Fingerprint Segmentation

In this thesis, a new algorithm has been proposed to segment the foreground of the fingerprint from the image under consideration. The algorithm uses three features, mean, variance and coherence. Based on these features, a rule system is built to help the algorithm to efficiently segment the image. In addition, the proposed algorithm combine split and merge with modified Otsu. Both enhancements techniques such as Gaussian filter and histogram equalization are applied to enhance and improve the quality of the image. Finally, a post processing technique is implemented to counter the undesirable effect in the segmented image. Fingerprint recognition system is one of the oldest recognition systems in biometrics techniques. Everyone have a unique and unchangeable fingerprint. Based on this uniqueness and distinctness, fingerprint identification has been used in many applications for a long period. A fingerprint image is a pattern which consists of two regions, foreground and background. The foreground contains all important information needed in the automatic fingerprint recognition systems. However, the background is a noisy region that contributes to the extraction of false minutiae in the system. To avoid the extraction of false minutiae, there are many steps which should be followed such as preprocessing and enhancement. One of these steps is the transformation of the fingerprint image from gray-scale image to black and white image. This transformation is called segmentation or binarization. The aim for fingerprint segmentation is to separate the foreground from the background. Due to the nature of fingerprint image, the segmentation becomes an important and challenging task. The proposed algorithm is applied on FVC2000 database. Manual examinations from human experts show that the proposed algorithm provides an efficient segmentation results. These improved results are demonstrating in diverse experiments.

MODELLING AND FORECASTING INFLATION RATES IN GHANA: AN APPLICATION OF SARIMA MODELS

Ghana faces a macroeconomic problem of inflation for a long period of time. The problem in somehow slows the economic growth in this country. As we all know, inflation is one of the major economic challenges facing most countries in the world especially those in African including Ghana. Therefore, forecasting inflation rates in Ghana becomes very important for its government to design economic strategies or effective monetary policies to combat any unexpected high inflation in this country. This paper studies seasonal autoregressive integrated moving average model to forecast inflation rates in Ghana. Using monthly inflation data from July 1991 to December 2009, we find that ARIMA (1,1,1)(0,0,1)12 can represent the data behavior of inflation rate in Ghana well. Based on the selected model, we forecast seven (7) months inflation rates of Ghana outside the sample period (i.e. from January 2010 to July 2010). The observed inflation rate from January to April which was published by Ghana Statistical Service Department fall within the 95% confidence interval obtained from the designed model. The forecasted results show a decreasing pattern and a turning point of Ghana inflation in the month of July.

Mätning och utvärdering av PM brännaren

The PM-brännaren (pellets burner) have on commission by the company been measured and evaluated in the combustion laboratory of SERC. The objective was to measure the perform-ance and the emissions of CO and NO for three different combustion powers and for start and stop conditions. The burner have been mounted in the Bionett-boiler from Ariterm and been adjusted by the company. The boiler has been connected to a buffer store that admits firing during long period with constant inlet temperature to the boiler. The measurements have been performed by operating the boiler on constant power until stationary conditions are reached. Thereafter the following two hours of operation have been evaluated. The results show that the burner fulfils the limit values for Blauer Engel labelling and the proposed limit values for Nordic Eco labelling. The measured concentration of NO is far below all organisations limit values for NOx. Concerning the start and stop emissions there are no demands from organisa-tions to compare with, but comparing with other boilers measured at SERC, the CO emissions from PM-brännaren is in the same order of magnitude.

Corporate Social Responsibility och lönsamhet : Finns det ett samband mellan företags rapporterade CSR-arbete och dess lönsamhet?

Bakgrund: Vilken roll har företag i vårt samhälle? Vilken funktion ska de fylla? Är företagens funktion att vara vinstmaximerande och enbart se till sitt eget bästa, eller har de ett större ansvar och skyldigheter mot samhället? Dessa frågor har diskuterats under lång tid och bilden av företag och företagande förändras kontinuerligt i takt med att samhället förändras. Tankarna om att företag har ett socialt ansvar, vid sidan av det ekonomiska, har spridit sig över världen och frågor som har dykt upp är om det finns någon motsättning mellan socialt ansvar och företagens vinstintresse. Eller kan det vara så att socialt ansvarstagande kan leda till ökad lönsamhet? Syfte: Att genom en empirisk undersökning ge en förklaring om svenska noterade bolags rapporterade arbete med CSR har en positiv inverkan på dess lönsamhet. Metod: För att uppnå syftet valdes en deduktiv kvantitativ metod för att kunna göra en statistisk generalisering. Det rapporterade CSR-arbetet operationaliseras med hjälp av Folksams rapport "Index för ansvarsfullt företagande" och lönsamhet mäts via avkastning på totalt kapital (ROA) samt vinstmarginal. Analysen genomförs med hjälp av multipla regressionsanalyser. Slutsats: Studiens resultat visar att företags rapporterade CSR-arbete har en positiv inverkan på svenska noterade företags lönsamhet, både mätt i avkastning på totalt kapital (ROA) och vinstmarginal.