A randomized voltage vector switching scheme for three-level powerinverters

In this paper, a feasibility study of a randomized space vector switching scheme for three-level inverters is reported. Based on the traditional space vector concept for pulse width modulation (PWM) inverters, the sequence of the space vector is randomized in this scheme. The overall vector, resulting from the randomization, is mathematically identical to that of the traditional space vector. It has been found that the randomized scheme can effectively spread the switching noise over a wide frequency range and at the same time keep the steady-state link capacitor voltage balanced. The proposed scheme has been implemented in real time in a digital controller and its features have been experimentally confirmed     

Risk factors associated with recidivism among extrafamilial child molesters.

This study examined the predictive efficacy of 10 rationally derived, archivally coded variables for assessing reoffense risk among extrafamilial child molesters. Follow-up data on 111 child molesters who were discharged from the Massachusetts Treatment Center between 1960 and 1984 were used. Degree of sexual preoccupation with children, paraphilias, and number of prior sexual offenses predicted sexual recidivism. Juvenile and adult antisocial behavior, paraphilias, and low amount of contact with children predicted nonsexual victim-involved and violent recidivism. Area under the receiver-operating characteristic curves in all three analyses indicated discrimination that was substantially better than chance, ranging from .73 to .79. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Facilities management, building maintenance and modernization link

The widening of interest and scope of property management and maintenance has attracted a greater diversity of professional disciplines into facilities management. Dr Quah, coordinator of CIB W70 on Management, Maintenance and Modernization of Building facilities, expresses her personal views on the current fascination with the subject.     

Classification and prediction of the critical heat flux using fuzzy theory and artificial neural networks

A new method to predict the critical heat flux (CHF) is proposed, based on the fuzzy clustering and artificial neural network. The fuzzy clustering classifies the experimental CHF data into a few data clusters (data groups) according to the data characteristics. After classification of the experimental data, the characteristics of the resulting clusters are discussed with emphasis on the distribution of the experimental conditions and physical mechanism. The CHF data in each group are trained in an artificial neural network to predict the CHF. The artificial neural network adjusts the weight so as to minimize the prediction error within the corresponding cluster. Application of the proposed method to the KAIST CHF data bank shows good prediction capability of the CHF, better than other existing methods.     

Integrated scheduling of flexible manufacturing systems employingautomated guided vehicles

Centralized and distributed automated guided vehicle system (AGVS) models for materials handling, and the model for part processing are integrated into a single coherent model. This formulation can be used to collectively schedule and control the entire flexible manufacturing system (FMS) as opposed to the traditional separate scheduling of part processing and material handling. The two AGVS models are based on Petri nets and can be directly used in the scheduling method that uses Petri nets for formulation and heuristic search for solution. This method employs a global search to seek the optimal operation of an entire FMS. Scheduling examples are presented and the method compares favorably with the results simulated using heuristic dispatch rules     

A neural network control system with parallel adaptive enhancementsapplicable to nonlinear servomechanisms

In this paper, we present a technique for using an additional parallel neural network to provide adaptive enhancements to a basic fixed neural network-based nonlinear control system. This proposed parallel adaptive neural network control system is applicable to nonlinear dynamical systems of the type commonly encountered in many practical position control servomechanisms. Properties of the controller are discussed, and it is shown that if Gaussian radial basis function networks are used for the additional parallel neural network, uniformly stable adaptation is assured and the approximation error converges to zero asymptotically. In the paper, the effectiveness of the proposed parallel adaptive neural network control system is demonstrated in real-time implementation experiments for position control in a servomechanism with asymmetrical loading and changes in the load     

Enhancement of oxide break-up by implantation of fluorine inpoly-Si emitter contacted p+-n shallow junctionformation

In this study, it is demonstrated that the incorporation of fluorine can enhance poly-Si/Si interfacial oxide break-up in the poly-Si emitter contacted p⁺-n shallow junction formation. The annealing temperature for breaking up the poly-Si/Si interfacial oxide has been found to be as low as 900°C. As a result, the junction depth of the BF₂-implanted device is much larger than that of the boron-implanted device