SWOT Analysis and Developing Strategies for the Realisation of Urban Livability in Tehran

The present study aims to analyse the strengths, weaknesses, opportunities and threats (SWOT) of managing the Tehran Metropolitan to help comprehend the status quo as well as the challenges to the ..

Bank Credits and Investment Growth of Agricultural Sector in Iran

This study were examined relationship between bank credits and investment growth of agricultural sector in Iran during the period of 1982-2011 by auto regressive distribution lag bounds test approach. Basically, the growth investing of the agricultural sector in Iran is related to oil revenues, bank credits, value added of agriculture sector and capital stock. The results confirm the existence of a long-run relationship between variables in model. In addition, according to the results, bank credit is the most significant variable in explaining the growth investing, so that increases access to it will encourage growth investment of the agricultural sector in Iran. The estimations show that elasticity of bank credits, oil revenues, stock investment and value added are 0.103, 0.015, 0.049 and -0.058 in the agricultural sector respectively

Bank Credits and Investment Growth of Agricultural Sector in Iran

This study were examined relationship between bank credits and investment growth of agricultural sector in Iran during the period of 1982-2011 by auto regressive distribution lag bounds test approach. Basically, the growth investing of the agricultural sector in Iran is related to oil revenues, bank credits, value added of agriculture sector and capital stock. The results confirm the existence of a long-run relationship between variables in model. In addition, according to the results, bank credit is the most significant variable in explaining the growth investing, so that increases access to it will encourage growth investment of the agricultural sector in Iran. The estimations show that elasticity of bank credits, oil revenues, stock investment and value added are 0.103, 0.015, 0.049 and -0.058 in the agricultural sector respectively

Meter placement algorithms to enhance distribution systems state estimation: Review, challenges and future research directions

Abstract Increasing the number of measurements in power distribution networks is crucial in improving the monitoring accuracy and operation quality. However, due to the large number of nodes in distribution networks, it is not economically possible to install meters in all nodes. State estimation as a useful tool can help to reduce the need for meters. The location of meters has a significant effect on the state estimation results. A comprehensive literature review of the optimal meter placement methods in distribution networks with the aim of improving state estimation is presented in this paper. These methods are compared in terms of the objective function and constraints of the optimization problem, relevant uncertainties, types of state estimation algorithms and the solution methods. This paper provides a detailed insight for researchers and network operators about the types of meter placement methods, their advantages and disadvantages, existing barriers, and future research areas

SSPS_DATA (17).sav

this data belongs to a study purposed to assess the psychometric properties of the translated Social Self-Compassion Scale (SSCS) with Iranian youths.</p

Automatic fetal biometry prediction using a novel deep convolutional network architecture

Fetal biometric measurements face a number of challenges, including the presence of speckle, limited soft-tissue contrast and difficulties in the presence of low amniotic fluid. This work proposes a convolutional neural network for automatic segmentation and measurement of fetal biometric parameters, including biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur length (FL) from ultrasound images that relies on the attention gates incorporated into the multi-feature pyramid Unet (MFP-Unet) network