941 resultados para constrained front-haul
Resumo:
Conventional residential construction results in a variety of local, regional, and global environmental impacts. It also may lead to unhealthy interior environments for building inhabitants. Green building, on the contrary, is a practice that reduces the environmental impacts of residential development, that produces healthier indoor environments, and that yields better long-term financial investments. This Capstone Project applies empirical research and analysis to identify the history and benefits of green building, to support the hypothesis that Colorado Front Range communities benefit most from municipal green-build programs, and to make subsequent program recommendations. Ultimately, this project may assist communities with implementing their own municipal green-build programs.
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The five installations operated by the Department of Defense (DoD) in the Front Range region of Colorado do not meet the DoD non-hazardous solid waste diversion goal of 40 percent, further impacting landfills and generating greenhouse gases. This applied capstone project identifies and evaluates best management practices of a Materials Recovery Facility (MRF), qualitatively and quantitatively, to increase solid waste diversion at a DoD MRF. An environmental benefits model quantified the externalities of increasing solid waste diversion at the installations. By implementing best management practices at a MRF, the DoD would divert an additional 1,400 tons of solid waste per year, resulting in the equivalent of 1,502,567 gallons of gasoline being saved, among many benefits presented in this capstone.
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The Denver metropolitan area is facing rapid population growth that increases the stress on already limited resources. Research and advanced computer modeling show that trees, especially those in urban areas, have significant environmental benefits. These benefits include air quality improvements, energy savings, greenhouse gas reduction, and possible water conservation. This Capstone Project applies statistical methods to analyze a small data set of residential homes and their energy and water consumption, as a function of their individual landscape. Results indicate that tree shade can influence water conservation, and that irrigation methods can be an influential factor as well. The Capstone is a preliminary analysis for future study to be performed by the Institute for Environmental Solutions in 2007.
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This article continues the investigation of stationarity and regularity properties of infinite collections of sets in a Banach space started in Kruger and López (J. Optim. Theory Appl. 154(2), 2012), and is mainly focused on the application of the stationarity criteria to infinitely constrained optimization problems. We consider several settings of optimization problems which involve (explicitly or implicitly) infinite collections of sets and deduce for them necessary conditions characterizing stationarity in terms of dual space elements—normals and/or subdifferentials.
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The Huangtupo landslide is one of the largest in the Three Gorges region, China. The county-seat town of Badong, located on the south shore between the Xiling and Wu gorges of the Yangtze River, was moved to this unstable slope prior to the construction of the Three Gorges Project, since the new Three Gorges reservoir completely submerged the location of the old city. The instability of the slope is affecting the new town by causing residential safety problems. The Huangtupo landslide provides scientists an opportunity to understand landslide response to fluctuating river water level and heavy rainfall episodes, which is essential to decide upon appropriate remediation measures. Interferometric Synthetic Aperture Radar (InSAR) techniques provide a very useful tool for the study of superficial and spatially variable displacement phenomena. In this paper, three sets of radar data have been processed to investigate the Huangtupo landslide. Results show that maximum displacements are affecting the northwest zone of the slope corresponding to Riverside slumping mass I#. The other main landslide bodies (i.e. Riverside slumping mass II#, Substation landslide and Garden Spot landslide) exhibit a stable behaviour in agreement with in situ data, although some active areas have been recognized in the foot of the Substation landslide and Garden Spot landslide. InSAR has allowed us to study the kinematic behaviour of the landslide and to identify its active boundaries. Furthermore, the analysis of the InSAR displacement time-series has helped recognize the different displacement patterns on the slope and their relationships with various triggering factors. For those persistent scatterers, which exhibit long-term displacements, they can be decomposed into a creep model (controlled by geological conditions) and a superimposed recoverable term (dependent on external factors), which appears closely correlated with reservoir water level changes close to the river's edge. These results, combined with in situ data, provide a comprehensive analysis of the Huangtupo landslide, which is essential for its management.
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Frontó valencià: reglament, instal·lacions, materials de joc i tàctica
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In many classification problems, it is necessary to consider the specific location of an n-dimensional space from which features have been calculated. For example, considering the location of features extracted from specific areas of a two-dimensional space, as an image, could improve the understanding of a scene for a video surveillance system. In the same way, the same features extracted from different locations could mean different actions for a 3D HCI system. In this paper, we present a self-organizing feature map able to preserve the topology of locations of an n-dimensional space in which the vector of features have been extracted. The main contribution is to implicitly preserving the topology of the original space because considering the locations of the extracted features and their topology could ease the solution to certain problems. Specifically, the paper proposes the n-dimensional constrained self-organizing map preserving the input topology (nD-SOM-PINT). Features in adjacent areas of the n-dimensional space, used to extract the feature vectors, are explicitly in adjacent areas of the nD-SOM-PINT constraining the neural network structure and learning. As a study case, the neural network has been instantiate to represent and classify features as trajectories extracted from a sequence of images into a high level of semantic understanding. Experiments have been thoroughly carried out using the CAVIAR datasets (Corridor, Frontal and Inria) taken into account the global behaviour of an individual in order to validate the ability to preserve the topology of the two-dimensional space to obtain high-performance classification for trajectory classification in contrast of non-considering the location of features. Moreover, a brief example has been included to focus on validate the nD-SOM-PINT proposal in other domain than the individual trajectory. Results confirm the high accuracy of the nD-SOM-PINT outperforming previous methods aimed to classify the same datasets.
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Drawing by Charles Bulfinch of proposed plans for University Hall which were later rejected. Includes sketches of the front exterior view of the University Hall, and separate floor plans for the ground and second floors. Bulfinch designed a ground floor with a chapel and four dining halls each holding 100 students, a second floor with a gallery in the chapel and three rooms over the dining halls for public examinations and meetings of the Corporation and Overseers; and a basement under the halls intended for a kitchen under the dining halls and recitation rooms under the chapel.
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Pen and ink drawing by Charles Bulfinch of the proposed cupola of University Hall. Pencil drawing of interior of cupola on verso.
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This drawing includes the intricate stonework designed by Charles Bulfinch for University Hall. Each stone is numbered or lettered to indicate the exact stones needed for the project.
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Title supplied by cataloger.