A study on effects of knowledge management on organizational entrepreneurship: A case study of educational system

Knowledge management plays an important role in business development specially in educational system. The proposed study designs and distributes a questionnaire among experts who are involved in education systems in province of Tehran, Iran. The population of this survey includes 1680 people who are enrolled in administration levels of this province and using a simple sapling technique is calculated as 313. The questionnaire consists of 30 questions in Likert scale and there are six categories for the proposed study of this paper including the concept of knowledge, management, knowledge tools, knowledge measurement, change management, knowledge content. We have used LISREL software package to find the relationship between entrepreneurship and knowledge management components. Based on the results of this survey, knowledge content is number one priority followed by knowledge tools and concept of knowledge. The other factors including management, knowledge measurement and change management are in lower levels of importance

Dynamics and Model-Based Control of Electric Power Steering Systems

Many automobile manufacturers are switching to Electric Power Steering (EPS) systems for their better performance and cost advantages over traditional Hydraulic Power Steering (HPS) systems. EPS compared to HPS offer lower energy consumption, lower total weight, and package flexibility at no cost penalty. Furthermore, since EPS systems can provide assistance to drivers independent of the vehicle driving conditions, new technologies can be implemented to improve the steering feel and safety, simultaneously. In this thesis, a neuromusculoskeletal driver and a high-fidelity vehicle model are developed in MapleSim to provide realistic simulations to study the driver-vehicle interactions and EPS systems. The vehicle model consists of MacPherson and multilink suspensions at front and rear equipped with a column-type EPS system. The driver model is a fully neuromusculoskeletal model of a driver arm holding the steering wheel, controlled by the driver's central nervous system. A hierarchical approach is used to capture the complexity of the neuromuscular dynamics and the central nervous system in the coordination of the driver's upper extremity activities. The proposed motor control framework has three layers: the first layer, or the path-planning layer, plans a desired vehicle trajectory and the required steering angles to perform the desired trajectory, the second layer (or the force distribution controller) actuates the musculoskeletal arm, and the final layer is added to ensure the precision control and disturbance rejection of the motor control units. The overall goal of this thesis is to study vehicle-driver interactions and to design a model-based EPS controller that considers the driver's characteristics. To design such an EPS controller, the high-fidelity driver-vehicle model is simplified to reduce the computational burden associated with the multibody and biomechanical systems. Then, four driver types are introduced based on the physical characteristics of drivers such as age and gender, and the corresponding parameters are incorporated in the model. Last but not least, a new model-based EPS controller is developed to provide appropriate assistance to each of the predefined driver types. To do this, the characteristic curves are tuned using a systematic optimization procedure to provide appropriate assistance to drivers with different physical strength, in order to have a similar road and steering feel. In this thesis, it is recommended that muscle fatigue be used as a measure of steering feel. Then, based on the tuned EPS characteristic curves, an observer-based optimal disturbance rejection controller, consisting of a linear quadratic regulator controller and a Kalman filter observer augmented with a shaping filter, is developed to deliver the assistance while attenuating external disturbances. The results show that it is possible to develop a model-based EPS controller that is optimized for a given driver population

Inverse Dynamics Modelling of Paralympic Wheelchair Curling

Accepted author manuscript version reprinted, by permission, from Journal of Applied Biomechanics, 2017 (ahead of print) 1-19, http://dx.doi.org/10.1123/jab.2016-0143. © Human Kinetics, Inc.Paralympic wheelchair curling is an adapted version of Olympic curling played by individuals with spinal cord injuries, cerebral palsy, multiple sclerosis, and lower extremity amputations. To the best of the authors’ knowledge, there has been no experimental or computational research published regarding the biomechanics of wheelchair curling. Accordingly, the objective of this research was to quantify the angular joint kinematics and dynamics of a Paralympic wheelchair curler throughout the delivery. The angular joint kinematics of the upper extremity were experimentally measured using an inertial measurement unit system; the translational kinematics of the curling stone were additionally evaluated with optical motion capture. The experimental kinematics were optimized to satisfy the kinematic constraints of a subject-specific multibody biomechanical model. The optimized kinematics were subsequently used to compute the resultant joint moments via inverse dynamics analysis. The main biomechanical demands throughout the delivery (i.e., in terms of both kinematic and dynamic variables) were about the hip and shoulder joints, followed sequentially by the elbow and wrist. The implications of these findings are discussed in relation to wheelchair curling delivery technique, musculoskeletal modelling, and forward dynamic simulations.This research was funded by Dr. John McPhee’s Tier I Canada Research Chair in Biomechatronic System Dynamics

A model-based approach to predict muscle synergies using optimization: application to feedback control

This Document is Protected by copyright and was first published by Frontiers. All rights reserved. it is reproduced with permission.This paper presents a new model-based method to define muscle synergies. Unlike the conventional factorization approach, which extracts synergies from electromyographic data, the proposed method employs a biomechanical model and formally defines the synergies as the solution of an optimal control problem. As a result, the number of required synergies is directly related to the dimensions of the operational space. The estimated synergies are posture-dependent, which correlate well with the results of standard factorization methods. Two examples are used to showcase this method: a two-dimensional forearm model, and a three-dimensional driver arm model. It has been shown here that the synergies need to be task-specific (i.e., they are defined for the specific operational spaces: the elbow angle and the steering wheel angle in the two systems). This functional definition of synergies results in a low-dimensional control space, in which every force in the operational space is accurately created by a unique combination of synergies. As such, there is no need for extra criteria (e.g., minimizing effort) in the process of motion control. This approach is motivated by the need for fast and bio-plausible feedback control of musculoskeletal systems, and can have important implications in engineering, motor control, and biomechanics.The authors wish to thank the Natural Sciences and Engineering Research Council of Canada (NSERC) for funding this study

Predictive Simulation of Reaching Moving Targets Using Nonlinear Model Predictive Control

This Document is Protected by copyright and was first published by Frontiers. All rights reserved. it is reproduced with permission.This article investigates the application of optimal feedback control to trajectory planning in voluntary human arm movements. A nonlinear model predictive controller (NMPC) with a finite prediction horizon was used as the optimal feedback controller to predict the hand trajectory planning and execution of planar reaching tasks. The NMPC is completely predictive, and motion tracking or electromyography data are not required to obtain the limb trajectories. To present this concept, a two degree of freedom musculoskeletal planar arm model actuated by three pairs of antagonist muscles was used to simulate the human arm dynamics. This study is based on the assumption that the nervous system minimizes the muscular effort during goal-directed movements. The effects of prediction horizon length on the trajectory, velocity profile, and muscle activities of a reaching task are presented. The NMPC predictions of the hand trajectory to reach fixed and moving targets are in good agreement with the trajectories found by dynamic optimization and those from experiments. However, the hand velocity and muscle activations predicted by NMPC did not agree as well with experiments or with those found from dynamic optimization.The authors would like to thank the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canada Research Chairs program for financial support of this research

Design and evaluation of an observer-based disturbance rejection controller for electric power steering systems

Mehrabi, N., McPhee, J., & Azad, N. L. Design and evaluation of an observer-based disturbance rejection controller for electric power steering systems. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 230(7), 867–884. Copyright © 2015 SAGE. Reprinted by permission of SAGE Publications. http://dx.doi.org/10.1177/0954407015596275The goal of this paper is to develop an observer-based disturbance rejection electric power steering (EPS) controller to provide steering assistance and improve the driver’s steering feel. For the purpose of control design, a control-oriented model of a vehicle with a column-assist EPS system is developed and verified against a high-fidelity multibody dynamics model of the vehicle. The high-fidelity model is used to mimic vehicle dynamics to study controller performance in realistic driving conditions. Then, a linear quadratic Gaussian approach is used to design an EPS optimal controller, in which a Kalman filter estimates the unmeasured steering system’s states and external disturbance. A new formulation for the linear quadratic regulator objective function is proposed to take advantages of the known information about the system dynamics to attenuate the disturbance and magnify the driver’s torque., Finally, the EPS controller is applied to the high-fidelity vehicle model in a software-in-the-loop simulation to evaluate its robustness and performance under realistic conditions. The results show that the proposed controller can effectively reduce the disturbance induced in the steering rack, and simultaneously magnify the driver’s steering torque by use of a bi-linear EPS characteristic curve. Then, to show the disturbance rejection properties of this EPS controller, its performance is compared with H2/H∞ and PID control designs using time and frequency domain analysis.Ontario Centres of Excellence (OCE)Natural Sciences and Engineering Research Council of Canada (NSERC)ToyotaMaplesof

Steering disturbance rejection using a physics-based neuromusculoskeletal driver model

This is an Accepted Manuscript of an article published by Taylor & Francis in Vehicle System Dynamics on 2016-06-17, available online: https://dx.doi.org/10.1080/00423114.2015.1050403The aim of this work is to develop a comprehensive yet practical driver model to be used in studying driver–vehicle interactions. Drivers interact with their vehicle and the road through the steering wheel. This interaction forms a closed-loop coupled human–machine system, which influences the driver's steering feel and control performance. A hierarchical approach is proposed here to capture the complexity of the driver's neuromuscular dynamics and the central nervous system in the coordination of the driver's upper extremity activities, especially in the presence of external disturbance. The proposed motor control framework has three layers: the first (or the path planning) plans a desired vehicle trajectory and the required steering angles to perform the desired trajectory; the second (or the musculoskeletal controller) actuates the musculoskeletal arm to rotate the steering wheel accordingly; and the final layer ensures the precision control and disturbance rejection of the motor control units. The physics-based driver model presented here can also provide insights into vehicle control in relaxed and tensed driving conditions, which are simulated by adjusting the driver model parameters such as cognition delay and muscle co-contraction dynamics.Ontario Centres of Excellence (OCE)Natural Sciences and Engineering Research Council of Canada (NSERC)ToyotaMaplesof

Molecular insights into the compatible and incompatible interactions between sugar beet and the beet cyst nematode

Background: Sugar beet (Beta vulgarissubsp.vulgaris) is an economically important crop that provides nearly one third of the global sugar production. The beet cyst nematode (BCN),Heterodera schachtii, causes major yield losses in sugar beet and other crops worldwide. The most effective and economic approach to control this nematode is growing tolerant or resistant cultivars. To identify candidate genes involved in susceptibility and resistance, the transcriptome of sugar beet and BCN in compatible and incompatible interactions at two time points was studied using mRNA-seq. Results: In the susceptible cultivar, most defense-related genes were induced at 4 dai while suppressed at 10 dai but in the resistant cultivar Nemakill, induction of genes involved in the plant defense response was observed at both time points. In the compatible interaction, alterations in phytohormone-related genes were detected. The effect of exogenous application of Methyl Jasmonate and ET-generator ethephon on susceptible plants was therefore investigated and the results revealed significant reduction in plant susceptibility. Genes putatively involved in the resistance of Nemakill were identified, such as genes involved in phenylpropanoid pathway and genes encoding CYSTM domain-containing proteins, F-box proteins, chitinase, galactono-1,4-lactone dehydrogenase and CASP-like protein. Also, the transcriptome of the BCN was analyzed in infected root samples and several novel potential nematode effector genes were found. Conclusions: Our data provides detailed insights into the plant and nematode transcriptional changes occurring during compatible and incompatible interactions between sugar beet and BCN. Many important genes playing potential roles in susceptibility or resistance of sugar beet against BCN, as well as some BCN effectors with a potential role asavrproteins were identified. In addition, our findings indicate the effective role of jasmonate and ethylene in enhancing sugar beet defense response against BCN. This research provides new molecular insights into the plant-nematode interactions that can be used to design novel management strategies against BCN

Is there a value for probiotic supplements in gestational diabetes mellitus? A randomized clinical trial

Background: Although several studies have found probiotics encouraging in prevention of gestational diabetes mellitus (GDM), the evidence for the use of probiotics in diagnosed GDM is largely limited. The aim of this study was to assess the effect of a probiotic supplement capsule containing four bacterial strains on glucose metabolism indices and weight changes in women with newly diagnosed GDM. Methods: Sixty-four pregnant women with GDM were enrolled into a double-blind placebo-controlled randomized clinical trial. They were randomly assigned to receive either a probiotic or placebo capsule along with dietary advice for eight consecutive weeks. The trend of weight gain along with glucose metabolism indices was assayed. Results: During the first 6 weeks of the study, the weight gain trend was similar between the groups. However, in the last 2 weeks of the study, the weight gain in the probiotic group was significantly lower than in the placebo group (p < 0.05). Fasting blood sugar (FBS) decreased in both intervention (from 103.7 to 88.4 mg/dl) and control (from 100.9 to 93.6 mg/dl) groups significantly, and the decrease in the probiotic group was significantly higher than in the placebo group (p < 0.05). Insulin resistance index in the probiotic group had 6.74 % reduction over the study period (p < 0.05). In the placebo group, however, there was an increase in insulin resistance index (6.45 %), but the observed change in insulin resistance was not statistically significant. Insulin sensitivity index was increased in both groups. The post-intervention insulin sensitivity index in the probiotic group was not significantly different from placebo when adjusted for the baseline levels. Conclusions: The probiotic supplement appeared to affect glucose metabolism and weight gain among pregnant women with GDM. This needs to be confirmed in other settings before a therapeutic value could be approved