Over half the U.S. labor force is employed by small business owners, yet only 50% of small businesses survive beyond 5 years. The purpose of this multiple case study was to explore sustainability strategies small business owners in the construction industry used to sustain their organization for longer than 5 years. The research population included 5 owners of small businesses in the construction industry in Georgia, who have been in operation for a minimum of 5 years. The conceptual framework for this study was general systems theory. Data were collected through semistructured interviews, organizational documentation reviews, and business plan reviews. Yin'€™s (2014) 4 principles of data collection were used to collect the data: use multiple sources of evidence, create a case study database, maintain a chain of evidence, and exercise care when using data from electronic sources. Data were triangulated using Yin's 5-€step analysis process: collecting data, grouping data into codes, grouping data into themes, assessing the themes, and developing conclusions. Member checking, transcript review, and triangulation of data were used to further validate the study. The 4 themes that emerged from the study were internal relationships, building the brand, specialization, and planning. The implications of the study for positive social change include the potential for small businesses in the construction industry to survive for longer than 5 years and to increase the number of individuals employed.

The system of Labor Pension in Taiwan deeply influences every class of labor and its intention and regulation of retirement system also affects to operation of government financial budget. The study aims to discuss the trend toward fewer children and the population aging which are somehow affecting forward finance perspective of holistic Labor Pension Fund. Especially, we confront an unbalance situation of population structure, how it reflected the contribution income of labor pension fund and its disbursement of pension payment and how it associated to operation of Labor Pension Fund. In addition, the government should be realized how to deal with the development of population in the future, gear up for designing a better supplementary measure. Therefore, the study will be analyzed with aspect of finance on the population aging phenomenon and how birth rate decline affect toward the New Labor Pension System and Old Labor Pension System. Hopefully, the study results can benefit our labor retirement policy. The study results as follows: A. For the trend toward fewer children, in the short term, the evidence shows that it is unclear either on contribution of the New Labor Pension System or Old Labor Pension System. However, in the mid- and long term, the contribution of fund will be gradually affected, beginning to decrease slowly with the contribution. B. For the population aging phenomenon, Old Labor Pension System on payment from fund indicted that incomes are much more than disbursements so it won¡¦t be a burden on Old Labor Pension Fund. On the contrary, due to different payment regulation between New Labor Pension System and Old Labor Pension System, the population aging is irrelevant to disbursement of New Labor Pension.

abstract: De facto potable reuse (DFR) occurs when surface water sources at drinking water treatment plants (DWTPs) contain treated effluents from upstream wastewater treatment plants (WWTPs). Contaminants of emerging concerns (CECs) originate from treated effluents (e.g., unregulated disinfection by-products, pathogenic microorganisms as Cryptosporidium oocyst, Giardia cyst, and Norovirus) can be present in surface water and pose human health risks linked to CECs. Previously developed De facto Reuse Incidence in our Nations Consumable Supply (DRINCS) model predicted DFR for the national largest DWTPs that serve >10,000 people (N = 2,056 SW intakes at 1,210 DWTPs). The dissertation aims to quantify DFR at all surface water intakes for smaller DWTPs serving ≤10,000 people across the United States and develop a programmed ArcGIS tool for proximity analysis between upstream WWTPs and DWTPs. The tested hypothesis is whether DWTPs serving ≤10,000 people are more likely to be impacted by DFR than larger systems serving > 10,000 people.The original DRINCS model was expanded to include all smaller DWTPs (N = 6,045 SW intakes at 3,984 DWTPs) in the U.S. First, results for Texas predicted that two-thirds of all SW intakes were impacted by at least one WWTP upstream. The level of DFR at SW intakes in Texas ranged between 1% to 20% under average flow and exceeded 90% during mild droughts. Smaller DWTPs in Texas had a higher frequency of DFR than larger systems while < 10% of these DWTPs employed advanced technology (AT) capable of removing CECs. Second, nationally over 40% of surface water intakes at all DWTPs were impacted by DFR under average flow (2,917 of 6,826). Smaller DWTPs had a higher frequency (1,504 and 1,413, respectively) of being impacted by upstream WWTP discharges than larger DWTPs. Third, the difference in DFR levels at smaller versus larger DWTPs was statistically unclear (t-test, p = 0.274). Smaller communities could have high risks to CECs as they rely on surface water from lower-order streams impacted by DFR. Furthermore, smaller DWTPs lack more than twice as advanced unit processes as larger DWTPs with 52.1% and 23%, respectively. DFR levels for DWTPs serving > 10,000 people were statistically higher on mid-size order streams (3, 5, and 8) than those for smaller DWTPs. Finally, DWTPs serving > 10,000 people could pose risks to a population impacted by DFR > 1% as 40 times as those served by smaller DWTPs with 71 million and 1.7 million people, respectively. The total exposed population to risks of CECs served by DWTPs impacted by upstream WWTP discharges (DFR >10%) was estimated at 12.3 million people in the United States. Future studies can use DRINCS results to conduct an epidemiological risk assessment for impacted communities and identify communities that would benefit from advanced technology to remove CECs. / Dissertation/Thesis / Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2020

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This work focuses on analysing and improving feature detection and matching. After creating an initial framework of study, four main areas of work are researched. These areas make up the main chapters within this thesis and focus on using the Scale Invariant Feature Transform (SIFT).The preliminary analysis of the SIFT investigates how this algorithm functions. Included is an analysis of the SIFT feature descriptor space and an investigation into the noise properties of the SIFT. It introduces a novel use of the a contrario methodology and shows the success of this method as a way of discriminating between images which are likely to contain corresponding regions from images which do not. Parameter analysis of the SIFT uses both parameter sweeps and genetic algorithms as an intelligent means of setting the SIFT parameters for different image types utilising a GPGPU implementation of SIFT. The results have demonstrated which parameters are more important when optimising the algorithm and the areas within the parameter space to focus on when tuning the values. A multi-exposure, High Dynamic Range (HDR), fusion features process has been developed where the SIFT image features are matched within high contrast scenes. Bracketed exposure images are analysed and features are extracted and combined from different images to create a set of features which describe a larger dynamic range. They are shown to reduce the effects of noise and artefacts that are introduced when extracting features from HDR images directly and have a superior image matching performance. The final area is the development of a novel, 3D-based, SIFT weighting technique which utilises the 3D data from a pair of stereo images to cluster and class matched SIFT features. Weightings are applied to the matches based on the 3D properties of the features and how they cluster in order to attempt to discriminate between correct and incorrect matches using the a contrario methodology. The results show that the technique provides a method for discriminating between correct and incorrect matches and that the a contrario methodology has potential for future investigation as a method for correct feature match prediction.