To evaluate and improve the efficiency of photovoltaic solar modules connected with linear pipes for water supply, a three-dimensional numerical simulation is created and simulated via commercial software (Ansys-Fluent). The optimization utilizes the principles of the 1st and 2nd laws of thermodynamics by employing the Response Surface Method (RSM). Various design parameters, including the coolant inlet velocity, tube diameter, panel dimensions, and solar radiation intensity, are systematically varied to investigate their impacts on energetic and exergitic efficiencies and destroyed exergy. The relationship between the design parameters and the system responses is validated through the development of a predictive model. Both single and mult

Commercial fish catch in the Iraqi marine waters from December 2018 to December 2019 was investigated. The study is based on three stations: the first station is located at the Shatt Al-Arab estuary, the second represents the area between the Shatt Al-Arab Estuary and open marine waters, and the third is associated with the Iraqi territorial marine waters. The total weight of the catch was 1881 kg, represented by 500, 654, and 727 kg in the first, second and third stations respectively. The third station was the highest with a majority of the family Sciaenidae by 464 kg, while the lowest was the family Scombridae by 0.5 kg. The total number of species included 37 species, belonging to 27 genera, 19 families, and 6 orders, the largest ord

This study investigates the influence of Strategic Consensus (SC) on Organizational Performance (OP), with Strategic Alignment (SA) serving as a mediating variable, within private academic institutions in Iraq. The research utilized scales developed to measure each variable: SC, OP, and SA, all of which are unidimensional. The sample comprised 131 senior participants, including deans and faculty council members, with questionnaires distributed across three institutions: Dijla University College (35 respondents), Baghdad College of Economic Sciences (31 respondents), and the University of Uruk (65 respondents). Data analysis employed various statistical techniques, including normality testing, confirmatory factor analysis, descriptive statis

Flexure members such as reinforced concrete (RC) simply supported beams subjected to two-point loading were analyzed numerically. The Extended Finite Element Method (XFEM) was employed for the treatment the non-smooth h behaviour such as discontinuities and singularities. This method is a powerful technique used for the analysis of the fracture process and crack propagation in concrete. Concrete is a heterogeneous material that consists of coarse aggregate, cement mortar and air voids distributed in the cement paste. Numerical modeling of concrete comprises a two-scale model, using mesoscale and macroscale numerical models. The effectiveness and validity of the Meso-Scale Approach (MSA) in modeling of the reinforced concrete beams w

The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

The distress of moisture induced damage in flexible pavement received tremendous attention over the past decades. The harmful effects of this distress expand the deterioration of other known distresses such as rutting and fatigue cracking. This paper focused on the efficiency of using the waste material of demolished concrete to prepare asphalt mixtures that can withstand the effect of moisture in the pavement. For this purpose, different percentages of waste demolished concrete (0, 10, 20, 30, 50, 70 and 100) were embedded as a replacement for coarse aggregate to construct the base course. The optimum asphalt contents were determined depending on the Marshall method. Then after, two parameters were founded to evaluate the moisture

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp