Prediction of neutralising antibodies for novel coronavirus with machine learning by Kho, Jordon Junyang

“…The best performing models were mean pooling models trained using SMOTE-N with accuracies of up to 82% and F1 scores of up to 84% after hyper-parameter tuning. …”
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A latching system for a perching UAV by Lam, Jonas Wai Jun

“…A section of this report presents an experiment to analyze the perching behavior of birds that was accomplished through the assistance of Flightmasters that provided trained birds for the experiment. The process of the experiment as well as the observations and recommendations for future experiments is also presented.…”
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Research of modeling and optimization approaches for hybrid ejector-based air conditioning cycle by Wang, Hao

“…Both simulation and experiment results indicate that the ANN trained with ELM possesses lesser deviation between actual value and predicted value than the ones with other learning algorithms. 3. …”
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Evaluating the generalisability of region-naïve machine learning algorithms for the identification of epilepsy in low-resource settings by Duta, I, Kariuki, SM, Ngugi, AK, Mwesige, AK, Masanja, H, Mwanga, DM, Owusu-Agyei, S, Wagner, R, Cross, JH, Sander, JW, Newton, CR, Sen, A, Jones, GD

“…When the models were trained using data from an increasing number of sites, mean internal performance decreased while external performance improved. …”

Multicenter double-blind study evaluating AI-driven detection of proximal deep vein thrombosis by Curry, N, Allen, E, Silsby, L, Goodacre, S, Deane, C, Deary, A, Foster, A, Griffiths, J, Sharma, R, Thomas, H, Mischewitz, S, Al-Noor, F

“…Further optimization of the software is required prior to use in clinical practice by nonradiology-trained health care professionals. (Funded by the Wellcome Trust [Wellcome Innovator Award 220505/Z/20/Z]. …”

Building a cyber iron dome : Israel’s cyber defensive envelope by Raska, Michael

“…Israel is developing “a national cyber defensive envelope” – a multi-layered cyber defence strategy leveraging automated computerised systems and highly-trained personnel that provide intelligence, early warning, passive and active defence, and offensive capabilities across civil-military networks.…”
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Enhancement of photoacoustic imaging systems for biomedical applications by Sharma, Arunima

“…DL relies on supervised learning, i.e., the network gets trained on pre-defined dataset to solve practical problems on new data. …”
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THE SECRETS OF PROFESSIONAL SALES CLOSING / by Seymour, Ian, author 655075

“…The Secrets Of Professional Sales Closing is a unique sales-closing manual written from personal experience by a top PRO-CLO, lan Seymour, who has personally closed in excess of $32 million of retail sales one on one and has trained thousands of salespeople all over the world. …”

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.

“…Previous efforts have attempted to train such operators using loss functions that match statistics. …”
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Minimalistic attacks : how little it takes to fool deep reinforcement learning policies by Qu, Xinghua, Sun, Zhu, Ong, Yew-Soon, Gupta, Abhishek, Wei, Pengfei

“…We formulate the adversarial attack by accommodating the three key settings, and explore their potency on six Atari games by examining four fully trained state-of-the-art policies. In Breakout, for example, we surprisingly find that: (i) all policies showcase significant performance degradation by merely modifying 0.01% of the input state, and (ii) the policy trained by DQN is totally deceived by perturbing only 1% frames.…”
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Impact of turbine- and farm-scale flow effects on wind farm performance by Kirby, A

“…The statistical emulators are trained using a multi-fidelity Gaussian Process on high-fidelity large-eddy simulations and low-fidelity wake model predictions. …”

Wanted : bus drivers. by Wong, Kang Wei., Lee, Jian Xuan., Teo, Hee Boon., Koh, Malcolm Sheng Wei.

“…It attempts to find out how bus drivers are recruited and trained to drive on our roads, and the severity of the bus driver shortage.…”
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Machine learning for denoising by Quek, Kenneth Joo Hong

“…The experiment results show that the trained model can outperform different denoising methods like BM3D, EPLL and WNNM by 0.60 PSNR, 0.46 PSNR and 0.30 PSNR respectively.…”
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Reinforcement learning for self-driving cars by Ho, Song Yan

“…The proposed model uses the minimal sensory input collected from the environment. The model was trained with reinforcement learning algorithm in the simulation environment to simulate traffic condition of seven-lane expressway. …”
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Development of a system to detect hidden information in a document using steganography software by Wuan, Neng Jie

“…The accuracy of detection depends on the trained Support Vector Machine (SVM) model used, and therefore, accuracy hinges on the type of training data and test images used. …”
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Open resource-aided image analytics by Zheng, Weihua

“…However, due to the different distribution of different data sets, the network trained on one training set is difficult to perform well on another data set. …”
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Learning object categories from Google’s image search by Fergus, R, Fei-Fei, L, Perona, P, Zisserman, A

“…Current approaches to object category recognition require datasets of training images to be manually prepared, with varying degrees of supervision. …”

Regression and classification approaches to eye localization in face images by Everingham, M, Zisserman, A

“…We investigate three approaches to the task: a regression approach aiming to directly minimize errors in the predicted eye positions, a simple Bayesian model of eye and non-eye appearance, and a discriminative eye detector trained using AdaBoost. By using identical training and test data for each method we are able to perform an unbiased comparison. …”

Tabula rasa: model transfer for object category detection by Aytar, Y, Zisserman, A

“…Our objective is transfer training of a discriminatively trained object category detector, in order to reduce the number of training images required. …”

Advancing healthcare with artificial intelligence: diagnostic accuracy of machine learning algorithm in diagnosis of diabetic retinopathy in the Brazilian population by dos Reis, Mateus A., Künas, Cristiano A., da Silva Araújo, Thiago, Schneiders, Josiane, de Azevedo, Pietro B., Nakayama, Luis F., Rados, Dimitris R. V., Umpierre, Roberto N., Berwanger, Otávio, Lavinsky, Daniel, Malerbi, Fernando K., Navaux, Philippe O. A., Schaan, Beatriz D.

“…The sample was fractionated in training (70%) and testing (30%) samples. A convolutional neural network was trained for image classification. …”
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