WAVELET TRANSFORM FOR MEDIUM-RANGE STREAMFLOWS PROJECTIONS IN NATIONAL INTERCONNECTED SYSTEM

This work aims to analyze the variability of average annual streamflow time series of the SIN (Brazil) and create a projection model of future streamflow scenarios from 3 to 10 years using wavelet transform. The streamflow time series were used divided into two periods: 1931 to 2005 and 2006 to 2017, for calibration and verification, respectively. The annual series was standardized, and by the wavelet transform, it was decomposed into two bands plus the residue for each Base Posts (BP) for later reconstruction. Then an autoregressive model per band and residue was made. The projection was obtained by adding the autoregressive models. For performance evaluation, a qualitative analysis of the cumulative probability distribution of the projected years and the likelihood were made. The model identified the probability distribution function of the projected years and obtained likelihood greater than 1 in most of the SIN regions, indicating that this methodology can capture the medium-range variability.

Cooperative Visual Augmentation Algorithm of Intelligent Vehicle Based on Inter-Vehicle Image Fusion

In a connected vehicle environment based on vehicle-to-vehicle (V2V) technology, images from front and ego vehicles are fused to augment a driver’s or autonomous system’s visual field, which is helpful in avoiding road accidents by eliminating the blind point (the objects occluded by vehicles), especially tailgating in urban areas. Realizing multi-view image fusion is a tough problem without knowing the relative location of two sensors and the fusing object is occluded in some views. Therefore, we propose an image geometric projection model and a new fusion method between neighbor vehicles in a cooperative way. Based on a 3D inter-vehicle projection model, selected feature matching points are adopted to estimate the geometric transformation parameters. By adding deep information, our method also designs a new deep-affine transformation to realize fusing of inter-vehicle images. Experimental results on KIITI (Karlsruhe Institute of Technology and Toyota Technological Institute) datasets are shown to validate our algorithm. Compared with previous work, our method improves the IoU index by 2~3 times. This algorithm can effectively enhance the visual perception ability of intelligent vehicles, and it will help to promote the further development and improvement of computer vision technology in the field of cooperative perception.

Essays in Risk Management

<p>This thesis consists of five chapters that examines risk and uncertainty within two frameworks: foreign exchange market and real options. The first chapter is a preliminary part that overviews the structure of thesis. In the second chapter, I examine the impact of scheduled macroeconomic announcements on realised variance in the Canadian dollar/US dollar foreign exchange market. Information shocks as a whole are made up of public information shocks and private information shocks. I measure the public information shocks from the analyst forecast surprise and the private information shocks from volatility sensitivity to liquidity variables. I find that the realized variance is driven mainly by the latter rather than the former. However, my results for the most important announcements are not significant, which might be due to these being well-analysed publicly. Spread, as a proxy of private information shocks, is the most important liquidity measure, showing a significant increase around the arrival of announcements. My results are robust to joint effects of liquidity variables, considering announcements throughout the day (times other than 8:30 announcement), alternative measures of volatility (absolute return and modified absolute return), evaluation of announcements for US and Canada separately, examine the impact of surprise in model, and the economic classification of announcements. In the third chapter, I aim to evaluate risk and uncertainty using real options technique. I develop a framework to evaluate representative agents’ behaviour in a real options switching framework. I set up three models with revertible switching process under uncertainty and solve these using the alternating direction implicit algorithm. The models break down into: cash-cost model, cash-time model, and projection model. The cash-cost model captures the cash expenses of switching whereas the cash-time model not only captures the cash cost but also the exact time cost, which is critical in horticulture. The projection model presents an approximation of cash-time model that has less computational complexity. The results of my sensitivity analyses indicate that increases in cost, time, volatility, drift, and discount rate have negative impacts on the switch frequency. If the correlation between two crops is positive, it has negative impacts on switch frequency, otherwise it has positive impacts. Differences between the models are more pronounced over longer periods. In the fourth and fifth chapters, I extend the cash-time model from chapter three to evaluate orchardists’ behaviour in the Hawke’s Bay region. Chapter four examines the dataset thoroughly and provide a statistical review of orchards that will be modeled in chapter five. Orchardists have the incentive to switch from one type of apple to another as the apple profits change. In my model, orchardists have the option to carry on with the existing apple trees or to switch to competing apple types by uprooting the existing apple trees and planting new ones or grafting on the existing rootstock. The uprooting strategy is relatively expensive but is instantaneous, and results in young (unproductive) apple trees with a long life ahead of them. In contrast, the grafting strategy is less expensive and faster but continues with old trees. I compute the optimal land value at each age of apple trees from one-year to 33-years old. My results show that grafting is the optimal strategy when trees are young, whereas planting becomes optimal when they are old. Examining the apple dataset, I find that orchardists are biased against uprooting and grafting relative to my predictions. The deviation from what my model proposes and what orchardists follow in reality might be due to the assumption of my model and possible factors in the orchards that my model does not capture. My results show that the deviation from optimal policy for small orchardists is not significantly different from large orchardists.</p>

Essays in Risk Management

<p>This thesis consists of five chapters that examines risk and uncertainty within two frameworks: foreign exchange market and real options. The first chapter is a preliminary part that overviews the structure of thesis. In the second chapter, I examine the impact of scheduled macroeconomic announcements on realised variance in the Canadian dollar/US dollar foreign exchange market. Information shocks as a whole are made up of public information shocks and private information shocks. I measure the public information shocks from the analyst forecast surprise and the private information shocks from volatility sensitivity to liquidity variables. I find that the realized variance is driven mainly by the latter rather than the former. However, my results for the most important announcements are not significant, which might be due to these being well-analysed publicly. Spread, as a proxy of private information shocks, is the most important liquidity measure, showing a significant increase around the arrival of announcements. My results are robust to joint effects of liquidity variables, considering announcements throughout the day (times other than 8:30 announcement), alternative measures of volatility (absolute return and modified absolute return), evaluation of announcements for US and Canada separately, examine the impact of surprise in model, and the economic classification of announcements. In the third chapter, I aim to evaluate risk and uncertainty using real options technique. I develop a framework to evaluate representative agents’ behaviour in a real options switching framework. I set up three models with revertible switching process under uncertainty and solve these using the alternating direction implicit algorithm. The models break down into: cash-cost model, cash-time model, and projection model. The cash-cost model captures the cash expenses of switching whereas the cash-time model not only captures the cash cost but also the exact time cost, which is critical in horticulture. The projection model presents an approximation of cash-time model that has less computational complexity. The results of my sensitivity analyses indicate that increases in cost, time, volatility, drift, and discount rate have negative impacts on the switch frequency. If the correlation between two crops is positive, it has negative impacts on switch frequency, otherwise it has positive impacts. Differences between the models are more pronounced over longer periods. In the fourth and fifth chapters, I extend the cash-time model from chapter three to evaluate orchardists’ behaviour in the Hawke’s Bay region. Chapter four examines the dataset thoroughly and provide a statistical review of orchards that will be modeled in chapter five. Orchardists have the incentive to switch from one type of apple to another as the apple profits change. In my model, orchardists have the option to carry on with the existing apple trees or to switch to competing apple types by uprooting the existing apple trees and planting new ones or grafting on the existing rootstock. The uprooting strategy is relatively expensive but is instantaneous, and results in young (unproductive) apple trees with a long life ahead of them. In contrast, the grafting strategy is less expensive and faster but continues with old trees. I compute the optimal land value at each age of apple trees from one-year to 33-years old. My results show that grafting is the optimal strategy when trees are young, whereas planting becomes optimal when they are old. Examining the apple dataset, I find that orchardists are biased against uprooting and grafting relative to my predictions. The deviation from what my model proposes and what orchardists follow in reality might be due to the assumption of my model and possible factors in the orchards that my model does not capture. My results show that the deviation from optimal policy for small orchardists is not significantly different from large orchardists.</p>

Reliable Template Matching for Image Detection in Vision Sensor Systems

Template matching is a simple image detection algorithm that can easily detect different types of objects just by changing the template without tedious training procedures. Despite these advantages, template matching is not currently widely used. This is because traditional template matching is not very reliable for images that differ from the template. The reliability of template matching can be improved by using additional information (depths for the template) available from the vision sensor system. Methods of obtaining the depth of a template using stereo vision or a few (two or more) template images or a short template video via mono vision are well known in the vision literature and have been commercialized. In this strategy, this paper proposes a template matching vision sensor system that can easily detect various types of objects without prior training. To this end, by using the additional information provided by the vision sensor system, we study a method to increase the reliability of template matching, even when there is a difference in the 3D direction and size between the template and the image. Template images obtained through the vision sensor provide a depth template. Using this depth template, it is possible to predict the change of the image according to the difference in the 3D direction and the size of the object. Using the predicted changes in these images, the template is calibrated close to the given image, and then template matching is performed. For ease of use, the algorithm is proposed as a closed form solution that avoids tedious recursion or training processes. For wider application and more accurate results, the proposed method considers the 3D direction and size difference in the perspective projection model and the general 3D rotation model.

Longitude and Latitude Based Received Signal Strength Difference Localization Models

In order to use the latitude and longitude coordinates for received signal strength difference (RSSD) localization, the errors of several spherical distance calculation methods and the error of arc length relative to string length were compared. The distance-calculation RSSD localization equations were established, including spherical accurate calculation RSSD, spherical approximate calculation RSSD, and normal cylindrical projection RSSD. And then, the optimization RSSD localization models based on geodetic coordinates and corresponding to the above equations were established, and the models were verified using the point by point search method with good convergence. The numerical results show there are a lot of weak localization areas for the RSSD localization networks lack of central stations with 4,5,6 stations. Among networks with central stations, there are only a small number of weak-localization areas for the concave 4 stations network, while there are no weak-localization areas for the networks composed of more stations. When the measurement errors and the additional losses of radio wave propagation are not considered, the localization errors of the spherical accurate model, the spherical approximate model and the equianglular projection model are very small, among which the second model has the shortest localization time. The localization errors of equidistance projection model and equal-area projection model are large, neither of which is suitable for the middle latitude and high latitude areas.

AN EMPLOYMENT PROJECTION MODEL IN THE INDUSTRIAL SECTOR IN THE STATE OF PAHANG: A CASE STUDY

Pahang is a state that is constantly intensifying development efforts to ensure the well-being of its people in achieving the target of becoming a viable state by 2050. However, the Covid-19 pandemic crisis has threatened the well-being of the population, especially the negative impact on the socio-economic landscape. As a result, almost all economic and social sectors were closed and has resulted in workers experiencing wage reductions, layoffs, and consequently rising unemployment rates. Therefore, Pahang state government needs to optimize all the opportunities available, among them is throughout efficient and effective management of employment resources. This study is a case study under the topic of employment resource management for the Pahang state government. The main objective of this study is to support Pahang state government in identifying the projected source of labor for the year 2020-2025, especially in the industrial sector. Apart from that, this study also seeks to help the Pahang state government by identifying factors related to the development of the industrial sector in line with the increase in employment resources. To realize the objectives of the study, secondary data were fully used in the data analysis. The results of the data analysis have projected that employment resources in the state of Pahang will increase approximately by 5,000 people a year and will reach a total of 1.77 million by 2025. The total labor force also increased from 748,000 in 2021 to 767,300 people in 2025 with Labor Force Participation Rate equivalent to 63.31%. At the same time the projection also records the total external labor force increasing to 42,400 people although at the same time the total working population increased to 733,600 people. The study also proposes employment projections in the industrial sector from 2021 to 2025. It is hoped that various initiatives that are implemented by various stakeholders to the industrial sector in Pahang could offers innovative employment opportunities to various sections of society to enhance socio-economic growth and spread the wellbeing to the society.