The effect of incomplete ionization on the turn-off behavior of FS IGBTs

This letter demonstrates for the first time the effect of the incomplete ionization (I.I.) of the transparent p-anode layer on the static and dynamic characteristics of the field-stop insulated gate bipolar transistors (FS IGBTs). This effect needs to be considered in FS IGBTs TCAD modeling to match accurately the device characteristics across a wide range of temperatures. The acceptor ionization energy (EA) governing the I.I. mechanism for the p-anode is extracted via matching the experimental turn-off waveforms and the static performance with Medici simulator. © 1980-2012 IEEE.

Behavior of RC beams retrofitted with CARDIFRC after thermal cycling

This study investigates the effect of thermal cycling on the performance of concrete beams retrofitted with CARDIFRC, a new class of high performance fiber-reinforced cement-based material that is compatible with concrete. Twenty four beams were subjected to 24 h thermal cycles between 25 and 90°C. One third of the beams were reinforced either in flexure only or in flexure and shear with conventional steel reinforcement and used as control specimens. The remaining sixteen beams were retrofitted with CARDIFRC strips to provide external flexural and/or shear strengthening. All beams were exposed to a varied number of 24 h thermal cycles ranging from 0 to 90 and were tested in four-point bending at room temperature. The tests indicated that the retrofitted members were stronger and stiffer than control beams, and more importantly, that their failure initiated in flexure without any signs of interfacial delamination cracking. The results of these tests are presented and compared to analytical predictions. The predictions show good correlation with the experimental results. © 2010 ASCE.

Unified analytic model for current-voltage behavior in amorphous oxide semiconductor TFTs

We present a simple and semi-physical analytical description of the current-voltage characteristics of amorphous oxide semiconductor thin-film transistors in the above-threshold and sub-threshold regions. Both regions are described by single unified expression that employs the same set of model parameter values directly extracted from measured terminal characteristics. The model accurately reproduces measured characteristics of amorphous semiconductor thin film transistors in general, yielding a scatter of < 4%. © 1980-2012 IEEE.

Does temporal discounting explain unhealthy behavior? A systematic review and reinforcement learning perspective.

The tendency to make unhealthy choices is hypothesized to be related to an individual's temporal discount rate, the theoretical rate at which they devalue delayed rewards. Furthermore, a particular form of temporal discounting, hyperbolic discounting, has been proposed to explain why unhealthy behavior can occur despite healthy intentions. We examine these two hypotheses in turn. We first systematically review studies which investigate whether discount rates can predict unhealthy behavior. These studies reveal that high discount rates for money (and in some instances food or drug rewards) are associated with several unhealthy behaviors and markers of health status, establishing discounting as a promising predictive measure. We secondly examine whether intention-incongruent unhealthy actions are consistent with hyperbolic discounting. We conclude that intention-incongruent actions are often triggered by environmental cues or changes in motivational state, whose effects are not parameterized by hyperbolic discounting. We propose a framework for understanding these state-based effects in terms of the interplay of two distinct reinforcement learning mechanisms: a "model-based" (or goal-directed) system and a "model-free" (or habitual) system. Under this framework, while discounting of delayed health may contribute to the initiation of unhealthy behavior, with repetition, many unhealthy behaviors become habitual; if health goals then change, habitual behavior can still arise in response to environmental cues. We propose that the burgeoning development of computational models of these processes will permit further identification of health decision-making phenotypes.

Experimental and numerical investigation of the seismic behavior of rectangular tunnels in soft soils

Underground structures constitute crucial components of the transportation networks. Considering their significance for modern societies, their proper seismic design is of great importance. However, this design may become very tricky, accounting of the lack of knowledge regarding their seismic behavior. Several issues that are significantly affecting this behavior (i.e. earth pressures on the structure, seismic shear stresses around the structure, complex deformation modes for rectangular structures during shaking etc.) are still open. The problem is wider for the non-circular (i.e. rectangular) structures, were the soilstructure interaction effects are expected to be maximized. The paper presents representative experimental results from a test case of a series of dynamic centrifuge tests that were performed on rectangular tunnels embedded in dry sand. The tests were carried out at the centrifuge facility of the University of Cambridge, within the Transnational Task of the SERIES EU research program. The presented test case is also numerically simulated and studied. Preliminary full dynamic time history analyses of the coupled soil-tunnel system are performed, using ABAQUS. Soil non-linearity and soil-structure interaction are modeled, following relevant specifications for underground structures and tunnels. Numerical predictions are compared to experimental results and discussed. Based on this comprehensive experimental and numerical study, the seismic behavior of rectangular embedded structures is better understood and modeled, consisting an important step in the development of appropriate specifications for the seismic design of rectangular shallow tunnels.

Self-organization of reflexive behavior from spontaneous motor activity.

In mammals, the development of reflexes is often regarded as an innate process. However, recent findings show that fetuses are endowed with favorable conditions for ontogenetic development. In this article, we hypothesize that the circuitry of at least some mammalian reflexes can be self-organized from the sensory and motor interactions brought forth in a musculoskeletal system. We focus mainly on three reflexes: the myotatic reflex, the reciprocal inhibition reflex, and the reverse myotatic reflex. To test our hypothesis, we conducted a set of experiments on a simulated musculoskeletal system using pairs of agonist and antagonist muscles. The reflex connectivity is obtained by producing spontaneous motor activity in each muscle and by correlating the resulting sensor and motor signals. Our results show that, under biologically plausible conditions, the reflex circuitry thus obtained is consistent with that identified in relation to the analogous mammalian reflexes. In addition, they show that the reflex connectivity obtained depends on the morphology of the musculoskeletal system as well as on the environment that it is embedded in.

Learning legged locomotion

Legged locomotion of biological systems can be viewed as a self-organizing process of highly complex system-environment interactions. Walking behavior is, for example, generated from the interactions between many mechanical components (e.g., physical interactions between feet and ground, skeletons and muscle-tendon systems), and distributed informational processes (e.g., sensory information processing, sensory-motor control in central nervous system, and reflexes) [21]. An interesting aspect of legged locomotion study lies in the fact that there are multiple levels of self-organization processes (at the levels of mechanical dynamics, sensory-motor control, and learning). Previously, the self-organization of mechanical dynamics was nicely demonstrated by the so-called Passive Dynamic Walkers (PDWs; [18]). The PDW is a purely mechanical structure consisting of body, thigh, and shank limbs that are connected by passive joints. When placed on a shallow slope, it exhibits natural bipedal walking dynamics by converting potential to kinetic energy without any actuation. An important contribution of these case studies is that, if designed properly, mechanical dynamics can generate a relatively complex locomotion dynamics, on the one hand, and the mechanical dynamics induces self-stability against small disturbances without any explicit control of motors, on the other. The basic principle of the mechanical self-stability appears to be fairly general that there are several different physics models that exhibit similar characteristics in different kinds of behaviors (e.g., hopping, running, and swimming; [2, 4, 9, 16, 19]), and a number of robotic platforms have been developed based on them [1, 8, 13, 22]. © 2009 Springer London.

Bipedal walking and running with compliant legs

Passive dynamics plays an important role in legged locomotion of the biological systems. The use of passive dynamics provides a number of advantages in legged locomotion such as energy efficiency, self-stabilization against disturbances, and generating gait patterns and behavioral diversity. Inspired from the theoretical and experimental studies in biomechanics, this paper presents a novel bipedal locomotion model for walking and running behavior which uses compliant legs. This model consists of three-segment legs, two servomotors, and four passive joints that are constrained by eight tension springs. The self-organization of two gait patterns (walking and running) is demonstrated in simulation and in a real-world robot. The analysis of joint kinematics and ground reaction force explains how a minimalistic control architecture can exploit the particular leg design for generating different gait patterns. Moreover, it is shown how the proposed model can be extended for controlling locomotion velocity and gait patterns with the simplest control architecture. © 2007 IEEE.

Morphological computation for adaptive behavior and cognition

Traditionally, in robotics, artificial intelligence and neuroscience, there has been a focus on the study of the control or the neural system itself. Recently there has been an increasing interest in the notion of embodiment not only in robotics and artificial intelligence, but also in the neurosciences, psychology and philosophy. In this paper, we introduce the notion of morphological computation, and demonstrate how it can be exploited on the one hand for designing intelligent, adaptive robotic systems, and on the other hand for understanding natural systems. While embodiment has often been used in its trivial meaning, i.e. "intelligence requires a body", the concept has deeper and more important implications, concerned with the relation between physical and information (neural, control) processes. Morphological computation is about connecting body, brain and environment. A number of case studies are presented to illustrate the concept. We conclude with some speculations about potential lessons for neuroscience and robotics. © 2006 Elsevier B.V. All rights reserved.

Behavior learning of a face robot based on the characteristics of human instruction

Computer simulation experiments were performed to examine the effectiveness of OR- and comparative-reinforcement learning algorithms. In the simulation, human rewards were given as +1 and -1. Two models of human instruction that determine which reward is to be given in every step of a human instruction were used. Results show that human instruction may have a possibility of including both model-A and model-B characteristics, and it can be expected that the comparative-reinforcement learning algorithm is more effective for learning by human instructions.