905 resultados para Database navigation


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The design of programs for broadcast disks which incorporate real-time and fault-tolerance requirements is considered. A generalized model for real-time fault-tolerant broadcast disks is defined. It is shown that designing programs for broadcast disks specified in this model is closely related to the scheduling of pinwheel task systems. Some new results in pinwheel scheduling theory are derived, which facilitate the efficient generation of real-time fault-tolerant broadcast disk programs.

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Ongoing work towards appearance-based 3D hand pose estimation from a single image is presented. A large database of synthetic hand views is generated using a 3D hand model and computer graphics. The views display different hand shapes as seen from arbitrary viewpoints. Each synthetic view is automatically labeled with parameters describing its hand shape and viewing parameters. Given an input image, the system retrieves the most similar database views, and uses the shape and viewing parameters of those views as candidate estimates for the parameters of the input image. Preliminary results are presented, in which appearance-based similarity is defined in terms of the chamfer distance between edge images.

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In outsourced database (ODB) systems the database owner publishes its data through a number of remote servers, with the goal of enabling clients at the edge of the network to access and query the data more efficiently. As servers might be untrusted or can be compromised, query authentication becomes an essential component of ODB systems. Existing solutions for this problem concentrate mostly on static scenarios and are based on idealistic properties for certain cryptographic primitives. In this work, first we define a variety of essential and practical cost metrics associated with ODB systems. Then, we analytically evaluate a number of different approaches, in search for a solution that best leverages all metrics. Most importantly, we look at solutions that can handle dynamic scenarios, where owners periodically update the data residing at the servers. Finally, we discuss query freshness, a new dimension in data authentication that has not been explored before. A comprehensive experimental evaluation of the proposed and existing approaches is used to validate the analytical models and verify our claims. Our findings exhibit that the proposed solutions improve performance substantially over existing approaches, both for static and dynamic environments.

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Many people suffer from conditions that lead to deterioration of motor control and makes access to the computer using traditional input devices difficult. In particular, they may loose control of hand movement to the extent that the standard mouse cannot be used as a pointing device. Most current alternatives use markers or specialized hardware to track and translate a user's movement to pointer movement. These approaches may be perceived as intrusive, for example, wearable devices. Camera-based assistive systems that use visual tracking of features on the user's body often require cumbersome manual adjustment. This paper introduces an enhanced computer vision based strategy where features, for example on a user's face, viewed through an inexpensive USB camera, are tracked and translated to pointer movement. The main contributions of this paper are (1) enhancing a video based interface with a mechanism for mapping feature movement to pointer movement, which allows users to navigate to all areas of the screen even with very limited physical movement, and (2) providing a customizable, hierarchical navigation framework for human computer interaction (HCI). This framework provides effective use of the vision-based interface system for accessing multiple applications in an autonomous setting. Experiments with several users show the effectiveness of the mapping strategy and its usage within the application framework as a practical tool for desktop users with disabilities.

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Both animals and mobile robots, or animats, need adaptive control systems to guide their movements through a novel environment. Such control systems need reactive mechanisms for exploration, and learned plans to efficiently reach goal objects once the environment is familiar. How reactive and planned behaviors interact together in real time, and arc released at the appropriate times, during autonomous navigation remains a major unsolved problern. This work presents an end-to-end model to address this problem, named SOVEREIGN: A Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goal-oriented Navigation system. The model comprises several interacting subsystems, governed by systems of nonlinear differential equations. As the animat explores the environment, a vision module processes visual inputs using networks that arc sensitive to visual form and motion. Targets processed within the visual form system arc categorized by real-time incremental learning. Simultaneously, visual target position is computed with respect to the animat's body. Estimates of target position activate a motor system to initiate approach movements toward the target. Motion cues from animat locomotion can elicit orienting head or camera movements to bring a never target into view. Approach and orienting movements arc alternately performed during animat navigation. Cumulative estimates of each movement, based on both visual and proprioceptive cues, arc stored within a motor working memory. Sensory cues are stored in a parallel sensory working memory. These working memories trigger learning of sensory and motor sequence chunks, which together control planned movements. Effective chunk combinations arc selectively enhanced via reinforcement learning when the animat is rewarded. The planning chunks effect a gradual transition from reactive to planned behavior. The model can read-out different motor sequences under different motivational states and learns more efficient paths to rewarded goals as exploration proceeds. Several volitional signals automatically gate the interactions between model subsystems at appropriate times. A 3-D visual simulation environment reproduces the animat's sensory experiences as it moves through a simplified spatial environment. The SOVEREIGN model exhibits robust goal-oriented learning of sequential motor behaviors. Its biomimctic structure explicates a number of brain processes which are involved in spatial navigation.

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A neural network system, NAVITE, for incremental trajectory generation and obstacle avoidance is presented. Unlike other approaches, the system is effective in unstructured environments. Multimodal inforrnation from visual and range data is used for obstacle detection and to eliminate uncertainty in the measurements. Optimal paths are computed without explicitly optimizing cost functions, therefore reducing computational expenses. Simulations of a planar mobile robot (including the dynamic characteristics of the plant) in obstacle-free and object avoidance trajectories are presented. The system can be extended to incorporate global map information into the local decision-making process.

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This thesis explores the use of electromagnetics for both steering and tracking of medical instruments in minimally invasive surgeries. The end application is virtual navigation of the lung for biopsy of early stage cancer nodules. Navigation to the peripheral regions of the lung is difficult due to physical dimensions of the bronchi and current methods have low successes rates for accurate diagnosis. Firstly, the potential use of DC magnetic fields for the actuation of catheter devices with permanently magnetised distal attachments is investigated. Catheter models formed from various materials and magnetic tip formations are used to examine the usefulness of relatively low power and compact electromagnets. The force and torque that can be exerted on a small permanent magnet is shown to be extremely limited. Hence, after this initial investigation we turn our attention to electromagnetic tracking, in the development of a novel, low-cost implementation of a GPS-like system for navigating within a patient. A planar magnetic transmitter, formed on a printed circuit board for a low-profile and low cost manufacture, is used to generate a low frequency magnetic field distribution which is detected by a small induction coil sensor. The field transmitter is controlled by a novel closed-loop system that ensures a highly stable magnetic field with reduced interference from one transmitter coil to another. Efficient demodulation schemes are presented which utilise synchronous detection of each magnetic field component experienced by the sensor. The overall tracking accuracy of the system is shown to be less than 2 mm with an orientation error less than 1°. A novel demodulation implementation using a unique undersampling approach allows the use of reduced sample rates to sample the signals of interest without loss of tracking accuracy. This is advantageous for embedded microcontroller implementations of EM tracking systems. The EM tracking system is demonstrated in the pre-clinical environment of a breathing lung phantom. The airways of the phantom are successfully navigated using the system in combination with a 3D computer model rendered from CT data. Registration is achieved using both a landmark rigid registration method and a hybrid fiducial-free approach. The design of a planar magnetic shield structure for blocking the effects of metallic distortion from below the transmitter is presented which successfully blocks the impact of large ferromagnetic objects such as operating tables. A variety of shielding material are analysed with MuMetal and ferrite both providing excellent shieling performance and an increased signal to noise ratio. Finally, the effect of conductive materials and human tissue on magnetic field measurements is presented. Error due to induced eddy currents and capacitive coupling is shown to severely affect EM tracking accuracy at higher frequencies.

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BACKGROUND: Outpatient palliative care, an evolving delivery model, seeks to improve continuity of care across settings and to increase access to services in hospice and palliative medicine (HPM). It can provide a critical bridge between inpatient palliative care and hospice, filling the gap in community-based supportive care for patients with advanced life-limiting illness. Low capacities for data collection and quantitative research in HPM have impeded assessment of the impact of outpatient palliative care. APPROACH: In North Carolina, a regional database for community-based palliative care has been created through a unique partnership between a HPM organization and academic medical center. This database flexibly uses information technology to collect patient data, entered at the point of care (e.g., home, inpatient hospice, assisted living facility, nursing home). HPM physicians and nurse practitioners collect data; data are transferred to an academic site that assists with analyses and data management. Reports to community-based sites, based on data they provide, create a better understanding of local care quality. CURRENT STATUS: The data system was developed and implemented over a 2-year period, starting with one community-based HPM site and expanding to four. Data collection methods were collaboratively created and refined. The database continues to grow. Analyses presented herein examine data from one site and encompass 2572 visits from 970 new patients, characterizing the population, symptom profiles, and change in symptoms after intervention. CONCLUSION: A collaborative regional approach to HPM data can support evaluation and improvement of palliative care quality at the local, aggregated, and statewide levels.

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BACKGROUND: The incidence and epidemiology of invasive fungal infections (IFIs), a leading cause of death among hematopoeitic stem cell transplant (HSCT) recipients, are derived mainly from single-institution retrospective studies. METHODS: The Transplant Associated Infections Surveillance Network, a network of 23 US transplant centers, prospectively enrolled HSCT recipients with proven and probable IFIs occurring between March 2001 and March 2006. We collected denominator data on all HSCTs preformed at each site and clinical, diagnostic, and outcome information for each IFI case. To estimate trends in IFI, we calculated the 12-month cumulative incidence among 9 sequential subcohorts. RESULTS: We identified 983 IFIs among 875 HSCT recipients. The median age of the patients was 49 years; 60% were male. Invasive aspergillosis (43%), invasive candidiasis (28%), and zygomycosis (8%) were the most common IFIs. Fifty-nine percent and 61% of IFIs were recognized within 60 days of neutropenia and graft-versus-host disease, respectively. Median onset of candidiasis and aspergillosis after HSCT was 61 days and 99 days, respectively. Within a cohort of 16,200 HSCT recipients who received their first transplants between March 2001 and September 2005 and were followed up through March 2006, we identified 718 IFIs in 639 persons. Twelve-month cumulative incidences, based on the first IFI, were 7.7 cases per 100 transplants for matched unrelated allogeneic, 8.1 cases per 100 transplants for mismatched-related allogeneic, 5.8 cases per 100 transplants for matched-related allogeneic, and 1.2 cases per 100 transplants for autologous HSCT. CONCLUSIONS: In this national prospective surveillance study of IFIs in HSCT recipients, the cumulative incidence was highest for aspergillosis, followed by candidiasis. Understanding the epidemiologic trends and burden of IFIs may lead to improved management strategies and study design.

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Gemstone Team Vision

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OBJECTIVE: To investigate the effect of statin use after radical prostatectomy (RP) on biochemical recurrence (BCR) in patients with prostate cancer who never received statins before RP. PATIENTS AND METHODS: We conducted a retrospective analysis of 1146 RP patients within the Shared Equal Access Regional Cancer Hospital (SEARCH) database. Multivariable Cox proportional hazards analyses were used to examine differences in risk of BCR between post-RP statin users vs nonusers. To account for varying start dates and duration of statin use during follow-up, post-RP statin use was treated as a time-dependent variable. In a secondary analysis, models were stratified by race to examine the association of post-RP statin use with BCR among black and non-black men. RESULTS: After adjusting for clinical and pathological characteristics, post-RP statin use was significantly associated with 36% reduced risk of BCR (hazard ratio [HR] 0.64, 95% confidence interval [CI] 0.47-0.87; P = 0.004). Post-RP statin use remained associated with reduced risk of BCR after adjusting for preoperative serum cholesterol levels. In secondary analysis, after stratification by race, this protective association was significant in non-black (HR 0.49, 95% CI 0.32-0.75; P = 0.001) but not black men (HR 0.82, 95% CI 0.53-1.28; P = 0.384). CONCLUSION: In this retrospective cohort of men undergoing RP, post-RP statin use was significantly associated with reduced risk of BCR. Whether the association between post-RP statin use and BCR differs by race requires further study. Given these findings, coupled with other studies suggesting that statins may reduce risk of advanced prostate cancer, randomised controlled trials are warranted to formally test the hypothesis that statins slow prostate cancer progression.

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The foraging activity of many organisms reveal strategic movement patterns, showing efficient use of spatially distributed resources. The underlying mechanisms behind these movement patterns, such as the use of spatial memory, are topics of considerable debate. To augment existing evidence of spatial memory use in primates, we generated movement patterns from simulated primate agents with simple sensory and behavioral capabilities. We developed agents representing various hypotheses of memory use, and compared the movement patterns of simulated groups to those of an observed group of red colobus monkeys (Procolobus rufomitratus), testing for: the effects of memory type (Euclidian or landmark based), amount of memory retention, and the effects of social rules in making foraging choices at the scale of the group (independent or leader led). Our results indicate that red colobus movement patterns fit best with simulated groups that have landmark based memory and a follow the leader foraging strategy. Comparisons between simulated agents revealed that social rules had the greatest impact on a group's step length, whereas the type of memory had the highest impact on a group's path tortuosity and cohesion. Using simulation studies as experimental trials to test theories of spatial memory use allows the development of insight into the behavioral mechanisms behind animal movement, developing case-specific results, as well as general results informing how changes to perception and behavior influence movement patterns.

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The Feeding Experiments End-user Database (FEED) is a research tool developed by the Mammalian Feeding Working Group at the National Evolutionary Synthesis Center that permits synthetic, evolutionary analyses of the physiology of mammalian feeding. The tasks of the Working Group are to compile physiologic data sets into a uniform digital format stored at a central source, develop a standardized terminology for describing and organizing the data, and carry out a set of novel analyses using FEED. FEED contains raw physiologic data linked to extensive metadata. It serves as an archive for a large number of existing data sets and a repository for future data sets. The metadata are stored as text and images that describe experimental protocols, research subjects, and anatomical information. The metadata incorporate controlled vocabularies to allow consistent use of the terms used to describe and organize the physiologic data. The planned analyses address long-standing questions concerning the phylogenetic distribution of phenotypes involving muscle anatomy and feeding physiology among mammals, the presence and nature of motor pattern conservation in the mammalian feeding muscles, and the extent to which suckling constrains the evolution of feeding behavior in adult mammals. We expect FEED to be a growing digital archive that will facilitate new research into understanding the evolution of feeding anatomy.

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X-ray crystallography is the predominant method for obtaining atomic-scale information about biological macromolecules. Despite the success of the technique, obtaining well diffracting crystals still critically limits going from protein to structure. In practice, the crystallization process proceeds through knowledge-informed empiricism. Better physico-chemical understanding remains elusive because of the large number of variables involved, hence little guidance is available to systematically identify solution conditions that promote crystallization. To help determine relationships between macromolecular properties and their crystallization propensity, we have trained statistical models on samples for 182 proteins supplied by the Northeast Structural Genomics consortium. Gaussian processes, which capture trends beyond the reach of linear statistical models, distinguish between two main physico-chemical mechanisms driving crystallization. One is characterized by low levels of side chain entropy and has been extensively reported in the literature. The other identifies specific electrostatic interactions not previously described in the crystallization context. Because evidence for two distinct mechanisms can be gleaned both from crystal contacts and from solution conditions leading to successful crystallization, the model offers future avenues for optimizing crystallization screens based on partial structural information. The availability of crystallization data coupled with structural outcomes analyzed through state-of-the-art statistical models may thus guide macromolecular crystallization toward a more rational basis.

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Team NAVIGATE aims to create a robust, portable navigational aid for the blind. Our prototype uses depth data from the Microsoft Kinect to perform realtime obstacle avoidance in unfamiliar indoor environments. The device augments the white cane by performing two signi cant functions: detecting overhanging objects and identifying stairs. Based on interviews with blind individuals, we found a combined audio and haptic feedback system best for communicating environmental information. Our prototype uses vibration motors to indicate the presence of an obstacle and an auditory command to alert the user to stairs ahead. Through multiple trials with sighted and blind participants, the device was successful in detecting overhanging objects and approaching stairs. The device increased user competency and adaptability across all trials.