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2024 International Conference on Advances in Modern Age Technologies for Health and engineering Science, AMATHE 2024

作者： Gracia, R. Lillian Priyadharsini, C. Caroline, B.Elizabeth Karunya Institute Of Technology And Sciences Division Of Computer Science And Engineering Coimbatore India Ifet College Of Engineering Division Of Electronics And Communication Engineering Villupuram India

ISBN: (纸本)9798350371567

The dust collection on solar panels situated in solar parks is a common problem faced by PV system operators, particularly in arid and dusty regions. Dust deposition reduces the transparency of the panel surface, leading to decreased sunlight absorption and thus reduced energy conversion efficiency. Traditional methods for detecting dust accumulation involve manual inspection or periodic cleaning schedules, both of which are labor-intensive, time-consuming, and often inefficient. Recent developments in deep learning and machine vision have made autonomous dust detection techniquesfeasible. Numerous techniques have been employed to identify and measure dust on solar panels, such as machine learning models and image processing algorithms. In this paper, the dataset of clean and dusty images of the solar panels utilized wasapplied to four state of the art models and then the EfficientnetB0 model was proposed to detect the dust over the solar panels. On comparing the EfficientnetB0 model with the other state of the art models, EfficientnetB0 yielded an impressive accuracy rate of approximately 85.92%. Further research and development in this field hold the potential to revolutionize the maintenance and operation of solar power plants, contributing to a greener and more sustainable future. © 2024 IEEE.

关键词： Solar panels

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Adaptive Intrusion Detection in Cyber-Physical Systems using Reinforcement Learning-Based Autoencoders 2

Adaptive Intrusion Detection in Cyber-Physical Systems using...

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2nd IEEE International Conference on Integrated Intelligence and Communication Systems, ICIICS 2024

作者： Rajathi, N. Divya, S. Anitha Elavarasi, S. Saritha, G. Jeya ramya, V. Department of Information Technology Kumaraguru College of Technology Coimbatore India Department of Computer Science and Business System Bannari Amman Institute of Technology Erode India Department of Computer Science and Engineering Sona College of Technology Salem India Department of Electronics and Communication Engineering Sri Sai Ram Institute of Technology Chennai India Department of Electronics and Communication Engineering Panimalar Engineering College Chennai India

ISBN: (纸本)9798331504960

The increasing integration of Cyber-Physical Systems (CPS) in critical infrastructure presents unique challenges for ensuring robust cybersecurity. Traditional Intrusion Detection Systems (IDS) often struggle with the dynamic, complex nature of CPS environments, making adaptive solutions essential. This paper presents an Adaptive Intrusion Detection System (AIDS) that leverages Reinforcement Learning-Based Autoencoders (RL-AE) to detect and respond to cyber intrusions in CPS environments. The proposed model combines the power of autoencoders for unsupervised anomaly detection with reinforcement learning to continuously adapt and improve detection accuracy. Experimental results on benchmark CPS datasets demonstrate that the RL-AE-based IDS achieves a detection accuracy of 98.3%, a precision rate of 96.8%, and a recall rate of 97.5%, effectively minimizing false positives to 2.4%. The system also demonstrated rapid adaptability, with a convergence time of less than 50 iterations in response to new attack patterns. These results highlight the model's ability to enhance system resilience and promote secure and efficient CPS operations in industrial and critical infrastructure applications. This approach provides a scalable and flexible IDS solution, promoting secure and resilient CPS operations in real-time, high-stakes environments. © 2024 IEEE.

关键词： Network intrusion

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Circadian Effect on Luminance Contrast Sensitivity

Transactions of Japanese Society for Medical and Biological ...

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Transactions of Japanese Society for Medical and Biological engineering 2022年第6期60卷 158-163页

作者： Yoshikawa, Mayu Nagai, Midori Koida, Kowa Department of Electronics Engineering College of Engineering National Institute of Technology Tokyo College Japan Electronics-Inspired Interdisciplinary Research Institute Toyohashi University of Technology Japan Department of Computer Science and Engineering Toyohashi University of Technology Japan

All biological functions, including vision, areaffected by timeof day. It is known that theretinal response to visual stimuli changes according to circadian rhythms. However, the effects on visually guided behavior were poorly understood, and previous results have been inconsistent. The previous studies examined the effect of time on contrast sensitivity were also inconsistent, one reason for this could be the order effects, such as fatigue due to long measurement times. To overcome this issue, we applied a tablet PC based measurement system which made the measuring contrast sensitivity quick and easy. Observers participated in the experiment every morning, noon, evening, and night, and performed a task to detect a Gabor patch. The results showed that sensitivity improved from morning to night, and this trend was more pronounced in the mid-to high-frequency band. The improvement was reproduced even when measurements were taken once daily at random times. These results suggest that the improvement was not due to intraday learning or fatigue. We confirmed that our experimental system is useful for measuring the diurnal variation in contrast sensitivity, as it is quick and easy to use. © 2022, Japan Soc. of Med. electronics and Biol. engineering. All rights reserved.

关键词： Fatigue of materials

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Development of an Application for Detecting Lung Cancer Using Machine Learning

Development of an Application for Detecting Lung Cancer Usin...

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2024 International Conference on Cybernation and Computation, CYBERCOM 2024

作者： Marathe, Abha Makadi, Sahil Meshram, Pratik Mahulkar, Amey Maurya, Ayush Mhaske, Krishna Vishwakarma Institute of Technology Department of Electronics and Telecommunication Engineering Pune India Vishwakarma Institute of Technology Department of Computer Science Pune India

ISBN: (纸本)9798331542344

Lung cancer continues to be a major contributor to cancer-related deaths globally, making it necessary to bring improvements in reliable and accurate detection methods. This study discusses lung cancer detection which uses an open source dataset about patient and 4 ML algorithms-Random Forest (RF), Support Vector Machines (SVM), Decision Tree (DT), and Logistic Regression (LR). To reduce the bias data shuffling was performed initially to randomize the order of tuples. Categorical variables changed to numerical variables with use of factorization for accurate algorithmic processing. Feature selection techniques like Mean Decrease in Impurity (MDI), Recursive Feature Elimination (RFE), and Random Forest Mean Decrease (RFMD) were used to reduce computation load without compromising performance. The study deeply evaluates model performance on the basis of sensitivity, specificity, accuracy, and detection rate. Among the algorithms, RF demonstrated superior accuracy when combined with the selected features. Visualizations using importance scores and confusion matrices provided deeper insights into the models, which aids in interpreting the findings. Finally, an app was developed with selected 8 features and RF to predict the lung cancer. This research demonstrates the vital role of ML in lung cancer diagnosis and its potential of early detection and treatment. The findings of research contributed in advancing the healthcare and addresses the global challenges of lung cancer. © 2024 IEEE.

关键词： Lung cancer

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Design and Implementation of a Decentralized Voting System Using Volta Blockchain 5

Design and Implementation of a Decentralized Voting System U...

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5th IEEE International Women in technology Conference, WINTECHCON 2024

作者： Arthi, M. Suganthi Evangeline, C. Bharadwaj, Rohit Avrit, M. Jaswant, Gogineni Siranjeevi, G.P. School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Electronics and Communication Engineering Sri Eshwar College of Engineering Coimbatore India

ISBN: (纸本)9798350374070

The drive for secure, open, and easily accessible voting systems has spurred the advance of decentralized blockchain-powered voting systems. This paper outlines the design and implementation of a decentralized voting system that utilizes the Hardhat Ether for testing and deployment, the Volta blockchain, Solidity smart contracts, and MetaMask for user interaction. Our approach ensures the confidentiality and integrity of votes by harnessing the irreversible and transparent properties of blockchain technology, enabling participation from any location with internet connectivity. Users can safely cast their ballots straight from their web browsers thanks to the inclusion of MetaMask, improving accessibility and usability. Furthermore, the application of Hardhat Ether simplifies the development process, enabling reliable deployment and testing protocols. This paper discusses the architecture, functionality, and security considerations of our decentralized voting system, highlighting its potential to revolutionize democratic processes worldwide. © 2024 IEEE.

关键词： Voting machines

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Virtual Twin Analytics: Advancing IoT Security through AI-Powered Software Informatics 1

Virtual Twin Analytics: Advancing IoT Security through AI-Po...

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1st International Conference on Software, Systems and Information technology, SSITCON 2024

作者： Nanthini, S. Jain, Upma Arora, Renuka Bhatia, Rishu Sutaria, Kruti Patil, Harshal Saveetha School of Engineering Department of Computer Science and Engineering Chennai India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Jagannath University Department of Computer Science and Engineering Haryana India Ganga Institute of Technology and Management Department of Electronics and Communication Engineering Haryana India Parul Institute of Engineering and Technology Faculty of Engineering and Technology Gujarat India School of Computer Science and Engineering Uttar Pradesh India

ISBN: (纸本)9798350352931

The Internet has grown in importance and impact over the years, causing people to become more reliant on it. The Internet has evolved into a major vector for cybercrime because to its ever-increasing user base. Over the last decade, the number of these computing systems - including desktops, laptops, smartphones, and the Internet of Things (IoT) - has skyrocketed. Among them, cell phones are practically integral to modern life. The popularity of web-based assaults has skyrocketed with the exponential growth in the number of individuals using the Internet. These web-based assaults are increasingly being combatted by security corporations. Unfortunately, new forms of these assaults are appearing all the time, making it hard for older security measures to stay up. Artificial intelligence (AI) is a source of optimism in the current cybersecurity landscape, offering a potential solution to the ever-changing digital dangers. The fast development of AI over the last decade has given rise to this optimism, because it is now impacting the expansion of every industry. With AI bringing so many advantages in every field, online security is one sector that just cannot afford to ignore it. This planned effort's work represents an advance in that direction. Critical online security issues have been the focus of this proposed work's study, which aims to address these issues using AI. Web security issues for desktop and mobile devices have been addressed in the proposed work. The planned work's contributions to online security are as follows: The 'MalCrawler' web crawler is a targeted tool for finding and exploring the web. This crawler makes it easy to gather websites, particularly ones that are harmful. It does a better job of collecting dangerous websites than a typical crawler. Additionally, it is built to circumvent the evasion strategies used by rogue websites. The crawler's ability to gather webpages - particularly dangerous ones - in order to provide datasets for ML-based an

关键词： Web crawler

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Comparative Analysis of Execution of CNN-Based Sanguine Data Transmission with LSB-SS and PVD-SS

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computer Systems Science & engineering 2023年第8期46卷 1707-1721页

作者： Alaknanda S.Patil G.Sundari Arun Kumar Sivaraman Department of Electronics and Communication Sathyabama Institute of Science and TechnologyChennaiTamil Nadu600119India School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India

The intact data transmission to the authentic user is becoming crucial at every moment in the current ***;is a technique for concealing the hidden message in any cover media such as image,video;and audio to increase the protection of *** resilience and imperceptibility are improved by choosing an appropriate embedding *** paper gives a novel system to immerse the secret information in different videos with different *** audio and video steganography with novel amalgamations are implemented to immerse the confidential auditory information and the authentic user’s face image.A hidden message is first included in the audio from the multimedia file;using LSB *** Stego-video is created in the second stage by merging the authorized user’s face into the frame of the video;by using PVD ***-audio is linked again with the stego-video in the third *** incorporated perspective techniques(LSB-SS and PVD-SS algorithms)with more significant data immersing capacity,good robustness and imperceptibility are proposed in this research *** spread spectrum approach is used to increase the complexity of secret data *** different video files are tested with different voice files with the results such as PSNR,SSIM,RMSE and MSE as 52.3,0.9963,0.0024 and 0.0000059,respectively.

关键词： Audio steganography data hiding information security pixel value differencing

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A Terse Review of Heart Diseases Estimation Using Machine Learning Practices

A Terse Review of Heart Diseases Estimation Using Machine Le...

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2024 International Conference on Communication, computer Sciences and engineering, IC3SE 2024

作者： Pawar, Rahul Dash, Amit Kumar Mittal, Gaurav Department Of Computer Science And Information Technology Bangalore India Noida Institute Of Engineering And Technology Department Of Electronical & Electronics Engineering Uttar Pradesh Greater Noida India Tula's Institute Department Of Computer Science And Engineering Dehradun India

ISBN: (纸本)9798350366846

Heart diseases, a primary cause of global fatalities, represent a growing social matter on a worldwide scale. The integration of machine learning with advancing technology has greatly benefited the medical field, resulting in the provision of seamless solutions characterized by high accuracy, consistency and toughness. These advancements help the patient society through early detection and reduced medical care costs. They also offer the medical fraternity capable, accessible, precise and consistent prediction systems. This paper provides a comprehensive enquiry of machine learning algorithms engaged for the prediction and classification of several cardiovascular diseases, we explore several modalities, including physiological signals, heart sounds and electronic health records, to achieve effective heart disease recognition. We also provide insights into popular machine learning systems, hybrid systems and fuzzy systems in this context. It is noted in this review that Support Vector Machines (SVM) have gained popularity and widespread usage, with neural networks and ensemble techniques following closely behind in terms of their application. All these approaches are compared based on accuracy metrics. © 2024 IEEE.

关键词： Hybrid systems

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A Modified Hexagonal Shaped Sub-6 GHz 5G Antenna in MIMO Configuration

A Modified Hexagonal Shaped Sub-6 GHz 5G Antenna in MIMO Con...

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2024 IEEE Microwaves, Antennas, and Propagation Conference, MAPCON 2024

作者： Porwal, Rahul Garg, Rahul Kumar Raj, Nikhil Nair, M.V. Deepak Department of Electronics and Communication Engineering The LNM Institute of Information Technology Jaipur India Department of Computer Science and Engineering University of Engineering and Management Jaipur India

ISBN: (纸本)9798350379693

A line-fed Modified Hexagon shaped 2-port planar antenna is presented for 5G application. The MIMO antenna is designed through combining the techniques of a modifying the radiator and defected ground structure. In the MIMO configuration, two replicas of the MIMO element are arranged orthogonal to ensure the pattern diversity. A cross shaped structure is integrated with the ground to enhance interelement isolation. The size and operating bandwidth of the MIMO antenna are 28×56 mm2 and 2.54 GHz to 5.46 GHz, respectively. This design advantageously offers a wide -15 dB bandwidth from 3.3 GHz to 5.0 GHz with a percentage bandwidth of 40.96% and a peak realized gain of 3.1 dBi at 3.3 GHz. Maximum isolation value of 33.55 dB is achieved while it is never less than 16.85 dB for the frequency of interest. The envelope correlation coefficient (ECC) © 2024 IEEE.

关键词： 5G mobile communication systems

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Analysis of Rain Visibility Attenuation on Free Space Optics (FSO) for South African Weather Conditions 4

Analysis of Rain Visibility Attenuation on Free Space Optics...

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4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Mahlobogwane, Zanele Mukubwa, Emmanuel Pillay, Nelendran Tshwane University of Technology Department of Computer Systems Engineering Pretoria South Africa Moi University KipKenya Department of Electrical and Communications Engineering Cheptiret Kenya Durban University of Technology Department of Electronics and Computer Engineering Durban South Africa

ISBN: (纸本)9798350395914

The Free Space Optics (FSO) is a high-speed connectivity system that has the same advantages of speed and bandwidth as that of optic fiber. In comparison to optic fiber, FSO is the preferred choice when it comes to cost and deployment period. However, one of the main challenges with FSO is the changing weather conditions that affect the signal since the transmitted signal is radiated through the atmosphere. This investigation focuses on examining the variables that influence the reduction of visibility at different wavelengths: 750nm, 780nm, 850nm, and 1550nm. The locations of interest concerning visibility and rain data are Pretoria, Upington, Bloemfontein, and Cape Town in the Republic of South Africa. Results indicate that fog attenuates the signal more when compared to rain. Furthermore, signals transmitted at 1550nm will attenuate the signal less when compared to the other wavelengths of interest. © 2024 IEEE.

关键词： Rain

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