This study aims to investigate the influence of air pollutant concentration and meteorological factors on the atmospheric visibility in Taipei basin. First of all, we collected air quality data measured by ambient air quality monitoring stations of EPA (Environmental Protection Administration) and the meteorological factors monitored by Tamsui and Taipei meteorological stations separately, based on the range of three observation directions. We then analyzed the data by PCA (principal component analysis) to determine the main effective factors on atmospheric visibility under low visibility condition. In order to comprehend the spatial and temporal distribution of atmospheric visibility, we collected the atmospheric visibility data from Taipei meteorological observation stations for the past twenty-two years (1984~2005), it showed that the atmospheric visibility increased gradually. The seasonal variation of visibility was also observed, the best season was autumn (10.7 km) and the worst season was spring (7.5 km). Furthermore, according to the monthly statistical results, the visibility trends in the Taipei Basin can be separated into three typical periods: low visibility period (January to May), transitional period (June to September), high visibility period (October to December). The average atmospheric visibilities observed at the Tamsui, Songshan, and Sindian directions were 10.66 km , 9.54 km and 8.44 km, respectively. In general, the visibility at the Tamsui direction was slightly higher than those from other two directions. The results showed that atmospheric visibility was influenced not only by air pollutant levels and meteorological factors, but also affected by local topography of Taipei Basin. This study revealed that the atmospheric visibility data led on the Tamsui, Songshan observation directions is better. Four intensive observations of atmospheric visibility were conducted during March 28~April 1, July 4~8, September 19~23, and November 14~18 in the year of 2006, respectively. The results showed that the atmospheric visibilities at Tamsui direction were generally higher than other two directions. The visibilities observed in the afternoon were generally higher than those in the morning. Results obtained from the principle component analysis showed that the atmospheric visibility in the Taipei Basin were mainly influenced by PM10, NOx and CO, that mobile sources was the main cause of low visibility in the Taipei Basin. In addition, Tamsui region were affected by PM10 and SO2 more than Songshan and Sindian regions, which was influenced by neighboring industrial and the power plants. In the meteorological factors, wind speed and temperature have more influence on atmospheric visibility, however, the relationship between atmospheric visibility and relative humidity was somehow irregular. The analysis of the spatial distribution of air pollutants showed that low visibilities can not be caused only by high air pollutant concentration within the region, it may caused by the rise of air pollutant concentration in the transition region.

With the aid of modern sensors it is possible to create models of buildings. These sensorstypically generate 3D point clouds and in order to increase interpretability and usability,these point clouds are often translated into 3D models.In this thesis a way of translating a 3D point cloud into a 3D model is presented. The basicfunctionality is implemented using Matlab. The geometric model consists of floors, wallsand ceilings. In addition, doors and windows are automatically identified and integrated intothe model. The resulting model also has an explicit representation of the topology betweenentities of the model. The topology is represented as a graph, and to do this GraphML isused. The graph is opened in a graph editing program called yEd.The result is a 3D model that can be plotted in Matlab and a graph describing the connectivitybetween entities. The GraphML file is automatically generated in Matlab. An interfacebetween Matlab and yEd allows the user to choose which rooms should be plotted.

Antioxidants are molecules capable of stabilizing and preventing oxidation. Certain peptides, protein hydrolysates, have shown antioxidant capacities, which are obtained once liberated from the native protein structure. Soy protein isolates (SPI) were enzymatically hydrolyzed by pepsin and pancreatin mixtures. The soy protein hydrolysates (SPH) were fractionated with sequential ultrafiltration (UF) and nanofiltration (NF) membrane steps. Heat pre-treatment of SPI at 95 degrees celsius (C) for 5 min prior to enzymatic hydrolysis was investigated for its effect on peptide distribution and antioxidant capacity. SPH were subjected to UF with a 10 kDa molecular weight cut off (MWCO) polysulfone membrane. UF permeate fractions (lower molecular weight than 10 kDa) were fractionated by NF with a thin film composite membrane (2.5 kDa MWCO) at pH 4 and 8. Similar peptide content and antioxidant capacity (α=0.05) were obtained in control and pre-heated SPH when comparing the respective UF and NF permeate and retentate fractions produced. FCR antioxidant capacities of the SPH fractions were significantly lower than their ORAC antioxidant capacities, and the distribution among the UF and NF fractions was generally different. Most UF and NF fractions displayed higher antioxidant capacities when compared to the crude SPI hydrolysates, showing the importance of molecular weight on antioxidant capacity of peptides. The permeate fractions produced by NF at pH 8 displayed the highest antioxidant capacity, expressed in terms of Trolox equivalents (TE) per total solids (TS): 5562 μmol TE/g TS for control SPH, and 5187 μmol TE/g TS for pre-heated SPH. Due to the improvement in antioxidant capacity of peptides by NF at pH 8, the potential for NF as a viable industrial fractionation process was demonstrated. Principal component analysis (PCA) of fluorescence excitation-emission matrix (EEM) data for UF and NF peptide fractions, followed by multi-linear regression analysis, was assessed for its potential to monitor and identify the contributions to ORAC and FCR, two in vitro antioxidant capacity assays, of SPH during membrane fractionation. Two statistically significant principal components (PCs) were obtained for UF and NF peptide fractions. Multi-linear regression models (MLRM) were developed to estimate their fluorescence and PCA-captured ORAC (ORAC-FPCA) and FCR (FCR-FPCA) antioxidant capacities. The ORAC-FPCA and FCR-FPCA antioxidant capacities for NF samples displayed strong, linear relationships at different pH conditions (R-squared>0.99). Such relationships are believed to reflect the individual and relative combined contributions of tryptophan and tyrosine residues present in the SPH fractions to ORAC and FCR antioxidant capacities. Therefore, the proposed method provides a tool for the assessment of fundamental parameters of antioxidant capacities captured by ORAC and FCR assays.

A detailed study is held in Lake Eymir, a shallow eutrophic lake, investigating the phosphorus concentrations in water and the bottom sediment. Water depth, secchi depth, TSS, sediment soluble total phosphorus, sediment soluble PO4-P, Chl-a , TKN, NH4-N, NO2-N, NO3-N, alkalinity, temperature, pH, conductivity, dissolved oxygen, turbidity and PAR parameters are monitored for 21 months and Principal Component Analysis (PCA) is applied to identify trend of phosphorus concentration in water column. Results indicated that total phosphorus concentrations in water column and sediment at lake bottom are susceptible to changes caused by the variations in other water quality parameters compared to average, surface and mid-depth values. Correlations observed between P and other parameters were the highest in Bottom &ndash / 3 data set. In order to model sediment soluble total phosphorus in Lake Eymir, chlorophyll-a, NH3, total phosphorus, PO4-P, temperature, conductivity, pH, turbidity, &Delta / T and dissolved oxygen are defined as effective parameters. Linear regression models were more successful in predicting sediment soluble phosphorus concentrations compared to non-linear ones. Turbidity is a good tracer for total phosphorus concentrations in Lake Eymir. Temperature is seasonally effective on phosphorus concentrations, and may create stratified water in summer. Stratification causes phosphorus to build up in bottom water layer. Particle size distribution results show that area of sampling point 1 has different characteristics compared to other sampling locations since it is located at the inlet. The exchange of phosphorus from water to sediment is mostly completed within the first 7-8 hours. On average, 30% of the exchange is completed in an hour. It is clearly seen that although sediment layer in the lake is a phosphorus source, it has not reached its phosphorus binding capacity yet. Adsorption isotherm is found to be pseudo-second-order with a coefficient of determination greater than 0.9909 at all sampling points. Sediment phosphorus content has been fractioned into NH4Cl-P, BD-P, NaOH-P and HCl-P in order to identify permanent and bioavailable parts. Fractionation results show that even if the soluble concentrations are low, they are high enough to cause eutrophication problems.

Retinal pigment epithelium (RPE) is a principal site of pathogenesis in age-related macular de-generation (AMD). AMD is a main source of vision loss even blindness in the elderly and there is no effective treatment right now. Our aim is to describe the relationship between the morphology of RPE cells and the age and genotype of the eyes. We use principal component analysis (PCA) or functional principal component method (FPCA), support vector machine (SVM), and random forest (RF) methods to analyze the morphological data of RPE cells in mouse eyes to classify their age and genotype. Our analyses show that amongst all morphometric measures of RPE cells, cell shape measurements (eccentricity and solidity) are good for classification. But combination of cell shape and size (perimeter) provide best classification.

A topic of research that is frequently studied in Structural Biology is the problem of determining the degree of similarity between two protein structures. The most common solution is to perform a three dimensional structural alignment on the two structures. Rigid structural alignment algorithms have been developed in the past to accomplish this but treat the protein molecules as immutable structures. Since protein structures can bend and flex, rigid algorithms do not yield accurate results and as a result, flexible structural alignment algorithms have been developed. The problem with these algorithms is that the protein structures are represented using thousands of atomic coordinate variables. This results in a great computational burden due to the large number of degrees of freedom required to account for the flexibility. Past research in dimensionality reduction techniques has shown that a linear dimensionality reduction technique called Principal Component Analysis (PCA) is well suited for high dimensionality reduction. This thesis introduces a new flexible structural alignment algorithm called FlexSADRA, which uses PCA to perform flexible structural alignments. Test results show that FlexSADRA determines better alignments than rigid structural alignment algorithms. Unlike existing rigid and flexible algorithms, FlexSADRA addresses the problem in a significantly lower dimensionality problem space and assesses not only the structural fit but the structural feasibility of the final alignment.

Microbial fuel cells were designed and operated using waste activated sludge as a substrate and as a source of microorganisms for the anodic chamber. Waste activated sludge provided a bacterial consortium predisposed to the solubilization of particulate matter and utilization of substrates commonly found in wastewater. Dissolved oxygen and ferricyanide were used as the electron acceptors in the catholytes. Microbial fuel cell comparisons were made while operating under identical conditions but using the two different electron acceptors. Comparisons were based on the electricity production observed during MFC operation, wastewater quality of the waste activated sludge anolytes and the community level physiological profiling of the microbial communities in the anolytes. Electrons liberated during substrate utilization in the anodic chamber traveled to the cathodic chamber where they reduced the electron acceptors. The anode and cathode chambers were connected by a Nafion ® proton exchange membrane to allow for cation migration. Various soluble carbon sources were dosed to the microbial fuel cells at measured intervals during operation via direct injection to the anolyte. During bovine serum albumin dosing, average power production levels reached 0.062 mW and 0.122 mW for the dissolved oxygen microbial fuel cell and the ferricyanide microbial fuel cell, respectively. These were 100% and 25% greater than the power production levels observed throughout the rest of the study. Increases in current production were observed following the dosing of sodium acetate, glucose and bovine serum albumin. No increase in current was observed following glycerol dosing. Sodium acetate dosing triggered an immediate response, while glucose and bovine serum albumin responded in approximately 2 minutes. A chemical oxygen demand mass balance was calculated for both microbial fuel cells. The lack of balance closure was attributed to unmeasured methane production. An accumulation of particulate waste activated sludge components was observed for both microbial fuel cells. The anolyte pH during operation was typically less than waste activated sludge pH, which was attributed to volatile fatty acid accumulation in the anolytes during fermentation processes. Community level physiological profiling was accomplished through the analysis of ecological data obtained with BIOLOG ® ECOplates. Samples were plated and analyzed under anaerobic conditions, mimicking the environment in the anode chamber of the MFCs. ECOplate data were transformed by a logarithmic function prior to principle component analysis. The community level physiological profiling indicated that shifts in the microbial community profile, as measured through the carbon source utilization patterns, occurred throughout acclimation and following the dosing of various carbon source substrates. Shifts due to glycerol dosing differed from shifts due to the dosing of sodium acetate, glucose and bovine serum albumin.

Saab Ericsson Space AB develops products for space for a predetermined price. Since the price is fixed, it is crucial to have a reliable prediction model to estimate the effort needed to develop the product. In general software effort estimation is difficult, and at the software department this is a problem. By analyzing metrics, collected from former projects, different prediction models are developed to estimate the number of person hours a software project will require. Models for predicting the effort before a project begins is first developed. Only a few variables are known at this state of a project. The models developed are compared to a current model used at the company. Linear regression models improve the estimate error with nine percent units and nonlinear regression models improve the result even more. The model used today is also calibrated to improve its predictions. A principal component regression model is developed as well. Also a model to improve the estimate during an ongoing project is developed. This is a new approach, and comparison with the first estimate is the only evaluation. The result is an improved prediction model. There are several models that perform better than the one used today. In the discussion, positive and negative aspects of the models are debated, leading to the choice of a model, recommended for future use.

A topic of research that is frequently studied in Structural Biology is the problem of determining the degree of similarity between two protein structures. The most common solution is to perform a three dimensional structural alignment on the two structures. Rigid structural alignment algorithms have been developed in the past to accomplish this but treat the protein molecules as immutable structures. Since protein structures can bend and flex, rigid algorithms do not yield accurate results and as a result, flexible structural alignment algorithms have been developed. The problem with these algorithms is that the protein structures are represented using thousands of atomic coordinate variables. This results in a great computational burden due to the large number of degrees of freedom required to account for the flexibility. Past research in dimensionality reduction techniques has shown that a linear dimensionality reduction technique called Principal Component Analysis (PCA) is well suited for high dimensionality reduction. This thesis introduces a new flexible structural alignment algorithm called FlexSADRA, which uses PCA to perform flexible structural alignments. Test results show that FlexSADRA determines better alignments than rigid structural alignment algorithms. Unlike existing rigid and flexible algorithms, FlexSADRA addresses the problem in a significantly lower dimensionality problem space and assesses not only the structural fit but the structural feasibility of the final alignment.

Microbial fuel cells were designed and operated using waste activated sludge as a substrate and as a source of microorganisms for the anodic chamber. Waste activated sludge provided a bacterial consortium predisposed to the solubilization of particulate matter and utilization of substrates commonly found in wastewater. Dissolved oxygen and ferricyanide were used as the electron acceptors in the catholytes. Microbial fuel cell comparisons were made while operating under identical conditions but using the two different electron acceptors. Comparisons were based on the electricity production observed during MFC operation, wastewater quality of the waste activated sludge anolytes and the community level physiological profiling of the microbial communities in the anolytes. Electrons liberated during substrate utilization in the anodic chamber traveled to the cathodic chamber where they reduced the electron acceptors. The anode and cathode chambers were connected by a Nafion ® proton exchange membrane to allow for cation migration. Various soluble carbon sources were dosed to the microbial fuel cells at measured intervals during operation via direct injection to the anolyte. During bovine serum albumin dosing, average power production levels reached 0.062 mW and 0.122 mW for the dissolved oxygen microbial fuel cell and the ferricyanide microbial fuel cell, respectively. These were 100% and 25% greater than the power production levels observed throughout the rest of the study. Increases in current production were observed following the dosing of sodium acetate, glucose and bovine serum albumin. No increase in current was observed following glycerol dosing. Sodium acetate dosing triggered an immediate response, while glucose and bovine serum albumin responded in approximately 2 minutes. A chemical oxygen demand mass balance was calculated for both microbial fuel cells. The lack of balance closure was attributed to unmeasured methane production. An accumulation of particulate waste activated sludge components was observed for both microbial fuel cells. The anolyte pH during operation was typically less than waste activated sludge pH, which was attributed to volatile fatty acid accumulation in the anolytes during fermentation processes. Community level physiological profiling was accomplished through the analysis of ecological data obtained with BIOLOG ® ECOplates. Samples were plated and analyzed under anaerobic conditions, mimicking the environment in the anode chamber of the MFCs. ECOplate data were transformed by a logarithmic function prior to principle component analysis. The community level physiological profiling indicated that shifts in the microbial community profile, as measured through the carbon source utilization patterns, occurred throughout acclimation and following the dosing of various carbon source substrates. Shifts due to glycerol dosing differed from shifts due to the dosing of sodium acetate, glucose and bovine serum albumin.