The national government gave up defense of mainland Chinese and a large number of accompanying troops retreated into Taiwan in 1949. After many years, these soldiers continually retired from the military. In order to take care of these groups of retired soldiers who had contributed to the nation, the Taiwanese government set up a veteran status system. These veterans are also Taiwanese citizens, but they hold a double citizenship, and they can benefit from different departments. This study started with veterans¡¦ social capital points of view in order to see the relationships between the soldiers¡¦ knowledge of welfare, level of needs for welfare use, their satisfaction with welfare, and the number of social capital they have received. The research randomly selected samples and used a face-to-face survey with 250 veterans who are Kaohsiung city citizens and aged 65 and over. Effective surveys of 225 were received. The results of the research show that the age factor influences the participants¡¦ satisfaction about the welfare system. The participants¡¦ veteran ranks, religious beliefs, and current living conditions are related to their knowledge and use of the welfare offered by the government. Veterans with middle-low income have less knowledge of the welfare from the Veterans Affairs Commission and the Department of Health, and also know less about the welfare items offered by the Department of Social Welfare. From the social capital point of view, the more abundant social capital the participants have, the higher knowledge of welfare they have. However, different social capital systems will also affect satisfaction with welfare used. Veterans are more satisfied with using welfare if social capital is abundant in the family system, the neighborhood, community system, and the Veterans Affairs Commission. On the other hand, veterans are less satisfied with using welfare if social capital abundance is evident in the Department of Social Welfare and other systems. In addition, the results also show a significant positive relationship between the participants¡¦ knowledge and use of welfare. The more welfare items they know, the more they use. These results offer suggestions to the individual government departments, including the Veterans Affairs Commission, Department of Social Welfare, and Department of Health, as well as interdepartmental collaboration. Each of the related departments should strengthen their welfare campaigns and service mechanisms. Most importantly, they should improve their integration in order to avoid overlapping and waste on welfare services. In addition, they must set up good referral and transition services and carry out the welfare measures to benefit the veterans in need.

In this thesis, I propose a method for establishing a personalized recommendation system for re-ranking web search results and recommending web contents. The method is based on personal reading interest which can be reflected by the user’s dwell time on each document or webpage. I acquire document-level dwell times via a customized web browser, or a mobile device. To obtain better precision, I also explore the possibility of tracking gaze position and facial expression, from which I can determine the attractiveness of different parts of a document. Inspired by idea of Google Knowledge Graph, I also establish a graph-based ontology to maintain a user profile to describe the user’s personal reading interest. Each node in the graph is a concept, which represents the user’s potential interest on this concept. I also use the dwell time to measure concept-level interest, which can be inferred from document-level user dwell times. The graph is generated based on the Wikipedia. According to the estimated concept-level user interest, my algorithm can estimate a user’s potential dwell time over a new document, based on which personalized webpage re-ranking can be carried out. I compare the rankings produced by my algorithm with rankings generated by popular commercial search engines and a recently proposed personalized ranking algorithm. The results clearly show the superiority of my method. I also use my personalized recommendation framework in other applications. A good example is personalized document summarization. The same knowledge graph is employed to estimate the weight of every word in a document; combining with a traditional document summarization algorithm which focused on text mining, I could generate a personalized summary which emphasize the user’s interest in the document. To deal with images and videos, I present a new image search and ranking algorithm for retrieving unannotated images by collaboratively mining online search results, which consists of online images and text search results. The online image search results are leveraged as reference examples to perform content-based image search over unannotated images. The online text search results are used to estimate individual reference images’ relevance to the search query as not all the online image search results are closely related to the query. Overall, the key contribution of my method lies in its ability to deal with unreliable online image search results through jointly mining visual and textual aspects of online search results. Through such collaborative mining, my algorithm infers the relevance of an online search result image to a text query. Once I estimate a query relevance score for each online image search result, I can selectively use query specific online search result images as reference examples for retrieving and ranking unannotated images. To explore the performance of my algorithm, I tested it both on a standard public image datasets and several modestly sized personal photo collections. I also compared the performance of my method with that of two peer methods. The results are very positive, which indicate that my algorithm is superior to existing content-based image search algorithms for retrieving and ranking unannotated images. Overall, the main advantage of my algorithm comes from its collaborative mining over online search results both in the visual and the textual domains. / published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

This research examines the time used by teenagers, aged 16 to 19 years, the types of activities teenagers do, and the impact of internet usage on their non-fixed activities during weekdays. The data employed for this research is the 2009 National Household Travel Survey (NHTS 2009). For this study, socio-demographic factors (such as age, gender, race, work status, immigrant status, number of individuals in the household, number of children in the household, number of workers in the household, household income, and others), non-fixed activities (at home, shopping, personal business, physical, recreational and social, meals, religious, and others), time spent on non-fixed activities, and internet use among teenagers were taken into consideration. The methodology in this research uses an ordered response model to analyze internet usage, and a Multiple Discrete Continuous Extreme Value model (MDCEV) to analyze the activity participation. The results show that individual and household demographic characteristics have an impact on internet usage, as well as, internet usage is found to have a significant impact on the activity participation behavior of teenagers. / text

There has been little understanding of how consumers adopt and use the mobile Internet. This dissertation seeks to bridge this gap in prior literature by focusing on consumers’ cross-platform consumption behavior on mobile devices. The first study of this dissertation addresses how the adoption of mobile applications influences the use of corresponding mobile websites. Pseudo-panel analysis based on repeated cross-sectional data suggests that the introduction of a mobile app by a major national media company leads to a significant increase in demand at the corresponding mobile news website. In addition, it reports that this effect is greater for consumers with higher appreciation for concentrated news content, with stronger propensity for a particular political viewpoint, and with fewer time constraints. The results are consistent with the interpretation that adoption of a provider’s news app stimulates corresponding mobile news website visits. The second study of this dissertation examines whether the quality of local fixed-line Internet service influences mobile Internet adoption and usage. An empirical analysis shows that local fixed-line Internet speed relates negatively to mobile Internet adoption and usage; if the local fixed-line connection is insufficient, consumers tend to get online through their mobile phones. Further, better local mobile Internet speed increases the likelihood of adopting and using the mobile Internet. Neither fixed-line nor mobile Internet speed has significant impacts on mobile-specific offline services such as taking photos or videos. In some circumstances, competition between the two platforms is stronger, such as among younger consumers and those living in areas with lower fixed-line Internet speeds.

Messenger RNA transcripts of αs2- and к-casein are translated at 25% of the efficiency of αs1- and β-casein transcripts; however, the molecular mechanisms governing the difference are unknown. We hypothesized that the bovine casein translational efficiency is influenced by characteristics of the untranslated regions (UTRs) and coding regions. The main objective of this study was to identify molecular mechanisms that explain differential translational regulation between bovine β- and αs2-casein by assessing the role of each putative translational regulatory factor found throughout full-length sequences in both in cellular and cell-free translation systems. This dissertation begins with the cloning and initial characterization of bovine β- and αs2-casein. Transcript analysis indicates that the two genes share similar characteristics of nucleotide sequence around the coding region and secondary structure. It is confirmed that αs2-casein mRNA has a lower translational efficiency compared to that of β-casein in a cell-free system. The latter portion of this thesis investigates further the UTRs and codon usage effect on difference in translational efficiency between β- and αs2-casein. Overall, our data suggest that β-casein 3’ UTR and αs2-casein 5’ UTR exert stimulatory effects on translation yet their effectiveness depends on the upstream and downstream sequences with which they are associated. Replacement of the UTRs of αs2-casein mRNA with those of β-casein did not stimulate translation. A stronger effect on translational efficiency was found in the coding region of αs2-casein which displays unfavourable codons at the 3’ terminus. Deletion of a 28-codon fragment from the 3’ terminus of the αs2-casein coding region increased translation to a par with β-casein. We suggest that the last 28 codons of αs2-casein is the main regulatory sequence that attenuates its expression and is responsible for the different translational expression of β- and αs2-casein mRNAs. Identification of regulatory factors that are responsible for translation efficiency improves our understanding of the molecular mechanisms of control of milk protein prodiction in secretory cells of the bovine mammary glands. / NSERC canada

The purpose of this project is to evaluate the effects of a campaign that Uppsalahem implemented in February 2013, in order to make their tenants consume less water. The result of the campaign is evaluated in terms of reduced water usage and reduced emissions of greenhouse gas related to the heating of the water through district heating. Four different residential areas in urban Uppsala, where Uppsalahem implemented their water saving campaign have been studied. All calculations are done in MATLAB. The results regarding water usage is presented in cubic meters and the greenhouse gas emissions are presented in terms of carbon dioxide equivalents. A sensitivity analysis of the data is performed in order to study natural occurring variances of water consumption over time. In order to determine which parameter has the greatest impact on reducing carbon dioxide emissions, a sensitivity analysis of the fuel mix used at the district heating power plant is made. The results show that there has been a reduction of water usage since after the campaign was implemented and the sensitivity analysis of the data indicates that there has been an especially large decrease in water consumption between the years 2012 and 2013. Further though, the results contain monthly irregularities in water usage in the different areas. This shows that the reduction of water consumption has not been temporally associated to the campaign, which indicates that the reduction might not be an effect of the campaign. Regarding carbon dioxide emissions, the sensitivity analysis indicates that the kind of fuel mix Vattenfall use at their district heating plant has a much greater impact than the individual water usage behaviors of the tenants.

No description available.

No description available.

This thesis investigates the use of combined field and satellite data for crop identification and area estimation in County Durham, Northeast England. The satellite data were obtained by the Thematic Mapper (TM) sensor onboard Landsat-5 on 31 May 1985. The TM data were geometrically corrected to the British National Grid and the county boundaries were digitized in order to apply the methodology used in this study on a county basis. The field data were obtained by applying a stratified random sampling strategy. The area was subdivided into five main strata and forty four 1km(_^2) sample units were randomly chosen and fully surveyed by the author using a pre-prepared questionnaire. The field area measurements were taken and the final hectarage estimates were obtained for each crop. The research demonstrated the ability of Landsat-TM data to discriminate between agricultural crops in the study area. Results obtained emphasised that satellite data can be used for identification of agricultural crops over large geographic areas with small field sizes and different environmental and physical features. A land-cover classification system appropriate to the study area was designed. Using the Landsat-TM data, the study produced a classification map of thirteen land-cover types with more than 80% accuracy. The classification accuracy was assessed quantitatively by using the known land-use information obtained from the sample units visited during the field survey. The study analysed the factors which influenced the degree of separability between different agricultural crops since some crops were more clearly identified than others. Using a double sampling method based on the combination of both Landsat- TM and field data in regression analysis, a hectarage estimate was produced for each crop type in County Durham. The results obtained showed that the regression estimator was always more efficient than the field estimator. Crop area estimated by regression reduced the imprecision in all strata and was more efficient in some strata than others. This indicated that a gain in precision was achieved by using Landsat- TM in conjunction with the field data. The results illustrated that stratification based on an environmental criterion was an efficient approach as far as the the application of agricultural remote sensing in County Durham is concerned. The stratified approach allowed each stratum to be analysed separately, thereby lessening the reliance on cloud free imagery for the whole county on any given date. Furthermore, the results obtained by this study suggest that it is possibile to link remote sensing data with existing county based information systems on agricultural and land-use.

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2005. / Includes bibliographical references (leaves 142-151). Also available in electronic version.