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Post-treatment methods enhance the fatigue strength of welded high-strength steel joints significantly. In industrial applications, one commonly applied technique is the high frequency mechanical impact (HFMI) treatment. Attained local benefits increasing fatigue strength are the compressive residual stress state, the reduced notch effect at the weld toe, and additionally the local work hardening of the material. This paper presents the set-up of a closed simulation loop including structural weld simulation, numerical computation of the HFMI-process, and a numerical evaluation of the local fatigue life.
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This paper addresses an optimal model reference adaptive system (MRAS) to design power system stabilizer (PSS) in multi-machine electric power systems. Weighting factors of the proposed MRAS are adjusted by particle swarm optimization (PSO) as well as its input signal is limited by a normalization technique to assure network stability. The proposed modified-optimal MRAS-PSS is evaluated against conventional PSS to demonstrate its advantages. In order to investigate the performance of the proposed MRAS-PSS under parametric uncertainties, three operating conditions are defined and simulated. Several nonlinear and time-domain simulations are carried out to validate the viability and effectiveness of the proposed MRAS-PSS under network uncertainties.
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Developing strategies for the water sector in integrated manner is essential. The present study details the development and uses of the Water Poverty Index (WPI) to be applied as a holistic tool for the conceptualization of water strategies in Egypt. The WPI herein considers the following: (i) water availability; (ii) access to water taking into account energy as a factor to water system operation; (iii) capacity to manage the water system considering the gender perspective; (iv) allocation of water uses considering the economic value of water; and (v) quality of the environment. The developed WPI was applied at the Egyptian governorates level and priorities to be achieved in their water sector were determined. The study concluded that, WPI as a summarized index combines into a single number a cluster of data is considered a robust tool to assist decision makers in determining priority to conduct prospect development plans in the water sector.
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La alteración de la marcha es frecuente en la esclerosis múltiple (EM) y tiene un gran impacto negativo en los pacientes pues conlleva a la pérdida progresiva de autonomía personal y social, y de productividad laboral. Esta guía pretende establecer recomendaciones para la evaluación del deterioro de la marcha y el uso de fampridina de liberación prolongada (fampridina-LP) como tratamiento de pacientes con EM y deterioro de la marcha en España.
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La mHealth, definida como la prestación de información o asistencia sanitaria a través del uso de dispositivos móviles o tabletas, se postula como una de las grandes apuestas para pacientes, proveedores e inversores. Una app es un programa, con unas características especiales, que se instala en un dispositivo móvil, ya sea tableta digital o teléfono inteligente, y que suele tener un tamaño reducido, y cuyo objetivo es facilitar la consecución de una tarea determinada o asistir en gestiones diarias, siendo el modo de interacción entre el usuario y la aplicación el tacto.
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Pattern recognition of Acoustic Emission (AE) data is generally performed based on prior knowledge about the acoustic signatures of material damage mechanisms. Traditionally, these signatures are implicitly assumed to be unaffected by damage accumulation during the fatigue life of the material. This study investigates the influence of cumulated damage under cyclic loading on the acoustic signatures of local fracture mechanisms in composites. Artificial AE sources are created using an ultrasonic transmitter and a Pencil Lead Break in order to reproduce various real-like AEs, such that the waveforms, measured at the sensor level, are characterized as similar to real acoustic signatures of local fractures in carbon/epoxy composites. It is shown that these waveforms are distorted with damage accumulation in both time and frequency domains, leading to important changes in the AE-features used in data classification. Consequently, this can engender unreliable statistical representation of the AE sources in such non-stationary media.
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The information communication technology (ICT) outsourcing market is growing larger every year from the increasing number of companies that utilize ICT outsourcing, as industry scale increases and industrial specialization intensifies. However, the current circumstance is that security accidents related to ICT outsourcing are continuously occurring at an increasing scale. There is a lack of studies measuring the level of security management of organizational ICT outsourcing, which is the first step in performing security management of ICT outsourcing. In addition, most studies focus on general organizational security management. Accordingly, this paper aimed to design a model to measure the level of security management of companies utilizing ICT outsourcing. Specifically, this paper analyzed security vulnerabilities that could occur in ICT outsourcing that may be mapped with the accorded security measures as solutions to deduce items for ICT outsourcing security inspections. Next, this paper developed an ICT outsourcing security level quantification model by verifying the validity of the security inspection items deduced and by estimating item-specific weighted points. Additionally, the applicability of the ICT outsourcing security level quantification model developed was verified by applying it to actual companies.
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Neurofeedback (NFB) allows subjects to learn self-regulation of neuronal brain activation based on information about the ongoing activation. The implementation of real-time functional magnetic resonance imaging (rt-fMRI) for NFB training now facilitates the investigation into underlying processes.
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Feedback-driven learning, observed across phylogeny and of clear adaptive value, is frequently operationalized in simple operant conditioning paradigms, but it can be much more complex, driven by abstract representations of success and failure. This study investigates the neural processes involved in processing success and failure during feedback learning, which are not well understood. Data analyzed were acquired during a multisession neurofeedback experiment in which ten participants were presented with, and instructed to modulate, the activity of their orbitofrontal cortex with the aim of decreasing their anxiety. We assessed the regional blood-oxygenation-level-dependent response to the individualized neurofeedback signals of success and failure across twelve functional runs acquired in two different magnetic resonance sessions in each of ten individuals. Neurofeedback signals of failure correlated early during learning with deactivation in the precuneus/posterior cingulate and neurofeedback signals of success correlated later during learning with deactivation in the medial prefrontal/anterior cingulate cortex. The intensity of the latter deactivations predicted the efficacy of the neurofeedback intervention in the reduction of anxiety. These findings indicate a role for regulation of the default mode network during feedback learning, and suggest a higher sensitivity to signals of failure during the early feedback learning and to signals of success subsequently.
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