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

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

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

Numerous regions in the city of Baghdad experience the congestion and traffic problems. Due to the religious and economic significance, Al-Kadhimiya city (inside the metropolitan range of Baghdad) was chosen as study area. The data gathering stage was separated into two branches: the questionnaire method which is utilized to estimate the traffic volumes for the chosen roads and field data collection method which included video recording and manual counting for the volumes entering the selected signal intersections. The stage of analysis and evaluation for the seventeen urban roads, one highway, and three intersections was performed by HCS-2000 software.The presented work plots a system for assessing the level of service

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

      A total of 1346 hard ticks (863♂ and 483 ♀) infested 104 camels, 60 alive camels with 93.33%  infestation rate and 44 carcasses of camels had 79.54% infestation rate The total infestation rate was 87.5 %. The current study results revealed ten species of hard ticks family Ixodidae Koch, 1844 related to genus Hyalomma as following: H. dromedarii Koch, 1844, H. schulzii Morel, 1969, H. turanicum Pomerantsev, 1946, H.  excavatum Koch, 1844, H. truncatum Koch, 1844, H. scupense Schulzii, 1919, H. marginatum Koch, 1844, H. anatolicum Koch, 1844, H. rufipes Koch, 1844, H. impeltatum Schulze & Schlottke, 1930 from camel Camelus dromedarius Linnaeus, 1758 collected from 21 regions belonging to six provinces in middle, w

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In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

Background: The treatment of dental tissues proceeding to adhesive procedures is a crucial step in the bonding protocol and decides the clinical success ofrestorations. This study was conducted in vitro, with the aim of evaluating thenanoleakage on the interface between the adhesive system and the dentine treated by five surface modalities using scanning electron microscopy and energydispersiveX-ray spectrometry. Materials and methods: Twenty five extracted premolars teeth were selected in the study. Standardized class V cavities were prepared on the buccal and lingual surfaces then the teeth divided into five main groups of (5 teeth in each group n=10) according to the type of dentine surface treatment that was used: Group (A): dentine was