204 research outputs found

    Developing a Constitutionally Appropriate Method of Circumventing Statutory Ouster Clauses

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    The Court's approach towards circumventing ouster clauses has varied dramatically over time. The original focus of the Court was on whether the body in question had 'jurisdiction' to make a decision. If they were found to be acting outside of their jurisdiction, this would justify circumventing the statutory ouster clause on the grounds that the body was acting ‘ultra vires’, and as such against the will of Parliament. This thesis has found ‘ultra vires’ to be an inappropriate theoretical foundation for judicial review, in its inability to properly delineate the boundaries of administrative power. Furthermore, the focus on ‘jurisdiction’ as central to the standard of judicial review has been criticised for its narrow and inflexible nature, and its failure to respect the unique contexts of each individual case. In the later cases of Cart and Privacy International, the courts rejected the narrow focus on ‘jurisdiction’ and ‘ultra vires’, favouring a more holistic approach to delineating the boundaries of judicial review. This approach embodies the modified ultra vires theory, which will be shown to provide the most appropriate basis for judicial review. It works to balance the intention of Parliament as evident in statute with the implied intention of Parliament to confer power within the boundaries of the Rule of Law, justifying the recent controversial decision in Privacy International

    Automated Avocado Yield Forecasting Using Multi-Modal Imaging

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    Yield forecasting is a common technique utilized to predict the amount of fruit expected at harvest. Orchard managers forecast yield to predict future packaging requirements, labor requirements, and to make agricultural decisions to help improve future yields. In order to forecast yield, one must first count the number of fruit on a representative sample of trees. Next, one must use a model to predict the total yield expected given the number of fruit counted. However, as population and labor costs continue to increase, a need for automation grows. While research has explored automated yield forecasting for various fruits, there currently isn\u27t any research on automated avocado detection/forecasting. This project explored various methods to automate avocado detection in an orchard setting using computer vision. Additionally, this project constructed a model to predict the yield of avocados at harvest when after counting the current number of avocados earlier in the year. The computer vision pipeline plans to utilizes both thermal images and visible RGB images to make an avocado classifier. However, this system has currently shows the potential of thermal-based avocado detection at various times of the day, segmenting all avocados from the background. Next, this project will continue to utilize visible RGB images to further eliminate the background

    Development of an Automatous Ground Robot for Strawberry Yield Monitoring

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    The objective of this project was to design and build an autonomous agricultural robot platform that is ready to be adapted for strawberry yield predication. The robot was required to have an all-electric drivetrain as a requirement for the project. A key requirement for this robot is to have the flexibility to be used with different crops and with different applications. It is also designed to be able to change width for use in fields with varying row spacing. The end product of these design requirements is a robot platform that has the capability of supporting a payload in excess of 200 pounds, allowing for installation of equipment for many different applications. The robot has four-wheel drive and four wheel steering capability, all with electric motors and actuators

    Feasibility of UAV Technology to Promote Crop Yield and Health through Normalized Difference Vegetation Index Imaging

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    Drone technology has skyrocketed over the past decade driving costs down and the number of potential applications up, one being agricultural crop monitoring. Normalized Difference Vegetation Index (NDVI) is an imaging technique used to visualize near infrared light, which happens to be a very good indicator of plant health and productivity. This project aims to explore the potential of Unmanned Aerial Vehicles (UAV’s) using NDVI imaging for crop monitoring and assess the feasibility of the process by developing a UAV with a NDVI camera to create NDVI maps from the aerial crop images. These maps will be cross referenced with soil samples to check for proof of concept and accuracy. The project will be presented at the 2015 American Society of Agricultural and Biological Engineering conference in New Orleans, Louisiana in the student poster and paper competition and at the Cal Poly BRAE senior project presentation banquet. The final product will illustrate the feasibility, efficiency, and economic benefits of UAV NDVI crop imaging and offer a solution to the dated and tedious process of crop monitoring that is currently physically walking the field

    Ge-on-Si Single Photon Avalanche Diode Performance Enhancement with Photonic Crystal Nano-hole Arrays

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    Germanium-on-silicon (Ge-on-Si) single photon avalanche diodes (SPADs) operating in the short-wave infrared (SWIR) have various applications such as long-range eye-safe LIDAR, quantum imaging, and quantum key distribution. These SPADs offer compatibility with Si foundries and potential cost advantages over existing InGaAs/InP devices. However, cooling is necessary to reduce dark-count rates (DCR), which limits photon absorption at 1550 nm wavelength. To address this, we propose integrating a photonic crystal (PC) nano-hole array structure on the Ge absorber layer. While this technique has shown enhanced responsivity in linear Ge detectors, its potential in Ge-on-Si SPADs remains unexplored. Our simulations consider temperature dependence and the impact of electric-field hot-spots on dark count rates. Through these simulations, we have identified means of enhancing single-photon detection efficiency (SPDE) without adversely affecting DCR. We predict significant improvements in performance, including at least a 2.5x enhancement in absorption efficiency

    Knowledge, perceptions and willingness to control designated invasive tree species in urban household gardens in South Africa

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    Many biological invasions result in negative impacts on the environment and human livelihoods, but simultaneously some also provide benefits that are valued differently by various stakeholders. To inform policy and management of invasive species it is important to assess landowners’ and broader society’s knowledge and perceptions of invasive species, something which is lacking in many contexts, especially in urban settings. In this study we interviewed 153 householders living in a medium-sized South African town who had declared invasive alien trees in their gardens. Less than half of the respondents could identify the invasive tree on their property and only one-third knew that it was an invasive alien species. There was a positive association between income and education levels with exposure to media about invasive alien species and respondents’ ability to identify the species and name any other invasive alien tree species. Knowledge levels were unequal across species. Amongst those who knew the tree was an invasive alien species, reasons why they retained it in their gardens included that it would be costly or too much effort to remove, they liked the tree, that it was not causing any harm and that the property was rented and so its removal was not their responsibility. However, the majority of people (83 %) were willing to have it removed from their garden if done for free by appropriate agencies, which is promising for compliance with new regulations on invasive species implemented at the end of 2014 in South Africa. The results also highlight the need for targeted and appropriate education and awareness programs amongst urban householders on invasive alien species, relevant legislation and their obligations

    Cal Poly agBOT 2017 Challenge Autonomous Corn Seeding Tractor

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    The Cal Poly agBOT team researched, designed, and built a Remote Controlled tractor to compete in Gerrish Farms’ agBOT Seeding Challenge 2017. The tractor was procured from the BioResource and Agricultural Engineering department. The tractor served as the base unit, with supporting components mounted onto it. Steering the tractor was accomplished with a auxiliary hydraulic motor mounted to the steering wheel. Throttle and choke were controlled by servo and linear actuator respectively. Both the three point hitch and PowerTakeoff was controlled by linear actuators. All controls were executed by an arduino microcontroller, which was equipped with a remote control. The steering was equipped with a potentiometer for steering feedback and travel direction of the tractor. The corn seeder attached to the three point was equipped with two hoppers, seed sensors, a seed rate motor, and two vacuums to switch between different seed varieties. The tractor effectively plants corn via remote control and competed on June 24th, 2017 at Gerrish Farms, Rockville, Indiana. The days leading up to the event, the tractor was loaded onto a trailer. Three students rented a truck, loaded it up with camping equipment, and hauled the Cal Poly agBOT to Indiana in ~47hrs, with a single 5hr stop to rest. The students and tractor arrived safely, unpacked, and tested the tractor at Gerrish Farms. The day before the competition, Gerrish Farms held an expo for the surrounding community and guests. Many people from all ages and expertise walked around and were thoroughly interested in the Cal Poly teams efforts. The students competed and turned back to California. We placed 2nd in our competition, bringing home $15,000 to support next years agBOT team

    The value of triage during periods of intense COVID-19 demand: simulation modelling study

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    Background: During the COVID-19 pandemic many intensive care units have been overwhelmed by unprecedented levels of demand. Notwithstanding ethical considerations, the prioritisation of patients with better prognoses may support a more effective use of available capacity in maximising aggregate outcomes. This has prompted various proposed triage criteria, although in none of these has an objective assessment been made in terms of impact on number of lives and life-years saved. Design: An open source computer simulation model was constructed for approximating the intensive care admission and discharge dynamics under triage. The model was calibrated from observational data for 9505 patient admissions to UK intensive care units. In order to explore triage efficacy under various conditions, scenario analysis was performed using a range of demand trajectories corresponding to differing non-pharmaceutical interventions.Results: Triaging patients at the point of expressed demand had negligible effect on deaths but reduces life-years lost by up to 8.4% (95% CI: 2.6% to 18.7%). Greater value may be possible through ‘reverse triage’, i.e. promptly discharging any patient not meeting the criteria if admission cannot otherwise be guaranteed for one that does. Under such policy, life-years lost can be reduced by 11.7% (2.8% to 25.8%), which represents 23.0% (5.4% to 50.1%) of what is operationally feasible with no limit on capacity and in absence of improved clinical treatments.Conclusions: The effect of simple triage is limited by a trade-off between reduced deaths within intensive care (due to improved outcomes) and increased deaths resulting from declined admission (due to lower throughput given the longer lengths of stay of survivors). Improvements can be found through reverse triage, at the expense of potentially complex ethical considerations.<br/
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