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11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Kaur, Amandeep Singh, Harveer Chandigarh School of Business Department of Master of Computer Application Jhanjeri India Sanskriti University Department of Computer Science Engineering Uttar Pradesh Mathura India

ISBN: (纸本)9781665487320

As well as an arrester, semi power and electromagnetic current distributions have been seen, which impacts the dependability and lifespan of the device. With the HV load resistor, a rating ring is used to provide an even spread of the electric field. The Finite Element Technique (FEM), a tried-and-true approach, is used to assess the effects of sorting ring characteristics. It contributes to extending the useful life of surge arrester ZnO blocks under extreme stress. Optimizer (PSO) and BAT techniques are used for validation. © 2022 IEEE.

关键词： Optimization

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Deep Learning-Based Diagnostic Tool for Brain Tumours 3

Deep Learning-Based Diagnostic Tool for Brain Tumours

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3rd International Conference on Innovative Sustainable Computational Technologies, CISCT 2023

作者： Singh, Arun Rakhra, Manik Singh, Dalwinder Sharma, Arvind Kumar, Rakesh Lovely Professional University Department of Computer Science & Engineering Jalandhar Phagwara India School of Computer Application Lovely Professional University Punjab Phagwara India Lovely Professional University Department of Mathematics Punjab Phagwara144411 India

ISBN: (纸本)9798350303360

In this work, we provide the results of our experiments on Brain Tumour Classification and explore their implications. MRI, short for magnetic resonance imaging, is a crucial piece of medical imaging technology that creates high-resolution pictures of the inside of a human body by combining radio waves, a strong magnetic field, and a computer. In this study, we employ a CNN-based Deep learning model to categorise cases of brain tumours. Common applications for CNNs (Convolutional Neural Networks) include video and image analysis. It processes images by first ingesting them and then convoluting them into smaller and smaller pieces. The convolutional layer analyses the input picture using a series of filters designed to identify elements like edges, curves, and patterns. Here, we constructed the CNN using data obtained from Kaggle. It contains roughly 3300 MRI scans of the brain, split into 4 groups (no tumours, meningioma tumours, glioma tumours, and pituitary tumours) and a total of 384 testing pictures. We used Keras to construct the model. The accuracy of the suggested project is quite high, coming in at 97.142%. The Confusion matrix is used to evaluate the precision. It is a data table for measuring the efficacy of an ML system. This provides the results of a comparison between the actual values in a dataset and the model's projected values in an easy-to-understand format. © 2023 IEEE.

关键词： Neuroimaging

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Using Classifier with Gated Recurrent Unit-Sigmoid Perceptron, Order to Get the Right Bird Species Detection 11

Using Classifier with Gated Recurrent Unit-Sigmoid Perceptro...

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11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Sikand, Rainy Singh, Harveer Chandigarh School of Business Department of Master of Computer Application Jhanieri India Sanskriti University Department of Computer Science Engineering Uttar Pradesh Mathura India

ISBN: (纸本)9781665487320

The method for classifying a picture using the CNN algorithm and various activation functions is the subject of this research study. From a human perspective, there are several sorts of situations found in birds, such as various sizes, altitudes, colours, and forms. There is a more substantial variety in photos to recognize the species of bird than there is in the accepted audio categorization of birds. Additionally, people have a really tough time identifying birds from photos. The system is suggested to support the concepts of identifying a portion of the birds and extracting the CNN characteristics using several convolutional layers in order to discriminate and categorise the birds. These characteristics are then gathered and presented to the decoder at that time for classification. Various bird photos and activation functions are used to test the CNN method. The nodes of the picture are checked to the different testing data sets, such as cifar-10 and Berkeley Birds 200, with order to determine their correctness. Python is used to create the suggested system in either Omnibus 3 or Dragonfly 3 programs. According to the experiment results and analyses, CNN with activated Re LU-Sigmoid outperforms CNN with the other activation functions in terms of accuracy. © 2022 IEEE.

关键词： Chemical activation

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Vision-Based Locomotion Control for Humanoid Robots: A Study on Vision-Guided Walking Strategies

Vision-Based Locomotion Control for Humanoid Robots: A Study...

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2023 International Conference on Computational Intelligence and Sustainable engineering Solution, CISES 2023

作者： Pandey, Saroj Kumar Kumar, Lalan Kumar, Gaurav Kumar, Ankit Singh, Kamred Udham Singh, Teekam Gla University Department of Computer Engineering & Applications UP Mathura India Gl Bajaj Institute of Technology and Management Department of Master of Computer Application India School of Computing Graphic Era Hill University Dehradun India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350323917

Recently, there has been a lot of research on using vision to direct humanoid robots as they walk. Focusing on the major methodologies, difficulties, and prospects, this review article presents an overview of the current state of study in the vision-guided walking of humanoid robots. In the first part of the study, we introduce vision-guided walking and go through the several methods that have been developed to execute it, such as visual serving, visual odometer, and visual simultaneous localization and mapping. The difficulties of vision-guided walking are then discussed;these include, but are not limited to, the necessity for accurate and strong computer vision algorithms, the robot's need to have a solid awareness of its own body and how it moves, and the need to maintain balance while walking. This paper provides a detailed review of the research on humanoid robots that use vision to direct their gait. Deep learning for vision-guided walking, tactile and proprioceptive sensing combined with vision, and reinforcement learning for adaptive walking are only a few of the issues covered in this overview. Future directions in vision-guided walking research are discussed in this paper. These include the development of more advanced and reliable computer vision algorithms, the incorporation of other modalities like tactile and auditory sensing, and the investigation of new applications for vision-guided walking in fields like healthcare and rehabilitation. © 2023 IEEE.

关键词： Anthropomorphic robots

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An Overview of Video Tampering Detection Techniques: State-of-the-Art and Future Directions

An Overview of Video Tampering Detection Techniques: State-o...

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2023 International Conference on Computational Intelligence and Sustainable engineering Solution, CISES 2023

ISBN: (纸本)9798350323917

In the realm of video processing and forensics, finding video tampering is a critical challenge. The purposeful change or manipulation of video material to conceal or falsely depict the original information is referred to as 'video tampering.' A significant demand for efficient video tampering detection methods has emerged in recent years as a result of the rise in false news, cyberbullying, and other types of criminal behavior. Modern approaches for detecting video manipulation may be generally divided into two categories: passive methods and aggressive methods. Whereas active methods entail putting digital watermarks or other identifiers on the video clip to aid tampering detection, passive methods rely on evaluating the video content for inconsistencies or artifacts generated during tampering. Techniques like sensor noise analysis, splicing detection, and forgery detection based on compression artifacts are examples of passive approaches. To find any discrepancies produced by manipulation, sensor noise analysis examines the noise patterns in the video. Splicing detection entails identifying the borders between several video segments and inspecting the content of each segment for irregularities. Analyzing the compressed video stream for irregularities caused during tampering is required for detecting forgeries based on compression artifacts. Techniques like digital watermarking, digital signatures, and fingerprinting are examples of active procedures. To detect any manipulation efforts, digital watermarking entails putting a digital watermark into the video clip. To confirm the legitimacy of the video clip, a digital signature is applied to it. To do fingerprinting, special characteristics from the video footage are extracted and saved in a database. In addition to the aforementioned methods, machine learning-based systems have also demonstrated promising outcomes in the identification of video manipulation. Using these methods, any tampering attempts in fresh mov

关键词： Authentication

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IoT based Truck Wheel Temperature Monitoring System

IoT based Truck Wheel Temperature Monitoring System

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2024 Asian Conference on Intelligent Technologies, ACOIT 2024

作者： Zaid, Mohd Ahmad, Nadeem Aljamal, Mohammed Patel, Sarosh Khan, Asif Dept. of Computer Science and Engineering Integral University Lucknow India Dept. of Electronics and Communication Engg. Goel Institute of Technology and Managment Lucknow India School of Engineering University of Bridgeport United States Integral Robotics Lab Dept. of Computer Application Integral University Lucknow India

ISBN: (纸本)9798350374933

The main objective of this paper is to design an IoT based truck wheel temperature monitoring system using Arduino board with the aim to overcome endanger and raise the safety measures for truck and goods. By designing and implementing a temperature-detecting system, we can detect the temperature of the wheels trucks. By the use of such detecting device we can prevent the major problem associated with wheel’s temperature and may avoid the major accidents. This monitoring system senses the temperature data of the wheel and transmits through the Wi-Fi module. In addition, it upgrades Thingspeak channel that can collect the data and it can easily be accessed by the transport agency and the truck driver. This can further be analysed using any computer system or mobile with internet connectivity anywhere across the globe to take real-time decision. The core function of the proposed detecting system is to monitor the real- time value of truck wheel temperature and to inform the concerned people. © 2024 IEEE.

关键词： Wi-Fi

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A High-capacity Information Hiding Scheme Based on Blakley Secret Sharing 4

A High-capacity Information Hiding Scheme Based on Blakley S...

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4th International Symposium on Artificial Intelligence and Intelligent Manufacturing, AIIM 2024

作者： Zhou, Jincheng Li, Yue Shen, Yujie Tang, Dan Cai, Hongliang Gong, Jing Bai, Ningchao School of Software Engineering Chengdu University of Information Technology Chengdu China Sichuan Province Engineering Technology Research Center of Support Software of lnformatization Application Chengdu China School of Computer Science and Engineering Sichuan University of Science & Engineering Yibin China Sichuan Provincial Big Data Technical Service Center Chengdu China

ISBN: (纸本)9798331541729

A high-capacity reversible information hiding scheme based on Blakley secret sharing is proposed to address the issues of low embedding rate and weak disaster recovery performance of images when using reversible information hiding to protect data in scenarios with large data transmission. The scheme employs Euclidean division and a two-dimensional modulus function to establish a robust mapping relationship between the secret information and the pixels of the cover image. Subsequently, the values derived from the preprocessing of the secret information are incorporated into the secret sharing method proposed by Blakley as the elements of the secret vector. The proposed scheme exploits the disaster-tolerance property of the secret sharing method and enhances the redundancy of the secret-carrying encrypted image, thereby improving the embedding rate and security of the algorithm while maintaining the security of the secret sharing. © 2024 IEEE.

关键词： Euclidean division Information hiding Modulus function Secret sharing

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Profiling Industrial 3D Parts with Complex Shapes Using 2D Imagery 15

Profiling Industrial 3D Parts with Complex Shapes Using 2D I...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Mahato, Nivedan Kaushik, Harshita Swadimath, Uma C. Arka Jain University Department of Mechnical Engineering Jharkhand Jamshedpur India Vivekananda Global University Department of Computer Science & Application Jaipur India School of Mangement - Pg Department of Management Karnataka Bangalore India

ISBN: (纸本)9798350370249

Commercial 3-D element profiling via second imagery is a modern technique to acquire the 3-D geometric characteristics of quite complicated shapes frequently encountered in industrial additives. This approach makes use of a set of pix taken from multiple angles to derive the corresponding 3-D profile of the component with the use of photogrammetry strategies. The resulting three-D statistics can be similarly characterized to evaluate the part's dimensional accuracy, floor texture, and different attributes. The novel technique described in this work augments conventional measuring methods and opens new possibilities for automated bodily asset evaluation, reverse engineering, and automated inspection. The method defined has potential programs in an extensive type of fields in which correct geometrical characterization of complex parts is important. © 2024 IEEE.

关键词： Characterization Commercial complex Complicated geometrical Photogrammetry Potential

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Integrated Intelligent Computing Models for Cognitive-Based Neurological Disease Interpretation in Children: A Survey

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EAI Endorsed Transactions on Pervasive Health and Technology 2024年 10卷

作者： Tandon, Archana Mazumdar, Bireshwar Dass Pal, Manoj Kumar Faculty of Computer Application United University Prayagraj India School of Computer Science Engineering and Technology Bennett University U.P Greater Noida India Faculty of Computer Science & Engineering United University Prayagraj India

INTRODUCTION: This piece of work provides the description of integrated intelligent computing models for the interpretation of cognitive-based neurological diseases in children. These diseases can have a significant impact on children's cognitive and developmental functioning. OBJECTIVES: The research work review the current diagnosis and treatment methods for cognitive based neurological diseases and discusses the potential of machine learning, deep learning, Natural language processing, speech recognition, brain imaging, and signal processing techniques in interpreting the diseases. METHODS: A survey of recent research on integrated intelligent computing models for cognitive-based neurological disease interpretation in children is presented, highlighting the benefits and limitations of these models. RESULTS: The significant of this work provide important implications for healthcare practice and policy, with strengthen diagnosis and treatment of cognitive-based neurological diseases in children. CONCLUSION: This research paper concludes with a discussion of the ethical and legal considerations surrounding the use of intelligent computing models in healthcare, as well as future research directions in this area. © 2024 A. Tandon et al.

关键词： Speech recognition

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ZKCross: An Efficient and Reliable Cross-Chain Authentication Scheme Based on Lightweight Attribute-Based Zero-Knowledge Proof 24th

ZKCross: An Efficient and Reliable Cross-Chain Authenticati...

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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Xu, Yuwei Cai, Hailang Chen, Jialuo Xiang, Qiao Xu, Jingdong Cheng, Guang School of Cyber Science and Engineering Southeast University Nanjing China Purple Mountain Laboratories for Network and Communication Security Nanjing China Engineering Research Center of Blockchain Application Supervision and Management Nanjing China School of Informatics Xiamen University Xiamen China College of Computer Science Nankai University Tianjin China

ISBN: (纸本)9789819615506

The consortium blockchain finds wide application in finance and logistics. However, these independent networks create information silos. Cross-chain authentication aims to bridge these gaps. It verifies qualifications across different blockchains, yet it can risk leaking sensitive data. The main methods include Attribute-Based Signatures (ABS) and Attribute-Based Zero-Knowledge Proof (ABZKP). ABZKP better handles key management, general applicability, and attribute verification than ABS. However, the current ABZKP suffers from large proof files and slow verification. Additionally, many schemes can’t handle sets of multiple attributes and may introduce centralization. Overall, the current schemes based on zero-knowledge proof still struggle to strike a balance between security and efficiency. We propose a reliable cross-chain authentication scheme. Our lightweight zero-knowledge proof algorithm enhances verification speed and reduces file size. We also introduce parallel verification to address security concerns. Security analysis and experiments show that ZKCross when properly configured, achieves near-perfect accuracy and outperforms others in size and speed. Thus, ZKCross stands as an efficient and dependable cross-chain authentication scheme. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Authentication Protocol

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