The research aims to determine the impact of employees’ retention strategy on organizational memory. This research is historical, descriptive, and analytical. The sample consists of 158 faculty members in five private colleges in Baghdad. The technique used to analyze the data is SEM (Structural Equation Modeling), and SPSS (Statistical Package for the Social Sciences). The research concludes that the employees retaining strategy plays a vital role in retaining employees and hence maintains organizational memory. The findings and recommendations of this research assure the administrations of private colleges that employees retention strategy play a vital role in retaining its employee and hence maintains organizational memory. This research differs from the previous researches in that it has not examined the reasons for leaving employees or the turnover, but looking for the reasons that inspire employees to remain in the organization. This research suggests that employees’ retention strategy helps the organization retain its employees, and as a consequence, maintaining organizational memory. Received: 21 September 2020 / Accepted: 1 November 2020 / Published: 17 January 2021
Two means used for saving fish samples, namely Freezing and Preservatives represented by Alcohol and Formalin. The Freezing was used in saving samples collected newly, in addition to use Alcohol and Formalin with different concentrations 70% of Alcohol and 10% of Formalin. The concentrations of some heavy metal elements were examined, such as Potassium, Phosphorus, Calcium, Manganese, Magnesium, Zinc, Iron, Copper and Boron in samples saved in Formalin and Alcohol and frozen at different durations. The concentration of some elements has been changed during the saving duration. The study was performed on the concentration of heavy elements in the Liza abu muscles of saved and frozen fish.
In this communication, introduce the split Mersenne and Mersenne-Lucas hybrid quaternions, also obtaining generating functions and Binet formulas for these hybrid quaternions and investigating some properties among them.
The current work aims to evaluate the association between genetic mutations in thymidylate synthetase (
<p>Energy and memory limitations are considerable constraints of sensor nodes in wireless sensor networks (WSNs). The limited energy supplied to network nodes causes WSNs to face crucial functional limitations. Therefore, the problem of limited energy resource on sensor nodes can only be addressed by using them efficiently. In this research work, an energy-balancing routing scheme for in-network data aggregation is presented. This scheme is referred to as Energy-aware and load-Balancing Routing scheme for Data Aggregation (hereinafter referred to as EBR-DA). The EBRDA aims to provide an energy efficient multiple-hop routing to the destination on the basis of the quality of the links between the source and destination. In
... Show MoreElectronic Health Record (EHR) systems are used as an efficient and effective method of exchanging patients’ health information with doctors and other key stakeholders in the health sector to obtain improved patient treatment decisions and diagnoses. As a result, questions regarding the security of sensitive user data are highlighted. To encourage people to move their sensitive health records to cloud networks, a secure authentication and access control mechanism that protects users’ data should be established. Furthermore, authentication and access control schemes are essential in the protection of health data, as numerous responsibilities exist to ensure security and privacy in a network. So, the main goal of our s
... Show MoreThe rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
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