The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines

This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re

Background : Xanthomatosis is a disease in which large tendon tumors can occur, especially in the Achilles tendon. This disease is a rare interesting orthopaedic condition.

Case Report:A case of a twenty eight year old girl patient with giant bilateral Achilles tendon xanthomas in which both tumors were resected.

There was no ulceration on the both sides. The patient was treated by total resection of the lesion and reconstruction using tendon transfer of the Peroneus brevis and Flexor hallusis longus. Postoperative treatment consisted of six weeks lower leg cast immobilization followed by partial weight bearing. After 4 months the patient was able to walk pain free without any difficultie

Background : Xanthomatosis is a disease in which large tendon tumors can occur, especially in the Achilles tendon. This disease is a rare interesting orthopaedic condition. Case Report:A case of a twenty eight year old girl patient with giant bilateral Achilles tendon xanthomas in which both tumors were resected. There was no ulceration on the both sides. The patient was treated by total resection of the lesion and reconstruction using tendon transfer of the Peroneus brevis and Flexor hallusis longus. Postoperative treatment consisted of six weeks lower leg cast immobilization followed by partial weight bearing. After 4 months the patient was able to walk pain free without any difficulties. It has been suggested that total resection with au

Background: periodontitis is a chronic inflammatory disease causing destruction of the tooth supporting structures, initiated by dental plaque and modified by environmental and genetic risk factors. Cyclooxygenase-2 (COX-2) enzyme is responsible for the production of prostaglandin E2, an important mediator in the chronic periodontitis (CP) pathogenesis. Polymorphisms in COX-2 gene have linked to CP in different populations. Aim: To study the association between Cyclooxygenase-2 single nucleotide polymorphism rs689466 (-1195A/G SNP) and chronic periodontitis in a sample of Iraqi population. Methods: One hundred Iraqi subjects divided into two groups: case group consisted of 70 CP patient (35 males and 35 females) with age range 30-55 year

This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K