The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

The aim of this paper to find Bayes estimator under new loss function assemble between symmetric and asymmetric loss functions, namely, proposed entropy loss function, where this function that merge between entropy loss function and the squared Log error Loss function, which is quite asymmetric in nature. then comparison a the Bayes estimators of exponential distribution under the proposed function, whoever, loss functions ingredient for the proposed function the using a standard mean square error (MSE) and Bias quantity (M_bias), where the generation of the random data using the simulation for estimate exponential distribution parameters different sample sizes (n=10,50,100) and (N=1000), taking initial

Several previous investigations and studies utilized silica fume (SF) or (micro silica) particles as supplementary cementitious material added as a substitute to cement-based mortars and their effect on the overall properties, especially on physical properties, strength properties, and mechanical properties. This study investigated the impact of the inclusion of silica fume (SF) particles on the residual compressive strengths and microstructure properties of cement-based mortars exposed to severe conditions of elevated temperatures. The prepared specimens were tested and subjected to 25, 250, 450, 600, and 900 °C. Their residual compressive strengths and microstructure were evaluated and compared with control samples (C

The availability of low- cost adsorbent namely Al-Khriet ( a substance found in the legs of Typha  Domingensis) as an agricultural waste material, for the removal of lead and cadmium from aqueous solution was investigated. In the batch tests experimental parameters were studied, including adsorbent dosage between (0.2-1) g, initial metal ions concentration between (50-200) ppm (single and binary) and contact time (1/2-6) h. The removal percentage of each ion onto Al-Khriet reached equilibrium in about 4 hours. The highest adsorption capacity was for lead (96%) while for cadmium it was (90%) with 50 ppm ions concentration, 1 g dosage of adsorbent and pH 5.5. Adsorption capacity in the binary mixture were reduce at about 8% for lead a

This research is devoted to study the strengthening technique for the existing reinforced concrete beams using external post-tensioning. An analytical methodology is proposed to predict the value of the effective prestress force for the external tendons required to close cracks in existing beams. The external prestressing force required to close cracks in existing members is only a part from the total strengthening force.
A computer program created by Oukaili (1997) and developed by Alhawwassi (2008) to evaluate curvature and deflection for reinforced concrete beams or internally prestressed concrete beams is modified to evaluate the deflection and the stress of the external tendons for the externally strengthened beams using Matlab

Efficient operations and output of outstanding quality distinguish superior manufacturing sectors. The manufacturing process production of bending sheet metal is a form of fabrication in the industry of manufacture in which the plate is bent using punches and dies to the angle of the work design. Product quality is influenced by plate material selection, which includes thickness, type, dimensions, and material. Because no prior research has concentrated on this methodology, this research aims to determine V-bending capacity limits utilizing the press bending method. The inquiry employed finite element analysis (FEA), along with Solidworks was the tool of choice to develop drawings of design and simulations. The ASTM E290

Concerns about the environment, the cost of energy, and safety mean that low-energy cold-mix asphalt materials are very interesting as a potential replacement for present-day hot mix asphalt. The main disadvantage of cold bituminous emulsion mixtures is their poor early life strength, meaning they require a long time to achieve mature strength. This research work aims to study the protentional utilization of waste and by-product materials as a filler in cold emulsion mixtures with mechanical properties comparable to those of traditional hot mix asphalt. Accordingly, cold mix asphalt was prepared to utilize paper sludge ash (PSA) and cement kiln dust (CKD) as a substitution for conventional mineral filler with percentages ranging fro

            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen