An issue of concern for maritime safety when operating a small to medium-sized sailboat is that the presence of hazards in the navigational route in the form of floating logs can lead to a severe collision if undetected. As a precautionary measure to prevent such a collision with a log, a 2D vision-based detection system is proposed. We take a combined approach involving predictive mapping by linear regression and saliency detection. This approach is found to overcome specific issues related to the illumination changes and unstructured environment in the dataset. The proposed method has been evaluated using precision and recall measures. This proof of concept demonstrates the potential of the method for deployment on a real-time onboard detection system. The algorithm is robust and of reasonable computational complexity. / Graduate

This project uses multiple linear regression to predict the value of Major League Baseball free agent contracts, inspired by the low volume of published research on this topic. I found one published paper that shared my research goal but its predictive power needed improvement. An in depth comparison of our models is carried out with k-fold cross validation mean square prediction error being used as the main standard. The predictor variables considered in my models were related to performance evaluation and position, and the response variable was inflation-adjusted average annual value of the contract. The result of the project is two linear regression models, one for hitters and one for pitchers.

Predicting student performance is an important part of the student modeling task in Intelligent Tutoring System (ITS). The state-of-art model for predicting student performance - Bayesian Knowledge Tracing (KT) has many critical limitations. One specific limitation is that KT has no underlying mechanism for memory decay represented in the model, which means that no forgetting is happening in the learning process. In addition we notice that numerous modification to the KT model have been proposed and evaluated, however many of these are often based on a combination of intuition and experience in the domain, leading to models without performance improvement. Moreover, KT is computationally expensive, model fitting procedures can take hours or days to run on large datasets. The goal of this research work is to improve the accuracy of student performance prediction by incorporating the memory decay factor which the standard Bayesian Knowledge Tracing had ignored. We also propose a completely data driven and inexpensive approach to model improvement. This alternative allows for researchers to evaluate which aspects of a model are most likely to result in model performance improvements based purely on the dataset features that are computed from ITS system logs.

This paper aims to calculate the all-inclusive European option price based on XVA model numerically. For European type options, the XVA can be calculated as so- lution of a BSDE with a specific driver function. We use the FT scheme to find a linear approximation of the nonlinear BSDE and then use linear regression Monte Carlo method to calculate the option price.

In global energy and industrial market, petroleum refining industry accounts for a major share. Through proper planning and the use of adequate mathematical models for the different processing units, many profit improving opportunities can be realized. The increasing crude oil price has also made refining of crude oil blends to be a common practice. This thesis aims to provide useful insight for planning of the integrated refinery subsystems. The main subsystems referred to are (1) The crude oil unloading subsystem (2) The production and product blending subsystem and (3) The product distribution subsystem. Aspen HYSYS® was first used to develop a rigorous model for crude distillation unit (CDU) and vacuum distillation unit (VDU). The rigorous model was validated with pilot plant data from literature. The information obtained from the rigorous model is further used to develop a model for planning of the CDU and VDU. This was combined with models (obtained from empirical correlations) for fluid catalytic cracker (FCC) and hydrotreater (HDT) units to form a mathematical programming planning model used for refinery production and product blending subsystem planning. Since two different types of crude were considered, the optimum volumetric mixing ratio, the sulphur content at that mixing ratio and the CDU flow rate were determined. The yields fraction obtained from the rigorous model were then used to generate regression model using least square method. The sulphur composition of the crude oil was used as independent variable in the regression model. The generated regression models were then used to replace the regular fixed yield approach in a refinery planning model and the results compared. From the results obtained, the proposed method provided an alternative and convenient means for estimating yields from CDU and VDU than the regular fixed yield approach. The proposed aggregate model for the production and products blending subsystem was integrated with the modified scheduling model for the crude unloading subsystem developed by Lee et al. (1996) and products distribution model developed by Alabi and Castro (2009) for refinery planning. It was found that the regression model could be integrated in a refinery planning model and that the CDU flow rate was maximised as compared to the non- integrated system.

Some highway agencies in the United States are experiencing frequent distresses in asphalt pavements on bridge approaches/departures. Commonly observed distresses include alligator cracking and rutting, which reduce roadway smoothness and safety. To lessen the distresses in pavements it is needed to investigate the extent and root causes of the problem. Based on Florida highway conditions, this research study mainly focused on1. Literature review and identification of the extent of the problem; 2. Collection of relevant pavement condition data and descriptive analysis; 3. Development of statistical models to determine factors influencing the distresses in asphalt pavements on bridge approaches/departures. To the best of my knowledge, this is the first study that uses a statistical model to determine the factors that are responsible for causing asphalt pavement distresses on bridge approaches/departures. As part of the literature review, a nationwide questionnaire survey was targeted towards U.S state DOTs. The data collection and analysis specific to the Florida highways found that in 2015 on Florida Interstate highways, about 27% bridges with asphalt pavements on their approaches/departures showed signs of cracking, and about 20% bridges have noticeable rutting in their approach or departure pavements. A random parameter linear regression model was applied to examine the factors that may influence distresses in asphalt pavements in Florida. Pavement condition was evaluated based on the Florida Department of Transportation (FDOT) 2015 pavement condition data and video log images, and other relevant data were collected from various sources such as FDOT Roadway Characteristics Inventory (RCI) database, FDOT pavement management reports, and FDOT Ground Penetrating Radar (GPR) survey reports. A constraint existed in the availability of the GPR data that can give pavement layer thickness, which limited the number of bridge approach pavement sections included in the statistical modeling. Based on the limited data, the estimated results from the random parameter linear regression model showed that the variables influencing distresses in asphalt pavements on bridge approaches/departures, in terms of rutting and roughness, may include pavement age, annual average daily truck traffic, and surface friction course.

The concept of "transnational" education has emerged over the past decade or more as a critical strategy for meeting the growing demand for higher education worldwide. Essentially, transnational higher education allows international providers with outstanding credentials to conduct degree programs at local sites in conjunction with local tertiary institutions. Due to the rapid expansion of transnational programmes and the proliferation of transnational education providers, both governments and parents have, however, raised questions about the quality of education provided through transnational mechanisms. Rapid technological development, coupled with the recent growth of new engineering specialty areas, has led to the development of outcomes-based criteria for engineering education by a range of international engineering professional bodies. The emergence of outcomes-based approaches requires new instruments to measure the success, or otherwise, of engineering programs offered by universities. This study was conducted at a Malaysian private college (pseudonym "Trans College" with the prime purpose of developing an authoritative measurement instrument for evaluating the quality of transnational engineering education. This study generated a theory-based 11-dimension Preliminary Conceptual Framework consisting of four Outcomes dimensions and seven Contributory dimensions for Transnational Engineering Education, and tested the integrity of the theoretical framework through surveys of enrolled students, staff, and representatives of employing agencies. The Preliminary Conceptual Framework was found to have a high degree of conceptual validity, as well as some limitations. The findings of the surveys enabled a Revised Conceptual Framework for Transnational Engineering Education to be developed through reliability test and validated by using confirmatory and exploratory factor analyses. The revised framework comprises five Outcomes and eight Contributory dimensions. It has been transposed into a 13-dimension revised survey instrument consisting of 25 Outcomes items clustered into five Outcomes dimensions, and 49 Contributory items clustered into eight Contributory dimensions. The developed survey instrument was then used to study the perceptions of students, staff, and employers regarding the quality of the transnational engineering education. Through performing t-tests, ANOVA, and other statistical analyses, the results of the study indicate that the quality of the transnational engineering education at Trans College was perceived by students, staff, and employers to be generally sound. It was also revealed that the Contributory construct can be adopted for measuring the satisfaction levels of students. Students, staff, and employers were also satisfied for the most part with their respective experiences of the programs in question. The study is believed to have considerable significance. First, it has generated a conceptual framework for measuring the quality of the transnational engineering education. The validated conceptual framework is transposed into a validated instrument that can be adapted for use by a range of other transnational educational providers. Second, it affirms the value of the "transnational" concept while also providing a number of recommendations for the enhancement of such programmes, particularly at Trans College. Third, the conceptual framework for the delivery of successful transnational engineering education derived from this study may help to improve the quality of transnational engineering programmes conducted in Malaysia, and make Malaysia "the centre of educational excellence" in the ASEAN region, with the transnational providers becoming hubs of tertiary education, and their networks spanning the globe.

<p>The association of exchange rates with stock returns and performance in major trading markets is widely accepted. The world’s economy has seen unprecedented growth of interdependent; as such the magnitude of the effect of exchange rates on returns will be even stronger. Since the author perceives the importance of exchange rates on stock returns, the author found it interesting to study the effect of exchange rates on some stocks traded on the Stock exchange.</p><p>There has been a renewed interest to investigate the relationship between returns and exchange rates as such; the author has chosen to investigate the present study to focus in the United Kingdom with data from the London Stock exchange .The author carried out his research on 18 companies traded on the London Stock Exchange in the process, using linear regression analysis. Taking into account the fact that the magnitude of exchange rate movements on stock returns is governed by a series of factors, the author did set up a selection criteria which spread across a series of industries ranging from financial services, manufacturing, aviation, mining, tobacco, fashion and food processing. All selected companies are of the FTSE 100 companies.</p><p>The author produced results that to some degree are consistent with predictions in the theoretical framework. The author find significant exposure of stock returns to changes in exchange rates for some companies in the sample of FTSE 100 firms used in the study. The author equally finds out that particular currencies may be of more risk to certain companies than to others by introducing euro values in to his regression equation. This gives the compelling evidence that these companies rely heavily on external sales and revenue.</p><p>The author, further employed lagged values of exchange rates in to his regression and found significant evidence of the possibility of mispricing for certain stocks and the impact of the previous days trading figures on present stock prices. The author believes that the weak responds in certain cases was as a result of hedging strategies put in place by these companies and risk management strategies which tend to minimise the effect of exchange rates movements.</p>

<p>En gren inom statistikteorin är den så kallade Regressionsanalysen där man studerar hur data från exempelvis ett stickprov kan anpassas till en graf. Skrivandet av denna uppsats har haft som syfte att studera några av de metoder som finns att tillgå vid bestämning av de ingående parametrarna i de enklare fallen av regression. Dessutom ges i de avslutande kapitlen exempel på den del inom regressionsanalysen som kallas Styckvis Linjär Regression eller <em>Piecewise Linear Regression.</em></p> / Presentationen är redan avklarad den 26 april 2010 kl. 11.30

The association of exchange rates with stock returns and performance in major trading markets is widely accepted. The world’s economy has seen unprecedented growth of interdependent; as such the magnitude of the effect of exchange rates on returns will be even stronger. Since the author perceives the importance of exchange rates on stock returns, the author found it interesting to study the effect of exchange rates on some stocks traded on the Stock exchange. There has been a renewed interest to investigate the relationship between returns and exchange rates as such; the author has chosen to investigate the present study to focus in the United Kingdom with data from the London Stock exchange .The author carried out his research on 18 companies traded on the London Stock Exchange in the process, using linear regression analysis. Taking into account the fact that the magnitude of exchange rate movements on stock returns is governed by a series of factors, the author did set up a selection criteria which spread across a series of industries ranging from financial services, manufacturing, aviation, mining, tobacco, fashion and food processing. All selected companies are of the FTSE 100 companies. The author produced results that to some degree are consistent with predictions in the theoretical framework. The author find significant exposure of stock returns to changes in exchange rates for some companies in the sample of FTSE 100 firms used in the study. The author equally finds out that particular currencies may be of more risk to certain companies than to others by introducing euro values in to his regression equation. This gives the compelling evidence that these companies rely heavily on external sales and revenue. The author, further employed lagged values of exchange rates in to his regression and found significant evidence of the possibility of mispricing for certain stocks and the impact of the previous days trading figures on present stock prices. The author believes that the weak responds in certain cases was as a result of hedging strategies put in place by these companies and risk management strategies which tend to minimise the effect of exchange rates movements.