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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, khan

“…Dead-Stock (DS), Slow-Moving (SM) and Fast- Moving (FM) using K-means algorithm. In the second phase we have proposed Most Frequent Pattern (MFP) algorithm to find frequencies of property values of the corresponding items. …”
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Arabic Speaker Identification System for Forensic Authentication Using K-NN Algorithm by Abdulwahid S., Mahmoud M.A., Abdulwahid N.

Development of a syncope classification algorithm from physiological signals acquired in tilt-table test by Gan, Ming Hong

“…Features that selected for the classification is mean of systolic and diastolic blood pressure, standard deviation of real variability of diastolic blood pressure, and the mean of systolic blood pressure in low and high frequency ratio. …”
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Classification of basal stem rot disease in oil palm using dielectric spectroscopy by Al-Khaled, Al-Fadhl Yahya Khaled

“…First, features selection algorithms (genetic algorithm (GA), random forest (RF), and support vector machine-feature selection (SVM-FS)) were used to select the most significant frequencies. …”
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Electromyography signal processing based on time and time-frequency representations for prosthesis application by Mahdavi, Farzaneh Akhavan

“…Mean Absolute Value (MAV), Root Mean Square (RMS), Zero Crossing (ZC) and Waveform Length (WL) were employed as feature extraction techniques in time domain and Wavelet Transform (WT) was used in time-frequency domain. …”
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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, Khan

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Benchmarking performance of document level classification and topic modeling by Bhatti, Muhammad Shahid, Ullah, Azmat, Latip, Rohaya, Sohail, Abid, Riaz, Anum, Hassan, Rohail

“…Bagging and deep dense neural network outperformed the other algorithms. The experimental results show that deep dense achieves 92.0% mean f1 score, and Bagging 95.0% f1 score.…”
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Acoustic echo cancellation using adaptive filter for Quranic accent signals by Kamarudin, Noraziahtulhidayu, Al Haddad, Syed Abdul Rahman, Basiron, Azli, Hassan Azhari, Rauf

“…AP indicates 93.9% for all of the classification algorithm in used, while for LMS and RLS the results are differed varies on different pattern classification algorithm stated whereby with LMS and PPCA classification, 96.9 % for accuracy and 84.8% accuracy for LMS and KNN. …”
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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Mohd Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

“…In this study, the wavelet transform (WT) de-noising technique, linear spectral mean frequency ( meanF) and nonlinear multiscale fuzzy entropy ( MFE) features were used. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines by Nagi J., Yap K.S., Tiong S.K., Ahmed S.K., Nagi F.

“…The proposed hybrid DTMF detector scheme is based on power spectrum analysis by means of the Discrete Fourier Transform (DFT). The Goertzel's Algorithm is used to estimate the seven fundamental DTMF carrier frequencies. …”

REAL TIME ABNORMAL SOUND DETECTION AND CLASSIFICATION FOR HOME ENVIRONMENT by MOHAMED AMIN, SITI NUR AZIMAH

“…In this project, a system is designed to have abnormal sound detection and classification. For abnormal sound detection, mean signal approach being used while for classification process, there two main methods being used which are features extraction using Mel-Frequency Cepstral Coefficient (MFCC) and classifier using Gaussian Mixture Model (GMM). …”
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Acoustic echo cancellation using adaptive filtering algorithms for quranic accents (Qiraat) identification by Kamarudin, Noraziahtulhidayu, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Abushariah, Mohammad A. M., Hashim, Shaiful Jahari, Hassan Azhari, Abd Rauf

“…Based on our experimental results, the AP algorithm achieved 93.9 % accuracy rate against all pattern classification techniques including PPCA, KNN, and GMM. …”
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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

“…Classic bag of visual words algorithm is based on k-means clustering and every SIFT features belongs to one cluster and it leads to decreasing classification results. …”
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Classification of muscle fatigue during prolonged driving by Ab Ghafar, Noor Azlyn, Azmi, Nur Liyana, Md Nor, Khairul Affendy, Nordin, Nor Hidayati Diyana

“…The EMG signals and the time when muscle fatigue was experienced by the subjects were recorded. The mean frequency (MNF) and median frequency (MDF) of the EMG signals were extracted as dataset features. …”
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Development of gender and race recognition system using speech and recognition by using frequency spectrum by Ng Siew Fong

“…In this thesis, the development of an algorithm and system that is able to recognize gender and races by using the speech frequency spectrum is presented. …”
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The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…A new form of input which consists of scalogram and spectrogram images that represents both time and frequency domains , are then introduced in the classification of wink-based EEG signals. …”
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An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa by Md Isa, Amalina Izzati

“…Inclusive with the design of UFLS is a new module referred as Load Shedding Module (LSM). Two new algorithms i.e., Load Classification based Fuzzy Logic (LCFL) and Binary Evolutionary Programming (BEP) are introduced in the module. …”
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A Comparison Of The Different Algorithms For Essential Tremor And Parkinson’s Disease Tremor Differentiation Based On Hand Tremor by Boey, Keen Huang

“…To assist specialist in making decisions when diagnosing the tremor, a tremor monitoring and differential diagnosis system is implemented using a wireless inertia measurement unit, to collect hand tremor data from patients and perform classifications of tremor. Four different types of tremor classification algorithms, namely the Tremor Stability Index (TSI), Mean Harmonic Peak Power (MHPP), Relative Energy (RE) and Empirical Mode Decomposition – Singular Value Decomposition (EMD-SVD) analysis had been tested with 153 postural tremor recordings and 154 rest tremor recordings collected from ET and PD patients. …”
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Frequent patterns minning of stock data using hybrid clustering association algorithm by B., Baharudin, A., Khan, K., Khan

“…Dead-Stock (DS), Slow-Moving (SM) and Fast-Moving (FM) using K-means algorithm. In the second phase we have proposed Most Frequent Pattern (MFP) algorithm to find frequencies of property values of the corresponding items. …”
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