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Proposal of a guide for talent evaluation and management based on a qualitative and three-staged approach
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Purpose

The key objective of the study is to understand the best processes that are currently used in managing talent in Australian higher education (AHE) and design a quantitative measurement of talent management processes (TMPs) for the higher education (HE) sector.

Design/methodology/approach

The three qualitative multi-method studies that are commonly used in empirical studies, namely, brainstorming, focus group discussions and semi-structured individual interviews were considered. Twenty-three individuals from six Australian universities participated in this study.

Findings

The qualitative study explored three key themes and ten subthemes of TMPs that are used in AHE. These were: (1) talent attraction, (2) talent development and (3) talent retention.

Research limitations/implications

This study only targeted one country (Australia) and one sector (HE).

Practical implications

This study offers three major contributions as follows: theoretical, practical and policy aspects. Theoretically, the study provides a value-add to Talent Management (TM) theory through designing a guide (conceptual model) of TMPs for the HE sector. Practically, it collects original qualitative data regarding TM in the HE domain. From a policy point of view, this study adds more debate around adding new ideas to Australian education strategic plans for HE.

Originality/value

This study has a unique methodology because of strengthening the effect of an in-depth case study. For instance, two different techniques were used for data analysis for the same research objective as follows: (1) both manual methods and content analysis software (NVivo 11) and (2) the three-stage approach. Using these techniques for the same purpose in one study can provide greater flexibility to examine the relationship between theory and data.

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Publication Date
Tue Dec 07 2021
Journal Name
2021 14th International Conference On Developments In Esystems Engineering (dese)
Content Based Image Retrieval Based on Feature Fusion and Support Vector Machine
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Publication Date
Wed Mar 29 2023
Journal Name
Journal Of Robotics
Real-Time SLAM Mobile Robot and Navigation Based on Cloud-Based Implementation
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This study investigates the feasibility of a mobile robot navigating and discovering its location in unknown environments, followed by the creation of maps of these navigated environments for future use. First, a real mobile robot named TurtleBot3 Burger was used to achieve the simultaneous localization and mapping (SLAM) technique for a complex environment with 12 obstacles of different sizes based on the Rviz library, which is built on the robot operating system (ROS) booted in Linux. It is possible to control the robot and perform this process remotely by using an Amazon Elastic Compute Cloud (Amazon EC2) instance service. Then, the map to the Amazon Simple Storage Service (Amazon S3) cloud was uploaded. This provides a database

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Publication Date
Sat Jan 01 2022
Journal Name
Geotechnical Engineering And Sustainable Construction
Evaluation of Live Load Distribution Factors of a Highway Bridge
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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Engineering
Electrical Conductivity as a General Predictor of Multiple Parameters in Tigris River Based on Statistical Regression Model
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Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned

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Publication Date
Mon Feb 01 2021
Journal Name
Https://www.researchgate.net/journal/university-of-baghdad-engineering-journal-1726-4073
Electrical Conductivity as a General Predictor of Multiple Parameters in Tigris River Based on Statistical Regression Model
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Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned above, which is a very

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Publication Date
Wed Mar 01 2023
Journal Name
Journal Of Engineering
Effect of a Parked Car Orientation on a Temperature Distribution and Cooling Load Calculation: Experimental Study
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When a vehicle is left parked in the sun for an extended period, the gathered heat causes damage to several interiors within the cabin and causes discomfort for people and animals left inside the car. In the present work, the effect of the orientation of a parked white minibus on temperature distribution and cooling load calculation is studied experimentally in an open environment. Two different cases were studied facing south and facing east. For several hours, the temperature inside the car cabin had been monitored and measured at five separate locations. The cooling load calculations are carried out based on the experimental measurements. The results show that the overheating of parked cars always happens as a result

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Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Comparison of Maximum Likelihood and some Bayes Estimators for Maxwell Distribution based on Non-informative Priors
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In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two different loss functions, the squared error loss function and the modified squared error loss function for comparison purpose. A simulation study has been developed in order to gain an insight into the performance on small, moderate and large samples. The performance of these estimators has been explored numerically under different conditions. The efficiency for the estimators was compared according to the mean square error MSE. The results of comparison by MSE show that the efficiency of Bayes est

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Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Comparison of Maximum Likelihood and some Bayes Estimators for Maxwell Distribution based on Non-informative Priors
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In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two different loss functions, the squared error loss function and the modified squared error loss function for comparison purpose. A simulation study has been developed in order to gain an insight into the performance on small, moderate and large samples. The performance of these estimators has been explored numerically under different conditions. The efficiency for the estimators was compared according to the mean square error MSE. The results of comparison by MSE show that the efficiency of B

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Publication Date
Thu Jun 29 2023
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Recognition of Upper Limb Movements Based on Hybrid EEG and EMG Signals for Human-Robot Interaction
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Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
SDPLL-Based Frequency Estimation of a Sinusoid in Colored Noise
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The problem of frequency estimation of a single sinusoid observed in colored noise is addressed. Our estimator is based on the operation of the sinusoidal digital phase-locked loop (SDPLL) which carries the frequency information in its phase error after the noisy sinusoid has been acquired by the SDPLL. We show by computer simulations that this frequency estimator beats the Cramer-Rao bound (CRB) on the frequency error variance for moderate and high SNRs when the colored noise has a general low-pass filtered (LPF) characteristic, thereby outperforming, in terms of frequency error variance, several existing techniques some of which are, in addition, computationally demanding. Moreover, the present approach generalizes on existing work tha

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