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

Background: A review of articles of method in treating compound phalangeal fractures by using mini-external fixator, elaborating the anatomy, mechanics, modalities of treatment, and complications of these types of fractures. Also, it compares between different studies regarding the functional results and final outcome. External fixation of phalangeal fractures is a good method for osteo synthesis in certain situations. The simplicity of the surgical procedure and the minimal disruption of the normal bone architecture also make it appealing.Objectives: Evaluating the functional results of the use of mini-external fixator for the treatment of compound fractures of phalangeal bones of the hand.Method: Our study consists of 15 patients, 12 w

The depletion of petroleum reserves and increasing environmental concerns have driven the development of eco-friendly asphalt binders. This research investigates the performance of natural asphalt (NA) modified with waste engine oil (WEO) as a sustainable alternative to conventional petroleum asphalt (PA). The study examines NA modified with 10%, 20%, and 30% WEO by the weight of asphalt to identify an optimal blend ratio that enhances the binder’s flexibility and workability while maintaining high-temperature stability. Comprehensive testing was conducted, including penetration, softening point, viscosity, ductility, multiple stress creep recovery (MSCR), linear amplitude sweep (LAS), energy-dispersive X-ray spectroscopy (EDX), F

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

The analysis of the root cause techniques is a reasonable option to be made to assess the root causes of the funding of construction projects. There are a variety of issues related to financing in construction industries in Iraq. The root,cause analysis is the impact of security and social conditions on financial funding. Variety tools of root cause analysis have originated from literature, as common methods for the detection of root causes. The purpose of this study was to identify and diagnose causes that lead to obstruction of financial funding in the construction projects in the republic of Iraq from the contractors' point of view and their interaction with a number of variables. The study diagnosed nine causes of fi

The current study involves placing 135 boreholes drilled to a depth of 10 m below the existing ground level. Three standard penetration tests (SPT) are performed at depths of 1.5, 6, and 9.5 m for each borehole. To produce thematic maps with coordinates and depths for the bearing capacity variation of the soil, a numerical analysis was conducted using MATLAB software. Despite several-order interpolation polynomials being used to estimate the bearing capacity of soil, the first-order polynomial was the best among the other trials due to its simplicity and fast calculations. Additionally, the root mean squared error (RMSE) was almost the same for the all of the tried models. The results of the study can be summarized by the production

This study was conducted to explore the effects of using ionized water on the productive and physiological performance of Japanese quails (Coturnix japonica). Our study was conducted at a private farm from 20th April, 2016 to 13th July, 2016 (84 d). One hundred 42-day-old Japanese quail chicks were used, divided randomly into 5 groups with 4 replicates. Treatments consisted in a control group (T1 - normal water:), alkaline (T2 - pH 8 and T3 - pH 9), and acidic water (T4 - pH 6 and T5 - pH 5). All birds were fed a balanced diet of energy and protein. The egg production ratio, egg weight, cumulative number of eggs, egg mass, feed conversion ratio, productivity per hen per week, and effects on plasma lipids, uric acid, glucose, calcium, and ph

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi