Introduction: Evaluation of hospital Information System (HIS) is a complex endeavor, in which all human, technical and organizational aspects should be considered. This study aimed to develop indicators for HIS evaluation.Methods: Present qualitative study was carried out through a cross-sectional method in 2012 in Kerman province, using Delphi technique. Given the objectives of this study, three independent phases were performed including literature review, providing draft indicators for HIS evaluation and reaching consensus. Required data were obtained through interviews and designed forms. Twenty-three experts composed the study population in interview and reaching consensus phases. Validity and reliability were confirmed through content validity and test-retest method, respectively. Data were analyzed using descriptive statistics.Results: Final set of indicators for HIS evaluation consisted of ninety-one indicators under 8 main topics, i.e. technical quality, software quality, architecture and interface quality, vendor quality, after-sale services quality, workflow support quality, support department, outcome quality and HIS cost.Conclusion: Given the complexity of Information System evaluation, all human, technical and organizational aspects have to be taken into account in any evaluation. Proposed indicators provide the possibility of comprehensive evaluation of HIS.

In this study, it is attempted to provide a proper assessment of flood status and flood risk for Tajan watershed. In this regard, by preparing flood hazard zoning maps and flood sensitivity analysis for the basin, susceptible areas have been identified and the extent of the hazard has been assessed for the basin. To this end, a fuzzy hierarchical fuzzy analysis (F-AHP) integrated model is used to prioritize, identify factors influencing flood events (including geological, climate, human factors, etc. ) and determine the extent of impact of each. Flood assessment indices (including flow velocity, flow depth, mean precipitation, evaporation, slope aspect, drift pattern, flood plain, road network and land cover) were used. This Information was transferred to the GIS environment after fuzzy evaluation in MATLAB and fuzzified/defuzzified index maps of the area were prepared. The goal of this work is to increase accuracy as well as integrate fuzzy models. These maps are used to identify flood sensitive areas (hazard maps) and hazard zoning (in 5 high-risk to low-risk groups). Based on the results of the hazard assessment, it has been identified that the most important concentration of flood sensitive areas in the main river is in relation to other parts and in the delta. Also, according to the drainage pattern of the region, especially in the eastern part of the basin, it has been determined that these areas also have a high sensitivity to flooding.

Objective(s): Taking the importance of end-users' satisfaction in the overall success of a HIS, this study was performed to assess their attitudes in different hospitals in Tehran.Methods: Interviews were made with officials of 20 hospitals in Tehran. Research tool was a questionnaire in 8 parts. Results: Sixty three officials entered into the study. The average age was 40.7 years and 62.1% were male. 80.5% of the respondents indicated that they were satisfied or very satisfied with HIS in their hospitals. In general several factors found to be important to the HIS users. These were: better communication and quicker and more effective access to data, reports and outputs, organization management, resources, proper training for managers and users, compliance assessment inside the organization, ease of learning and implementation, effective support, and ease of use. Conclusion: The development of hospital Information Systems in Iran is in its early stages and despite their considerable progresses during recent years, they still require more investment in order to satisfy the administrators' and end users' expections.

Irregular patterns of precipitations from temporal as well as spatial perspectives not only cause destructions but also waste surface water resources. Hence, controlling surface water and leading the flood to underground stores improve the efficiency of water usage. Selecting appropriate sites for optimal use of water floods is one of the most important factors in recharging underground water tables in dry lands where the agricultural and rangelands are vulnerable. Traditional methods of site selections are, however, time consuming and error prone. This paper attempts to; analyze existing schemes of site selection; introduces an appropriate method of locating flood-spreading sites using Geospatial Information System; implements the strategy in a case study; and scientifically assesses its results. The study area of this research is Samal sub-basin covering 31571.7 ha of Ahrom basin in Boushehr province. In the present research, factors pertain to earth sciences (quaternary units, slope and landuse) and hydrology (runoff infiltration rate and aquifers’ depth) are considered. Information layers are weighted, classified and integrated through several models such as boolean logics, index overlay and fuzzy logics. The results are then checked against the existing sites to estimate their accuracy. The results of this research demonstrated that fuzzy logic operators including gamma=0.1, gamma=0.2 and products of fuzzy logics yield the best when compared to control fields and therefore, the models are introduced as the most suitable site selection strategies for flood spreading.

Urban Expansion Model (UEM) was adapted to simulate urbanization which implements Geospatial Information Systems (GIS), Artificial Neural Networks (ANNs) and Remote Sensing (RS). Two satellite imageries with specific time interval, socio-economic and environmental variables have been employed in order to simulate urban expansion. Socio-economic and environmental variables were used as inputs while construction and non- construction areas were used as outputs to train the neural network. Calibration of proposed model was performed with area under the ROC Curve (AROC) and Kappa Statistic (KS) which are non-shape performance metric. A real-life case study of Tehran Metropolitan Area (TMA) is presented to demonstrate the process. This paper presents a version of the UEM which parameterized for TMA and explores how factors such as road, building area, service centre, green space, elevation, aspect and slope can influence urbanization. Having urban expansion model with specific time interval and assuming the existence of the same rate of urbanization, new construction areas of region can be predicted. The overall accuracy of the model to predict new construction areas was 80% and 78% with AROC and KS, respectively.

In recent years, the growth of population, increase in environmental pollution, and changes in human’s life style, a dramatic increase in the number of asthmatic patients has been observed. In addition, the Lack of suitable solution for the cure of asthma shows us the necessity of recent researches for controlling of the exacerbation of asthma in order to improve patients’ quality of life. Environmental condition in a spatio-temporal perspective enables us to do some predictive analytics in order to providing this ability to the asthmatic patients to have self-checking in addition to the medication by personal physician. Ubiquitous patient monitoring System which is enabled by Geospatial perspective can assist us to provide such services to the asthmatic patients in both outdoor and indoor environments. In this paper, we monitor ubiquitously asthmatic patients in a Ubiquitous GIS environment by considering 8 important environmental asthma triggers including CO, NO, O3, PM10, SO2, Temperature, Humidity, and Pressure, and 4 medical records of current status of asthmatic patients. In fact, to achieve a better modeling with divided our research to two parts: User Model and Contextual Model. For implementation of Ubiquitous Asthma model (UbiAsthma), this survey is done by consideration of 30 patients in Tehran city. To develop our prediction model in UbiAsthma, at first we used VIKOR method to reclassified current patients’ medical classification to a novel and applicable classification for providing context-aware services. Secondly, after classification of patients, one patient is selected and the Information related to FVC and FEV1 of the patient in 86 different locations within 47 days is collected. The patient was equipped by CO pollutant sensor (MQ9) and Temperature, Humidity, and Pressure sensors collection by smart-phone in order to having of a real-time database for the patient’s trajectory. Also, we utilized O3, NO, SO2, and PM10 for all 86 locations as static database in our model. After data collection and manipulation, Artificial Neural Network (ANN) is used for doing predictive analysis for asthmatic patients’ status. The result of test and train of ANN method shows that UbiAsthma model has 0.0230 evaluation error in prediction of asthmatic patients’ status, which is a considerable output in our model.

With increasing traffic density on Iran’s regional corridors, the probability of accident occurrence has increased accordingly. The main objective of this paper is to develop an ontology-driven Geospatial Information System to induct major crash rules for vehicles accident severity prediction which has the full domain knowledge and logical reasoning ability based on ontology. In the proposed approach, Geographic Information System (GIS) provides a platform both for spatial data analysis and for visualizing relationships between spatial and non-spatial data. Furthermore, the ontology is employed to represent Geospatial and attribute domain knowledge related to road, environment and vehicle. Crash rules are acquired by integrating experts knowledge with the rules which are extracted using the Separate-and-Conquer rule induction approach. These rules are transformed to Semantic Web Rule Language (SWRL) syntax for reasoning in crash severity estimation engine. To evaluate the proposed method, a System prototype in the Qazvin-Rasht (Iran) regional transportation corridor as a case study is implemented. The results show that the proposed approach can efficiently induce major crash rules and predict accident prone vehicles crash severity with respect to real-time road, driver and environmental Information in the vicinity of vehicle current location.

Railway transportation System is composed of interactions among a set of equipment and operations determining the capability and capacity of the railway System in terms of cargo and passenger transportation. The structure of capacity in rail transport is different from that of other methods of transport and especially road transport. Parameters affecting the capacity of rail transport Systems are very extensive, depending on type of route in terms of the route geometry and the technologies used in operation. The ability and capacity of carrying freight and passenger in a rail transport network is a function of various parameters in the path of the fleet such as route characteristics (slope, arc, electric signs System, speed limitations, tunnels, etc.), features of fleet (locomotive speed, weight, type of pulling force, type of wagons, etc.), features and characteristics of operations in stations (loading and unloading System and equipment of stations), type of operation and schedule of departure in the rail network (speed and type of trains), construction or reopening of stations, and tracking. All these factors define and determine the capacity of a rail transport System and the nodes for utilization of the network. For this purpose, capacity calculation and analysis of changes in any factor affecting it are important as the corresponding knowledge imposes large contributions in enhancing operating level of existing railway networks. There are various methods for calculating the capacity, of which one may select one depending on the network type and application. As of now, in Iran, considering the variety of applications planned for railway network (cargo, passenger transportation, or a mixed of the two), so-called practical capacity method (Scott’s formula) is used to calculate line capacity. Accordingly, current procedures followed in data gathering and obtaining effective parameters on line capacity calculation, as well as actual capacity calculation and analysis are performed manually, resulting in some discrepancies in different calculations and results. Further, there are chances that, planning based on an inappropriate estimation of line capacity, a portion of actual line capacity remains unused. As such, the present research, which is the first on the topic, aims at using capabilities of geographic Information System (GIS) to design and implement a web-based GIS service to determine the state of railway network capacity via a novel approach which offers higher efficiency than conventional methods. For this purpose, a base GIS environment was designed and connected to different databases run by Islamic Republic Of Iran Railways Co., including the travel database, to observe current state of the network in terms of capacity and propose solutions to further exploit unused capacity of the network and address bottle-necks of railway network capacity usage. The use of this method not only resulted in enhanced pace and accuracy of network capacity calculations, but also brought about better managerial decision-making to use unused capacity of the network and sell this capacity to applicant companies and generate further revenue for Islamic Republic Of Iran Railways Co., to the extent that, prior to any new season or year, one could sign appropriate contracts to address the demand raised by cargo owners and passengers across the railway network.

Despite the traffic increases at the World airports, little works have been done to improve vehicles and airplanes services, increase efficiency and decrease service automobile voluminous of large number. With GIS abilities, airport managers would like using its potential for development and management of airports. So new issue in GIS is formed with AGIS title to study GIS applications in airport as wide and corporation all world airports and GIS specialists. This paper presents an application of GIS analyses in airport field. The main innovation of this research is offline spatiotemporal data analysis and introducing an efficient algorithm for service automobiles allocation optimization with reduction in departure time deferment constraint. Allocation has been done by considering the aircraft push and tow required time and its distance to a service car. In this proposed solution servicing operation optimizes with considering two situations: one that service car returns to its Equipment Parking Area or EPA when delivering service and in another situation service car parks in Equipment Staging Area or ESA. Numerical results of using proposed method in Mehrabad international airport indicate in both situations, departure delay is lesser than usual method. Outcomes of minimizing service cars are: traffic reduction, increase management efficiency, decrease hazards due to large number of service cars and increase safety in airport field.