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IndRT-GCNets: Knowledge Reasoning with Independent Recurrent Temporal Graph Convolutional Representations

Computers, Materials & Continua 2024年第1期78卷 695-712页

作者： Yajing Ma Gulila Altenbek Yingxia Yu College of Information Science and Engineering Xinjiang UniversityUrumqi830017China Xinjiang Laboratory of Multilanguage Information Technology Xinjiang UniversityUrumqi830017China The Base of Kazakh and Kirghiz Language of National Language Resource Monitoring and Research Center on Minority Languages Xinjiang UniversityUrumqi830017China

Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurrent Temporal Graph Convolution Networks(IndRT-GCNets)framework to efficiently and accurately capture event attribute *** framework models the knowledge graph sequences to learn the evolutionary represen-tations of entities and relations within each ***,by utilizing the temporal graph convolution module in the evolutionary representation unit,the framework captures the structural dependency relationships within the knowledge graph in each ***,to achieve better event representation and establish effective correlations,an independent recurrent neural network is employed to implement auto-regressive ***,static attributes of entities in the entity-relation events are constrained andmerged using a static graph constraint to obtain optimal entity ***,the evolution of entity and relation representations is utilized to predict events in the next subsequent *** multiple real-world datasets such as Freebase13(FB13),Freebase 15k(FB15K),WordNet11(WN11),WordNet18(WN18),FB15K-237,WN18RR,YAGO3-10,and Nell-995,the results of multiple evaluation indicators show that our proposed IndRT-GCNets framework outperforms most existing models on knowledge reasoning tasks,which validates the effectiveness and robustness.

关键词： Knowledge reasoning entity and relation representation structural dependency relationship evolutionary representation temporal graph convolution

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A Method of Multimodal Emotion Recognition in Video Learning Based on Knowledge Enhancement

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Computer systems science & engineering 2023年第11期47卷 1709-1732页

作者： Hanmin Ye Yinghui Zhou Xiaomei Tao School of Information Science and Engineering Guilin University of TechnologyGuilin541004China Guangxi Key Laboratory of Embedded Technology and Intelligent System Guilin University of TechnologyGuilin541004China Guangxi Key Lab of Multi-Source Information Mining and Security Guangxi Normal UniversityGuilin541004China

With the popularity of online learning and due to the significant influence of emotion on the learning effect,more and more researches focus on emotion recognition in online *** of the current research uses the comments of the learning platform or the learner’s expression for emotion *** research data on other modalities are *** of the studies also ignore the impact of instructional videos on learners and the guidance of knowledge on *** of the need for other modal research data,we construct a synchronous multimodal data set for analyzing learners’emotional states in online learning *** data set recorded the eye movement data and photoplethysmography(PPG)signals of 68 subjects and the instructional video they *** the problem of ignoring the instructional videos on learners and ignoring the knowledge,a multimodal emotion recognition method in video learning based on knowledge enhancement is *** method uses the knowledge-based features extracted from instructional videos,such as brightness,hue,saturation,the videos’clickthrough rate,and emotion generation time,to guide the emotion recognition process of physiological *** method uses Convolutional Neural Networks(CNN)and Long Short-Term Memory(LSTM)networks to extract deeper emotional representation and spatiotemporal information from shallow *** model uses multi-head attention(MHA)mechanism to obtain critical information in the extracted deep ***,Temporal Convolutional Network(TCN)is used to learn the information in the deep features and knowledge-based ***-based features are used to supplement and enhance the deep features of physiological ***,the fully connected layer is used for emotion recognition,and the recognition accuracy reaches 97.51%.Compared with two recent researches,the accuracy improved by 8.57%and 2.11%,*** the four public data sets,our proposed method also achieves bett

关键词： Emotion recognition video learning physiological signal knowledge enhancement deep learning CNN LSTM TCN

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A new RCNN-RF for efficient and robust parking lot available detection 16

A new RCNN-RF for efficient and robust parking lot available...

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16th International Conference on Digital Image Processing, ICDIP 2024

作者： Zhang, Qian Ran, Yaqin Luo, Di Xu, Kaili Shi, Jilaing School of Data Science and Information Engineering GuiZhou MinZu University Guiyang550025 China Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guiyang550025 China

ISBN: (数字)9781510682917

ISBN: (纸本)9781510682900

It's very meaningful to conduct the driver to the parking space available in the parking lot clearly and accurately by computer vision and computational intelligence. While it is an extremely difficult task, because of the scene complexity in the parking lot. In this paper, a new computational intelligence technology is proposed to detect parking spaces available in the parking lot outdoor based on fusing of Region Convolution Neural Network (RCNN) and random forests (RF), and we called it as RCNN-RF. Within the RCNN-RF, a new activation function is design. And with the help of random forests, RCNN-RF overcomes scene complexity includes illumination, weather, and slight occlusion successfully. Extensive experimental results on the benchmark dataset named PKLot and the self-built dataset named GZMU-LOT outperform those of the state-of-the-art, and it shows the superiority of our proposed RCNN-RF method. © 2024 SPIE.

关键词： Random forests

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Sea ice drift vector extraction based on feature matching using CS-1 Images

Sea ice drift vector extraction based on feature matching us...

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2023 International Conference on Frontiers of Ocean science and technology, ICFOST 2023

作者： Yang, Y.L. Xie, T. School of Remote Sensing and Geomatics Engineering Nanjing University of Information Science and Technology Nanjing210044 China Laboratory for Regional Oceanography and Numerical Modelling Qingdao National Laboratory for Marine Science and Technology Qingdao266000 China

The study emphasizes the crucial role of sea ice drift in Arctic climate research and the protection of human activities. Employing C-SAR/01 (CS-1) imagery as the primary data source, the study assesses the effectiveness of the ORB feature matching algorithm for extracting Arctic Sea ice drift vectors. Additionally, it investigates the spatial distribution variations in the drift vectors extracted from the HH and HV polarization channels. The accuracy of the extracted drift vectors is validated using manually extracted sea ice drift data. Experimental results reveal a significant disparity in the number of drift vectors extracted from CS-1 HV polarization images compared to HH polarization images. The sea ice drift vectors extracted using the Oriented fast and Roasted Bried (ORB) operator demonstrate an average velocity error of less than 0.27 cm/s (0.31 km/d) and an average direction error of less than 5.66° in HV polarization images. © Published under licence by IOP Publishing Ltd.

关键词： Vectors

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Deciphering decadal urban ozone trends from historical records since 1980

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National science Review 2024年第11期11卷 117-129页

作者： Haolin Wang Xiao Lu Paul I.Palmer Lin Zhang Keding Lu Ke Li Tatsuya Nagashima Ja-Ho Koo Hiroshi Tanimoto Haichao Wang Meng Gao Cheng He Kai Wu Shaojia Fan Yuanhang Zhang School of Atmospheric Sciences Sun Yat-sen University and Key Laboratory of Tropical Atmosphere-Ocean System Ministry of Education Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) School of Geo Sciences University of Edinburgh National Centre for Earth Observation University of Edinburgh Laboratory for Climate and Ocean-Atmosphere Studies Department of Atmospheric and Oceanic SciencesSchool of PhysicsPeking University State Key Joint Laboratory of Environmental Simulation and Pollution Control The State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution ControlCollege of Environmental Sciences and Engineering Peking University Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science &Technology National Institute for Environmental Studies Department of Atmospheric Sciences Yonsei University Department of Geography Hong Kong Baptist University Department of Civil and Environmental Engineering University of California

Ozone pollution is a major environmental threat to human health. Timely assessment of ozone trends is crucial for informing environmental policy. Here we show that for the most recent decade（2013–2022） in the northern hemisphere, warm-season（April–September） mean daily 8-h average maximum ozone increases much faster in urban regions with top ozone levels(mainly in the North China Plain, 1.2 ± 1.3 ppbv year-1) than in other, low-ozone regions(0.2 ± 0.9 ppbv year-1). These trends widen the ozone differences across urban regions, and increase extreme pollution levels and health threats from a global perspective. Comparison of historical trends in different urban regions reveals that ozone increases in China during 2013–2022 differ in magnitude and mechanisms to historical periods in other regions since *** reflects a unique chemical environment characterized by exceptionally high nitrogen oxides and aerosol concentrations, where reducing ozone precursor emissions leads to substantial ozone *** increase in China has slowed down in 2018–2022 compared to 2013–2017, driven by ongoing emission reductions, but with ozone-favorable weather conditions. Historical ozone evolution in Japan and South Korea indicates that ozone increases should be suppressed with continuous emission *** temperature and associated wildfires have also reversed ozone decreases in the USA and Europe,with anthropogenic ozone control slowing down in recent decades.

关键词： air quality surface ozone trends

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Differentially Private Federated Stochastic Primal-Dual Learning for Internet of Vehicles

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IEEE Internet of Things Journal 2025年第11期12卷 17034-17050页

作者： Li, Yiwei Wang, Shuai Chang, Tsung-Hui Xiamen University of Technology Fujian Key Laboratory of Communication Network and Information Processing Xiamen361024 China University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Chinese University of Hon g Kong School of Science and Engineering Shenzhen518172 China Shenzhen Research Institute of Big Data Shenzhen518172 China

Federated learning (FL) has the potential to empower Internet of Vehicles (IoV) networks by enabling smart vehicles (SVs) to participate in the learning process under the orchestration of a vehicular service provider while keeping data locally. In this article, we propose a novel federated stochastic primal-dual algorithm with differential privacy (FedSPD-DP) to ensure robust privacy protection for FL based IoV (FL-IoV) systems. The FedSPD-DP algorithm leverages multiple steps of local stochastic gradient descent (SGD) and partial client participation (PCP) to improve communication efficiency while incorporating differential privacy (DP) to ensure privacy protection. Our theoretical analysis explores the impact of these strategies on learning performance. Specifically, we demonstrate that the data sampling strategy and PCP enhance data privacy, while a larger number of local SGD steps may increase privacy leakage, revealing a nontrivial tradeoff between communication efficiency and privacy protection. Extensive experiments on real-world data validate the effectiveness of the proposed algorithm, showing superior performance compared to state-of-the-art FL algorithms, and confirming the analytical results and properties. © 2014 IEEE.

关键词： Federated learning

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Creating Collaborative Data Representations Using Matrix Manifold Optimal Computation and Automated Hyperparameter Tuning 3

Creating Collaborative Data Representations Using Matrix Man...

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3rd IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2023

作者： Nosaka, Keiyu Yoshise, Akiko Graduate School of Science and Technology University of Tsukuba Tsukuba Japan Institute of System and Information Engineering University of Tsukuba Tsukuba Japan

ISBN: (纸本)9798350333862

Balancing performance and privacy in centralized machine learning, especially in sensitive domains such as medicine and finance, remains a significant issue. Concerns about data confidentiality result in a reluctance to share confidential data even among related entities, hindering integrated analysis despite its acknowledged benefits. Recent advancements in distributed data analysis have provided a solution to the concern, particularly through the framework of federated learning. This framework enables multiple clients to train models collaboratively while preserving the confidentiality of their data. Fed-DR-Filter extends federated learning by introducing the Privacy-Preserving Data Representation (PPDR) transformation algorithm that converts private datasets into a Global Data Representation (GDR) across multiple clients [4]. The GDR retains the correlation of the original data while ensuring its confidentiality. The PPDR is obtained by adding noise to the GDR, which is then used to filter noisy labels in federated learning environments based on the preserved correlation. Another recent development in distributed data analysis is Data Collaboration Analysis (DCA) [5]. It employs Collaborative Data Representation (CDR), a data representation almost identical to GDR, to directly generate high-performance models without the need for model sharing or iterative communication among clients. The present study builds the crucial role of CDRs and GDRs in DCA and Fed-DR-Filter by proposing a novel method for CDR creation with a solid theoretical foundation. The purpose is to enhance the performance of these techniques by providing an alternative and more effective algorithm for CDR and GDR creation. The primary contributions of this study include a novel optimization for CDR creation utilizing matrix manifold optimization and automated hyperparameter tuning. An algorithm for solving this problem is proposed with its empirical evaluation of artificial and real-world dataset

关键词： Metadata

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Method for Detecting DoH Communications from Non-Encrypted information at a Middlebox 11

Method for Detecting DoH Communications from Non-Encrypted I...

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11th International Symposium on Computing and Networking Workshops, CANDARW 2023

作者： Takanashi, Yuya Kimura, Shigetomo University of Tsukuba Graduate School of Science and Technology Tsukuba Japan University of Tsukuba Faculty of Engineering Information and System Tsukuba Japan

ISBN: (纸本)9798350306941

DNS over HTTPS (DoH) enhances user privacy by encrypting DNS communications over HTTPS instead of plaintext. When all DNS messages are sent in plaintext, DNS queries can be examined and domain filtering applied if the queried domain name is identified as a phishing site or other such undesirable site. However, if DNS messages are encrypted over HTTPS, it can create many problems for network administrators. This paper proposes a method for detecting DoH communications from only non-encrypted information on a middlebox between user and resolvers by exploiting the fact that users always send a DNS query before they access a new domain. The middlebox can also identify the destination of the detected DoH traffic so that network administrators can recommend users to send DNS messages to a local DoH resolver with domain filtering instead of sending them to an open DoH resolver. In experiments to detect DoH communications during real communication from a web browser we achieved detection accuracy rates reaching 100% under certain parameters when the number of access IP addresses exceeded 350. To confirm the accuracy and generalizability of our experiments, the proposed method was also applied to captured HTTPS traffic data involving different web browsers and different DoH resolvers with an almost identical level of detection accuracy. © 2023 IEEE.

关键词： Web browsers

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The electronic and optical properties in InAs and GaSb bulk materials: A First-Principles Approach 11

The electronic and optical properties in InAs and GaSb bulk ...

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11th International Symposium on Precision Mechanical Measurements

作者： Gong, Ruixin Zhu, Lianqing Liu, Zhiying School of Opto-Electronic Engineering Changchun University of Science and Technology China Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology University Beijing100015 China

ISBN: (纸本)9781510680296

In this work, we investigated the electronic and optical properties of traditional semiconductor materials, InAs and GaSb. By constructing crystal structures for InAs and GaSb, we performed calculations using the first-principles Density Functional Theory (DFT) with the HSE+SOC method. In contrast to the results obtained using the traditional PBE algorithm, which yielded a negative or zero bandgap for InAs, our calculations provided theoretical support and accurately determined the bandgap values of 0.3658 eV for InAs and 0.772 eV for GaSb. These results align well with the experimentally reported bandgap values for the bulk materials. Furthermore, by strictly adhering to the validity conditions of DFT, we obtained accurate optical properties that are consistent with experimental results. Based on the optical characteristics of InAs and GaSb semiconductor materials, it was demonstrated that have a high performance for absorbing light. These findings provide a possibility for using DFT calculations in the development of second-generation InAs/GaSb superlattice infrared detectors. © 2024 SPIE.

关键词： Infrared detectors

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Video Conference system in Mixed Reality Using a Hololens

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Computer Modeling in engineering & sciences 2023年第1期134卷 383-403页

作者： Baolin Sun Xuesong Gao Weiqiang Chen Qihao Sun Xiaoxiao Cui HaoGuo Cishahayo Remesha Kevin Shuaishuai Liu Zhi Liu School of Information Science and Engineering Shandong UniversityQingdao266000China State Key Laboratory of Digital Multi-Media Technology Hisense Co.Ltd.Qingdao266000China

The mixed reality conference system proposed in this paper is a robust,real-time video conference application software that makes up for the simple interaction and lack of immersion and realism of traditional video conference,which realizes the entire process of holographic video conference from client to cloud to the *** paper mainly focuses on designing and implementing a video conference system based on AI segmentation technology and mixed *** mixed reality conference system components are discussed,including data collection,data transmission,processing,and mixed reality *** data layer is mainly used for data collection,integration,and video and audio *** network layer uses Web-RTC to realize peer-to-peer data *** data processing layer is the core part of the system,mainly for human video matting and human-computer interaction,which is the key to realizing mixed reality conferences and improving the interactive *** presentation layer explicitly includes the login interface of the mixed reality conference system,the presentation of real-time matting of human subjects,and the presentation *** the mixed reality conference system,conference participants in different places can see each other in real-time in their mixed reality scene and share presentation content and 3D models based on mixed reality technology to have a more interactive and immersive experience.

关键词： Mixed reality AI segmentation hologram video conference Web-RTC

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