The present study addressed "Performance Appraisal of Human Resource Management and Its Effect on Achieving the Organizational Success", for the topics of performance appraisal of human resource management and the organizational success gained an increasing interest being relatively important and modern topics which had a great effect on the future of organizations.

The study aimed at revealing the pattern of appraising the performance of human resource management for the study sample, and whether it was qualified to lead the ministry towards the organizational success, for this purpose two main hypotheses were formulated: 1) there is a positive significant correlation between both variables: performanc

In contrast to the classical antibacterial sulfa drugs that are unsubstituted or monosubstituted, our newly synthesized analogs were designed to obtain sulfonamide moiety containing disubstituted hetero nitrogen atom. These compounds were formed successfully by chlorosulfonation of acetanilide and the product was treated with different cyclic amines and finally amide hydrolysis was necessary to get agents that were analyzed for IR, UV, CHN, melting points and solubility. At last, we studied their antibacterial activity on certain types of bacteria and we noticed the inactivity due to possible steric factor. Principly, this means these products have no inhibiting action against the used microbes.

A substantial percentage of the world’s energy consumption (almost 40%) and carbon dioxide (CO2) emissions (around 37%) come from the construction industry, especially schools. This work presents a new hybrid artificial intelligence (AI) engineering model that aims to maximize energy performance on campuses in a holistic way. Modules for data-driven forecasting, metaheuristic optimization, and real-time adaptive control are all part of the concept. A thorough energy simulation of a university campus building is used in conjunction with the AI model to assess its performance through a co-simulation framework. Findings show that yearly peak electricity demand may be reduced by 18.7% and total site energy consumption by 22.4% when co

Linear motor offers several features in many applications that require linear motion. Nevertheless, the presence of cogging force can deteriorate the thrust of a permanent magnet linear motor. Using several methodologies, a design of synchronous single sided linear iron-core motor was proposed. According to exact formulas with surface-mounted magnets and concentrated winding specification, which are relying on geometrical parameters. Two-dimensional performance analysis of the designed model and its multi-objective optimization were accomplished as a method to reduce the motor cogging force using MAXWELL ANSYS. The optimum model design results showed that the maximum force ripple was approximatrly reduced by 81.24%compared to the origina

In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N