In this research we have tackled the role of Talent management (as a private variable) within (the Talent attraction, the Talent management performance, Talent development and Talent retention) on strategic performance reinforcement ( accredited variable) within its dimensions ( financial perspective, costumer perspective, internal operations perspective and learning and development perspective). The research conducted on sample of some college teachers from two of Sumer's colleges. The research problem represented by the broad organization's competition as well as universities; which led these colleges to investigate it's skillful human staff to meet it's strategic performance. 

To meet the aims of

Abstract

                The aim of the research is to demonstrate the impact of long-term investment on profitability, and in order to achieve this goal, long-term investment was chosen, represented by (the ratio of long-term investments to total investments, the ratio of long-term investment to the total (deposits) as independent variables, and studying its impact on the dependent variable, which is profitability as measured by the rate of return on investments, the rate of return on equity. In order to reach the results, the inductive approach and the analytical descriptive approach were used, and the research found a significant impac

Inherent fluctuations in the availability of energy from renewables, particularly solar, remain a substantial impediment to their widespread deployment worldwide. Employing phase-change materials (PCMs) as media, saving energy for later consumption, offers a promising solution for overcoming the problem. However, the heat conductivities of most PCMs are limited, which severely limits the energy storage potential of these materials. This study suggests employing circular fins with staggered distribution to achieve improved thermal response rates of PCM in a vertical triple-tube heat exchanger involving two opposite flow streams of the heat-transfer fluid (HTF). Since heat diffusion is not the same at various portions of the PCM unit,

Objective. This study aimed to evaluate the orthodontic bond strength and enamel-preserving ability of a hydroxyapatite nanoparticles-containingself-etch system following exposure to various ageing methods. Materials and Methods. Hydroxyapatite nanoparticles (nHAp) were incorporated into an orthodontic self-etch primer (SEP, Transbond™ plus) in three different concentrations (5%, 7%, and 9% wt) and tested versus the plain SEP (control) for shear bond strength (SBS), adhesive remnant index (ARI) scores, and enamel damage in range-finding experiments using premolar teeth. The best-performing formulation was further exposed to the following four artificial ageing methods: initial debonding, 24 h water storage, one-month water stora

This research is based on the descriptive and analytical methodology. The importance of studying labor laws and labor unions in Japan between 1889 and 1946 constitutions is because Japan was out of a feudal phase, and had no idea about the factory system and industrialization in their modern sense before the Meiji era. Generally, its labor system used to be mostly familial, and the economic system was based on agriculture. This called for the enactment of legislations and laws appropriate for the coming phase in Meiji era. Thus, this paper examines the role of Meiji government in enacting labor legislations and laws when he came to power in 1896, and his new constitution in 1889 and the civil code of 1896. It further examines the way Mei

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

The paper studies the description of the colloquial and popular vocabulary  used by wholesales tradesmen in Varonech before the Bolshevik Revolution . The vocabulary were used in the personal letters written by the poet and sent to famous poets and critics like Belenisky, kryvesky and Malsheve. And some were sent to his father and his sister. Not only did these letter bear the personal taste, but they represented a literary product reflecting on the poet's impressions, views, ambitions, and opinion in arts, poetry, prose, and theatre. The researcher used about thirty instances of various levels of grammar, style and phonology, all representing colloquial vocabulary used commonly at the time of Alexi&nbsp

واقع الدراسات الاورومتوستطية في الجامعات العراقية "دراسة حالة كلية العلوم السياسية - جامعة بغداد"

The current researsh is aimed to pay attention on concept of human resources hard (Difficult) to manage. Such style of human resourcses has emerged to form anew challenge for busniess organizations.

Management such human resources entails first determing incentives of their behaviour models. Analyzing these models will be important to strategical management of them from work.

In nutshell, this researsh try to recommendation of contemporary literature about future of difficult (hard) human resources management.

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c