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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Swarup, Lakshya Jayadurga, R. Borade, Monali R. Ramachandran, T. Singh, Akhilendra Pratap Prabha, Savita Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Master of Business Administration Chennai127 India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Faculty of Engineering and Technology Department of Mechanical Engineering Karnataka Bangalore India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Engineering Jaipur India

ISBN: (纸本)9798350319125

Wi-wireless networks are becoming more pervasive and are frequently the primary goal of malicious attackers. Therefore, it is miles crucial that wireless networks are nicely secured to defend their users from malicious moves. DNS-based total authentication is a promising answer for attaining ease of authentication of wi-wireless customers in an open Wi-Fi community. This paper surveys numerous current works that discover the wi-fits wireless of DNS-based total authentication for Wi-Fi wireless community safety. especially this paper opinions three one-of-a-kindwireless strategies of using DNS for authentication purposes: making use of DNS's cache for identifying windows-primarily based Wi-Fi wireless clients;Open Mobile Alliance (OMA)'s tool control (DM) projects to relaxed get right of entry to;and a modern scheme for protecting the use of the DNS-based techniques. Wi-finally, this paper discusses a few safety-demanding situations and future studies directions. © 2023 IEEE.

关键词： authentication initiatives management protecting secured

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Color image restoration by filtering methods: a review

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Soft Computing 2024年第13-14期28卷 7755-7782页

作者： Salamat, Nadeem Missen, Malik Muhammad Saad Akhtar, Nadeem Mustahsan, Muhammad Surya Prasath, V.B. Department of Mathematics Khawaja Fareed University of Engineering and Information Technology Rahim Yar Khan64200 Pakistan Department of Computer Science and IT The Islamia University of Bahawalpur Bahawalpur63100 Pakistan Division of Biomedical Informatics Cincinnati Children’s Hospital Medical Center CincinnatiOH45229 United States Department of Computer Science Pediatrics and Biomedical Informatics University of Cincinnati CincinnatiOH45221 United States

Digital images are corrupted with noise, and image denoising is an important step in image processing modules. In this review, the latest developments in filtering methods for color image restoration are analyzed. These algorithms are compared in terms of objective image quality measures and divided into major classes, such as spatial domain, switching and wavelet filtering methods. These classes are based on the particular methodology used in image denoising algorithms and further subdivided to show their classification in terms of noise models utilized, application style, and stages the filters applied in images. In particular, we present a review of filtering methods in color image denoising, published over the past two decades. Our classification and succinct descriptions of color image restoration by these mathematical filtering techniques and their characterizations can help choose the appropriate ones for various downstream image processing tasks. © The Author(s) 2024.

关键词： Restoration

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A Deep Drive Analysis Framework on Emotions of Users in Attention Driven Systems 8

A Deep Drive Analysis Framework on Emotions of Users in Atte...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Dharshini, S. Akshita, Ravula Panigrahi, Suman Varma, Nadimpalli Sai Kiran Kumar Thangavel, Senthil Somasudaram, K. Abel Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Tamil Nadu Coimbatore India Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Coimbatore India Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Mathematics Tamil Nadu India Cape Peninsula University of Technology Faculty of Informatic and Design Department of Information Technology South Africa

ISBN: (纸本)9798350376425

One of the ways humans communicate is by using facial expressions. In psychology, the detection of emotions or facial expressions requires analysis and assessment of decisions in predicting a person's emotions or group of people in communicating. Emotion is powerful in many ways because it can influence a decision and urge people to act. This emotion like anger, happiness, sadness, disgust, fear, surprise, and neutral detection is used for human behaviour and understanding, action of mental disorders, and synthetic human expressions. This can be used in healthcare, marketing, and manufacturing. Here the paper is based on marketing where we can detect the emotions of the people watching the ads. This emotion detection for the ads can be used for predictions like whether customers will like the product or not, whether the sales will increase or not, etc. The methodology used to predict human emotion through the face is CNN and MobileNetV2 with LSTM which is a pretrained model. The architecture involves pre-processing of the data, feature detection, face detection, and detection of emotion. There are various datasets used for detecting emotions like FER-2013, JAFFE, CK+, etc. Here the FER-2013 is used. The performance of the model is measured by using confusion matrix, recall, precision, f1-score, and accuracy. © 2024 IEEE.

关键词： Face recognition

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Analyzing and Developing the Security of DNS-Based Authentication in Wireless Sensor Network 3

Analyzing and Developing the Security of DNS-Based Authentic...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Sharma, Umesh Chand Kumar, Jambi Ratna Raja Kumari, Meenakshi Anandhasilambarasan, D. Latha, B. Jadhav, Prranjali Mangalayatan University Department of Computer Science Aligarh India Genba Sopanrao Moze College of Engineering Balewadi Department of Computer Engineering Maharashtra Pune India Usha Martin University Faculty of Business Mangagement & Commerce Ranchi India Karpagam Academy of Higher Education Department of Computer Science Engineering Coimbatore India Prince Shri Venkateshwara Padmavathy Engineering College Department of Information Technology Chennai India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India

ISBN: (纸本)9798350319125

Analyzing and developing the safety of DNS-based total Authentication in Wireless Sensor Networks (WSNs) is a critical research vicinity that is being actively pursued. While preceding work has blanketed authentication strategies to relax the communications between a node and its base station, our studies focus on analyzing the authentication schemes used to set up a comfy verbal exchange in a wireless Sensor network among nodes. We look at the assets of Symmetric and asymmetric Authentication Protocols for WSNs and examine their effectiveness in terms of their authentication effectiveness and overhead. We also discuss how they can be incorporated with current authentication schemes used for WSNs. We then gift a singular protocol that uses DNS-based Authentication to safely set up a verbal exchange in a Wi-Fi Sensor network. Ultimately, we put in force and tested our protocol and the degree of its overall performance in simulated surroundings. Our experiments' results show that our protocol gives an effective authentication answer for WSNs. © 2023 IEEE.

关键词： authentication effectiveness exchange experiments schemes

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Performance Analysis of Three Spectrum Sensing Detection Techniques with Ambient Backscatter Communication in Cognitive Radio Networks

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computer Modeling in engineering & sciences 2023年第10期137卷 813-825页

作者： Shayla Islam Anil Kumar Budati Mohammad Kamrul Hasan Saoucene Mahfoudh Syed Bilal Hussian Shah Institute of Computer Science&Digital Innovation ICSDIUCSI UniversityKuala Lumpur56000Malaysia Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan Malaysia(UKM)Selangor43600Malaysia School of Engineering Computing and InformaticsDar Al-Hekma UniversityJeddah22246Saudi Arabia

In wireless communications, the Ambient Backscatter Communication (AmBC) technique is a promisingapproach, detecting user presence accurately at low power levels. At low power or a low Signal-to-Noise Ratio(SNR), there is no dedicated power for the users. Instead, they can transmit information by reflecting the ambientRadio Frequency (RF) signals in the spectrum. Therefore, it is essential to detect user presence in the spectrum forthe transmission of data without loss or without collision at a specific time. In this paper, the authors proposed anovel Spectrum Sensing (SS) detection technique in the Cognitive Radio (CR) spectrum, by developing the *** Matched Filter Detection with Inverse covariance (MFDI), Cyclostationary Feature Detection with Inversecovariance (CFDI) and Hybrid Filter Detection with Inverse covariance (HFDI) approaches are used with AmBCto detect the presence of users at low power levels. The performance of the three detection techniques is measuredusing the parameters of Probability of Detection (PD), Probability of False Alarms (Pfa), Probability of MissedDetection (Pmd), sensing time and throughput at low power or low SNR. The results show that there is a significantimprovement via the HFDI technique for all the parameters.

关键词： Ambient backscatter communication cognitive radio MFDI CFDI HFDI

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Arabic Handwritten Document OCR Solution with Binarization and Adaptive Scale Fusion Detection

Arabic Handwritten Document OCR Solution with Binarization a...

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Novel Intelligent and Leading Emerging sciences Conference (NILES)

作者： Alhossien Waly Bassant Tarek Ali Feteha Rewan Yehia Gasser Amr Ahmed Fares Computer Science and Engineering Departement Faculty of Engineering Egypt-Japan University of Science & Technology E-JUST Alexandria Egypt Electrical Engineering Department Faculty of Engineering Benha University Cairo Egypt

ISBN: (数字)9798350378511

ISBN: (纸本)9798350378528

The problem of converting images of text into plain text is a widely researched topic in both academia and industry. Arabic handwritten Text Recognation (AHTR) poses additional challenges due to diverse handwriting styles and limited labeled data. In this paper we present a complete OCR pipeline that starts with line segmentation using Differentiable Binarization and Adaptive Scale Fusion techniques to ensure accurate detection of text lines. Following segmentation, a CNN-BiLSTM-CTC architecture is applied to recognize characters. Our system, trained on the Arabic Multi-Fonts Dataset (AMFDS), achieves a Character Recognition Rate (CRR) of 99.20% and a Word Recognition Rate (WRR) of 93.75% on single-word samples containing 7 to 10 characters, along with a CRR of 83.76% for sentences. These results demonstrate the system's strong performance in handling Arabic scripts, establishing a new benchmark for AHTR systems.

关键词： Optical losses Adaptation models Accuracy Text recognition Optical character recognition Pipelines Optical computing Optical fiber networks Character recognition Optimization

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Estimating finger joint angles by surface EMG signal using feature extraction and transformer-based deep learning model

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Biomedical Signal Processing and Control 2024年 87卷

作者： Putro, Nur Achmad Sulistyo Avian, Cries Prakosa, Setya Widyawan Mahali, Muhammad Izzuddin Leu, Jenq-Shiou Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taiwan Department of Computer Science and Electronics Faculty of Mathematics and Natural Sciences Universitas Gadjah Mada Indonesia Department of Electronics and Informatics Engineering Faculty of Engineering Universitas Negeri Yogyakarta Indonesia

Human-machine interfaces frequently use electromyography (EMG) signals. Based on previous work, feature extraction has a great deal of influence on the performance of EMG pattern recognition. Furthermore, the Deep Learning method is supposed to increase performance and not depend on feature engineering. However, directly processing raw signals will require a higher computation rate. This study proposed a new method that combines feature extraction and Deep Learning to address those issues while improving performance, reducing architecture size, and producing a more representative output. The proposed architecture employs the Transformer model as the backbone to get the correlation between elements and focus on the important information for estimating the flexion-extension of finger joint angles. This study uses experiment three of the NinaPro (Non-Invasive Adaptive Hand Prosthetics) DB5 dataset. Each experiment produces 16 Surface EMG data streams from two Myo Armbands devices representing 22 finger joint angles as output. This study compares the windowing process, feature extraction, execution time, and results with previous studies. The results show that the proposed model outperforms the previous study, from 0.957 in the previous study to become 0.970 in this study for the R-Square score. This result is obtained using 100 data points for the windowing process and Median Frequency for the best feature extraction method. © 2023

关键词： Feature extraction

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High Pressure Water Solar Collector as Potential of Mini Steam Power Plant in Iraq 7

High Pressure Water Solar Collector as Potential of Mini Ste...

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7th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2023

作者： Zaynal, Hussein I. Hussain, Abadal-Salam T. Taha, Taha A. Yass, Alaa. A. Ahmed, Saadaldeen Rashid Ahmed, Shouket A. Al-Kitab University Department of Computer Engineering Technology Altun Kupri Iraq Al-Kitab University Technical Engineering College Department of Medical Instrumentation Techniques Engineering Kirkuk Altun Kupri Iraq Technical University Unit of Renewable Energy Northern Kirkuk Iraq Northern Technical University Department of Electrical Engineering Technology Kirkuk Iraq Bayan University Collage of Engineering and Science Department Computer Science Kurdistan region Erbil Iraq

ISBN: (纸本)9798350383065

This paper explores the potential of utilizing high-pressure water solar collectors as a crucial component in mini steam power plants. The study focuses on integrating solar thermal energy with steam turbines to enhance electricity generation efficiency. By combining parabolic troughs with combined-cycle plants, the paper demonstrates the potential to minimize investment costs associated with the solar field while reducing CO2 emissions linked to conventional plants. A comprehensive analysis of the methodology is provided, encompassing hardware and software installation, advantages, challenges, and future trends. The results and discussions underscore the feasibility of incorporating high-pressure water solar collectors into existing power plants and outline the necessary modifications for successful integration. While solar energy adoption is still in its nascent stages in Iraq, where installation costs and limited expertise pose challenges, the paper highlights the significance of overcoming these barriers to promote energy-efficient systems. It is worth to conclude that by emphasizing the need for collaborative efforts involving private developers, financial institutions, and the government to drive the development and implementation of high-pressure water solar collectors for sustainable energy generation. © 2023 IEEE.

关键词： Solar thermal energy

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Breast Cancer Detection Based Microwave Imaging Using Single Antipodal Vivaldi Antenna

Breast Cancer Detection Based Microwave Imaging Using Single...

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2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics, RI2C 2022

作者： Tangwachirapan, Shalermchon Sawangsri, Panupong Pinitkiatisakul, Pitchvara Thongdit, Preecha Thaiwirot, Wanwisa Nakhon Pathom Rajabhat University Faculty of Science and Technology Department of Telecommunication Engineering Nakhon Pathom Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand

ISBN: (数字)9781665473248

ISBN: (纸本)9781665473248

This paper presents breast cancer detection based on microwave imaging using single antipodal Vivaldi antenna. The breast cancer detection system mainly consists of antipodal Vivaldi antenna, vector network analyzer, breast phantom, and rotation platform. The artificial breast phantom is fabricated by using gelatin-oil mixture technology as fat and cancerous cell. The difference for relative permittivity and conductivity between cancerous cell and normal tissue is around 4:1 and 6:1, respectively. The process of breast cancer detection and imaging are presented. The measured results show that the cancerous cell embedded inside the breast phantom can be detected. In addition, the graphical user interface (GUI) for creating the 2D MWI is developed using MATLAB. © 2022 IEEE.

关键词： Graphical user interfaces

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Optimal Machine Learning Enabled Intrusion Detection in Cyber-Physical System Environment

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computers, Materials & Continua 2022年第9期72卷 4691-4707页

作者： Bassam A.Y.Alqaralleh Fahad Aldhaban Esam A.AlQarallehs Ahmad H.Al-Omari MIS Department College of Business AdministrationUniversity of Business and TechnologyJeddah21448Saudi Arabia School of Engineering Princess Sumaya University for TechnologyAmman11941Jordan Faculty of Science Computer Science DepartmentNorthern Border UniversityArar91431Saudi Arabia

Cyber-attacks on cyber-physical systems(CPSs)resulted to sensing and actuation misbehavior,severe damage to physical object,and safety *** learning(ML)models have been presented to hinder cyberattacks on the CPS environment;however,the non-existence of labelled data from new attacks makes their detection quite *** Detection System(IDS)is a commonly utilized to detect and classify the existence of intrusions in the CPS environment,which acts as an important part in secure CPS *** developments in deep learning(DL)and explainable artificial intelligence(XAI)stimulate new IDSs to manage cyberattacks with minimum complexity and high *** this aspect,this paper presents an XAI based IDS using feature selection with Dirichlet Variational Autoencoder(XAIIDS-FSDVAE)model for *** proposed model encompasses the design of coyote optimization algorithm(COA)based feature selection(FS)model is derived to select an optimal subset of ***,an intelligent Dirichlet Variational Autoencoder(DVAE)technique is employed for the anomaly detection process in the CPS ***,the parameter optimization of the DVAE takes place using a manta ray foraging optimization(MRFO)model to tune the parameter of the *** order to determine the enhanced intrusion detection efficiency of the XAIIDS-FSDVAE technique,a wide range of simulations take place using the benchmark *** experimental results reported the better performance of the XAIIDSFSDVAE technique over the recent methods in terms of several evaluation parameters.

关键词： Cyber-physical systems explainable artificial intelligence deep learning security intrusion detection metaheuristics

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