Estimating multivariate location and scatter with both affine equivariance and positive break down has always been difficult. Awell-known estimator which satisfies both properties is the Minimum volume Ellipsoid Estimator (MVE) Computing the exact (MVE) is often not feasible, so one usually resorts to an approximate Algorithm. In the regression setup, algorithm for positive-break down estimators like Least Median of squares typically recomputed the intercept at each step, to improve the result. This approach is called intercept adjustment. In this paper we show that a similar technique, called location adjustment, Can be applied to the (MVE). For this purpose we use the Minimum Volume Ball (MVB). In order to lower the (MVE) objective function. An exact algorithm for calculating the (MVB) is presented. As an alternative to (MVB) location adjustment we propose () location adjustment, which does not necessarily lower the (MVE) objective function but yields more efficient estimates for the location part. Simulations Compare the two type of location adjustment.
In data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum me
Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security
... Show MoreWith the advent of the globalization, the rapid development in technology and the intensity of competition companies attemptto maintain competition advantages and retain customers. The traditional methods in managerial accounting become irrelevance to achieve the objectives of these companies especially with the rapid changes in modern manufacturing environment .Thus there is a need to new tools in accounting such as lean accounting, which is considered as a costing method that support creating value for the customer by costing the entire value stream, eliminating waste in the accounting process, reduced lead time, improved quality, lowered time delivery and increased available capacity. Using value stream focuses not only on the waste&n
... Show MoreThe objective of this work is to study the influence of end milling cutting process parameters, tool material and geometry on multi-response outputs for 4032 Al-alloy. This can be done by proposing an approach that combines Taguchi method with grey relational analysis. Three cutting parameters have been selected (spindle speed, feed rate and cut depth) with three levels for each parameter. Three tools with different materials and geometry have been also used to design the experimental tests and runs based on matrix L9. The end milling process with several output characteristics is solved using a grey relational analysis. The results of analysis of variance (ANOVA) showed that the major influencing parameters on multi-objective response w
... Show MoreThe main aim of this paper is to study how the different estimators of the two unknown parameters (shape and scale parameter) of a generalized exponential distribution behave for different sample sizes and for different parameter values. In particular,
. Maximum Likelihood, Percentile and Ordinary Least Square estimators had been implemented for different sample sizes (small, medium, and large) and assumed several contrasts initial values for the two parameters. Two indicators of performance Mean Square Error and Mean Percentile Error were used and the comparisons were carried out between different methods of estimation by using monte carlo simulation technique .. It was obse
... Show MoreMammals are under threat worldwide due to deforestation, hunting, and other human activities. In Iraq, a total of 93 species of wild mammals have been recorded including species with global conservation concern. Bamo Mountain is situated within the Zagros Mountains in northern Iraq which is a suitable habitat for wild mammals. Due to scarcity of the field survey efforts and cryptic behavior, monitoring of the wild mammals fauna in Zagros Mountain seems challenging. Therefore, we used a camera trap which seems to be an ideal way to determine species diversity of wild mammals in Bamo Mountain. Moreover, interviews with local villagers were performed. The mammalian diversity of Bamo Mountain is not fully explored but seemed threatened by lo
... Show MoreA simple, accurate, and cost-efficient UV-Visible spectrophotometric method has been developed for the determination of naphazoline nitrate (NPZ) in pure and pharmaceutical formulations. The suggested method was based on the nucleophilic substitution reaction of NPZ with 1,2-naphthoquinone-4-sulfonate sodium salt in alkaline medium at 80°C to form an orange/red-colored product of maximum absorption (λmax) at 483 nm. The stoichiometry of the reaction was determined via Job's method and limiting logarithmic method, and the mechanism of the reaction was postulated. Under the optimal conditions of the reaction, Beerʼs law was obeyed within the concentration range 0.5–50 μg/mL, the molar absorptivity value (ε) was 5766.5 L × mol–1 × c
... Show MoreIn this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot
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