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Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on

Issue 6 • Date Nov. 2007

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Displaying Results 1 - 25 of 40
  • Table of contents

    Page(s): C1 - 853
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    Freely Available from IEEE
  • IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans publication information

    Page(s): C2
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    Freely Available from IEEE
  • Imitation of Human-Eye Motion—How to Fix Gaze of an Active Vision System

    Page(s): 854 - 863
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    This paper is about gaze control in active vision. The problem to tackle is, given a camera imaging a particular 3-D point, to place the 3-D point at the center of the image by rotating the camera about its own optical center. For separating this procedure from structure estimation, we use a normalized camera coordinate system, which leads to formulation defined on the unit sphere. In designing the algorithm, we try to avoid the disadvantages of local coordinates or approximation. For this purpose, we design the algorithm by considering the intrinsic geometric properties of the underlying space, not using any kinds of parameterization or approximation. The proposed algorithm is simple and of a closed form, and that makes it suitable for real-time application. View full abstract»

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  • A Multiagent Approach to Q-Learning for Daily Stock Trading

    Page(s): 864 - 877
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    The portfolio management for trading in the stock market poses a challenging stochastic control problem of significant commercial interests to finance industry. To date, many researchers have proposed various methods to build an intelligent portfolio management system that can recommend financial decisions for daily stock trading. Many promising results have been reported from the supervised learning community on the possibility of building a profitable trading system. More recently, several studies have shown that even the problem of integrating stock price prediction results with trading strategies can be successfully addressed by applying reinforcement learning algorithms. Motivated by this, we present a new stock trading framework that attempts to further enhance the performance of reinforcement learning-based systems. The proposed approach incorporates multiple Q-learning agents, allowing them to effectively divide and conquer the stock trading problem by defining necessary roles for cooperatively carrying out stock pricing and selection decisions. Furthermore, in an attempt to address the complexity issue when considering a large amount of data to obtain long-term dependence among the stock prices, we present a representation scheme that can succinctly summarize the history of price changes. Experimental results on a Korean stock market show that the proposed trading framework outperforms those trained by other alternative approaches both in terms of profit and risk management. View full abstract»

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  • Dynamic Auctions for On-Demand Services

    Page(s): 878 - 886
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    In this paper, we consider a market in which a finite number of firms compete in prices for the incoming demand for service. Upon every customer arrival, an independent auctioneer gathers bids from each one of the competing queuing systems and assigns the incoming customer to the system that submitted the lowest bid. We provide a simple characterization of Markov Perfect equilibrium in terms of ldquoindifference prices,rdquo i.e., price levels at which players are indifferent between committing available capacity or withholding it. We identify sufficient conditions for socially efficient performance in equilibrium. View full abstract»

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  • Integrating Task- and Work Domain-Based Work Analyses in Ecological Interface Design: A Process Control Case Study

    Page(s): 887 - 905
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    In this paper, we present a case study wherein several work analysis methods were incorporated in the design of a graphical interface for a petrochemical production process. We follow this case from the application of the work analysis methods, through the consolidation of information requirements, to the design of a novel interface that integrates the requirements. The findings confirm earlier assertions that task-based and work domain-based analysis frameworks identify unique and complementary requirements for effective information systems that are intended to support supervisory control of complex systems. It further provides the first industrial demonstration of ecological interface forms based on integrated task-and work domain-based work requirements. View full abstract»

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  • Ecological Interface Design for Petrochemical Process Control: An Empirical Assessment

    Page(s): 906 - 920
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    Abnormal events in process plants cost the petrochemical industry billions of dollars annually. In part, these events are difficult to deal with because contemporary interfaces do not adequately inform operators about the state of the process. Laboratory simulator studies have shown that, in comparison with contemporary interfaces, ecological interfaces can lead to more effective monitoring and control behavior. However, ecological interfaces derived from work-domain analysis differ from more traditional human-centered interfaces that use a task analysis to inform the design process. A companion paper demonstrated an ecological interface that integrates both work-domain- and task-based information. A second ecological interface was created, drawing exclusively from the traditional work-domain-based analysis. Professional operators used the novel interfaces in an industrial petrochemical process simulator to monitor for, diagnose, and respond to several types of process events. Operators using the work-domain-based ecological interface completed trials more quickly and executed fewer control actions than their counterparts using the current process displays. Operators using the integrated (task- and work-domain-based) ecological interface also showed these benefits and, in addition, showed improved fault diagnoses and better performance scores. The implications and opportunities for introducing ecological interfaces into industrial control rooms are discussed. View full abstract»

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  • Intercity Bus Scheduling Model Incorporating Variable Market Share

    Page(s): 921 - 932
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (407 KB) |  | HTML iconHTML  

    In this paper, we develop an intercity bus scheduling model for a variable market share. The proposed model, unlike the past intercity bus scheduling models, does not assume a fixed market share. Instead, passenger choice behaviors in competitive markets are considered. The model is formulated as a nonlinear mixed integer program that is characterized as nondeterministic polynomial-time hard. We develop a solution algorithm to efficiently solve the model. The test results, which are based on a major Taiwan intercity bus carrier, show the good performance of the model and the solution algorithm. View full abstract»

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  • On the Design of Safety Communication Systems for Vehicles

    Page(s): 933 - 945
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    Statistics show that the number of casualties due to traffic accidents exceeds one million each year. For the development of systems that prevent vehicle collisions, vehicular communication is considered a promising technology. This paper focuses on design aspects of communication systems that support the development of collaborative active safety systems such as collision warning and collision avoidance. We introduce a design method for safety communication systems that includes a set of analyses and a reasoning system for modeling and analyzing traffic scenarios. An overview of a specific solution for communication is presented in this paper. This solution proposes techniques for network organization and data dissemination that make use of contextual information. This allows the development of a communication system that is adaptable to the specifics of the traffic situation. View full abstract»

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  • Antisocial Behavior of Agents in Scheduling Mechanisms

    Page(s): 946 - 954
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    Truthful task scheduling mechanisms are designed to cope with the selfishness of the participating agents. They assume that the agents are selfish; each agent's goal is to maximize its own profit. However, this is not always the case; an agent may want to cause losses to the other agents besides maximizing its profit. Such an agent is said to be an antisocial agent. An antisocial agent will try to gain as much profit as possible relative to the other agents. This paper presents an antisocial strategy which can be used by the antisocial agents to inflict losses on the other agents participating in a task scheduling mechanism on related machines. This paper also studies, by simulation, the effect of different parameters, such as the degree of antisociality on the relative losses that can be inflicted on the participating agents. View full abstract»

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  • Toward a Service-Oriented Development Through a Case Study

    Page(s): 955 - 969
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (665 KB)  

    The rapidly emerging technology of Web services paves a new cost-effective way of engineering software to quickly develop and deploy Web applications by dynamically integrating other independently developed Web-service components to conduct new business transactions. This paper reports our efforts on designing and developing a Web service of pass-through authentication (PTA) for 12 online electronic-payment Web applications. In accordance with how a PTA service is developed and integrated with a corresponding back-end e-payment system, our strategies can be categorized in three stages: end-to-end integration stage, Web-services-enabled stage, and Web-services-oriented stage. Derived from real-world industrial experience, this three-stage pathway can be applied to a broad range of Web-application development projects to guide smooth transformation from a specific application-oriented design and development model toward a reusable Web-services-oriented model. Furthermore, this paper contributes to an engineering process that leads to practical Web-services-oriented software development. New research issues revealed by this project are also reported. View full abstract»

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  • Development and Evaluation of a Bayesian Low-Vision Navigation Aid

    Page(s): 970 - 983
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    Way finding in unfamiliar environments can pose a challenge to anyone but can be particularly challenging to someone who has some sort of visual loss. In this paper, we describe an indoor navigation aid that uses Bayesian statistics to localize and guide an individual from an unspecified location within a building to a specific destination. We also present three studies investigating the efficacy of this system as a low-vision navigation aid. Two studies were conducted in virtual indoor buildings using desktop virtual reality (VR) and one study was conducted in a real building. All three studies investigated navigation performance with versus without the navigation aid. In all three studies, subjects traveled a shorter distance with the navigation aid than without it. In the VR studies, the navigation aid actually improved performance over navigating with normal vision. View full abstract»

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  • Human Body Posture Classification by a Neural Fuzzy Network and Home Care System Application

    Page(s): 984 - 994
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    A new classification approach for human body postures based on a neural fuzzy network is proposed in this paper, and the approach is applied to detect emergencies that are caused by accidental falls. Four main body postures are used for posture classification, including standing, bending, sitting, and lying. After the human body is segmented from the background, the classification features are extracted from the silhouette. The body silhouette is projected onto horizontal and vertical axes, and then, a discrete Fourier transform is applied to each projected histogram. Magnitudes of significant Fourier transform coefficients together with the silhouette length-width ratio are used as features. The classifier is designed by a neural fuzzy network. The four postures can be classified with high accuracy according to experimental results. Classification results are also applicable to home care emergency detection of a person who suddenly falls and remains in the lying posture for a period of time due to experiments that were performed. View full abstract»

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  • Teams, Computer Modeling, and Design

    Page(s): 995 - 1004
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    This paper presents selected findings from a three-year research project that was funded by the Human Sciences domain of the U.K. Ministry of Defence's scientific research program. A significant number of military systems are operated by teams of varying sizes, and there is a trend toward greater teamwork in the future, as technological advances enable enhanced cooperation between geographically distributed personnel. The need to be able to determine the most appropriate team structure for the most effective performance is becoming greater. The approach that is presented here has taken theoretical concepts from the team performance literature, developed them into an enhanced theoretical formulation, operationalized them, selected representative tradeoff criteria, and implemented them using a computer-modeling tool. The program that was undertaken was able to demonstrate that operationalizing team structure and team-performance-shaping factors in specific behavioral terms in this way has immense potential to generate quantitative output, allowing meaningful comparisons among design or operational alternatives. In addition, the discipline of the operationalization process provides a means for enriching theoretical concepts by grounding them in realistic behavioral terms, and this can lead to enhanced theorizing. Furthermore, once the initial data are collected and the model is built, modification is neither labor nor time intensive. The approach could be developed further to apply to many more team structure and performance concepts. We believe that this will enhance both the theory and the value of team-structure modeling for practical application in system design in the future. View full abstract»

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  • On the Time Series K-Nearest Neighbor Classification of Abnormal Brain Activity

    Page(s): 1005 - 1016
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    Epilepsy is one of the most common brain disorders, but the dynamical transitions to neurological dysfunctions of epilepsy are not well understood in current neuroscience research. Uncontrolled epilepsy poses a significant burden to society due to associated healthcare cost to treat and control the unpredictable and spontaneous occurrence of seizures. The objective of this study is to develop and present a novel classification technique that is used to classify normal and abnormal (epileptic) brain activities through quantitative analyses of electroencephalogram (EEG) recordings. Such technique is based on the integration of sophisticated approaches from data mining and signal processing research (i.e., chaos theory, k-nearest neighbor, and statistical time series analysis). The proposed technique can correctly classify normal and abnormal EEGs with a sensitivity of 81.29% and a specificity of 72.86%, on average, across ten patients. Experimental results suggest that the proposed technique can be used to develop abnormal brain activity classification for detecting seizure precursors. Success of this study demonstrates that the proposed technique can excavate hidden patterns/relationships in EEGs and give greater understanding of brain functions from a system perspective, which will advance current diagnosis and treatment of epilepsy. View full abstract»

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  • Enhancing Human Face Detection by Resampling Examples Through Manifolds

    Page(s): 1017 - 1028
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (592 KB) |  | HTML iconHTML  

    As a large-scale database of hundreds of thousands of face images collected from the Internet and digital cameras becomes available, how to utilize it to train a well-performed face detector is a quite challenging problem. In this paper, we propose a method to resample a representative training set from a collected large-scale database to train a robust human face detector. First, in a high-dimensional space, we estimate geodesic distances between pairs of face samples/examples inside the collected face set by isometric feature mapping (Isomap) and then subsample the face set. After that, we embed the face set to a low-dimensional manifold space and obtain the low-dimensional embedding. Subsequently, in the embedding, we interweave the face set based on the weights computed by locally linear embedding (LLE). Furthermore, we resample nonfaces by Isomap and LLE likewise. Using the resulting face and nonface samples, we train an AdaBoost-based face detector and run it on a large database to collect false alarms. We then use the false detections to train a one-class support vector machine (SVM). Combining the AdaBoost and one-class SVM-based face detector, we obtain a stronger detector. The experimental results on the MIT + CMU frontal face test set demonstrated that the proposed method significantly outperforms the other state-of-the-art methods. View full abstract»

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  • Visual Interactive Systems for End-User Development: A Model-Based Design Methodology

    Page(s): 1029 - 1046
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    This paper is about the development of systems whose end users are professional people working in a specific domain (e.g., medicine, geology, mechanical engineering); they are expert in that domain, but not necessarily expert in nor even conversant with computer science. In several work organizations, end users need to tailor their software systems to better adapt them to their requirements and even to create or modify software artifacts. These are end-user development activities and are the focus of this paper. A model of the interaction between users and systems, which also takes into account their reciprocal coevolution during system usage, is discussed. This model is used to define a methodology aimed at designing software environments that allow end users to become designers of their own tools. The methodology is illustrated by discussing two experimental cases. View full abstract»

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  • The Effect of Color-Contrasting Shadows on a Dynamic 3-D Laparoscopic Surgical Task

    Page(s): 1047 - 1053
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (293 KB)  

    Laparoscopic surgery is performed using long instruments that enter the abdomen through small incisions while viewing the workspace on a video monitor. Because of the viewing limitations that are inherent in the imaging system, depth perception is severely limited compared to direct viewing in open surgery. Previous studies have demonstrated that the addition of shadows can improve performance in tasks under laparoscopic conditions. This study examined the effect of color-contrasting shadows on performance in a depth-perception-dependent laparoscopic task. It was hypothesized that the added contrast of colored shadows would make them more pronounced on the dark-red background found in the body, thus improving performance. Twenty-four novice participants performed a dynamic pick-and-place task under three different lighting conditions on two differently colored backgrounds. Results showed that the presence of both colored and black shadows improved performance by 10% compared to no shadows, but the colored shadows did not provide a significant advantage over the black shadows. View full abstract»

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  • Web Navigation Prediction Using Multiple Evidence Combination and Domain Knowledge

    Page(s): 1054 - 1062
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (520 KB)  

    Predicting users' future requests in the World Wide Web can be applied effectively in many important applications, such as web search, latency reduction, and personalization systems. Such application has traditional tradeoffs between modeling complexity and prediction accuracy. In this paper, we study several hybrid models that combine different classification techniques, namely, Markov models, artificial neural networks (ANNs), and the All-Kth-Markov model, to resolve prediction using Dempster's rule. Such fusion overcomes the inability of the Markov model in predicting beyond the training data, as well as boosts the accuracy of ANN, particularly, when dealing with a large number of classes. We also employ a reduction technique, which uses domain knowledge, to reduce the number of classifiers to improve the predictive accuracy and the prediction time of ANNs. We demonstrate the effectiveness of our hybrid models by comparing our results with widely used techniques, namely, the Markov model, the All-Kth-Markov model, and association rule mining, based on a benchmark data set. View full abstract»

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  • Review of Low Frame Rate Effects on Human Performance

    Page(s): 1063 - 1076
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (471 KB)  

    In this paper, we conducted a comprehensive survey of the effects of different frame rates (FRs) on human performance and reviewed more than 50 studies and summarized them in the areas of psychomotor performance, perceptual performance, behavioral effects, and subjective perception. Overall, there seems to be strong support for a threshold of around 15 Hz for many tasks, including those that are psychomotor and perceptual in nature. Less impressive yet acceptable performance may be accomplished at around 10 Hz for many tasks. Subjective reactions to the quality and watchability of videos seem to support rates of 5 Hz, although videos presented at 15 Hz and above are generally more widely preferred. These generalizations regarding superior and acceptable FRs may also be subject to the effects of several moderating factors such as display characteristics, nature of the tasks, viewing condition, additional cues, and user experience. View full abstract»

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  • Fuzzy System Learned Through Fuzzy Clustering and Support Vector Machine for Human Skin Color Segmentation

    Page(s): 1077 - 1087
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1300 KB)  

    This paper proposes a Fuzzy System learned through Fuzzy Clustering and Support Vector Machine (FS-FCSVM). The FS-FCSVM is a fuzzy system constructed by fuzzy if-then rules with fuzzy singletons in the consequence. The structure of FS-FCSVM is constructed by fuzzy clustering on the input data, which helps to reduce the number of rules. Parameters in FS-FCSVM are learned through a support vector machine (SVM) for the purpose of achieving higher generalization ability. In contrast to nonlinear kernel-based SVM or some other fuzzy systems with a support vector learning mechanism, both the number of parameters/rules in FS-FCSVM and the computation time are much smaller. FS-FCSVM is applied to skin color segmentation. For color information representation, different types of features based on scaled hue and saturation color space are used. Comparisons with a fuzzy neural network, the Gaussian kernel SVM, and mixture of Gaussian classifiers are performed to show the advantage of FS-FCSVM. View full abstract»

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  • Improve Computer-Aided Diagnosis With Machine Learning Techniques Using Undiagnosed Samples

    Page(s): 1088 - 1098
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (658 KB)  

    In computer-aided diagnosis (CAD), machine learning techniques have been widely applied to learn a hypothesis from diagnosed samples to assist the medical experts in making a diagnosis. To learn a well-performed hypothesis, a large amount of diagnosed samples are required. Although the samples can be easily collected from routine medical examinations, it is usually impossible for medical experts to make a diagnosis for each of the collected samples. If a hypothesis could be learned in the presence of a large amount of undiagnosed samples, the heavy burden on the medical experts could be released. In this paper, a new semisupervised learning algorithm named Co-Forest is proposed. It extends the co-training paradigm by using a well-known ensemble method named Random Forest, which enables Co-Forest to estimate the labeling confidence of undiagnosed samples and easily produce the final hypothesis. Experiments on benchmark data sets verify the effectiveness of the proposed algorithm. Case studies on three medical data sets and a successful application to microcalcification detection for breast cancer diagnosis show that undiagnosed samples are helpful in building CAD systems, and Co-Forest is able to enhance the performance of the hypothesis that is learned on only a small amount of diagnosed samples by utilizing the available undiagnosed samples. View full abstract»

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  • Technology-Assisted Learning and Learning Style: A Longitudinal Field Experiment

    Page(s): 1099 - 1112
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (570 KB)  

    From a student's perspective, technology-assisted learning provides convenient access to interactive contents in a hyperlinked multimedia environment that allows increased control over the pace and timing of the presented material. Previous research examining different aspects of technology-assisted learning has found equivocal results concerning its effectiveness and outcomes. We extend prior studies by conducting a longitudinal field experiment to compare technology-assisted with face-to-face learning for students' learning of English. Our comparative investigation focuses on learning effectiveness, perceived course learnability, learning-community support, and learning satisfaction. In addition, we analyze the effects of different learning styles in moderating the effectiveness of and satisfaction with technology-assisted learning. Overall, our results show significantly greater learning effectiveness with technology-assisted learning than with conventional face-to-face learning. Learning style has noticeable influences on the effectiveness and outcomes of technology-assisted learning. We also observe an apparently important interaction effect with the medium for delivery, which may partially explain the equivocal results of previous research. View full abstract»

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  • Sociocultural Games for Training and Analysis

    Page(s): 1113 - 1130
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1708 KB)  

    This paper presents a theory for role-playing simulation games intended to support analysts (and trainees) with generating and testing alternative competing hypotheses on how to influence world conflict situations. Simulated leaders and followers capable of playing these games are implemented in a cognitive modeling framework, called the Performance Moderator Function Server (PMFserv), which covers value systems, personality and cultural factors, emotions, relationships, perception, stress/coping style, and decision making. Of direct interest, as Section I-A explains, is codification and synthesis of best-of-breed social-science models within PMFserv to improve the internal validity of agent implementations. Sections II and III present this for leader profiling instruments and group-membership decision making, respectively. Section IV then offers two real-world case studies (The Third Crusade and SE Asia Today) where agent models are subjected to Turing and correspondence tests under each case study. In sum, substantial effort on game realism, best-of-breed social-science models, and agent validation efforts is essential if analysis and training tools are to help explore cultural issues and alternative ways to influence outcomes. Such exercises, in turn, are likely to improve the state of the science as well. View full abstract»

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  • Sliding Mode Control of Kicking a Soccer Ball in the Sagittal Plane

    Page(s): 1131 - 1139
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (229 KB) |  | HTML iconHTML  

    Collision modeling and control are important aspects of simulation of many human and robotic tasks. A scientific inquiry into a foot-ball collision is made in this paper from the perspective of dynamics, control, modeling, and simulation. As an extension of the Hertzian contact model, our generalized compliant collision model with nonlinear elasticity and damping is tested by a human lower limb kicking a soccer ball. The experiment-based elasticity is used to model the energy transfer of the foot-ball collision and overcome some problems caused by impulse impact modeling. The nonlinear damping in proportion to a restitution-related constant eliminates impact discontinuity. A robust sliding mode controller is developed to track the preplanned trajectory against modeling uncertainties and impact disturbances. The collision duration (about 0.014 s), the ball departure velocity (31.83 m/s), the average foot-ball collision force (about 975.5 N), and the ball peak deformation (about 0.079 m) obtained by simulation match the reported results. The observed three phases of the foot-ball collision are confirmed by our simulation, and the ldquofollow-throughrdquo phenomenon in sports is demonstrated. View full abstract»

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Aims & Scope

The fields of systems engineering and human machine systems: systems engineering includes efforts that involve issue formulation, issue analysis and modeling, and decision making and issue interpretation at any of the lifecycle phases associated with the definition, development, and implementation of large systems.

 

This Transactions ceased production in 2012. The current retitled publication is IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Dr. Witold Pedrycz
University of Alberta