<p>The thesis applies performance evaluation of pharmaceutical company in Bangladesh. It means evaluate how well the company performs. The main aim is achieved through ratio analysis of two pharmaceutical (Beximco and Square pharmaceutical) companies in Bangladesh. The main data collection from the annual financial reports on Beximco and square pharmaceutical companies in 2007 to 2008.Different financial ratio are evaluated such liquidity ratios, asset management ratios, profitability ratios, market value ratios, debt management ratios and finally measure the best performance between two companies. The mathematical calculation was establish for ratio analysis between two companies from 2007-2008.It is most important factors for performance evaluation. The graphical analysis and comparisons are applies between two companies for measurement of all types of financial ratio analysis. Liquidity ratio is conveying the ability to repay short-term creditors and it total cash. It determines perform of short term creditor of both pharmaceutical companies under the three categories such as current ratio, quick ratio and cash ratio. Asset management ratio is measurement how to effectively a company to use and controls its assets. Its also quantify into seven categories for both pharmaceutical companies such as account receivable turnover, average collection period, inventory turnover, account payable turnover ,account payable turnover in days ,fixed asset turnover ,total asset turnover. Profitability ratio is evaluate how well a company is performing by analyzing and how profit was earned relative to sales, total assets and net worth for both pharmaceutical companies. Debt coverage ratio is performing that the property insufficient to collect their mortgage for both companies and market value is perform the stockholder to analysis their future market value of the stock market. Overall analyses are measurement the best one between Beximco and Square pharmaceutical companies.</p>

ABSTRACT The purpose of this research study is to determine if the rate of unintentional injury death in selected medical districts differs significantly among citizen and non-citizen males ages 20-65 living in the United Arab Emirates (UAE). A profile of unintentional injury deaths was generated by specific cause for the six medical districts of Ajman, Dubai, Fujairah, Ra’s al-Khaimah, Sharjah and Umm al-Qaiwain managed for the UAE Ministry of Health for the years 2006-2008. During this time period the six medical districts reported a total of 14,101 deaths. Males were found to represent 73.9 per cent of the deaths reported by the six medical districts managed by the UAE Ministry of health for the years 2006-2008. Non –citizen males represented 74.8 per cent of the male fatalities reported by the six medical districts managed by the UAE Ministry of health for the years 2006-2008. Fatality rates for males ages 20-65 were generated and analyzed by citizen status and season of the year. This age group represented 6,141 deaths. In the two medical districts with the highest population (Dubai & Sharjah) unintentional injury deaths represented 77.1% of the total unintentional deaths reported by all the six medical districts managed by the UAE Ministry of Health for the years 2006-2008. A Chi-Square found the rate of fatalities among 20-65 years old male citizens and non-citizens in the six medical districts managed by the UAE Ministry of Health for the years 2006-2008 differed significantly by cause of unintentional injury death. The observed rate of death from accidental falls for non-citizen 20-65 males was found to be higher than expected for male citizens in the same age group. The observed unintentional injury death rate for males ages 20-65 caused by motor vehicle & traffic accidents and for accidental poisoning found the death rate for UAE citizens to be higher than the rate for non-citizens living in the UAE. The results of this study demonstrate the need for the reporting and analysis of unintentional deaths at the medical district level in the UAE by subgroups such as citizen status and age group.

<p>Intercultural communication (ICC) is one of the most relevant fields for investigation in post-colonial Africa and post-apartheid South Africa, given the movements between people from African countries and the wide range of attractions, both economic and social, that South Africa holds for people from other African countries. This study reports on intercultural communication in post-democratic South Africa in an era marked by what Appadurai (1990) calls &lsquo / flows&rsquo / . Greenmarket Square in the heart of Cape Town, well known as a hub for informal traders, local people and tourists, was chosen as the site for this study, because of the rich cultural diversity of the role-players. The principal aim of this research is to examine how people from different cultural backgrounds in this particular space of Greenmarket Square communicate with one another, and where the &lsquo / intercultural fault-lines&rsquo / (Olahan, 2000) occur, keeping in mind how ICC could be improved in such a space. My position as a trader in the market placed me in an ideal &lsquo / insider&rsquo / position to do the research. The theory of spatiality (Vigouroux, 2005 / Blommaert et al. 2005) was used to show how the space of Greenmarket Square affected intercultural communication. Discourse analysis was also applied to the data to show how the various roleplayers were socially constructed by others. Saville-Troike&rsquo / s (1989) ethnography of communicative events was also used to bring out other barriers that were not identified by spatiality and discourse analysis. Aspects like scene, key, message form and content, the observed rules for interaction and where these rules were broken and to what effect as well as the norms for interpretation were considered during the analysis of this qualitative data. The analysis showed that spatiality, social constructions of &lsquo / the other&rsquo / and other factors like nonverbal communication and differences between communicative styles in high and low context cultures (LCC/HCC), had a major impact on intercultural communication at Greenmarket Square, frequently leading to complete breakdowns in communication. Many of the traders interviewed acknowledged that they needed to improve their competence in intercultural communication. The study concludes with a number of recommendations on how people can become more &ldquo / interculturally competent&rdquo / (Katan, 2004) in a globalized world.</p>

Linear time-invariant approximations of nonlinear systems are used in many applications and can be obtained in several ways. For example, using system identification and the prediction-error method, it is always possible to estimate a linear model without considering the fact that the input and output measurements in many cases come from a nonlinear system. One of the main objectives of this thesis is to explain some properties of such approximate models. More specifically, linear time-invariant models that are optimal approximations in the sense that they minimize a mean-square error criterion are considered. Linear models, both with and without a noise description, are studied. Some interesting, but in applications usually undesirable, properties of such optimal models are pointed out. It is shown that the optimal linear model can be very sensitive to small nonlinearities. Hence, the linear approximation of an almost linear system can be useless for some applications, such as robust control design. Furthermore, it is shown that standard validation methods, designed for identification of linear systems, cannot always be used to validate an optimal linear approximation of a nonlinear system. In order to improve the models, conditions on the input signal that imply various useful properties of the linear approximations are given. It is shown, for instance, that minimum phase filtered white noise in many senses is a good choice of input signal. Furthermore, the class of separable signals is studied in detail. This class contains Gaussian signals and it turns out that these signals are especially useful for obtaining approximations of generalized Wiener-Hammerstein systems. It is also shown that some random multisine signals are separable. In addition, some theoretical results about almost linear systems are presented. In standard methods for robust control design, the size of the model error is assumed to be known for all input signals. However, in many situations, this is not a realistic assumption when a nonlinear system is approximated with a linear model. In this thesis, it is described how robust control design of some nonlinear systems can be performed based on a discrete-time linear model and a model error model valid only for bounded inputs. It is sometimes undesirable that small nonlinearities in a system influence the linear approximation of it. In some cases, this influence can be reduced if a small nonlinearity is included in the model. In this thesis, an identification method with this option is presented for nonlinear autoregressive systems with external inputs. Using this method, models with a parametric linear part and a nonparametric Lipschitz continuous nonlinear part can be estimated by solving a convex optimization problem. / Linjära tidsinvarianta approximationer av olinjära system har många användningsområden och kan tas fram på flera sätt. Om man har mätningar av in- och utsignalerna från ett olinjärt system kan man till exempel använda systemidentifiering och prediktionsfelsmetoden för att skatta en linjär modell utan att ta hänsyn till att systemet egentligen är olinjärt. Ett av huvudmålen med den här avhandlingen är att beskriva egenskaper för sådana approximativa modeller. Framförallt studeras linjära tidsinvarianta modeller som är optimala approximationer i meningen att de minimerar ett kriterium baserat på medelkvadratfelet. Brusmodeller kan inkluderas i dessa modelltyper och både fallet med och utan brusmodell studeras här. Modeller som är optimala i medelkvadratfelsmening visar sig kunna uppvisa ett antal intressanta, men ibland oönskade, egenskaper. Bland annat visas det att en optimal linjär modell kan vara mycket känslig för små olinjäriteter. Denna känslighet är inte önskvärd i de flesta tillämpningar och innebär att en linjär approximation av ett nästan linjärt system kan vara oanvändbar för till exempel robust reglerdesign. Vidare visas det att en del valideringsmetoder som är framtagna för linjära system inte alltid kan användas för validering av linjära approximationer av olinjära system. Man kan dock göra de optimala linjära modellerna mer användbara genom att välja lämpliga insignaler. Bland annat visas det att minfasfiltrerat vitt brus i många avseenden är ett bra val av insignal. Klassen av separabla signaler detaljstuderas också. Denna klass innehåller till exempel alla gaussiska signaler och just dessa signaler visar sig vara speciellt användbara för att ta fram approximationer av generaliserade wiener-hammerstein-system. Dessutom visas det att en viss typ av slumpmässiga multisinussignaler är separabel. Några teoretiska resultat om nästan linjära system presenteras också. De flesta metoder för robust reglerdesign kan bara användas om storleken på modellfelet är känd för alla tänkbara insignaler. Detta är emellertid ofta inte realistiskt när ett olinjärt system approximeras med en linjär modell. I denna avhandling beskrivs därför ett alternativt sätt att göra en robust reglerdesign baserat på en tidsdiskret modell och en modellfelsmodell som bara är giltig för begränsade insignaler. Ibland skulle det vara önskvärt om en linjär modell av ett system inte påverkades av förekomsten av små olinjäriteter i systemet. Denna oönskade påverkan kan i vissa fall reduceras om en liten olinjär term tas med i modellen. En identifieringsmetod för olinjära autoregressiva system med externa insignaler där denna möjlighet finns beskrivs här. Med hjälp av denna metod kan modeller som består av en parametrisk linjär del och en ickeparametrisk lipschitzkontinuerlig olinjär del skattas genom att man löser ett konvext optimeringsproblem.

The thesis applies performance evaluation of pharmaceutical company in Bangladesh. It means evaluate how well the company performs. The main aim is achieved through ratio analysis of two pharmaceutical (Beximco and Square pharmaceutical) companies in Bangladesh. The main data collection from the annual financial reports on Beximco and square pharmaceutical companies in 2007 to 2008.Different financial ratio are evaluated such liquidity ratios, asset management ratios, profitability ratios, market value ratios, debt management ratios and finally measure the best performance between two companies. The mathematical calculation was establish for ratio analysis between two companies from 2007-2008.It is most important factors for performance evaluation. The graphical analysis and comparisons are applies between two companies for measurement of all types of financial ratio analysis. Liquidity ratio is conveying the ability to repay short-term creditors and it total cash. It determines perform of short term creditor of both pharmaceutical companies under the three categories such as current ratio, quick ratio and cash ratio. Asset management ratio is measurement how to effectively a company to use and controls its assets. Its also quantify into seven categories for both pharmaceutical companies such as account receivable turnover, average collection period, inventory turnover, account payable turnover ,account payable turnover in days ,fixed asset turnover ,total asset turnover. Profitability ratio is evaluate how well a company is performing by analyzing and how profit was earned relative to sales, total assets and net worth for both pharmaceutical companies. Debt coverage ratio is performing that the property insufficient to collect their mortgage for both companies and market value is perform the stockholder to analysis their future market value of the stock market. Overall analyses are measurement the best one between Beximco and Square pharmaceutical companies.

With the advent of high-throughput genomic and proteomic technologies, in conjunction with the difficulty in obtaining even moderately sized samples, small-sample classifier design has become a major issue in the biological and medical communities. Training-data error estimation becomes mandatory, yet none of the popular error estimation techniques have been rigorously designed via statistical inference or optimization. In this investigation, we place classifier error estimation in a framework of minimum mean-square error (MMSE) signal estimation in the presence of uncertainty, where uncertainty is relative to a prior over a family of distributions. This results in a Bayesian approach to error estimation that is optimal and unbiased relative to the model. The prior addresses a trade-off between estimator robustness (modeling assumptions) and accuracy. Closed-form representations for Bayesian error estimators are provided for two important models: discrete classification with Dirichlet priors (the discrete model) and linear classification of Gaussian distributions with fixed, scaled identity or arbitrary covariances and conjugate priors (the Gaussian model). We examine robustness to false modeling assumptions and demonstrate that Bayesian error estimators perform especially well for moderate true errors. The Bayesian modeling framework facilitates both optimization and analysis. It naturally gives rise to a practical expected measure of performance for arbitrary error estimators: the sample-conditioned mean-square error (MSE). Closed-form expressions are provided for both Bayesian models. We examine the consistency of Bayesian error estimation and illustrate a salient application in censored sampling, where sample points are collected one at a time until the conditional MSE reaches a stopping criterion. We address practical considerations for gene-expression microarray data, including the suitability of the Gaussian model, a methodology for calibrating normal-inverse-Wishart priors from unused data, and an approximation method for non-linear classification. We observe superior performance on synthetic high-dimensional data and real data, especially for moderate to high expected true errors and small feature sizes. Finally, arbitrary error estimators may be optimally calibrated assuming a fixed Bayesian model, sample size, classification rule, and error estimation rule. Using a calibration function mapping error estimates to their optimally calibrated values off-line, error estimates may be calibrated on the fly whenever the assumptions apply.

In wireless communications, channel estimation is necessary for coherent symbol detection. This thesis considers a network which consists of two transceivers communicating with the help of a relay applying the amplify-and-forward (AF) relaying scheme. The training based channel estimation technique is applied to the proposed network where the numbers of the training sequence transmitted by the two transceivers, are different. All three terminals are equipped with a single antenna for signal transmission and reception. Communication between the transceivers is carried out in two phases. In the first phase, each transceiver sends a transmission block of data embedded with known training symbols to the relay. In the second phase, the relay retransmits an amplified version of the received signal to both transceivers. Estimates of the channel coefficients are obtained using the Maximum Likelihood (ML) estimator. The performance analysis of the derived estimates are carried out in terms of the mean squared error (MSE) and we determine conditions required to increase the estimation accuracy. / UOIT

In this thesis a machine vision based indoor navigation system is presented. This is achieved by using rotationally independent optimized color reference labels and a geometrical camera calibration model which determines a set of camera parameters. All reference labels carry one byte of information (0 to 255), which can be designed for different values. An algorithm in Matlab has been developed so that a machine vision system for N number of symbols can recognize the symbols at different orientations. A camera calibration model describes the mapping between the 3-D world coordinates and the 2-D image coordinates. The reconstruction system uses the direct linear transform (DLT) method with a set of control reference labels in relation to the camera calibration. The least-squares adjustment method has been developed to calculate the parameters of the machine vision system. In these experiments it has been demonstrated that the pose of the camera can be calculated, with a relatively high precision, by using the least-squares estimation.

I detta 10-poängsarbete går jag igenom hur min egenhändigt producerade kvadratrotsalgoritm fungerar praktiskt och teoretiskt. Med denna algoritm kan man för hand räkna ut kvadratrötter som innehåller 50-60 värdesiffror. Med de tidigare kända algoritmerna för kvadratrötter kan man räkna ut 5-6 värdesiffror. Min algoritm fungerar inte på samma sätt som de tidigare använda kvadratrotsalgoritmerna men den är lika korrekt. Stor tyngdvikt i arbetet har därför lagts på att visa på att det finns flera olika korrekta algoritmer för våra vanliga räknesätt. Arbetet innehåller också en kort skildring av den pågående debatten huruvida algoritmräkning i grundskolan hämmar elevernas matematiska tänkande eller inte.

A linear periodically time-varying (LPTV) system is a linear time-varying system with the coefficients changing periodically, which is widely used in control, communications, signal processing, and even circuit modeling. This thesis concentrates on identification of LPTV systems. To this end, the representations of LPTV systems are thoroughly reviewed. Identification methods are developed accordingly. The usefulness of the proposed identification methods is verified by the simulation results.<p> A periodic input signal is applied to a finite impulse response (FIR)-LPTV system and measure the noise-contaminated output. Using such periodic inputs, we show that we can formulate the problem of identification of LPTV systems in the frequency domain. With the help of the discrete Fourier transform (DFT), the identification method reduces to finding the least-squares (LS) solution of a set of linear equations. A sufficient condition for the identifiability of LPTV systems is given, which can be used to find appropriate inputs for the purpose of identification.<p> In the frequency domain, we show that the input and the output can be related by using the discrete Fourier transform (DFT) and a least-squares method can be used to identify the alias components. A lower bound on the mean square error (MSE) of the estimated alias components is given for FIR-LPTV systems. The optimal training signal achieving this lower MSE bound is designed subsequently. The algorithm is extended to the identification of infinite impulse response (IIR)-LPTV systems as well. Simulation results show the accuracy of the estimation and the efficiency of the optimal training signal design.