Learning and convergence analysis of neural-type structurednetworks

A class of feedforward neural networks, structured networks, has recently been introduced as a method for solving matrix algebra problems in an inherently parallel formulation. A convergence analysis for the training of structured networks is presented. Since the learning techniques used in structured networks are also employed in the training of neural networks, the issue of convergence is discussed not only from a numerical algebra perspective but also as a means of deriving insight into connectionist learning. Bounds on the learning rate are developed under which exponential convergence of the weights to their correct values is proved for a class of matrix algebra problems that includes linear equation solving, matrix inversion, and Lyapunov equation solving. For a special class of problems, the orthogonalized back-propagation algorithm, an optimal recursive update law for minimizing a least-squares cost functional, is introduced. It guarantees exact convergence in one epoch. Several learning issues are investigated.     

Opposite-channel-based charge injection in SOI MOSFET's under hotcarrier stress

By operating one channel of a typical SOI MOSFET in avalanche while keeping the opposite channel accumulated, charge injection into the opposite gate takes place. Three independent experiments are described that demonstrate the occurrence of this opposite-channel based charge injection. The experimental results are in agreement with PISCES numerical simulations     

A Glance into Social and Evolutionary Aspects of an Artifact Ecology for Collaborative Learning through the Lens of Distributed Cognition

There is steadily growing interest in the design and evaluation of digitally enhanced spaces in the real-world where users use, combine, and appropriate different physical and digital tools based on the task at hand. Under the notion of “ubiquitous computing,” researchers have explored tools and theories to analyze, understand, and model users in complex socio-technical systems. Yet, even though theoretical approaches play a significant role in the work of practitioners, there is a general difficulty in applying them, pushing researchers to explore methodological frameworks with clearer guidelines. Using the distributed cognition for teamwork (DiCoT) framework, we study collaboration and communication patterns, physical movement, and social structures of two groups of learners working on a design problem as they evolve over a 3-month period. Through an in-depth investigation, we present detailed accounts of the social and evolutionary models of DiCoT for each group. Our analysis enriches the DiCoT framework by identifying five new principles: social emersion and social circles of privacy for the social model, and continuity, mutual adaptation, and semantics of body for the evolutionary model. This article contributes to HCI research by refining and extending the existing DiCoT framework and elaborating on two dimensions that have previously been under-developed in the literature.     

A review of current research in manufacturing shop design integration

The importance of the manufacturing shop design in the successful operation of a production system is well documented and, as a result, significant work has been devoted to this area. Due to the inherent complexity of the global shop design problem, much research has focused on individual sub-problems, including the layout of manufacturing resources, the design of the shop aisle network, and the selection of the material handling equipment, rather than addressing the integrated problem directly. This paper reviews literature contributions to shop design integration, as well as partial integration schemes such as the design for operation and control of material handling systems. Furthermore, it examines the ability of models and solution approaches for individual sub-problems of shop design to support integration schemes.     

基建仓库

基建仓库项目位于莱瓦顿的Harlingervaart运河岸边,作为周边建筑的仓库,它具有独特的趣味性良好的形体感,因此被认为是立于运河沿岸广场上的一座雕塑。建筑的入口处挑出悬臂,并且顺势突出建筑南侧的体量     

Evaluation of ACC vehicles in mixed traffic: lane change effects and sensitivity analysis

Almost every automobile company is producing vehicles with adaptive cruise control (ACC) system onboard that enables a vehicle to do automatic vehicle following in the longitudinal direction. The ACC system is designed for driver's comfort and safety and to operate with manually driven vehicles. These characteristics of ACC were found to have beneficial effects on the environment and traffic flow characteristics by acting as filters of a wide class of traffic disturbances. It has been argued that the smooth response of ACC vehicles to high-acceleration disturbances or large position errors creates large gaps between the ACC vehicle and the vehicle ahead inviting cut-ins and therefore generating additional disturbances that would not have been created if all vehicles had been manually driven. In this paper, we examine the effect of lane changes on the benefits suggested by Bose and Ioannou as well as the sensitivity of these benefits with respect to various variables such as the penetration of the ACC vehicles, level of traffic disturbances etc. We demonstrate, using theory, simulations, and experiments, that during lane changes, the smoothness of the ACC vehicle response attenuates the disturbances introduced by a cut-in or an exiting vehicle in a way that is beneficial to the environment when compared with similar situations where all vehicles are manually driven. We concluded that a higher number of possible cut-ins that may occur due to the larger gaps created during high-acceleration maneuvers by the vehicle in front of the ACC vehicle, will not annul the benefits obtained in the absence of such cut-ins when compared with the situation of similar maneuvers but with no cut-ins in the case of 100% manually driven vehicles.     

Robust switching adaptive control of multi-input nonlinear systems

During the last decade a considerable progress has been made in the design of stabilizing controllers for nonlinear systems with known and unknown constant parameters. New design tools such as adaptive feedback linearization, adaptive back-stepping, control Lyapunov functions (CLFs) and robust control Lyapunov functions (RCLFs), nonlinear damping and switching adaptive control have been introduced. Most of the results developed are applicable to single-input feedback-linearizable systems and parametric-strict-feedback systems. These results, however, cannot be applied to multi-input feedback-linearizable systems, parametric-pure-feedback systems and systems that admit a linear-in-the-parameters CLF. In this paper, we develop a general procedure for designing robust adaptive controllers for a large class of multi-input nonlinear systems. This class of nonlinear systems includes as a special case multi-input feedback-linearizable systems, parametric-pure-feedback systems and systems that admit a linear-in-the-parameters CLF. The proposed approach uses tools from the theory of RCLF and the switching adaptive controllers proposed by the authors for overcoming the problem of computing the feedback control law when the estimation model becomes uncontrollable. The proposed control approach has also been shown to be robust with respect to exogenous bounded input disturbances