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2nd International Conference on Advance computing and Innovative Technologies in engineering, ICACITE 2022

作者： Surya, S. Rajasekaran, P. Yuriy, Shvets Johar, Siti Sarawati Tripathi, Amrendra Magno Ventayen, Randy Joy Computer Science and Engineering School of Computing Kalasalingam University India Information Technology Dr. N.G.P Institute of Technology India Financial University under the Goverment of Russian Federation Institute of Control of Science Ras Moscow Russia Centre for General Studies and Co-curricular Universiti Tun Hussein Onn Malaysia Department of Social Science Parit Raja Johor Darul Takzim Batu Pahat86400 Malaysia School of Computer Science Upes Dehradun India Pangasinan State University Lingayen Campus Philippines

ISBN: (纸本)9781665437899

The current economic and competitive environment has enabled many businesses and industries to implement digital for enhancing the business operations and support in addressing the overall objectives. Dur to this there is a mounting avalanche information being shared between the individuals, companies and governments, the increase in the usage of mobile devices, internet, social media and other ecommerce services has supported in increasing the volume of data. This trend is expected to grow exponentially and hence there is a requirement to provide wireless network in an effective manner, the increased usage of data and information has resulted in facing various failures, like call drops for mobile users, low bandwidth for internet users etc. Hence, it is highly necessary to implement tools to understand the failure prediction, prevention and recovery on the network. Hence, this study is focused in investigating the impact of big data analysis in protecting the wireless networks from such failures and support in processing large volume of information in an effective manner, the big data analytics can also extract useful data will enable in addressing the concerned parties so as to make critical decisions. In this study, the researcher intends to conduct the survey using closed ended questionnaire from the individuals so as to measure the effectiveness of applying big data for failure prevention, protection and recovery in the wireless network. © 2022 IEEE.

关键词： Wireless networks

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On the periodic solutions of the three-body problem

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National Science Review 2019年第6期6卷 1070-1071页

作者： Shijun Liao Xiaoming Li Advanced Center of Computing School of Naval Architecture Ocean and Civil EngineeringShanghai Jiao Tong University School of Physics and Astronomy Shanghai Jiao Tong University MOE Key Laboratory of Disaster Forecast and Control in Engineering School of Mechanics and Construction Engineering Jinan University

The motion of three bodies that attract each other by universal gravitation was first investigated by Newton [1] and was reconsidered by many great mathematicians and scientists, including Euler, Lagrange, Poincaré [2] and Hilbert. The famous three-body problem has had a great influence on physics, mathematics and non-linear dynamics. It has led to a new

关键词： On the periodic solutions of the three-body problem

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Hierarchical Bit-Wise Differential Coding (HBDC) of Point Cloud Attributes

Hierarchical Bit-Wise Differential Coding (HBDC) of Point Cl...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Yan Huang Bin Wang C.-C. Jay Kuo Hui Yuan Jingliang Peng School of Software Shandong Universtiy University of Southern California School of Control Science and Engineering Shandong Universtiy Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan School of Information Science and Engineering University of Jinan

Targeting both computing and coding efficiencies, we propose in this work a novel hierarchical bit-wise differential coding scheme to compress point cloud attributes. The encoder firstly quantizes and organizes the points into an octree structure and, for each internal node, picks its attribute(s) from a child named source child. Next, the encoder conducts a top-down scanning of the hierarchy. For each node with more than one child, it computes the bit-wise attribute difference between the current node and each non-source child by exclusive-OR and encodes the difference with an arithmetic coder. Further, a table look-up approach is proposed to accelerate the online source child identification. The proposed scheme produces superior computing and coding efficiencies for lossless point cloud attribute compression, outperforming the MPEG benchmark coders by large margins in our experiments.

关键词： Three-dimensional displays Image color analysis Conferences Octrees Transform coding Benchmark testing Signal processing

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A Power Grid Start-Up Work Ticket Event Extraction Method Based on Domain Knowledge Graph Enhanced Model 2

A Power Grid Start-Up Work Ticket Event Extraction Method Ba...

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2nd International Conference on Electronic Materials and Information engineering, EMIE 2022

作者： Qiu, Longgang Ping, Yuan Zhang, Yue Jiang, Guangji Huang, Shuai Zhang, Yong Deng, Min Chen, Congtan Zhang, Pei Rao, Guozheng State Grid Huainan Electric Power Supply Company Anhui Province Huainan232000 China NARI Group Corporation Co. Ltd. State Grid Electric Power Research Institute Co. Ltd. Jiangsu Province Nanjing211106 China Beijing KeDong Electric Power Control System Co. Ltd. Haidian District Beijing100192 China School of Electrical Engineering Beijing Jiaotong University Beijing100091 China College of Intelligence and Computing Tianjin University Tianjin300350 China

ISBN: (纸本)9781713865629

The power grid start-up work ticket event extraction has excellent challenges in its text mining. However, exiting extraction models usually rely on hand-crafted features and ignore the domain knowledge. To better understand the context knowledge of the power grid start-up work ticket, we propose a power grid start-up work ticket event extraction method based on domain knowledge graph enhanced model. Our model has several features. First, our model is a joint end-to-end model. It helps to jointly perform both trigger detection and argument detection with shared parameters. Second, we integrate CNN and Bi-LSTM-CRF to detect event triggers. Third, we propose Conceptual Context Tree-LSTM (CC Tree-LSTM) with the shortest path to detect event arguments. Multiple experiments have proved that the framework of this paper is superior to other comparison methods in the Precision, Recall, and F1 score of event extraction tasks. The Precision, Recall, and F1 score of our model reach 0.8032, 0.8127, and 0.8079. It verifies the feasibility and effectiveness of the method. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Extraction

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Size-Invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection

arXiv

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arXiv 2024年

作者： Li, Feiran Xu, Qianqian Bao, Shilong Yang, Zhiyong Cong, Runmin Cao, Xiaochun Huang, Qingming Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Institute of Information Science Beijing Jiaotong University Beijing China School of Control Science and Engineering Shandong University Jinan China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Cyber Science and Tech. Sun Yat-Sen University Shenzhen Campus China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China

This paper explores the size-invariance of evaluation metrics in Salient Object Detection (SOD), especially when multiple targets of diverse sizes co-exist in the same image. We observe that current metrics are size-sensitive, where larger objects are focused, and smaller ones tend to be ignored. We argue that the evaluation should be size-invariant because bias based on size is unjustified without additional semantic information. In pursuit of this, we propose a generic approach that evaluates each salient object separately and then combines the results, effectively alleviating the imbalance. We further develop an optimization framework tailored to this goal, achieving considerable improvements in detecting objects of different sizes. Theoretically, we provide evidence supporting the validity of our new metrics and present the generalization analysis of SOD. Extensive experiments demonstrate the effectiveness of our method. The code is available at https://***/Ferry-Li/SI-SOD. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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Data protection and provenance in cloud of things environment: Research challenges

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International Journal of Information and Computer Security 2020年第4期12卷 416-435页

作者： Wang, Chundong Yang, Lei Guo, Hao Wan, Fujin Key Laboratory of Computer Vision and System Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Ministry of Education Tianjin University of Technology Tianjin China Global Energy Internet Research Institute Beijing University of Technology Tianjin China Department of College of Computer and Control Engineering Nankai University Tianjin China

Internet of things are increasingly being deployed over the cloud (also referred to as cloud of things) to provide a broader range of services. However, there are serious challenges of CoT in the data protection and security provenance. This paper proposes a data privacy protection and provenance model (DPSPM) based on CoT. It can protect the privacy data of the users and trace the source of leaked data. In detail, security encryption and watermarking algorithms are proposed. Meanwhile, we use the improved k-anonymity data masking algorithm and pseudo-row watermarking algorithm in this scheme. Those algorithms can carry out security control over the whole process of data publishing, especially in data encryption, data masking and provenance verification. Finally, the experimental results show that our scheme has good efficiency. It is proved that the data masking time is proportional to the parameters k and L, the results also show good robustness to the common database watermarking attacks. © 2020 Inderscience Enterprises Ltd.

关键词： Data privacy

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Electrical and mechanical sensor-based mass flow rate measurement system: A comparative approach 4

Electrical and mechanical sensor-based mass flow rate measur...

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4th International Conference on Robotics and Automation Sciences, ICRAS 2020

作者： Abrar, Usama Shi, Liu Jaffri, Nasif Raza Short, Michael Hasham, Khawar North China Electric Power University School of Control and Computer Engineering Beijing102206 China Teesside University School of Computing Engineering and Digital Technologies Middlesbrough ClevelandTS1 3BA United Kingdom Interactive Group Islamabad Pakistan

ISBN: (纸本)9781728198576

Gas-Solid flow finds its application in various industries such as chemical and food processes, pharmaceuticals, automobile and power generation. The precise measurement and real-time monitoring of the flow process have garnered a lot of attraction in the modern industrial era. The effective utilization, with high efficiency, of the resources have compelled the researchers to investigate Gas-Solid flow monitoring and measurement process for the last two decades. Efforts are extended to design instruments for flow pattern visualization and quantification of mass flow rate. Generally, volumetric flow concentration and velocity profile of the solid particles are required to find the mass flow rate (MRF) in the case of non-invasive measurement techniques. This paper proposes a novel non-invasive mass flow rate measurement system for solid particles where electrical and mechanical sensors are simultaneously used to compensate each other's associated drawbacks. The solid particles are allowed to slide along an insulated inclined channel under the effect of gravity. The velocity profile and volumetric flow concentration are calculated using electrical sensors. Furthermore, load cell serves as a second sensor to calculate the mass flow rate. The experimental results from both the sensors are compared to investigate the accuracy and relative errors of both the sensors under different conditions. © 2020 IEEE.

关键词： Capacitive sensors

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A Survey of Robot Manipulation in Contact

arXiv

引用

arXiv 2021年

作者： Suomalainen, Markku Karayiannidis, Yiannis Kyrki, Ville Center of Ubiquitous Computing Faculty of Information Technology and Electrical Engineering University of Oulu Finland Systems and Control Department of Electrical Engineering Chalmers University of Technology Gothenburg Sweden Intelligent Robotics research group Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Helsinki Finland

In this survey, we present the current status on robots performing manipulation tasks that require varying contact with the environment, such that the robot must either implicitly or explicitly control the contact force with the environment to complete the task. Robots can perform more and more manipulation tasks that are still done by humans, and there is a growing number of publications on the topics of 1) performing tasks that always require contact and 2) mitigating uncertainty by leveraging the environment in tasks that, under perfect information, could be performed without contact. The recent trends have seen robots perform tasks earlier left for humans, such as massage, and in the classical tasks, such as peg-in-hole, there is a more efficient generalization to other similar tasks, better error tolerance, and faster planning or learning of the tasks. Thus, in this survey we cover the current stage of robots performing such tasks, starting from surveying all the different in-contact tasks robots can perform, observing how these tasks are controlled and represented, and finally presenting the learning and planning of the skills required to complete these tasks. © 2021, CC BY.

关键词： Surveys

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Hamiltonian Learning using Machine Learning Models Trained with Continuous Measurements

arXiv

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arXiv 2024年

作者： Tucker, Kris Rege, Amit Kiran Smith, Conor Monteleoni, Claire Albash, Tameem Department of Applied Math University of Colorado Boulder United States Department of Computer Science University of Colorado Boulder United States Center for Quantum Information and Control University of New Mexico University of New Mexico AlbuquerqueNM United States Department of Electrical and Computer Engineering University of New Mexico AlbuquerqueNM United States INRIA Centre de Recherche de Paris France Center for Computing Research Sandia National Laboratories AlbuquerqueNM87185 United States

We build upon recent work on using Machine Learning models to estimate Hamiltonian parameters using continuous weak measurement of qubits as input. We consider two settings for the training of our model: (1) supervised learning where the weak measurement training record can be labeled with known Hamiltonian parameters, and (2) unsupervised learning where no labels are available. The first has the advantage of not requiring an explicit representation of the quantum state, thus potentially scaling very favorably to a larger number of qubits. The second requires the implementation of a physical model to map the Hamiltonian parameters to a measurement record, which we implement using an integrator of the physical model with a recurrent neural network to provide a model-free correction at every time step to account for small effects not captured by the physical model. We test our construction on a system of two qubits and demonstrate accurate prediction of multiple physical parameters in both the supervised and unsupervised contexts. We demonstrate that the model benefits from larger training sets establishing that it is in fact "learning," and we show robustness to errors in the assumed physical model by achieving accurate parameter estimation in the presence of unanticipated single particle relaxation. © 2024, CC BY.

关键词： Qubits

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Parallel Systems Framework: A Safe and Efficient Testbed for Unmanned Ships

Parallel Systems Framework: A Safe and Efficient Testbed for...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Long Fu Zhen Shen Xisong Dong Yunjun Han Shuguang Yang Gang Xiong Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Schoool of Rail Transportation Shandong Jiaotong University Jinan China State Key Laboratory for Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

In this study, unmanned ships test platform based on the parallel systems framework is proposed to improve the test efficiency and accuracy of unmanned ships in complex ocean environment. The parallel intelligence theory and ACP approach, the efficient interaction between virtual and real environment is achieved, which provides more comprehensive and accurate data for unmanned ships testing. Future research will further expand the scope of virtual environment simulation and improve systems accuracy and response speed to a wider range of unmanned ships test requirements.

关键词： Accuracy Oceans Virtual environments Digital twins Marine vehicles Testing

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