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Direct approach for mining association rules from structured XML data
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The RNN was used to detect patterns present in satellite image. A novel feature extraction algorithm was developed to extract the feature vectors. …”
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Analysis of Traffic Accident Patterns Using Association Rule Mining
Published 2024“…This study also demonstrated the practicality of the apriori algorithm in analyzing extensive datasets to extract actionable insights. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…A multi-objective feature technique is developed in this study to extract the most influential subsets of input variables with the maximum relevancy and minimum redundancy. …”
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Antidepressant Treatment Response Prediction With Early Assessment of Functional Near-Infrared Spectroscopy and Micro-RNA
Published 2025“…To address this, the aim of the current study is to investigate MDD ATR at three response levels using fNIRS and micro-ribonucleic acids (miRNAs). Our proposed algorithm includes a custom inter-subject variability reduction based on the principal component analysis (PCA). …”
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Development Of Semi-Automatic Liver Segmentation Method For Three-Dimensional Computed Tomography Dataset
Published 2017“…Low contrast of liver boundary with neighbouring organs, high shape variability of liver and presence of various liver pathologies will affect the accuracy of automatic liver segmentation and thus make automatic liver segmentation a challenging task. …”
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Monograph -
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Spectral and prosodic feature extractions for classical Arabic accents recognition among Malay speakers / Noor Jamaliah Ibrahim
Published 2021“…The variability of speech patterns produced by individuals is unique. …”
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Thesis -
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Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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Skyline queries on data with uncertain dimensions for efficient computation
Published 2018“…The effect of manipulating the independent variables is studied on the dependent variables which are number of pairwise comparisons and processing time. …”
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Development of sorting system for oil palm in vitro shoots using machine vision approach
Published 2014“…Ultimately, the sorting algorithm performance came to be evaluated by support vector machine algorithm. …”
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An efficient and lightweight detection method for stranded elastic needle defects in complex industrial environments using VEE-YOLO
Published 2025“…Precise integration of spatial structural and channel information further enhanced the model’s overall feature extraction capability. Finally, EIoU Loss replaced CIoU Loss to address bounding box aspect ratio variability and sample imbalance challenges, significantly improving overall detection task performance. …”
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Detection and Classification of Moving Objects for an Automated Surveillance System
Published 2006“…Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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