published_or_final_version / Mathematics / Master / Master of Philosophy

The deficiencies of traditional dendrometry mean improvements in methods of tree mensuration are necessary in order to obtain accurate tree metrics for applications such as resource appraisal, and biophysical and ecological modelling. This thesis tests the potential of SfM-MVS (Structure-fromMotion with Multi-View Stereo-photogrammetry) using the software package PhotoScan Professional, for accurately determining linear (2D) and volumetric (3D) tree metrics. SfM is a remote sensing technique, in which the 3D position of objects is calculated from a series of photographs, resulting in a 3D point cloud model. Unlike other photogrammetric techniques, SfM requires no control points or camera calibration. The MVS component of model reconstruction generates a mesh surface based on the structure of the SfM point cloud. The study was divided into two research components, for which two different groups of study trees were used: 1) 30 small, potted ‘nursery’ trees (mean height 2.98 m), for which exact measurements could be made and field settings could be modified, and; 2) 35 mature ‘landscape’ trees (mean height 8.6 m) located in parks and reserves in urban areas around the South Island, New Zealand, for which field settings could not be modified. The first component of research tested the ability of SfM-MVS to reconstruct spatially-accurate 3D models from which 2D (height, crown spread, crown depth, stem diameter) and 3D (volume) tree metrics could be estimated. Each of the 30 nursery trees was photographed and measured with traditional dendrometry to obtain ground truth values with which to evaluate against SfM-MVS estimates. The trees were destructively sampled by way of xylometry, in order to obtain true volume values. The RMSE for SfM-MVS estimates of linear tree metrics ranged between 2.6% and 20.7%, and between 12.3% and 47.5% for volumetric tree metrics. Tree stems were reconstructed very well though slender stems and branches were reconstructed poorly. The second component of research tested the ability of SfM-MVS to reconstruct spatially-accurate 3D models from which height and DBH could be estimated. Each of the 35 landscape trees, which varied in height and species, were photographed, and ground truth values were obtained to evaluate against SfM-MVS estimates. As well as this, each photoset was thinned to find the minimum number of images required to achieve total image alignment in PhotoScan and produce an SfM point cloud (minimum photoset), from which 2D metrics could be estimated. The height and DBH were estimated by SfM-MVS from the complete photosets with RMSE of 6.2% and 5.6% respectively. The height and DBH were estimated from the minimum photosets with RMSE of 9.3% and 7.4% respectively. The minimum number of images required to achieve total alignment was between 20 and 50. There does not appear to be a correlation between the minimum number of images required for alignment and the error in the estimates of height or DBH (R2 =0.001 and 0.09 respectively). Tree height does not appear to affect the minimum number of images required for image alignment (R 2 =0.08).

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Emotions have been noted for their crucial role in survival behaviour relating to resistance to cross-cultural ambiguity. Today's globalised multinational corporations (MNCs) have recognised the importance of developing their diverse workforces' intercultural sensitivity (ICS) – a worldview towards cultural difference – as a means of reducing resistance to cross-cultural ambiguity hence maintaining a professional multicultural work environment. However, no studies have yet been made investigating the role of emotional intelligence (EI) in enhancing intercultural sensitivity and simultaneously regulating emotions produced from resistance to cultural difference. Therefore, this study has explored the role of EI in enhancing ICS aiming at increasing the effectiveness of intercultural training within the context of multinational organisations. A theoretical framework was constructed presenting the idea of EI entry-points into intercultural sensitivity and resistance to difference. Through an inductive research approach, a chosen multinational airline company's flight attendants were targeted with in-depth semi-structured interviews. Grounded theory analysis was applied. The analysis resulted in the development of a grounded emotional-cognitive intercultural adaptation process together with three adaptive cognitive states. These were named: Learn, Understand, and Know. Each cognitive state was noted to be associated with a particular emotional state that causes the interacting individual to shift into the relevant cognitive state. The emotions surprise and curiosity were found to be associated with Learn while empathy was found to be associated with Understand, and finally acceptance was found to be associated with Know. The research results strongly support the proposed EI entry-points within the grounded emotional-cognitive content of the produced intercultural adaptation process. The results address the research aim regarding the role of EI in enhancing ICS. Through the EI entry-points, ICS is indirectly enhanced through the development of intercultural performance as EI mental abilities are proposed which would regulate one's behaviour towards the three grounded emotional-cognitive intercultural adaptation states. The developed model is suggested to contribute to enhancing the effectiveness of intercultural training. The trainee's intercultural performance could be enhanced through directing the emotional-cognitive dynamics, during intercultural interaction, towards the empirically grounded set of emotional-cognitive states. As linking EI and ICS remains an important and under-explored topic, it is hoped that the findings of this study will present a better understanding of the dynamics of emotions within the context of multinational organisations, as well as the role of EI in enhancing ICS, subsequently leading to further research.

An integrated simulation, learning, and game-theoretic framework is proposed to address the dynamics of supply chain competition. The proposed framework is composed of 1) simulation-based game platform, 2) game solving and analysis module, and 3) multi-agent reinforcement learning module. The simulation-based game platform supports multi-paradigm modeling, such as agent-based modeling, discrete-event simulation, and system dynamics modeling. The game solving and analysis module is designed to include various parts including strategy refinement, data sampling, game solving, equilibrium conditions, solution evaluation, as well as comparative statistics under varying parameter values. The learning module facilitates the decision making of each supply chain competitor under the stochastic and uncertain environments considering different learning strategies. The proposed integrated framework is illustrated for a supply chain system under the newsvendor problem setting in several phases. At phase 1, an extended newsvendor competition considering both the product sale price and service level under an uncertain demand is studied. Assuming that each retailer has the full knowledge of the other retailer's decision space and profit function, we derived the existence and uniqueness conditions of a pure strategy Nash equilibrium with respect to the price and service dominance under additive and multiplicative demand forms. Furthermore, we compared the bounds and obtained various managerial insights. At phase 2, to extend the number of decision variables and enrich the payoff function of the problem considered at phase 1, a hybrid simulation-based framework involving systems dynamics and agent-based modeling is presented, followed by a novel game solving procedure, where the procedural components include strategy refinement, data sampling, gaming solving, and performance evaluation. Various numerical analyses based on the proposed procedure are presented, such as equilibrium accuracy, quality, and asymptotic/marginal stability. At phase 3, multi-agent reinforcement learning technique is employed for the competition scenarios under a partial/incomplete information setting, where each retailer can only observe the opponent' behaviors and adapt to them. Under such a setting, we studied different learning policies and learning rates with different decay patterns between the two competitors. Furthermore, the convergence issues are discussed as well. Finally, the best learning strategies under different problem scenarios are devised.

This work presents two research efforts, one involving planetary science education research and a second involving the surface composition of Mars. In the former, student beliefs and reasoning difficulties associated with the greenhouse effect were elicited through student interviews and written survey responses from >900 US undergraduate non-science majors. This guided the development of the Greenhouse Effect Concept Inventory (GECI), an educational research tool designed to assess pre- and post-instruction conceptual understanding of the greenhouse effect. Three versions of this multiple-choice instrument were administered to >2,500 undergraduates as part of the development and validation process. In contrast to previous research efforts regarding causes, consequences, and solutions to the enhanced greenhouse effect, the GECI focuses primarily on the physics of energy flow through Earth's atmosphere. The GECI is offered to the science education community as a research tool for assessing instructional strategies on this topic.It was confirmed that the study population subscribes to several previously identified beliefs. These include correct understandings that carbon dioxide is an important greenhouse gas and the greenhouse effect increases planetary surface temperatures. Students also commonly associate the greenhouse effect with increased penetration of sunlight into and trapping of solar energy in the atmosphere. Students intermix concepts associated with the greenhouse effect, global warming, and ozone depletion. Reinforcing the latter concept, a majority believe that the Sun radiates most of its energy as ultraviolet light. Students also describe inaccurate and incomplete trapping models, which include permanent trapping, trapping through reflection, and trapping of gases and pollution. Another reasoning difficulty involves the idea that Earth's surface radiates energy primarily during the nighttime.The second research effort describes the distribution of chlorine on Mars measured by the Mars Odyssey Gamma Ray Spectrometer (GRS). The distribution of chlorine is heterogeneous across the surface, with a concentration of high chlorine centered over the Medusa Fossae Formation. The distribution of chlorine correlates positively with hydrogen and negatively with silicon and thermal inertia. Four mechanisms (aeolian, volcanic, aqueous, and hydrothermal) are discussed as possible factors influencing the distribution of chlorine measured within the upper few tens of centimeters of the surface.

Today, the competition between companies are very strong and fighted. In particular, small-medium size companies (SMEs) need to upgrade continuously in order to be in line with new technologies and new strategies that tends to develop companies in terms of productivity and quality. SMEs need, indeed, to be always competitive in a changeable market and to achieve competitive advantage through implementation of new technologies and theoretical methods or techniques. The implementation of those methods leads the company to increase its level of productivity and quality in order to achieve a competitive place within the market. The Gunasekaran framework is a tool which is useful in order to achieve a higher level of productivity and quality within a SME. This framework was studied and analyzed in order to be applied in a real life situation. This research focuses on the application of the same framework in a Mexican small company with the aim to develop and increase the level of productivity and quality of one department. Within the application of this framework, were applied the main concepts explained by the same Gunasekaran and they were analyzed in order to understand if a possible application could be useful to achieve success within the department.

Subject of research: : Kaišiadorys state forest enterprise, Žiežmariai district, central part of Strošiūnai forest. Goals of the research: Using Strošiūnai forest 1904, 1947, 1977, 1987 and 2002 years forest inventory data describe forest settlement, forest inventory works, changes in forest resources and possible reasons for that. Methodology: comparative analysis using data grouping, comparing data, indicators specialization, average values and percentages calculation and generalization methods. Research results: Strošiūnai forest, like separate economic unit was created in 1871 during forest inventory works carried out at Bačkonys (55,5 ha), Žasliai (225,4 ha) forests and Strošiūnai forest (804,2 ha), total 1085,2 ha.In years 1871-1904 total area increased by 37,9 ha, woodlands - 46,4 ha (0,8%), areas covered by forests 62,1 ha (2,5%), decreased areas without forest 15,6 ha (1,7%), agriculutural land 0,4 ha and land not used 8,2 ha (0,8%). Total forest area in years 1947-2002 decreased by 25,6 ha, forestland 2,7 ha, woodlands increased by 24%. Not a forestland area decreased by - 22,9ha (1,7%). Area of land dedicated for technological use increased by 21ha (1,6%), agricultural land decreased by 13 ha (1%). In years 1871-1904 pinewoods decreased from 92,7% to 89,8%, birch woodlands stayed the same, spruce forestland increased - from 3,4% to 7,7%. In years 1947-2002 pinewoods decreased almost a half from 82,1% to 46,0%. Areas with spruce increased almost three times (2... [to full text]

La recherche qui suit porte sur l'évaluation du profil de personnalité des cyclistes sur route élites québécois. Elle vise à mieux connaître ces athlètes qui se sacrifient sur le terrain pour voir si ceux-ci ont des comportements adaptés malgré la « pression de performance » qui leur incombe. Les cyclistes vivent beaucoup de stress physique et psychologique. L'entraînement intensif, les compétitions, les échecs sportifs, la retraite précoce, l'appui conditionnel des commanditaires, etc. sont autant de facteurs susceptibles d'engendrer des vulnérabilités comportementales. Notre recherche vise donc à évaluer la personnalité des cyclistes professionnels québécois pour être en mesure de leur offrir un encadrement physique et psychologique conséquent et adéquat, à la hauteur de leur investissement sportif. 20 cyclistes sur route élites canadiens ont été évalués via le TCI (Temparement and Character Inventory) qui permet de définir le caractère des individus selon 3 dimensions (détermination, coopération et transcendance) et le tempérament des individus selon 4 dimensions (recherche de nouveautés, évitement du danger, dépendance à la récompense et persistance). Tous les cyclistes participants étaient de niveau élite, âgés de 19 à 35 ans et de sexe masculin. Ils ont eu à remplir un questionnaire auto-administré de 226 questions (Vrai ou Faux). Un groupe témoin de 20 sujets a également rempli le TCI. Les résultats montrent en somme qu'il existe peu de différences entre le groupe de cyclistes et le groupe témoin. Les premiers obtiennent des scores plus élevés pour la dimension de « persistance ». C'est dire que les sportifs participants accusent d'une plus grande détermination que le groupe témoin. Les athlètes obtiennent par ailleurs des résultats plus faibles pour la dimension « dépendance à la récompense » laissant présumer qu'ils sont plus pragmatiques et plus rationnels que le groupe témoins. Ces résultats sont encourageants puisqu'ils laissent croire que les cyclistes élites canadiens ont des comportements adaptés à leur pratique. ______________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : cyclistes, profil de personnalités, pression de performance, Temparement and Character Inventory, comportement, athlètes

We study simulation optimization methods for the stochastic economic lot scheduling problem. In contrast to prior research, we focus on methods that treat this problem as a black box. Based on a large-scale numerical study, we compare approximate dynamic programming with a global search for parameters of simple control policies. We propose two value function approximation schemes based on linear combinations of piecewise- constant functions as well as control policies that can be described by a small set of parameters. While approximate value iteration worked well for small problems with three products, it was clearly outperformed by the global policy search as soon as problem size increased. The most reliable choice in our study was a globally optimized fixed-cycle policy. An additional analysis of the response surface of model parameters on optimal average cost revealed that the cost effect of product diversity was negligible. (authors' abstract)