Nurses lived experiences on the nurse-patient relationship by Koo, Alvina Min En

“…This study examines the perspectives of Singaporean non-palliative care trained nurses (NPNs), working in local general hospitals, on their experiences in forming the nurse-patient relationship (NPR) with their patients. …”
Get full text

Autonomous learning machine for online big data analysis by Ng, Jia Yu

“…The use of autoencoder information can be utilized in overcoming the convergence problem which arises when random samples are used for model training [1]. Two separate autoencoders were trained for normal products and defective products respectively. …”
Get full text

An empirical study on family and healthcare professionals as interpreters for limited English proficient patients (LEPPs): role of interpreters and societal challenges of medical t... by Yeung, Lis Lok Hei

“…This poses a problem in medical consultation as most medical personnel in Singapore are trained in English. To solve this problem, ad hoc interpreters are tasked to bridge the language gap. …”
Get full text

A community-based intervention (the Omama Project) improves neurodevelopment in impoverished 2-year-old Roma children: a quasi-experimental observational study by Fernandes, M, Matuskova, O, Babelova, R, Santosa, WB, Shaw, O, Hrica, P

“…The intervention was delivered between 3 weeks and 20 months in weekly home-based sessions by trained Roma women from matched settlements to RIs. …”

Effect of ADC to respiratory sound classification by Lau, Benson Yong Zhi

“…The signal will then be undergoing the ADC algorithm before sending it to the trained classifier to study the effect of ADC on sound classification. …”
Get full text

Tactile identification of textures using machine learning/ deep learning by Goh, Jun Bin

“…Thereafter, the unseen dataset of a material can be tested on the newly trained Machine Learning/ Deep Learning model, to predict and identify the material as a result. …”
Get full text

Body movement mimic – video-based human body motion transfer by Mamuduri, Paulani

“…The first approach used depth maps from pre-trained depth estimator MiDaS to guide keypoint detection in the First Order Motion Model. …”
Get full text

Image aesthetic style classification and region detection using Convolutional Neural Network by Xue, Chuhui

“…By using this pre-trained model, we then apply Faster R-CNN [1] algorithm on image aesthetic style region detection. …”
Get full text

Generative pretrained autoregressive transformer graph neural network applied to the analysis and discovery of novel proteins by Buehler, Markus J

“…While our model is trained to ultimately perform eight distinct tasks, with available datasets, it can be extended to solve additional problems. …”
Get full text

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

“…This study aims to assess the feasibility of applying MI-BCI models pre-trained using data from healthy individuals to detect MI in stroke patients. …”
Get full text

Model-based convolutional neural network approach to underwater source-range estimation by Chen, R., Schmidt, H.

“…When tested with data simulated in environments that deviate slightly from the training environment, this approach shows improved prediction accuracy and lower mean-absolute-error (MAE) compared to MFP. …”
Get full text

Computational optimization of cell culture media for cultured meat production by Reji, Rinta Pullamkottu

“…ESM-2 was trained on amino acid sequences for masked residue prediction in order to extract residue-level features to be embedded into the graphical input. …”
Get full text

Genetic algorithm based deep learning model adaptation for improvising the motor imagery classification by R, Vishnupriya, Robinson, Neethu, M, Ramasubba Reddy

“…It is particularly encouraging that a subject-independent model can be trained using a large amount of other subjects’ data. …”
Get full text

Predicting rifampicin resistance in M. tuberculosis using machine learning informed by protein structural and chemical features by Lynch, C, Adlard, D, Fowler, P

“…</p> <br> <p><strong>Methods:</strong> We built a Test+Train dataset comprising 219 susceptible mutations. …”

Neural adaptive prediction by Ramaswamy Ashok Tenkasi

“…The main objective if this project is to demonstrate the effectiveness of the proposed approach for the n-step ahead prediction using neural networks, which are trained using real plant data.…”
Get full text

Teachers' perceptions of history and history teaching in secondary schools by Yeo, Hwee Joo.

“…The study was undertaken with the objective to provide a better understanding to the perceptions and practices of trained History teachers.…”
Get full text

Adversarial robustness of deep reinforcement learning by Qu, Xinghua

“…Over the past decades, the advancements in deep reinforcement learning (DRL) have demonstrated that deep neural network (DNN) policies can be trained to prescribe near-optimal actions in many complex tasks. …”
Get full text

Deep learning-based concrete image analysis and generalization capability by Qian, Hanjie

“…Since the training data and test data belong to different distributions, and directly applying a trained model can be highly risky. …”
Get full text

Road damage detection for autonomous driving vehicles using YOLOv8 and salp swarm algorithm by Nik Ahmad Farihin, Mohd Zulkifli, Zuriani, Mustaffa, Mohd Herwan, Sulaiman

“…The YOLOv8n model is trained with SSA on the RDD2022 dataset, specifically using data from India and China, to find the optimal parameters. …”
Get full text

Evaluation of Deep Neural Operator Models Toward Ocean Forecasting by Rajagopal, Ellery, Babu, Anantha N. S., Ryu, Tony, Haley, Patrick J., Mirabito, Chris, Lermusiaux, Pierre F. J.

Get full text