目标属性为肯定和否定的多目标决策问题解的有效性条件

本文建立了一类目标属性为肯定和否定的多目标决策模型,定义了相应的有效性。并在此基础上,讨论了有效性条件。     

Improvement in estimating the population mean in simple random sampling using information on auxiliary attribute

This paper proposes some estimators for the population mean by adapting the estimator in Singh et al. (2008) [5] to the ratio estimators presented in Kadilar and Cingi 2006 [2]. We obtain mean square error (MSE) equation for all proposed estimators, and show that all proposed estimators are always more efficient than ratio estimator in Naik and Gupta (1996) [3], and Singh et al. (2008) [5]. The results have been illustrated numerically by taking some empirical population considered in the literature.     

A stochastic approach to capture crystal plasticity

A stochastic crystal plasticity model is proposed and applied within the rate-independent regime. As opposed to conventional deterministic algorithms wherein multiple slip systems are activated and redundant constraints may exist, the new Monte Carlo plasticity (MCP) paradigm is based on a stochastic chain of singly activated slip systems and thus avoids the possible ill-condition associated with multi-slip algorithms. The choice of the activated slip system is made at each Monte Carlo (MC) step based on the Metropolis algorithm. The MCP model is implemented within a Material Point Method (MPM) as a constitutive model to capture the elasto-plastic behavior of polycrystalline materials. A comparison with a commonly used singular value decomposition (SVD) algorithm indicates that MCP offers superior computational efficiency while maintaining comparable accuracy.     

On the efficiency of a testimator for the mean of an inverse Gaussian distribution

Though the sample mean is a natural estimator for the mean μ of an Inverse Gaussian (IG) distribution having another parameter λ, when a guess μ₀ for μ seems plausible, an alternative adaptive estimator which shrinks towards μ₀ when a preliminary test for H₀:μ = μ₀ is tenable or else towards , is considered a suitable competitor. Certain numerical illustrations are presented showing higher efficiency of such a testimator over in several situations when the sample size is small and λ is either known or unknown.     

Finding the efficiency score and RTS characteristic of DMUs by means of identifying the efficient frontier in DEA

Data envelopment analysis (DEA) is basically a linear programming based technique used for measuring the relative performance of organizational units, referred to as decision-making units (DMUs), where the presence of multiple inputs and outputs makes comparisons difficult. The ability of identifying frontier DMUs prior to the DEA calculation is of extreme importance to an effective and efficient DEA computation. In this paper, a method for identifying the efficient frontier is introduced. Then, the efficiency score and returns to scale (RTS) characteristic of DMUs will be produced by means of the equation of efficient frontier.     

Wavelet-Based Estimation for Univariate Stable Laws

Stable distributions are characterized by four parameters which can be estimated via a number of methods, and although approximate maximum likelihood estimation techniques have been proposed, they are computationally intensive and difficult to implement. This article describes a fast, wavelet-based, regression-type method for estimating the parameters of a stable distribution. Fourier domain representations, combined with a wavelet multiresolution approach, are shown to be effective and highly efficient tools for inference in stable law families. Our procedures are illustrated and compared with other estimation methods using simulated data, and an application to a real data example is explored. One novel aspect of this work is that here wavelets are being used to solve a parametric problem, rather than a nonparametric one, which is the more typical context in wavelet applications.     

A graphical characterization of the efficient set for?convex multiobjective problems

In this paper, a graphical characterization, in the decision space, of the properly efficient solutions of a convex multiobjective problem is derived. This characterization takes into account the relative position of the gradients of the objective functions and the active constraints at the given feasible solution. The unconstrained case with two objective functions and with any number of functions and the general constrained case are studied separately. In some cases, these results can provide a visualization of the efficient set, for problems with two or three variables. Besides, a proper efficiency test for general convex multiobjective problems is derived, which consists of solving a single linear optimization problem.     

Evaluating the effectiveness and efficiency of voice therapy using transnasal flexible laryngoscopy: a randomized controlled trial

Transnasal flexible laryngoscopy (TFL) is an examination of laryngeal anatomy and physiology using continuous light. TFL is being used increasingly by voice pathologists in treatment but with little scientific evidence to support it. The purpose of this study was to evaluate the effectiveness and efficiency of TFL as a therapeutic tool. The study used a prospective randomized controlled trial. Fifty dysphonic subjects were recruited and randomly assigned to either a traditional treatment group or a TFL-assisted treatment group. The effectiveness of voice therapy in both treatment groups was measured with a package of voice outcome measures. Subjects in both treatment groups demonstrated statistically significant improvements after voice therapy (perceptual auditory rating of voice quality measurement p < 0.01; instrumental electroglottographic measurement p < 0.01; patient questionnaire measurement p < 0.01). The time taken to complete treatment in both groups was recorded. The average (median) time taken to complete voice therapy in the TFL-assisted treatment group was 2 hours less than in the traditional treatment group (p < 0.01). Voice therapy with TFL as a therapy tool was effective and more efficient than traditional voice therapy.     

Benchmarking with quality-adjusted DEA (Q-DEA) to seek lower-cost high-quality service: Evidence from a U.S.bank application

Benchmarking is a widely cited method to identify and adopt best-practices as a means to improve performance. Data envelopment analysis (DEA) has been demonstrated to be a powerful benchmarking methodology for situations where multiple inputs and outputs need to be assessed to identify best-practices and improve productivity in organizations. Most DEA benchmarking studies have excluded quality, even in service-sector applications such as health care where quality is a key element of performance. This limits the practical value of DEA in organizations where maintaining and improving service quality is critical to achieving performance objectives. In this paper, alternative methods incorporating quality in DEA benchmarking are demonstrated and evaluated. It is shown that simply treating the quality measures as DEA outputs does not help in discriminating the performance. Thus, the current study presents a new, more sensitive, quality-adjusted DEA (Q-DEA), which effectively deals with quality measures in benchmarking. We report the results of applying Q-DEA to a U.S. bank's 200-branch network that required a method for benchmarking to help manage operating costs and service quality. Q-DEA findings helped the bank achieve cost savings and improved operations while preserving service quality, a dimension critical to its mission. New insights about ways to improve branch operations based on the best-practice (high-quality low-cost) benchmarks identified with Q-DEA are also described in the paper. This demonstrates the practical need and potential benefits of Q-DEA and its efficacy in one application, and also suggests the need for further research on measuring and incorporating quality into DEA benchmarking. The review process of this paper was handled by the Edit-in-Chief Peter Hammer.     

Transfer functions of US transducers for harmonic imaging and bubble responses

Current medical diagnostic echo systems are mostly using harmonic imaging. This means that a fundamental frequency (e.g., 2 MHz) is transmitted and the reflected and scattered higher harmonics (e.g., 4 and 6 MHz), produced by nonlinear propagation, are recorded. The signal level of these harmonics is usually low and a well-defined transfer function of the receiving transducer is required. Studying the acoustic response of a single contrast bubble, which has an amplitude in the order of a few Pascal, is another area where an optimal receive transfer function is important.

We have developed three methods to determine the absolute transfer function of a transducer. The first is based on a well-defined wave generated by a calibrated source in the far field. The receiving transducer receives the calibrated wave and from this the transfer functions can be calculated. The second and third methods are based on the reciprocity of the transducer. The second utilizes a calibrated hydrophone to measure the transmitted field. In the third method, a pulse is transmitted by the transducer, which impinges on a reflector and is received again by the same transducer. In both methods, the response combined with the transducer impedance and beam profiles enables the calculation of the transfer function.

The proposed methods are useful to select the optimal piezoelectric material (PZT, single crystal) for transducers used in reception only, such as in certain 3D scanning designs and superharmonic imaging, and for selected experiments like single bubble behavior.

We tested and compared these methods on two unfocused single element transducers, one commercially available (radius 6.35 mm, centre frequency 2.25 MHz) the other custom built (radius 0.75 mm, centre frequency 4.3 MHz). The methods were accurate to within 15%.