The Experts below are selected from a list of 17415 Experts worldwide ranked by ideXlab platform

T. P. Andriacchi - One of the best experts on this subject based on the ideXlab platform.

  • A Markerless Motion Capture System to Study Musculoskeletal Biomechanics: Visual Hull and Simulated Annealing Approach
    Annals of Biomedical Engineering, 2006
    Co-Authors: S. Corazza, L. Mündermann, A. M. Chaudhari, T. Demattio, C. Cobelli, T. P. Andriacchi
    Abstract:

    Human motion capture is frequently used to study musculoskeletal biomechanics and clinical problems, as well as to provide realistic animation for the entertainment industry. The most popular technique for human motion capture uses markers placed on the skin, despite some important drawbacks including the impediment to the motion by the presence of skin markers and relative movement between the skin where the markers are placed and the underlying bone. The latter makes it difficult to estimate the motion of the underlying bone, which is the variable of interest for biomechanical and clinical applications. A model-based markerless motion capture system is presented in this study, which does not require the placement of any markers on the subject's body. The described method is based on visual hull reconstruction and an a priori model of the subject. A custom version of adapted fast Simulated Annealing has been developed to match the model to the visual hull. The tracking capability and a quantitative validation of the method were evaluated in a virtual environment for a complete gait cycle. The obtained mean errors, for an entire gait cycle, for knee and hip flexion are respectively 1.5° (±3.9°) and 2.0° (±3.0°), while for knee and hip adduction they are respectively 2.0° (±2.3°) and 1.1° (±1.7°). Results for the ankle and shoulder joints are also presented. Experimental results captured in a gait laboratory with a real subject are also shown to demonstrate the effectiveness and potential of the presented method in a clinical environment.

  • a markerless motion capture system to study musculoskeletal biomechanics visual hull and Simulated Annealing Approach
    Annals of Biomedical Engineering, 2006
    Co-Authors: S. Corazza, L. Mündermann, A. M. Chaudhari, T. Demattio, C. Cobelli, T. P. Andriacchi
    Abstract:

    Human motion capture is frequently used to study musculoskeletal biomechanics and clinical problems, as well as to provide realistic animation for the entertainment industry. The most popular technique for human motion capture uses markers placed on the skin, despite some important drawbacks including the impediment to the motion by the presence of skin markers and relative movement between the skin where the markers are placed and the underlying bone. The latter makes it difficult to estimate the motion of the underlying bone, which is the variable of interest for biomechanical and clinical applications. A model-based markerless motion capture system is presented in this study, which does not require the placement of any markers on the subject's body. The described method is based on visual hull reconstruction and an a priori model of the subject. A custom version of adapted fast Simulated Annealing has been developed to match the model to the visual hull. The tracking capability and a quantitative validation of the method were evaluated in a virtual environment for a complete gait cycle. The obtained mean errors, for an entire gait cycle, for knee and hip flexion are respectively 1.5 degrees (+/-3.9 degrees ) and 2.0 degrees (+/-3.0 degrees ), while for knee and hip adduction they are respectively 2.0 degrees (+/-2.3 degrees ) and 1.1 degrees (+/-1.7 degrees ). Results for the ankle and shoulder joints are also presented. Experimental results captured in a gait laboratory with a real subject are also shown to demonstrate the effectiveness and potential of the presented method in a clinical environment.

Chihhung Tsai - One of the best experts on this subject based on the ideXlab platform.

  • optimization of wire electrical discharge machining for pure tungsten using a neural network integrated Simulated Annealing Approach
    Expert Systems With Applications, 2010
    Co-Authors: Hsienching Chen, Jenchang Lin, Yungkuang Yang, Chihhung Tsai
    Abstract:

    This study analyzed variation of cutting velocity and workpiece surface finish depending on wire electrical discharge machining (WEDM) process parameters during manufacture of pure tungsten profiles. A method integrating back-propagation neural network (BPNN) and Simulated Annealing algorithm (SAA) is proposed to determine an optimal parameter setting of the WEDM process. The specimens are prepared under different WEDM process conditions based on a Taguchi orthogonal array table. The results of 18 experimental runs were utilized to train the BPNN predicting the cutting velocity, roughness average (Ra), and roughness maximum (Rt) properties at various WEDM process conditions and then the SAA Approaches was applied to search for an optimal setting. In addition, the analysis of variance (ANOVA) was implemented to identify significant factors for the WEDM process and the proposed algorithm was also compared with respect to the confirmation experiments. The results of proposed algorithm and confirmation experiments are show that the BPNN/SAA method is effective tool for the optimization of WEDM process parameters.

  • optimization of wire electrical discharge machining for pure tungsten using a neural network integrated Simulated Annealing Approach
    Expert Systems With Applications, 2010
    Co-Authors: Hsienching Chen, Yungkuang Yang, Chihhung Tsai
    Abstract:

    This study analyzed variation of cutting velocity and workpiece surface finish depending on wire electrical discharge machining (WEDM) process parameters during manufacture of pure tungsten profiles. A method integrating back-propagation neural network (BPNN) and Simulated Annealing algorithm (SAA) is proposed to determine an optimal parameter setting of the WEDM process. The specimens are prepared under different WEDM process conditions based on a Taguchi orthogonal array table. The results of 18 experimental runs were utilized to train the BPNN predicting the cutting velocity, roughness average (Ra), and roughness maximum (Rt) properties at various WEDM process conditions and then the SAA Approaches was applied to search for an optimal setting. In addition, the analysis of variance (ANOVA) was implemented to identify significant factors for the WEDM process and the proposed algorithm was also compared with respect to the confirmation experiments. The results of proposed algorithm and confirmation experiments are show that the BPNN/SAA method is effective tool for the optimization of WEDM process parameters.

S. Corazza - One of the best experts on this subject based on the ideXlab platform.

  • A Markerless Motion Capture System to Study Musculoskeletal Biomechanics: Visual Hull and Simulated Annealing Approach
    Annals of Biomedical Engineering, 2006
    Co-Authors: S. Corazza, L. Mündermann, A. M. Chaudhari, T. Demattio, C. Cobelli, T. P. Andriacchi
    Abstract:

    Human motion capture is frequently used to study musculoskeletal biomechanics and clinical problems, as well as to provide realistic animation for the entertainment industry. The most popular technique for human motion capture uses markers placed on the skin, despite some important drawbacks including the impediment to the motion by the presence of skin markers and relative movement between the skin where the markers are placed and the underlying bone. The latter makes it difficult to estimate the motion of the underlying bone, which is the variable of interest for biomechanical and clinical applications. A model-based markerless motion capture system is presented in this study, which does not require the placement of any markers on the subject's body. The described method is based on visual hull reconstruction and an a priori model of the subject. A custom version of adapted fast Simulated Annealing has been developed to match the model to the visual hull. The tracking capability and a quantitative validation of the method were evaluated in a virtual environment for a complete gait cycle. The obtained mean errors, for an entire gait cycle, for knee and hip flexion are respectively 1.5° (±3.9°) and 2.0° (±3.0°), while for knee and hip adduction they are respectively 2.0° (±2.3°) and 1.1° (±1.7°). Results for the ankle and shoulder joints are also presented. Experimental results captured in a gait laboratory with a real subject are also shown to demonstrate the effectiveness and potential of the presented method in a clinical environment.

  • a markerless motion capture system to study musculoskeletal biomechanics visual hull and Simulated Annealing Approach
    Annals of Biomedical Engineering, 2006
    Co-Authors: S. Corazza, L. Mündermann, A. M. Chaudhari, T. Demattio, C. Cobelli, T. P. Andriacchi
    Abstract:

    Human motion capture is frequently used to study musculoskeletal biomechanics and clinical problems, as well as to provide realistic animation for the entertainment industry. The most popular technique for human motion capture uses markers placed on the skin, despite some important drawbacks including the impediment to the motion by the presence of skin markers and relative movement between the skin where the markers are placed and the underlying bone. The latter makes it difficult to estimate the motion of the underlying bone, which is the variable of interest for biomechanical and clinical applications. A model-based markerless motion capture system is presented in this study, which does not require the placement of any markers on the subject's body. The described method is based on visual hull reconstruction and an a priori model of the subject. A custom version of adapted fast Simulated Annealing has been developed to match the model to the visual hull. The tracking capability and a quantitative validation of the method were evaluated in a virtual environment for a complete gait cycle. The obtained mean errors, for an entire gait cycle, for knee and hip flexion are respectively 1.5 degrees (+/-3.9 degrees ) and 2.0 degrees (+/-3.0 degrees ), while for knee and hip adduction they are respectively 2.0 degrees (+/-2.3 degrees ) and 1.1 degrees (+/-1.7 degrees ). Results for the ankle and shoulder joints are also presented. Experimental results captured in a gait laboratory with a real subject are also shown to demonstrate the effectiveness and potential of the presented method in a clinical environment.

Sriparna Saha - One of the best experts on this subject based on the ideXlab platform.

  • Combining feature selection and classifier ensemble using a multiobjective Simulated Annealing Approach: application to named entity recognition
    Soft Computing, 2013
    Co-Authors: Asif Ekbal, Sriparna Saha
    Abstract:

    In this paper, we propose a two-stage multiobjective-Simulated Annealing (MOSA)-based technique for named entity recognition (NER). At first, MOSA is used for feature selection under two statistical classifiers, viz. conditional random field (CRF) and support vector machine (SVM). Each solution on the final Pareto optimal front provides a different classifier. These classifiers are then combined together by using a new classifier ensemble technique based on MOSA. Several different versions of the objective functions are exploited. We hypothesize that the reliability of prediction of each classifier differs among the various output classes. Thus, in an ensemble system, it is necessary to find out the appropriate weight of vote for each output class in each classifier. We propose a MOSA-based technique to determine the weights for votes automatically. The proposed two-stage technique is evaluated for NER in Bengali, a resource-poor language, as well as for English. Evaluation results yield the highest recall, precision and F -measure values of 93.95, 95.15 and 94.55 %, respectively for Bengali and 89.01, 89.35 and 89.18 %, respectively for English. Experiments also suggest that the classifier ensemble identified by the proposed MOO-based Approach optimizing the F -measure values of named entity (NE) boundary detection outperforms all the individual classifiers and four conventional baseline models.

  • a multiobjective Simulated Annealing Approach for classifier ensemble named entity recognition in indian languages as case studies
    Expert Systems With Applications, 2011
    Co-Authors: Asif Ekbal, Sriparna Saha
    Abstract:

    In this paper, we propose a Simulated Annealing (SA) based multiobjective optimization (MOO) Approach for classifier ensemble. Several different versions of the objective functions are exploited. We hypothesize that the reliability of prediction of each classifier differs among the various output classes. Thus, in an ensemble system, it is necessary to find out the appropriate weight of vote for each output class in each classifier. Diverse classification methods such as Maximum Entropy (ME), Conditional Random Field (CRF) and Support Vector Machine (SVM) are used to build different models depending upon the various representations of the available features. One most important characteristics of our system is that the features are selected and developed mostly without using any deep domain knowledge and/or language dependent resources. The proposed technique is evaluated for Named Entity Recognition (NER) in three resource-poor Indian languages, namely Bengali, Hindi and Telugu. Evaluation results yield the recall, precision and F-measure values of 93.95%, 95.15% and 94.55%, respectively for Bengali, 93.35%, 92.25% and 92.80%, respectively for Hindi and 84.02%, 96.56% and 89.85%, respectively for Telugu. Experiments also suggest that the classifier ensemble identified by the proposed MOO based Approach optimizing the F-measure values of named entity (NE) boundary detection outperforms all the individual models, two conventional baseline models and three other MOO based ensembles.

Daniel Delahaye - One of the best experts on this subject based on the ideXlab platform.

  • A Simulated Annealing Approach to 3D Strategic Aircraft Deconfliction based on En-Route Speed Changes under Wind and Temperature Uncertainties
    Transportation research. Part C Emerging technologies, 2019
    Co-Authors: Valentin Courchelle, Manuel Soler, Daniel González-arribas, Daniel Delahaye
    Abstract:

    We tackle the problem of minimizing the number of aircraft potential conflicts via speed regulations and taking into account uncertainties on aircraft position due to wind and temperature. The resolution is done at a strategic level, before any of the aircraft has departed. Owing to the complexity of this kind of optimisation problem, a Simulated Annealing metaheuristic Approach is employed. A scenario with four hours of traffic overflying the Spanish (structured, continental) airspace has been selected. Inputted traffic provides routes, Mach profiles (considered to be constant), and altitude profiles as in their flight plans. Probabilistic weather forecasts from an Ensemble Prediction System are employed. Solutions provide constant speed profiles that slightly differ from those in the flight plans. It is shown that the number of conflicts can be significantly reduced by slightly modifying flight plan speeds while not altering the routes, nor the altitudes, both selected by the airspace user. The impact of this resolution strategy in flight efficiency is also analyzed.