LiDAR (Light Detection and Ranging) directly measures canopy vertical structures, and provides an effective remote sensing solution to accurate and spatiallyexplicit mapping of forest characteristics, such as canopy height and Leaf Area Index. However, many factors, such as large data volume and high costs for data acquisition, precludes the operational and practical use of most currently available LiDARs for frequent and large-scale mapping. At the same time, a growing need is arising for realtime remote sensing platforms, e.g., to provide timely information for urgent applications. This study aims to develop an airborne profiling LiDAR system, featured with on-the-fly data processing, for near real- or real- time forest inventory. The development of such a system involves implementing the on-board data processing and analysis as well as building useful regression-based models to relate LiDAR measurements with forest biophysical parameters. This work established a paradigm for an on-the-fly airborne profiling LiDAR system to inventory regional forest resources in real- or near real- time. The system was developed based on an existing portable airborne laser system (PALS) that has been previously assembled at NASA by Dr. Ross Nelson. Key issues in automating PALS as an on-the-fly system were addressed, including the design of an archetype for the system workflow, the development of efficient and robust algorithms for automatic data processing and analysis, the development of effective regression models to predict forest biophysical parameters from LiDAR measurements, and the implementation of an integrated software package to incorporate all the above development. This work exploited the untouched potential of airborne laser profilers for realtime forest inventory, and therefore, documented an initial step toward developing airborne-laser-based, on-the-fly, real-time, forest inventory systems. Results from this work demonstrated the utility and effectiveness of airborne scanning or profiling laser systems for remotely measuring various forest structural attributes at a range of scales, i.e., from individual tree, plot, stand and up to regional levels. The system not only provides a regional assessment tool, one that can be used to repeatedly, remotely measure hundreds or thousands of square kilometers with little/no analyst interaction or interpretation, but also serves as a paradigm for future efforts in building more advanced airborne laser systems such as real-time laser scanners.

Some research suggests that development of professional learning communities might be the organizational strategy that could make school reform more successful. While most schools have not institutionalized the essential components of learning organizations, studies have demonstrated that these attributes must be developed if professional staffs are to realize the full benefit of organizational learning and in the process, create a context of improvement. The primary intent of this study was to learn and understand how principal behaviors influenced the development of shared leadership, shared vision, and supportive conditions; three essential dimensions of professional learning communities. Secondly, this study investigated how these conditions differed among schools which have and have not sustained high levels of student learning. Understanding the influence of principal leadership on conditions for organizational learning can be partially understood through either quantitative or qualitative methods. From this perspective, the mixed methods design utilized in this study allowed both qualitative and quantitative data to be analyzed and interpreted as evidence in understanding the study's problem. Principal and teacher focus-group interviews were used to create a deeper understanding of how principals worked to create conditions for organizational learning. Kouzes and Posner's (2002) Leadership Practices Inventory - Self and Observer Forms were utilized to identify, describe, and measure the perceived leadership practices of principals. The findings of this investigation suggest that principal leadership is a key factor in creating conditions for organizational learning and sustaining high levels of student achievement. Principals in this study who effectively identified and modeled espoused values were perceived to be highly visionary and appeared more effective at sharing leadership, inspiring vision, and creating supportive conditions. Principals who were able to develop a shared vision among staff created strong collaborative cultures characterized by an uncompromised focus on student learning. The findings of this study also indicated that principals who effectively Model the Way, Inspire a Shared Vision, and Enable Others to Act, distributed leadership among staff and demonstrated a systems orientation to leading.

A photochemical mechanism is a very important component of an air quality model, which simulates the change of pollutant concentrations due to chemical reactions in the air. The accuracy of model prediction is directly impacted by the photochemical mechanism. In this study, two state-of-the-science photochemical mechanisms, SAPRC07 and Master Chemical Mechanism (MCM) v3.1, were implemented in the Community Multi-scale Air Quality Model (CMAQ) version 4.6 developed by the US EPA to study a high ozone (O3) episode during the 2000 Texas Air Quality Study (TexAQS) from August 16, 2000 to September 7, 2000. Predicted O3 concentrations by S07C are lower than those of S99 with a maximum difference as high as 20 percent. The two mechanisms also show significant differences in the predicted OH, PAN, HCHO and HNO3 concentrations. Although the two mechanisms predict different ozone concentrations, the relative response factors (RRFs) of O3 at rural, urban and industrial sites under emission controls of anthropogenic NOx and VOC by factors 0.6 – 1.4 predicted by the two mechanisms are very similar. Predicted O3 concentrations by MCM are similar to those of SAPRC07. The MCM predicted total VOC OH reactivity is similar to the SAPRC07 predictions at a suburban site where biogenic emissions dominate the OH reactivity and is slightly lower than the SAPRC07 predictions at an industrial site where anthropogenic emissions dominate. Besides, the predicted 1-hr and 24-hr average concentrations of major O3 precursor VOCs by MCM show under predictions of alkanes and alkenes by a factor of 2-5, 6 for ethane and 8.5 for propane. Major aromatic compounds generally agree better with observations, although benzene is under-predicted by 80 percent. Species specific emission adjustment factors can be derived from these direct comparisons to improve emission inventories in future studies. At the Clinton Drive site, most of the under-predictions occur in the afternoon when industrial facilities are in the immediate upwind direction and the missing industrial emissions are likely evaporative sources whose emission rates are temperature dependent.

Always, researchers are trying to use different ways to describe the concept ¡§Motivation¡¨. Different definition of motivation will develop different theory. However, there are two points under below at least: First is the fitness of the culture, the concept of the Western would have the specific background, will not fit in the individual person with other culture. Second, to ease the verifying of the science, most of the researches only discuss the relationship of immediate variables but neglect the influence of individual personality in different points of time. This study will combine the concepts of motivation and creativity through integrating work motivation theories and following up Teresa M. Amabile¡¦s research to build up the ¡§Personal Creative Process Model¡¨. The research model includes: the environment of organization, the process of perception, motivation, behavior and outcome. Especially, process of perception includes personality, criterion and response. ¡§Criterion¡¨ refers to personal need and value which are influenced by social environment and culture in country. Addition, ¡§Response¡¨ refers to attitude and emotion which are influenced by time. In this study, I use the concepts, ¡§Criterion¡¨ and ¡§Response¡¨, to compensate the loss of old motivation theories. Supposing the variable, ¡§Criterion¡¨, is determined, this study¡¦s purpose will find out the relationship of other variables and how these variables influence creativity. Next, using questionnaire to capture responses of college student and work adult will help us to understand the relationship of these responses. The questionnaire, this study uses, includes: ¡§Cognitive Style Instrument¡¨, ¡§What Is Happening in This Class? Questionnaire¡¨, ¡§KEYS¡¨ and ¡§The Work Preference Inventory¡¨. In addition, this study uses the grade of students to represent personal creativity and analyze the relationship between creativity and other constructs. The conclusion shows cognitive style indeed affects creativity, but the relations are different from theory. Furthermore, cognitive style and response/motivation are almost independent. To infer, the response and motivation are intervening variables between personality and creativity. Finally, regression analysis by students, this study got the result: ¡§Close by the factor is the key element of the creativity performance¡¨.

In this study, the seat inventory control problem is considered for airline networks from the perspective of a risk-averse decision maker. In the revenue management literature, it is generally assumed that the decision makers are risk-neutral. Therefore, the expected revenue is maximized without taking the variability or any other risk factor into account. On the other hand, risk-sensitive approach provides us with more information about the behavior of the revenue. The risk measure we consider in this study is the probability that revenue is less than a predetermined threshold level. In the risk-neutral cases, while the expected revenue is maximized, the probability of revenue being less than such a predetermined level might be high. We propose three mathematical models to incorporate the risk measure under consideration. The optimal allocations obtained by these models are numerically evaluated in simulation studies for example problems. Expected revenue, coefficient of variation, load factor and probability of the poor performance are the performance measures in the simulation studies. According to the results of these simulations, it shown that the proposed models can decrease the variability of the revenue considerably. In other words, the probability of revenue being less than the threshold level is decreased. Moreover, expected revenue can be increased in some scenarios by using the proposed models. The approach considered in this thesis is especially proposed for small scale airlines because risk of obtaining revenue less than the threshold level is more for this type of airlines as compared to large scale airlines.

Increased product proliferation and global competition are forcing companies within the supply chain to adopt new strategies. Postponement is an effective strategy that allows companies to be agile and cost effective in dealing with the dynamics of global supply chains. Postponement centres around delaying activities in the supply chain until real information about the market is available, which reduces the complexity and uncertainty of dealing with a proliferation of products. A two-echelon divergent supply chain entailing a central production facility and N retailers facing stochastic demand is studied within the inventory-distribution system. A periodic review order-up-to strategy is incorporated at all echelons. Unique to the study, five different systems are created and the effectiveness of several postponement strategies (form and transshipment) under various operational settings are compared. The importance of postponement under an integrated supply chain context and its contribution to various sector implementations are also discussed. Simulation is used to analyze the performance of the systems especially with respect to cost, order lead time and the effectiveness of transshipment policies. The study is unique in determining factors that favour one system implementation over another and distinguishing sector requirements that support postponement. In the study, postponement is found to be an effective strategy in dealing with managing item variety, demand uncertainty and differences in review periods in the two echelon supply chain for different experimental settings.

We consider a manufacturing system with stochastic demand and predictable production yield. The manufacturer has predetermined prices and limited production capacity in each period. The producer also has the option to save some inventory for future periods even if there is demand in the current period. The demand that is not met is lost or may be backordered for only one period. Our objective is to maximize the expected profit by choosing optimal production, save and backorder quantities in each period. We formulate this problem as a Markov Decision Process where the state of the system is represented by the net inventory and the efficiency parameter. We show that a modified (Y, S, B) policy is optimal in each period. At the end, we have some computational analysis to examine the effects of yield on the optimal decisions.

In this master thesis study, new inventory control mechanisms are developed for the repairables in Nedtrain. There is a multi-item, multi echelon system with a continuous review and one for one replenishment policy and there are different demand supply options in each control mechanism. There is an aggregate mean waiting time constraint in each local warehouse and the objective is to minimize the total system cost. The base stock levels in each warehouse are determined with an approximation method. Then different demand supply options are compared with each other.

Vendor Managed Inventory (VMI) is a business practice in which vendors monitor their customers&rsquo / inventories, and decide when and how much inventory should be replenished. VMI has attracted a lot of attention due to its benefits. In this study, we analyze the benefits of VMI in a supply chain consisting of a single retailer and a single capacitated supplier under stochastic demand. We propose a VMI setting and compare the vendor managed system with the traditional system to quantify the benefits of VMI. In our proposed VMI system, the retailer shares the inventory level information with the supplier, which is not available in traditional system / and the supplier is responsible to keep the retailer&rsquo / s inventory level between the specified minimum and maximum values, called (z,Z) levels, set by a contract. We examine the benefits of such a VMI system for each member and for the overall chain / and analyze the effects of system parameters on these benefits. The performance of VMI in coordinating the overall chain is examined under different system parameters.

In this dissertation, we consider a multi-item two-echelon inventory distribution system in which the central warehouse operates with (Q, R) policy, and each local warehouse implements base-stock policy. The objective is to find the policy parameters minimizing the relevant system-wide costs subject to an aggregate mean response time constraint at each facility. We first propose an exact solution procedure based on a branch-and-price algorithm to find the relevant policy parameters of the system considered. Then, we propose four alternative heuristics to find the optimal or near-optimal policy parameters of large practical-size systems. The first heuristic, which we call the Lagrangian heuristic, is based on the simultaneous approach and relies on the integration of a column generation method and a greedy algorithm. The other three heuristics are based on the sequential approach, in which first the order quantities are determined using a batch size heuristic, then the reorder levels at the central warehouse and the basestock levels at the local warehouses are determined through the same method used for the Lagrangian heuristic. We also propose a lower bound for the system-wide cost. Later, we extend our study to compound Poisson demand. The performance of the Lagrangian heuristic is found to be extremely well and improves even further as the number of parts increases. Also the computational requirement of the heuristic is quite tolerable. This makes the heuristic very promising for large practical industry-size problems. The performance of the sequential heuristics is also satisfactory, but not as much as the Lagrangian heuristic.