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REVIEWING THE IMPLICATIONS OF TRAINING FOR ACADEMIC ADMINISTRATION STAFF AT CENTRAL MICHIGAN UNIVERSITY
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Training has an effect on employees’ performances. Accordingly, the person who is responsible for employees’ development must figure out the most effective way to train and develop employees. Central Michigan University (CMU) has recognized the importance of providing appropriate training for employees who have a duty in advising students. The reason is that these employees have a significant impact on students’ educational performances. Thus, special attention to this category of employees is needed to improve advising quality. This research attempted to explore the impact of training on academic advising at CMU. Face-to-face interviews and online surveys were used as data collection tools for this study. The study scope consisted of professional and administrative employees who provide academic advising for students and two employees who provide academic advising for students in the MSA department. The primary question asked, what are the impacts of training on academic advisors at CMU? From the data collection, we found out that training had a major role in increasing the performance of professional and administrative employees when they served in an academic advising capacity. However, there were obstacles that the employees believed should be addressed, including unequal chances to receive training, inconsistent training, a focus on certain skills while others were ignored, a lack of trainers, problems in scheduling enough training time, lack of resources for maintaining policy awareness. Thus, this study provided recommendations to eliminate the negative outcomes of those obstacles. we suggested applying practices such as performing needs assessment for employees, evaluating training outcomes, presenting equal opportunities for receiving training, and providing available resources for employees to stay updated on the policy.  

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Publication Date
Wed Sep 01 2021
Journal Name
Expert Systems With Applications
A long short-term recurrent spatial-temporal fusion for myoelectric pattern recognition
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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Mon Oct 30 2023
Journal Name
Traitement Du Signal
A Comprehensive Review on Machine Learning Approaches for Enhancing Human Speech Recognition
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
IFFT-Based Microwave Non-Destructive Testing for Delamination Detection and Thickness Estimation
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Publication Date
Mon Aug 01 2022
Journal Name
Water, Air, & Soil Pollution
Cladophora Algae Modified with CuO Nanoparticles for Tetracycline Removal from Aqueous Solutions
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Modified algae with nano copper oxide (CuO) were used as adsorption media to remove tetracycline (TEC) from aqueous solutions. Functional groups, morphology, structure, and percentages of surfactants before and after adsorption were characterised through Fourier-transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Several variables, including pH, connection time, dosage, initial concentrations, and temperature, were controlled to obtain the optimum condition. Thermodynamic studies, adsorption isotherm, and kinetics models were examined to describe and recognise the type of interactions involved. Resultantly, the best operation conditions were at pH 7, contact time

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of King Saud University - Science
Three iterative methods for solving second order nonlinear ODEs arising in physics
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Publication Date
Wed Apr 28 2021
Journal Name
Journal Of Engineering
A Ultra-broadband Thin Metamaterial Absorber for Ku and K Bands Applications
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In this paper, a design of the broadband thin metamaterial absorber (MMA) is presented. Compared with the previously reported metamaterial absorbers, the proposed structure provides a wide bandwidth with a compatible overall size. The designed absorber consists of a combination of octagon disk and split octagon resonator to provide a wide bandwidth over the Ku and K bands' frequency range. Cheap FR-4 material is chosen to be a substate of the proposed absorber with 1.6 thicknesses and 6.5×6.5 overall unit cell size. CST Studio Suite was used for the simulation of the proposed absorber. The proposed absorber provides a wide absorption bandwidth of 14.4 GHz over a frequency range of 12.8-27.5 GHz with more than %90 absorp

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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Serum CXCL 9 as a Potential Biomarker for Patients with Ulcerative Colitis
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Background: Ulcerative colitis (UC) is an inflammatory bowel disease restricted to the large intestine, characterized by superficial ulceration. It is a progressive and chronic disease requiring long-term treatment. Although its etiology remains unknown, it is suggested that environmental factors influence genetically susceptible individuals, leading to the onset of the disease. (C-X-C) ligand 9 is a chemokine that belongs to the CXC chemokine family, it plays a role in the differentiation of immune cells such as cytotoxic lymphocytes, natural killer T cells, and macrophages. Its interaction with its corresponding receptor CXCR3 which is expressed by a variety of cells such as effector T cells, CD8+ cytotoxic T cells, and macrophage

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Publication Date
Sun Mar 28 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
A Light Weight Multi-Objective Task Offloading Optimization for Vehicular Fog Computing
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Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mo

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Constructing a Software Tool for Detecting Face Mask-wearing by Machine Learning
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       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific

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