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AdaPIP: Adaptive picture-in-picture guidance for 360° film watching

Computational Visual Media 2024年第3期10卷 487-503页

作者： Yi-Xiao Li Guan Luo Yi-Ke Xu Yu He Fang-Lue Zhang Song-Hai Zhang Department of Computer Science and Technology Tsinghua UniversityBeijingChinaand Beijing National Research Center for Information Science and Technology(BNRist)Tsinghua UniversityBeijingChina Key Laboratory of Space Utilization Technology and Engineering Center for Space UtilizationChinese Academy of SciencesBeijingChina Victoria University of Wellington WellingtonNew Zealand

360°videos enable viewers to watch freely from different directions but inevitably prevent them from perceiving all the helpful *** mitigate this problem,picture-in-picture(PIP)guidance was proposed using preview windows to show regions of interest(ROIs)outside the current view *** identify several drawbacks of this representation and propose a new method for 360° film watching called *** enhances traditional PIP by adaptively arranging preview windows with changeable view ranges and *** addition,AdaPIP incorporates the advantage of arrow-based guidance by presenting circular windows with arrows attached to them to help users locate the corresponding ROIs more *** also adapted AdaPIP and Outside-In to HMD-based immersive virtual reality environments to demonstrate the usability of PIP-guided approaches beyond 2D *** user experiments on 2D screens,as well as in VR environments,indicate that AdaPIP is superior to alternative methods in terms of visual experiences while maintaining a comparable degree of immersion.

关键词： 360°videos picture-in-picture(PIP) virtual reality(VR) visual guidance

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Temporal Refinement Graph Convolutional Network for Skeleton-Based Action Recognition

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1586-1598页

作者： Zhuang, Tianming Qin, Zhen Ding, Yi Deng, Fuhu Chen, Leduo Qin, Zhiguang Raymond Choo, Kim-Kwang University of Electronic Science and Technology of China Network and Data Security Key Laboratory of Sichuan Province Chengdu Sichuan610054 China University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu Sichuan610054 China School of Advanced Technology Suzhou Jiangsu215123 China University of Texas at San Antonio Department of Information Systems and Cyber Security San AntonioTX78249 United States

Human skeleton data, which has served in the aspect of human activity recognition, ought to be the most representative biometric characteristics due to its intuitivity and visuality. The state-of-the-art approaches mainly focus on improving modeling spatial correlations within graph topologies. However, the interframes motional representations are also of vital importance, and we argue that they are worth paying attention to and exploring. Therefore, a temporal refinement module with contrastive learning mechanism is proposed, fuzing as a complementary to the conventional spatial graph convolution layer. In addition, in order to further exploiting the interframe variances and generalizing graph convolutional network (GCN) operation to temporal dimension, a temporal-correlation matrix is introduced to effectively capture dynamic dependencies within frame-pairs, enhancing semantic feature representation. Moreover, since GCN is a typical local operator which lacks of capability to fully model the long-term relations along spatial and temporal variation, to move beyond the limitation, a spatial-temporal cascaded aggregation (STCA) module is designed to enlarge the receptive filter scale. The overall recognition framework consists of three above novelties, which is capable of achieving remarkable performance by evaluating on benchmark datasets (i.e., NTU RGB+D 60, NTU RGB+D 120, PKU-MMD, and Kinetics Skeleton 400). Extensive experiments demonstrate the effectiveness of the proposed framework, e.g., performing recognition accuracy rate of 90.9% and 96.8% on NTU RGB+D 60, 87.9% and 88.9% on NTU RGB+D 120. © 2020 IEEE.

关键词： Convolution

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Research on De-identification Applications of LLMs in Medical Records

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International Journal of Network Security 2025年第1期27卷 213-222页

作者： Hwang, Min-Shiang Fatima, Kanza Wang, Yang-Shu Wu, Nan-I Lin, Iuon-Chang Department of Computer Science & Information Engineering Asia University 500 Lioufeng Rd. Wufeng Taichung41354 Taiwan Department of Management Information Systems National Chung Hsing University Taiwan Department of Information Management Lunghwa University of Science and Technology Taoyuan33306 Taiwan

The primary objective of this research is to develop and promote efficient and secure de-identification technology to address the application of sensitive personal information in healthcare big data. Considering the outstanding performance of large language models (such as GPT) in understanding text, we aim to utilize these advanced models to process medical records. Compared to traditional methods such as manual processing, rule-based, or machine learning methods, large language models can more effectively de-identify unstructured medical record data. We can enhance the recognition and de-identification accuracy of personal identification information in medical records through deep learning techniques. Additionally, the contextual understanding capabilities of large language models can comprehensively process medical record data, ensuring that the de-identification process does not affect the integrity and availability of medical information. Therefore, the research methodology will include model training, optimization, and validation to ensure that the developed de-identification technology achieves efficient and reliable results in practical applications. We explore different large language models, considering the diversity of personal medical data to address various de-identification needs in different medical record data. In this article, we propose three research issues for de-identification: 1) Research on the application of deep language models and de-identification technology in medical cases;2) optimization of prompt engineering to enhance de-identification of medical cases by large language models;3) Optimization and promotion of de-identification technology for practical applications in the medical. © (2025), (Femto Technique Co., Ltd.). All rights reserved.

关键词： Electronic health record

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Ultrathin BiOCl crystals grown in highly disordered vapor micro-turbulence for deep ultraviolet photodetectors

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Rare Metals 2024年第11期43卷 5921-5931页

作者： Qing Guo Xiu-Jun Wang Lin Wang Xin Ye A-Lei Li Xiao-Hang Pan Yun-Lei Zhong Yong Zhang Li-Xing Kang Key Laboratory of Multifunctional Nanomaterials and Smart Systems Division of Advanced MaterialsSuzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China Key Laboratory of Molecular Optoelectronic Sciences Department of ChemistrySchool of ScienceTianjin UniversityTianjin 300072China School of Electronic and Information Engineering Changshu Institute of TechnologyChangshu 215500China

Crystallization,while a common process in nature,remains one of the most mysterious *** its physical mechanisms is essential for obtaining high-quality ***,crystals grown by thermal evaporation or sublimation nucleate the substrate facing the evaporation ***,a novel vapor micro-turbulence mass transport mechanism in the growth process of ultrathin BiOCl single crystals has been *** this mechanism,the precursor vapor bypasses the solid substrate,forming micro-turbulent vaporizing flows to nucleate on the surface of the substrate facing away from the evaporation *** nucleation kinetics,fast shear flows are known to cause secondary nucleation,increasing nucleation quantity while decreasing the final size of the ***,the nucleation and growth process of BiOCl crystals are controlled by adjusting the micro-turbulence intensity to reduce shear flow energy and dilate phase distribution,resulting in BiOCl crystals with uniform distribution and regular *** structural and morphological characterization confirms the high crystallization quality of the obtained crystals,and the performance of the constructed solar-blind photodetectors is comparable to that of similar *** findings contribute to a deeper understanding of vapor mass transport and crystal growth techniques and may be useful for applications related to metal oxide crystals.

关键词： Ultrathin metal oxides crystals Micro-turbulence Microspacing sublimation Ultraviolet photodetectors Crystallization

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Ordered Clustering-Based Semantic Music Recommender System Using Deep Learning Selection

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Computers, Materials & Continua 2025年第5期83卷 3025-3057页

作者： Weitao Ha Sheng Gang Yahya D.Navaei Abubakar S.Gezawa Yaser A.Nanehkaran School of Computer Science and Technology Weinan Normal UniversityWeinan714099China School of Information&Engineering Yancheng Teachers UniversityYancheng224002China Department of Computer and Technology Engineering Qazvin BranchIslamic Azad UniversityQazvin34199-15195Iran School of Information Engineering Sanming UniversitySanming365004China Department ofManagement Information Systems Faculty of Economics and Administrative SciencesCankayaUniversityAnkara06790Türkiye

Music recommendation systems are essential due to the vast amount of music available on streaming platforms,which can overwhelm users trying to find new tracks that match their *** systems analyze users’emotional responses,listening habits,and personal preferences to provide personalized suggestions.A significant challenge they face is the“cold start”problem,where new users have no past interactions to guide *** improve user experience,these systems aimto effectively recommendmusic even to such users by considering their listening behavior and music *** paper introduces a novel music recommendation system that combines order clustering and a convolutional neural network,utilizing user comments and rankings as ***,the system organizes users into clusters based on semantic similarity,followed by the utilization of their rating similarities as input for the convolutional neural *** network then predicts ratings for unreviewed music by ***,the system analyses user music listening behaviour and music *** popularity can help to address cold start users as ***,the proposed method recommends unreviewed music based on predicted high rankings and popularity,taking into account each user’s music listening *** proposed method combines predicted high rankings and popularity by first selecting popular unreviewedmusic that themodel predicts to have the highest ratings for each *** these,the most popular tracks are prioritized,defined by metrics such as frequency of listening across *** number of recommended tracks is aligned with each user’s typical listening *** experimental findings demonstrate that the new method outperformed other classification techniques and prior recommendation systems,yielding a mean absolute error(MAE)rate and rootmean square error(RMSE)rate of approximately 0.0017,a hit rate of 82.45%,an average normalized discounted cumulative gain

关键词： Music recommender system order clustering deep learning

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Development of an atmospheric fluorocarbon plasma jet generated by pulse modulated microwave discharge

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Plasma science and technology 2023年第11期25卷 91-100页

作者：陈思乐任鑫柳陈兆权徐笑娟程涛李平张冠军卢新培 School of Electrical and Information Engineering Anhui University of TechnologyMa’anshan 243032People’s Republic of China School of Electrical and Information Engineering Anhui University of Science and TechnologyHuainan 232001People’s Republic of China State Key Laboratory of Electrical Insulation and Power Equipment School of Electrical EngineeringXi’an Jiaotong UniversityXi’an 710049People’s Republic of China State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and TechnologyWuhan 430074People’s Republic of China

Atmospheric fluorocarbon plasma plays an important role in the surface modification of insulating materials like *** existing fluorocarbon plasma is usually generated by dielectric barrier discharge,which has a low concentration of reactive species and may cause insufficient surface *** work attempts to develop an atmospheric fluorocarbon plasma jet using a coaxial transmission line resonator by microwave discharge with locally enhanced electric field and high *** gas temperature is reduced by pulse modulation *** kinds of working gases,pure CF_(4),Ar/CF_(4)and He/CF_(4),are utilized to generate the atmospheric microwave fluorocarbon plasma *** discharge images,optical emission spectra,electron densities and gas temperatures are studied *** results show that the Ar/CF_(4)plasma jet has the best comprehensive performance,such as strong discharge intensity and controllable gas *** electron density of the Ar/CF_4plasma jet has a magnitude of 10~(20)m^(-3),indicating a higher density than that of the frequently used dielectric barrier *** the other conditions unchanged,the gas temperature at the end of the Ar/CF_(4)plasma jet can be reduced from 410.2 to 347.3 K by decreasing the duty cycle of the modulated pulse from 0.5 to ***,the microwave Ar/CF_(4)plasma jet is considered to be a promising fluorocarbon plasma source for surface fluorination of polymers.

关键词： microwave discharge atmospheric pressure plasma jet fluorocarbon plasma(Some figures may appear in colour only in the online journal)

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Compound Product of Hypermatrices

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Journal of systems science & Complexity 2024年第1期37卷 169-183页

作者： CHENG Daizhan MENG Min ZHANG Xiao JI Zhengping Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China Department of Control Science and Engineering School of Electronics and Information EngineeringTongji UniversityShanghai 201210China National Center for Mathematics and Interdisciplinary Sciences Chinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100149China.

The semi-tensor product(STP)of matrices is generalized to multidimensional arrays,called the compound product of *** product is first defined for three-dimensional hypermatrices with compatible orders and then extended to general *** different types of hyperdeterminants are introduced and certain properties are *** Lie groups and Lie algebras corresponding to the hypermatrix products are ***,these results are applied to dynamical systems.

关键词： Compound semi-tensor product hyperdeterminants hypereigenvalues and hypereigenvectors hypergeneral linear groups hypermatrices.

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Image Hiding with High Robustness Based on Dynamic Region Attention in the Wavelet Domain

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Computer Modeling in engineering & sciences 2024年第10期141卷 847-869页

作者： Zengxiang Li Yongchong Wu Alanoud Al Mazroa Donghua Jiang Jianhua Wu Xishun Zhu Department of Information Engineering Gongqing CollegeNanchang UniversityJiujiang332020China School of Information Engineering Gongqing Institute of Science and TechnologyJiujiang332020China Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhou511400China School of Information Engineering Nanchang UniversityNanchang330031China School of Mathematics and Statistics Hainan Normal UniversityHaikou571158China

Hidden capacity,concealment,security,and robustness are essential indicators of hiding ***,hiding algorithms tend to focus on algorithmic capacity,concealment,and security but often overlook the robustness of the *** practical applications,the container can suffer from damage caused by noise,cropping,and other attacks during transmission,resulting in challenging or even impossible complete recovery of the secret *** image hiding algorithm based on dynamic region attention in the multi-scale wavelet domain is proposed to address this issue and enhance the robustness of hiding *** this proposed algorithm,a secret image of size 256×256 is first decomposed using an eight-level Haar wavelet *** wavelet transform generates one coefficient in the approximation component and twenty-four detail bands,which are then embedded into the carrier image via a hiding *** the recovery process,the container image is divided into four non-overlapping parts,each employed to reconstruct a low-resolution secret *** lowresolution secret images are combined using densemodules to obtain a high-quality secret *** experimental results showed that even under destructive attacks on the container image,the proposed algorithm is successful in recovering a high-quality secret image,indicating that the algorithm exhibits a high degree of robustness against various *** proposed algorithm effectively addresses the robustness issue by incorporating both spatial and channel attention mechanisms in the multi-scale wavelet domain,making it suitable for practical *** conclusion,the image hiding algorithm introduced in this study offers significant improvements in robustness compared to existing *** ability to recover high-quality secret images even in the presence of destructive attacksmakes it an attractive option for various *** research and experimentation can explore the algorith

关键词： Image hiding robustness wavelet transform dynamic region attention

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Seastar: A Cache-Efficient and Load-Balanced Key-Value Store on Disaggregated Memory

Seastar: A Cache-Efficient and Load-Balanced Key-Value Store...

引用

2024 IEEE International Conference on Cluster Computing, CLUSTER 2024

作者： Du, Jingwen Wang, Fang Feng, Dan Zeng, Dexin Yi, Sheng Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System China School of Computer Science and Technology Huazhong University of Science and Technology China Shenzhen Huazhong University of Science and Technology Research Institute China

ISBN: (纸本)9798350358711

In modern datacenters, memory disaggregation un-packs monolithic servers to build independent network-connected compute and memory pools, greatly improving resource uti-lization. Existing memory-disaggregated key-value stores adopt ownership sharing or ownership partitioning for request scheduling and they all show poor performance and scalability. The former generates multiple cache misses and multiple network round trips due to poor cache locality, while the latter fails to fully use resources on all Compute Nodes (CNs) due to load imbalance. In this paper, we propose Seastar, a fast and scalable key-value store that achieves high cache locality as well as load balancing. To enable high concurrency and ensure linearizability, Seastar exploits a self-verification version chain to provide out-of-place atomic updates and ensure consistent reads. To improve cache locality, Seastar leverages a pair-based ownership assigning scheme to assign the processing permission of requests corre-sponding to each key to a CN pair through two independent hash functions. To ensure load balancing among CNs, Seastar proposes a decentralized power-of-two-choices routing scheme to route the requests to the less-loaded CNs in CN pairs for handling. Experimental results demonstrate that Seastar improves the throughput by up to 6.7x and significantly reduces the latency compared with state-of-the-art memory-disaggregated key-value stores. © 2024 IEEE.

关键词： Scalability

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Frequency Agile Strategy Design of Radar Network for Wideband Sweep Jamming via Coalition Formation Game

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IEEE Transactions on Aerospace and Electronic systems 2025年第3期61卷 7906-7919页

作者： Liao, Maosen Xiong, Kui Zhang, Long Yu, Xianxiang Cui, Guolong University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100089 China School of Information and Communication Engineering Chengdu611731 China UESTC Shenzhen Institute for Advanced Study Chengdu611731 China

This article proposes an intelligent frequency agile design strategy for radar network using coalition game theory to counter wideband sweep jamming, which is formulated as a two-stage decision-making problem. In the first stage, the entire frequency agile range is divided into several non-overlapping agile subrange, and each radar selects a frequency agile subrange to join, which is solved by the coalition formation algorithm. Then, after achieving a stable coalition partition, a distributed multi-agent reinforcement learning algorithm is developed to address the specific carrier frequency selection problem within each coalition. By combining these two stages of the frequency agile design strategy, a joint coalition formation game and distributed Q-learning algorithm (CFDQ) is proposed. Finally, numerical simulations are conducted to illustrate the superiority of the proposed algorithm over several typical frequency agile strategies. © 1965-2011 IEEE.

关键词： Jamming

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