The concept of decolonization of trauma has intrigued researchers for years due to its prolonged effect on personal and cultural levels. The process of intellectual decolonization involves defensive survival mechanisms, such as cultural rituals using traditional practices, nostalgic dialogues that idealize memories and recollections, and conversations about identity to navigate postcolonial trauma displacement. Symbolic connections evoke strong emotional responses, bridging the gap between the characters‘ physical dislocation and their imaginary homeland. Cocooning identity represents a space where a multidimensional self emerges—one that holds the victim of trauma, the survivor who endures, and the narrator, who constructs an idealized

In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint

Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model  in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling  the Symmetric gray scale texture image and estimating by using

This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different

In this research, some robust non-parametric methods were used to estimate the semi-parametric regression model, and then  these methods were compared using the MSE comparison criterion, different sample sizes, levels of variance, pollution rates, and three different models were used. These methods are S-LLS S-Estimation -local smoothing, (M-LLS)M- Estimation -local smoothing, (S-NW) S-Estimation-NadaryaWatson Smoothing, and (M-NW) M-Estimation-Nadarya-Watson Smoothing.

The results in the first model proved that the (S-LLS) method was the best in the case of large sample sizes, and small sample sizes showed that the

Transforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the pr

ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel

In light of the enquiry raised by the Economist Mary Finn in 1995 concluding that high utilization in absorptive capacity of the economy is of inflationary tendency for industrial countries due to the equality between high rates of utilization of absorptive capacity and resource – shortage conditions leading to price inflation, the same idea was used to prove that budget utilization of operational costs and elevating absorptive capacity at the expense of investment budget leads to inflationary tendency that becomes a burden on financing the step- in policy of the Central bank to control prices through its foreign currency reserves at a time when the economy turned  into an importer of non- tradable goods and being subject

The present study is concerned with Biostratigraphy of the Early-Middle Miocene outcrops of Jeribe Formation in the Zurbatiyah area, Wasit Governorate, Eastern Iraq. Forty-two Samples collected from Shur Sharin and AL-Hashima outcrop sections. The fossil content is rich in large and small benthic foraminifera; Twenty-one species and genus are identified in this study, in addition to coral, gastropoda, pelecypoda, ostracoda, alge, echinoid and shell fragments. According to the presence of benthic foraminifera, two Biozone have been identified in the Jeribe: Austrotrillina asmariensis-Dendritina rangi Concurrent Zone and Borelis melo curdica range zone.The age of the Formation determined as Early-Middle Miocene depending on these Bioz