receives inaccurate information. Second, the non‐linear tracking differentiator can guarantee to gain quick convergence speed. To validate this algorithm, a model of three degrees of freedom upper limb rehabilitation robot is established using MATLAB R2019b and three situations including strong spasm and weak spasm are carried out to prove the effectiveness and reliability of the control algorithm designed.

Study on the Mechanism of Liuwei Dihuang Pills in Treating Parkinson's Disease Based on Network Pharmacology.

Background Parkinson's disease (PD) is a common neurodegenerative disease in middle-aged and elderly people. Liuwei Dihuang (LWDH) pills have a good effect on PD, but its mechanism remains unclear. Network pharmacology is the result of integrating basic theories and research methods of medicine, biology, computer science, bioinformatics, and other disciplines, which can systematically and comprehensively reflect the mechanism of drug intervention in disease networks. Methods The main components and targets of herbs in LWDH pills were obtained through Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Its active components were screened based on absorption, distribution, metabolism, and excretion (ADME); the PD-related targets were obtained from the Genecards, OMIM, TTD, and DRUGBANK databases. We used R to take the intersection of LWDH- and PD-related targets and Cytoscape software to construct the drug-component-target network. Moreover, STRING and Cytoscape software was used to analyze protein–protein interactions (PPI), construct a PPI network, and explore potential protein functional modules in the network. The Metascape platform was used to perform KEGG pathway and GO function enrichment analyses. Finally, molecular docking was performed to verify whether the compound and target have good binding activity. Results After screening and deduplication, 210 effective active ingredients, 204 drug targets, 4333 disease targets, and 162 drug-disease targets were obtained. We consequently constructed a drug-component-targets network and a PPI-drug-disease-targets network. The results showed that the hub components of LWDH pills were quercetin, stigmasterol, kaempferol, and beta-sitosterol; the hub targets were AKT1, VEGFA, and IL6. GO and KEGG enrichment analyses showed that these targets are involved in neuronal death, G protein-coupled amine receptor activity, reactive oxygen species metabolic processes, membrane rafts, MAPK signaling pathways, cellular senescence, and other biological processes. Molecular docking showed that the hub components were in good agreement with the hub targets. Conclusion LWDH pills have implications for the treatment of PD since they contain several active components, target multiple ligands, and activate various pathways. The hub components possibly include quercetin, stigmasterol, kaempferol, and beta-sitosterol and act through pairing with hub targets, such as AKT1, VEGFA, and IL6, to regulate neuronal death, G protein-coupled amine receptor activity, reactive oxygen species metabolic process, membrane raft, MAPK signaling pathway, and cellular senescence for the treatment of PD.

The teaching of computer ethics on computer science and related degree programmes. a European survey

Within the Computer Science community, many ethical issues have emerged as significant and critical concerns. Computer ethics is an academic field in its own right and there are unique ethical issues associated with information technology. It encompasses a range of issues and concerns including privacy and agency around personal information, Artificial Intelligence and pervasive technology, the Internet of Things and surveillance applications. As computing technology impacts society at an ever growing pace, there are growing calls for more computer ethics content to be included in Computer Science curricula. In this paper we present the results of a survey that polled faculty from Computer Science and related disciplines about teaching practices for computer ethics at their institutions. The survey was completed by respondents from 61 universities across 23 European countries. Participants were surveyed on whether or not computer ethics is taught to Computer Science students at each institution, the reasons why computer ethics is or is not taught, how computer ethics is taught, the background of staff who teach computer ethics and the scope of computer ethics curricula. This paper presents and discusses the results of the survey.

COMMERCIAL AND RESEARCH CLUSTERING OF AUGMENTED REALITY: DISCOURSES AND DIVIDES BETWEEN AR APPS AND APPLICATIONS

Although the majority of Augmented Reality (AR) scholarship is based in Computer Science disciplines, it is nevertheless important to consider emergent trends in AR discourses as research and development shifts from technology labs to media markets. While technical understandings of AR are necessary, they are insufficient to understand how networked spatial computing is augmenting everyday life. In response, this paper maps and compares two specific AR discourses for nodes of power and authority. First, it systematically reviews how AR research citations are shifting from science and technical foci to applied uses of AR via a systematic scientometric review. That work allows, among other insights, consideration of the extent disciplinary boundaries shaped how AR is understood and innovated. Second is contrasting these evolving patterns with current consumer exposure to AR via a critical technocultural discourse analysis (CTDA) of the presentation of phone-based AR apps available on the iOS App Store and Google Play. Comparative discussion of these inquiries adds to understandings of how AR is conceptualised in research and commercial discourses, and how these data might inform future research and practice in the socialisation of AR systems, media, and experience.