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2nd International Conference on Edge Computing and Applications, ICECAA 2023

作者： Ramanan, K. Vashali, S. Nanthini, S. Thaqfeen, M. Hifaya Sivaraja, P.M. Maheswari, G. Uma Npr College of Engineering and Technology Department of Computer Science Engineering TamilNadu India Amrita College of Engineering Department of Computer Science Engineering TamilNadu India Rmk College of Engineering and Technology Department of Computer Science Engineering TamilNadu Chennai India

ISBN: (纸本)9798350347579

In a time when LPG is increasingly used as a fuel source for factories, houses, and cars, any accidental releases would have devastating consequences. Detectors for LPG leaks should be placed in potentially hazardous places as a precaution. Therefore, the purpose of this study is to develop an LPG leak detection and reaction system using a microcontroller. The MQ-6 gas sensor is used to detect leaks, and the user is notified by GSM-based text message and an audible alarm. LPG supply was cut off to reduce waste and avoid mishaps, which was a primary function of the system. This was accomplished by consulting datasheets while deciding which components to include in the circuit design, and by running simulations of the circuit in Proteus to check its viability. When the amount of LPG in the air reaches a certain level, the system sends a text message to a user-specified cell phone number stored in the microcontroller and concurrently triggers the warning buzzer and displays the data on an LCD. The LPG supply may be cut off by sending a signal to the solenoid valve. This setup notifies you of a gas leak and immediately cuts off the gas supply, so you don't waste any fuel and don't risk any mishaps. LPG vendors and consumers alike will benefit greatly from this approach. © 2023 IEEE.

关键词： Microcontrollers

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Scalable SubXPCA on a Distributed Platform Applied to Classification of Hyperspectral Images 8

Scalable SubXPCA on a Distributed Platform Applied to Classi...

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

作者： Rupa, Bogolu Negi, Atul School of Computer and Information Sciences University of Hyderabad India Vardhaman College of Engineering Department of Computer Science and Engineering Telangana Hyderabad India

ISBN: (纸本)9798331531539

The exponential growth of technological advancements in satellite and airborne remote sensing is giving rise to large volumes of high-dimensional hyperspectral image data. Apache Spark is one of the most popular, extensively used and open-source distributed processing frameworks, which is proven effective in processing large volumes of remotely sensed hyperspectral images in a time-efficient manner. Open-source distributed processing frameworks have proven effective in processing large volumes of remotely sensed hyperspectral images quickly and efficiently. While computational power has been increasing, the rate of data accumulation is more than the processing capabilities. Therefore, more efficient algorithms such as dimensionality reduction are needed to process and get accurate performance for the application. This paper proposes an efficient and parallel spectral dimensionality reduction approach based on feature partitioning principal component analysis called scalable SubXPCA. We implemented scalable SubXPCA on a spark cluster distributed environment. We compared scalable SubXPCA against other distributed feature partitioning and various non-feature partitioning dimensionality reduction methods. Our experiments on different real and synthetic datasets of hyperspectral images confirm that SubXPCA classification performance is not only better than its competitors but also that the running time of SubXPCA is better in distributed processing than serial processing. As the size of the hyperspectral image dataset increased, SubXPCA showed a speed up factor of 5.7× and more in the spark cluster compared to the serial version. © 2024 IEEE.

关键词： Dimensionality reduction

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Novel Approach to Image Similarity Estimation and Object Matching: Leveraging ViT Architecture and Euclidean Distance Metric 20

Novel Approach to Image Similarity Estimation and Object Mat...

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

作者： Ardehkhani, Pegah Ardehkhani, Pouya Hooshmand, Haniyeh Sharif University of Technology Department of Industrial Engineering Tehran Iran Faculty of Engineering University of Tehran Deep Learning Research Lab Department of Computer Engineering Tehran Iran Faculty of Engineering University of Tehran Department of Computer Engineering Tehran Iran

ISBN: (纸本)9798350383942

In addressing the challenge of image similarity estimation on the MNIST dataset, our research drives from conventional Siamese network methodologies by incorporating Vision Transformer (ViT) architecture. Departing from the standard MNIST dataset, we introduced a novel paired dataset tailored to enhance the capabilities of similarity estimation. The innovation lies in the utilization of ViT as the core foundation for extracting features, followed by the application of Euclidean distance metrics on the dual input. This departure from the traditional approach not only broadens the scope of image similarity assessment but also enhances the model's discriminative power. Notably, the model attains a commendable test accuracy of 97.14% with a patch size of 7, underscoring the efficacy of our proposed methodology. This work it not only adds to the changing scenery of the image similarity estimation while also emphasizing the importance of leveraging non-conventional architectures to achieve enhanced performance in this domain. © 2024 IEEE.

关键词： Deep learning

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LIoT-Enabled Smart Wearables for Improved Visual Impairment Navigation

LIoT-Enabled Smart Wearables for Improved Visual Impairment ...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Yeole, Prasad Labade, Yash Wabale, Nikhil Patil, Rahul Wagh, Siddhant William, P. Sanjivani College of Engineering Department of Computer Engineering India Research and Development at Sanjivani College of Engineering India

ISBN: (纸本)9798350369106

This study introduces a novel Internet of Things (IoT) assistive technology designed to increase the mobility and self-sufficiency of visually impaired people. Over 40 million individuals, including over 1.6 million children, are visually impaired in India, and getting around in daily life is still exceedingly difficult. Walking canes and other traditional aids are not always effective in identifying hazards at different heights and angles. The suggested system integrates smart shoes and spectacles with buzzers, microcontrollers, and ultrasonic sensors. The smart glasses recognise obstructions at head height by extending detection beyond the level of the shoes, which continuously monitors the ground for obstacles. The system ensures better spatial awareness by alerting users in real-time with audio when an obstacle is spotted. The IoT-enabled communication between shoes and smart glasses is a significant innovation since it enables synchronized obstacle identification and reaction. With its all-encompassing coverage, this integrated strategy enhances user mobility and safety. The system is lightweight, ergonomically sound, dependable, and made for everyday use. Future additional improvements might include GPS integration for accurate navigation and machine learning for anticipatory obstacle identification. This study demonstrates how people with visual impairments can live much better thanks to wearable Internet of Things devices. © 2024 IEEE.

关键词： Assistive technology

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Predicting the Power Spectrum of Amplified OFDM Signals Using Higher-Order Intercept Points

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Chinese Journal of Electronics 2022年第2期31卷 213-219页

作者： YAN Siyuan YANG Xianzhen WANG Xiaoru LI Fu Department of Electrical and Computer Engineering Portland State University School of Computer Science and Technology Beijing University of Posts and Telecommunications

Orthogonal frequency-division multiplexing(OFDM) has been developed into a popular modulation scheme for wireless communication systems, used in applications such as LTE and 5 G. In wireless communication systems, nonlinearity caused by radio frequency(RF)amplifiers will generate distortions to both passband and adjacent channels such that the transmission quality is degraded. The study of this article aims to predict the power spectrum for OFDM based signals at the output of an RF amplifier due to the nonlinearity. In this article,based on Taylor polynomial coefficients, a power spectrum expression for amplified OFDM signals in terms of intercept points(up to nth-order) is derived. This model is useful to RF engineers in choosing and testing RF amplifiers with appropriate specifications, such as intercept points and gain, to meet the requirements of wireless standards. Measurements are carried out to confirm the results of the proposed model.

关键词： adjacent channels modulation scheme radio frequency amplifiers power spectrum expression Taylor polynomial coefficients RF amplifier higher-order intercept points passband channels amplified OFDM signals OFDM modulation wireless communication systems radiofrequency amplifiers wireless standards radio networks polynomials orthogonal frequency-division multiplexing OFDM based signals

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DESIGN AND TUNING ASPECTS OF A PSS BASED ON THE COMPLETE NONLINEAR SYNCHRONOUS GENERATOR MODEL 14

DESIGN AND TUNING ASPECTS OF A PSS BASED ON THE COMPLETE NON...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Alexandridis, Theodosis A. Barbagianni, Maria G. Alexandridis, Antonio T. School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Department of Electrical and Computer Engineering University of Patras Greece

ISBN: (纸本)9781837242689

A new insight is given in the analysis of the standard power system stabilizer (PSS) design problem that results in some important methodology novelties. The problem is investigating in a new manner based on the complete nonlinear model of the synchronous generator (SG), in combination with the well-known lead-lag compensator characteristics. According to the deployed theoretical analysis, a novel, simple and reliable PSS design procedure is established that is expected to contribute to the system stability and good response with clearly smooth and fast damping on the local frequency oscillatory behaviour of the SG. Following the proposed methodology, different design and gain tuning cases are examined by conducting extended simulations. All the comparisons between the results, fully confirm the theoretical analysis and indicate the superiority of the proposed design procedure. © The Institution of engineering & Technology 2024.

关键词： Damping

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Enhancing Image Quality with GAN Super Resolution Evaluation 5

Enhancing Image Quality with GAN Super Resolution Evaluation

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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Kumari, Saumya Jha, Resham Ray, Aarushi Bilgaiyan, Saurabh Gourisaria, Mahendra Kumar Sharma, Ashish School of Computer Engineering Kiit Deemed to Be University Odisha Bhubaneswar India Gla University Department of Computer Engineering and Applications Mathura India

ISBN: (纸本)9798350379945

The present study presents a novel approach to enhance the quality of celebrity photos by utilizing an innovative framework known as Profile SR-GAN. The aim is to increase the resolution of low-quality celebrity photos, so they appear significantly better. In this work, Generative Adversarial Network (GAN) has been applied as it is highly efficient at generating images. Two key performance metrics have been used, PSNR and SSIM, to evaluate the effectiveness of our approach. In comparison to the noise in the original low-quality photographs, PSNR enables us to determine how clear the high-resolution images are. SSIM analyzes brightness, contrast, and general structure to assist us compare the original and upgraded photos. The effectiveness of GAN model has been demonstrated in enhancing the image resolution through our detailed study. This research study has gained a greater knowledge of this technique's effectiveness and its potential uses in many contexts. © 2024 IEEE.

关键词： Generative adversarial networks

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Human intelligence-based metaverse for co-learning of students and smart machines

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Journal of Ambient Intelligence and Humanized Computing 2023年第6期14卷 7695-7718页

作者： Lee, Chang-Shing Wang, Mei-Hui Reformat, Marek Huang, Sheng-Hui Department of Computer Science and Information Engineering National University of Tainan Tainan Taiwan Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Information Technology Institute University of Social Sciences Warsaw Poland

This paper proposes a Human Intelligence (HI)-based Computational Intelligence (CI) and Artificial Intelligence (AI) Fuzzy Markup Language (CI&AI-FML) Metaverse as an educational environment for co-learning of students and machines. The HI-based CI&AI-FML Metaverse is based on the spirit of the Heart Sutra that equips the environment with teaching principles and cognitive intelligence of ancient words of wisdom. There are four stages of the Metaverse: preparation and collection of learning data, data preprocessing, data analysis, and data evaluation. During the data preparation stage, the domain experts construct a learning dictionary with fuzzy concept sets describing different terms and concepts related to the course domains. Then, the students and teachers use the developed CI&AI-FML learning tools to interact with machines and learn together. Once the teachers prepare relevant material, students provide their inputs/texts representing their levels of understanding of the learned concepts. A Natural Language Processing (NLP) tool, Chinese Knowledge Information Processing (CKIP), is used to process data/text generated by students. A focus is put on speech tagging, word sense disambiguation, and named entity recognition. Following that, the quantitative and qualitative data analysis is performed. Finally, the students’ learning progress, measured using progress metrics, is evaluated and analyzed. The experimental results reveal that the proposed HI-based CI&AI-FML Metaverse can foster students' motivation to learn and improve their performance. It has been shown in the case of young students studying Software engineering and learning English. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Students

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Forecasting Geomagnetic Storms for Earth Using LSTM with Solar Wind and IMF Features

Forecasting Geomagnetic Storms for Earth Using LSTM with Sol...

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2024 International Conference on Innovations in Science, engineering and Technology, ICISET 2024

作者： Shammi, Nusrat Jahan Ashraf, Taqia Ifty, Rashedul Arefin Rahman, Md. Ziaur International Islamic University Chittagong Kumira Department of Computer Science and Engineering Chattogram4318 Bangladesh Chittagong University of Engineering and Technology Department of Computer Science and Engineering Chittagong4349 Bangladesh

ISBN: (纸本)9798350355499

When the solar wind interacts with Earth's field, it can cause geomagnetic storms, which pose serious risks to vital infrastructure such as satellite communication, GPS systems, and electric power transmission. We presented a novel method for forecasting the Disturbance Storm-Time Index (Dst) using a long-short-term memory (LSTM) neural network in order to meet the urgent requirement for precise predictions. Our model employs sensing data from NASA's ACE and NOAA's DSCOVR satellites to analyze the complex relationship between interplanetary magnetic field & plasma from solar wind & sunspot activity. These factors are crucial to understanding geomagnetic disturbances. The LSTM model accumulates complex patterns and temporal relationships within the space weather data by including real-time data assimilation, resulting in enhanced weather prediction capabilities. Evaluation metrics like the root mean square error (RMSE) and coefficient of determination (R2) are used to assess the model's performance and reliability. The outcomes indicate that the LSTM model is highly effective in accurately predicting geomagnetic storms. The predicted values offer vital information for operators of satellites, power grids and magnetic navigation systems, enabling them to implement preemptive actions to mitigate the effects of any disruptions caused by geomagnetic storms. The research we accomplished helps to improve the approaches employed for forecasting space weather. This provides decision-makers with a useful and timely tool to strengthen vital systems and prepare for geomagnetic disturbances. © 2024 IEEE.

关键词： NASA

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Flood Risk Assessment and Interpretation Using Explainable AI 2

Flood Risk Assessment and Interpretation Using Explainable A...

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Sharma, Swati Tomar, Vivek Arora, Sangeeta Gupta, Nishant KIET Group of Institutions Delhi - NCR Computer Science & Engineering Department Ghaziabad India University Computer Science & Engineering Department Dehradun India KIET Group of Institutions Delhi-NCR Computer Applications Department Ghaziabad India SET Department of Computer Science & Engineering Sharda University Greater Noida India

ISBN: (纸本)9798350368109

Floods are the unforeseen situations to the society which causes high risk to the society. For proactive action, it is important to identify locations based on past results. It is necessary to take measures before the situation gets worst. For the benefit of society, a novel approach to map flood risk usinga balanced dataset and an Extra Tree Classifier. The Extra Tree Classifier performs better with the Shapely Additive explanation values. It shows improvement towards decision making processes to reduce the causality at the time of floods. The proposed method achieves the accuracy of 93.61% for the estimating flood danger effects on a particular location. In this paper quantitative study was done to handle the challenges to predict the flood danger using the artificial intelligence ethically. © 2024 IEEE.

关键词： Risk assessment

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