In simulation, time averages are important for estimating equilibrium parameters. In particular, we would like to have the variance, bias and mean-square error for time averages. First, we will discuss various factors and their effect on the bias, the variance and the mean-square error. We will use the Markovian Event System to model various systems, including M/M/1 queues, M/E_k/1 queues, M/M/c queues, sequential queues, inventory systems and queueing networks. We use a numerical method for the computation of the variance, the bias and the mean-square error of the time average. The effectiveness of the method is tested by experimenting with models of various stochastic systems. The contribution of this thesis is to use numerical and graphical interpretations to study the general characteristics of the measures. The important characteristics included in our study are decomposability and periodicity.

In this paper, we explore the relationship between a Global Mood Time Series, provided by Wall Street Birds, and the Dow Jones Industrial Average (DJIA) from April 2011 to December 2011. My econometric results show that there is no long run equilibrium relationship between the level of global mood and the level of the DJIA. These results apply to the whole period, as well as in the six-month subperiods. Furthermore, daily changes in global mood do not Granger cause DJIA returns. However, changes in global mood do appear to be useful in forecasting the volatility of the DJIA, and my results suggest that GARCH models of volatility of large-cap indexes, and potentially the market as a whole, could be strengthened by including online sentiment measures of Big Data. Measuring global mood, and quantifying its impacts, can potentially lead to superior portfolio construction as forecasting volatility is an important input in portfolio optimization. The results, as a whole, suggest that Big Data can have important implications for investment decision-making.

Distributed generation is expected to play a significant role in remedying the many shortcomings in today’s energy market. In particular, fuel cell power generation will play a big part due to several advantages. Still, it is faced with its own challenges to tap into its potential as a solution to the crisis. The responsibilities of the Power Conditioning Unit (PCU), and thus its design, are therefore complex, yet critical to the fuel cell system’s performance and ability to meet the requirements. To this end, the dc-dc converter, considered the most critical component of the PCU for optimum performance, is closely examined. The selected converter is first modeled to gain insight into its behavior for the purpose of designing suitable compensators. MATLAB is then used to study the results using the frequency domain, and it was observed that the converter offers its own unique challenges in terms of closed-loop performance and stability. These limitations must therefore be carefully accounted for and compensated against when designing the control loops to achieve the desired objectives. Negative feedback control to ensure robustness is then discussed. The insertion of a second inner loop in Current Mode Control (CMC) offers several key advantages over single-loop Voltage Mode Control (VMC). Furthermore, the insertion of a Current Error Amplifier (CEA) in Average Current Mode Control (ACMC) helps overcome many of the problems present in Peak Current Mode Control (PCMC) whilst allowing much needed design flexibility. It is therefore well suited for this application in an attempt to improve the dynamic behavior and overcoming the shortcomings inherent in the converter. The modulator and controller for ACMC are then modeled separately and combined with the converter’s model previously derived to form the complete small-signal model. A suitable compensation network is selected based on the models and corresponding Bode plots used to assess the system’s performance and stability. The resulting Bode plot for the complete system verifies that the design objectives are clearly met. The complete system was also built in MATLAB/Simulink, and subjected to external disturbances in the form of stepped load changes. The results confirm the system’s excellent behavior despite the disturbance, and the effectiveness of the control strategy in conjunction with the derived models. To meet the demand in many applications for power sources with high energy density and high power density, it is constructive to combine the fuel cell with an Energy Storage System (ESS). The hybrid system results in a synergistic system that brings about numerous potential advantages. Nevertheless, in order to reap these potential benefits and avoid detrimental effects to the components, a suitable configuration and control strategy to regulate the power flow amongst the various sources is of utmost importance. A robust and flexible control strategy that allows direct implementation of the ACMC scheme is devised. The excellent performance and versatility of the proposed system and control strategy are once again verified using simulations. Finally, experimental tests are also conducted to validate the results presented in the dissertation. A scalable and modular test station is built that allows an efficient and effective design and testing process of the research. The results show good correspondence and performance of the models and control design derived throughout the thesis.

Examensarbete beskriver hur ett analysverktyg har skapats för materialförbrukningen på Motorunderhållsavdelningen på Volvo Aero Corporation. Analysverktyget tar fram snittlistor och inköpslistor till motorn PW100. Dokumentering vid skapandet av analysverktyget sker i sju delar. Genom att skapa ett analysverktyg kan de strategiska materialplanerarna på Volvo Aero lätt generera en snittlista eller en inköpslista som baseras på historisk data. Tidigare var de strategiska materialplanerana tvungna att beräkna snittlistor manuellt och mycket handpåläggning gjorde att resultatet inte alltid var pålitligt. En förstudie gjordes för att få en bättre inblick i den nuvarande organisationen och hur arbetet styrs på motorunderhållsavdelningen på Volvo Aero. Intervjuer utfördes löpande samtidigt som en litteraturstudie inom området logistik gjordes. Detta för att få tillräckligt med kunskap till att skapa ett analysverktyg utifrån behov. En kravspecifikation togs fram för att bestämma vad analysverktyget skall innehålla för funktioner. Eftersom en stor mängd data hanterades användes Microsoft Access. Data hämtades från databasen SAP. Analysverktyget är uppbygd i tre delar: 1. Snittlista: Visar den genomsnittliga förbrukningen av material för vald motortyp och underhållstyp. 2. Lagersaldo: Kontrollerar vad som finns i lager utifrån vald motortyp och underhållstyp. Nya och begagnade delar är valbara. 3. Inkommande material: Visar material som inte har levererats in utifrån vald motortyp och underhållstyp. Utifrån dessa tre delar skapades en inköpslista. Inköpslistan innehåller motortyp, materialnummer, materialbeskrivning, kvantitet, pris och ABC-klassifikation. Noggrannare listor kan tas fram vilket leder till minskad kapitalbindning och en förbättrad leveransservice. Resultatet blir mer faktabaserat eftersom tidigare historik uttnyttjas. / The thesis report describes the way of creating an analysis tool for material consumption at the department of engine service at Volvo Aero Corporation. The analysis tool generates average lists and purchase lists for PW100 engine. The documentation of the analysis tool is described in seven parts. By using the tool the structural material planner can in an easy manner generate lists that are based on earlier historical data. Instead of creating lists manually the material planner can gain more accurate lists much faster. Previously there were no fact based results in comparison with today. Pre studies were made to gain a better insight of the current organization and processes at the engine service department. Interviews with staff as well literature studies in the field of storage and spare parts manage has given possibilities to create an analysis tool. Plan of requirements were created to specify the features of the analysis tool. The program Microsoft Access was chosen due to the amout of data to construct the analysis tool. All information was brought from the database SAP. The analysis tool was built in three integrated parts: 1. Average list: shows the average consumption of material for selected engine and maintenance type. 2. Stock status: checks the stock for material for selected engine and maintenance type. New and used material is selectable. 3. Incoming material: shows incoming material that is undelivered for selected engine and maintenance type. By these three integrated parts the analysis tool generates a purchase list. The list contains engine type, material number, material description, quantity, price and ABC-classification. By implementing the analysis tool in the daily work purchases will be more accurate. Capital binding will decrease as well.

Distributed generation is expected to play a significant role in remedying the many shortcomings in today’s energy market. In particular, fuel cell power generation will play a big part due to several advantages. Still, it is faced with its own challenges to tap into its potential as a solution to the crisis. The responsibilities of the Power Conditioning Unit (PCU), and thus its design, are therefore complex, yet critical to the fuel cell system’s performance and ability to meet the requirements. To this end, the dc-dc converter, considered the most critical component of the PCU for optimum performance, is closely examined. The selected converter is first modeled to gain insight into its behavior for the purpose of designing suitable compensators. MATLAB is then used to study the results using the frequency domain, and it was observed that the converter offers its own unique challenges in terms of closed-loop performance and stability. These limitations must therefore be carefully accounted for and compensated against when designing the control loops to achieve the desired objectives. Negative feedback control to ensure robustness is then discussed. The insertion of a second inner loop in Current Mode Control (CMC) offers several key advantages over single-loop Voltage Mode Control (VMC). Furthermore, the insertion of a Current Error Amplifier (CEA) in Average Current Mode Control (ACMC) helps overcome many of the problems present in Peak Current Mode Control (PCMC) whilst allowing much needed design flexibility. It is therefore well suited for this application in an attempt to improve the dynamic behavior and overcoming the shortcomings inherent in the converter. The modulator and controller for ACMC are then modeled separately and combined with the converter’s model previously derived to form the complete small-signal model. A suitable compensation network is selected based on the models and corresponding Bode plots used to assess the system’s performance and stability. The resulting Bode plot for the complete system verifies that the design objectives are clearly met. The complete system was also built in MATLAB/Simulink, and subjected to external disturbances in the form of stepped load changes. The results confirm the system’s excellent behavior despite the disturbance, and the effectiveness of the control strategy in conjunction with the derived models. To meet the demand in many applications for power sources with high energy density and high power density, it is constructive to combine the fuel cell with an Energy Storage System (ESS). The hybrid system results in a synergistic system that brings about numerous potential advantages. Nevertheless, in order to reap these potential benefits and avoid detrimental effects to the components, a suitable configuration and control strategy to regulate the power flow amongst the various sources is of utmost importance. A robust and flexible control strategy that allows direct implementation of the ACMC scheme is devised. The excellent performance and versatility of the proposed system and control strategy are once again verified using simulations. Finally, experimental tests are also conducted to validate the results presented in the dissertation. A scalable and modular test station is built that allows an efficient and effective design and testing process of the research. The results show good correspondence and performance of the models and control design derived throughout the thesis.

Since the introduction of CUSUM statistic by E.S. Page (1951), detection of change or a structural break in time series has gained significant interest as its applications span across various disciplines including economics, industrial applications, and environmental data sets. However, many of the early suggested statistics, such as CUSUM or MOSUM, lose their effectiveness when applied to time series data. Either the size or power of the test statistic gets distorted, especially for higher order autoregressive moving average processes. We use the test statistic from Gombay and Serban (2009) for detecting change in the mean of an autoregressive process and show how the application of sieve bootstrap to the time series data can improve the performance of our test to detect change. The effectiveness of the proposed method is illustrated by applying it to economic data sets.

In simulation, time averages are important for estimating equilibrium parameters. In particular, we would like to have the variance, bias and mean-square error for time averages. First, we will discuss various factors and their effect on the bias, the variance and the mean-square error. We will use the Markovian Event System to model various systems, including M/M/1 queues, M/E_k/1 queues, M/M/c queues, sequential queues, inventory systems and queueing networks. We use a numerical method for the computation of the variance, the bias and the mean-square error of the time average. The effectiveness of the method is tested by experimenting with models of various stochastic systems. The contribution of this thesis is to use numerical and graphical interpretations to study the general characteristics of the measures. The important characteristics included in our study are decomposability and periodicity.

The rise in digital technology has also rose the use of digital images. The digital imagesrequire much storage space. The compression techniques are used to compress the dataso that it takes up less storage space. In this regard wavelets play important role. Inthis thesis, we studied the Haar wavelet system, which is a complete orthonormal systemin L2(R): This system consists of the functions j the father wavelet, and y the motherwavelet. The Haar wavelet transformation is an example of multiresolution analysis. Ourpurpose is to use the Haar wavelet basis to compress an image data. The method ofaveraging and differencing is used to construct the Haar wavelet basis. We have shownthat averaging and differencing method is an application of Haar wavelet transform. Afterdiscussing the compression by using Haar wavelet transform we used another method tocompress that is based on singular value decomposition. We used mathematical softwareMATLAB to compress the image data by using Haar wavelet transformation, and singularvalue decomposition.

The fast growing waste stream of electronic and other complex consumer products is making the bulk recycling problem an important environmental protection issue. These products must be recycled because they contain hazardous materials such as lead and mercury. The focus of this thesis is the development of systematic methods for designing systems to recover mixed plastics from electronic products such as computers and televisions. Bulk recycling systems are similar to other chemical engineering process systems. Therefore they can be synthesized and designed using some existing techniques that have been applied to distillation and reaction systems. However, the existence of various uncertainties from different sources, such as the variation of component fractions and product prices, makes it crucial to design a flexible and sustainable system, and is also a major challenge in this research. Another challenge is that plastics can be separated by different mechanisms based on different properties, but separating a mix of plastics often requires using a combination of different methods because they can have overlapping differentiating properties. Therefore many decisions are to be made including which methods to choose and how to connect them. To address the problem systematically, the design under uncertainty problem was formulated as a stochastic Mixed Integer Nonlinear Program (sMINLP). A Sample Average Approximation (SAA) method wrapped on the Outer Approximation method has been developed in this thesis to solve such problems efficiently. Therefore, large design under uncertainty problems can be solved without intractable computational difficulty. To allow making choices from separation methods by different mechanisms, this research modeled various plastics separation methods taking account of the distribution of particle properties and unified them using a canonical partition curve representation. Finally, an overall design method was proposed in this work to incorporate the design of size reduction units into the separation system. This research is the first formal development of a systematic method in this area to account for uncertainties and interactions between process steps.

Neutral particles play an important role on the performance of tokamak plasmas. In this dissertation, the original TEP methodology has been extended to take into account linearly (DP_1) and quadratically (DP_2) anisotropic distributions of angular fluxes for calculations of transmission probabilities. Three approaches, subdivision of optically thick regions, expansion of collision sources and the diffusion approximation, have been developed and implemented to correct effects of the preferential probability of collided neutrals escaping back across the incident surface. Solving the diffusion equation via the finite element method has been shown to be the most computationally efficient and accurate for a broader range of D/l by comparisons with Monte Carlo simulations. The average neutral energy (ANE) approximation has been developed and implemented into the GTNEUT code. The average neutral energy approximation has been demonstrated to be more accurate than the original local ion temperature (LIT) approximation for optically thin regions. The simulations of the upgraded GTNEUT code excellently agree with the DEGAS predictions in DIII-D L-mode and H-mode discharges, and the results of both the codes are in a good agreement with the experimental measurements.