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FML-based prediction agent and its application to game of Go

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FML-based prediction agent and its application to game of Go

Joint World Congress of International Fuzzy systems Association and International Conference on Soft Computing and Intelligent systems (IFSA-SCIS)

作者： Chang-Shing Lee Chia-Hsiu Kao Mei-Hui Wang Sheng-Chi Yang Yusuke Nojima Ryosuke Saga Nan Shuo Naoyuki Kubota Dept. of Computer Science and Information Engineering National University of Tainan Tainan Taiwan Dept. of Electrical Engineering and Information Science Osaka Prefecture University Osaka Japan Dept. of System Design Tokyo Metropolitan University Tokyo Japan

ISBN: (纸本)9781509049189

In this paper, we present a robotic prediction agent including a darkforest Go engine, a fuzzy markup language (FML) assessment engine, an FML-based decision support engine, and a robot engine for game of Go application. The knowledge base and rule base of FML assessment engine are constructed by referring the information from the darkforest Go engine located in NUTN and OPU, for example, the number of MCTS simulations and winning rate prediction. The proposed robotic prediction agent first retrieves the database of Go competition website, and then the FML assessment engine infers the winning possibility based on the information generated by darkforest Go engine. The FML-based decision support engine computes the winning possibility based on the partial game situation inferred by FML assessment engine. Finally, the robot engine combines with the human-friendly robot partner PALRO, produced by Fujisoft incorporated, to report the game situation to human Go players. Experimental results show that the FML-based prediction agent can work effectively.

关键词： Games Engines Robots Cloud computing Predictive models Databases Markup languages

Feature Enhancement of Noisy Image by Dyadic Wavelet Analysis

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Feature Enhancement of Noisy Image by Dyadic Wavelet Analysi...

2017 2nd International Conference on computer, Mechatronics and Electronic engineering(CMEE 2017)

作者： Zheng-hong HUANG Li XIA Chongqing Engineering Laboratory for Detection Control and Integrated System School of Computer Science and Technology Chongqing Technology and Business University School of mathematics and statistics Chongqing Technology and Business University

The image de-noising method is proposed by multiresolution representations of the dyadic wavelet transformation. Firstly, the original image are decomposed using dyadic wavelet transformation, then the image can be de-noised by way of adopting different thresholds according to the different scales of wavelet coefficients, and finally nonlinear enhancing function are applied for wavelet coefficients with the enhancement method in the corresponding scales. Experiments of the medical images show that compared to the image enhancement method, our approach improves the information entropy and contrast improvement index of the images, enhances edge texture of images.

关键词： Dyadic wavelet transform Multiresolution representations Threshold function Image enhancement

Design of hybrid damping controller based on multi-target gravitational search optimization algorithm in a multi-machine power system with high penetration of PV park

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Journal of Central South University 2016年第5期23卷 1163-1175页

作者： Y.Hashemi H.Shayeghi M.Moradzadeh A.Safari Technical Engineering Department University of Mohaghegh Ardabili Centre of Excellence for Power System Automation and Operation Department of Electrical EngineeringIran University of Science and Technology Centre for Engineering Innovation Department of Electrical and Computer EngineeringUniversity of Windsor Electrical Energy Laboratory Department of Electrical EnergySystems and AutomationGhent University Department of Electrical Engineering Azarbaijan Shahid Madani University

A mathematical approach was proposed to investigate the impact of high penetration of large-scale photovoltaic park(LPP) on small-signal stability of a power network and design of hybrid controller for these units.A systematic procedure was performed to obtain the complete model of a multi-machine power network including *** damping of oscillations focusing on inter-area oscillatory modes,a hybrid controller for LPP was *** performance of the suggested controller was tested using a 16-machine 5-area *** results indicate that the proposed hybrid controller for LPP provides sufficient damping to the low-frequency modes of power system for a wide range of operating *** method presented in this work effectively indentifies the impact of increased PV penetration and its controller on dynamic performance of multi-machine power network containing *** results demonstrate that the model presented can be used in designing of essential controllers for LPP.

关键词： hybrid controller multi-objective optimization large-scale photovoltaic park small-signal scrutiny

Identifying hazardousness of sewer-pipeline gas-mixture using classification methods a comparative study

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arXiv 2017年

作者： Ojha, Varun Kumar Dutta, Parmartha Chaudhuri, Atal IT4Innovations VSB Technical University of Ostrava Ostrava Czech Republic Dept. of Computer Science and Engineering Jadavpur University Kolkata India Dept. of Computer and System Sciences Visva-Bharati University India

In this work, we formulated a real-world problem related to sewerpipeline gas detection using the classification-based approaches. The primary goal of this work was to identify the hazardousness of sewer-pipeline to offer safe and non-hazardous access to sewer-pipeline workers so that the human fatalities, which occurs due to the toxic exposure of sewer gas components, can be avoided. The dataset acquired through laboratory tests, experiments, and various literature-sources were organized to design a predictive model that was able to identify/classify hazardous and non-hazardous situation of sewer-pipeline. To design such prediction model, several classification algorithms were used and their performances were evaluated and compared, both empirically and statistically, over the collected dataset. In addition, the performances of several ensemble methods were analyzed to understand the extent of improvement offered by these methods. The result of this comprehensive study showed that the instance-based-learning algorithm performed better than many other algorithms such as multi-layer perceptron, radial basis function network, support vector machine, reduced pruning tree, etc. Similarly, it was observed that multi-scheme ensemble approach enhanced the performance of base predictors. Copyright © 2017, The Authors. All rights reserved.

关键词： Classification (of information)

Parallelism and Optimization of Numerical Ocean Forecasting Model

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Journal of Ocean University of China 2016年第5期15卷 783-788页

作者： XU Jianliang PANG Renbo TENG Junhua LIANG Hongtao YANG Dandan College of Information Science and Engineering Ocean University of China Department of Computer and Network National Marine Environmental Forecasting Center Division of Information System National Marine Environmental Forecasting Center

According to the characteristics of Chinese marginal seas, the Marginal Sea Model of China(MSMC) has been developed independently in China. Because the model requires long simulation time, as a routine forecasting model, the parallelism of MSMC becomes necessary to be introduced to improve the performance of it. However, some methods used in MSMC, such as Successive Over Relaxation(SOR) algorithm, are not suitable for parallelism. In this paper, methods are developedto solve the parallel problem of the SOR algorithm following the steps as below. First, based on a 3D computing grid system, an automatic data partition method is implemented to dynamically divide the computing grid according to computing resources. Next, based on the characteristics of the numerical forecasting model, a parallel method is designed to solve the parallel problem of the SOR algorithm. Lastly, a communication optimization method is provided to avoid the cost of communication. In the communication optimization method, the non-blocking communication of Message Passing Interface(MPI) is used to implement the parallelism of MSMC with complex physical equations, and the process of communication is overlapped with the computations for improving the performance of parallel MSMC. The experiments show that the parallel MSMC runs 97.2 times faster than the serial MSMC, and root mean square error between the parallel MSMC and the serial MSMC is less than 0.01 for a 30-day simulation(172800 time steps), which meets the requirements of timeliness and accuracy for numerical ocean forecasting products.

关键词： parallelism partition steps faster serial dynamically forecasting marginal overlapped neighbor

Some solutions of fractional order partial differential equations using adomian decomposition method

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arXiv 2017年

作者： Javed, Iqra Ahmad, Ashfaq Hussain, Muzammil Iqbal, S. Department of Informatics and System University of Management and Technology Lahore Pakistan Department of Electronics University of Lahore Lahore Pakistan School of Engineering Science University of Science and Technology of China China Department of Computer Science University of Management and Technology Lahore Pakistan

The Adomian decomposition method is a semi-analytical method for solving ordinary and partial nonlinear differential equations. The aim of this paper is to apply Adomian decomposition method to obtain approximate solutions of nonlinear fractional order partial differential equations with fractional derivatives. The fractional derivatives are taken in the sense of Caputo. The solutions of fractional PDEs are calculated in the form of convergent series. Approximate solutions obtained through the decomposition method have been numerically evaluated, and presented in the form of graphs and tables, and then these solutions are compared with the exact solutions and the results rendering the explicitness, effectiveness and good accuracy of the applied method. Finally, it is observed that the applied method \(i.e. Adomian decomposition method\) is prevailing and convergent method for the solutions of nonlinear fractional-order partial deferential problems. Copyright © 2017, The Authors. All rights reserved.

关键词： Partial differential equations

Ultrasensitive tunability of the direct bandgap of two-dimensional InSe flakes via strain engineering

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arXiv 2018年

作者： Li, Yang Wang, Tianmeng Wu, Meng Cao, Ting Chen, Yanwen Sankar, Raman Ulaganathan, Rajesh K. Chou, Fangcheng Wetzel, Christian Xu, Cheng-Yan Louie, Steven G. Shi, Sufei Department of Chemical and Biological Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Department of Physics University of California at Berkeley BerkeleyCA94720 United States Materials Sciences Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Institute of Physics Academia Sinica Nankang Taipei11529 Taiwan Center for Condensed Matter Science National Taiwan University Taipei10617 Taiwan Department of Physics and Astronomy Rensselaer Polytechnic Institute TroyNY12180 United States School of Materials Science and Engineering Harbin Institute of Technology Harbin150001 China Department of Electrical Computer and System Engineering Rensselaer Polytechnic Institute TroyNY12180 United States

InSe, a member of the layered materials family, is a superior electronic and optical material which retains a direct bandgap feature from the bulk to atomically thin few-layers and high electronic mobility down to a single layer limit. We, for the first time, exploit strain to drastically modify the bandgap of two-dimensional (2D) InSe nanoflakes. We demonstrated that we could decrease the bandgap of a few-layer InSe flake by 160 meV through applying an in-plane uniaxial tensile strain to 1.06% and increase the bandgap by 79 meV through applying an in-plane uniaxial compressive strain to 0.62%, as evidenced by photoluminescence (PL) spectroscopy. The large reversible bandgap change of ~ 239 meV arises from a large bandgap change rate (bandgap strain coefficient) of few-layer InSe in response to strain, ~ 154 meV/% for uniaxial tensile strain and ~ 140 meV/% for uniaxial compressive strain, representing the most pronounced uniaxial strain-induced bandgap strain coefficient experimentally reported in two-dimensional *** developed a theoretical understanding of the strain-induced bandgap change through first-principles DFT and GW calculations. We also confirmed the bandgap change by photoconductivity measurements using excitation light with different photon energies. The highly tunable bandgap of InSe in the infrared regime should enable a wide range of applications, including electro-mechanical, piezoelectric and optoelectronic devices. Copyright © 2018, The Authors. All rights reserved.

关键词： Energy gap

Commodity dynamic pricing and inventory joint decision-making model based on specific power demand function

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Revista Tecnica de la Facultad de Ingenieria Universidad del Zulia 2016年第4期39卷 74-81页

作者： Sun, Dejie Liu, Wenyuan Zhang, Jie School of Information Science and Engineering Yanshan University Qinhuangdao Hebei066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao Hebei066004 China

Dynamic pricing and inventory play a respective role. The purpose of inventory is to try best to maintain an even production speed and efficiently ease supply-and-demand contradiction during the production process and among enterprises in the supply chain. However, dynamic pricing aims at maximizing revenues by setting commodities or services at different price levels according to diversified demands of consumers and different commodity or service price evaluation by consumers in different periods. Therefore, it is important for enterprises to optimize their dynamic pricing strategies and commodity inventory so as to maximize value of researches. However, demands for tangible commodities are uncertain. Generally speaking, the commodity demand volume should first be confirmed before any specific analysis. Therefore, this paper focuses on introducing the commodity demand function and relevant factors influencing the commodity demand volume. The utility function describing consumers' demands for a single commodity is analyzed. The specific power demand function model based on utility maximization is built through the utility function. At last, we conduct an in-depth analysis and simulation of the model.

关键词： Economics

Surgical data science-from concepts toward clinical translation

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arXiv 2020年

作者： Maier-Hein, Lena Eisenmann, Matthias Sarikaya, Duygu März, Keno Collins, Toby Malpani, Anand Fallert, Johannes Feussner, Hubertus Giannarou, Stamatia Mascagni, Pietro Nakawala, Hirenkumar Park, Adrian Pugh, Carla Stoyanov, Danail Vedula, Swaroop S. Cleary, Kevin Fichtinger, Gabor Forestier, Germain Gibaud, Bernard Grantcharov, Teodor Hashizume, Makoto Heckmann-Nötzel, Doreen Kenngott, Hannes G. Kikinis, Ron Mündermann, Lars Navab, Nassir Onogur, Sinan Sznitman, Raphael Taylor, Russell H. Tizabi, Minu D. Wagner, Martin Hager, Gregory D. Neumuth, Thomas Padoy, Nicolas Collins, Justin Gockel, Ines Goedeke, Jan Hashimoto, Daniel A. Joyeux, Luc Lam, Kyle Leff, Daniel R. Madani, Amin Marcus, Hani J. Meireles, Ozanan Seitel, Alexander Teber, Dogu Ückert, Frank Müller-Stich, Beat P. Jannin, Pierre Speidel, Stefanie Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Medical Faculty Heidelberg University Heidelberg Germany Department of Computer Engineering Faculty of Engineering Gazi University Ankara Turkey LTSI Inserm UMR 1099 University of Rennes 1 Rennes France IRCAD Strasbourg France The Malone Center for Engineering in Healthcare The Johns Hopkins University BaltimoreMD United States KARL STORZ SE and Co. KG Tuttlingen Germany Department of Surgery Klinikum Rechts der Isar Technical University of Munich Munich Germany The Hamlyn Centre for Robotic Surgery Imperial College London London United Kingdom ICube University of Strasbourg CNRS France IHU Strasbourg Strasbourg France Altair Robotics Lab University of Verona Verona Italy Department of Surgery Anne Arundel Health System AnnapolisMD United States Johns Hopkins University School of Medicine BaltimoreMD United States Department of Surgery Stanford University School of Medicine StanfordCA United States Wellcome/EPSRC Centre for Interventional and Surgical Sciences University College London London United Kingdom Department for General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg Germany The Sheikh Zayed Institute for Pediatric Surgical Innovation Children's National Hospital WashingtonDC United States The Perk Lab Queen's University KingstonON Canada University of Haute-Alsace Mulhouse France Faculty of Information Technology Monash University ClaytonVIC Australia University of Toronto TorontoON Canada The Li Ka Shing Knowledge Institute of St. Michael's Hospital TorontoON Canada Kyushu University Fukuoka Japan Kitakyushu Koga Hospital Fukuoka Japan Department of Radiology Brigham and Women's Hospital Harvard Medical School BostonMA United States Computer Aided Medical Procedures Technical University of Munich Munich Germany Department of Computer Science The Johns Hopkins University Baltim

Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery. Surgical Data science (SDS) is a new research field that aims to improve the quality of interventional healthcare through the capture, organization, analysis and modeling of data. While an increasing number of data-driven approaches and clinical applications have been studied in the fields of radiological and clinical data science, translational success stories are still lacking in surgery. In this publication, we shed light on the underlying reasons and provide a roadmap for future advances in the field. Based on an international workshop involving leading researchers in the field of SDS, we review current practice, key achievements and initiatives as well as available standards and tools for a number of topics relevant to the field, namely (1) infrastructure for data acquisition, storage and access in the presence of regulatory constraints, (2) data annotation and sharing and (3) data analytics. We further complement this technical perspective with (4) a review of currently available SDS products and the translational progress from academia and (5) a roadmap for faster clinical translation and exploitation of the full potential of SDS, based on an international multi-round Delphi process. © 2020, CC BY.

关键词： Deep learning