Sharif Digital Repository

Thermal expansion and hot deformation are two phenomena causing dimensional errors in investment casting. This error occurs in dimensions between the die and wax pattern. Therefore, the wax's thermo-physical and thermo-mechanical properties, the metal die features, and the process parameters affect the dimensions of the wax pattern. Some important effective process parameters are the injection temperature, die temperature, and holding time. In this paper, the effect of injection parameters on the dimensional accuracy of the wax model created by a metallic die is studied. The Taguchi formulation based on the design of experiments is applied to obtain the optimum condition in achieving the... 

Brain Computer Interfaces (BCI) are an important concept of biomedical engineering because of their ability to improve life conditions for people with different disabilities. Lots of studies have worked on important characteristics of BCI systems, such as speed and accuracy, whereas price is an important aspect too. Thus, a low cost BCI system with high accuracy clearly can help more people. Our purpose in this study is to design a P300 based BCI system using a low-priced EEG headset which has an acceptable accuracy. Our final design got a mean real-time accuracy of 93.3% which is comparable to systems with much more expensive hardware. © 2019 IEEE  

Scattering of a Gaussian beam by a spherical dielectric object is studied using the vectorial Gaussian beam tracing method. Expansion to a few Gaussian beams with the smaller waists has been used to extend the method to a more generalized one. This method can be applied to a large variety of different shape objects and incident beam profiles. Numerical results of this computationally fast method show a good agreement with the results represented in the literature. © 2004 IEEE  

Thermal neutron analysis (TNA) technology has been used for the non-destructive detection of explosives. The system uses a relatively weak 252Cf neutron source (1.03.107 n/s) and two 3″3×″ NaI(Tl) detectors. The presence of explosives is confirmed via detection of the 10.83 MeV prompt gamma-ray associated with nitrogen decay. The MCNP4A code was used to simulate the neutron and gamma transport through the system. The thermal neutron flux in the activation position was measured using gold and indium foils. The measured thermal neutron flux was lower, by not more than 9.5%, than that of simulation. In this report the results of the preliminary tests on the system are described  

Cone penetration tests have long been used to characterize snowpack stratigraphy. With the development of sophisticated digital penetrometers such as the SnowMicroPen, vertical profiles of snow hardness can now be measured at a spatial resolution of a few micrometers. By using small penetrometer tips at this high vertical resolution, further details of the penetration process are resolved, leading to many more stochastic signals. An accurate interpretation of these signals regarding snow characteristics requires advanced data analysis. Here, the failure of ice connections and the pushing aside of separated snow grains during cone penetration lead to a combination of (a) diffusive noise, as... 

We present an attempt to improve the performance of multi-class image segmentation systems based on a multilevel description of segments. The multi-class image segmentation system used in this paper marks the segments in an image, describes the segments via multilevel feature vectors and passes the vectors to a multi-class object classifier. The focus of this paper is on the segment description section. We first propose a robust, scale-invariant texture feature set, named directional differences (DDs). This feature is designed by investigating the flaws of conventional texture features. The advantages of DDs are justified both analytically and experimentally. We have conducted several... 

The trend of gold price in the market is the most important consideration for the investors of the gold, and serves as the basis of gaining profit, so there are scholars who try to forecast the gold price. Forecasting accuracy is one of the most important factors involved in selecting a forecasting method. Besides, nowadays artificial intelligence (AI) techniques are becoming more and more widespread because of their accuracy, symbolic reasoning, flexibility and explanation capabilities. Among these techniques, particle swarm optimization (PSO) is one of the best AI techniques for optimization and parameter estimation. In this study a PSO-based time series model for the gold price... 

This paper deals with the application of Fast Fourier Transform Base Method (FFTBM) with signal mirroring (FFTBM-SM) to assess accuracy of MELCOR code. This provides deeper insights into how the accuracy of MELCOR code in predictions of thermal-hydraulic parameters varies during transients. The case studied was modeling of Station Black-Out (SBO) accident in PSB-VVER integral test facility by MELCOR code. The accuracy of this thermal-hydraulic modeling was previously quantified using original FFTBM in a few number of time-intervals, based on phenomenological windows of SBO accident. Accuracy indices calculated by original FFTBM in a series of time-intervals unreasonably fluctuate when the... 

Normal human breathing exhibits complex variability in both respiratory rhythm and volume. Analyzing such nonlinear fluctuations may provide clinically relevant information in patients with complex illnesses such as asthma. We compared the cycle-by-cycle fluctuations of inter-breath interval (IBI) and lung volume (LV) among healthy volunteers and patients with various types of asthma. Continuous respiratory datasets were collected from forty agematched men including 10 healthy volunteers, 10 patients with controlled atopic asthma, 10 patients with uncontrolled atopic asthma, and 10 patients with uncontrolled non-atopic asthma during 60 min spontaneous breathing. Complexity of breathing... 

In this paper, the design of an adaptive tracking control for a class of switched uncertain multiple-input–multiple-output nonlinear systems in the strict-feedback form with unmodeled dynamics in the presence of three types of input nonlinearity under arbitrary switching has been addressed. By means of an intelligent approximator like a fuzzy logic system or a neural network, the unknown dynamics are estimated. The unmodeled dynamics have been tackled with a dynamic signal. A universal framework for describing different types of input nonlinearity including saturation, backlash, and dead zone has been utilized. By applying the backstepping approach and the common Lyapunov function method,... 

Fingerprint is widely used in identification and verification systems. In this paper, we present a novel feature extraction method based on Gabor filter and Recursive Fisher Linear Discriminate (RFLD) algorithm, which is used for fingerprint identification. Our proposed method is assessed on images from the biolab database. Experimental results show that applying RFLD to a Gabor filter in four orientations, in comparison with Gabor filter and PCA transform, increases the identification accuracy from 85.2% to 95.2% by nearest cluster center point classifier with Leave-One-Out method. Also, it has shown that applying RFLD to a Gabor filter in four orientations, in comparison with Gabor filter... 

In the application of parallel robots, it is necessary to calibrate the geometric parameters and improve the positioning accuracy for accurate task performance. Traditionally, to perform system calibration, one needs to measure a number of robot poses using an external measuring device. However, this process is often time-consuming, expensive and difficult for robot on-line calibration. In this paper, a methodical way of self-calibrating of Hexaglide parallel robot is introduced. This method is performable only by measuring input joint variables in some sets of configurations where in each set center of the end-effector is fixed, but orientations are different. Simulations give us an idea... 

Because of errors in the geometric parameters of the parallel robots, it is necessary to calibrate them to improve the positioning accuracy for accurate task performance. Traditionally, to perform system calibration, one needs to measure a number of robot poses using an external measuring device. However, this process is often time-consuming, expensive and difficult for robot on-line calibration. In this paper, a methodical way of self-calibrating of Hexaglide parallel robot is introduced. This method is performable only by measuring input joint variables and errors of positioning relative to the desired position in some sets of configurations where in each set the desired position is fixed,... 

Crash forecasting enables safety planners to take appropriate actions before casualty or loss occurs. Identifying and analyzing the attributes influencing forecasting accuracy is of great importance in road crash forecasting. This study aims to model the forecasting accuracy of 31 provinces using their macroeconomic variables and road traffic indicators. Iran's road crashes throughout 2011–2018 are calibrated and cross-validated using the Holt-Winters (HW) forecasting method. The sensitivity of crash forecast reliability is studied by a regression model. The results suggested that the root mean square error (RMSE) of crash prediction increased among the provinces with higher and more variant... 

The aim of a brain-computer interface (BCI) system is to establish a new communication system that translates human intentions, reflected by measures of brain signals such as magnetoencephalogram (MEG), into a control signal for an output device. In this paper, an algorithm is proposed for discriminating MEG signals, which were recorded during hand movements in four directions. These signals were presented as data set 3 of BCI competition IV. The proposed algorithm has four main stages: pre-processing, primary feature extraction, the selection of efficient features, and classification. The classification stage was a combination of linear SVM and linear discriminant analysis classifiers. The... 

There is a growing attention in subspace learning using tensor-based approaches in high dimensional spaces. In this paper we first indicate that these methods suffer from the Heteroscedastic problem and then propose a new approach called Heteroscedastic Multilinear Discriminant Analysis (HMDA). Our method can solve this problem by utilizing the pairwise chernoff distance between every pair of clusters with the same index in different classes. We also show that our method is a general form of Multilinear Discriminant Analysis (MDA) approach. Experimental results on CMU-PIE, AR and AT&T face databases demonstrate that the proposed method always perform better than MDA in term of classification... 

Robotic reduction of long bones is associated with the need for considerable force and high precision. To balance the accuracy, payload, and workspace, we have designed a new six degrees-offreedom three-legged wide-open robotic system for long-bone fracture reduction. Thanks to the low number of legs and their nonsymmetrical configuration, the mechanism enjoys a unique architecture with a frontally open half-plane. This facilitates positioning the leg inside the mechanism and provides a large workspace for surgical maneuvers, as shown and compared to the well-known Gough-Stewart platform. The experimental tests on a phantom reveal that the mechanism is well capable of applying the desired... 

This paper has presented a novel discriminative parameters calibration approach based on the Model Distance Maximizing (MDM) to improve the performance of our previous proposed robustness method named spectral subtraction (SS) in likelihoodmaximizing framework. In the previous work, for adjusting the spectral over-subtraction factor of SS, conventional ML approach is used that only utilizes the true model without considering other confused models. This makes it very probably to reach a suboptimal solution. While in MDM, by maximizing the dissimilarities among models, the performance of our speech recognizer-based spectral subtraction method could be further improved. Experimental results... 

This paper gives the results of simulation and experimental investigation on the effects of random signals on the accuracy of micro-stepping control positioning. For studying and simulation of the effect of random noise signals on performance of the accurate position control systems, such as Hybrid Stepper Motors (HSMs), a micro-step driver and controlling unit using PID controller has been designed and constructed. Several parametric studies have been carried out including different white noise power and micro-step per revolution. Tracking problem for a HSM model has been simulated, and the experimental study for similar cases has been carried out by implementing the designed controller in...