286 results
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2. Inter part 2 Computer Science Guess Papers 2024 Punjab boards
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Computer science ,General interest ,News, opinion and commentary - Abstract
Intermediate annual exams under BISE Lahore and other Punjab boards are underway. The following is a suggested guess paper for the 2024 final board exams in Computer Science, applicable to [...]
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- 2024
3. South African research contributions to Lecture Notes in Computer Science, 1973-2022.
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Naudé, Filistéa and Kroeze, Jan H.
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COMPUTER science ,ARTIFICIAL intelligence ,RESEARCH personnel ,AUTHORSHIP collaboration ,PERIODICAL articles - Abstract
Lecture Notes in Computer Science (LNCS) is a globally recognised publication outlet for the field of Computer Science, including in South Africa. In this study, spanning from 1973 to 2022, we investigated the research participation of South African based authors in LNCS. The publication output and citation impact of these authors were compared to the global Computer Science and LNCS output. The authorship patterns and collaborative behaviour of South African LNCS papers were explored, and a keyword or topic analysis also conducted. Of the total of 518 662 LNCS papers published globally between 1973 and 2022, South African based researchers contributed 1150 papers (0.22%). The LNCS papers from South Africa exhibit a strong collaborative publication culture, with 1043 (91%) co-authored and 107 (9%) singleauthored works. Local LNCS researchers prefer institutional collaboration (43%), followed by international (37%) and national collaboration (11%). Europe emerged as the most significant collaboration partner for LNCS researchers in South Africa. Of the 1150 papers, 836 (73%) had received citations, while 314 (27%) had not. On average, papers published by South African based authors received 6.05 citations, compared to the global LNCS average of 9.49 citations per paper. A keyword analysis revealed that the majority of papers by South African authors focus on artificial intelligence. The results indicate that, although LNCS serves as a reputable dissemination platform for Computer Science research output both globally and locally, South African authors should consider publishing more journal articles to build and improve their researcher profiles. Significance: * The study shows that LNCS is the most frequent publication outlet for Computer Science researchers, globally and in South Africa. * The study offers insight into the publication output, authorship patterns, collaborative behaviour and citation impact of South African based Computer Science researchers. [ABSTRACT FROM AUTHOR]
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- 2024
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4. Preface of the Special Issue Dedicated to Selected Papers from IWOCA 2022.
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Bazgan, Cristina and Fernau, Henning
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WATERMARKS ,COMPUTER science ,DATA structures ,INDEPENDENT sets ,BIPARTITE graphs - Abstract
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]
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- 2024
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5. From Crisis to Opportunity: Practices and Technologies for a More Effective Post-COVID Classroom
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Jeremie Regnier, Ethan Shafer, Edward Sobiesk, Nicholas Stave, and Malcolm Haynes
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In our post-pandemic world, where the majority of higher education institutions have transitioned back to in-person classes, this paper argues that we must not return to pre-COVID teaching practices. Instead, we have the obligation and opportunity to create an educational experience and environment that better facilitates learning and instruction. This paper presents post-COVID best practices for employing technology in higher education based on an original survey and follow-up interviews of seventeen computing instructors at our institution. After a literature review, we describe four general categories of practices that enhance the post-COVID classroom: online student activities, digital instructor notes, remote classroom participation and collaboration, and a paperless classroom. For each of these categories, we provide vignettes to illustrate scope and intent. We also offer recommendations for addressing digital dishonesty, required infrastructure, institutional support, and being prepared to seamlessly return to a blended or fully remote environment in the event of another crisis. Finally, we identify additional emerging technological challenges and opportunities that require further effort. Overall, this paper emphasizes the need for a shift towards improved practices in the classroom rather than just a return to pre-pandemic norms. We believe implementing these recommendations will result in a more flexible, accessible, and robust post-COVID educational experience.
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- 2024
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6. Text-based paper-level classification procedure for non-traditional sciences using a machine learning approach.
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Moctezuma, Daniela, López-Vázquez, Carlos, Lopes, Lucas, Trevisan, Norton, and Pérez, José
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MACHINE learning ,COMPUTER science ,INFORMATION science ,CLASSIFICATION ,CARTOGRAPHY - Abstract
Science as a whole is organized into broad fields, and as a consequence, research, resources, students, etc., are also classified, assigned, or invited following a similar structure. Some fields have been established for centuries, and some others are just flourishing. Funding, staff, etc., to support fields are offered if there is some activity on it, commonly measured in terms of the number of published scientific papers. How to find them? There exist well-respected listings where scientific journals are ascribed to one or more knowledge fields. Such lists are human-made, but the complexity begins when a field covers more than one area of knowledge. How to discern if a particular paper is devoted to a field not considered in such lists? In this work, we propose a methodology able to classify the universe of papers into two classes; those belonging to the field of interest, and those that do not. This proposed procedure learns from the title and abstract of papers published in monothematic or "pure" journals. Provided that such journals exist, the procedure could be applied to any field of knowledge. We tested the process with Geographic Information Science. The field has contacts with Computer Science, Mathematics, Cartography, and others, a fact which makes the task very difficult. We also tested our procedure and analyzed its results with three different criteria, illustrating its power and capabilities. Interesting findings were found, where our proposed solution reached similar results as human taggers also similar results compared with state-of-the-art related work. [ABSTRACT FROM AUTHOR]
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- 2024
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7. Analysing the Evolution of Student Interaction Patterns in a Massive Private Online Course
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Di Sun, Gang Cheng, and Heng Luo
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Recently, researchers have proposed to leverage technology-supported data (log files) to investigate temporal and sequential patterns of interaction behaviors in learning processes. There are two major challenges to be addressed: clarifying the positioning of interaction levels and identifying the evolution of the interaction action patterns in learning processes, particularly for students with differing achievements. This paper explores the use of sequential pattern mining to address the evolution of student action patterns in Massive Private Online Courses (MPOCs) and compare these patterns between different achievement groups. The study was conducted with first-year undergraduate computer science students enrolled in a computer application course at a traditional open university in one of the Chinese provinces (N = 1375). The results showed the development of various action patterns in each phase of the course and the distinct action patterns for high-achieving and low-achieving students. The findings of study provide a new perspective for instructors and students to understand interaction patterns at the fine-grained level, and can help instructional designers develop learner-cantered courses and platforms to improve online learning.
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- 2024
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8. Using Debugging as a Platform for Transdisciplinary Learning
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Nicole Panorkou, Toni York, and Erell Germia
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In this paper we discuss the types of knowledge used by six middle school students as they engaged with a debugging task designed to integrate ideas from computer science, mathematics and science. Our findings show that the computational thinking practice of debugging is a rich source of opportunities to integrate these different disciplines. The analysis illustrates how the types of knowledge the students did and did not use at each step of the debugging process were related to their ability to succeed at each step. Our work contributes to theory and practice by uncovering implications for studying debugging through two refined frameworks and for designing debugging tasks to support transdisciplinary learning.
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- 2024
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9. Benefits of international collaboration in computer science: a case study of China, the European Union, and the United States
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Gómez-Espés, Alberto, Färber, Michael, and Jatowt, Adam
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- 2024
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10. Guest Editorial: Special Issue on Semantic Computing.
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D'Auria, Daniela
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SPARQL (Computer program language) ,KNOWLEDGE graphs ,SEMANTIC computing ,MOBILE computing ,QUESTION answering systems ,COMPUTER science - Abstract
The International Journal of Semantic Computing has published a special issue on Semantic Computing, which includes five selected papers from the 17th IEEE International Conference on Semantic Computing. Semantic Computing focuses on the derivation, description, integration, and use of semantics for various resources. The papers in the special issue cover topics such as intent detection, constructing probabilistic models from knowledge graphs, unsupervised estimation of subjective content descriptions, the influence of noisy labels on question answering systems, and automatic domain-adaptive sentiment analysis. Each paper presents innovative approaches and findings in their respective areas of research. [Extracted from the article]
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- 2024
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11. Foreword: special issue on CCSN-22.
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Bhushan, Bharat
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SENSOR networks ,TELECOMMUNICATION systems ,COMPUTER science ,WIRELESS communications ,APPLICATION software - Abstract
This document is a foreword for a special issue of the journal Microsystem Technologies. The special issue features selected papers from the 11th International Conference on Computing, Communication and Sensor Network (CCSN) held in September 2022 at Utkal University in Bhubaneswar, Odisha, India. The conference covered various interdisciplinary areas such as computing, communication, sensor networks, and circuit designs. The papers included in this special issue have undergone a rigorous review process and were selected for publication. The foreword expresses the hope that readers will find the papers informative. [Extracted from the article]
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- 2024
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12. Clinical Pearl: The Clinical Relevance of Neonatal Informatics.
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Falciglia, Gustave H., Hageman, Joseph R., Hussain, Walid, Alkureishi, Lolita Alcocer, Shah, Kshama, and Goldstein, Mitchell
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MEDICAL logic ,CRITICALLY ill ,PATIENTS ,ARTIFICIAL intelligence ,NEONATAL intensive care units ,ACUTE kidney failure in children ,COMPUTER science ,NEONATAL intensive care ,HOSPITAL nurseries ,INFORMATION science ,ELECTRONIC health records ,WATER-electrolyte balance (Physiology) ,QUALITY assurance ,ALGORITHMS ,CHILDREN - Abstract
The article focuses on the importance of clinical informatics in neonatal care, highlighting its potential to provide critical resources for clinicians. Topics include the specialized data needed for neonatal care, the challenges in transitioning from paper to electronic health records, and the impact of informatics on real-time patient management and research.
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- 2024
13. A Multifunctional, Low Cost and Sustainable Neonatal Database System.
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Pinheiro, Joaquim M. B., Fisher, Marilyn, Munshi, Upender K., Khalak, Rubia, Tauber, Kate A., Cummings, James J., Cerone, Jennifer B., Monaco-Brown, Meredith, Geis, Gina, Chowdhry, Rehman, Fay, Mary, Paul, Anshu A., Levine, Carolyn, Pan, Phillip, and Horgan, Michael J.
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DATABASES ,DATA quality ,NEONATAL intensive care ,NEONATAL intensive care units ,COMPUTER science ,DATABASE management ,PERINATAL death ,QUALITY assurance ,DECISION making ,INFORMATION science ,NEONATOLOGY ,ELECTRONIC health records ,ECONOMICS - Abstract
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]
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- 2024
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14. Introduction to the Special Issue: Resources for Undergraduate Cryptology.
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Boersma, Stuart, Christensen, Chris, and Millichap, Christian
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CRYPTOGRAPHY ,COMPUTATIONAL mathematics ,UNDERGRADUATES ,NUMBER theory - Abstract
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]
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- 2024
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15. Is ChatGPT making scientists hyper-productive? The highs and lows of using AI
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Prillaman, McKenzie
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- 2024
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16. Israeli mathematician Avi Wigderson clinches ACM A.M. Turing Award
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Computer science ,Algorithms ,Algorithm - Abstract
Byline: Just Earth News ACM, the Association for Computing Machinery, has named Avi Wigderson as recipient of the 2023 ACM A.M. Turing Award for foundational contributions to the theory of [...]
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- 2024
17. Maximum Matching Sans Maximal Matching: A New Approach for Finding Maximum Matchings in the Data Stream Model.
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Feldman, Moran and Szarf, Ariel
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TRIANGLES ,DATA modeling ,COMBINATORIAL optimization ,GREEDY algorithms ,COMPUTER science ,ALGORITHMS - Abstract
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]
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- 2024
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18. The nearest point problems in fuzzy quasi-normed spaces.
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Wu, Jian-Rong and Liu, He
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CONVEX sets ,MATHEMATICAL optimization ,FUZZY sets ,POINT set theory ,COMPUTER science ,NORMED rings - Abstract
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]
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- 2024
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19. Tools and Methods of Program Analysis : 6th International Conference, TMPA 2021, Tomsk, Russia, November 25–27, 2021, Revised Selected Papers
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Rostislav Yavorskiy, Ana Rosa Cavalli, Anna Kalenkova, Rostislav Yavorskiy, Ana Rosa Cavalli, and Anna Kalenkova
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- Software engineering, Artificial intelligence, Application software, Computer networks, Computer science, Programming languages (Electronic computers)
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This book constitutes the refereed proceedings of the 6th International Conference on Tools and Methods of Program Analysis, TMPA 2021, held in Tomsk, Russia, during November 25–27, 2021.The 15 full papers and 3 short papers included in this book were carefully reviewed and selected from 45 submissions. They focus on various aspects of application of modern methods of data science to the analysis of software quality.
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- 2024
20. Agents and Artificial Intelligence : 15th International Conference, ICAART 2023, Lisbon, Portugal, February 22–24, 2023, Revised Selected Papers
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Ana Paula Rocha, Luc Steels, Jaap van den Herik, Ana Paula Rocha, Luc Steels, and Jaap van den Herik
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- Artificial intelligence, Computer science, Computers, Computers, Special purpose, Computer networks, Image processing—Digital techniques, Computer vision
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This book contains the revised and extended versions of selected papers from the 15th International Conference on Agents and Artificial Intelligence, ICAART 2023, held in Lisbon, Portugal, during February 22–24, 2023. The 23 full papers included in this book were carefully reviewed and selected from 306 submissions. The conference was organized in 2 tracks as follows: One track focuses on Agents, Multi-Agent Systems and Software Platforms, Distributed Problem Solving and Distributed AI in general. The other track focuses mainly on Artificial Intelligence, Knowledge Representation, Planning, Learning, Scheduling, Perception Reactive AI Systems, and Evolutionary Computing and other topics related to Intelligent Systems and Computational Intelligence.
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- 2024
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