In recent years, the Asian dust storms occurred frequently. It was estimated that approximately eight hundred million metric tons of Asian dusts transported to the atmosphere yearly. During the dust storm period, Asian dusts not only induce poor air quality, but also reduce atmospheric visibility and influence human health. In order to investigate the physicochemical characteristics and source allocation of Asian dusts, this study collect the Asian dusts in the Pescadores Islands during the years of 2002~2006. In addition, this study collected top soils in three regions of Inner Mongolia and resuspended the soil samples in a resuspension chamber to analyze their chemical composition. Moreover, this study applied enrichment factor analysis (EF) and grey relational analysis to allocate the potential sources of Asian dusts and compare them with the transportation routes obtained from backward trajectory. During Asian dust storm periods, the concentration of atmospheric particulate matter (PM10) in the Pescadores Islands increased significantly, probably is 3~6 times of PM10 during non-dust storm periods. Among them, coarse particles (PM2.5-10) particularly rose from 10~30 £gg/m3 to 80~130 £gg/m3 and the size distribution changed from bi-modal distribution to single modal distribution of coarse particles during Asian dust storm periods. This study further analyzed the chemical composition of Asian dusts, including water-soluble ionic species, carbon contents, and metallic contents. For fine particles (PM2.5), the order of water-soluble ionic species was SO42- > NH4+ > NO3- > Cl- > Ca2+ > Na+ > K+ > Mg2+ > F-. For coarse particles (PM2.5-10), the order of water-soluble ionic species was Cl- > SO42- > NO3- > Na+ > Ca2+ > NH4+ > Mg2+ > K+ > F-. The carbon contents distributes mainly in fine particles. The major contents of both fine and coarse particles were crustal elements (i.e. Al, Fe, Na, Mg, K, Ca, and Sr). In addition to the analysis of physicochemical characteristics of Asian dusts, this study applied HYSPLIT MODEL to figure out their transportation routes by backward trajectory. According to the backward trajectories, this study compartmentalized Asian dusts storm transportation routes into three categories: Eastward Transportation and Retraced (ETR), Southeasterly Transportation and Circumrotated (STC), and Straight Southeasterly Transportation (SST). Analyzing the spatial and temporary background variables to investigate the influence of transportation routes on Asian dusts¡¦ physicochemical characteristic. This study revealed that the physicochemical characteristics were very similar for same category of Asian dust storms, which can be used to allocate the source regions of Asian dust storms. This study resuspended the soil samples collected in Inner Mongolia inside a resuspension chamber and collected the suspended particles (PM2.5, PM2.5-10) for chemical analysis. Chemical analysis results indicated that the fingerprints of chemical composition for different regions were similar but still distinguishable, which can be used to identify the source areas of Asian dusts. This study further compare and correlate the Asian dusts collected at the Pescadores Islands during Asian dust storm periods with the soils collected in Inner Mongolia chemically by enrichment factor and grey relational analysis. This study further compared the source allocation of Asian dust storms obtained from enrichment factor, grey relational analysis, and backward trajectory and found the results of these three methods were quite similar. For enrichment factor analysis, 88% of similarity was obtained by using two separate reference elements (Al and Fe). The similarity of backward trajectory and grey relational analysis reached as high as 83%. Moreover, the backward trajectory and enrichment factor were similar up to 75%, while the grey relational analysis and enrichment factor were similar up to 69%. Overall, two out of three aforementioned methods can effectively allocate the source regions of Asian dusts by 94%, while all three methods can successfully allocate the source regions of Asian dusts by 56%. Comparison of three aforementioned methods showed that they can be applied to allocate the source regions of Asian dusts.

Kaohsiung region with high percentage (6-8%) of poor air quality (PSI>100) has been announced officially by Taiwan Environmental Protection Administration (TEPA) as the worst air quality region among seven Air Quality Zones (AQZ) in Taiwan. Air pollutant dispersion was influenced by many factors including meteorology and topography. Particulate matter (PM) transportation caused by northeastern monsoon and/or sea land breeze might resulted in air pollution episodes. In summer, PM might be transported back and forth across the coastline of Kaohsiung region by sea land breeze. Particularly, high PM10 concentration has been observed at the inland sites in the daytime due to sea breeze. In autumn and winter, PM could be transported northeasterly to the inland range and covered a huge area of entire region. The objective of this study was to investigate the accumulation of particulate matter in the near-ocean region due to northeastern monsoon and sea-land breeze, and the spatial and temporal distribution of PM in the coastal region of Southern Taiwan. This study investigated the effects of sea-land breeze and northeastern monsoon on the spatial distribution and temporal variation of particulate matter in the atmosphere around the coastal region of South Taiwan. Particulate matter was simultaneously sampled both inland and offshore during five intensive sampling periods on August 16-17, 2006, November 2-3, 2006, January 24-25, 2007, March 6-7, 2007 and May 2-3, 2007, respectively. Inland monitoring was conducted at two sampling sites associated with fourteen Taiwan ambient air quality monitoring stations, while offshore monitoring was conducted at the Hsiau-Liou-Chiou (HLC) island (approximately 14 km offshore) and on an air quality monitoring boat. In August and November, 2006 and May 2007, sea-land breeze was observed during sampling period and sea breeze arose from 9:00 A.M. to 24:00 P.M. The average wind velocity was 1~4 m/sec during the sampling period. In January and March, 2007, prevail wind direction was north and northeast (300 o ~30 o), that was influenced by northeastern monsoon. The average wind velocity was 2~4 m/sec during the sampling period. The backward trajectories of air parcel transported toward the inland ambient air quality sampling sites around the coastal region of South Taiwan were plotted during the sea land breeze and northeastern monsoon periods. The results showed that distribution of PM10 was significantly influenced by sea land breezes. During the sea-land breeze periods, sea breezes blown in the early morning would transport the offshore PM10 back to the inland sites in Kaohsiung metropolitan area resulting in high PM10 concentration in the afternoon. On the contrary, high PM10 concentration observed during the northeastern monsoon periods was mainly brought from northerly wind which transported PM10 originated from the northern region (i.e. Tainan and Yunlin Counties) to Kaohsiung metropolitan area. This study further compared the atmospheric aerosols sampled at Kaohsiung metropolitan area with the resuspended sands blown from top soils collected near the riversides. An enrichment factor (EF) was applied to correlate the downwind atmospheric aerosols at three TEPA sampling sites in Kaohsiung to top soil sources originated from Tachia river, Zhoushui river, Tesngwen river and Kaoping river, respectively. This study revealed that atmospheric aerosols sampled at Southern Taiwan can be correlated to top soil sources near the riversides. Further investigation of enrichment factors indicated that, among four rivers, Kaoping river had the highest correlation to PM10 sampled in Kaohsiung. The enrichment factors were in the order of Kaoping river (EF=0.8~1.9) > Tsengwen river (EF=0.8~2.6) > Zhuos river (EF=1.0~2.8) > Tachia river (EF=1.1~4.2). The results indicated that atmospheric aerosols (i.e. PM10) had relatively higher correlation with the nearest river, Kaoping river, than other three rivers.

In recent years, the air quality of Kinmen-Xiamen region has deteriorated gradually, and PM10 was always the worst air quality indicator. Particularly, high PM10 concentration has been observed in spring and winter. The objective of this study was to characterize the chemical properties of atmospheric aerosol particles sampled at Xiamen Bay located at the west coast of Taiwan Strait by sampling atmospheric particles and using chemical mass balance (CMB) receptor model for source apportionment, which indicated the difference of background and episode periods. Furthermore, this study applied HYSPLIT model to figure out the transportation routes of polluted air mass by backward trajectory. Seven particulate matter (PM) sampling sites at Xiamen Bay, three sites at Kinmen Island and four sites at metro Xiamen, were selected for this particular study. Particulate matter sampling included regular and intensive sampling. Intensive sampling was conducted to collect PM2.5 and PM2.5-10 with dichotomous samplers in the spring and winter of 2008 and 2009, while regular sampling was conducted to collect PM10 with high-volume samplers twice a month since March 2008. Results from PM sampling indicated that atmospheric particles had a tendency to accumulate in Xiamen Bay all year round, particularly in spring and winter. Five sampling sites inside the Xiamen Bay had relatively higher PM concentration than two sampling sites outside the Xiamen Bay. It suggested that local emission at the Xiamen Bay was superior to long-range transportation from the Northeastern Monson. A superimposition phenomenon was regularly observed during the episodes at Xiamen Bay. The most abundant water-soluble ionic species of PM were SO42-, NO3-, and NH4+ at Xiamen Bay, the major chemical species of PM were secondary aerosols (i.e. (NH4)2SO4 and NH4NO3). Crustal elements (e.g. Ca, Mg, Fe, and Al) and anthropogenic elements (e.g. Zn and Pb) dominated the chemical species of particles. Backward trajectory results indicated that polluted air mass originated from Asian continent moved directly to Kinmen-Xiamen region in winter and spring, while air mass originated from the southwestern and southeastern ocean did not pass polluted region in summer, which result in better air quality of Kinmen-Xiamen region in summer than those in winter and spring. Results from CMB receptor modeling showed that the major sources of atmospheric PM10 at Kinmen-Xiamen region were soil dust, secondary aerosol, petroleum industry, motor vehicle exhanst, iron and steel industry, cement industry, Diesel vehicle exhanst marine aersols, and vegetative burning. The stationary sources were the major contributor accounting for approximately 50% of PM10 in Kinmen. It suggested that atmospheric particles were mainly originated from cross-boundary transport rather than local emission sources since there are no such kinds of industrial factories in Kinmen.

ABSTRACT In this study, we conducted an intensive sampling of Asian dusts at Pescadores Islands for heavy Asian continental sandstorms (ACS) from February 22 to March 6, 2008. To investigate the succession of anthropogenic and natural pollutants for the ACS transportation, PM2.5 and PM2.5-10 were sampled by two dichotomous samplers once every four hours during the ACS periods, and furthermore analyzed their physicochemical properties, including mass concentrations, particle size distribution, water-soluble ionic species, carbonaceous contents, and metallic contents. Experimental results indicated that it was mainly fine particles (PM2.5) prior to the ACS, and the percentage of anthropogenic species (i.e., SO42-, NH4+, NO3-, Zn, Mn and OC) increased dramatically. However, it changed to coarse particles while the ACS overwhelming, and the percentage of crustal/marine species (i.e., Cl-, Na+, Ca2+, Mg2+, Ca, Al, Mg and EC) increased. After the ACS, the concentrations of all species decreased substantially. However, the percentage of Cl- and Na+ increased, suggesting that sea breeze has constant influences on local suspended particles. In addition to the analysis of physicochemical properties of Asian dusts, this study applied a HYSPLIT MODEL to figure out the transportation routes and the source regions of the ACS. Backward trajectory analysis showed that the ACS was originated from the east portion of Inner Mongolia, namely the Onqin Daga Sandy Land and the Horqin Sandy Land. Moreover, seventeen soil samples were collected from the Tengger Desert, the Mu Us Desert, the Onqin Daga Sandy Land, and the Horqin Sandy Land in Inner Mongolia during the year of 2005. The soil samples were resuspended in a resuspension chamber and then collected by a dichotomous sampler. This study focused on PM2.5-10 particles that mainly influence the downwind regions, and then took the ACS samples and the resuspended soil samples to measure the Sr isotopic characteristics of 87Sr/86Sr ratios by a multiple-collector inductively coupled plasma mass spectrometry (MC-ICP-MS). To characterize the isotopic properties of resuspended dust particles from the ACS source regions in northern China, and to correlate Asian dusts at the downwind regions of ACS with the source regions by Duncan¡¦s Multiple Range Test (DMR). The DMR results showed that the ACS was probably originated from the east portion of Inner Mongolia, namely the Onqin Daga Sandy Land and the Horqin Sandy Land, which concurred with the backward trajectory analysis.

<p>When working with embedded systems, secure and fast applications are desired. To achieve this the applications needs to be analyzed and optimized so that they will not be deadlocked or communicate inefficiently. For this purpose an analysis program that can track communications, deadlocks and response times is needed. Operating System Embedded, OSE, is a wide spread real-time operating system that is used in embedded systems. OSE-applications are excellent candidates for analysis and there exists such a tool, VirtualTime, for that purpose. To analyze an OSE-application a model needs to be written that VirtualTime can analyze. This takes up time and effort as the models can require a lot of work to write.</p><p>In this thesis we have investigated and implemented a prototype that translates OSE-application code into VirtualTime simulation model code. We used the transformation tool TXL to translate communication and timing behaviors. In the translation one needs to preserve the communication and timing behavior and throw away other unnecessary code in the OSE-application. This complicates the translation and sophisticated methods like backward slicing might be necessary. A proposed method in this thesis could help with the problem.</p>

No description available.

<p>Financial stock market data, for various reasons, frequently contain missing values. One reason for this is that, because the markets close for holidays, daily stock prices are not always observed. This creates gaps in information, making it difficult to predict the following day’s stock prices. In this situation, information during the holiday can be “borrowed” from other countries’ stock market, since global stock prices tend to show similar movements and are in fact highly correlated. The main goal of this study is to combine stock index data from various markets around the world and develop an algorithm to impute the missing values in individual stock index using “information-sharing” between different time series. To develop imputation algorithm that accommodate time series-specific features, we take multiple imputation approach using dynamic linear model for time-series and panel data. This algorithm assumes ignorable missing data mechanism, as which missingness due to holiday. The posterior distributions of parameters, including missing values, is simulated using Monte Carlo Markov Chain (MCMC) methods and estimates from sets of draws are then combined using Rubin’s combination rule, rendering final inference of the data set. Specifically, we use the Gibbs sampler and Forward Filtering and Backward Sampling (FFBS) to simulate joint posterior distribution and posterior predictive distribution of latent variables and other parameters. A simulation study is conducted to check the validity and the performance of the algorithm using two error-based measurements: Root Mean Square Error (RMSE), and Normalized Root Mean Square Error (NRMSE). We compared the overall trend of imputed time series with complete data set, and inspected the in-sample predictability of the algorithm using Last Value Carried Forward (LVCF) method as a bench mark. The algorithm is applied to real stock price index data from US, Japan, Hong Kong, UK and Germany. From both of the simulation and the application, we concluded that the imputation algorithm performs well enough to achieve our original goal, predicting the stock price for the opening price after a holiday, outperforming the benchmark method. We believe this multiple imputation algorithm can be used in many applications that deal with time series with missing values such as financial and economic data and biomedical data.</p> / Thesis

This thesis is based on the use of mathematical theories, modelling, and simulations to study the transmission dynamics of HIV/AIDS in the presence of PrEP (pre-exposure prophylaxis) in the MSM (men who have sex with men) population in the United States. A new deterministic model for HIV/AIDS that incorporates PrEP is designed and used to assess the population-level impact of the use of PrEP on the transmission dynamics within an MSM population. Conditions for the effective control (or elimination) and persistence of HIV/AIDS in the MSM population are determined by rigorously analyzing this model. Uncertainty and sensitivity analysis is carried out to determine the effect of the uncertainties in the parameter values on the response variable (the associated reproduction number) and to identify the top-five parameters that have the most effect on the disease transmission dynamics. Numerical simulations show that HIV burden decreases with increasing PrEP coverage. / October 2015

No description available.

Sequential Monte Carlo (SMC) and Forward Filtering Backward Sampling (FFBS) are the two most often seen algorithms for Bayesian state space models analysis. Various results regarding the applicability has been either claimed or shown. It is said that SMC would excel under nonlinear, non-Gaussian situations, and less computationally expansive. On the other hand, it has been shown that with techniques such as Grid approximation (Hore et al. 2010), FFBS based methods would do no worse, though still can be computationally expansive, but provide more exact information. The purpose of this report to compare the two methods with simulated data sets, and further explore whether there exist some clear criteria that may be used to determine a priori which methods would suit the study better. / text