A simple two dimensional MODEL of thin film GROWTH based on the ballestic aggregation of hard disks is proposed. In this MODEL the impinging hard disks travel in straight line and initially "stick" to the first previously deposited hard disk they contact. Previously (Dirks and Leamy (1977)) (1) the criterion for relaxation has been migration of the impinging disk to the nearest pocket formed by two additional disks. In this MODEL, however, relaxation is dependent on the surrounding geometry of the previously deposited atoms. The deposited disk may "relax" into a position where it then contact three, two or one previously deposited disk(s). Zone I region which is mainly influenced by shadowing effects with limited adatoms diffusion is simulated. The influence of deposition rate, self-shadowing effect, substrate roughness including amorphous substrates were investigated. Results are in good agreement with the Structure Zone MODEL (SZM) predictions for thin metallic films.

There are two approaches for simulating memory as well as learning in artificial intelligence; the functionalistic approach and the cognitive approach. The necessary condition to put the second approach into account is to provide a MODEL of brain activity that contains a quite good congruence with observational facts such as mistakes and forgotten experiences. Given that human memory has a solid core that includes the components of our identity, our family and our hometown, the major and determinative events of our lives, and the countless repeated and accepted facts of our culture, the more we go to the peripheral spots the data becomes flimsier and more easily exposed to oblivion. It was essential to propose a MODEL in which the topographical differences are quite distinguishable. In our proposed MODEL, we have translated this topographical situation into quantities, which are attributed to the nodes. The result is an edge-weighted graph with mass-based values on the nodes which demonstrates the importance of each atomic proposition, as a truth, for an intelligent being. Furthermore, it DYNAMICally develops and modifies, and in successive phases, it changes the mass of the nodes and weight of the edges depending on gathered inputs from the environment.

Multi-facet dependency of human life on COMPUTER networks and its widespread vulnerability has made network robustness a necessity. With cost as a limiting factor, network robustness is considered as a great challenge for network administrators. This goal would be achievable by prioritizing the vulnerabilities based on their risk and choosing the most hazardous ones for elimination. Nowadays, CVSS is being used as the most widely used vulnerability scoring system. In CVSS, vulnerability ranking is based on its intrinsic features while temporal features such as the probability of developing exploitation tools, are ignored. So, DYNAMIC risk evaluation is not possible with CVSS and it is incapable of performing effective vulnerability discretion. This is because, only limited number of vulnerabilities are available for prioritization of infinite number of vulnerabilities. In addition, CVSS only ranks single step attacks whilst a wide variety of attacks are multi-step attacks. In this paper, a security system is proposed that is an improvement over CVSS and some other existing vulnerability scoring systems. It performs DYNAMIC risk evaluation of multi-step attacks by considering vulnerabilities' temporal features. As the introduced MODEL is developed based on security metrics of the security MODEL, security evaluation of multi-step attacks is now possible by CVSS. Also, the capability of risk evaluation of zero-day attacks is one unique feature of the proposed system which cannot be accomplished by the present vulnerability scoring systems. In CVSS, the impact of exploiting 35. 5% of vulnerabilities on confidentiality, integrity and availability are scored the same. But, in the proposed system, by considering the relative priority of the three mentioned security parameters, vulnerability discrimination of risk score of the mentioned percentage of vulnerabilities may be possible. On the other hand, the continuity of the probability assessment function of the proposed method in comparison to the discrete one in CVSS, improves the score diversity.

A two dimensional molecular DYNAMIC (atomistic) simulation MODEL was used to investigate the relationship between the nano-structure and the deposition parameters; namely, substrate temperature, deposition rate, angle of incidence, surface roughness. Qualitative agreements with the predictions of the structure zone MODEL (SZM) and the theoretical results of Srolovitze and coworkers (1988), as well as expectations through changes in the activated processes during film GROWTH due to changes in deposition parameters (Grovenor and coworkers (1984)) are obtained. It is shown that by enhancing the atomic mobility (i.e., increasing the substrate temperature or/and lowering the deposition rate) films of higher density with fewer voids are produced. By increasing the deposition angle, the nano-structure of the film changes from a dense film with few voids, to a nano-structure with columns/boundless inclined with the same angle (b) towards the incidence atoms with elongated voids. The angle b increases with increasing the deposition angle (a), and in agreement with the tangent rule (Dirks and Leamy (1977)). The angle of bundles (or the angle of the formation of the voids between atomic bundles), and columnar structure are caused by shadowing effects. Results showed that b decreases slowly with increasing surface mobility (i.e., increasing the substrate temperature or/and reducing the deposition rate). In general, the MODEL provides almost all predicted results and agrees well with observations.

Better irrigation management and more efficient management of crop production require MODELing of plant GROWTH and crop yield. More applicable MODELs are usually simple and requires less and accessible inputs. The objective of this study was to develop a MODEL for GROWTH and yield prediction of saffron under various irrigation regimes. In this MODELing soil water budget and other simple relationships for evapotranspiration partitioning, leaf area index determination and leaf dry mattertranspiration function, corm-transpiration function and saffron-corm function were used. The developed MODEL was calibrated based on available data of basin irrigation experiment under different irrigation regimes and verified based on independent data under different climatic conditions. In calibration, the comparison between predicted and measured values of different crop parameters did not show any significant difference (P=0.05) and MODEL was able to estimate LAI (with NRMSE=0.16), crop evapotranspiration (NRMSE=0.19), surface evaporation (NRMSE=0.22), leaf dry matter (NRMSE=0.33) and corm yield (NRMSE=0.19) and saffron yield (NRMSE=0.16) properly. In validation, the statistical results of comparison between predicted and measured values of various crop parameters were different and MODEL was able to estimate corm and saffron yield with acceptable accuracy. Furthermore, this MODEL might be used only for saffron crop because the incorporated crop functions are developed for saffron.

ICT plays an important role in accelerating economic GROWTH, especially in today's age of the Internet and mobile telecommunications. Due to the upward trend in the use of information and communication technology in the countries of the world, this part of the economy demands a lot of attention. Improved policies due to the impact of information and communication technology on the economy are one of the top programs of governments in developed and developing countries. A review of the literature shows that few systematic studies have examined the role of information and communication technology in GDP GROWTH and the impact of various variables on the role of information and communication technology has not been sufficiently studied. The present study uses systematic approach and system DYNAMICs methodology and examine interactions of ICT variables including ICT access, ICT development, ICT usage etc. with macroeconomic variables such as GDP, total factor productivity, ICT Capital examines ICT's value-added share of GDP and so on and presents a conceptual MODEL of the role of ICT in GDP GROWTH. The qualitative MODEL designed in this study can be the basis for future quantitative research and mathematical simulation with a systematic approach to information and communication technology and GDP.

The present paper describes the Uzawa (1965)–Lucas (1988) type two-sector MODEL of endogenous GROWTH, in which morover goods and services sector emphasizes also the production of human capital, as well as simulates the time paths of macro variables assuming that the Iranian economy behaves under the hypothesis of denoted MODEL. Therefore it's practiced on DYNAMIC optimization and solving the control problem of maximization the present value of representative agent’s flow of future utility (due consumption) in infinite horizon subject to constraints in physical and human formation using the pontryagain's maximum princliple.Then, for the differential equations system obtained, the DYNAMICs, the existence and determinacy of the steady state, analyzing also the balanced GROWTH paths are studied in two cases parametric and numeric with estimated values for Iranian economy. By using Iranian economy available data in period 1974-2007 various coefficients have been estimated and time paths of GDP and other variables simulated. The results of this study indicate that on the balanced GROWTH path the real GDP annual GROWTH rate in Iran is about 4.7%. Furthermore, an increase in technological parameter for education sector and output elasticity with respect to human capital can makes increase in this rate of GROWTH and economy moves to the higher balanced GROWTH path so that this subject confirms the role and importance of human capital in economic GROWTH.

The aim of this study was to analyze the effects of global warming on plant GROWTH degree day in the future decades. To this aim, simulated daily temperature data were drawn from EHOM database and under A1B scenario during 2015-2050 from Germany Plank Max. Then, daily degree data were downscaled with a separation of 0. 27*. 027 degrees longitude and latitude, covering around 30*30 km of Iran, by regional climate MODEL designed at the Abdul Salam Center for Theoretical Physics, Italy. Finally, a matrix with dimensions of 13140*2140 was obtained that rows represent degree day and columns represent stations (cells). The threshold of 5 ° was selected to calculate the GROWTH degree day. Finally, the monthly average of GROWTH degree day was calculated in a matrix with dimensions of 12*2140 in MATLAB software. Then, the map of average of GROWTH degree day was designed through Surfer software. The results showed that June and July had the highest average monthly GROWTH rate in the 100-1000 degree-day. In summer months, the highest degree day was observed in Khozestan plain. With regard to the degree day in spring and summer, Iran can be divided into three areas of mountains and interior foothills, internal pits and external foothills, and plains and southern coast.

Tracking multiple objects (MOT) is an important topic in almost all COMPUTER vision-related areas. One of the most vital challenges in front of MOT’s algorithms is data association, particularly when partial or complete occlusions occur. On the other hand, the human can handle this challenge in everyday scenarios for example while driving a car on a highway or riding a bicycle. Accordingly, we used a brain-inspired method to propose an MOT algorithm that can overcome the above challenge. The proposed method is based on DYNAMIC neural field as a brain-inspired algorithm that can mimic both neural and cognitive functions of the brain. Besides, we benefited from COMPUTER vision techniques to find targets and extract features such as their locations, directions, and velocities. We applied our method on an online dataset containing videos recorded from natural movements of zebrafish larvae. Evaluation results using two metrics MOTA and MOTP showed that the proposed method has a promising performance compared to the state-of-the-art algorithms. It can associate all information correctly both in the presence and absence of occlusion events.