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3rd Odisha International Conference on Electrical Power engineering, Communication and Computing technology, ODICON 2024

作者： Ramya Manaswi, V. Saketh, Meduri Ravi Tejha, Mandumula Sai Karthikeya, Atluri Sai Prakash, Dharani Chandra Alkhayyat, Ahmad Gokaraju Rangaraju Institute of Engineering and Technology Dept. of Computer Science Engineering Hyderabad India Gitam University Dept. of Computer Science Engineering with Specialisation of Cybersecurity Hyderabad India K.G Reddy College of Engineering and Technology Dept. of Electronics & Communication Engineering Telangana Hyderabad India College of Technical Engineering The Islamic University Dept. of Computers Techniques Engineering Najaf Iraq

ISBN: (纸本)9798350354379

The JARVIS AI Support System represents a remarkable fusion of modern technology, blending a sophisticated GUI design, seamless voice control, and inventive features like the captivating 'Air Canvas' facilitated by OpenCV. This AI-driven virtual assistant offers users a natural and intuitive experience, allowing them to effortlessly perform tasks such as browsing the web, interacting with a chatbot, and executing dynamic voice- controlled actions. Moreover, the system showcases advanced capabilities including motion detection and facial recognition with an accuracy of 95% in multiple runs. Leveraging the power of computer vision, the Air Canvas feature empowers users to express creativity through fluid hand gestures, while voice commands effortlessly manage diverse tasks. This innovative project presents an approachable way to interact with technology in the world of AI. © 2024 IEEE.

关键词： Face recognition

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Slotted V Shaped Compact Wideband Antenna with Partial Ground Plane for Microwave Based Head Imaging Applications 6

Slotted V Shaped Compact Wideband Antenna with Partial Groun...

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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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Blockchain-Based Music Streaming Services: A Novel Approach to Transparent Artist Control 3

Blockchain-Based Music Streaming Services: A Novel Approach ...

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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Ashtagi, Rashmi Deshmukh, Tanmay Jadhav, Swati Bidwe, Ranjeet Akkalkot, Afsha Buchade, Amar Uke, Nilesh Banerjee, Sudipta Vishwakarma Institute of Technology Dept. of Computer Engineering Pune India Symbiosis Institute of Technology Dept. of Cse Pune India Coep Technological University Dept. Name of Computer Engineering Pune India Data Science Vishwakarma Institute Technology Dept. of Artificial Intelligence Pune India Indira College of Engineering and Management Pune India Symbiosis Institute of Technology Pune India

ISBN: (纸本)9798350354348

Artists have historically used music as a form of personal expression. However, due to the centralized nature of music streaming services, artists receive only a small percentage of the revenue generated and have no control over their content produced. To address these issues, a revolutionary technique is needed that provides artists with greater control and transparency over their output. This paper focuses on a decentralized strategy that utilizes blockchain technology to facilitate direct interaction between artists and users, enabling artists to upload their music, sell songs, and receive royalties. The implementation of blockchain technology could potentially revolutionize the music industry by ensuring that rightful owners receive payment for their music while reducing the waste of paying intermediaries. Without intermediaries involved in the distribution process, the music industry could pay out more royalties to rights holders automatically and instantaneously. The proposed solution also addresses piracy concerns through the use of encryption and watermarking techniques. Blockchains provide security, confidentiality, tamper-proofing, traceability, control, and oversight over information. By developing a secure, self-installing, cross-platform reader positioned on the header of the digital content file, The research empowers data owners to manage the flow of information even after it has been made available. The suggested approach enables content owners to control their digital content and monitor its most popular components after distribution. The blockchain-based system also benefits from token distribution among the content's owner, distributor, and consumer. The simulation results demonstrate that our approach is capable of overcoming the flaws of the existing system. © 2024 IEEE.

关键词： Blockchain

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Experimental Verification of Rotating Sliding Mode Control with Composite Reaching Law Approach for Voltage Source Inverters 21

Experimental Verification of Rotating Sliding Mode Control w...

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21st International Bhurban Conference on Applied Sciences and technology, IBCAST 2024

作者： Haroon, Faheem Waqar, Asad Aamir, Muhammad Abbas, Syed Hayder Ali, Syed Umaid Qaisar, Saeed Mian Bahria University Dept: Electrical Engineering Islamabad Pakistan Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology Dept: Electrical and Computer Engineering Haripur Pakistan Effat University Dept. Electrical and Computer Engineering Jeddah21478 Saudi Arabia

ISBN: (纸本)9798331516680

In modern power systems, power electronic interfaces like Voltage Source Inverters (VSIs) uses advanced control strategies to ensure high-quality voltage regulation, significantly enhancing system stability and reliability for various applications. This paper introduces a novel voltage regulation method for VSIs using Sliding Mode Control (SMC) under extreme load variations [1]. Besides robustness, SMC is prone to chattering, causing power losses, reduced efficiency, and compromised transient response. To address chattering, an adaptive sliding surface selection mechanism that utilizes the Rotating Sliding Surface (RSS) technique and a new reaching law based on state variable magnitudes, which dynamically adjusts the control gain is proposed here. This composite reaching law uses exponential, power, and difference functions to achieve rapid convergence and reduce chattering. The sliding surface is chosen with a time-varying slope based on error variables. Tests on a single-phase VSI with varying loads demonstrate that the C-ERL-RSS SMC achieves a well-regulated output voltage with just 0.25% THD, reduced chattering, and minimal tracking time. Additionally, implementing the C-ERL-RSS SMC and PRERL SMC on a two-level three-phase VSI under varying load conditions shows superior efficiency and stability, with a low THD of 1.1%. Experimental evaluation on MicroLabBox-dSPACE 1202 for VSIs under extreme conditions reveals that the proposed technique excels in voltage regulation, offering fast transient response and low THD of 1.12% and 2.1% for single-phase and three-phase VSIs, respectively. © 2024 IEEE.

关键词： Transient analysis

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Relating Muscle Activity and Mouse Sensitivity in FPS Game Players Using Surface EMG Signals 5

Relating Muscle Activity and Mouse Sensitivity in FPS Game P...

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5th International Conference on Biomedical engineering, IBIOMED 2024

作者： Prajapati, Vaibhav Turlapaty, Anish C. Sarma, Himangshu Ghorai, Mrinmoy Indian Institute of Information Technology Dept. of Electronics and Communication Engineering Sri City India Indian Institute of Information Technology Dept. of Computer Science and Engineering Sri City India

ISBN: (纸本)9798350389265

In the domain of first-person shooter (FPS) gaming, mouse sensitivity is crucial for performance. This paper presents an analysis showing the correlation between specific muscle activity and mouse movement. We analyzed mouse movements from twelve subjects with varying sensitivity levels. A new dataset electromyography analysis of human activity database 8 (EMAHA-DB8), is introduced which involved four mouse designs and two game modes: Medium (normal movement) and Hard (aggressive movement). Sensitivity settings were standardized using effective dots per inch (eDPI), calculated as Mouse DPI multiplied by in-game sensitivity. Hand muscle activity was measured using five Noraxon Ultium wireless surface electromyography (sEMG) sensors with Ag/AgCl electrodes. Various regression models, including Random Forest, Support Vector Regressor, K-Nearest Neighbors Regressor, MLP Regressor, and Gradient Boost Regressor, were used to predict eDPI from muscle movement patterns. Sequential feature selection identified the top ten features, highlighting the most significant muscles for predicting sensitivity. The results demonstrate that the Extensor Carpi Radialis (ECR) is the most active muscle, followed by the Extensor Digitorum (ED), while playing the chosen FPS game. These findings give insights for ergonomic and personalized equipment design to enhance gaming experience and performance. © 2024 IEEE.

关键词： Decision trees

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Deciphering Deceit: Multimodal Classification of Optimal Algorithms for Fake Website Detection 3

Deciphering Deceit: Multimodal Classification of Optimal Alg...

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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Thombre, Supriya Doifode, Vaibhaw Kokardekar, Sakshi Hasija, Udit Wazalwar, Sampada Yeshwantrao Chavan College of Engineering Dept. of Computer Technology Nagpur India Yeshwantrao Chavan College of Engineering Dept. of Electrical Engineering Nagpur India Kpit Technologies Limited Pune India Bhartiya Vidyapeeth College of Engineering Dept. of Computer Science and Engineering New Delhi India G.H. Raisoni College of Engineering Dept. of Information Technology Nagpur India

ISBN: (纸本)9798350354348

Detecting fake website URLs is crucial in today's digital era, where online scams and malicious/ fraudulent activities abound. Such websites pose a myriad of problems in the digital landscape, ranging from financial loss and identity theft to the dissemination of misinformation and the erosion of trust in online platforms. Individuals who fall victim to fraudulent websites may suffer financial repercussions, as they may unknowingly disclose confidential information such as details of credit card or login credentials. Moreover, fake websites can deceive users by spreading false information or promoting illegitimate products and services, which can undermine public trust in online sources and exacerbate societal issues such as misinformation and cybercrime. Therefore, there is a pressing need to detect fake websites promptly to mitigate these risks and protect users' privacy, financial security, and trust in the online environment. This study by the authors evaluates the predictive performance of five machine learning (ML) models - Random Forest (RF) Classifier, Decision Tree (DT)) Classifier, K-Neighbors (KN) Classifier, SGD Classifier and Gaussian NB (GNB) - in the reference of malicious and fake website URL detection. Leveraging a diverse dataset encompassing both benign and malicious URLs, our analysis encompasses rigorous evaluation metrics. The results highlight distinct strengths and weaknesses among the models, offering valuable insights for practitioners seeking to optimize predictive capabilities in the realm of cybersecurity. These findings contribute to the ongoing refinement of machine learning strategies for effective malicious URL detection and mitigation. © 2024 IEEE.

关键词： Phishing

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Development of Logical ERD for Automation of Performance Evaluation Data in Railway Facilities

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Transactions of the Korean Institute of Electrical Engineers 2023年第10期72卷 1244-1249页

作者： Oh, Wan-Shik Kwon, Jung-Yun Kim, Jong-Woon Dept. of Korea Railway Electrification Technology Association Korea Republic of Dept. of Computer and Multimedia Engineering Dongguk Univerity Korea Republic of Dept. of Industrial Engineering Pusan National Univerity Korea Republic of

A performance evaluation system for railroad facilities is being implemented to strengthen safety management and prepare for the continuous aging ofrailroad facilities. By developing a logical ERD (Entity Relationship Diagram) for the implementation of automated railroad facility performance evaluation, we aim to establish an efficient system to predict future performance changes and demands of railroad facilities, enabling timely maintenance and reinforcement of the infrastructure in an efficient manner. The logical ERD is structured with a detailed design applying evaluation method metrics. The evaluation results are calculated by multiplying the evaluation values and the weights of the evaluation items. The system allows for immediate evaluations for all equipment and sections of railway facilities, as well as for evaluation items without modifying the source, and it is designed to easily change the weights to facilitate evaluations. © 2023 Korean Institute of Electrical Engineers. All rights reserved.

关键词： Railroads

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W-Net Plus: Dnn for Spatial Saliency Prediction in Videos 1

W-Net Plus: Dnn for Spatial Saliency Prediction in Videos

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1st IEEE International Conference on Innovations in High Speed Communication and Signal Processing, IHCSP 2023

作者： Sharma, Gaurav Singh, Maheep Kumain, Sandeep Chand National Institute of Technology Dept. of Computer Science Engineering Srinagar India

ISBN: (纸本)9798350345957

Deep neural networks (DNNs) have been employed recently to identify saliency in images and videos. Different models have been suggested to predict spatiotemporal as well as temporal and spatial saliency. In this study, a model called W-net Plus is proposed for predicting spatial saliency in videos. The newly proposed model not only translates information from the encoder to the decoder but also from the decoder to the encoder, and it is inspired by U -net architecture. The proposed model has been evaluated by the author(s) on various data sets, and they have obtained noteworthy findings for the F - Max, structural similarity (S-measure), and Mean Absolute Error (MAE) measurement parameters, demonstrating its effectiveness and survivability. No stage of the training involves the utilization of transfer learning in the work. © 2023 IEEE.

关键词： Deep neural networks

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Enhancing Siamese Neural Network Performance with Custom Local Binary Patterns for Face Matching 8

Enhancing Siamese Neural Network Performance with Custom Loc...

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8th IEEE International Conference on Information and Communication technology, CICT 2024

作者： Koranga, Pawan Singh Indian Institute of Technology Kharagpur Dept. of Computer Science and Engineering Kharagpur India School of Computer Sciences Upes Dehradun248001 India

ISBN: (纸本)9798331531539

In this study, we investigate the efficacy of incorporating custom local binary patterns (LBP) as a preprocessing technique to enhance the performance of Siamese neural networks for face matching tasks. Our research focuses on training Siamese models using the DC Face dataset and comparing their performance when trained with and without LBP integration. The custom LBP function is designed to capture fine-grained texture details from facial images, providing robust feature representations that are invariant to variations in lighting conditions and facial expressions. Through rigorous experimentation and evaluation, we analyze the impact of LBP on the threshold point for image differentiation and compare the matching accuracy of Siamese models trained with and without LBP. Our findings reveal significant improvements in matching accuracy and robustness when utilizing the texture features extracted by the custom LBP function. By encoding local pixel structures and capturing subtle facial characteristics, LBP-enhanced Siamese models demonstrate enhanced performance in accurately matching faces across different images. Further-more, our study highlights the importance of using domain-specific preprocessing techniques, such as LBP, to optimize the capabilities of Siamese neural networks for face matching tasks. The results underscore the effectiveness of customizing feature extraction methods to suit the characteristics of the dataset, leading to improved matching accuracy and robustness. Overall, our research contributes valuable insights into the role of LBP in enhancing the performance of Siamese neural networks for image-based similarity tasks, with implications for various real-world applications in face recognition and biometric authentication. © 2024 IEEE.

关键词： Local binary pattern

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Breast Cancer Prediction Using Artificial Intelligence technology 4

Breast Cancer Prediction Using Artificial Intelligence Techn...

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4th International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Akila, V. Christaline, J. Anita Srm Institute of Science and Technology Vadapalani Dept. of Electronics and Communication Engineering Chennai India Vellore Institute of Technology School of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350343670

The aim of the project is to compare the performance of four different machine learning algorithms for breast cancer prediction such as decision tree, logistic regression, XG boost, and CAT boost. We used a dataset of patient medical records containing various clinical factors to train and test the algorithms. Accurate diagnosis and early detection are essential for enhancing patient outcomes. Data mining is a prominent tool in the healthcare industry for processing massive amounts of data. To examine massive amounts of complicated medical data, researchers use a variety of data mining and machine learning approaches. The use of these strategies can help medical practitioners forecast the onset of breast cancer. © 2024 IEEE.

关键词： Algorithms Breast cancer Data mining Machine Learning

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