There is no doubt that Jane Austen is one of the most studied authors of the late 18th and early 19th centuries. Her female characters have been extensively studied and they seem to have aroused much interest as manifestations of the conduct of their time. Her heroines have realized that there were many mistakes in the rules of conduct that controlled and restricted their behaviors. Thus, they have found no fault in correcting these mistakes, by behaving naturally without acting. Elizabeth Bennet the heroine of Pride and Prejudice and Marianne Dashwood of Sense and Sensibility are the chosen examples of that kind of women.

A total of 589 fishes, belonging to 23 species were collected from eight different localities
in north and mid Iraq during 1993. The parasitological inspection of such fishes revealed the
presence of 59 parasite species and two fungi. Among such parasites, five monogenetic
trematodes were recorded on the gills of some fishes for the first time in Iraq. These
included:- Ancyrocephalus vanbenedenii on Liza abu from Tigris river at Al-Zaafaraniya,
south of Baghdad; Dactylogyrus anchoratus on Cyprinus carpio from Tigris river at Al –
Zaafaranya D. minutus on C. carpio from both Tigris river at Al-Zaafaraniya and Euphrates
river at Al-Qadisiya dam lake; Discocotyle sagittata on L. abu from both the drainage system
at

This paper proposes a novel finite-time generalized proportional integral observer (FTGPIO) based a sliding mode control (SMC) scheme for the tracking control problem of high order uncertain systems subject to fast time-varying disturbances. For this purpose, the construction of the controller consists of two consecutive steps. First, the novel FTGPIO is designed to observe unmeasurable plant dynamics states and disturbance with its higher time derivatives in finite time rather than infinite time as in the standard GPIO. In the FTGPO estimator, the finite time convergence rate of estimations is well achieved, whereas the convergence rate of estimations by classical GPIO is asymptotic and slow. Secondly, on the basis of the finite and fast e

In this paper, preliminary test Shrinkage estimator have been considered for estimating the shape parameter α of pareto distribution when the scale parameter equal to the smallest loss and when a prior estimate α0 of α is available as initial value from the past experiences or from quaintance cases. The proposed estimator is shown to have a smaller mean squared error in a region around α0 when comparison with usual and existing estimators.

ABSTRACT

The study aimed to evaluate the information label of some local pickle products and estimate sodium benzoate therein. 85 samples of locally made pickles were collected from Baghdad city markets and randomly from five different areas in Baghdad it included (Al-Shula, Al-Bayaa, Al-Nahrawan, Al-Taji, and Abu Ghraib), which were divided into groups P1, P2, P3, P4 and P5, respectively, according to those areas,  samples information label was scanned and compared with the Iraqi standard specification for the information card of packaged and canned food IQS 230, the results showed that 25.9% of the samples were devoid of the indication card informa

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).

The current research creates an overall relative analysis concerning the estimation of Meixner process parameters via the wavelet packet transform. Of noteworthy presentation relevance, it compares the moment method and the wavelet packet estimator for the four parameters of the Meixner process. In this paper, the research focuses on finding the best threshold value using the square root log and modified square root log methods with the wavelet packets in the presence of noise to enhance the efficiency and effectiveness of the denoising process for the financial asset market signal. In this regard, a simulation study compares the performance of moment estimation and wavelet packets for different sample sizes. The results show that wavelet p

In this paper, point estimation for parameter ? of Maxwell-Boltzmann distribution has been investigated by using simulation technique, to estimate the parameter by two sections methods; the first section includes Non-Bayesian estimation methods, such as (Maximum Likelihood estimator method, and Moment estimator method), while the second section includes standard Bayesian estimation method, using two different priors (Inverse Chi-Square and Jeffrey) such as (standard Bayes estimator, and Bayes estimator based on Jeffrey's prior). Comparisons among these methods were made by employing mean square error measure. Simulation technique for different sample sizes has been used to compare between these methods.

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p