DEA based dimensionality reduction for classification problems satisfying strict non-satiety assumption

This study shows how data envelopment analysis (DEA) can be used to reduce vertical dimensionality of certain data mining databases. The study illustrates basic concepts using a real-world graduate admissions decision task. It is well known that cost sensitive mixed integer programming (MIP) problems are NP-complete. This study shows that heuristic solutions for cost sensitive classification problems can be obtained by solving a simple goal programming problem by that reduces the vertical dimension of the original learning dataset. Using simulated datasets and a misclassification cost performance metric, the performance of proposed goal programming heuristic is compared with the extended DEA-discriminant analysis MIP approach. The holdout sample results of our experiments shows that the proposed heuristic approach outperforms the extended DEA-discriminant analysis MIP approach.     

Decomposing profit inefficiency in DEA through the weighted additive model

An issue that has received little attention in the Data Envelopment Analysis literature is the decomposition of profit inefficiency by means of measures that account all sources of technical inefficiency. In this paper we introduce a new way to measure and decompose profit inefficiency through weighted additive models. All our results are derived from a new Fenchel-Mahler inequality using duality theory.     

Efficiency measurement using independent component analysis and data envelopment analysis

Efficiency measurement is an important issue for any firm or organization. Efficiency measurement allows organizations to compare their performance with their competitors’ and then develop corresponding plans to improve performance. Various efficiency measurement tools, such as conventional statistical methods and non-parametric methods, have been successfully developed in the literature. Among these tools, the data envelopment analysis (DEA) approach is one of the most widely discussed. However, problems of discrimination between efficient and inefficient decision-making units also exist in the DEA context (Adler and Yazhemsky, 2010). In this paper, a two-stage approach of integrating independent component analysis (ICA) and data envelopment analysis (DEA) is proposed to overcome this issue. We suggest using ICA first to extract the input variables for generating independent components, then selecting the ICs representing the independent sources of input variables, and finally, inputting the selected ICs as new variables in the DEA model. A simulated dataset and a hospital dataset provided by the Office of Statistics in Taiwan’s Department of Health are used to demonstrate the validity of the proposed two-stage approach. The results show that the proposed method can not only separate performance differences between the DMUs but also improve the discriminatory capability of the DEA’s efficiency measurement.     

On the relative efficiency of alternative modes of producing a public sector output: The case of the developmentally disabled

This paper examines the relative efficiency of alternative methods of producing care for the developmentally disabled. A linear programming framework is used to construct a production frontier which allows measurement of relative efficiency among institutions in the sample. Tests are performed to detect influential observations in the data which might result from measurement error which could distort the efficiency measures. Different types of institutions are compared in terms of average efficiency. Policy implications of the analysis are discussed in the concluding section.     

超流氦获取实验液位数据采集与测试系统研究

针对超流氦获取与传输实验设计的数据采集系统由控制柜、工控机、显示器三部分组成。使用板卡PCI-1620对工控机的串口进行扩展,使系统能够同时采集8个RS232信号。其中液位信息是非常重要的物性参数,针对获取与传输实验液氦杜瓦设计定制的超导液位计,能够与整个测控系统一起完成液位信息的采集、转换和记录。     

Noise Characterization for Laser Interferometer Gravitational Wave Detectors

This work incorporates a review of the status, in Australia, of data analysis for gravitational wave detection using laser interferometers, within an overview of the present state of such research in the world generally. In this context, data analysis refers not so much to signal simulation as to what might be called the thorough process of noise characterization and the subsequent, quality-controlled signal extraction. To the extent that problems identified here arise for all currently planned instruments, there is necessarily a global component to the discussion presented. In Australia, there are unique circumstances, associated with attempting to carry out work in gravitational wave detection, which demand also a local aspect to the ensuing discussion.     

Bit-rate Flexible Picosecond Pulse Width Conversion with All-optical Mono-stable Multivibrator Laser Diode

An optical mono-stable multivibrator laser diode (MM-LD) is realized by using a multi-electrode distributed feedback laser diode. All-optical pulse-width conversion of ultra-short pulses to non-return-to-zero (NRZ) is achieved using an MM-LD. The MM-LD is adopted for a wide range of bit-rates between 2-10 Gbit/s by tuning the DC bias. Data format transformation from 10-Gbit/s return-to-zero optical signals to NRZ optical-signals is achieved with error free operation. Converted optical signals, which have a narrower spectral bandwidth and lower peak power than when input, are transmitted using a 1.3-μm zero dispersion fiber (1.3Aλ₀-SMF).     

活塞式压气机性能测试实验台的研制与应用

基于数据采集与处理技术设计了低成本活塞式压气机性能测试实验台,重点讨论了系统硬件和软件的组成特点,分析了实测的p-α图、p-V图和多变指数.实际应用表明,该实验台可以真实再现压气机的热力过程,既可以用于压气机热力学分析的本科实验,又可以用于压气机运行故障的诊断分析.     

Testing procedures for detection of linear dependencies in efficiency models

The validity of many efficiency measurement methods rely upon the assumption that variables such as input quantities and output mixes are independent of (or uncorrelated with) technical efficiency, however few studies have attempted to test these assumptions. In a recent paper, Wilson (2003) investigates a number of independence tests and finds that they have poor size properties and low power in moderate sample sizes. In this study we discuss the implications of these assumptions in three situations: (i) bootstrapping non-parametric efficiency models; (ii) estimating stochastic frontier models and (iii) obtaining aggregate measures of industry efficiency. We propose a semi-parametric Hausmann-type asymptotic test for linear independence (uncorrelation), and use a Monte Carlo experiment to show that it has good size and power properties in finite samples. We also describe how the test can be generalized in order to detect higher order dependencies, such as heteroscedasticity, so that the test can be used to test for (full) independence when the efficiency distribution has a finite number of moments. Finally, an empirical illustration is provided using data on US electric power generation.