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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
Tue Nov 01 2022
Journal Name
2022 International Conference On Data Science And Intelligent Computing (icdsic)
An improved Bi-LSTM performance using Dt-WE for implicit aspect extraction
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In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

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Publication Date
Mon Aug 01 2022
Journal Name
Water, Air And 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
Fri Jan 01 2021
Journal Name
Agrosystems, Geosciences & Environment
Cover crop influence on soil water dynamics for a corn–soybean rotation
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Abstract<p>Crop production is reduced by insufficient and/or excess soil water, which can significantly decrease plant growth and development. Therefore, conservation management practices such as cover crops (CCs) are used to optimize soil water dynamics, since CCs can conserve soil water. The objective of this study was to determine the effects of CCs on soil water dynamics on a corn (<italic>Zea mays</italic> L.)–soybean [<italic>Glycine max</italic> (L.) Merr.] rotation at three soil depths over 3 yr. The study was conducted at the Chariton County Cover Crop Soil Health Research and Demonstration Farm (CCSH) in Missouri. Initial CC establishment occurred in 2012. Volumetric soil water </p> ... Show More
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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Tue Jun 15 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Natural Products as A Promising Therapy for SARS COV-2; An Overview
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Recently emerging pandemic SARS CoV-2 conquered our world since December 2019. Continuous efforts have been done to find out effective immunization and precise treatment stetratigies A way from therapeutic options that were tried in SARS CoV-2, an increased attention is directed to predict natural products and mainly phytochemicals as collaborative measures for this crisis. In this review, most of the mentioned compounds specially flavonoids (biacalin, hesperidin, quercetin, luteolin,, and phenolic (resveratrol, curcumin, and theaflavin) exert their effect through interfering with the action of one or more of this proteins (spike protein, papain like protease, 3 chymotrypsin like cysteine protease, and RNA dependent RNA 

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Publication Date
Wed Mar 01 2023
Journal Name
Results In Engineering
Low-cost autonomous car level 2: Design and implementation for conventional vehicles
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Publication Date
Mon Feb 05 2052
Journal Name
Partial Differential Equations In Applied Mathematics
A hybrid analytical method for fractional order Klein–Gordon and Burgers equations
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Publication Date
Thu Jan 02 2020
Journal Name
Journal Of The College Of Languages (jcl)
Iranian Jews’ Customs and Traditions in The Works of Dorrit Rabinyan (A Study in The Alley of Almond Bushes in Omerijan ): מסורת ומנהגים יהודי אירן ביצירותה של דורית רביניאן " עיון ברומן סמטת השקדות בעומריג'אן "
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The orient culture and heritage has directly influenced ,in a way or another , the literary works which recently have been noted by the oriental  Jews inside and outside of Israel. Several Jewish writers, who came from the orient  (especially from Iran ), have written their works while influenced by traditions and customs of the Iranian society, in which they were born , lived , and raised, and by the writers who were born in that society and then moved to Israel and lived there as a result of the Zionism and its notorious promises to gather Jewish people from all over the world to establish their national home at the expense of the Palestinian   land and people.

       That final

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