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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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). …”
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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. …”
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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

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Transfer-recursive-ensemble learning for multi-day COVID-19 prediction in India using recurrent neural networks by Chakraborty, Debasrita, Goswami, Debayan, Ghosh, Susmita, Ghosh, Ashish, Chan, Jonathan H., Wang, Lipo

“…Each of the four models then gives 7-day ahead predictions using the recursive learning method for the Indian test data. The final prediction comes from an ensemble of the predictions of the different models. …”
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Visual event recognition in videos by learning from web data by Duan, Lixin, Xu, Dong, Tsang, Ivor Wai-Hung, Luo, Jiebo

“…Second, we propose a new transfer learning method, referred to as Adaptive Multiple Kernel Learning (A-MKL), in order to 1) fuse the information from multiple pyramid levels and features (i.e., space-time features and static SIFT features) and 2) cope with the considerable variation in feature distributions between videos from two domains (i.e., web video domain and consumer video domain). …”
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Enhanced intrusion detection model based on principal component analysis and variable ensemble machine learning algorithm by John, Ayuba, Isnin, Ismail Fauzi, Madni, Syed Hamid Hussain, Muchtar, Farkhana

“…This paper proposes a variable ensemble machine learning method to solve the problem and achieve a low variance model with high accuracy and low false alarm. …”
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Speeding up deep neural network training with decoupled and analytic learning by Zhuang, Huiping

“…A fully decoupled learning method using delayed gradients (FDG) is first proposed which addresses all the three lockings. …”
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Transferring a deep learning model from healthy subjects to stroke patients in a motor imagery brain-computer interface by Nagarajan, Aarthy, Robinson, Neethu, Ang, Kai Keng, Chua, Karen Sui Geok, Chew, Effie, Guan, Cuntai

“…Motor imagery (MI) brain-computer interfaces (BCIs) based on electroencephalogram (EEG) have been developed primarily for stroke rehabilitation, however, due to limited stroke data, current deep learning methods for cross-subject classification rely on healthy data. …”
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High cycle fatigue characterisation and modelling of 316L stainless steel processed by laser powder bed fusion by Zhang, Meng

“…Lastly, considering the numerous influencing factors arising from the process and the associated failure behaviours, a neuro-fuzzy-based machine learning method was applied to provide an effective unifying approach for high cycle fatigue life prediction. …”
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Offline eLearning for undergraduates in health professions : a systematic review of the impact on knowledge, skills, attitudes and satisfaction by Wark, Petra A., Rasmussen, Kristine, Belisario, José Marcano, Molina, Joseph Antonio, Loong, Stewart Lee, Cotic, Ziva, Papachristou, Nikos, Riboli–Sasco, Eva, Car, Lorainne Tudor, Musulanov, Eve Marie, Zhang, Yanfeng, Kunz, Holger, George, Pradeep Paul, Heng, Bee Hoon, Wheeler, Erica Lynette, Al Shorbaji, Najeeb, Svab, Igor, Atun, Rifat, Majeed, Azeem, Car, Josip

“…To inform investments in offline eLearning, we need to establish its effectiveness in terms of gaining knowledge and skills, students’ satisfaction and attitudes towards eLearning. Methods: We conducted a systematic review of offline eLearning for students enrolled in undergraduate, health–related university degrees. …”
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