KINEMATICS STUDY OF JUNIOR AMATEUR GOLFERS IN SINGAPORE

Qualitative tools for golf motion analysis like video and graphical overlay have provided competitive golfers in Singapore feedback on their swing. The analysis of this information tends to be subjective due to a lack of reliable quantifiable kinematics information. The authors applied the methods perlormed by Mc Laughlin and Best [1994], Robinson [1994] and Miura and Nauro [1998] on two professional players and six national age group players. Differences were found in how the two groups of players swing, in particular their setup and translation of their Center of Mass (COM) at Middle of Backswing (MBS) and Ball Impact Frame (BIF). Angle displacement of the shoulder-hip axis was studied and found to be pertinent to the kinetic link analysis. This parameter could serve as an intermediary for quantitative and qualitative analysis

Bidirectional Representation Learning from Transformers using Multimodal Electronic Health Record Data to Predict Depression

Advancements in machine learning algorithms have had a beneficial impact on representation learning, classification, and prediction models built using electronic health record (EHR) data. Effort has been put both on increasing models' overall performance as well as improving their interpretability, particularly regarding the decision-making process. In this study, we present a temporal deep learning model to perform bidirectional representation learning on EHR sequences with a transformer architecture to predict future diagnosis of depression. This model is able to aggregate five heterogenous and high-dimensional data sources from the EHR and process them in a temporal manner for chronic disease prediction at various prediction windows. We applied the current trend of pretraining and fine-tuning on EHR data to outperform the current state-of-the-art in chronic disease prediction, and to demonstrate the underlying relation between EHR codes in the sequence. The model generated the highest increases of precision-recall area under the curve (PRAUC) from 0.70 to 0.76 in depression prediction compared to the best baseline model. Furthermore, the self-attention weights in each sequence quantitatively demonstrated the inner relationship between various codes, which improved the model's interpretability. These results demonstrate the model's ability to utilize heterogeneous EHR data to predict depression while achieving high accuracy and interpretability, which may facilitate constructing clinical decision support systems in the future for chronic disease screening and early detection.Comment: in IEEE Journal of Biomedical and Health Informatics (2021

Predictive Modelling Using Unstructured Data From Online Forums: A Case Study on E-cigarette Users

In the age of the digital economy, social media, forums and other online platforms have played active parts in our daily activities. The amount of data digitized and recorded in these platforms have surged exponentially. Many believed that this underexplored unstructured data sources have huge potential in offering insights to policy makers and companies. This paper aims to propose a hybrid approach using inductive and deductive reasoning to identify motivational factors to use e-cigarettes for predictive modelling. A total of 790 comments and discussions relevant to e-cigarette use and motivations to use e-cigarette were scraped and stored from online forums like Reddit, Vapingunderground and e-cigarette-forum. A series of text analytics were conducted on the text corpus and the cluster analysis enabled us to build a predictive model. Using Bayesian Structural Equation Modelling, we concluded that the constructs derived by clustering, i.e. Cost and Convenience and Enjoyment, have significant associations with smokers trying to quit smoking. While health-related issues were inherent to the notion of quitting smoking, enjoyment, cost and convenience were motivational factors which will generate favourable response towards quitting smoking. The findings showed encouraging results from a methodological standpoint and offered insights to policy makers and companies on health-related issues pertaining to the use of e-cigarettes

Quasiparticle thermal Hall angle and magnetoconductance in YBa_2Cu_3O_x

We present a way to extract the quasiparticle (qp) thermal conductivity Kappa_e and mean-free-path in YBa_2Cu_3O_x, using the thermal Hall effect and the magnetoconductance of Kappa_e. The results are very consistent with heat capacity experiments. Moreover, we find a simple relation between the thermal Hall angle Theta_Q and the H-dependence of Kappa_e, as well as numerical equality between Theta_Q and the electrical Hall angle. The findings also reveal an anomalously anisotropic scattering process in the normal state.Comment: 4 pages in Tex, 5 figures in EPS; replaced on 5/12/99, minor change

Fermi Surface reconstruction in the CDW state of CeTe3 observed by photoemission

CeTe3 is a layered compound where an incommensurate Charge Density Wave (CDW) opens a large gap (400 meV) in optimally nested regions of the Fermi Surface (FS), whereas other sections with poorer nesting remain ungapped. Through Angle-Resolved Photoemission, we identify bands backfolded according to the CDW periodicity. They define FS pockets formed by the intersection of the original FS and its CDW replica. Such pockets illustrate very directly the role of nesting in the CDW formation but they could not be detected so far in a CDW system. We address the reasons for the weak intensity of the folded bands, by comparing different foldings coexisting in CeTe3

Transport properties of the layered Rh oxide K_0.49RhO_2

We report measurements and analyses of resistivity, thermopower and Hall coefficient of single-crystalline samples of the layered Rh oxide K_0.49RhO_2. The resistivity is proportional to the square of temperature up to 300 K, and the thermopower is proportional to temperature up to 140 K. The Hall coefficient increases linearly with temperature above 100 K, which is ascribed to the triangular network of Rh in this compound. The different transport properties between Na_xCoO_2 and K_0.49RhO_2 are discussed on the basis of the different band width between Co and Rh evaluated from the magnetotransport.Comment: 3 figures, submitted to PR

Strongly Coupled Matter-Field and Non-Analytic Decay Rate of Dipole Molecules in a Waveguide

The decay rate \gam of an excited dipole molecule inside a waveguide is evaluated for the strongly coupled matter-field case near a cutoff frequency \ome_c without using perturbation analysis. Due to the singularity in the density of photon states at the cutoff frequency, we find that \gam depends non-analytically on the coupling constant $\ggg$ as $\ggg^{4/3}$. In contrast to the ordinary evaluation of \gam which relies on the Fermi golden rule (itself based on perturbation analysis), \gam has an upper bound and does not diverge at \ome_c even if we assume perfect conductance in the waveguide walls. As a result, again in contrast to the statement found in the literature, the speed of emitted light from the molecule does not vanish at \ome_c and is proportional to $c\ggg^{2/3}$ which is on the order of $10^3 \sim 10^4$ m/s for typical dipole molecules.Comment: 4 pages, 2 figure