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检索条件"任意字段=2021 10th International Conference on Computing and Pattern Recognition"

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Adaptive scheduling strategy of fog computing tasks with different priority for intelligent production lines 10

Adaptive scheduling strategy of fog computing tasks with dif...

引用

10th Annual international conference of Information and Communication Technology (ICICT)

作者： Xu, Fulong Yin, Zhenyu Gu, Ai Li, Yue Yu, Haoyu Zhang, Feiqing Chinese Acad Sci Shenyang Inst Comp Technol Shenyang Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

Fog computing has been widely deployed in intelligent production lines to provide real-time computing services for terminal devices to alleviate the transmission problem between cloud and terminal. Nevertheless, when there are many services provided in a single fog node, how to choose an optimal data processing path is a challenge to minimize optimization latency and power consumption while ensuring the reliable transmission of data with different priorities. To address the problems as mentioned above in this paper, we first propose a joint evaluation model of time latency and power consumption based on task priority. then, we formulate a fog computing adaptive scheduling algorithm (FCAS) based on dynamic programming to obtain the optimal path for processing data with different priorities at fog nodes. Experimental results illustrate that our proposed evaluation model and algorithm have lower power consumption, high efficiency, and higher reliability. (C) 2021 the Authors. Published by Elsevier B.V.

关键词： Intelligent production line Fog node Adaptive scheduling Multi-objective optimization Dynamic programming algorithm

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Metallic pattern Prediction For Surface Wave Antennas Using Bidirectional Gated Recurrent Unit Neural Network 10

Metallic Pattern Prediction For Surface Wave Antennas Using ...

引用

10th IEEE-APS Topical conference on Antennas and Propagation in Wireless Communications (APWC) / 22nd international conference on Electromagnetics in Advanced Applications (ICEAA) / USNC-URSI Radio Science Meeting (USNC-URSI RSM)

作者： Yang, Jiashu Tong, Kin-Fai UCL Dept Elect & Elect Engn London WC1E 7JE England

ISBN: (纸本)9781665413886

this work presents a surface wave antenna metallic pattern prediction from electric field in near-field by applying Bidirectional Gated Recurrent Unit neural network prediction model. the metallic pattern of the proposed antenna has been predicted by using Bi-GRU neural network model with prediction accuracy 100% at 34.5G1Iz. Different uniform mark-space-ratios (MSR) of the metallic pattern do not affect the metallic pattern prediction accuracy.

关键词： Surface wave antennas holographic antennas electric field (E-field) prediction recurrent neural network (RNN) bidirectional gated recurrent unit (Bi-GRU)

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Learning Readers' News Preferences with Support Vector Machines

Learning Readers' News Preferences with Support Vector Machi...

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10th international conference on Artificial Neural Networks and Genetic Algorithms

作者： Hensinger, Elena Flaounas, Ilias Cristianini, Nello Univ Bristol Intelligent Syst Lab Bristol BS8 1TH Avon England

ISBN: (纸本)9783642202667

We explore the problem of learning and predicting popularity of articles from online news media. the only available information we exploit is the textual content of the articles and the information whether they became popular by users clicking on them or not. First we show that this problem cannot be solved satisfactorily in a naive way by modelling it as a binary classification problem. Next, we cast this problem as a ranking task of pairs of popular and non-popular articles and show that this approach can reach accuracy of up to 76%. Finally we show that prediction performance can improve if more content-based features are used. For all experiments, Support Vector Machines approaches are used.

关键词： pattern recognition Data mining Applications Machine learning

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Video Character recognition through Hierarchical Classification

Video Character Recognition Through Hierarchical Classificat...

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11th international conference on Document Analysis and recognition (ICDAR)

作者： Shivakumara, Palaiahnakote Trung Quy Phan Lu, Shijian Tan, Chew Lim Natl Univ Singapore Sch Computing Singapore 117548 Singapore Inst Infocomm Res Singapore Singapore

ISBN: (纸本)9780769545202

We present a new video character recognition method based on hierarchical classification. In the first step, we propose a method for character segmentation of the text line detected by the text detection method. the segmentation algorithm uses dynamic programming to find least-cost paths in the gray domain to identify the spaces between characters. For the segmented characters, we get a Canny edge image as input for the character recognition step. We introduce hierarchical classification based on voting criteria with structural features to classify 62 character classes into different smaller classes. We divide the perimeter of a character into 8 segments according to 8 directions at the centroid. then the shape of each segment is studied to recognize the characters based on distances between the centroid and end points, and distances between the midpoint and end points. Our experiments on 1462 characters of upper case, lower case and numerals shows that 10% samples per class for training is enough to obtain 94.5% recognition accuracy. the dataset is chosen from TRECVID database of 2005 and 2006.

关键词： Structural features Hierarchical classification Invariant features Confusion matrix Video character recognition

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Reservoir computing in Rehabilitation Video Analyses 10

Reservoir Computing in Rehabilitation Video Analyses

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10th IEEE international conference on Cybernetics and Intelligent Systems and IEEE conference on Robotics, Automation and Mechatronics, CIS-RAM 2023

作者： Yang, Dongping Xu, Tie Lin, Feng Zhejiang Lab Research Institute for Artificial Intelligence Hangzhou China

ISBN: (纸本)9798350303087

Spatio-temporal information processing is fundamental in rehabilitation video analyses. Current strategies for spatio-temporal pattern recognition usually involve explicit feature extraction followed by feature aggregation, which requires a large amount of labeled data. there are two major challenges for recognizing complex spatio-temporal patterns. One is on extracting the representative features;and the other is on extracting the temporal structure, in particular, the temporal order, of image sequences. Reservoir computing (RC) offers a promising tool by enabling automatic and accurate analyses of complex movement patterns in rehabilitation videos. Unlike traditional machine learning techniques, RC does not require explicit training of the reservoir connections, which is less data- demanding, more resistant to overfilling and easier to implement. the unique properties make it an attractive option for analyzing rehabilitation video data, where patients may experience changes in their movement patterns over time with a large data flow for processing. By analyzing new video data, the reservoir can adapt and refine its output to reflect the patient's current conditions. © 2023 IEEE.

关键词： Machine learning

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Software Design pattern approach to develop Login Framework 3

Software Design Pattern approach to develop Login Framework

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3rd international conference on computing for Sustainable Global Development (INDIACom)

作者： Pithva, Keval A. Vaghela, Ravirajsinh K. Gujarat Vidyapith Ahmadabad Gujarat India

ISBN: (纸本)9789380544199

User Authentication module plays a crucial role in a software system. this module must be very well defined by Cyber Security Experts. It takes much versatility according to changes in environment as well as technology. User authentication may be provided in several ways like user credentials, biological identification, One Time Password and many more. It is difficult and complex to manage future requirement & day to day changes in authentication module. the framework is one of the ways to provide the solution to the problem. there are many tread-offs to design the framework. this paper focuses on software design pattern based framework for authentication module. Using this design pattern based login framework, developers can easily manage future requirement. It provides extensibility and flexibility to applications.

关键词： Design pattern Framework GOF Java Login

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CFFU Cycle Design Mode of Programmable Creases - An Example of Fibonacci Folding Sequence pattern 10th

CFFU Cycle Design Mode of Programmable Creases - An Example ...

引用

10th international conference on Culture and computing (C and C) Held as Part of the 24th international conference on Human-Computer Interaction (HCII)

作者： Chen, Chiung-Hui Lin, Meng-Chih Asia Univ 500 Lioufeng Rd Taichung 41354 Taiwan

ISBN: (纸本)9783031054341;9783031054334

Kirigami is a Japanese art of paper cutting. It is used to obtain three-dimensional shapes via cutting and folding the paper. Origami, however, is based on a series of precise geometric folding without any other changes to the paper. With the characteristics of dimensional change and form transformation as well as the advantages of being able to expand and zoom, both Kirigami and Origami have great potential in cross-domain applications. these include biomedical materials, deformable robots, adaptable building cortex, and aerospace science. these applications show different requirements for folding by Kirigami or Origami. this study considered that the knowledge of design must include the operational process used to solve design problems.

关键词： Programmable creases Kirigami Folding

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DSWHAR: A Dynamic Sliding Window Based Human Activity recognition Method 19

DSWHAR: A Dynamic Sliding Window Based Human Activity Recogn...

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2022 IEEE SmartWorld, 19th IEEE international conference on Ubiquitous Intelligence and computing, 2022 IEEE international conference on Autonomous and Trusted Vehicles conference, 22nd IEEE international conference on Scalable computing and Communications, 2022 IEEE international conference on Digital Twin, 8th IEEE international conference on Privacy computing and 2022 IEEE international conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Sun, Li Yang, Xiaodong Hu, Chunyu School of Computer Science and Technology Jinan250353 China Shandong Academy of Intelligent Computing Technology Jinan250101 China Institute of Computing Technology Chinese Academy of Sciences The Beijing Key Laboratory of Mobile Computing and Pervasive Device Beijing100190 China

ISBN: (纸本)9798350346558

Sensory data has been widely used for human activity recognition (HAR), where sliding window (SW) is one of the typical methods to segment continuous signals. Most existing HAR methods select fixed-length sliding windows for different activities. However, with complex and diverse human activities, a single fixed sliding window is not suitable for acquiring features of different activities. Some studies have dynamically adjusted the window size based on the activity of feature difference segmentation, but the continuous occurrence of the activity can lead to an oversized window for segmentation and easily introduce additional noise leading to degradation of classification performance. To tackle the above problem, we propose a novel dynamic sliding window based human activity recognition method, called DSWHAR. In the training phase, DSWHAR firstly explores the relationship between the optimal sliding window length and the signal spectrum of each target activity, then a candidate window set is built for the target activity and multiple classifiers are trained using different windows. During the recognition phase, the latest prediction probability is used to dynamically select a suitable window for the next prediction, and the corresponding classifier is used for the final recognition. We compare DSWHAR with the method with fixed sliding windows and dynamic sliding window algorithm on the MHEALth dataset, respectively, and the experimental results show that DSWHAR not only achieves better overall HAR accuracy but also has unbiased performance on different activities. © 2022 IEEE.

关键词： pattern recognition

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Towards Non-intrusive Sleep pattern recognition in Elder Assistive Environment

Towards Non-intrusive Sleep Pattern Recognition in Elder Ass...

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7th international conference on Autonomic and Trusted computing

作者： Ni, Hongbo Abdulrazak, Bessam Zhang, Daqing Wu, Shu Yu, Zhiwen Zhou, Xingshe Wang, Shengrui Northwestern Polytech Univ Sch Comp Sci Xian Shaanxi Peoples R China Univ Sherbrooke Dept Comp Sherbrooke PQ Canada Inst Telecom Handicom Lab Paris France

ISBN: (纸本)9783642163548

Quality of sleep is an important attribute of an elder's health state and its assessment is still a challenge. the sleep pattern is a significant aspect to evaluate the quality of sleep, and how to recognize elder's sleep pattern is an important issue for elder-care community. With the pressure sensor matrix to monitor the elder's sleep behavior in bed, this paper presents an unobtrusive sleep postures detection and pattern recognition approaches. Based on the proposed sleep monitoring system, the processing methods of experimental data and the classification algorithms for sleep pattern recognition are also discussed.

关键词： Sleep pattern elder-care pressure sensor naive bayes random forest

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Image indexing using weighted color histogram

Image indexing using weighted color histogram

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10th international conference on Image Analysis and Processing, ICIAP 1999

作者： Park, Du-Sik Park, Jong-Seung Kim, Tae Yong Han, Joon Hee Signal Processing Lab. Samsung A.I.T. Yongin Korea Republic of Human Computing Research Dept. ETRI Taejon Korea Republic of Department of Computer Science and Engineering POSTECH San 31 Hyo-Ja-Dong Pohang 790-784 Korea Republic of

ISBN: (纸本)0769500404

Image indexing is the process of image retrieval from databases of images or videos based on their contents. Specifically histogram-based algorithms are considered to be effective for color image indexing. We suggest a new method of color space quantization in the CIELUV color space, named weighted LUV quantization. With this method, each bin in the LUV space has a different weighting factor, which is applied to the histogram intersection. the weighted LUV histogram intersection provides the advantage of perceptual uniformity of the CIELUV color space. An additional advantage is the consideration of perceptual sensitivity to more saturated colors by the use of a weighting factor. © 1999 IEEE.

关键词： Image retrieval

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