Sharif Digital Repository

Electroweak production of the top quark is measured for the first time in pp collisions at √s=7TeV, using a data set collected with the CMS detector at the LHC and corresponding to an integrated luminosity of 36pb-1. With an event selection optimized for t-channel production, two complementary analyses are performed. The first one exploits the special angular properties of the signal, together with background estimates from the data. The second approach uses a multivariate analysis technique to probe the compatibility with signal topology expected from electroweak top-quark production. The combined measurement of the cross section is 83.6±29.8(stat+syst)±3.3(lumi) pb, consistent with the... 

In this article the methodology proposed by Li and Wang for mixed qualitative and quantitative modeling and simulation of temporal behavior of processing unit is reexamined and extended to more complex case. The main issue of their approach considers the multivariate statistics of principal component analysis (PCA), along with clustered fuzzy digraphs and reasoning. The PCA and fuzzy clustering provide tools to categorize the quantitative dynamic trends, describing the temporal behavior of joint human-process interactions qualitatively, and through the proposed neuro-fuzzy reasoning the system responses can be obtained when the system is exposed to uncertain disturbances. First, the method... 

Spinal load models have become an increasingly valuable tool for the evaluation of the stress placed on the spine. In order to get an accurate representation of these spinal loads, they must be compared to known tolerance values. Bone mineral content and density of the lumbar spine of 23 males and 21 females was measured using a dual energy x-ray absorptiometry. Compression tolerance values were predicted by previously published studies based upon bone mineral levels. Anthropometric measurements were recorded and related to the compression tolerance values through the use of multivariate linear regression techniques. Compression tolerance values based on the bone mineral content or density... 

Since the product quality of many industrial processes depends upon more than one dependent variable or attribute, they are either multivariate or multi-attribute in nature. Although multivariate statistical process control is receiving increased attention in the literature, little work has been done to deal with multi-attribute processes. In this article, we develop a new methodology to monitor multi-attribute processes. To do this, first we transform multi-attribute data in a way that their marginal probability distributions have almost zero skewness. Then, we estimate the transformed covariance matrix and apply the well-known T2 control chart. In order to illustrate the proposed method... 

In the real world, there are complex decision-making problems in which a variety of intertwined factors and hierarchical structures exist, and it is difficult or impossible to solve these problems using classical methods. The prioritization of circular economy (CE) adoption barriers is one such complex problem that cannot be solved using current classical methods. Hence, in this paper, for the first time, a new method, namely, FBWDS, is developed. FBWDS derives from the combination of fuzzy best–worst method (BWM), fuzzy decision-making trial and evaluation laboratory (DEMATEL), and Supermatrix structure. This proposed method establishes weights of the intertwined factors in hierarchical... 

This paper presents a study of the Taguchi design method to optimise the rate of electrophoretic deposition (EPD) of Bioglass® particles from aqueous suspensions. The effect of Bioglass® concentration, pH and electric field was investigated. An orthogonal array of L16 type with mixed levels of the control factors was utilized. Multivariate analysis of variance (MANOVA) and regression analysis based on the partial least-square method were used to identify the significant factors affecting the deposition rate and its stability during constant-voltage EPD. It was found that the pH of the suspension significantly influences the deposition rate whereas the applied electric field has the smallest... 

Representational similarity analysis (RSA) summarizes activity patterns for a set of experimental conditions into a matrix composed of pairwise comparisons between activity patterns. Two examples of such matrices are the condition-by-condition inner product and correlation matrix. These representational matrices reside on the manifold of positive semidefinite matrices, called the Riemannian manifold. We hypothesize that representational similarities would be more accurately quantified by considering the underlying manifold of the representational matrices. Thus, we introduce the distance on the Riemannian manifold as a metric for comparing representations. Analyzing simulated and real fMRI... 

Objective: Spine kinematics, kinetics, and trunk muscle activities were evaluated during different stages of a fatigue-induced symmetric lifting task over time. Background: Due to neuromuscular adaptations, postural behaviors of workers during lifting tasks are affected by fatigue. Comprehensive aspects of these adaptations remain to be investigated. Method: Eighteen volunteers repeatedly lifted a box until perceived exhaustion. Body center of mass (CoM), trunk and box kinematics, and feet center of pressure (CoP) were estimated by a motion capture system and force-plate. Electromyographic (EMG) signals of trunk/abdominal muscles were assessed using linear and nonlinear approaches. The L5-S1... 

In this paper, a heuristic threshold policy is developed to detect and classify the states of a multivariate quality control system. In this approach, a probability measure called belief is first assigned to the quality characteristics and then the posterior belief of out-of-control characteristics is updated by taking new observations and using a Bayesian rule. If the posterior belief is more than a decision threshold, called minimum acceptable belief determined using a heuristic threshold policy, then the corresponding quality characteristic is classified out-of-control. Besides using a different approach, the main difference between the current research and previous works is that the... 

A new approach is developed in this paper to detect general mean shifts of multivariate quality control systems and to determine the quality characteristic(s) responsible for the shift. This approach takes advantage of both a decomposition method and an EWMA-based control statistics that are employed for multivariate normal distributions. In order to evaluate the performance of the proposed methodology, simulation studies are provided to estimate the in- and out-of-control average run lengths under different mean and variance shift scenarios. Simulation experiments are also given to compare the performances of the proposed procedure with the ones of the well-known MEWMA and MCUSUM methods.... 

Temporal synchronization of neuronal activity plays an important role in various brain functions such as binding, cognition, information processing, and computation. Patients suffering from disorders such as Alzheimer’s disease or schizophrenia show abnormality in the synchronization patterns. Electroencephalography (EEG) is a cheap, non-invasive, and easy-to-use method with fine temporal resolution. Modern multichannel EEG data are increasingly being used in brain studies. Traditional approaches for identifying synchronous activity in EEG are through univariate techniques such as power spectral density or bivariate techniques such as coherence. In this paper, we review two methods for... 

Enterprise Resource Planning systems (ERP) play a significant role in the management of businesses processes. Determining the influential factors that are positioned behind a successful ERP implementation is critical to gain the most value-added from competitive potentials of such systems. The driver of current research is to gain a deeper understanding of the various subjective criteria to measure ERP implementation success with the aim of enhancing the chance success through investigating ERP implementation performance indicators. By exploring the international literature, a comprehensive list of potential success factors of ERP systems is identified which are complementary and critical to... 

Control charts are the best tools to monitor main process parameters, and the Multivariate Exponentially Weighted Moving Average, MEWMA, type of this tool is used when there are several correlated quality characteristics to be monitored simultaneously where detecting small deviations of the characteristics is desired. In this paper, the models of both the economic and the economic-statistical design problems of MEWMA control charts are solved by a Particle Swarm Optimization (PSO) approach. The comparison study between the economic and the economic-statistical designs shows better statistical performances of the economic-statistical design with negligible increase in cost. Furthermore, in... 

Independent Component Analysis (ICA) can be used to decompose functional Magnetic Resonance Imaging (fMRI) data into a set of statistically independent images which are likely to be the sources of fMRI data. After applying ICA, a set of independent components are produced, and then, a "meaningful" subset from these components must be identified, because a large majority of components are non-interesting. So, interpreting the components is an important and also difficult task. In this paper, we propose a criterion based on the entropy of time courses to automatically select the components of interest. This method does not require to know the stimulus pattern of the experiment  

This paper describes an attempt to shed some light on road safety in Asia Pacific region by characterizing and assessing its road accidents. The relevant national road accident data were extracted from centralized data sources of international agencies. Due to data incompleteness and missing values, 21 Asia Pacific countries, presenting more than half of the world's population, were selected for detailed analysis. The study database consisted of 7 variables, covering years 1980 and 1995. The univariate and multivariate statistical analyses for the selected countries showed interesting results and relations for the selected variables. Accident rates, reflecting road accident risk and... 

A new methodology is proposed in this paper to both monitor an overall mean shift and classify the states of a multivariate quality control system. Based on the Bayesian rule (Montgomery, Introduction to statistical quality control, 5th edn. Wiley, New York, USA, 2005), the belief that each quality characteristic is in an out-of-control state is first updated in an iterative approach and the proof of its convergence is given. Next, the decision-making process of the detection and classification the process mean shift is modeled. Numerical examples by simulation are provided in order to understand the proposed methodology and to evaluate its performance. Moreover, the in-control and... 

Teratozoospermia is one of conditions that can cause male infertility. The mechanism of teratozoospermia remains unclear. The knowledge of the metabolites in human seminal plasma (HSP) is meaningful for the pathological study of teratozoospermia. Analysis of changed metabolites in HSP can help understand the cellular mechanism, find the novel biomarkers and subsequently design a diagnosis test. In this study, the analysis of samples performed by proton nuclear magnetic resonance spectroscopy (1H NMR spectroscopy) to identify the various metabolites, with the aim of finding metabolic profiles and biomarkers related to male infertility. Eighteen de-regulated metabolites were identified in... 

In a production process, when the quality of a product depends on more than one characteristic, multivariate quality control techniques are used. Although multivariate statistical process control is receiving increased attention in the literature, little work has been done to deal with multi-attribute processes. In this paper, a new methodology has been developed to monitor multi-attribute processes, in which the defect counts are important and different types of defect are dependent random variables. In order to do this, based on the symmetric square root transformation concept, first, multi-attribute data is transformed, such that the correlation between variables either vanishes or... 

Incomplete self-similarity (ISS) concept is employed to develop the equations from existing experimental results of flow over an oblique rectangular sharp-crested weir for both free and submerged flow. The stage-discharge relationship is obtained by theoretical analysis, based on the application of the dimensional analysis and the ISS theory. For analysis, the relations were found by trial and error procedure using the SPSS mathematical computer program that estimates the relation among multi-variable functions. Thus, equations to estimate the flow characteristics for both free and submerged flow are proposed. The results show a better compatibility with the experimental data than the... 

Various control charts have been proposed to monitor generalized linear pro les in Phase II. However, the robustness of the proposed methods in detecting di erent types and especially di erent directions of changes is not well-studied in the literature. In real-world applications, di erent kinds of change such as drift and multiple changes are likely to occur, which can be isotonic (increasing) or antitonic (decreasing). This paper studies the robustness of the Rao Score Test (RST) method, T2, and Multivariate Exponential Weighted Moving Average (MEWMA) in di erent types, drift and multiple, and directions of changes. The RST method also bene ts from a change-point detection approach whose...