In today's world, we are witnessing the launch, maintenance, control and exploitation of various projects. Projects that have high costs and optimal use of this capital in the current economy of the country are highly regarded by managers. On the other hand, each project is expected to achieve its predetermined goals at a specified time. Today, the necessity of rapid construction of subway lines in Tehran's metropolitan area, which is involved in severe traffic jams, is not covered by anyone. Despite the understanding of this issue by the authorities and the good actions taken so far in this direction. However, more effort and a greater determination to reach the acceptable speed in the construction and completion of metro lines is necessary. Quick implementation of projects is based on the principles of concurrent engineering, called Fast tracking, in construction projects. In the Fast delivery method, solutions such as resource enhancement, synchronous engineering, overlapping phases, value engineering, teamwork by the multi-functional team, improving communication and information transfer, and accelerating decision making, using efficient contractual methods (transferring risks as Effective way, which by using the correct methods, accelerates the implementation of the project. Therefore, in this article, management strategies for implementing Fast tracking projects in the development projects of the country have been investigated.

In this paper a Fast, reliable and robust algorithm against occlusion for visual tracking of a pre-defined target in sequence images based on adapting template of target edges with search space edges is presented. At first, target window is specified by user and then the proposed algorithm determines an appropriate model for the target by choosing the best edges of the target window. Moreover, to increase robustness against occlusion, target model has been divided into four equal divisions and by performing a logical AND between the template of each division edges and search space edges and then by counting its non-zero pixels, resemblance matrix for each division of target is obtained. In a case that values of the resemblance matrix are less than values of threshold matrix, the desired division is considered occluded and then by taking the effects of non-occluded divisions into account, the exact location of the target in each frame is determined. In the tracking values, in case of appropriate condition respect to background condition, the model of target edges is updated. Selecting dominant edges, multi dividing and updating the target template, has resulted in increasing the robustness of the algorithm against some vital challenges such as changing in ambient and target light, and occurring occlusion over target. The simplicity of this algorithm has provided the possibility of real-time implementation in OpenCV environment using C language, that achieves averagely to more than 60 frames per second for a computer with 2.6 GHZ CPU and 4 GB RAM. Moreover, comparing the results of the proposed algorithm to other algorithms, revealed a higher speed and greater reliability.

This paper presents a model-based approach for the global maximum power point (GMPP) tracking of solar strings under partial shading conditions. In the proposed method, the GMPP voltage is estimated without any need to solve numerically the implicit and nonlinear equations of the photovoltaic (PV) string model. In contrast to the existing methods in which first the locations of all the local peaks on the P-V curve are estimated and next the place of the GMPP is selected among them, the suggested method estimates directly the GMPP without any need for the evaluation of the other local peaks. The obtained GMPP voltage is then given as a reference value to the input voltage controller of a DC-DC boost converter to regulate the output voltage of the solar string at the GMPP voltage in various irradiation conditions. Furthermore, the values of the temperature and irradiation level of each PV module within the PV string are estimated, and therefore, the proposed method does not need to thermometers and pyranometers. This makes it as a reliable and low-cost GMPP tracking method. The theoretical aspects on which the proposed GMPP algorithm is established are also discussed. The comparison of the numerical results of the suggested GMPP tracking scheme with the existing methods at different environmental conditions shows the satisfactory operation of the proposed technique from the speed and accuracy point of views.

It is highly expected that partially shaded condition (PSC) occurs due to the moving clouds in a large photovoltaic (PV) generation system (PGS). Several peaks can be seen in the P-V curve of a PGS under such PSC which decreases the efficiency of conventional maximum power point tracking (MPPT) methods. In this paper, an adaptive neuro-fuzzy inference system (ANFIS) is proposed based on particle swarm optimization (PSO) for MPPT of PV modules. After tuning the parameters of the fuzzy system, including membership function parameters and consequent part parameters, to obtain maximum power point (MPP), a DC/DC boost converter connects the PV array to a resistive load. ANFIS reference model is used to control duty cycle of the DC/DC boost converter, so that maximum power is transferred to the resistive load. Comparing the proposed method with PSO alone method and firefly algorithm (FA) alone shows its efficacy and high speed tracking of MPP under PSC. Due to the fact that these optimization algorithms have online applications, the convergence time of the algorithms is very important. The simulation results show that the convergence time for the proposed ANFIS-based method is lower than 0. 15 second, while it is nearly three second for PSO and FA methods.

Clouds, because of their significant effects on energy balance on the ground surface and in the atmosphere, has always been considered by different meteorologists and climatologists. The ability of remote sensing in the assessment of cloud characteristics has been proven by in the study of their changes in different locations and times. One of the important aspects of the study regarding the clouds, is to determine the pressure at their top, which the aim of the current study is to present a Fast method for its determine by using MODIS images.Therefore, by using Radiosonde data in Mehrabad and Kermanshah stations, the atmospheric temperature profile was extracted. Then using a five stages technique, the pixels of the considered image were grouped into 4 different categories including cloudy, possibly cloudy, possibly non- cloud and non- cloudy. Then by using LSE model on channels 31 and 32 of MODIS, the emissivity of cloud in cloudy pixels was determined.Then by using this temperature and the temperature profile extracted from Radiosonde data, the pressure at the top of the clouds were extracted. To review the accuracy of the obtained results, the results obtained from Fast CTP method with those of standard CTP method were compared. Based on this comparison, it is found that the presented method for the clouds with optical depth of more than 10 is optimal and the results obtained from CTP model, shows a very small difference. But the difference regarding the thin clouds with low optical depth (lower than 10) is considerably great in comparing with the clouds of high optical depth.

Background and purpose: Trauma is the fourth leading cause of death in some developing countries and the second cause of death among young people in Iran. Focused assessment with sonography for trauma (Fast) as part of the preliminary examination is invaluable in emergency care. The aim of this study was to evaluate the accuracy of Fast in determining free abdominal fluid in traumatic patients admitted in an emergency department.Materials and methods: A cross-sectional study was carried out in 150 trauma patients in emergency department (Imam Teaching Hospital, Sari, Iran). Fast reports for presence of free fluid in the abdomen by emergency residents were compared with those of abdominal and pelvic CT scan (oral and intravenous contrast). Sensitivity, specificity, positive predictive value and negative predictive value were evaluated.Results: The mean age of patients was 37.02±14.46. There were 26 (84%) males and 24 (16%) females. In Fast and CT scan of the abdomen with oral and IV contrast 13 (8.7%) and 10 patients (6.7%) were reported with free fluid in the abdomen.|Conclusion: Ultrasound is a reliable tool for assessing trauma patients that can be performed with reasonable accuracy. Emergency physicians are constantly available upon admission, therefore, ultrasound plays an important role in decisions made for trauma patients in emergency departments.

Emergence of electronic resources on the web has caused some problems for librarians and information specialists. The problems are how to describe these resources and how to provide subject access for facilitating their discovery and retrieval. Passage of time has revealed that the use made of LCSH (Library of Congress Subject Headings) in the electronic environment is limited and to some extent impossible. So it may be useful to design a rich, simple and understandable subject heading scheme which is compatible with the electronic environment while introducing Fast subject headings, this article examines its compatibility with widespread metadata schemes, such as Dublin Core and MARC 21. Fast is developed for information organization, discovery and retrieval in the 21st century. The scheme is based on LCSH's controlled vocabulary but it is more faceted and post-coordinated than it.

Purpose: To compare the sensitivity, specificity and validity of SITAFast (SiF) strategy with the standard full thershold (SFT) algorithm in the Humphrey field analyzer. Materials &Methods: As an observational case series, twenty glaucoma patients (37 eyes) who were referred to Emam Reza & Ghaem eye clinic, central field testing was performed with the central 30-2 program using SFT and SiF strategies. Both tests were carried out on four different days in a span of two weeks. Sensitivity, specificity, validity, time saved, and the extent of defect in SITA Fast strategies were compared with those of SFT. Results: The sensitivity of SFT & SiF was 93.3%. Specificity of SFT & SiF was 71.4% & 57.4% respectively. The validity of SFT & SiF was 89.2% & 86.5% respectively. The mean time in SFT, SiF were 14.6 min & 5.45 min, respectively. Defects in gray scale was shallower in SiF (significant at P<1%, P<0.5%) but defects in the pattern deviation plots tended to be more in SITA Fast strategy but there was no significant difference in statistics. Conclusion: SITA Fast strategy has good sensitivity and is significantly Faster as compared with the SFT algorithm. Test time is much shorter so common use of SiF is suggested. In children, old age patients and patients who has difficulty in concentration, SiF is superior to SFT.