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检索条件"任意字段=Proceedings of the 2019 8th International Conference on Computing and Pattern Recognition"

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Research on Parallel Topology Analysis Algorithm Based on Simulated Annealing 8

Research on Parallel Topology Analysis Algorithm Based on Si...

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IEEE 8th Joint international Information Technology and Artificial Intelligence conference (ITAIC)

作者： Wang Xin-liang Chen Jian-Lin Ma Tian-Fang Liu Zhi-huai Liu Na Fang Wei Liu Xue-bin Zhang Li-Wei Wu Jun Hami Yuxin Energy Ind Res Inst Co Ltd Hami 839000 Peoples R China Henan Polytech Univ Sch Phys & Elect Informat Engn Jiaozuo 454000 Henan Peoples R China Hami Vocat & Tech Coll Hami 839000 Peoples R China

ISBN: (纸本)9781538681787

In the high-voltage power grid of coal mine, the existing adaptive topology analysis algorithm based on the correlation matrix for coal mine high-voltage power grid can effectively identify the network topology and construct a network topology analysis model to provide a basis for subsequent short-circuit current calculation and setting calculation. However, the topology analysis algorithm based on the correlation matrix takes much time. As the scale of the high-voltage power grid network of the coal mine increases, the time consumption will increase sharply as well. However, the prior-to-first-served parallel topology analysis algorithm has been used to reduce the topology analysis time consumption to some extent. On this basis, this article proposes a parallel topology analysis algorithm based on the simulated annealing and optimizes the scheduling strategy of parallel topology analysis. the simulation results show that compared with the prior-to-first-served parallel topology analysis algorithm, the parallel annealing topology analysis algorithm can further reduce the time consumption and improve the computational efficiency. And when the number of available threads increases, its computational efficiency will improve more significantly.

关键词： Topology analysis Simulated annealing High-voltage grid of coal mine Parallel computing

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Robust Facial Expression recognition Based on Local Tri-directional Coding pattern 12th

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12th international conference on Complex, Intelligent, and Software Intensive Systems (CISIS)

作者： Tong, Ying Chen, Rui Yang, Jie Wu, Minghu PLA Univ Sci & Technol Coll Commun Engn Nanjing 210007 Jiangsu Peoples R China Nanjing Inst Technol Dept Commun Engn Nanjing 211167 Jiangsu Peoples R China Hubei Univ Technol Hubei Key Lab High Efficiency Utilizat Solar Ener Wuhan Hubei Peoples R China

ISBN: (纸本)9783319936598;9783319936581

Automatic facial expression recognition system has broad applications prospect in the field of computer vision, and of which the precision of facial expression feature extraction is the crucial factor for improving recognition accuracy. Whereas the traditional Local Binary pattern has the shortcomings of inaccurate feature description and large feature size, in this paper we propose a novel feature descriptor, namely local tri-directional coding pattern (LtriDCP), to overcome the above two flaws. First, we adopt Kirsch masks to compute convolution values of each pixel in 8 directions, which can accurately represent the texture information of facial expression compared with the coding scheme of LBP. Second, considering that the difference of facial expression is mainly characterized in the texture change of horizontal, vertical and diagonal directions in eye, mouth, forehead and other facial areas, we only encode three convolution values in the corresponding directions to reduce feature size but still retain superior performance. Experimental results on JAFFE database show that LtriDCP outperforms several state-of-the-art feature descriptors and demonstrate its effectiveness.

关键词： Facial Expression recognition Local Binary pattern Kirsch mask

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Personal Oral Health Advisor Using Multimodal Sensing and Machine Learning with Smartphones and Cloud computing 8

Personal Oral Health Advisor Using Multimodal Sensing and Ma...

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8th IEEE international conference on Cloud computing in Emerging Markets, CCEM 2019

作者： Pingali, Lalitha Inventure Academy Bangalore India

ISBN: (纸本)9781728163345

the mouth is considered a mirror of the overall health of the body and yet there is no personal device available today that can be used at home to monitor oral health. While this is true across the world, the need is even more acute in emerging markets. For instance, there is only one dentist for every 150000 people in rural India. the objective of this project is to create a cost-effective, multimodal, personal oral sensing device that automatically classifies sensed data and provides interactive advice about oral health. Based on surveys of dentists and doctors about the types of information that would be useful, this paper presents POHA, a handheld home device that integrates image, video, smell, temperature, and 3D orientation sensing, and communicates with a Smartphone via USB and Bluetooth. POHA scans the mouth and teeth of a person while they perform a brushing-like motion. this research work developed image and smell classification models by training machine learning algorithms with hundreds of images collected from the web and air quality values of various mouth odors obtained with a low-cost gas sensor. Initial experiments show greater than 80% accuracy in detecting dental cavities, gingivitis, and bad breath. this project also involved developing a Smartphone application that provides users real-time views of sensed data, shows classification results and advice, collects health information, and stores tagged sensor data in a central cloud database. this first-of-its-kind device fits easily into one's daily routine, provides preventive advice, and encourages seeing a dentist or a doctor. POHA also provides doctors for the first time with tagged daily oral sensing data from millions of people that would be invaluable for medical research in detecting, preventing, and predicting numerous diseases that have oral manifestations. © 2019 IEEE.

关键词： Smartphones

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Reddit sentiment analysis to improve election predictions 4

Reddit sentiment analysis to improve election predictions

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4th international conference on Big Data Analytics, Data Mining and Computational Intelligence 2019, BigDaCI 2019 and the 8th international conference on theory and Practice in Modern computing 2019, TPMC 2019

作者： Hwang, Bryant Korea International School Korea Republic of

ISBN: (纸本)9789898533920

Despite high rates of past success, the majority of polling agencies were unable to predict the outcome of the 2016 United States presidential election between Hillary Clinton and Donald Trump. Further research has hypothesized that these agencies underestimated the amount of support for Trump and overestimated the representation of recent college graduates. Sentiment analysis of posts on popular social media sites presents promising possibilities for better gauging public opinion. In our research, we analyze positive and negative sentiment in Reddit posts from key dates during the 2016 election that mention either candidate. the results of our study match the results of a poll conducted by the New York Times, which showed that public opinion for Trump tended to stay consistent while Clintons positive sentiment decreased over time. Our study also shows that public opinion expressed on Reddit changed drastically in accordance to major events, like debates and email controversies. Alone, our work in sentiment analysis does not produce statistically significant enough results to predict the final outcome of an election, but having the ability to gauge public opinion through social networks is a powerful way that polling agencies and researchers can strengthen their predictions in real time. © Multi conference on Computer Science and Information Systems, MCCSIS 2019. All rights reserved.

关键词： Forecasting

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A Review on Various Techniques of Brain Tumor Boundary Detection 6

A Review on Various Techniques of Brain Tumor Boundary Detec...

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6th international conference on computing for Sustainable Global Development (INDIACom)

作者： Dharnia, Sunita Wasson, Vikas Chandigarh Univ CSE Dept Ajitgarh Punjab India

ISBN: (纸本)9789380544342

Common and disparate brains may be segmented by registering objective image with an outline. An outline may be described as the grouping of an intensity image and respectively segmented image. After registering the outline model and objective image, outline labels are propagated to objective image. In previous years, researchers have discovered segmentation algorithms to match outlines, subjects, query and also strategies for outline structure. this work presents a survey of several automated techniques for outline based segmentation of MRI images. In this survey researcher tried to highlight the weakness and strengths of outline based techniques using the concepts of artificial intelligence techniques and recommend new research directions in the field of medical science. Basically, paper focused on presenting the different criterion for detection and segmentation methods. Initially, paper described the algorithms on the basis of outline based strategy: label propagation, methods based upon the threshold, region and probabilistic techniques. On the basis of medical objective the methods are described: the brain and its inside structures segmentation with the damaged area of brains. In this paper a comparison of the literature review's result is also available. this paper presents a brief survey on automated segmentation and detection mechanism of damaged area of brains to classify the abnormality of brains.

关键词： Brain Tumor Segmentation Algorithms Magnetic Resonance Imaging (MRI) pattern recognition Machine Learning and Artificial Intelligence

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8th conference on Foundations of Systems Biology in Engineering, FOSBE 2019 - proceedings

8th Conference on Foundations of Systems Biology in Engineer...

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8th conference on Foundations of Systems Biology in Engineering, FOSBE 2019

the proceedings contain 47 papers. the topics discussed include: biomolecular signal tracker with fast time response;efficient learning in metabolic pathway designs through optimal assembling;multiobjective optimization of gene circuits for metabolic engineering;leveraging resource competition for part characterization in cell-free extracts;bayesian model selection in synthetic biology: factor levels and observation functions;impact of changing cell-cell communication network in models of epithelial pattern formation;a comparison of methods for quantifying prediction uncertainty in systems biology;literature and data-driven based inference of signaling interactions using time-course data;challenges in the calibration of large-scale ordinary differential equation models;and disturbance response analysis of cell-to-cell communication systems based on spatial frequency decomposition.

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Model of an Intellectual Information System for Recognizing Users of a Social Network Using Bioinspired Methods 1

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8th Computer Science On-Line conference (CSOC)

作者： Samoylov, Alexey Kucherova, Margarita Tchumichev, Vladimir Southern Fed Univ Inst Comp Technol & Informat Secur Taganrog Russia

ISBN: (数字)9783030198107

ISBN: (纸本)9783030198107

the analysis of social networks is one of the actively developing areas of research for today. In addition to methods of modeling social relations, the interest for researchers is also the methods of obtaining initial data. the analysis carried out by the authors showed that, as initial data, analysts use profile information, various types of activities. Consideration of photo albums and video files as a source of data on users of social networks was not considered. At the same time, by identifying the user's face and further searching it in photographs and video files in other profiles, an expansion of the list of basic data available to the analyst is achieved. the problems associated with the recognition and identification of the person in the photo and video are well known and not fully resolved. the greatest difficulty here is the problem of scene variation, since the angle and location of the faces in the photo and video cannot be known in advance. the article presents the results of solving the problem of scene variation, presented in the form of a model of an information system using bionspirited methods. this system and the method incorporated in it are intended for preliminary image processing in order to broaden the range of permissible scene variations.

关键词： pattern recognition Object identification Photometry Intellectual system Social networks Analysis

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1st international Workshop on Machine Learning and Medical Engineering for Cardiovasvular Healthcare, MLMECH 2019, and the 8th international Joint Workshops on computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2019, held in conjunction with 22nd international conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2019

1st International Workshop on Machine Learning and Medical E...

引用

1st international Workshop on Machine Learning and Medical Engineering for Cardiovasvular Healthcare, MLMECH 2019, and the 8th international Joint Workshops on computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2019, held in conjunction with 22nd international conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2019

ISBN: (纸本)9783030333263

the proceedings contain 24 papers. the special focus in this conference is on international Workshop on Machine Learning and Medical Engineering for Cardiovasvular Healthcare, and the international Joint Workshops on computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, held in conjunction with international conference on Medical Image computing and Computer Assisted Intervention. the topics include: Healthy Vessel Wall Detection Using U-Net in Optical Coherence Tomography;tracking of Intracavitary Instrument Markers in Coronary Angiography Images;abdominal Aortic Aneurysm Segmentation Using Convolutional Neural Networks Trained with Images Generated with a Synthetic Shape Model;A Multi-label Learning Method to Detect Arrhythmia Based on 12-Lead ECGs;random 2.5D U-net for Fully 3D Segmentation;towards Quantifying Neurovascular Resilience;the Effect of Labeling Duration and Temporal Resolution on Arterial Transit Time Estimation Accuracy in 4D ASL MRA Datasets - A Flow Phantom Study;ARVBNet: Real-Time Detection of Anatomical Structures in Fetal Ultrasound Cardiac Four-Chamber Planes;Attention-Guided Decoder in Dilated Residual Network for Accurate Aortic Valve Segmentation in 3D CT Scans;LabelECG: A Web-Based Tool for Distributed Electrocardiogram Annotation;deep Learning to Improve Heart Disease Risk Prediction;Automatic Detection of ECG Abnormalities by Using an Ensemble of Deep Residual Networks with Attention;Automatic Multi-label Classification in 12-Lead ECGs Using Neural Networks and Characteristic Points;Arrhythmia Classification with Attention-Based Res-BiLSTM-Net;preface;Multi-label Classification of Abnormalities in 12-Lead ECG Using 1D CNN and LSTM;particle Swarm Optimization for Great Enhancement in Semi-supervised Retinal Vessel Segmentation with Generative Adversarial Networks;mlmech-miccai 2019 preface;an Approach to Predict Multiple Cardiac Diseases.

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A Decentralized Context-aware Cross-domain Authorization Scheme for Pervasive computing 2019

A Decentralized Context-aware Cross-domain Authorization Sch...

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proceedings of the 2019 8th international conference on Networks, Communication and computing

作者： Bin Song Min Gao Henan University of Science and Technology and Henan International Joint Laboratory of Cyberspace Security Applications Luoyang China Luoyang Institute of Science and Technology Luoyang China

ISBN: (纸本)9781450377027

Context-aware access control is one of the most frequently used methods for making authorization decisions in pervasive computing environments. To the best of our knowledge, most previous relevant researches resorted to centralized schemes to preserve all the contextual information. As a result, they neglected actual circumstances where the sources of contextual information are generally decentralized among multiple management domains with different security policies. For the sake of cross-domain access control, in this paper we present a distributed context-aware authorization mechanism for pervasive computing applications. With the help of logical language theory, we demonstrate how the proposed model can attain the goal of effective reliability assurance and privacy protection by way of constructing a decision tree dynamically, according to the current contextual information.

关键词： security privacy context-awareness pervasive computing cross-domain access control

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Breaking the code on broken tablets: the learning challenge for annotated cuneiform script in normalized 2D and 3D datasets 15

Breaking the code on broken tablets: The learning challenge ...

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15th IAPR international conference on Document Analysis and recognition, ICDAR 2019

作者： Mara, Hubert Bogacz, Bartosz FCGL-Forensic Computational Geometry Laboratory IWR-Interdisciplinary Center for Scientific Computing Ruprecht-Karls-Universitat Heidelberg Heidelberg Germany

ISBN: (纸本)9781728128610

the number of known cuneiform tablets is assumed to be in the hundreds of thousands. the Hilprecht Archive Online contains 1977 high-resolution 3D scans of tablets. the online cuneiform database CDLI catalogs metadata for more than 100.000 tablets. While both are accessible publicly, large-scale machine learning and pattern recognition on cuneiform tablets remain elusive. the data is only accessible by searching web pages, the tablet identifiers between collections are inconsistent, and the 3D data is unprepared and challenging for automated processing. We pave the way for large-scale analyses of cuneiform tablets by assembling a cross-referenced benchmark dataset of processed cuneiform tablets: (i) frontally aligned 3D tablets with pre-computed high-dimensional surface features, (ii) six-views raster images for off-the-shelf image processing, and (iii) metadata, transcriptions, and transliterations, for a subset of 707 tablets, for learning alignment between 3D data, image and linguistic expression. this is the first dataset of its kind and of its size in cuneiform research. this benchmark dataset is prepared for ease-of-use and immediate availability for computational researches, lowering the barrier to experiment and apply standard methods of analysis, at https://***/10.11588/data/IE8CCN. © 2019 IEEE.

关键词： Metadata

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