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检索条件"任意字段=11th International Conference on Intelligent Data Engineering and Automated Learning"

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international Joint conference SOCO18-CISIS18-ICEUTE18: San Sebastin, Spain, June 6-8, 2018 Proceedings

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2018年

作者： Manuel Graña José Manuel Löpez-Guede Oier Etxaniz Álvaro Herrero José António SáEz Héctor Quintián Emilio S Corchado

ISBN: (纸本)9783319941196

this book includes papers presented at SOCO 2018, CISIS 2018 and ICEUTE 2018, all held in the beautiful and historic city of San Sebastian (Spain), in June 2018. Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate, and analyze highly complex issues and phenomena. After a rigorous peer-review process, the 13th SOCO 2018 international Program Committee selected 41 papers, with a special emphasis on optimization, modeling and control using soft computing techniques and soft computing applications in the field of industrial and environmental enterprises. the aim of the 11th CISIS 2018 conference was to offer a meeting opportunity for academic and industry researchers from the vast areas of computational intelligence, information security, and data mining. the need for intelligent, flexible behaviour by large, complex systems, especially in mission-critical domains, was the catalyst for the overall event. Eight of the papers included in the book were selected by the CISIS 2018 international Program Committee. the international Program Committee of ICEUTE 2018 selected 11 papers for inclusion in these conference proceedings.

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11th international Andrei Ershov Memorial conference on Perspectives of System Informatics, PSI 2017

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11th international Andrei Ershov Memorial conference on Perspectives of System Informatics, PSI 2017

ISBN: (纸本)9783319743127

the proceedings contain 31 papers. the special focus in this conference is on Perspectives of System Informatics. the topics include: Lightweight non-intrusive virtual machine introspection;a distributed approach to coreference resolution in multiagent text analysis for ontology population;a framework for dynamical construction of software components;A transformation-based approach to developing high-performance GPU programs;domain engineering the Magnolia way;approximating event system abstractions by covering their states and transitions;implementing the symbolic method of verification in the C-light project;highlights of the rice-shapiro theorem in computable topology;a memory model for deductively verifying linux kernel modules;a human-in-the-loop perspective for safety assessment in robotic applications;indexing of hierarchically organized spatial-temporal data using dynamic regular octrees;An approach to the validation of XML documents based on the model driven architecture and the object constraint language;compositional relational programming with name projection and compositional synthesis;whaleProver: First-order intuitionistic theorem prover based on the inverse method;distributed in situ processing of big raster data in the cloud;statistical approach to increase source code completion accuracy;using the subject area ontology for automating learning processes and scientific investigation;Runtime specialization of postgreSQL query executor;MicroTESK: A tool for constrained random test program generation for microprocessors;Enriching textual Xtext-DSLs with a graphical GEF-based editor;multi-level static analysis for finding error patterns and defects in source code;Towards automated static verification of GNU C programs;domain specific semantic validation of *** annotations;pipelined bottom-up evaluation of datalog programs: the push method;PosDB: A distributed column-store engine.

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How to design game-based healthcare applications for children? A study on children’s game preferences 11

How to design game-based healthcare applications for childre...

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11th international conference on Health Informatics, HEALthINF 2018 - Part of 11th international Joint conference on Biomedical engineering Systems and Technologies, BIOSTEC 2018

作者： de Vette, A.F.A. Tabak, M. Vollenbroek-Hutten, M.M.R. University of Twente Faculty of Electrical Engineering Mathematics and Computer Science Telemedicine Group P.O. Box 217 Enschede7500 AE Netherlands Roessingh Research and Development Telemedicine Group P.O. Box 310 Enschede7500 AH Netherlands

ISBN: (纸本)9789897582813

Game-based design can be used to develop engaging health applications for children. this engagement can only be realised when design is tailored to their preferences. In this study we investigate game preferences of children and translate these into design recommendations. Game preferences of children aged 6 to 12 were assessed through a questionnaire. Outcomes were classified by means of the 7D framework which divides game content into seven linear domains. Significant differences in mean scores among demographic subgroups were explored. Sixty-five children participated (M=9 years, SD=0.24, 36 boys, 29 girls, 8 children with asthma). data showed high preference for content in domains novelty (Mnovelty=63) and dedication (Mdedication=70). Analysis resulted in subdivision of scores based on gender, age and playing frequency. Striking differences in scores were found between boys and girls in discord (Mboys=62, Mgirls=19), intensity (Mboys=60, Mgirls=27), rivalry (Mboys=53, Mgirls=31) and threat (Mboys=64, Mgirls=25). To design games for children we recommend to stimulate curiosity by offering variation and discovery, to enable achievement, learning and social contact. A divergence in preferences for boys and girls must be regarded. Opposed to boys, girls may lose interest in games that have violent or scary content, that are mainly competitive or demand continuous effort. Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

关键词： Game design

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Uninorm based regularized fuzzy neural networks 11

Uninorm based regularized fuzzy neural networks

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11th IEEE international conference on Evolving and Adaptive intelligent Systems, EAIS 2018

作者： De Campos Souza, Paulo Vitor Silva, Gustavo Rodrigues Lacerda Torres, Luiz Carlos Bambirra Information Governance Secretaries Federal Center for Technological Education of Minas Gerais-CEFET-MG Belo Horizonte Brazil Graduate Program in Electrical Engineering-Universidade Federal de Minas Gerais-Av. Antônio Carlos 6627 Belo HorizonteMG31270-901 Brazil

ISBN: (纸本)9781538613764

this paper proposes a training algorithm for fuzzy neural networks that can generate consistent and accurate models while adding some level of interpretation to applied problems. learning is achieved through extreme learning machine concepts, allowing the adjustment of parameters during the training phase using a fast and straightforward approach. the use of the regularization in the inner layers of the model will enable it to be more precise and selfish since a reduced set of fuzzy rules can be extracted from the final result of the network. the proposed approach was evaluated through pattern classification problems using real datasets of large and small sizes. the achieved results were compared to the results obtained using another state of the art classifiers. Statistical analysis of the results suggests the proposed approach as a promising alternative to performing classification with some level of model interpretability. © 2018 IEEE.

关键词： Fuzzy neural networks

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Pediatric Spine Segmentation and Modeling Using Machine learning

Pediatric Spine Segmentation and Modeling Using Machine Lear...

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international conference on Ultra Modern Telecommunications and Workshops (ICUMT)

作者： Jan Mikulka Daniel Chalupa Kamil Říha Milan Filipovič Marek Dostál Department of Theoretical and Experimental Electrical Engineering Brno University of Technology Brno Czech Republic Department of Telecommunications Brno University of Technology Brno Czech Republic Department of Orthopedic Surgery The University Hospital Brno Brno Czech Republic Clinic of Radiology and Nuclear Medicine The University Hospital Brno Brno Czech Republic

Scoliosis embodies the most frequent three-dimensional spinal deformity in children. Only timely treatment during the growth of the spine may significantly reduce related health problems inflicted by the deformity on adults. the results obtained via conservative therapy are problematic, and a certain degree of curvature already requires surgical treatment that at the time of writing consists of repeated spinal surgeries posing a high risk of complications. the aim is to use a spine model for computer based simulation of changes in the stress on the spine during idiopathic and syndromic deformity correction via vertebral osteotomy. A machine-learning toolbox for 3D Slicer has been developed. the toolbox has a form of an application extension. Preprocessing of the data, training and usage of the classifier is possible through a simple and modern graphical user interface. the extension is capable of performing a variety of helpful tasks such as an analysis of the impact of the size of the training vector and feature selection on classifier precision. the results suggest that the training vector size can be minimized for all of the tested classifiers. Furthermore, the random forest classifier's performance seems to be resistant to training parameter changes. Support vector machine is sensitive to training parameter changes with optimal values concentrated in a narrow feature space.

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Proceedings - international conference on Developments in eSystems engineering, DeSE

Proceedings - International Conference on Developments in eS...

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11th international conference on Developments in eSystems engineering, DeSE 2018

ISBN: (纸本)9781538667125

the proceedings contain 61 papers. the topics discussed include: flexural static energy of steel fiber rubberized concrete beams with layered distribution;learning analytics and serious games: analysis of interrelation;prediction of Parkinson disease using gait signals;data science to improve patient management system;measuring the performance characteristics of MBSE techniques with bim for the construction industry;steganalysis of RGB images using merged statistical features of color channels;healthcare services innovations based on the state of the art technology trend industry 4.0;fog computing framework for Internet of things applications;and improve the accuracy of dirichlet reputation system for web services.

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Categorical Modeling Method of intelligent WorkFlow 1

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6th international conference on Mining Intelligence and Knowledge Exploration (MIKE)

作者： Craciunean, Daniel-Cristian Karagiannis, Dimitris Lucian Blaga Univ Sibiu Comp Sci & Elect Engn Dept Sibiu Romania Univ Vienna Fac Comp Sci Vienna Austria

ISBN: (数字)9783030059187

ISBN: (纸本)9783030059187;9783030059170

A category as well as a model is a mixture of graphical information and algebraic operations. therefore, category language seems to be the most general to describe the models. It can provide us with the features that must characterize both the DSL language and the Modeling Method concept. the theory of categories works with patterns or forms in which each of these forms describe different aspects of the real world. Category theory offers both, a language, and a lot of conceptual tools to efficiently handle models. An important aspect of modeling is building complex functions from a given set of simple functions, using different operations on functions such as composition and repeat composition. Category theory is exactly the right algebra for such constructions. the category theory creates the premises for the development of intelligent workflow modeling tools equipped with advanced analysis tools and automated learning mechanisms adapted to analyze and improve processes. the model allows on-line process information extraction, automatic learning from these data and self-improvement.

关键词： Modeling method Metamodel intelligent WorkFlow Category theory Categorical modeling method

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Species categorization via MicroRNAs based on 3’UTR target sites using sequence features 9

Species categorization via MicroRNAs based on 3’UTR target ...

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9th international conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2018 - Part of 11th international Joint conference on Biomedical engineering Systems and Technologies, BIOSTEC 2018

作者： Yousef, Malik Levy, Dalit Allmer, Jens Community Information Systems Zefat Academic College Zefat13206 Israel Applied Bioinformatics Wageningen University and Research Wageningen Netherlands

ISBN: (纸本)9789897582806

Proteins define phenotypes and their dysregulation leads to diseases. Post-translational regulation of protein abundance can be achieved by microRNAs (miRNAs). therefore studying this method of gene regulation is of high importance. MicroRNAs interact with their target messenger RNA via hybridization within a specialized molecular framework. Many miRNAs and their targets have been identified and they are listed in various databases like miRTarBase. the experimental identification of functional miRNA-mRNA pairs is difficult and, therefore, they are detected computationally which is complicated due to missing negative data. Machine learning has been used for miRNA and target detection and many features have been described for miRNAs and miRNA:mRNA target duplexes generally on a per species basis. However, many claims of cross-kingdom regulation via miRNAs have been made and, therefore, we were interested whether it is possible to differentiate among species based on the target sequence in the mRNA alone. thus, we investigated whether miRNA targets sites within the 3’UTR can be differentiated between species based on k-mer features only. Target information of one species was used as positive examples and the others as negative ones to establish machine learning models. It was observed that few features were sufficient for successful categorization of mircoRNA targets to species. For example mouse versus Caenorhabditis elegans reached up to 97% average accuracy over 100 fold cross validation. the simplicity of the approach, based on just k-mers, is promising for automatic categorization systems. In the future, this approach will help scrutinize alleged cross-kingdom regulation via miRNAs in respect to miRNA from one species targeting mRNAs in another. Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： Machine learning

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Audio data Hiding Using Octal Modulus Function Based Unsigned Integer Sample Values

Audio Data Hiding Using Octal Modulus Function Based Unsigne...

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Joint international conference on Computer engineering, Network and intelligent Multimedia (CENIM) / 11th AUN/SEED-Net Regional conference on Computer and Information engineering (RCCIE)

作者： Al-Hooti, Mohammed Hatem Ali Ahmad, Tohari Djanali, Supeno Inst Teknol Sepuluh Nopember Dept Informat Surabaya Indonesia Sanaa Univ Fac Comp & Informat Technol Sanaa Yemen

ISBN: (纸本)9781538675090

data hiding is proposed as a solution that helps to secure any significant information. these techniques conceal the existence of a secret message that is confidentially inserted into multimedia covers such as text, audio, video, or image. Audio data hiding is a recent research topic which is aimed to securely transfer an imperceptible stego file. this stego is transferred to the destination carrying a high payload. Commonly, schemes in steganography are classified into two domains: time and frequency. In the time domain, varied LSB techniques are proposed but these techniques are known as the simplest algorithms in the field of steganography. In this paper, an audio data hiding algorithm based on octal modulus function is presented. this method is conducted based on modifying the cover samples. the original samples are subtracted by the difference between the secret message digit and the same sample remainder value. three testing implementations are conducted by changing the base of unsigned integer (uint) function (e.g. uint8, uint16, or uint24) of the cover audio samples. the performance is evaluated regarding both the capacity and quality. this evaluation is performed based on varying the cover samples values using uint8, uint16, and uint24, so SNR values are approximately 32, 80, 129 dB, respectively. the values of SNR are obtained after fully embedding the cover file wherein each sample there are 3 secret bits.

关键词： Audio data Hiding Steganography Octal Modulus Function Information Security Network Security

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Cultivating Situational Interest in Blended learning Environment 11th

Cultivating Situational Interest in Blended Learning Environ...

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11th international conference on Blended learning (ICBL)

作者： Hui, Yan Keung Li, Chen Qian, Sheng Kwok, Lam-for City Univ Hong Kong Dept Comp Sci 83 Tat Chee Ave Kowloon Hong Kong Peoples R China

ISBN: (纸本)9783319945057;9783319945040

According to the theories of interest and self-determination in education psychology, students' academic performance will be positively affected by situational interest and learning motivation. For improving the design of an engineering course at the City University of Hong Kong in a blended learning environment, we apply these two theories to form a new conceptual model and verify it through an experimental study in which a total number of 61 undergraduate students participated during a whole 13-week course. In this study, we aim at finding out how situational interest can be cultivated. the data analysis results show that the learning motivation can further cultivate the situational interest on top of the individual interest, and the perceived usefulness of instructional design can enhance students' learning satisfaction and learning motivation. Our findings make theoretical contributions by combining these two theories and demonstrate the importance of these theories on the instructional design.

关键词： Situational interest theory of Interest Self-determination theory Instructional design

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