NOODLE++: a 3 Dimensional Net-based Object-orientated Development Model

HKU CS Tech Report TR-95-04Object-oriented analysis and design methodologies are considered as the most popular software development methods for the 1990s. A common drawback, however, is that they have been developed informally. There is no theoretical framework enabling us to define precisely the object-oriented concepts involved, to solve concurrency problems, and to verify the correctness of the implementation. We propose a 3-dimensional net structure behind object-oriented software development. This structure consolidates the concepts of classes, inheritance, overloading and message passing through a single model. Inheritance and overloading can be unified with message passing in a 3-dimensional representation, but are physically differentiable by occupying the vertical and horizontal planes,respectively, of the model. Furthermore, the formal model can be mapped to various object-oriented analysis and design notations. The theoretical framework can thus be adopted for systems validation and verification for existing methodologies. The liveness and consistencies of objects can be verified, and inheritance and interaction coupling can be identified and checked.preprintThis research is supported in part by a grant of the Research Grants Council

Breast cancer and screening in Hong Kong: Letter to the editor

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Covariant Hamiltonian Field Theory

A consistent, local coordinate formulation of covariant Hamiltonian field theory is presented. Whereas the covariant canonical field equations are equivalent to the Euler-Lagrange field equations, the covariant canonical transformation theory offers more general means for defining mappings that preserve the form of the field equations than the usual Lagrangian description. It is proved that Poisson brackets, Lagrange brackets, and canonical 2-forms exist that are invariant under canonical transformations of the fields. The technique to derive transformation rules for the fields from generating functions is demonstrated by means of various examples. In particular, it is shown that the infinitesimal canonical transformation furnishes the most general form of Noether's theorem. We furthermore specify the generating function of an infinitesimal space-time step that conforms to the field equations.Comment: 93 pages, no figure

Smoking cessation and carotid atherosclerosis: The guangzhou biobank cohort studydCVD

Introduction Smoking has been shown to be associated with carotid atherosclerosis in cross-sectional and prospective studies in Western populations. However, few studies have examined the reversal of risk resulting from quitting smoking, and the results are conflicting. Methods 959 men aged 50e85 years were randomly selected from phase III (2006e2007) of the Guangzhou Biobank Cohort Study into this cross-sectional study. Common carotid artery intima-media thickness (CCAIMT) was measured by B-mode ultrasonography, and carotid artery plaques were identified. Major cardiovascular risk factors, including fasting triglyceride, low-density and high-density lipoprotein (LDL and HDL) cholesterol and glucose, and systolic and diastolic blood pressure, were assessed. Results CCA-IMT and the number of carotid plaque increased from never to former to current smokers (both p≤0.001). Among former smokers compared to current smokers, after adjustment for cigarette pack-years and other potential confounders, the adjusted ORs (95% CI) for quitting for 1-9, 10-19 and 20+ years were 0.77 (0.47 to 1.26), 0.45 (0.26 to 0.79) and 0.37 (0.17 to 0.77) for the presence of CCA atherosclerosis, and 0.69 (0.43 to 1.12), 0.47 (0.27 to 0.82) and 0.45 (0.23 to 0.96) for the presence of carotid plaques, respectively. Longer duration of quitting smoking was also significantly associated with decreasing risk of the severity of CCA atherosclerosis and carotid plaques (all p≤0.001). Conclusion Smoking cessation was beneficial in attenuating the risk of carotid atherosclerosis associated with cigarette smoking. The short duration of cessation in earlier studies is a likely explanation for the inconsistent results.published_or_final_versio

Fruit and vegetable consumption and cardiovascular risk factors in older Chinese: The Guangzhou Biobank Cohort Study

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Systematic differences among never, occasional and moderate alcohol users in southern China, and its use in alcohol research: a cross-sectional study

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Alcohol use and gamma-glutamyltransferase using a mendelian randomization design in the Guangzhou Biobank Cohort Study

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Polynomial Growth Harmonic Functions on Finitely Generated Abelian Groups

In the present paper, we develop geometric analytic techniques on Cayley graphs of finitely generated abelian groups to study the polynomial growth harmonic functions. We develop a geometric analytic proof of the classical Heilbronn theorem and the recent Nayar theorem on polynomial growth harmonic functions on lattices \mathds{Z}^n that does not use a representation formula for harmonic functions. We also calculate the precise dimension of the space of polynomial growth harmonic functions on finitely generated abelian groups. While the Cayley graph not only depends on the abelian group, but also on the choice of a generating set, we find that this dimension depends only on the group itself.Comment: 15 pages, to appear in Ann. Global Anal. Geo

Recognizing flu-like symptoms from videos

© 2014 Hue Thi et al.; licensee BioMed Central Ltd. Background: Vision-based surveillance and monitoring is a potential alternative for early detection of respiratory disease outbreaks in urban areas complementing molecular diagnostics and hospital and doctor visit-based alert systems. Visible actions representing typical flu-like symptoms include sneeze and cough that are associated with changing patterns of hand to head distances, among others. The technical difficulties lie in the high complexity and large variation of those actions as well as numerous similar background actions such as scratching head, cell phone use, eating, drinking and so on. Results: In this paper, we make a first attempt at the challenging problem of recognizing flu-like symptoms from videos. Since there was no related dataset available, we created a new public health dataset for action recognition that includes two major flu-like symptom related actions (sneeze and cough) and a number of background actions. We also developed a suitable novel algorithm by introducing two types of Action Matching Kernels, where both types aim to integrate two aspects of local features, namely the space-time layout and the Bag-of-Words representations. In particular, we show that the Pyramid Match Kernel and Spatial Pyramid Matching are both special cases of our proposed kernels. Besides experimenting on standard testbed, the proposed algorithm is evaluated also on the new sneeze and cough set. Empirically, we observe that our approach achieves competitive performance compared to the state-of-the-arts, while recognition on the new public health dataset is shown to be a non-trivial task even with simple single person unobstructed view. Conclusions: Our sneeze and cough video dataset and newly developed action recognition algorithm is the first of its kind and aims to kick-start the field of action recognition of flu-like symptoms from videos. It will be challenging but necessary in future developments to consider more complex real-life scenario of detecting these actions simultaneously from multiple persons in possibly crowded environments