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

Cultural and identity scars have been engraved in the body of ethnic minority of Muslims in America due to the bloody attacks of 9/11. These events have created thus traumatic experiences on the party who witnessed the events at close and the people on whom the blame is conclusively directed, Muslim Americans. For Americans, the attacks resulted in a proud reassertion of the national virtue and communal integrity from which Muslim Americans were excluded. This reassertion is accompanied for Muslims by a reconstruction of a cultural identity away from their origin homeland and under pressures and prejudices that made the process of reconstruction to be severely challenging. Accordingly, the challenge needed to be portrayed to overcome the d

An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing two different key sets for each layer. Th

Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

The present study was carried out to determine the bacterial isolates and study their antimicrobial susceptibility in case of burned wound infections. 70 burn wound swabs were taken from patients, who presented invasive burn wound infection from both sex and average age of 3-58 years, admitted to teaching medical Al- Kendi hospital from October 2007 to June 2008. Pseudomonas aeruginosa was found to be the most common isolate (48.9%) followed by Staphylococcus aureus (24.4%), Citrobacter braakii (13.3%), Enterobacter spp. (11.1%), Coagulase-negative Staphylococci (11.1%), Proteus vulgaris (6.66%), Corynebacterium spp. (6.66%), Micrococcus (6.66%), Proteus mirabilis (4.44%), Enterococcus faecalis (4.44%), E.coli (4.44%), Klebsiella spp. (2.22

Lacing reinforcement plays a critical role in the design and performance of reinforced concrete (RC) slabs by distributing the applied loads more evenly across the slab, ensuring that no specific area of the slab is overloaded. In this study, nine slabs, divided into three groups according to the investigated parameters, were meticulously designed and evaluated to study the interplay between the lacing reinforcement and other key parameters. Each slab was crafted for simple support and was subjected to both static and repeated two-point load tests. The lacing reinforcement had an angle of 45° with various tension and lacing steel. The repeated-tested specimens with lacing reinforcement experienced smaller ductility than those of s

Lacing reinforcement plays a critical role in the design and performance of reinforced concrete (RC) slabs by distributing the applied loads more evenly across the slab, ensuring that no specific area of the slab is overloaded. In this study, nine slabs, divided into three groups according to the investigated parameters, were meticulously designed and evaluated to study the interplay between the lacing reinforcement and other key parameters. Each slab was crafted for simple support and was subjected to both static and repeated two-point load tests. The lacing reinforcement had an angle of 45° with various tension and lacing steel. The repeated-tested specimens with lacing reinforcement experienced smaller ductility than those of s

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.