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Research Article
Multi-source remote sensing image registration based on Contourlet transform and multiple feature fusion
Huan Liu, Genfu Xiao, Yunlan Tan, Chunjuan Ouyang
Available online   doi: 10.1007/s11633-018-1163-6
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Image registration is an indispensable component in multi-source remote sensing image processing. In this paper, we put forward a remote sensing image registration method by including an improved multi-scale and multi-direction Harris algorithm and a novel compound feature. Multi-scale circle Gaussian Combined invariant moments and multi-direction gray level co-occurrence matrix are extracted as features for image matching. The proposed algorithm is evaluated on numerous multi-source remote sensor images with noise and illumination changes. Extensive experimental studies prove that our proposed method is capable of receiving stable and even distribution of key points as well as obtaining robust and accurate correspondence matches. It is a promising scheme in multi-source remote sensing image registration.
Experimental Evaluation of Certain Pursuit and Evasion Schemes for Wheeled Mobile Robots
Amit Kumar, Aparajita Ojha
Available online   doi: 10.1007/s11633-018-1151-x
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Image Encryption Algorithm Based on Compressive Sensing and Fractional DCT via Polynomial Interpolation
Ya-Ru Liang, Zhi-Yong Xiao
Available online   doi: 10.1007/s11633-018-1159-2
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Modeling of a Smart Nano Force Sensor Using Finite Elements and Neural Networks
Menacer Farid, Kadri Abdelmalek, Dibi Zohir
Available online   doi: 10.1007/s11633-018-1155-6
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The aim of this work is to model and analyze the behavior of a new smart nano force sensor. To do so, the carbon nanotube has been used as a suspended gate of a metal-oxide-semiconductor field-effect transistor (MOSFET). The variation of the applied force on the carbon nanotube (CNT) generates a variation of the capacity of the transistor oxide-gate and therefore the variation of the threshold voltage, which allows the MOSFET to become a capacitive nano force sensor. The sensitivity of the nano force sensor can reach 0.124 31 V/nN. This sensitivity is greater than results in the literature. We have found through this study that the response of the sensor depends strongly on the geometric and physical parameters of the CNT. From the results obtained in this study, the increase in the applied force has as a consequence an increase in the value of the threshold voltage VTh of the MOSFET. In this paper, we first used artificial neural networks to faithfully reproduce the response of the nano force sensor model. This neural model is called direct model. Then, secondly, we designed an inverse model called an intelligent sensor which allows linearization of the response of our developed force sensor.
A robust face recognition method combining LBP with multi-mirror symmetry for images with various face interferences
Shui-Guang Tong, Yuan-Yuan Huang, Zhe-Ming Tong
Available online   doi: 10.1007/s11633-018-1153-8
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Synthesize Robot Programs with Interactive Tutor Mode
Hao Li, Yu-Ping Wang, Tai-Jiang Mu
Available online   doi: 10.1007/s11633-018-1154-7
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Predictive adaptive Kalman filter and its application to INS/UWB-integrated human localization with missing UWB-based measurement
Yuan Xu, Tao Shen, Xi-Yuan Chen, Li-Li Bu, Ning Feng
Available online   doi: 10.1007/s11633-018-1157-4
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Accurate classification of EEG signals using neural networks trained by hybrid population-physic-based algorithm
Sajjad Afrakhteh, Mohammad-Reza Mosavi, Mohammad Khishe, Ahmad Ayatollahi
Available online   doi: 10.1007/s11633-018-1158-3
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Development of STEP AP224 extractor for interfacing feature based CAPP to STEP-NC (AP238)
Deepanshu Srivastava, Venkateswara Rao Komma
Available online   doi: 10.1007/s11633-018-1144-9
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An Operator based Nonlinear Vibration Control System Using a Flexible Arm with Shape Memory Alloy
Hiroki Matsumori, Ming-Cong Deng, Yuichi Noge
Available online   doi: 10.1007/s11633-018-1149-4
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Motion-Force Transmissibility Characteristic Analysis of a Redundantly Actuated and Overconstrained Parallel Machine
Hai-Qiang Zhang, Hai-Rong Fang, Bing-Shan Jiang
Available online   doi: 10.1007/s11633-018-1156-5
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Auto-tuning of FOPI Controllers for TITO Processes with Experimental Validation
Gargi Baruah, Somanath Majhi, Chitralekha Mahanta
Available online   doi: 10.1007/s11633-018-1140-0
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Dynamic Performance Evaluation of a Redundantly Actuated and Over-constrained Parallel Manipulator
Hai-Qiang Zhang, Hai-Rong Fang, Bing-Shan Jiang, Shuai-Guo Wang
Available online   doi: 10.1007/s11633-018-1147-6
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Predictive control based on fuzzy supervisor for PWARX hybrid models
Olfa Yahya, Zeineb Lassoued, Kamel Abderrahim
Available online   doi: 10.1007/s11633-018-1148-5
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Time-space Viewpoint Planning for Guard Robot with Chance Constraint
Igi Ardiyanto, Jun Miura
Available online   doi: 10.1007/s11633-018-1146-7
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Phenomenological Based Soft Sensor for Online Estimation of Slurry Rheological Properties
Jenny L. Diaz C., Diego A. Muñoz, Hernan Alvarez
Available online   doi: 10.1007/s11633-018-1132-0
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Fuzzy Behavior-Based control of Three Wheeled Omnidirectional Mobile robot
Nacer Hacene, Boubekeur Mendil
Available online   doi: 10.1007/s11633-018-1135-x
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A Practical Approach to Representation of Real-Time Building Control Applications in Simulation
Azzedine Yahiaoui
Available online   doi: 10.1007/s11633-018-1131-1
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Emergency supply chain management based on Rough Set - House of Quality
Yuan He, Xue-Dong Liang, Fu-Min Deng, Zhi Li
Available online   doi: 10.1007/s11633-018-1133-z
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Performance Evaluation and Improvement of Chipset Assembly & Test Production Line Based on Variability
Chang-Jun Li, Zong-Shi Xie, Xin-Ran Peng, Bo Li
Available online   doi: 10.1007/s11633-018-1129-8
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New LMI Conditions for Reduced-Order Observer of Lipschitz Discrete-Time Systems: Numerical and Experimental Results
Noussaiba GasmiI, Assem Thabet, Mohamed Aoun
Available online   doi: 10.1007/s11633-018-1160-9
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The objective of this paper is to propose a reduced-order observer for a class of Lipschitz nonlinear discrete-time systems. The conditions that guarantee the existence of this observer are presented in the form of linear matrix inequalities (LMIs). To handle the Lipschitz nonlinearities, the Lipschitz condition and the Young′s relation are adequately operated to add more degrees of freedom to the proposed LMI. Necessary and sufficient conditions for the existence of the unbiased reduced-order observer are given. An extension to \begin{document}$\mathcal{H}_\infty$\end{document} performance analysis is considered in order to deal with \begin{document}$\mathcal{H}_\infty$\end{document} asymptotic stability of the estimation error in the presence of disturbances that affect the state of the system. To highlight the effectiveness of the proposed design methodology, three numerical examples are considered. Then, high performances are shown through real time implementation using the ARDUINO MEGA 2560 device.
A Hybrid Time Frequency Response and Fuzzy Decision Tree for Non-Stationary Signal Analysis and Pattern Recognition
N. R. Nayak, P. K. Dash, R. Bisoi
Available online   doi: 10.1007/s11633-018-1113-3
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A Creative Approach to Reducing Ambiguity in Scenario-based Software Architecture Analysis
Xi-Wen Wu, Chen Li, Xuan Wang, Hong-Ji Yang
Available online   doi: 10.1007/s11633-017-1102-y
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Low-Latency Data Gathering with Reliability Guaranteeing in Heterogeneous Wireless Sensor Networks
Tian-Yun Shi, Jian Li, Xin-Chun Jia, Wei Bai, Zhong-Ying Wang, Dong Zhou
Available online   doi: 10.1007/s11633-017-1074-y
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Composite Control of Nonlinear Singularly Perturbed Systems via Approximate Feedback Linearization
Aleksey Kabanov, Vasiliy Alchakov
Available online   doi: 10.1007/s11633-017-1076-9
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Optimal Design of Fuzzy-AGC Based on PSO&RCGA to Improve Dynamic Stability of Interconnected Multi Area Power Systems
Ali Darvish Falehi
Available online   doi: 10.1007/s11633-017-1064-0
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Robust Neural Control of Discrete Time Uncertain Nonlinear Systems Using Sliding Mode Backpropagation Training Algorithm
Imen Zaidi, Mohamed Chtourou, Mohamed Djemel
Available online   doi: 10.1007/s11633-017-1062-2
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A Linear Quadratic Controller Design Incorporating a Parametric Sensitivity Constraint
Mohamed Yagoubi
Available online   doi: 10.1007/s11633-016-1048-5
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Study of performance and reliability of urethral valve driven by ultrasonic-vaporized steam
Zhen Hu, Xiao Li, Ting Guan
Available online   doi: 10.1007/s11633-016-1026-y
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Function projective lag synchronization of chaotic systems with certain parameters via adaptive-impulsive control
Xiu-Li Chai, Zhi-Hua Gan
Available online   doi: 10.1007/s11633-016-1020-4
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Convergence Analysis of a New MaxMin-SOMO Algorithm
Atlas Khan, Yan-Peng Qu, Zheng-Xue Li
Available online   doi: 10.1007/s11633-016-0996-0
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Decomposition based Fuzzy Model Predictive Control approaches of Interconnected Nonlinear Systems
Latifa Dalhoumi, Mohamed Chtourou, Mohamed Djemel
Available online   doi: 10.1007/s11633-016-1021-3
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Contribution of the Field-Programmable Gate Array for complex control algorithms: Sensorless Direct Torque Fuzzy Control with Extended Kalman Filter of an Induction Motor
Saber Krim, Soufien Gdaim, Abdellatif Mtibaa, Mohamed Faouzi Mimouni
Available online   doi: 10.1007/s11633-016-1017-z
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Sequential Fault Diagnosis using An Inertial Velocity Differential Evolution Algorithm
Xiao-Hong Qiu, Yu-Ting Hu, Bo Li
Available online   doi: 10.1007/s11633-016-1008-0
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Stabilization for a Class of Discrete-time Switched Large-scale Systems with Parameter Uncertainties
Chang-Chun Sun
Available online   doi: 10.1007/s11633-016-0966-6
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A Novel Self-adaptive Circuit Design Technique based on Evolvable Hardware
Jun-Bin Zhang, Jin-Yan Cai, Ya-Feng Meng, Tian-Zhen Meng
Available online   doi: 10.1007/s11633-016-1000-8
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Simultaneous Identification of Process Structure, Parameter and Time-Delay Based on Non-Negative Garrote
Jian-Guo Wang, Qian-Ping Xiao, Tiao Shen, Shi-Wei Ma, Wen-Tao Rao, Yong-Jie Zhang
Available online   doi: 10.1007/s11633-015-0948-0
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Energy Efficient Scheduler of Aperiodic jobs for Real-Time Embedded Systems
Hussein El Ghor, E. M. Aggoune
Available online   doi: 10.1007/s11633-016-0993-3
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H∞ state estimation for stochastic Markovian jumping Neural Network with time-varying delay and leakage delay
Ya-Jun Li, Zhao-Wen Huang, Jing-Zhao Li
Available online   doi: 10.1007/s11633-016-0955-9
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Design of Ethernet based data acquisition system for yaw rate and longitudinal velocity measurement in automobiles
K. Arun Venkatesh, N. Mathivanan
Available online   doi: 10.1007/s11633-016-0968-4
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Review
Key Crowdsourcing Technologies for Product Design and Development
Xiao-Jing Niu, Sheng-Feng Qin, John Vines, Rose Wong, Hui Lu
2019,  vol. 16,  no. 1,   pp. 1-15 ,  doi: 10.1007/s11633-018-1138-7
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Traditionally, small and medium enterprises (SMEs) in manufacturing rely heavily on a skilled, technical and professional workforce to increase productivity and remain globally competitive. Crowdsourcing offers an opportunity for SMEs to get access to online communities who may provide requested services such as generating design ideas or problem solutions. However, there are some barriers preventing them from adopting crowdsourcing into their product design and development (PDD) practice. In this paper, we provide a literature review of key crowdsourcing technologies including crowdsourcing platforms and tools, crowdsourcing frameworks, and techniques in terms of open call generation, rewarding, crowd qualification for working, organization structure of crowds, solution evaluation, workflow and quality control and indicate the challenges of integrating crowdsourcing with a PDD process. We also explore the necessary techniques and tools to support the crowdsourcing PDD process. Finally, we propose some key guidelines for coping with the aforementioned challenges in the crowdsourcing PDD process.
A Survey of the Research Status of Pedestrian Dead Reckoning Systems Based on Inertial Sensors
Yuan Wu, Hai-Bing Zhu, Qing-Xiu Du, Shu-Ming Tang
2019,  vol. 16,  no. 1,   pp. 65-83 ,  doi: 10.1007/s11633-018-1150-y
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With the development of micro-electromechanical systems (MEMS), miniaturized, low-power and low-cost inertial measurement units (IMUs) have been widely integrated into mobile terminals and smart wearable devices. This provides the prospect of a broad application for the inertial sensor-based pedestrian dead-reckoning (IPDR) systems. Especially for indoor navigation and indoor positioning, the IPDR systems have many unique advantages that other methods do not have. At present, a large number of technologies and methods for IPDR systems are proposed. In this paper, we have analyzed and outlined the IPDR systems based on about 80 documents in the field of IPDR in recent years. The article is structured in the form of an introduction-elucidation-conclusion framework. First, we proposed a general framework to explore the structure of an IPDR system. Then, according to this framework, the IPDR system was divided into six relatively independent sub-problems, which were discussed and summarized separately. Finally, we proposed a graph structure of IPDR systems, and a sub-directed graph, formed by selecting a combined path from the start node to the end node, skillfully constitutes a technical route of one specific IPDR system. At the end of the article, we summarized some key issues that need to be resolved before the IPDR systems are widely used.
Research Article
Potential Bands of Sentinel-2A Satellite for Classification Problems in Precision Agriculture
Tian-Xiang Zhang, Jin-Ya Su, Cun-Jia Liu, Wen-Hua Chen
2019,  vol. 16,  no. 1,   pp. 16-26 ,  doi: 10.1007/s11633-018-1143-x
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Various indices are used for assessing vegetation and soil properties in satellite remote sensing applications. Some indices, such as normalized difference vegetation index (NDVI) and normalized difference water index (NDWI), are capable of simply differentiating crop vitality and water stress. Nowadays, remote sensing capabilities with high spectral, spatial and temporal resolution are available to analyse classification problems in precision agriculture. Many challenges in precision agriculture can be addressed by supervised classification, such as crop type classification, disease and stress (e.g., grass, water and nitrogen) monitoring. Instead of performing classification based on designated indices, this paper explores direct classification using different bands information as features. Land cover classification by using the recently launched Sentinel-2A image is adopted as a case study to validate our method. Four approaches of featured band selection are compared to classify five classes (crop, tree, soil, water and road) with the support vector machines (SVMs) algorithm, where the first approach utilizes traditional empirical indices as features and the latter three approaches adopt specific bands (red, near infrared and short wave infrared) related to indices, specific bands after ranking by mutual information (MI), and full bands of on-board sensors as features, respectively. It is shown that a better classification performance can be achieved by directly using the selected bands after MI ranking compared with the one using empirical indices and specific bands related to indices, while the use of all 13 bands can marginally improve the classification accuracy than MI based one. Therefore, it is recommended that this approach can be applied for specific Sentinel-2A image classification problems in precision agriculture.
Effective Crowd Anomaly Detection Through Spatio-temporal Texture Analysis
Yu Hao, Zhi-Jie Xu, Ying Liu, Jing Wang, Jiu-Lun Fan
2019,  vol. 16,  no. 1,   pp. 27-39 ,  doi: 10.1007/s11633-018-1141-z
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Abnormal crowd behaviors in high density situations can pose great danger to public safety. Despite the extensive installation of closed-circuit television (CCTV) cameras, it is still difficult to achieve real-time alerts and automated responses from current systems. Two major breakthroughs have been reported in this research. Firstly, a spatial-temporal texture extraction algorithm is developed. This algorithm is able to effectively extract video textures with abundant crowd motion details. It is through adopting Gabor-filtered textures with the highest information entropy values. Secondly, a novel scheme for defining crowd motion patterns (signatures) is devised to identify abnormal behaviors in the crowd by employing an enhanced gray level co-occurrence matrix model. In the experiments, various classic classifiers are utilized to benchmark the performance of the proposed method. The results obtained exhibit detection and accuracy rates which are, overall, superior to other techniques.
Multi-layer Contribution Propagation Analysis for Fault Diagnosis
Ruo-Mu Tan, Yi Cao
2019,  vol. 16,  no. 1,   pp. 40-51 ,  doi: 10.1007/s11633-018-1142-y
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The recent development of feature extraction algorithms with multiple layers in machine learning and pattern recognition has inspired many applications in multivariate statistical process monitoring. In this work, two existing multi-layer linear approaches in fault detection are reviewed and a new one with extra layer is proposed in analogy. To provide a general framework for fault diagnosis in succession, this work also proposes the contribution propagation analysis which extends the original definition of contribution of variables in multivariate statistical process monitoring. In fault diagnosis stage, the proposed contribution propagation analysis for multi-layer linear feature extraction algorithms is compared with the fault diagnosis results of original contribution plots associated with single layer feature extraction approach. Plots of variable contributions obtained by the aforementioned approaches on the data sets collected from a simulated benchmark case study (Tennessee Eastman process) as well as an industrial scale multiphase flow facility are presented as a demonstration of the usage and performance of the contribution propagation analysis on multi-layer linear algorithms.
A Reliability Aware Protocol for Cooperative Communication in Cognitive Radio Networks
Munam Ali Shah, Si-Jing Zhang, Hong-Ji Yang
2019,  vol. 16,  no. 1,   pp. 84-92 ,  doi: 10.1007/s11633-016-0995-1
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One of the challenging tasks in cognitive radio (CR) networks is to agree on a common control channel to exchange control information. This paper presents a novel medium access control (MAC) protocol for CR network which efficiently and intelligently establishes a common control channel between CR nodes. The proposed protocol is the first CR MAC protocol which is hybrid in nature and lies between global common control channel (GCCC) and non-GCCC family of MAC protocols. The dynamic nature of the protocol makes the CR nodes converge on a newly found control channel quicker whenever the interference from a licensed user is sensed. The analytical results show that the dynamic, hybrid and adaptive nature of proposed protocol yields higher throughputs when compared with other CR MAC protocols.
Virtual Plate Based Controlling Strategy of Toy Play for Robot's Communication Development in JA Space
Wei Wang, Xiao-Dan Huang
2019,  vol. 16,  no. 1,   pp. 93-101 ,  doi: 10.1007/s11633-016-1022-2
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Toy play is a basic skill for a humanoid robot after it has joint attention (JA) ability. Because such skill is helpful for human-robot interaction and cooperation, we must realize this skill to enhance the robot's communication ability with person. In this paper, we researched a toy play controlling strategy in JA space based on a virtual plate with a serial robot arm, which has five degrees of freedom (5-DoF). For this purpose, a reachable space of joint attention was constructed firstly. And then the toy play controlling strategy was proposed in details. Here we used a virtual plate to enhance the toy play effect. In order to realize this skill better, toy play energy and some restraining relations were analyzed. By contrasting the audio waveform in the experiments, good performance effect of toy play was demonstrated.
Iterative Selection of GOB Poles in the Context of System Modeling
Anis Khouaja, Hassani Messaoud
2019,  vol. 16,  no. 1,   pp. 102-111 ,  doi: 10.1007/s11633-016-0984-4
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Abstract:
This paper is concerned with the problem of system identification using expansions on generalized orthonormal bases (GOB). Three algorithms are proposed to optimize the poles of such a basis. The first two algorithms determine a GOB with optimal real poles while the third one determines a GOB with optimal real and complex poles. These algorithms are based on the estimation of the dominant mode associated with a residual signal obtained by iteratively filtering the output of the process to be modelled. These algorithms are iterative and based on the quadratic error between the linear process output and the GOB based model output. They present the advantage to be very simple to implement. No numerical optimization technique is needed, and in consequence there is no problem of local minima as is the case for other algorithms in the literature. The convergence of the proposed algorithms is proved by demonstrating that the modeling quadratic error between the process output and the GOB based model is decreasing at each iteration of the algorithm. The performance of the proposed pole selection algorithms are based on the quadratic error criteria and illustrated by means of simulation results.
Special Spectral Approach to Solutions of SISO LTI H-Optimization Problems
Evgeny I. Veremey
2019,  vol. 16,  no. 1,   pp. 112-128 ,  doi: 10.1007/s11633-017-1110-y
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Abstract:
The paper is devoted to \begin{document}$H$\end{document}-optimization problems for linear time invariant (LTI) systems with scalar control, external disturbance and measurement noise. All these problems can be numerically solved with the help of the well-known universal approaches based on Riccati equations, linear matrix inequalities (LMI) or maximum entropy technique. Nevertheless, in our opinion there exists a possibility to increase the computational efficiency of synthesis using a special spectral approach to the above mentioned problems in frequency domain. Some relevant details are discussed and efficient numerical algorithms are proposed for the practical implementation of spectral approach. One of its virtues is a possibility to present optimal solutions in a specific form, which is convenient for investigation.
Research Article
Optimization RFID-enabled Retail Store Management with Complex Event Processing
Shang-Lian Peng, Ci-Jian Liu, Jia He, Hong-Nian Yu, Fan Li
2019,  vol. 16,  no. 1,   pp. 52-64 ,  doi: 10.1007/s11633-018-1164-5
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Abstract:
Radio frequency identification (RFID) enabled retail store management needs workflow optimization to facilitate real-time decision making. In this paper, complex event processing (CEP) based RFID-enabled retail store management is studied, particularly focusing on automated shelf replenishment decisions. We define different types of event queries to describe retailer store workflow action over the RFID data streams on multiple tagging levels (e.g., item level and container level). Non-deterministic finite automata (NFA) based evaluation models are used to detect event patterns. To manage pattern match results in the process of event detection, optimization algorithm is applied in the event model to share event detection results. A simulated RFID-enabled retail store is used to verify the effectiveness of the method, experiment results show that the algorithm is effective and could optimize retail store management workflow.
Correlation of Direct Piezoelectric Effect on EAPap under Ambient Factors
Li-Jie Zhao, Chang-Ping Tang, Peng Gong
2010,  vol. 7,  no. 3,   pp. 324-329, doi: 10.1007/s11633-010-0510-z
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The Effect of Interatomic Potentials on the Molecular Dynamics Simulation of Nanometric Machining
Akinjide Oluwajobi, Xun Chen
2011,  vol. 8,  no. 3,   pp. 326-332, doi: 10.1007/s11633-011-0588-y
Abstract PDF SpringerLink
Feature Selection and Feature Learning for High-dimensional Batch Reinforcement Learning: A Survey
De-Rong Liu, Hong-Liang, Li Ding Wang
2015,  vol. 12,  no. 3,   pp. 229-242, doi: 10.1007/s11633-015-0893-y
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Adaptive Terminal Sliding Mode Control for Rigid Robotic Manipulators
Mezghani Ben Romdhane Neila, Damak Tarak
2011,  vol. 8,  no. 2,   pp. 215-220, doi: 10.1007/s11633-011-0576-2
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Adaptive Fuzzy Sliding Mode Power System Stabilizer Using Nussbaum Gain
Emira Nechadi, Mohamed Naguib Harmas, Najib Essounbouli, Abdelaziz Hamzaoui
2013,  vol. 10,  no. 4,   pp. 281-287, doi: 10.1007/s11633-013-0722-0
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A New Method for Modelling and Simulation of the Dynamic Behaviour of the Wheel-rail contact
Arthur Anyakwo, Crinela Pislaru, Andrew Ball
2012,  vol. 9,  no. 3,   pp. 237-247, doi: 10.1007/s11633-012-0640-6
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Exponential Nonlinear Observer Based on the Differential State-dependent Riccati Equation
Hossein Beikzadeh, Hamid D. Taghirad
2012,  vol. 9,  no. 4,   pp. 358-368, doi: 10.1007/s11633-012-0656-y
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Unknown Inputs Observer for a Class of Nonlinear Uncertain Systems: An LMI Approach
Kamel Mohamed, Mohammed Chadli, Mohamed Chaabane
2012,  vol. 9,  no. 3,   pp. 331-336, doi: 10.1007/s11633-012-0652-2
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Coordination Control of Greenhouse Environmental Factors
Feng Chen, Yong-Ning Tang, Ming-Yu Shen
2011,  vol. 8,  no. 2,   pp. 147-153, doi: 10.1007/s11633-011-0567-3
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Fault Tolerant Control for Networked Control Systems with Packet Loss and Time Delay
Ming-Yue Zhao, He-Ping Liu, Zhi-Jun Li, De-Hui Sun
2011,  vol. 8,  no. 2,   pp. 244-253, doi: 10.1007/s11633-011-0579-z
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Second-order Sliding Mode Approaches for the Control of a Class of Underactuated Systems
Sonia Mahjoub, Faiçal Mnif, Nabil Derbel
2015,  vol. 12,  no. 2,   pp. 134-141, doi: 10.1007/s11633-015-0880-3
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Adaptive Tracking Control of an Autonomous Underwater Vehicle
Basant Kumar Sahu, Bidyadhar Subudhi
2014,  vol. 11,  no. 3,   pp. 299-307, doi: 10.1007/s11633-014-0792-7
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Position Control of Electro-hydraulic Actuator System Using Fuzzy Logic Controller Optimized by Particle Swarm Optimization
Daniel M. Wonohadidjojo, Ganesh Kothapalli, Mohammed Y. Hassan
2013,  vol. 10,  no. 3,   pp. 181-193, doi: 10.1007/s11633-013-0711-3
Abstract PDF SpringerLink
A Method for Trust Management in Cloud Computing: Data Coloring by Cloud Watermarking
Yu-Chao Liu, Yu-Tao Ma, Hai-Su Zhang, De-Yi Li, Gui-Sheng Chen
2011,  vol. 8,  no. 3,   pp. 280-285, doi: 10.1007/s11633-011-0583-3
Abstract PDF SpringerLink
Adaptive Backstepping Sliding Mode Trajectory Tracking Control for a Quad-rotor
Xun Gong, Zhi-Cheng Hou, Chang-Jun Zhao, Yue Bai, Yan-Tao Tian
2012,  vol. 9,  no. 5,   pp. 555-560, doi: 10.1007/s11633-012-0679-4
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State Feedback Sliding Mode Control without Chattering by Constructing Hurwitz Matrix for AUV Movement
Huan-Yin Zhou, Kai-Zhou Liu, Xi-Sheng Feng
2011,  vol. 8,  no. 2,   pp. 262-268, doi: 10.1007/s11633-011-0581-5
Abstract PDF SpringerLink
Self-contained Capsubot Propulsion Mechanism
Nazmul Huda, Hong-Nian Yu, Samuel Oliver
2011,  vol. 8,  no. 3,   pp. 348-356, doi: 10.1007/s11633-011-0591-3
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A New Sliding Function for Discrete Predictive Sliding Mode Control of Time Delay Systems
Abdennebi Nizar, Ben Mansour Houda, Nouri Ahmed Said
2013,  vol. 10,  no. 4,   pp. 288-295, doi: 10.1007/s11633-013-0723-z
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Sliding Mode Control with Disturbance Observer for Class of Nonlinear Systems
Lei-Po Liu, Zhu-Mu Fu, Xiao-Na Song
2012,  vol. 9,  no. 5,   pp. 487-491, doi: 10.1007/s11633-012-0671-z
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Delay Dependent Robust Stability of Singular Systems with Additive Time-varying Delays
N. Chaibi, E. H. Tissir, A. Hmamed
2013,  vol. 10,  no. 1,   pp. 85-90 , doi: 10.1007/s11633-013-0700-6
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Current Issue

2019 Vol.16 No.1

Table of Contents

ISSN 1476-8186

E-ISSN 1751-8520

CN 11-5350/TP

Editors-in-chief
Tieniu TAN, Chinese Academy of Sciences Guoping LIU, University of South Wales Huosheng HU, University of Essex

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  • Spring Festival Holiday Notice
    To celebrate the traditional Chinese New Year, the editorial office will be closed from Feb. 2nd (Saturday) to Feb. 15th (Friday), 2019. The ScholarOne Manuscript System will be opened during the holiday. Wish you and your families all the best for a happy and healthy Chinese New Year!
  • 2019 International Academic Conference List
    International Journal of Automation and Computing (IJAC) maintains this list of conferences at the beginning of each year that are highly relevant to current hot research topics, including artificial intelligence, machine learning, computer vision, pattern recognition, robotics and automatic control.
  • ICAC'19 Call for Papers
    Paper submission deadline:30 April 2019
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