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20th CSI International Symposium on Artificial Intelligence and Signal Processing, AISP 2024

作者： Ghasemi, Ali Sharifi-Tehrani, Omid Safahan Institute of Higher Education Department of Electrical and Communication Engineering Isfahan Iran

ISBN: (纸本)9798350383942

Radio-frequency communication system performance can be affected by interference signal. Although spread spectrum techniques can provide a level of robustness for secure communication, but they can be still affected by strong interferences. Therefore, early detection and estimation of interference signal presence can enable the user or system to make preemptive actions. In the current article, a new detection and estimation strategy utilizing flipped Toeplitz-covariance-matrix Frobenius-norm is proposed for single-tone continuous-wave interference. By bordering the autocorrelation matrix, the Frobenius norm is calculated in each step. Then the derivation is obtained and the Fourier transform of the result, provides the input signal frequency. This method could be utilized for early caution level in secure-communication direct-sequence system. The efficiency of the introduced algorithm is verified by real dataset simulation and comparison with some other methods which shows good performance. © 2024 IEEE.

关键词： Secure communication

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Image Restoration and Enhancement of Retinal images Using Multi-Resolution Dual CNN

Image Restoration and Enhancement of Retinal images Using Mu...

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2024 International Conference on Brain computer Interface and Healthcare Technologies, iCon-BCIHT 2024

作者： Tojo, Laya Devi, Manju Sujith, Annie The Oxford College of Engineering Department of Electronics & Communication Communication Bengaluru India Jyothy institute of Technology Department of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9798331540067

In this paper we propose a Multi-resolution Dual Convolutional Neural Network (MR-DCNN) which is used to denoise the images. By incorporating sparse mechanism in dual networks, implementing a 2-tier architecture and by downscaling the width and height of CNN layers, we could reduce the computational complexity and achieve better performance and speed. The observed values prove that the novel MR-DCNN method can upgrade the visual quality without even compromising on PSNR, SSIM and MSE values. The suggested MR DCNN method outperforms numerous modern image enhancing techniques, based on objective and subjective results. Later, we propose the MR-DCNN method to boost the visual quality of low contrast retinal images. The MR-DCNN incorporated helps to enhance the visual quality by denoising the images and also removing fading effects. This novel formulation attains further improvement than existing schemes, and proves significant development in PSNR, SSIM and MSE values and visual quality perception. The presented scheme enhances the retinal image quality by improving the clarity. The MR-DCNN approach could deliver ophthalmologists with novel strategies to rectify retinal diseases from fundus images. This will lessen the amount of manual grading required, which will assist to cut down on pointless, expensive referrals. © 2024 IEEE.

关键词： Convolutional neural networks

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Decentralized Demand Management Based on Alternating Direction Method of Multipliers Algorithm for Industrial Park with CHP Units and Thermal Storage

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Journal of Modern Power Systems and Clean Energy 2022年第1期10卷 120-130页

作者： Jingdong Wei Yao Zhang Jianxue Wang Lei Wu Peiqi Zhao Zhengting Jiang School of Electrical Engineering Xi’an Jiaotong UniversityXi’anChina Electrical and Computer Engineering Department Stevens Institute of TechnologyHobokenUSA

This paper proposes a decentralized demand management approach to reduce the energy bill of industrial park and improve its economic gains.A demand management model for industrial park considering the integrated demand response of combined heat and power(CHP)units and thermal storage is firstly ***,by increasing the electricity outputs of CHP units during peak-load periods,not only the peak demand charge but also the energy charge can be *** thermal storage can efficiently utilize the waste heat provided by CHP units and further increase the flexibility of CHP *** heat dissipation of thermal storage,thermal delay effect,and heat losses of heat pipelines are considered for ensuring reliable solutions to the industrial *** proposed model is formulated as a multi-period alternating current(AC)optimal power flow problem via the second-order conic programming *** alternating direction method of multipliers(ADMM)algorithm is used to compute the proposed demand management model in a distributed manner,which can protect private data of all participants while achieving solutions with high *** case studies validate the effectiveness of the proposed demand management approach in reducing peak demand charge,and the performance of the ADMM-based decentralized computation algorithm in deriving the same optimal results of demand management as the centralized approach is also validated.

关键词： Alternating direction method of multipliers(ADMM) combined heat and power(CHP)unit demand management industrial park integrated demand response(IDR) thermal storage

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A New MRACS Approach for Overcome Unmeasurable Disturbance Using State Variables Taking from the Model 6

A New MRACS Approach for Overcome Unmeasurable Disturbance U...

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6th International Conference on electrical engineering and Control Technologies, CEECT 2024

作者： Wei, Yongdong Liu, Xiaojing Kong, Jiayi Fang, Wen Cheng, Zixuan Beijing Institute of Graphic Communication Department of Mechanical and Electrical Engineering Beijing China

ISBN: (纸本)9798331528096

This paper proposes a MRACS approach based on Popov hyperstability theory to address unmeasurable disturbances by utilizing state variables derived from the *** use of this approach simplifies the system structure and reduces the number of adjustable parameters. It also addresses the issue of directly measuring the object's state and significantly minimizes noise interference. An adjustable linear compensator is used to remove the assumption of strictly positive real. The proposed method is more effective than the current MRAC method when dealing with measured interference of known forms, demonstrating improved performance in error modeling, adaptive rate, and stability *** simulations demonstrate the effectiveness of this approach. The output of the controlled system closely aligns with that of the reference model, even in situations with unmeasurable interference, indicating a higher application value for the method. © 2024 IEEE.

关键词： Model reference adaptive control

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Optimizing Packet Delivery in Underwater Wireless Sensor Networks: A Comparative Study of Genetic Bee Colony and Ant Colony Algorithms 9

Optimizing Packet Delivery in Underwater Wireless Sensor Net...

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9th International Conference on communication and Electronics Systems, ICCES 2024

作者： Kannappan, A. Kolagani, Nagesh Kandaswamy, Vijay Anand Vishnupriyan, J. Saveetha School of Engineering Simats Department of Electronics and Communication Engineering Chennai India Saveetha School of Engineering Simats Department of Computer Science and Engineering Chennai India Chennai Institute of Technology Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350377972

Physically Underwater communication adopt the bio inspired genetic bee colony formed network communication structures. Underwater environment condition communication is established between the Transmitting node and in between several clustering relay nodes to reach receiver nodes. Transmitting nodes are placed on sea bed areas at certain depth and clustering relay nodes are placed in various underwater depth conditions dipping the sensor nodes. Also, underwater battery life is very hard and battery replacement is a very tough task. Hence, an alternate solution of optimization battery capacity utilization is used. This optimization algorithm improves Packet delivery ratio by comparing genetic bee algorithm with Ant colony algorithm. Hence, equivalence of two algorithms implemented in underwater conditions. The genetic bee colony Algorithm produces better output results more than 4 to 6 percentage compared to ant colony parameter output. The genetic bee colony algorithm offers a maximum clustering node technique compared to ant colony algorithm. Its greater support for saving energy consumption extending battery life. © 2024 IEEE.

关键词： Ant colony optimization

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A New MRACS Design Scheme for Higher-Order System Follows Lower-Order Model Taking State Variables from the Model

A New MRACS Design Scheme for Higher-Order System Follows Lo...

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2024 IEEE International Conference on Control Science and Systems engineering, ICCSSE 2024

作者： Fang, Wen Liu, Xiaojing Kong, Jiayi Cheng, Zixuan Wei, Yongdong Beijing Institute of Graphic Communication Department of Mechanical and Electrical Engineering Beijing China

ISBN: (纸本)9798331517199

This paper presents a novel Model Reference Adaptive Control System (MRACS) design scheme for higher-order systems based on Popov hyperstability theory. The proposed approach enables higher-order systems to track lower-order models by utilizing state variables extracted directly from the model. To address the challenge of unmeasurable plant states and mitigate noise interference, a virtual ascending method is employed. Additionally, an adjustable linear compensator is introduced to eliminate the need for the strictly positive real condition. Simulation results demonstrate that the controlled plant effectively follows the reference model's output, validating the robustness of the proposed design. © 2024 IEEE.

关键词： Model reference adaptive control

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Efficient Fault Classification in Rotating Machinery Using the K-Nearest Neighbor Algorithm 1

Efficient Fault Classification in Rotating Machinery Using t...

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

作者： Kumar, Sujit Kumari, Alka Priya, Shalu Bharti, Nisha Nandani, Durgesh Kumar, Manish Government Engineering College Banka Electrical Engineering Department Bihar India Government Engineering College Banka Electronics and Communication Engineering Department Bihar India Government Engineering College Banka Computer Science Engineering Department Bihar India Indian Institute of Technology Patna Electrical Engineering Department Bihar India

ISBN: (纸本)9798350377002

Rotating machines are widely used in industries. Rolling bearings, which are essential components of these ma-chines, are prone to damage. Therefore, diagnosing faults in rolling bearings quickly and accurately is crucial for maintenance purposes. Machine learning has become a very effective tool for diagnosing faults in rolling bearings. The KNN Algorithm is one such technique that effectively categorizes faults. This study proposes an intelligent fault classification system for bearing faults based on the KNN Algorithm. The proposed model accurately identifies different types of fault conditions in rolling bearings. Our proposed model achieves superior results and has been compared with existing methods. © 2024 IEEE.

关键词： Rotating machinery

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DeepFakeGuard: Safeguarding Digital Platforms Against Fake Profiles Using AI 4

DeepFakeGuard: Safeguarding Digital Platforms Against Fake P...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Swarna Sudha, M. Manjula, S. Bharathi, Indira Krishnasamy, Valarmathi Vijayalakshmi, K. Ramco Institute of Technology Department of Computer Science and Engineering Rajapalayam India School of Computer Science and Engineering Vellore Institute of Technology Chennai India PSR Engineering College Department of Electronics and Communication Engineering Sivakasi India

ISBN: (纸本)9798331523923

This research introduces DeepFakeGuard, a hybrid deep learning framework designed to detect fake profiles on social media platforms, addressing the growing threat of fraudulent accounts online. DeepFakeGuard integrates multiple data modalities, including textual, visual, behavioral, and network features, to accurately classify profiles as real or fake. Leveraging advanced deep learning models such as BERT for textual analysis, ResNet for image processing, and LSTM for modeling behavioral patterns, DeepFakeGuard provides a comprehensive and robust solution for identifying fake profiles across diverse platforms. The framework processes a rich set of profile characteristics, including account information, posting behavior, post sentiment, and network relationships, ensuring a multi-dimensional analysis of social media accounts. The hybrid architecture of DeepFakeGuard merges outputs from individual sub-models, which are then processed through dense layers for final classification using a sigmoid activation function. This multi-faceted approach significantly enhances detection accuracy, precision, and recall compared to traditional methods. The framework is highly scalable and adaptable to various social media platforms, offering a versatile tool for strengthening online security. With strong performance metrics, including high classification accuracy, DeepFakeGuard demonstrates its potential for real-world applications in mitigating the risks associated with fake profiles. By fostering secure and trustworthy social media environments, this research contributes to the ongoing fight against fraudulent accounts, paving the way for safer online interactions. © 2025 IEEE.

关键词： Contrastive Learning

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Independent Control Over Passbands in Highly Selective and Compact Triple-Band Bandpass Filter Based on Substrate Integrated Waveguide

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Progress In Electromagnetics Research B 2023年 100卷 133-154页

作者： Chaudhury, Soumit S. Awasthi, Seema Singh, Rajat K. Department of Electronics and Communication Engineering Faculty of Science and Technology ICFAI Foundation for Higher Education Hyderabad India Department of Electrical Engineering Indian Institute of Technology Kanpur Kanpur India Department of Electronics and Communication Engineering Indian Institute of Information Technology Allahabad Allahabad India

This paper proposes a method of independent control over each passband in a high performance triple bandpass filter, which is an essential requirement in the field of microwave communication systems. Individual techniques are presented here to control the excited modes that are responsible for the generation of triple passbands based on substrate integrated waveguide loaded with semi-circular mushroom resonators. Initially, a circular substrate integrated waveguide (CSIW) loaded with two cascaded semi-circular mushroom resonators (ScMRs) with distinct modifications and orientations in the schematic is employed to generate three passbands. The fundamental mode and next higher order mode of the entire resonator structure are utilized to generate three passbands, and distinct techniques of mode perturbations and variation in coupling strength are introduced to independently control the excited modes. Subsequently, the methods established to control the excited modes are employed to independently control the center frequencies (CFs) of three passbands. All those methods established to control the CFs of the three passbands are verified with experimental results which show good agreement with the simulated ones. © (2023), All Rights Reserved.

关键词： Substrate integrated waveguides

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Building Robust Fraud Detection Model for Insurance Claims Using SMOTE 3rd

Building Robust Fraud Detection Model for Insurance Claims U...

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3rd International Conference on Universal Threats in Expert Applications and Solutions, UNI-TEAS 2024

作者： Malathi, M. Armash, S. M. Mohammed Kavitha, S. Chinthamani, B. Sinthia, P. Department of Electronics and Communication Engineering Rajalakshmi Institute of Technology Chennai India UG Scholar Department of Computer and Communication Engineering Rajalakshmi Institute of Technology Chennai India Department of Electrical and Electronics Engineering Saveetha Engineering College Chennai India Department of Electronics and Instrumentation Engineering Easwari Engineering College Chennai India Department of Biomedical Engineering Saveetha Engineering College Chennai India

ISBN: (纸本)9789819738090

The insurance fraud claim detection is a critical task in the insurance industry. Various methodologies were proposed in terms of detecting fraud claims but the main thing is handling the proportionality between the fraud and non-fraud cases in the dataset before it was given to the model, in that case class imbalance may occur. Class imbalance where the number of fraudulent claims is significantly lower than legitimate claims which pose a challenge for accurate fraud detection. In this paper, we employed [Elreedy and Atiya in Inf Sci 505:32–64, 2019] Synthetic Minority Over-sampling Technique (SMOTE) algorithm to address the imbalance problem and enhance the performance of the fraud claim detection model. SMOTE is a popular technique for oversampling the minority class by creating synthetic samples that are similar to the existing minority class instances. By generating synthetic examples, SMOTE helps in balancing the class distribution and allows the model to learn from a more representative dataset. This technique is particularly effective when the available data is limited and insufficient to capture the complexities of the limited class. This process results in a larger and more balanced dataset, enabling the model to learn from a diverse range of fraudulent claim patterns. By applying SMOTE to our dataset, we are able to overcome the class imbalance issue and improve the performance of the fraud claim detection model. The resampled dataset provides a more accurate representation of the underlying distribution, leading to enhanced detection of fraudulent claims. We evaluate the performance of the model by measuring various metrics such as accuracy, precision, recall and F1-score. Our findings demonstrate the effectiveness of SMOTE in addressing class imbalance with improved random forest and LightGBM model for fraud claim detection process. The utilization of SMOTE contributes to better identification of fraudulent insurance claims, reducing potential losses an

关键词： Crime

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