This thesis describes two main projects; the first one is the optimization of a hierarchical search strategy to search for unknown pulsars. This project is divided into two parts; the first part (and the main part) is the semi-coherent hierarchical optimization strategy. The second part is a coherent hierarchical optimization strategy which can be used in a project like Einstein@Home. In both strategies we have found that the 3-stages search is the optimum strategy to search for unknown pulsars. For the second project we have developed a computer software for a coherent Multi-IFO (Interferometer Observatory) search. To validate our software, we have worked on simulated data as well as hardware injected signals of pulsars in the fourth LIGO science run (S4). While with the current sensitivity of our detectors we do not expect to detect any true Gravitational Wave signals in our data, we can still set upper limits on the strength of the gravitational waves signals. These upper limits, in fact, tell us how weak a signal strength we would detect. We have also used our software to set upper limits on the signal strength of known isolated pulsars using LIGO fifth science run (S5) data. / Diese Dissertation besteht aus zwei Projekten: Im ersten Projekt wird die Optimierung einer hierarchischen Strategie zum Auffinden von 'unbekannten' Pulsaren beschrieben. Der erste Teil besteht dabei aus einer semi-kohärenten und der zweite Teil aus einer kohärenten Optimierungsstrategie, wie sie in Projekten wie Einstein@Home verwendet werden kann. In beiden Ansätzen erwies sich eine 3-Stufensuche als optimale Suchstrategie für 'unbekannte' Pulsare. Für das zweite Projekt entwickelten wir eine Software für eine kohärente Multi-IFO (Interferometer Observatory) Suche. Zum Validieren der Software verwendeten wir sowohl simulierte Daten als auch Hardware induzierte Signale von Pulsaren aus dem vierten 'LIGO Science run' (S4). Wir erwarten nicht, mit der aktuellen Empfindlichkeit unserer Detektoren echte GW- Signale aufzunehmen, können jedoch obere Grenzen für die Stärke der Gravitationswellen-Signale bestimmen. Diese oberen Grenzen geben uns an, wie schwach ein gerade noch detektierbares Signal werden kann. Ferner benutzten wir die Software um eine obere Grenze für bekannte, isolierte Pulsare zu bestimmen, wobei wir Daten aus dem fünften 'LIGO Science run (S5) verwendeten.

The determination and application of Analytical Threshold (AT) is a vital part of the forensic Deoxyribonucleic Acid (DNA) internal validation process. AT is the relative fluorescence unit (RFU) signal at which allelic peaks can be confidently distinguished from baseline noise. Several methods of calculating AT are currently being implemented within the forensic DNA community. These methods may utilize DNA negative sample data, DNA positive sample data, or both in their calculations. In this study, two of the DNA positive-based AT calculation techniques were chosen for assessment and comparison. The simplified upper limit approach (ULA) and the cost-based approach. ATs were calculated for each dye channel using a dilution series of 3 single source DNA samples ranging from 0.05-0.8ng. The ATs calculated via the cost-based approach consistently exhibited lower values than those determined via the ULA. As a result, the incidence of allelic drop-out exhibited by these AT values was also consistently lower, with an equivalent or only marginally increased incidence of baseline noise drop-in. These results indicated that the cost-based approach may be a more effective and practical method of calculating AT than the ULA, particularly in the analysis of low DNA template samples.

隨著經濟全球化、分工化的趨勢下，我國企業為提升競爭力並獲取更高的利潤，逐漸將企業轉移至大陸。根據投審會的統計，台灣企業單一年度在大陸的核准投資金額已從初期1991年的1.74億美元，成長至2002年的67.23億美元，去年2010年更達到146.17億美元，中國大陸已取代美國成為台灣最大的對外投資地區。然而兩岸之間敏感的政治因素，政府對於投資大陸之上限、技術及資本市場一直存在相當之限制，使得台商為了規避相關法規之限制，掙脫「台資」身份投資中國大陸的枷鎖，紛紛以各種合法及不合法的管道突圍。 有鑑於違規投資大陸事件層出不窮，我國遂於2008年放寬投資大陸之相關規定，其中影響最鉅的為投資上限淨值，將其從40%改為60%。雖然限制條件放寬了，但是投資大陸上限仍舊存在，對於投資大陸需求較高的企業，為提高投資大陸的金額，可能會透過各種管道，其中包括盈餘管理之可能。 本研究即在探討我國相關法令中，對於企業投資中國大陸的限制存在那些限制，而企業為了規避這些限制可能採取那些手法，並以計算投資上限的淨值作為主要的研究標的，探討公司是否會進行淨值管理。本研究實證結果顯示，投資大陸比例接近其限額之企業，相較於投資大陸比例很低的企業，確實較有可能透過盈餘管理，以達到提高投資中國大陸限額的目的。 / With the tendency of global economic development and collaboration, it is necessary for our enterprises to transfer their operating center to China in order to promote competition and get more profit. According to the statistics by Investment Commission, the approve amount to invest in China from Taiwanese entrepreneurs in a year has increased from 0.174 billion in 1991 to 6.723 billion in 2002. In 2010, the amount is up to 14.617 billion. Mainland China has substituted for the US to become Taiwan’s major investment area. But the sensitive political issues between two sides of Taiwan Strait make Taiwan government establish many constraints, including the upper limit for investment in China, the technology and the capital market. To avoid the regulations of constraints and the “Taiwanese identity”, Taiwanese entrepreneurs use many legal and illegal ways to invest in China. Because illegal events about investment in China emerged one after another incessantly, our government relaxed a part of the regulations in 2008. The most influence in the regulations of constraints is the upper limit for investment; it changed from 40% to 60%. Although the constraints have relaxed, the upper limit for investment still exists. For those enterprises with higher investment demand, there is still a possibility for them to use ways to enhance the investment amount, including earnings management. The purpose of this research is to clarify the regulatory policy of Taiwan government toward investment in China, and the ways enterprises use to avoid the constraints. Besides, the main object of research is net worth which is calculated for the upper limit for investment. The empirical results demonstrate that enterprises whose investments are close to the upper limit are more likely to use earnings management to enhance the investment amount than enterprises whose investments are far away from the upper limit.

In the present paper, we identify several distributions from Physics and study their applicability to phenomena such as distribution of income, wealth, and expenditure. Firstly, we apply logistic distribution to these data and we find that it fits very well the annual data for the entire income interval including for upper income segment of population. Secondly, we apply Fermi-Dirac distribution to these data. We seek to explain possible correlations and analogies between economic systems and statistical thermodynamics systems. We try to explain their behaviour and properties when we correlate physical variables with macroeconomic aggregates and indicators. Then we draw some analogies between parameters of the Fermi-Dirac distribution and macroeconomic variables. Thirdly, as complex systems are modelled using polynomial distributions, we apply polynomials to the annual sets of data and we find that it fits very well also the entire income interval. Fourthly, we develop a new methodology to approach dynamically the income, wealth, and expenditure distribution similarly with dynamical complex systems. This methodology was applied to different time intervals consisting of consecutive years up to 35 years. Finally, we develop a mathematical model based on a Hamiltonian that maximises utility function applied to Ramsey model using Fermi-Dirac and polynomial utility functions. We find some theoretical connections with time preference theory. We apply these distributions to a large pool of data from countries with different levels of development, using different methods for calculation of income, wealth, and expenditure.

In this thesis we present new results for the 99.9% confidence level flux upper limits on the pulsed VHE gamma ray signal coming from the Crab pulsar. In order to achieve optimum hadronic background suppression we implement a new neural network based selection technique and apply it to Cherenkov shower imaging data from the WHIPPLE 10m IACT telescope at Mount Hopkins Arizona. Special emphasis will be given to the fact that the neural network selector is trained with real data exclusively. An energy estimator for gamma ray induced extensive air shower events has been derived from Monte Carlo simulations using the Monte Carlo framework GrISU. This estimator, applied to the image data, serves as input to the neural set selector and is needed to determine the energy dependent flux upper limits. We compare our results to the results from previous studies and the performance of our neural network selection technique to the so-called Supercuts and Optimized Supercuts methods.The new flux upper limits and the new technique show the potential to settle the question about the production mechanism of pulsar radiation. However, the current analysis does not answer this question fully.