Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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

Stuck pipe is a prevalent and costly issue in drilling operations, with the potential to cost the petroleum industry billions of dollars annually. To reduce the likelihood of this issue, efforts have been made to identify the causes of stuck pipes. The main mechanisms that cause stuck pipes include drill cutting of the formation, inappropriate hole-cleaning, wellbore instability, and differential sticking forces, particularly in highly deviated wellbores. The significant consequences of a stuck pipe include an increase in well costs and Non-Productive Time (NPT), and in the worst-case scenario, the loss of a wellbore section and down-hole equipment, or the need to sidetrack, plug, or abandon the well. This paper provides a comprehensive

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance

MT Suhail, SA Hussein, MN Abdulhussein, WQ Abdaullateef, M khairallah Aid…, Migration Letters, 2024

Carbazone Derivatives (CD) (semicarbazone, semithiocarbasone) are produced by the condensation reaction between a aldehyde (or ketone) with a carbazide derivatives (semicarbazide, semithiocarbazide). CD and their metal complexes existent a wide range of implementation that stretch from their ply in the medicinal and pharmaceutical area because of their major significant pharmacological characteristic such as anti-fungal,anti-bacterial, anti-cancer, anti-human immunodeficiency virus, anti-inflammation, anti-neoplastic,inhibition corrosion, antioxidation, antiradical. This paper reviews the definition, importance and various applications of carbazone derivatives with transitional meta

In this review, previous studies on the synthesis and characterization of the metal Complexes with paracetamol by elemental analysis, thermal analysis, (IR, NMR and UV-Vis (spectroscopy and conductivity. In reviewing these studies, the authors found that paracetamol can be coordinated through the pair of electrons on the hydroxyl O-atom, carbonyl O-atom, and N-atom of the amide group. If the paracetamol was a monodentate ligand, it will be coordinated by one of the following atoms O-hydroxyl, O-carbonyl or N-amide. But if the paracetamol was bidentate, it is coordinated by atoms (O-carbonyl and N-amide), (O-hydroxyl and N-amide) or (O-carbonyl and O-hydroxyl). The authors also found that free paracetamol and its complexes have antimicrobial