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Multiple types of disease-associated RNAs identification for disease prognosis and therapy using heterogeneous graph learning

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science China(Information sciences) 2024年第8期67卷 341-342页

作者： Wenxiang ZHANG Hang WEI Wenjing ZHANG Hao WU Bin LIU School of Computer Science and Technology Beijing Institute of Technology School of Computer Science and Technology Xidian University Department of Teaching and Research Shenzhen University General Hospital Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging National-Regional Key Technology Engineering Laboratory for Medical UltrasoundSchool of Biomedical Engineering Shenzhen University Medical School Advanced Research Institute of Multidisciplinary Science Beijing Institute of Technology

Identifying disease-associated RNAs is crucial in revealing the pathogenic mechanisms of diseases [1], and biologists have made notable progress in this field [2]. However, more effective computational methods are needed to provide reference disease-associated RNAs, reducing the manpower and material resources required for biological experiments.

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Pharmaceutical Supply chain Risk Assessment During COVID-19 Epidemic

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IFAC-PapersOnLine 2022年第10期55卷 2203-2208页

作者： W Daoud BenAmor A Labella H Moalla Frikha L Martínez López Quantitative Methods Economic and Computer Sciences department Higher Institute of Industrial Management of Sfax Tunisia. Computer Science Department University of Jaén Spain.

The global health products supply chain is negatively influenced by the COVID-19 pandemic. Moreover, the risks in the pharmaceutical supply chain (PSC) have increased. Assessment and mitigation risks in PSC are essential issues to control and counter these risks. In this study, a 2-Tuple ARAS-BWM approach, which combines ARAS and BWM methods under linguistic 2-Tuple environment, is proposed to evaluate and address various risks to the best mitigation strategies in the pharmaceutical industry in Tunisia during COVID-19. Noted that the main risk identified in the PSC is related to supply and suppliers and its best mitigation strategy is reducing risk.

关键词： 2-Tuple BWM 2-Tuple linguistic environment ARAS COVID-19 Pharmaceutical supply chain risk assessment risk mitigation strategy

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Digital Competence of Specialists: Development Technology in a Higher Education Institution

Digital Competence of Specialists: Development Technology in...

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International Conference on Advanced computer Information Technologies (ACIT)

作者： Halyna Henseruk Serhii Martyniuk Oksana Vasylenko Yuliia Henseruk Viktor Henseruk Valerii Habrusiev Department of Computer Science and Teaching Methods Ternopil Volodymyr Hnatiuk National Pedagogical University Ternopil Ukraine Department of Theory and Practice of Translation Anhalt University of Applied Sciences Köthen Germany Department of English Philology and Methods of Teaching English Ternopil Volodymyr Hnatiuk National Pedagogical University Ternopil Ukraine Department of Pedagogy and Management of Education Ternopil Volodymyr Hnatiuk National Pedagogical University Ternopil Ukraine

ISBN: (数字)9798350350043

ISBN: (纸本)9798350350050

In a digital society, professionals who are professionally competent and have a variety of skills are increasingly in demand. Digital skills are important and form the basis of the digital competence of specialists. The purpose of the study is to analyse regulatory documents in the context of the development of digital competence of specialists, to develop, substantiate and implement the trajectory of its development in a higher education institution. A questionnaire for self-assessment by bachelor’s and master’s students and practitioners of their own level of digital competence has been developed, which contains 12 descriptors and their detailed description. Based on the analysis of regulatory documents and the survey results, the author outlines the need to include disciplines in the training programmes for specialists that would contribute to the development of their digital competence. The authors have developed a technology for the system of development of digital competence of specialists. The design stage is substantiated, which includes three blocks: academic disciplines, self-education and professional self-development. The role of professional disciplines in digital technologies in the development of digital competence of specialists is determined. The study emphasises that continuity and continuity in the training of specialists in the context of the use of digital technologies in various aspects of activity is important in this development.

关键词： Training Surveys Text analysis Trajectory Information technology

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A note on a ode model of micro rna-dependent regulation of messenger rna levels

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2021年第4期83卷 171-176页

作者： Olteanu, Mircea Ştefan, Radu Department of Mathematical Methods and Models Faculty of Applied Sciences University "Politehnica" of Bucharest Romania Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science University "Politehnica" of Bucharest Romania

We study the qualitative behavior (invariance, boundedness and equilibria) of the solutions of a mathematical model describing the dynamics of microRNA AGO complexes and mRNA targets interaction. © 2021, Politech... 详细信息

关键词： Ordinary differential equations

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Enhancing Timely Graduations: An Explainable AI Approach to Predict Academic Risks in South African Students

Enhancing Timely Graduations: An Explainable AI Approach to ...

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Electrical, computer and Energy Technologies (ICECET), International Conference on

作者： Lenny Bokgoshi Khanyisile Sixhaxa Ashwini Jadhav Seipati Nyamane Ritesh Ajoodha School of Computer Science and Applied Mathematics University of Witwatersrand Johannesburg South Africa Science Teaching and Learning Unit Faculty of Science University of Witwatersrand Johannesburg South Africa Department of Computer Science and Information Technology Sol Plaatje University Kimberley South Africa

With rising dropout rates and extended degree completion times in South African institutions, there's a pressing need to better understand and address the hurdles faced by students during their academic journey. This research harnesses the power of explainable AI to predict and classify students based on their likelihood of not completing their degrees on time. Utilizing synthetic data generated via a Bayesian network, we used predictive models that categorize students into four distinct risk profiles. This clarity in prediction not only illuminates the underlying causes of academic delays but also empowers faculty, advisors, and student support services with actionable insights. The goal of this research is to facilitate timely interventions, tailored support, and seamless transitions for students transferring between universities, ensuring more students can realize their academic aspirations within expected time frames.

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A High-Capacity Image Steganography Based on LSB Inversion and Summing of Bit Pairs

A High-Capacity Image Steganography Based on LSB Inversion a...

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Novel Intelligent and Leading Emerging sciences Conference (NILES)

作者： Loay Mamdouh Saddam Bekhet Department of Computer Science Faculty of Computers and Artificial Intelligence South Valley University Hurghada Egypt Department of Quantitative Methods Faculty of Commerce South Valley University Qena Egypt

ISBN: (数字)9798350378511

ISBN: (纸本)9798350378528

Nowadays, computer users face a challenge in maintaining the security of their information. There are many techniques for transferring information safely over networks. Image steganography, one of these techniques, is an effective way to conceal important information. The Least Significant Bit (LSB) technique is a famous method for data hiding. This technique exchanges the LSBs of the cover image pixel with the mystery message bits. However, it was always the challenging problem of increasing the number of bits utilized for embedding that led to a decreased quality of the stego image. Hence, this research targets optimizing the stego image quality by inverting the LSBs of image pixels to reduce the changes that occur in pixels. This paper proposes a new method based on summing the pairs and inverting the LSBs of the cover image pixels. The secret data are arranged in pairs, and then the sum of every two successive pairs is computed. After that, the secret bits are embedded by inverting the pixel bits depending on that sum. Finally, for more enhancement of the results, some of the inverted bits will be inverted again. Rigorous experiments using benchmark datasets confirm that the proposed scheme yields superior results compared to the substitution LSB scheme. Also, shows the effectiveness of the proposed approach in achieving a high payload with acceptable visual quality for stego image that cannot be noticed by human eyes when compared with state-of-the-art steganography techniques.

关键词： Image quality Visualization Steganography Gray-scale Benchmark testing Distortion computer security Standards Faces Payloads

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Automatic Traffic Control of Autonomous Vessels in Coastal Waters

Automatic Traffic Control of Autonomous Vessels in Coastal W...

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2023 International Conference "Quality Management, Transport and Information Security, Information Technologies", IT and QM and IS 2023

作者： Sedova, Nelly A. Sedov, Viktor A. Bazhenov, Ruslan I. Alutina, Elena F. Gorbunova, Tatiana N. Ledovskikh, Irina A. Maritime State University named after G.I. Nevelskoy Automatic and Information Systems Vladivostok Russia Maritime State University named after G.I. Nevelskoy Electrician Theoretical Bases Vladivostok Russia Sholom-Aleichem Priamursky State University Information Systems and Mathematics Birobidzhan Russia Blagoveschensk State Pedagogical University Computer Science and Methods of Teaching Computer Science Blagoveschensk Russia Moscow State University of Civil Engineering Applied Mathematics Moscow Russia Mathematics and Information Technology Pacific National University Khabarovsk Russia

ISBN: (纸本)9798350340532

The paper examines an approach to arrange marine autonomous surface ships (both with and without crew) traffic surveillance illustrated with the Amur Bay and the Golden Horn Bay water area of the city of Vladivostok. The approach involves real-time application of a computer alliance based on General Packet Radio Service (GPRS) and Global Positioning System (GPS) satellite navigation technologies. The research presents the diagram of the system to observe autonomous surface ships located in the coastal area, as well as the assessment algorithm of the current navigation. Machine learning methods applied for analyzing the obtained information contribute to the fast and quite accurate review of the surface navigation, as well as hazard evaluation of vehicles caught in the area of heading in a sea autonomous surface vessel assessment. © 2023 IEEE.

关键词： Global positioning system

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Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects

arXiv

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arXiv 2024年

作者： Wang, Yingrong Wu, Anpeng Li, Haoxuan Liu, Weiming Miao, Qiaowei Xiong, Ruoxuan Wu, Fei Kuang, Kun The College of Computer Science and Technology Zhejiang University Zhejiang Province Hangzhou310027 China The Center for Data Science Peking University Beijing China The Department of Quantitative Theory & Methods Emory University United States

This paper focuses on developing Pareto-optimal estimation and policy learning to identify the most effective treatment that maximizes the total reward from both short-term and long-term effects, which might conflict with each other. For example, a higher dosage of medication might increase the speed of a patient's recovery (short-term) but could also result in severe long-term side effects. Although recent works have investigated the problems about short-term or long-term effects or the both, how to trade-off between them to achieve optimal treatment remains an open challenge. Moreover, when multiple objectives are directly estimated using conventional causal representation learning, the optimization directions among various tasks can conflict as well. In this paper, we systematically investigate these issues and introduce a Pareto-Efficient algorithm, comprising Pareto-Optimal Estimation (POE) and Pareto-Optimal Policy Learning (POPL), to tackle them. POE incorporates a continuous Pareto module with representation balancing, enhancing estimation efficiency across multiple tasks. As for POPL, it involves deriving short-term and long-term outcomes linked with various treatment levels, facilitating an exploration of the Pareto frontier emanating from these outcomes. Results on both the synthetic and real-world datasets demonstrate the superiority of our method. Copyright © 2024, The Authors. All rights reserved.

关键词： Pareto principle

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Exploring the Impact of Random Distribution Choices on Particle Swarm Optimization: An Initial Analysis 27

Exploring the Impact of Random Distribution Choices on Parti...

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27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023

作者： Kolodziejczyk, Joanna Tarasenko, Yuliia Sulikowski, Piotr Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Zolnierska 49 Szczecin71-210 Poland National Institute of Telecommunications ul. Szachowa 1 Warsaw04-894 Poland Department of Information Systems Engineering Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Zolnierska 49 Szczecin71-210 Poland

Particle Swarm Optimization (PSO) is a robust stochastic optimization algorithm for solving complex and constrained optimization problems. This paper aims to systematically investigate the influence of diverse random number distributions on the learning parameters of PSO and evaluate the algorithm's sensitivity based on these parameters. To this end, several exhaustive numerical experiments were conducted on several test functions, including asymmetric Sphere, Easom, and Csendes. Initially, appropriate random distributions were identified for the learning parameters and proceeded to compare these distributions using all potential combinations. The sensitivity of PSO to these parameters was evaluated using the mean best score, the relative proximity of the best particle to the theoretical optimum, and the average objective function evaluations. The most significant contribution of this research lies in the insights derived from the experimental data. The discovery was that highly skewed and long-tailed distributions such as Chi, Chi-square, Lomax, and Exponential often underperform. On the other hand, distributions that are bounded proportionally to the problem domain consistently surpass the performance of the standard uniform distribution. These findings significantly enhance the understanding of PSO algorithms and provide valuable guidelines for their practical deployment. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： Particle Swarm Optimization random number distribution stochastic optimization

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A Strategy for Retrospective Evaluation of Students SQL Learning Engagements

A Strategy for Retrospective Evaluation of Students SQL Lear...

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Electrical, computer, Communications and Mechatronics Engineering (ICECCME), International Conference on

作者： Chukwuka Victor Obionwu Kalu Oji Kalu Paul Blockhaus David Broneske Gunter Saake Faculty of Computer Science Otto-von-Guericke University Germany Faculty of Computer Science Otto-von-Guericke University Magdeburg Germany Research Infrastructure and Methods Department German Centre for Higher Education Research and Science Studies Hannover Lower Saxony Germany

The adoption of e-learning pedagogy in educational institutions has become increasingly prevalent, and it has proffered solutions to notable deficiencies that existed in the traditional learning pedagogy. However, it has also opened up new sets of challenges. One such challenge is the management of the huge amounts of data generated by students in the course of their daily interaction with various e-learning subsystems. Furthermore, as these systems are mostly online assessment systems, In-depth evaluation of student’s interaction is mostly coarse, and a strategy for retrospective evaluation of students’ interaction data for improved knowledge acquisition is mostly lacking. In our own peculiar scenario, an understanding of the challenges experienced by students in their pursuit of Structured Query Language knowledge acquisition was necessary. A strategy we adopted to tackle the challenge of gaining retrospective insight into student’s learning engagements is the use of error codes, and a real-time analytics. Thus, we are able to understand the extent to which our teaching strategy is effective against reducing stress resulting in exercise task engagement, and other learning challenges that may affect knowledge acquisition by individual students in the course of their learning interactions. We show that the error code strategy is an effective indicator for tracking, and intervening on student’s Structured Query Language (SQL) based learning interactions. Our evaluation further showed that syntax errors are the most prevalent type of error encountered by students learning SQL.

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