a. khodayari

 The theory of organizational trauma or organizational crisis, is one of the theories to deal with organizational unrest. Some of these crises show signs of a traumatic experience. If not properly managed, the experience of mass harm appears to disappear under the surface behind the mask of silence, leading to dysfunctional tissue behavior. The aim of the present study is to design an organizational trauma model for Sports Organization in the Municipality of Tehran.

Survey methods are, mixed with exploratory approaches. Qualitative sampling were performed  using the view of 11 faculty / managers and statistical sampling in the snowball sampling method and  quantitative section, considering that  5 to 10 people are required for each item,  so 350 people were selected by stratified random sampling method. The means of collecting data for the qualitative part of the interview was semi-structured, in that the results of the interview were designed in the form of a questionnaire with three main components. Expert content validity and composition validity (exploratory and confirmatory factor analysis) and combined reliability indicators include Cronbach's alpha, divergence and convergence validity, and structural equation modeling, SPSS software Version 23 and LISREL version 8.54 were used.

The results showed the final model in 3 factors: individual factors 26.268, structural and technological 21.517, environmental factors 15.228, which in total had 62.841% predictability. Also individual (T-Value = 11.70, β = 0.93), environmental (T-Value = 12.122, β = 0.92) and structural factors (T-Value = 9.91, = 0.76) b) had a significant effect on the concept of organizational trauma. In the goodness-of-fit test, a total of seven indicators of model fit were confirmed, so all three identified factors can be integrated into the structural model of the research.

The results presented in this paper insinuate that in-service training, salaries and benefits based on organizational position and years of service and taking into account various environmental factors can be fruitful in developing the proposed model.

In recent years, the utilization of Information Technology (IT) in various sportive areas, especially football, has increased. Therefore, this study aimed to determine the effects of IT on the quality of Iran Pro League (The highest division of professional football in Iran) referees' performance. The research design of the present study is descriptive-correlational. The statistical population included 200 referees working in Iran Pro League in 2017 and it is a finite population (N=20). The questionnaires of accepting and applying IT as well as the Supervision and Monitoring form were used to measure the studied variables in the research. The Sign test was used for comparing the referees' performances before and after utilizing IT. The multivariate regression analysis was used for investigating the relationships and SPSS software version 23 was used to analyze the results. The significance level was considered P<0.05. The results of this research showed that the performance difference among referees before and after utilizing IT is significant (Sig=0.001). Also, the findings suggest that there is a positive and significant relationship between the utilization of IT and the quality of referees' performance (Sig=0.001). Among the subscales of IT, the highest share of clarification belongs to the subscale of willingness of applying IT with regression coefficient 0.567 and other subscales like understanding the easiness of applying IT (0.531), the attitude towards IT (0.460), understanding the usefulness of IT (0.416) and the utilization of IT (0.388) follow, respectively. Based on the results of the research, the authorities of the referee committee are advised to utilize the instructions related to the utilization of IT for decreasing referees' mistakes.

The purpose of this paper is to design and optimize an intelligent fuzzy-logic controller for a three-degree of freedom (3DOF) artificial finger with shape-memory alloy (SMA) wire actuators. The robotic finger is constructed using three SMA wires as tendons to bend each phalanx of the finger around its revolute joint and three torsion springs which return the phalanxes to their original positions. A PID controller is designed to control the rotation of each phalanx. The gains of the controller are defined and optimized using the genetic algorithm. Finally, a fuzzy PID controller is presented to improve the performance of the system. The performance of the designed controller to achieve the desired output is simulated and also tested. The rotation of each link of both prototype robot and simulated model is measured. The experimental results show that the fuzzy controller can reach the desired angle in less time and the output signal is uniform. Moreover, the simulation results indicate that the closed-loop control system of the simulated robot is in good agreement with the prototype robot.

One of the best vibration control methods using smart actuators are semi-active approaches which are as strong as active methods and need no external energy supply such as passive ones. Compared with piezoelectric-based, magnetostrictive-based control methods have higher coupling efficiency, higher Curie temperature, higher flexibility to be integrated with curved structures and no depolarization problems. Semi-active methods are well-developed for piezoelectrics but magnetostrictive-based approaches are not as efficient, powerful and well-known as piezoelectric-based methods.  The aim of this work is to propose a powerful semi-active control method using magnetostrictive actuators. In this paper a new type of semi-active suppression methods using magnetostrictive materials is introduced which contains an equipped vibrating structure with magnetostrictive patches wound by a pick-up coil connected to an electronic switch and a capacitor. The novelty of the proposed damping method is switching on the coil current signal using mentioned switch and capacitor which is briefly named SSDC (synchronized switch damping on capacitor). In this paper the characteristics of the semi-active pulse-switching damping technique with magnetostrictive materials are studied and numerical results show significant damping for almost all types of excitations.

The Global Positioning System (GPS) and an Inertial Navigation System (INS) are two basic navigation systems. Due to their complementary characters in many aspects, a GPS/INS integrated navigation system has been a hot research topic in the recent decade. The Micro Electrical Mechanical Sensors (MEMS) successfully solved the problems of price, size and weight with the traditional INS. Therefore they are commonly applied in GPS/INS integrated systems. The biggest problem of MEMS is the large sensor errors, which rapidly degrade the navigation performance in an exponential speed. Three levels of GPS/IMU integration structures, i.e. loose, tight and ultra tight GPS/IMU navigation, are proposed by researchers. The loose integration principles are given with detailed equations as well as the basic INS navigation principles. The Extended Kalman Filter (EKF) is introduced as the basic data fusion algorithm, which is also the core of the whole navigation system to be presented. The kinematic constraints of land vehicle navigation, i.e. velocity constraint and height constraint, are presented. A detailed implementation process of the GPS/IMU integration system is given. Based on the system model, we show the propagation of position standard errors with the tight integration structure under different scenarios. A real test with loose integration structure is carried out, and the EKF performances as well as the physical constraints are analyzed in detail.

In this paper, the behavior of one chain of small heat shock protein based on molecular dynamic simulation is modeled by the nonlinear identifier. Molecular dynamic simulation is timeconsuming due to the high load of calculations, and providing a model of system behavior facilitates utilizing protein as a bio nano robot in a shorter time. The ARC1 is a molecular Chaperone with swarm structure containing 12 chains. Each chain of small heat shock protein contains two sections; arm and the central cavity which is introduced as a bionanorobot for their special biological structure and their reaction to external forces. The conformational changes of protein with one chain due to external excitation have been analyzed. In addition to system identification of one chain of small heat shock protein, the effect of temperature, pH, and content of solvent are examined on the behavior of bionanorobot arm and a central cavity in a wide range of variation. The results show that minimum number of error is relevant to the adaptive neuro fuzzy system identifier. Modeling the behavior of one chain provides a suitable condition to control the central cavity and bionanorobot arm in a shorter period of time compared to the molecular dynamic simulation.

Advanced Driver Assistance Systems (ADAS) benefit from current infrastructure to discern environmental information. Traffic signs are global guidelines which inform drivers from near characteristics of paths ahead. Traffic Sign Recognition (TSR) system is an ADAS that recognize traffic signs in images captured from road and show information as an adviser or transmit them to other ADASs. In this paper presents a novel machine vision algorithm for traffic sign recognition based on fuzzy sets. This algorithm is a pipeline consists of multiple fuzzy set that create a fuzzy space here called Super Fuzzy Set (SFS). SFS helped to design a flexible and fast algorithm for recognizing traffic signs in a real-time application. Designed algorithm was implemented in computer-based system and checked on a test car in real urban environment. 83.34% accuracy rate was obtained in real-time test.

In recent years due to improvements of technology within automobile industry, design process of advanced driver assistance systems for collision avoidance and traffic management has been investigated in both academics and industrial levels. Detection of traffic signs is an effective method to reach the mentioned aims. In this paper a new intelligent driver assistance system based on traffic sign detection with Persian context is designed. The main goal of this system is to assist drivers to choose their path based on traffic signs more precisely. To reach this purpose, a new framework by using of fuzzy logic was used for detection of traffic signs in videos which have has been captured from a vehicle path in highways. Fuzzy logic increases inference and intelligent capabilities in smart systems to make correct decision making in online conditions. Then, the combination of Maximally Stable Extermal Regions (MSER) and Canny Edge Detector Algorithms are used to detect road sign’s texts detection. MSER algorithm is aimed at assists to detect regions in an image that differ in properties, for example in brightness or color, compared to surrounding regions. Also, canny edge detector uses a multi-stage algorithm to detect a wide range of edges in the images. Thereafter, morphological mask operator is used to join individual characters for final detection of texts in the traffic signs. Finally, MATLAB Optical Character Recognition (OCR) is employed to recognize the detected texts. This new framework gives an overall text detection and recognition rate of .

Due to the increasing demand for traveling in public transportation systems and increasing traffic of vehicles, nowadays vehicles are getting to be intelligent to increase safety, reduce the probability of accident and also financial costs. Therefore, today, most vehicles are equipped with multiple safety control and vehicle navigation systems. In the process of developing such systems, simulation has become a cost-effective chance for the fast evolution of computational modeling techniques. The most popular microscopic traffic flow model is car following models which are increasingly being used by transportation experts to evaluate new Intelligent Transportation System (ITS) applications. The control of car following is essential to its safety and its operational efficiency. This paper presents a car-following control system that was developed using a fuzzy model predictive control (FMPC). This system was used to simulate and predict the future behavior of a Driver-Vehicle-Unit (DVU) and was developed based on a new idea to calculate and estimate the instantaneous reaction of a DVU. At the end, for experimental evaluation, the FMPC system was used along with a human driver in a driving simulator. The results showed that the FMPC has better performance in keeping the safe distance in comparison with real data of human drivers behaviors. The proposed model can be recruited in driver assistant devices, safe distance keeping observers, collision prevention systems and other ITS applications.

In this paper a control system has been designed to improve traffic conditions in car following maneuver. There are different methods to design a control system. In this paper design approach is based on the Fuzzy sliding mode control (FSMC) system. The aim of designing FSMC system is to achieve safe and desire longitudinal distance and less lateral displacement. In order to control and obtain desired longitudinal and lateral movements, suitable values of composite torque and steering angle is generated. At first to design of FSMC system, a nonlinear dynamics model of vehicle with three degrees of freedom is presented and validated with real traffic data. Then, the performance of the FSMC system has been evaluated by real car following data. At the end, the simulation results of FSMC are compared with the first and second order sliding mode control. Simulation result shows that performance of FSMC is better than sliding mode control. Also by comparing between FSMC and real driver, it is shown that FSMC is much safer than a real human driver in keeping the longitudinal distance and also the FSMC produces less lateral displacement in the lateral movement too.

Overtaking a slow lead vehicle is a complex maneuver because of the variety of overtaking conditions and driver behavior. In this study, two novel prediction models for overtaking behavior are proposed. These models are derived based on multi-input multi-output adaptive neuro-fuzzy inference system (MANFIS). They are validated at microscopic level and are able to simulate and predict the future behavior of the overtaking vehicle in real traffic flow. In these models, the kinematic features of Driver-Vehicle-Units (DVUs) such as distance, velocity, and acceleration are used. Unlike the previous models, where some variables of the two involved vehicles are considered to be constant, in this paper, instantaneous values of the variables are considered. The first model predicts the future value of the longitudinal acceleration and the movement angle of the overtaking vehicle. The other model predicts the overtaking trajectory for the overtaking vehicle. The second model is designed for two different vehicle classes: motorcycles and autos. Also, the result of the trajectory prediction model is compared with the result of other models. This comparison provides a better chance to analyze the performance of this model. Using the field data, the outputs of the MANFIS models are validated and compared with the real traffic dataset. The simulation results show that these two MANFIS models have a very close compatibility with the field data and reflect the situation of the traffic flow in a more realistic way. These models can be used for all types of drivers and vehicles and also in other roads and are not limited to certain types of situations. The proposed models can be employed in ITS applications and the like.

The lane change maneuver is among the most popular driving behaviors. It is also the basic element of important maneuvers like overtaking maneuver. Therefore, it is chosen as the focus of this study and novel multi-input multi-output adaptive neuro-fuzzy inference system models (MANFIS) are proposed for this behavior. These models are able to simulate and predict the future behavior of a Driver-Vehicle-Unit in the lane change maneuver for various time delays. To design these models, the lane change maneuvers are extracted from the real traffic datasets. But, before extracting these maneuvers, several conditions are defined which assure the extraction of only those lane change maneuvers that have a smooth and uniform trajectory. Using the field data, the outputs of the MANFIS models are validated and compared with the real traffic data. In addition, the result of these models is compared with the result of other trajectory models. This comparison provides a better chance to analyze the performance of these models. The simulation results show that these models have a very close compatibility with the field data and reflect the situation of the traffic flow in a more realistic way.

Car-following models, as the most popular microscopic traffic flow modeling, is increasingly being used by transportation experts to evaluate new Intelligent Transportation System (ITS) applications. A number of factors including individual differences of age, gender, and risk-taking behavior, have been found to influence car-following behavior. This paper presents a novel idea to calculate the Driver-Vehicle Unit (DVU) instantaneous reaction delay of DVU as the human effects. Unlike previous works, where the reaction delay is considered to be fixed, considering the proposed idea, three input-output models are developed to estimate FV acceleration based on soft computing approaches. The models are developed based on the reaction delay as an input. In these modeling, the inputs and outputs are chosen with respect to this feature to design the soft computing models. The performance of models is evaluated based on field data and compared to a number of existing car-following models. The results show that new soft computing models based on instantaneous reaction delay outperformed the other car-following models. The proposed models can be recruited in driver assistant devices, safe distance keeping observers, collision prevention systems and other ITS applications.