Geobase Information System Impacts on Space Image Formats

As Geobase Information Systems increase in number, size and complexity, the format compatability of satellite remote sensing data becomes increasingly more important. Because of the vast and continually increasing quantity of data available from remote sensing systems the utility of these data is increasingly dependent on the degree to which their formats facilitate, or hinder, their incorporation into Geobase Information Systems. To merge satellite data into a geobase system requires that they both have a compatible geographic referencing system. Greater acceptance of satellite data by the user community will be facilitated if the data are in a form which most readily corresponds to existing geobase data structures. The conference addressed a number of specific topics and made recommendations

Development and application of operational techniques for the inventory and monitoring of resources and uses for the Texas coastal zone. Volume 1: Text

The author has identified the following significant results. Image interpretation and computer-assisted techniques were developed to analyze LANDSAT scenes in support of resource inventory and monitoring requirements for the Texas coastal region. Land cover and land use maps, at a scale of 1:125,000 for the image interpretation product and 1:24,000 for the computer-assisted product, were generated covering four Texas coastal test sites. Classification schemes which parallel national systems were developed for each procedure, including 23 classes for image interpretation technique and 13 classes for the computer-assisted technique. Results indicate that LANDSAT-derived land cover and land use maps can be successfully applied to a variety of planning and management activities on the Texas coast. Computer-derived land/water maps can be used with tide gage data to assess shoreline boundaries for management purposes

Timely and reliable evaluation of the effects of interventions: a framework for adaptive meta-analysis (FAME)

Most systematic reviews are retrospective and use aggregate data AD) from publications, meaning they can be unreliable, lag behind therapeutic developments and fail to influence ongoing or new trials. Commonly, the potential influence of unpublished or ongoing trials is overlooked when interpreting results, or determining the value of updating the meta-analysis or need to collect individual participant data (IPD). Therefore, we developed a Framework for Adaptive Metaanalysis (FAME) to determine prospectively the earliest opportunity for reliable AD meta-analysis. We illustrate FAME using two systematic reviews in men with metastatic (M1) and non-metastatic (M0)hormone-sensitive prostate cancer (HSPC)

Application of remote sensing to selected problems within the state of California

There are no author-identified significant results in this report

A Quality Improvement Project to Evaluate Auditor Satisfaction with Different Data Collection Methods for Auditing Compliance with Catheter Associated Urinary Tract Infection (CAUTI) Prevention Standards

Executive Summary A Quality Improvement Project to Evaluate Auditor Satisfaction with Different Data Collection Methods for Auditing Compliance with (CAUTI) Prevention Standards Problem Catheter-associated urinary tract infections (CAUTIs) are among the most common healthcare-associated infection (HAI) in the United States, representing about 40% of all HAIs (Palmer, Lee, Dutta-Linn, Wroe & Hartmann, 2013). Approximately 25% of indwelling urinary catheters are unnecessary and may potentially lead to CAUTIs if not maintained, cleaned, and cared for appropriately (Nazarko, 2012). Literature suggests that preventing CAUTIs is possible by implementing evidence based prevention standards. The PICO research question for CAUTI prevention and prevention standard data collection is: In a sampling of clinical auditors (P) does implementation of an electronic audit tool to collect data on compliance with CAUTI prevention care standards in addition to education on the electronic audit tool (I) differ from paper form auditing for CAUTI prevention care standards (C) and does it impact auditor satisfaction and/or data collected using the new tool (O). Goal The goal of this project was to assess if there were differences in paper versus electronic audit collection methods by evaluating pre- and post-implementation auditor satisfaction. In addition, an assessment of the two collection methods was completed to evaluate consistency related to number of audits collected and notable changes in compliance, thereby providing insight into if electronic data capture (EDC) is a reliable and efficient method. Objectives Project objectives included determining auditor satisfaction with paper versus electronic data collection methods and evaluation of implications of reliability with data collection methods by maintaining consistency with data. Plan Following Institutional Review Board approval from Regis University, the project was implemented and data were collected retro- and prospectively. There was an organizational transition to EDC, a questionnaire was distributed eliciting feedback from auditors on their satisfaction level, and compliance with the prevention standards was assessed for consistency pre- and post-implementation of the EDC tool. Questionnaire data were coded and entered into a spreadsheet and statistical software was used to determine if there were significant changes in auditor satisfaction. Finally, an assessment of differences in processes used to collect CAUTI prevention standard data was completed. Outcomes and Results Nine clinical auditors and one data analyst were exposed to both paper and EDC tools and completed the questionnaire. While there was not a statistically significant increase in satisfaction, there was a clinically significant increase in auditor satisfaction. There was a statistically significant difference noted between pre- and post- implementation compliance data, but this does not prove a causal relationship due to other confounding factors. There was also a statistically significant decrease in average time it took for auditors to collect audit data

The Relationship between Anthropometric Variables and Features of Electromyography Signal for Human-Computer Interface

http://doi.org/10.4018/978-1-4666-6090-8 ISBN 13 : 9781466660908 EISBN13: 9781466660915International audienceMuscle-computer interfaces (MCIs) based on surface electromyography (EMG) pattern recognition have been developed based on two consecutive components: feature extraction and classification algorithms. Many features and classifiers are proposed and evaluated, which yield the high classification accuracy and the high number of discriminated motions under a single-session experimental condition. However, there are many limitations to use MCIs in the real-world contexts, such as the robustness over time, noise, or low-level EMG activities. Although the selection of the suitable robust features can solve such problems, EMG pattern recognition has to design and train for a particular individual user to reach high accuracy. Due to different body compositions across users, a feasibility to use anthropometric variables to calibrate EMG recognition system automatically/semi-automatically is proposed. This chapter presents the relationships between robust features extracted from actions associated with surface EMG signals and twelve related anthropometric variables. The strong and significant associations presented in this chapter could benefit a further design of the MCIs based on EMG pattern recognition

State-dependent modulation of cortico-spinal networks

Beta-band rhythm (13-30 Hz) is a dominant oscillatory activity in the sensorimotor system. Numerous studies reported on links between motor performance and the cortical and cortico-spinal beta rhythm. However, these studies report divergent beta-band frequencies and are, additionally, based on differently performed motor-tasks (e.g., motor imagination, muscle contraction, reach, grasp, and attention). This diversity blurs the role of beta in the sensorimotor system. It consequently challenges the development of beta-band activity-dependent stimulation protocols in the sensorimotor system. In this vein, we studied the functional role of beta-band cortico-cortical and cortico-spinal networks during a motor learning task. We studied how the contribution of cortical and spinal beta changes in the course of learning, and how this modulation is affected by afferent feedback to the sensorimotor system. We furthermore researched the relationship to motor performance. Consider that we made our study in the absence of any residual movement to allow our findings to be translated into rehabilitation programs for severely affected stroke patients. This thesis, at first, investigates evoked responses after transcranial magnetic stimulation (TMS). This revealed two different beta-band networks, i.e., in the low and high beta-band reflecting cortical and cortico-spinal activity. We, then, used a broader frequency range in the beta-band to trigger passive opening of the hand (peripheral feedback) or cortical stimulation (cortical feedback). While a unilateral hemispheric increase in cortico-spinal synchronization was observed in the group with peripheral feedback, a bilateral hemispheric increase in cortico-cortical and cortico-spinal synchronization was observed for the group with cortical feedback. An improvement in motor performance was found in the peripheral group only. Additionally, an enhancement in the directed cortico-spinal synchronization from cortex to periphery was observed for the peripheral group. Similar neurophysiological and behavioral changes were observed for stroke patients receiving peripheral feedback. The results 6 suggest two different mechanisms for beta-band activity-dependent protocols depending on the feedback modality. While the peripheral feedback appears to increase the synchronization among neural groups, cortical stimulation appears to recruit dormant neurons and to extend the involved motor network. These findings may provide insights regarding the mechanism behind novel activity-dependent protocols. It also highlights the importance of afferent feedback for motor restoration in beta-band activity-dependent rehabilitation programs

E-Tickets and Advanced Technologies for Efficient Construction Inspections

The Kentucky Transportation Cabinet (KYTC), like many state transportation agencies, has seen demand for high-quality infrastructure skyrocket even as it endures reductions in staff numbers. To mitigate the effects of declining staff and bolster construction efficiency, the Cabinet has experimented with a variety of e-construction technologies, the goal of which are to abolish paper-based workflows and improve project-site monitoring activities. This research investigated the performance of three e-construction technologies on KYTC pilot projects — e-ticketing, paver mounted thermal profilers, and intelligent compaction. E-ticketing reduced the amount of time needed to retrieve material tickets and facilitated comparisons of theoretical tonnages to actual tonnages. Inspectors also reduced their exposure to hazardous jobsite conditions through the use of e-ticketing, while contractors strengthened their operational efficiencies. Paver mounted thermal profilers collected temperature data whose accuracy was not significantly different from temperature data gathered using conventional infrared guns. The spatially continuous data generated by profilers can aid in later monitoring of pavement performance and can be used to perform forensic investigations of pavement distress. Although other state transportation agencies have adopted intelligent compaction with considerable success, it produced inaccurate data on asphalt temperature and roller passes. Several factors may have contributed to this unexpected result, such as poor communication between project stakeholders and incorrectly executed equipment setup. The three technologies could potentially be adopted on a more widespread basis; however, it is critical to offer adequate training to equipment and software users, ensure that project stakeholders coordinate and communicate with one another, and be conscientious in the deployment and management of equipment

Solar Energy Program: Chapter from the Energy and EnvironmentalDivision Annual Report 1980

Solar energy has become a major alternative for supplying a substantial fraction of the nation's future energy needs. The U.S. Department of Energy (DOE) supports activities ranging from the demonstration of existing technology to research on future possibilities. At Lawrence Berkeley Laboratory (LBL), projects are in progress that span a wide range of activities, with the emphasis on research to extend the scientific basis for solar energy applications, and on preliminary development of new approaches to solar energy conversion. To assess various solar applications, it is important to quantify the solar resource. Special instruments have been developed and are now in use to measure both direct solar radiation and circum-solar radiation, i.e., the radiation from near the sun resulting from the scattering of sunlight by small particles in the atmosphere. These measurements serve to predict the performance of solar designs that use focusing collectors employing mirrors or lenses to concentrate the sunlight. Efforts have continued at a low level to assist DOE in demonstrating existing solar technology by providing the San Francisco Operations Office (SAN) with technical support for its management of commercial-building solar demonstration projects. Also, a hot water and space-heating system has been installed on an LBL building as part of the DOE facilities Solar Demonstration Program. LBL continues to provide support for the DOE Appropriate Energy Technology grants program. Evaluations are made of the program's effectiveness by, for example, estimating the resulting potential energy savings. LBL also documents innovative features and improvements in economic feasibility as compared to existing conventional systems or applications. In the near future, we expect that LBL research will have a substantial impact in the areas of solar heating and cooling. Conventional and new types of high-performance absorption air conditioners are being developed that are air-cooled and suitable for use with flat plate or higher-temperature collectors. Operation of the controls test facility and computer modeling of collector loop and building load dynamics are yielding quantitative evaluations of the performance of different control strategies for active solar-heating systems. Research is continuing on ''passive'' approaches to solar heating and cooling, where careful considerations of architectural design, construction materials, and the environment are used to moderate a building's interior climate. Computer models of passive concepts are being developed and incorporated into building energy analysis computer programs which are in the public domain. The resulting passive analysis capabilities are used in systems studies leading to design tools and in the design of commercial buildings on a case study basis. The investigation of specific passive cooling methods is an ongoing project; for example, a process is being studied in which heat-storage material would be cooled by radiation to the night sky, and would then provide ''coolness'' to the building. Laboratory personnel involved in the solar cooling, controls, and passive projects are also providing technical support to the Active Heating and Cooling Division and the Passive and Hybrid Division of DOE in developing program plans, evaluating proposals, and making technical reviews of projects at other institutions and in industry. Low-grade heat is a widespread energy resource that could make a significant contribution to energy needs if economical methods can be developed for converting it to useful work. Investigations continued this year on the feasibility of using the ''shape-memory'' alloy, Nitinol, as a basis for constructing heat engines that could operate from energy sources, such as solar-heated water, industrial waste heat, geothermal brines, and ocean thermal gradients. Several projects are investigating longer-term possibilities for utilizing solar energy. One project involves the development of a new type of solar thermal receiver that would be placed at the focus of a central receiver system or a parabolic dish. The conversion of the concentrated sunlight to thermal energy would be accomplished by the absorption of the light by a dispersion of very small particles suspended in a gas. Another project is exploring biological systems. In particular, we are investigating the possibility of developing a photovoltaic cell, based on a catalyst (bacteriorhodopsin) which converts light to electrical ion flow across the cell membrane of a particular bacteria

Comparison of regression models for estimation of isometric wrist joint torques using surface electromyography

Background: Several regression models have been proposed for estimation of isometric joint torque using surfaceelectromyography (SEMG) signals. Common issues related to torque estimation models are degradation of modelaccuracy with passage of time, electrode displacement, and alteration of limb posture. This work compares theperformance of the most commonly used regression models under these circumstances, in order to assistresearchers with identifying the most appropriate model for a specific biomedical application.Methods: Eleven healthy volunteers participated in this study. A custom-built rig, equipped with a torque sensor,was used to measure isometric torque as each volunteer flexed and extended his wrist. SEMG signals from eightforearm muscles, in addition to wrist joint torque data were gathered during the experiment. Additional data weregathered one hour and twenty-four hours following the completion of the first data gathering session, for thepurpose of evaluating the effects of passage of time and electrode displacement on accuracy of models. AcquiredSEMG signals were filtered, rectified, normalized and then fed to models for training.Results: It was shown that mean adjusted coefficient of determination (R2a) values decrease between 20%-35% fordifferent models after one hour while altering arm posture decreased mean R2avalues between 64% to 74% fordifferent models.Conclusions: Model estimation accuracy drops significantly with passage of time, electrode displacement, andalteration of limb posture. Therefore model retraining is crucial for preserving estimation accuracy. Data resamplingcan significantly reduce model training time without losing estimation accuracy. Among the models compared,ordinary least squares linear regression model (OLS) was shown to have high isometric torque estimation accuracycombined with very short training times