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14th International Conference on Advanced computer information Technologies, ACIT 2024

作者： Melnyk, Bohdan Stakhiv, Petro Melnyk, Nataliya Franko, Yuriy Seniv, Bohdan Martsenyuk, Yevgeniya Ivan Franko National University of Lviv Department of Information Systems of Management Lviv Ukraine Lviv Polytechnic National University Department of Theoretical and General Electrical Engineering Lviv Ukraine Ternopil Volodymyr Hnatiuk National Pedagogical University Department of Computer Technologies Ternopil Ukraine Banking Business Department of Financial Technologies Ternopil Ukraine Ukrainian National University Department of Computer Science West Ternopil Ukraine

ISBN: (纸本)9798350350036

The article is devoted to the development of software for the implementation of the stochastic optimization method. The classical method of the directed cone and its modification are considered. Its shortcomings in the process of searching for the global minimum are pointed out. To improve the search, it is proposed to use algorithms with adaptation of optimization parameters. The architecture of software implementation of optimization algorithms of the directed cone method is proposed. Appropriate software was developed. It was tested on the example of optimization of the structured cable system of the telecommunications network. For this, a corresponding optimization problem is formulated. The results of its solution and application of optimization algorithms are analyzed. © 2024 IEEE.

关键词： Optimization algorithms

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Improving Graph Machine Learning Performance Through Feature Augmentation Based on Network Control Theory

Improving Graph Machine Learning Performance Through Feature...

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Mediterranean Conference on Control and Automation (MED)

作者： Anwar Said Obaid Ullah Ahmad Waseem Abbas Mudassir Shabbir Xenofon Koutsoukos Computer Science Department Vanderbilt University Nashville TN Electrical Engineering Department University of Texas at Dallas Richardson TX Systems Engineering Department University of Texas at Dallas Richardson TX Computer Science Department Information Technology University Lahore Pakistan

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

Network control theory (NCT) offers a robust analytical framework for understanding the influence of network topology on dynamic behaviors, enabling researchers to decipher how certain patterns of external control measures can steer system dynamics towards desired states. Distinguished from other structure-function methodologies, NCT's predictive capabilities can be coupled with deploying Graph Neural Networks (GNNs), which have demonstrated exceptional utility in various network-based learning tasks. However, the performance of G NN s heavily relies on the expressiveness of node features, and the lack of node features can greatly degrade their performance. Furthermore, many real-world systems may lack node-level information, posing a challenge for GNNs. To tackle this challenge, we introduce a novel approach, NCT-based Enhanced Feature Augmentation (NCT-EFA), that assimilates average controllability, along with other centrality indices, into the feature augmentation pipeline to enhance GNNs performance. Our evaluation of NCT-EFA, on six benchmark GNN models across two experimental setting-solely employing average controllability and in combination with additional centrality metrics-showcases an improved performance reaching as high as 11 %. Our results demonstrate that incorporating NCT into feature enrichment can substantively extend the applicability and heighten the performance of GNNs in scenarios where node-level information is unavailable.

关键词： Automation System dynamics Network topology Pipelines Machine learning Benchmark testing Controllability

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Generative AI for Secure and Privacy-Preserving Mobile Crowdsensing

arXiv

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arXiv 2024年

作者： Yang, Yaoqi Zhang, Bangning Guo, Daoxing Du, Hongyang Xiong, Zehui Niyato, Dusit Han, Zhu College of Communications Engineering Army Engineering University of PLA Nanjing210000 China School of Computer Science and Engineering NTU Singapore Singapore Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore Singapore Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States

Recently, generative AI has attracted much attention from both academic and industrial fields, which has shown its potential, especially in the data generation and synthesis aspects. Simultaneously, secure and privacy-preserving mobile crowdsensing (SPPMCS) has been widely applied in data collection/ acquirement due to an advantage on low deployment cost, flexible implementation, and high adaptability. Since generative AI can generate new synthetic data to replace the original data to be analyzed and processed, it can lower data attacks and privacy leakage risks for the original data. Therefore, integrating generative AI into SPPMCS is feasible and significant. Moreover, this paper investigates an integration of generative AI in SPPMCS, where we present potential research focuses, solutions, and case studies. Specifically, we firstly review the preliminaries for generative AI and SPPMCS, where their integration potential is presented. Then, we discuss research issues and solutions for generative AI-enabled SPPMCS, including security defense of malicious data injection, illegal authorization, malicious spectrum manipulation at the physical layer, and privacy protection on sensing data content, sensing terminals' identification and location. Next, we propose a framework for sensing data content protection with generative AI, and simulations results have clearly demonstrated the effectiveness of the proposed framework. Finally, we present major research directions for generative AI-enabled SPPMCS. © 2024, CC BY.

关键词： Privacy-preserving techniques

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GrAC: Graph-Based Anonymous Credentials from Identity Graphs on Blockchain

GrAC: Graph-Based Anonymous Credentials from Identity Graphs...

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IEEE International Conference on Blockchain (Blockchain)

作者： Wenyi Tang Shankha Shubhra Mukherjee Seongho Park Changhao Chenli Hyunok Oh Jihye Kim Taeho Jung Computer Science and Engineering University of Notre Dame Notre Dame IN USA Information Systems Hanyang University Seoul South Korea Computer Science Indiana Institute of Technology Fort Wayne IN USA Electrical Engineering Kookmin University Seoul South Korea

ISBN: (数字)9798350351590

ISBN: (纸本)9798350351606

With the growing need for privacy and self-sovereign identity, traditional identity management relying on centralized data registries not only represents single points of failure but also lacks transparency and control over users' identity information. With the built-in tamper-proofness and transparency, blockchain has been widely studied to accommodate the challenges in traditional identity management. Still, it usually comes with privacy concerns due to its public accessibility. Anonymous credentials take advantage of the recent progress in zero-knowledge proof, allowing the unlinkable presentation of only the necessary attributes for a service to guarantee anonymity. However, the existing anonymous credentials require a secondary issuer to verify and manage the anonymized credentials, which compromises the overall transparency and causes indirect management of the user's identity. In this paper, we propose GrAC, a blockchain-based identity management system based on a novel identity graph, which allows users and identity providers to securely store and manage identity information on the blockchain without intermediate entities. GrAC also includes an anonymous authentication protocol suite based on zero-knowledge proof, allowing users to generate one-time anonymous credentials that selectively reveal minimal information to the service provider for authentication. The analysis and evaluations show that Gr Achas a reasonable overhead and provides adequate anonymity protection while removing the need for intermediate issuers.

关键词： Privacy Data privacy Protocols Authentication Blockchains Protection Identity management systems

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Discrepancies of remote techno-tolerance due to COVID-19 pandemic within Arab middle-east countries

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Journal of Umm Al-Qura University for engineering and Architecture 2023年第3期14卷 151-165页

作者： Abu-Hashem, Muhannad A. Gutub, Adnan Salem, Osama Shambour, Mohd Khaled Shambour, Qusai Shehab, Mohammad Izzat, Ahmad Alrawashdeh, Mufda J. Department of Geomatics Architecture and Planning Faculty King Abdulaziz University Jeddah Saudi Arabia Computer Engineering Department College of Computer and Information Systems Umm Al-Qura University Makkah Saudi Arabia Educational Technology and E-Learning Department College of Education Umm Al-Qura University Makkah Saudi Arabia The Custodian of the Two Holy Mosques Institute for Hajj and Umrah Research Umm Al-Qura University Makkah Saudi Arabia Software Engineering Department Faculty of IT Al-Ahliyya Amman University Amman Jordan Artificial Intelligence & Software Engineering Departments Faculty of Information Technology Aqaba University of Technology Aqaba Jordan Faculty of Engineering and Information Technology Israa University Gaza Palestine Department of Mathematics College of Sciences and Arts Qassim University Al-Ras Saudi Arabia

The coronavirus disease (COVID-19) changed the world’s lifestyle switching many techno-services to be provided remotely instead of direct usual physical interactions between people. This study focused on university students’ perceptions of this virtual technology-engineering change as discrepancies to be analyzed. The research surveyed 777 different students from four Arab middle-east neighboring countries, with related demographics and specifications, expressing full remarkable experiences of e-technology in virtual as well as traditional performances helping reveal overall tolerance possibilities. The study adopted examination technology via ANOVA to test discrepancies within students' perceptions for overall multi-factors deep analysis classification. The exploration highlighted an interesting range of pros and cons remarks including feminism and economic effect as well as other cultural and engineering interaction issues, raising signals to essentially consider and mutually benefit from adequate future generation e-techno adaptation within the region. © The Author(s) 2023.

关键词： ANOVA COVID-19 E-techno Students’ perceptions Traditional and virtual classes

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Trends, Opportunities, and Challenges in Detecting Depressive Disorders Through Mobile Devices: A Review 2

Trends, Opportunities, and Challenges in Detecting Depressiv...

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2nd International Conference on computer System, information Technology, and electrical engineering, COSITE 2023

作者： Elwirehardja, Gregorius Natanael Isnan, Mahmud Perbangsa, Anzaludin Samsinga Muchtar, Kahlil Pardamean, Bens Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Mahmud Isnan Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Information System Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh23111 Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798350343069

Depressive Disorders (DD) is one of the most prevalent mental disorders in the world that may lead to suicide cases. To prevent the latter, ubiquitous early detection systems may be effective. Recent studies have since researched the development of such systems by exploiting several forms of data, including video, audio, Ecological Momentary Assessments (EMA), and passive sensing data using sensors embedded in mobile devices. To summarize the trends, opportunities, and existing challenges in this field, this study reviewed 15 papers to answer four research questions. EMA was the most popular data to be used in this task, but other approaches, such as using video, audio, and typing behaviors, may be considered due to the subjectivity of EMA. These data were typically recorded using smartphones and analyzed using Machine Learning (ML). However, most of the developed systems had yet to be implemented. Overall, it was concluded that further studies may need to explore usages of more objective data in multimodal approaches as well as consider using Mobile Cloud Computing (MCC) to deploy these systems to provide more effective and efficient diagnoses. Future studies must also take into account the existing challenges of the data and infrastructures, such as the weaknesses of several data types, limitations of mobile devices, as well as the challenges of diagnosis approaches. © 2023 IEEE.

关键词： Machine learning

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Infrastructure-dependent ramp-metering control for METANET-s

Infrastructure-dependent ramp-metering control for METANET-s

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IEEE Conference on Decision and Control

作者： Ayda Kamalifar Carlo Cenedese Michele Cucuzzella Antonella Ferrara Department of Electrical Computer Science and Biomedical Engineering University of Pavia Pavia Italy Department of Information Technology and Electrical Engineering ETH Zürich Zürich Switzerland Center for Systems and Control ENTEG Faculty of Science and Engineering (FSE) University of Groningen (UG) Nijenborgh 4 Groningen the Netherlands

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we propose a novel infrastructure-dependent ramp-metering control for the recently proposed METANET with service station (METANET-s) model, i.e., a second-order macroscopic traffic model that, compared to the classical METANET, incorporates the dynamics of service stations on highways. We study the effect of a ramp-metering control scheme on a highway stretch with a service station and show that it is capable of actively regulate internal traffic demand attempting to exit the service station via its on-ramp, on top of contributing to decrease the traffic congestion on the mainstream. In fact, the proposed control scheme effectively prevents the backlog of vehicles attempting to merge back onto the mainstream. This dynamic control mechanism is further endowed by a route guidance control strategy increasing the share of vehicles stopping at the service station during main-stream congestion periods, e.g. via incentives. The combined effect of our control schemes allows to take full advantage of the presence of service stations, reducing the overall traffic congestion. Simulation results demonstrate the effectiveness of the proposed control strategies.

关键词： Simulation Merging Numerical models Vehicle dynamics Traffic congestion

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Analyzing Multi-Hop WSN Connectivity using Poisson Point Processes: A Layered Model for Quality of Service Assurance

Analyzing Multi-Hop WSN Connectivity using Poisson Point Pro...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Arash Sahbafard Fjolla Ademaj-Berisha Davide Dardari Andreas Springer Martin Voigt Vejling Hans-Peter Bernhard Silicon Austria Labs GmbH Linz Johannes Kepler University Linz Institute for Communications Engineering and RF-Systems Linz Austria Department of Electrical Electronic and Information Engineering University of Bologna Cesena Italy Departments of Mathematical Sciences and of Electronic Systems Aalborg University Aalborg Øst Denmark

ISBN: (数字)9798350362244

ISBN: (纸本)9798350362251

Wireless Sensor Networks (WSNs) play a pivotal role in diverse domains such as environmental sensing, industrial monitoring, and entertainment. This paper focuses on modeling the connectivity of the link considering the quality of service (QoS) criterion. This is a baseline for considering the probability density function (PDF) of the node’s distance from the base station (BS) to form a multi-hop wireless sensor networks (WSNs) structure. We delve into modeling the connectivity behavior in multi-hop networks, addressing scenarios involving non-homogeneous Poison Point Process (NHPPP) and homogeneous Poison Point Process (HPPP). Furthermore, we introduce closed-form expressions with reduced computational complexity. This contribution establishes a comprehensive framework for understanding and enhancing the performance of multi-hop wireless sensor networks.

关键词： Wireless communication Wireless sensor networks Toxicology Closed-form solutions Computational modeling Spread spectrum communication Quality of service Probability density function Sensors Computational complexity

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Key Success Factor of Marketing Intelligence in Higher Education: Systematic Literature Review

Key Success Factor of Marketing Intelligence in Higher Educa...

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International Conference on information Management and Technology (ICIMTech)

作者： Fathy Radhia Albert Budi Christian Edi Purnomo Putra Sugiarto Hartono Henricus Bambang Triantono Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia College of Electrical Engineering and Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan

Marketing Intelligence (MI) is the process of collecting and applying information to formulate effective marketing strategies. Currently, the information on MI at XYZ University still does not fully describe the user's needs and it can be improved so that its use can be successfully used by end-users. The research question is what key success factors are needed to build marketing intelligence in higher education. The objective of this study is to ascertain the critical success factors of marketing intelligence needed by universities. This study uses a qualitative research method, namely SLR conducting a Systematic Literature Review (SLR) that involves a comprehensive analysis of marketing intelligence. This research produces several factors that determine the success of marketing intelligence, consisting of Technology; Strategic, Tactical, Operational; Small and Medium Enterprise (SM E)'s Performance; Predictors and Consequences; Customer Satisfaction and Loyalty; Environment; Concept, Overview; Sales Forces; External Intelligence; Internal information; Talent Management; Individual Sources; information Sources; Personal Factors; and Organizational. The impact of this research is that universities that aim to develop and implement marketing intelligence can pay attention to technology, personal factors, and strategic/tactical/operational variables which are the 3 critical variables for building marketing intelligence.

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Implementation of Gamified Programming Learning Assistant System

Implementation of Gamified Programming Learning Assistant Sy...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Htoo Htoo Sandi Kyaw Keiichi Kaneko Nobuo Funabiki Wen-Chung Kao Department of Computer and Information Science Tokyo University of Agriculture and Technology Tokyo Japan Department of Information and Communication Systems Okayama University Okayama Japan Department of Electrical Engineering National Taiwan Normal University Taipei Taiwan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Despite the rapid growth of the ICT sector, there is a gap between it and STEM education, resulting in high dropout rates in computer science and engineering programs. This has led to many vacancies in the ICT job market. A major challenge is that traditional teaching methods fail to engage students in difficult and abstract STEM subjects like programming. To overcome this, innovative technology-enhanced learning solutions are needed. In the past, we created a Programming Learning Assistant System (PLAS) to help novice students learn programming. PLAS provides various types of exercises to develop code reading and writing skills at different levels. In this paper, we implement the gamification into PLAS to enhance students' understanding of programming concepts, boost their confidence, spark their interest in STEM fields, and increase engagement in the course through interactive and stimulating scenarios.

关键词： computer languages Codes Education Games Writing Problem-solving Sparks Programming profession Consumer electronics STEM

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