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Russian Advances in Fuzzy Systems and Soft computing: Selected Contributions to the 8th international conference on "Fuzzy Systems, Soft Soft computing and Intelligent Technologies",FSSCIT 2020

作者： Tulupyev, Alexandr Kharitonov, Nikita Saint Petersburg State University University Embankment 7/9 St Petersburg199034 Russia SPIIRAS 14-Ya Liniya V.O. 39 St Petersburg199178 Russia

Algebraic Bayesian networks are related to the class of probabilistic graphical models. As a machine learning model they are required to be trained on some data set. this work is dedicated to the frequentist approach to machine learning of a knowledge pattern as a local learning of the Algebraic Bayesian network. the theoretical explanation of approach is provided and the algorithm is described. the algorithm’s pseudocode is presented, its theoretical complexity is calculated. then an experiment is conducted and real estimates of the algorithm's implementation time of work are received. © 2020 CEUR-WS. All rights reserved.

关键词： Bayesian networks

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Artificial Intelligence Gamified AAL Solution 15th

Artificial Intelligence Gamified AAL Solution

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15th Mediterranean conference on Medical and Biological Engineering and computing (MEDICON)

作者： Pinto, Marta Pereira, Mario Raposo, Diana Simoes, Marco Castelo-Branco, Miguel Intellicare Coimbra Portugal CIBIT FMUC Coimbra Portugal CISUC Coimbra Portugal ICNAS Coimbra Portugal

ISBN: (纸本)9783030316358;9783030316341

GameAAL - Gamification Supporting Active and Assisted Living is an innovative system to monitor elderly daily life activities and provide neurocognitive stimulation games. the solution is focused at filling a gap on existing Ambient Assisted Living solutions, promoting social interaction and mobility of end-users using gamification and machine learning techniques. For each goal achieved, the system unlocks a reward providing the user with the chance of winning free admissions in cultural events supplied by community partners. A Proof of Concept of AAL ecosystem and TV interface is ongoing with 26 real end-users, reporting good acceptability and willingness to use the system.

关键词： AAL ADL pattern recognition Gamification Cognitive training

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8th international conference on Communications, Signal Processing, and Systems, CSPS 2019

8th International Conference on Communications, Signal Proce...

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8th international conference on Communications, Signal Processing, and Systems, CSPS 2019

ISBN: (纸本)9789811394089

the proceedings contain 326 papers. the special focus in this conference is on Communications, Signal Processing, and Systems. the topics include: Research on Motor Speed Estimation Method Based on Electric Vehicle;A Novel Virtual Cell Power Allocation and Interference Merging Algorithm in UDN;device-Free Sensing for Gesture recognition by Wi-Fi Communication Signal Based on Auto-encoder/decoder Neural Network;detection of Sleep Apnea Based on Cardiopulmonary Coupling;study on a Space-Air-Ground Integrated Data Link Networks Architecture;similar Cluster Based Continuous Bag-of-Words for Word Vector Training;Research on Integrated Waveform of FDA Radar and Communication Based on Linear Frequency Offsets;research on Parameter Configuration of Deep Neural Network Applied on Speech Enhancement;mid-Infrared Characteristic Analysis of Stability Index of Vehicle Gasoline;coverage Probability Analysis of D2D Communication Based on Stochastic Geometry Model;application of Mid-Infrared Characteristic Analysis Technology in Gasoline Quality Control;A Generalized Sampling Based Method for Digital Predistortion of RF Power Amplifiers;Optimum Design of Intersatellite Link Based on STK;integrated Detection and Tracking in Asynchronous Moving Radar Network;fault-Tolerant Decompression Method of Compressed Chinese Text Files;Classification of Human Motion Status Using UWB Radar Based on Decision Tree Algorithm;A Sub-aperture Division Method for FMCW CSAR Imaging;an Experimental Study of Sea Target Detection of Passive Bistatic Radar Based on Non-cooperative Radar Illuminators;Design of a Quasi-Real-Time Communication System for LEO Satellites Using Beidou Short-Message Service;A Physically Decoupled Onboard Control Plane for Software Defined LEO Constellation Network;Study of Fault pattern recognition for Spacecraft Based on DTW Algorithm.

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uPAD: Unsupervised Privacy-Aware Anomaly Detection in High Performance computing Systems 8th

uPAD: Unsupervised Privacy-Aware Anomaly Detection in High P...

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8th international conference on pattern recognition Applications and Methods (ICPRAM)

作者： Ghiasvand, Siavash Tech Univ Dresden Dresden Germany

ISBN: (纸本)9789897583513

Rapid growing complexity of HPC systems in response to demand for higher computing performance, results in higher probability of failures. Early detection of failures significantly reduces the damages caused by failure via impeding their propagation through system. Various anomaly detection mechanism are proposed to detect failures in their early stages. Insufficient amount of failure samples in addition to privacy concerns extremely limits the functionality of available anomaly detection approaches. Advances in machine learning techniques, significantly increased the accuracy of unsupervised anomaly detection methods, addressing the challenge of insufficient failure samples. However, available approaches are either domain specific, inaccurate, or require comprehensive knowledge about the underlying system. Furthermore, processing certain monitoring data such as system logs raises high privacy concerns. In addition, noises in monitoring data severely impact the correctness of data analysis. this work proposes an unsupervised and privacy-aware approach for detecting abnormal behaviors in general HPC systems. Preliminary results indicate high potentials of autoencoders for automatic detection of abnormal behaviors in HPC systems via analyzing anonymized system logs using fast-trainable noise-resistant models.

关键词： pattern Detection Time Series Analysis Anomaly Detection Neural Networks Noise Mitigation

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8th international Workshop on New Frontiers in Mining Complex patterns, NFMCP 2019, held in conjunction with the European conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2019

8th International Workshop on New Frontiers in Mining Comple...

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8th international Workshop on New Frontiers in Mining Complex patterns, NFMCP 2019, held in conjunction with the European conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2019

ISBN: (纸本)9783030488604

the proceedings contain 9 papers. the special focus in this conference is on New Frontiers in Mining Complex patterns. the topics include: A heuristic approach for sensitive pattern hiding with improved data quality;interpretable survival gradient boosting models with bagged trees base learners;neural hybrid recommender: Recommendation needs collaboration;discovering discriminative nodes for classification with deep graph convolutional methods;soft voting windowing ensembles for learning from partially labelled streams;Disentangling aspect and opinion words in sentiment analysis using lifelong PU learning;customer purchase behavior prediction in e-commerce: A conceptual framework and research agenda.

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Mobile Application: Mobile Assistance for Visually Impaired People - Speech Interface System (SIS) 8

Mobile Application: Mobile Assistance for Visually Impaired ...

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8th international conference on Information Technology and Multimedia, ICIMU 2020

作者： Norkhalid, Abdul Majid Faudzi, Masyura Ahmad Ghapar, Azimah Abdul Rahim, Fiza Abdul College of Computing and Informatics Universiti Tenaga Nasional Department of Informatics Malaysia

ISBN: (纸本)9781728173108

the evolution of technology has been made to bring the most benefits to human-being on communication and to facilitate their day-to-day activities. Technologies contribution, such as mobile application, has been proved to have a high capability to cater to the needs of a person with disabilities. the usage of smartphone is limited for visually impaired(VI) community as most of the currently available mobile application are not user-friendly for people with vision disability. Although smartphones nowadays are offering accessibility services such as TalkBack for Android and VoiceOver for iOS, these accessibilities provide fewer functions on navigating the VI community. A speech interface system(SIS) in mobile application combined with object and distance detection could help the VI community to navigate to their destination only with the use of a smartphone. this Systematic Literature Review (SLR) provide our findings on the present study of speech recognition projects and the requirement issues of speech recognition in mobile application platform throughout supporting VI people. three journal databases (Google Scholar, IEEE Explore and Science Direct) has been searching throughout this SLR with articles ranging from the year of 2013-2019. A result of 136 article titles, abstracts of 73 articles were examined, 35 full-text articles were selected for final review. A total of 19 articles are analyzed. the purpose of the SLR is to collect the technique, evaluation methods and the validation of the projects. © 2020 IEEE.

关键词： Smartphones

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Convergence of Intelligent Data Acquisition and Advanced computing Systems

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SENSORS 2021年第7期21卷 2262页

作者： Stamatescu, Grigore Sachenko, Anatoliy Popescu, Dan Univ Politehn Bucuresti Dept Automat & Ind Informat 313 Splaiul Independentei Bucharest 060042 Romania Kazimierz Pulaski Univ Technol & Humanities Radom Dept Informat Ul Malczewskiego 29 PL-26600 Radom Poland West Ukrainian Natl Univ Res Inst Intelligent Comp Syst 3 Peremoga Sq UA-46020 Ternopol Ukraine

the special issue welcomed submissions as extended versions of conference articles published in the proceedings of the “10th IEEE international conference on Intelligent Data Acquisition and Advanced computing Systems: Technology and Applications (IDAACS’2019)” allowing the authors to expand on their theoretical and experimental contributions. Potential topics of the special issue that were initially defined were mapped onto the core areas and special streams of the IDAACS’2019 conference, and included but were not limited to: advanced instrumentation and data acquisition systems, advanced mathematical methods for data acquisition and computing systems, computational intelligence for instrumentation and data acquisition systems, data analysis and modeling, intelligent distributed systems and remote control, intelligent information systems, data mining, and ontology, Internet of things, pattern recognition, digital image, and signal processing, intelligent instrumentation and data acquisition systems in advanced manufacturing for Industry 4, intelligent robotics and sensors, machine learning, application for smart buildings and smart cities. [2] presents a system that combines scalar, ground level measurements, from sensor networks with aerial robotic platforms (UAVs) as data collection and communication relay infrastructure. Data are colected through existing building automation system (BAS) infrastructure with wireless components for sensing, room temperature sensors, and control, motor valves for the heating elements.

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Bangla Handwritten Basic Character recognition Using Deep Convolutional Neural Network 8

Bangla Handwritten Basic Character Recognition Using Deep Co...

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Joint 8th international conference on Informatics, Electronics and Vision (ICIEV) / 3rd international conference on Imaging, Vision and pattern recognition (icIVPR) / international conference on Activity and Behavior computing (ABC)

作者： Saha, Chandrika Faisal, Rahat Hossain Rahman, Md Mostafijur Univ Barishal Dept Comp Sci & Engn Barishal Bangladesh

ISBN: (纸本)9781728107882

Bangla is one of the mostly spoken languages all over the world, nonetheless, efforts on Bangla handwritten character recognition is not adequate. the use of Deep Convolutional Neural Network (DCNN) based classifiers has become a triumph over the state of art machine learning techniques. Using DCNN model to classify Bangla isolated basic characters can provide better output because of its ability to detect many hidden features from an image. In this paper, a new DCNN model, namely, BBCNet-15 is proposed for Bangla handwritten basic character recognition. the proposed model consists of 6 convolution layers, 6 max pooling layers, 2 fully connected layers followed by the softmax output unit. To avoid overfitting dropout regularization technique is used. the implementation of the proposed DCNN model is evaluated on a benchmark dataset, CMATERdb 3.1.2 which contains 50 character classes including 39 consonants and 11 vowels. the experimental evaluation of BBCNet-15 on the dataset provides a recognition accuracy of 96.40% which outperforms some prominent techniques in existence.

关键词： Deep learning Convolutional Neural Network pattern recognition Optical Character recognition Bangla Handwritten Character recognition

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Bi-Directional Selectivity Refinement Network for Salient Object Detection 8

Bi-Directional Selectivity Refinement Network for Salient Ob...

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8th international conference on Digital Home, ICDH 2020

作者： Yuan, Junbin Li, Peiting Xu, Qinzhen Lin, Zhenyang Lin, Xueying Gong, Yongyi South China Normal University School of Computer Science Guangzhou510631 China Guangdong University of Foreign Studies Intelligent Health and Visual Computing Lab Guangzhou510006 China School of Information Science and Technology Guangdong University of Foreign Studies Guangzhou510006 China

ISBN: (纸本)9781728192345

Salient object detection is a fundamental computer vision task. the majority of current algorithms focus on the use of edge information. However, these algorithms are limited to one-way auxiliary training or feature fusion to improve salient features. In this paper, we propose a novel framework for salient object detection, called Bi-Directional Selectivity Refinement Network (BSRN). Our framework aims to simultaneously refine salient features and perfect edge features through a Bi-directional Selectivity Refinement Module (BSRM). In this process, we innovatively combine short connections and attention mechainsm to fully use multi-scale features, selectively enhance features, reduce redundancy and suppress distractors. Besides, in order to improve the adaptability to detect multi-scale objects and achieve better result, we also propose a Multi-scale Feature Extraction Module (MFEM) to capture global contextual information. Extensive experiments conducted on four benchmark datasets demonstrate that our method outperforms 10 similar methods. © 2020 IEEE.

关键词： Feature extraction

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Integrating Activity recognition and Nursing Care Records: the System, Experiment, and the Dataset 8

Integrating Activity Recognition and Nursing Care Records: t...

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作者： Inoue, Sozo Mairittha, Tittaya Mairittha, Nattaya Hossain, Tahera Kyushu Inst Technol 1-1 Sensui Cho Tobata Kitakyushu Fukuoka 8048550 Japan

ISBN: (纸本)9781728107882

In this paper, we introduce a system that integrates activity recognition, which collects various activities of the elderly people of a nursing care facility in Japan. this system incorporates various activity levels, sensor data through smartphones, and records by nurses for a period of 4 months. there are 28 activity labels, recorded by a number of staffs/nurses. the system architecture has mobile application to encode data and a networked system in the 6-floored facility, covering a number of residents. the system is designed in such a manner that even a non-expert nurse or user can manage this system. After introducing the entire system and data collection procedure, we recognized the acitivities by exploiting some statistical features and Extremely Randomized Tree. We noticed that there are discrepancies between start and end recording time-stamps. therefore, we explored a time correction technique. the dataset is an extensive one and it can be explored for various activity recognition in smart-homes or elder care facilities. the dataset includes the sensor data from staffs' smartphones, activity labels, and care details input using the system.

关键词： Smart phones Medical services Activity recognition Cloud computing Servers Machine learning Metadata

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