This work presents the construction of a test apparatus for air-conditioning application that is flexible in changing a scaled down adsorbent bed modules. To improve the heat and mass transfer performance of the adsorbent bed, a finned-tube of the adsorbent bed heat exchanger was used. The results show that the specific cooling power (SCP) and the coefficient of performance (COP) are 163 W/kg and 0.16, respectively, when the cycle time is 40 min, the hot water temperature is 90^oC, the cooling water temperature is 30^oC and the evaporative water temperature is 11.4^oC.

This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K

The paper presents a highly accurate power flow solution, reducing the possibility of ending at local minima, by using Real-Coded Genetic Algorithm (RCGA) with system reduction and restoration. The proposed method (RCGA) is modified to reduce the total computing time by reducing the system in size to that of the generator buses, which, for any realistic system, will be smaller in number, and the load buses are eliminated. Then solving the power flow problem for the generator buses only by real-coded GA to calculate the voltage phase angles, whereas the voltage magnitudes are specified resulted in reduced computation time for the solution. Then the system is restored by calculating the voltages of the load buses in terms

12 membered Schiff base macrocyclic ligands, 6,7,14,15-tetra phenyl-1,2,3,4, 4a,8a, 9,10, 11,12, 12a,16a-dodecahydro dibenzo [b,h] [1,4,7,10] tetraazacyclododecine L1, and 14 membered Schiff base macrocyclic ligands, 6,8,15,17-tetramethyl-1,2,3,4, 4a,7,9a, 10,11,12,13,13a,16,18a-tetra decahydro dibenzo[b,i] [1, 4,8,11] cyclotetradecine tetraaza L2, 7,16-bis(2,4- dichloro benz ylidene)-6,8,15,17-tetra methyl-1,2,3,4, 4a,7,9a, 10, 11,12, 13, 13a,16,18a-tetra deca hydro dibenzo [b,i] [1,4,8,11] tetra azacyclo tetra decine L3 and 6,8,15, 17-tetramethyl-1,2,3, 4,4a,9a,10, 11,12,13,13a,18a-dodecahydro dibenzo [b,i] [1,4,8, 11] tetraazacyclo tetradecine (7,16-diylidene) bis(methanylyli dene) bis (N,N-dimethylaniline) L4 were synthesized by condens

A new set of metal complexes by the general formula [M(P)2(H2O)2]Cl2 has been prepared through the interaction of the new Ligand [N1, N4-bis(4-methoxyphenyl)succinamide] (P) derived from succinyl chloride with p-anisidine with the transition metal ions [Cu(II), Mn(II), Cd(II), Co(II) and Ni(II)]. Compounds diagnosed by TGA, 1 H, 13CNMR and Mass spectra (for (P)), Fourier-transform infrared and Electronic spectrum, Magnetic measurement, molar conduct, (%M, %C, %H, %N). These measurements indicate that (P) is associated with the metal ion in a bi-dentate fashion by nitrogen atoms (the amide group), and the octahedral composition of these complexes is suggested. Staphylococcus Aureus (+) and Escherichia Coli (–) were studied for the antibact

Rotational Piezoelectric Energy Harvesting (RPZTEH) is widely used due to mechanical rotational input power availability in industrial and natural environments. This paper reviews the recent studies and research in RPZTEH based on its excitation elements and design and their influence on performance. It presents different groups for comparison according to their mechanical inputs and applications, such as fluid (air or water) movement, human motion, rotational vehicle tires, and other rotational operational principal including gears. The work emphasises the discussion of different types of excitations elements, such as mass weight, magnetic force, gravity force, centrifugal force, gears teeth, and impact force, to show their effect

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

Assessment of annual wind energy potential for three selected sites in Iraq has been analyzed in the present work. The wind velocities data from August 2014 to July 2015 were collected from the website of Weather Underground Organization (WUO) at stations elevation (35m, 32m, and 17m) for Baghdad, Najaf, and Kut Al-Hai respectively. Extrapolation of stations elevation and wind velocities was used to estimate wind velocities at (60m, 90m, and 120m). The objectives are to analyze the wind speed data and assess the wind energy potential for wind energy applications. Computer code for MATLAB software has been developed to solve the mathematical model. The results are presented as a monthly and annual average for wind velocities, standard deviat