Search Results - (( wave classification learning algorithm ) OR ( java application mining algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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Machine learning approach for stress detection based on alpha-beta and theta-beta ratios of EEG signals by Altaf, Hunain, Ibrahim, Siti Noorjannah, Mohd Azmin, Nor Fadhillah, Asnawi, Ani Liza, Walid, Balqis Hanisah, Harun, Noor Hasmiza

“…This study will ultimately contribute to society's development with improved robust machine learning algorithm for binary classification.…”
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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

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Assessment of cognitive load using multimedia learning and resting states with deep learning perspective by Qayyum, A., Faye, I., Malik, A.S., Mazher, M.

“…It is a well-understood fact that the brain activity increases with the increased demand of cognition. The deep learning algorithm based on Pre-trained convolutional neural network (CNN) networks have been used as a transfer learning for the classification of rest and cognitive states and also assessed the cognitive load using brain waves particularly alpha wave. …”
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Empirical Analysis of Intra vs. Inter-Subject Variability in VR EEG-Based Emotion Modelling by N.S. Suhaimi, J. Teo, J. Mountstephens

“…The highest subject-dependent classification accuracy achieved was 97.9% while the highest subject-independent classification accuracy obtained was 91.4% throughout the brain wave spectrum (α, β, γ, δ, θ). …”
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Earthquake multi-classification detection based velocity and displacement data filtering using machine learning algorithms by Murti M.A., Junior R., Ahmed A.N., Elshafie A.

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Comparative study of informative acoustic features for VTOL UAV faulty prediction using machine learning by Mohd Sani, Fareisya Zulaikha, Makhtar, Siti Noormiza, Mohd Nor, Elya, Kamarudin, Nur Diyana, Md Ali, Syaril Azrad, Md Ali, Kurnianingsih

“…The propeller faulty conditions are predicted based on informative features extracted from statistical time domain parameters of three audio wave features. Pitch, zero-crossing and short-time energy are selected as the significant audio features for the machine learning classification algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

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Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification by Al-Sharhan, Salah, Bimba, Andrew

“…EEG signal analysis involves multi-frequency non-stationary brain waves from multiple channels. Segmenting these signals, extracting features to obtain the important properties of the signal and classification are key aspects of detecting epileptic seizures. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Complexity Analysis of EEG in Patients With Social Anxiety Disorder Using Fuzzy Entropy and Machine Learning Techniques by Al-Ezzi, A., Al-Shargabi, A.A., Al-Shargie, F., Zahary, A.T.

“…The main objective of this study is to analyze the electroencephalogram (EEG) complexity of 88 SAD subjects, subdivided into 4 balanced groups (22 severe, 22 moderate, 22 mild, and 22 healthy controls (HCs) using Fuzzy Entropy measure (FE) and machine learning algorithms. In addition, this study aimed at designing a computer-aided diagnosis system to identify the severity of SAD (severe, moderate, mild, and HC) in different EEG frequency bands (delta, theta, alpha, and beta). …”
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Detection of the river sediment deposition area at Kuala Perlis river mouth using Landsat 8 OLI within the years 2019, 2020 and 2021 / Nur Zakira Ain Zamrun by Zamrun, Nur Zakira Ain

“…Therefore, this study aimed to compare the best method for foreseeing river sediment deposition between K-Means unsupervised image classification machine learning and water spectral indices (MNDWI) to analyze the areas most influenced by deposited river sediments from the clustered images. …”
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Beyond Sentiment Analysis: A Review of Recent Trends in Text Based Sentiment Analysis and Emotion Detection by Lai Po Hung, Suraya Alias

“…The trend of text-based emotion detection has shifted from the early keyword-based comparisons to machine learning and deep learning algorithms that provide more flexibility to the task and better performance.…”
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Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems by Manap, Zahariah

“…The key attributes that establish the classification learning sessions are the channel parameters extracted from the ray tracing generated multipath signals. …”
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Development of an automated detector and counter for bagworm census by Ahmad, Mohd Najib

“…The development of an image processing algorithm for detection and counting of Metisa plana Walker, a species of Malaysia’s local bagworm using image segmentation was proposed as it was found to be better than the thermal approach after some preliminary field tests. …”
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