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A new incremental relational association rules mining approach 22

A new incremental relational association rules mining approa...

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22nd international conference on Knowledge-Based and intelligent Information and engineering Systems (KES)

作者： Miholca, Diana-Lucia Czibula, Gabriela Crivei, Liana Maria Babes Bolyai Univ Dept Comp Sci 1 M Kogalniceanu St Cluj Napoca 400084 Romania

Online data mining techniques are used to uncover relevant patterns in complex data which are dynamic by nature and thus continuously extended with real-time arriving data streams. Relational association rules (RARs), a data analysis and mining concept, extend the classical association rules so as to capture different relations between the attributes characterizing the data. This paper introduces a new Incremental Relational Association Rule Mining (IRARM) approach with the aim of progressively adapting the interesting relational association rules identified in a data set, when it is enlarged with new instances. We have experimentally evaluated IRARM on publicly available data sets. The reduction in mining time when using IRARM against mining from scratch emphasizes its efficiency in adapting the rules to real-time data extension. (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： data mining Unsupervised learning Relational association rules

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data-driven Fault Diagnosis of Induction Motors Using a Stacked Autoencoder Network

Data-driven Fault Diagnosis of Induction Motors Using a Stac...

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international conference on Electrical Machines and Systems (ICEMS)

作者： Audun Johannessen Skylvik Kjell G. Robbersmyr Huynh Van Khang Department of Engineering Sciences University of Agder Grimstad Norway

ISBN: (纸本)9781728133997

Current signatures from an induction motor are normally used to detect anomalies in the condition of the motor based on signal processing techniques. However, false alarms might occur if using signal processing analysis alone since missing frequencies associated with faults in spectral analyses does not guarantee that a motor is fully healthy. To enhance fault diagnosis performance, this paper proposes a machinelearning based method using in-built motor currents to detect common faults in induction motors, namely inter-turn stator winding-, bearing- and broken rotor bar faults. This approach utilizes single-phase current data, being pre-processed using Welch's method for spectral density estimation. Further, several deep learning features are extracted using stacked autoencoder networks. The proposed scheme can predict the faults at high accuracy while reducing expertise demand. The proposed method is validated on an in-house laboratory setup under variable speed and load conditions, showing a classification accuracy over 95%. Furthermore, multiple support vector machine and k-nearest neighbor classifiers are tested with the same data for a comparative study. Finally, the performance of di erent fault classifiers are evaluated based on accuracy, computational burden and classification consistency.

关键词： Induction motors Feature extraction Training Machine learning Classification algorithms Support vector machines Training data

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intelligent predictive maintenance control using augmented reality

Intelligent predictive maintenance control using augmented r...

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international conference on Process Control (PC)

作者： Michal Kostoláni Justín Murín Štefan Kozák Faculty of Electrical Engineering and Information Technology Slovak University of Technology in Bratislava Bratislava Slovak Republic Faculty of Informatics Pan-European University Bratislava Slovak Republic

Modern manufacturing industry is currently facing significant challenges with regard to the concept of Industry 4.0. The promise of increased productivity and flexibility in manufacturing processes can not be achieved without implementation of systems and advance methods based on smart technologies. Implementation of Industrial Internet of Things (IIoT), Condition Monitoring, Big data, Cloud computing, virtual and augmented reality in maintenance processes will significantly increase the effectivy and quality of manufacturing processes as well as eliminate the human factor. Under this perspective, cyber- physical systems can be accessible from remote location; process paramters can be visualized at real time and prediction of unexpected production stop due to machine breakdown will be significantly reduced. The paper deals with the development of effective approach to real-time process control using parameters visualization of manufacturing process with the use of augmented reality smart glasses. Collected data from condition monitoring sensors from electric monorail system are evaluated in real time and visualized in the field of maintainer view. Critical values from field of sensors are highlighted and enable to predict manufacturing breakdowns. On real example from automotive industry will be demonstrated the signification and effectivity for maintenance of electric monorail system and potential for application in different types of modern industrial processes with the focus on rule-based intelligent predictive maintenance control.

关键词： Augmented reality Industries Real-time systems Predictive maintenance data visualization Sensors

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Experiences and perspectives of Technology-enhanced learning and teaching in higher education - Serbian case 22

Experiences and perspectives of Technology-enhanced learning...

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22nd international conference on Knowledge-Based and intelligent Information and engineering Systems (KES)

作者： Ivanovic, Mirjana Milicevic, Aleksandra Klasnja Aleksic, Veljko Bratic, Brankica Mandic, Milinko Univ Novi Sad Fac Sci Trg Dositeja Obradovica 3 Novi Sad 21000 Serbia Univ Kragujevac Fac Tech Sci Svetog Save 65 Cacak 32000 Serbia Univ Novi Sad Fac Educ Podgoricka 4 Sombor 25000 Serbia

This paper presents different approaches, experiences and perspectives of using technologies in higher education institutions. Particular case studies of application of social media (especially wikis), game-based learning and various technology -enhanced learning tools in different courses at several Serbian institutions are presented. In-house developed intelligent tutoring system Protus and possibilities to enhance it by software agents and eye-tracking are also shown in detail. Our experiences of using different technology-enhanced learning tools and mechanisms showed that educational processes must be modernized and enhanced by technological progress. (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： technology enhanced learning wiki educational games intelligent tutoring eye-tracking

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2018 22nd international Computer Science and engineering conference, ICSEC 2018

2018 22nd International Computer Science and Engineering Con...

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22nd international Computer Science and engineering conference, ICSEC 2018

ISBN: (纸本)9781538681640

The proceedings contain 74 papers. The topics discussed include: IoT platform for precision positioning service for highly autonomous vehicles;energy-aware and performance-aware of workflow application with hybrid scheduling algorithm on cloud computing;an event driven approach to create UML models;hybrid approach towards the assessment of a drill condition using deep learning and the support vector machine;the brick pavement production using waste plastic as ingredients together;hybrid BA/ATS for economic dispatch problem;quadrature oscillator/universal filter using CCCII with adjustable gain;aerial-to-surface communication and data transferring system for environmental survey;potential use of smart kitchen management application (SKM);and rapid building of software-based SDN testbed using SDN owl.

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Vehicle avoidance reaction by two step motion flow cluster 22

Vehicle avoidance reaction by two step motion flow cluster

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22nd international Computer Science and engineering conference, ICSEC 2018

作者： Rassameepaiboon, Woranon Assawinchaichote, Wudhichai Electronics and Telecommunication Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand

ISBN: (纸本)9781538681640

Presently we have seen the road accidents in every day. Automobile manufacturers then have created a system that aims to reduce and prevent such accidents. The most popular ones include intelligent collision warning system and intelligent braking system. However, such systems are not able to cover every case and could even cause more accidents. Interactive accident avoidance system with 2 steps movement detection is therefore a recommended method to reduce and prevent accidents with more efficiency. This study focuses on the feature of this system, which is forward movement detection and automatic obstacles avoidance. With this, external environment will be distinguished from object movement before calculating the duration that the vehicle would possibly hit the object. This duration will then be grouped, and the clustering data will be used for vehicle control i.e. to turn left, right, or stop. Finally, to show the effectiveness of our designed approach, we have used the computer simulation to show the results of our proposed method. © 2018 IEEE.

关键词： Optical flows

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Raising driver attentiveness with unconscious learning effect 22

Raising driver attentiveness with unconscious learning effec...

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22nd international conference on Knowledge-Based and intelligent Information and engineering Systems (KES)

作者： Ito, Toshio Sudo, Shuji Shibaura Inst Technol Minuma Ku 307 Fukasaku Saitama 3378570 Japan

When changing lanes or making a right or left turn, drivers need to conduct a series of actions, such as checking the surroundings, turning on the turn signal, and steering. In this study, we alert the drivers who did not check the environment completely before making lane changes or turns, with a gentle alarm sound. Experiments with a driving simulator have shown that drivers can be unconsciously trained to carry out the needed series of actions. Therefore, in this paper, we report the effectiveness of unconscious learning with the gentle alarm sound. (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： human machine interface alarm driving simulator safety confirmation alarm driving simulator safety confirmation

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Artificial intelligent research assistant for aerospace design synthesis—solution logic 22

Artificial intelligent research assistant for aerospace desi...

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22nd AIAA international Space Planes and Hypersonics Systems and Technologies conference, 2018

作者： McCall, Thomas Seyed Alavi, Kiarash Rana, Loveneesh Chudoba, Bernd AVD Laboratory UT Arlington Dept. of Mechanical and Aerospace Engineering ArlingtonTX76019 United States

ISBN: (数字)9781624105777

ISBN: (纸本)9781624105777

This paper has two objectives. First, the identification and communication of a research endeavor driving towards an aerospace artificial intelligence design and research assistant. The second objective is to present the evaluation of a proof of concept to employ a neural network to aerospace vehicle sizing. This test is part of the development effort to arrive at an intelligent assistant. The goal is to test the viability of a machine learning augmented synthesis tool with the intent to decrease the time to design convergence. The topic is approached from three avenues. First, a consideration of intelligence itself as best defined by humanity is considered, with the objective to identify key components to intelligence. The consideration of both natural and artificial intelligence provides direction into the definition of requirements for the system. This is the second avenue of approach. The second avenue leading to the overall objective, is the definition of a proposed artificial intelligence design environment. A key component to this system is identified as a readily modular synthesis approach that is both quick and computationally attractive. This requirement leads to the development and subsequent comparison of a neural network synthesis architecture compared to a standard synthesis software approach—the objective of this document. In order to test and demonstrate overall functionality, the case study chosen to be implemented is a hypervelocity lifting body reentry vehicle. The learning sets include five primary design parameters. The final outcome is the evaluation of a machine learning algorithmic approach to synthesis from a learned design data set versus the execution results of the subroutine developed synthesis code. © 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Machine learning

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A Computer Vision System for Guava Disease Detection and Recommend Curative Solution Using Deep learning Approach

A Computer Vision System for Guava Disease Detection and Rec...

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international conference on Computer and Information Technology (ICCIT)

作者： A S M Farhan Al Haque Rubaiya Hafiz Md. Azizul Hakim G. M. Rasiqul Islam Department of Computer Science and Engineering Daffodil International University Dhaka Bangladesh

ISBN: (数字)9781728158426

ISBN: (纸本)9781728158433

Guava disease has become a tremendous problem for the production of guava which has undeviating effect on the socioeconomic development of the farmers. This phenomenon leads to initiate an automated computer vision based guava disease detection system that may detect malicious guava and guide to early cure approaches, resulting reduction of relative economic loss. Considering the fact, in this paper we have proposed a convolutional neural network (CNN) based guava disease detection and curative suggestion providing system. We have collected the images of guava affected by anthracnose, fruit rot and fruit canker along with disease free guava from different districts of Bangladesh. In this paper, we have applied three CNN models and experimentally found that the third model has outperformed the other two with an accuracy of 95.61%. For meticulous experimentation, performance metrics like precision, recall and F1 score is evaluated and found to yield great results.

关键词： Diseases Training Deep learning Image recognition Mathematical model data models Production

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National university rankings based on open data: A case study from Serbia 22

National university rankings based on open data: A case stud...

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22nd international conference on Knowledge-Based and intelligent Information and engineering Systems (KES)

作者： Ivancevic, Vladimir Lukovic, Ivan Univ Novi Sad Fac Tech Sci Trg Dositeja Obradovica 6 Novi Sad 21000 Serbia

We investigate the potential of using open data about higher education and research activities as a basis for constructing university rankings at the national level. In our case study, open data from the Ministry of Education, Science, and Technological Development of Serbia served as a foundation for deriving indicators of university performance and calculating ranks of universities from Serbia. In addition to reviewing notable international rankings of universities, we extracted the international standings of universities from Serbia and discussed the national university rankings that were generated during our investigation. (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： university ranking performance indicator open data higher education research Serbia

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