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Research Article
Semi-supervised Ladder Networks for Speech Emotion Recognition
Jian-Hua Tao, Jian Huang, Ya Li, Zheng Lian, Ming-Yue Niu
Available online   doi: 10.1007/s11633-019-1175-x
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As a major component of speech signal processing, speech emotion recognition has become increasingly essential to understanding human communication. Benefitting from deep learning, many researchers have proposed various unsupervised models to extract effective emotional features and supervised models to train emotion recognition systems. In this paper, we utilize semi-supervised ladder networks for speech emotion recognition. The model is trained by minimizing the supervised loss and auxiliary unsupervised cost function. The addition of the unsupervised auxiliary task provides powerful discriminative representations of the input features, and is also regarded as the regularization of the emotional supervised task. We also compare the ladder network with other classical autoencoder structures. The experiments were conducted on the interactive emotional dyadic motion capture (IEMOCAP) database, and the results reveal that the proposed methods achieve superior performance with a small number of labelled data and achieves better performance than other methods.
Expression Analysis Based on Face Regions in Read-world Conditions
Zheng Lian, Ya Li, Jian-Hua Tao, Jian Huang, Ming-Yue Niu
Available online   doi: 10.1007/s11633-019-1176-9
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Facial emotion recognition is an essential and important aspect of the field of human-machine interaction. Past research on facial emotion recognition focuses on the laboratory environment. However, it faces many challenges in real-world conditions, i.e., illumination changes, large pose variations and partial or full occlusions. Those challenges lead to different face areas with different degrees of sharpness and completeness. Inspired by this fact, we focus on the authenticity of predictions generated by different <emotion, region> pairs. For example, if only the mouth areas are available and the emotion classifier predicts happiness, then there is a question of how to judge the authenticity of predictions. This problem can be converted into the contribution of different face areas to different emotions. In this paper, we divide the whole face into six areas: nose areas, mouth areas, eyes areas, nose to mouth areas, nose to eyes areas and mouth to eyes areas. To obtain more convincing results, our experiments are conducted on three different databases: facial expression recognition + ( FER+), real-world affective faces database (RAF-DB) and expression in-the-wild (ExpW) dataset. Through analysis of the classification accuracy, the confusion matrix and the class activation map (CAM), we can establish convincing results. To sum up, the contributions of this paper lie in two areas: 1) We visualize concerned areas of human faces in emotion recognition; 2) We analyze the contribution of different face areas to different emotions in real-world conditions through experimental analysis. Our findings can be combined with findings in psychology to promote the understanding of emotional expressions.
Control of a Two-wheeled Machine with Two-directions Handling Mechanism Using PID and PD-FLC Algorithms
Khaled M. Goher, Sulaiman O. Fadlallah
Available online   doi: 10.1007/s11633-019-1172-0
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This paper presents a novel five degrees of freedom (DOF) two-wheeled robotic machine (TWRM) that delivers solutions for both industrial and service robotic applications by enlarging the vehicle′s workspace and increasing its flexibility. Designing a two-wheeled robot with five degrees of freedom creates a high challenge for the control, therefore the modelling and design of such robot should be precise with a uniform distribution of mass over the robot and the actuators. By employing the Lagrangian modelling approach, the TWRM′s mathematical model is derived and simulated in Matlab/Simulink®. For stabilizing the system′s highly nonlinear model, two control approaches were developed and implemented: proportional-integral-derivative (PID) and fuzzy logic control (FLC) strategies. Considering multiple scenarios with different initial conditions, the proposed control strategies′ performance has been assessed.
An Efficient Adaptive Hierarchical Sliding Mode Control Strategy Using Neural Networks for 3D Overhead Cranes
Viet-Anh Le, Hai-Xuan Le, Linh Nguyen, Minh-Xuan Phan
Available online   doi: 10.1007/s11633-019-1174-y
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In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfaces represented by two actuated and un-actuated subsystems in the bridge crane. Parameters of the controller are then intelligently estimated, where uncertain parameters due to disturbances in the 3D overhead crane dynamic model are proposed to be represented by radial basis function networks whose weights are derived from a Lyapunov function. The proposed approach allows the crane system to be robust under uncertainty conditions in which some uncertain and unknown parameters are highly difficult to determine. Moreover, stability of the sliding surfaces is proved to be guaranteed. Effectiveness of the proposed approach is then demonstrated by implementing the algorithm in both synthetic and real-life systems, where the results obtained by our method are highly promising.
Image Encryption Application of Chaotic Sequences Incorporating Quantum Keys
Bin Ge, Hai-Bo Luo
Available online   doi: 10.1007/s11633-019-1173-z
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This paper proposes an image encryption algorithm LQBPNN (logistic quantum and back propagation neural network) based on chaotic sequences incorporating quantum keys. Firstly, the improved one-dimensional logistic chaotic sequence is used as the basic key sequence. After the quantum key is introduced, the quantum key is incorporated into the chaotic sequence by nonlinear operation. Then the pixel confused process is completed by the neural network. Finally, two sets of different mixed secret key sequences are used to perform two rounds of diffusion encryption on the confusing image. The experimental results show that the randomness and uniformity of the key sequence are effectively enhanced. The algorithm has a secret key space greater than 2182. The adjacent pixel correlation of the encrypted image is close to 0, and the information entropy is close to 8. The ciphertext image can resist several common attacks such as typical attacks, statistical analysis attacks and differential attacks.
Pedestrian Height Estimation and 3D Reconstruction Using Pixel-resolution Mapping Method Without Special Patterns
Bing-Xing Wu, Suat Utku Ay, Ahmed Abdel-Rahim
Available online   doi: 10.1007/s11633-019-1170-2
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Extracting the three-dimensional (3D) information including location and height of a pedestrian is important for vision-based intelligent traffic monitoring systems. This paper tackles the relationship between pixels′ actual size and pixels′ spatial resolution through a new method named pixel-resolution mapping (P-RM). The proposed P-RM method derives the equations for pixels′ spatial resolutions (XY-direction) and object′s height (Z-direction) in the real world, while introducing new tilt angle and mounting height calibration methods that do not require special calibration patterns placed in the real world. Both controlled laboratory and actual world experiments were performed and reported. The tests on 3D mensuration using proposed P-RM method showed overall better than 98.7% accuracy in laboratory environments and better than 96% accuracy in real world pedestrian height estimations. The 3D reconstructed images for measured points were also determined with the proposed P-RM method which shows that the proposed method provides a general algorithm for 3D information extraction.
Robust Disturbance Rejection based Control with Extended-state Resonant Observer for Sway Reduction in Uncertain Tower-Cranes
Horacio Coral-Enriquez, Santiago Pulido-Guerrero, John Cortés-Romero
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In this paper, the problem of load transportation and robust mitigation of payload oscillations in uncertain tower-cranes is addressed. This problem is tackled through a control scheme based on the philosophy of Active-Disturbance-Rejection. Here, a general disturbance model built with two dominant components: polynomial and harmonic, is stated. Then, a disturbance observer is formulated through state-vector augmentation of the tower-crane model. Thus, better performance of estimations for system states and disturbances is achieved. The control law is then formulated to actively reject the disturbances but also to accommodate the closed-loop system dynamics even under system uncertainty. The proposed control schema is validated via experimentation using a small-scale tower-crane, and compared with other relevant ADRC-based techniques. The experimental results show that the proposed control scheme is robust under parametric uncertainty of the system, and provides improved attenuation of payload oscillations even under system uncertainty.
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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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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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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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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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.
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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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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Research Article
A Fault Tolerant Control Scheme Using the Feasible Constrained Control Allocation Strategy
Mehdi Naderi, Tor Arne Johansen, Ali Khaki Sedigh
Available online   doi: 10.1007/s11633-019-1168-9
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This paper investigates the necessity of feasibility considerations in a fault tolerant control system using the constrained control allocation methodology where both static and dynamic actuator constraints are considered. In the proposed feasible control allocation scheme, the constrained model predictive control (MPC) is employed as the main controller. This considers the admissible region of the control allocation problem as its constraints. Using the feasibility notion in the control allocation problem provides the main controller with information regarding the actuator′s status, which leads to closed loop system performance improvement. Several simulation examples under normal and faulty conditions are employed to illustrate the effectiveness of the proposed methodology. The main results clearly indicate that closed loop performance and stability characteristics can be significantly degraded by neglecting the actuator constraints in the main controller. Also, it is shown that the proposed strategy substantially enlarges the domain of attraction of the MPC combined with the control allocation as compared to the conventional MPC.
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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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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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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Current Issue

2019 Vol.16 No.3

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
Global Visitors