Wage dispersion is one of the social and economic issues arousing public concern in Hong Kong. There are many studies exploring the possible causes and changes in wage dispersion. They often focus on the study of summary measures such as Gini and Theil indexes, or adopt OLS-based regression approach. In foreign studies on wage dispersion, Oaxaca-Blinder decomposition, originated from Oaxaca (1974) and Blinder (1973), is a common method of decomposing changes or differences in mean wages between two groups into wage structure effect and composition effect, and then further decomposing the two effects into contributions of each control variable. Nevertheless, focusing on summary measures or decomposing mean wages can just give people an insight into the causes and changes in general wage dispersion but not the entire wage distribution. As pointed out by Chi, Li and Yu (2007), the estimation of the entire wage distribution and decomposition of the distributional changes in wage dispersion has been attracting the attention of labour economists. This thesis adopts a distributional approach proposed by Firpo, Fortin and Lemieux (2007) to study the changes in wage dispersion of Hong Kong since 1980s. The FFL approach comprises a two-stage procedure. Firstly, changes in dispersion are divided into wage structure effect and composition effect without directly estimating a wage-setting model. This is done by doing a proper reweighting to obtain counterfactual wage vectors. Kernel density estimation is used for visualizing the wage distribution in different years and the counterfactuals; secondly, novel recentered influence function (RIF) regressions across quantiles are performed to further decompose the two effects into contributions of each control variable. The findings are outlined as follows: first, there was an increase in wage dispersion over the whole wage distribution from 1980s but a decrease from 2001 to 2006; second, the composition effect dominates the wage structure effect over years; third, changes in the distribution of characteristics and the returns to these characteristics are highly responsive to each other, suggesting that our labour market is highly responsive to structural changes; fourth, The common wage-determining factors may not be able to explain the earnings-profile of low wage earners well. In brief, the development of the economy since 1980s increased the wage dispersion over years. Nevertheless, the economic downturn due to external shocks and internal unfavourable events and general skill-upgrading in labour-intensive industries decreased the wage dispersion since 2000s.

Understanding spatial perspectives on the spread and incidence of a disease is invaluable for public health planning and intervention. Choropleth maps are commonly used to provide an abstraction of disease risk across geographic space. These maps are derived from aggregated population counts that are known to be affected by the small numbers problem. Kernel density estimation methods account for this problem by producing risk estimates that are based on aggregations of approximately equal population sizes. However, the process of aggregation often combines data from areas with non-uniform spatial and population characteristics. This thesis presents a new method to aggregate space in ways that are sensitive to their underlying risk factors. Such maps will enable better public health practice and intervention by enhancing our ability to understand the spatial processes that result in disparate health outcomes.

This thesis analyzes the end-user quality of service (QoS) in cellular mobile networks using device-side measurements. Quality of service in a wireless network is a significant factor in determining a user's satisfaction. Customers' perception of poor QoS is one of the core sources of customer churn for telecommunications companies. A core focus of this work is on assessing how user density impacts QoS within cellular networks. Kernel density estimation is used to produce user density estimates for high, medium, and low density areas. The QoS distributions are then compared across these areas. The k-sample Anderson-Darling test is used to determine the degree to which user densities vary over time. In general, it is shown that users in higher density areas tend to experience overall lower QoS levels than those in lower density areas, even though these higher density areas service more subscribers. The conducted analyses highlight the value of mobile device-side QoS measurements in augmenting traditional network-side QoS measurements. / Graduate

Lagrangian particle models are useful for modelling pollutants in the atmosphere. They simulate the spread of pollutants by modelling trajectories of individual particles. However, to be useful, these models require a density estimate. The standard method to use has been boxcounting, but kernel density estimator (KDE) is an alternative. How KDE is used varies as there is no standard implementation. Primarily, it is the choice of kernel and bandwidth estimator that determines the model. In this report I have implemented a KDE for FOI’s Lagrangian particle model LPELLO. The kernel I have used is a combination between a uniform and Gaussian kernel. Four different bandwidth estimators has been tested, where two are global and two are variable. The first variable bandwidth estimator is based on the age of released particles, and the second is based on the turbulence history of the particles. The methods have then been tested against boxcounting, which by using an exceedingly large number of particles can be seen as the true concentration. The tests indicate that KDE method generally performs better than boxcounting at low particle numbers. The variable bandwidth estimators also performed better than both global bandwidth estimators. To achive a firmer conclusion, more testing is needed. The results indicate that KDE in general, and variable bandwidth estimators in specific, are useful tools for concentration estimate.

Water shortages resulting from increased demand or reduced supply may be addressed, in part, by redirecting recycled water for irrigation, industrial reuse, groundwater recharge, and as effluent discharge returned to streams. Recycled water is an essential component of integrated water management and broader adoption of recycled water will increase water conservation in water-stressed coastal communities. This study examined spatial patterns of recycled water use in Florida in 2009 and 2015 to detect gaps in distribution, quantify temporal change, and identify potential areas for expansion. Databases of recycled water products and distribution centers for Florida in 2009 and 2015 were developed by combining the 2008 and 2012 Clean Water Needs Survey databases with Florida’s 2009 and 2015 Reuse Inventory databases, respectively. Florida increased recycled water production from 674.85 mgd in 2009 to 738.15 mgd in 2015, an increase of 63.30 mgd. The increase was primarily allocated to use in public access areas, groundwater recharge, and industrial reuse, all within the South Florida Water Management District (WMD). In particular, Miami was identified in 2009 as an area of opportunity for recycled water development, and by 2015 it had increased production and reduced the production gap. Overall, South Florida WMD had the largest increase in production of 44.38 mgd (69%), while Southwest Florida WMD decreased production of recycled water by 1.68 mgd, or 3%. Overall increase in use of recycled water may be related to higher demand due to increased population coupled with public programs and policy changes that promote recycled water use at both the municipal and individual level.

京都大学 / 新制・課程博士 / 博士(経済学) / 甲第24375号 / 経博第662号 / 新制||経||302(附属図書館) / 京都大学大学院経済学研究科経済学専攻 / (主査)教授 西山 慶彦, 教授 江上 雅彦, 講師 柳 貴英 / 学位規則第4条第1項該当 / Doctor of Economics / Kyoto University / DFAM

This research estimated the spatial-temporal patterns of tornadoes in the continental United States from 1950-2019 using the National Weather Service Storm Prediction Center’s Severe Weather GIS (SVRGIS) database. This study employed Space-Time Cube Analysis and Linear Kernel Density (Kernel Density Linear Process, (KDLP)) rather than the standard Kernel Density Estimation (KDE) approach; to evaluate whether tornado hotspot locations and intensities shift over time. The first phase of the study utilized KDLP to map changes in tornado hotspots and qualitatively assess decadal shifts in hotspot locations and intensities by occurrence and magnitude between decades using ArcGIS Pro and CrimeStat. Next an Emerging Hot Spot Analysis (EHSA) was employed to identify the changes in tornado occurrence and magnitude. ESHA results identified, by both occurrence and magnitude, significant intensifying hot spots in the Southeast region and diminishing hot spots in the Great Plains indicating an east-south-east shift.

No description available.

Data streams are ordered sets of values that are fast, continuous, mutable, and potentially unbounded. Examples of data streams include the pervasive time series which span domains such as finance, medicine, and transportation. Mining data streams require approaches that are efficient, adaptive, and scalable. For several stream mining tasks, knowledge of the data's probability density function (PDF) is essential to deriving usable results. Providing an accurate model for the PDF benefits a variety of stream mining applications and its successful development can have far-reaching impact to the general discipline of stream analysis. Therefore, this research focuses on the construction of efficient and effective approaches for estimating the PDF of data streams. In this work, kernel density estimators (KDEs) are developed that satisfy the stringent computational stipulations of data streams, model unknown and dynamic distributions, and enhance the estimation quality of complex structures. Contributions of this work include: (1) theoretical development of the local region based KDE; (2) construction of a local region based estimation algorithm; (3) design of a generalized local region approach that can be applied to any global bandwidth KDE to enhance estimation accuracy; and (4) application extension of the local region based KDE to multi-scale outlier detection. Theoretical development includes the formulation of the local region concept to effectively approximate the computationally intensive adaptive KDE. This work also analyzes key theoretical properties of the local region based approach which include (amongst others) its expected performance, an alternative local region construction criterion, and its robustness under evolving distributions. Algorithmic design includes the development of a specific estimation technique that reduces the time/space complexities of the adaptive KDE. In order to accelerate mining tasks such as outlier detection, an integrated set of optimizations are proposed for estimating multiple density queries. Additionally, the local region concept is extended to an efficient algorithmic framework which can be applied to any global bandwidth KDEs. The combined solution can significantly improve estimation accuracy while retaining overall linear time/space costs. As an application extension, an outlier detection framework is designed which can effectively detect outliers within multiple data scale representations. / Ph. D.

There has been little research comprehensively documenting wildlife species in Harenna Forest within the Bale Mountains National Park of Ethiopia. This area is one of the few remaining afro-alpine biodiversity hotspots and is home to numerous endemic plants and animals and offers socio-economic benefits to the neighboring communities. Human population pressure, weak land protection policies, and uncertain land tenure rights have led to increases in farmland for subsistence and coffee farming, livestock grazing, and reduction of afro-alpine, shrubland and grassland habitats. Given these challenges, I used 48 camera trap stations to produce an inventory of wildlife species and to determine factors influencing occupancy (i.e., habitat use), detection, and temporal activity and overlap. I recorded 26 terrestrial and arboreal mammalian species and I had sufficient data to model occupancy for 13 species and temporal activity for 14 species. Occupancy and detection were generally higher for herbivores and omnivores (occupancy: 0.28-0.97; detection: 0.1-0.54) than carnivores (occupancy: 0.31-0.80; detection: 0.04-0.18). I found more evidence of positive anthropogenic impacts on herbivore and omnivore occupancy than negative, while detection was influenced by habitat or landscape features, rather than by humans. Carnivore occupancy was largely unaffected by anthropogenic or habitat variables, but detection was strongly, and mostly positively, influenced by anthropogenic impacts. Temporal activity analyses revealed that, for herbivores and omnivores, only tree hyraxes (Dendrohyrax arboreus) and crested porcupines (Hystrix cristata) were nocturnal, Menelik bushbucks (Tragelaphus scriptus meneliki) were crepuscular, and the remaining species ranged from diurnal to cathemeral. Neither similar body size nor similar diet affected overlap between species pairs. However, overlap with human temporal activity was low for Menelik bushbucks (Δ=0.45) and common duikers (Sylvicapra grimmia) appeared to become less active at stations with high human use. For carnivores, leopards (Panthera pardus) and honey badgers (Mellivora capensis) were crepuscular, and the remaining species were nocturnal. I found evidence that carnivores overlapped less when they were more similar in body size to other carnivores (average Δ=0.67-0.71) compared to species more dissimilar in body size (average Δ=0.75), although there was variation across species. In general, carnivores overlapped much less with humans (average Δ=0.20) than did herbivores (average Δ=0.52) and omnivores (average Δ=0.43). Spotted hyenas (Crocuta crocuta), in particular, appeared to alter activity to reduce overlap with humans. This study provides baseline information on presence, distribution, and activity of large- and medium-sized terrestrial and arboreal mammals in an understudied biodiversity hotspot. My findings are concerning for biodiversity conservation as rare and endangered species (e.g., mountain nyalas (Tragelaphus buxtoni), Ethiopian wolves (Canis simensis)) were rarely or never photographed, and larger carnivores (e.g., lions (Panthera leo), leopards, jackals), generally had low capture rates. The species with higher capture rates, occupancy, and activity tended to be those that can tolerate or take advantage of human activity and disturbance. Species sensitive to human disturbance eventually may be lost unless measures can be put in place to reduce human impacts. This baseline knowledge is important for future studies examining trends in mammalian wildlife populations, such as site extinction and colonization, or changes in overlap with humans, in a landscape that is continuing to experience human-caused, landscape change. / Master of Science / Harenna forest, which is located in Bale Mountains National Park, Ethiopia is an important habitat to both wildlife and people. However, it faces a number of challenges as a result of population growth leading to increased coffee farming and livestock grazing resulting in reduced habitat for wildlife species. I used 48 cameras located across the forest to record presence of terrestrial mammals and document their distribution and daily activity across the landscape. I also used data such as vegetation indices, elevation, and distances to human-disturbed areas to determine what influenced wildlife species. Cameras recorded 26 species of mammals. I had enough data to determine distribution for 13 species and daily activity for 14 species. I found that presence across the landscape and activity of herbivores and omnivores was generally higher than that of carnivores. Additionally, I found that human activity or disturbance often had a positive influence on herbivore and omnivore distribution, but my ability to detect species in camera traps was primarily influenced by habitat or landscape features. Carnivore distribution on the landscape was not influenced much by humans or habitat, but their detectability was often positively influenced by presence of humans. In addition to daily activity, I also analyzed overlap in activity between species pairs and between species and humans, to determine whether wildlife changed their temporal activity to overlap less with similar sized competitors or in response to high human use. For herbivores and omnivores, I found that tree hyraxes and crested porcupines were active at night, Menelik's bushbucks were active at sunrise and sunset, and cape bushbucks, common duiker, olive baboon, bushpig, and giant forest hogs were active either during the day or throughout the day and night. I found little evidence that the herbivores or omnivores avoided each other temporally and only the Menelik bushbuck and duiker appeared to avoid humans. For carnivores, I found that leopards and honey badgers were active early morning and evening, and the common genet, African civet, white-tailed mongoose, and spotted hyenas were all active at night only. Carnivores generally overlapped less with humans than herbivores and omnivores. I found some evidence that carnivores more similar in body size had lower temporal overlap with each other and that spotted hyaenas appeared to avoid activity during times of day when humans were active. My study not only provides baseline information on terrestrial and arboreal mammals present in Harenna forest, Ethiopia, but is also necessary for understanding how wildlife species use the landscape and particularly how presence of humans influences wild animal behavior. My findings are concerning for biodiversity conservation because I had few to no photographs, respectively, of the endangered mountain nyala and Ethiopian wolf. In fact, most of the species with a wide distribution on the landscape, or with high activity, were common or smaller species that are tolerant of, or could take advantage of, human disturbance. Without concerted effort to curtail the current landscape change caused by humans, the area is likely to lose species less tolerant of humans, and biodiversity will ultimately decline.