Quantifying the Risk of Wildfire Ignition by Power Lines under Extreme Weather Conditions

Utilities in California conduct Public Safety Power Shut-offs (PSPSs) to eliminate the elevated chances of wildfire ignitions caused by power lines during extreme weather conditions. We propose Wildfire Risk Aware operation planning Problem (WRAP), which enables system operators to pinpoint the segments of the network that should be de-energized. Sustained wind and wind gust can lead to conductor clashing, which could ignite surrounding vegetation. The 3D non-linear vibration equations of power lines are employed to generate a dataset that considers physical, structural, and meteorological parameters. With the help of machine learning techniques, a surrogate model is obtained which quantifies the risk of wildfire ignition by individual power lines under extreme weather conditions. The cases illustrate the superior performance of WRAP under extreme weather conditions in mitigating wildfire risk and serving customers compared to the naive PSPS approach and another method in the literature. Cases are also designated to sensitivity analysis of WRAP to critical load-serving control parameters in different weather conditions. Finally, a discussion is provided to explore our wildfire risk monetization approach and its implications for WRAP decisions

Analysis of the Basics and Curriculum of Teaching Creative and Critical Thinking Skills in Elementary School

The aim of this study was to extract the basics and objectives of the curriculum for teaching creative and critical thinking skills in the elementary course of the Iranian educational system. In order to conduct this research, a qualitative approach and contractual content analysis method were used. The participants of the study were 12 experts in the fields of curriculum planning, philosophy of education and psychology who were selected by purposive sampling. The instrument used was a semi-structured interview. According to the research findings, first the basics of the thinking skills training curriculum (creative and critical) were examined, which were divided into three sections: philosophical and value basics, psychological basics, and sociological basics. In the section on philosophical and value principles, the main categories were the emphasis on formal and public education, the emphasis on the values of thinking, and the emphasis on the merits of thinking. The main categories extracted for psychological foundations were emphasis on rationality, application of emotional and social dimensions, and attention to participation and cooperation. Finally, the main categories selected for the sociological foundations were scrutiny, social critique, and self-criticism. For the appropriate purposes of teaching creative and critical thinking, based on the opinion of experts, two main categories of intrapersonal skills and extrapersonal skills were selected. In the category of intrapersonal skills, principles such as technical skills, problem-solving skills and moral skills, and in the category of extrapersonal skills, the principles of emotional competence, cognitive competence and social competence are extracted

Dizajn robusnog neuro-adaptivnog regulatora za žično pogonjene paralelne robote

In this study, a robust neuro-adaptive controller for cable-driven parallel robots is proposed. The robust neuro-adaptive control system is comprised of a computation controller and a robust controller. The computation controller containing a neural-network-estimator with radial basis function activator is the principal controller and the robust controller is designed to achieve tracking performance. An on-line tuning method is derived to tune the parameters of the neural network for estimating the controlled system dynamic function. To investigate the effectiveness of the robust adaptive control, the design methodology is applied to control a cable-driven parallel robot. Simulation results demonstrate that the proposed robust adaptive control system can achieve favorable tracking performances for the robot.U ovome redu predstavljen je neuro-adaptivni regulator za žično pogonjene paralelne robote. Robusni neuro-adaptivni regulator sastoji se od računalnog regulatora i robusnog regulatora. Računalni regulator koji sadrži estimator s neuronskom mrežom s radijalnom aktivacijskom funkcijom je glavni regulator u "on-line" metoda podešavanja parametara neuronske mreže za estimaciju dinamike sustava upravljanja. Efikasnost sustava adaptivnog, robusnog regulatora testirana je na na žično pogonjenom paralelnom robotu. Simulacijski rezultati pokazuju da se predloženim robusnim i adaptivnim regulatorom mogu dobiti zadovoljavajuće performance prilikom slijeđenja

On nonlinear vibration behavior of piezo-magnetic doubly-curved nanoshells

In this paper, nonlinear vibration behaviors of multi-phase Magneto-Electro-Elastic (MEE) doubly-curved nanoshells have been studied employing Jacobi elliptic function method. The doubly-curved nanoshell has been modeled by using nonlocal elasticity and classic shell theory. An exact estimation of nonlinear vibrational behavior of smart doubly-curved nanoshell has been obtained via Jacobi elliptic function method. This method can incorporate the influences of higher order harmonics leading to an exact estimation of nonlinear vibration frequency. It will be indicated that nonlinear vibrational frequency of doubly-curved nanoshell relies on nonlocal effect, material composition, curvature radius, center deflection and electro-magnetic field.Scopu

Radiation protection of patients in diagnostic and interventional radiology in Asian countries: Impact of an IAEA project

Recognizing the lack of information on image quality and patient doses in most countries in Asia, the International Atomic Energy Agency (IAEA) initiated a project to assess the status of imaging technology, practice in conventional radiography, mammography, computed tomography (CT) and interventional procedures, and to implement optimisation actions. A total of 20 countries participated. Obsolete practices of use of fluoroscopy for positioning, photofluorography, chest fluoroscopy and conventional tomography were reported by 4 out of 7 countries that provided this information. Low-kV technique for chest radiography is in use in participating countries for 20-85% of cases, and manual processing is in 5-85% of facilities in 5 countries. Instances of the use of adult CT protocol for children in three participating countries were observed in 10-40% of hospitals surveyed. After implementation of a Quality Control programme, the image quality in conventional radiography improved by zero to 13 percentage points in certain countries and dose reduction was from 10% to 85%. In mammography, poor quality, ranging from 10 to 29% of images in different countries was observed. The project increased attention to dose quantities and dose levels in computed tomography, although doses in most cases were not higher than reference levels. In this study 16-19% of patients in interventional cardiology received doses that have potential for either stochastic risk or tissue reaction. This multi-national study is the first of its kind in the Asia, and it provided insight into the situation and opportunities for improvement. (c) 2012 Elsevier Ireland Ltd. All rights reserved

On The Design of The Robust Neuro-Adaptive Controller for Cable-driven Parallel Robots

In this study, a robust neuro-adaptive controller for cable-driven parallel robots is proposed. The robust neuro-adaptive control system is comprised of a computation controller and a robust controller. The computation controller containing a neural-network-estimator with radial basis function activator is the principal controller and the robust controller is designed to achieve tracking performance. An on-line tuning method is derived to tune the parameters of the neural network for estimating the controlled system dynamic function. To investigate the effectiveness of the robust adaptive control, the design methodology is applied to control a cable-driven parallel robot. Simulation results demonstrate that the proposed robust adaptive control system can achieve favorable tracking performances for the robot.U ovome redu predstavljen je neuro-adaptivni regulator za žično pogonjene paralelne robote. Robusni neuro-adaptivni regulator sastoji se od računalnog regulatora i robusnog regulatora. Računalni regulator koji sadrži estimator s neuronskom mrežom s radijalnom aktivacijskom funkcijom je glavni regulator u "on-line" metoda podešavanja parametara neuronske mreže za estimaciju dinamike sustava upravljanja. Efikasnost sustava adaptivnog, robusnog regulatora testirana je na na žično pogonjenom paralelnom robotu. Simulacijski rezultati pokazuju da se predloženim robusnim i adaptivnim regulatorom mogu dobiti zadovoljavajuće performance prilikom slijeđenja