In this master thesis, the problem of tracking groups using an image sequence dataset is examined. Target tracking can be defined as the problem of estimating a target's state given prior knowledge about its motion and some sensor measurements related to the target's state. A popular method for target tracking is e.g. the Kalman filter. However, the Kalman filter is insufficient when there are multiple targets in the scene. Consequently, alternative multitarget tracking methods must be applied along with methods for estimating the number of targets in the scene. Multitarget tracking can however be difficult when there are many unresolved targets, e.g. associating observations with targets in dense crowds. A viable simplification is group target tracking, keeping track of groups rather than individual targets. Furthermore, group target tracking is preferred when the user wants to know the motion and extension of a group in e.g. evacuation scenarios. To solve the problem of group target tracking in video surveillance, a combination of GM-PHD filtering and mean shift clustering is proposed. The GM-PHD filter is an approximation of Bayes multitarget filter. Pedestrian detections converted into flat world coordinates from the image dataset are used as input to the filter. The output of the GM-PHD filter consists of Gaussian mixture components with corresponding mean state vectors. The components are divided into groups by using mean shift clustering. An estimate of the number of members and group shape is presented for each group. The method is evaluated using both single camera measurements and two cameras partly surveilling the same area. The results are promising and present a nice visual representation of the groups' characteristics. However, using two cameras gives no improvement in performance, probably due to differences in detections between the two cameras, e.g. a single pedestrian can be observed being at two positions several meters apart making it difficult to determine if it is a single pedestrian or multiple pedestrians.

Recent criminological scholarship characterizes media attention to aggressive girls, or “mean girls,” as a moral panic, which is correlated with the creation of increasingly punitive antibullying policies in North America. Content analysis was used to uncover how news attention to youth aggression around the time of Reena Virk’s murder contributed to this moral panic in Toronto newspapers. Results indicate that Virk’s murder helped change the frequency and nature of news coverage of girls’ bullying. Reporting on girls’ bullying significantly increased and the dominant news frame falsely presented girls’ bullying as a major and rising problem in schools. The news coverage coincided with the development of more punitive Canadian youth policies. Recommendations for future research, theoretical development, and media practice are provided. / UOIT

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Microscopic traffic simulation is useful tool in analysing traffic and estimating the capacity and level of service of road networks. In this thesis, the four legged Idrottsparken roundabout in the city of Norrkoping in Sweden is analysed by using the microscopic traffic simulation package AIMSUN. For this purpose, data regarding traffic flow counts, travel times and queue lengths were collected for three consecutive weekdays during both the morning and afternoon peak periods. The data were then used in model building for simulation of traffic of the roundabout. The Root Mean Square Error (RMSE) method is used to get the optimal parameter value between queue length and travel time data and validation of travel time data are carried out to obtain the basic model which represents the existing condition of the system. Afterward, the results of the new models were evaluated and compared to the results of a SUMO model for the same scenario model. Based on calibrated and validated model, three alternative scenarios were simulated and analysed to improve efficiency of traffic network in the roundabout. The three scenarios includes: (1) add one free right turn in the north and east sections; (2) add one free right turn in the east and south sections; and (3) addition of one lane in roundabout. The analysis of these scenarios shows that the first and second scenario are only able to reduce the queue length and travel time in two or three legs, while the third scenario is not able to improve the performance of the roundabout. In this research, it can be concluded that the first scenario is considered as the best scenario compared to the second scenario and the third scenario. The comparison between AIMSUN and SUMO for the same scenario shows that the results have no significance differences. In calibration process, to get the optimal parameter values between the model measurements and the field measurements, both of AIMSUN and SUMO uses two significantly influencing parametersfor queue and travel time. AIMSUN package uses parameter of driver reaction time and the maximum acceleration, while SUMO package uses parameter of driver imperfection and also the driver rection time.

This thesis includes three chapters on electricity and natural gas prices. In the first chapter, we give a brief introduction to the characteristics of power prices and propose a mean reversion jump diffusion model, in which jump intensity depends on temperature data and overall system load, to model electricity prices. Compared to the models used in the literature, we find the model proposed in this chapter is better to capture the tail behavior in the electricity prices. In the second chapter, we use the model proposed in the first chapter to simulate the spark spread option and value the power generations. In order to simulate power generation, we first propose and estimate mean reversion jump diffusion model for natural gas prices, in which jump intensity is defined as a function of temperature and storage. Combing the model with the electricity models in chapter 1, we find that the value of power generation is closer to the real value of the power plants as reflected in the recent market transaction than one obtains from many other models used in literature. The third chapter investigates extremal dependence among the energy market. We find a tail dependence that exceeds the Pearson correlation ρ, which means the traditional Pearson correlation is not appropriate to model tail behavior of oil, natural gas and electricity prices. However, asymptotic dependence is rejected in all pairs except Henry Hub gas return and Houston Ship Channel gas return. We also find that extreme value dependence in energy market is stronger in bull market than that in bear market due to the special characteristics in energy market, which conflicts the accepted wisdom in equity market that tail correlation is much higher in periods of volatile markets from previous literature.

DOES INCREASING FLOW TO A HIGH FLOW NASAL CANNULA AFFECT MEAN AIRWAY PRESSURE IN AN IN VITRO MODEL? Introduction: High-flow nasal cannulas (HFNC) have become popular with many institutions for administration of oxygen (O2). HFNCs are also being used in pediatric and neonatal populations for administration of continuous positive airway pressure (CPAP) as a treatment for respiratory distress. Adult patients are being treated with HFNCs in a effort to provide a high percentage of O2 and correct hypoxemia and other related conditions. The purpose of this study was to examine the effect of increasing flow via a HFNC to an in vitro model to examine the effect of flow on mean airway pressure (MPAW). Method: An in vitro model to simulate non-labored and labored spontaneous breathing was developed using a Michigan Instrument Laboratory Test and Training Lung (MIL TTL) driven by a Hamilton Galileo ventilator to produce a negatively based, inspired tidal volume. Flow was introduced to the MIL TTL via a 41 French double lumen endotracheal tube. Airway pressure measurements were observed via a pressure monitoring port placed between the MIL TTL and the endotracheal tube and connected to the auxiliary pressure monitoring port located on the front of the Galileo ventilator. A Vapotherm 2000i with adult transfer chamber and adult cannula, a Fisher Paykel Optiflow, and a generic HFNC consisting of a concha column and a Salter labs high-flow cannula were tested at 20, 30, and 40LPM flowrates. Data was recorded using two respiratory rates (12 and 24) and two peak flowrates (35 and 65LPM) to simulate non-labored and labored breathing. All other parameters were unchanged and the I:E ratio was consistent. Data Analysis: SPSS 16.0 for Windows was used to analyze all data for this study. Descriptive statistics, one-way analysis of variance (ANOVA), and post hoc Bonferroni was used for this study. A p value less than 0.05 were considered significant. Results: Average MPAW for all devices were increased at all three flowrates. MPAW was highest at 40LPM flow producing 3.1cmH2O averaged for all HFNCs and both respiratory patterns. The difference in MPAW produced by the three HFNCs were also significant with at p=0.000 at all flow rates. Post hoc Bonferroni adjusted probabilities further showed all device comparisons significant except for Vapotherm-Vapotherm Labored at 30 and 40 LPM flow rates and Vapotherm-Generic Labored at 20 LPM at p<0.05. These three comparisons were at p>0.05 and were statistically equal. The generic HFNC produced the highest MPAW (3.5cmH2O). Conclusion: Increased flow via a HFNC does increase MPAW. The Vapotherm, Optiflow, and generic HFNC did not produce the same level of MPAW in this study.

The mean value engine model (MVEM) is a mathematical model derived from basic physical principles such as conservation of mass and energy equations. Although the MVEM is based on some simplified assumptions and time averaged combustion engine parameters, it models the engine with a reasonable approximation and gives a satisfactory amount of information about the physics of the fluid energy passing through an engine system. MVEM can predict an engine’s main external variables such as crankshaft speed and manifold pressure, and important internal variables, such as volumetric and thermal efficiencies. Usually, the differential equations used in MVEM will predict fuel film flow, manifold pressure, and crankshaft speed. Because of its simplicity and short simulation time, the MVEM is widely used for engine control development. A mean value engine based on mathematical and parametric equations has recently been developed in the new MapleSim software. The model consists of three main components: the throttle body, the manifold, and the engine. The new MVEM uses combinations of causal and acausal components along with lookup tables and parametric equations. Adjusting the parameters allows the model to be used for new engines of interest. The model is forward-looking and so benefits from both Maple’s powerful mathematical tool and Modelica’s modern equation-based language. A set of throttle angle and mass flow data is used to find the throttle angle function, and to validate the throttle mass flow rates obtained from the model and the experiment.

In this thesis, we investigate the problem of channel estimation in the amplify-and-forward cooperative communication systems when the networks could be in the presence of selfish relays. The information received at the destination will be detected and then used to estimate the channel. In previous studies, the relays will deliver the information under the prerequisite for cooperation and the destination can receive the information sent from the source without any possible selfish relay. Therefore, the channel will be estimated under this over idealistic assumption. Unfortunately, the assumption does not make sense in real applications. Currently, we don¡¦t have a mechanism to guarantee the relays will always be cooperative. The performance of channel estimation will be significantly degraded when the selfish relays present in the network. Therefore, this thesis considers an amplify-and-forward cooperative communication system with direct transmission and proposes a detection mechanism to overcome the misbehaving relay problem. The detection mechanism employed estimation is based on likelihood ratio test using both direct transmission and relayed information. The detection result will then be used to reconstruct the codeword used for estimating product channel gain of the source-to-relay and relay- to-destination links. The mathematical derivation for the considered problem is developed and numerical simulations for illustration is also carried out in the thesis. The numerical simulation results verify that the proposed method is indeed able to achieve robust channel estimation.

MV is the traditional method to treat international portfolio selection problems, which bases its theory on the assumption of Normal Distribution. However, during economy recession the portfolio return turns out to be a fat tail distribution. Therefore, in this sense, we explore Roy’s SF criterion and apply the extreme theory to the historical data. We demonstrate how such portfolios would perform during the Asian Crisis, IT Bubble Bust and the Financial Crisis separately. We also compare the SF portfolio’s performance to the MV portfolio’s performance, therefore to check, SF and MV portfolio, which will outperform during bust and boom of the economy. The Asian Crisis was marked with great currency devaluation and lower currency return on equity. The Dot.Com Bubble Busts was known for its sharp plummet in the stock market, while, the Financial Crisis was known as the large falls in the US stock market and elsewhere. They are the extreme events of the world capital markets, which in some way contribute to the non-normal distribution. Simulated results over the 1997-2010 period which include six busts and booms: the Asian Crisis, period after Asian Crisis, IT Bubble Bust, period after IT Bubble Bust, The Financial Crisis and period after The Financial Crisis, indicate that SF portfolio outperforms MV portfolio during most of the times, this result is especially obvious for Indonesian and Thailand.

According to the observational data in the northeast coast of Taiwan when the strong typhoon invaded, it was found that abnormal water variation happened several times, and all the abnormal water levels (storm surge) were higher than the normal engineering consideration. In this study, the variation of mean water level (wave set-up & wave set-down) due to progressive wave over a seabed with specific profile has been investigated. This specific seabed is simulated by the hydrodynamic physical models in the laboratory. Two kinds of experimental models are arranged; one is combined by three sections: slope, platform, and vertical wall, and another is combined by slope and vertical. Furthermore, two different slopes of 1/10 and 1/30 were considered. All experimental conditions were controlled such that incident waves break on slope and mean water levels were measured. In the first model arrangement, surf similarity parameter and dimensionless parameters form by incident and break wave condition are found to be functions of relative max mean water level, but when slope is steep(1/10), the relation between these dimensionless parameters is not obviously. In the second model arrangement, mean water level variation is compared with the theoretical value of single slope. When slope is mild(1/30), experimental results of mean water levels quit agree with theoretical value; when slope is steep(1/10), caused by the reflection of vertical wall, mean water levels in the break point and surf zone are different form theoretical value significantly.