WBANs (Wireless Body Area Network) are expected to consume very low electrical power. One of the most important factors of energy consumption in WBAN is the presence of interference between the transmitter and receiver nodes. In this paper، a fuzzy-genetic based power control method is proposed to intelligently align transmission power of sensor nodes within a WBAN. This technique utilizes the concepts of genetic algorithms to set up membership functions of fuzzy controller and its knowledge base so that by controlling the level of transmission power of each sensor، the entire network energy consumption is reduced by mitigating the impact of interference in neighborhood nodes. Compared to distributed Greedy power control algorithm، it is shown that the proposed genetic-fuzzy power control approach can reduce power consumption by at least 34 percent.

Counter-urbanization has been defined with many definitions in research literature as increasing of the small town population in the process of urban expansion and development. This study investigates the counter-urbanization process in Isfahan metropolitan area based on an exploratory method using the population and immigration data, diurnal commuting, and the immigration motivators. The results show that, during different periods, population growth has been changed from the greater cities’ metropolitan area to the small towns. So that, there is less population growth near the main greater cities during the last decade. Regarding the immigration as well as migration effectiveness over the population, and immigration motivators, it can be said that the most important parameters of small towns’ expansion near the greater cities are better habitation opportunities, and finding better jobs. Furthermore, decreasing the diurnal commuting close to the greater cities shows that small towns, which are farther from the greater city, have more autonomy. In addition, based on polarization reversal model, and population development investigation in metropolitan areas, there are population development from the greater cities’ centre to the periphery area, which is leaded to decrease the population of the main greater city, and increase the population absorption in small towns. Consequently, the urbanization of Isfahan metropolitan area has entered to a counter-urbanization phase.

Identification of the exact location of an exon in a DNA sequence is an important research area of bioinformatics. The main issues of the previous signal processing techniques are accuracy and robustness for the exact locating of exons. To address the mentioned issues, in this study, a method has been proposed based on deep learning. The proposed method includes a new preprocessing, a new mapping method, and a multi-scale modified and hybrid deep neural network. The proposed preprocessing method enriches the network to accept and encode genes at any length in a new mapping method. The proposed multi-scale deep neural network uses a combination of an embedding layer, a modified CNN, and an LSTM network. In this study, HMR195, BG570, and F56F11.4 datasets have been used to compare this work with previous studies. The accuracies of the proposed method have been 0.982, 0.966, and 0.965 on HMR195, BG570, and F56F11.4 databases, respectively. The results reveal the superiority and effectiveness of the proposed hybrid multi-scale CNN-LSTM network.

In this paper, we intend to focus on the sensor network applications in firefighting. A distributed algorithm is developed for the sensor network to guide firefighters through a burning area. The sensor network models the danger of the area under coverage as obstacles, and has the property to adapt itself against possible changes. The protocol developed, will integrate the artificial potential field of the sensors with the information of the intended place of moving firefighter so that it guides the firefighter step by step through the sensor network by choosing the safest path in dangerous zones. This protocol is simulated by Visual-Sense and the simulation results are available.

The optimal distribution system planning is recognized as a very complex problem due to the large number of variables and candidate network configurations.Many factors have affected distribution planning problem such as load forecasting, load growth, load density, substation sizing and sitting, feeder sizing and routing and so on. Most of the models and mathematical methods have been developed and applied to either of the voltage levels in distribution network planning. In this paper, two new approaches have been developed for rural distribution network planning and optimization. In the first approach, this problem has been solved by a suitable searching method to determine the optimal configuration of network and the voltage level of each section of the feeder. This method determines the sizing of distribution feeder and transformer in each section of the feeder. Also, the results of this algorithm are evaluated by some of the main parameters such as load growth coefficient, lifetime of equipment and energy price. In the latter, this problem is solved by particle swarm optimization (PSO).At the end of this paper, both of these two algorithms have been applied to a real test network of Gilan Regional Electricity Company and the results have been shown and compared.

Wide-area protection of electric power transmission networks against faults was the main motivation behind the invention of synchronized phasor measurements. However, global positioning system (GPS) signal loss and synchronization errors on the one hand and variability of external network parameters on the other hand have prohibited utilization of wide-area protection of transmission network. This paper introduces a novel approach for wide-area protection in order to address the above-mentioned problems. By utilizing the measurements provided by phasor measurement units (PMU) located at border substations of the internal protected network, the proposed approach will be independent of external network parameters. Moreover the proposed formulation avoids using phase angle of PMU measurements, as opposed to existing methods that are vulnerable to loss or incorrect value of even one of phase angles of voltage/current synchrophasors. Another advantage of the proposed approach is avoidance of zero-sequence network parameters as well as identifying the faulted line regardless of fault type and its resistance. Simulation studies for the 9-bus Western Systems Coordination Council (WSCC) confirm high accuracy of the proposed approach in identifying the faulted transmission line.

This paper proposes a Linear Matrix Inequality (LMI) based H¥ robust controller design method for enhancement of damping of inter-area oscillations in a multimachine power system network. A Four-input, Single-output H¥ controller is designed for a Thyristor Controlled Series Compensator (TCSC) employing Wide Area Measurement (WAM) based stabilizing signals as generator speed. The major concern of signal transmission delay in wide area measurement is overcome here using the novel concept of Synchronized Speed Phasor Measurement (SSPM) and Global Position Satellite System (GPS) technology. The controller design has been carried out based on H¥ mixed-sensitivity formulation in an LMI framework with pole-placement constraint. The performance of the controller has been examined employing eigenvalue as well as time domain analysis in the face of different operating scenarios of a 14 area real power system network comprising of 24 generators, 203 buses and 266 lines. The designed controller has been found to be robust against varying generation and load power demand as well as for transmission line outage.

Traditionally in pinch technology method it is assumed that all heat exchangers in heat exchanger network design obey a single cost model due to the assumption that all heat exchangers in a network use the same material. This means that the total cost of the network is based on the assumption that uniform materials are used throughout the construction of the network. The results of these methods are an approximation of the actual cost. The method introduced here enables the user to obtain more precise cost. The first step divides the total cost of the heat exchanger into the cost of the tube and the cost of the shell. Cost of heat exchanger is obtained by addition of the tubes and shell cost. The second step uses binary variables to show the cost benefits of the different streams. In this step we evaluate the physical components of the stream which could cause corrosion while others are restricted. The third model step for this method determines the stream which passes through the shell or tubes based on the physical property of the stream. The last step, a cost model is defined whose results show the cost of a heat exchanger network based on mixed materials of construction and pressure drop in a heat exchanger design.