Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used

     Cloth simulation and animation has been the topic of research since the mid-80's in the field of computer graphics. Enforcing incompressible is very important in real time simulation. Although, there are great achievements in this regard, it still suffers from unnecessary time consumption in certain steps that is common in real time applications.   This research develops a real-time cloth simulator for a virtual human character (VHC) with wearable clothing. This research achieves success in cloth simulation on the VHC through enhancing the position-based dynamics (PBD) framework by computing a series of positional constraints which implement constant densities. Also, the self-collision and collision wit

This project sought to fabricate a flexible gas sensor based on a short functionalized multi-walled carbon nanotubes (f-MWCNTs) network for nitrogen dioxide gas detection. The network was prepared by filtration from the suspension (FFS) method and modified by coating with a layer of polypyrrole conductive polymer (PPy) prepared by the oxidative chemical polymerization to improve the properties of the network. The structural, optical, and morphological properties of the f-MWCNTs and f-MWCNTs/PPy network were studied using X-ray diffraction (XRD), Fourie-transform infrared (FTIR), with an AFM (atomic force microscopy). XRD proved that the structure of f-MWCNTs is unaffected by the synthesis procedure. The FTIR spectra verified the existence o

The background subtraction is a leading technique adopted for detecting the moving objects in video surveillance systems. Various background subtraction models have been applied to tackle different challenges in many surveillance environments. In this paper, we propose a model of pixel-based color-histogram and Fuzzy C-means (FCM) to obtain the background model using cosine similarity (CS) to measure the closeness between the current pixel and the background model and eventually determine the background and foreground pixel according to a tuned threshold. The performance of this model is benchmarked on CDnet2014 dynamic scenes dataset using statistical metrics. The results show a better performance against the state-of the art

Bootstrap is one of an important re-sampling technique which has given the attention of  researches recently. The presence of outliers in the original data set may cause serious problem to the classical bootstrap when the percentage of outliers are higher than the original one. Many methods are proposed to overcome this problem such  Dynamic Robust Bootstrap for LTS (DRBLTS) and Weighted Bootstrap with Probability (WBP). This paper try to show the accuracy of parameters estimation by comparison the results of both methods. The bias , MSE and RMSE are considered. The criterion of the accuracy is based on the RMSE value since the method that provide us RMSE value smaller than other is con

Background: Sprite coding is a very effective technique for clarifying the background video object. The sprite generation is an open issue because of the foreground objects which prevent the precision of camera motion estimation and blurs the created sprite. Objective: In this paper, a quick and basic static method for sprite area detection in video data is presented. Two statistical methods are applied; the mean and standard deviation of every pixel (over all group of video frame) to determine whether the pixel is a piece of the selected static sprite range or not. A binary map array is built for demonstrating the allocated sprite (as 1) while the non-sprite (as 0) pixels valued. Likewise, holes and gaps filling strategy was utilized to re

The undetected error probability is an important measure to assess the communication reliability provided by any error coding scheme. Two error coding schemes namely, Joint crosstalk avoidance and Triple Error Correction (JTEC) and JTEC with Simultaneous Quadruple Error Detection (JTEC-SQED), provide both crosstalk reduction and multi-bit error correction/detection features. The available undetected error probability model yields an upper bound value which does not give accurate estimation on the reliability provided. This paper presents an improved mathematical model to estimate the undetected error probability of these two joint coding schemes. According to the decoding algorithm the errors are classified into patterns and their decoding