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Advances in Artificial Intelligence, Big Data and Algorithms - Proceedings of the 3rd international conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2023

Advances in Artificial Intelligence, Big Data and Algorithms...

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3rd international conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2023

ISBN: (纸本)9781643684444

The proceedings contain 149 papers. The topics discussed include: effects of AI on smart agriculture: a case study of digital agriculture base;image retrieval-based product identification for automatic checkout systems;application of lightweight emotion recognition model in intelligent construction site monitoring;research on the application of smart wearable in the emotional management of the elderly;artificial intelligence technology in the field of broadcasting and hosting;intelligent inspection method for photovoltaic modules based on image processing and deep learning;application of AI algorithms in power system load forecasting under the new situation;research on the intelligent operation and maintenance control system of power distribution network based on big data technology;research progress of intelligent rail transit train control system;and design and implementation of intelligent potted plant management system based on internet of Things.

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Why ET Can't Phone Home: A Global View on IP-based Geoblocking at VoWiFi 24

Why ET Can't Phone Home: A Global View on IP-based Geoblocki...

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22nd Annual international conference on Mobile systems, Applications and Services (MOBISYS)

作者： Gegenhuber, Gabriel K. Frenzel, Philipp E. Weippl, Edgar Univ Vienna Fac Comp Sci Doctoral Sch Comp Sci Vienna Austria SBA Res Vienna Austria Univ Vienna Fac Comp Sci Vienna Austria

ISBN: (纸本)9798400705816

In current cellular network generations (4G, 5G) the IMS (IP Multimedia Subsystem) plays an integral role in terminating voice calls and short messages. Many operators use VoWiFi (Voice over Wi-Fi, also Wi-Fi calling) as an alternative network access technology to complement their cellular coverage in areas where no radio signal is available (e.g., rural territories or shielded buildings). In a mobile world where customers regularly traverse national borders, this can be used to avoid expensive international roaming fees while journeying overseas, since VoWiFi calls are usually invoiced at domestic rates. To not lose this revenue stream, some operators block access to the IMS for customers staying abroad. This work evaluates the current deployment status of VoWiFi among worldwide operators and analyzes existing geoblocking measures on the IP layer by measuring connectivity from over 200 countries. We show that a substantial share (IPv4: 14.6%, IPv6: 65.2%) of operators implement geoblocking at the DNS- or VoWiFi protocol level, and highlight severe drawbacks in terms of emergency calling service availability.

关键词： geoblocking telecommunication roaming cellular networks mobile networks VoWiFi Wi-Fi calling IMS net neutrality censorship network measurements

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Comparison of CTR-OFB Modes for AES-256-based InSAR Interferogram Encryption with a GEFFE Key Generator 6

Comparison of CTR-OFB Modes for AES-256-based InSAR Interfer...

引用

6th international conference on Pattern Analysis and Intelligent systems, PAIS 2024

作者： Benamara, Karim Saidi, Riad Bentahar, Tarek Djellab, Hanane Cherrid, Nada Belhocine, Yacine University Echahid Cheikh Larbi Tebessi Laboratory of Mathematics Informatics And Systems Electrical Engineering Department Tébessa Algeria University Mustapha Ben Boulaid Batna2 Common Base Science And Technology Department Batna Algeria University Echahid Cheikh Larbi Tebessi Electrical Engineering Department Tébessa Algeria University Guelma Lti Laboratory of Guelma Algeria University Mustapha Ben Boulaid Batna2 Electronic Department Batna Algeria

ISBN: (纸本)9798350350265

In order to secure transmitted satellite images, in particular interferograms from inSAR systems, and to guarantee their original quality, different encryption algorithms are used. Considering the limited computing resources and power for the proper functioning of satellites, taking into account the very difficult working environment which creates defects caused by radiation in on-board electronics, especially in encryption systems. A comparison is made in this work between the use of two encryption modes: Cipher FeedBack (CFB) and Counter-mode encryption (CTR), with a cryptosystem based on AES-256 using a key generated by a GEFFE generator, In order to measure the effectiveness of these two modes in securing InSAR interferograms, an analysis of the quality of this specific type of satellite image is conducted before and after encryption by comparing the original interferogram with the decrypted one. To perform this analysis, several quantitative metrics are used, including structural similarity index (SSIM), SHA-256 hash function, Mean Squared Error (MSE), Peak signal-toNoise Ratio (PSNR), and statistical analysis, such as the analysis of original histograms, encrypted, and decrypted interferograms, as well as a differential analysis, where the results obtained were satisfactory for both modes, showing that the OFB mode is the most suitable for securing this type of satellite image. © 2024 IEEE.

关键词： Hash functions

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Research on image Recognition Method and Personalized Recommendation Model based on Deep Learning 5

Research on Image Recognition Method and Personalized Recomm...

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5th international conference on Artificial Intelligence and Advanced Manufacturing, AIAM 2023

作者： Liu, Feng Guo, Weiwei Department of Electrical and Information Engineering Heilongjiang University of Technology JiXi China

ISBN: (纸本)9781839539848

In response to the problems of low accuracy and poor user experience caused by cold start and incomplete consideration of user timing preferences in traditional recommendation systems, the article proposes an image recognition method and personalized recommendation model based on deep learning. The model is based on a short-term and short-term memory network model, first extracting keywords from user behavior item features, and establishing feature vectors between user behavior and images;Then, the feature vectors of user behavior and images are sorted in chronological order to obtain a list of user interest points. Then, feature maps and cosine similarity are used to calculate the similarity between images, and the target user's preference for different feature keywords is obtained, providing a data basis for personalized recommendations;finally, by repeatedly adjusting the training parameters through the constructed deep training model, a more accurate recommendation list is obtained. The recommendation algorithm is linearly combined with image similarity to provide personalized recommendations for users. Obtaining test data through the internet, identifying selected images, obtaining personalized recommendation lists through recognition results, and comparing them with traditional methods. After comparative analysis, the proposed image recognition method has higher recommendation accuracy compared to the recommendation model. © The Institution of Engineering & technology 2023.

关键词： Recommender systems

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A classroom student behavior detection model based on coordinate attention and fused residual networks along with its talent evaluation system 3

A classroom student behavior detection model based on coordi...

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3rd international conference on Advanced Algorithms and signal image Processing, AASIP 2023

作者： Zhang, Yang Du, Changyu Ji, Peng Zhao, Lei Sun, Qiao Qu, Chuanzhe Beijing Fibrlink Communcations Co. Ltd State Grid Information and Telecommunction Co. Ltd Beijing China

ISBN: (纸本)9781510668522

With the continuous development of the internet+ education concept and the rapid advancement of online, offline, and blended teaching technologies, the existing methods of evaluating students based on teachers' subjective opinions are insufficiently objective and lack a solid foundation. To improve this situation, we propose a classroom student behavior detection model based on coordinate attention and fused residual networks, along with its talent evaluation system. The classroom student behavior detection model, based on coordinate attention and fused residual networks, effectively combines the coordinate attention mechanism and residual networks. It highlights the relevant information in student image samples by effectively utilizing channel and spatial information. The talent evaluation system accumulates and analyzes classroom data through the first application terminal, forming a learning quality report that judges the quality of talent training and provides type information of talent training. Additionally, the system receives human resource information data through the second data terminal and performs employment classification based on talent information data, obtaining occupational tendency data. Therefore, this thesis will help enhance the reliability and accuracy of human resource judgment and increase the compatibility between human resources and careers. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Quality control

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RF signal Classification-based Drone Identification with Multimodal Database 23

RF Signal Classification-based Drone Identification with Mul...

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23rd IEEE international conference on Communication technology, ICCT 2023

作者： Mao, Shengjian Yu, Ningning Li, Miao Zhou, Chengwei Shi, Zhiguo College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province China International Joint Innovation Center Zhejiang University Haining314400 China

ISBN: (纸本)9798350325959

The aim of this paper is to conduct a comprehensive review of existing UAV classification and identification methods. We will analyze the evolution of these methods and propose an anti-UAV RF detection and identification technique based on a self-constructed UAV RF signal dataset. This dataset utilizes a Universal Software Radio Peripheral (USRP) to capture the communication RF signals of 24 UAVs within an urban environment. Subsequently, we will undertake feature extraction and time-frequency signal statistical analysis of various UAV RF signals. We will employ machine learning methods for Classification-based Drone Identification. Our ultimate objective is to achieve UAV signal identification and classification using optimization techniques within a reasonable time frame. © 2023 IEEE.

关键词： RF database RF signal signal identification UAV identification USRP

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Deep Learning-based Noise Reduction Techniques in Electronic signal Processing 9

Deep Learning-Based Noise Reduction Techniques in Electronic...

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9th international conference on Science, technology, Engineering and Mathematics, ICONSTEM 2024

作者： Johari, Lalit Ramya, P. Suganya, M. Praveena, Hirald Dwaraka Lathamageshwari, P.S. Rajendiran, M. Iftm University Department of Computer Applications Uttar Pradesh Moradabad244102 India Bannari Amman Institute of Technology Department of Electronics And Communication Engineering Tamil Nadu Sathyamangalam638401 India Annapoorana Engineering College Department of Electronics And Communication Engineering Tamil Nadu Salem636308 India Department of Electronics And Communication Engineering Andhra Pradesh Tirupati517102 India Tamil Nadu Kavaraipettai601206 India Panimalar Engineering College Department of Computer Science And Engineering Tamil Nadu Chennai600123 India

ISBN: (纸本)9798350365092

This paper explores the operation of deep literacy- grounded noise reduction ways in electronic signal processing. Noise hindrance poses a significant challenge in colorful signal processing operations, impacting the delicacy and trustability of data analysis and interpretation. Traditional noise reduction styles frequently calculate on heuristic approaches or signal processing algorithms, which may have limited effectiveness, especially in complex and dynamic surroundings. In discrepancy, deep literacy algorithms, similar as convolutional neural networks(CNNs) and intermittent neural networks(RNNs), offer promising results for noise reduction by learning complex patterns and connections directly from data. This paper determines the state- of- the- art deep literacy- grounded noise reduction ways, including denoising autoencoders, generative inimical networks(GANs), and intermittent neural network- grounded models. Case studies and experimental results demonstrate the effectiveness and performance of these ways in colorful signal processing tasks, similar as audio denoising, image restoration, and biomedical signal processing. The integration of deep literacy- grounded noise reduction styles into electronic signal processing systems shows significant eventuality for perfecting signal quality and enhancing the delicacy of data analysis in different operations. © 2024 IEEE.

关键词： Recurrent neural networks

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Blockchain based System for Secure Production Information Management 8

Blockchain Based System for Secure Production Information Ma...

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8th international conference on Communication, image and signal Processing, CCISP 2023

作者： Yuanyuan, Liu Qianyi, Zhan Zhenping, Xie Yuan, Liu College of Artificial Intelligence and Computer Jiangnan University WuXi China Jiangnan University Jiangsu Key Laboratory of Media Design and Software Technology WuXi China Jiangnan University Jiangsu Key Laboratory of Media Design and Software WuXi China

ISBN: (纸本)9798350305838

In the field of production, the collection, transmission, and storage of production information have a significant impact on production management. This paper proposes a blockchain-based secure production information storage and management system to address the issues of incomplete information collection, unreliable data transmission, and data isolation in traditional production information management systems. The system leverages the immutability and decentralization properties of blockchain technology to enable secure and efficient storage and transmission of the data. Moreover, a 'step-hyperledger' structural mode is established for various business links in the pre-production, during-production, and post-production processes of safety production to achieve hierarchical management of data storage and full-process traceability. Combined with big data analysis techniques, the system facilitates effective pre-warning and efficient accountability after an incident. Simulation experiments and stress tests are conducted to validate the traceability interface of the system. The results indicate that the system demonstrates good stability even under the condition of multiple concurrent users, meeting the expected requirements and exhibiting certain advantages over traditional safety production systems. © 2023 IEEE.

关键词： Blockchain

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Research on IR-RGB image Fusion Method based on Target Perception and Hue Correction

Research on IR-RGB Image Fusion Method Based on Target Perce...

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international conference on Communications, signal Processing, and systems, CSPS 2023

作者： Jiang, Qianjun Lin, Di Hao, Zongbo Chang, He Li, Xin University of Electronic Science and Technology of China Sichuan Chengdu China

ISBN: (纸本)9789819975396

In this paper, a hue-corrected IR-RGB fusion method is proposed based on object perception. We use the salient object detection network to detect the original IR image to obtain the salient regions in the image and then use the object bounding box in the dataset label to remove the noise information and retain the object area of interest. In order to implement different fusion schemes for the target area and the background area in the model, this paper trains a generator to synthesize the target fusion image, trains the target discriminator to identify the pixel intensity and hue information of the target *** trains the background discriminator to identify Gradient information for the background. To improve the performance of downstream object detection tasks, an object detection network is added to the generative model, and an object detection loss is used to guide image fusion. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Generative adversarial networks

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An Encrypted Data System for EDGE-based Steganography-based Message Disbursement in images 6th

An Encrypted Data System for EDGE-Based Steganography-Based ...

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6th international conference on Smart Computing and Informatics, SCI 2024

作者： Sruthi, Pinamala Bhaskar, T. Reddy, Avala Raji Vinesh Shanker, G. Golla, Venkateswarlu Prathima, Y. CMR College of Engineering and Technology Telangana Hyderabad India Department of CSE CMR College of Engineering and Technology Telangana Hyderabad India Department of Mechanical Engineering CMR Technical Campus Telangana Hyderabad India Department of CSE CMR Technical Campus Telangana Hyderabad India CMR Engineering College Telangana Hyderabad India Department of CSE CMR Engineering College Telangana Hyderabad India

ISBN: (纸本)9789819619801

Data security is seen as an essential issue in the modern society. There are several ways to send data via the internet. Therefore, there needs to be data security between the sender and the recipient. One method of concealing information within other forms of media so that it is undetectable is steganography. images are typically regarded as cover media in steganography owing to their high representational redundancy and widespread usage online. Because of their tiny size, content versatility, and visual robustness, images are frequently used in cover media. This makes them an excellent medium for sending covert messages throughout the internet. In this work, edge-based steganography is used to conceal data in an image by hiding it in the image’s edge pixels. The edge detection process uses the Canny Edge Algorithm. With this approach, the total quantity of data to be embedded is taken into consideration while choosing edges;that is, the more data to be incorporated, the more weak connections in the image are used for embedding. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Steganography

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