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检索条件"任意字段=Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition"

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12th international conference on Innovative Mobile and Internet Services in Ubiquitous computing, IMIS 2018

12th International Conference on Innovative Mobile and Inter...

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12th international conference on Innovative Mobile and Internet Services in Ubiquitous computing, IMIS 2018

ISBN: (纸本)9783319935539

the proceedings contain 95 papers. the special focus in this conference is on Innovative Mobile and Internet Services in Ubiquitous computing. the topics include: Implementation of WiFi P2P based DTN routing and gateway for disaster information networks;A new contents delivery network mixing on static/dynamic heterogeneous DTN environment;Predicate clustering-based entity-centered graph pattern recognition for query extension on the LOD;discrimination of eye blinks and eye movements as features for image analysis of the around ocular region for use as an input interface;dynamic group formation for an active learning system using smartphone to improve learning motivation;Evaluation of 13.56 MHz RFID system considering communication distance between reader and tag;an efficient routing protocol via depth adjustment and energy gradation in underwater wireless sensor networks;Vulnerability analysis on the image-based authentication through the PS/2 interface;differential-evolution-earthworm hybrid meta-heuristic optimization technique for home energy management system in smart grid;A spacecraft AIT visualization control system based on VR technology;an efficient home energy management and power trading in smart grid;hierarchical based coordination strategy to efficiently exchange the power among micro-grids;weighted cuckoo search based load balanced cloud for green smart grids;foged energy optimization in smart homes;short term load forecasting based on deep learning for smart grid applications;efficient resource allocation model for residential buildings in smart grid using fog and cloud computing;feature selection and extraction along with electricity price forecasting using big data analytics;proposal of a disaster support expert system using accumulated empirical data.

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Optimizing assignment of students to courses based on learning activity analytics 12

Optimizing assignment of students to courses based on learni...

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12th international conference on Educational Data Mining, EDM 2019

作者： Shimada, Atsushi Mouri, Kousuke Taniguchi, Yuta Ogata, Hiroaki Taniguchi, Rin-Ichiro Konomi, Shin'ichi Department of Advanced Information Technology Kyushu University Japan Institute of Engineering Tokyo University of Agriculture and Technology Japan Academic Center for Computing and Media Studies Kyoto University Japan Faculty of Arts and Science Kyushu University Japan

ISBN: (纸本)9781733673600

In this paper, we focus on optimizing the assignment of students to courses. the target courses are conducted by different teachers using the same syllabus, course design, and lecture materials. More than 1,300 students are mechanically assigned to one of ten courses taught by different teachers. therefore, mismatches often occur between students' learning behavior patterns and teachers' approach to teaching. As a result, students may be less satisfied, have a lower level of understanding of the material, and achieve less. To solve these problems, we propose a strategy to optimize the assignment of students to courses based on learning activity analytics. the contributions of this study are 1) clarifying the relationship between learning behavior pattern and teaching based on learning activity analytics using large-scale educational data, 2) optimizing the assignment of students to courses based on learning behavior pattern analytics, and 3) demonstrating the effectiveness of assignment optimization via simulation experiments. © EDM 2019 - proceedings of the 12th international conference on Educational Data Mining. All rights reserved.

关键词： Students

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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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A Framework for the Automatic Combination and Evaluation of Gene Selection Methods 12th

A Framework for the Automatic Combination and Evaluation of ...

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12th international conference on Practical Applications of Computational Biology and Bioinformatics (PACBB)

作者： Grasnick, Bastien Perscheid, Cindy Uflacker, Matthias Hasso Plattner Inst Potsdam Germany

ISBN: (纸本)9783319987026;9783319987019

High-throughput RNA-Sequencing technologies produce large gene expression datasets whose analysis leads to a better understanding and treatment of diseases like cancer. the data's high dimensionality poses challenges to its computational analysis, which is addressed by applying gene selection. Traditional gene selection methods are based on the data only. In turn, integrative approaches include curated biological information from external knowledge bases in the gene selection process, which improves result accuracy and computational complexity. this paper presents a framework for comparing knowledge based and computational gene selection. Moreover, a novel integrative method of the automatic combination of both approaches is presented. Results on a cancer dataset show that simple computational methods enriched by external knowledge can compete with complex computational techniques.

关键词： Gene expression data analysis Gene selection pattern recognition

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ACM international conference Proceeding Series

ACM International Conference Proceeding Series

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12th Innovations in Software Engineering conference, ISEC 2019

ISBN: (纸本)9781450362153

the proceedings contain 34 papers. the topics discussed include: is virtual reality product development different? an empirical study on VR product development practices;thrusthetero: a framework to simplify heterogeneous computing platform programming using design abstraction;an approach to identify use case scenarios from textual requirements specification;change-proneness of object-oriented software using combination of feature selection techniques and ensemble learning techniques;enhancing test cases generated by concolic testing;a knowledge centric approach to conceptualizing robotic solutions;making sense of actor behavior: an algebraic filmstrip pattern and its implementation;a software framework for adaptive signal analytics based on autonomic service components;modeling and coverage analysis of programs with exception handling;the value of software architecture recovery for maintenance;evolution traceability roadmap for business processes;key factors in scaling up agile team in matrix organization;and a case study exploring supply chain systems using actor based simulation.

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12th international conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2018

12th International Conference on Practical Applications of C...

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12th international conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2018

ISBN: (纸本)9783319987019

the proceedings contain 26 papers. the special focus in this conference is on Practical Applications of Computational Biology and Bioinformatics. the topics include: A bioinformatics protocol for quickly creating large-scale phylogenetic trees;Deep learning analysis of binding behavior of virus displayed peptides to AuNPs;compression of amino acid sequences;NET-ASAR: A tool for DNA sequence search based on data compression;Can an integrative SNP approach substitute standard identification in comprehensive case/control analyses?;simple pattern-only heuristics lead to fast subgraph matching strategies on very large networks;in silico predictions for fucoxanthin production by the diatom phaeodactylum tricornutum;EvoPPI: A web application to compare protein-protein interactions (PPIs) from different databases and species;a review on metabolomics data analysis for cancer applications;parameter estimation of essential amino acids in Arabidopsis thaliana using hybrid of bees algorithm and harmony search;a framework for the automatic combination and evaluation of gene selection methods;parallel cellular automaton tumor growth model;MOSCA: An automated pipeline for integrated metagenomics and metatranscriptomics data analysis;metabolite integration pipeline for the improvement of human metabolic models;a genetic programming approach applied to feature selection from medical data;A DNA sequence corpus for compression benchmark;17α-ethinylestradiol analysis of endo- and exometabolome of ulva lactuca (chlorophyta) by 1H-NMR spectroscopy and bioinformatics tools;in silico modeling and simulation approach for apoptosis caspase pathways;Molecular dynamic simulations suggest that P152R mutation within MeCP2 can lead to higher DNA binding affinity and loss of selective binding to methylated DNA.

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Finding Principal Semantics of Style in Art 12

Finding Principal Semantics of Style in Art

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12th IEEE international conference on Semantic computing (ICSC)

作者： Kim, Diana S. Liu, Bingchen Elgammal, Ahmed Mazzone, Marian Rutgers State Univ Dept Comp Sci New Brunswick NJ 08901 USA Coll Charleston Dept Art & Architectural Hist Charleston SC 29401 USA

ISBN: (纸本)9781538644072

We investigate a novel mechanism to interpret each coordinate of Deep Neural Network (DNN) activations with concepts aligned with art principles such as light, shape, pattern, line, and textures. After training state-of-the-art DNN architectures as paintings style classifiers, we collect activations from the second to last layer of DNN and conduct a data analysis. Based on the interpretation results, we can demonstrate which art principles are essential when machines understand styles and also can decipher each coordinates value in the context of relatedness to specific art principles.

关键词： pattern recognition Machine learning Deep neural network Unsupervised learning Semantic interpretation of DNN features Art principles

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Cough Detection Using Hidden Markov Models 12th

Cough Detection Using Hidden Markov Models

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12th international conference on Social computing, Behavioral-Cultural Modeling, and Prediction (SBP) / conference of the Behavioral-Representation-in-Modeling-and-Simulation- Society (BRiMS)

作者： Teyhouee, Aydin Osgood, Nathaniel D. Univ Saskatchewan Saskatoon SK Canada

ISBN: (纸本)9783030217419;9783030217402

Respiratory infections and chronic respiratory diseases impose a heavy health burden worldwide. Coughing is one of the most common symptoms of many such infections, and can be indicative of flare-ups of chronic respiratory diseases. Whether at a clinical or public health level, the capacity to identify bouts of coughing can aid understanding of population and individual health status. Developing health monitoring models in the context of respiratory diseases and also seasonal diseases with symptoms such as cough has the potential to improve quality of life, help clinicians and public health authorities with their decisions and decrease the cost of health services. In this paper, we investigated the ability to which a simple machine learning approach in the form of Hidden Markov Models (HMMs) could be used to classify different states of coughing using univariate (with a single energy band as the input feature) and multivariate (with a multiple energy band as the input features) binned time series using both of cough data. We further used the model to distinguish cough events from other events and environmental noise. Our Hidden Markov algorithm achieved 92% AUR (Area Under Receiver Operating Characteristic Curve) in classifying coughing events in noisy environments. Moreover, comparison of univariate with multi-variate HMMs suggest a high accuracy of multivariate HMMs for cough event classifications.

关键词： Cough detection Machine learning Hidden Markov Model Frequency domain Time domain pattern recognition Spectrogram Health care Public health

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Transformer Anomaly recognition Method Based on Abnormal Characteristics of DGA Data 12

Transformer Anomaly Recognition Method Based on Abnormal Cha...

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12th international conference on the Properties and Applications of Dielectric Materials (ICPADM)

作者： Zhang, Peng Qi, Bo Yang, Pei Zhang, Ruoyu Li, Chengrong North China Elect Power Univ State Key Lab Alternate Elect Power Syst Renewabl Beijing 102206 Peoples R China Global Energy Interconnect Res Inst Co Ltd Adv Comp & Big Data Lab SGCC Beijing 102209 Peoples R China

ISBN: (纸本)9781538657881

Power transformer is one of the key electrical apparatus in power system and its reliability has directly correlation on the safety of power system. this paper presents anomaly recognition method of oil chromatographic data based on distributed computing, aiming at the existing problems that the study fails to use abnormal features of oil chromatographic data effectively to identify the abnormal and lack of the problem of identifying method for massive data anomaly. First, obtain the characteristics of abnormal data through the analysis of a large number of oil spectrum anomaly data sequence. then, Form anomaly recognition method. the method uses abnormal features of oil chromatographic data as judgment index of abnormal mode. If any abnormal pattern is met, the abnormal data can be identified. Abnormal recognition of transformer oil chromatographic data is realized on distributed computing platform. Accuracy rate of anomaly recognition is up to 89.3%. Experimental results show that this method is accurate and can be applied to distributed computing platform.

关键词： power transformer oil chromatogram data abnormal features anomaly recognition distributed computing

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Measurements of Cloud Base Height and Coverage using Elastic Multiangle Lidar Scans at the Pierre Auger Observatory 38

Measurements of Cloud Base Height and Coverage using Elastic...

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38th international Cosmic Ray conference, ICRC 2023

作者： Pallotta, Juan Vicente Rodriguez, Jorge Ruben Abdul Halim, A. Abreu, P. Aglietta, M. Allekotte, I. Almeida Cheminant, K. Almela, A. Aloisio, R. Alvarez-Muñiz, J. Ammerman Yebra, J. Anastasi, G.A. Anchordoqui, L. Andrada, B. Andringa, S. Aramo, C. Araújo Ferreira, P.R. Arnone, E. Arteaga Velázquez, J.C. Asorey, H. Assis, P. Avila, G. Avocone, E. Badescu, A.M. Bakalova, A. Balaceanu, A. Barbato, F. Bartz Mocellin, A. Bellido, J.A. Berat, C. Bertaina, M.E. Bhatta, G. Bianciotto, M. Biermann, P.L. Binet, V. Bismark, K. Bister, T. Biteau, J. Blazek, J. Bleve, C. Blümer, J. Boháčová, M. Boncioli, D. Bonifazi, C. Bonneau Arbeletche, L. Borodai, N. Brack, J. Brichetto Orchera, P.G. Briechle, F.L. Bueno, A. Buitink, S. Buscemi, M. Büsken, M. Bwembya, A. Caballero-Mora, K.S. Cabana-Freire, S. Caccianiga, L. Caracas, I. Caruso, R. Castellina, A. Catalani, F. Cataldi, G. Cazon, L. Cerda, M. Cermenati, A. Chinellato, J.A. Chudoba, J. Chytka, L. Clay, R.W. Cobos Cerutti, A.C. Colalillo, R. Coleman, A. Coluccia, M.R. Conceição, R. Condorelli, A. Consolati, G. Conte, M. Convenga, F. Correia dos Santos, D. Costa, P.J. Covault, C.E. Cristinziani, M. Cruz Sanchez, C.S. Dasso, S. Daumiller, K. Dawson, B.R. de Almeida, R.M. de Jesús, J. de Jong, S.J. de Mello Neto, J.R.T. De Mitri, I. de Oliveira, J. de Oliveira Franco, D. de Palma, F. de Souza, V. De Vito, E. Del Popolo, A. Deligny, O. Denner, N. Deval, L. di Matteo, A. Dobre, M. Dobrigkeit, C. D’Olivo, J.C. Domingues Mendes, L.M. dos Anjos, R.C. Ebr, J. Ellwanger, F. Emam, M. Engel, R. Epicoco, I. Erdmann, M. Etchegoyen, A. Evoli, C. Falcke, H. Farmer, J. Farrar, G. Fauth, A.C. Fazzini, N. Feldbusch, F. Fenu, F. Fernandes, A. Fick, B. Figueira, J.M. Filipčič, A. Fitoussi, T. Flaggs, B. Fodran, T. Fujii, T. Fuster, A. Galea, C. Galelli, C. García, B. Gaudu, C. Gemmeke, H. Gesualdi, F. Gherghel-Lascu, A. Ghia, P.L. Giaccari, U. Giammarchi, M. Glombitza, J. Gobbi, F. Gollan, F. Golup, G. Gómez Berisso, M. Buenos Aires Argentina Observatorio Pierre Auger Av. San Martín Norte 304 Malargüe5613 Argentina San Carlos de Bariloche Argentina Departamento de Física Departamento de Ciencias de la Atmósfera y los Océanos FCEyN Universidad de Buenos Aires and CONICET Buenos Aires Argentina IFLP Universidad Nacional de La Plata and CONICET La Plata Argentina Buenos Aires Argentina CONICET U.N.R. Facultad de Ciencias Bioquímicas y Farmacéuticas U.N.R. Rosario Argentina Mendoza Argentina Buenos Aires Argentina International Center of Advanced Studies Instituto de Ciencias Físicas ECyT-UNSAM CONICET Campus Miguelete – San Martín Buenos Aires Argentina Argentina Observatorio Pierre Auger and Comisión Nacional de Energía Atómica Malargüe Argentina Universidad Tecnológica Nacional Facultad Regional Buenos Aires Buenos Aires Argentina University of Adelaide AdelaideSA Australia Brussels Belgium Vrije Universiteit Brussels Brussels Belgium Centro Federal de Educação Tecnológica Celso Suckow da Fonseca Petropolis Brazil Brazil Universidade de São Paulo Escola de Engenharia de Lorena SP Lorena Brazil Universidade de São Paulo Instituto de Física de São Carlos SP São Carlos Brazil Universidade de São Paulo Instituto de Física SP São Paulo Brazil Universidade Estadual de Campinas IFGW SP Campinas Brazil Universidade Estadual de Feira de Santana Feira de Santana Brazil Universidade Federal de Campina Grande Centro de Ciencias e Tecnologia Campina Grande Brazil Universidade Federal do ABC SP Santo André Brazil Universidade Federal do Paraná Setor Palotina Palotina Brazil Universidade Federal do Rio de Janeiro Instituto de Física RJ Rio de Janeiro Brazil Observatório do Valongo RJ Rio de Janeiro Brazil Universidade Federal Fluminense EEIMVR RJ Volta Redonda Brazil Universidad de Medellín Medellín Colombia Universidad Industrial de Santander Bucaramanga Colombia Charles University Faculty of Mathematics and Physics Institute of Particle and

Cloud features significantly affect the reconstruction of extensive air showers, and their characterization plays an important role in atmospheric monitoring. A multi-directional characterization of the cloud pattern is provided by a combination of several instruments of the atmospheric monitoring network at the Pierre Auger Observatory (Mendoza Province, Argentina). In this work, we present the results of an analysis of the cloud measurements using data taken from 2007 to 2022 by the elastic lidars positioned in the proximity of the fluorescence detector (FD) sites. these systems provide hourly measurements of cloud coverage and base height above FD. the ansatz of horizontal homogeneity of cloud structures is tested by comparing the hourly measurements of cloud base height and coverage done simultaneously at different lidar locations. these results allow a detailed description of cloud patterns observed above the array throughout the whole period. the variation of cloud parameters is shown and quantitative conclusions about cloud homogeneity across the array of the Pierre Auger Observatory are given. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Miocene

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