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Framework for adaptive computation offloading in IoT applications 17

Framework for adaptive computation offloading in IoT applica...

引用

9th Asia-Pacific Symposium on Internetware, Internetware 2017

作者： Chen, Shihong Liu, Bichun Chen, Xing Zhang, Ying Huang, Gang College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China Institute of Software School of Electronics Engineering and Computer Science Peking University Beijing China Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing China

ISBN: (纸本)1595930361

The internet of things (IoT) attracts great interest in many application domains concerned with monitoring and control of physical phenomena. IoT applications try to provide more and more functionality and then they inevitably become so complex as to make the limits of devices worse, which may lead to poor performance of applications. Computation offloading is a promising way to improve the performance of an IoT application by executing some parts of the application on remote devices or servers. However, supporting such capability is not easy for application developers due to (1) adaptability: IoT applications often face changes of runtime environments so that the adaptation on offloading is needed. (2) effectiveness: when the device context changes, it needs to dynamically decide the deployment plan of computation tasks, and the reduced execution time must be greater than the network delay and extra overheads caused by offloading. This paper proposes a framework which supports IoT applications with adaptive computation offloading capability. First, a design pattern is proposed to enable an application to be computation offloaded on-demand. Second, an estimation model is presented to automatically decide the deployment plan for offloading. Third, a framework is implemented to support the design pattern and the estimation model. A thorough zxevaluation on the real-world application is proposed, and the results show that our approach can help reduce execution time by over 45% in most scenarios.

关键词： computation offloading

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A Fine Segmentation Method for the Outer Boundary of Tire Image Steel Belt Based on Adaptive Thresholding Under Local Histogram Statistical Features

A Fine Segmentation Method for the Outer Boundary of Tire Im...

引用

International Conference on Image, Vision and intelligent Systems, ICIVIS 2023

作者： Liu, Hua Li, Nan Hao, Jinyi Xia, Yingjie Li, Jinping School of Information Science and Engineering University of Jinan Jinan250022 China Shandong Provincial Key Laboratory of Network-Based Intelligent Computing University of Jinan Jinan250022 China Shandong College and University Key Laboratory of Information Processing and Cognitive Computing in 13th Five-Year Jinan250022 China

ISBN: (纸本)9789819708543

The accuracy of defect detection in various locations is directly affected by the influence of precise segmentation of radial tire images. As the need for high-quality tires has grown, so has interest in the steel belt region. This region contains a diversity of textures and is impacted by shadows, and only a rough segmentation of this region has been achieved in the available literature, but this is interfered with by other areas, resulting in unsatisfactory defect detection in this region. As a result, we present a fine segmentation method for boundary mutation that takes advantage of the projection property of the local narrow window. First, the histogram adhesion change detection algorithm is designed;next, the narrow sliding window’s histogram peak width change algorithm is designed;finally, a wide sliding window is used for vertical projection, and the absolute value of the histogram change rate at the boundary is designed to maximize the algorithm. To calculate the outside boundary of the steel belt, the difference between the three sets of coordinates is kept within a specific error range. The detection was performed on 1,000 self-constructed data sets, with an accuracy rate of 94% and a detection speed of 0.1 s The experiments show that the algorithm can segment the steel belt’s outer boundary more finely and robustly, and it has a strong segmentation effect for images with a near texture angle and tire sidewall cord angle. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Textures

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A Hierarchical Multi-label Propagation Algorithm for Overlapping Community Discovery in Social networks

A Hierarchical Multi-label Propagation Algorithm for Overlap...

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2014 11th Web information System and Application Conference(第十一届全国web信息系统及其应用学术会议)

作者： Song Shi Yuzhong Chen Mingyue Fang Wanhua Li Shining College of Mathematics and Computer Science Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University FuZhou China

ISBN: (纸本)9781479957286

Multi-label propagation algorithms (MLPAs) have nearly linear time complexity, but the accuracy and stability still need to be improved when applied to overlapping community *** from the idea that boundary nodes are more probable to appear in the overlapping regions of different communities, a Hierarchical Multi-label Propagation Algorithm (HMPA) based on node hierarchy and label propagation gain for overlapping community discovery in social networks is proposed in this paper, HMPA consists of three ***, HMPA utilizes LPAm to unfold initial non-overlapping ***, a PageRank-like method is proposed to mark the hierarchy of each node according to the initial partition of the first ***, multi-label propagation algorithm considering label propagation gain between nodes, which is calculated based on node hierarchy, is introduced to refine overlapping *** results on both the synthetic and real world networks show that the proposed algorithm can effectively solve the problems of traditional multi-label propagation algorithms in terms of accuracy and stability.

关键词： overlapping community detection multi-label propagation node hierarchy propagation gain

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A chaotic artificial bee colony algorithm based on lévy search

A chaotic artificial bee colony algorithm based on lévy sea...

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作者： Lin, Shijie Dong, Chen Wang, Zhiqiang Guo, Wenzhong Chen, Zhenyi Ye, Yin College of Mathematics and Computer Science Fuzhou University Fuzhou350116 China Key Laboratory of Information Security of Network Systems Fuzhou350116 China Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350116 China Department of Electrical Engineering University of South Florida TampaFL33620 United States

A Lévy search strategy based chaotic artificial bee colony algorithm (LABC) is proposed in this paper. The chaotic sequence, global optimal mechanism and Lévy flight mechanism were introduced respectively into the initialization, the employed bee search and the onlooker bee search. The experiments show that the proposed algorithm performed better in convergence speed, global search ability and optimization accuracy than other improved ABC. Copyright © 2018 The Institute of Electronics, information and Communication Engineers.

关键词： Evolutionary algorithms

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Super-Resolution of Defocus Thread Image Based on Cycle Generative Adversarial networks 12th

Super-Resolution of Defocus Thread Image Based on Cycle Gene...

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12th IFIP TC 12 International Conference on intelligent information processing, IIP 2022

作者： Jiang, Pengfei Xu, Wangqing Li, Jinping School of Information Science and Engineering University of Jinan Jinan250022 China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan250022 China Shandong College and University Key Laboratory of Information Processing and Cognitive Computing in 13th Five-Year Jinan250022 China

ISBN: (纸本)9783031039478

The dual camera calibration measurement method can realize low-cost and high-precision bolt dimension measurement by using two microscope cameras. But the height difference between the thread crest and root exceeds the depth of field, and the thread image becomes defocus, which seriously affects the measurement accuracy. For this reason, a super-resolution method for defocus thread image based on cyclic generative adversarial networks is proposed. We collected focus thread images and defocus thread images as training data. Two encoders are used in the generation network to extract image defocus features and content features. And a sub-pixel convolution layer is added to the decoder to achieve image super-resolution. A loss function based on adversarial loss and cycle-consistent loss is constructed to realize unsupervised training of the network, thereby achieve super-resolution of defocus thread images. The experimental results show that, in the simulated defocus images, the method has superiority in image detail preservation, sharpness improvement and peak signal to noise ratio. In the bolt dimension measurement task, it can effectively reconstruct the clear thread image and thus provide the measurement accuracy to 0.01 mm. © 2022, IFIP International Federation for information processing.

关键词： Optical resolving power

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Web server security evaluation method based on multi-source data

Web server security evaluation method based on multi-source ...

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International Conference on Cloud computing, Big Data and Blockchain (ICCBB)

作者： Kedong Wu Xiaoling Gao Yanhua Liu Provincial Key Laboratory of Network Computing and Intelligent Information Processing College of Mathematics and Computer Science Fuzhou University Fuzhou Fujian Fujian Fuzhou Fujian China

ISBN: (纸本)9781728112787

Traditional web security assessments are evaluated using a single data source, and the results of the calculations from different data sources are different. Based on multi-source data, this paper uses Analytic Hierarchy Process to construct an evaluation model, calculates the weight of each level of indicators in the web security evaluation model, analyzes and processes the data, calculates the host security threat assessment values at various levels, and visualizes the evaluation results through ECharts+WebGL technology.

关键词： Security Servers IP networks XML information processing Data models Safety

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Learning knowledge representation across knowledge graphs 31

Learning knowledge representation across knowledge graphs

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31st AAAI Conference on Artificial Intelligence, AAAI 2017

作者： Cai, Pengshan Li, Wei Feng, Yansong Wang, Yuanzhuo Jia, Yantao CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Science Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing China Institute of Computer Science and Technology Peking University Beijing China

ISBN: (纸本)9781577357865

Distributed knowledge representation learning (KRL) methods encode both entities and relations in knowledge graphs (KG) in a lower-dimensional semantic space, which model relatively dense knowledge graphs well and greatly improve the performance of knowledge graph completion and knowledge reasoning. However, existing KRL methods including Trans(E, H, R, D and Sparse) hardly obtain comparative performances on sparse KGs where most of entities and relations have very low frequencies. Furthermore, all existing methods target at KRL on one knowledge graph independently. The embeddings of different KGs are independent with each other. In this paper, we propose a novel cross-knowledge- graph (cross-KG) KRL method which learns embeddings for two different KGs simultaneously. Through projecting semantic related entities and relations in two KGs to a uniform semantic space, our method could learn better embeddings for sparse KGs by incorporating information from another relatively larger and denser KG. The learned embeddings are also helpful for downstream cross-KGs or cross-linguals tasks like ontology alignment. The experiment results show that our method could significandy outperform corresponding baseline methods on knowledge graph completion on single KG and cross-KG entity prediction and mapping tasks. © 2017, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Knowledge graph

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Positioning and Pressing Elevator Button by Binocular Vision and Robot Manipulator

Positioning and Pressing Elevator Button by Binocular Vision...

引用

2018 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2018

作者： Fang, Tiyu Chen, Huiwu Shi, Jianjie Li, Jinping University of Jinan School of Information Science and Engineering Jinan250022 China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan Shandong250022 China Shandong College University Key Laboratory of Information Processing and Cognitive Computing in 13th Fiveyear Jinan Shandong250022 China

ISBN: (纸本)9781728105512

There are two key problems of anthropomorphic dual-arm robot up and down floors which are path planning and pressing buttons of elevator automatically. Our research group has solved the problem of robot path planning based on electronic map in early stage. As for the problem of pressing buttons automatically, two issues still need to be handled, including positioning elevator buttons in three-dimensional space and pressing specific button automatically by the manipulator of robot. At present, our research group has achieved the accurate detection and recognition of elevator target button in the image. Besides, for the core issue, a new method of pressing target button automatically by manipulator with binocular vision servo is proposed. First, the binocular measurement is applied to get the distance and declination relationships between robot itself and target button, then we shall find the precise position of target button in visual three-dimensional coordinate system and transform its position into the three-dimensional coordinate system which takes robot shoulder as the origin. Thus, the manipulator movement model can be established by constructing relationships between the declination of three degrees of freedom and the real-time coordinates of manipulator, which contains extension of shoulder joint, Internal rotation of shoulder joint and flexion-extension function of elbow joint, and each of them as a separate dimension. On the basis of this model, the PWM (Pulse Width Modulation) control technology is employed to make the manipulator terminal close to target button autonomously. Finally, with deviation relationships between the manipulator terminal and target button as well as the threshold which is set to modulate manipulator, the goal of pressing target button by manipulator can be achieved eventually. Furthermore, the algorithm was tested on medium-sized wheeled dual-arm robot Hawk and results obtained verify the feasibility of the method proposed above ca

关键词： Robot applications

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A Combined Structure Optimization Method in Community Detection

A Combined Structure Optimization Method in Community Detect...

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第二届中国互联网学术年会

作者： Yuzhong Chen Xiaohui Qiu Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing Fuzhou 350108 China

Community Detection in social networks is usually considered as an objective optimization *** to the objective function,the global optimum cannot describe the real partition well,and it is time *** this paper,a layered optimization framework is designed to improve the optimization process,reduce the scale of network and increase the quality of *** framework consists of three parts: finding cores in networks,repairing isolated nodes and optimization in a new constructed weighted network which is a compressed network of the origin ***,the equivalency of modularity optimization in the new compressed weighted network and the original one is ***,a combined algorithm of community Detection named DBPSO including similarity-based clustering,isolated nodes repairing strategies and a modified particle swarm optimization is proposed according to the layered optimization *** addition,a suitable mutation strategy for particle swarm optimization (PSO) is introduced to guarantee the convergence and global search ***,the experiments are conducted to evaluate the proposed algorithm by using the synthetic and real-world network *** results show that the proposed algorithm can effectively extract the intrinsic community structure of social networks.

关键词： Layered Optimization Framework Community Detection Particle Swarm Optimization Modularity

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A model of three points for location estimation in wireless sensor networks

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2013 2nd International Symposium on Materials Science and Engineering Technology, ISMSET 2013

作者： Xie, Shao Guo Hu, Yan Jun Wang, Yi Jiang, Fang Liu, Jing Jing Wang, Ying Guan Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education AnHui University Hefei China Key Laboratory of Wireless Sensor Network and Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences 865 Changning Road Shanghai 200050 China

ISBN: (纸本)9783037858028

In this paper, we propose a novel model of three points named TP for location estimation in wireless sensor networks (WSNs) with random deployment of anchor nodes. In this model, we select three anchor nodes which have the strongest received signal strength (RSS) for location estimation, the centroid algorithm and the method of intersection of judgment are used to estimate the location of unknown nodes. To further exploit three nearest intersection points in TP, the enhanced TP (ETP) is proposed. The simulation results show that the proposed models outperform MMSE and BML in terms of the localization accuracy for WSNs. Moreover, the localization accuracy of the proposed models in scenario 2 with random deployment of anchor nodes are better than in scenario 1 with planned deployment of anchor nodes. Additionally, compared with MMSE and BML, ETP and TP can reduce the environmental impact on location estimation. © (2013) Trans Tech Publications, Switzerland.

关键词： Location

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