Liver segmentation in medical images is still considered as a challenge in computer diagnosis systems. In this paper, an optimal algorithm based on the adaptive water flow model for segmentation is introduced. This algorithm first processes the image by means of a transfer function designed based on the probability distribution function of the brightness levels of the liver pixels to distinguish the liver region from the rest of the parts. Then, with the help of the rainfall algorithm, which is controlled based on the spatial information and light levels of the liver, possible areas of the liver are extracted, and further, the possible areas of the liver are classified with a layered perceptron neural network, using shape and texture features. Classification of areas instead of pixels has increased the efficiency of the algorithm. The obtained experimental results show a far more appropriate performance in comparison with other evaluation algorithms Manuscript profile

In recent years, the use of renewable energy sources to produce electricity in the power system has grown a lot. Compared to fossil fuels, these resources do not pollute the environment and there is no concern about their depletion. The problem of renewable energy sources is that their production power is variable due to the changes of these sources. Accordingly, in order to reduce the uncertainty of the production capacity of renewable energy sources, it is tried to use these sources in a combined manner. In this article, a method is introduced to determine the appropriate combination of renewable energy sources in order to reduce the uncertainty of their production power. In this method, the average, standard deviation, and the histogram related to the production power of the hybrid structure are obtained, and based on this, a structure with less uncertainty is determined. The proposed method has been used to determine the appropriate structure of renewable units in Bushehr region. Manuscript profile

Due to the importance of distribution systems, optimal planning and safety of these networks are very important. On the other hand, electric vehicles are one of the main characteristics of future electricity distribution networks. The uncoordinated and unmanaged presence of electric vehicles as an additional load in the network can aggravate problems such as voltage drop, voltage stability and increase in network losses. In order to alleviate the effects caused by the uncontrolled presence of these cars, it is necessary to manage their required power in coordination with other dispersed production sources. Therefore, we should try to reduce losses by properly planning the charging and discharging of cars, along with scattered productions, having the right voltage and, as a result, better economic efficiency. Therefore, in this article, the optimal use of electric car parking lots with the presence of renewable energy sources in the distribution system has been studied. Optimization of the problem, a new meta-heuristic algorithm based on the flower pollination algorithm was used to determine the variables of the problem, including the optimal capacity and location of solar sources, as well as electric parking lots and diesel generators in the distribution network. The problem is subject to network operation restrictions (thermal line restrictions, network bus voltage restrictions, etc.), the number of cars in electric parking lots, the permitted power capacity of solar units, and the capacity of diesels have been optimized. In this study, the capability of the proposed method based on the flower pollination algorithm has been evaluated with other algorithms. The simulation was done on the distribution network of 33 IEEE buses, and the results show that the convergence speed and accuracy of the proposed method is high. Manuscript profile

Most of the energy consumed in the building is consumed during the operation of the building. If you save on this part of the building energy, you can have a great impact on energy consumption. One way to control energy consumption in buildings is to use building energy labels. In order to provide an energy label, it must be possible to identify the factors affecting the energy consumption of the building. Introducing and studying energy-related indicators is one of the appropriate methods for managing energy consumption. With the help of these indicators, energy consumption can be managed and optimized. In this paper, by examining the main sectors of energy consumption in the buildings using the hierarchical analysis method (in order to label and optimize the energy consumption of office buildings), effective Attributes have been identified and introduced. The systematic search focuses on a variety of sources, including documents, databases, conferences, and various journals. First, search terms are selected. After the findings of library studies, field studies are conducted. This data can be described as experimental or new data. In the present study, two questionnaires were used to conduct field studies and obtain the required information. Improving energy consumption and reducing environmental pollution are key to sustainable energy. As the major consumer of energy, the building sector accounts for more than 40% of total energy consumption. One of the most important consumers of energy are office buildings, which include applications such as air conditioning, heating, cooling, hot water and various equipment. In this research, office buildings have been divided into different sections with the help of previous studies, and then in each section, the relevant Attributes have been extracted from the literature review. A total of 62 indices were extracted in 12 different sections. . Manuscript profile

The construction of wind farms in areas with high isochronic number, high tower height, intensification of the electric field due to the sharp tips of the blades and the possible contact of the blades with the nearby clouds, the importance of checking the overvoltage applied to the network The power by the high frequency wave makes the lightning brighter. Also, the wind turbine grounding system should be designed in such a way that, in addition to achieving impedance specifications with standard steady state values, it can effectively drain the lightning current into the ground. In this article, in the simulation of the earth system, the soil ionization phenomenon and the high frequency behavior of its electrodes have been considered so that it can be used as a reference potential to measure the voltage of all points. Then, the vector fitting method has been used to model the earth system. Of course, the input of the vector fitting method can be considered the frequency response of each element which is calculated numerically using common methods such as the FDTD method. Since the use of a more accurate calculation method provides more reliable results to the users, therefore, in this article, the overvoltage to a 2 megawatt wind turbine has been investigated using EMTP specialized software. Manuscript profile

According to the statements of the World Organization, the most important factor threatening humans is cardiac arrhythmias. According to the latest global health statistics, nearly 50% of deaths are due to heart diseases. According to research, 25% of deaths due to heart diseases can be revived with timely and correct diagnosis. The electrocardiogram signal is the most important and dependent signal related to the heart. Registration of this signal is low-cost, fruitful, and powerful in detecting arrhythmias. Feature extraction is the most important part of recognition and processing. Deep features based on convolutional neural networks are very powerful and can be done without manual intervention. In this article, deep features are extracted using deep learning based on a convolutional neural network. Then the classification results were calculated with an average accuracy of 99.3% and an average sensitivity of 99.1% with 10-fold cross-validation. According to the obtained results, it can be said that the proposed method has the ability to classify cardiac arrhythmias with acceptable accuracy. Manuscript profile

Due to the importance of distribution systems, optimal planning and safety of these networks are very important. On the other hand, electric vehicles are one of the main characteristics of future electricity distribution networks. The uncoordinated and unmanaged presence of electric vehicles as an additional load in the network can aggravate problems such as voltage drop, voltage stability and increase in network losses. In order to alleviate the effects caused by the uncontrolled presence of these cars, it is necessary to manage their required power in coordination with other dispersed production sources. Therefore, we should try to reduce losses by properly planning the charging and discharging of cars, along with scattered productions, having the right voltage and, as a result, better economic efficiency. Therefore, in this article, the optimal use of electric car parking lots with the presence of renewable energy sources in the distribution system has been studied. Optimization of the problem, a new meta-heuristic algorithm based on the flower pollination algorithm was used to determine the variables of the problem, including the optimal capacity and location of solar sources, as well as electric parking lots and diesel generators in the distribution network. The problem is subject to network operation restrictions (thermal line restrictions, network bus voltage restrictions, etc.), the number of cars in electric parking lots, the permitted power capacity of solar units, and the capacity of diesels have been optimized. In this study, the capability of the proposed method based on the flower pollination algorithm has been evaluated with other algorithms. The simulation was done on the distribution network of 33 IEEE buses, and the results show that the convergence speed and accuracy of the proposed method is high. Manuscript profile

According to the statements of the World Organization, the most important factor threatening humans is cardiac arrhythmias. According to the latest global health statistics, nearly 50% of deaths are due to heart diseases. According to research, 25% of deaths due to heart diseases can be revived with timely and correct diagnosis. The electrocardiogram signal is the most important and dependent signal related to the heart. Registration of this signal is low-cost, fruitful, and powerful in detecting arrhythmias. Feature extraction is the most important part of recognition and processing. Deep features based on convolutional neural networks are very powerful and can be done without manual intervention. In this article, deep features are extracted using deep learning based on a convolutional neural network. Then the classification results were calculated with an average accuracy of 99.3% and an average sensitivity of 99.1% with 10-fold cross-validation. According to the obtained results, it can be said that the proposed method has the ability to classify cardiac arrhythmias with acceptable accuracy. Manuscript profile

In recent years, the use of renewable energy sources to produce electricity in the power system has grown a lot. Compared to fossil fuels, these resources do not pollute the environment and there is no concern about their depletion. The problem of renewable energy sources is that their production power is variable due to the changes of these sources. Accordingly, in order to reduce the uncertainty of the production capacity of renewable energy sources, it is tried to use these sources in a combined manner. In this article, a method is introduced to determine the appropriate combination of renewable energy sources in order to reduce the uncertainty of their production power. In this method, the average, standard deviation, and the histogram related to the production power of the hybrid structure are obtained, and based on this, a structure with less uncertainty is determined. The proposed method has been used to determine the appropriate structure of renewable units in Bushehr region. Manuscript profile

Most of the energy consumed in the building is consumed during the operation of the building. If you save on this part of the building energy, you can have a great impact on energy consumption. One way to control energy consumption in buildings is to use building energy labels. In order to provide an energy label, it must be possible to identify the factors affecting the energy consumption of the building. Introducing and studying energy-related indicators is one of the appropriate methods for managing energy consumption. With the help of these indicators, energy consumption can be managed and optimized. In this paper, by examining the main sectors of energy consumption in the buildings using the hierarchical analysis method (in order to label and optimize the energy consumption of office buildings), effective Attributes have been identified and introduced. The systematic search focuses on a variety of sources, including documents, databases, conferences, and various journals. First, search terms are selected. After the findings of library studies, field studies are conducted. This data can be described as experimental or new data. In the present study, two questionnaires were used to conduct field studies and obtain the required information. Improving energy consumption and reducing environmental pollution are key to sustainable energy. As the major consumer of energy, the building sector accounts for more than 40% of total energy consumption. One of the most important consumers of energy are office buildings, which include applications such as air conditioning, heating, cooling, hot water and various equipment. In this research, office buildings have been divided into different sections with the help of previous studies, and then in each section, the relevant Attributes have been extracted from the literature review. A total of 62 indices were extracted in 12 different sections. . Manuscript profile

The construction of wind farms in areas with high isochronic number, high tower height, intensification of the electric field due to the sharp tips of the blades and the possible contact of the blades with the nearby clouds, the importance of checking the overvoltage applied to the network The power by the high frequency wave makes the lightning brighter. Also, the wind turbine grounding system should be designed in such a way that, in addition to achieving impedance specifications with standard steady state values, it can effectively drain the lightning current into the ground. In this article, in the simulation of the earth system, the soil ionization phenomenon and the high frequency behavior of its electrodes have been considered so that it can be used as a reference potential to measure the voltage of all points. Then, the vector fitting method has been used to model the earth system. Of course, the input of the vector fitting method can be considered the frequency response of each element which is calculated numerically using common methods such as the FDTD method. Since the use of a more accurate calculation method provides more reliable results to the users, therefore, in this article, the overvoltage to a 2 megawatt wind turbine has been investigated using EMTP specialized software. Manuscript profile

Liver segmentation in medical images is still considered as a challenge in computer diagnosis systems. In this paper, an optimal algorithm based on the adaptive water flow model for segmentation is introduced. This algorithm first processes the image by means of a transfer function designed based on the probability distribution function of the brightness levels of the liver pixels to distinguish the liver region from the rest of the parts. Then, with the help of the rainfall algorithm, which is controlled based on the spatial information and light levels of the liver, possible areas of the liver are extracted, and further, the possible areas of the liver are classified with a layered perceptron neural network, using shape and texture features. Classification of areas instead of pixels has increased the efficiency of the algorithm. The obtained experimental results show a far more appropriate performance in comparison with other evaluation algorithms Manuscript profile