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9th EAI international conference on IoT as a Service, IoTaaS 2023

9th EAI International Conference on IoT as a Service, IoTaaS...

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9th EAI international conference on IoT as a Service, IoTaaS 2023

ISBN: (纸本)9783031705069

The proceedings contain 33 papers. The special focus in this conference is on IoT as a Service. The topics include: Highway Obstacle Recognition based on Improved YOLOv7 and Defogging Algorithm;cloud Gaming Resource Management Platform based on Edge Intelligence;hardware-Efficient Polar Decoder for 5G internet of Things Communication;Design and Optimization of a Solar-Powered IRS and Relay Assisted MEC System;highway image Enhancement Method based on Jade;method and Practice of Borehole Group Detection in Borehole Drilling based on Six-Axis Sensing;Deep Reinforcement Learning-based Channel and Power Allocation in Multibeam LEO Satellite systems;CSI-based signal Reconstruction for WiFi Localization;an Indoor Navigation Algorithm Using Multi-dimensional Euclidean Distance and the Adaptive Particle Filter;Research on the PID Controllers Algorithm of the Quad Rotor;based on the Nonlinear State Equations of 6-DOF Robot with Application to Autonomous Flight;a Study on Collaborative Lane Change Decision Making of Multi-automated Vehicles based on Deep Graph Reinforcement Learning;a Short Term Traffic Prediction Model based on Deep Capture of Temporal Periodic Drift;multi-agent Reinforcement Learning for Cooperative On-Ramp Merging of Connected Automated Vehicles;SVM Multi-class Classification Method for Device Identification Using Eye Diagram Parameters;users Collaborative Computing for Hierarchical Federated Learning based on Incentive Mechanism;spatio-Temporal Traffic Prediction of Wireless Communication Network based on Multi-source Data;flying Ad-Hoc Network Routing Protocol based on Backward Algorithm;A Novel HPSO-IGWO Algorithm for Rapidly Searching Optimal Fire Rescue Paths based on IoT Architecture;A Hybrid WOA-MTCNN Algorithm for Accurate Face Detection based on IoT Architecture.

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6th EAI international conference on Advanced Hybrid Information Processing, ADHIP 2022

6th EAI International Conference on Advanced Hybrid Informat...

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6th EAI international conference on Advanced Hybrid Information Processing, ADHIP 2022

ISBN: (纸本)9783031287862

The proceedings contain 109 papers. The special focus in this conference is on Advanced Hybrid Information Processing. The topics include: Design of Remote Video Surveillance System based on Cloud Computing;physical Movement Monitoring Method of College Physical Education Students based on Genetic Algorithm;research on Large Data Mining for Online Education of Mobile Terminal based on Block Chain technology;Separation Algorithm of Fixed Wing UAV Positioning signal based on AI;research on Hybrid Maintenance Cost Prediction of Smart Grid based on Multi-dimensional Information;infrared image Face Recognition Method based on signal Interference technology;remote Tutoring System of Ideological and Political Course based on Mobile Client;operational Risk Prevention and Control Monitoring of Smart Financial System based on Deep Learning;remote Monitoring Method of Athlete Training Intensity based on Mobile internet of Things;research on Equipment Management System of Smart Hospital based on Data Visualization;Design of Pond Water Quality Monitoring System based on Mobile UAV technology;Design of Information Consultation System for the Whole Process of Construction Engineering based on BIM technology;the Mobile Teaching Method of Law Course based on Wireless Communication technology;design of Financial and Economic Monitoring System based on Big Data Clustering;recommendation Method of College English Online Mobile Teaching Resources based on Big Data Mining Algorithm;Design of Electronic Communication Power Monitoring System based on GPRS technology;online Interactive Platform for College English Intensive Reading Teaching based on Cloud Service;intelligent Platform for College English Blended Teaching based on Mobile Learning;preface.

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Dual-image Reversible Information Hiding Scheme Using Staggered Turtle Shells 17th

Dual-Image Reversible Information Hiding Scheme Using Stagge...

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17th international conference on Intelligent Information Hiding and Multimedia signal Processing (IIH-MSP) / 14th international conference on Frontiers of Information technology, Applications and Tools (FITAT)

作者： Lee, Chin-Feng Shen, Jau-Ji Ye, Yu-Yun Chaoyang Univ Technol Dept Informat Management Taichung 41349 Taiwan Natl Chung Hsing Univ Dept Management Informat Syst Taichung 40277 Taiwan

ISBN: (纸本)9789811910531;9789811910524

This paper proposed a two-image real-time and reversible data hiding method based on the staggered turtle shell concealment technology. First, the dual-turtle shells are continuously staggered on the diagonal of a reference matrix. The embedding rules are developed to conceal confidential message accordingly. The experimental results show that the time that our proposed method takes to build the reference matrix, and embed secret information is faster than other TS-based dual-image data hiding schemes. Moreover, the scheme is simple and maintains certain good performance.

关键词： Dual-image data hiding Reversible data hiding Turtle shell-based hiding

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Review on the image Encryption with Hyper-Chaotic systems 5th

Review on the Image Encryption with Hyper-Chaotic Systems

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5th international conference on Soft Computing and signal Processing, ICSCSP 2022

作者： Pathak, Arghya Pal, Subhashish Karmakar, Jayashree Mondal, Hrishikesh Mandal, Mrinal Kanti Department of Physics National Institute of Technology Durgapur713209 India Department of Physics Dr. B. C. Roy Engineering College Durgapur713206 India MUSE Lab Indian Institute of Technology Gandhinagar382355 India Department of Physics Durgapur Government College Durgapur713214 India

ISBN: (纸本)9789811986680

image encryption using a chaotic system is a widely used technique. But, cryptanalysis of most chaotic encryption algorithms pointed out the disadvantages or drawbacks of the chaotic systems. As a remedy, a new and more efficient chaotic system with higher dimension is used recently and named as a hyper-chaotic system. The conditions of an efficient encryption algorithm can be fulfilled effectively by a hyper-chaotic system. Recently, several hyper-chaotic systems are proposed by different researchers, and some of them are used in image encryption techniques. But, some recent cryptanalysis on hyper-chaotic image encryption shows the drawback of these system. This work will discuss different hyper-chaotic systems on the basis of their efficiency to use in image encryption. This discussion will also include the parameters based on which one can choose an efficient hyper-chaotic system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Chaotic systems

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Residual Learning and Deep Learning Models for image Denoising in Medical Applications

Residual Learning and Deep Learning Models for Image Denoisi...

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international conference on. Cryptology and Network Security with Machine Learning, ICCNSML 2023

作者： Srivastava, Atul Rana, Harshita Misra, Manoj Kumar Singh, Youddha Beer Amity School of Engineering and Technology AUUP Lucknow India Pranveer Singh Institute of Technology Kanpur India Galgotia College of Engineering and Technology UP Greater Noida India

ISBN: (纸本)9789819706402

The utilization of CT scans in medical diagnostics has seen a consistent and substantial rise. However, this increased usage has raised concerns regarding the potential harmful effects of radiation exposure on patients. Reducing the radiation dose can result in more noise in the captured images, which can negatively impact the radiologist's ability to make accurate judgments with confidence. The most commonly encountered types of noise in medical images include Gaussian noise, speckle noise, and salt and pepper noise. Numerous significant efforts have been made to enhance image quality by eliminating this noise, and deep learning-based methods have gained popularity due to their effectiveness in handling various types of noise and image datasets. Within the research community, various neural network variations, such as autoencoders, generative adversarial networks (GANs), residual networks, convolutional neural networks (CNNs), and regularized neural networks, have gained immense popularity. In this paper, we comprehensively discuss eleven highly impactful approaches for image denoising based on deep learning techniques. We assess the performance of these methods using two quantitative and effective metrics: structural SIMilarity (SSIM) and peak signal-to-noise ratio (PSNR). © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： image enhancement

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A Multi-Layered Model for Medical image Fusion 5

A Multi-Layered Model for Medical Image Fusion

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5th international conference on Inventive Research in Computing Applications, ICIRCA 2023

作者： Prasad, Kanakam Siva Rama Rao, N. Srinivasa Thippagudisa, Kishore Babu Bhavana, Gundapureddy Jayasri, Paletipati Silpa, Vaka Lakshmi, Bojupalli Pace Institute of Technology and Sciences Department of Cse India

ISBN: (纸本)9798350321425

Medical image fusion (MIF) merges the data from various medical images into one image to get the more detailed data. This technique can improve the accuracy of medical diagnosis and treatment. image Processing (IP) is a domain the process the images based on requirement and IP plays a significant role in medical image fusion, as itenables extracting and manipulating relevant information from medical images. Deep Learning (DL) is sub-domain that can extract accurate features dynamically to overcome issues in existing systems. This studydescribes the DL model combined with image fusion to show better results. The proposed multi-layered medical image fusion model can improve the detection and diagnosis of Magnetic resonance imaging (MRI) fused with Computerized Tomography (CT) images. The proposed model focused on detecting brain tumors from MRI input images. Performance is analyzed based on parameters such as Peak signal Noise Ratio (PSNR), root mean square error (RMSE), and Entropy (EN). © 2023 IEEE.

关键词： Magnetic resonance imaging

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A Cooperative Spectrum Sensing Method based on Feature Extraction and Fusion Clustering 14th

A Cooperative Spectrum Sensing Method Based on Feature Extr...

引用

14th EAI international conference on Wireless and Satellite systems, WiSATS 2024

作者： Li, Jian Li, Yue Chen, Xiaoxu Heilongjiang University Harbin150080 China

ISBN: (纸本)9783031861956

To improve the performance of spectrum sensing at low SNR, a collaborative spectrum sensing method based on feature extraction and fusion clustering is proposed (FEFC). First, the sampling matrix of the received signal is vectorially decomposed to obtain the I and Q component signals. Second, Cholesky decomposition is applied to the covariance matrices of the I and Q signals to fully extract their features and construct the two dimensional feature vectors. The K-Means clustering algorithm is used to optimize the initial parameters of the Gaussian Mixture Model (GMM), effectively preventing it from falling into local minima under low SNR. Finally, the feature vectors of the signals are classified using GMM clustering optimized by the K-Means algorithm to obtain the final spectrum sensing results. Simulation results show that this method reduces the convergence time of GMM and improves the accuracy of model classification. It effectively enhances the performance of spectrum sensing compared to other mainstream methods. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： signal to noise ratio

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Dual image Reversible Data Hiding based on Coordinate Vector Directions via Communication Networking 23

Dual Image Reversible Data Hiding Based on Coordinate Vector...

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8th international conference on Cloud Computing and internet of Things, CCIOT 2023

作者： Lee, Chin-Feng Chan, Kuo-Chung Dept. of Information Management Chaoyang University of Technology Taichung41349 Taiwan

ISBN: (纸本)9798400708046

In this paper, an innovative reversible dual image information hiding technique is proposed, which utilizes the coordinate vectors generated by the original pixel pairs to hide secret information at two combined locations in four directions. In the process of image transmission, it is not easy to be detected, and the receiver of the image data can completely restore the stego image to the original image, which is very suitable for the transmission of confidential information such as medicine or intelligent transportation. In recent years, many researchers have used this technique to improve the quality of embedded steganographic images and the ability to hide secret information. In the field of digital image information hiding, embedding capacity and Peak signal-to-Noise Ratio (PSNR) are two important quantitative evaluation indicators. The higher the PSNR value, the closer the distorted digital image quality is to the original digital image. If the PSNR is higher than 30dB, it is generally considered to be ideal image quality. We extract two pixels from the original image and embed the secret information according to different hidden parameters and . The minimum hiding ability is 1 bit per pixel (bpp) or above. According to our experimental results, when the hidden capacity of the steganographic image is 1 bpp, the PSNR value of the image is 50.65 dB, and when the hidden capacity is 2 bpp, the PSNR value of the image is 37.88 dB. This means that our proposed method has good image quality and embedding capacity. © 2023 ACM.

关键词： Pixels

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A Comparative Analysis on Computational and Security Aspects in IoT Domain

A Comparative Analysis on Computational and Security Aspects...

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international conference on Advances in Data-driven Computing and Intelligent systems, ADCIS 2022

作者： Khare, Ankit Rajput, Pushpendra Kumar Pal, Raju Aarti Himalayan School of Science and Technology Swami Rama Himalayan University Uttarakhand Dehradun248016 India School of Computer Science University of Petroleum and Energy Studies Uttarakhand Dehradun248007 India CSE and IT Department Jaypee Institute of Information Technology Uttar Pradesh Noida201309 India Lovely Professional University Punjab Phagwara144001 India

ISBN: (纸本)9789819932498

In the modern world, technology is intricately intertwined with every aspect of our daily lives. Additionally, tasks including file access, downloading, cloud computing, image recognition, and video cassette playback are managed by remote devices at homes and workplaces. The internet of Things (IoT), which refers to all these internet-connected gadgets, is employed in a variety of settings, including smart cities and the health care industry. To share a large volume of data among these devices, computational and security aspects are two major concerns. This paper discusses and presents analysis of computational and security aspects used in the internet of Things (IoT). The authors explore the theoretical as well as the computational aspects in terms of usability and domain variability. The paper also presents exploration of methods, automation strategies along with their advantages and disadvantages in terms of prospective computation with current scenarios. Finally, the authors highlighted future research perspective in the area based on the comparison and analysis. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： internet of things

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Securing Patient Information in Connected Healthcare systems in the Age of Pervasive Data Collection 3

Securing Patient Information in Connected Healthcare Systems...

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3rd IEEE international Mediterranean conference on Communications and Networking, MeditCom 2023

作者： Dimitrievski, Ace Loncar-Turukalo, Tatjana Trajkovik, Vladimir Faculty of Computer Science and Engineering Skopje Macedonia University of Novi Sad Centre of Excellence for Vibro-Acoustic Systems and Signal Processing Faculty of Technical Sciences Serbia

ISBN: (纸本)9798350333732

This paper explores the ethical and security challenges of integrating internet of Things technologies into health-care systems. We examine real-world ethical dilemmas, including privacy and security of personal and medical data. We also analyze security in connected healthcare systems, focusing on securing data transmission, preventing data exfiltration, and mitigating the risk of de-anonymization of data. We propose a fog-based architecture and data avoidance principle to address and minimize the risks to patient data, intending to navigate the ethical landscape of IoT in healthcare, ensuring patient privacy. © 2023 IEEE.

关键词： Data privacy

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