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A versatile framework for analyzing galaxy image data by incorporating Human-in-the-loop in a large vision model

Chinese Physics C 2024年第9期48卷 176-187页

作者： Ming-Xiang Fu Yu Song Jia-Meng Lv Liang Cao Peng Jia Nan Li Xiang-Ru Li Ji-Feng Liu A-Li Luo Bo Qiu Shi-Yin Shen Liang-Ping Tu Li-Li Wang Shou-Lin Wei Hai-Feng Yang Zhen-Ping Yi Zhi-Qiang Zou National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China College of Electronic Information and Optical Engineering Taiyuan University of TechnologyTaiyuan 030024China School of Astronomy and Space Science University of Chinese Academy of SciencesBeijing 101408China Key lab of Space Astronomy and Technology National Astronomical ObservatoriesBeijing 100101China School of Computer Science South China Normal UniversityGuangzhou 510631China CAS Key Laboratory of Optical Astronomy National Astronomical ObservatoriesBeijing 100101China University of Chinese Academy of Sciences NanjingNanjing 211135China University of Science and Technology Beijing Beijing 100083China Shanghai Astronomical Observatory Chinese Academy of SciencesShanghai 200030China School of Computer and Information Dezhou UniversityDezhou 253023China Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China School of Computer Science and Technology Taiyuan University of Science and TechnologyTaiyuan 30024China School of Mechanical Electrical and Information EngineeringShandong UniversityWeihai 264209China Nanjing University of Posts&Telecommunications Nanjing 210023China School of Science University of Science and Technology LiaoningAnshan 114051China

The exponential growth of astronomical datasets provides an unprecedented opportunity for humans to gain insight into the ***,effectively analyzing this vast amount of data poses a significant *** response,astronomers are turning to deep learning techniques,but these methods are limited by their specific training sets,leading to considerable duplicate *** overcome this issue,we built a framework for the general analysis of galaxy images based on a large vision model(LVM)plus downstream tasks(DST),including galaxy morphological classification,image restoration object detection,parameter extraction,and *** the low signal-to-noise ratios of galaxy images and the imbalanced distribution of galaxy categories,we designed our LVM to incorporate a Human-in-the-loop(HITL)module,which leverages human knowledge to enhance the reliability and interpretability of processing galaxy images *** proposed framework exhibits notable fewshot learning capabilities and versatile adaptability for all the abovementioned tasks on galaxy images in the DESI Legacy Imaging *** particular,for the object detection task,which was trained using 1000 data points,our DST in the LVM achieved an accuracy of 96.7%,while ResNet50 plus Mask R-CNN reached an accuracy of 93.1%.For morphological classification,to obtain an area under the curve(AUC)of~0.9,LVM plus DST and HITL only requested 1/50 of the training sets that ResNet18 *** addition,multimodal data can be integrated,which creates possibilities for conducting joint analyses with datasets spanning diverse domains in the era of multi-messenger astronomy.

关键词： artificial intelligence large vision model human-in-the-loop astronomy galaxies

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A Robust Key Exchange and Tamper-Resistant Protocol for HAN and NAN Networks in Smart Grids

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IEEE Internet of Things Journal 2025年第12期12卷 21394-21403页

作者： Ayub, Muhammad Faizan Li, Xiong Mahmood, Khalid Shamshad, Salman Das, Ashok Kumar Wang, Guijuan University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu611731 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Korea University College of Informatics Department of Computer Science and Engineering Anam-ro Seoul145 Korea Republic of Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250353 China

Smart Grids (SG) rely on Home Area Networks (HAN) and Neighborhood Area Networks (NAN) to ensure efficient power distribution, real-time monitoring, and seamless communication between smart devices. Despite these advantages, the use of public communication channels in HAN and NAN networks introduces critical challenges, such as vulnerability to impersonation, physical tampering, and scalability issues in resource-constrained environments. These issues compromise the stability, reliability, and security of SG environments. Existing protocols often fail to adequately address these challenges, particularly in ensuring resistance to physical tampering of supply lines and impersonation attacks. Additionally, they struggle to minimize the computation, communication, and energy costs associated with securing a resource-constrained SG environment. Therefore, we propose a robust key exchange and tamper-resistant protocol for HAN and NAN networks to address these limitations. The proposed protocol leverages the Physical Unclonable Function (PUF) mechanism to offer physical tampering resistance to smart meters. We validate our protocol formally using the Random or Real (RoR) model, which confirms its security robustness. Additionally, our informal security analysis highlights the protocol's resilience against impersonation, physical tampering attacks, etc. We analyze and compare the performance of the proposed protocol, which further demonstrates our protocol's effectiveness and security compared to competing protocols. Moreover, the proposed protocol achieves resource efficiency with 45.99% and 58.85% substantial reductions in computation overhead and energy overhead, respectively, compared to competing protocols. These results showcase the protocol's enhanced security and practicality for resource-constrained SG environments. © 2014 IEEE.

关键词： Authentication Protocol

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CodGRU: Covariate gated attention GRU for short term runoff forecasting 24

CodGRU: Covariate gated attention GRU for short term runoff ...

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4th International Conference on Signal Processing and Communication technology, SPCT 2024

作者： Cao, Jiahao Xiao, Tong Cao, Zhe School of Computer Science and Engineering Chongqing University of Science and Technology Chongqing China Shenzhen Branch of China Academy of Urban Planning and Design Guangdong Shenzhen China

ISBN: (纸本)9798400710636

Runoff simulation and forecasting are critical for effective watershed management, yet their complexity and nonlinear characteristics pose significant challenges. The generation of runoff is the result of the interaction between multiple factors such as precipitation, soil moisture, topography, and human activities, making this dynamic process extremely complex and difficult to model accurately. Traditional models are often based on an understanding of these natural processes but may fall short when dealing with complex real-world scenarios. To address these issues, this study has developed a dynamic gated feature selection model with attention mechanisms (CodGRU), specifically designed for multi-watershed hourly runoff forecasting. By dynamically adjusting the weights of input variables and selecting the most important features, CodGRU can better capture the key factors influencing runoff, thereby improving the accuracy of forecasting. The test results of five watersheds on the real dataset show that the CodGRU model performs excellently in multi-watershed hourly-scale forecasting, outperforming the existing mainstream models and providing reliable support for water resource management and disaster forecasting and mitigation. © 2024 Copyright held by the owner/author(s).

关键词： Soil moisture

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Intelligent Monitoring System for Automatic Air Conditioning System 5

Intelligent Monitoring System for Automatic Air Conditioning...

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5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Manikandan, P. Swedheetha, C. Ram Mohan, R.L. Kumar, Sandala Likith Reddy, Peram Damodar Sri Sai, Pachabotla Adithya Kalasalingam Academy of Research and Education Department of Electronics and Communication Engineering Krishnankoil India Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India

ISBN: (纸本)9798331518097

In order to improve indoor air quality, optimize energy consumption and avoid the accidents due to gas leakage, this paper proposes an intelligent air conditioning system that integrates several sensors such as DHT11, PIR sensors, MG6 Gas sensor and PMS7003 sensor and control mechanisms. An Arduino Mega, the system's central component, synchronizes data from several sensors to efficiently control the air conditioner and other linked equipment. This system keeps track of how many people enter and leave the space, enabling the air conditioning system to modify its settings in real time according to occupancy. When the room is empty, this feature saves energy. If gas leakage is present, system notifies users through a buzzer and turn off the AC. Many users often forget to clean their AC filters regularly, which can lead to reduced efficiency, higher energy consumption, and poorer air quality. Our innovative AC system addresses this common issue. Once the dust level crosses a predefined threshold, the system triggers a clean filter alert, reminding to act before it affects performance. Also, the air conditioner kicks on to cool the room if the outside temperature is high and the inside temperature is higher than an acceptable level. In contrast, the air conditioner is shut off to avoid needless cooling if the inside temperature is low. A display unit shows temperature, humidity, occupancy, gas levels, and dust concentration. This integrated technique automatically modifies the system's operation based on conditions, ensuring not only a more hygienic and comfortable environment but also improved energy efficiency © 2024 IEEE.

关键词： Air quality

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Robust Malicious Domain Detection Based on Spatio-Temporal Hypergraph Networks 22

Robust Malicious Domain Detection Based on Spatio-Temporal H...

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22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Gong, Liangyi Lv, Kunxian Long, Chun Fu, Hao Wang, Huanran Wan, Wei Yang, Wu Chinese Academy of Sciences Computer Network Information Center Beijing China University of Chinese Academy of Sciences Beijing China Harbin Engineering University School of Computer Science and Technology Heilongjiang China

ISBN: (纸本)9798331509712

Malicious domains serve as significant resources for adversaries to execute cyber attacks and are crucial indicators for detecting network intrusions. In practical scenarios, malicious domains associated with various attacks are intermingled within DNS traffic, leading to variability in the performance of machine learning-based detection methods. To address this challenge, we have collected extensive DNS traffic data spanning 12 months from a real-world large-scale network with 1 million users. From this dataset, we have extracted numerous requested domains, encompassing 267 attacks that exploit malicious domain names. Furthermore, we have observed that the distinct properties of malicious domains associated with different attacks contribute to the fluctuating performance of machine learning-based detection models. Consequently, we have introduced a spatiotemporal hypergraph network model, which establishes high-order relationships among domain properties to enhance the generalization capability and robustness of the detection model. The results of extensive testing experiments demonstrate that our model achieves remarkable performance, with an average precision of 97% and recall of 98%. © 2024 IEEE.

关键词： Network intrusion

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Predictive Modeling Techniques of Social Dynamics in Multilayer Social Networks: A Survey 4th

Predictive Modeling Techniques of Social Dynamics in Multila...

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4th International Conference on Smart Systems: Innovations in Computing, SSIC 2023

作者： Jaya Krishna, Raguru Vamshi Krishna, B. Gopalakrishnan, T. Anagha, P. Kumar Sharma, Vijay Prasad Sharma, Devi Department of Computer Science and Engineering Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India Department of Computer and Communication Engineering and Department of Information Technology Manipal University Jaipur Jaipur India

ISBN: (纸本)9789819736898

Various techniques involved in analyzing social media data have become an important aspect of research. There is a need for efficient techniques to explore huge amounts of data for information prediction like product rating, political election prediction, viral marketing, and information cascading, etc. Nowadays multilayer social networks offer huge platforms for getting opinion reviews and recommendations about any user-interested topic. In multilayer social networks, multiple users are connected and the relationship between them is represented in different layers indicating different connections and interactions. Network structure is more complex and the social interactions between the individuals are dynamic in nature. This study reviews a thorough overview of multilayer social network predictive modeling methodologies and examines contemporary multilayer social network algorithms that have been published in the literature. In addition, we also discussed various key issues and algorithms to address the issues. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Prediction models

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Enhancing Storage and Computational Efficiency in Federated Multimodal Learning for Large-Scale Models 41

Enhancing Storage and Computational Efficiency in Federated ...

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41st International Conference on Machine Learning, ICML 2024

作者： Zhang, Zixin Qi, Fan Xu, Changsheng School of Computer Science and Engineering Tianjin University of Technology Tianjin China Institute of Automation Chinese Academy of Sciences Beijing China

The remarkable generalization of large-scale models has recently gained significant attention in multimodal ***, deploying heterogeneous large-scale models with different modalities under Federated Learning (FL) to protect data privacy imposes tremendous challenges on clients' limited computation and *** this work, we propose M2FEDSA to address the above *** realize modularized decomposition of large-scale models via Split Learning (SL) and only retain privacy-sensitive modules on clients, alleviating storage *** freezing large-scale models and introducing two specialized lightweight adapters, the models can better focus on task-specific knowledge and enhance modality-specific knowledge, improving the model's adaptability to different tasks while balancing *** addition, M2FEDSA further improves performance by transferring multimodal knowledge to unimodal clients at both the feature and decision levels, which leverages the complementarity of different *** experiments on various multimodal classification tasks validate the effectiveness of our proposed *** code is made available publicly at https://***/M2FedSA/M-2FedSA. Copyright 2024 by the author(s)

关键词： Federated learning

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Comparative Study on the Analysis of the Performance of Transfer Learning and the Customized Convolutional Neural Network to Detect Eyewear 4

Comparative Study on the Analysis of the Performance of Tran...

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4th IEEE Global Conference for Advancement in technology, GCAT 2023

作者： Varun Prakash, J.M. Kodipalli, Ashwini Rao, Trupthi Kumaraswamy, S. Dept of Computer Science and Engineering Global Academy of Technology Karnataka Bangalore India Dept of Artificial Intelligence and Data Science Global Academy of Technology Karnataka Bengaluru India

ISBN: (纸本)9798350305258

In this paper, we propose a method for eyewear detection using Convolutional Neural Networks (CNNs). The objective of the study is to accurately classify images into two classes: "Glasses" and "No Glasses." The proposed approach is evaluated on a dataset comprising a total of 5000 images, with a training set consisting of 1947 images in the "Glasses" class and 1554 images in the "No Glasses" class. The testing set includes 834 images in the "Glasses" class and 665 images in the "No Glasses" class. We evaluate the eyewear detection performance using various evaluation metrics, including accuracy, precision, and recall. The outcomes demonstrate how well the suggested CNN-based technique for eyeglasses detection works. The trained model achieves an overall accuracy of 99.17%, with a precision of 0.76% and a recall of 0.44% on the testing set. The discovery advances the field of computer vision and creates new opportunities for improving eyeglasses detection methods through further additional study. © 2023 IEEE.

关键词： Accuracy Evaluation computer Vision Convolutional Neural Network Eyewear detection Feature Extraction Image Classification

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Achieving high strength-ductility synergy in a Mg_(97)Y_(1)Zn_(1)Ho_(1) alloy via a nano-spaced long-period stacking-ordered phase

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Journal of Magnesium and Alloys 2023年第4期11卷 1321-1331页

作者： Mingyu Fan Ye Cui Yang Zhang Xinghao Wei Xue Cao Peter K.Liaw Yuansheng Yang Zhongwu Zhang Key Laboratory of Superlight Materials and Surface Technology Ministry of EducationCollege of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin 150001PR China College of Computer Science and Technology Harbin Engineering UniversityHarbin 150001PR China Department of Materials Science and Engineering The University of TennesseeKnoxvilleTN 37996-2100USA Institute of Metal Research Chinese Academy of SciencesShenyang 110016PR China

Achieving high strength in Mg alloys is usually accompanied by ductility ***,a novel Mg97Y1Zn1Ho1 at.%alloy with a yield strength of 403 MPa and an elongation of 10%is *** strength-ductility synergy is obtained by a comprehensive strategy,including a lamella bimodal microstructure design and the introduction of nano-spaced solute-segregated 14H long-period stacking-ordered phase(14H LPSO phase)through rare-earth Ho *** lamella bimodal microstructure consists of elongated un-recrystallized(un-DRXed)coarse grains and fine dynamically-recrystallized grains(DRXed regions).The nano-spaced solute-segregated 14H LPSO phase is distributed in DRXed *** outstanding yield strength is mainly contributed by grain-boundary strengthening,18R LPSO strengthening,and fiberlike reinforcement strengthening from the nano-spaced 14H LPSO *** high elongation is due primarily to the combined effects of the bimodal and lamellar microstructures through enhancing the work-hardening capability.

关键词： Mg wrought alloy Mechanical properties Long-period stacking-ordered(LPSO)phase Age-strengthening behavior Strengthening mechanism

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Parallel String Permutation using MPI 15

Parallel String Permutation using MPI

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Saldanha, Blen Joswin Sowjanya Kini, N.Gopalakrishna Rao, Ashwath B. Department of Computer Science and Engineering Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal576 104 India

ISBN: (纸本)9798331300579

A permutation is a mathematical technique for determining the number of possible arrangements in any set where the particular sequence of the arrangements *** of permutations of a string is a complex task, especially for long strings, and it frequently takes a long *** address this issue, parallelization becomes critical to explore the vast solution space *** this paper, the parallelized solution for generating string permutations using the Message Passing Interface (MPI) programming model is *** proposed algorithm divides the workload among multiple processors to render a subset of total *** a comparative analysis with a sequential approach, the performance of the parallel algorithm is *** findings emphasize the potential advantages of parallelization in reducing the overall computation time for string permutation generation. © Grenze Scientific Society, 2024.

关键词： Character sets

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