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8th International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2019

作者： Liu, Zhiqiang Jiang, Jingfei Lei, Guoqing Chen, Kai Qin, Buyue Zhao, Xiaoqiang Artificial Intelligence Research Center National Innovation Institute of Defense Technology Beijing China National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China College of Computer National University of Defense Technology Changsha China College of System Engineering National University of Defense Technology Changsha China

This paper proposes a heterogeneous processor design for CNN-based AI applications on IoT devices. The heterogeneous processor contains an embedded RISC-V CPU that works as a general processor and an efficient CNN-accelerator that supports a variety of CNN models with a list of macro instructions. For demonstration, we implement a prototype on an FPGA platform with the RISC-V CPU working under 20 MHz and the CNN accelerator working under 100 MHz. As a case study, we run a CNN-based face detection and recognition application on this prototype. The prototype can process one image in 0.72 seconds and an ASIC implementation working under 400 MHz can process one image in less than 0.15 seconds by estimation, which can satisfy the needs for many IoT scenarios such as access control systems and check-in systems. © 2020 The Authors. Published by Elsevier B.V.

关键词： Internet of things

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Backstepping Sliding Mode Control for Continuous Casting Mold Vibration Displacement System Driven by Servo Motor 36

Backstepping Sliding Mode Control for Continuous Casting Mol...

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第36届中国控制会议

作者： LI Jianxiong GUO Cui FANG Yiming ZHANG Qiyu Key Lab of Industrial Computer Control Engineering of Yanshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling

ISBN: (纸本)9781538629185

Aiming at the time-varying load torque disturbance in the vibration displacement system of continuous casting mold driven by servo motor,an extended state observer(ESO) based backsteppmg sliding mode control method is ***,a mapping function is established to deal with the non-uniqueness of the nonlinear inverse relationship from eccentric shaft angle to mold ***,an ESO is constructed to estimate the time-varying load torque,and the estimate of load torque is employed to compensate the disturbance in *** a backsteppmg sliding mode controller is then developed for the vibration displacement system of continuous casting mold,which can guarantee the asymptotical stability and the robust stability of the resulting closed-loop ***,simulation results are given to show the effectiveness of the proposed method.

关键词： servo motor drive system vibration displacement system extended state observer backstepping sliding mode control

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Fish Feeding Behavior Recognition Using Adaptive DMCA-UMT Algorithm

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Journal of Beijing Institute of technology 2023年第3期32卷 285-297页

作者： Caiwei Yang Xinting Yang Kaijie Zhu Chao Zhou National Engineering Research Center for Information Technology in Agriculture Beijing 100097China Information Technology Research Center Beijing Academy of Agriculture and Forestry SciencesBeijing 100097China National Engineering Laboratory for Agri-product Quality Traceability Beijing 100097China College of Computer and Information Engineering Tianjin Agricultural UniversityTianjin 300384China

Realtime analyzing the feeding behavior of fish is the premise and key to accurate guidance on *** identification of fish behavior using a single information is susceptible to various *** overcome the problems,this paper proposes an adaptive deep modular co-attention unified multi-modal transformers(DMCA-UMT).By fusing the video,audio and water quality parameters,the whole process of fish feeding behavior could be ***,for the input video,audio and water quality parameter information,features are extracted to obtain feature vectors of different ***,deep modular co-attention(DMCA)is introduced on the basis of the original cross-modal encoder,and the adaptive learnable weights are *** feature vector of video and audio joint representation is obtained by automatic learning based on fusion ***,the information of visual-audio modality fusion and text features are used to generate clip-level moment *** query decoder decodes the input features and uses the prediction head to obtain the final joint moment retrieval,which is the start-end time of feeding the *** results show that the mAP Avg of the proposed algorithm reaches 75.3%,which is37.8%higher than that of unified multi-modal transformers(UMT)algorithm.

关键词： aquaculture multi-modal fusion deep modular co-attention(DMCA) unified multimodal transformers(UMT) video moment retrieval

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Integrity constraints in OWL ontologies based on grounded circumscription

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Frontiers of computer Science 2013年第6期7卷 812-821页

作者： Dantong OUYANG College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun 130012 China National Engineering Research Center of Geophysics Exploration Instruments Changchun 130026 China

The extensions for logic-based knowledge bases with integrity constraints are rather popular. We put forward an alternative criteria for analysis of integrity constraints in Web ontology language （OWL） ontology under the closed world assumption. According to this criteria, grounded circumscription is applied to define integrity constraints in OWL ontology and the satisfaction of the integrity constraints by minimizing extensions of the predicates in integrity con- straints. According to the semantics of integrity constraints, we provide a modified tableau algorithm which is sound and complete for deciding the consistency of an extended ontol- ogy. Finally, the integrity constraint validation is converted into the corresponding consistency of the extended ontology. Comparing our approach with existing integrity constraint validation approaches, we show that the results of our approach are more in accordance with user requirements than other approaches in certain cases.

关键词： semantic Web description logic ontology integrity constraints grounded circumscription

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Rapid simulations of atmospheric data assimilation of hourly-scale phenomena with modern neural networks 23

Rapid simulations of atmospheric data assimilation of hourly...

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2023 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023

作者： Li, Yiyuan Ju, Xiting Xiao, Yi Jia, Qilong Zhou, Yongxiao Qian, Simeng Lin, Rongfen Yang, Bin Shi, Shupeng Liu, Xin Gao, Jie Wang, Zhen Liu, Sha Tan, Jian Wang, Xuan Hu, Zhengding Yan, Limin Xue, Wei Tsinghua University Beijing China National Supercomputing Center in Wuxi Wuxi China National Research Center of Parallel Computer Engineering and Technology Wuxi China University of Science and Technology of China Hefei China Beijing Sankuai Online Technology Co. Ltd Beijing China Department of Computer Technology and Application Qinghai University Xining China

ISBN: (纸本)9798400701092

Atmospheric data assimilation is essential for numerical weather prediction. Ensemble data assimilation connects multiple instances of an atmospheric model through a Kalman filter-based algorithm, which is regarded as a challenging computing task today. In this work, we build a fast, low-cost, and scalable atmospheric data assimilation prototype, DIDA, for the new-generation Sunway supercomputer, including: (1) a framework that enables flexible deployment of components, and manages and optimizes data communication among modules, achieving maximum resource efficiency;(2) an accurate, robust, UNet-based surrogate model for atmospheric dynamic simulation to generate the background ensemble;(3) a batch-LETKF algorithm with high-performance eigenvalue decomposition, which is up to 7.37 times faster than existing numerical libraries while exhibiting almost linear scalability. Experimental evaluations show that our AI-integrated ensemble data assimilation prototype can complete hour-cycle assimilation in minutes, maintain linear scalability, and save an order of magnitude of computing resources, compared with the traditional method. © 2023 Owner/Author(s).

关键词： Supercomputers

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Non-uniform clustering routing protocol of wheat farmland based on effective energy consumption

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International Journal of Agricultural and Biological engineering 2021年第3期14卷 163-170页

作者： Yisheng Miao Chunjiang Zhao Huarui Wu College of Computer Science Beijing University of TechnologyBeijing 100124China National Engineering Research Center for Information Technology in Agriculture Beijing 100097China Beijing Research Center for Information Technology in Agriculture Beijing Academy of Agriculture and Forestry SciencesBeijing100097China

Wireless sensor network(WSN)can achieve real-time data collection and transmission of environment,soil,meteorology,crop physiology and other information in *** data provided by WSN could be used for decision making and management,which is very important in precision *** farmland wireless sensor network has the characteristics of wide coverage area,long planting period,inconvenient energy supply,and serious impact of crop environment on wireless signal *** protocol is an important method to achieve long-term WSN monitoring by selecting an appropriate path with low energy consumption for data *** to the phenomenon of uneven environment and channel parameters caused by intensive crop growth in farmland,a non-uniform clustering routing protocol based on effective energy consumption(UCEEC)was proposed in this *** method combined with the characteristics of multi-path fading of farmland environment *** idea of image segmentation was *** with high similarity were divided into a cluster area by the dissimilarity between nodes in order to improve the intracluster communication ***,a multi-hop path selection method between cluster-heads based on the estimation of two-hop effective energy consumption is *** energy consumption cost factor is calculated by the effective energy consumption and the average energy consumption within the cluster to achieve the minimum and balance of the overall energy consumption of the *** results show that,compared with the existing Maximum Residual Energy Based Routing(MREBR)protocol,minimum Energy Consumption Based Routing(MEC)routing protocols,UCEEC improves the energy balance effect between nodes,prolongs the network life cycle,and realizes efficient energy utilization of wireless sensor network data collection in the complex environment of wheat field.

关键词： farmland wireless sensor networks multi-path fading channel routing protocol energy optimization

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Effectiveness and Methodologies of Virtual Reality Dental Simulators for Veneer Tooth Preparation Training: Randomized Controlled Trial

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Journal of medical Internet research 2025年 27卷 e63961页

作者： Yaning Li Hongqiang Ye Wenxiao Wu Jiayi Li Xiaohan Zhao Yunsong Liu Yongsheng Zhou Department of Prosthodontics Peking University School and Hospital of Stomatology National Center of Stomatology National Clinical Research Center for Oral Diseases National Engineering Research Center of Oral Biomaterials and Digital Medical Devices Beijing Key Laboratory of Digital Stomatology 22 Zhongguancun South Avenue Haidian District Beijing 100081 China 86 ***. The State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China.

Background:Virtual reality (VR) simulators are increasingly used in dental education, offering advantages such as repeatable practice and immediate feedback. However, evidence comparing their efficacy to traditional phantom heads for veneer preparation training remains limited. Objective:This study aimed to compare the effectiveness of 2 widely used VR simulators (Unidental and Simodont) against traditional phantom heads for veneer tooth preparation training and evaluate the impact of training sequence (simulator-first vs phantom-head-first) on skill acquisition. Methods:A randomized controlled trial was conducted with 80 fourth-year dental students from Peking University School of Stomatology. Participants were stratified by gender and academic performance, then equally allocated to 8 groups. Groups 1-3 trained exclusively using Unidental, Simodont, or phantom heads, respectively, while groups 4-8 followed hybrid sequences combining simulator and phantom-head training. Each participant performed veneer preparations on a maxillary central incisor. Preparations were evaluated by a blinded instructor using a validated 100-point rubric assessing marginal integrity (30%), preparation depth (25%), proximal contour (25%), and surface smoothness (20%). Posttraining questionnaires (100-point scale) compared user perceptions of simulator realism, haptic feedback, and educational value. Results:There were no statistically significant differences in the preparation quality among groups using different training methods (Unidental: 88.9, SD 3.6; Simodont: 88.6, SD 1.6; phantom heads: 89.4, SD 2.8; P=.81) or different training methodologies (simulator-first vs phantom-head-first) (simulator first: P=.18; phantom head first: P=.09, different sequences of Unidental: P=.16; different sequences of Simodont: P=.11). However, significant differences were observed between the evaluations of the 2 simulators in terms of realism of the odontoscope's reflection (Simodont: 55.6, SD 33.7; Un

关键词： artificial intelligence augmented reality dental education dental simulator dentistry students effectiveness methodology orthodontics simulated reality tooth preparation training veneers virtual reality

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Towards a blockchain-SDN-based secure architecture for cloud computing in smart industrial IoT

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Digital Communications and Networks 2023年第2期9卷 411-421页

作者： Anichur Rahman Md Jahidul Islam Shahab S.Band Ghulam Muhammad Kamrul Hasan Prayag Tiwari Department of Computer Science and Engineering National Institute of Textile Engineering and Research(NITER)Constituent Institute of the University of DhakaSavarDhaka1350Bangladesh Department of Computer Science and Engineering Green University of BangladeshDhakaBangladesh Future Technology Research Center College of FutureNational Yunlin University of Science and TechnologyDouliouTaiwanChina Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia Department of Information and Communication Engineering Hankuk University of Foreign StudiesSouth Korea Department of Computer Science Aalto UniversityFinland

Some of the significant new technologies researched in recent studies include BlockChain(BC),Software Defined Networking(SDN),and Smart Industrial Internet of Things(IIoT).All three technologies provide data integrity,confidentiality,and integrity in their respective use cases(especially in industrial fields).Additionally,cloud computing has been in use for several years *** information is exchanged with cloud infrastructure to provide clients with access to distant resources,such as computing and storage activities in the *** are also significant security risks,concerns,and difficulties associated with cloud *** address these challenges,we propose merging BC and SDN into a cloud computing platform for the *** paper introduces“DistB-SDCloud”,an architecture for enhanced cloud security for smart IIoT *** proposed architecture uses a distributed BC method to provide security,secrecy,privacy,and integrity while remaining flexible and *** in the industrial sector benefit from the dispersed or decentralized,and efficient environment of ***,we described an SDN method to improve the durability,stability,and load balancing of cloud *** efficacy of our SDN and BC-based implementation was experimentally tested by using various parameters including throughput,packet analysis,response time,bandwidth,and latency analysis,as well as the monitoring of several attacks on the system itself.

关键词： Smart IIoT Blockchain SDN IoT Security Privacy OpenFlow SDN-Controller Data security Cloud computing Cloud management

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CMANet: A CNN-Mamba aggregation network for face super-resolution

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Pattern Recognition 2025年 168卷

作者： Wu, Ziyi Lu, Tao Zhang, Yanduo Chai, Xiaoyu Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China Computer School Hubei University of Arts and Science Xiangyang China National Engineering Research Center for Multimedia Software Wuhan University Wuhan China

Currently, most face super-resolution (FSR) methods rely on convolutional neural networks (CNNs) or Transformers, both of which have inherent limitations: CNNs suffer from a limited receptive field, while Transformers introduce quadratic computational complexity due to self-attention. In recent years, Mamba has effectively addressed these challenges using the state space model (SSM), excelling in global modeling. However, due to the highly structured nature of face images, relying solely on global modeling is insufficient for high-quality reconstruction. It is crucial to preserve global structural information while enhancing local texture details. While Mamba excels in global modeling, it lacks the ability to effectively extract local details. To eliminate this issue, we propose the CNN-Mamba Aggregation Network (CMANet) for FSR, which consists of two branches: a CNN branch and a Mamba branch. The CNN branch is a traditional end-to-end FSR network, in which the proposed Multi-Scale Residual Block (MSRB) extracts multi-scale local details. The Mamba branch, the core of the network, is built upon a UNet architecture. Its central component is a carefully designed Dual Scan Mamba Block (DSMB), which combines the Dual Scan Mamba Module (DSMM) and Feature Refinement Feed-Forward Network (FR-FFN). The DSMM enhances the global modeling capabilities of the SSM in both plane and channel scanning directions, while the FR-FFN refines the expressiveness and adaptability of the features. Finally, CMANet reconstructs high-fidelity face images by aggregating features from both branches. Extensive experimental results show that our model significantly outperforms many advanced methods in both objective metrics and subjective image quality. © 2025 Elsevier Ltd

关键词： Convolutional neural networks

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Generative Adversarial Networks:Introduction and Outlook

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IEEE/CAA Journal of Automatica Sinica 2017年第4期4卷 588-598页

作者： Kunfeng Wang Chao Gou Yanjie Duan Yilun Lin Xinhu Zheng Fei-Yue Wang IEEE State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Qingdao Academy of Intelligent Industries State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences University of Chinese Academy of Sciences Department of Computer Science and Engineering University of Minnesota Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology

Recently, generative adversarial networks(GANs)have become a research focus of artificial intelligence. Inspired by two-player zero-sum game, GANs comprise a generator and a discriminator, both trained under the adversarial learning *** goal of GANs is to estimate the potential distribution of real data samples and generate new samples from that *** their initiation, GANs have been widely studied due to their enormous prospect for applications, including image and vision computing, speech and language processing, etc. In this review paper, we summarize the state of the art of GANs and look into the future. Firstly, we survey GANs' proposal background,theoretic and implementation models, and application ***, we discuss GANs' advantages and disadvantages, and their development trends. In particular, we investigate the relation between GANs and parallel intelligence,with the conclusion that GANs have a great potential in parallel systems research in terms of virtual-real interaction and integration. Clearly, GANs can provide substantial algorithmic support for parallel intelligence.

关键词： ACP approach adversarial learning generative adversarial networks(GANs) generative models parallel intelligence zero-sum game

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