The Experts below are selected from a list of 8013 Experts worldwide ranked by ideXlab platform
Wen-nung Lie - One of the best experts on this subject based on the ideXlab platform.
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A Framework of Enhancing Image Steganography With Picture Quality Optimization and Anti-Steganalysis Based on Simulated Annealing Algorithm
IEEE Transactions on Multimedia, 2010Co-Authors: Guo-shiang Lin, Yi-ting Chang, Wen-nung LieAbstract:Picture quality and statistical undetectability are two key issues related to steganography techniques. In this paper, we propose a closed-loop computing framework that iteratively searches Proper modifications of pixels/coefficients to enhance a base steganographic scheme with optimized picture quality and higher anti-steganalysis capability. To achieve this goal, an anti-steganalysis tester and an embedding controller-based on the simulated annealing (SA) algorithm with a Proper Cost Function-are incorporated into the processing loop to conduct the convergence of searches. The Cost Function integrates several performance indices, namely, the mean square error, the human visual system (HVS) deviation, and the differences in statistical features, and guides a Proper direction of searches during SA optimization. Our proposed framework is suitable for the kind of steganographic schemes that spreads each message information into multiple pixels/coefficients. We have selected two base steganographic schemes for implementation to show the applicability of the proposed framework. Experiment results show that the base schemes can be enhanced with better performances in image PSNR (by more than 5.0 dB), file-size variation, and anti-steganalysis pass-rate (by about 10% ~ 86%, at middle to high embedding capacities).
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A Framework of Enhancing Image Steganography With Picture Quality Optimization and Anti-Steganalysis Based on Simulated
2010Co-Authors: Guo-shiang Lin, Yi-ting Chang, Wen-nung LieAbstract:Picture quality and statistical undetectability are two key issues related to steganography techniques. In this paper, we propose a closed-loop computing framework that iteratively searches Proper modifications of pixels/coefficients to enhance a base steganographic scheme with optimized picture quality and higher anti-steganalysis capability. To achieve this goal, an anti-steganalysis tester and an embedding controller—based on the simulated annealing (SA) algorithm with a Proper Cost Function—are incorporated into the processing loop to conduct the convergence of searches. The Cost Function integrates several performance indices, namely, the mean square error, the human visual system (HVS) deviation, and the differences in statistical features, and guides a Proper direction of searches during SA optimization. Our proposed framework is suitable for the kind of steganographic schemes that spreads each message informa- tion into multiple pixels/coefficients. We have selected two base steganographic schemes for implementation to show the appli- cability of the proposed framework. Experiment results show that the base schemes can be enhanced with better performances in image PSNR (by more than 5.0 dB), file-size variation, and anti-steganalysis pass-rate (by about 10% 86%, at middle to high embedding capacities).
S. Ali A. Moosavian - One of the best experts on this subject based on the ideXlab platform.
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Optimal formation and control of cooperative wheeled mobile robots
Comptes Rendus Mécanique, 2015Co-Authors: Adel Abbaspour, Khalil Alipour, Hadi Zare Jafari, S. Ali A. MoosavianAbstract:Abstract In this paper, the optimal formation of a team of wheeled robot is dealt with for manipulating a common object. The robotic team has been commanded to transport the object from an initial pose along a specified path to a terminal pose. To this end, a Proper Cost Function encompassing various aspects will be established and the grasping points of the object will be then determined employing various numerical optimization techniques such as Simulated Annealing, Genetic Algorithm and Particle Swarm Optimization. Finally, the team is controlled using a virtual structure-based approach and multiple-impedance-control strategy so as the obtained optimal formation can be realized.
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ICRA - Point-to-point stable motion planning of wheeled mobile robots with multiple arms for heavy object manipulation
2011 IEEE International Conference on Robotics and Automation, 2011Co-Authors: Khalil Alipour, S. Ali A. MoosavianAbstract:Heavy object manipulation by wheeled mobile manipulators may lead to serious consequences such as postural instability, and this necessitates dynamically stable planning based on systematic analysis to better predict and eliminate the possibility of toppling down. In the present study, stable motion planning is investigated for wheeled mobile manipulators during heavy object manipulation tasks. It is assumed that the initial and final poses of a heavy payload are specified. Based on these known postures of the payload two Proper configurations for robotic system is defined. Then, between these two initial and final poses, appropriate trajectories for multiple robotic arms relative to the moving base are planned without considering the postural stability of the system. Next, motion of the moving base is planned so that the stability of the overall system is guaranteed while its predetermined initial and final positions and velocities are fulfilled. To this end, the problem of stable planning is solved as an optimization problem. A Proper Cost Function is considered, to be minimized, which is a measure of the control effort to be used for the platform motion. Moreover, using the new dynamic postural Moment-Height Stability (MHS) measure, a constraint denoting the system dynamic stability is derived and satisfied. The proposed planning approach is applied to move a heavy object with a wheeled robotic system that consists of two manipulators, where the obtained results reveal a stable optimal motion besides satisfaction of various practical aspects.
Javier Cuadrado - One of the best experts on this subject based on the ideXlab platform.
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A fair and EMG-validated comparison of recruitment criteria, musculotendon models and muscle coordination strategies, for the inverse-dynamics based optimization of muscle forces during gait
Journal of NeuroEngineering and Rehabilitation, 2021Co-Authors: Florian Michaud, Mario Lamas, Urbano Lugrís, Javier CuadradoAbstract:Experimental studies and EMG collections suggest that a specific strategy of muscle coordination is chosen by the central nervous system to perform a given motor task. A popular mathematical approach for solving the muscle recruitment problem is optimization. Optimization-based methods minimize or maximize some criterion (objective Function or Cost Function) which reflects the mechanism used by the central nervous system to recruit muscles for the movement considered. The Proper Cost Function is not known a priori, so the adequacy of the chosen Function must be validated according to the obtained results. In addition of the many criteria proposed, several physiological representations of the musculotendon actuator dynamics (that prescribe constraints for the forces) along with different musculoskeletal models can be found in the literature, which hinders the selection of the best neuromusculotendon model for each application. Seeking to provide a fair base for comparison, this study measures the efficiency and accuracy of: (i) four different criteria within the static optimization approach (where the physiological character of the muscle, which affects the constraints of the forces, is not considered); (ii) three physiological representations of the musculotendon actuator dynamics: activation dynamics with elastic tendon, simplified activation dynamics with rigid tendon and rigid tendon without activation dynamics; (iii) a synergy-based method; all of them within the framework of inverse-dynamics based optimization. Motion/force/EMG gait analyses were performed on ten healthy subjects. A musculoskeletal model of the right leg actuated by 43 Hill-type muscles was scaled to each subject and used to calculate joint moments, musculotendon kinematics and moment arms. Muscle activations were then estimated using the different approaches, and these estimates were compared with EMG measurements. Although no significant differences were obtained with all the methods at statistical level, it must be pointed out that a higher complexity of the method does not guarantee better results, as the best correlations with experimental values were obtained with two simplified approaches: the static optimization and the physiological approach with simplified activation dynamics and rigid tendon, both using the sum of the squares of muscle forces as objective Function.
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A Fair and EMG-validated Comparison of Recruitment Criteria, Musculotendon Models and Muscle Coordination Strategies, for the Inverse-dynamics Based Optimization of Muscle Forces During Gait
2020Co-Authors: Florian Michaud, Mario Lamas, Urbano Lugrís, Javier CuadradoAbstract:Abstract Experimental studies and EMG collections suggest that a specific strategy of muscle coordination is chosen by the central nervous system to perform a given motor task. A popular mathematical approach for solving the muscle recruitment problem is optimization. Optimization-based methods minimize or maximize some criterion (objective Function or Cost Function) which reflects the mechanism used by the central nervous system to recruit muscles for the movement considered. The Proper Cost Function is not known a priori, so the adequacy of the chosen Function must be validated according to the obtained results. In addition of the many criteria proposed, several physiological representations of the musculotendon actuator dynamics along with different musculoskeletal models can be found in the literature, which hinders the selection of the best neuromusculotendon model for each application. Seeking to provide a fair base for comparison, this study measures the efficiency and accuracy of: i) four different criteria; ii) one static and three physiological representations of the musculotendon actuator dynamics; iii) a synergy-based method; all of them within the framework of inverse-dynamics based optimization. Motion/force/EMG gait analyses were performed on ten healthy subjects. A musculoskeletal model of the right leg actuated by 43 Hill-type muscles was scaled to each subject and used to calculate joint moments, musculotendon kinematics and moment arms. Muscle activations were then estimated using the different approaches, and these estimates were compared with EMG measurements. Although similar results were obtained with all the methods, it must be pointed out that a higher complexity of the method does not guarantee better results, as the best correlations with experimental values were obtained with two simplified approaches.
Guo-shiang Lin - One of the best experts on this subject based on the ideXlab platform.
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A Framework of Enhancing Image Steganography With Picture Quality Optimization and Anti-Steganalysis Based on Simulated Annealing Algorithm
IEEE Transactions on Multimedia, 2010Co-Authors: Guo-shiang Lin, Yi-ting Chang, Wen-nung LieAbstract:Picture quality and statistical undetectability are two key issues related to steganography techniques. In this paper, we propose a closed-loop computing framework that iteratively searches Proper modifications of pixels/coefficients to enhance a base steganographic scheme with optimized picture quality and higher anti-steganalysis capability. To achieve this goal, an anti-steganalysis tester and an embedding controller-based on the simulated annealing (SA) algorithm with a Proper Cost Function-are incorporated into the processing loop to conduct the convergence of searches. The Cost Function integrates several performance indices, namely, the mean square error, the human visual system (HVS) deviation, and the differences in statistical features, and guides a Proper direction of searches during SA optimization. Our proposed framework is suitable for the kind of steganographic schemes that spreads each message information into multiple pixels/coefficients. We have selected two base steganographic schemes for implementation to show the applicability of the proposed framework. Experiment results show that the base schemes can be enhanced with better performances in image PSNR (by more than 5.0 dB), file-size variation, and anti-steganalysis pass-rate (by about 10% ~ 86%, at middle to high embedding capacities).
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A Framework of Enhancing Image Steganography With Picture Quality Optimization and Anti-Steganalysis Based on Simulated
2010Co-Authors: Guo-shiang Lin, Yi-ting Chang, Wen-nung LieAbstract:Picture quality and statistical undetectability are two key issues related to steganography techniques. In this paper, we propose a closed-loop computing framework that iteratively searches Proper modifications of pixels/coefficients to enhance a base steganographic scheme with optimized picture quality and higher anti-steganalysis capability. To achieve this goal, an anti-steganalysis tester and an embedding controller—based on the simulated annealing (SA) algorithm with a Proper Cost Function—are incorporated into the processing loop to conduct the convergence of searches. The Cost Function integrates several performance indices, namely, the mean square error, the human visual system (HVS) deviation, and the differences in statistical features, and guides a Proper direction of searches during SA optimization. Our proposed framework is suitable for the kind of steganographic schemes that spreads each message informa- tion into multiple pixels/coefficients. We have selected two base steganographic schemes for implementation to show the appli- cability of the proposed framework. Experiment results show that the base schemes can be enhanced with better performances in image PSNR (by more than 5.0 dB), file-size variation, and anti-steganalysis pass-rate (by about 10% 86%, at middle to high embedding capacities).
Gang Feng - One of the best experts on this subject based on the ideXlab platform.
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Distributed path optimisation of mobile sensor networks for AOA target localisation
IET Control Theory & Applications, 2019Co-Authors: Ziwen Yang, Shanying Zhu, Cailian Chen, Xinping Guan, Gang FengAbstract:The path optimisation problem of mobile sensor networks for arrival-of-angle (AOA) target localisation, using the consensus-based extended information filter is considered, in this study. A new idea of equipping sensors with information-driven mobility to improve the estimation accuracy with respect to a stationary target is proposed by the authors. A gradient descent method is used for mobile sensors, which are subject to geometric constraints, to choose the next optimal waypoints. The corresponding optimisation problem is solved in a distributed manner, by selecting a Proper Cost Function for each mobile sensor. It is shown that the boundedness of the estimation error is guaranteed. Moreover, they find that the mobility of sensors does decrease the estimation error bounds compared with the static sensor networks, which is beneficial for the localisation performance. Simulation is carried out to show the effectiveness of the proposed method.
