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Towards additive manufacturing oriented geometric modeling using implicit functions

Visual Computing for Industry,Biomedicine,and Art 2018年第1期1卷 95-110页

作者： Qingde Li Qingqi Hong Quan Qi Xinhui Ma Xie Han Jie Tian School of Engineering and Computer Science University of HullHull HU67RXUK Software School Xiamen UniversityXiamenChina School of Computer Science and Control Engineering North University of ChinaTaiyuanChina Intelligent Bioinformatics Systems Division Institute of AutomationThe Chinese Academy of SciencesBeijingChina

Surface-based geometric modeling has many advantages in terms of visualization and traditional subtractive manufacturing using computer-numerical-control cutting-machine ***,it is not an ideal solution for additive manufacturing because to digitally print a surface-represented geometric object using a certain additive manufacturing technology,the object has to be converted into a solid ***,converting a known surface-based geometric representation into a printable representation is essentially a redesign process,and this is especially the case,when its interior material structure needs to be *** specify a 3D geometric object that is ready to be digitally manufactured,its representation has to be in a certain volumetric *** this research,we show how some of the difficulties experienced in additive manufacturing can be easily solved by using implicitly represented geometric *** surface-based geometric representation is subtractive manufacturing-friendly,implicitly described geometric objects are additive manufacturing-friendly:implicit shapes are 3D printing *** implicit geometric representation allows to combine a geometric shape,material colors,an interior material structure,and other required attributes in one single description as a set of implicit functions,and no conversion is *** addition,as implicit objects are typically specified procedurally,very little data is used in their specifications,which makes them particularly useful for design and visualization with modern cloud-based mobile devices,which usually do not have very big storage ***,implicit modeling is a design procedure that is parallel computing-friendly,as the design of a complex geometric object can be divided into a set of simple shape-designing tasks,owing to the availability of shape-preserving implicit blending operations.

关键词： Additive manufacturing 3D printing-friendly CAD Implicit function Isosurface Level-set Function-based shape modeling Implicit modeling

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Hierarchic Stabilization of Flying Convex-Path-Following Formations Part II: Underactuated Agents

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IFAC-PapersOnLine 2019年第12期52卷 352-357页

作者： Mohamed I. El-Hawwary Department of Electrical Power Engineering Faculty of Engineering Cairo University Giza 12613 Egypt Division of Decision and Control Systems School of Electrical Engineering & Computer Science KTH Royal Institute of Technology SE-100 44 Stockholm Sweden

In this paper the flying convex-path-following formations problem (FCxPFF) is solved for two cases of underactuated rigid bodies. In the first case the the rigid bodies have a single degree of underactuation with two thrusts and three torques. In the second, they have two degrees of underactuation with a single thrust. The solution builds on the one developed for fully-actuated agents in Part I of the paper. In addition, the way the solution is tailored for underactuation relies on further utilization of hierarchic set stabilization, and reduction. Additional remarks on the benefits of the approach, and simulation results of the proposed solutions are presented.

关键词： Formation control distributed stabilization underactuated systems hierarchical control reduction

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A framework for personalized competitive programming training 17

A framework for personalized competitive programming trainin...

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17th International Conference on Information Technology Based Higher Education and Training, ITHET 2018

作者： Di Mascio, Tania Laura, Luigi Temperini, Marco Dept. of Information Engineering Computer Science and Mathematics University of l'Aquila Italy Dept. of Computer Control and Management Engineering Sapienza University Rome Italy

ISBN: (纸本)9781538646236

Programming Contests are a special branch in the general area of training and education programming support and cover an important role in the area of computer science. Rather than the direct provision of concepts and exercises related to programming, the main concern is on the algorithms and data structures managed while composing the solution to a problem, and the quality of the solution program itself. Training via web for programming contests is mainly comprised of the activity of producing solutions to problems offered by the online system (online training platforms), whereas a solution is a program, submitted by the student, and it has to be evaluated, in order to assess the programming performance, and give suggestions about the quality of the solution, so to make the experience an informative (learning) one. To the best of our knowledge, supporting a personalized approach and possibly recommendations given by the system, is a challenge. In this paper we tackle the problem of supporting students in their online training toward the participation in a programming contest, aiming at defining a framework that can allow recommendations, under the form of suggestions, to the learner, about the next programming problem to undertake, and that can foster motivation in students by means of a lightweight, badge-based, gamified approach. © 2018 IEEE.

关键词： Students

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Privacy-preserving medical treatment system through nondeterministic finite automata

arXiv

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arXiv 2020年

作者： Yang, Yang Deng, Robert H. Liu, Ximeng Wu, Yongdong Weng, Jian Zheng, Xianghan Rong, Chunming School of Information Systems Singapore Management University Singapore College of Mathematics and Computer Science Fuzhou University Fujian China State Key Laboratory of Integrated Services Networks Xidian University Guangdong Provincial Key Laboratory of Data Security and Privacy Protection Guangzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China School of Information Systems Singapore Management University Singapore Singapore Department of Computer Science Jinan University Guangdong China College of Mathematics and Computer Science Fuzhou University Fujian China Department of Electronic Engineering and Computer Science University of Stavanger Norway MingByte Technology Qingdao China

In this paper, we propose a privacy-preserving medical treatment system using nondeterministic finite automata (NFA), hereafter referred to as P-Med, designed for the remote medical environment. P-Med makes use of the nondeterministic transition characteristic of NFA to flexibly represent the medical model, which includes illness states, treatment methods and state transitions caused by exerting different treatment methods. A medical model is encrypted and outsourced to the cloud to deliver telemedicine services. Using P-Med, patient-centric diagnosis and treatment can be made on-the-fly while protecting the confidentiality of a patient's illness states and treatment recommendation results. Moreover, a new privacy-preserving NFA evaluation method is given in P-Med to get a confidential match result for the evaluation of an encrypted NFA and an encrypted data set, which avoids the cumbersome inner state transition determination. We demonstrate that P-Med realizes treatment procedure recommendation without privacy leakage to unauthorized parties. We conduct extensive experiments and analyses to evaluate efficiency. Copyright © 2020, The Authors. All rights reserved.

关键词： Diseases

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An exploratory study on machine learning to couple numerical solutions of partial differential equations

arXiv

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arXiv 2020年

作者： Tang, Hansong Li, L. Grossberg, M. Liu, Y.J. Jia, Y.M. Li, S.S. Dong, W.B. Civil Engineering Department City College of New York City University of New York New York10031 United States Department of Control Science and Engineering University of Shanghai for Science and Technology Shanghai200093 China Department of Computer Science City College of New York City University of New York New York10031 United States School of Mathematics Georgia Institute of Technology GA30332 United States School of Automation Science and Electrical Engineering Beihang University Beijing10083 China School of Hydraulic and Hydroelectric Engineering Xi'an University of Technology Shaanxi710048 China

As further progress in the accurate and efficient computation of coupled partial differential equations (PDEs) becomes increasingly difficult, it has become highly desired to develop new methods for such computation. In deviation from conventional approaches, this short communication paper explores a computational paradigm that couples numerical solutions of PDEs via machine-learning (ML) based methods, together with a preliminary study on the paradigm. Particularly, it solves PDEs in subdomains as in a conventional approach but develops and trains artificial neural networks (ANN) to couple the PDEs' solutions at their interfaces, leading to solutions to the PDEs in the whole domains. The concepts and algorithms for the ML coupling are discussed using coupled Poisson equations and coupled advection-diffusion equations. Preliminary numerical examples illustrate the feasibility and performance of the ML coupling. Although preliminary, the results of this exploratory study indicate that the ML paradigm is promising and deserves further research. Copyright © 2020, The Authors. All rights reserved.

关键词： Neural networks

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A Concept of an Adaptive Luminaire with Variable Luminous Intensity Distribution 7

A Concept of an Adaptive Luminaire with Variable Luminous In...

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7th Lighting Conference of the Visegrad Countries, LUMEN V4 2018

作者： Lesko, Marcin Wachta, Henryk Baran, Krzysztof Rozowicz, Antoni Faculty of Electrical and Computer Engineering Rzeszow University of Technology Rzeszow Poland Automatic Control and Computer Science Kielce University of Technology Faculty of Electrical Engineering Kielce Poland

ISBN: (纸本)9781538679234

The article presents an innovative concept of adaptive luminaire with variable luminous intensity distribution. It enables adjustment of photometric characteristic of luminaire to variable arrangement of the facility, including the quantitative regulation of luminous flux and spatial distribution. A solution presented in this paper was developed as part of a research project titled 'Development of the Intelligent Light Distribution System SOLLS ACTIVE SKY' and is the subject of patent application. The authors present the results of simulation tests in terms of the possibility of obtaining different luminous intensity distribution and lighting parameters on the working plane, with variable position relative to the arrangement of the luminaires. The use of a luminaire with variable luminous intensity distribution as part of an adaptive lighting system allows for quick and cost-free introduction of changes in the lighting of selected functional zones inside the facility. It is possible to adjust the lighting in case of changes in the size or position of the working plane, while the position of luminaire is constant. © 2018 IEEE.

关键词： Optical systems

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Two-line graphs of partial Latin rectangles

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Electronic Notes in Discrete Mathematics 2018年 68卷 53-58页

作者： Danan, Eiran Falcón, Raúl M. Kotlar, Dani Marbach, Trent G. Stones, Rebecca J. Department of Computer Science Tel-Hai College Upper Galilee Israel School of Building Engineering Universidad de Sevilla Sevilla Spain College of Computer and Control Engineering Nankai University Tianjin China

Two-line graphs of a given partial Latin rectangle are introduced as vertex-and-edge-coloured bipartite graphs that give rise to new autotopism invariants. They reduce the complexity of any currently known method for ... 详细信息

关键词： adequate partition autotopism group entry invariant partial Latin rectangle

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Think That Attackers Think: Using First-order Theory of Mind in Intrusion Response System

Think That Attackers Think: Using First-order Theory of Mind...

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IEEE Global Communications Conference

作者： Qiumei Cheng Chunming Wu Bin Hu Dezhang Kong Boyang Zhou College of Computer Science and Technology Zhejiang University Hangzhou China Zhejiang Lab Hangzhou China College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

The intrusion response system is dedicated to automatically respond to sophisticated network intrusions, which is a sequential decision-making problem for autonomous agents. The current Markov decision process (MDP) or stochastic games based solutions suffer from several weaknesses: (i) The MDP-based approach is unable to explicitly model the opponents;(ii) The Nash equilibrium approach of stochastic games cannot handle the condition with multi equilibria. Existing studies have not considered the cognitive ability of the agent and lack of explicit opponent modeling. Inspired by recursive reasoning, this paper introduces a theory of mind (ToM)-based stochastic game-theoretic approach to reason about the beliefs and behaviors of the attackers. Each agent maintains different order ToM beliefs concerning his opponent with explicit opponent modeling. In order to accurately predict the attacker's action with nested beliefs, we utilize the Bayesian attack graph (BAG) to model multi-step attacks scenarios. In addition, the agent is allowed to learn from new information to adjust his beliefs and learning speed. Simulation results validate that ToM modeling performs well in the intrusion response system than random defense actions. Besides, a defender with first-order ToM beliefs always wins an attacker with zero-order ToM beliefs.

关键词： Games Bayes methods Stochastic processes Predictive models Game theory Measurement

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Predictive Maintenance of Air Conditioning Systems Using Supervised Machine Learning

Predictive Maintenance of Air Conditioning Systems Using Sup...

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International Conference on Intelligent Systems Applications to Power Systems (ISAP)

作者： Shrishti Trivedi Sahil Bhola Archit Talegaonkar Prerna Gaur Shreya Sharma Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi India Computer Science Engineering Indraprastha Institute of Information Technology New Delhi India

ISBN: (数字)9781728131924

ISBN: (纸本)9781728131931

Various types of faults can occur in an air conditioner resulting in a decrease in efficiency, a rise in energy consumption, and increasing maintenance costs. Hence predictive maintenance becomes important. In this paper, the two most common types of faults - gas leakage and capacitor malfunction have been detected using the decision tree machine learning algorithm. The data for faulty and operating air conditioners have been collected using distributed sensors, microcontroller, and dedicated circuitry and analyzed using MATLAB Classification App Learner Toolbox. The results obtained by the decision tree for fault detection and diagnosis and load monitoring were then compared with results obtained by support vector machine and the prediction accuracy for the decision tree was found to be higher. The presented research work can identify the air conditioner which is faulty as well as predicts the type of fault at an early stage to do maintenance beforehand.

关键词： Circuit faults Decision trees Machine learning algorithms Intelligent sensors Air conditioning Fault detection

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Visual SLAM Based on Dynamic Object Removal

Visual SLAM Based on Dynamic Object Removal

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IEEE International Conference on Robotics and Biomimetics

作者： Hanjie Liu Guoliang Liu Guohui Tian Shiqing Xin Ze Ji School of Control Science and Engineering Shandong University Jinan Shandong China School of Computer Science and Technology Shandong University Qingdao Shandong China School of Engineering Cardiff University Cardiff UK

Visual simultaneous localization and mapping (SLAM) is the core of intelligent robot navigation system. Many traditional SLAM algorithms assume that the scene is static. When a dynamic object appears in the environment, the accuracy of visual SLAM can degrade due to the interference of dynamic features of moving objects. This strong hypothesis limits the SLAM applications for service robot or driverless car in the real dynamic environment. In this paper, a dynamic object removal algorithm that combines object recognition and optical flow techniques is proposed in the visual SLAM framework for dynamic scenes. The experimental results show that our new method can detect moving object effectively and improve the SLAM performance compared to the state of the art methods.

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