Background and Purpose: Vehicles are considered as one of the most demanded equipment in a defense organization, if they are not serviced in a timely and efficient manner, they are considered as a threat to that organization. On the other hand, due to the significant increase in data related to maintenance of these devices in the organization under study, in this study, data mining technique has been used to increase the data conversion into information rate and knowledge discovery in order to prevent cease of missions. The purpose of this paper is to present the architecture of classifying the data generated from the reference and breakdowns of passenger cars of the studied organization and to predict the distances between their breakdowns through data mining method in order to plan their maintenance and repairs. Methods: Based on this, the required data for a sample including 150 Light Vehicles were extracted. In this research, year of construction of the car, distance traveled and cause of failure as input variables and the intervals between failures as output variables were defined. Findings: Based on data mining principles and using SPSSModeler software, Vehicles were grouped based on the distances between breakdowns (km) with the C&R tree algorithm. Conclusion: according to the outputs analysis, the maintenance and repair group of the studied organization should adjust the service and inspection plan of the Vehicles based on the grouping done in the research and by considering the suggestions provided.

Background and Aim: Maintenance budget is the most effective factor in the mobility and timely provision of categories and it is tool that if not used properly or carefully prepared and adjusted will cause many problems in carrying out the missions of the organization. This research has provided a pattern for the optimal maintenance budget assignment of the police land Vehicles. Method: This research is applied in terms of purpose and exploratory in terms of nature. The Delphi method was used to identify the components and indicators of the model and the best-worst method (BWM) was used by Lingo software to calculate the weights of the components and indicators (importance factor). The reliability of the instrument was confirmed based on the compatibility rate, which was less than 0. 1. Findings: Data analysis led to the identification of seven components of the type of police unit with a weight of 0. 480, vehicle measurement with a weight of 0. 118, regional climate with a weight of 0. 111, vehicle model with a weight of 0. 099, quality of maintenance in the police category with a weight of 0. 094, type of disciplinary zone with a weight of 0. 083 and the economy of the region with a weight of 0. 015 plus 30 indexes. Conclusion: Considering the components of unit type, vehicle navigation and regions climate, is placed in the first to third ranks of importance and economies of the regions in the lowest priority, it is worthwhile adminstration of planning and maintenance in maintenance funds assignment for operational categories, for Vehicles with higher measurement and areas with hot and humid climates, consider higher budget respect to the other units.

Despite the growing trend of car use in cities, a significant part of the users of city roads is drivers. Level-crossing intersections are a common passageway for pedestrians and Vehicles, and due to the large volume of traffic in these areas, the sLightest irregularity in the flow of traffic causes a severe reduction in the capacity of the intersection. Violation of red Lights by drivers is one of the problematic factors in traffic Light intersections and the occurrence of traffic accidents for pedestrians. The present study aimed to identify the factors affecting this phenomenon, by combining a set of data observed from 101 Vehicles, demographic variables such as age, gender, coverage, and weight of drivers were examined as possible parameters affecting red Light violation. The results were evaluated by statistical tests to determine the significance of the effect of each variable. Examination of each of the behavioral indicators showed that red Light violations were consistently related to age, gender, and clothing, and weight.

Based on the usage types of commercial Vehicles, these Vehicles are divided into several groups which can provide various mobile services in health sectors in different circumstances such as deprived areas, tourist resorts and critical situations. Based on opportunity recognition theory of demand-side; this research is trying to identify and prioritize the opportunities of using Vehicles in Iran mobile health clinics. The research population consists of healthcare experts and the data collected in qualitative part of research by the semi-structured interviews, were assessed by content analysis and open coding techniques and statistical techniques were applied to analyze collected data from the questionnaires in quantitative part. To prioritize the types of opportunities recognized in the qualitative phase, Friedman test was used. The results of this research reveals that many opportunities in mobile services in health core sector were categorized into five main areas including education and counseling, screening, immunization, specialized health and laboratory.

Vibrations can have favorable or undesirable effects on systems. The discomfort of the Vehicles as a result of moving on rough roads is an example of the adverse effects of vibrations. A variety of dampers are used to prevent these damages. MR is one of the advanced technologies in the field of suspension systems. There is a lot of research today to increase the damping force, reduce construction costs, and design and simulate a damper with ease of construction, which indicates the necessity of a progressive research. In this paper, after the theoretical reviews the equations governing the mechanical model (by the Bingham plastic model), the electromagnetic field (by the Maxwell and Amp law) and the flow field (by the Naviers-Stokes equation) Until a double-rod Damper, which is an exquisite example of these dampers, is designed and simulated through the Camsol software through a multiphysics coupling (fluid-solid-magnet) interaction and then analyze the results. Also, the sample designed, unlike previous examples of these dampers, does not require a gas compensatory chamber. The information obtained from the simulation results showed that due to the requirements of a Light car aid that requires a damping force of more than 1000 Nm, the damper is a suitable semi -active device and can produce the minimum amount of the required in the required intense force. Transportation and other areas, such as the suspension of Light cars, should be used and improve the comfort and increase the quality of the vehicle.

Background and Aim: Maintenance is one of the most important parts in the planning of any organization today and its role in the NAJA is more than other government organizations. The purpose of this study was to identify the requirements for TPM implementation in the NAJA Light vehicle network. Method: This research is applied which has been done with a qualitative method. Data collection methods included interviews and documentary methods (archival studies) and non-documentary methods (non-archival studies). Content analysis and coding methods have been used to analyze the information. Findings: The research findings have shown that according to the results obtained from the review and analysis of themes related to the implementation requirements of TPM in the NAJA’ s Light Vehicles maintenance, totally 43 basic themes and 7 constructive themes (including: knowledge and education, cultural, process And technology, management, manpower, operational, planning) were found. According to the Pareto principle and the 20/80 law, from total of 43 basic themes identified, 8 themes with the highest percentage of importance have been identified, which include teaching TPM principles to employees and executives, providing new IT infrastructure including CMMS, training Maintenance with TPM direction, support and participation of managers and senior organizational officials, anticipation of motivational stimulants in staff and units, convincing provinces and independent units of the TPM implementation importance, establishing new and standard repair centers in accordance with TPM, Full PM implementation.

In this paper, according to the detection and tracking of the moving Vehicles at junctions, a rapid method is proposed which is based on intelligent image processing. In the detection part, the Gaussian mixture model has been used to obtain the moving parts. Then, the targets have been detected using HOG features extracted from training images, Ada-boost Cascade Classifier and the trained SVM. At the tracking part, a number of key points on the image of the vehicle were identified at first. The center of mass of the object and the edges were used to obtain these key points because these points are primarily important and more common in tracking rigid bodies. Then, these points were tracked in consecutive frames using definitive adaptive procedures. Also, the Kalman filter has been used to estimate new locations when the detector is not able to detect the targets. The major advantage of this method in comparison with the previous methods is its resistance against vehicle's overlapping and changes in Illuminations, so that the detection accuracy is 90. 80% on overloaded traffic scenes and 88. 75% on the tracking Vehicles.

A two-week tunnel study was conducted in Monterrey, Mexico during June 2009 to characterize volatile organic compound (VOC) emissions from the local vehicle fleet and estimate the corresponding emission factors (EFs). The Loma Larga Tunnel (LLT), a 532 meter-long structure that is mainly used by Lightduty gasoline-powered Vehicles was used as the experimental set-up. Ambient air samples (2-hour averages) were taken inside the LLT using 6 L SUMMAÒ-polished canisters. Samples collected in the canisters were analyzed for Total Non-Methane Hydrocarbons (TNMHC) and 53 individual VOCs using high-resolution GC-MS. Identified individual VOCs accounted for ~80% of the TNMHCs. The most abundant VOCs, on a molar basis, were ethene (13.8%), acetylene (9.0%), isopentane (7.1%), toluene (5.6%), and n-butane (5.5%).High correlations were obtained for known markers of vehicular emissions. Particularly, for the ethene/ acetylene ratio values between 1.1 and 2.4 were obtained (R2=0.95), indicating the presence of Vehicles with a working catalytic converter. Estimated EFs were compared to values reported in similar studies elsewhere, including one in Mexico City. Results indicate that the Vehicles in the LLT tend to emit lower molecular weight VOCs (in the C2 to C6 range). Reactivity of the emissions, expressed propylene-equivalent concentrations, was estimated resulting in an important contribution of the olefins (including isoprene) to the ozone-forming potential of the emitted mixtures.

Background and Purpose: Traffic accidents are one of the most important causes of death in Iran and impose a financial, psychological and pain costs on families and society. The purpose of research is to identify the causes of accidents of Light Vehicles in West Azerbaijan; “human, vehicle, road, environmental and management” factors. Method: This research is practical in purpose and descriptive-survey in terms of method. Firstly, through library studies, primary criteria and sub-criteria were extracted in accidents of Light Vehicles, and research questionnaires were compiled. Then these questionnaires were distributed among the experts. In this way, the best and worst criteria and sub-criteria were obtained. Also, the weight of these criteria and sub-criteria was determined by the best-worst method (BWM). To determine the validity and reliability of the questionnaire, Lausche's coefficient and Cronbach's alpha coefficient were used. Findings: 33 sub-criteria were categorized in the five main criteria including human (drivers), road, environmental and management  factors. The result showed that human factor with weight of 0.36 has the highest priority. Also, the criteria of vehicle and road with a weight of 0.24 and 0.18 were in the next priorities, respectively. Conclusion: The human factor has greatest effect on the occurrence of accidents and incidents of Light Vehicles. Other main criteria including "vehicle, road, environmental and management" factors are the next priorities. According to the obtained results, it is possible to prevent the occurrence of road accidents in West Azarbaijan and the occurrence of financial problems and injuries taking appropriate decisions with low cost.