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Impact of investigator personality pattern on job stress at the General inspectors of offices /applied thesis
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This research studied the relationship of patterns of investigator personality with the big five dimensions (Extraversion, stability, interoperability, openness, and personal benevolent), in facing the job stress with its resources(characteristics of the role, quality of work, organizational structure, work environment, organizational policies, social relations, and organizational processes) which the investigators exposed to it at the General Inspectors Offices.

The researcher derived the idea of ​​research from the importance of the work of these offices in a confrontation of various cases of financial and administrative corruption in Iraq at the present time, since itis one of the most important inspection and control organizations in Iraq, through its strategic role in fighting the corruption, and enabling an appropriate environment for the comprehensive development of the anti-corruption system, and its specialized role in control on ministries and public organizations, and raise the level of their performance through the exercise of inspection and control functions that represented by audit, inspection, investigation, and performance appraisal. As well as, the large stress that the workers faced it in these offices, especially the investigators, because of the seriousness and importance of their work, which leads to a feeling of stress at work which may affect their performance and achievement of offices objectives in the fight against the scourge of corruption, since it requires that those employees must have personal attributes correspond to the nature of their work to cope with the stress they experience and reduce its negative effects.

The aim of the research is to deepen the understanding of the nature of the personal patterns of investigators of general Inspectors Offices and the extent of their adaptation to job stress that they are exposed to at work to take advantage of it now and in the future in the proper selection, appointment and investiture of employees according to their personalities and how important and dangerous tasks that fall upon themselves, to reach the desired objectives.

The researcher used a questionnaire as an essential tool for data collection, as well as interviews and the experience of the researcher during his work in one of these offices for several years. The questionnaire was distributed to a random sample of (140) people across (7) offices of General Inspectors in (7) ministries, the sample selected represent (20%) of the original community for each Office. For data processing, the researcher used statistical methods and tests.

Based on the measuring of research variables and diagnosing it, and testing correlations, effect, and differences among them. The research concluded a set of conclusions and the most important was (Personal investigators patterns (Neuroticism, Extraversion, Agreeableness, openness to experience) in the offices of inspectors general affect job stress they are exposed to).

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Publication Date
Tue May 01 2018
Journal Name
Environmental Technology & Innovation
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Mon Aug 01 2016
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Mon Aug 27 2018
Journal Name
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The fall angle of sun rays on the surface of a photovoltaic PV panel and its temperature is negatively affecting the panel electrical energy produced and efficiency. The fall angle problem was commonly solved by using a dual-axis solar tracker that continually maintains the panel orthogonally positioning to the sun rays all day long. This leads to maximum absorption for solar radiation necessary to produce maximum amount of energy and maintain high level of electrical efficiency. To solve the PV panel temperature problem, a Water-Flow Double Glazing WFDG technique has been introduced as a new cooling tool to reduce the panel temperature. In this paper, an integration design of the water glazing system with a dual-axis tracker has been ac

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Wed Jun 26 2019
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It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in

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Publication Date
Sat Jan 01 2022
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In this work, an efficient energy management (EEM) approach is proposed to merge IoT technology to enhance electric smart meters by working together to satisfy the best result of the electricity customer's consumption. This proposed system is called an integrated Internet of things for electrical smart meter (2IOT-ESM) architecture. The electric smart meter (ESM) is the first and most important technique used to measure the active power, current, and energy consumption for the house’s loads. At the same time, the effectiveness of this work includes equipping ESM with an additional storage capacity that ensures that the measurements are not lost in the event of a failure or sudden outage in WiFi network. Then then these measurement

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Publication Date
Mon Mar 29 2021
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Tue Feb 13 2018
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