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  1. 1

    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    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
  2. 2

    Smart fall detection by enhanced SVM with fuzzy logic membership function by Harum, Norharyati, Khalil, Mohamad Kchouri, Hazimeh, Hussein, Obeid, Ali

    Published 2023
    “…So far, the most widely used fall prediction methods collect data from inertial measurement unit (IMU) sensors. …”
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    Article
  3. 3

    Development of rheumatoid arthritis classification from electronic image sensor using ensemble method by Sharon, H., Elamvazuthi, I., Lu, C.-K., Parasuraman, S., Natarajan, E.

    Published 2020
    “…The data classification is accessed using holdout and 10-fold cross-validation evaluation methods. …”
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    Article
  4. 4

    A comparative study of vibrational response based impact force localization and quantification using radial basis function network and multilayer perceptron by Hossain, M.S., Ong, Z.C., Ismail, Z., Khoo, S.Y.

    Published 2017
    “…Time-domain peak-to-peak and peak arrival time features were extracted from accelerometer data to use as network inputs. …”
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    Article
  5. 5

    Terahertz sensing analysis for early detection of ganoderma boninense disease using near infrared (NIR) spectrometer by Mas Ira Syafila, Mohd Hilmi Tan

    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
  6. 6

    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid by Gaeid, Khalaf Salloum

    Published 2012
    “…The fault detection algorithm identifies the time and location of each fault. …”
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    Thesis
  7. 7

    Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak by Abd Razak, Hana'

    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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    Thesis
  8. 8

    Correlation-based subset evaluation of feature selection for dynamic Malaysian sign language by Sutarman, .

    Published 2016
    “…In this study, the images has been captured using a kinect sensor based skeletal algorithms. …”
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    Thesis
  9. 9
  10. 10

    Internet of Things (IoT) based activity recognition strategies in smart homes: a review by Babangida, Lawal, Perumal, Thinagaran, Mustapha, Norwati, Yaakob, Razali

    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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    Article
  11. 11

    Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

    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
  12. 12

    Wavelet-Based Fractal Analysis of rs-fMRI for Classification of Alzheimer�s Disease by Sadiq, A., Yahya, N., Tang, T.B., Hashim, H., Naseem, I.

    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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    Article
  13. 13

    A systematic literature review on outlier detection in wireless sensor networks by Safaei, Mahmood, Asadi, Shahla, Driss, Maha, Boulila, Wadii, Alsaeedi, Abdullah, Chizari, Hassan, Abdullah, Rusli, Safaei, Mitra

    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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    Article
  14. 14

    Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

    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. …”
    text::Thesis
  15. 15

    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

    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
  16. 16

    Improving Prediction Accuracy and Extraction Precision of Frequency Shift from Low-SNR Brillouin Gain Spectra in Distributed Structural Health Monitoring by Nordin N.D., Abdullah F., Zan M.S.D., Bakar A.A.A., Krivosheev A.I., Barkov F.L., Konstantinov Y.A.

    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…”
    Article
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    Design and development of prototype robot gripper for object weight measurement by Almassri, Ahmed M. M.

    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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    Thesis
  19. 19

    Autonomous road roundabout detection and navigation system for smart vehicles and cities using laser simulator–fuzzy logic algorithms and sensor fusion by Ali, Mohammed A. H., Musa, Mailah, Jabbar, Waheb A., Moiduddin, Khaja, Ameen, Wadea, Alkhalefah, Hisham

    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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    Article
  20. 20

    Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study by Wenjun, Ji, Adamchuk, Viacheslav I., Song, Chao Chen, Mat Su, Ahmad S., Ismail, Ashraf, Qianjun, Gan, Zhou, Shi, Biswas, Asim

    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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    Article