Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes by Bosschieter, Tomas M., Xu, Zifei, Lan, Hui, Lengerich, Benjamin J., Nori, Harsha, Painter, Ian, Souter, Vivienne, Caruana, Rich

“…We use an Explainable Boosting Machine (EBM), a high-accuracy glass-box learning method, for the prediction and identification of important risk factors. …”
Get full text

Transfer learning application on snake classification by Tananda, Hans

“…This is possible by applying machine learning methods to classify the snake images and creating a simple mobile application for public use. …”
Get full text

Aiding therapy using speech emotion recognition by Koh, En Rong

“…We will explore the use of a Convolutional Neural network, a type of Deep Learning method, to train and predict human emotions. …”
Get full text

Video surveillance for intelligent transportation system by Liu, Jiamin

“…Artificial Intelligence (AI) with matching learning method had been widely used in this field in recent years. …”
Get full text

Adaptive function modal learning neural networks by Kang, Miao

“…Modal learning method is a neural network learning term that refers to a single neural network which combines with more than one mode of learning. …”
Get full text

Exploring cultural competence through the 'humans of Malaysia project by Marof, Aini Azeqa

“…This experiential learning method provided students with a platform to apply essential social psychology concepts such as intergroup relations, contact theory, attribution, and attitude change in authentic, real-world environments. …”
Get full text

Medicine distribution pattern detection in pharmaceutical supply chains: a new Kth-proximity density-distance-based method by Delgoshaei, Aidin, Mohd Ariffin, Mohd Khairol Anuar

“…Originality/value: In this research, the machine learning method based on the nearest neighbor has been used for the first time in the design of the supply chain network.…”
Get full text

Minimum number of inertial measurement units needed to identify signiicant variations in walk patterns of overweight individuals walking on irregular surfaces by Sikandar, Tasriva, Rabbi, Mohammad Fazle, Kamarul Hawari, Ghazali, Altwijri, Omar, Almijalli, Mohammed, Ahamed, Nizam Uddin

“…We then used deep learning method to verify whether the IMU data recorded from the identified body locations could classify walk patterns across the surfaces. …”
Get full text
Get full text

Statistical modeling of fully nonlinear hydrodynamic loads on offshore wind turbine monopile foundations using wave episodes and targeted CFD simulations through active sampling by Guth, Stephen, Katsidoniotaki, Eirini, Sapsis, Themistoklis P.

“…The novelty of our framework lies in its efficient construction of the surrogate model, utilizing the Gaussian process regression machine learning technique and a Bayesian active learning method to sequentially sample wave episodes that contribute to accurate predictions of extreme hydrodynamic forces. …”
Get full text

Lane detection algorithm for autonomous vehicle using machine learning by Wu, Guan Jie

“…Hence, there is a need to shift from traditional computer vision algorithms to deep learning method in feature extraction. Convolution neural network (CNN) has been the de facto feature extraction module in computer vision. …”
Get full text

Reallocation of time between device-measured movement behaviours and risk of incident cardiovascular disease by Walmsley, R, Chan, S, Smith-Byrne, K, Ramakrishnan, R, Woodward, M, Rahimi, K, Dwyer, T, Bennett, D, Doherty, A

“…</p> <p><strong>Conclusion</strong> Machine-learning methods classified movement behaviours accurately in free-living accelerometer data. …”

The Effect Of Blended Learning And critical Thinking On Tertiary EFL Argumentative Writing In China by Wang, Yuling

“…With the rapid development of Information and Communications Technology (ICT), the blended learning method is widespread in English-as-a-Foreign-Language (EFL) instruction. …”
Get full text

Computer Supported Cooperative Work and Social Computing : 15th CCF Conference, ChineseCSCW 2020, Shenzhen, China, November 7-9, 2020, Revised Selected Papers / by CCF Conference on Computer Supported Cooperative Work and Social Computing (15th : 2020 : Shenzhen, China), organiser 642953, Sun, Yuqing, editor 642954, Liu, Dongning, editor 642955, Liao, Hao, 1986-, editor 642956, Fan, Hongfei, editor 642957, Gao, Liping, editor 642958

Refining learning models in grammatical inference by Wang, Xiangrui

“…We introduce the use of recurrent neural networks (RNNs) and present a pruning learning method to avoid the exponential space costs. …”
Get full text

Factor modeling for clustering high-dimensional time series by Zhang, Bo, Pan, Guangming, Yao, Qiwei, Zhou, Wang

“…We propose a new unsupervised learning method for clustering a large number of time series based on a latent factor structure. …”
Get full text

Data-efficient modeling for power consumption estimation of quadrotor operations using ensemble learning by Dai, Wei, Zhang, Mingcheng, Low, Kin Huat

“…We employed an ensemble learning method, namely stacking, to develop a data-driven model using flight records of three different types of quadrotors. …”
Get full text

Robot programming using augmented reality by Chong, Jonathan Wun Shiung

“…The Piecewise Linear Parameterization (PLP) algorithm and a curve learning method based on Bayesian neural networks and reparameterization are proposed. …”
Get full text

Exploring disease axes as an alternative to distinct clusters for characterizing sepsis heterogeneity by Zhang, Zhongheng, Chen, Lin, Liu, Xiaoli, Yang, Jie, Huang, Jiajie, Yang, Qiling, Hu, Qichao, Jin, Ketao, Celi, Leo A., Hong, Yucai

“…The top-down transfer learning method (model trained on cohorts with greater severity was transferred to cohorts with lower severity score) had a higher NMI value than the bottom-up approach (median [Q1, Q3]: 0.64 [0.49, 0.78] vs. 0.23 [0.2, 0.31], p < 0.001). …”
Get full text

A Non‐Intrusive Machine Learning Framework for Debiasing Long‐Time Coarse Resolution Climate Simulations and Quantifying Rare Events Statistics by Barthel Sorensen, B., Charalampopoulos, A., Zhang, S., Harrop, B. E., Leung, L. R., Sapsis, T. P.

“…Here, the scope is to formulate a learning method that allows for correction of dynamics and quantification of extreme events with longer return period than the training data. …”
Get full text

Hermes: Boosting the Performance of Machine-Learning-Based Intrusion Detection System through Geometric Feature Learning by Zhang, Chaoyu, Shi, Shanghao, Wang, Ning, Xu, Xiangxiang, Li, Shaoyu, Zheng, Lizhong, Marchany, Randy, Gardner, Mark, Hou, Y. Thomas, Lou, Wenjing

Get full text