628 results
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2. LGâs contribution into AI and the research paper submission to ICLR 2024
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LG Electronics Inc. ,Consumer electronics industry ,Artificial intelligence ,Computer science ,Consumer electronics industry ,Artificial intelligence ,Consumer news and advice ,General interest - Abstract
In a bid to invest in Artificial Intelligence, consumer group LG recently earned some academic bragging rights as two of its research papers focused on AI were chosen and presented [...]
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- 2024
3. Reflective Practices among Secondary School Computer Science Teachers: Their Point of View
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Lubna Mohammed Alshamrani
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Reflective practice is an essential catalyst through which the benefits of teaching and learning can be reaped. Through it, weaknesses and strengths can be identified in a way that helps raise the level of addressing challenges that may arise as well as overcome them. This paper presents the critical reflective practices among computer science secondary school teachers from their point of view in Riyadh, Saudi Arabia. To this extent, the study aims to determine the degree of critical reflective practices among computer science secondary school teachers in Riyadh from their perspective. The paper also seeks to investigate the effects of variables such as gender, qualifications and experience on the perceptions of the aforementioned teachers, towards the critical reflective practices among computer science secondary school teachers. The study tool is a questionnaire which consisted of two dimensions and was distributed to a population of 739 participants. From this, the study sample comprised (223) computer science teachers working in secondary school in Riyadh. The findings revealed that there is no significant difference in the estimation degree concerning the critical reflective practices due to the gender. From the results, it was also established that there is no significant difference in the degree of estimation in relation to the critical reflective practices due to educational qualification variables. On the contrary however, there is a significant difference in the degree of estimation in regard to the critical reflective practices due to the years of experience variable. These differences were evident in a group of those with more than 10 years of experience. The other findings produced by the study highlight that the participants are in agreement about the importance of critical reflective practices. The degree of reflective practice, which is from the participants' point of view, is considered to be of a high value. The majority of the subjects opted to agree with the practice of reflection after a training session. It was determined from the results that some of the most common strategies favored by practitioners involved the communal practice of mind reflection with individuals from outside the school.
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- 2024
4. 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
5. An Operations Research-Based Teaching Unit for Grade 11: The ROAR Experience, Part II
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Gabriella Colajanni, Alessandro Gobbi, Marinella Picchi, Alice Raffaele, and Eugenia Taranto
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In this paper, we continue describing the project and the experimentation of "Ricerca Operativa Applicazioni Reali" (ROAR; in English, Real Applications of Operations Research), a three-year project for higher secondary schools, introduced. ROAR is composed of three teaching units, addressed to Grades 10, 11, and 12, respectively, having the main aim to improve students' interest, motivation, and skills related to Science, Technology, Engineering, and Mathematics disciplines by integrating mathematics and computer science through operations research. In a previous paper, we reported on the design and implementation of the first unit, started in Spring 2021 at the scientific high school IIS Antonietti in Iseo (Brescia, Italy), in a Grade-10 class. Here, we focus on the second unit, carried out in Winter/Spring 2022 with the same students, now in a Grade-11 class. In particular, we describe objectives, prerequisites, topics and methods, the organization of the lectures, digital technologies used, and a challenging final project. Moreover, we analyze the feedback from students and teachers involved in the experimentation.
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- 2024
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6. 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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7. 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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8. 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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9. Impact of artificial intelligence and machine learning in the insurance industry: A bibliometric analysis 2000-2022.
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Selvakumar, Lokesh and Shanmugam, Vasantha
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ARTIFICIAL intelligence ,BIBLIOMETRICS ,INSURANCE companies ,COMPUTER science ,COMPUTER science conferences ,MACHINE learning ,CONFERENCE papers - Abstract
Artificial Intelligence (AI) and Machine Learning (ML) transforming the Insurance industry by improving efficiency, reducing costs, and providing a better customer experience. As these technologies continue to evolve, more innovation can be expected in the Insurance industry. A Bibliographic analysis is conducted for scientific mapping based on 1,084 SCOPUS-indexed publications between the year 2000-2022 using VOSviewer Application. The Analysis was conducted based on Publications by year, Source, Author, Affiliation, Country, Type, Subject Area and Funding Sponsors. The research found the result, the year 2022 had the highest publication of 203, through documents per year by the source of Lecture Notes In Computer Science Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics at 43 publications, Bauder, R.A. author is the maximum contributor, Harvard Medical School has been the major affiliate, United States of America, has the maximum 341 publications, Conference paper has the majority participation at 412 documents at 38 percent and Keywords "Artificial intelligence", Machine Learning" and "Insurance" has the highest occurrence. The maximum number of publications inthe field of computer science at 28 percent. Overall, this bibliographic analysis provides a comprehensive overview of the current state of research in AI and Machine Learning in the Insurance industry and highlights the potential for further innovation and development in this field. [ABSTRACT FROM AUTHOR]
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- 2024
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10. Tapping into early PhD aspirations to advance gender equity in computing: predicting PhD interest among upward transfer students
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Blaney, Jennifer M., Feldon, David F., and Litson, Kaylee
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- 2024
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11. Digital Modes of Interpretation of Pictish Sculpture
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Sharon Pisani, Alan Miller, and Mark Hall
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Cultural heritage is no longer something that can only be experienced in a museum exhibition. Digital tools have facilitated the distribution of material relating to artefacts, both in its representation and in presenting its context. This paper describes how digital modelling techniques can be synthesised with 3D scanning to digitally restore artefacts and create authentic replicas of their original states. The digital artefacts can then be used to assist the process of interpreting these artefacts in diverse forms, both in the museum and outside the museum. The study looks at Pictish sculpture as a case-study, restoring 3D models of two stones, and creating varying opportunities for their interpretation. As part of this study, new interactive tools, a virtual reality environment, and a virtual tour are built to assist immersive interpretation of the Pictish sculpture. The application of these digitised objects serves as an opportunity for informal learning. These applications were evaluated during a drop-in session. Findings show that all participants enjoyed the immersive mode of learning with 89% also showing a willingness to learn more about the topic.
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- 2024
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12. 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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13. Mapping the Literature on Artificial Intelligence in Academic Libraries: A Bibliometrics Approach.
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Hussain, Akhtar and Ahmad, Shakil
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ARTIFICIAL intelligence ,ACADEMIC libraries ,DATABASES ,EVIDENCE gaps ,INFORMATION science ,COMPUTER science ,BIBLIOMETRICS ,CITATION indexes - Abstract
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]
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- 2024
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14. 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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15. 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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16. Preface of the Special Issue Dedicated to Selected Papers from DLT 2022.
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Diekert, Volker and Volkov, Mikhail
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LANGUAGE acquisition , *PHILOSOPHY of language , *FORMAL languages , *LEGISLATIVE committees , *COMPUTER science - Abstract
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]
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- 2024
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17. 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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18. Smart Buildings: A Comprehensive Systematic Literature Review on Data-Driven Building Management Systems.
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Taboada-Orozco, Adrian, Yetongnon, Kokou, and Nicolle, Christophe
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CONSTRUCTION management ,INDUSTRIALIZED building ,INTELLIGENT buildings ,INFORMATION & communication technologies ,COMPUTER science - Abstract
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]
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- 2024
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19. A STATE-OF-THE-ART REVIEW OF THE BWM METHOD AND FUTURE RESEARCH AGENDA.
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ECER, Fatih
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EVIDENCE gaps ,DATABASES ,COMPUTER science ,MULTIPLE criteria decision making ,BIBLIOMETRICS - Abstract
The superiority of BWM over other weighting methods for obtaining the weight values of the attributes is that it achieves high-confidence results with a reasonable number of pairwise comparisons. Although the best-worst method (BWM) is a well-known multi-criteria decision-making (MCDM) method that has been successfully utilized in almost all scientific areas to solve challenging real-life problems, no research has comprehensively examined the state-of-the-art in this regard. The present study depicts a detailed overview of publications concerned with BWM during the period 2015–2022. Based on the information obtained from the Scopus database, this work presents a big picture of current research on BWM. In other words, this paper analyzes the existing literature about BWM and identifies thematic contexts, application areas, emerging trends, and remaining research gaps to shed light on future research agendas aligning with those gaps. Further, the most recent BWM research is analyzed in the top ten scientific areas, from engineering to materials science. “Engineering”, “computer science”, and “business, management, and accounting” are the hottest fields of BWM research. China is the most active country regarding “engineering” and “computer science”, whereas India is the leader in “business, management, and accounting”. The study also reveals that there are still many research gaps in BWM research. The big picture taken in this study will not only showcase the current situation of BWM research but will also positively impact the direction and quality of new research. [ABSTRACT FROM AUTHOR]
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- 2024
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20. Students Unlock the Power of Real Systems: An Experiential Learning in System Software Course.
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Kulenavar, Nagaratna D., Sujatha C., Umadevi F. M., Indira B., Hanchinamani, G. S., and Jayalaxmi G. N.
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SYSTEMS software ,EXPERIENTIAL learning ,INSTRUCTIONAL systems ,COMPUTER science students ,COMPUTER science ,CONCEPT mapping - Abstract
System Software is a fundamental core course for undergraduate students of Computer Science and Engineering. The traditional approach to teaching the System Software course within the School of Computer Science and Engineering lacked a meaningful connection to real-world machine architectures, leading to disinterest and reduced engagement among undergraduate students. This paper introduces an innovative teaching method designed to empower students to grasp the system programs of real systems effectively. Our approach involves effortlessly integrating the delivery of system software content with the Atmel AVR ATmega32 real-time machine, which students have previously encountered in a prior semester. Moreover, this paper provides a detailed examination of the use of a hypothetical machine in traditional teaching methodologies. While this method allowed for a more in-depth exploration of system software concepts, it struggled to establish a practical link to real machine. The novel teaching approach employed in this study adopts a unique method that links all the system software concepts with the practical system program of a real-time machine. This paper also explains how the advances in Technology has played a crucial role in considering real-time machines as examples. And it also discusses the limitations of teaching concepts using only hypothetical machine and concise overview of the chosen real-time machine is provided, followed by the observation of enhanced knowledge of system software concepts through its integration. To measure the effectiveness of the proposed methodology, we also gathered valuable feedback from the students. The course result analysis shows substantial improvement in understanding the concepts, performance and lifelong learning of the students. [ABSTRACT FROM AUTHOR]
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- 2024
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21. Some Scientific Results of the 16th International Conference PRIP-2023.
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Ablameyko, S. V., Gurevich, I. B., Nedzved, A. M., and Yashina, V. V.
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The main scientific results of the 16th International Conference on Pattern Recognition and Information Processing (PRIP-2023), Minsk, Republic of Belarus, October 2023, are reviewed and analyzed. The history of this series of conferences is outlined, and its significant role in the development of the theory and practice of image analysis, pattern recognition, and artificial intelligence is indicated. A list of articles in the special issue is provided, prepared from reports selected by the PRIP-2023 Program Committee. [ABSTRACT FROM AUTHOR]
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- 2024
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22. 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
23. 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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24. STANDARDIZATION: RESEARCH TRENDS, CURRENT DEBATES, AND INTERDISCIPLINARITY.
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GRILLO, FILIPPO, WIEGMANN, PAUL MORITZ, DE VRIES, HENK J., BEKKERS, RUDI, TASSELLI, STEFANO, YOUSEFI, AMIN, and VAN DE KAA, GEERTEN
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LITERATURE reviews ,PERFORMANCE standards ,BUSINESS success ,STANDARDIZATION ,COMPUTER science - Abstract
Standards are ubiquitous in contemporary society and play a clear role in technological development, organizational functioning, and business success. Standards are very diverse and often boundary crossing in terms of stakeholders and impact, but are such diversity and range reflected by academic studies? We take stock of standardization research over the past decade, considering the full interdisciplinary breadth of this growing field. We use bibliometrics and network analysis to map emergent trends, and conduct an in-depth review of the literature. In doing so, we find thatmanagement science, along with economics, is at the core of work on standardization, bridging academic disciplines, and leading theoretical development. Technical disciplines, such as engineering and computer science, supply the largest body of literature, but rarely cross disciplinary boundaries and remain rather isolated. Building on our review, we discuss current debates and controversies and distill four interpretative perspectives on the recent and current developments of standardization research. Finally, we propose a research agenda for standardization research and practice for the years to come. [ABSTRACT FROM AUTHOR]
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- 2024
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25. Exploring Android Obfuscators and Deobfuscators: An Empirical Investigation.
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Ebad, Shouki A. and Darem, Abdulbasit A.
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PROGRAMMING languages ,COMPUTER science ,RESEARCH personnel ,ACADEMIC programs ,SMARTPHONES ,SALINE injections - Abstract
Researchers have proposed different obfuscation transformations supported by numerous smartphone protection tools (obfuscators and deobfuscators). However, there is a need for a comprehensive study to empirically characterize these tools that belong to different categories of transformations. We propose a property-based framework to systematically classify twenty cutting-edge tools according to their features, analysis type, programming language support, licensing, applied obfuscation transformations, and general technical drawbacks. Our analysis predominantly reveals that very few tools work at the dynamic level, and most tools (which are static-based) work for Java or Java-based ecosystems (e.g., Android). The findings also show that the widespread adoption of renaming transformations is followed by formatting and code injection. In addition, this paper pinpoints the technical shortcomings of each tool; some of these drawbacks are common in static-based analyzers (e.g., resource consumption), and other drawbacks have negative effects on the experiment conducted by students (e.g., a third-party library involved). According to these critical limitations, we provide some timely recommendations for further research. This study can assist not only Android developers and researchers to improve the overall health of their apps but also the managers of computer science and cybersecurity academic programs to embed suitable obfuscation tools in their curricula. [ABSTRACT FROM AUTHOR]
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- 2024
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26. 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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27. 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
- Full Text
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28. Teachers Use AI to Grade Papers. Is It Any Good?
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Randazzo, Sara
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- *
GENERATIVE artificial intelligence , *ARTIFICIAL intelligence , *TEACHERS - Published
- 2024
29. Special Issue on Control and Applications of Multi-Agent Systems.
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Osuka, Koichi, Tsunoda, Yusuke, Imahayashi, Wataru, and Aotani, Takumi
- Subjects
MULTIAGENT systems ,COMPUTER science ,SOCIAL systems ,MACHINE learning ,GRAPH theory ,REINFORCEMENT learning - Abstract
"Multi-agent systems (MAS)" have been extensively studied across various fields, including robotics, economics, biology, and computer science. A distinctive feature of these systems is the ability of multiple agents, each with different characteristics, to perform system-wide tasks through local bottom-up interactions. Furthermore, design and control methods for system networks based on graph theory are being developed. Recent applications of these methods include autonomous driving technology, smart grids, and understanding social systems. This special issue aims to deepen the understanding of MAS, focusing on their control and applications. It features 16 papers, including one review paper. The accepted papers cover a wide range of topics, including reinforcement learning, autonomous mobility systems, and machine learning, presenting the latest research findings on MAS. These studies provide valuable insights into various aspects and potential applications of MAS. We hope that this issue will be beneficial to our readers and contribute to the advancement of future research. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
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30. Emerging opportunities of using large language models for translation between drug molecules and indications.
- Author
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Oniani, David, Hilsman, Jordan, Zang, Chengxi, Wang, Junmei, Cai, Lianjin, Zawala, Jan, and Wang, Yanshan
- Subjects
LANGUAGE models ,GENERATIVE artificial intelligence ,DRUG discovery ,MOLECULES ,EVIDENCE gaps - Abstract
A drug molecule is a substance that changes an organism's mental or physical state. Every approved drug has an indication, which refers to the therapeutic use of that drug for treating a particular medical condition. While the Large Language Model (LLM), a generative Artificial Intelligence (AI) technique, has recently demonstrated effectiveness in translating between molecules and their textual descriptions, there remains a gap in research regarding their application in facilitating the translation between drug molecules and indications (which describes the disease, condition or symptoms for which the drug is used), or vice versa. Addressing this challenge could greatly benefit the drug discovery process. The capability of generating a drug from a given indication would allow for the discovery of drugs targeting specific diseases or targets and ultimately provide patients with better treatments. In this paper, we first propose a new task, the translation between drug molecules and corresponding indications, and then test existing LLMs on this new task. Specifically, we consider nine variations of the T5 LLM and evaluate them on two public datasets obtained from ChEMBL and DrugBank. Our experiments show the early results of using LLMs for this task and provide a perspective on the state-of-the-art. We also emphasize the current limitations and discuss future work that has the potential to improve the performance on this task. The creation of molecules from indications, or vice versa, will allow for more efficient targeting of diseases and significantly reduce the cost of drug discovery, with the potential to revolutionize the field of drug discovery in the era of generative AI. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
31. Approximations for Throughput Maximization.
- Author
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Hyatt-Denesik, Dylan, Rahgoshay, Mirmahdi, and Salavatipour, Mohammad R.
- Subjects
APPROXIMATION algorithms ,COMPUTER scheduling ,COMPUTER science ,DYNAMIC programming ,OPEN-ended questions - Abstract
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]
- Published
- 2024
- Full Text
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32. Blockchain Integration and Its Impact on Renewable Energy.
- Author
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Taherdoost, Hamed
- Subjects
INTELLIGENT transportation systems ,BLOCKCHAINS ,RENEWABLE energy sources ,ALTERNATIVE fuels ,ENERGY consumption ,COMPUTER science ,MICROGRIDS ,REGULATORY compliance - Abstract
This paper investigates the evolving landscape of blockchain technology in renewable energy. The study, based on a Scopus database search on 21 February 2024, reveals a growing trend in scholarly output, predominantly in engineering, energy, and computer science. The diverse range of source types and global contributions, led by China, reflects the interdisciplinary nature of this field. This comprehensive review delves into 33 research papers, examining the integration of blockchain in renewable energy systems, encompassing decentralized power dispatching, certificate trading, alternative energy selection, and management in applications like intelligent transportation systems and microgrids. The papers employ theoretical concepts such as decentralized power dispatching models and permissioned blockchains, utilizing methodologies involving advanced algorithms, consensus mechanisms, and smart contracts to enhance efficiency, security, and transparency. The findings suggest that blockchain integration can reduce costs, increase renewable source utilization, and optimize energy management. Despite these advantages, challenges including uncertainties, privacy concerns, scalability issues, and energy consumption are identified, alongside legal and regulatory compliance and market acceptance hurdles. Overcoming resistance to change and building trust in blockchain-based systems are crucial for successful adoption, emphasizing the need for collaborative efforts among industry stakeholders, regulators, and technology developers to unlock the full potential of blockchains in renewable energy integration. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
33. Maximum Matching Sans Maximal Matching: A New Approach for Finding Maximum Matchings in the Data Stream Model.
- Author
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Feldman, Moran and Szarf, Ariel
- Subjects
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]
- Published
- 2024
- Full Text
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34. Graph based modelling of prosopographical datasets. Case study: Romans 1by1.
- Author
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Varga, Rada and Bornhofen, Stefan
- Subjects
DATABASES ,COMPUTER science ,ROMAN Empire, 30 B.C.-A.D. 476 ,INSCRIPTIONS - Abstract
In this paper, we present and discuss a promising research avenue, that is the use of graph-based models and software for prosopographical data sets. Our case study will be constituted by Romans 1by1 (http://romans1by1.com/), a digital-born prosopography focusing on people attested in classical era inscriptions; it presently hosts approximately 18,000 open access persons files. The project aimed at employing new techniques and methodologies that come from other fields (i.e. computer science), in order to approach the study of ancient population in an innovative way, to ease the research, and to create an open-access tool, available for the academic community. In the scope of this paper, we use Romans1by1 as an example to explore the perspectives of ingesting the information from a prosopographical relational database into a graph database. Graph based modelling was employed to reveal data and details on the lives of the 'ordinary' people who lived in the Roman Empire. [ABSTRACT FROM AUTHOR]
- Published
- 2024
35. The nearest point problems in fuzzy quasi-normed spaces.
- Author
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Wu, Jian-Rong and Liu, He
- Subjects
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]
- Published
- 2024
- Full Text
- View/download PDF
36. Dynamic Logic. New Trends and Applications : 5th International Workshop, DaLí 2023, Tbilisi, Georgia, September 15–16, 2023, Revised Selected Papers
- Author
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Nina Gierasimczuk, Fernando R. Velázquez-Quesada, Nina Gierasimczuk, and Fernando R. Velázquez-Quesada
- Subjects
- Computer science, Mathematical logic, Logic programming, Software engineering, Computer networks
- Abstract
This book constitutes the revised selected papers of the 5th International Workshop on Dynamic Logic. New Trends and Applications, DaLí 2023, held in Tbilisi, Georgia, during September 15–16, 2023. The 8 full papers in this book were carefully reviewed and selected from 10 submissions. They deal with new trends and applications in the area of Dynamic Logic.
- Published
- 2024
37. Rewriting Logic and Its Applications : 15th International Workshop, WRLA 2024, Luxembourg City, Luxembourg, April 6–7, 2024, Revised Selected Papers
- Author
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Kazuhiro Ogata, Narciso Martí-Oliet, Kazuhiro Ogata, and Narciso Martí-Oliet
- Subjects
- Software engineering, Computer science, Machine theory, Computer engineering, Computer networks, Computer science—Mathematics, Discrete mathematics
- Abstract
This book constitutes revised selected papers from the refereed proceedings of the 15th International Workshop on Rewriting Logic and Its Applications, WRLA 2024, held in Luxembourg City, Luxembourg, during April 6–7, 2024. The 11 full papers included in this book were carefully reviewed and selected from 16 submissions. They focus on several topics, e.g., foundations; rewriting as a logical and semantic framework; rewriting languages; verification techniques; applications; and education.
- Published
- 2024
38. Graph Drawing and Network Visualization : 31st International Symposium, GD 2023, Isola Delle Femmine, Palermo, Italy, September 20–22, 2023, Revised Selected Papers, Part I
- Author
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Michael A. Bekos, Markus Chimani, Michael A. Bekos, and Markus Chimani
- Subjects
- Computer science, Computer science—Mathematics, Discrete mathematics, Image processing—Digital techniques, Computer vision, Data structures (Computer science), Information theory, Application software, Signal processing
- Abstract
This two-volume set LNCS 14465-14466 constitutes the proceedings of the 31st International Symposium on Graph Drawing and Network Visualization, GD 2023, held in Isola delle Femmine, Palermo, Italy, in September 2023. The 31 full papers, 7 short papers, presented together with 2 invited talks, and one contest report, were thoroughly reviewed and selected from the 100 submissions. The abstracts of 11 posters presented at the conference can be found in the back matter of the volume. The contributions were organized in topical sections as follows: beyond planarity; crossing numbers; linear layouts; geometric aspects; visualization challenges; graph representations; graph decompositions; topological aspects; parameterized complexity for drawings; planar graphs; frameworks; algorithmics.
- Published
- 2024
39. Bio-Inspired Computing: Theories and Applications : 18th International Conference, BIC-TA 2023, Changsha, China, December 15–17, 2023, Revised Selected Papers, Part I
- Author
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Linqiang Pan, Yong Wang, Jianqing Lin, Linqiang Pan, Yong Wang, and Jianqing Lin
- Subjects
- Artificial intelligence, Computer networks, Computers, Special purpose, Computer systems, Computer science, Computer science—Mathematics
- Abstract
The two-volume set CCIS 2061 and 2062 constitutes the refereed post-conference proceedings of the 18th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2023, held in Changsha, China, during December 15–17, 2023.The 64 revised full papers presented in these proceedings were carefully reviewed and selected from 168 submissions. The papers are organized in the following topical sections: Volume I: Evolutionary Computation and Swarm Intelligence; and Membrane Computing and DNA ComputingVolume II: Machine Learning and Applications; and Intelligent Control and Application.
- Published
- 2024
40. Agents and Artificial Intelligence : 15th International Conference, ICAART 2023, Lisbon, Portugal, February 22–24, 2023, Revised Selected Papers
- Author
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Ana Paula Rocha, Luc Steels, Jaap van den Herik, Ana Paula Rocha, Luc Steels, and Jaap van den Herik
- Subjects
- Artificial intelligence, Computer science, Computers, Computers, Special purpose, Computer networks, Image processing—Digital techniques, Computer vision
- Abstract
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.
- Published
- 2024
41. Software Engineering and Formal Methods. SEFM 2023 Collocated Workshops : CIFMA 2023 and OpenCERT 2023, Eindhoven, The Netherlands, November 6–10, 2023, Revised Selected Papers
- Author
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Alessandro Aldini and Alessandro Aldini
- Subjects
- Software engineering, Computer systems, Computer science, Computer programming
- Abstract
This volume constitutes the papers of two workshops which were held in conjunction with the 21st International Workshop on Software Engineering and Formal Methods, SEFM 2023 Collocated Workshops, held in Eindhoven, The Netherlands, on November 6–10, 2023 The 10 full papers presented in this book were carefully reviewed and selected from 16 submissions. SEFM 2023 Collocated Workshops presents the following two workshops: 5th International Workshop on Cognition: Interdisciplinary Foundations, Models and Applications (CIFMA 2023) 11th International Workshop on Open Community approaches to Education, Research and Technology (OpenCERT 2023)
- Published
- 2024
42. Simulation of the weighted product method integrated with the CSE-UCLA evaluation model.
- Author
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Divayana, Dewa Gede Hendra
- Subjects
- *
COMPUTER science , *EVALUATORS - Abstract
The purpose of this paper was to show a calculation simulation of the Weighted Product method integrated with the CSE-UCLA evaluation model in determining the best recommendations for decision support. There are four evaluation components of the CSE-UCLA model that are used as standards for evaluation, including system assessment, program planning, program implementation, program improvement, and program certification. In addition, there are 10 evaluation aspects are used as alternative recommendations. The process of determining the best recommendation was carried out by simulating the calculation of the Weighted Product method, which consists of five stages, including preliminary data preparation, weights normalization, Vector-S calculation, Vector-V calculation, and determination of recommendations based on ranking results. The simulation results of the Weighted Product method resulted in three aspects of the CSE- UCLA evaluation model which became the best recommendations with a preference value was 0.1008. Those aspects included: aspect-1, aspect-7, and aspect-10. This paper has a positive impact on developing the insight of evaluators and education observers about innovation. This innovation demonstrates the use of the Weighted Product method in the field of computer science that can be used in determining the evaluation aspects of the CSE-UCLA model which are the best recommendations for decision support. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
43. Is ChatGPT making scientists hyper-productive? The highs and lows of using AI.
- Author
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Prillaman, McKenzie
- Abstract
Large language models are transforming scientific writing and publishing. But the productivity boost that these tools bring could have a downside. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
44. Taking Flight for a Greener Planet: How Swarming Could Help Monitor Air Pollution Sources.
- Author
-
Baumgart, Jan, Mikołajewski, Dariusz, and Czerniak, Jacek M.
- Subjects
AIR pollution monitoring ,POLLUTION monitoring ,AIR pollution ,SUSTAINABILITY ,COMMERCIAL drones - Abstract
As the world grapples with the pressing challenge of environmental sustainability, the need for innovative solutions to combat air pollution has become paramount. Air pollution is a complex issue that necessitates real-time monitoring of pollution sources for effective mitigation. This paper explores the potential of swarm algorithms applied as a novel and efficient approach to address this critical environmental concern. Swarm algorithms offer a promising framework for coordinating fleets of drones to collaboratively monitor and analyze air pollution sources. The unique capabilities of drones, including their agility, accessibility, and versatility, make them ideal candidates for aerial data collection. When harnessed in a swarm, these drones can create a dynamic and adaptable network that provides a more comprehensive and fine-grained understanding of air pollution dynamics. This paper delves into the conceptual foundations of using swarm algorithms in drone-based air pollution monitoring. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
45. Wasserstein GAN-based architecture to generate collaborative filtering synthetic datasets.
- Author
-
Bobadilla, Jesús and Gutiérrez, Abraham
- Subjects
DEEP learning ,GENERATIVE adversarial networks ,RECOMMENDER systems ,COMPUTER vision ,COMPUTER science - Abstract
Currently, generative applications are reshaping different fields, such as art, computer vision, speech processing, and natural language. The computer science personalization area is increasingly relevant since large companies such as Spotify, Netflix, TripAdvisor, Amazon, and Google use recommender systems. Then, it is rational to expect that generative learning will increasingly be used to improve current recommender systems. In this paper, a method is proposed to generate synthetic recommender system datasets that can be used to test the recommendation performance and accuracy of a company on different simulated scenarios, such as large increases in their dataset sizes, number of users, or number of items. Specifically, an improvement in the state-of-the-art method is proposed by applying the Wasserstein concept to the generative adversarial network for recommender systems (GANRS) seminal method to generate synthetic datasets. The results show that our proposed method reduces the mode collapse, increases the sizes of the synthetic datasets, improves their ratings distributions, and maintains the potential to choose the desired number of users, number of items, and starting size of the dataset. Both the baseline GANRS and the proposed Wasserstein-based WGANRS deep learning architectures generate fake profiles from dense, short, and continuous embeddings in the latent space instead of the sparse, large, and discrete raw samples that previous GAN models used as a source. To enable reproducibility, the Python and Keras codes are provided in open repositories along with the synthetic datasets generated to test the proposed architecture (https://github.com/jesusbobadilla/ganrs.git). [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
46. How to Navigate the Pitfalls of AI Hype in Health Care.
- Author
-
Suran, Melissa and Hswen, Yulin
- Subjects
DATA privacy ,ARTIFICIAL intelligence ,MEDICAL care ,COMPUTER science ,COLLEGE teachers - Abstract
In this Medical News article, Arvind Narayanan, PhD, a professor of computer science at Princeton University, discusses the benefits of using artificial intelligence in research and clinical settings while remaining cautious of hype, biases, and data privacy issues. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
47. Evaluating support systems and interface efficiency in Hour of Code's Minecraft Adventurer.
- Author
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Toukiloglou, Pavlos and Xinogalos, Stelios
- Subjects
COMPUTER science ,EMPIRICAL research ,PERFORMANCE evaluation ,USER interfaces ,LEARNING - Abstract
Hour of Code is a widely recognized global event that aims to introduce programming to novice users and integrate computer science into education. This paper presents an analysis of the effectiveness of the support system and user interface of Minecraft Adventurer, a serious game designed for the Hour of Code global event. Although previous studies have primarily focused on the educational benefits of Hour of Code games, there has been limited research on their support methods. Therefore, this paper aims to address this gap with an empirical study of the experience of 104 students who played the game for one hour. Student progress was tracked by an administering teacher and after the game session, a questionnaire was administered to collect data on the participant's perceptions of the support system, interface efficiency, and overall experience with Hour of Code. The results of the study reveal significant problems with the aforementioned systems, which apply not only to Minecraft Adventurer but also to several other similar serious games. Additionally, the findings showed a correlation between the utilization of the support system and student performance, indicating that student's comprehension of the support system significantly influences their learning outcomes. This paper concludes by providing potential solutions to address the identified insufficiencies, offering valuable insights for future researchers and game developers on the design and evaluation of serious games for educational purposes. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
48. Modular relaxed indistinguishability and the aggregation problem.
- Author
-
Bibiloni-Femenias, M. D. M. and Valero, O.
- Subjects
ARTIFICIAL intelligence ,OPERATOR functions ,COMPUTER science ,BOREDOM ,REFLEXIVITY - Abstract
The notion of indistinguishability operator plays a central role in a large number of problems that arise naturally in decision-making, artificial intelligence, and computer science. Among the different issues studied for these operators, the aggregation problem has been thoroughly explored. In some cases, the notion of indistinguishability operator can be too narrow and, for this reason, we can find two different extensions of such notion in the literature. On the one hand, modular indistinguishability operators make it possible to measure the degree of similarity or indistinguishability with respect to a parameter. On the other hand, relaxed indistinguishability operators delete the reflexivity condition of classical indistinguishability operators. In this paper, we introduced the notion of modular relaxed indistinguishability operator unifying under the same framework all previous notions. We focused our efforts on the study of the associated aggregation problem. Thus, we introduced the notion of modular relaxed indistinguishability operator aggregation function for a family of t-norms extending the counterpart formulated for classical non-modular relaxed indistinguishability operators. We provided characterizations of such functions in terms of triangle triplets with respect to a family of t-norms. Moreover, we addressed special cases where the operators fulfill a kind of monotony and a condition called small-self indistinguishability. The differences between the modular and the non-modular aggregation problem were specified and illustrated by means of suitable examples. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
49. A Survey of Knowledge Graph Approaches and Applications in Education.
- Author
-
Qu, Kechen, Li, Kam Cheong, Wong, Billy T. M., Wu, Manfred M. F., and Liu, Mengjin
- Subjects
KNOWLEDGE graphs ,KNOWLEDGE representation (Information theory) ,HIGHER education research ,GRAPH algorithms ,UNIVERSITIES & colleges ,COMPUTER science - Abstract
This paper presents a comprehensive survey of knowledge graphs in education. It covers the patterns and prospects of research in this area. A total of 48 relevant publications between 2011 and 2023 were collected from the Web of Science, Scopus, and ProQuest for review. The findings reveal a sharp increase in recent years in the body of research into educational knowledge graphs which was mainly conducted from institutions in China. Most of the relevant research work adopted a quantitative method, such as performance evaluation, user surveys, and controlled experiments, to assess the effectiveness of knowledge graph approaches. The findings also suggest that knowledge graph approaches were primarily researched and implemented in higher education institutions, with a focus on computer science, mathematics, and engineering. The most frequently addressed objectives included enhancing knowledge representation and providing personal learning recommendations, and the most common applications were concept instruction and educational recommendations. Diverse data resources, such as course materials, student learning behaviours, and online encyclopaedia, were processed to implement knowledge graph approaches in different scenarios. Relevant technical means employed for the implementation of knowledge graphs dealt with the purposes of building knowledge ontology, achieving recommendations, and creating knowledge graphs. Various pedagogies such as personalised learning and collaborative learning are supported by the knowledge graph approaches. The findings also identified key limitations in the relevant work, including insufficient information for knowledge graph construction, difficulty in extending applications across subject areas, the restricted scale and scope of data resources, and the lack of comprehensive user feedback and evaluation processes. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
50. Improved homomorphic evaluation for hash function based on TFHE.
- Author
-
Wei, Benqiang and Lu, Xianhui
- Subjects
MATHEMATICAL optimization ,DATA integrity ,COMPUTER science ,CONFERENCES & conventions ,CRYPTOGRAPHY - Abstract
Homomorphic evaluation of hash functions offers a solution to the challenge of data integrity authentication in the context of homomorphic encryption. The earliest attempt to achieve homomorphic evaluation of SHA-256 hash function was proposed by Mella and Susella (in: Cryptography and coding—14th IMA international conference, IMACC 2013. Lecture notes in computer science, vol 8308. Springer, Heidelberg, pp 28–44, 2013. https://doi.org/10.1007/978-3-642-45239-0%5f3.) based on the BGV scheme. Unfortunately, their implementation faced significant limitations due to the exceedingly high multiplicative depth, rendering it impractical. Recently, a homomorphic implementation of SHA-256 based on the TFHE scheme (Homomorphic evaluation of SHA-256. https://github.com/zama-ai/tfhe-rs/tree/main/tfhe/examples/sha256%5fbool) brings it from theory to reality, however, its current efficiency remains insufficient. In this paper, we revisit the homomorphic evaluation of the SHA-256 hash function in the context of TFHE, further reducing the reliance on gate bootstrapping and enhancing evaluation latency. Specifically, we primarily utilize ternary gates to reduce the number of gate bootstrappings required for logic functions in message expansion and addition of modulo 2 32 in iterative compression. Furthermore, we demonstrate that our optimization techniques are applicable to the Chinese commercial cryptographic hash SM3. Finally, we give specific comparative implementations based on the TFHE-rs library. Experiments demonstrate that our optimization techniques lead to an improvement of approximately 35–50% compared with the state-of-the-art result under different cores. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
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