Noise-free Determination of Isochromatic Fringe Order by Load Stepping

The traditional ambiguity in the sign of fractional retardation in certain zones of the model by phase shifting technique has been overcome with the development of load stepping in digital photoelasticity. However, the existing methodology of load stepping introduces several points in the model domain that are subjected to excessive noise. A new methodology has been proposed that combines the merits of load stepping and phase shifting to obtain fractional retardation free of noise and ambiguity over the model domain.     

A review of some damage tolerance design approaches for aircraft structures

Damage tolerance design is becoming a necessity in the design of modern aircraft although its importance was recognized as long as four centuries ago by Leonardo da Vinci. Two decades ago structural design engineers and research workers felt the need of incorporating damage tolerance in the design of aircraft structure. Due to a lack of comprehensive damage tolerance methodology large scale component test results were used to develop empirical damage tolerance methods. Recently, linear elastic fracture mechanics has been used in predicting residual strength and crack growth rates in damaged structure. As a result of these efforts significant developments in cracked structure analytical methodology have been achieved. The recent Air Force requirement to apply linear elastic fracture mechanics approach in damage tolerance design of aircraft structures, warrants and critical review of various approaches. In this paper an attempt has been made to critically review some damage tolerance design approaches and their application to aircraft structures.

The paper consists of three main sections: The first section reviews the residual strength analysis methodology, assumptions and limitations of each method are discussed through a simple example. The second part surveys the various crack propagation laws, including linear and non-linear ranges and spectrum loading effects. In the third and last section, fracture mechanics methodology is applied to several types of built-up structural components under spectrum loading conditions. The comparison of test results and analysis of complex structures indicate that simple methods of fracture mechanics can be applied to find the damage tolerant strength and rate of crack growth.

The review presented in this paper indicates that the majority of work done in development of fracture mechanics analytical methodology has been based on data obtained from small scale laboratory specimens tested under closely controlled conditions of damage and environment. The validity of the methodology for complex structure under complex loading conditions has not been established. Before the results of a fracture mechanics analytical methodology can be accepted with a high degree of confidence many realism factors must be properly accounted for in the analysis.     

Frequency domain interpretation of power ratio metric for cognitive radio systems

Software radio (SWR) is an enabling technology for cognitive radio (CR) systems which promises to (de) modulate any signal, at any frequency. SWR signal therefore is composed of different standard's signals, and each standard's signal is either multicarrier or multiplex of single carriers. This combination leads to high temporal fluctuations and thus SWR signal inherits high peak to average power ratio (PAPR) or simply high power ratio (PR). Nonlinear analogue components (amplifiers, converters etc.) cause distortions (in and out of band distortion) for high PR signals which result in system performance degradation. Usually PR problem is addressed in time domain, and here frequency domain interpretation of PR which is more appropriate in SWR context is presented. Gaussian equivalence between SWR signal and orthogonal frequency division multiplexing (OFDM) signal is proved first to accentuate high PR issue in SWR as OFDM suffers the same problem. Then frequency domain interpretation of PR metric is discussed which results in a PR upper bound. This PR upper bound depends only upon spectral values of the signal thus associates spectrum with PR. As a result this bound assists in spectrum access for CR systems by providing PR metric information related to any available bandwidth. Thus bandwidth allocation in a spectrum access scenario under PR constraint is simplified.     

时程分析考虑高阶振型影响的多频段地震波选择方法研究

针对结构抗震时程分析输入地震波选择问题,以加速度反应谱（或设计谱）为目标谱,在反应谱平台段和结构基本周期附近误差双控指标中,引入了由归一化振型参与系数确定的前几阶振型的权重系数,提出了考虑多频段加权匹配的时程分析输入地震波选择方法,以充分考虑高阶振型的影响。以美国SAC Steel Project提出的9层和20层抗弯钢框架Benchmark结构为实例,为方便将建议选波方法与较多地震波输入时程分析结果进行比较,以简单地震信息初选的小型地震波数据库中的20条地震波的均值（放大系数）谱作为目标谱,以这20条地震波时程分析得到的结构最大基底剪力和层间位移角均值为目标反应,前者考虑弹性状态,后者对应弹塑性情况。将按该文方法选出的3条波输入下结构反应均值与目标反应进行了比较分析,初步证实了建议选波方法的可行性。将该文方法与ASCE 7-05地震波输入要求方法对比,在弹塑性反应状态下,两者对结构最大层间位移角沿楼层分布规律的估计以及薄弱层位置的判断均与目标反应较为一致。ASCE 7-05方法输入下结构反应均大于目标反应,偏于安全。而按该文方法输入存在高估和低估结构反应的情况,建议附加\     

Calibration of adhesion models based on Bayesian inference

The use of composite materials in a myriad of applications fostered the development of reliable procedures to connect components with adhesives. This led to a demand for reliable adhesion models to be used in engineering designs that are based on computer simulations. This paper presents a strategy to be used for calibration of adhesion models. The proposed methodology is built on the formalism of Statistical Inverse Problems. Uncertainties about the unknowns are inferred using Population-Based Markov Chain Monte Carlo and Adaptive Metropolis. It is proposed to perform model assessments based on the analysis of a validation metric. Realizations of the validation metric are computed with the posterior densities of model parameters that are provided by the calibration process. The analysis of the validation metric allows for model selection to be performed. Some numerical experiments are presented with noise-contaminated data. The calibration strategy proved effective when dealing with both the nonlinearity and nondifferentiability of the adhesion constitutive equation.     

Automatic ordering of isochromatic fringes - a new methodology

The intensity variations in the isochromatic fringe field are significant and even minute variations can be recorded using the modern day CCD cameras. The sodium vapour source (589. 3 nm) used in general has upto 4% of another wavelength of 589. 6 nm. In view of this, the minimum intensity forming a fringe is affected and is significant at high density fringe zones. This aspect is used to identify sources and sinks in the fringe field and a new methodology for fringe ordering is proposed. It requires only one image to be processed and hence is equally applicable for static and dynamic problems.     

Modelling robustness in serial multi-stage manufacturing processes

The study of robustness in single-stage manufacturing has been explored by a large number of researchers and practitioners. However, modelling of robustness in multi-stage manufacturing using multivariate data is seldom used. The aim of this paper is to develop a methodology to model process robustness in a serial multi-stage manufacturing system. Combining statistical regression, Taylor series expansion, the root-sum-squares method and a variation model, the methodology proposes a measurement system for robustness. The resulting metric, while quantifying robustness, measures absorbed and transmitted variations across the stages of a manufacturing process. Using the methodology in a serial two-stage worm gear manufacturing process, the levels of robustness and both absorbed and transmitted variations are determined, thus identifying significant variations across manufacturing stages. The details of this application with the types of corrective actions as required for minimisation of process performance deterioration are presented.     

Noninvasive near-infrared blood glucose monitoring using a calibration model built by a numerical simulation method: Trial application to patients in an intensive care unit

We have applied a new methodology for noninvasive continuous blood glucose monitoring, proposed in our previous paper, to patients in ICU (intensive care unit), where strict controls of blood glucose levels are required. The new methodology can build calibration models essentially from numerical simulation, while the conventional methodology requires pre-experiments such as sugar tolerance tests, which are impossible to perform on ICU patients in most cases. The in vivo experiments in this study consisted of two stages, the first stage conducted on healthy subjects as preliminary experiments, and the second stage on ICU patients. The prediction performance of the first stage was obtained as a correlation coefficient (r) of 0.71 and standard error of prediction (SEP) of 28.7 mg/dL. Of the 323 total data, 71.5% were in the A zone, 28.5% were in the B zone, and none were in the C, D, and E zones for the Clarke error-grid analysis. The prediction performance of the second stage was obtained as an r of 0.97 and SEP of 27.2 mg/dL. Of the 304 total data, 80.3% were in the A zone, 19.7% were in the B zone, and none were in the C, D, and E zones. These prediction results suggest that the new methodology has the potential to realize a noninvasive blood glucose monitoring system using near-infrared spectroscopy (NIRS) in ICUs. Although the total performance of the present monitoring system has not yet reached a satisfactory level as a stand-alone system, it can be developed as a complementary system to the conventional one used in ICUs for routine blood glucose management, which checks the blood glucose levels of patients every few hours.     

Anisotropic mesh adaption by metric‐driven optimization

We describe a Gauss–Seidel algorithm for optimizing a three‐dimensional unstructured grid so as to conform to a given metric. The objective function for the optimization process is based on the maximum value of an elemental residual measuring the distance of any simplex in the grid to the local target metric. We analyse different possible choices for the objective function, and we highlight their relative merits and deficiencies. Alternative strategies for conducting the optimization are compared and contrasted in terms of resulting grid quality and computational costs. Numerical simulations are used for demonstrating the features of the proposed methodology, and for studying some of its characteristics. Copyright © 2004 John Wiley & Sons, Ltd.     

CLASSIFICATION OF THE FATIGUE DOMAIN AND PREDICTION OF DAMAGE WITH CRACK EXTENSION PARAMETERS

The whole fatigue domain has been divided into six Werent zones, each governed by a separate fatigue regime. Some of these regimes coincide with a known classification of fatigue, and others are new regimes, where new prediction methods have been introduced. The proposed predictions are to be considered as practical curve fitting relations for special cases, but those cases can also be fairly general and useful for design purposes. The proposed fatigue diagram can be used as a basis for a quantified explanation of several known fatigue phenomena.     

Blind image quality assessment through anisotropy

We describe an innovative methodology for determining the quality of digital images. The method is based on measuring the variance of the expected entropy of a given image upon a set of predefined directions. Entropy can be calculated on a local basis by using a spatial/spatial-frequency distribution as an approximation for a probability density function. The generalized Rényi entropy and the normalized pseudo-Wigner distribution (PWD) have been selected for this purpose. As a consequence, a pixel-by-pixel entropy value can be calculated, and therefore entropy histograms can be generated as well. The variance of the expected entropy is measured as a function of the directionality, and it has been taken as an anisotropy indicator. For this purpose, directional selectivity can be attained by using an oriented 1-D PWD implementation. Our main purpose is to show how such an anisotropy measure can be used as a metric to assess both the fidelity and quality of images. Experimental results show that an index such as this presents some desirable features that resemble those from an ideal image quality function, constituting a suitable quality index for natural images. Namely, in-focus, noise-free natural images have shown a maximum of this metric in comparison with other degraded, blurred, or noisy versions. This result provides a way of identifying in-focus, noise-free images from other degraded versions, allowing an automatic and nonreference classification of images according to their relative quality. It is also shown that the new measure is well correlated with classical reference metrics such as the peak signal-to-noise ratio.     

Energy market segmentation for distributed energy resources implementation purposes

The new power market scene has made its actors aware of the importance of offering customers a set of products according to their specific needs. At the same time, a desirable massive deployment of distributed energy resources would require that the products be designed for specific purposes for each type of customer. For these reasons, it is essential to identify the energy behaviour of different customer segments existing in the electricity market. This paper presents a segmentation methodology that allows the identification of different types of customers in accordance with their energy use. This segmentation is conceptually different from the one that is currently performed by the utilities, which is based on commercial premises, but has been designed to be compatible with the current data organisation at the utilities. These characteristics make the proposed segmentation unique and useful to many energy-related applications. This segmentation methodology presented has been developed in the framework of EU-DEEP, a large VI-Framework Program of the European Commissions, where it was used to assess which segments are suitable for the implementation of distributed energy resources. The connection with this project is also discussed in the paper     

Bayesian Nonmetric Successive Categories Multidimensional Scaling

A Bayesian nonmetric successive categories multidimensional scaling (MDS) method is proposed. The proposed method can be seen as a Bayesian alternative to the maximum likelihood multidimensional successive scaling method proposed by Takane (1981), or as a nonmetric extension of Bayesian metric MDS by Oh and Raftery (2001). The model has a graded-response type measurement model part and a latent metric MDS part. All the parameters are jointly estimated using a Markov chain Monte Carlo (MCMC) estimation technique. Moreover, WinBUGS/OpenBUGS code for the proposed methodology is also given to aid applied researchers. The proposed method is illustrated through the analysis of empirical two-mode three-way similarity data.

     

基于相似性的轴类零件CAPP系统研究

介绍了基于相似性的轴类零件CAPP系统的框架结构,建立了面向对象的零件几何、工艺特征信息描述、索引方法以及实例的相似匹配策略,解决了复杂层次结构的实例表示和具有异构实例之间相似检索的计算,建立了基于特征相似匹配原理生成零件的加工工艺的新方法.     

Asymptotically optimum detection of primary user in cognitive radio networks

Traditionally, the frequency spectrum is licensed to users by government agencies in a fixed manner where the licensee has exclusive right to access the allocated band. However, with increasing demand for the spectrum and scarcity of vacant bands, a spectrum policy reform seems inevitable. Meanwhile, recent measurements suggest the possibility of sharing spectrum among different parties subject to interference-protection constraints. In order to enable access to an unused licensed spectrum, a secondary user has to monitor licensed bands and opportunistically transmit whenever no primary signal is detected. Spectrum-sharing between a primary licensee and a group of secondary users has been studied. The structure of an asymptotically optimum detector based on the measurements of all secondary users is derived and the effect of the quantisation error in such a system is evaluated. Also, it is shown that by using the proposed detector in a sequential detection structure, it is possible to shorten the decision time needed by the detector. The results show the superiority of the proposed detector to other schemes.     

An inheritance complexity metric for object-oriented code: A cognitive approach

Software metrics should be used in order to improve the productivity and quality of software, because they provide critical information about reliability and maintainability of the system. In this paper, we propose a cognitive complexity metric for evaluating design of object-oriented (OO) code. The proposed metric is based on an important feature of the OO systems: Inheritance. It calculates the complexity at method level considering internal structure of methods, and also considers inheritance to calculate the complexity of class hierarchies. The proposed metric is validated both theoretically and empirically. For theoretical validation, principles of measurement theory are applied since the measurement theory has been proposed and extensively used in the literature as a means to evaluate the software engineering metrics. We applied our metric on a real project for empirical validation and compared it with Chidamber and Kemerer (CK) metrics suite. The theoretical, practical and empirical validations and the comparative study prove the robustness of the measure.     

Reduction of optical beat interference using gain-saturated RSOA in upstream WDM/SCM optical links

A new scheme for reducing optical beat interference (OBI) noise in optical network units is proposed for subcarrier multiplexing-based access network applications. The optical spectrum of the transmit lasers is broadened by using a radio frequency (RF) clipping tone with a modulation depth greater than one. This reduces the impact of the OBI noise. The distortions caused by an RF clipping tone are also suppressed by introducing a gain-saturated reflective optical amplifier, which shows the characteristics of high-pass filter. The proposed scheme has been verified by measuring the error vector magnitude of 16QAM signal with 20 Mbps. Error-free transmission has been achieved even when the light of OBI-noise-causing lasers is stronger than that of the signal laser by 7 dB     

Validation of reliability computational models using Bayes networks

This paper proposes a methodology based on Bayesian statistics to assess the validity of reliability computational models when full-scale testing is not possible. Sub-module validation results are used to derive a validation measure for the overall reliability estimate. Bayes networks are used for the propagation and updating of validation information from the sub-modules to the overall model prediction. The methodology includes uncertainty in the experimental measurement, and the posterior and prior distributions of the model output are used to compute a validation metric based on Bayesian hypothesis testing. Validation of a reliability prediction model for an engine blade under high-cycle fatigue is illustrated using the proposed methodology.     

Statistical Control of a Six Sigma Process

Six Sigma as a methodology for quality improvement is often presented and deployed in terms of the dpmo metric, i.e., defects per million opportunities. As the sigma level of a process improves beyond three, practical interpretation problems could arise when conventional Shewhart control charts are applied during the Control phase of the define-measure-analyze-improve-control framework. In this article, some alternative techniques are described for the monitoring and control of a process that has been successfully improved; the techniques are particularly useful to Six Sigma Black Belts in dealing with high-quality processes. The approach used would thus ensure a smooth transition from a low-sigma process management to maintenance of a high-sigma performance in the closing phase of a Six Sigma project.     

Predicting response spectra for earthquake signals generated as filtered noise

Generating families of earthquake signals which in mean fulfill a given response spectrum can be done by filtering white noise through a linear filter and multiplying the filtered signal with a time-window function. To design the filters, the response spectrum of the filtered white noise sequences must be predicted. In the past years several methods for doing this have been suggested.In this article, we have modified some of these methods and also proposed a new method. We have compared the methods by doing simulations. It was found that the proposed method was useful for predicting response spectra of signals with slow decaying time-window functions. A further benefit of the proposed method is that it could be used for predicting response spectra with time varying frequency content.