Sharif Digital Repository

Functional quality in the mechanical products is governed mainly by the degree of satisfaction of the design requirements, which itself depends on the variations in the effective variables. The functional parameters cannot be easily measured in mass production, and thus, are not usually considered as a direct inspection objective. Process capability indices are useful tools for evaluating the ability of a process to produce the dependent variables of a product that meet certain specifications. In this paper, the conventional process capability concept is extended to develop a computational tool for analysis of the functional quality of a mechanical product. Through defining new proper... 

Corner-case analysis is a well-known technique to cope with occasional deviations occurring during the manufacturing process of semiconductors. However, the increasing amount of process variation in nanometer technologies has made it inevitable to move toward statistical analysis methods, instead of deterministic worst-case-based techniques, at all design levels. We show that by statically considering statistical effects of random and systematic process variation on performance and power consumption of a Multiprocessor System-on-Chip (MPSoC), significant power improvement can be achieved by static software-level optimizations such as task and communication scheduling. Moreover, we analyze... 

Shape analysis plays an important role in many medical imaging studies. One of the recent shape analysis methods uses the Laplace Beltrami eigenvalues which is also used in this paper for global shape comparison of hippocampus of normal subjects and epileptic patients. Popularity of the Laplace Beltrami operator in this field is due to its isometry-invariance which avoids pre-processing steps like mapping, registration, and alignment. In addition, it is capable of revealing fine details in shapes that makes this method a good choice for deformation detecting purposes like epilepsy diagnosis. To examine capability of the proposed method, statistical analysis and two ways of classification,... 

Experiments are performed to evaluate the impact of trip wires on the turbulence intensity in a few low speed wind tunnels. Trip wires of different sizes are installed at different positions in the contraction section of four different wind tunnels and measurements are made at various free stream velocities. The results indicate that the pressure distributions are altered compared to the clean condition. Trip wires move the adverse pressure gradient toward the inlet of the contraction section. Consequently, the turbulence intensity in the test section of the wind tunnels is reduced and the flow uniformity is improved considerably. Frequency and statistical analysis are performed and the... 

Several methods have been proposed to construct Statistical Shape Model (SSM) to aim image analysis using computer in field Computer Aided Diagnosis (CAD), Computer Assisted Surgery (CAS), and other medical applications by providing a prior knowledge. The major challenge for liver shape model is a high variation in geometry such as size, shape and volume between livers. In this paper, we have presented a new technique for the automatic Multi-Scale Statistical Shape Model (MS-SSM) of three-dimensional (3-D) liver from volumetric segmented images data. The procedure included both building of Spherical Harmonics shape description and the Wavelet transform. Principal Component Analysis (PCA) was... 

We present an image steganographic technique to preserve the first-order and the second-order statistics of the host image. Experimental results show that the proposed method can preserve the image quality and also resists typical statistical analysis based attacks. The new steganography method solves the distortion problem with the HKC algorithm and hence thwarts the Kuo attack. The method is based on the idea of histogram shift, in which two empty bins are produced in the image histogram that are then filled up using their neighboring bins through the embedding process. © 2009 IEEE  

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... 

We describe a method for analyzing the stochasticity in non-stationary data for the beat-to-beat fluctuations in the heart rates of healthy subjects, as well as those with congestive heart failure. The method analyzes the return time series of the data as a Markov process, and computes the Markov time scale, i.e., the time scale over which the data are a Markov process. We also construct an effective stochastic continuum equation for the return series. We show that the drift and diffusion coefficients, as well as the amplitude of the return time series for healthy subjects are distinct from those with CHF. Thus, the method may potentially provide a diagnostic tool for distinguishing healthy... 

The present study was designed to search for metabolic biomarkers and their correlation with serum zinc in Crohn's disease patients. Crohn's disease (CD) is a form of inflammatory bowel disease that may affect any part of the gastrointestinal tract and can be difficult to diagnose using the clinical tests. Thus, introduction of a novel diagnostic method would be a major step towards CD treatment.Proton nuclear magnetic resonance spectroscopy ( 1H NMR) was employed for metabolic profiling to find out which metabolites in the serum have meaningful significance in the diagnosis of CD. CD and healthy subjects were correctly classified using random forest methodology. The classification model for... 

Paenibacillus polymyxa ATCC 21830 was used for the production of curdlan gum for first time. A Box-Behnken experimental design was applied to optimize six variables of batch fermentation culture each at three levels. Statistical analyses were employed to investigate the direct and interactive effects of variables on curdlan production. Optimum cultural conditions were temperature (50. °C), pH (7), fermentation time (96. h), glucose (100. g/L), yeast extract (3. g/L) and agitation speed (150. rpm). The yield of curdlan production was 6.89. g/L at optimum condition medium. Response surface methodology (RSM) and artificial neural network (ANN) were used to model cultural conditions of curdlan... 

This study presents a novel method for fault location of transmission lines by multiple fault current measurements. In contrast to conventional methods, it is proposed to utilise several current measurements, which may be far from the faulted line. The circuit equations of the network are used to express each fault current as a function of fault location. Fault location is then estimated using a least-squares estimation technique. To achieve a robust estimation of fault location, statistical hypotheses-testing is employed for identifying erroneous measurements. The method is applicable to both synchronised and unsynchronised measurements. Moreover, fault location can be estimated regardless... 

Smoking is known as a major cause of chronic obstructive pulmonary disease (COPD) and hence immediate and effective interventions are required for its elimination. This study aimed to collect valid data with regard to cigarette smoking in adult population of north of Iran for policy making by a meta-analysis of the documents of national non-communicable disease risk factors surveillance system. We investigated relevant evidences by searching in published and non-electronic databases. Data were extracted based on variables such as year of the study, sex, age group and prevalence of smoking habit. Based on results of heterogeneity, we applied fixed or random effects model to estimate the... 

A combination of peak alignment methods and multivariate curve resolution (MCR) is proposed for handling retention time shifts and modeling of comprehensive two-dimensional gas chromatographic (GC × GC) data in the case of univariate detection systems such as in flame ionization detection (FID) or in total ion current mass spectrometry (TIC-MS) detection. A new bilinear peak alignment (BPA) method, based on MCR, is first proposed to correct for progressive within run retention time shifts in GC × GC due to temperature programming effects on second chromatographic dimension. The performance of the proposed peak alignment method is compared to that of the correlation optimized warping (COW)... 

In this work, a novel smartphone application entitled ". MVC app" is developed to perform different multivariate calibration methods. This app is designed for chemists who are not expert in programming or in advanced statistics. The developed application can use any Android-powered device as an environment for running. It is an easy to use app which can simply install in your smartphone and play. Different multivariate calibration methods, such as multiple linear regression (MLR), principal component regression (PCR) and partial least squares (PLS) are included in this app. As an instance, for performing PLS modeling, first calibration and validation data sets are imported (via USB or... 

Abstract A system designer needs to estimate the behavior of a system interconnection based on different patterns of switching which happen around an interconnect. Two different scenarios are supposed to estimate the effect of interconnect issues on system performance. First, based on a normalization technique for decreasing the number of a transfer function variables, a definitive environment for one interconnect is considered and an optimized look-up-table for the wire time delay is generated. Using some sampling methods, fast accessible look-up-tables are proposed for CAD tools in very simple and small one. A 4×4×4 table for the wire delay is introduced which results in very fast... 

Increasing delay and power variation has become a major challenge to designing high performance Multiprocessor System-On-Chips (MPSoC) in deep sub-micron technologies. As a result, a paradigm shift from deterministic to statistical design methodology at all levels of the design hierarchy is inevitable. In this paper, we propose a static variation-aware task scheduling and power mode selection algorithm for MPSoCs. The proposed algorithm is able to maximize the total power yield of the chip under a given performance yield constraint by searching for the optimal task scheduling and power mode selection policy for a specified multiprocessor platform. Experimental results are gathered by...