Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti

This paper demonstrates the construction designing analysis and control strategies for fully tracking concentrated solar thermal by using programmable logic control in the city of Erbil-Iraq. This work used the parabolic dish as a concentrated solar thermal. At the focal point, the collected form of energy is used for heating a (water) in the receiver, analyzing this prototype in real-time with two different shapes of the receiver and comparing the results. For tracking the parabolic dish, four light-dependent resistors are used to detect the sun's position in the sky so that the tracking system follows it to make the beam radiation perpendicular to the collector surface all of the time during the day for maximum solar p

One of the most recent research areas in subsurface applications, including well drilling, is the use of eco-friendly and sustainably synthesized nanoparticles to improve drilling fluid efficiency. Typically, Shale formations present significant challenges to traditional drilling fluids, including fluid infiltration and shale swelling, which jeopardize wellbore stability. Although water-based drilling fluids (WBM) are environmentally preferred, their performance often requires enhancement through advanced additives. This study thus examines the synthesis of silica (SiO₂) and alumina (Al₂O₃) nanoparticles (NPs) using sustainable methods, employing Iraqi bentonite for silica and recycled aluminum scrap for alumina, to improve WBM effici

The present research has investigated the effect of microwave energy on improving the flow properties of heavy crude oil. The fragmentation of crude oil molecules was carried out with and without using 1 and 10 wt. % concentration of various types of H-donors like tetralin, cyclohexane, and naphtha.  Microwave power of 320, 385, and 540 W and radiation time 1-9 min, and temperature were studied. The kinematic viscosity and asphaltene content were measured for evaluation the improving of heavy crude oil.    Results show that viscosity of crude oil decreased with increase H-donor concentration, a maximum percentage of viscosity reduction was10.63 % for tetralin at 6 min radiation time, while 8.67%, and 7.34% for cyclohexane a

   The present research was conducted to synthesis Y-Zeolite by sol-gel technique using MWCNT (multiwalled carbon nanotubes) as crystallization medium to get a narrow range of particle size distribution with small average size compared with ordinary methods. The phase pattern, chemical structure, particle size, and surface area were detected by XRD, FTIR, BET and AFM, respectively. Results shown that the average size of Zeolite with and without using MWCNT were (92.39) nm and (55.17) nm respectively .Particle size range reduced from (150-55) nm to (130-30) nm. The surface area enhanced to be (558) m2/g with slightly large pore volume (0.231) km3/g was obtained. Meanwhile, degree of crystallization decreased to 120%.

This paper presents a deterministic system that combines textual semantic data from panoramic images with LiDAR point clouds in a mobile mapping setup. Urban scenes often include textual elements, such as signs and business names, that provide key details typically missing from LiDAR-based urban digital twins. The presented method uses deep learning-based OCR to extract text from street panoramas and then categorizes it into urban types using a rule-based classifier. Text regions are geometrically projected into the LiDAR environment by converting image coordinates into viewing rays that intersect LiDAR surfaces, such as facades. Data from multiple panoramas are merged with confidence-weighted spatial clustering to produce consisten

Simple and sensitive batch and Flow-injection spectrophotometric methods for the determination of Procaine HCl in pure form and in injections were proposed. These methods were based on a diazotization reaction of procaine HCl with sodium nitrite and hydrochloric acid to form diazonium salt, which is coupled with chromatropic acid in alkaline medium to form an intense pink water-soluble dye that is stable and has a maximum absorption at 508 nm. A graphs of absorbance versus concentration show that Beer’s law is obeyed over the concentration range of 1-40 and 5-400 µg.ml-1 of Procaine HCl, with detection limits of 0.874 and 3.75 µg.ml-1 of Procaine HCl for batch and FIA methods respectively. The FIA average sample throughput was 70 h-1. A

Metronidazole-MIPs were prepared by using (MDZ) as the template as well as allylchloride (AYC) or allylbromide (AYB) as monomer, used (TMPTA) tri-methylol propane tri-acrylate or ethylene glycol di-methyl acrylate (EGDMA) as cross-linker and initiator used (BP) benzyl peroxide. By using different plasticizers (di butyl Phthalate (DBPH), Nitrobenzene (NB), oleic acid (OA) and paraffin) for MDZ-MIP1 and (Di-butyl sebecate (DBS), Di-methyl acrylate (DMA), Tributylphosphate(TBP) and Tris(ethylhexyl phosphate (TEHP) ) for MDZ-MIP2. Membranes of MIPs were prepared in PVC matrix. The characterizations of each electrode were determined The Slope range from (55.083 - 43.711) mV/decade, Limit of Detection (8 X 10 -4- 2 X 10-6) and Linearity