simulation

Groundwater is the most important water resource for drinking and agricultural usage especially in arid and semi-arid regions. So, it is important to note its quality. Nitrate is one of the groundwater pollutants which is mostly derived from agricultural and wastewater sources. Since nitrate determination using sampling was very expensive and limited, it is necessary to use new prediction methods like artificial neural network. The use of artificial neural networks in hydrological studies of the last decade shows that these models have a high ability to discover the relationship between data and recognize patterns. The success of neural network models in estimating different parameters of water sources has always been emphasized by different researchers.

Due to the completely random and dynamic nature of the cloud environment, as well as the high volume of jobs, one of the significant challenges in this environment is proper online job scheduling. Most of the algorithms are presented based on heuristic and meta-heuristic approaches, which result in their inability to adapt to the dynamic nature of resources and cloud conditions. In this paper, we present a distributed online algorithm with the use of two different learning automata for each scheduler to schedule the jobs optimally. In this algorithm, the placed workload on every virtual machine is proportional to its computational capacity and changes with time based on the cloud and submitted job conditions. In proposed algorithm, two separate phases and two different LA are used to schedule jobs and allocate each job to the appropriate VM, so that a two phase adaptive algorithm based on LA is presented called TPALA. To demonstrate the effectiveness of our method, several scenarios have been simulated by CloudSim, in which several main metrics such as makespan, success rate, average waiting time, and degree of imbalance will be checked plus their comparison with other existing algorithms. The results show that TPALA performs at least 4.5% better than the closest measured algorithm.

Urban land allocation, planning and management are a complicate problem challenging the decision makers and policy writers all around the Word. The multi objectivity nature of the problem has engaged researchers to deal with the environmental, ecological, economical, social, recreational, commercial, and residential problems simultaneously, in any region, for better decision making. These modelers neglected to consider people’s satisfaction and wellbeing due to land allocation, planning, and development. Complex problems as such as land allocation and planning are in need of suitable integrated model building for solution and analysis. It was to this end that this author proposes a system dynamics approach for studying the impacts of the decisions made, by the policy makers in the long run, on the community’ satisfaction using computer simulation. Taking one land allocation decision into consideration, the results of our proposed dynamic modeling points to this reality that people’s level of satisfaction improves, their level of incomes enhance, and the quality of their lives increases with the passage of time.

The Internet of Things (IoT) now connects over nine billion devices. This number is predicted to approach 20 billion in the near future, and the number of things is rapidly expanding, implying that a large amount of data will be created. To handle the connected things, an infrastructure must be built. Cloud computing (CC) has become necessary in the analysis and data storage for IoT. A cloud broker, which is an intermediate in the infrastructure that controls connected things in cloud computing, is discussed in this study. An optimization problem is examined for maximizing the broker's profit and system availability while minimizing request response time and energy consumption. For this purpose, an objective function is proposed and solved using the Black Widow Optimization (BWO) algorithm. Subsequently, the obtained results are compared with the particle swarm optimization (PSO) algorithms. The results indicate that the BWO algorithm could outperform the PSO algorithm, and it can provide much better results considering different scenarios.

In this article, the pen tip angles of a robotic arm taken from a human hand with the ability to write Latin words in upper and lower case with axes and degrees of freedom that are in accordance with the anatomy of the human hand are simulated and designed. This robotic arm is simulated along with the code that is implemented in MATLAB and the output of the designed system is reported in this article and its errors are also investigated. There is the issue of replacing robotic equipment instead of humans in high-precision industrial work, which is sometimes in difficult conditions that are beyond the ability and endurance of humans, but with the help of robots, these activities can be performed completely. And energy resources, time and raw materials are also saved because the use of the robot keeps the accuracy of the repetition activity the same in all stages of the work and the speed of the work can be controlled.

The heartbeat is triggered by a sinoatrial node in the heart. If the sinoatrial node is disrupted for any reason or if there is a problem with the heart's electrical signal path, the heart rate will decrease or become impaired; in which case the cardiac pacemaker could control the heart function. The pacemaker is an electrical stimulator that causes the heart to expand and contract and triggers pulses to the heart when needed or permanently. Since the pacemaker is placed inside the patient's body, it should be designed based on the minimum power consumption. Besides, frequency adjustment in this device is necessary to regulate heart rate in a variety of arrhythmias. In this paper, logic cells of quantum cellular automata are utilized to design a pulse generator circuit in a heart oscillator, where power consumption and dimensions are minimal. An important feature of the proposed circuit is the ability to adjust the output pulse frequency. The efficiency of this circuit has been evaluated using QCAdesigner simulator and desirable results have been obtained in terms of power consumption level. The simulation results also show very low power consumption for the designed circuit.

Network simulation is a technique that models network behavior by performing transaction calculations between different network entities and using mathematical formulas and taking observations of network products. A network simulator is a software program have been applied to analyze the performance of a computer network without the presence of a real network. Hardware equipment, equipment configuration, communication, and routing protocols and network traffic modeled in simulation software and the behavior of the network and its components examined from different dimensions. The user can also customize the simulation software according to their needs. Simulation software has different uses, and the user can use these tools to model their network by recognizing this software. In terms of research, it is difficult to create a network, especially large networks, in a real-time scenario, and it is not easily possible to carry out it in the real world, and it is very costly. So, simulators help network developers to control whether the network can work in real-time or not, or whether it is efficient enough. This reduces the time and cost of network application testing.Today, simulation technology is successfully used to model, design and manage a variety of intelligent systems. Numerous tools have been created in this regard. In this article, we review and compare important network simulators such as CloudSim, GloMoSim, GNS3, NS-2, Opnet, OMNet ++, NetSim, NS-3, AVRORA, Packet Tracer, QualNet, J-Sim, REAL and OptSim and their results. These comparisons express from several perspectives in the tables.

Data grids support access to widely distributed storage for large numbers of users accessing potentially many files. To enhance access time, replication at nearby sites may be used. Data replication, a technique much investigated bydata grid researchers in past years creates multiple replicas offile and places them in conventional locations to shorten fileaccess times. One of the problems in data replication iscreation of replicas, replica placement and replica selection. Dynamic creation of replicas in an appropriate site by datareplication strategy can increase the systems performance.In this paper, we propose a data replication algorithm, called the Utility-base Data Replication (UDR) algorithm that improves file access time. Each grid site has its own capabilities and characteristics; therefore, choosing one specific site from many sites that have the needed data is a key and significant decision. The replica selection problem has been studied by many researchers who only considered response time as a criterion for the selection process. Therefore, in this study, we addressed the problem of how to select the best replica for the user's jobs. Our approach is simulated using a data grid simulator, OptorSim, developed by European Data Grid projects. Comparing to the previous work the experimentation shows the improvement in the overall performance.

Computation of the second order delay in RC-tree based circuits is important during the design process of modern VLSI systems with respect to having tree structure circuits. Calculation of the second and higher order moments is possible in tree based networks. Because of the closed form solution, computation speed and the ease of using the performance optimization in VLSI design methods such as floor planning, placement and routing, the Elmore delay metric is widely implemented for past generation circuits. However, physical and logical synthesis optimizations require fast and accurate analysis techniques of the RC networks. Elmore first proposed matching circuit moments to a probability density function (PDF), which led to the widespread implementation of it in many networks. But the accuracy of Elmore metric is sometimes unacceptable for the RC interconnect problems in today’s CMOS technologies. The main idea behind our approach is based on the moment matching technique with the power-lognormal distribution and proposing the closed form formula for the delay evaluation of the RC-tree networks. The primary advantages of our approach over the past proposed metrics are the ease of implementation, reduction of the complexity and proposing an efficiency formula without referring to lookup tables. Simulation results confirmed that our method illustrates a good degree of accuracy and the relative average of errors is less than 20%.