By Topic

Networking, Sensing and Control (ICNSC), 2010 International Conference on

Date 10-12 April 2010

Filter Results

Displaying Results 1 - 25 of 140
  • Automatic speed-bias correction with flow-density relationships

    Page(s): 1 - 7
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (785 KB) |  | HTML iconHTML  

    Accurate and reliable speeds measured with local traffic sensors are critically important for many applications, such as travel time estimation, state estimation and prediction and dynamic traffic control. Many local sensors (e.g. the dual induction loops used in The Netherlands, UK and in Germany) calculate average speed by arithmetic time averaging, which leads to strongly biased estimates. This paper proposes a speed-bias correction algorithm based on notions from first order traffic flow theory and empirical flow-density relationships, using only a limited number of parameters. On the basis of a microscopic simulation study, it is demonstrated that this algorithm is able to correct the speed bias due to time averaging considerably. A more extensive version of this paper can be found at http://dux.ict.tbm.tudelft.nl/Research/SpeedCorr.pdf. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An efficient model-based method for coordinated control of urban traffic networks

    Page(s): 8 - 13
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (490 KB) |  | HTML iconHTML  

    Traffic control is an effective and also efficient approach to reduce traffic jams. To alleviate the traffic congestion in an urban traffic network, a traffic control strategy that can coordinate the whole traffic network from a global point of view, is required. In this paper, an advanced control strategy, i.e. Model Predictive Control (MPC), is applied to control and coordinate urban traffic networks. However, the on-line computational complexity becomes a big challenge when the scale of the traffic network gets larger. To overcome this problem, the MPC control strategy is reformulated and solved efficiently on-line by a Mixed-Integer Linear Programming (MILP) solver. An MPC controller based on MILP is established and studied for the urban traffic network in different traffic scenarios. The simulation results show that the MILP-based MPC controller is a promising approach to reduce the on-line computational complexity of MPC controllers for urban traffic networks. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Granular value-function approximation for road network traffic control

    Page(s): 14 - 19
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (489 KB) |  | HTML iconHTML  

    The research discussed in this paper aims at developing fast stable learning agents for large-scale complex systems including network traffic signal control systems. The control system is based on reinforcement learning (RL), an important research area in distributed AI with a wide area of applications including real-time control. RL-based control may also be suitable for distributed domains that are subject to time and environmental contingencies. Based on this assumption, the goal in this paper is to investigate ways to make RL excel at on-line, continuous state and action space tasks by incorporating the concept of fuzzy granulation as (powerful) function approximation tool: we argue why this may strongly improve the learning speed of the algorithm. The potential implications of this research are better running times, allowing us to consider much larger problem sizes. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A distributed simulator for road network control

    Page(s): 20 - 25
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (965 KB) |  | HTML iconHTML  

    This paper is about a distributed implementation of a road traffic simulator. The simulator will be used in an integrated, operational system for road traffic monitoring, visualization, prediction and control. The distributed implementation is needed in order to make the simulator scalable (especially with respect to road network size) and to make it comply with real-time requirements stemming from on-line use in control and decision support systems, with emphasis on network control rather than local control. The underlying traffic model is a first order, multi-class model. The implementation has been tested with the network of the Amsterdam A10 beltway. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Architecture-based development of road traffic management systems

    Page(s): 26 - 31
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (479 KB) |  | HTML iconHTML  

    Road traffic problems, such as congestion and accidents, are high in many countries, leading to economic losses, environmental damage due to increased pollution, waste of time in congestion and lives lost. In order to reduce these problems, Road Traffic Management Systems (RTMS) are applied, for example, in activities such as controlling, monitoring, and visualizing traffic in motorways and urban roads. The development of RTMS is challenging. RTMS are large socio-technical systems, which means that organizational and regulatory policies, rules, processes and constraints have to be taken into consideration. This framework needs to be represented in what is called the domain architecture. However, defining the domain architecture relates more to the RTMS domain than to the technical solution. The software architecture is fundamental for the organization of the system, comprising the sub-systems, important software components and the relationship between them and the environment, and to document all important technical decisions. In this article, both the domain and the software architecture are proposed for developing RTMS. The approach is used in practice as shown by the HARS case study. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Improve the positioning accuracy for wireless sensor nodes based on TFDA and TFOA using data fusion

    Page(s): 32 - 37
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (570 KB) |  | HTML iconHTML  

    In wireless sensor networks (WSN), location information acquisition is critical to guarantee their performance. This paper presents the positioning methods in WSN with based on the linear frequency modulation continuous wave (FMCW) techniques. Reference nodes with known locations transmit linear FMCW reference signals, while other sensor nodes estimate their locations based on the time frequency difference arrival (TFDA) or time frequency of arrival (TFOA). The geometric locations of RNs affect the location accuracy. In order to overcome the geometric dilution of precision (GDOP) effect and improve the location accuracy, the data fusion method is proposed. The location estimates from TFDA and TFOA are combined using Bayes rule. The simulation results show that the data fusion method enjoys higher location accuracy. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Optimal network reconfiguration of electrical distribution systems using real coded quantum inspired evolutionary algorithm

    Page(s): 38 - 43
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (563 KB) |  | HTML iconHTML  

    Network reconfiguration is an important tool to optimize the operating conditions of an electrical distribution system. This is accomplished modifying the network structure of distribution feeders by changing the open/close status of sectionalizing switches. This not only reduces the power losses, but also relieves the overloading of the network components. Network reconfiguration belongs to a complex family of problems because of their combinatorial nature and multiple constraints. This paper proposes a solution to this problem, using a Real Coded Quantum Inspired Evolutionary Algorithm (RCQIEA), with a novel codification. In this paper, RCQIEA is tested and compared to an Exhaustive Algorithm (EA), a Heuristic algorithm (HA) and a Genetic Algorithm (GA) on three test systems. Simulation results show that RCQIEA performs better than EA, HA and GA in terms of speed and accuracy. RCQIEA is a highly scalable algorithm as well. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A new method based on the spatial differencing technique for DOA estimation

    Page(s): 44 - 48
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (709 KB) |  | HTML iconHTML  

    In this paper, a new method is presented for DOA estimation of a number of uncorrelated and coherent signals simultaneously impinging on the far field of a uniform linear array (ULA). In the proposed method, the uncorrelated sources are firstly estimated by MUSIC, and then they are eliminated by the spatial dirrerencing technique, finally, the coherent signals are estimated by using ESPRIT based on the spatial differencing matrix. Compare with the previous works, the proposed approach can improve DOA estimation accuracy, as well as increase the maximum number of detectable signals. The performances of some relevant algorithms are compared via simulations, and the effectiveness of the proposed method is verified. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Joint source-channel coding/decoding by combining RVLC and VLC for CCSDS IDC coefficients

    Page(s): 49 - 52
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (478 KB) |  | HTML iconHTML  

    In this paper, we have proposed a joint source-channel coding/decoding approach by combining RVLC and VLC for CCSDS IDC coefficients, which can be applied in space communication. In the CCSDS IDC standard, the DC coefficients are given special protection by using a reversible coding/decoding scheme since they are especially significant for the reconstructed image quality. Specifically, the DC coefficients are encoded by reversible variable length codes (RVLCs) after using alternating run-length encoding, which can simplify the code-table design and decrease the decoding complexity by transforming the variable length coded DC coefficients into very few symbols. Simulation results show that this approach can greatly alleviate error propagation and improve the error-resilient performance of the DC coefficients, which can greatly improve the transmitted image quality. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Research on the precision processing method for softness abrasive two-phase flow based on LSM

    Page(s): 53 - 57
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (533 KB) |  | HTML iconHTML  

    According to the precision machining problem of the structural surface mould manufacturing process, a method for soft grits two-phase flow precision processing on the level set method (LSM) is proposed. Based on the topological structure transformation of LSM, the mechanics model of liquid-liquid two phase flow in mould structuring surface precision machining was established. And the interface parameters of the abrasive two-phase flow were captured. Combining the Navier-Stokes equation, Volume of fluid Method (VOF) and SIMPLEC algorithm, the basic motion rule and related physical parameters of abrasive two-phase flow are solved. Because the simulation results of speed and pressure changes of the softness abrasive two-phase flow through 90° square bent tube are in accordance with test results of Taylor etc, which validated the effectiveness of proposed method. It contributes to the further research on softness abrasive flow precision machining. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A novel EM-based MAP channel estimation for MIMO-OFDM systems

    Page(s): 58 - 61
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (488 KB) |  | HTML iconHTML  

    For MIMO-OFDM system, expectation maximum (EM) is used to decrease the complexity of maximum a posteriori probability (MAP) channel estimation algorithm. However, EM-based MAP algorithm generates the low mean square error (MSE) performance at high signal noise rate (SNR) because of the convergent feature of EM algorithm. According to this issue, a modified EM-based MAP (MEM-MAP) channel estimation algorithm is proposed. The proposed algorithm improves convergent property of EM algorithm at high SNR by introducing an equivalent model. Then, according to the idea that MIMO channels in angle domain can be assumed to be independent, most significant taps (MST) technique in angle domain is used to improve the MSE performance of MEM-MAP algorithm. Simulation results indicate the effectiveness of the proposed algorithm. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Split torque type gearbox fault detection using acoustic emission and vibration sensors

    Page(s): 62 - 66
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (978 KB) |  | HTML iconHTML  

    In comparison with a traditional planetary gearbox, the split torque gearbox (STG) potentially offers lower weight, increased reliability, and improved efficiency. These benefits have driven the helicopter OEMs to develop products using the STG. However, this may pose a challenge for the current gear analysis methods used in Health and Usage Monitoring Systems (HUMS). Gear analysis uses time synchronous averages to separates in frequency gears that are physically close to a sensor. The effect of a large number of synchronous components (gears or bearing) in close proximity may significantly reduce the fault signal (decreased signal to noise) and therefore reduce the effectiveness of current gear analysis algorithms. As of today, only a limited research on STG fault diagnosis using vibration sensors has been conducted. In this paper, an investigation on STG fault detection using both vibration and acoustic emission (AE) sensors is reported. In particular, signals of both vibration and AE sensors on a notational STG type gearbox were collected from seeded fault tests. Gear fault features were extracted from vibration signals using a Hilbert-Huang Transform (HHT) based algorithm and from AE signals using AE analysis. These fault features were input to a K-nearest neighbor (KNN) algorithm for fault detection. The investigation results showed that both vibration and AE sensors were capable of detecting the gear fault in a STG. However, in terms of locating the source of the fault, AE sensors outperformed vibration sensors. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Research on fault diagnosis method of blast furnace based on clustering combine SVMs dynamic pruned binary tree

    Page(s): 67 - 70
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (476 KB) |  | HTML iconHTML  

    Since fault diagnosis of blast furnace is very important in manufacturing, in this paper, a new strategy based on clustering combining SVMs pruned binary tree is proposed to solve diagnosis problem in blast furnace. According to the relations of categories in multi-class problem, it is needless to distinguish all the sorts. In order to improve classification efficiency, advantage of clustering and support vector machine is combined. According to the similarity of different samples' sorts, a binary tree is constructed rationally to accelerate fault diagnosis efficiency. The class similarity is determine according to class distance and distribution sphere in feature space, the similarity is used to determine the classification order of hierarchical multi-class classify SVMs. The training samples and corresponding SVMs sub-classifiers are selectively re-constructed to make sure bigger classification margin and good generalization ability. The results of simulation experiments show that the proposed method is faster in training and classifying, better in classification correctness and generalization. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Prognosis-enhanced reconfiguration control

    Page(s): 71 - 75
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (616 KB) |  | HTML iconHTML  

    This paper attempts to make a conceptual illustration of fault prognosis-enhanced reconfiguration control. The definition of fault propagation and the proposed control adaptation algorithm ensuring the mission completion are discussed in this paper, along with some illustrative examples on prognosis-enhanced reconfiguration control of servomechanisms. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A fast detecting algorithm for surface mount devices based on complex moment

    Page(s): 76 - 79
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (665 KB) |  | HTML iconHTML  

    In electronic manufacturing process, Surface Mount Devices, such as Ball Grid Array or Quad Flat Package, are difficult to locate precisely because of image noise. To improve the detecting accuracy, this paper analyzed the difficulties of detecting SMDs and then proposed a new fast detecting algorithm based on complex moment, which utilizes moment invariance to determine the position and angle of Surface Mount Devices and eliminate the locating uncertainty from local noise. The experiments demonstrated that the proposed algorithm can detect Surface Mount Devices' position and angle efficiently and is more reliable than the algorithm based on edge detecting. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Virtual exercise environment for promoting active lifestyle for people with lower body disabilities

    Page(s): 80 - 84
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (703 KB) |  | HTML iconHTML  

    This paper presents the development and evaluation of the use of virtual reality technology, together with appropriately adapted exercise through an augmented reality interface, to create Virtual Exercise Environments (VEEs). These environments allow persons with lower body disabilities to exercise and train just like what people do in real world. This paper presents our current research on VEE to facilitate participation and adherence using a VEE as a prototype, using common-off-the-shelf hardware components. The major aim of this paper is to make exercise more enjoyable and less repetitious for people with lower body disabilities. Responses of 26 participants is presented and analyzed. Based on the responses, people with lower body disabilities showed higher satisfaction with every aspect of the environment than people without disabilities, from which we can conclude that our VEE is more suitable for people with lower body disabilities. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Design of an intelligent control scheme based on predictive theory

    Page(s): 85 - 88
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (579 KB) |  | HTML iconHTML  

    This research work describes an intelligent control scheme for deriving a severe nonlinear system via the predictive control theory. In line with the control scheme proposed, the system behavior is first represented by a multilinear model approach (MLA), while a multi-GPC approach (MGA) is realized based on acquired outcomes. Subsequently, an intelligent decision maker system (IDMS) is realized to derive both the MGA and the MLA, at each instant of time. In this control scheme, the desirable control action in correspondence with the system behavior is instantly updated to apply to the system. In order to display the effectiveness of the proposed control scheme, simulations are carried out and its results are compared with those obtained using the traditional predictive control scheme, as a benchmark approach. The results verify the validity of the control scheme proposed in comparison with the previous one. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Subsensory stimulation and visual/auditory biofeedback for balance control in amputees

    Page(s): 89 - 94
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1036 KB) |  | HTML iconHTML  

    In this study, we hypothesized that the static standing weight bearing steadiness and dynamic walking weight shifting stability could be improved by providing neuromuscular facilitation using subsensory stimulation and visual-auditory biofeedback in amputee respectively. To test this hypothesis, a computer protocol with sensory feedback neuromuscular facilitation system was developed and used for clinical assessment. Seven unilateral transtibial amputees who consecutively worn prosthetics over two years were recruited. Experimental results show a reduction in all of the postural sway related indices and increase in single-leg holding time index during static quiet standing by applying subsensory stimulation. With visual-auditory biofeedback for providing clue for heel contact and toe push-off condition during dynamic ambulation, an improvement in all four dynamic walking weight shifting stability indices in amputees was verified. This study provided evidence that sensory feedback neuromuscular stimulation may put amputees at better balance capability. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A novel reinforcement learning framework for sensor subset selection

    Page(s): 95 - 100
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (575 KB) |  | HTML iconHTML  

    The problem of selecting a subset of sensors in a distributed object tracking environment that optimizes an objective function consisting of a trade-off between data accuracy and energy consumption is known to be NP-hard. The problem is exacerbated because of the uncertainty and dynamic nature of either sensor characteristics or the environment or both. We propose, for the first time, a novel framework based on a reinforcement learning approach, to deal with the problems of computational complexity, dynamic nature and uncertainty for sensor subset selection. Our proposed sensor subset selection approach is completely decentralized and sensors do not need to know even the presence of other sensors in the system. This makes our approach extremely scalable and easy to implement in a distributed system. To the best of our knowledge, this is the first application of reinforcement learning to the domain of sensor subset selection. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Performance modeling of an opportunistic spectrum sharing wireless network with unreliable sensing

    Page(s): 101 - 106
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (526 KB) |  | HTML iconHTML  

    Opportunistic Spectrum Sharing (OSS) has recently attracted increasing interest. We analytically model a wireless network that allows opportunistic spectrum sharing and analyze its performance through a queueing theoretic framework. The OSS system consists of the secondary users opportunistically sharing a set of spectrum resources with the primary users over a coverage area. The secondary users equipped with cognitive radios sense channels that are unused by the primary users and then make use of the idle channels. An ongoing secondary user also detects when a primary user accesses its channel and then either moves to another idle channel or moves to a waiting pool. Unreliable spectrum sensing is possible which are modeled by false alarm and misdetection events. We solve the steady-state probability of the system and derive several performance metrics of interest. Numerical and simulation results are presented. The proposed modeling method can be used to evaluate the performance of future opportunistic spectrum sharing networks. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A new detecting algorithm for chip based on B-spline wavelet

    Page(s): 107 - 110
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (773 KB) |  | HTML iconHTML  

    Locating and detecting algorithm for chip is important in visual detection of electronic manufacturing process. Its performance directly affects the speed and accuracy of assembling chip on Printed Circuit Board. This paper analyzed the common algorithms' disadvantages in locating accuracy. Then based on the above analysis, a new algorithm was proposed, in which B-spline is used to detect edge accurately and help to mount chip more precisely. Experiment results demonstrated that the proposed algorithm's performance is better than SUSAN and Canny algorithms' in locating accuracy and stability, and can meet the practical demand of mounting chip. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Effective camera motion analysis approach

    Page(s): 111 - 116
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (564 KB) |  | HTML iconHTML  

    Camera motion analysis (CMA) is very useful for many video content analysis tasks, but few works competently handle the videos with significant camera or object motion. In this paper, we present an effective CMA approach for such challenging cases. The effectiveness of our approach comes from two aspects: (1) reliably matching keypoints on consecutively sampled frames, where both the appearance similarity and motion smoothness of keypoints are considered; (2) effectively distinguishing background keypoints from foreground ones by a novel and advanced voting process, where the voting weights of keypoints are dynamically adjusted to guarantee that the influence of foreground motion can be largely reduced in CMA. Thus, a parametric camera motion model can be naturally derived by the accurate estimation of the motion of background keypoints. The experimental results on the TRECV2005 dataset and 500 shots from seven classic action movies demonstrate the effectiveness of our approach. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • FM jammer excision by using time-varying AR filter in spread spectrum communication systems

    Page(s): 117 - 121
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (538 KB) |  | HTML iconHTML  

    The time varying jammer signal degrades the performance of spreading spectrum communication systems. In this paper, time-varying autoregressive (TV-AR) modelling is used to represent nonstationary jammer signals. The modelling approach leads to an effective technique for jammer excision. In this work, jammer components parameterized by their instantaneous frequencies (IF) are effectively removed using the TV-AR filtering. The approach results in a minimum distortion to the desired DS/SS signals in communications. In order to reduce the computation complexity, orthogonal polynomials are used for the basis function of TV-AR model. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Compressive sensing approach based mapping and localization for mobile robot in an indoor wireless sensor network

    Page(s): 122 - 127
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (932 KB) |  | HTML iconHTML  

    Reliable navigation in the Wireless Sensor Networks (WSNs) always require mobile robot do localization and environment map building processes, which depends heavily on estimating the position of the features within the entire surroundings, that means as a sensor receiving platform, the robot needs to detect and process information transmitted from sensors as much as possible, in order to perform tasks. However, some large and complex deployed wireless sensor network environments, in which sensor information are relatively sparse compared with the number of sensor sources, usually make the robot hard to receive enough crucial information. To make robot know its position and construct the environment map with minimal sensing information. We propose a novel navigation algorithm based on RF wireless sensor networks to simultaneous localization and mapping (SLAM) approach, thus, a new framework that allows a team of robots to build a map of the parameter of interest with a small number of measurements is presented. By using the recent results in the area of compressive sensing, we show how the robots can build a map with limited number of sensing measurements. The proposed algorithm is conceptually simple and easy to implement. Simulation and experimental results show that good result can be achieved using the proposed method. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Simultaneous localization and mapping (SLAM) for indoor autonomous mobile robot navigation in wireless sensor networks

    Page(s): 128 - 132
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1048 KB) |  | HTML iconHTML  

    Recently, considerable attention has been focused on the investigation of the use of wireless sensor networks (WSN) to drive mobile robot for efficient exploration in unknown environments. The process of navigation depends heavily on estimating the position of the features provided by sensor within the entire environment. This paper proposes a novel navigation algorithm based on RF wireless sensor networks to simultaneous localization and mapping (SLAM) for an indoor autonomous mobile robot. Triangulation localization method is employed to make the robot locates itself and knows its pose. A simple yet efficient two-step particle filter is applied for map building. Simulation and experimental results show that good localization can be achieved using the proposed method. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.