The mite ectoparasite Varroa destructor, poses a serious threat for the survival of the Apis mellifera colonies. The intensive use of acaricidal products is one of the most common methods for defending bees from Varroa that can cause the contamination of the wax foundation used in beekeeping. The natural honeycomb management could provide a solution for this problem, because it involves the use of frames without wax foundation which allows the bees to build a complete comb ex novo. On the other hand, colonies which are free to build cells of their choice, usually build a number of drone cells higher than colonies managed with the wax foundation. This could potentially lead to several negative consequences because the V. destructor reproductive success is greater on drone broods than on worker broods. The aim of the present study was to examine the colony development, to evaluate the honey production and to monitor the growth of V. destructor infestations and associated virus infections in Apis mellifera colonies managed by using natural honeycombs compared with the conventional management. Several colony parameters were measured in spring and summer. The strength of the colony was used to estimate the worker and drone populations. In order to measure the V. destructor infestations were used several methods, such as the natural mite fall, the powdered sugar roll, the soapy water and the brood cell uncapping. Molecular analysis was performed in order to measure the viral load of five Apis mellifera viruses. The honey produced was measured by collecting the honey stored in the supers, which are boxes placed on a beehive for bees to store. The results showed that the higher presence of drone brood in the colonies managed using the natural honeycomb did not negatively affect the colony development nor the mite V. destructor population compared to control colonies. The molecular analysis showed that the DWV was the most common virus found in bee samples, and its viral load was more influenced from the mite infestation rate than from the treatment. The analysis carried out in this study showed that the natural honeycomb management can represent a valid alternative to the wax foundation. This kind of colony management thus appears to contradict our primary hypothesis which was that letting the bees build their own honeycomb would have led to a significant increase in the V. destructor infestation. Productivity data did not provide reliable results about the difference between the natural honeycomb and the conventional colony management due to climatic adversities. Further studies will be performed to better investigate this aspect. Data about the natural mite fall and the estimation of the mite population in the phoretic/reproductive phases provided a useful starting point for further studies on the correct timing to carry out acaricide treatments both in conventional and natural honeycomb managed colonies.

Bathymetric mapping is an important tool for reservoir management, typically completed before reservoir construction. Historically, bathymetric maps were produced by interpolating between points measured at a relatively large spacing throughout a reservoir, typically on the order of a few, up to 10, meters or more depending on the size of the reservoir. These measurements were made using traditional survey methods before the reservoir was filled, or using sonar surveys after filling. Post-construction issues such as sedimentation and erosion can change a reservoir, but generating updated bathymetric maps is difficult as the areas of interest are typically in the sediment deltas and other difficult-to-access areas that are often above water or exposed for part of the year. We present a method to create complete reservoir bathymetric maps, including areas above the water line, using small unmanned aerial vehicle (sUAV) photogrammetry combined with multi-beam sonar data--both established methods for producing topographic models. This thesis presents methods to create accurate above-water shoreline models using images from sUAVs, processed using a commercial software package and a method to accurately knit sonar and Structure from Motion (SfM) data sets by matching slopes. The models generated by both approaches are point clouds, which consist of points representing the ground surface in three-dimensional space. Generating models from sUAV-captured images requires ground control points (GCPs), i.e., points with a known location, to anchor model creation. We explored issues with ground control spacing, masking water regions (or omitting water regions) in the images, using no GCPs, and incorrectly tagging a GCP. To quantify the effect these issues had on model accuracy, we computed the difference between generated clouds and a reference point cloud to determine the point cloud error. We found that the time required to place GCPs was significantly more than the time required to capture images, so optimizing GCP density is important. We found that we needed to mask water and areas related to distant regions and sky in images used for model creation. This is because water, objects in the far oblique distance, and sky confuse the algorithms that match points among images. Our sonar point clouds, while self-consistent, were not accurately georeferenced. We demonstrate a method using cross-sections of the transition between the above-water clouds and sonar clouds to geo-locate the sonar data and accurately knit the two data sets. Shore line topography models and integration of sonar and drone data is a niche area that leverages current advances in data collection and processing. Our work was applied at three different reservoirs to show that accurate post-construction reservoir bathometry maps can assist with reservoir management. A report is included that compares historical bathymetric maps with the current bathymetric maps at each of the three different reservoirs. A guide to perform the drone surveys is included in the report's appendix.

With the expansion of unmanned aircraft system (UAS) technologies, there is a growing need for UAS Traffic Management (UTM) systems to promote safe operation and development. To be successful, these UTM systems must be able to detect and track multiple drones in the presence of clutter. This paper examines the implementation of different algorithms on a compact, X-band, frequency modulated continuous wave (FMCW) radar in an effort to enable more accurate detection and estimation of drones. Several algorithms were tested through post processing on actual radar data to determine their accuracy and usefulness for this system. A promising result was achieved through the application of pulse-Doppler processing. Post processing on recorded radar data showed that a moving target indicator successfully separated a target from clutter. An improvement was also noted for the implementation of phase comparison monopulse which accurately estimated angle of arrival (AOA) and required fewer computations than digital beamforming.The second part of this thesis explains the work done on an adaptive broadband, real time beamformer for RF interference (RFI) mitigation. An effective communication system is reliable and can counteract the effects of jamming. Beamforming is an appropriate solution to RFI. To assist in this process FPGA firmware was developed to prepare signals for frequency domain beamforming. This system allows beamforming to be applied to 150 MHz of bandwidth. Future implementation will allow for signal reconstruction after beamforming and demodulation of a communication signal.

Raptor nests on human-built structures represent a significant source of conflict as they can result in bird mortality, fires, structure damage, service distribution, or power outages when falling nest materials or animals connect with energized conductors. Power companies, such as the Tennessee Valley Authority (TVA), wish to mitigate these conflicts to avoid service disruptions. In this dissertation, I present my work towards understanding and mitigating the interactions between Ospreys (Pandion haliaetus) and human-made structures. To achieve this, I explored multiple elements of conflict identification, monitoring, and basic ecology of the target species to better inform conflict mitigation. In Chapter I, I modelled the influence of suitable habitat and transmission infrastructure distribution on the potential risk of nest-infrastructure conflict within the TVA power service area. My integrative model would be most useful to utilities when adjacent (i.e., within 10 km) areas to ‘risky’ zones are also considered when looking at mitigation efforts and pre-development planning. Going forward, similar models for other species and for distribution structures may benefit utilities such as TVA. In Chapter II, I aimed to identify the most suitable nest monitoring technique for Ospreys, as nest information is required to make informed decisions for conflict mitigation (e.g., nest removal). I found that unoccupied aircraft systems, or drones, are less disturbing and more time-efficient than other methods tested. In the last two chapters, I focused on obtaining detailed information on the basic ecology of Ospreys in the southeastern United States, which represent an understudied population. My findings in Chapter III contribute to general migration ecology theory, identify key stopover areas for Ospreys in Florida, provide valuable comparisons for further investigations, highlight areas for future research, and identify possible metrics relevant to conservation and management action. Lastly, I quantified the genetic diversity and structure of southeastern Ospreys to generate hypotheses for future testing and provide valuable comparisons for further investigations. While gene flow appears to be high and sampled regions show little genetic differentiation, more research is required to elucidate patterns of cryptic population structure and provide concrete implications for management decisions (e.g., source population for translocation programs).

En esta investigación, se estableció como objetivo general justificar la protección del derecho fundamental a la intimidad frente al uso civil de drones, para este fin, se tomó en cuenta la Ley Nº 30740, Ley que regula el uso y las operaciones de los sistemas de aeronaves pilotadas a distancia (RPAS) y se detectó que no tienen una utilidad real y concreta para proteger el derecho a la intimidad de las personas, toda vez que, su objeto es proteger la seguridad aérea. Es por ello, que, de acuerdo con los objetivos específicos, se tomó en cuenta el modelo europeo y norteamericano, que regula el uso civil de drones y también su protección de derecho a la intimidad y privacidad. El método que se realizó fue analítico descriptivo de tipo documental, que examina la doctrina y normativa vigente y estándares de diversos autores. Los resultados permiten advertir que la vía correcta desde un ámbito Constitucional es regular una ley que limite el uso civil de los drones en garantía del derecho a la intimidad y que haga más efectivo su protección, frente a los riesgos que presenta su uso y que la jurisprudencia no resulta eficiente para protegerlo en un Estado garantista como el nuestro. / In this investigation, it was established as a general objective to justify the protection of the fundamental right to privacy against the civil use of drones, for this purpose, Law N°. 30740, Law that regulates the use and operations of information systems, was taken into account. Remotely Piloted Aircraft (RPAS), and it was detected that they do not have a real and concrete use to protect people's right to privacy since their purpose is to protect aviation security. That is why, according to the specific objectives, keep in mind the European and North American models, which regulate the civil use of drones and the protection of the right to intimacy and privacy. The method used was a descriptive analytical method of documentary type, which examines the doctrine and regulations in force and the standards of various authors. The results allow us, to warn that the correct path from a Constitutional level is to regulate a law that limits the civil use of drones, guarantees the right to privacy, and in this way, its protection against the risks that it presents becomes more effective. Its use and the jurisprudence are not effective for its protections in a guarantor State like ours.

Scientists can better understand wetlands environments by collecting data they are interested in via sensor networks. However the deployment of these sensor nodes manually can be disruptive to these sensitive environments. We develop a set of algorithms for autonomously differentiating land from water via aerial imagery using an unmanned aerial vehicle (UAV). The UAV takes a picture of the area, clusters, classifies, defines regions, and then communicates the regions to other UAVs responsible for deploying the sensor nodes. These UAVs run an algorithm to determine the optimal locations for sensor nodes such that they completely cover the regions and allow for communication between the nodes in the sensor network. Our classifier training algorithm identifies the best classifier using clusters and we compare its successful classification rate to a pixel-based approach and we see classification rates of 89.6%. This classifier feeds into our online algoorithm that the UAV successfully uses to classify the Calaveras River in California. In our simulations to determine the most effective algorithm for determining where the place the sensor nodes in a sensor network, we found Triangular Geometric Tessellation was the optimal algorithm, able to achieve 91.5% coverage in concave areas and 88.2% coverage in convex areas with relatively low computational complexity.

Unmanned Aircraft Systems (UAS) face one common challenge when integrating with the existing manned aircraft population in the National Airspace System (NAS). To unlock the full efficiency of UAS, the UAS integrator must comply with an onboard pilot’s requirement to see-and-avoid other aircraft while operating. Commercially available Detect-and-Avoid (DAA) sensor technologies have been developed to attempt to comply with this requirement. UAS integrators must use these sensors to meet or exceed the performance of a human pilot. This thesis covers research done to integrate an array of commercially made DAA sensors with a large Group 3 UAS both in hardware and software that was later flight tested and evaluated for usability. A fast-time simulation is presented using the principles of the National Aeronautics and Space Administration's (NASA) Detect-and-AvoID Alerting Logic for Unmanned Systems (DAIDALUS). Last, open-source tools are presented to assist future integrators in validating their DAA solutions.

No description available.

Mänsklig aktivitet har ökat utsläppen av växthusgaser i atmosfären så mycket att det påverkat klimatet och spås förändra det mer om inte åtgärder vidtas för att utsläppen ska minksa och helst upphöra helt. För att lindra effekterna av koldioxid, som är den växthusgas med störst påverkan, kan skogen spela en stor roll. För att veta vilka åtgärder som är lämpliga krävs förståelse för hur olika ingrepp i skogen påverkar dess upptag och utsläpp. Under några decennier har koncentrationer och flöden av växthusgaser mätts med hjälp av fasta master. De är dock för få för att kunna generalisera resultaten över hela landskap. Här undersöks hur teknikläget för mobila mätmetoder ser ut idag via en litteratur- och surveyundersökning. Samtliga respondenter är hoppfulla och tror att det bara är en tidsfråga innan tekniken finns för att kunna använda sig av små drönare för att kunna genomföra mätningar av gaser över skogsmark. Ett koncept för en pilotstudie har tagits fram där koldioxidkoncentrationer ska mätas.

L'objectif principal de ce projet de maîtrise est de développer un algorithme de commande prédictive permettant aux aéronefs sans pilote (UAVs) de se rendre à des cibles immobiles dont les positions sont connues. Il faut toutefois que les aéronefs évitent, en cours de route, des obstacles ellipsoïdaux statiques qui sont détectés par les aéronefs lorsqu'ils en sont assez près. De plus, l'information sur les obstacles détectés doit ^etre transmisse aux autres aéronefs. Pour chacun de ces aéronefs, l'information est reçue seulement s'il est à portée de communication. Il est présumé que chaque aéronef possède un pilote automatique, système de commande à bord, qui le stabilise. Ainsi, l'algorithme doit déterminer les commandes à transmettre au pilote automatique. L'algorithme développé a été testé avec succès en simulation et l'aide d'un système "Hardware-In-the-Loop" (HIL). / The main objective of this master's project is to develop a predictive control algorithm that will allow unmanned aerial vehicles (UAVs) to intercept static targets of known position. UAVs must however avoid static ellipsoidal obstacles detected on-route, when they are in close proximity to the aircrafts. Information on the detected obstacles must also be transmitted to fellow UAVs. Each aircraft can receive information from another aircraft, only if they are in communication range. Moreover, it is assumed that each aircraft is equipped with an autopilot (on-board control device) to stabilize the UAV in-flight. The predictive control algorithm must thus determine the commands to transmit to the autopilot. The developed algorithm was tested in simulation and with a Hardware-In-the-Loop (HIL) system, both of which yielded successful results.