Linear motor for multi-car elevators, design and position measurement

Multi-car elevator is an emerging technology consisting of two or more elevator cars moving independently in an elevator hoistway, which has become more appealing as building heights increase. In this paper, the design and drive methodologies for a linear motor driven multi-car elevator system with independently moving cars is introduced together with experimental results. Additionally, a safety method developed for the linear motor elevator and the conditions necessary for its proper operation are discussed. The new results introduced in this paper are in the areas of the design method of the linear motor for multi-car elevator system, and the preliminary results for the position measurement system

Threshold Selection, Hypothesis Tests, and DOE Methods

Threshold selection - a selection mechanism for noisy evolutionary algorithms - is put into the broader context of hypothesis testing. Theoretical results are presented and applied to a simple model of stochastic search and to a simplified elevator simulator. Design of experiments methods are used to validate the significance of the results

Design and implementation of a linear motor for multi-car elevators

The multi-car elevator system is a revolutionary new technology for high-rise buildings, promising outstanding economic benefits, but also requiring new technology for propulsion, safety and control. In this paper we report on experimental results with new components for linear motor driven multi-car elevators. We show that linear synchronous motors with optimized design and with our new safety and control system can be considered as core components of a new generation of elevator systems. The main new results concern the development of a safety system integrated into the propulsion system, the design methodology of a linear motor optimized for the multi-car elevator task, and the motion control system that is expected to be usable for extra high-rise buildings

Reliability and clinical usefulness of the personality inventory for DSM-5 in clinically referred adolescents. A preliminary report in a sample of Italian inpatients

Background The DSM-5 Alternative Model of Personality Disorders (AMPD) provides the opportunity to integrate the needed developmental perspective in the assessment of personality pathology. Based on this model, Krueger and colleagues (2012) developed the Personality Inventory for DSM-5 (PID-5), which operationalizes the proposed DSM-5 traits. Methods Eighty-five consecutively admitted Italian adolescent inpatients were administered the Italian translation of the PID-5, in order to obtain preliminary data on PID-5 reliability and clinical usefulness in clinically referred adolescents. Results With the possible exception of the PID-5 Suspiciousness scale, all other PID-5 scales evidenced adequate internal consistency reliability (i.e., Cronbach's α values of at least .70, most being greater than .80). Our data seemed to yield at least partial support for the construct validity of the PID-5 scales also in clinical adolescents, at least in terms of patterns of associations with dimensionally assessed DSM-5 Section II PDs that were also included in the DSM-5 AMPD (excluding Antisocial PD because of the participants' minor age). Finally, our data suggested that the clinical usefulness of the PID-5 in adolescent inpatients may extend beyond PDs to profiling adolescents at risk for life-threatening suicide attempts. In particular, PID-5 Depressivity, Anhedonia, and Submissiveness trait scales were significantly associated with adolescents' history of life-threatening suicide attempts, even after controlling for a number of other variables, including mood disorder diagnosis. Discussion As a whole, our study may provide interesting, albeit preliminary data as to the clinical usefulness of PID-5 in the assessment of adolescent inpatients

Optimal Elevator Group Control by Evolution Strategies

Efficient elevator group control is important for the operation of large buildings. Recent developments in this field include the use of fuzzy logic and neural networks. This paper summarizes the development of an evolution strategy (ES) that is capable of optimizing the neuro-controller of an elevator group controller. It extends the results that were based on a simplified elevator group controller simulator. A threshold selection technique is presented as a method to cope with noisy fitness function values during the optimization run. Experimental design techniques are used to analyze first experimental results

Numerical Implementation of the QuEST Function

This paper deals with certain estimation problems involving the covariance matrix in large dimensions. Due to the breakdown of finite-dimensional asymptotic theory when the dimension is not negligible with respect to the sample size, it is necessary to resort to an alternative framework known as large-dimensional asymptotics. Recently, Ledoit and Wolf (2015) have proposed an estimator of the eigenvalues of the population covariance matrix that is consistent according to a mean-square criterion under large-dimensional asymptotics. It requires numerical inversion of a multivariate nonrandom function which they call the QuEST function. The present paper explains how to numerically implement the QuEST function in practice through a series of six successive steps. It also provides an algorithm to compute the Jacobian analytically, which is necessary for numerical inversion by a nonlinear optimizer. Monte Carlo simulations document the effectiveness of the code.Comment: 35 pages, 8 figure