Charge multipole Coulomb scattering form factors in ⁴⁸Ca nucleus have been reproduced utilizing the theory of nuclear shell. The efficient two-body nuclear potential fpbm is considered to construct the-spin orbit term LS vectors with Harmonic Oscillator HO potential as a wave function of single particle in Fp shell. Discarded spaces ( core + higher configuration) are taken into account through the Core polarization effect by model space with accurate two-body potential of Gogny to  interact the LS operating particles with the discarded space pair ( particle-hole) with energy of excitation equal to 2ћω. Gogny interaction has been selected as it had succeeded in nuclear shell theory. The computed results were compared with th

Manual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that

The study aims to make an in-depth  analysis and the financial account components in the Iraqi balance of payments because it reflects the economic center of the country towards outside world, it also helps in making decision about monetary and financial policies, finance and foreign Trade the importance of FDI for Iraq lies as an important sources as wells provides advanced technology  and job chances, It also avoids the country negative effects of borrowing processes from abroad . for analyzing direct and indirect foreign investment on the balance of payments and financial account in a period between (2003 to 2015), a community and research sample have been selected, presented in CBI/ Balance of payments. Department,

This study focuses on CFD analysis in the field of the shell and double concentric tube heat exchanger. A commercial CFD package was used to resolve the flow and temperature fields inside the shell and tubes of the heat exchanger used. Simulations by CFD are performed for the single shell and double concentric tube.

This heat exchanger included 16 tubes and 20 baffles. The shell had a length of 1.18 m and its diameter was 220 mm. Solid Works 2014, ANSYS 15.0 software was used to analyze the fields of flow and temperature inside the shell and the tubes. The RNG k-ε model was used and it provided good results. Coarse and fine meshes were investigated, showing that aspect ratio has no significant effect. 14 million

The current study was conducted on 504(Ros-308) broiler chicks reared in Animal farms belong to College of Agriculture, University of Baghdad during the period 28/9/2017- 9/11/2018 to determine the effect of ginseng additive on the performance of chicks. Results of study showed a significant effect (p≤0.05) of exposure period an Red blood cells, 3.56×106ml3 of blood was in bird, which exposure to 2hr at heat shock. In 42 day at age 106 ×38 ml3 of blood can noticed in the blood at birds, which exposure to 2hr in 21-42 days at 3 days of age. No significant effect at ginseng on blood cells. The results showed a significant effect (p≤0.05) of interaction on red blood cells at 21 and 42 days of age and the average cells between these ages

This study seeks to address the impact of marketing knowledge dimensions (product, price, promotion, distribution) on the organizational performance in relation to a number of variables which are (efficiency, effectiveness, market share, customer satisfaction), and seeks to reveal the role of marketing knowledge in organizational performance.

In order to achieve the objective of the study the researcher has adopted a hypothetical model that reflects the logical relationships between the variables of the study. In order to reveal the nature of these relationships, several hypotheses have been presented as tentative solutions and this study seeks to verify the validity of these hypotheses.

This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining