Search Results - (( course evaluation based algorithm ) OR ( text classification matching algorithm ))
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Converged Classification Network For Matching Cost Computation
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An Ar Natural Marker Similarities Measurement Algorithm For E-Biodiversity
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Non-fiducial based electrocardiogram biometrics with kernel methods
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Android Mobile Malware Classification Based on System Call and Permission Using Tokenization
Published 2024thesis::master thesis -
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Iban Plaited Mat Motif Classification using Adaptive Smoothing
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Automated study plan generator using rule-based and knapsack problem
Published 2022“…A quantitative methodology through expert’s reviews and questionnaire survey was conducted to evaluate the accuracy of the proposed algorithm. The proposed algorithm shows high accuracy. …”
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Using algorithmic taxonomy to evaluate lecturer workload
Published 2006“…Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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Using web questionnaire for web-based course evaluation: advantages and disadvantages
Published 2017“…This article examines some advantages and disadvantages of conducting Web survey research especially for Web-based course evaluation at Iranian university E-learning centers. …”
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Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal
Published 2006“…Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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A new mobile malware classification for call log exploitation
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Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal
Published 2006“…Lecturer workload at universities includes three major categories: teaching, research and services.Teaching workload is influence by various factors such as level taught courses, number of student, credit and contact hour and off campus or on campus course design.The UPM has a KM Portal that contains sets of metadata on lecturer profile and knowledge assets.The Lecturer profile contains information lecturer teaching, research, publication and many more.We constructed an algorithmic taxonomy based at the lecturer profile data to measure lecturer teaching workload.This method measures the lecturer teaching workload.The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset.Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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