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7th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2025

作者： Hossain, Zakir Hossain, Iffat Sania Kabir, Md Farhad Rahman, Ashequr Gharami, Arun Kumar Sumi, Sayeda Sufia Ahamed, Asif College of Engineering and Computer Science California State University NorthridgeCA United States Martin V. Smith School of Business & Economics California State University Channel Island CamarilloCA United States Marshall School of Business University of Southern California Los Angeles United States College of Business Westcliff University IrvineCA United States Lamar University Industrial and Systems Engineering BeaumontTX United States College of Engineering and Technology Westcliff University IrvineCA United States

ISBN: (纸本)9798331507022

Artificial intelligence (AI) has recently witnessed unprecedented levels of growth in its use for decision-making processes. This trend has extended to all sectors of the global economy, promoting innovation and the need to automate business functions. However, the black-box nature of many AI systems has raised concerns relating to trust, transparency, and accountability. This paper investigates in detail the potential of Explainable AI (XAI) in addressing these legitimate concerns that come with AI integration. Through a systematic review of existing XAI techniques and their application in business analytics, we show that the shift toward the use of explainable models not only enhances decision-making but also addresses the trust issue that restrictive the growth of AI in the business world. The literature further addresses the moral issues regarding the decision to explain one's AI model, how firms should modify their decision-making processes to incorporate XAI and the related consequences of such a change. As such, organizations are in a position to reap the full benefits of AI by aligning AI models with the rationale and expectation of human beings without compromising accountability, fairness and transparency. © 2025 IEEE.

关键词： Decision making

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Statistical Characterization of RIS-Assisted UAV Communications in Terrestrial and Non-Terrestrial Networks Under Channel Aging

Statistical Characterization of RIS-Assisted UAV Communicati...

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IEEE International Conference on Communications (ICC)

作者： Thanh Luan Nguyen Georges Kaddoum Tri Nhu Do Zygmunt J. Haas Department of Electrical Engineering École de Technologie Supérieure (ETS) Montréal QC Canada Artificial Intelligence & Cyber Systems Research Center Lebanese American University Electrical Engineering Department Polytechnique Montréal Montréal QC Canada Department of Computer Science University of Texas at Dallas TX USA School of Electrical and Computer Engineering Cornell University Ithaca NY USA

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

This paper studies the statistical characterization of ground-to-air (G2A) and reconfigurable intelligent surface (RIS)-assisted air-to-ground (A2G) communications with unmanned aerial vehicles (UAVs) in terrestrial and non-terrestrial networks under the impact of channel aging. We first model the G2A and A2G signal-to-noise ratios (SNRs) as non-central complex Gaussian quadratic random variables (RVs) and derive their exact probability density functions, offering a unique characterization for the A2G SNR as the product of two scaled non-central chi-square RVs. Moreover, we also find that, for a large number of RIS elements, the RIS-assisted A2G channel can be characterized as a single Rician fading channel. Our results reveal the presence of channel hardening in A2G communication under low UAV speeds, where we derive the maximum target spectral efficiency (SE) for a system to maintain a consistent required outage level. Meanwhile, high UAV speeds, exceeding 50 m/s, lead to a significant performance degradation, which cannot be mitigated by increasing the number of RIS elements.

关键词： Spectral efficiency Rician channels Reconfigurable intelligent surfaces Aging Probability density function Autonomous aerial vehicles Air to ground communication

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Improving Information Freshness in Edge-Assisted Smart Grids: An AoI-Aware Routing Strategy for Neighborhood Area Networks

Improving Information Freshness in Edge-Assisted Smart Grids...

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IEEE International Conference on industrial Informatics (INDIN)

作者： Hossam Farag Mostafa Kotb Čedomir Stefanović Mikael Gidlund Department of Electronic Systems Aalborg University Denmark Department of Electrical Engineering Aswan University Egypt Department of Informatics Universität Hamburg Germany Mathematics Department Aswan University Egypt Department of Computer and Electrical Engineering Mid Sweden University Sweden

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

The integration of edge controllers into smart grid infrastructures facilitates advanced functionalities and high re-sponsiveness, thereby bolstering the overall efficiency of the energy grid. The freshness of the sensing information received at the edge controller, captured by the Age of Information (AoI) metric, is vital to maintain system stability, where outdated information may lead to incorrect responses to grid conditions, potentially causing inefficiencies or system disruptions. However, the timeliness of the transmitted updates is mainly compromised by the delay and congestion within the routing links in the Neighborhood Area Network (NAN). In this work, we develop an intelligent routing strategy to improve the AoI of the Routing Protocol for Low-power and lossy networks (RPL), which is the common routing protocol for smart grids. Our proposed method is based on an AoI-aware parent selection mechanism, by which a node becomes attached to the parent with the highest probability of delivering a packet within a predefined AoI threshold. The prediction is made based on a supervised machine learning model, trained using the collection of heterogeneous routing metrics. The performance of the proposed method is evaluated via extensive discrete-event simulations and the results show its potency to improve the peak AoI and the AoI violation probability compared to the standard RPL.

关键词： Measurement Computational modeling Predictive models Power system stability Routing Routing protocols Stability analysis Smart grids Sensors Standards

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Experimental implementation of chaos-based video encryption using visible light communication technology

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Applied Optics 2025年第9期64卷 C101-C118页

作者： Fotso, Sorel Bagio Nono Mbé, Jimmi Hervé Talla Takotue, Jean Ernest Takougang, Armand Cyrille Nzeukou Ndjiongue, Alain Richard Research Unit of Condensed Matter Electronics and Signal Processing Department of Physics University of Dschang P.O. Box 67 Dschang Cameroon Research Unit of Automation and Applied Computer Department of Electrical Engineering IUT-FV Bandjoun University of Dschang P.O. Box: 134 Bandjoun Cameroon Laboratory of Industrial Systems and Environmental Engineering Fotso Victor University Institute of Technology University of Dschang P.O. Box 134 Bandjoun Cameroon School of Electrical and Information Engineering Faculty of Engineering and the Built Environment University of the Witwatersrand Johannesburg South Africa

Simulations are commonly used to develop and evaluate video encryption algorithms. Although these approaches are useful for demonstrating theoretical feasibility and algorithm performance, they neglect practical challenges and real-world communication conditions. This oversight creates a critical gap in evaluating their effectiveness and security in practical applications. In this paper, we describe a novel, to the best of our knowledge, video encryption scheme that employs a modified chaotic Colpitts oscillator, a customized Josephus problem, and ribonucleic acid (RNA) operations, and is implemented in visible light communication (VLC) environment. The modified Colpitts oscillator reveals significant phenomena, the most prominent for this study being chaos. The encryption scheme involves block scrambling and pixel-level permutation employing a customized Josephus problem and a column and row shifting technique. Diffusion is then achieved through a custom Josephus problem-oriented RNA operation combined with basic RNA operations and cipher block chaining (CBC). Based on the results, we found that the customized Josephus problem-based permutation performed more efficiently than traditional methods, whereas the column and row shifting permutation was more robust. By eliminating key sequence coding and item-to-item operations, the proposed RNA operation reduces computational overhead. This video encryption scheme is proven to be effective and resilient at securing video data transmitted over the VLC channel, and it constitutes a significant advancement in areas such as surveillance, medical imaging, and military communication requiring robust secured video data. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Medical imaging

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TSO-DSO Coordinated Operational Planning in the Presence of Shared Resources $i,m,o,t$

TSO-DSO Coordinated Operational Planning in the Presence of ...

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Power Tech Conference

作者： Micael Simoes Andre G. Madureira Filipe Soares Joao Pecas Lopes Center for Power and Energy Systems INESC TEC Porto Portugal Intelligent Clean Energy Systems LIST Belvaux Luxembourg Department of Electrical and Computer Engineering Faculty of Engineering of University of Porto Porto Portugal

Electric power systems are currently experiencing a profound change, as increasing amounts of Renewable Energy Sources (RESs) displace conventional forms of generation. This development has gone hand-in-hand with an increasing share of distributed power generation being connected directly to the Distribution Network (DN), and the widespread of other types of Distributed Energy Resources (DERs), such as Energy Storage Sytems (ESSs), Electric Vehicles (EVs), and active (flexible) consumers. As these trends are expected to continue, this will require a profound revision of the way Transmission System Operators (TSOs) and Distribution System Operators (DSOs) interact with each other to fully benefit from the growing flexibility that is available at the DN level. In this work we propose a new tool for the coordinated operational planning of transmission and distribution systems, considering the existence of shared resources that can be simultaneously used by TSO and DSOs for the optimal operation of their networks. The tool uses advanced distributed optimization techniques, namely the Alternating Direction Method of Multipliers (ADMM) in order to maintain data privacy of the several agents involved in the optimization problem, and keep the tractability of the problem. The proposed tool is applied to modified IEEE test systems, and the results obtained highlight the benefits of the proposed coordination mechanism to solve problems occurring simultaneously at the transmission and DN-levels.

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Femtosecond Filament Coupled with Structured Light for Free Space Optical Communication

Femtosecond Filament Coupled with Structured Light for Free ...

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CLEO: Science and Innovations, S and I 2022

作者： Reza, Saad Bin Ali Wang, Tianhong Buldt, Finn Bassène, Pascal N'Gom, Moussa Electrical Computer and Systems Engineering Department Rensselaer Polytechnic Institute TroyNY United States Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute TroyNY United States

We created a 4-bit communication channel for free-space optical communication (FSO) through a segmented space division multiplexing method using structured light coupled with a femtosecond-laser induced filament. ... 详细信息

ISBN: (纸本)9781557528209

关键词： Optical communication

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Comparative Study between KNN and CNN's Techniques for Kidney Stone Detection

Comparative Study between KNN and CNN's Techniques for Kidne...

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Smart Computing and Application (ICSCA), International Conference on

作者： Fahdah M. Al-Tbenawey Shoayee Alotaibi Marwa Salem Shamaila Mir Zahida Mir Department of Computer Science and Information Computer Science and Engineering College University of Ha'il Hail Saudi Arabia Department of Electrical Communication and Electronics Systems Engineering Faculty of Engineering Modern Science and Arts University (MSA) Cairo Egypt

This paper aims to determine the better technique for kidney stone detection between K-Nearest Neighbor (KNN) and Convolutional Neural Networks (CNNs). As well known, the presence of kidney stones is an important topic that deserves discussion regarding expected medical outcomes. Most of the detection measures comprise CT scans, ultrasounds, and abdominal X-rays. These measures have varying effectiveness levels, hence used in the detection to prepare patients for specific treatment options. Patients' treatment options comprise percutaneous nephrolithotomy (PCNL), extracorporeal shockwave lithotripsy (ESWL), and ureteroscopy. The different detection techniques carried out for the patients are essential to test whether the patient has small or large kidney stones. One essential technique is using conventional neural networks (CNNs) technology. In this paper kidney, stone detection will be carried out using both of K-Nearest Neighbor (KNN) and CNN's techniques. A comparison between both techniques will be carried out to figure out the better. All of the simulations are carried out using MATLAB.

关键词： Support vector machines Image segmentation Ultrasonic imaging Ultrasonic variables measurement Particle separators Neural networks X-rays

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Development of an Appearance-based Eye Tracking System with Convolutional Neural Network Integrated in a Learning Management Application

Development of an Appearance-based Eye Tracking System with ...

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International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)

作者： Jason Samuel Ching Alec Franz Cresencio Issey Gabriel Dee Florenz Howard Domingo Melvin Cabatuan Alma Maria Jennifer Gutierrez Department of Electronics and Computer Engineering De La Salle University Manila Philippines Goko Department of Electronics and Computer Engineering De La Salle University Manila Philippines Department of Industrial and Systems Engineering De La Salle University Manila Philippines

ISBN: (数字)9798350381177

ISBN: (纸本)9798350381184

This study introduces an appearance-based eye tracking system, integrated into a Learning Management System (LMS) with IoT implementation, for monitoring students during online quizzes. Utilizing DenseNet121 as the base Convolutional Neural Network (CNN) model, the system employs a 13-point calibration process to refine gaze predictions according to user position. The LMS is designed to record the user's face images and generate gaze and fixation maps during quizzes, which professors can review after the quiz. The output also includes a collated view of students' gaze data. Extensive testing, including face detection model comparisons, led to the selection of DenseNet121 for the model, which demonstrated high accuracy with an average Euclidean distance of 21.86 mm and an angular error of 2.50°. In the ideal setup, the system achieved a notable average Euclidean distance of 10.67 mm and a gaze angle error of 1.22°. The Multi-Layer Perceptron (MLP) calibration model further enhanced accuracy, achieving as low as 5.52 mm in average Euclidean distance. Controlled experiments with 33 participants indicated robust performance, particularly under direct lighting and without eyeglasses, with an average angular error of 4°, surpassing the targeted 5° error rate. The system's user interface likewise received positive feedback, reflected in the System Usability Scale (SUS) scores of 78.86 (Good) and 89.58 (Excellent) from the students and professors, respectively.

关键词： Accuracy Error analysis Gaze tracking Euclidean distance Predictive models User interfaces Calibration

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Enhancing Wireless Networks with Attention Mechanisms: Insights from Mobile Crowdsensing

arXiv

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arXiv 2024年

作者： Yang, Yaoqi Du, Hongyang Xiong, Zehui Niyato, Dusit Jamalipour, Abbas Han, Zhu College of Communications Engineering Army Engineering University of PLA Nanjing210000 China College of Computing and Data Science NTU Singapore Singapore Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore Singapore School of Electrical and Computer Engineering University of Sydney SydneyNSW2006 Australia Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States

The increasing demand for sensing, collecting, transmitting, and processing vast amounts of data poses significant challenges for resource-constrained mobile users, thereby impacting the performance of wireless networks. In this regard, from a case of mobile crowdsensing (MCS), we aim at leveraging attention mechanisms in machine learning approaches to provide solutions for building an effective, timely, and secure MCS. Specifically, we first evaluate potential combinations of attention mechanisms and MCS by introducing their preliminaries. Then, we present several emerging scenarios about how to integrate attention into MCS, including task allocation, incentive design, terminal recruitment, privacy preservation, data collection, and data transmission. Subsequently, we propose an attention-based framework to solve network optimization problems with multiple performance indicators in large-scale MCS. The designed case study have evaluated the effectiveness of the proposed framework. Finally, we outline important research directions for advancing attention-enabled MCS. © 2024, CC BY.

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Hybrid Autonomous Underwater Glider (HAUG) Obstacle Detection and Avoidance

Hybrid Autonomous Underwater Glider (HAUG) Obstacle Detectio...

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11th IEEE International Conference on System engineering and Technology, ICSET 2021

作者： Putra, A. A. Gde Jenana Trilaksono, Bambang Riyanto Hidayat, Egi Muhammad Idris School of Electrical Engineering and Informatics Institut Teknologi Bandung Control and Computer Systems Research Group Bandung Indonesia

ISBN: (纸本)9781665437660

Hybrid Autonomous Underwater Glider (HAUG) is a vehicle used for underwater missions such as monitoring and finding new underwater resources. HAUG has good endurance and maneuverability compared to conventional Autonomous Underwater Vehicle (AUV) and Autonomous Underwater Glider (AUG). It is because HAUG has two operational modes. They are AUV and AUG's operational mode. When HAUG is in some missions, it may be faced with an obstacle that can be a threat to the HUG's safety. Therefore, HAUG should have the ability to detect and avoid obstacles. Gemini 720 im Imaging Forward Looking Sonar (FLS) is used for obstacle detection in this work. The main issue of underwater obstacle detection is noisy data received by sonar. Therefore, by designing an obstacle detection, it will overcome those issues. Frost filter and local histogram entropy are used in the sonar data processing. The processed sonar data are provided in the local sonar frame then will be used by obstacle avoidance systems. BK-product fuzzy and reactive algorithms are used for obstacle avoidance. In this paper, we added some procedures to those obstacle avoidance algorithms to handle the huge or non-complex u-shaped obstacle. Both of the obstacle detection and avoidance simulations are in ROS (Robot Operating System). The obstacle detection simulation shows that the different sizes of obstacles can be detected with average errors of approximately 0.335 meters. The obstacle avoidance simulations are in AUV's mode with no ocean current applied. The obstacle avoidance simulated in this work is with two cases. Using simulated lidar as a sensor's output and using sonar's plugin provided by Gazebo. The obstacle avoidance using simulated lidar shows that the error's value is approximately 10.12 meters, 103.62 meters, and 354.4 meters respectively. The obstacle avoidance simulation with sonar's plugin shows that the error's value is 6.55 meters. © 2021 IEEE.

关键词： Meters Laser radar Simulation Operating systems Sonar Robot sensing systems systems engineering and theory

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