998 resultados para Transit Planning


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Introduction: This study aimed to determine the potential role and guidelines for implementation of skill-based peer mentoring for radiotherapy planning education. Methods: After four weekly mentoring sessions, both Year 3 mentors (n=9) and Year 2 mentees (n=9) were invited to complete a short online questionnaire relating to the impact of the initiative. The tool contained a mixture of Likert-style questions concerning student enjoyment and perceived usefulness of the initiative as well as more qualitative open questions that gathered perceptions of the peer mentoring process, implementation methods and potential future scope. Results: Several key discussion themes related to benefits to each stakeholder group, challenges arising, improvements and potential future directions. There were high levels of enjoyment and perceived value of the mentoring from both sides with 100% of the 18 respondents enjoying the experience. The informal format encouraged further learning, while mentors reported acquisition of valuable skills and gains in knowledge. Conclusions: Peer mentoring has a valuable and enjoyable role to play in radiotherapy planning training and helps consolidate theoretical understanding for experienced students. An informal approach allows for students to adopt the most appropriate mentoring model for their needs while providing them with a free space to engender additional discussion.

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It is now 10 years since the disease we now know as SARS-severe acute respiratory syndrome-caused more than 700 deaths around the world and made more than 8,000 people ill. More recently, in 2009 the global community experienced the first influenza pandemic of the 21st century-the 2009 H1N1 influenza pandemic. This paper analyses the major developments in international public health law relating to infectious diseases in the period since SARS and considers their implications for pandemic planning.

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This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.

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This paper presents stylized models for conducting performance analysis of the manufacturing supply chain network (SCN) in a stochastic setting for batch ordering. We use queueing models to capture the behavior of SCN. The analysis is clubbed with an inventory optimization model, which can be used for designing inventory policies . In the first case, we model one manufacturer with one warehouse, which supplies to various retailers. We determine the optimal inventory level at the warehouse that minimizes total expected cost of carrying inventory, back order cost associated with serving orders in the backlog queue, and ordering cost. In the second model we impose service level constraint in terms of fill rate (probability an order is filled from stock at warehouse), assuming that customers do not balk from the system. We present several numerical examples to illustrate the model and to illustrate its various features. In the third case, we extend the model to a three-echelon inventory model which explicitly considers the logistics process.

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This paper addresses the problem of singularity-free path planning for the six-degree-of-freedom parallel manipulator known as the Stewart platform manipulator. Unlike serial manipulators, the Stewart platform possesses singular configurations within the workspace where the manipulator is uncontrollable. An algorithm has been developed to construct continuous paths within the workspace of the manipulator by avoiding singularities and ill-conditioning. Given two end-poses of the manipulator, the algorithm finds out safe (well-conditioned) via points and plans a continuous path from the initial pose to the final one. When the two end-poses belong to different branches and no singularity-free path is possible, the algorithm indicates the impossibility of a valid path. A numerical example has also been presented as illustration of the path planning strategy.

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Governments and intergovernmental organisations have long recognised that space communities – the ultimate ‘settlements at the edge’ – will exist one day and have based their first plans for these on another region ‘at the edge’, the Antarctic. United States President Eisenhower proposed to the United Nations in 1960 that the principles of the Antarctic Treaty be applied to outer space and celestial bodies (State Department, n.d.). Three years later the UN adopted the Declaration of Legal Principles Governing the Activities of States in the Exploration and Use of Outer Space and in 1967 that became the Outer Space Treaty. According to the UN Office for Outer Space Affairs, ‘the Treaty was opened for signature by the three depository Governments (the Russian Federation, the United Kingdom and the United States of America) in January 1967, and it entered into force in October 1967’ (Office for Outer Space Affairs, n.d). The status of the treaty (at time of writing) was 89 signatories and 102 parties (Office for Disarmament Affairs, n.d.). Other related instruments include the Rescue Agreement, the Liability Convention, the Registration Convention and the Moon Agreement (Office for Outer Space Affairs, n.d.-a). Jumping to the present, a newsagency reported in July 2014 (Reuters, 2014) that the British Government had shortlisted eight aerodromes in its search for a potential base for the UK’s first spaceplane flights which Ministers want to happen by 2018 (UK Space Agency, 2014). The United States already has a spaceport, in New Mexico (Cokley, Rankin, Heinrich, & McAuliffe, 2013)...

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A number of hurdles must be overcome in order to integrate unmanned aircraft into civilian airspace for routine operations. The ability of the aircraft to land safely in an emergency is essential to reduce the risk to people, infrastructure and aircraft. To date, few field-demonstrated systems have been presented that show online re-planning and repeatability from failure to touchdown. This paper presents the development of the Guidance, Navigation and Control (GNC) component of an Automated Emergency Landing System (AELS) intended to address this gap, suited to a variety of fixed-wing aircraft. Field-tested on both a fixed-wing UAV and Cessna 172R during repeated emergency landing experiments, a trochoid-based path planner computes feasible trajectories and a simplified control system executes the required manoeuvres to guide the aircraft towards touchdown on a predefined landing site. This is achieved in zero-thrust conditions with engine forced to idle to simulate failure. During an autonomous landing, the controller uses airspeed, inertial and GPS data to track motion and maintains essential flight parameters to guarantee flyability, while the planner monitors glide ratio and re-plans to ensure approach at correct altitude. Simulations show reliability of the system in a variety of wind conditions and its repeated ability to land within the boundary of a predefined landing site. Results from field-tests for the two aircraft demonstrate the effectiveness of the proposed GNC system in live operation. Results show that the system is capable of guiding the aircraft to close proximity of a predefined keyhole in nearly 100% of cases.

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This research improved the measurement of public transport accessibility by capturing; travellers' behaviour; diversity of public transport mode; and the subjectivity of travellers' decision in the complex transport networks. The results of this research not only highlighted the importance of considering public transport network characteristics but also, revealed the impact of public transport diversity in the modelling of public transport accessibility. The research developed a hybrid discrete choice model with a nested logit structure to treat the correlation among the public transport mode choices and, a logit correction factor to rectify the correlation among the stop choices.

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This research has made substantial and novel contributions to the body of knowledge by combining mixed, quantitative and qualitative analyses to understand the potential uptake of a proposed Bus Rapid Transit (BRT) system by commuters in a developing country's megacity, using Dhaka, Bangladesh as the case study. The quantitative analysis took a unique approach by dividing the analysis into an exploratory analysis of Revealed Preference (RP) survey data, modelling with RP data and modelling with Preferred Mode Selection (PMS) survey data. The qualitative analysis also made a novel contribution by taking a "lesson drawing" approach from model cities in analysing Dhaka's transport environment.

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Cities are the most dramatic manifestations of human activities on the surface of the earth. These human-dominated organisms—i.e., cities—degrade natural habitats, simplify species composition, disrupt hydrological systems, and modify energy flow and nutrient cycling. Today, these consequential impacts of human activities, originated from population increase, rapid urbanization, high private motor vehicle dependency, deregulated industrialization and mass livestock production, are increasing exponentially and causing great deal of environmental, social, and economic challenges both at global and local scales. In such a situation, establishment of sustainable cities, through sustainable urban development practices, is seen as a potential panacea to combat these challenges responsibly, effectively, and efficiently. This paper offers a critical review of the key literature on the issues relating to planning, development and management of sustainable cities, introduces the contributions from the Special Issue, and speculates on the prospective research directions to place necessary mechanisms to secure a sustainable urban future for all.

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Complex social factors and health issues challenge equitable health outcomes for many people, in particular those living in marginalised communities. Primary health care promises solutions through population health and health promotion approaches to improve social conditions (determinants) affecting health with emphasis on change at systems levels. Yet short-term efficiency focus policy decisions without long-term planning can undermine the effectiveness of primary health care. The workshop goal is to explore opportunities and share ideas about population health planning in Primary Health Networks and other community health care settings, so as to draw out opportunities, challenges and forward thinking health planning and health promotion strategies.

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Regional planning faces numerous decision making uncertainties related to the complex interdependencies between urban and regional centres. Questions about how to achieve sustainable planning solutions across regions are a key uncertainty and relate to a lack of information about the actual achievement of outcomes as proposed by the objectives of a plan. Regional plan implementation and its impact on environmental, social and economic outcomes have been little explored within Australian urban and regional planning research. Despite a desire to improve the conditions across Australian regions, ambiguity persists regarding the results of regional planning efforts. Of the variables affecting regional planning, scholars argue that governance has a significant impact on achieving outcomes (see Pahl-Wostl 2009). In order to better analyse the impact of governance, we propose a set of governance indicators to examine decisions across regional planning institutions and apply this to governance models across Queensland’s regions. We contend that these governance indicators can support a more rigorous assessment of the impacts of governance models on plan implementation and outcomes. We propose that this is a way to better understand the relationship between planning and outcomes across urban and regional areas.

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Robot Path Planning (RPP) in dynamic environments is a search problem based on the examination of collision-free paths in the presence of dynamic and static obstacles. Many techniques have been developed to solve this problem. Trapping in a local minima and maintaining a Real-Time performance are known as the two most important challenges that these techniques face to solve such problem. This study presents a comprehensive survey of the various techniques that have been proposed in this domain. As part of this survey, we include a classification of the approaches and identify their methods.

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Algorithms for planning quasistatic attitude maneuvers based on the Jacobian of the forward kinematic mapping of fully-reversed (FR) sequences of rotations are proposed in this paper. An FR sequence of rotations is a series of finite rotations that consists of initial rotations about the axes of a body-fixed coordinate frame and subsequent rotations that undo these initial rotations. Unlike the Jacobian of conventional systems such as a robot manipulator, the Jacobian of the system manipulated through FR rotations is a null matrix at the identity, which leads to a total breakdown of the traditional Jacobian formulation. Therefore, the Jacobian algorithm is reformulated and implemented so as to synthesize an FR sequence for a desired rotational displacement. The Jacobian-based algorithm presented in this paper identifies particular six-rotation FR sequences that synthesize desired orientations. We developed the single-step and the multiple-step Jacobian methods to accomplish a given task using six-rotation FR sequences. The single-step Jacobian method identifies a specific FR sequence for a given desired orientation and the multiple-step Jacobian algorithm synthesizes physically feasible FR rotations on an optimal path. A comparison with existing algorithms verifies the fast convergence ability of the Jacobian-based algorithm. Unlike closed-form solutions to the inverse kinematics problem, the Jacobian-based algorithm determines the most efficient FR sequence that yields a desired rotational displacement through a simple and inexpensive numerical calculation. The procedure presented here is useful for those motion planning problems wherein the Jacobian is singular or null.