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Experimental Evaluation of OTFS for Underwater Acoustic Communications 100

Experimental Evaluation of OTFS for Underwater Acoustic Comm...

引用

100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Xue, Yukang Zhu, Xiyuan Khan, Uzma Zheng, Y. Rosa Lehigh University Dept. of Electrical & Computer Engineering BethlehemPA United States

ISBN: (纸本)9798331517786

This paper applies the Orthogonal Time-Frequency Space (OTFS) modulation to underwater mobile acoustic communications where the communication channel suffers from severe multipath and Doppler effects simultaneously. Field experiments have been conducted with acoustic transmission at a center frequency of 115 kHz and a data rate of 11.5 kilosymbols per second. We propose a new Turbo Decision Feedback Equalizer and Decoder (TDFED) for the receiver and the experimental results demonstrate the superior performance of the proposed TDFED algorithm over existing MMSE equalizers. © 2024 IEEE.

关键词： Decision feedback equalizers

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Optimizing Renewable Energy Management and Demand Response with Ant Colony Optimization: A Pathway to Enhanced Grid Stability and Efficiency

Optimizing Renewable Energy Management and Demand Response w...

引用

2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Islam, Riadul Kabir, Shaharier Shufian, Abu Rabbi, Md Shahiduzzaman Akteruzzaman, Md Lamar University Dept. of Electrical and Computer Engineering Texas United States American International University-Bangladesh Dept. of Electrical and Electronic Engineering Dhaka Bangladesh Dhaka Bangladesh

ISBN: (纸本)9798331541125

The integration of renewable energy sources into the power grid presents significant challenges due to their inherent variability and unpredictability. Efficient management of these sources and the effective implementation of demand response strategies are crucial for maintaining grid stability and optimizing energy usage. This study presents a comprehensive evaluation of the performance of Ant Colony Optimization (ACO) in optimizing microgrid operations compared to other modern algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA). The primary metrics of analysis include energy cost, renewable energy utilization, grid stability, and demand response effectiveness. Through a detailed dataset analysis and algorithmic implementation, the results indicate that ACO consistently outperforms its counterparts across all key performance indicators. ACO achieved the lowest energy cost, maximized renewable energy utilization, and maintained superior grid stability and demand response effectiveness. These findings highlight the potential of ACO as a robust optimization technique for enhancing the efficiency and sustainability of microgrid systems. The study underscores the importance of selecting appropriate algorithms to meet the complex and dynamic challenges of modern energy systems, promoting a transition towards greener and more reliable energy infrastructure. © 2025 IEEE.

关键词： Demand response

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Harmony Forecast: Using Machine Learning to Predict Relationship Quality 1

Harmony Forecast: Using Machine Learning to Predict Relation...

引用

1st IEEE International Conference on Smart Power Control and Renewable Energy, ICSPCRE 2024

作者： Nallagonda, Harshitha Sai Kondra, Varun Teja Gorla, Srinivas Samantula, Mohankrishna Gitam Deemed to be University Dept. of Computer Science and Engineering Visakhapatnam India

ISBN: (纸本)9798350377002

Several things influence human relations. Many of each other's personality traits can have an impact on a relationship between two people. These characteristics have the power to strengthen their love or spark conflict. Personality traits can be used to evaluate the quality of the relationship between the partners. To determine whether the individual will maintain or end the relationship, the relationship's quality has been evaluated based on personality traits. A thorough analysis has been conducted on the personality traits that impact relationships to determine whether they will have an impact, might have an impact or have no impact at all. A study was carried out to investigate the impact of personality traits on relationships. The relationship quality was assessed based on the personality trait which will make the person stay in the relationship, might or might not stay, or not stay in the relationship. The data collected and the pre-existing data combined was used to calculate the relationship quality. © 2024 IEEE.

关键词： Adversarial machine learning

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A Fusion-Based Approach to Multiclass Retinal Disease Classification: Transfer Learning Strategy with CBAM Integration 2

A Fusion-Based Approach to Multiclass Retinal Disease Classi...

引用

2nd International Conference on Power, electrical, Electronics and Industrial Applications, PEEIACON 2024

作者： Nath, Bijoy Deb Afroge, Shyla Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi Bangladesh

ISBN: (纸本)9798331517984

Eye diseases pose significant global public health challenges, often resulting to irreversible blindness if untreated. Early, precise diagnosis of these disorders is critical. In this paper, we address this crucial issue using transfer learning methods for the categorization of multiple eye disorders. The proposed architecture features a fusion-based technique that combines EfficientNetB0 and MobileNetV3Large convolutional neural networks (CNNs) for feature extraction and incorporates Convolutional Block Attention Module (CBAM), which dynamically focuses on significant regions of the images, enhancing the model's discriminative capability. Our proposed model achieves outstanding performance on two separate datasets: 97.85% accuracy on the Eye Disease Classification (EDC) dataset and 91.96% on the Ocular Disease Intelligent Recognition (ODIR) dataset, surpassing existing state-of-the-art approaches in ocular disease classification. By developing the proposed model, we intend to contribute to the creation of more effective diagnostic tools and eventually enhance patient outcomes in ophthalmology. © 2024 IEEE.

关键词： Ophthalmology

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FPGA-based Hardware Acceleration for Model Predictive Control of Power Electronic Converters 50

FPGA-based Hardware Acceleration for Model Predictive Contro...

引用

50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Guo, Zhengchen Nelms, R. Mark Dept. of Electrical and Computer Engineering Auburn University AuburnAL United States

ISBN: (纸本)9781665464543

Model predictive control (MPC) has gained considerable attention in power electronics but the high computational demands preclude its embedded and real-time implementation. This paper presents a novel FPGA-based hardware acceleration approach for MPC implementation in power electronic converters, enabling real-time, embedded operation with a total processing time potentially less than 1 µs, effectively eliminating the computational bottleneck. Furthermore, a comprehensive design guideline of FPGA-based hardware acceleration is presented using a buck converter as example, including top architecture programming to bottom calculation kernels design. This FPGA-based hardware acceleration framework for MPC is versatile, offering potential applicability across a wide range of power electronic systems. Simulation and experimental results using a buck converter with 5-step prediction horizon validate the efficacy of this approach. © 2024 IEEE.

关键词： Buck converter

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Non-Invasive Oral Cancer Detection Using Hyperspectral Imaging and Advanced Spectral Unmixing Models

Non-Invasive Oral Cancer Detection Using Hyperspectral Imagi...

引用

2024 IEEE International Conference on Intelligent Computing and Emerging Communication Technologies, ICEC 2024

作者： Ayyapa, Valluri Kothamasu, Kesava Sriram Killaru, Priyusha Muddana, Saadhivik Aala, Suresh Gutha, Vamsi Kumar, Mukkara Prasana Chinnadurai, Sunil SRM University Dept.of Electronics and Communication Engineering AP India SRM University Dept. of Computer Science and Engineering AP India SRM University Dept. of Computer Science AP India

ISBN: (纸本)9798331508432

Oral cancer is a significant global health concern, often leading to high mortality rates due to late-stage diagnosis and the lack of effective early detection methods. Despite advances in medical science, the absence of reliable early diagnostic tools remains a critical challenge. Hyperspectral imaging (HSI) has emerged as a powerful noninvasive technology, capturing detailed spectral information across a wide range of wavelengths. This allows for accurate differentiation between cancerous and healthy tissues, improving early detection and enhancing treatment outcomes. In this study, we propose the use of HSI for early oral cancer diagnosis. To address the scarcity of labeled data, we developed a synthetic hyperspectral dataset that includes spectral signatures of both normal and cancerous tissues. The dataset was generated using a bilinear mixing model, with key spectral features extracted through Vertex Component Analysis (VCA) and abundances computed using Non-Negative Least Squares (NNLS). The model's performance was evaluated using Spectral angle distance (SAD) and Root mean square error (RMSE) metrics. Our findings demonstrate that HSI significantly improves the accuracy of early oral cancer detection, outperforming traditional methods. This work highlights the potential of advanced imaging technologies in revolutionizing cancer diagnosis, offering a robust framework for non-invasive detection and showcasing the effectiveness of synthetic datasets in medical imaging research. © 2024 IEEE.

关键词： Deep Learning Hyperspectral Imaging (HSI) Non-Negative Least Squares (NNLS) Oral Cancer Detection Root Mean Square Error (RMSE) Spectral Angle Distance (SAD) Synthetic Dataset Vertex Component Analysis (VCA)

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Enhancing Micro-LED Pixel Circuit Performance through Threshold Voltage Compensation Utilizing LTPO Technology

Enhancing Micro-LED Pixel Circuit Performance through Thresh...

引用

International Conference on Display Technology, 2024

作者： Li, Yan Im, Hwarim Moon, Kook Chol Kim, Yong-Sang Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

In this paper, we proposed a new low-temperate polycrystalline silicon and oxide (LTPO) thin film transistor (TFT) pixel circuit for micro light-emitting diode (µLED) displays. This design considers the current-sensitive attributes of µLEDs and employs a hybrid driving approach involving Pulse Width Modulation (PWM) and Pulse Amplitude Modulation (PAM). The proposed pixel circuit can not only compensate the threshold voltages of the two driving TFTs, but also reduce the voltage drop by current (IR drop) of the entire backplane through compensation and offset. © 2024 John Wiley and Sons Inc. All rights reserved.

关键词： Pixels

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Real-Time Gaze Tracking for Online Examination

Real-Time Gaze Tracking for Online Examination

引用

2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Bisht, Preyanshu Kumar, Suresh Netaji Subhas University of Technology Dept. of Computer Science and Engineering Delhi India

ISBN: (纸本)9798331508685

The exponential growth in online education has increased the demand for automated systems to ensure academic integrity during online examinations. A real-time proctoring system addresses this need by monitoring a student's eye gaze and head movements during an exam. This system leverages Dlib's pre-trained frontal face detector and 68-point facial landmark predictor to detect facial features and track the direction of eye movement and head position. By analyzing these metrics, the system can flag behaviors associated with potential cheating, such as looking away from the screen for extended periods. This paper discusses the design and implementation of the proctoring system, details the detection algorithms, and evaluates its effectiveness for real-time monitoring. © 2025 IEEE.

关键词： Online systems

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From Pixels to Diagnosis: Convolutional Neural Networks in Tuberculosis Screening 6

From Pixels to Diagnosis: Convolutional Neural Networks in T...

引用

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

作者： Zihan, Tanvir Mahtab Zami, Abduz Ahmed, Mohiuddin Islam, Rakibul Ahmed, Fahim Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi Bangladesh Uiu Dept. of Cse Dhaka Bangladesh

ISBN: (纸本)9798350385779

Tuberculosis (TB) is a chronic lung disease that constitutes one of the top 10 global causes of death. Timely and precise identification of TB is critical, as untreated cases can pose life-threatening risks. Traditional radiographic interpretation by trained professionals is subjective, time-consuming, and prone to human error. This study proposes an automated deep learning-based approach for TB detection from chest X-ray images, based on EfficientNet-B0 architecture. The Convolutional Neural Network (CNN) extracts discriminative features, allowing it to differentiate between normal and abnormal lung patterns indicative of TB. Our choice of the EfficientNet-B0 architecture played a pivotal role in the success of our TB detection model. Training and evaluation were conducted on three distinct datasets: Tuberculosis (TB) Chest X-ray Database, Shenzhen Hospital CXR Set, and Montgomery County CXR Set. The key breakthrough is attaining an accuracy of 99.29% on the Tuberculosis (TB) Chest X-ray Database and 98.50% on the combined dataset. This study presents a promising approach for automated TB screening using readily available chest X-ray images, potentially improving diagnostic accuracy and efficiency, especially in resource-limited settings. We compared our scores with those of other works and found that ours significantly outperforms them. © 2024 IEEE.

关键词： Diagnosis

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Multivariate Analysis of Urban Air Pollution: Clustering and Patterns Across Major Asian Cities

Multivariate Analysis of Urban Air Pollution: Clustering and...

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2024 IEEE International Conference on Future Machine Learning and Data science, FMLDS 2024

作者： Rahman, Anika Khatun, Mst. Taskia Stamford University Bangladesh Dept. of Computer Science & Engineering Dhaka Bangladesh

ISBN: (纸本)9798350391213

This study analyzes air pollution in Asian cities using the Global Air Pollution Data, consisting of 6,196 entries from 31 countries. Our primary goal is to identify pollution patterns through multivariate analysis and evaluate the effectiveness of six clustering algorithms: K-Means, Hierarchical Clustering, DBSCAN, Gaussian Mixture Models (GMM), Agglomerative Clustering, and Spectral Clustering. Performance was assessed using Silhouette Score, Davies-Bouldin Index, Calinski-Harabasz Index, WCSS, Cohesion, and Separation. The novelty of this work lies in the comparative analysis of these clustering methods on air pollution data, providing new insights into pollution dynamics across Asian cities. The analysis identified four distinct clusters- 'High Pollution', 'Moderate Pollution', 'Ozone-Dominated Pollution', and 'Low Pollution'- with K-Means proving to be the most effective. Significant disparities were found, particularly in South and East Asia, where countries like India, China, and Pakistan exhibited the highest pollution levels. Additionally, an examination of capital cities revealed specific pollution patterns and the primary pollutants-PM2.5, NO2, CO, and Ozone-aiding in identifying sources and affected regions. These findings underscore the need for targeted regional pollution control strategies. © 2024 IEEE.

关键词： Haze pollution

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