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4th international Workshop on Multimodal Brain Image Analysis, MBAI 2019, and the 7th international Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2019, held in conjunction with the 22nd international conference on Medical Imaging and computer Assisted Intervention, MICCAI 2019

4th International Workshop on Multimodal Brain Image Analysi...

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4th international Workshop on Multimodal Brain Image Analysis, MBAI 2019, and the 7th international Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2019, held in conjunction with the 22nd international conference on Medical Imaging and computer Assisted Intervention, MICCAI 2019

ISBN: (纸本)9783030332259

the proceedings contain 23 papers. the special focus in this conference is on Multimodal Brain Image Analysis. the topics include: Biological Knowledge Guided Deep Neural Network for Brain Genotype-Phenotype Association Study;learning Human Cognition via fMRI Analysis Using 3D CNN and Graph Neural Network;CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation;brainPainter: A Software for the Visualisation of Brain Structures, Biomarkers and Associated Pathological Processes;structural Similarity Based Anatomical and Functional Brain Imaging Fusion;multimodal Brain Tumor Segmentation Using Encoder-Decoder with Hierarchical Separable Convolution;prioritizing Amyloid Imaging Biomarkers in Alzheimer’s Disease via learning to Rank;diffeomorphic Metric learning and Template Optimization for Registration-Based Predictive Models;3D Mapping of Serial Histology Sections with Anomalies Using a Novel Robust Deformable Registration Algorithm;spatiotemporal Modeling for Image Time Series with Appearance Change: application to Early Brain Development;An Edge Enhanced SRGAN for MRI Super Resolution in Slice-Selection Direction;surface Foliation Based Brain Morphometry Analysis;mixture Probabilistic Principal Geodesic Analysis;a Geodesic Mixed Effects Model in Kendall’s Shape Space;An As-Invariant-As-Possible GL+(3) -Based Statistical Shape Model;exploring Functional Connectivity Biomarker in Autism Using Group-Wise Sparse Representation;classifying Stages of Mild Cognitive Impairment via Augmented Graph Embedding;mapping the Spatio-Temporal Functional Coherence in the Resting Brain;Species-Preserved Structural Connections Revealed by Sparse Tensor CCA;identification of Abnormal Cortical 3-Hinge Folding Patterns on Autism Spectral Brains;exploring Brain Hemodynamic Response Patterns via Deep Recurrent Autoencoder;3D Convolutional Long-Short Term Memory Network for Spatiotemporal Modeling of fMRI Data.

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Deep learning: application of the LSTM model in the categorization of tweets on violence in the city of Belém 4

Deep learning: Application of the LSTM model in the categori...

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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： Da Costa, Jonatã Paulino Dos Santos, Aurea Milene Teixeira Barbosa Da Mata, Eulália Carvalho Da Silva, Marcelino Silva Aranha, Priscila Siqueira Francês, Carlos Renato Lisboa UFPA - Unniversidade Federal do Pará Rua Augusto Corrêa 0 -Guamá Belém-ParáCEP 66075-110 Brazil

ISBN: (纸本)9789898533920

Twitter has more than 313 million users, is considered a subjective social network of content generation on the Internet, not only used to disclose personal information, but shares opinions and information about events and events in general, being a great source of research for the discovery of knowledge among relevant data. In this context, the present work presents a study on the implementation (application) of the Recurrent Neural Network LSTM for the analysis and classification of tweets that are related to crime and not crime. the set of data that is the object of the survey comes from an account of a newspaper in the city of Belém, containing 20000 records in a period of two months. the results obtained with the use of RNR LSTM proved to be quite satisfactory, reaching accuracy in some cases of 90% correctness. Based on the results of this research, we observed the effectiveness of this method in the analysis of feelings in comparison with other algorithms such as Nayve Bayes, Convolutional Neural Networks used in the literature. Because it is a network that uses a Long-Term Memory technique, it can adapt to large time intervals, such as Twitter texts. © Multi conference on computer Science and Information Systems, MCCSIS 2019. All rights reserved.

关键词： Python

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4th international conference on Future Data and Security Engineering, FDSE 2017

4th International Conference on Future Data and Security Eng...

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4th international conference on Future Data and Security Engineering, FDSE 2017

ISBN: (纸本)9783662588079

the proceedings contain 7 papers. the special focus in this conference is on Future Data and Security Engineering. the topics include: On semi-supervised learning with sparse data handling for educational data classification;logistic regression methods in selected medical information systems;mapping requirements specifications into a formalized blockchain-enabled authentication protocol for secured personal identity assurance;gait recognition with multi-region size convolutional neural network for authentication with wearable sensors;agile software engineering methodology for information systems’ integration projects;effectiveness of object oriented inheritance metrics in software Reusability;security analysis of administrative role-based access control policies with contextual information;Metamorphic malware detection by PE analysis with the longest common sequence;a steganography technique for images based on wavelet transform;Estimating the assessment difficulty of CVSS environmental metrics: An experiment;activity recognition from inertial sensors with convolutional neural networks;accuracy improvement for glucose measurement in handheld devices by using neural networks;towards a domain specific framework for wearable applications in internet of things;development and implementation of a web application for the management of data recorded by a carbon monoxide sensor;Privacy-aware data analysis middleware for data-driven EHR systems;an exact consensus-based network intrusion detection system;binary tree based deterministic positive selection approach to network security;application of rough sets to negative selection algorithms;focusing on precision- and trust-propagation in knowledge processing systems;MITIS - An insider threats mitigation framework for information systems;fast top-q and top-k query answering;integrating knowledge-based reasoning algorithms and collaborative filtering into e-learning material recommendation system.

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A System Dynamics computer Model to Assess the Effects of Action Games on the Development of Children with Special Need 4

A System Dynamics Computer Model to Assess the Effects of Ac...

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4th international conference on Information Management and Technology, ICIMTech 2019

作者： Satria, thomas Galih Sardjono, Wahyu Panggabean, Francisco Maruli Game Application Technology Program School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information Systems Management Department Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781728133331

Special needs children have a tendency to play more games than children with development in general. Game play activities are often carried out by children with special needs can be a support learning and therapy due to his players the game has interaction without having to meet with his co-star in person. Starting from these data, this study aims to create a model of the System Dynamics approach. Data collected will be simulated by variables other support. the simulation results of the model will be seen autistic children therapy behavior. the results are then analyzed to create an alternative to the existing model. the benefit of this research is to know the description of game play to treatment of children with special needs. the results of simulation showed that playing games in an average time children with autism play therapy can help improve the quality of children with autism if children with autism play the game in a long time actually showed a decrease. © 2019 IEEE.

关键词： System theory

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4th international conference on Smart Computing and Communications, SmartCom 2019

4th International Conference on Smart Computing and Communic...

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4th international conference on Smart Computing and Communications, SmartCom 2019

ISBN: (纸本)9783030341381

the proceedings contain 40 papers. the special focus in this conference is on Smart Computing and Communications. the topics include: I2P Anonymous Communication Network Measurement and Analysis;plot Digitizing over Big Data Using Beam Search;trust-Aware Resource Provisioning for Meteorological Workflow in Cloud;do Top Social Apps Effect Voice Call? Evidence from Propensity Score Matching Methods;Cognitive Hierarchy Based Coexistence and Resource Allocation for URLLC and eMBB;smart Custom Package Decision for Mobile Internet Services;a Space Dynamic Discovery Scheme for Crowd Flow of Urban City;automated Classification of Attacker Privileges Based on Deep Neural Network;nnD: Shallow Neural Network Based Collision Decoding in IoT Communications;a Smart Roll Wear Check Scheme for Ensuring the Rolling Quality of Steel Plates;subordinate Relationship Discovery Method Based on Directed Link Prediction;an Elephant Flow Detection Method Based on machine learning;AI Enhanced Automatic Response System for Resisting Network threats;A Cross-Plane Cooperative DDoS Detection and Defense Mechanism in Software-Defined Networking;a Hardware Trojan Detection Method Design Based on TensorFlow;Resolving the Loop in High-Level SDN Program for Multi-table Pipeline Compilation;DC Coefficients Recovery from AC Coefficients in the JPEG Compression Scenario;a Performance Evaluation Method of Coal-Fired Boiler Based on Neural Network;Analysis and Prediction of Commercial Big Data Based on WIFI Probe;Design and Optimization of Camera HAL Layer Based on Android;an Improved Prediction Model for the Network Security Situation;music Rhythm Customized Mobile application Based on Information Extraction;computational Challenges and Opportunities in Financial Services;A Shamir threshold Model Based Recoverable IP Watermarking Scheme.

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Multi-spectral Palmprint Recognition with Deep Multi-view Representation learning 4th

Multi-spectral Palmprint Recognition with Deep Multi-view Re...

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4th international conference on machine learning and Intelligent Communications, MLICOM 2019

作者： Xu, Xiangyu Xu, Nuoya Li, Huijie Zhu, Qi College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing210093 China

ISBN: (纸本)9783030323875

With the widespread application of biometrics in identification systems, palmprint recognition technology, as an emerging biometric technology, has received more and more attention in recent years. Palmprint recognition mainly focuses on image acquisition, preprocessing, feature selection and image matching. Feature extraction and matching are usually the most essential processes in palmprint recognition, and most of the research is based on feature selection and image matching, and many researchers use rich knowledge in machine learning and computer vision to solve these problems. In this paper, we propose a deep multi-view representation learning based multi-spectral palmprint fusion method, which uses deep neural networks to extract feature representation of multi-spectral palmprint images for palmprint classification. In this manner, the unique features of different spectral palmprint images can be used to learn a view-invariant representation of each palmprint. By using view-invariant representation, we can get better palmprint recognition performance than single modality. Experiments are performed on PolyU palmprint data set to validate the effectiveness of the proposed method. © 2019, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Feature extraction

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Taxi service pricing based on online machine learning 4th

Taxi service pricing based on online machine learning

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4th international conference on Data Mining and Big Data, DMBD 2019

作者： Avdeenko, Tatiana Khateev, Oleg Novosibirsk State Technical University 20 K. Marksa Avenue Novosibirsk630073 Russia

ISBN: (纸本)9789813295629

In present paper we propose an approach to the dynamic taxi service pricing based on data mining from the large database of cases accumulated in the company. We believe that historical data on decisions made by experienced managers in the past contain valuable information on the most subtle parameters that influence decision making, but cannot be taken into account in the direct optimization formulations proposed in the literature. the analysis of existing clustering methods is carried out and the Enhanced Self-Organizing Incremental Neural Network (ESOINN) is chosen which is the most suitable for online learning with a previously unknown number of clusters. A comparative analysis of the accuracy of the proposed method has been carried out. It is discovered that ESOINN shows the best accuracy of prediction in a realistic situation with acceptable waiting time. We also presented a web application implementing the proposed approach. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Decision making

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Semantic Relationship Study between Citing and Cited Scientific Articles Using Topic Modeling 19

Semantic Relationship Study between Citing and Cited Scienti...

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proceedings of the 4th international conference on Big Data and Internet of things

作者： Sara Mifrah Ben Lahmar El Habib Laboratory for Information Processing and Modeling Hassan II University of Casablanca Cdt Driss El Harti Sidi Othman Casablanca Morocco

ISBN: (纸本)9781450372404

In the evaluation of scientific research, it is clear that 'scientific quality' is proving to be one of the most important criteria, and in the case of research for development, it is on an equal footing with another key dimension: relevance for development. the evaluation criteria and procedures are very similar to those applied in the evaluation of research in general: peer reviews, panels, bibliometric indices, etc ... the practical application of these tools in the case of research for development can sometimes be quite difficult. there is, however, a general consensus that quality should be expressed identically for any scientific research, with the same problems and constraints. In this article and to evaluate a scientific article, we thought to study the semantic relationship between the citing article and the other cited, we based on the Topic modeling theme with the choice of LDA and LDA2VEC algorithms applied to the corpus Nips (1987-2017) then on the citations of each article of the corpus.

关键词： Topic Modeling Cosine-Similarity machine learning Natural language processing

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Ant colony optimization for markov blanket-based feature selection. application for precision medicine 1

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4th international conference on machine learning, Optimization, and Data Science, LOD 2018

作者： Sinoquet, Christine Niel, Clément LS2N UMR CNRS 6004 Université de Nantes 2 rue de la Houssinière Nantes Cedex44322 France

ISBN: (数字)9783030137090

ISBN: (纸本)9783030137083

In this work, we address feature subset selection in the case when the variables exert a null or weak marginal effect on the target variable, a situation called "pure" epistasis hereafter. We explore the Markov blanket approach, to tackle epistasis detection, and we introduce SMMB-ACO. this method combines Markov blanket learning with stochastic and ensemble features and guides the stochastic sampling process by incorporating ant colony optimization. We first analyze the impact of parameter adjustment on SMMB-ACO complexity. then using simulated and real data, we compare SMMB-ACO with four other methods, including its former version SMMB. We show that SMMB-ACO compares well with three state-of-the-art methods and that SMMB-ACO is more stable than SMMB. On the real dataset, the detection ability of SMMB-ACO is close to that of the best approach, which is a slow method, and SMMB-ACO is the fastest algorithm behind a much less performing method. © Springer Nature Switzerland AG 2019.

关键词： Bayesian networks

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4th international conference on Signal and Information Processing, Networking and computers, ICSINC 2018

4th International Conference on Signal and Information Proce...

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4th international conference on Signal and Information Processing, Networking and computers, ICSINC 2018

ISBN: (纸本)9789811317323

the proceedings contain 36 papers. the special focus in this conference is on Signal and Information Processing, Networking and computers. the topics include: Research on a component-based universal spacecraft telemetry system design method;design and verification of attitude and orbit control system based on integrated electronic technology for micro-small satellite;Design of OBDH software test platform based on QEMU;study of high-speed serial data transmission of high-resolution remote sensing camera;Reduced-dynamic EKF-based GPS+BDS real-time orbit determination;application of satellite interference imaging technology in building safety monitoring;precision temperature measurement method for spacecraft based on reference resistor;pointing coordinate system error correction method for integration of laser communication terminal into satellite;the on board data analysis about the open flag current of digital sun sensor;wireless sensor network protocol based on hierarchical merkle tree;dynamic optimal simulation and analysis of the load chassis of fly-around satellite;Simulation study of DSP’s total dose resistance circuit based on step by step analysis method;the angular momentum management method based on CMGs for the fast maneuvering satellites;Analysis of LTE FDD band 8 terminal in LTE network;discussion about the application of big data in information management system of disease control and prevention laboratory in guizhou province;a novel algorithm of geographical portraits based on telecommunication data;a Novel Architecture and machine learning Algorithm for the Prediction of User Equipment Replacing;using massive mobile signaling to monitor the highway traffic;data quality management and measurement;centralization and collaboration in 5G ultra-dense network architecture.

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