No description available.

Thesis (M.S.)--Oregon State University, 1970. / Typescript. Includes bibliographical references (leaves 43-45). Also available on the World Wide Web.

Thesis (M.S.)--Oregon State University, 1972. / Typescript (photocopy). Includes bibliographical references. Also available on the World Wide Web.

Thesis (Ph. D.)--Ohio State University, 2004. / Includes bibliographical references (p. 156-166).

With widespread use of pesticides in modern agriculture, the impacts of spray drift have become a topic of considerable interest. The drifting of sprays is a highly complex process influenced by many factors. Advances in aerial application technology and in our ability to measure drift, coupled with the adoption of new technologies for regulating pesticide application have necessitated further research in the pesticide application process. Experiments were conducted to quantify spray drift and describe its movement from aerial applications of pesticide. The effects of spray quality, atomizer type and ground cover were examined. Initial airborne drift amounts were greater than downwind deposits, thus not all of the drifting spray was deposited in the measuring area. Total off-target movement of spray was significantly greater for Fine compared to Coarse sprays. Rotary and hydraulic atomizers, both producing Fine sprays, produced statistically similar off-target movement of sprays. Similarly, no significant statistical differences in spray drift between applications to bare ground and applications to a headed barley crop canopy were not identified. Contrary to expectations, aerial application to bare ground seemed to result in less off-target movement than application to a crop canopy. The vertical spray cloud profiles were similar for all applications with the greatest amount of spray present at the height of release. Spray concentrations diminished from that height upward with diffusion and downward with deposition. The empirical data disagreed with the mechanistic model AgDISP which is currently used in the Canadian regulatory process. The model over-predicted drift deposition by a factor of two to five. Variability in spray deposit values could not be attributed to average differences in meteorological conditions at the time of application. Experiments with appropriate protocols for increased sensitivity may be required to more accurately report subtle differences in drift at distances greater than 200 m from the target area.

This is a master thesis of the Master of Science degree program in Applied Physics and Electrical Engineering (Y) at Linköping University. The goal of the projectis to develop an application for creating a map in real time from a video camera on a miniature unmanned aerial vehicle. This thesis project and report is a first exploratory study for this application. It implements a prototype method and evaluates it on sample sequences from an on-board video camera. The method first looks for good points to follow in the image and then tracks them in a sequence.The image is then pasted, or merged, together with previous images so that points from the different images align. Two methods to find good points to follow are examined with focus on real-time performance. The result is that the much faster FAST detector method yielded satisfactory results good enough to replace the slower standard method of the Harris-Stephens corner detector. It is also examined whether it is possible to assume that the ground is a flat surface in this application or if a computationally more expensive method estimating altitude information has to be used. The result is that at high altitudes or when the ground is close to flat in reality and the camera points straight downwards a two-dimensional method will do. If flying lower or with high objects in the picture, which is often the case in this application, it must to be taken into account that the points really are at different heights, hence the ground can not be assumed to be flat.

This thesis work was undertaken to develop a new high level command for an unmanned aerial vehicle. The command is assumed to make the UAV follow a reference position that is placed on a certain distance to an object. At the same time the UAV is assumed to move more smoothly than the reference position and the UAV is allowed to follow the reference position with margin. The problem was solved with an automatic control system that takes the reference position as input signal and has a fictitious position as output signal. The fictitious position moves smoothly inside the margin and irregular behavior of the reference position is smoothed out by the automatic control system. The fictitious position is affected by strong feedback outside the margin and weak feedback inside the margin. This makes the fictitious position to stay inside the margin and moves smoothly inside the margin. The UAV follows the fictitious position instead of the reference position. In this way the UAV holds a certain distance to an object and at the same time moves smoother than the object.

With widespread use of pesticides in modern agriculture, the impacts of spray drift have become a topic of considerable interest. The drifting of sprays is a highly complex process influenced by many factors. Advances in aerial application technology and in our ability to measure drift, coupled with the adoption of new technologies for regulating pesticide application have necessitated further research in the pesticide application process. Experiments were conducted to quantify spray drift and describe its movement from aerial applications of pesticide. The effects of spray quality, atomizer type and ground cover were examined. Initial airborne drift amounts were greater than downwind deposits, thus not all of the drifting spray was deposited in the measuring area. Total off-target movement of spray was significantly greater for Fine compared to Coarse sprays. Rotary and hydraulic atomizers, both producing Fine sprays, produced statistically similar off-target movement of sprays. Similarly, no significant statistical differences in spray drift between applications to bare ground and applications to a headed barley crop canopy were not identified. Contrary to expectations, aerial application to bare ground seemed to result in less off-target movement than application to a crop canopy. The vertical spray cloud profiles were similar for all applications with the greatest amount of spray present at the height of release. Spray concentrations diminished from that height upward with diffusion and downward with deposition. The empirical data disagreed with the mechanistic model AgDISP which is currently used in the Canadian regulatory process. The model over-predicted drift deposition by a factor of two to five. Variability in spray deposit values could not be attributed to average differences in meteorological conditions at the time of application. Experiments with appropriate protocols for increased sensitivity may be required to more accurately report subtle differences in drift at distances greater than 200 m from the target area.

The red imported fire ant (RIFA) was introduced to the United States from South America over 75 years ago, and has become a pest in wildlife settings. Hydramethylnon fire ant bait has been the industry standard for controlling the red imported fire ant. It can be compared to novel baits, and used to evaluate different aerial application techniques, such as the "skip swath" method. Two baits, hydramethylnon and metaflumizone, and a skipped-swath method were evaluated through observations of the activity levels of RIFA mounds and abundance. The effects of RIFA on other ant species were determined by eliminating RIFA with insecticides, and then sampling for all remaining ant species. Measurements of RIFA mound activity was done by recording their response to the vibration of wire flags located in active mounds. This method indicated control of RIFA with hydramethylnon and metaflumizone from 61 to 180 d post-treatment. Additional monitoring for RIFA activity, in the same plots, was done with baited vials. These results indicated that complete control of RIFA was never achieved with either hydramethylnon or metaflumizone within 180 d post-treatment; however, there were significant reductions in RIFA population as a result of both chemical baits from 3-92 d post-treatment. A reduction of RIFA populations occurred with both baits, as determined through scheduled sampling of all ant species using baited vials. Native ants, such as Dorymyrmex spp., were found in higher numbers once RIFA populations were reduced, indicating that the two ant species compete for resources such as food and space. Dorymyrmex spp. numbers were suppressed by RIFA populations, while other ants, such as Paratrechina spp. were unaffected.

Unmanned Aerial Vehicles (UAVs) are being used more frequently in surveillance scenarios for both civilian and military applications. One such application addresses a UAV patrolling a perimeter, where certain stations can receive alerts at random intervals. Once the UAV arrives at an alert site it can take two actions: 1. Loiter and gain information about the site. 2. Move on around the perimeter. The information that is gained is transmitted to an operator to allow him to classify the alert. The information is a function of the amount of time the UAV is at the alert site, also called the dwell time, and the maximum delay. The goal of the optimization is to classify the alert so as to maximize the expected discounted information gained by the UAV's actions at a station about an alert. This optimization problem can be readily solved using Dynamic Programming. Even though this approach generates feasible solutions, there are reasons to experiment with different approaches. A complication for Dynamic Programming arises when the perimeter patrol problem is expanded. This is that the number of states increases rapidly when one adds additional stations, nodes, or UAVs to the perimeter. This in effect greatly increases the computation time making the determination of the solution intractable. The following attempts to alleviate this problem by implementing a Reinforcement Learning technique to obtain the optimal solution, more specifically Q-Learning. Reinforcement Learning is a simulation-based version of Dynamic Programming and requires lesser information to compute sub-optimal solutions. The effectiveness of the policies generated using Reinforcement Learning for the perimeter patrol problem have been corroborated numerically in this thesis.