996 resultados para adaptive sampling


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Objectives: This methodological paper reports on the development and validation of a work sampling instrument and data collection processes to conduct a national study of nurse practitioners’ work patterns. ---------- Design: Published work sampling instruments provided the basis for development and validation of a tool for use in a national study of nurse practitioner work activities across diverse contextual and clinical service models. Steps taken in the approach included design of a nurse practitioner-specific data collection tool and development of an innovative web-based program to train and establish inter rater reliability of a team of data collectors who were geographically dispersed across metropolitan, rural and remote health care settings. ---------- Setting: The study is part of a large funded study into nurse practitioner service. The Australian Nurse Practitioner Study is a national study phased over three years and was designed to provide essential information for Australian health service planners, regulators and consumer groups on the profile, process and outcome of nurse practitioner service. ---------- Results: The outcome if this phase of the study is empirically tested instruments, process and training materials for use in an international context by investigators interested in conducting a national study of nurse practitioner work practices. ---------- Conclusion: Development and preparation of a new approach to describing nurse practitioner practices using work sampling methods provides the groundwork for international collaboration in evaluation of nurse practitioner service.

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Aim: This paper is a report of a study of variations in the pattern of nurse practitioner work in a range of service fields and geographical locations, across direct patient care, indirect patient care and service-related activities. Background. The nurse practitioner role has been implemented internationally as a service reform model to improve the access and timeliness of health care. There is a substantial body of research into the nurse practitioner role and service outcomes, but scant information on the pattern of nurse practitioner work and how this is influenced by different service models. --------- Methods: We used work sampling methods. Data were collected between July 2008 and January 2009. Observations were recorded from a random sample of 30 nurse practitioners at 10-minute intervals in 2-hour blocks randomly generated to cover two weeks of work time from a sampling frame of six weeks. --------- Results: A total of 12,189 individual observations were conducted with nurse practitioners across Australia. Thirty individual activities were identified as describing nurse practitioner work, and these were distributed across three categories. Direct care accounted for 36.1% of how nurse practitioners spend their time, indirect care accounted for 32.2% and service-related activities made up 31.9%. --------- Conclusion. These findings provide useful baseline data for evaluation of nurse practitioner positions and the service effect of these positions. However, the study also raises questions about the best use of nurse practitioner time and the influences of barriers to and facilitators of this model of service innovation.

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This paper presents research in response to environmental concerns we face today. In a search for a better method to manage spaces and building resources consumed excessively through traditional top-down architectural solutions, the research began by speculating that the building spaces and resources can be managed by designing architectural systems that encourage a bottom-up approach. In other words, this research investigates how to design systems that encourage occupants and users of buildings to actively understand, manage and customise their own spaces. Specific attention is paid to the participation of building users because no matter how sophisticated the system is, the building will become as wasteful as conventional buildings if users cannot, or do not want to, utilise the system effectively. The research is still in its early stages. The intension of this paper is to provide a background to the issue, discuss researches and projects relevant to, but not necessarily about, architecture, and introduce a number of hypothesis and investigations to realise adaptable, participatory and sustainable environments for users.

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In this paper we present a novel distributed coding protocol for multi-user cooperative networks. The proposed distributed coding protocol exploits the existing orthogonal space-time block codes to achieve higher diversity gain by repeating the code across time and space (available relay nodes). The achievable diversity gain depends on the number of relay nodes that can fully decode the signal from the source. These relay nodes then form space-time codes to cooperatively relay to the destination using number of time slots. However, the improved diversity gain is archived at the expense of the transmission rate. The design principles of the proposed space-time distributed code and the issues related to transmission rate and diversity trade off is discussed in detail. We show that the proposed distributed space-time coding protocol out performs existing distributed codes with a variable transmission rate.

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Ocean processes are dynamic and complex events that occur on multiple different spatial and temporal scales. To obtain a synoptic view of such events, ocean scientists focus on the collection of long-term time series data sets. Generally, these time series measurements are continually provided in real or near-real time by fixed sensors, e.g., buoys and moorings. In recent years, an increase in the utilization of mobile sensor platforms, e.g., Autonomous Underwater Vehicles, has been seen to enable dynamic acquisition of time series data sets. However, these mobile assets are not utilized to their full capabilities, generally only performing repeated transects or user-defined patrolling loops. Here, we provide an extension to repeated patrolling of a designated area. Our algorithms provide the ability to adapt a standard mission to increase information gain in areas of greater scientific interest. By implementing a velocity control optimization along the predefined path, we are able to increase or decrease spatiotemporal sampling resolution to satisfy the sampling requirements necessary to properly resolve an oceanic phenomenon. We present a path planning algorithm that defines a sampling path, which is optimized for repeatability. This is followed by the derivation of a velocity controller that defines how the vehicle traverses the given path. The application of these tools is motivated by an ongoing research effort to understand the oceanic region off the coast of Los Angeles, California. The computed paths are implemented with the computed velocities onto autonomous vehicles for data collection during sea trials. Results from this data collection are presented and compared for analysis of the proposed technique.

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Autonomous underwater gliders are robust and widely-used ocean sampling platforms that are characterized by their endurance, and are one of the best approaches to gather subsurface data at the appropriate spatial resolution to advance our knowledge of the ocean environment. Gliders generally do not employ sophisticated sensors for underwater localization, but instead dead-reckon between set waypoints. Thus, these vehicles are subject to large positional errors between prescribed and actual surfacing locations. Here, we investigate the implementation of a large-scale, regional ocean model into the trajectory design for autonomous gliders to improve their navigational accuracy. We compute the dead-reckoning error for our Slocum gliders, and compare this to the average positional error recorded from multiple deployments conducted over the past year. We then compare trajectory plans computed on-board the vehicle during recent deployments to our prediction-based trajectory plans for 140 surfacing occurrences.

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In recent years, ocean scientists have started to employ many new forms of technology as integral pieces in oceanographic data collection for the study and prediction of complex and dynamic ocean phenomena. One area of technological advancement in ocean sampling if the use of Autonomous Underwater Vehicles (AUVs) as mobile sensor plat- forms. Currently, most AUV deployments execute a lawnmower- type pattern or repeated transects for surveys and sampling missions. An advantage of these missions is that the regularity of the trajectory design generally makes it easier to extract the exact path of the vehicle via post-processing. However, if the deployment region for the pattern is poorly selected, the AUV can entirely miss collecting data during an event of specific interest. Here, we consider an innovative technology toolchain to assist in determining the deployment location and executed paths for AUVs to maximize scientific information gain about dynamically evolving ocean phenomena. In particular, we provide an assessment of computed paths based on ocean model predictions designed to put AUVs in the right place at the right time to gather data related to the understanding of algal and phytoplankton blooms.

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Data collection using Autonomous Underwater Vehicles (AUVs) is increasing in importance within the oceano- graphic research community. Contrary to traditional moored or static platforms, mobile sensors require intelligent planning strategies to manoeuvre through the ocean. However, the ability to navigate to high-value locations and collect data with specific scientific merit is worth the planning efforts. In this study, we examine the use of ocean model predictions to determine the locations to be visited by an AUV, and aid in planning the trajectory that the vehicle executes during the sampling mission. The objectives are: a) to provide near-real time, in situ measurements to a large-scale ocean model to increase the skill of future predictions, and b) to utilize ocean model predictions as a component in an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. We present an algorithm designed to generate paths for AUVs to track a dynamically evolving ocean feature utilizing ocean model predictions. This builds on previous work in this area by incorporating the predicted current velocities into the path planning to assist in solving the 3-D motion planning problem of steering an AUV between two selected locations. We present simulation results for tracking a fresh water plume by use of our algorithm. Additionally, we present experimental results from field trials that test the skill of the model used as well as the incorporation of the model predictions into an AUV trajectory planner. These results indicate a modest, but measurable, improvement in surfacing error when the model predictions are incorporated into the planner.

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Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection. We consider the use of ocean model predictions to determine the locations to be visited by an AUV, which then provides near-real time, in situ measurements back to the model to increase the skill of future predictions. The motion planning problem of steering the vehicle between the computed waypoints is not considered here. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks. We design a sampling plan and present experimental results with AUV retasking in the Southern California Bight (SCB) off the coast of Los Angeles.

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Harmful Algal Blooms (HABs) have become an important environmental concern along the western coast of the United States. Toxic and noxious blooms adversely impact the economies of coastal communities in the region, pose risks to human health, and cause mortality events that have resulted in the deaths of thousands of fish, marine mammals and seabirds. One goal of field-based research efforts on this topic is the development of predictive models of HABs that would enable rapid response, mitigation and ultimately prevention of these events. In turn, these objectives are predicated on understanding the environmental conditions that stimulate these transient phenomena. An embedded sensor network (Fig. 1), under development in the San Pedro Shelf region off the Southern California coast, is providing tools for acquiring chemical, physical and biological data at high temporal and spatial resolution to help document the emergence and persistence of HAB events, supporting the design and testing of predictive models, and providing contextual information for experimental studies designed to reveal the environmental conditions promoting HABs. The sensor platforms contained within this network include pier-based sensor arrays, ocean moorings, HF radar stations, along with mobile sensor nodes in the form of surface and subsurface autonomous vehicles. FreewaveTM radio modems facilitate network communication and form a minimally-intrusive, wireless communication infrastructure throughout the Southern California coastal region, allowing rapid and cost-effective data transfer. An emerging focus of this project is the incorporation of a predictive ocean model that assimilates near-real time, in situ data from deployed Autonomous Underwater Vehicles (AUVs). The model then assimilates the data to increase the skill of both nowcasts and forecasts, thus providing insight into bloom initiation as well as the movement of blooms or other oceanic features of interest (e.g., thermoclines, fronts, river discharge, etc.). From these predictions, deployed mobile sensors can be tasked to track a designated feature. This focus has led to the creation of a technology chain in which algorithms are being implemented for the innovative trajectory design for AUVs. Such intelligent mission planning is required to maneuver a vehicle to precise depths and locations that are the sites of active blooms, or physical/chemical features that might be sources of bloom initiation or persistence. The embedded network yields high-resolution, temporal and spatial measurements of pertinent environmental parameters and resulting biology (see Fig. 1). Supplementing this with ocean current information and remotely sensed imagery and meteorological data, we obtain a comprehensive foundation for developing a fundamental understanding of HAB events. This then directs labor- intensive and costly sampling efforts and analyses. Additionally, we provide coastal municipalities, managers and state agencies with detailed information to aid their efforts in providing responsible environmental stewardship of their coastal waters.

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This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.

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This paper argues a model of adaptive design for sustainable architecture within a framework of entropy evolution. The spectrum of sustainable architecture consists of efficient use of energy and material resource in the life-cycle of buildings, active involvement of the occupants into micro-climate control within the building, and the natural environment as the physical context. The interactions amongst all the parameters compose a complex system of sustainable architecture design, of which the conventional linear and fragmented design technologies are insufficient to indicate holistic and ongoing environmental performance. The latest interpretation of the Second Law of Thermodynamics states a microscopic formulation of an entropy evolution of complex open systems. It provides a design framework for an adaptive system evolves for the optimization in open systems, this adaptive system evolves for the optimization of building environmental performance. The paper concludes that adaptive modelling in entropy evolution is a design alternative for sustainable architecture.

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Attending potentially dangerous and traumatic incidents is inherent in the role of emergency workers, yet there is a paucity of literature aimed at examining variables that impact on the outcomes of such exposure. Coping has been implicated in adjusting to trauma in other contexts, and this study explored the effectiveness of coping strategies in relation to positive and negative posttrauma outcomes in the emergency services environment. One hundred twenty-five paramedics completed a survey battery including the Posttraumatic Growth Inventory (PTGI; Tedeschi & Calhoun, 1996), the Impact of Events Scale–Revised (IES-R; Weiss & Marmar, 1997), and the Revised-COPE (Zuckerman & Gagne, 2003). Results from the regression analysis demonstrated that specific coping strategies were differentially associated with positive and negative posttrauma outcomes. The research contributes to a more comprehensive understanding regarding the effectiveness of coping strategies employed by paramedics in managing trauma, with implications for their psychological well-being as well as the training and support services available.

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This paper addresses the tradeoff between energy consumption and localization performance in a mobile sensor network application. The focus is on augmenting GPS location with more energy-efficient location sensors to bound position estimate uncertainty in order to prolong node lifetime. We use empirical GPS and radio contact data from a largescale animal tracking deployment to model node mobility, GPS and radio performance. These models are used to explore duty cycling strategies for maintaining position uncertainty within specified bounds. We then explore the benefits of using short-range radio contact logging alongside GPS as an energy-inexpensive means of lowering uncertainty while the GPS is off, and we propose a versatile contact logging strategy that relies on RSSI ranging and GPS lock back-offs for reducing the node energy consumption relative to GPS duty cycling. Results show that our strategy can cut the node energy consumption by half while meeting application specific positioning criteria.

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This paper presents an explanation of why the reuse of building components after demolition or deconstruction is critical to the future of the construction industry. An examination of the historical cause and response to climate change sets the scene as to why governance is becoming increasingly focused on the built environment as a mechanism to controlling waste generation associated with the process of demolition, construction and operation. Through an annotated description to the evolving design and construction methodology of a range of timber dwellings (typically 'Queenslanders' during the eras of 1880-1900, 1900-1920 & 1920-1940) the paper offers an evaluation to the variety of materials, which can be used advantageously by those wishing to 'regenerate' a Queenslander. This analysis of 'regeneration' details the constraints when considering relocation and/ or reuse by adaption including deconstruction of building components against the legislative framework requirements of the Queensland Building Act 1975 and the Queensland Sustainable Planning Act 2009, with a specific examination to those of the Building Codes of Australia. The paper concludes with a discussion of these constraints, their impacts on 'regeneration' and the need for further research to seek greater understanding of the practicalities and drivers of relocation, adaptive and building components suitability for reuse after deconstruction.