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2021 International Conference on Information science and Communications Technologies, ICISCT 2021

作者： Raximov, Nodir Primqulov, Oybek Daminova, Barno Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Dept. of Software of Information Technologies Tashkent Uzbekistan Karshi State University Methods of Teaching Computer Science Karshi Uzbekistan

ISBN: (纸本)9781665432580

The article describes artificial intelligence, which is now widely used and developed in the field of information technology and is a part of our life. The basic concepts and classifications of artificial intelligence, its features, areas of research, analytical data on the stages of development are described. At the same time, the role and functions of artificial intelligence in intelligent systems, as well as approaches in the field of application are presented. © 2021 IEEE.

关键词： Intelligent systems

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Contactless hand tremor amplitude measurement using smartphones: development and pilot evaluation

arXiv

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arXiv 2023年

作者： Bungay, James Emokpae, Osasenaga Relton, Samuel D. Alty, Jane Williams, Stefan Fang, Hui Wong, David C. The Department of Computer Science University of Manchester United Kingdom The Leeds Institute of Health Sciences University of Leeds United Kingdom The University of Tasmania Australia University of Leeds United Kingdom Leeds Teaching Hospitals Trust United Kingdom The Department of Computer Science Loughborough University United Kingdom

Background - Physiological tremor is defined as an involuntary and rhythmic shaking. Tremor of the hand is a key symptom of multiple neurological diseases, and its frequency and amplitude differs according to both disease type and disease progression. In routine clinical practice, tremor frequency and amplitude are assessed by expert rating using a 0 to 4 integer scale. Such ratings are subjective and have poor inter-rater reliability. There is thus a clinical need for a practical and accurate method for objectively assessing hand tremor. Objective - to develop a proof-of-principle method to measure hand tremor amplitude from smartphone videos. methods - We created a computer vision pipeline that automatically extracts salient points on the hand and produces a 1-D time series of movement due to tremor, in pixels. Using the smartphones’ depth measurement, we convert this measure into real distance units. We assessed the accuracy of the method using 60 videos of simulated tremor of different amplitudes from two healthy adults. Videos were taken at distances of 50, 75 and 100 cm between hand and camera. The participants had skin tone II and VI on the Fitzpatrick scale. We compared our method to a gold-standard measurement from a slide rule. Bland-Altman methods agreement analysis indicated a bias of 0.04 cm and 95% limits of agreement from -1.27 to 1.20 cm. Furthermore, we qualitatively observed that the method was robust to differences in skin tone and limited occlusion, such as a band-aid affixed to the participant’s hand. Clinical relevance - We have demonstrated how tremor amplitude can be measured from smartphone videos. In conjunction with tremor frequency, this approach could be used to help diagnose and monitor neurological diseases. © 2023, CC BY.

关键词： Smartphones

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Analytical Modeling and Empirical Validation of Performability of Service- and Cloud-Based Dynamic Routing Architecture Patterns

Analytical Modeling and Empirical Validation of Performabili...

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Asia-Pacific Conference on Software Engineering

作者： Amirali Amiri Uwe Zdun André van Hoorn Faculty of Computer Science Research Group Software Architecture University of Vienna Vienna Austria Department of Informatics Software Engineering and Construction Methods University of Hamburg Hamburg Germany

Many dynamic routing architectural patterns are available, including distributed routing, e.g., using the sidecar pattern, or centralized routing, e.g., using event stores or service buses. Different Quality-of-Service (QoS) factors influence routing schemas and technology selection, such as performance, reliability, scalability, and control properties offered by the patterns. An analytical model can formalize the QoS factors and facilitate the architectural decision-making when changing the routing scheme, i.e., to more distributed or centralized routing. So far, the impact of these architectural patterns on performability, i.e., the overall performance of a system with impeded reliability, has not been extensively studied. This is important because deciding to increase performance, e.g., by parallel processing of requests, may lead to decreased reliability because of the added points of a crash. We propose an analytical performability model during component crashes. For the empirical validation of our proposed model, we ran an extensive experiment of 2412 hours of runtime on a private cloud infrastructure and Google Cloud Platform. The low prediction error of 1.75 % indicates the high accuracy of our performability model. These results provide important insights when making architectural decisions regarding service- and cloud-based dynamic routing.

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Engineering Educators’ Adoption and implementation of Project-Based Learning: Experiences from a South Indian University

Engineering Educators’ Adoption and implementation of Proje...

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IEEE International Conference on teaching, Assessment and Learning for Engineering (TALE)

作者： Anjal P Dijo Anantha Krishnan K. P. N. P. Subheesh Aby John S M Anzar Sajin Sachidananthan Department of Computer Science and Engineering Federal Institute of Science and Technology India Department of Computer Science and Engineering College of Engineering Kerala India Teaching Learning Centre SRM University - AP Andhra Pradesh India Faculty of Philology RUDN University Moscow Russia Department of Electronics and Communication Engineering TKM College of Engineering Kollam India Curriculum Research and Development U-DNA Educational Foundation Anantapur Andhra Pradesh India

ISBN: (数字)9798350376234

ISBN: (纸本)9798350376241

This research investigates the attitudes and perceptions of engineering educators in Kerala, India, towards the implementation of Project-Based Learning (PjBL) within the framework of APJ Abdul Kalam Technological University (APJAKTU), Kerala. Despite the growing emphasis on experiential learning, only limited research studies focus on understanding the attitudes and perceptions of engineering faculty members towards PjBL. Against this backdrop, the present study aims to critically examine the readiness of engineering educators in adopting and identifying PjBL strategies for its effective integration into engineering curricula. The paper explores various dimensions of engineering educators’ engagement with PjBL, including faculty interest levels, satisfaction of implementation, perceived effectiveness, and career implications. The data were collected from engineering faculty members by distributing a comprehensive questionnaire titled Project-Based Learning in Engineering Education in Kerala (PLEEK), uniquely designed by the researchers. The research findings reveal that over 90% of the surveyed faculty members have shown keen interest in implementing PjBL, while the remaining respondents exhibited a neutral stance. This underscores a noteworthy receptivity to PjBL among engineering educators in Kerala. Suggestions from participants indicate that, if implemented correctly, PjBL would be highly effective, although time constraints pose a significant challenge. The results obtained are pivotal as they provide an explicit idea of the current status of the engineering education settings and the discrepancies between traditional theoretical instruction and project-based learning.

关键词： Engineering profession Time factors Engineering education

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ESLDL: An Integrated Deep Learning Model for Egyptian Sign Language Recognition 3

ESLDL: An Integrated Deep Learning Model for Egyptian Sign L...

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3rd Novel Intelligent and Leading Emerging sciences Conference, NILES 2021

作者： Ehssan Aly, Soha Ahmed Hassanin, Aya Bekhet, Saddam Helwan University Faculty of Computers And Artificial Intelligence Department of Computer Science Helwan Egypt South Valley University Faculty of Commerce Department of Quantitative Methods Qena Egypt

ISBN: (纸本)9781665421577

Sign languages is a critical requirement that helps deaf people to express their needs, feelings and emotions using a variety of hand gestures throughout their daily life. This language had evolved in parallel with spoken languages, however, it do not resemble its counterparts in the same way. Moreover, it is as complex as any other spoken language, as each sign language embodies hundreds of signs, that differs from the next by slight changes in hand shape, position, motion direction, face and body parts contributing to each sign. Unfortunately, sign languages are not globally standardized, where the language differs between countries and has its own vocabulary and varies although they might look similar. Furthermore, publicly available datasets are limited in quality and most of the available translation services are expensive, due to the required skilled human personnel. This paper proposes a deep learning approach for sign language detection that is finely tailored for the Egyptian sign language (special case of the generic sign language). The model is built to harnesses the power of convolutional and recurrent networks by integrating them together to better recognize the sign language spatio-temporal data-feed. In addition, the paper proposes the first Egyptian sign language dataset for emotion words and pronouns. The experimental results demonstrated the proposed approach promising results on the introduced dataset using combined CNN with RNN models. © 2021 IEEE.

关键词： Recurrent neural networks

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ESTIMATING THE FALSE DISCOVERY RISK OF (RANDOMIZED) CLINICAL TRIALS IN MEDICAL JOURNALS BASED ON PUBLISHED p-VALUES

arXiv

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arXiv 2023年

作者： Schimmack, Ulrich Bartoš, František Department of Psychology University of Toronto Mississauga Mississauga Canada Department of Psychological Methods University of Amsterdam Amsterdam Netherlands Institute of Computer Science Czech Academy of Sciences Prague Czech Republic

The influential claim that most published results are false raised concerns about the trustworthiness and integrity of science. Since then, there have been numerous attempts to examine the rate of false-positive results that have failed to settle this question empirically. Here we propose a new way to estimate the false positive risk and apply the method to the results of (randomized) clinical trials in top medical journals. Contrary to claims that most published results are false, we find that the traditional significance criterion of α = .05 produces a false positive risk of 13%. Adjusting α to .01 lowers the false positive risk to less than 5%. However, our method does provide clear evidence of publication bias that leads to inflated effect size estimates. These results provide a solid empirical foundation for evaluations of the trustworthiness of medical research. © 2023, CC BY.

关键词： Risk perception

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A Regularized Hypergraph Recommendation Algorithm with Attention Mechanism 7

A Regularized Hypergraph Recommendation Algorithm with Atten...

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7th IEEE International Conference on Cloud Computing and Intelligence Systems, CCIS 2021

作者： Zhu, Tingting Chen, Jianrui Wang, Zhihui He, Meixia The Key Laboratory of Modern Teaching Technology Ministry of Education Xi'an China Department of Computer Science Shaanxi Normal University Xi'an710199 China

ISBN: (纸本)9781665441490

Collaborative filtering is one of the most commonly used recommendation technologies in recommender systems. However, it has the problems of sparse score data and low recommendation accuracy. To address these problems, we propose a regularized hypergraph recommendation algorithm with attention mechanism. We can fully mine the high-order relationships in the hyperedges without loss of information. In addition, we apply users' attributes information to calculate the attraction of an item to the attributes, and then get the similarity between items. In order to calculate the similarity more accurately, the relations of items to attributes are divided into two cases: likes and dislikes. Moreover, according to the different attention of users to different items, we introduce the attention mechanism. Finally, we build and optimize the regularization function to obtain the predictive scores and recommendation lists. Experimental results on Movielens-100K and Movielens-1M demonstrate the effectiveness of our proposed algorithm. © 2021 IEEE.

关键词： Collaborative filtering

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Integrating AI-based adaptive learning into the flipped classroom model to enhance engagement and learning outcomes

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computers and Education: Artificial Intelligence 2025年 8卷

作者： Katona, Jozsef Gyonyoru, Klara Ida Katonane Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemet Hungary Department of Applied Quantitative Methods Faculty of Finance and Accountancy Budapest University of Economics and Business Budapest Hungary Department of Organizational Development and Communication Science Institute of Social Sciences University of Dunaujvaros Dunaujvaros Hungary

This study explores the integration of the AI-powered adaptive learning system within the flipped classroom model and discusses programming education. The increasing demand for the acquisition of programming skills in the digital era generates the development of innovative pedagogical approaches to help students overcome the difficulties in mastering programming concepts. The study investigates how AI-based adaptive feedback influences student engagement, motivation, and learning outcomes. This study was conducted for 13 weeks, with two groups of undergraduate students. In one of the groups, tshe traditional flipped classroom model was applied, while in the other group, AI-driven adaptive learning tools were introduced. In this research methodology, a mixed-methods approach was adopted, integrating quantitative analyses with qualitative data. These showed that the experimental group demonstrated significant improvements in learning results and motivation, thereby realiszing the value of real-time, personalized feedback provided through the AI system. The qualitative findings revealed that with the AI system, there was an increase in student autonomy;thus, there is increased responsibility among students to collaborate in in-class participation, which helps enhance a more dynamic and cooperative learning environment. On the whole, these findings reveal important implications of the integration of AI into flipped classrooms, while at the same time, they reveal how to make the modernization of programming education achieve a better overall experience in student learning. © 2025 The Authors

关键词： Contrastive Learning

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About Digital Twins, agents, and multiagent systems: a cross-fertilisation journey

arXiv

引用

arXiv 2022年

作者： Mariani, Stefano Picone, Marco Ricci, Alessandro Department of Sciences and Methods of Engineering University of Modena and Reggio Emilia Italy Department of Computer Science and Engineering University of Bologna Italy

Digital Twins (DTs) are rapidly emerging as a fundamental brick of engineering cyber-physical systems, but their notion is still mostly bound to specific business domains (e.g. manufacturing), goals (e.g. product design), or application domains (e.g. the Internet of Things). As such, their value as general purpose engineering abstractions is yet to be fully revealed. In this paper, we relate DTs with agents and multiagent systems, as the latter are arguably the most rich abstractions available for the engineering of complex socio-technical and cyber-physical systems, and the former could both fill in some gaps in agent-oriented engineering and benefit from an agent-oriented interpretation—in a cross-fertilisation journey. © 2022, CC BY.

关键词： Multi agent systems

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FairTP: A Prolonged Fairness Framework for Traffic Prediction 39

FairTP: A Prolonged Fairness Framework for Traffic Predictio...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Xia, Jiangnan Yang, Yu Shen, Jiaxing Wang, Senzhang Cao, Jiannong School of Computer Science and Engineering Central South University China Centre for Learning Teaching and Technology The Education University of Hong Kong Hong Kong School of Data Science Lingnan University Hong Kong The Department of Computing The Hong Kong Polytechnic University Hong Kong

ISBN: (纸本)157735897X

Traffic prediction is pivotal in intelligent transportation systems. Existing works focus mainly on improving overall accuracy, overlooking a crucial problem of whether prediction results will lead to biased decisions by transportation authorities. In practice, the uneven deployment of traffic sensors in different urban areas produces imbalanced data, making the traffic prediction model fail in some urban areas and leading to unfair regional decision-making that eventually severely affects equity and quality of residents’ life. Existing fairness machine learning models struggle to maintain fair traffic prediction over prolonged periods. Although these models might achieve fairness at certain time slots, this static fairness will break down as traffic conditions change. To fill this research gap, we investigate prolonged fair traffic prediction, introducing two novel fairness metrics, i.e., region-based static fairness and sensor-based dynamic fairness, tailored to fairness fluctuations over time and across areas. An innovative prolonged fairness traffic prediction framework, namely FairTP, is then proposed. FairTP achieves prolonged fairness by alternating between "sacrifice" and "benefit" the prediction accuracy of each traffic sensor or area, ensuring that the number of these two actions are balanced over time. Specifically, FairTP incorporates a state identification module to discriminate whether the traffic sensors or areas are in a "sacrifice" or "benefit" state, thereby enabling prolonged fairness-aware traffic predictions. Additionally, we devise a state-guided balanced sampling strategy to select training examples to further enhance prediction fairness by mitigating the performance disparities among areas with uneven sensor distribution over time. Extensive experiments in two real-world datasets show that FairTP significantly improves prediction fairness without causing significant accuracy degradation. Copyright © 2025, Association for the Advancement of Ar

关键词： Traffic control

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