Search Results - (( developing function methods algorithm ) OR ( data extraction sensor algorithm ))
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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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Development of rheumatoid arthritis classification from electronic image sensor using ensemble method
Published 2020“…Over a long period of time, RA causes harm to the bone and cartilage of the joints, weakens the jointsâ�� muscles and tendons, eventually causing joint destruction. Sensors such as accelerometer, wearable sensors, and thermal infrared camera sensor are widely used to gather data for RA. …”
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Terahertz sensing analysis for early detection of ganoderma boninense disease using near infrared (NIR) spectrometer
Published 2023“…Spectral data are collected from 6 samples of inoculated and non-inoculated oil palm samples at nursery stages using an integrated NIRS sensor. …”
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Thesis -
4
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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Abstract data extraction and reformation for IoT
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Final Year Project / Dissertation / Thesis -
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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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7
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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8
Wavelet-Based Fractal Analysis of rs-fMRI for Classification of Alzheimer�s Disease
Published 2022“…The resting-state functional magnetic resonance imaging (rs-fMRI) modality has gained widespread acceptance as a promising method for analyzing a variety of neurological and psychiatric diseases. …”
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Abnormal data detection model based on autoencoder and random forest algorithm: camera sensor data in autonomous driving systems
Published 2025“…In the field of autonomous driving, abnormal data will directly affect the safety of autonomous driving systems, especially in terms of abnormal camera sensor data. …”
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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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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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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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Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study
Published 2019“…In this field, it was not possible to predict extractable P and K using all tested sensor combinations or algorithms. …”
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Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions
Published 2019“…These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
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Investigating optimal smartphone placement for identifying stairs movement using machine learning
Published 2023“…Specifically, this study focuses on investigating the optimal placement of smartphones to extract tri- axis accelerometer data from the inertial sensors during stair movement. …”
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Wearable Sensor Feature Fusion for Human Activity Recognition (HAR) : A Proposed Classification Framework
Published 2022“…Due to the extensive feature engineering and human feature extraction required by traditional machine learning algorithms, they are time consuming to develop. …”
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Proceeding
