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A Hospital Appointment System based on Privacy Protection 6

A Hospital Appointment System Based on Privacy Protection

引用

6th international conference on Futuristic Trends in Networks and Computing Technologies, FTNCT 2024

作者： Zhang, Shaojian Ye, Jun School of Cyberspace Security Hainan University Haikou570228 China Key Laboratory of Internet Information Retrieval of Hainan Province Haikou570228 China

With the rapid development of information technology, the user privacy and data security of hospital appointment systems are becoming increasingly important. Medical data contains sensitive content such as personal health information and diagnosis and treatment records, which, once leaked, may seriously damage the privacy and security of patients. The causes of data breaches include improper access control, cyber attacks, storage system vulnerabilities, and improper handling of data by partners. How to prevent data leakage effectively has become the key direction of medical data privacy protection research. This paper aims to design and implement a hospital appointment system based on privacy protection, using DES encryption algorithm, LSB image steganography algorithm and MD5 salt algorithm to implement management, reservation, encryption and steganography functions for administrators and users based on Java web. The administrator system provides management functions for hospital resources and appointment status. To ensure data security, the system uses MD5 salt encryption algorithm to encrypt and store privacy information in the database. The user system provides users with convenient and fast appointment services. In order to protect user privacy, the system adopts DES encryption algorithm and LSB image steganography method to encrypt and steganize user registration and medical information. This system not only implements basic hospital appointment functions, but also fully considers user privacy and data security. The advantage and novelty of this scheme is that it can protect the privacy of the user's medical data, make the user's private data invisible ciphertext form, and embed it in the picture to eliminate steganography during the transmission process, so as to realize the safe transmission and storage of the data. © 2025 The Author(s). Published by Elsevier B.V.

关键词： Steganography

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A Rolling Bearing Fault Diagnosis Method based on Synchrosqueezed Wavelet Transform and SE-ResNet 24

A Rolling Bearing Fault Diagnosis Method based on Synchrosqu...

引用

9th international conference on Cyber Security and Information Engineering, ICCSIE 2024

作者： Liu, Ye Xu, Yanhe Qin, Hui Niu, Xinqiang School of Civil and Hydraulic Engineering Huazhong University of Science and Technology China State Key Laboratory of Hydroscience and Engineering Tsinghua University China

ISBN: (纸本)9798400718137

Rolling bearings are vital components in rotary machines where even minor faults can lead to the collapse of the entire mechanical system, resulting in significant economic losses. The condition monitoring and fault diagnosis of rolling bearings are crucial for safe operation of complex industrial systems. Traditional fault diagnosis methods mainly depend on expert experience, which leads to obvious deficiencies in diagnostic efficiency, especially in terms of accuracy. To address the issues of traditional bearing fault diagnosis relying on expert experience and low efficiency and accuracy of fault diagnosis, a bearing fault diagnosis model combining synchrosqueezed wavelet transform (SWT) and SE-ResNet is proposed. Firstly, the one-dimensional non-stationary bearing vibration signal is converted into a high-frequency two-dimensional time-frequency image through SWT, which serves as the input for the convolutional neural network;Secondly, an attention mechanism is introduced to construct an SE-ResNet model for extracting two-dimensional image features, which enhances the attention of important features and thus enhances the network’s representation ability;Finally, the results of fault diagnosis are output through Softmax layer. To validate the capacity of the proposed model, experiments with the bearing dataset collected from Case Western Reserve University (CWRU) were conducted. The results show that the transfer learning accuracy of the CWRU dataset is 86.25% to 99%. This method has good feasibility, good convergence performance, and has high practical application value. © 2024 Copyright held by the owner/author(s).

关键词： Synchros

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A Federated Learning Approach for Enhancing Autonomous Vehicles image Recognition 4

A Federated Learning Approach for Enhancing Autonomous Vehic...

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4th international conference on Computer Communication and the internet, ICCCI 2022

作者： Stergiou, Konstantinos D. Psannis, Konstantinos E. Vitsas, Vasileios Ishibashi, Yutaka University of Macedonia Department of Applied Informatics Thessaloniki Greece International Hellenic University Department of Information and Electronic Engineering Thessaloniki Greece Nagoya Institute of Technology Graduate School of Engineering Nagoya Japan

ISBN: (数字)9781665469920

ISBN: (纸本)9781665469920

Traffic sign recognition is vital for the success of the autonomous vehicles paradigm in mobile edge computing. We present a Federated Learning implementation based on a Lenet-5 CNN architecture which can enhance edge computing systems on unsupervised feature classification problems. Experiments demonstrated that our model can deliver satisfactory performance on traffic sign image recognition. Also our research has shown that less resources can be utilized on client devices to run the local training models. However, heavy data processing must be shifted to intermediate edge computing layers requiring more computing resources and the optimization of parameters such as latency, bandwidth, and privacy. © 2022 IEEE.

关键词： image recognition

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Multi-Objective Trapping of UAVs Swarm based on Gene Regulatory Networks 13

Multi-Objective Trapping of UAVs Swarm Based on Gene Regulat...

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13th IEEE international conference on CYBER technology in Automation, Control, and Intelligent systems, CYBER 2023

作者： Xu, Peng Shi, Ze Fan, Zhun College of Engineering International Cooperation Base of Evolution Intelligence and Robotics of Guangdong Province Shantou University Shantou515063 China

ISBN: (纸本)9798350315196

Encirclement mode formation in swarm robotic systems is a long-term hot research topic. Most of the encirclement control models designed by traditional methods are based on global information. This paper proposes a distributed unmanned swarm control method. The approach is based on gene regulatory network models and does not rely on any direct communication. The gene regulatory network model will generate a concentration field based on the input target and obstacle information, which will be used by the unmanned swarm to autonomously assign targets and guide the unmanned swarm to move towards the target. In this method, the UAV only needs to obtain the local information within the sensing range through the sensors carried by itself, and can complete the assignment and encirclement tasks of multiple targets by itself, getting rid of the unmanned swarm's dependence on global information. Finally, the validity and reliability of the proposed model are verified by simulating in an obstacle environment. © 2023 IEEE.

关键词： Genes

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A Non-Local Means Algorithm-based Raman-OTDR for High-Performance Distributed Temperature Sensing 15

A Non-Local Means Algorithm-based Raman-OTDR for High-Perfor...

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15th international conference on Information Optics and Photonics, CIOP 2024

作者： Yan, Ziheng He, Jun Du, Bin Xu, Xizhen Xu, Baijie Li, Zhuoda Wang, Yiping Key Laboratory of Optoelectronic Devices and Systems Ministry of Education/Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors Shenzhen University Shenzhen518060 China

ISBN: (数字)9781510686175

ISBN: (纸本)9781510686168

Raman-optical-time-domain-reflectometry (R-OTDR) based distributed temperature sensing (DTS) is of great significance in extremely harsh environment. In this work, we propose a non local means (NLM) algorithm for R-OTDR performance improvement without modifying the hardware architecture. The NLM algorithm real-time reconstruct the two-dimensional temperature image by utilizing a first-in-first-out data transmission protocol. These images are incorporated to mitigate the complexity of calculating Euclidean distances between neighborhoods within two-dimensional spatial-temporal domains. This approach significantly improves the response speed of the system. To verify the sensing performance improvement of the NLM, we built a standard R-OTDR system and affirm the seamless continuity of temperature variations spanning a broad range from 40 °C to 80 °C over an extensive distance of 9.68 km assisted by a standard platinum resistor. The temperature accuracy decreases from 1.4 °C to 0.55 °C at sensing temperature of 100 °C. The results effectively reconcile the conventional trade-off between high temperature resolution and high-speed response. What’s more, an average temperature resolution is 0.05 °C at the end of fiber. In all, the Raman DTS system based on NLM algorithm achieve high temperature resolution. This achievement holds immense potential for diverse applications, including dynamic monitoring in the realms of energy development, oil and gas exploration, allied fields, and so on. © 2024 SPIE.

关键词： Optical fibers

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Research on interference avoidance technology for low Earth orbit satellite based on spatial processing 2

Research on interference avoidance technology for low Earth ...

引用

2nd international conference on signal image Processing and Communication, ICSIPC 2022

作者： Zhao, Changlin Liu, Ziwei Zhang, Gengxin College of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications Jiangsu Nanjing210003 China

ISBN: (纸本)9781510657694

With the rapid development of low earth orbit (LEO) satellite systems, the interference between LEO satellite constellations using the same frequency has become increasingly prominent. Because of the large number and high dynamic characteristic of LEO systems, the traditional interference avoidance methods have great limitations. based on existing interference avoidance methods, this paper establishes a mathematical model of the interference avoidance for LEO satellite systems, and proposes an interference avoidance method using spatial processing. Aiming at the fatal main lobe interference avoidance problem, the method turns main lobe interference into side lobe interference by switching the beam of earth station to other satellites within the visual range. Then it uses adaptive beamforming method of side lobe null broadening to suppress side lobe interference in high dynamic environment. The interference scenario between OneWeb and Starlink constellations is used for simulation. The results turn out that the proposed method can effectively reduce the interference between LEO constellations and improve the link quality. © 2022 SPIE.

关键词： Orbits

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4th international conference on 3D Imaging Technologies- Multidimensional signal Processing and Deep Learning, 3D IT-MSP&DL 2022

4th International Conference on 3D Imaging Technologies- Mul...

引用

4th international conference on 3D Imaging Technologies- Multidimensional signal Processing and Deep Learning, 3D IT-MSP and DL 2022

ISBN: (纸本)9789819912292

The proceedings contain 51 papers. The special focus in this conference is on 3D Imaging Technologies- Multidimensional signal Processing and Deep Learning. The topics include: Research on the Application of 3D Modeling technology in Mechanical Structure Teaching;2D Numerical Model Used to Investigate the Influence of Vegetation on Geomorphological Evolution of Mudflats;design and Experimental Verification of High Functional Density Cubesat System;space Design of Exhibition Hall based on Virtual Reality;Identification of Expressway Traffic States based on the Enhanced FCM Algorithm;algorithms Applied in Soft Tissue Deformation Simulation: A Survey;soft Tissue Cutting based on Position Dynamics;research on Application technology of Multi-source Fusion of 3D Digital Resources in Power Grid;rapid Identification of Herbaceous Biomass based on Raman Spectrum Analysis;a Knowledge Representation Method for Hierarchical Diagnosis Decision-Making Under Uncertain Conditions;research on Spam Detection with a Hybrid Machine Learning Model;research on Weld Defect Object Detection based on Multi-channel Fusion Convolutional Neural Network;Design and Research of Highway Tunnel Construction Positioning System based on UWB;research on Cross Domain Data Analysis and Data Mining technology of Power Grid Digital Benefits;graph Convolutional Neural Networks for Drug Target Affinity Prediction in U-Shaped and Skip-Connection Architectures;SOC Estimation of Lithium Titanate Battery based on Variable Temperature Equivalent Model;research and Implementation of Hybrid Storage Method for Multi-source Heterogeneous Data of Electric Distribution Network;Research on Measuring Method of Ball Indentation based on MATLAB image Edge Detection;multi-feature Extraction of Mineral Zone of Tabling Through Deep Semantic Segmentation.

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DID-IDS: A Novel Diffusion-based Imbalanced Data Intrusion Detection System 11

DID-IDS: A Novel Diffusion-based Imbalanced Data Intrusion D...

引用

2023 IEEE 11th international conference on Information, Communication and Networks, ICICN 2023

作者： Zhang, Wenxin Chen, Zijie Chen, Dongwei Li, Jianqing Pan, Yuanyuan Macau University of Science and Technology School of Computer Science and Engineering China Zhuhai China

ISBN: (纸本)9798350314014

With the continuous expansion of the volume of internet, the methods and forms of network attacks have also improved and developed, which requires advanced intrusion detection system. Although deep learning methods achieve remarkable success in the accuracy of intrusion detection over traditional methods, a great number of balanced data are required in the training process. However, in the real-life circumstance, the ratio between benign and abnormal data is not balanced. To address this issue, this paper proposes a novel intrusion detection system, called Diffusion-based Imbalanced Data Intrusion Detection System (DID-IDS). In this system, in order to enhance the correlation between data features, the table data are firstly transformed into the image data. Then, the converted images are sent to the diffusion model to generate high-quality fake images for data enhancement purposes. Finally, the enhanced data set is used to train the Convolutional Neural Network (CNN) model for intrusion detection to improve prediction accuracy. The experimental results show that the proposed system has better performance compared to intrusion detection systems using traditional or Generative Adversarial Networks (GAN) based data augmentation methods. © 2023 IEEE.

关键词： Deep learning

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Enhancing IoT-Edge Computation with Data Forwarding based Decentralized Deep Neural Networks 7

Enhancing IoT-Edge Computation with Data Forwarding based De...

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7th international conference on image Information Processing, ICIIP 2023

作者： Prasad, B.M.G. Jopate, Rachappa Savita, Pankaj Basi Reddy, A. Shankar, B. Prabu Arunkumar, M.S. Department of Cse Andhra Pradesh Kurnool518452 India University of Technology And Applied Sciences - Al Mussanah Department of Information Technology Al Muladha Muscat Oman Sagar Institute of Science & Technology Bhopal Organization-Sagar Institute of Science & Technology Department of Cse Madhya Pradesh Bhopal India Mohan Babu University School of Computing Department of Computer Science And Engineering Andhra Pradesh Tirupati India Alliance University Alliance College of Engineering And Design Department of Computer Science And Engineering Karnataka Banglore India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science And Technology Department of Computer Science And Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350371406

The incorporation of edge computing has become essential in the big data and internet of Things age to tackle issues related to latency, real-time processing, and data scale. This paper delves into the imperative need for edge computing within the context of big data environments. Distributed deep learning methodologies are explored, encompassing a diverse array of deep learning models. Particularly, a novel paradigm named Data Forwarding based Decentralized Deep Neural Network (DF-DDNN) is introduced to achieve low latency IoT-Edge computation. In order to reduce latency in Io T ecosystems, the DF-DDNN model makes use of edge devices' processing capabilities. By strategically distributing data processing and computation at the edge, this model seeks to overcome inherent limitations of conventional Io T architectures, with a keen focus on network, processing, and overall latencies. The research provides a thorough performance evaluation that compares the DF-DDNN model's performance versus conventional IoT models in a number of areas. The outcomes demonstrate how much better the suggested DF-DDNN model is than traditional IoT systems. Notably, improvements are evident in terms of reduced network latency, accelerated processing speeds, and overall latency mitigation. This research underscores the critical importance of embracing edge computing in the context of big data and deep learning applications. The DF-DDNN model emerges as a promising avenue for advancing IoT-Edge computation, effectively addressing latency concerns and augmenting the performance of IoT-enabled systems. © 2023 IEEE.

关键词： Edge computing

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LUT-based Area-Optimized Accurate Multiplier Design for signal Processing Applications 4th

LUT-Based Area-Optimized Accurate Multiplier Design for Sign...

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4th EAI international conference on Cognitive Computing and Cyber Physical systems, IC4S 2023

作者： Satyanarayana, B.V.V. Lakshmi, B. Kanaka Sri Kumar, G. Prasanna Srinivas, K. Department of ECE Vishnu Institute of Technology Bhimavaram534202 India

ISBN: (纸本)9783031488870

Multipliers play a role in various aspects of smart cities, which can be used in many applications like Traffic management, energy management and environmental management etc. The wide variety of applications of multipliers are in the field of signal processing and image processing. FPGA design of multiplier is one of the complex tasks in Digital electronics. Most of the designs uses DSP blocks, these multipliers are complex and occupies much area in FPGA. Accurate multiplier design with low area on FPGA is the challenging task. The proposed method is accurate multiplier design, which is designed only using lookup table (LUT). The proposed design has low power and reduced area because of using simple LUT’s for generating partial product. The proposed accurate multipliers reduce 10% less Hardware on vertex 7 FPGA compared to existing designs. © 2024, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Field programmable gate arrays (FPGA)

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