Love Thy Neighbor: Income Distribution and Housing Preferences

Do homeowners prefer living in an area with a more equal distribution of income? We answer this question by estimating a semi-parametric hedonic pricing model for about 90,000 housing units transacted in Hong Kong between 2005 and 2006. We first identify a hedonic price function by locally regressing the rental price of the housing unit on its intrinsic and neighborhood characteristics, one of which is the Gini coefficient for household income of the constituency area. We then combine the estimates with a log utility function to obtain the heterogeneous preference parameters. Finally, we estimate the joint distribution of the preference parameters and demographics. We find that most homeowners have a strong distaste for inequality in their neighborhood, and the distaste increases with income and goes down with education level. Counterfactual experiments show that reallocating Public Rental Housing by half can increase the welfare of homeowners by about HK$8,000 on average per year, an amount which is equivalent to increasing the housing unit by 20 square feet or reducing the age of the unit by 5 years.hedonic pricing; housing; income inequality

A continuing mission to optimize the care of older women with breast cancer

The majority of cases of breast cancer occur in the older population who are often un-represented in clinical trials. Given the growing ageing population globally, it becomes urgent and important to identify an optimal approach so that older women with breast cancer are neither under- or over-treated. An inter-disciplinary research program is ongoing to investigate differing tumor biology according to age, and the potential use of a geriatric assessment tool, aiming to help select older women with primary breast cancer for a personalized and optimal treatment. Full considerations of the biology of the patient’s cancer and the geriatric domains of the patient must be taken into account when making treatment decisions

A new modified Newton\u27s method for minimizing factorable functions.

Dept. of Mathematics and Statistics. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1988 .C468. Source: Masters Abstracts International, Volume: 40-07, page: . Thesis (M.Sc.)--University of Windsor (Canada), 1988

Indexing and Retrieval of 3D Articulated Geometry Models

In this PhD research study, we focus on building a content-based search engine for 3D articulated geometry models. 3D models are essential components in nowadays graphic applications, and are widely used in the game, animation and movies production industry. With the increasing number of these models, a search engine not only provides an entrance to explore such a huge dataset, it also facilitates sharing and reusing among different users. In general, it reduces production costs and time to develop these 3D models. Though a lot of retrieval systems have been proposed in recent years, search engines for 3D articulated geometry models are still in their infancies. Among all the works that we have surveyed, reliability and efficiency are the two main issues that hinder the popularity of such systems. In this research, we have focused our attention mainly to address these two issues. We have discovered that most existing works design features and matching algorithms in order to reflect the intrinsic properties of these 3D models. For instance, to handle 3D articulated geometry models, it is common to extract skeletons and use graph matching algorithms to compute the similarity. However, since this kind of feature representation is complex, it leads to high complexity of the matching algorithms. As an example, sub-graph isomorphism can be NP-hard for model graph matching. Our solution is based on the understanding that skeletal matching seeks correspondences between the two comparing models. If we can define descriptive features, the correspondence problem can be solved by bag-based matching where fast algorithms are available. In the first part of the research, we propose a feature extraction algorithm to extract such descriptive features. We then convert the skeletal matching problems into bag-based matching. We further define metric similarity measure so as to support fast search. We demonstrate the advantages of this idea in our experiments. The improvement on precision is 12\% better at high recall. The indexing search of 3D model is 24 times faster than the state of the art if only the first relevant result is returned. However, improving the quality of descriptive features pays the price of high dimensionality. Curse of dimensionality is a notorious problem on large multimedia databases. The computation time scales exponentially as the dimension increases, and indexing techniques may not be useful in such situation. In the second part of the research, we focus ourselves on developing an embedding retrieval framework to solve the high dimensionality problem. We first argue that our proposed matching method projects 3D models on manifolds. We then use manifold learning technique to reduce dimensionality and maximize intra-class distances. We further propose a numerical method to sub-sample and fast search databases. To preserve retrieval accuracy using fewer landmark objects, we propose an alignment method which is also beneficial to existing works for fast search. The advantages of the retrieval framework are demonstrated in our experiments that it alleviates the problem of curse of dimensionality. It also improves the efficiency (3.4 times faster) and accuracy (30\% more accurate) of our matching algorithm proposed above. In the third part of the research, we also study a closely related area, 3D motions. 3D motions are captured by sticking sensor on human beings. These captured data are real human motions that are used to animate 3D articulated geometry models. Creating realistic 3D motions is an expensive and tedious task. Although 3D motions are very different from 3D articulated geometry models, we observe that existing works also suffer from the problem of temporal structure matching. This also leads to low efficiency in the matching algorithms. We apply the same idea of bag-based matching into the work of 3D motions. From our experiments, the proposed method has a 13\% improvement on precision at high recall and is 12 times faster than existing works. As a summary, we have developed algorithms for 3D articulated geometry models and 3D motions, covering feature extraction, feature matching, indexing and fast search methods. Through various experiments, our idea of converting restricted matching to bag-based matching improves matching efficiency and reliability. These have been shown in both 3D articulated geometry models and 3D motions. We have also connected 3D matching to the area of manifold learning. The embedding retrieval framework not only improves efficiency and accuracy, but has also opened a new area of research

Treatment Strategies and Survival Outcomes in Breast Cancer

Treatment strategies for breast cancer are wide-ranging and often based on a multi-modality approach, depending on the stage and biology of the tumour and the acceptance and tolerance of the patient. They may include surgery, radiotherapy, and systemic therapy (endocrine therapy, chemotherapy, and targeted therapy). Advances in technologies such as oncoplastic surgery, radiation planning and delivery, and genomics, and the development of novel systemic therapy agents alongside their evaluation in ongoing clinical trials continue to strive for improvements in outcomes. In this Special Issue entitled, ‘Treatment strategies and survival outcomes in breast cancer’, a number of original research articles are included covering a diversity of studies, from pre-clinical and translational biomarker studies to clinical trials and population-based studies. They evaluated survival and other outcomes, including quality of life, in the context of pre-diagnosis (screening), as well as early and advanced stages of breast cancer

Prostrating Walk in the Campaign against Sino-Hong Kong Express Railway: Collective Identity of Native Social Movement

Occupation, blockage and storming are not rare in social movements a decade after China resuming sovereignty in Hong Kong. The organizers and participants usually involve locally born young people. Some of them are secondary school students in their teens. They are known as the fourth generation or post-1980s born Hongkongers. The paper examines the cultural context of social movements involving these youth activists. It mainly studied the campaign against the Sino-Hong Kong Express Railway development project. The project called for the demolition of the Tsoi Yuen Village, a small rural village located on its designed route. Since then, the role of younger generation in social movements has been generally recognized. Social media are widely employed in all stages of the movements with citizen journalists actively involved. The impressive ‘prostrating walk’ imitating Tibetan pilgrims becomes the symbol of these youth activists. It keeps appearing in other campaigns including Occupy Central in Hong Kong in 2014. This paper argues that the rise of nativism, advancement in ICT technology and shifting towards new social movements contribute to the dominant role of youth in recent social movements of Hong Kong. Collective identity of Hongkonger in response to the top-down assimilation by China, strengthens the movement