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19th International Conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Omer, Muhammad Ali, Sardar Jaffar Raza, Syed M. Le, Duc-Tai Choo, Hyunseung Dept. of Computer Science and Engineering Sungkyunkwan University Suwon Korea Republic of Dept. of AI Systems Engineering Sungkyunkwan University Suwon Korea Republic of James Watt School of Engineering University of Glasgow Glasgow United Kingdom Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9798331507817

Air pollution remains a critical issue, adversely affecting public health and the environment. In this study, we utilize the Air Quality index dataset from Kaggle to analyze temporal and seasonal variations of key pollutants, specifically Carbon Monoxide (CO), Nitrogen Oxides (NOx), and Benzene (C6H6 ). Building upon this analysis, we predict Absolute Humidity (AH), a vital meteorological factor influencing pollutant dispersion, using Machine Learning (ML) and Deep Learning (DL) techniques. Three ML techniques, Linear Regression (LR), Random Forest (RF), and Support Vector Regression (SVR), and three DL techniques, Artificial Neural Network (ANN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM), are employed for predicting AH. The results indicate that while the RF model achieved the lowest Mean Absolute Error (MAE) among ML methods (0.02), the CNN model, despite having an MAE of 0.04, demonstrated statistical superiority through paired t-tests and Wilcoxon signed-rank tests (p © 2025 IEEE.

关键词： Convolutional neural networks

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Benchmark Study on YOLOv8 Variants in Localized Multiclass Fault Detection in PCBs 6

Benchmark Study on YOLOv8 Variants in Localized Multiclass F...

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6th International Conference on electrical engineering and Information and Communication Technology, ICEEICT 2024

作者： Najib, Taeef Muntasir, Fahim Wasi, Wasif Al Wazed Sidetrek Dhaka Bangladesh Brac University Dept. of Computer Science and Engineering Dhaka Bangladesh Rajshahi University of Engineering and Technology Dept. of Electrical and Electronic Engineering Rajshahi Bangladesh

ISBN: (纸本)9798350385779

Detecting surface faults on PCBs is critical for ensuring device dependability and performance. Manual PCB inspection methods like X-ray imaging struggle to ensure quality control due to limitations in speed and defect characterization. However, advanced automated technologies, such as object detection models like YOLOv8, have emerged as a more efficient solution. This study focuses on evaluating the performance of different YOLOv8 variants in identifying and classifying various defects on PCBs. A benchmark of how each modification of the model performs detection and the factors behind were investigated here. It was determined that, YOLOv8 is sensitive to the amount of data it is being trained on, as the larger models tend to overlearn on smaller datasets. YOLOv8-m had the best performance, 97.1% precision, concerning the time taken and epoch count, over others. Large YOLOv8 variants, such as YOLOv8x, are also computationally expensive. The models were trained for 200 epochs with a patience value set at 50. Both increasing the number of data points and the resources will improve the performance and facilitate the overall training procedures. A significant gap in automated electronics production is addressed by this study: precise PCB fault localization for higher reliability of the product. © 2024 IEEE.

关键词： Fault detection

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Analytical Approach Towards Radiological Image-based Fracture Assessment Using Artificial Intelligence 1

Analytical Approach Towards Radiological Image-based Fractur...

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1st International Conference on Computing, sciences and Communications, ICCSC 2024

作者： Sylvia, Takhellambam Dubey, Sanjay Kumar Thongam, Khelchandra Amity University Computer Science & Engineering Dept. Uttar Pradesh Noida India National Institute of Technology Manipur Computer Science & Engineering Dept. Imphal India

ISBN: (纸本)9798350353648

The utilization of Artificial Intelligence (AI) techniques has been prevalent in various applications and the gradual increase in implementation towards healthcare sectors has scaled up. computer aided diagnosis has emerged as a major research area directed toward efficient use of resources. Fracture of bone has been a popular health problem associated with risk for mortality. Fractures are frequent in the long bones or the weight-bearing bones. AI techniques to accurately detect and classify fractures are still a challenging task beyond the conventional methods. Our objective is to assess the effectiveness of multiple algorithms in identifying and categorizing ankle fractures using radiological images. This review paper focuses on several available approaches of Deep-Learning (DL) and Machine-Learning (ML) regarding Ankle Fracture Classification and Identification based on Radiological Images for Medical Applications. The goal is to assist physicians and orthopaedics with simple and realistic decision support systems. In addition to a comprehensive analysis of the research, this study looked at several real-world examples of AI applications in the healthcare industry. Consequently, it is critical to have a fundamental grasp of these ML and DL algorithms to be ready for upcoming advancements in AI. We have reviewed and classified scientific conference and journal articles used for various AI techniques and offer future utility as a comparative analysis for further research in healthcare sectors. © 2024 IEEE.

关键词： Deep learning

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On the Application of Inexact Computation for Low Power SHA-256

On the Application of Inexact Computation for Low Power SHA-...

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2023 Workshop on Electronics Communication engineering, WECE 2023

作者： Ismail, Ahmed Shaaban Shalaby, Ahmed Abu-Elyazeed, Mohamed Fathy Electronics and Electrical Communications Dept Faculty of Engineering Cairo University Cairo Egypt Computer Science Dept. Faculty of Computer and Artificial Intelligence Benha University Benha Egypt

ISBN: (纸本)9781510672574

The adoption of IoT has raised concerns about security as life-threatening attacks become more common. To address this, ultra-lightweight secure SoCs become a demand to ensure trusted operation in the presence of untrusted IPs while meeting power and area constraints. Integrity, one of the main components of security, is the prevention of protected data modification without detection. Hash functions are used to ensure data integrity in secure systems. In this paper, we propose a low-power implementation of a hash function by using approximate adders in SHA-256 implementation. First, approximate adders’ designs were investigated, where we tested the output uniqueness of each of them, as the output uniqueness of an adder improves the properties of hash results. Then, the chosen adders are utilized for hash implementation. Next, the Avalanche test is applied to evaluate the properties of the proposed hash functions. Synthesis and simulation results show that using an approximate adder reduces the power consumed in the combinational part by up to 66% while the avalanche test results are reduced gradually from 50% to 25%. © 2024 SPIE. All rights reserved.

关键词： Adders

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Encoding Cyclic Redundancy Checked Sequences 5

Encoding Cyclic Redundancy Checked Sequences

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5th IEEE Middle East and North Africa COMMunications Conference, MENACOMM 2025

作者： Abdel-Ghaffar, Khaled A. S. University of California Dept. Electrical and Computer Engineering DavisCA95616 United States

ISBN: (纸本)9798331519957

The undetected error probability of cyclic redundancy checks (CRC) combined with an error-correcting code in a concatenated coding scheme is considered. It is shown that this probability depends very much on the encoding of the cyclic redundancy checked sequences into codewords in the error-correcting code. Furthermore, it is proved that the average undetected error probability of the concatenated code over all linear encoders of the error-correcting code is about 1/2 of that of the error-correcting code, where is the degree of the CRC polynomial. In particular, for any CRC polynomial of degree , there exists an encoding function of the error-correcting code such that the undetected error probability of the concatenated scheme is at most 1/2 of that of the error-correcting code. © 2025 IEEE.

关键词： Concatenated codes

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Observation-Transformed Distributed Detection in Sensor Networks 59

Observation-Transformed Distributed Detection in Sensor Netw...

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59th Annual Conference on Information sciences and Systems, CISS 2025

作者： Cao, Lei Viswanathan, Ramanarayanan University of Mississippi Dept. of Electrical and Computer Engineering OxfordMS38677 United States

ISBN: (纸本)9798331513269

Distributed detection (DD) plays a crucial role in sensor networks, where sensors gather data from a region of interest and report their observations to a fusion center (FC). The FC then makes a decision regarding a specific task, such as determining the presence or absence of a target. Given the constraints imposed by the transmission power, bandwidth, and noise impact in both sensing and data reporting channels, what should be reported from the sensors significantly affects the final detection accuracy. Existing methods include observation-untransformed DD (UDD), codewords-based DD (CDD), and quantized-but-uncoded DD (QDD). In this paper, we attempt to find the optimal sensor decision rule, i.e., the best transform for the observed data to be reported, by formulating the task as a functional optimization problem. To bypass the difficulty of theoretically solving the problem, we present two methods: an approximation function and a numerical solution for the Gaussian noise case. Our simulation results demonstrate that a variation of the hyperbolic tangent function can be an effective approximation of the optimal transform. This work could lead to further studies on the optimal design for distributed detection. © 2025 IEEE.

关键词： Hyperbolic functions

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Challenges of Integrating Blockchain Technology into Educational Institutions

Challenges of Integrating Blockchain Technology into Educati...

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2024 International Symposium on Networks, computers and Communications, ISNCC 2024

作者： Ali, Abbas Hussein Yavanoǧlu, Uraz Graduate School of Informatics Gazi University Dept. Of Computer Science Ankara Turkey Gazi University Faculty of Engineering Dept. of Computer Engineering Ankara Turkey

ISBN: (纸本)9798350364910

The latest advancements in blockchain technology have significantly influenced several sectors, such as banking, healthcare, and supply chain networks. Because of its distinct attributes, like decentralization, trustworthiness, and security, this technology has recently been employed in the field of education. While the blockchain is bright, several problems, such as legal, immutability, and scalability questions, continue to hinder its adoption in education. In this paper, we look at educational application system in terms of blockchain-based solutions that have been created for educational purposes, as well as the potential challenges of blockchain technology in the field of education. © 2024 IEEE.

关键词： Blockchain technology educational application

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DURATION-BASED INVESTIGATION OF USER CONTENT CHOICES IN THE EXIT OF FILTER BUBBLES 6

DURATION-BASED INVESTIGATION OF USER CONTENT CHOICES IN THE ...

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6th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2024

作者： Bunza, Rabiatu DEPT. OF COMPUTER SCIENCE FACULTY OF SCIENCE AND ENGINEERING SWANSEA UNIVERSITY United Kingdom

ISBN: (纸本)9798350394634

Content personalization on social platforms has been linked to the creation of filter bubbles. The algorithms provide content recommendations based on the user’s browsing history and interests, which limits content diversity. Studies have been conducted on platforms such as Facebook and YouTube to investigate user awareness and strategies to exit filter bubbles. However, no study has employed a multi-platform, user-centered perspective in investigating filter bubble exit through change in search content, as well as the duration of the content transition across multiple platforms. This study examines the duration of user exit of filter bubbles, across three social platforms;TikTok, YouTube Shots, and Instagram Reels, as well as the impact of word similarity on the duration of the transition between contents, across the platforms. The methodology applied involved triggering the filter bubble effect through user interactions with the search content across the different platforms. Findings revealed that the mean time of a transition between search terms on TikTok is significantly higher than the mean time on Instagram reels, and YouTube shorts. Similarly, the study identified differences in the duration of transition across the different platforms, due to the similarity of the search terms. Apart from improving user awareness of a filter bubble exit strategy, this study contributes to Human-computer Interaction research by highlighting some design implications for future social media application design. © 2024 IEEE.

关键词： Social networking (online)

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High-Power Dual-Polarized Reconfigurable Reflectarray with All-Metal Antenna and Stacked Phase Shifters

High-Power Dual-Polarized Reconfigurable Reflectarray with A...

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2025 United States National Committee of URSI National Radio science Meeting, USNC-URSI NRSM 2025

作者： Hossain, Muhammad Mubasshir Valera, Tatiana Venkatakrishnan, Satheesh B. Volakis, John L. Electrical and Computer Engineering Dept. Florida International University MiamiFL United States

ISBN: (纸本)9781946815200

High-power all-metal antenna arrays with dual-polarization and wide-angle scanning capabilities are well-suited for directed energy applications. Keeping this in consideration, a dual-polarized reconfigurable reflectarray is proposed to maximize the effective isotropic radiated power (EIRP) of a high-power phased array system. © 2025 USNC-URSI.

关键词： Reflection

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Back EMF Protection Circuit Design and Modeling Method of the PMSM of the Small Autonomous Underwater Vehicle by Underwater Discharge

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Transactions of the Korean Institute of electrical Engineers 2022年第5期71卷 471-478页

作者： Cho, Won-Hyo Lee, Byoung Kuk Dept. of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

In this paper, we identify the electric power problem of the high-speed underwater discharge in a small autonomous underwater vehicle(AUV) and propose a circuit design method to protect it. High-speed underwater discharge of an AUV arouse propeller rotates due to the water flow. Excessive initial propeller rotation generates a back EMF of the motor and causes a voltage increase at the DC terminal of the inverter. To figure out this problem, a simulation was performed to limit the back EMF in a simplified environment. Then, a simulation-based controller protection circuit was proposed. Finally, the validity of the proposed simulation and the superiority of the protection circuit were confirmed through the actual underwater discharge test. Copyright © The Korean Institute of electrical Engineers

关键词： Autonomous underwater vehicles

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