This research investigates the impact a Remotely Operated Vehicle (ROV) program has on student interest in, and perception of, technology and engineering (sTEm). ROV programs embed areas of science, technology, engineering and math (STEM) into their curriculum; however, emphasis for this study is placed on interest and perception of the "T" and "E" of STEM. Although there are many articles detailing the benefits of ROV programs, there is little empirical data documenting the impact on student interest and perception of sTEm. This study outlines the background of a few major ROV programs in the U.S.; specifically Utah Underwater Robotics (UUR), an ROV statewide program within a landlocked state, the methods for gathering data and findings from a sTEm survey instrument administered to over 300 students ranging from 6th to 12th grade who participated in a five-month ROV program and near 50 students who did not. Key findings include: 1. Males were more interested in technology and engineering than females, regardless of whether they participated in the UUR ROV program. 2. Male and female students in the UUR program were more interested and had a more positive perception of engineering than those who did not participate in the UUR ROV program. 3. Females in the UUR program reported more interest in engineering careers and activities than females not in the program. 4. Females in the program reported more interest and self-efficacy in science than females not in the program. 5. Males in the UUR program reported more awareness of the positive and negative consequences of technology and engineering than those who did not participate.

Human intervention and natural phenomenon cause change in land use day by day. Availability of accurate land use information is essential for many applications like natural resource management, planning and monitoring programs. Landuse Change has become a central component in current strategies for managing natural resources and monitoring environmental change. Because of the rapid development in the field of land use mapping, there is an increase in studies of land use change worldwide. Providing an accurate assessment of the extent and health of the world’s forest, grassland and agricultural resources has become an important priority. By printed maps without any statistics or only statistics without any map can not solve this visualization problem. Because printed maps have not attracted as much attention as statistics among the people because of it is limited applications (Himiyama, 2002). Remotely sensed data like aerial photographs and satellite imageries are undoubtedly the most ideal data for extracting land use change information. Satellite images are the most economical way of getting data for different times. The multitude of existing software helps getting information from satellite image also in manipulating the information. The approach used in this study to classify satellite images and change detection based on Satellite images Landsat MSS (1972), Landsat TM (1989) and Landsat ETM (1999) for using supervised classification methods like maximum likelihood (MAXLIKE), MAHALCLASS and time series analysis of CROSSTAB. After performed these hard and soft classifiers the research showed the significant Landuse change in the study area of Chakoria Sundarban mangrove forest. Remote sensing is the modern tools for detecting change pattern and behaviours of coastal environment (Saifuzzaman, 2000). So, those tools are used in the research work for better change analysis of the study area. For analyzing, evaluation and mapping environmental change detection of different years remotely sensed data have been undertaken. The present research provides some suggestions and recommendations as per research findings in order to optimize the utility of coastal resources and to maintain the sustainability of the resources, coastal land use control and there by stabilizing the coastal vulnerable area of chakoria Sundarban.

<p>Human intervention and natural phenomenon cause change in land use day by day. Availability of accurate land use information is essential for many applications like natural resource management, planning and monitoring programs. Landuse Change has become a central component in current strategies for managing natural resources and monitoring environmental change. Because of the rapid development in the field of land use mapping, there is an increase in studies of land use change worldwide. Providing an accurate assessment of the extent and health of the world’s forest, grassland and agricultural resources has become an important priority. By printed maps without any statistics or only statistics without any map can not solve this visualization problem. Because printed maps have not attracted as much attention as statistics among the people because of it is limited applications (Himiyama, 2002). Remotely sensed data like aerial photographs and satellite imageries are undoubtedly the most ideal data for extracting land use change information. Satellite images are the most economical way of getting data for different times. The multitude of existing software helps getting information from satellite image also in manipulating the information. The approach used in this study to classify satellite images and change detection based on Satellite images Landsat MSS (1972), Landsat TM (1989) and Landsat ETM (1999) for using supervised classification methods like maximum likelihood (MAXLIKE), MAHALCLASS and time series analysis of CROSSTAB. After performed these hard and soft classifiers the research showed the significant Landuse change in the study area of Chakoria Sundarban mangrove forest. Remote sensing is the modern tools for detecting change pattern and behaviours of coastal environment (Saifuzzaman, 2000). So, those tools are used in the research work for better change analysis of the study area. For analyzing, evaluation and mapping environmental change detection of different years remotely sensed data have been undertaken. The present research provides some suggestions and recommendations as per research findings in order to optimize the utility of coastal resources and to maintain the sustainability of the resources, coastal land use control and there by stabilizing the coastal vulnerable area of chakoria Sundarban.</p><p> </p>

The objective of this thesis is to develop a general obstacle segmentation algorithm for use on board a ground based unmanned vehicle (GUV). The algorithm processes video data captured by a single monocular camera mounted on the GUV. We make the assumption that the GUV moves on a locally planar surface, representing the ground plane. We start by deriving the equations of the expected motion field (observed by the camera) induced by the motion of the robot on the ground plane. Given an initial view of a presumably static scene, this motion field is used to generate a predicted view of the same scene after a known camera displacement. This predicted image is compared to the actual image taken at the new camera location by means of an optical flow calculation. Because the planar assumption is used to generate the predicted image, portions of the image which mismatch the prediction correspond to salient feature points on objects which lie above or below the ground plane, we consider these objects obstacles for the GUV. We assume that these salient feature points (called seed pixels ) capture the color statistics of the obstacle and use them to initialize a Bayesian region growing routine to generate a full obstacle segmentation. Alignment of the seed pixels with the obstacle is not guaranteed due to the aperture problem, however successful segmentations were obtained for natural scenes. The algorithm was tested off line using video captured by a camera mounted on a GUV.

This thesis considers various aspects of the use of ground-based methods and remote sensing of Biological Soil Crusts (BSC). They are mostly distributed in winter rainfall dominated areas such as those at Middleback Field Centre (MFC) in South Australia. They can be used potentially as an indicator of rangeland condition by estimating grazing pressure (trampling). Two BSC based indicators for rangeland condition assessment are species composition and cover. While there is strong agreement that BSC composition is a good indicator, there is less agreement that BSC cover alone is a good indicator. Although BSC have been included in previous remotely-sensed studies, their spectral characteristics, and hence their contributions to remotely-sensed spectral signatures, are not well known. Data collection methods were refined for suitable method selection, stratification and site characterization, and morphological/ functional group classification. Cover data of BSC were collected using a 100 m line-intercept method on the stratified land units and statistical analyses were based on the cover variance analyses. Spectra of BSC groups were collected and characterized for different remote sensing indices. Five grazing gradient models based on collected spectra were developed for the evaluation of BSC effect on remotely-sensed data. Both existing and newly developed remote sensing indices were examined for BSC detection. Sampling for cover of BSC in the field showed that there is indeed a detectable change with distance from water, suggesting that BSC cover can be used as an indicator of rangeland condition, provided that appropriate stratification of the study sites is carried out prior to sampling, and spectral differences in morphological and functional groups are taken into account. Spectral analysis of BSC components showed that different classes of organisms in the crusts have different spectral characteristics, and in particular, that the (commonly-used) perpendicular vegetation index (PD54) is not suitable for detecting BSC. On the other hand, ground-level spectral modelling showed that the Normalized Difference Vegetation Index (NDVI) and Soil Stability Index (SSI) did show a distinguishable contribution from BSC. A procedure for detecting cover of BSC was developed for image taken during the period after an effective rain, in contrast to the normal practice of selecting images of dry surfaces for interpretation. The most suitable intervals appears to be 2-4 days after rain in late autumn, winter and early spring. Of the existing indices, the SSI is the best for estimating cover of BSC from Landsat images. However, eight new indices, specifically designed for detection of BSC were developed during the cource of this work. The best results were obtained for indices using using the middle-infrared bands. These results are promising for application to rangeland monitoring and suggest that BSC cover is an important indicator of rangeland condition if appropriate stratification, classification and data-collection methods are used. The effects of BSC cover on a remotely-sensed method are considerable, and thus they can not be neglected during image interpretation. There are different phenological patterns for BSC, annual and perennial elements, thus there is the possibility for the selection of imagery based on each phenological stage to detect these elements. Application of certain indices such as the PD54 may create mis-estimation of land covers. Although some of the existing and newly developed indices had significant results for BSC cover estimation, there is a requirement for a standalone remotely-sensed method to conclude the best index.

In the past decade, the design and manufacturing of intelligent multipurpose underwater vehicles has increased significantly. In the wide range of studies conducted in this field, the flexibility and autonomy of these devices with respect to their intended performance had been widely investigated. This work is related to the design and manufacturing of a small and lightweight autonomous underwater vehicle (AUV) with vision capabilities allowing detecting and contouring obstacles. It is indeed an exciting challenge to build a small and light submarine AUV, while making tradeoffs between performance and minimum available space as well as energy consumption. In fact, due to the ever-increasing in equipment complexity and performance, designers of AUVs are facing the issues of limited size and energy consumption. By using a pair of thrusters capable to rotate 360o on their axis and implementing a mass shifter with a control loop inside the vehicle, this later can efficiently adapt its depth and direction with minimal energy consumption. A prototype was fabricated and successfully tested in real operating conditions (in both pool and ocean). It includes the design and embedding of accurate custom multi-purpose sensors for multi-task operation as well as an enhanced coordinated system between a high-speed processor and accustomed electrical/mechanical parts of the vehicle, to allow automatic controlling its movements. Furthermore, an efficient tracking system was implemented to automatically detect and bypass obstacles. Then, fuzzy-based controllers were coupled to the main AUV processor system to provide the best commands to safely get around obstacles with minimum energy consumption. The fabricated prototype was able to work for a period of three hours with object tracking options and five hours in a safe environment, at a speed of 0.6 m/s at a depth of 8 m.

The work presented in the thesis concerns the design and development of a novel thruster fault diagnosis and accommodation system (PDAS) for overactuated, open-frame underwater vehicles. The remotely operated vehicles (ROVs) considered in this thesis have four thrusters for motion in the horizontal plane with three controllable degrees of freedom (DoF). Due to the redundancy resulting from this configuration, for the case of a partial fault or a total fault in a single thruster it is possible to reallocate control among operable thrusters in order that the ROV pilot is able to maintain control of the faulty ROV and to continue with missions. The proposed PDAS consists of two subsystems: a fault diagnosis subsystem (FDS) and a fault accommodation subsystem (FAS). The FDS uses fault detector units to monitor thruster states. Robust and reliable interrogation of thruster states, and subsequent identification of faults, is accomplished using methods based on the integration of selforganising maps and fuzzy logic clustering. The FAS uses information provided by the FDS to perform an appropriate redistribution of thruster demands in order to accommodate faults. The FAS uses a hybrid approach for control allocation, which integrates the pseudoinverse method and the fixed-point iterations method. A control energy cost function is used as the optimisation criteria. In fault-free and faulty cases the FAS finds the optimal solution, which minimises this criteria. The concept of feasible region is developed in order to visualise thruster velocity saturation bounds. The PDAS provides a dynamic update of saturation bounds using a complex three-dimensional visualisation of the feasible region (attainable command set), such that the ROV pilot is informed with the effects of thruster fault accommodation, incorporated in the new shape of the attainable command set. In this way the ROV pilot can easy adapt to newly created changes and continue the mission in the presence of a fault. The prototype of the PDAS was developed in the MATLAB environment as a Simulink model, which includes a nonlinear model of an ROV with 6 DOF, propulsion system and a hand control unit. The hand control unit was simulated in hardware using a joystick as input device to generate command signals. Different fault conditions are simulated in order to investigate the performance of the PDAS. A virtual underwater world was developed, which enabled tuning, testing and evaluation of the PDAS using simulations of two underwater vehicles (FALCON, Seaeye Marine Ltd. and URIS, University of Girona) in a 'realistic' underwater environment. The performance of the PDAS was demonstrated and evaluated via tank trials of the FALCON ROV in QinetiQ Ocean Basin Tank at Haslar, where the existing control software was enhanced with the PDAS algorithm. The results of real-world experiments confirmed the effectiveness of the PDAS in maintaining vehicle manoeuvrability and in preserving the vehicle mission in the presence of thruster faults.

Orientador: Prof. Dr. Magno Enrique Mendoza Meza / Coorientadora: Profª. Drª. Silvia Lenyra Meirelles Campos Titotto / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Mecânica, Santo André, 2018.

In power utilities the subject reliability is a permanent worry. In this new context, some solutions have been developed and researched to an alternative to improve the performance on service restoration when there are consumers without power supply. Among possible solutions the installation of remotely-controlled switches represents a solution that has been adopted by many companies due its cost benefit. The allocation of these devices is essential to assess the different criterions and characteristics, so the use of multi-criteria decision making to evaluate these characteristics and especially to allow the measurement of expert s opinion in power distribution systems is essential. Therefore, the objective of this work is to propose a new methodology for the allocation of these devices in electric distribution systems based on AHP - Analytic Hierarchy Process decision making for validation of the best locations to install theses device. The contribution and innovation of this work consist in adding to the allocation methodology a validation of expert opinion, discarding those that present a very low consistency and thus making the final answer more exact and in accordance with the proposal, through a variation of the AHP methodology. / Em empresas de sistemas de potência a confiabilidade é uma preocupação constante. Nesse novo contexto, algumas soluções têm sido desenvolvidas e pesquisadas como alternativa para melhorar sua performance em propiciar um retorno do fornecimento de energia elétrica aos seus consumidores quando estes estão desenergizados. Dentre as soluções possíveis, a instalação de chaves telecomandadas tem representado uma solução cada vez mais adotada por várias empresas de energia devido ao seu custo benefício. Na alocação desses equipamentos é essencial considerar diferentes critérios e características, desta maneira o uso de uma metodologia de decisão multicriterial é necessário e especialmente para permitir a mensuração da opinião de especialistas do setor de sistemas de distribuição. Então, o objetivo desse trabalho é propor uma nova metodologia de alocação desses dispositivos em sistemas de distribuição de energia baseado na metodologia de tomada de decisão AHP - Analytic Hierarchy Process para validação das melhores localizações para instalar esses equipamentos. A grande contribuição e inovação desse trabalho consiste apresentar uma metodologia de alocação desses equipamentos, uma validação da opinião dos especialistas, descartando aquelas que apresentam uma baixa consistência e desta forma tornando a resposta final mais exata e de acordo com o proposto, através de uma variação da metodologia AHP.

Biological diversity is a key component in assessing ecosystem health. Alteration, degradation and loss of habitat due to human influence is currently the primary stressor resulting in decreases in diversity. Reliable assessment of large areas in terms of biological integrity are needed for conservation and preservation efforts. Remotely sensed data provide an integrated view of reflected electromagnetic energy over large areas of the earth. These energy patterns provide unique spectral signatures which can be correlated to land cover and habitat. This research sought relationships between traditional ecological measures and information gathered from satellite digital imagery. Reliable interpretation of earth surface characteristics relies largely on accurate rectification to a map projection and subsequent thematic classification. Use of the Global Positioning System (GPS) for rectification was superior than digitizing topographical maps. Differentially corrected GPS locations provided optimum rectification with SPOT satellite imagery while marginally better rectifications were obtained for Landsat MSS imagery using uncorrected GPS positions. SPOT imagery provided more accurate land cover classifications than did MSS. Detection of temporal land cover change using MSS imagery was hampered by confusion among intermediate successional classes. Confusion between upland and bottomland forest classes occurred with both SPOT and MSS. Landscape analyses using thematic maps produced from the previously discussed endeavors suggested that terrestrial habitat in the Ray Roberts Lake area became more fragmented and complex in shape. Habitat patches became smaller but more numerous. Forested areas were most effected and conservation efforts should focus on management strategies that promote vegetation succession and forest maturation. Remotely sensed SPOT data were successfully used to predict tree basal area. There were no significant relationships found with other in situ measures or between MSS data and any vegetation measures. Remote sensing provided information suitable for large scale projects concerning landscape-level ecological issues. Rectification and classification accuracies were the primary factors influencing meaningful interpretation. Project goals should determine the scale of remotely sensed data and acceptable level of accuracy.