Search Results - (( data normalization based algorithm ) OR ( data extraction sensor algorithm ))
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Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks
Published 2014“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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Conference or Workshop Item -
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Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak
Published 2020“…Four traits was discovered namely spine, pelvis, knee and ankle. Next, data collection of normal and anomalous behaviour is collected using Kinect sensor. …”
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Vision-Based Autonomous Vehicle Driving Control System
Published 2005“…A completely autonomous vehicle is one in which a computer performs all the tasks that the human driver normally would. However, this study only focuses on driving control system that based on vision sensor. …”
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Vision-based autonomous vehicle driving control system
Published 2005“…A completely autonomous vehicle is one in which a computer performs all the tasks that the human driver normally would. However, this study only focuses on driving control system that based on vision sensor. …”
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Human activity and posture classification using smartphone sensors and Matlab mobile
Published 2022“…Motion signals from three subjects are measured, data is preprocessed using a filtering technique, features are extracted, feature normalization is used to reduce bias in data measurement, and activities are classified. …”
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Proceeding Paper -
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Correlation-based subset evaluation of feature selection for dynamic Malaysian sign language
Published 2016“…In this study, the images has been captured using a kinect sensor based skeletal algorithms. The feature extraction was done by normalizing the position and size of the user, by taking eight out of 20 joints that contribute in identifying the movement of the hands; left hand, right hand, left wrist, right wrist, left elbow, right elbow, torso and head. …”
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Abstract data extraction and reformation for IoT
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Final Year Project / Dissertation / Thesis -
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Wavelet-Based Fractal Analysis of rs-fMRI for Classification of Alzheimer�s Disease
Published 2022“…The classification algorithm developed based on the nonfractal connectivity feature and support vector machine classifier has shown an excellent performance, with an accuracy of 90.3 and 83.3 for the XHSLF dataset and ADNI dataset, respectively. …”
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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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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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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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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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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…To make the sensor more reliable, temperature data must be collected over the length of the cable, or distributed data rather than point data. …”
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Jogging activity recognition using k-NN algorithm
Published 2022“…Jogging activity recognition using the k-NN algorithm is a system that can help users collect information data of user speed movement using speed sensor and give the classification of jogging activity to the user. …”
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Academic Exercise -
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Improving Prediction Accuracy and Extraction Precision of Frequency Shift from Low-SNR Brillouin Gain Spectra in Distributed Structural Health Monitoring
Published 2023“…Brillouin scattering; Concretes; Curve fitting; Data handling; Extraction; Fiber optic sensors; Fiber optics; Learning algorithms; Machine learning; Structural health monitoring; BOTDA; Brillouin frequency shift extraction; Brillouin frequency shifts; Brillouin gain spectrum; Correlation techniques; Distributed fiber-optic sensors; Frequency shift; Generalized linear model; Low signal-to-noise ratio; Prediction accuracy; Signal to noise ratio; algorithm; fiber optics; noise; signal noise ratio; Algorithms; Fiber Optic Technology; Noise; Signal-To-Noise Ratio…”
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Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke
Published 2019“…This is further worsen by the use of single sensors modality and machine learning algorithms. …”
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Design and development of prototype robot gripper for object weight measurement
Published 2014“…The proposed work also includes the development of new algorithm for data extraction and signal conditioning analysis that will be loaded into the microcontroller system. …”
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Autonomous road roundabout detection and navigation system for smart vehicles and cities using laser simulator–fuzzy logic algorithms and sensor fusion
Published 2020“…A real-time roundabout detection and navigation system for smart vehicles and cities using laser simulator–fuzzy logic algorithms and sensor fusion in a road environment is presented in this paper. …”
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