Search Results - (( java application sensor algorithm ) OR ( knowledge evaluation using algorithm ))
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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Article -
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Design Of Robot Motion Planning Algorithm For Wall Following Robot
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Monograph -
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Using algorithmic taxonomy to evaluate lecturer workload
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Human activity recognition via accelerometer and gyro sensors
Published 2023“…To implement the data engineering system proposed, two mobile applications, SensorData and SensorDataLogger with user-friendly interfaces and intuitive functionalities are developed using Java programming language and Android Studio. …”
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Final Year Project / Dissertation / Thesis -
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Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall
Published 2013“…The performance of the training algorithms was evaluated using standard performance evaluation measures—root mean square error, coefficient of efficiency, and the time and number of epochs required to reach a predefined accuracy. …”
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Citation Index Journal -
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Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal
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Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal
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Reliability fuzzy clustering algorithm for wellness of elderly people
Published 2019“…Thus, the objective of this paper is to propose a reliable fuzzy clustering algorithm using z-numbers. This model will demonstrate the capability to handle the knowledge of human being and uncertain information in evaluating the wellness of chronic kidney disease (CKD) patients. …”
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A new multiple ant colonies optimization algorithm utilizing average pheromone evaluation mechanism
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Disparity between theory & practice beyond the worst-case competitive analysis
Published 2019“…In an online problem, the algorithms is presented with a sequence on input in a serial fashion such that the algorithm does not have knowledge about the future inputs. …”
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Proceeding Paper -
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Classification models for higher learning scholarship award decisions
Published 2018“…Each model was evaluated using technical evaluation metric, such contingency table metrics, and accuracy, precision, and recall measures. …”
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Hybrid subjective evaluation method using weighted subsethood - based (WSBA) rule generation algorithm
Published 2013“…The use of fuzzy rules, which were extracted directly from input data through Weighted Subsethood-based (WSBA) Rule Generation Algorithm.WSBA rule generation use the subsethood values to generate the weights which finally produced the fuzzy general rules.The rules generated through the data provided knowledge in developed fuzzy rule The fuzzy rules embedded in the framework of subjective evaluation method showed advantages in generalizing the evaluation of the performance achievement, where the evaluation process can be conducted consistently in producing good evaluation results with the use of the membership set score.The results from the numerical examples are comparable to other fuzzy evaluation methods, even with the use of small rule size.…”
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An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions
Published 2025“…AI in KMS is used in the knowledge creation process. The Bert2Bert model is used in the multi-document summarisation of Indonesian language knowledge in the knowledge combination process. …”
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Thesis -
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Hybrid subjective evaluation of rule Exraction Algorithm using Weighted Subsethood-Based (WSBA)
Published 2013“…Fuzzy rules are important elements that being highlighted in any fuzzy expert system.This research proposes the framework of subjective performance evaluation using fuzzy technique for ranking the performance of the financial performance of a company under a multi criteria environment.There are a lot of techniques used such as fuzzy similarity function, fuzzy synthetic decision and satisfaction function have been adopted.The framework is based on fuzzy multi-criteria decision-making that consists of fuzzy rules.The use of fuzzy rules, which were extracted directly from input data through Weighted Subsethood-based (WSBA) Rule Generation Algorithm.WSBA rule generation use the subsethood values to generate the weights which finally produced the fuzzy general rules.The rules generated through the data provided knowledge in developed fuzzy rule The fuzzy rules embedded in the framework of subjective evaluation method showed advantages in generalizing the evaluation of the performance achievement, where the evaluation process can be conducted consistently in producing good evaluation results with the use of the membership set score.The results from the numerical examples are comparable to other fuzzy evaluation methods, even with the use of small rule size.…”
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Conference or Workshop Item -
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Evaluation of fall detection classification approaches
Published 2012“…The acceleration data with a total data of 6962 instances and 29 attributes were used to evaluate the performance of the different classification algorithm. …”
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A Mobile Application For Stock Price Prediction
Published 2021“…These prediction algorithms were evaluated using 6 sectors of Bursa Malaysia stocks which are in total 216 stocks. …”
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Final Year Project / Dissertation / Thesis -
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Thesis -
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…Accordingly, the corresponding genetic operators are adapted to suite the medoid and to incorporate much clustering-specific domain knowledge. The algorithm is also preceded with careful seeding using mathematically proved to converge k-means++ algorithm. …”
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Thesis -
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