Search Results - data extraction ((sensor algorithm) OR (means algorithm))
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1
Improved measurement of blood pressure by extraction of characteristic features from the cuff oscillometric waveform
Published 2015“…We present a novel approach to improve the estimation of systolic (SBP) and diastolic blood pressure (DBP) from oscillometric waveform data using variable characteristic ratios between SBP and DBP with mean arterial pressure (MAP). …”
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ANALYSIS OF BIOSENSOR PHYSIOLOGICAL SIGNALS FOR ASSESSMENT OF NEUROLOGICAL STATUS
Published 2018“…All the data signals of the 20 subjects will then be processed with features extraction method using mean, maximum (Max), minimum (Min), mean absolute deviation (MAD), Standard deviation (STD), interquartile range (IQR) and summation (Sum). …”
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Final Year Project -
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Facial expression recognition using stretchable sensor and multilayer feedforward backpropagation neural network
Published 2025“…Statistical features including mean, root mean square (RMS), variance and standard deviation are extracted and used to train a multilayer feedforward backpropagation neural network algorithm in classifying four expressions: neutral, happy, sad, and disgust. …”
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Abstract data extraction and reformation for IoT
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Final Year Project / Dissertation / Thesis -
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Novel CE-CBCE feature extraction method for object classification using a low-density LiDAR point cloud
Published 2021“…However due to low computing capacity, complicated algorithms are incompatible to be performed on the device, with sparse information further limits the feature available for extraction. …”
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Internet of Things (IoT) based activity recognition strategies in smart homes: a review
Published 2022“…In this work, we focus our review on activity recognition implementation strategies by examining various sensors and sensing technologies used to collect useful data from IoT devices, reviewing preprocessing and feature extraction techniques, as well as classification algorithms used to recognize human activities in smart homes. …”
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Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin
Published 2016“…The result of this research show that nearly all image has accuracy more than 80% that prove that K-Means clustering algorithm are suitable as method for extracting meaningful information in images.…”
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Thesis -
8
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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An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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Thesis -
10
Optimized clustering with modified K-means algorithm
Published 2021“…Generally, the proposed modified k-means algorithm is able to determine the optimum number of clusters for huge data.…”
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Thesis -
11
Pattern Discovery Using K-Means Algorithm
Published 2024“…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
Proceedings Paper -
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An efficient fuzzy C-least median clustering algorithm
Published 2021“…Clustering is a kind of unsupervised data mining technique which describes general working behavior, pattern extraction and extracts useful information from time series data. …”
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The classification of skateboarding trick manoeuvres: A K-nearest neighbour approach
“…An amateur skateboarder (23 years of age ± 5.0 years’ experience) executed five tricks for each type of trick repeatedly on a customized ORY skateboard (IMU sensor fused) on a cemented ground. A number of features were extracted and engineered from the IMU data, i.e., mean, skewness, kurtosis, peak to peak, root mean square as well as standard deviation of the acceleration and angular velocities along the primary axes. …”
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Pattern discovery using k-means algorithm
Published 2014“…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
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Conference or Workshop Item -
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Correlation-based subset evaluation of feature selection for dynamic Malaysian sign language
Published 2016“…One factor is the quality of the data or information held. The process of data model extraction will be more difficult if the information held is irrelevant or contains redundancies, or if the data obtained contains high noise. …”
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17
Clustering of rainfall data using k-means algorithm
Published 2019“…Clustering algorithms in data mining is the method for extracting useful information for a given data. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…Order of input data and rescaling the input data for standardization influence K-Means in giving accurate results. …”
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Thesis -
19
A systematic literature review on outlier detection in wireless sensor networks
Published 2020“…Therefore, an efficient local/distributed data processing algorithm is needed to ensure: (1) the extraction of precise and reliable values from noisy readings; (2) the detection of anomalies from data reported by sensors; and (3) the identification of outlier sensors in a WSN. …”
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Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data
Published 2023“…Automatic indexing; Big data; Cluster analysis; Extraction; Factorization; Indexing (of information); Information retrieval; K-means clustering; Natural language processing systems; Open source software; Open systems; Pattern matching; Software quality; Software testing; Text mining; Hadoop; Key phrase extractions; Map-reduce; Pattern-matching technique; Porters; Pre-processing algorithms; Software environments; Unlabeled; Matrix algebra…”
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