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The growth of computational intelligence technology has witnessed its application in numerous fields. Power system study is not left behind as far as computational intelligence trend is concerned. In power system community, optimization process is one of the crucial efforts for most remedial action to maintain the power system security. Basically, power scheduling refers to prior to fact action (such as scheduling generators to generate certain powers for next week). Power scheduling process is one of the most important routines in power systems. Scheduling of generators in a power transmission system is an important scheme; especially its offline studies to identify the security status of the system. This determines the cost effectiveness in power system planning. This paper investigates the performance of multi-verse based evolutionary programming (lowest EP) technique in the application of power system scheduling to ensure loss is gained by the system. Losses in the system can be controlled through this implementation which can be realized through the validation on a chosen reliability test system as the main model. Validation on IEEE 30-Bus Reliability Test System resulted that both techniques are reliable and robust in addressing this issue.

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Agriculture is a risky activity. In this field, all types of natural, societal and economical risks provide a susceptible environment for the producers. Supporting the producers in agriculture sector against revenue fluctuations plays an important role in increasing motivation and production. The government develops schemes and policies to support the producers, and performance insurance is one of them. Crop insurance supports the farmers against the loss of and or damage to farmer and prevents the farmers' revenue fluctuations. In this study, it’s been tried to model the farmers' participation in the rice insurance scheme in Qaemshahr County. To do so, using Positive Mathematical Programming (PMP), the farmers' behavior in regard with participating in rice crop insurance scheme and the consequence of this participation was studied. The required data was collected from the farmers of Qaemshahr County for a three-year agricultural period (2011-2013) via questionanaire. Based on the results of this study, introducing the rice crop insurance to the farmers, all of the representative farms in the insurance scheme participated in. An increase in the under-cultivation rice farms and their gross margin was the result of this participation. Decreasing the governments support of the insurance premium, will have negative effect on the increasing of the under-cultivation rice farms and their gross margin.

Agriculture is a risky activity. In this field, all types of natural, societal and economical risks provide a susceptible environment for the producers. Supporting the producers in agriculture sector against revenue fluctuations plays an important role in increasing motivation and production. The government develops schemes and policies to support the producers, and performance insurance is one of them. Crop insurance supports the farmers against the loss of and or damage to farmer and prevents the farmers' revenue fluctuations. In this study, it’s been tried to model the farmers' participation in the rice insurance scheme in Qaemshahr County. To do so, using Positive Mathematical Programming (PMP), the farmers' behavior in regard with participating in rice crop insurance scheme and the consequence of this participation was studied. The required data was collected from the farmers of Qaemshahr County for a three-year agricultural period (2011-2013) via questionanaire. Based on the results of this study, introducing the rice crop insurance to the farmers, all of the representative farms in the insurance scheme participated in. An increase in the under-cultivation rice farms and their gross margin was the result of this participation. Decreasing the governments support of the insurance premium, will have negative effect on the increasing of the under-cultivation rice farms and their gross margin.

This article is from Sensors (Basel, Switzerland) , volume 14 . Abstract Over-the-air dissemination of code updates in wireless sensor networks have been researchers' point of interest in the last few years, and, more importantly, security challenges toward the remote propagation of code updating have occupied the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strength, having their concentration on the constrained nature of wireless sensor network (WSN) nodes. For authentication purposes, most of them have used a Merkle hash tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be at a standard level. Therefore, they have not investigated the tree structure for mission-critical situations in which security has to be at the maximum possible level (e.g., military applications, healthcare). Considering this, we investigate existing security models used in over-the-air dissemination of code updates for possible vulnerabilities, and then, we provide a set of countermeasures, correspondingly named Security Model Requirements. Based on the investigation, we concentrate on Seluge, one of the existing over-the-air programming schemes, and we propose an improved version of it, named Seluge++, which complies with the Security Model Requirements and replaces the use of the inefficient Merkle tree with a novel method. Analytical and simulation results show the improvements in Seluge++ compared to Seluge.

This article is from Sensors (Basel, Switzerland) , volume 14 . Abstract Over-the-air dissemination of code updates in wireless sensor networks have been researchers' point of interest in the last few years, and, more importantly, security challenges toward the remote propagation of code updating have occupied the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strength, having their concentration on the constrained nature of wireless sensor network (WSN) nodes. For authentication purposes, most of them have used a Merkle hash tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be at a standard level. Therefore, they have not investigated the tree structure for mission-critical situations in which security has to be at the maximum possible level (e.g., military applications, healthcare). Considering this, we investigate existing security models used in over-the-air dissemination of code updates for possible vulnerabilities, and then, we provide a set of countermeasures, correspondingly named Security Model Requirements. Based on the investigation, we concentrate on Seluge, one of the existing over-the-air programming schemes, and we propose an improved version of it, named Seluge++, which complies with the Security Model Requirements and replaces the use of the inefficient Merkle tree with a novel method. Analytical and simulation results show the improvements in Seluge++ compared to Seluge.

Abstract — Selection of a viable irrigation cropping system, while considering all agronomy and extension constraints, has always been a scientific and professional challenge for agricultural scientists and practitioners. However, this prevailing challenge can be scientifically addressed using optimization techniques among them linear programming model. The model could take in the initially introduced percentage of crops as an entry point for optimization subjected to all introduced constraints while maximizing the farming income. Favorably, Microsoft Excel program includes a linear programming solver tool, which could be utilized for this purpose. The solver tool could easily be accessed from Excel program Data menu after activating the Add-Ins part of the Excel Options.   Accordingly, a simple and low input linear model was developed applying the Excel Solver tool to optimize the irrigation cropping pattern for the Mekabo small-scale irrigation scheme currently under construction in the Tigray region in Ethiopia. The input parameters were collected from field surveys and an assessment of the on-farm agronomic conditions. The objective function was subjected to agronomy and extension constraints as well as minimum required crop levels to comply with food security strategy. The model could find a viable solution while all constraints and optimality conditions were satisfied. A sensitivity analysis was also performed to analyze all other likely development scenarios. This paper will introduce the developed model and will discuss the processes led to the attainment of an optimized cropping pattern