Theory of the norm-induced metric in atmospheric dynamics by Koh, Tieh-Yong, Wan, F.

“…The approach is based on the rigorous mathematics of normed vector spaces and the law of energy conservation in physics. …”
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Development of novel attention galibration protocols for EEG-based BCI system by Tchen, Jee Ern

“…The collected data from calibration will be used to train a support-vector machine (SVM), which will provide real-time classification of the user’s attention states. …”
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The interaction problem of two Zener–Stroh cracks with a nearby inhomogeneity by Fan, M., Xiao, Zhongmin, Zhang, Yanmei

“…The influence of material properties, crack–crack positions and other parameters, such as crack length and Burgers vector of the Zener–Stroh crack, on the target crack tip stress intensity factor, plastic zone size and crack tip opening displacement are examined. …”
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Evaluation of three potential machine learning algorithms for predicting the velocity and turbulence intensity of a wind turbine wake by Purohit, Shantanu, Ng, Eddie Yin Kwee, Ijaz Fazil Syed Ahmed Kabir

“…In this paper, three machine learning (ML) algorithms, Support Vector Regression (SVR), Artificial Neural Networks (ANN), and Extreme Gradient Boosting (XGBoost), are validated to estimate the velocity and turbulence intensity of a wind turbine's wake at distinct downstream distances. …”
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Detection & classification of diabetes type II & diabetes neuropathy using foot images by Chen, Yun Xuan.

“…After the reduction of the data with the help of Principle Component Analysis (PCA), the data is being fed into the classifiers, Gaussian Mixture Model (GMM) and Support Vector Machine (SVM). Thereafter, Graphic User Interface (GUI) in Matlab is applied. …”
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Using deep learning for studying spread-F in the ionosphere by Luwanga, Christopher

“…The methods explored in this work include Support Vector Machines and convolutional neural networks (CNN). …”
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Classification of normal and malignant ventricular arrhythmia ECG rhythms using machine learning tools by Prabhakaran, Sahithya

“…The deep residual Convolutional Neural Network (CNN) achieved the highest accuracy of 0.967 as compared to the deep residual CNN with transfer learning and VFPred, which is a fusion of signal processing and Support Vector Machine (SVM). Despite its high performance in accuracy, it fell short in terms of F1 score and recall, with VFPred achieving the highest F1 score of 0.877. …”
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Development of client server AI services with Mac OS by Ng, Alexander Rui Hao

“…Image searching is performed using a KNN vector search on the feature embeddings.…”
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Defending against phishing attacks by Tan, Justin Jui Kit

“…Key models, including Support Vector Machine (SVM), Random Forest, Gradient Boosting, and K-Nearest Neighbors (KNN), were applied to identify distinct URL features indicative of phishing behavior. …”
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Screening for interaction domain in vault nanocapsules by Vania, Maya

“…We constructed four plasmids in E. coli expression vector pET-11a and pET-28a encoding MVP domain 3-4, 3-5, 2-5 and mCherry fused with mINT. …”
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Creating a visual music interface via emotion detection by Lim, Clement Shi Hong.

“…By exploiting the use of short-time analysis techniques together with the Support Vector Machine Classifier, it is possible to classify music based on emotions. …”
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Platform development for control of induction machine (Part II control algorithm verification) by Kang, Jia Yi

“…In addition two different commonly used modulation technique, Space Vector Pulse width modulation (SVPWM) and Sinusoidal Pulse Width modulation(SPWM) will be employed in driving the motor and their difference will be investigated and compared. …”
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Heart murmurs detection techniques by Wong, Zhen Kang

“…These techniques helped to improve the accuracy of the classification by transforming the features obtained to a set of principal components and removing the lesser linearly separable features respectively. Support Vector Machine were then used as the classifier in this project to classify the result, and subsequently used to process the accuracy, specificity and the sensitivity of the algorithm. …”
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Building a low cost advanced driver assistance system : human detection by Tan, Yan Ling

“…For this project, the detection system making use of Histogram of Oriented Gradient (HOG) feature descriptor, alongside with Support Vector Machine (SVM) classifier would be studied. …”
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EEG-based emotional stress recognition using deep learning techniques by Lai, Michelle Wei Ting

“…We will be comparing the accuracies of Support Vector Machine (SVM) subject dependent and CNN subject dependent. …”
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Recent advances in chitosan-based carriers for gene delivery by Cao, Ye, Tan, Yang Fei, Wong, Yee Shan, Liew, Melvin Wen Jie, Venkatraman, Subbu

“…Over the years, efforts have been dedicated to develop efficient gene delivery vectors to overcome these systemic barriers. Chitosan, a versatile polysaccharide, is an attractive non-viral vector material for gene delivery mainly due to its cationic nature, biodegradability and biocompatibility. …”
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Learning Bregman distance functions for semi-supervised clustering by Wu, Lei., Hoi, Steven C. H., Jin, Rong., Zhu, Jianke., Yu, Nenghai.

“…It aims to learn a Bregman distance function using a nonparametric approach that is similar to Support Vector Machines. We emphasize that the proposed scheme is more general than the conventional approach for distance metric learning, and is able to handle high-dimensional data efficiently. …”
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Threat intelligence using machine learning packet dissection by Sowinski-Mydlarz, Viktor, Li, Jun, Ouazzane, Karim, Vassilev, Vassil

“…Four machine learning models, i.e., Neural Networks, Support Vector Machines, Logistic Regression and Linear Regression, are applied respectively to calculate the probability of suspicious packets. …”
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Degradation monitoring and characterization in lithium-ion batteries via the asymptotic local approach by Couto, LD, Reniers, J, Zhang, D, Howey, DA, Kinnaert, M

“…Model parameter changes induce changes in the mean of the residual vector which is asymptotically normally distributed with a specified variance. …”

Developing a Framework of Measuring Course Summative Assessment for A Big Classroom (S/O 13870) by Ahmad Mustaffa, Nurakmal, Zulkifli, Malina, Indra@ Murat, Rusdi

“…A study was conducted on a service course of Elementary Statistics in Universiti Utara Malaysia.CLOs’ scores were calculated and analyzed on the results of 110 students in one semester using three different methods: Average, Threshold and Performance Vector. The achievement of CLOs is then grouped and tabulated in a Course Performance Report for assessing students’ performance in the course. …”
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