Journal articles on the topic 'Motion Capture Analysis Optimization'
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JOÃO, FILIPA, ANTÓNIO VELOSO, SANDRA AMADO, PAULO ARMADA-DA-SILVA, and ANA C. MAURÍCIO. "CAN GLOBAL OPTIMIZATION TECHNIQUE COMPENSATE FOR MARKER SKIN MOVEMENT IN RAT KINEMATICS?" Journal of Mechanics in Medicine and Biology 14, no. 05 (August 2014): 1450065. http://dx.doi.org/10.1142/s0219519414500651.
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The motion of the skeletal estimated from skin attached marker-based motion capture(MOCAP) systems is known to be affected by significant bias caused by anatomical landmarks mislocation but especially by soft tissue artifacts (such as skin deformation and sliding, inertial effects and muscle contraction). As a consequence, the error associated with this bias can propagate to joint kinematics and kinetics data, particularly in small rodents. The purpose of this study was to perform a segmental kinematic analysis of the rat hindlimb during locomotion, using both global optimization as well as segmental optimization methods. Eight rats were evaluated for natural overground walking and motion of the right hindlimb was captured with an optoeletronic system while the animals walked in the track. Three-dimensional (3D) biomechanical analyses were carried out and hip, knee and ankle joint angular displacements and velocities were calculated. Comparison between both methods demonstrated that the magnitude of the kinematic error due to skin movement increases in the segmental optimization when compared with the global optimization method. The kinematic results assessed with the global optimization method matches more closely to the joint angles and ranges of motion calculated from bone-derived kinematics, being the knee and hip joints with more significant differences.
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Ferryanto, F., Andi Isra Mahyuddin, and Motomu Nakashima. "DEVELOPMENT OF A MARKERLESS OPTICAL MOTION CAPTURE SYSTEM BY AN ACTION SPORTS CAMERA FOR RUNNING MOTION." ASEAN Engineering Journal 12, no. 2 (June 1, 2022): 37–44. http://dx.doi.org/10.11113/aej.v12.16760.
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A marker-based optical motion capture system is often used to obtain the kinematics parameters of a running analysis. However, the attached marker could affect the participant's movement, and the system is costly because of the exclusive cameras. Due to its drawbacks, the present research aimed to develop an affordable markerless optical motion capture system for running motion. The proposed system used an action sports camera to acquire the running images of the participant. The images were segmented to get the silhouette of the participant. Then, a human body model was generated to provide a priori information to track participants' segment position. The subsequent procedure was image registration to estimate the pose of the participant's silhouette. The transformation parameters were estimated by particle swarm optimization. The optimization output in the form of the rotation angle of the body segment was then employed to identify right or left lower limbs. To validate the results of the optimization, a manual matching was conducted to obtain the actual rotation angle for all body segments. The correlation coefficient between the rotation angle from image registration and the actual rotation angle was then evaluated. It was found that the lowest correlation coefficient was 0.977 for the left foot. It implies that the accuracy of the developed system in the present work is acceptable. Furthermore, the results of the kinematics analysis have good agreement with the literature. Therefore, the developed system, not only yields acceptable running parameters, but also affordable since it uses an action sports camera and easy to use.
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Ping, An, Jian Wang, Ruofan Xiao, Renying Liu, Yanan Chang, and Qingmin Li. "Trap Parameters Optimization Based on Metal Particle Dynamic Simulation Method." Symmetry 14, no. 6 (June 9, 2022): 1187. http://dx.doi.org/10.3390/sym14061187.
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Insulation failure usually occurs in AC gas-insulated transmission (AC GIL) in field operation, in which the primary cause is the charged motion of metal particles in the electric filed. At present, the particle inhibition method applied is to design particle traps on the inner wall of the GIL shell. However, due to the large randomness of the charged motion for metallic particles and the limitations of field test methods, a particle trap has not yet been designed from the perspective of particle trapping effectiveness. In this paper, firstly, referring to the size of a running 252 kV AC GIL, a 1:1 scaled 3-D similarity simulation model is established to obtain the dynamic characteristics of particles with different sizes under the operating voltage level. This model can form symmetry between the real equipment, and its simulated simulation trajectory can achieve symmetry with the actual one. Secondly, an experimental platform that can easily capture the motion of the particles is set up to experimentally verify the symmetry between the field operating equipment and the simulation model. Finally, the particle traps are set on both sides of the concave and convex surface of the basin insulator, and an optimization scheme for the design of the particle trap is proposed from three aspects: the electric field regulation of the trap, the captured probability of particles, and the trap location. The proposed research shows that, with respect to the motion characteristics of the particles, this paper selects circular hole-shaped trap and its thickness, slot spacing, and slot width are 10 mm, 6 mm, and 8 mm, respectively. When the traps are arranged, one at the bottom of the shell at 70 mm and 80 mm from each side of the concave and convex insulator, the capture probability of the traps on both sides can be as high as 78% and 70%, respectively. Therefore, the analysis and optimization method in this paper has important reference value according to similarity concepts for optimizing particle traps in AC GIL at a certain voltage level.
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Chen, Peng, Ping Jun Xia, Yue Dong Lang, and Ying Xue Yao. "A Human-Centered Virtual Assembly System." Applied Mechanics and Materials 16-19 (October 2009): 796–800. http://dx.doi.org/10.4028/www.scientific.net/amm.16-19.796.
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Virtual manufacturing technology has become an effective method for decision and planning in manufacturing. Due to ergonomics problems are widely concerned in assembly design planning, a human-centered virtual assembly system framework is proposed for ergonomics analysis for assembly operation in this paper. The six-layer framework integrates virtual human modeling, motion capture and recognition, ergonomics evaluation and virtual assembly process planning as an organic whole. Data exchanging and system function are discussed based on this framework. The work in virtual reality (VR) technology, motion capture technology, ergonomics method and optimization method for implementing the system is also described. The framework would provide a new approach for the combination of virtual manufacturing and ergonomics analysis in the future.
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Wang, Yong, Jing Cao, Nan Ye, Shouming Sun, Junfeng Li, and Zhenyong Bo. "Cooperative capture trajectory optimization of multi-space robots using an improved multi-objective fruit fly algorithm." Open Astronomy 31, no. 1 (January 1, 2022): 405–16. http://dx.doi.org/10.1515/astro-2022-0198.
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Abstract Considering that some tasks will require the consistency of the position and attitude of the end-effector, multi-space-robot cooperative capture also needs to consider the synchronization of the two capture arms. Taking the dual-space robots as example, the trajectory planning problem before cooperative capture is focused. First, a drive-transform method based on trapezoidal velocity interpolation is proposed, which combines the advantages of these two methods to obtain the SE(3) motion trajectory, in which the attitude and position are planned synchronously. Then, the trajectory optimization model of cooperative capture is established, which takes the optimal time and the minimum attitude disturbance of the base as the optimization goals, and simultaneously satisfies that the two capture arms reach the capture point synchronously. In order to solve this multi-objective optimization problem, a dual-population multi-objective fruit fly algorithm based on non-dominated sorting was proposed. Finally, the simulation example of dual-space robots shows that the proposed algorithm is effective, and the analysis of the optimal solution set demonstrates that the optimized cooperative capture trajectory is smooth and synchronous.
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Li, Shun, Liqing Cui, Changye Zhu, Baobin Li, Nan Zhao, and Tingshao Zhu. "Emotion recognition using Kinect motion capture data of human gaits." PeerJ 4 (September 15, 2016): e2364. http://dx.doi.org/10.7717/peerj.2364.
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Automatic emotion recognition is of great value in many applications, however, to fully display the application value of emotion recognition, more portable, non-intrusive, inexpensive technologies need to be developed. Human gaits could reflect the walker’s emotional state, and could be an information source for emotion recognition. This paper proposed a novel method to recognize emotional state through human gaits by using Microsoft Kinect, a low-cost, portable, camera-based sensor. Fifty-nine participants’ gaits under neutral state, induced anger and induced happiness were recorded by two Kinect cameras, and the original data were processed through joint selection, coordinate system transformation, sliding window gauss filtering, differential operation, and data segmentation. Features of gait patterns were extracted from 3-dimentional coordinates of 14 main body joints by Fourier transformation and Principal Component Analysis (PCA). The classifiers NaiveBayes, RandomForests, LibSVM and SMO (Sequential Minimal Optimization) were trained and evaluated, and the accuracy of recognizing anger and happiness from neutral state achieved 80.5% and 75.4%. Although the results of distinguishing angry and happiness states were not ideal in current study, it showed the feasibility of automatically recognizing emotional states from gaits, with the characteristics meeting the application requirements.
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Simonetto, Enrico, Andrea Ghiotti, and Stefania Bruschi. "Feasibility of Motion-Capture Techniques Applied to Tube Bending." Key Engineering Materials 651-653 (July 2015): 1128–33. http://dx.doi.org/10.4028/www.scientific.net/kem.651-653.1128.
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Tube bending is one of the most relevant manufacturing processes for the production of structural elements, but it suffers from the problem of springback that requires the tuning of the process parameters at every launch of new production batches. Off-line optimization approaches can be found in literature, but they often require complex characterization of the material properties or the application of approaches based on numerical simulation analyses. So, the development of new and more flexible on-line approaches to measure and correct the springback is crucial especially for highly automated machines as for example the tube benders. The paper presents a new measurement approach, based on the application of motion-capture techniques, to provide real-time measurements of the bent tube orientation, in order to decrease the time for the set-up of the main process parameters. A new methodology as well as a new experimental apparatus for the in-line monitoring of the tube springback is presented, as well as the evaluation of its accuracy when applied to the industrial process. An Inertial Measurement Unit (IMU) is linked to the tube during bending and the measurements from three gyroscopes and three accelerometers are used to perform the computation of the tube orientation in the 3D space. The proposed approach appeared promising for the evaluation of the springback through the measurement of the final angular configuration reached after bending.
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Bao, Hongshu, and Xiang Yao. "Human Motion Data Retrieval Based on Staged Dynamic Time Deformation Optimization Algorithm." Complexity 2020 (December 14, 2020): 1–11. http://dx.doi.org/10.1155/2020/6650924.
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In recent years, with the rapid development of computer storage capabilities and network transmission capabilities, users can easily share their own video and image information on social networking sites, and the amount of multimedia data on the network is rapidly increasing. With the continuous increase of the amount of data in the network, the establishment of effective automated data management methods and search methods has become an increasingly urgent need. This paper proposes a retrieval method of human motion data based on motion capture in index space. By extracting key frames from the original motion to perform horizontal dimensionality reduction and defining features based on Laban motion analysis, the motion segment is subjected to vertical feature dimensionality reduction. After extracting features from the input motion segment, motion matching is performed on the index space. This paper designs the optimization method of the phased dynamic time deformation algorithm in time efficiency and analyzes the optimization method of the phased dynamic time deformation algorithm in time complexity. Considering the time efficiency redundancy, this paper optimizes the time complexity of the phased dynamic time deformation method. This improves the time efficiency of the staged dynamic time warping algorithm, making it suitable for larger-scale human motion data problems. Experiments show that the method in this paper has the advantage of speed, is more in line with the semantics of human motion, and can meet the retrieval requirements of human motion databases.
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Sun, Chong, and Xiaolei Hou. "Passive impact/vibration control and isolation performance optimization for space noncooperative target capture." International Journal of Advanced Robotic Systems 17, no. 1 (January 1, 2020): 172988141989538. http://dx.doi.org/10.1177/1729881419895388.
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On-orbit capture is an important technique for the space debris removal, refueling, or malfunction satellite repairing. While due to the uncertainty of the motion parameters of the space noncooperative target, the impact between the capture device and the noncooperative target during the capturing process is inevitable, which may bring strong vibration perturbation to the base satellite, and potentially alter the position and the attitude of the servicing spacecraft, or even cause failure of on-orbit tasks. This article presents a new and alternative method for passive suppression of spacecraft impact and perturbation during noncooperative spacecraft capture. The passive device based on bioinspired X-shape is installed between the satellite and the capture device. In the capture process, nonlinear damping of the passive isolation structure can significantly reduce impact/vibration perturbation. For performance analysis, dynamic equations of the isolation system are established. Based on which, the relationship between structure parameters and isolation performance is systematically analyzed. Experiments are conducted for verification of the effectiveness of the proposed method. Moreover, an optimal process using the non-dominated sorting genetic algorithm II optimization method is developed to minimize impact/vibration perturbation effect, and optimal solutions can provide useful reference for the passive isolation system design.
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Iaboni, Craig, Deepan Lobo, Ji-Won Choi, and Pramod Abichandani. "Event-Based Motion Capture System for Online Multi-Quadrotor Localization and Tracking." Sensors 22, no. 9 (April 23, 2022): 3240. http://dx.doi.org/10.3390/s22093240.
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Motion capture systems are crucial in developing multi-quadrotor systems due to their ability to provide fast and accurate ground truth measurements for tracking and control. This paper presents the implementation details and experimental validation of a relatively low-cost motion-capture system for multi-quadrotor motion planning using an event camera. The real-time, multi-quadrotor detection and tracking tasks are performed using a deep learning network You-Only-Look-Once (YOLOv5) and a k-dimensional (k-d) tree, respectively. An optimization-based decentralized motion planning algorithm is implemented to demonstrate the effectiveness of this motion capture system. Extensive experimental evaluations were performed to (1) compare the performance of four deep-learning algorithms for high-speed multi-quadrotor detection on event-based data, (2) study precision, recall, and F1 scores as functions of lighting conditions and camera motion, and (3) investigate the scalability of this system as a function of the number of quadrotors flying in the arena. Comparative analysis of the deep learning algorithms on a consumer-grade GPU demonstrates a 4.8× to 12× sampling/inference rate advantage that YOLOv5 provides over representative one- and two-stage detectors and a 1.14× advantage over YOLOv4. In terms of precision and recall, YOLOv5 performed 15% to 18% and 27% to 41% better than representative state-of-the-art deep learning networks. Graceful detection and tracking performance degradation was observed in the face of progressively darker ambient light conditions. Despite severe camera motion, YOLOv5 precision and recall values of 94% and 98% were achieved, respectively. Finally, experiments involving up to six indoor quadrotors demonstrated the scalability of this approach. This paper also presents the first open-source event camera dataset in the literature, featuring over 10,000 fully annotated images of multiple quadrotors operating in indoor and outdoor environments.
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Sano, Mina. "Statistical Analysis of Elements of Movement in Musical Expression in Early Childhood Using 3D Motion Capture and Evaluation of Musical Development Degrees Through Machine Learning." World Journal of Education 8, no. 3 (June 25, 2018): 118. http://dx.doi.org/10.5430/wje.v8n3p118.
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This study aims to analyze the developmental characteristics of early childhood musical expressions from aviewpoint of movement elements, and to devise a method to evaluate the development regarding musical expressionin early childhood using machine learning. Previous studies regarding motion capture have shown analysis resultssuch as specific actions and responses to music (Burger et al, 2013). In this study, firstly, ANOVA was attempted onfull-body movements. The author quantitatively analyzed the motion capture data regarding 3-year-old, 4-year-old,and 5-year-old children in the nursery schools (n=84) and kindergartens (n=94) through a three-way non-repeatedANOVA. As a result, a statistically significant difference was observed in movement of body parts. Specifically, righthand movement such as moving distance and the moving average acceleration showed a significance of difference.Secondly, machine learning (decision trees, Sequential Minimum Optimization algorithm (SMO), Support VectorMachine (SVM) and neural network (multilayer perceptron)) was deployed to build classification models forevaluation of degree of musical development classified by educators with simultaneously recorded children’s videowith associated motion capture data. Among varieties of trained classification models, multilayer perceptron obtainedbest results of confusion matrix and showed fair classifying precision and usability to support educators to evaluatechildren’s achievement degree of musical development. As a result of the machine learning of multilayeredperceptron, the movement of the pelvis has a strong relationship with musical development degree. Its classificationaccuracy found consistent to affirm the availability to utilize the model to support educators to evaluate children’sattainment of musical expression.
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Yu, Na, Qing Wang, and Shichao Cao. "ROAD RECOGNITION TECHNOLOGY OF AGRICULTURAL NAVIGATION ROBOT BASED ON ROAD EDGE MOVEMENT OBSTACLE DETECTION ALGORITHM." INMATEH Vol.61 61, no. 2 (August 31, 2020): 281–92. http://dx.doi.org/10.35633/inmateh-61-31.
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In order to recognize the road effectively, agricultural robots mainly rely on the tracking and detection data of road obstacles. Traditional obstacle detection mainly studies how to use multiple fusion methods such as vision and laser to analyse structured and simplified indoor scenes. The working environment of agricultural robots is a typical unstructured outdoor environment. Therefore, based on the environmental characteristics of agricultural robot navigation, the mean displacement algorithm is introduced to detect and study the obstacles aiming at the road edge. After explaining the advantages and principle flow of the mean displacement algorithm to effectively realize motion capture, the feasibility of target location and tracking research is discussed. After that, the bottom data acquisition and analysis model is constructed based on the road navigation data of agricultural robots. To capture the movement obstacles of road edge and build the foundation of road recognition technology. In order to improve the effectiveness of motion obstacle capture and detection, a moving target detection algorithm is proposed to optimize and update the mean displacement algorithm, and constructs a feature-oriented hybrid algorithm motion capture model. The simulation results indicate that the proposed optimization model can effectively improve the tracking efficiency of non-rigid targets in outdoor environment, and the number of evaluation iterations can reach 3.5621 times per frame, which shows that the research has good theoretical and practical value.
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Peng, Yongwei, and Weiyi Gao. "Research on Reconstruction of Basketball Training Action Trajectory Based on Improved K-Means Clustering Algorithm." Wireless Communications and Mobile Computing 2022 (April 14, 2022): 1–9. http://dx.doi.org/10.1155/2022/9531266.
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The automatic capture and analysis of basketball game movements can guide basketball training and provide an effective method for improving the efficiency of basketball training. This paper introduces the research status of clustering methods in the field of trajectory data mining and reconstruction in detail. By analyzing the trajectory data under the constraints of the road network, the spatiotemporal characteristics of the existing trajectory clustering methods, and the deficiencies of the existing trajectory clustering methods, a new trajectory clustering method based on trajectory segmentation and spatiotemporal similarity measurement is implemented. A motion capture and reconstruction method for basketball training based on visual image K-means clustering algorithm is proposed. Multiresolution frame scanning technology is used to collect machine images of basketball training movements, and edge contour processing is performed on the collected high-resolution basketball training movement images. Feature detection uses the three-dimensional model reconstruction method to segment the basketball training action area and combines the irregular triangle network model to realize the machine vision block template matching processing of basketball training actions and capture the basketball training action in the Gaussian fuzzy affine space. In time and feature extraction, wavelet lifting technology is used to identify the ambiguity of basketball training movements, image enhancement technology is used to improve the resolution and adaptability of basketball training movement capture, and machine vision image processing methods are used to achieve basketball training movement capture optimization. The simulation results show that the method has better adaptability and higher feature recognition ability for basketball training motion capture and improves the feature extraction and adaptive capture reconstruction ability of basketball training motion.
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Zhang, Xiang, Gongbing Shan, Ye Wang, Bingjun Wan, and Hua Li. "Wearables, Biomechanical Feedback, and Human Motor-Skills’ Learning & Optimization." Applied Sciences 9, no. 2 (January 10, 2019): 226. http://dx.doi.org/10.3390/app9020226.
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Biomechanical feedback is a relevant key to improving sports and arts performance. Yet, the bibliometric keyword analysis on Web of Science publications reveals that, when comparing to other biofeedback applications, the real-time biomechanical feedback application lags far behind in sports and arts practice. While real-time physiological and biochemical biofeedback have seen routine applications, the use of real-time biomechanical feedback in motor learning and training is still rare. On that account, the paper aims to extract the specific research areas, such as three-dimensional (3D) motion capture, anthropometry, biomechanical modeling, sensing technology, and artificial intelligent (AI)/deep learning, which could contribute to the development of the real-time biomechanical feedback system. The review summarizes the past and current state of biomechanical feedback studies in sports and arts performance; and, by integrating the results of the studies with the contemporary wearable technology, proposes a two-chain body model monitoring using six IMUs (inertial measurement unit) with deep learning technology. The framework can serve as a basis for a breakthrough in the development. The review indicates that the vital step in the development is to establish a massive data, which could be obtained by using the synchronized measurement of 3D motion capture and IMUs, and that should cover diverse sports and arts skills. As such, wearables powered by deep learning models trained by the massive and diverse datasets can supply a feasible, reliable, and practical biomechanical feedback for athletic and artistic training.
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Li, Yueru. "Dance Motion Capture Based on Data Fusion Algorithm and Wearable Sensor Network." Complexity 2021 (June 23, 2021): 1–11. http://dx.doi.org/10.1155/2021/2656275.
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In this paper, through an in-depth study and analysis of dance motion capture algorithms in wearable sensor networks, the extended Kalman filter algorithm and the quaternion method are selected after analysing a variety of commonly used data fusion algorithms and pose solving algorithms. In this paper, a sensor-body coordinate system calibration algorithm based on hand-eye calibration is proposed, which only requires three calibration poses to complete the calibration of the whole-body sensor-body coordinate system. In this paper, joint parameter estimation algorithm based on human joint constraints and limb length estimation algorithm based on closed joint chains are proposed, respectively. The algorithm is an iterative optimization algorithm that divides each iteration into an expectation step and a great likelihood step, and the best convergence value can be found efficiently according to each iteration step. The feature values of each pose action are fed into the algorithm for model learning, which enables the training of the model. The trained model is then tested by combining the collected gesture data with the algorithmic model to recognize and classify the gesture data, observe its recognition accuracy, and continuously optimize the model to achieve accurate recognition of human gesture actions.
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Tang, Xu, Ying Luo, and Bin Han. "Fractional-Order Gas Film Model." Fractal and Fractional 6, no. 10 (October 3, 2022): 561. http://dx.doi.org/10.3390/fractalfract6100561.
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In this paper, a fractional-order model of the gas film is proposed for the dynamic characteristics of an air bearing. Based on the dynamic characteristics common between gas film and viscoelastic body, the idea of the fractional-order equivalent modeling of the dynamic characteristics of the gas film is presented to improve the modeling accuracy. Four fractional-order gas film (FOGF) models are introduced based on generalization of traditional viscoelastic models. The analysis of the characteristics of the FOGF models shows that the FOGF model can capture more complex dynamic characteristics and fit the real dynamic data of the gas film better than traditional models. A genetic algorithm particle swarm optimization (GA-PSO) method is used for parameter identification of the proposed models. The experimental results tested on the air bearing motion platform show that the FOGF models are superior in accuracy to the traditional equivalent models for the gas film. In particular, the fractional-order Maxwell gas film (FOMGF) model has the best capture accuracy compared to the other FOGF models and traditional models.
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Rafique, Samina, M. Najam-ul-Islam, M. Shafique, and A. Mahmood. "Neuro-fuzzy control of sit-to-stand motion using head position tracking." Measurement and Control 53, no. 7-8 (July 15, 2020): 1342–53. http://dx.doi.org/10.1177/0020294020938079.
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Based on the clinical evidence that head position measured by the multisensory system contributes to motion control, this study suggests a biomechanical human-central nervous system modeling and control framework for sit-to-stand motion synthesis. Motivated by the evidence for a task-oriented encoding of motion by the central nervous system, we propose a framework to synthesize and control sit-to-stand motion using only head position trajectory in the high-level-task-control environment. First, we design a generalized analytical framework comprising a human biomechanical model and an adaptive neuro-fuzzy inference system to emulate central nervous system. We introduce task-space training algorithm for adaptive neuro-fuzzy inference system training. The adaptive neuro-fuzzy inference system controller is optimized in the number of membership functions and training cycles to avoid over-fitting. Next, we develop custom human models based on anthropometric data of real subjects. Using the weighting coefficient method, we estimate body segment parameter. The subject-specific body segment parameter values are used (1) to scale human model for real subjects and (2) in task-space training to train custom adaptive neuro-fuzzy inference system controllers. To validate our modeling and control scheme, we perform extensive motion capture experiments of sit-to-stand transfer by real subjects. We compare the synthesized and experimental motions using kinematic analyses. Our analytical modeling-control scheme proves to be scalable to real subjects’ body segment parameter and the task-space training algorithm provides a means to customize adaptive neuro-fuzzy inference system efficiently. The customized adaptive neuro-fuzzy inference system gives 68%–98% improvement over general adaptive neuro-fuzzy inference system. This study has a broader scope in the fields of rehabilitation, humanoid robotics, and virtual characters’ motion planning based on high-level-task-control scheme.
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Hu, Weiming, Xinchu Shi, Zongwei Zhou, Junliang Xing, Haibin Ling, and Stephen Maybank. "Dual L1-Normalized Context Aware Tensor Power Iteration and Its Applications to Multi-object Tracking and Multi-graph Matching." International Journal of Computer Vision 128, no. 2 (October 16, 2019): 360–92. http://dx.doi.org/10.1007/s11263-019-01231-y.
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Abstract The multi-dimensional assignment problem is universal for data association analysis such as data association-based visual multi-object tracking and multi-graph matching. In this paper, multi-dimensional assignment is formulated as a rank-1 tensor approximation problem. A dual L1-normalized context/hyper-context aware tensor power iteration optimization method is proposed. The method is applied to multi-object tracking and multi-graph matching. In the optimization method, tensor power iteration with the dual unit norm enables the capture of information across multiple sample sets. Interactions between sample associations are modeled as contexts or hyper-contexts which are combined with the global affinity into a unified optimization. The optimization is flexible for accommodating various types of contextual models. In multi-object tracking, the global affinity is defined according to the appearance similarity between objects detected in different frames. Interactions between objects are modeled as motion contexts which are encoded into the global association optimization. The tracking method integrates high order motion information and high order appearance variation. The multi-graph matching method carries out matching over graph vertices and structure matching over graph edges simultaneously. The matching consistency across multi-graphs is based on the high-order tensor optimization. Various types of vertex affinities and edge/hyper-edge affinities are flexibly integrated. Experiments on several public datasets, such as the MOT16 challenge benchmark, validate the effectiveness of the proposed methods.
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McCann, Brennan, and Morad Nazari. "Control and maintenance of fully-constrained and underconstrained rigid body motion on Lie groups and their tangent bundles." Journal of Geometric Mechanics 14, no. 1 (2022): 29. http://dx.doi.org/10.3934/jgm.2022002.
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<p style='text-indent:20px;'>Presented herein are a class of methodologies for conducting constrained motion analysis of rigid bodies within the Udwadia-Kalaba (U-K) formulation. The U-K formulation, primarily devised for systems of particles, is advanced to rigid body dynamics in the geometric mechanics framework and a novel development of U-K formulation for use on nonlinear manifolds, namely the special Euclidean group <inline-formula><tex-math id="M1">\begin{document}$ {\mathsf{SE}(3)}$\end{document}</tex-math></inline-formula> and its second order tangent bundle <inline-formula><tex-math id="M2">\begin{document}${\mathsf{T}^2\mathsf{SE}(3)} $\end{document}</tex-math></inline-formula>, is proposed in addition to the formulation development on Euclidean spaces. Then, a Morse-Lyapunov based tracking controller using backstepping is applied to capture disturbed initial conditions that the U-K formulation cannot account for. This theoretical development is then applied to fully-constrained and underconstrained scenarios of rigid-body spacecraft motion in a lunar orbit, and the translational and rotational motions of the spacecraft and the control inputs obtained using the proposed methodologies to achieve and maintain those constrained motions are studied.</p>
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Gao, Hongtao, and Biao Li. "Establishment of Motion Model for Wave Capture Buoy and Research on Hydrodynamic Performance of Floating-Type Wave Energy Converter." Polish Maritime Research 22, s1 (September 1, 2015): 106–11. http://dx.doi.org/10.1515/pomr-2015-0041.
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Abstract Floating-type wave energy converter has the advantages of high wave energy conversion efficiency, strong shock resistance ability in rough sea and stable output power. So it is regarded as a promising energy utilization facility. The research on hydrodynamic performance of wave capture buoys is the precondition and key to the wave energy device design and optimization. A simplified motion model of the buoys in the waves is established. Based on linear wave theory, the equations of motion of buoys are derived according to Newton’s second law. The factors of wave and buoys structural parameters on wave energy absorption efficiency are discussed in the China’s Bohai Sea with short wave period and small wave height. The results show that the main factor which affects the dynamic responses of wave capture buoys is the proximity of the natural frequency of buoys to the wave period. And the incoming wave power takes a backseat role to it at constant wave height. The buoys structural parameters such as length, radius and immersed depth, influence the wave energy absorption efficiency, which play significant factors in device design. The effectiveness of this model is validated by the sea tests with small-sized wave energy devices. The establishment methods of motion model and analysis results are expected to be helpful for designing and manufacturing of floating-type wave energy converter.
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Zhang, Jun, Ruixin Liang, Newman Lau, Qiwen Lei, and Joanne Yip. "A Systematic Analysis of 3D Deformation of Aging Breasts Based on Artificial Neural Networks." International Journal of Environmental Research and Public Health 20, no. 1 (December 27, 2022): 468. http://dx.doi.org/10.3390/ijerph20010468.
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The measurement and prediction of breast skin deformation are key research directions in health-related research areas, such as cosmetic and reconstructive surgery and sports biomechanics. However, few studies have provided a systematic analysis on the deformations of aging breasts. Thus, this study has developed a model order reduction approach to predict the real-time strain of the breast skin of seniors during movement. Twenty-two women who are on average 62 years old participated in motion capture experiments, in which eight body variables were first extracted by using the gray relational method. Then, backpropagation artificial neural networks were built to predict the strain of the breast skin. After optimization, the R-value for the neural network model reached 0.99, which is within acceptable accuracy. The computer-aided system of this study is validated as a robust simulation approach for conducting biomechanical analyses and predicting breast deformation.
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Wang, Lipeng, Junjie Tian, Jiazheng Du, Siyuan Zheng, Jianye Niu, Zhengyan Zhang, and Jiang Wu. "A Hybrid Mechanism-Based Robot for End-Traction Lower Limb Rehabilitation: Design, Analysis and Experimental Evaluation." Machines 10, no. 2 (January 27, 2022): 99. http://dx.doi.org/10.3390/machines10020099.
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Conventional lower-limb rehabilitation robots cannot provide in-time rehabilitation training for stroke patients in the acute stage due to their large size and mass as well as their complex wearing process. Aiming to solve the problems, first, a novel hybrid end-traction lower-limb rehabilitation robot (HE-LRR) was designed as the lower-limb rehabilitation requirement of patients in the acute stage, in this paper. The usage of (2-UPS + U)&(R + RPS)&(2-RR) hybrid mechanism and a mirror motion actuator had the advantages of compact structure, large working space and short wearing time to the HE-LRR. Then, the mobility of the HE-LRR was calculated and the motion property was analyzed based on screw theory. Meanwhile, the trajectory planning of the HE-LRR was carried out based on MOTOmed® motion training. Finally, the motion capture and surface electromyography (sEMG) signal acquisition experiments in the MOTOmed motion training were performed. The foot trajectory experimental effect and the lower-limb muscle groups activation rules were studied ulteriorly. The experimental results showed that the HE-LRR achieved good kinematic accuracy and lower limb muscle groups training effect, illustrating that the HE-LRR possessed good application prospects for the lower-limb rehabilitation of patients in the acute stage. This research could also provide a theoretical basis for improving the standardization and compliance of lower-limb robot rehabilitation training.
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Hiley, Michael J., and Maurice R. Yeadon. "The Effect of Cost Function on Optimum Technique of the Undersomersault on Parallel Bars." Journal of Applied Biomechanics 28, no. 1 (February 2012): 10–19. http://dx.doi.org/10.1123/jab.28.1.10.
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The undersomersault, or felge, to handstand on parallel bars has become an important skill in Men’s Artistic Gymnastics as it forms the basis of many complex variations. To receive no deductions from the judges, the undersomersault must be performed without demonstrating the use of strength to achieve the final handstand position. Two male gymnasts each performed nine undersomersaults from handstand to handstand while data were recorded using an automatic motion capture system. The highest and lowest scoring trials of each gymnast, as determined by four international judges, were chosen for further analysis. Three optimization criteria were used to generate undersomersault technique during the swing phase of the skill using a computer simulation model: minimization of peak joint torques, minimization of horizontal velocity before release, and maximization of angular momentum. The techniques used by both gymnasts could be explained using the second optimization criterion which facilitated further skill development. The first optimization criterion generated a technique advocated for beginners where strength might be expected to be a limiting factor. The third optimization criterion resulted in a different type of undersomersault movement of greater difficulty according to the FIG Code of Points.
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Wu, Changcheng, Tianci Song, Zilong Wu, Qingqing Cao, Fei Fei, Dehua Yang, Baoguo Xu, and Aiguo Song. "Development and Evaluation of an Adaptive Multi-DOF Finger with Mechanical-Sensor Integrated for Prosthetic Hand." Micromachines 12, no. 1 (December 30, 2020): 33. http://dx.doi.org/10.3390/mi12010033.
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To realize the adaptive grasping of objects with diverse shapes and to capture the joint angles of the finger, a multi degree of freedom (DOF) adaptive finger for prosthetic hand is proposed in this paper. The fingers are designed with three joints. The maximum rotation angle of the finger joints is 90°. The angle at which the finger joints bend can be captured. Firstly, the prototype design, forward kinematics and force analysis of phalanges are described in detail. In order to achieve an adaptive motion pattern similar to that of the human hand, this paper investigates the optimization of the torsion spring stiffness coefficient so that the metacarpophalangeal (MCP) joints, proximal interphalangeal (PIP) joints, and distal interphalangeal (DIP) joints of the bionic finger meet a motion ratio of approximately 3:3:1. Then, in order to realize the joint angle measurement in the process of grasping an object, the mechanical-sensor integrated finger joint is designed, and the composition, angle measurement principle and measurement circuit are introduced in detail. Finally, joint angle measurement, movement law evaluation and object grasping experiments are performed to verify the validity of the designed finger. The experimental results show that the root-mean-square (RMS) of the DIP, PIP and MCP angle measurement errors are 0.36°, 0.59° and 0.32°, respectively. The designed finger is able to grasp objects with different shapes stably.
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Li, Zhishuang, and Fengqing Li. "Movement Analysis and Action Optimization of Physical Education Teaching Practice Based on Multisensing Perception." Journal of Sensors 2022 (May 4, 2022): 1–11. http://dx.doi.org/10.1155/2022/5075122.
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Correct and effective physical education teaching can not only improve students’ physical quality but also exercise students’ willpower, which is an important content to promote students’ all-round development. However, according to the current teaching situation in our country, in the actual teaching process, there is a situation of incongruity between teaching and sports development, which leads to the decline of the quality of physical education teaching in our country and affects the development of students’ comprehensive quality. Based on these problems, starting from the relationship between teaching and sports, this paper analyzes the coordinated development between physical education teaching and training in colleges and universities and builds a physical education teaching quality monitoring system. The research results of this paper show that (1) when using traditional recognition of various motion patterns, it can recognize various behavior patterns, and the average recognition accuracy is 90.1%. The accuracy is 94.3%. Compared with the traditional recognition mode, the average recognition accuracy is increased by 4.2%, and the recognition result is better. Compared with the recognition results of the first set of experiments, for the more difficult to distinguish upstairs and downstairs, the recognition accuracy is increased by 9% and 7%, respectively, and the recognition accuracy of backward is increased by 6%. (2) Before receiving the teaching, the test results of each index of the members of the routine group and the training group were basically the same, and there was no major difference. After the T -test was performed between the conventional group and the training group, the results showed that the P values of the evaluation results of the two groups were both above 0.05. The experimental results showed that the initial conditions of the two groups could be regarded as the same before receiving the teaching. Combining the evaluation results of the two groups before the training, we can conclude that under the condition that the initial conditions are basically the same, and the training conditions and environment are basically the same, the trainees who have received the mode training method have obtained better physical fitness indicators. The improvement and the effect are greatly optimized compared with the mode training. (3) Among the 8-spoke images captured by the experiment, the multisensor motion analysis model proposed in this paper has the highest action recognition accuracy. When the first picture is taken, the recognition accuracy is 98%. The recognition accuracy rate is also increasing, and when the eighth image is taken, the action recognition accuracy rate reaches 99%. Among the three different models, the multisensor motion analysis model proposed in the article has the shortest page response time. When the number of tests is 10, the average page response time is 0.4 seconds. When the number of tests increases to 70, the average page response time reaches 1.0 seconds, and the success rate of the multisensor motion analysis model has remained at 100%. The average response time will increase with the increase of the number of tests, and the experimental results also show that the detection performance of the multisensor motion analysis model is the highest.
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Imbrie-Moore, Annabel M., Matthew H. Park, Michael J. Paulsen, Mark Sellke, Rohun Kulkami, Hanjay Wang, Yuanjia Zhu, et al. "Biomimetic six-axis robots replicate human cardiac papillary muscle motion: pioneering the next generation of biomechanical heart simulator technology." Journal of The Royal Society Interface 17, no. 173 (December 2020): 20200614. http://dx.doi.org/10.1098/rsif.2020.0614.
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Papillary muscles serve as attachment points for chordae tendineae which anchor and position mitral valve leaflets for proper coaptation. As the ventricle contracts, the papillary muscles translate and rotate, impacting chordae and leaflet kinematics; this motion can be significantly affected in a diseased heart. In ex vivo heart simulation, an explanted valve is subjected to physiologic conditions and can be adapted to mimic a disease state, thus providing a valuable tool to quantitatively analyse biomechanics and optimize surgical valve repair. However, without the inclusion of papillary muscle motion, current simulators are limited in their ability to accurately replicate cardiac biomechanics. We developed and implemented image-guided papillary muscle (IPM) robots to mimic the precise motion of papillary muscles. The IPM robotic system was designed with six degrees of freedom to fully capture the native motion. Mathematical analysis was used to avoid singularity conditions, and a supercomputing cluster enabled the calculation of the system's reachable workspace. The IPM robots were implemented in our heart simulator with motion prescribed by high-resolution human computed tomography images, revealing that papillary muscle motion significantly impacts the chordae force profile. Our IPM robotic system represents a significant advancement for ex vivo simulation, enabling more reliable cardiac simulations and repair optimizations.
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Shield, Stacey, Ricardo Jericevich, Amir Patel, and Ardian Jusufi. "Tails, Flails, and Sails: How Appendages Improve Terrestrial Maneuverability by Improving Stability." Integrative and Comparative Biology 61, no. 2 (May 29, 2021): 506–20. http://dx.doi.org/10.1093/icb/icab108.
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Abstract Trade-offs in maneuverability and stability are essential in ecologically relevant situations with respect to robustness of locomotion, with multiple strategies apparent in animal model systems depending on their habitat and ecology. Free appendages such as tails and ungrounded limbs may assist in navigating this trade-off by assisting with balance, thereby increasing the acceleration that can be achieved without destabilizing the body. This comparative analysis explores the inertial mechanisms and, in some cases, fluid dynamic mechanisms by which appendages contribute to the stabilization of gait and perturbation response behaviors in a wide variety of animals. Following a broad review of examples from nature and bio-inspired robotics that illustrate the importance of appendages to the control of body orientation, two specific cases are examined through preliminary experiments: the role of arm motion in bipedal gait termination is explored using trajectory optimization, and the role of the cheetah’s tail during a deceleration maneuver is analyzed based on motion capture data. In both these examples, forward rotation of the appendage in question is found to counteract the unwanted forward pitch caused by the braking forces. It is theorized that this stabilizing action may facilitate more rapid deceleration by allowing larger or longer-acting braking forces to be applied safely.
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Ennaiem, Ferdaws, Abdelbadiâ Chaker, Juan Sebastián Sandoval Arévalo, Med Amine Laribi, Sami Bennour, Abdelfattah Mlika, Lotfi Romdhane, and Saïd Zeghloul. "Sensitivity Based Selection of an Optimal Cable-Driven Parallel Robot Design for Rehabilitation Purposes." Robotics 10, no. 1 (December 31, 2020): 7. http://dx.doi.org/10.3390/robotics10010007.
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This paper deals with the design of an optimal cable-driven parallel robot (CDPR) for upper limb rehabilitation. The robot’s prescribed workspace is identified with the help of an occupational therapist based on three selected daily life activities, which are tracked using a Qualisys motion capture system. A preliminary architecture of the robot is proposed based on the analysis of the tracked trajectories of all the activities. A multi-objective optimization process using the genetic algorithm method is then performed, where the cable tensions and the robot size are selected as the objective functions to be minimized. The cables tensions are bounded between two limits, where the lower limit ensures a positive tension in the cables at all times and the upper limit represents the maximum torque of the motor. A sensitivity analysis is then performed using the Monte Carlo method to yield the optimal design selected out of the non-dominated solutions, forming the obtained Pareto front. The robot with the highest robustness toward the disturbances is identified, and its dexterity and elastic stiffness are calculated to investigate its performance.
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SUN, JIYU, MINGZE LING, CHUNXIANG PAN, DONGHUI CHEN, JIN TONG, and XIN LI. "BIOMIMETIC STRUCTURE DESIGN OF DRAGONFLY WING VENATION USING TOPOLOGY OPTIMIZATION METHOD." Journal of Mechanics in Medicine and Biology 14, no. 04 (July 3, 2014): 1450078. http://dx.doi.org/10.1142/s021951941450078x.
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Scientists have carried out research for various biomimetic applications based on the dragonfly wings because of the superb flying skills and lightsome posture. The wings of dragonflies are mainly composed of veins and membranes, which give rise to the special characteristics of their wings that make dragonflies being supremely versatile, maneuverable fliers. Mimicking the dragonfly wing motion is of great technological interest from application's point of view. However, the major challenge is the biomimetic fabrication to replicate the wing motion due to the very complex nature of the wing venation of dragonfly wings. In this regard, the topology optimization method (TOM) is useful to simplify object's structure while retaining its mechanical properties. In this paper, TOM is employed to simplify and optimize the venation structure of dragonfly (Pantala flavescens Fabricius) wing that is captured by a 3D scanner and numerical reconfiguration. Combined with the material parameters obtained from nanoindentation testing, the quantitative models are established based on a finite element (FE) analysis and discussed in static range. The quantitative models are then compared with the square frame, staggered grid frame and hexagonal frame to examine the potentials of the biomimetic structure design for the fabrication of greenhouse roof.
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Amaral, Giovanni, Pedro Mello, Lucas do Carmo, Izabela Alberto, Edgard Malta, Alexandre Simos, Guilherme Franzini, Hideyuki Suzuki, and Rodolfo Gonçalves. "Seakeeping Tests of a FOWT in Wind and Waves: An Analysis of Dynamic Coupling Effects and Their Impact on the Predictions of Pitch Motion Response." Journal of Marine Science and Engineering 9, no. 2 (February 10, 2021): 179. http://dx.doi.org/10.3390/jmse9020179.
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The present work highlights some of the dynamic couplings observed in a series of tests performed in a wave basin with a scaled-model of a Floating Offshore Wind Turbine (FOWT) with semi-submersible substructure. The model was moored by means of a conventional chain catenary system and an actively controlled fan was used for emulating the thrust loads during the tests. A set of wave tests was performed for concomitant effects of not aligned wave and wind. The experimental measurements illustrate the main coupling effects involved and how they affect the FOWT motions in waves, especially when the floater presents a non-negligible tilt angle. In addition, a frequency domain numerical analysis was performed in order to evaluate its ability to capture these effects properly. The influence of different modes of fan response, floater trim angles (changeable with ballast compensation) and variations in the mooring stiffness with the offsets were investigated in the analysis. Results attest that significant changes in the FOWT responses may indeed arise from coupling effects, thus indicating that caution must be taken when simplifying the hydrodynamic frequency-domain models often used as a basis for the simulation of FOWTs in waves and in optimization procedures for the design of the floater and mooring lines.
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Zimmer, Alexandra, Anna Hilsmann, Wieland Morgenstern, and Peter Eisert. "Imposing temporal consistency on deep monocular body shape and pose estimation." Computational Visual Media 9, no. 1 (October 18, 2022): 123–39. http://dx.doi.org/10.1007/s41095-022-0272-x.
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AbstractAccurate and temporally consistent modeling of human bodies is essential for a wide range of applications, including character animation, understanding human social behavior, and AR/VR interfaces. Capturing human motion accurately from a monocular image sequence remains challenging; modeling quality is strongly influenced by temporal consistency of the captured body motion. Our work presents an elegant solution to integrating temporal constraints during fitting. This increases both temporal consistency and robustness during optimization. In detail, we derive parameters of a sequence of body models, representing shape and motion of a person. We optimize these parameters over the complete image sequence, fitting a single consistent body shape while imposing temporal consistency on the body motion, assuming body joint trajectories to be linear over short time. Our approach enables the derivation of realistic 3D body models from image sequences, including jaw pose, facial expression, and articulated hands. Our experiments show that our approach accurately estimates body shape and motion, even for challenging movements and poses. Further, we apply it to the particular application of sign language analysis, where accurate and temporally consistent motion modelling is essential, and show that the approach is well-suited to this kind of application.
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Ueno, Ryo, Alessandro Navacchia, Nathan D. Schilaty, Gregory D. Myer, Timothy E. Hewett, and Nathaniel A. Bates. "Anterior Cruciate Ligament Loading Increases With Pivot-Shift Mechanism During Asymmetrical Drop Vertical Jump in Female Athletes." Orthopaedic Journal of Sports Medicine 9, no. 3 (March 1, 2021): 232596712198909. http://dx.doi.org/10.1177/2325967121989095.
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Background: Frontal plane trunk lean with a side-to-side difference in lower extremity kinematics during landing increases unilateral knee abduction moment and consequently anterior cruciate ligament (ACL) injury risk. However, the biomechanical features of landing with higher ACL loading are still unknown. Validated musculoskeletal modeling offers the potential to quantify ACL strain and force during a landing task. Purpose: To investigate ACL loading during a landing and assess the association between ACL loading and biomechanical factors of individual landing strategies. Study Design: Descriptive laboratory study. Methods: Thirteen young female athletes performed drop vertical jump trials, and their movements were recorded with 3-dimensional motion capture. Electromyography-informed optimization was performed to estimate lower limb muscle forces with an OpenSim musculoskeletal model. A whole-body musculoskeletal finite element model was developed. The joint motion and muscle forces obtained from the OpenSim simulations were applied to the musculoskeletal finite element model to estimate ACL loading during participants’ simulated landings with physiologic knee mechanics. Kinematic, muscle force, and ground-reaction force waveforms associated with high ACL strain trials were reconstructed via principal component analysis and logistic regression analysis, which were used to predict trials with high ACL strain. Results: The median (interquartile range) values of peak ACL strain and force during the drop vertical jump were 3.3% (–1.9% to 5.1%) and 195.1 N (53.9 to 336.9 N), respectively. Four principal components significantly predicted high ACL strain trials, with 100% sensitivity, 78% specificity, and an area of 0.91 under the receiver operating characteristic curve ( P < .001). High ACL strain trials were associated with (1) knee motions that included larger knee abduction, internal tibial rotation, and anterior tibial translation and (2) motion that included greater vertical and lateral ground-reaction forces, lower gluteus medius force, larger lateral pelvic tilt, and increased hip adduction. Conclusion: ACL loads were higher with a pivot-shift mechanism during a simulated landing with asymmetry in the frontal plane. Specifically, knee abduction can create compression on the posterior slope of the lateral tibial plateau, which induces anterior tibial translation and internal tibial rotation. Clinical Relevance: Athletes are encouraged to perform interventional and preventive training to improve symmetry during landing.
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Alexandru, Cătălin. "Optimizing the control system of a single-axis sun tracking mechanism." MATEC Web of Conferences 184 (2018): 01002. http://dx.doi.org/10.1051/matecconf/201818401002.
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The work shows the optimization of the control system for the single-axis solar tracker that equips a solar panel, with the aim to increase the energetic efficiency of the system by maximizing the quantity of incident solar radiation that is captured - absorbed by the panel. The single-axis solar tracker is driven by a linear actuator, the optimization study intending to determine the optimal configuration (in terms of tuning factors) of the controller, which is a PID (Proportional-Integral-Derivative) device, in order to accurately achieve the motion (tracking) law imposed on the solar panel. The solar tracker was approached as a mechatronic system, the mechanical device (developed in ADAMS - Automatic Dynamic Analysis of Mechanical Systems) and the control system (developed in EASY5 - Engineering Analysis System) being integrated at the level of virtual prototype, in the concurrent engineering concept.
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Schiebl, Jonas, Mark Tröster, Wiem Idoudi, Elena Gneiting, Leon Spies, Christophe Maufroy, Urs Schneider, and Thomas Bauernhansl. "Model-Based Biomechanical Exoskeleton Concept Optimization for a Representative Lifting Task in Logistics." International Journal of Environmental Research and Public Health 19, no. 23 (November 23, 2022): 15533. http://dx.doi.org/10.3390/ijerph192315533.
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Occupational exoskeletons are a promising solution to prevent work-related musculoskeletal disorders (WMSDs). However, there are no established systems that support heavy lifting to shoulder height. Thus, this work presents a model-based analysis of heavy lifting activities and subsequent exoskeleton concept optimization. Six motion sequences were captured in the laboratory for three subjects and analyzed in multibody simulations with respect to muscle activities (MAs) and joint forces (JFs). The most strenuous sequence was selected and utilized in further simulations of a human model connected to 32 exoskeleton concept variants. Six simulated concepts were compared concerning occurring JFs and MAs as well as interaction loads in the exoskeleton arm interfaces. Symmetric uplifting of a 21 kg box from hip to shoulder height was identified as the most strenuous motion sequence with highly loaded arms, shoulders, and back. Six concept variants reduced mean JFs (spine: >70%, glenohumeral joint: >69%) and MAs (back: >63%, shoulder: >59% in five concepts). Parasitic loads in the arm bracing varied strongly among variants. An exoskeleton design was identified that effectively supports heavy lifting, combining high musculoskeletal relief and low parasitic loads. The applied workflow can help developers in the optimization of exoskeletons.
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Tagliante, Fabien, Tuan M. Nguyen, Lyle M. Pickett, and Hyung Sub Sim. "Large-Eddy Simulation of Laser-Ignited Direct Injection Gasoline Spray for Emission Control." Energies 14, no. 21 (November 3, 2021): 7276. http://dx.doi.org/10.3390/en14217276.
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Large-Eddy Simulations (LES) of a gasoline spray, where the mixture was ignited rapidly during or after injection, were performed in comparison to a previous experimental study with quantitative flame motion and soot formation data [SAE 2020-01-0291] and an accompanying Reynolds-Averaged Navier–Stokes (RANS) simulation at the same conditions. The present study reveals major shortcomings in common RANS combustion modeling practices that are significantly improved using LES at the conditions of the study, specifically for the phenomenon of rapid ignition in the highly turbulent, stratified mixture. At different ignition timings, benchmarks for the study include spray mixing and evaporation, flame propagation after ignition, and soot formation in rich mixtures. A comparison of the simulations and the experiments showed that the LES with Dynamic Structure turbulence were able to capture correctly the liquid penetration length, and to some extent, spray collapse demonstrated in the experiments. For early and intermediate ignition timings, the LES showed excellent agreement to the measurements in terms of flame structure, extent of flame penetration, and heat-release rate. However, RANS simulations (employing the common G-equation or well-stirred reactor) showed much too rapid flame spread and heat release, with connections to the predicted turbulent kinetic energy. With confidence in the LES for predicted mixture and flame motion, the predicted soot formation/oxidation was also compared to the experiments. The soot location was well captured in the LES, but the soot mass was largely underestimated using the empirical Hiroyasu model. An analysis of the predicted fuel–air mixture was used to explain different flame propagation speeds and soot production tendencies when varying ignition timing.
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Bi, Rui, Shu Gan, Xiping Yuan, Raobo Li, Sha Gao, Weidong Luo, and Lin Hu. "Studies on Three-Dimensional (3D) Accuracy Optimization and Repeatability of UAV in Complex Pit-Rim Landforms As Assisted by Oblique Imaging and RTK Positioning." Sensors 21, no. 23 (December 4, 2021): 8109. http://dx.doi.org/10.3390/s21238109.
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Unmanned Aerial Vehicles (UAVs) are a novel technology for landform investigations, monitoring, as well as evolution analyses of long−term repeated observation. However, impacted by the sophisticated topographic environment, fluctuating terrain and incomplete field observations, significant differences have been found between 3D measurement accuracy and the Digital Surface Model (DSM). In this study, the DJI Phantom 4 RTK UAV was adopted to capture images of complex pit-rim landforms with significant elevation undulations. A repeated observation data acquisition scheme was proposed for a small amount of oblique-view imaging, while an ortho-view observation was conducted. Subsequently, the 3D scenes and DSMs were formed by employing Structure from Motion (SfM) and Multi-View Stereo (MVS) algorithms. Moreover, a comparison and 3D measurement accuracy analysis were conducted based on the internal and external precision by exploiting checkpoint and DSM of Difference (DoD) error analysis methods. As indicated by the results, the 3D scene plane for two imaging types could reach an accuracy of centimeters, whereas the elevation accuracy of the orthophoto dataset alone could only reach the decimeters (0.3049 m). However, only 6.30% of the total image number of oblique images was required to improve the elevation accuracy by one order of magnitude (0.0942 m). (2) An insignificant variation in internal accuracy was reported in oblique imaging-assisted datasets. In particular, SfM-MVS technology exhibited high reproducibility for repeated observations. By changing the number and position of oblique images, the external precision was able to increase effectively, the elevation error distribution was improved to become more concentrated and stable. Accordingly, a repeated observation method only including a few oblique images has been proposed and demonstrated in this study, which could optimize the elevation and improve the accuracy. The research results could provide practical and effective technology reference strategies for geomorphological surveys and repeated observation analyses in sophisticated mountain environments.
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Kuseyri, Sina. "Constrained H∞ control of gyroscopic ship stabilization systems." Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment 234, no. 3 (March 10, 2020): 634–41. http://dx.doi.org/10.1177/1475090220903217.
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We suggest a constrained [Formula: see text] control scheme for gyroscopic marine vehicle stabilization systems with output and control constraints. The [Formula: see text] performance is used to measure the roll angle reduction of the vessel relative to wave disturbances in regular beam seas. Time-domain constraints, representing requirements for precession angle of gyroscopes and for actuator saturation, are captured using the concept of reachable sets and state-space ellipsoids. A state feedback solution to the constrained [Formula: see text] stabilization control problem is proposed in the framework of linear matrix inequality optimization and multiobjective control. This approach can potentially achieve the best possible vessel comfort with respect to roll motion by allowing constrained variables free as long as they remain within given bounds. Analysis and simulation results for roll dynamics of the vessel coupled with the gyroscopic actuator control system show possible improvements on roll motion stabilization while respecting time-domain hard constraints.
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Niemann, Friedrich, Christopher Reining, Fernando Moya Rueda, Nilah Ravi Nair, Janine Anika Steffens, Gernot A. Fink, and Michael ten Hompel. "LARa: Creating a Dataset for Human Activity Recognition in Logistics Using Semantic Attributes." Sensors 20, no. 15 (July 22, 2020): 4083. http://dx.doi.org/10.3390/s20154083.
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Optimizations in logistics require recognition and analysis of human activities. The potential of sensor-based human activity recognition (HAR) in logistics is not yet well explored. Despite a significant increase in HAR datasets in the past twenty years, no available dataset depicts activities in logistics. This contribution presents the first freely accessible logistics-dataset. In the ’Innovationlab Hybrid Services in Logistics’ at TU Dortmund University, two picking and one packing scenarios were recreated. Fourteen subjects were recorded individually when performing warehousing activities using Optical marker-based Motion Capture (OMoCap), inertial measurement units (IMUs), and an RGB camera. A total of 758 min of recordings were labeled by 12 annotators in 474 person-h. All the given data have been labeled and categorized into 8 activity classes and 19 binary coarse-semantic descriptions, also called attributes. The dataset is deployed for solving HAR using deep networks.
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Foo, Ming Jeat, Jen-Shuan Chang, and Wei Tech Ang. "Real-Time Foot Tracking and Gait Evaluation with Geometric Modeling." Sensors 22, no. 4 (February 20, 2022): 1661. http://dx.doi.org/10.3390/s22041661.
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Gait evaluation is important in gait rehabilitation and assistance to monitor patient’s balance status and assess recovery performance. Recent technologies leverage on vision-based systems with high portability and low operational complexity. In this paper, we propose a new vision-based foot tracking algorithm specially catering to overground gait assistive devices, which often have limited view of the users. The algorithm models the foot and the shank of the user using simple geometry. Through cost optimization, it then aligns the models to the point cloud, showing the back view of the user’s lower limbs. The system outputs the poses of the feet, which are used to compute the spatial-temporal gait parameters. Seven healthy young subjects are recruited to perform overground and treadmill walking trials. The results of the algorithm are compared with the motion capture system and a third-party gait analysis software. The algorithm has a fitting rotational and translational errors of less than 20 degrees and 33 mm, respectively, for 0.4 m/s walking speed. The gait detection F1 score achieves more than 96.8%. The step length and step width errors are around 35 mm, while the cycle time error is less than 38 ms. The proposed algorithm provides a fast, contactless, portable, and cost-effective gait evaluation method without requiring the user to wear any customized footwear.
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Sawant, Manisha, Mayur Kishor Shende, Andrés E. Feijóo-Lorenzo, and Neeraj Dhanraj Bokde. "The State-of-the-Art Progress in Cloud Detection, Identification, and Tracking Approaches: A Systematic Review." Energies 14, no. 23 (December 3, 2021): 8119. http://dx.doi.org/10.3390/en14238119.
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A cloud is a mass of water vapor floating in the atmosphere. It is visible from the ground and can remain at a variable height for some time. Clouds are very important because their interaction with the rest of the atmosphere has a decisive influence on weather, for instance by sunlight occlusion or by bringing rain. Weather denotes atmosphere behavior and is determinant in several human activities, such as agriculture or energy capture. Therefore, cloud detection is an important process about which several methods have been investigated and published in the literature. The aim of this paper is to review some of such proposals and the papers that have been analyzed and discussed can be, in general, classified into three types. The first one is devoted to the analysis and explanation of clouds and their types, and about existing imaging systems. Regarding cloud detection, dealt with in a second part, diverse methods have been analyzed, i.e., those based on the analysis of satellite images and those based on the analysis of images from cameras located on Earth. The last part is devoted to cloud forecast and tracking. Cloud detection from both systems rely on thresholding techniques and a few machine-learning algorithms. To compute the cloud motion vectors for cloud tracking, correlation-based methods are commonly used. A few machine-learning methods are also available in the literature for cloud tracking, and have been discussed in this paper too.
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Singh, DK, SR Karumanchi, A. Mandal, YB Katpatal, and A. Usmani. "Effect of earthquake excitation on circular tunnels: Numerical and experimental study." Measurement and Control 52, no. 7-8 (May 22, 2019): 740–57. http://dx.doi.org/10.1177/0020294019847705.
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This paper studies the behaviour of circular tunnel subjected to dynamic excitation. Tunnels with three different diameters were selected to perform the shake table test at three different covers. The dry sandy soil was used for testing. The mechanical properties like Young’s modulus and shear modulus of sand was calculated from bender element test. The soil–tunnel interface coefficient was calculated from the direct shear test. The soil pressure generated due to dynamic loading were measured by soil pressure transducers. The actual motion of shake table was captured by hand-held vibration analyser. The tunnel was placed parallel and perpendicular to the direction of shaking. The three-dimensional finite-element model was developed for tunnel with both the orientations. The tunnel was assumed to be elastic. Dry sand was assumed to follow non-linear elasto-plastic material using Mohr–Coulomb failure criterion with non-associated flow rule. The results obtained from numerical analysis are compared with experimental results and are expressed in the form of peak dynamic stresses. The time history and fast Fourier transform results of dynamic stresses are also compared. It shows reasonable agreement with both values. Finally, the seismic design guidelines for tunnel are suggested.
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Wang, Zhongzhou, Haixuan Sun, Bidou Wang, and Peng Wang. "Adaptive pseudo-rigid-body model for generalized cross-spring pivots under combined loads." Advances in Mechanical Engineering 12, no. 12 (December 2020): 168781402096653. http://dx.doi.org/10.1177/1687814020966539.
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Generalized cross-spring pivots (CSPs) are widely used as revolute joints in precision machinery. However, pseudo-rigid-body (PRB) models cannot capture the parasitic motions of a generalized CSP exactly under combined loads; moreover, the characteristic parameters used in PRB methods must be recomputed using optimization techniques. In this study, we develop two simple and accurate PRB models for generalized CSPs. First, a PRB method for a beam is developed based on the beam constraint model and the instantaneous center model, where the beam is modeled as two rigid links joined at a pivot via a torsion spring. Subsequently, two PRB models of the generalized CSP, comprising a four-bar model for accuracy and a pin-joint model for stiffness, are constructed based on a kinematic analysis using the proposed PRB method. A deflection characteristic analysis is then conducted to determine the relationship between the proposed model and the existing models. Finally, the PRB models for the pivot under the action of combined loads are validated via finite element analysis. The error evaluation indicates that the proposed PRB models are more accurate than the results from existing methods. The PRB models proposed here can be used in parametric design of compliant mechanisms.
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Broniszewski, Jakub, and Janusz Ryszard Piechna. "Fluid-Structure Interaction Analysis of a Competitive Car during Brake-in-Turn Manoeuvre." Energies 15, no. 8 (April 15, 2022): 2917. http://dx.doi.org/10.3390/en15082917.
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The relationship between the presented work and energy conservation is direct and indirect. Most of the literature related to energy-saving focuses on reducing the aerodynamic drag of cars, which typically leads to the appearance of vehicle motion instabilities at high speeds. Typically, this instability is compensated for by moving aerodynamic body components activated above a certain speed and left in that position until the vehicle speed drops. This change in vehicle configuration results in a significant increase in drag at high velocities. The presented study shows a fully coupled approach to fluid–structure interaction analyses of a car during a high-speed braking-in-turn manoeuvre. The results show how the aerodynamic configuration of a vehicle affects its dynamic behaviour. In this work, we used a novel approach, combining Computational Fluid Dynamics (CFD) analysis with the Multibody Dynamic System. The utilisation of an overset technique allows for car movement in the computational domain. Adding Moving Reference Frame (MRF) to this motion removes all restrictions regarding car trajectory and allows for velocity changes over time. We performed a comparative analysis for two aerodynamic configurations. In the first one, a stationary rear airfoil was in a base position parallel to a trunk generating low drag. No action of the driver was assumed. In the second scenario, brake activation initiates the rotation of the rear airfoil reaching in 0.1 s final position corresponding to maximum aerodynamic downforce generation. Also, no action of the driver was assumed. In the second scenario, the airfoil was moving from the base position up to the point when the whole system approached its maximum downforce. To determine this position, we ran a separated quasi-steady analysis in which the airfoil was rotating slowly to avoid transient effects. The obtained results show the importance of the downforce and load balance on car stability during break-in-turn manoeuvres. They also confirm that the proposed methodology of combining two independent solvers to analyse fluid–structure phenomena is efficient and robust. We captured the aerodynamic details caused by the car’s unsteady movement.
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Chen, Yu-Hsuan, Wei-Chang Li, Xi-Wen Xiao, Chieh-Cheng Yang, and Chien-Hao Liu. "Design Optimization of a Compact Double-Ended-Tuning-Fork-Based Resonant Accelerometer for Smart Spindle Applications." Micromachines 11, no. 1 (December 30, 2019): 42. http://dx.doi.org/10.3390/mi11010042.
Full textAbstract:
With the rapid developments of the Industrial Era 4.0, numerous sensors have been employed to facilitate and monitor the quality of machining processes. Among them, accelerometers play an important role in chatter detection and suppression for reducing the tool down-time and increasing manufacturing efficiency. To date, most commonly seen accelerometers have relatively large sizes such that they can be installed only on the housing of spindles or the surfaces of workpieces that may not be able to directly capture actual vibration signals or obstruct the cutting process. To address this challenge, this research proposed a compact, wide-bandwidth resonant accelerometer that could be embedded inside high-speed spindles for real-time chatter monitoring and prediction. Composed of a double-ended tuning fork (DETF), a proof mass, and a support beam, the resonant accelerometer utilizes the resonance frequency shift of the DETF due to the bending motions of the structure during out-of-plane accelerations as the sensing mechanism. The entire structure based on commercially available quartz tuning forks (QTFs) with electrodes for symmetric-mode excitations. The advantages of this structure include low noise and wide operation bandwidth thanks to the frequency modulation scheme. A theoretical model and finite element analysis were conducted for designs and optimizations. Simulated results demonstrated that the proposed accelerometer has a size of 9.76 mm × 4.8 mm × 5.5 mm, a simulated sensitivity of 0.94 Hz/g, and a simulated working bandwidth of 3.5 kHz. The research results are expected to be beneficial for chatter detection and intelligent manufacturing.
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Huber, David E., and Juan G. Santiago. "Ballistic dispersion in temperature gradient focusing." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 464, no. 2091 (December 18, 2007): 595–612. http://dx.doi.org/10.1098/rspa.2007.0161.
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Molecular dispersion is caused by both molecular diffusion and non-uniform bulk fluid motion. While the Taylor–Aris dispersion regime is the most familiar regime in microfluidic systems, an oft-overlooked regime is that of purely kinematic (or ballistic) dispersion. In most microfluidic systems, this dispersion regime is transient and quickly gives way to Taylor–Aris dispersion. In electrophoretic focusing methods such as temperature gradient focusing (TGF), however, the characteristic time scales for dispersion are fixed, and focused peaks may never reach the Taylor limit. In this situation, generalized Taylor dispersion analysis is not applicable. A heuristic model is developed here which accounts for both molecular diffusion and advective dispersion across all dispersion regimes, from pure diffusion to Taylor dispersion to pure advection. This model is compared to results from TGF experiments and accurately captures both the initial decrease and subsequent increase in peak widths as electric field strength increases. The results of this combined analytical and experimental study provide a useful tool for estimation of dispersion and optimization of TGF systems.
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Gao, Moyao, Zhanli Wang, Zaixiang Pang, Jianwei Sun, Jing Li, Shuang Li, and Hansi Zhang. "Electrically Driven Lower Limb Exoskeleton Rehabilitation Robot Based on Anthropomorphic Design." Machines 10, no. 4 (April 7, 2022): 266. http://dx.doi.org/10.3390/machines10040266.
Full textAbstract:
To help people with impairment of lower extremity movement regain the ability to stand and walk, and to enhance limb function, this study proposes an anthropomorphic design of an electrically driven, lower-limb exoskeleton rehabilitation robot. The angular range of the robot’s motion was determined according to the characteristics of the targeted lower-limb joints; the robot was given an active–passive anthropomorphic design with 12 degrees of freedom. The multi-degree-of-freedom hip exoskeleton, bionic artificial knee exoskeleton and passive rigid-flexible coupling ankle exoskeleton can assist patients in rehabilitation exercises with better wear comfort and exercise flexibility. A kinetic model of the seven-rod lower-limb exoskeleton rehabilitation robot was built, and data analysis of the dynamically captured motion trajectory was conducted. These provided a theoretical basis for gait planning and the control system of the lower-limb exoskeleton rehabilitation robot. The results show that the lower-limb exoskeleton rehabilitation robot system possesses sound wearing comfort and movement flexibility, and the degree of freedom of movement of the exoskeleton robot matches well with that of human movement. The robot can thus provide effective assistance to patients’ standing and walking rehabilitation training.
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Gall, Juergen, Bodo Rosenhahn, Thomas Brox, and Hans-Peter Seidel. "Optimization and Filtering for Human Motion Capture." International Journal of Computer Vision 87, no. 1-2 (November 15, 2008): 75–92. http://dx.doi.org/10.1007/s11263-008-0173-1.
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Xu, Demin, Yiming Li, Yue Zhang, Hui Xu, Tianlai Li, and Xingan Liu. "Effects of orientation and structure on solar radiation interception in Chinese solar greenhouse." PLOS ONE 15, no. 11 (November 6, 2020): e0242002. http://dx.doi.org/10.1371/journal.pone.0242002.
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In order to further improve the utilization of solar energy in Chinese Solar Greenhouse (CSG), this paper systematically studied the effects of orientation and structure on solar radiation interception in CSG. A solar radiation model has been developed based on the previous research, which taking solar motion law, meteorological data, and optical properties of materials into consideration. The established model was used to optimize the orientation and structure of CSG. The analysis of structure considered two major structural parameters, which are the ridge height and the horizontal projection of the rear roof. Moreover, the widely used Liao-Shen type Chinese solar greenhouse (CSG-LS) has been taken as the prototype in the present research, and the measured data of the typical clear day was used for the model validation. The results showed that the ridge height has a remarkable influence on the solar energy captured by CSG-LS. Compared with the optimization of a single factor, the comprehensive optimization of orientation and structure can increase the solar radiation interception of the rear wall by 3.95%. Considering the limiting factor of heat storage-release capacity and the shading effect on the greenhouse structure, the optimal lighting construction of the CSG-LS (with a span of 9.0 m) was specified as 7~9° from south to west of azimuth angle, 4.5~4.7 m ridge height, and 1.4~1.6 m horizontal projection of the rear roof at 42°N latitude. The proposed solar radiation model can provide scientific guidance for the CSG-LS construction in different areas.
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Rojas-Lertxundi, Sendoa, J. Ramón Fernández-López, Sergio Huerta, and Pablo García Bringas. "Motion capture systems for jump analysis." Logic Journal of the IGPL 25, no. 6 (November 7, 2017): 890–901. http://dx.doi.org/10.1093/jigpal/jzx030.
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AbstractThis article presents several methods used in motion capture to measure jumps. The traditional systems to acquire jump information are force plates, but they are very expensive to most people. Amateur sports enthusiasts who want to improve their performance, do not have enough money to spend in professional systems ($+/-20.000$EUR). The price reduction of electronic devices, specifically the inertial measurement units (IMU), are generating new methods of motion capture. In this article we present the state-of the-art motion capture systems for this purpose, from the classical force plates to latest released IMUs. Experiments show that the IMU is equally valid for measuring vertical jump.
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Al-Obaidli, Houd, Rajesh Govindan, and Tareq Al-Ansari. "Multidimensional Risk-Based Real Options Valuation for Low-Carbon Cogeneration Pathways." Energies 16, no. 3 (January 24, 2023): 1250. http://dx.doi.org/10.3390/en16031250.
Full textAbstract:
Energy price fluctuations pose a significant risk and uncertainty to financial investments for new developments in conventional power and freshwater cogeneration facilities. This study attempts to address the problem of making robust valuation for low-carbon energy project investments subject to multi-dimensional price risk, particularly looking at some key research questions: (a) how does the correlation structure, or independence, between the price risks affect the project value; and (b) does adding flexibility in investment enhance or worsen the project valuation, given (a). This study identified three price factors with significant fluctuations that impact conventional power generation, namely: wholesale electricity spot price, natural gas spot price, and CO2 market price. The price factors were used to construct a multidimensional risk model and evaluate investment decisions for cogeneration project expansion in the future based on a low-carbon energy mix. To this end, five cogeneration configurations using combined-cycle gas turbine (CCGT) integrated with solar photovoltaics (PV) and carbon capture and storage (CCS) technologies were assessed. A combined price risk was initially estimated by transforming the given price factors representing maximum covariance using principal component analysis (PCA). The trend and volatilities in the major principal component scores (the combined price risk indicator) were modelled using the geometric Brownian motion stochastic process, whose parameters were determined and then used to perform time-series simulation and generate multiple realisations of the principal component. A back transformation was then applied to obtain the simulated values representing future uncertainties in the price factors. The effect of price risk and uncertainties were subsequently evaluated using a recombining binomial lattice model for real options analysis (ROA). There were financial gains when PV was mixed with conventional natural gas-fired technology. Investment in cogeneration configurations with (a) 25% PV share provided a 53% gain in the extended net present value (e–NPV); and (b) 50% PV share provided a 124% e–NPV gain when compared to the baseline cogeneration system with no PV shares. The analyses demonstrate that PV technology is a better hedging option than CCS against future market uncertainty and price volatility.