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6th International Conference on Electrical Information and Communication Technology, EICT 2023

作者： Moue, Sonia Akter Samsuzzaman, Md. Mahmud, Md Zulfiker Siddiquea, Sefat Talukder, Md Siam Majumder, Sarna Patuakhali Science And Technology University Faculty of Computer Science And Engineering Bangladesh Jagannath University Dept. of Computer Science and Engineering Bangladesh Patuakhali Science and Technology University Faculty of Computer Science and Engineering Dumki Patuakhali Bangladesh

ISBN: (纸本)9798350370836

This study presents a detailed description of a Slotted V Shaped Compact Wideband Antenna designed for the purpose of microwave-based head imaging. The antenna under consideration comprises a radiating patch with a Vshaped slot and a partial ground with slots. Slots have been found to significantly improve the efficiency, dispersion of current, gain, and various other aspects of antennas. The antenna under consideration has a maximum gain of 5.85, operates within the frequency range of 4 to 8.06 GHz, and is deemed suitable for head imaging applications. The dimensions of the antenna under consideration are 0.33λ × 0.667λ × 0.21λ, where λ represents the wavelength, at a lower frequency of 4 GHz. Additionally, the antenna is equipped with a 50 ohm microstrip transmission line. The antenna is fabricated on a cost-effective FR4 substrate with a thickness of 1.5 mm. The antenna under consideration achieves a fractional bandwidth of 67.33% within the frequency range of 4 to 8 GHz. In order to optimize antenna performance, a comprehensive parametric analysis is carried out utilizing the widely recognized software tools HFSS and CST. The experimental testing and analysis of the prototype antenna yielded findings that exhibited a satisfactory level of concurrence with the corresponding calculations. © 2023 IEEE.

关键词： Brain

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Unleashing the Potential of Women in Leadership Roles within the Evolving Landscape of Machine Learning and Technology

Unleashing the Potential of Women in Leadership Roles within...

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2024 IEEE International Conference on Intelligent Systems and Advanced Applications, ICISAA 2024

作者： Tiwari, Madhuri Giri, Neeraj Suman, Sanjay Kumar Chandanan, Amit Kumar Peneti, Subhashini Choudhury, Shibanjali GGITS Dept of Data Science MP Jabalpur India IES Institute of Technology and Management IES University Department of Computer Science and Engineering MP Bhopal462044 India St. Martin's Engineering College Dept. of ECE Telangana Secunderabad India Department of Computer Science and Engineering C G Bilaspur India MLR Institute of Technology Dept. of CSE Telangana Hyderabad India Techno College of Engineering Dept. of CSE Tripura Agartala India

ISBN: (纸本)9798331539948

The innovative Gender-Empowered Leadership Development (GELD) programme promotes gender equality in fast-paced technology and machine learning leadership positions. This was a US government initiative. BiasMitigator, Skillenhancer, and CultureCatalyst work together to eliminate gender prejudice, improve employee skills, and improve workplace morale. Programs collaborate to achieve these aims. CultureCatalyst promotes a pleasant environment, SkillEnhancer improves skills over time, and BiasMitigator eliminates gender prejudice across the firm. All three projects assist the organization achieve its aims. This study compares GELD to normal approaches to better understand the situation. This illustrates how intricate its procedure is. © 2024 IEEE.

关键词： BiasMitigator CultureCatalyst GenderEmpowered Leadership Development Inclusion Leadership Development Machine Learning SkillEnhancer Technology Traditional Methods Women in Leadership

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Modular Design of Solid-State Transformer with High Flexibility

Modular Design of Solid-State Transformer with High Flexibil...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Ma, Zhuxuan Cao, Hui Zhao, Yue University of Arkansas Dept. of Electrical Engineering and Computer Science FayettevilleAR United States

ISBN: (纸本)9798350376067

This paper presents a modular solid state transformer (SST) design incorporating dual active bridge and cascaded H-Bridge topologies to enhance electric vehicle (EV) charging infrastructure. By using modular design concept for the power cell hardware, the proposed SST can be suitable for industrial usage with low manufacturing cost, and low maintenance complexity. With various combinations of the power cells, the whole SST converter has high flexibility for the power scale and circuit topology. This guarantees the fast installation and high transportability of the SST, suitable for the high-demanded EV charging applications. The design detail of the busbar used for the SST has been presented, which shows how to reduce the stray inductance of the busbar while keeping its high current conduction ability and high insulation. To validate the high current conduction ability of the busbar, finite element analysis is conducted to assess busbar current density and temperature. Finally, an advanced control strategy is introduced to effectively reduce DC link ripple, eliminating the need for bulky components. © 2024 IEEE.

关键词： Busbars

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Weighted butterfly optimization algorithm with intuitionistic fuzzy Gaussian function based adaptive-neuro fuzzy inference system for covid-19 prediction

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Materials Today: Proceedings 2022年 56卷 3317-3324页

作者： Sundaravadivel, T. Mahalakshmi, V. Dept. of Computer Science and Engineering Annamalai University Tamil Nadu India

Covid-19 cases are increasing each day, however none of the countries successfully came up with a proper approved vaccine. Studies suggest that the virus enters the body causing a respiratory infection post contact with a disease. Measures like screening and early diagnosis contribute towards the management of COVID- 19 thereby reducing the load of health care systems. Recent studies have provided promising methods that will be applicable for the current pandemic situation. The previous system designed a various Machine Learning (ML) algorithms such as Decision Tree (DT), Random Forest (RF), XGBoost, Gradient Boosting Machine (GBM) and Support Vector Machine (SVM) for predicting COVID-19 disease with symptoms. However, it does not produce satisfactory results in terms of true positive rate. And also, better optimization methods are required to enhance the precision rate with minimum execution time. To solve this problem the proposed system designed a Weighted Butterfly Optimization Algorithm (WBOA) with Intuitionistic fuzzy Gaussian function based Adaptive-Neuro Fuzzy Inference System (IFGF-ANFIS) classifier for predicting the magnitude of COVID- 19 disease. The principle aim of this method is to design an algorithm that could predict and assess the COVID-19 parameters. Initially, the dataset regarding COVID-19 is taken as an input and preprocessed. The parameters included are age, sex, history of fever, travel history, presence of cough and lung infection. Then the optimal features are selected by using Weighted Butterfly Optimization Algorithm (WBOA) to improve the classification accuracy. Based on the selected features, an Intuitionistic fuzzy Gaussian function based Adaptive-Neuro Fuzzy Inference System (IFGF-ANFIS) classifier is utilized for classifying the people having infection possibility. The studies conducted on this proposed system indicates that it is capable of producing better results than the other systems especially in terms of accuracy, precision,

关键词： COVID-19

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Wormhole Attack Detection in the Internet of Things using a Hybrid Deep Learning Model 3

Wormhole Attack Detection in the Internet of Things using a ...

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3rd International Conference on Intelligent data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Geo Francis, E. Sheeja, S. Antony John, E.F. Joseph, Jismy Dept. of Computer Science Karpagam Academy of Higher Education Tamil Nadu Coimbatore India Dept. of Data Science Sri Krishna Adithya College of Arts and Science Tamil Nadu Coimbatore India Kerala Thrissur India Kerala Mala India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527549

Internet growth has led to widespread adoption and transmission of the IoT in numerous areas. From personal networks to industrial applications, healthcare to transportation, IoT is everywhere. Due to their widespread usage, attackers deploy sophisticated methods and software to infiltrate IoT networks. IoT devices' low processing power and resources can threaten security and privacy. This vulnerability has inspired attackers to undertake a variety of attacks against IoT networks. Wormhole attacks (WHA) are routing attacks which can interrupt IoT network packet routing and flow. To address the security issues related to IoT devices, a novel hybrid deep Learning (DL) method is proposed to classify potential security risks in IoT circumstances. The proposed module combines the Bidirectional Long Short-Term Memory with attention mechanism (ABS-BiLSTM) and AlexNet CNN to achieve higher detection accuracy. The security service provided by the proposed monitoring solution ensures compatibility among various IoT network communication protocols. The results clearly show that the effectiveness and excellence of the schemes in terms of network performance, accuracy, and detection speed enhancement. © 2025 IEEE.

关键词： Network intrusion

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Classification of Mental Workload Using 1D-CNN with Transfer Learning 1

Classification of Mental Workload Using 1D-CNN with Transfer...

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1st International Conference on Pioneering Developments in computer science and Digital Technologies, IC2SDT 2024

作者： Chaturvedi, Sushil Ahirwal, Mitul Kumar Maulana Azad National Institute of Technology Dept. of Computer Science and Engineering Bhopal India

ISBN: (纸本)9798350365016

Mental workload (MWL) can be explained as the ratio of a participant's mental effort to their brain capability when performing activities. A significant challenge in the field of MWL classification for brain-computer interfaces (BCIs) based on electroencephalograms (EEGs) is the variability among individuals. It commonly takes unnecessary time to retrain the classification model from starting for a new subject. To address the individual variations among different subjects, a one-dimensional convolutional neural network along with transfer learning (1D CNN-TL) is proposed in this work. The end-to-end 1D-CNN learns the common features of EEG signals and, to tackle the problem of difference in EEG for individuals, a transfer learning technique is used that does fine-tuning on fully connected (FC) layers for a new participant having less training data. The average test accuracy (mean±stdv) of 65.18± 8.37 is achieved over the Cross-session mental workload dataset. The suggested method can achieve satisfying results for new unknown data with less time and fewer training data. © 2024 IEEE.

关键词： Convolutional neural networks

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An Empirical Study of Precision Agriculture

An Empirical Study of Precision Agriculture

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2024 IEEE Students Conference on engineering and Systems, SCES 2024

作者： Tirumalasetti, Gnana Kartheek Kandula, Ajay Kumar Shaik, Abdul Basheer Yendluri, Baladithya Kalluri, Hemantha Kumar SRM University AP Dept. of Computer Science Engineering Andhra Pradesh Vijayawada India

ISBN: (纸本)9798350374711

The demand for food production has led to advancements in precision agriculture, aiming to enhance crop yield and quality. This study investigates the application of deep learning algorithms, including GoogLeNet, RESNET-50, MobileNet-v2, VGG-16, and ShuffleNet, for automated plant disease detection. The research utilizes a dataset comprising images of citrus diseases to train and evaluate the models. Results show promising accuracy rates, highlighting the potential of deep learning in optimizing resource utilization and facilitating timely interventions in agriculture. © 2024 IEEE.

关键词： Citrus diseases Deep learning Image classification Plant disease detection Precision agriculture

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Futuristics Technologies for Reduction of Plastic Waste 13

Futuristics Technologies for Reduction of Plastic Waste

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13th International Conference on System Modeling and Advancement in Research Trends, SMART 2024

作者： Dhiman, Riya Sharma, Ashish Chandigarh University Dept. of Computer Science Mohali India Chandigarh University Dept. of Electrical Engineering Mohali India

ISBN: (纸本)9798350380583

Plastic plays a vital role in daily life most of the food items, Baggies, vegetables are packed in plastic material. As plastic is non-biodegradable there are harming effect on human beings and animals. Due to these global warming also increases. Although 80% Fishes, 88% Vertebrates, 56% Mammals and 52% Reptiles are affected due to plastic waste. In this work with the various techniques proposed like Eco-bricks, Furniture, Replace Plastic By Bamboo and also Doormats are made through the Plastic Waste. It is seen that by using above techniques significantly reduce the harmful effect of plastic and there is improvement in life of human beings and animals also the alternative techniques to reuse the plastic and to replace plastic are proposed with which there is a increase in the earning of poor peoples. Above techniques are helpful to decrease the employment and also by using these techniques more than 60% of plastic reuse, with this the temperature is also decreased. © 2024 IEEE.

关键词： Invertebrates

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Optimization of ARIA Block Cipher Implementation on RISC-V Systems through Instruction Extension 10

Optimization of ARIA Block Cipher Implementation on RISC-V S...

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10th International Conference on Platform Technology and Service, PlatCon 2024

作者： Yun, Dongwook Iqbal, Muhammad Kim, Howon Dept. of Computer Science&Engineering Pusan National University Busan Korea Republic of

ISBN: (纸本)9798350367874

Cryptographic modules in Internet of Things (IoT) devices have had limited use, primarily to meet key requirements such as efficiency and lightweight. However, as IoT devices fulfill more complex roles and handle sensitive information, the need for efficient and lightweight cryptographic modules is increasing. However, traditional software- or hardware-based implementations to provide cryptographic modules result in a tradeoff between efficiency and lightweight. The emergence of the RISC-V architecture presents a new strategy to unify these distinct implementation approaches. RISC-V provides a modular Instruction Set Architecture (ISA) and support for user-extended instructions to enable the configuration of optimal system architectures. Therefore, a new cryptographic algorithm implementation method that integrates existing implementation methods can be presented. This paper presents various strategies for implementing ARIA block cipher, a Korean standard cryptographic algorithm, on a lightweight RISC-V system. © 2024 IEEE.

关键词： Cryptography

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DriveQ: A Dedicated Vehicle-to-Vehicle Communication System for Enhancing Road Safety and Traffic Management

DriveQ: A Dedicated Vehicle-to-Vehicle Communication System ...

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2024 International Conference on E-Mobility, Power Control and Smart Systems, ICEMPS 2024

作者： Sunil, K.S. Biju, Alan Aiswarya Arun, G. Joy, Prince V. Rathul Krishnan, R. Government Engineering College Dept. of Computer Science & Engg. Kerala Idukki India

ISBN: (纸本)9798350394399

Modern urban transportation systems confront significant challenges, including escalating traffic congestion, accidents, and inefficient traffic management. One critical aspect contributing to these issues is the limited means of communication between vehicles, which represents a missed opportunity to en-hance road safety and traffic efficiency. To address these concerns and facilitate smarter transportation solutions, there's a need for an efficient, standardized, and secure Vehicle-to-Vehicle (V2V) communication system capable of seamlessly sharing real-time data between vehicles. DriveQ mainly focuses on implementing a dedicated V2V communication system that enhances road safety and traffic management. V2V communication technology is a revolutionary development that depends on Dedicated Short-Range Communication (DSRC), a specialized communication method enabling vehicles to exchange critical information such as location, speed, and status in real-time. In addition to providing exceptionally low latency communication, DSRC is essential for broadcasting messages that improve road safety by facilitating quick and easy communication between vehicles. The system allows users to view and share real-time data and allows us to connect with nearby vehicles within a specific range. With the help of this function, drivers can take preventative measures to keep themselves safe. DriveQ has a broad range of applications including Stop Sign Movement Assistance, Forward Collision Warning, Pre-Crash Warning, and Curve Speed Warning. © 2024 IEEE.

关键词： Vehicle to vehicle communications

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