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6th international conference on Optimization and Applications, ICOA 2020

作者： Adil, Nouhaila Lakhbab, Halima MACS Laboratory Hassan II University Dept. of Mathematics and Computer Sciences Casablanca Morocco LIMSAD Laboratory Hassan II University Dept. of Mathematics and Computer Sciences Casablanca Morocco

ISBN: (纸本)9781728166544

the work presented focuses on the resolution of the multi compartment vehicle routing problem (MCVRP), a variant of the general vehicle routing problem (VRP). An adapted discrete Bat Algorithm (DBA) is applied and numerical results are compared to results obtained by a Greedy Randomized Adaptive Search Procedure (GRASP). the algorithm proved to be efficient and further studies can be done to enhance its performance. © 2020 IEEE.

关键词： Vehicles

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Gearbox Noise Reduction and Diagnostic Analysis by EEMD Algorithm and DWT Fault Signal

Gearbox Noise Reduction and Diagnostic Analysis by EEMD Algo...

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IEEE international conference on Power, Intelligent Computing and Systems (ICPICS)

作者： Chang Sun Yingming Liu Changchun Automobile Vocational and Technical University Changchun China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374322

In order to improve the fault diagnosis ability of the crusher gearbox, a new noise reduction technology through EEMD-DWT is designed by comprehensively using the noise reduction technology of Ensemble Empirical Mode Decomposition (EEMD) algorithm and discrete Wavelet Transform (DWT), ensuring that useful features can be retained on the premise of removing noise. the smooth signal is obtained through the noise reduction processing of the EEMD-DWT method, and the characteristics of the signal waveform are also ideally restored, achieving excellent noise reduction performance. the research results show that after noise reduction by EEMD-DWT, a waveform with obvious impact characteristics is formed, which has a significant inhibitory effect on the noise components with amplitudes near zero, and realizes the retention of the original vibration characteristics under the condition of removing noise. the EEMD-DWT noise reduction method of this design has better noise reduction performance compared with other single noise reduction methods, and can meet the actual noise reduction analysis requirements in the vibration process of the crusher gearbox. this research can effectively make up for the deficiency of EEMD in the aspect of vibration signal noise reduction, improve the fault identification efficiency of the gearbox, and can also be applied to other transmission mechanisms, with high promotion value.

关键词： Vibrations Fault diagnosis Empirical mode decomposition Design methodology Noise reduction Noise Wavelet analysis discrete wavelet transforms

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Recommendation Engines: Traditional vs Deep Learning Approaches 6

Recommendation Engines: Traditional vs Deep Learning Approac...

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6th international conference on Computing, Communication and Security, ICCCS 2021

作者： Dhawad, Aniket Sarkar, Suranjana Agarwal, Amit Darlapudi, Rama Kishore Wells Fargo International Solutions Private Limited Enterprise Analytics and Data Science Artificial Intelligence-Center of Excellence Bangalore India

ISBN: (纸本)9781665440394

With digitlzation growing by leap and bounds, websites are now overloaded with products and information density, making it challenging for customers to choose between a variety of products. the Recommendation engine enables companies to deliver their customers more personalized and customized products or information efficiently. As a result, the recommendation engine eventually helps in boosting different business performance metrics such as revenues, Click- through Rates (CTRs), conversions, etc., for these companies significantly. And in the long run, it also optimizes user experience, thus translating to higher customer satisfaction and retention. In this paper, we will highlight some of the contemporary algorithms used in building high-performance recommendation engines, illustrate use cases from Tech Giants that can be applied in the context of the banking and financial services domain and identify major challenges that are open for further research work. Also, in this paper, we will be using recommendation engine and recommender system alternatively as both are synonymous. © 2021 IEEE.

关键词： Recommender systems

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Buckling analysis of square Functionally Graded Material (FGM) plate using discrete Kirchhoff Mindlin Triangular (DKMT) element 6

Buckling analysis of square Functionally Graded Material (FG...

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6th international conference on mathematics: Pure, applied and Computation, ICOMPAC 2020

作者： Harahap, M.P.S. Maknun, I.J. Katili, I. Civil Engineering Department Universitas Indonesia Depok16424 Indonesia

this paper presents the convergence behavior of discrete Kirchhoff Mindlin Triangular (DKMT) element in buckling analysis under uniaxial compression of square plate problems. the DKMT element has a good result for a thin plate and a thick plate. For the Functionally Graded Material (FGM) problem, the DKMT element is reformulated. FGM is a graded composite material that has high-temperature and structural flexibility resistance. the numerical results of mechanical buckling of square FGM plate under uniaxial compression using the DKMT element are reported. the critical buckling of the square FGM plate is compared to the reference existing solutions. the effects of parametric variation, such as the type of meshing, boundary conditions, power-law index, and ratio L/h are presented. the results show that the DKMT element gives good results on the buckling analysis of square FGM plate problems. © Published under licence by IOP Publishing Ltd.

关键词： Functionally graded materials

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Board Knowledge and Bank Risk-Taking. An international Analysis 1

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6th international conference on Dynamics Games and Science, DGS-VI-2018, 19th Latin American conference on Economic theory, JOLATE 2018 and 21st international Consortium on applied Bioeconomy Research, ICABR 2017

作者： Gómez-Escalonilla, E. Parte, L. Madrid Spain

ISBN: (数字)9783030781637

ISBN: (纸本)9783030781620

Corporate governance mechanism and board knowledge are crucial variables to mitigate bank risk taking. this study focuses on two variables related to board members profile: the knowledge of board members by the accumulated experience in the same company (Board Tenure), and the expertise of board members derived from previous competences obtained in the industry or by specific training in the financial field (Board Skills). Using a sample of 156 banks from 37 countries for the period 2009–2017, the association between both corporate governance variables and bank risk is tested through the Generalized Method of Moments model. the results show that specific financial skills decrease the level of bank risk. In contrast, there are no conclusive results on board tenure and the risk measures analyzed. © 2021, Springer Nature Switzerland AG.

关键词： Risk assessment

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A discrete mutualism model: Analysis and exploration of a financial application

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applied NUMERICAL mathematics 2020年 149卷 141-152页

作者： Roberts, J. A. Kavallaris, N. I. Rowntree, A. P. Univ Chester Dept Math Thornton Sci PkPool Lane Chester CH2 4NU Cheshire England

We perform a stability analysis on a discrete analogue of a known, continuous model of mutualism. We illustrate how the introduction of delays affects the asymptotic stability of the system's positive nontrivial equilibrium point. In the second part of the paper we explore the insights that the model can provide when it is used in relation to interacting financial markets. We also note the limitations of such an approach. (C) 2019 IMACS. Published by Elsevier B.V. All rights reserved.

关键词： discrete system Stability Delay Finance Stock markets Modelling Ecology Mutualism

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An Efficient Method for Addressing COVID-19 Proximity Related Issues in Autonomous Shuttles Public Transportation 1

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18th international conference on Artificial Intelligence Applications and Innovations (AIAI)

作者： Tsiktsiris, Dimitris Lalas, Antonios Dasygenis, Minas Votis, Konstantinos Tzovaras, Dimitrios Ctr Res & Technol Hellas Inst Informat Technol 6th Km Xarilaou Thermi Thessaloniki 57001 Greece Univ Western Macedonia Dept Elect & Comp Engn Kozani 50100 Greece

ISBN: (数字)9783031083334

ISBN: (纸本)9783031083334;9783031083327

the COVID-19 pandemic has created significant restrictions to passenger mobility through public transportation. Several proximity rules have been applied to ensure sufficient distance between passengers and mitigate contamination. In conventional transportation, abiding by the rules can be ensured by the driver of the vehicle. However, this is not obvious in Autonomous Vehicles (AVs) public transportation systems, since there is no driver to monitor these special circumstances. Since, AVs constitute an emerging mobility infrastructure, it is obvious that creating a system that can provide a sense of safety to the passenger, when the driver is absent, is a challenging task. Several studies employ computer vision and deep learning techniques to increase safety in unsupervised environments. In this work, an image-based approach, supported by novel AI algorithms, is proposed as a service to increase the COVID-19 safety rules adherence of the passengers inside an autonomous shuttle. the proposed real-time service, can detect deviations from proximity rules and notify the authorized personnel, while it is possible to be further extended in other application domains, where automated proximity assessment is critical.

关键词： Autonomous vehicles Public transportation Neural networks Image processing

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Privacy Protection Scheme for Personal Health Record System Using Blockchain Based on Homomorphic Encryption

Privacy Protection Scheme for Personal Health Record System ...

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Educational Innovation (ECEI), IEEE Eurasian conference on

作者： Cho-Pu Lin Zhen-Yu Wu Chia-Hui Liu Department of International Business Lunghwa University of Science and Technology Taoyuan Taiwan Department of Information Management National Penghu University of Science and Technology Penghu Taiwan Department of Applied Mathematics Chinese Culture University Taipei Taiwan

With the advancement and popularization of science and technology, much research explores the provision of health care services or health management with the assistance of information technology in addition to traditional clinical diagnosis. Personal Health Records (PHR) are available for personalized health record information in the autonomous management system. the personal health record system is to improve disease management or strengthen personal health management. However, users are concerned about the safety and confidentiality of PHR in healthcare systems. In 2008, the blockchain architecture was proposed by Satoshi as a peer-to-peer network architecture that contains a Distributed Ledger Technology (DLT). In this study, we proposed a blockchain-based PHR system using the homomorphic encryption to improve the privacy and security of the users. It allows a third party to perform operations on the ciphertext which can be retrieved correctly later, while the privacy and security of the nodes on the chain are ensured and provided for multiple users to protect the security of their information.

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Stereo matching based on visual sensitive information 6

Stereo matching based on visual sensitive information

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6th international conference on Image, Vision and Computing, ICIVC 2021

作者： Wang, Hewei Pathan, Muhammad Salman Dev, Soumyabrata Beijing University of Technology Beijing China School of Computer Science University College Dublin Ireland ADAPT SFI Research Centre Dublin Ireland Beijing-Dublin International College Beijing China

ISBN: (纸本)9781665443685

the area of computer vision is one of the most discussed topics amongst many scholars, and stereo matching is its most important sub fields. After the parallax map is transformed into a depth map, it can be applied to many intelligent fields. In this paper, a stereo matching algorithm based on visual sensitive information is proposed by using standard images from Middlebury dataset. Aiming at the limitation of traditional stereo matching algorithms regarding the cost window, a cost aggregation algorithm based on the dynamic window is proposed, and the disparity image is optimized by using left and right consistency detection to further reduce the error matching rate. the experimental results show that the proposed algorithm can effectively enhance the stereo matching effect of the image providing significant improvement in accuracy as compared with the classical census algorithm. the proposed model code, dataset, and experimental results are available at https://***/WangHewei16/Stereo-Matching. © 2021 IEEE.

关键词： Computer vision

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Research on Traffic Information Extraction Approach Based on Image Deep Learning 6

Research on Traffic Information Extraction Approach Based on...

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6th international conference on Transportation Information and Safety, ICTIS 2021

作者： Lu, Manke He, Yi Cao, Bo Wang, Yihong Xu, Feng Intelligent Transport Systems Research Center Wuhan University of Technology Wuhan China China Merchants International Technology Company Limited Shenzhen China China Transport Telecommunication & Information Center Beijing China

ISBN: (纸本)9781665497138

With the rapid development of deep learning methods in the field of computer vision, the effective methods can be applied to the classification and positioning of traffic targets based on real traffic data. this paper studies the application of convolutional neural network in the real traffic information extraction field. the YOLOv3 target detection algorithm, the Faster RCNN target detection algorithm and the SSD target detection algorithm are used to detect vehicles in the images collected in same road condition, and generate the result graph of the target detection. the experimental results show that the YOLOv3 target detection algorithm, Faster RCNN target detection algorithm and SSD target detection algorithm can identify all traffic targets in the traffic road images. It reveals the three algorithms meet the detection needs, and help to achieve non-contact traffic flow collection and feature recognition. Meanwhile these algorithms can provide technical means for traffic supervision and safety improvement. © 2021 IEEE.

关键词： Deep learning

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