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43rd Chinese Control Conference, CCC 2024

作者： Yuan, Haoran Wu, Jiande Xiong, Xin Yunnan University Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan Kunming650500 China Kunming University of Science and Technology Faculty of Information Engineering and Automation Yunnan Kunming650500 China Kunming University of Science and Technology Yunnan Key Laboratory of Intelligent Control and Application Yunnan Kunming650500 China

ISBN: (纸本)9789887581581

In order to explore the impact of pipe diameter, bend-diameter ratio and bend angle on the erosion of slurry pipe, a numerical simulation method approach grounded in Computational Fluid Dynamics - Dense Discrete Phase Model (CFD-DDPM) is proposed. Firstly, the geometric models of bends with different pipe diameters, bend-diameter ratios, and bend angles are constructed;secondly, the slurry pipe erosion model based on Dense Discrete Phase Model (DDPM) is constructed;then, model validation is conducted on the slurry pipe erosion model to affirm the accuracy of the model;finally, the computational fluid dynamics method is employed to simulate the erosion and wear behavior of the pipeline, to investigate the impact of pipe diameter, bend-diameter ratio and bend angle on the erosion and wear of the slurry pipeline. At the same time, gray correlation analysis was also used to analyze the significant relationship between the three pipeline factors and erosion and wear. The results show that the main erosion area is not determined, with the change of the pipeline parameters, the most serious erosion area will move;the effect of different pipeline parameter variations on the erosion rate is different, in which the pipe diameter of the largest impact, the second largest bend-diameter ratio, the smallest impact of the bend angle. Therefore, in the design of slurry pipeline, should first consider the influence of pipe diameter factors. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Slurry pipelines

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Representing Multiview Time-Series Graph Structures for Multivariate Long-Term Time-Series Forecasting

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 2651-2662页

作者： Wang, Zehao Fan, Jin Wu, Huifeng Sun, Danfeng Wu, Jia Hangzhou Dianzi University Department of Computer Science and Technology Hangzhou310018 China Zhejiang Provincial Key Laboratory of Industrial Internet in Discrete Industries Hangzhou310018 China Zhejiang Normal University Laboratory of Intelligent Education Technology and Application of Zhejiang Province Hangzhou310018 China Macquarie University School of Computing SydneyNSW2113 Australia

Multivariate long-term time-series forecasting tasks are very challenging tasks in many real-world application areas. Recently, researchers focus on designing robust and effective methods, and have made considerable progress. However, there are several issues with existing models that need to be overcome. First, the lack of a relationship structure between multivariate variables needs to be addressed. Second, most models only have a weak ability to capture local dynamic changes across the entire long-term time-series. Third, current models suffer from high computational complexity and unsatisfactory accuracy. To figure out the abovementioned issues, we propose an effective and efficient method called multiview time-series graph structure representation (MTGSR). MTGSR uses GCNs to construct topological relationships in the multivariate time-series from three different perspectives: time, dimension, and crossing segments. Variation trends in different dimensions are extracted through a difference operation to construct topological maps that reflect the correlations between different dimensions. To capture the dynamically changing characteristics of fluctuation correlations between adjacent local sequences, MTGSR constructs a cross graph by calculating correlation coefficients between adjacent local sequences. Extensive experiments show that MTGSR reduces errors by 17.41% over the state of the art. In addition, memory use is decreased by 66.52% and the running time is reduced by 78.09%. © 2020 IEEE.

关键词： Forecasting

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Generalized bias-variance evaluation of TREC participated systems 14

Generalized bias-variance evaluation of TREC participated sy...

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23rd ACM International Conference on Information and Knowledge Management, CIKM 2014

作者： Zhang, Peng Hao, Linxue Song, Dawei Wang, Jun Hou, Yuexian Hu, Bin Tianjin Key Laboratory of Cognitive Computing and Application Tianjin University China Computing Department Open University United Kingdom Department of Computer Science University College London United Kingdom Ubiquitous Awareness and Intelligent Solutions Lab. Lanzhou University China

ISBN: (纸本)9781450325981

Recent research has shown that the improvement of mean retrieval effectiveness (e.g., MAP) may sacrifice the retrieval stability across queries, implying a tradeoff between effectiveness and stability. The evaluation of both effectiveness and stability are often based on a baseline model, which could be weak or biased. In addition, the effectiveness-stability tradeoff has not been systematically or quantitatively evaluated over TREC participated systems. The above two problems, to some extent, limit our awareness of such tradeoff and its impact on developing future IR models. In this paper, motivated by a recently proposed bias-variance based evaluation, we adopt a strong and unbiased "baseline", which is a virtual target model constructed by the best performance (for each query) among all the participated systems in a retrieval task. We also propose generalized bias-variance metrics, based on which a systematic and quantitative evaluation of the effectiveness-stability tradeoff is carried out over the participated systems in the TREC Ad-hoc Track (1993-1999) and Web Track (2010-2012). We observe a clear effectiveness-stability tradeoff, with a trend of becoming more obvious in more recent years. This implies that when we pursue more effective IR systems over years, the stability has become problematic and could have been largely overlooked. Copyright 2014 ACM.

关键词： System stability

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Reliability Analysis of Heterogeneous Sensor-Cloud Systems against Targeted Attacks

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China Communications 2022年第8期19卷 181-197页

作者： Hao Peng Zhen Qian Guangquan Xu Kejie Mao Kangtian Li Dandan Zhao Department of Computer Science and Engineering Zhejiang Normal UniversityJinhua Zhejiang 321004China Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province Zhejiang Normal UniversityJinhua Zhejiang 321004China The Big Data School Qingdao Huanghai UniversityQingdao Shandong 266427China College of Intelligence and Computing Tianjin UniversityTianjin 300072China

Based on the wide application of cloud computing and wireless sensor networks in various fields,the Sensor-Cloud System(SCS)plays an indispensable role between the physical world and the network ***,due to the close connection and interdependence between the physical resource network and computing resource network,there are security problems such as cascading failures between systems in the *** this paper,we propose a model with two interdependent networks to represent a sensor-cloud ***,based on the percolation theory,we have carried out a formulaic theoretical analysis of the whole process of cascading *** the system’s subnetwork presents a steady state where there is no further collapse,we can obtain the largest remaining connected subgroup components and the penetration ***,this result is the critical maximum that the coupled SCS can *** verify the correctness of the theoretical results,we further carried out actual simulation *** results show that a scale-free network priority attack’s percolation threshold is always less than that of ER network which is priority ***,when the scale-free network is attacked first,adding the power law exponentλcan be more intuitive and more effective to improve the network’s reliability.

关键词： sensor-cloud systems targeted attacks heterogeneous networks reliability analysis system security

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A New Predefined Time Stability Theorem and its application in Multi-Modal Memristive Neural Network Synchronization

A New Predefined Time Stability Theorem and its Application ...

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2023 IEEE International Conference on Memristive computing and applications, ICMCA 2023

作者： Zhao, Hui Zhou, Lei Wang, Qingjie Liu, Aidi Peng, Jingliang School of Information Science and Engineering University of Jinan Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan China College of Information Science and Engineering Northeastern University Shenyang China Collaborative Innovation Center of Memristive Computing Application Qilu Institute of Technology Jinan China

ISBN: (纸本)9798350316230

This article proposes a new predefined-time (PDT) stability theorem, which offers more evident advantages compared to previous predefined-time stability. Firstly, based on the limitations of existing PDT stability, this theorem relaxed the limitations of sufficient conditions, which fill the gap in the research on PDT stability. Secondly, the PDT synchronization of multi-modal memristive neural networks (MM-MNN) is analyzed by the usability of the new judgment theorem. A matching PDT controller is designed and sufficient synchronization control conditions is obtained by utilizing generalized Lyapunov functional method, set-valued mapping, inequality analysis technique and differential inclusion theory. Meanwhile, the topological characteristics of multi-modal neuron and its impact on network synchronization behavior are presented. Finally, we provide some confirmatory numerical simulations. © 2023 IEEE.

关键词： Topology

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Temperature dependence of commensurate magnetic resonance in cuprate superconductors 5th

Temperature dependence of commensurate magnetic resonance in...

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5th Conference on New Advances in Condensed Matter Physics, NACMP 2018

作者： Lan, Yu Kuang, Lülin Hunan Provincial Key Laboratory of Intelligent Information Processing and Application College of Physics and Electronic Engineering Hengyang Normal University Hengyang421002 China National Research Center for High-Performance Computing Engineering Technology Sugon Beijing100193 China

ISBN: (纸本)9783035713275

Within the kinetic energy driven superconducting mechanism, we have studied the temperature dependence of commensurate magnetic resonance in cuprate superconductors. It is shown that the commensurate magnetic resonance peak at the antiferromagnetic wave vector point persists in the superconducting state until the temperature rises to the superconducting transition temperature Tc. The intensity of the resonance peak decreases with increasing temperature which is just like the temperature dependence of the superconducting gap parameter. Our results are in qualitative agreement with the inelastic neutron scattering experimental data and reflect that the commensurate magnetic resonance is closely related to the creation of the charge carrier pairs and thus the superconducting mechanism of cuprate superconductors. © 2018 Trans Tech Publications, Switzerland

关键词： Temperature distribution

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Vision based intelligent traffic light management system using Faster R‐CNN

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 932-947页

作者： Syed Konain Abbas Muhammad Usman Ghani Khan Jia Zhu Raheem Sarwar Naif R.Aljohani Ibrahim A.Hameed Muhammad Umair Hassan Department of Computer Science and Engineering University of Engineering and TechnologyLahorePakistan Zhejiang Key Laboratory of Intelligent Education Technology and Application Zhejiang Normal UniversityJinhuaChina OTHEM Manchester Metropolitan UniversityManchesterUK Faculty of Computing and Information Technology King Abdulaziz UniversityJeddahSaudi Arabia Department of ICT and Natural Sciences Norwegian University of Science and Technology(NTNU)ÅlesundNorway

Transportation systems primarily depend on vehicular flow on roads. Developed coun-tries have shifted towards automated signal control, which manages and updates signal synchronisation automatically. In contrast, traffic in underdeveloped countries is mainly governed by manual traffic light systems. These existing manual systems lead to numerous issues, wasting substantial resources such as time, energy, and fuel, as they cannot make real‐time decisions. In this work, we propose an algorithm to determine traffic signal durations based on real‐time vehicle density, obtained from live closed circuit television camera feeds adjacent to traffic signals. The algorithm automates the traffic light system, making decisions based on vehicle density and employing Faster R‐CNN for vehicle detection. Additionally, we have created a local dataset from live streams of Punjab Safe City cameras in collaboration with the local police authority. The proposed algorithm achieves a class accuracy of 96.6% and a vehicle detection accuracy of 95.7%. Across both day and night modes, our proposed method maintains an average precision, recall, F1 score, and vehicle detection accuracy of 0.94, 0.98, 0.96 and 0.95, respectively. Our proposed work surpasses all evaluation metrics compared to state‐of‐the‐art methodologies.

关键词： access control artificial intelligence computer vision intelligent control

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Growth of High-Quality InP Nanowires with PN Junctions Using an Improved Chemical Vapor Deposition

Growth of High-Quality InP Nanowires with PN Junctions Using...

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2024 International Conference on Next Generation Electronics and Photonics, INGEP 2024

作者： Yao, Xinliang Liu, Xingpeng Yuan, Kui Su, Jiande Song, Shuxiang Liu, Linsheng Guangxi Key Laboratory of Brain-Inspired Computing and Intelligent Chips Key Laboratory of Integrated Circuits and Microsystems Education Department of Guangxi Zhuang Autonomous Region School of Electronic and Information Engineering School of Integrated Circuits Guangxi Normal University Guilin541004 China Guangxi Key Laboratory of Precision Navigation Technology and Application Guilin University of Electronic Technology Guilin541004 China

Nanowires grown by traditional chemical vapor deposition (CVD) systems often suffer from low crystal quality and difficulties in realizing complex device structures. To address these issues, we propose an improved CVD system with a source switching unit to enhance the controllability of source materials. By combining reverse gas flow and high-temperature degassing processes, high-quality InP nanowires with pn junctions were successfully grown. Scanning electron microscopy and photoluminescence spectroscopy revealed that the as-grown nanowires exhibit smooth surfaces, no significant defects, and high crystal quality. Furthermore, a single InP nanowire with a pn junction demonstrated rectifying characteristics and fast photoswitch response (less than 14.2 ms). These results suggest that the improved CVD method provides a new approach for low-cost fabrication of high-quality nanodevices. © Published under licence by IOP Publishing Ltd.

关键词： Nanowires

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A Hf0.5Zr0.5O2 Non-Volatile Capacitor Based on SrTiO3 Substrate 3

A Hf0.5Zr0.5O2 Non-Volatile Capacitor Based on SrTiO3 Substr...

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3rd International Conference on New Materials, Machinery, and Vehicle Engineering, NMMVE 2024

作者： Liu, Xingpeng Wei, Chunshu Tang, Huiping Peng, Yiming Jiang, Chunsheng Aurora Technologies Co. Ltd. Guangzhou511453 China Guangxi Key Laboratory of Precision Navigation Technology and Application Guilin University of Electronic Technology Guilin541004 China Guangxi Key Laboratory of Brain-inspired Computing and Intelligent Chips School of Electronic and Information Engineering Guangxi Normal University Guilin541004 China

ISBN: (纸本)9781510686267

The rapid of development of the Internet of Things (Iot), 5G communications, and smart technologies placing higher demands on storage-integrated hardware devices. The discovery of HfO2-based ferroelectric materials has opened up a new avenue for achieving low-power logic and high-density non-volatile memory by utilizing this silicon-tolerant ferroelectric material. In this work, a 10 nm Hf0.5Zr0.5O2 (HZO) ferroelectric films ware prepared on SrTiO3 (STO) substrate using an atomic layer deposition system (ALD). After rapid annealing treatment, the surface roughness of HZO films showed nanometer level (Ra∼1.033 nm, Rq∼1.321 nm). HZO ferroelectric films with molybdenum (Mo) electrodes exhibit low coercive field (Ec∼1.48 MV/cm) and excellent ferroelectric property (2Pr∼56.143 μC/cm2, and 2Pmax∼ 81.070 μC/cm2). Under the fatigue signal of 100 kHz, the device exhibits stable anti-fatigue characteristics. Mo/HZO/Mo/STO devices exhibit fast response time (1ms) and stable polarization retention characteristics (over 103 s). This work introduces a novel method for the next-generation non-volatile memory solutions (NVM). © 2024 SPIE.

关键词： Ferroelectric films

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Cascade Detector Based on Multi-scale Features for Small Objects in Various Backgrounds of Remote Sensing 2nd

Cascade Detector Based on Multi-scale Features for Small Obj...

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2nd International Conference on Image, Vision and intelligent Systems, ICIVIS 2022

作者： Li, Yan Han, Shi-Yuan Xu, Tao Yang, Xiao-hui Lu, Qiu Shen, Yuan University of Jinan Jinan250022 China China High-Resolution Earth Observation System Shandong Center of Data and Application University of Jinan Jinan250022 China Shandong Provincial Key Laboratory of Network-Based Intelligent Computing University of Jinan Jinan250022 China

ISBN: (纸本)9789819909223

Different from natural images, remote sensing images in complex backgrounds have the challenges of small object feature extraction with small size, few available features, and high localization accuracy requirements. Consequently, it is difficult to detect these small objects with mainstream object detection methods. To enhance the retention of small object feature details during feature extraction and characteristics enhancement, this paper improves the Cascade R-CNN algorithm to solve the above problems of small object detection. Res2Net was used to enhance feature representation and feature fusion to extract features with fine-grained and rich semantic information. PAFPN was used for learning high-resolution features with large perceptual fields to perceive contextual information from the area around the object for inference. Cascade R-CNN was used as a high-quality detector by continuously increasing the threshold of IOU. Experiments show that the detection performance of the method proposed in this paper is 4.3% higher than that of the current mainstream deep learning methods, which is significantly better than other mainstream detection methods. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Feature extraction

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