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Thermal Vision RC Tank for Human Detection in Disaster Area Using IoT 5

Thermal Vision RC Tank for Human Detection in Disaster Area ...

引用

5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Jyotsna, P. Sanjay Surendar, B. Sharan, B. Dhanaselvam, J. Saravanakumar, K. Rajesh, R. Sri Krishna College of Technology Dept of Instrumentation and Control Engineering Coimbatore India Sri Krishna College of Technology Dept. of Electrical and Electronics Engineering Coimbatore India Indian Institute of Technology Department of Engineering Design Chennai India

ISBN: (纸本)9798350385649

In this modern era of technology, still conventional methods (human and trained dogs) are being used to find and rescue the victims, who are buried under the rubble after natural or human-made destruction. Offering a revolutionary solution, this robot outperforms traditional methods of searching for individuals during rescue operations. Another key initiative is the integration of IoT technologies, which will facilitate communications and data exchange. These rescue efforts come with significant risks for both rescuers and the victims aim to save. Compared to current methods, this robot performs exceptionally well in locating people during rescue missions. Its main advantage lies in its incorporation of advanced sensors, particularly those capable of detecting body heat and infrared signals. This technological enhancement allows the robot to identify individuals even in challenging conditions, such as darkness, smoke, or clutter, where regular cameras struggle. © 2024 IEEE.

关键词： Cameras

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Enhancing Energy Efficiency and Renewable Integration in Industrial Plants through DC Microgrids: A Case Study for an Ethylene Plant 25

Enhancing Energy Efficiency and Renewable Integration in Ind...

引用

25th International Middle East Power System Conference, MEPCON 2024

作者： Gomaa, Abdallah. M. Abdelrahim, Ahmed Atteya, Inji. I. Ahmed Ashour, Hamdy Arab Academy for Science Technology and Maritime Transport Dept. of Electrical and Control Engineering Alexandria Egypt Arab Academy for Science Technology and Maritime Transport Dept. of Basic and Applied Science Alexandria Egypt

ISBN: (纸本)9798350379648

As industrial plants seek to improve energy efficiency and reduce carbon emissions in line with climate change mitigation strategies, the implementation of DC microgrids presents a promising solution. This study investigates the potential of DC microgrids to enhance energy efficiency and facilitate the integration of renewable energy resources, particularly solar photovoltaic (PV) systems, in industrial settings. The research focuses on the advantages of DC microgrids over traditional AC systems, specifically in reducing the number of conversion stages required for system design. A case study of an ethylene plant is presented to illustrate the benefits of implementing a DC microgrid in an industrial environment. The study employs ETAP and PVsyst software for analysis and simulations. Results demonstrate that the adoption of a DC microgrid leads to a significant reduction in conversion losses, resulting in enhancing the overall system efficiency by 9.5%. Furthermore, The DC microgrid enhanced the benefits of integrating the same PV capacity, reducing grid energy consumption and carbon emissions by 20.5% compared to the AC microgrid. The findings have important implications for industrial energy management and sustainable manufacturing practices in the context of global efforts to combat climate change. © 2024 IEEE.

关键词： carbon emissions DC microgrid energy efficiency Ethylene plants PV system uninterruptible power supply variable speed drives

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SES: Smart Education System 5

SES: Smart Education System

引用

5th International Conference on Computer and Applications, ICCA 2023

作者： Alyammahi, Wadha Alrabaee, Saed United Arab Emirates University College of Information Technology Dept. of Computer and Network Engineering Dept. of Information Systems and Security AlAin United Arab Emirates

ISBN: (纸本)9798350303254

Responding to inefficiencies in traditional classroom management methods, this paper proposes an innovative, technology-driven approach to enhance educational processes. Central to our proposal is the development of a facial recognition system designed for efficient student attendance tracking, thus eliminating time-consuming roll calls. Additionally, we plan to introduce interactive whiteboard features to enrich classroom dynamics between students and faculty. However, our approach extends beyond mere attendance tracking and interactive learning. We aim to launch a Program Learning Outcomes (PLO) and Course Learning Outcomes (CLO) mapper. Leveraging Natural Language Processing (NLP) techniques, this tool will auto-align CLOs with PLOs, facilitating a more efficient curriculum development process. We also suggest implementing a feature powered by YOLOv5 to monitor and assess student attention in the classroom. Our comprehensive suite of tools is designed to equip educators with resources to refine their teaching strategies and boost student learning outcomes. By integrating facial recognition for attendance, interactive whiteboard features, NLP-based CLO/PLO mapping, and attention monitoring, we aspire to provide a robust solution enabling educators to adapt their teaching methods to students' unique needs. © 2023 IEEE.

关键词： Students

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Leveraging Potential of Deep Learning for Fruit Quality Detection: A Review 14

Leveraging Potential of Deep Learning for Fruit Quality Dete...

引用

14th International Conference on Advances in Computing, control, and Telecommunication Technologies, ACT 2023

作者： Bathe, Kavita Shinde, Shruti Khan, Mohammad Isa Mali, Shrutik K.J.Somaiya Institute of Engineering & Information Technology Dept. of Computer Engineering Mumbai India

Detection of the quality of fruits is essential for the health of humans as well as animals for sustainable agriculture. The quality of the fruit determines its price and directly impacts the agricultural sector thereby the economy. The early detection of the quality of the fruit can lead to the adoption of various techniques to further improve fruit quality, quantity and yield. Conventional methods include humans visually observing the fruit and checking for deformities. Moreover, IoT-based systems are used for this purpose,but satisfactory results have not been observed. Recent progress and research in deep learning methodologies have shown remarkable results for the aforementioned task which may lead to improvement in agricultural outcomes. However, the potential of deep learning methods for real-time fruit quality detection remains under-explored. This study aims to present a comprehensive review of widely adapted methods for fruit quality detection and provide future research scope and directions to the researchers as well as provide a clearer picture of quality determination using cutting-edge technologies. © Grenze Scientific Society, 2023.

关键词： Fruits

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Fingerprint generation and authentication though Adaptive convolution generative adversarial network (ADCGAN) 7

Fingerprint generation and authentication though Adaptive co...

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7th International Multi-Topic ICT Conference: IMTIC 2023

作者： Mustafa, Syed Muhammad Nabeel Zehra, Syeda Sundus Baber, Alina Siddiqui, Maria Andleeb Ned University of Engineering and Technology Dept. of Computer Science & Information Technology Karachi Pakistan Sir Syed University of Engineering and Technology Dept of Software Engineering Karachi Pakistan

ISBN: (纸本)9798350338461

Fingerprints are crucial in identification of humans. The uniqueness of finger prints makes it an interesting subject. Fingerprints are termed as a technique used to define, assess, and quantify a person's physical and behavioral property. Deep learning has made its application in all the major fields such as natural language processing, computer vision and speech processing. Deep learning has also found its application in the important subject of fingerprint synthesis and biometric. The ever-growing complexity of fingerprint authentication issues, from cellphone authentication to airport security systems, seems to be best handled by these models. In recent years, deep learning-based models have been used more and more to raise the accuracy of various fingerprint recognition systems. The persuasive capacity of Generative Adversarial Networks (GANs) to generate believable instances can be credibly taken from an existing distribution of samples. GAN exhibits exceptional performance on data generation-based tasks and also encourages study in privacy and security. In this work, using Adaptive Deep Convolution Generative Adversarial Networks (ADCGAN), we develop a model that generates and authenticate the fingerprints. A Socofing dataset was trained on ADGAN model. The model gave 92% accuracy. The conduct of fingerprint research has been made possible due to ADGAN, without restrictions related to the confidential nature of biometric data. © 2023 IEEE.

关键词： Generative adversarial networks

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An Investigation for Cursive Context-Specific Printed Script Recognition Techniques 20

An Investigation for Cursive Context-Specific Printed Script...

引用

20th International Multi-Conference on Systems, Signals and Devices, SSD 2023

作者： Rafique, Humera Javid, Tariq Hamdard University Graduate School of Engineering Sciences & Information Technology Dept. of Electrical Engineering Karachi Pakistan

ISBN: (纸本)9798350332568

Selecting suitable techniques and datasets for a machine learning problem is a great challenge. This research investigates the available machine learning architectures, datasets, and software tools, for cursive context-specific printed text. Despite the existence of millions of speakers around the globe and rich literary history of more than thousands of years, it is hard to find computational linguistic works related to the Punjabi Shahmukhi script, a member of Perso-Arabic context-specific script - a low-resource language family. An investigation of related work through collected statistics inspired by the popularity and success of artificial neural networks and associated techniques have presented. The historical development of the script follows it in a literary sense and the importance and motivation in the development of optical character recognition systems, algorithms, and techniques. The paper discussed the available datasets and the need for a custom dataset. Based on recent research trends in machine learning frameworks, the work presents the most popular deep learning techniques, convolutional neural networks, and recursive neural networks for cursive context-specific scripts. This paper incorporates actual knowledge to promote research in machine learning and natural language processing disciplines and the selection of algorithms, architectures, and resources. © 2023 IEEE.

关键词： Network architecture

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A Study on Gait Pattern Identification and MNA Detection Methodologies used for Human Medical Diagnosis using Wearable Sensors 7

A Study on Gait Pattern Identification and MNA Detection Met...

引用

7th International Conference on Trends in Electronics and Informatics, ICOEI 2023

作者： Pushpalatha, S. Math, Shrishail Puiari, Chandrakanth G Dr. Ambedkar Institute of Technology Dept. of Information Science and Engineering Bengaluru India Sri Krishna Institute of Technology Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350397284

In ambulatory monitoring, different sensors such as pulse oximetry, accelerometer, gyroscope, etc. are used for monitoring probes. Generally, these sensors are used for monitoring daily physical activity, stress, and sleep pattern of the respective probe. However, the measurement obtained from these sensors is highly affected due to motion and noise artifacts (MNAs). This study conducts a survey of various existing methodologies presented for mitigating motion and noise artifact of measurement obtained through wearable sensors. The survey is composed of both supervised and non-supervised techniques used for mitigating MNAs, detecting HAR, and classifying Obstructive Sleep Apnea (OSA) using wearables. This survey further highlights research issues in monitoring probes using wearable sensors and presents a future solution to overcome research issues. © 2023 IEEE.

关键词： Wearable sensors

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Enhancing Power Grid Resilience: Advanced Strategies for Detecting and Analyzing Faults in Three-Phase Transmission Lines

Enhancing Power Grid Resilience: Advanced Strategies for Det...

引用

2024 IEEE International Conference on information technology, Electronics and Intelligent Communication Systems, ICITEICS 2024

作者： Ahmed, Khandakar Rabbi Shayer, Khandokar Shadman Shuvo, Jahidul Islam Haque, F.M. Mahmudul Salam, Towfika Miraz, Shafiun Noman, Abdullah Al Sobuj, Md. Shohanur Islam Arafat, Md. Yaqub Rial, Md Istiak Hasan Miyan Research Institute International University of Business Agriculture and Technology Uttara Model Town Dhaka Bangladesh Dept. of Mechatronics Engineering Kazla Rajshahi6204 Bangladesh American International University-Bangladesh Dept. of Electrical & Electronic Engineering Dhaka Bangladesh Ahsanullah University of Science and Technology Dept. of Electrical & Electronic Engineering Dhaka Bangladesh Dept. of Computer Science and Engineering Rajshahi Bangladesh Jahangirnagar University Dept. of Institute of Information Technology Saver Dhaka1342 Bangladesh Hajee Mohammad Danesh Science and Technology University Dept. of Electrical and Electronic Engineering Dhaka Bangladesh International University of Business Agriculture and Technology Dept. of Mechanical Engineering Dhaka Bangladesh Dept. of Computer Science and Engineering Andhra Pradesh Kakinada533291 India

ISBN: (纸本)9798350382693

Power system fault analysis is a process that establishes the bus voltages and line currents when various fault types occur. Three-phase balanced faults and unbalanced faults are two categories of power system faults. Single line-to-ground, line-to-line, and double line-to-ground faults are three different types of unbalanced faults that can occur on transmission lines for power systems. Fault analysis is used to choose and set the proper protective devices and switchgear. Determining the bus voltages and line currents is critical while investigating power system issues. Numerous mathematical calculation techniques are shown in the process, which is challenging to do by hand. The calculation can be performed quickly on a computer using a Simulink created using MATLAB. However, an error occurs when inverting an extensive bus system's Y-bus to Z-bus in the conventional short circuit study;this paper offers a solution that is solved using 'MATLAB SIMULINK' to reduce error. © 2024 IEEE.

关键词： Power system analysis

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Sign Language Detection Using Action Recognition LSTM Deep Learning Model 2

Sign Language Detection Using Action Recognition LSTM Deep L...

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2nd IEEE International Conference on Networks, Multimedia and information technology, NMITCON 2024

作者： Snehalatha, N. Mohana Kumar, S. Kavitha, H. Nisha, S. Gowda, Puttabore Krishna Prasad, Sj Jss Academy of Technical Education Dept. of Computer Science and Engineering Bangalore India Bangalore India Siddaganga Institute of Technology Dept. of Information Science Tumukur India Bangalore India Ramaiah Institute of Technology Dept. of Me Bangalore India Visvesvaraya College of Engineering Dept. of Ec University Bangalore India

ISBN: (纸本)9798350372892

This project aims to develop a system that can recognize sign language gestures in real-time using computer vision techniques. The system is designed to bridge the communication gap between individuals with different hearing abilities by enabling accurate and effective communication through sign language. To achieve this, an image datasets is created, consisting of labeled images of sign language gestures for alphabets, digits, or other signs. This datasets is used to train a deep neural network using transfer learning techniques. Transfer learning involves leveraging the knowledge gained from pre-trained models, such as VGG-16 and ResNet, to accelerate the training process and improve the accuracy of the model. The trained deep neural network is then deployed in a real- time setting where it processes video feeds or live camera feeds to recognize and interpret sign language gestures. The system is designed to be user-friendly, with an intuitive interface that can be easily used by individuals with hearing difficulties or those who do not understand sign language The accuracy of the system is evaluated using various performance metrics such as accuracy, precision, recall, and F1 score. The system is tested in different environments, including noisy and low-light settings, to ensure that it can recognize sign language gestures accurately. Overall, this work demonstrates the potential of computer vision and deep learning techniques to improve communication for individuals with hearing difficulties. It also highlights the importance of developing accessible technologies that can enable effective communication and improve the quality of life for individuals with disabilities © 2024 IEEE.

关键词： Deep neural networks

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Securing Flutter Applications: A Comprehensive Study 7

Securing Flutter Applications: A Comprehensive Study

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2023 7th International Conference On Computing, Communication, control And Automation, ICCUBEA 2023

作者： Rambhia, Palash Shinde, Parth Bamane, Kalyan D.Y. Patil College of Engineering Dept. of Information Technology Pune India

ISBN: (纸本)9798350304268

When using Flutter, creating multi-platform native applications is economical. Because Flutter apps are instantly converted into native code, developers think security is not a major concern. Flutter apps, like many other common mobile apps, are susceptible to security issues. When utilised in hostile environments, applications created using Flutter are vulnerable to manipulation and dynamic attacks. Hackers skilled in reverse engineering binaries can easily take advantage of security holes in Flutter apps. Comprehensive security mechanisms, such as runtime detections to discover changes or manipulation, are needed to protect Flutter apps. Even though Flutter has grown to be a popular framework among developers, creating apps without the right security precautions could have disastrous implications on the company. In this article, we will examine security practices that are currently in use or that may be applied in Flutter, as well as tools and approaches for protecting our apps. We will also study future upgrades to Flutter application security. © 2023 IEEE.

关键词： Flutter Framework Mobile Apps Multiplatform Security

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