This thesis proposes a new chroma keying method that can automatically detect background, foreground, and unknown regions. For background color detection, we use K-means clustering in color space to calculate the limited number of clusters of background colors. We use spatial information to clean the background regions and minimize the unknown regions. Our method only needs minimum inputs from user. For unknown regions, we implement the alpha matte based on Wang's robust matting algorithm, which is considered one of the best algorithms in the literature, if not the best. Wang's algorithm is based on modified random walk. We proposed a better color selection method, which improves matting results in the experiments. In the thesis, a detailed implementation of robust matting is provided. The experimental results demonstrate that our proposed method can handle images with one background color, images with gridded background, and images with difficult regions such as complex hair stripes and semi-transparent clothes.

Sverige klassificerades år 2004 som det aktietätaste landet i världen, då hela 77 procent av befolkningen var exponerad mot aktiemarknaden i någon form. År 2012 uppgick innehaven på svenska börsen till 3 715 miljarder kronor. Utvecklingen på aktiemarknaden är därför något som berör merparten av Sveriges befolkning. Investerare har sedan börsens introduktion försökt förutse marknadens utveckling för att finna de vinnande aktierna. Detta har utmynnat i flera olika sätt att analysera marknaden, exempelvis genom teknisk och fundamental analys. En tredje omtalad metod är kalenderanomalier, vilket baseras på kända mönster som tenderar att inträffa under vissa perioder på handelsåret. Detta sätt att prediktera börsens utveckling har väckt författarnas intresse och ligger till grund för studiens genomförande. Studien har undersökt fem av de mest kända kalenderanomalierna; Januarieffekten, Januaribarometern, Turn-of-the-month, Sell-in-May och Holiday Effect. Syftet har varit att utvärdera om dessa anomalier existerar på Stockholmsbörsens tio officiella branschindex, samt om investerare kan utnyttja dem för att uppnå högre riskjusterad avkastning än respektive index. För att utvärdera anomaliernas existens samt investerares möjlighet till överavkastning har författarna skapat 55 syntetiska portföljer. Detta motsvarar en portfölj för varje anomali och bransch, samt för OMXSB. Undersökningsperioden som portföljerna varit aktiva på sträcker sig från 2000-01-03 till 2012-12-31. När portföljerna inte varit aktiva på marknaden har dessa investerats i SSVX 3 mån, vilket har använts som riskfri ränta i studien. Med ett deduktivt angreppssätt och en positivistisk kunskapssyn har författarna genomfört en kvantitativ undersökning på Stockholmsbörsens officiella branschindex. Studiens teoretiska referensram baseras på tre välkända teorier, varav två motsätter sig anomaliers existens medan den tredje bekräftar. De teorier som talar mot kalenderanomaliers existens är Random Walk och Effektiva Marknadshypotesen medan Behavioral Finance är den teori som ställer sig positiv till anomalierna. För att säkerställa studiens statistiska resultat har en regressionsanalys samt ett t-test används. Dessutom har Jensens Alfa legat till grund för att beräkna portföljernas riskjusterade avkastning. Studiens resultat bekräftar att kalenderanomalier existerar på flera av Stockholmsbörsens branschindex samt OMXSB. Starkaste anomalierna är Turn-ofthe-month och Sell-in-May som återfinns på flera av branscherna medan resterande kalenderanomalier endast uppvisat svaga resultat. Intressantast ur en investerares perspektiv är givetvis om resultatet går att använda för att uppnå överavkastning. Totalt är det 16 portföljer som kan användas av investerare för att uppnå högre riskjusterad avkastning än respektive index. Resultatet indikerar därför att den svenska marknaden inte är helt effektiv men att kalenderanomalier inte alltid går att utnyttja.

By equipping vehicles with the on-board wireless facility, the newly emerged vehicular networking targets to provision the broadband serves to vehicles. As such, a variety of novel and exciting applications can be provided to vehicular users to enhance their road safety and travel comfort, and finally raise a complete change to their on-road life. As the content distribution and media/video streaming, such as Youtube, Netflix, nowadays have become the most popular Internet applications, to enable the efficient content distribution and audio/video streaming services is thus of the paramount importance to the success of the vehicular networking. This, however, is fraught with fundamental challenges due to the distinguished natures of vehicular networking. On one hand, the vehicular communication is challenged by the spotty and volatile wireless connections caused by the high mobility of vehicles. This makes the download performance of connections very unstable and dramatically change over time, which directly threats to the on-top media applications. On the other hand, a vehicular network typically involves an extremely large-scale node population (e.g., hundreds or thousandths of vehicles in a region) with intense spatial and temporal variations across the network geometry at different times. This dictates any designs to be scalable and fully distributed which should not only be resilient to the network dynamics, but also provide the guaranteed quality-of-service (QoS) to users. The purpose of this dissertation is to address the challenges of the vehicular networking imposed by its intrinsic dynamic and large-scale natures, and build the efficient, scalable and, more importantly, practical systems to enable the cost-effective and QoS guaranteed content distribution and media streaming services to vehicular users. Note that to effective- ly deliver the content from the remote Internet to in-motion vehicles, it typically involves three parts as: 1.) an infrastructure grid of gateways which behave as the data depots or injection points of Internet contents and services to vehicles, 2.) protocol at gateways which schedules the bandwidth resource at gateways and coordinates the parallel transmissions to different vehicles, and 3.) the end-system control mechanism at receivers which adapts the receiver’s content download/playback strategy based on the available network throughput to provide users with the desired service experience. With above three parts in mind, the entire research work in this dissertation casts a systematic view to address each part in one topic with: 1.) design of large-scale cost-effective content distribution infrastructure, 2.) MAC (media access control) performance evaluation and channel time scheduling, and 3.) receiver adaptation and adaptive playout in dynamic download environment. In specific, in the first topic, we propose a practical solution to form a large-scale and cost-effective content distribution infrastructure in the city. We argue that a large-scale infrastructure with the dedicated resources, including storage, computing and communication capacity, is necessary for the vehicular network to become an alternative of 3G/4G cellular network as the dominating approach of ubiquitous content distribution and data services to vehicles. On addressing this issue, we propose a fully distributed scheme to form a large-scale infrastructure by the contributions of individual entities in the city, such as grocery stores, movie theaters, etc. That is to say, the installation and maintenance costs are shared by many individuals. In this topic, we explain the design rationale on how to motivate individuals to contribute, and specify the detailed design of the system, which is embodied with distributed protocols and performance evaluation. The second topic investigates on the MAC throughput performance of the vehicle-to- infrastructure (V2I) communications when vehicles drive through RSUs, namely drive-thru Internet. Note that with a large-scale population of fast-motion nodes contending the chan- nel for transmissions, the MAC performance determines the achievable nodal throughput and is crucial to the on-top applications. In this topic, using a simple yet accurate Marko- vian model, we first show the impacts of mobility (characterized by node velocity and moving directions) on the nodal and system throughput performance, respectively. Based on this analysis, we then propose three enhancement schemes to timely adjust the MAC parameters in tune with the vehicle mobility to achieve the maximal the system throughput. The last topic investigates on the end-system design to deliver the user desired media streaming services in the vehicular environment. In specific, the vehicular communications are notoriously known for the intermittent connectivity and dramatically varying throughput. Video streaming on top of vehicular networks therefore inevitably suffers from the severe network dynamics, resulting in the frequent jerkiness or even freezing video playback. To address this issue, an analytical model is first developed to unveil the impacts of network dynamics on the resultant video performance to users in terms of video start-up delay and smoothness of playback. Based on the analysis, the adaptive playout buffer mechanism is developed to adapt the video playback strategy at receivers towards the user-defined video quality. The proposals developed in the three topics are validated with the extensive and high fidelity simulations. We believe that our analysis developed in the dissertation can provide insightful lights on understanding the fundamental performance of the vehicular content distribution networks from the aspects of session-level download performance in urban vehicular networks (topic 1), MAC throughput performance (topic 2), and user perceived media quality (topic 3). The protocols developed in the three topics, respectively, offer practical and efficient solutions to build and optimize the vehicular content distribution networks.

Recent computational models and physiological studies suggest that simple, two-alternative forced-choice decision making can be conceptualized as the gradual accumulation of sensory evidence. Accordingly, information is sampled over time from a sensory stimulus, giving rise to an activation function. A response is emitted when this function reaches a criterion level of activity. Critically, the phenomenon known as speed-accuracy tradeoff (SAT) is modeled as a shift in the response boundaries (criterion). As speed stress increases and criterion is lowered, the information function travels less distance before reaching threshold. This leads to faster overall responses, but also an increase in error rate, given that less information is accumulated. Psychophysiological data using EEG and single-unit recordings from monkey cortex suggest that these accumulator models are biologically plausible. The present work is an effort to strengthen this position. Specifically, it seeks to demonstrate a neural correlate of criterion and demonstrate its relationship to behavior. To do so, subjects performed a letter discrimination paradigm under three levels of speed stress. At the same time, electroencephalogram (EEG) was used to derive a measure known as the lateralized readiness potential, which is known to reflect ongoing motor preparation in motor cortex. In Experiment 1, the amplitude of the LRP was related to speed stress: as subjects were forced to respond more quickly, less information was accumulated before making a response. In other words, criterion lowered. These data are complicated by Experiment 2, which found that there are boundary conditions for this effect to obtain.

This thesis conducts a comprehensive examination on the random walk behavior of 29 foreign exchange rates over the period of floating exchange regime, using variance-ratio tests. The cross-country and time-series test show that random walk model cannot be rejected on majority, and the random walk behavior is quite volatile across the whole floating exchange regime period. It then goes further to explore possible factors that can explain the probability of rejection/ non-rejections on random walk model using linear as well as nonlinear probability models, and find that the factors such as capital openness and investment-to-trade ratio significantly increases the chance of its exchange rate exhibiting random walk behavior.

This thesis provides a study of various boundary problems for one and two dimensional random walks. We first consider a one-dimensional random walk that starts at integer-valued height k > 0, with a lower boundary being the x-axis, and on each step moving downward with probability q being greater than or equal to the probability of going upward p. We derive the variance and the standard deviation of the number of steps T needed for the height to reach 0 from k, by first deriving the moment generating function of T. We then study two types of two-dimensional random walks with four boundaries. A Type I walk starts at integer-valued coordinates (h; k), where0 < h < m and 0 < k < n. On each step, the process moves one unit either up, down, left, or right with positive probabilities pu, pd, pl, pr, respectively, where pu + pd + pl + pr = 1. The process stops when it hits a boundary. A Type II walk is similar to a Type I walk except that on each step, the walk moves diagonally, either left and upward, left and downward, right and downward, or right and upward with positive probabilities plu, pld, prd, pru, respectively. We mainly answer two questions on these two types of two-dimensional random walks: (1) What is the probability of hitting one boundary before the others from an initial starting point? (2) What is the average number of steps needed to hit a boundary? To do so, we introduce a Markov Chains method and a System of Equations method. We then apply the obtained results to a boundary problem involving two independent one-dimensional random walks and answer various questions that arise. Finally, we develop a conjecture to calculate the probability of a two-sided downward-drifting Type II walk with even-valued starting coordinates hitting the x-axis before the y-axis, and we test the result with Mathematica simulations

No description available.

This thesis proposes a new chroma keying method that can automatically detect background, foreground, and unknown regions. For background color detection, we use K-means clustering in color space to calculate the limited number of clusters of background colors. We use spatial information to clean the background regions and minimize the unknown regions. Our method only needs minimum inputs from user. For unknown regions, we implement the alpha matte based on Wang's robust matting algorithm, which is considered one of the best algorithms in the literature, if not the best. Wang's algorithm is based on modified random walk. We proposed a better color selection method, which improves matting results in the experiments. In the thesis, a detailed implementation of robust matting is provided. The experimental results demonstrate that our proposed method can handle images with one background color, images with gridded background, and images with difficult regions such as complex hair stripes and semi-transparent clothes.

By equipping vehicles with the on-board wireless facility, the newly emerged vehicular networking targets to provision the broadband serves to vehicles. As such, a variety of novel and exciting applications can be provided to vehicular users to enhance their road safety and travel comfort, and finally raise a complete change to their on-road life. As the content distribution and media/video streaming, such as Youtube, Netflix, nowadays have become the most popular Internet applications, to enable the efficient content distribution and audio/video streaming services is thus of the paramount importance to the success of the vehicular networking. This, however, is fraught with fundamental challenges due to the distinguished natures of vehicular networking. On one hand, the vehicular communication is challenged by the spotty and volatile wireless connections caused by the high mobility of vehicles. This makes the download performance of connections very unstable and dramatically change over time, which directly threats to the on-top media applications. On the other hand, a vehicular network typically involves an extremely large-scale node population (e.g., hundreds or thousandths of vehicles in a region) with intense spatial and temporal variations across the network geometry at different times. This dictates any designs to be scalable and fully distributed which should not only be resilient to the network dynamics, but also provide the guaranteed quality-of-service (QoS) to users. The purpose of this dissertation is to address the challenges of the vehicular networking imposed by its intrinsic dynamic and large-scale natures, and build the efficient, scalable and, more importantly, practical systems to enable the cost-effective and QoS guaranteed content distribution and media streaming services to vehicular users. Note that to effective- ly deliver the content from the remote Internet to in-motion vehicles, it typically involves three parts as: 1.) an infrastructure grid of gateways which behave as the data depots or injection points of Internet contents and services to vehicles, 2.) protocol at gateways which schedules the bandwidth resource at gateways and coordinates the parallel transmissions to different vehicles, and 3.) the end-system control mechanism at receivers which adapts the receiver’s content download/playback strategy based on the available network throughput to provide users with the desired service experience. With above three parts in mind, the entire research work in this dissertation casts a systematic view to address each part in one topic with: 1.) design of large-scale cost-effective content distribution infrastructure, 2.) MAC (media access control) performance evaluation and channel time scheduling, and 3.) receiver adaptation and adaptive playout in dynamic download environment. In specific, in the first topic, we propose a practical solution to form a large-scale and cost-effective content distribution infrastructure in the city. We argue that a large-scale infrastructure with the dedicated resources, including storage, computing and communication capacity, is necessary for the vehicular network to become an alternative of 3G/4G cellular network as the dominating approach of ubiquitous content distribution and data services to vehicles. On addressing this issue, we propose a fully distributed scheme to form a large-scale infrastructure by the contributions of individual entities in the city, such as grocery stores, movie theaters, etc. That is to say, the installation and maintenance costs are shared by many individuals. In this topic, we explain the design rationale on how to motivate individuals to contribute, and specify the detailed design of the system, which is embodied with distributed protocols and performance evaluation. The second topic investigates on the MAC throughput performance of the vehicle-to- infrastructure (V2I) communications when vehicles drive through RSUs, namely drive-thru Internet. Note that with a large-scale population of fast-motion nodes contending the chan- nel for transmissions, the MAC performance determines the achievable nodal throughput and is crucial to the on-top applications. In this topic, using a simple yet accurate Marko- vian model, we first show the impacts of mobility (characterized by node velocity and moving directions) on the nodal and system throughput performance, respectively. Based on this analysis, we then propose three enhancement schemes to timely adjust the MAC parameters in tune with the vehicle mobility to achieve the maximal the system throughput. The last topic investigates on the end-system design to deliver the user desired media streaming services in the vehicular environment. In specific, the vehicular communications are notoriously known for the intermittent connectivity and dramatically varying throughput. Video streaming on top of vehicular networks therefore inevitably suffers from the severe network dynamics, resulting in the frequent jerkiness or even freezing video playback. To address this issue, an analytical model is first developed to unveil the impacts of network dynamics on the resultant video performance to users in terms of video start-up delay and smoothness of playback. Based on the analysis, the adaptive playout buffer mechanism is developed to adapt the video playback strategy at receivers towards the user-defined video quality. The proposals developed in the three topics are validated with the extensive and high fidelity simulations. We believe that our analysis developed in the dissertation can provide insightful lights on understanding the fundamental performance of the vehicular content distribution networks from the aspects of session-level download performance in urban vehicular networks (topic 1), MAC throughput performance (topic 2), and user perceived media quality (topic 3). The protocols developed in the three topics, respectively, offer practical and efficient solutions to build and optimize the vehicular content distribution networks.

The work in this thesis can be divided into two different parts. In the first part, we suggest an approximate edge 3-coloring polynomial time algorithm for cubic graphs. For any cubic graph with n vertices, using this coloring algorithm, we get an edge 3-coloring with at most n/3 error vertices. In the second part, we study Jim Propp's Rotor-Router model on some non-bipartite graph. We find the difference between the number of chips at vertices after performing a walk on this graph using Propp model and the expected number of chips after a random walk. It is known that for line of integers and d-dimenional grid, this deviation is constant. However, it is also proved that for k-ary infinite trees, for some initial configuration the deviation is no longer a constant and say it is D. We present a similar study on some non-bipartite graph constructed from k-ary infinite trees and conclude that for this graph with the same initial configuration, the deviation is almost (k²)D.