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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Das, Polash Kumar Hu, Bin Liu, Chang Cui, Kaixin Ranjan, Prabhat Xiong, Gang School of Electronic and Information Engineering South China University of Technology Guangzhou China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Science Beijing China College of Computer Science Sichuan University Chengdu China Cloud Computing Center Chinese Academy of Science Dongguan China

ISBN: (纸本)9781728128535

In biometrics, face recognition methods are achieving momentum with recent progress in the computer vision(CV). Face recognition is widely used in the identification of an individual's identity. Unfortunately, in recent research work has revealed this face biometrics system is unprotected to spoofing attacks using by very low price instrument such as printed 2D photos attack, 3D masking attack and taking videos using smart devices (reply attack). Therefore, a Liveness Attack Detection (LAD) approach is needed to improve the high-quality security of face recognition system. Most of the earlier worked LAD methods for face anti-spoofing methods have highlight on using the handcrafted features, which are developed by expert knowledge of researcher. As example Gabor filter, Histogram of Oriented Gradients, local ternary pattern, and the Local Binary Pattern. Because of that, the extracted features consider limited factors of the problem, yielding a capture accuracy that is very low and changes with the point of presentation in attack face images. The deep learning method has developed in the computer vision research community, which is proven to be suitable for automatically training. In this article, we approach to mix or combine the handcrafted features and deep neural network features to design the discriminant face spoofing detection. The handcrafted features were based on LBP analysis. We examine the features information from the brightness and the chrominance channels using LBP descriptor. In deep features, we present an approach based on pre-trained convolutional neural network VGG-16 model using static features to recognize video and printed(2D) photo attacks. By attaching this two types of image features on our dataset and public databases, we get good results to identify real and attack images feature, called hybrid features, which has better discrimination ability to understand spoofing image feature. © 2019 IEEE.

关键词： Local binary pattern

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A course in air traffic control for developing countries development and implementation

A course in air traffic control for developing countries dev...

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2003 IEEE Aerospace Conference

作者： Dimirovski, Georgi Marko Dogus University Dept. of Computer Engineering and Information Technologies Acibadem Zeamet Sk. No: 21 Kadikoy TR-81010 Istanbul Turkey SS Cyril and Metbodius University Inst. of Automation and Systems Engineering FEE Karpos 2 Rugjer Boskovic b.b. MK-1000 Skopje Macedonia

ISBN: (纸本)078037651X

This paper presents a working implementation of a course in Air Traffic Control (in the Rep. of Macedonia), which is believed to be properly tailored according to the needs of small developing countries that are likely to be users of this technology only. One version was designed for the undergraduate studies in Traffic Engineering at the Technical Faculty (TFB) in Bitola. The other version is designed for the graduate studies in automation & systems Engineering at Faculty of Electrical Engineering (FEE) in Skopje. While it may not he widely suitable for developing countries in general, it is believed these have largely met the objectives for such dedicated comes. Since, in all countries, some knowledge on air traffic control is indispensable in order to meet the internationally approved criteria, requirements and standards for proper world-wide air traffic operations. © 2003 IEEE.

关键词： Air traffic control

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Code Clone Detection Using Boosting Algorithms 3

Code Clone Detection Using Boosting Algorithms

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3rd International Conference on Advanced Research in Computing, ICARC 2023

作者： Thanoshan, M.V. Banujan, Kuhaneswaran Kumara, B.T.G.S. Prasanth, S. Li, Zhenni Paik, Incheon Sabaragamuwa University of Sri Lanka Department of Computing and Information Systems Belihuloya Sri Lanka Sabaragamuwa University of Sri Lanka Department of Physical Sciences and Technologies Belihuloya Sri Lanka Guangdong University of Technology School of Automation Guangzhou510006 China University of Aizu School of Computer Science and Engineering Aizu-Wakamatsu Japan

ISBN: (纸本)9798350347371

To increase programming productivity, developers often copy and paste the source code with or without changing it. However, they may also introduce significant downsides in the long run, including complicating the software and raising maintenance costs. The activity of duplicating the code is known as code cloning. They are classified into four types - Type-1, Type-2, Type-3, and Type-4. In this paper, the author presents a machine-learning approach for detecting code clones of all kinds except for Type-2. Abstract Syntax Trees are used to extract features from the methods. A distance combination approach combines two feature vectors of a pair of methods and their class labels. Once the dataset is finalised, a machine- learning approach is utilised to classify the clone type. Moreover, boosting classifiers like XGBoost, CatBoost, LightGBM, Gradient Boosting and AdaBoost are evaluated for the highest classification accuracy. From the results obtained, LightGBM outperformed all the other classifiers with the highest F1 score of 0.81. This study would motivate future researchers to focus on identifying the Type-2 clones and extracting novel features in determining the clone types. © 2023 IEEE.

关键词： Adaptive boosting

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Random search with k-prototypes algorithm for clustering mixed datasets

Random search with k-prototypes algorithm for clustering mix...

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作者： Pham, Duc-Truong Suarez-Alvarez, Maria M. Prostov, Yuriy I. Manufacturing Engineering Centre School of Engineering Cardiff University Cardiff CF24 3AA United Kingdom Department of Information Systems College of Computer and Information Sciences King Saud University Riyadh 11543 Saudi Arabia Department of Higher Mathematics Moscow Institute of Radio Engineering Electronics and Automation-Technical University 78 Vernadskogo pr. Moscow 117454 Russia

A new algorithm to cluster datasets with mixed numerical and categorical values is presented. The algorithm, called RANKPRO (random search with k-prototypes algorithm), combines the advantages of a recently introduced population-based optimization algorithm called the bees algorithm (BA) and k-prototypes algorithm. The BA works with elite and good solutions, and continues to look for other possible extrema solutions keeping the number of testing points constant. However, the improvement of promising solutions by the BA may be time-consuming because it is based on random neighbourhood search. On the other hand, an application of the k-prototypes algorithm to a promising solution may be very effective because it improves the solution at each iteration. The RANKPRO algorithm balances two objectives: it explores the search space effectively owing to random selection of new solutions, and improves promising solutions fast owing to employment of the k-prototypes algorithm. The efficiency of the new algorithm is demonstrated by clustering several datasets. It is shown that in the majority of the considered datasets when the average number of iterations that the k-prototypes algorithm needs to converge is over 10, the RANKPRO algorithm is more efficient than the k-prototypes algorithm. © 2011 The Royal Society.

关键词： Iterative methods

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Optimal sequential vector quantization of Markov sources

Optimal sequential vector quantization of Markov sources

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IEEE International Symposium on information Theory

作者： V.S. Borkar S.K. Mitter S.C. Tatikonda Department of Computer Science and Automation Indian Institute of Science Bangalore India Laboratory for Information and Decision Systems M.I.T. Cambridge MA USA

The problem of optimal sequential vector quantization of Markov sources is cast as a stochastic control problem with partial observations and constraints, leading to useful existence results for optimal codes and thei... 详细信息

关键词： Vector quantization Optimal control Communication system control Laboratories Stochastic processes Rate distortion theory Block codes Encoding computer science automation

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Blockchain-based EVs Charging Right Trading Model

Blockchain-based EVs Charging Right Trading Model

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China International Electrical and Energy Conference (CIEEC)

作者： Yuanyuan Li You Ma Zhiqin Zhu Guanqiu Qi Zhihao Zhou Xin Huang College of Automation Chongqing University of Posts and Telecommunications Chongqing China Computer Information Systems Department State University of New York at Buffalo State Buffalo USA

The traditional charging transaction model between electric vehicles (EVs) and the grid has low transparency and difficult settlement. To address this problem, this paper designs a demand-side response charging right transaction mechanism based on blockchain technology. First, a trinity of blockchain transaction system of power distribution network (PDN)-charging station (CS)-EVs is constructed. Second, a charging reservation mechanism and a creditworthiness evaluation mechanism is established to schedule the power quota of CS. Finally, the test results show the fairness and efficiency of the proposed charging right trading model.

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THD reduction with grid synchronized inverter’s power injection of renewable sources

THD reduction with grid synchronized inverter’s power injec...

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International Symposium on Power Electronics, Electrical Drives, automation and Motion, SPEEDAM

作者： Péter Görbe Attila Magyar Katalin M. Hangos Department of Electrical Engineering and Information Systems University of Pannonia Veszprém Hungary Process Control Research Group Computer and Automation Research Institute Budapest Hungary

A control method for small domestic power plants using renewable energy is described in this paper. This method is not only capable of optimizing the working point of the plant but also implements active power factor correction and lowers the extant harmonic distortion in the line. The novel element in the proposed complex controller structure is the upper harmonic controller that minimizes the amplitudes of the 3rd, 5th 7th, 9th, and the 11th upper harmonic component in the output voltage. The proposed controller has been investigated by simulation in Matlab environment, and as a result, substantial improvement of the output voltage and current waveform could be achieved. Robustness of the method against nonlinear loads has also been tested.

关键词： Power factor correction Costs Power generation Voltage control Harmonic distortion Robustness Nonlinear distortion Solar power generation Power supplies Inverters

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The Architecture of Intelligent Agent-based Educational System for Training Students in a Technical University

The Architecture of Intelligent Agent-based Educational Syst...

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International Conference on information Technologies in Engineering Education (Inforino)

作者： Anatoly Shvetsov Svetlana Rzheutskaya Anna Sergushicheva Alexey Sukonschikov Igor Andrianov Dmitry Kochkin Dept. of Information Systems and Technologies Vologda State University Vologda Russia Dept. of Automation and Computer Engineering Vologda State University Vologda Russia

ISBN: (数字)9781728148106

ISBN: (纸本)9781728148113

The article presents the development, implementation and approbation of a multi-level architecture of the intelligent agent-based educational system for training of technical specialists. The proposed architecture combines openness, flexibility and good scalability. This article shows how these quality indicators were achieved through a combination of multi-agent and service-oriented approaches. It describes the purpose and components of each level, presents some key aspects of the implementation and shows the results of pedagogical experiments.

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Stable third-order tensor representation for colour image classification

Stable third-order tensor representation for colour image cl...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Dacheng Tao S. Maybank Weiming Hu Xuelong Li School of Computer Science and Information Systems Birkbeck College University of London UK National Lab of Pattern Recognition Institute of Automation Chinese Academy and Sciences China

General tensors can represent colour images more naturally than conventional features; however, the general tensors' stability properties are not reported and remain to be a key problem. In this paper, we use the tensor minimax probability (TMPM) to prove that the tensor representation is stable. The proof is based on the random subspace method through a large number of experiments.

关键词： Tensile stress Color Machine learning Computational complexity Kernel Covariance matrix Machine learning algorithms Learning systems Minimax techniques Humans

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A Complementary Modularized Ramp Metering Approach Based on Iterative Learning Control and ALINEA

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IEEE Transactions on Intelligent Transportation systems 2011年第4期12卷 1305-1318页

作者： Zhongsheng Hou Xin Xu Jingwen Yan Jian-Xin Xu Gang Xiong Advanced Control Systems Laboratory School of Electronic and Information Engineering Beijing Jiaotong University BJTU Beijing China Institute of Automation College of Mechatronics and Automation National University of Defense Technology Changsha China Department of Electrical and Computer Engineering National University of Singapore Singapore Automation Institute Chinese Academy of Sciences (CAS) Beijing China

Ramp metering is an effective tool for traffic management on freeway networks. In this paper, we apply iterative learning control (ILC) to address ramp metering in a macroscopic-level freeway environment. By formulating the original ramp metering problem as an output regulating and disturbance rejection problem, ILC has been applied to control the traffic response. The learning mechanism is further combined with Asservissement Linéaire d'Entrée Autoroutière (ALINEA) in a complementary manner to achieve the desired control performance. The ILC-based ramp metering strategy and the modified modularized ramp metering approach based on ILC and ALINEA in the presence of input constraints are also analyzed to highlight the advantages and the robustness of the proposed methods. Extensive simulations are given to verify the effectiveness of the proposed approaches.

关键词： Traffic control Mathematical model Convergence Learning systems Feedforward neural networks

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