The Impact of Data Imputation Methodologies on Knowledge Discovery

The purpose of this research is to investigate the impact of Data Imputation Methodologies that are employed when a specific Data Mining algorithm is utilized within a KDD (Knowledge Discovery in Databases) process. This study will employ certain Knowledge Discovery processes that are widely accepted in both the academic and commercial worlds. Several Knowledge Discovery models will be developed utilizing secondary data containing known correct values. Tests will be conducted on the secondary data both before and after storing data instances with known results and then identifying imprecise data values. One of the integral stages in the accomplishment of successful Knowledge Discovery is the Data Mining phase. The actual Data Mining process deals significantly with prediction, estimation, classification, pattern recognition and the development of association rules. Neural Networks are the most commonly selected tools for Data Mining classification and prediction. Neural Networks employ various types of Transfer Functions when outputting data. The most commonly employed Transfer Function is the s-Sigmoid Function. Various Knowledge Discovery Models from various research and business disciplines were tested using this framework. However, missing and inconsistent data has been pervasive problems in the history of data analysis since the origin of data collection. Due to advancements in the capacities of data storage and the proliferation of computer software, more historical data is being collected and analyzed today than ever before. The issue of missing data must be addressed, since ignoring this problem can introduce bias into the models being evaluated and lead to inaccurate data mining conclusions. The objective of this research is to address the impact of Missing Data and Data Imputation on the Data Mining phase of Knowledge Discovery when Neural Networks are utilized when employing an s-Sigmoid Transfer function, and are confronted with Missing Data and Data Imputation methodologie

The Impact of Data Imputation Methodologies on Knowledge Discovery

The purpose of this research is to investigate the impact of Data Imputation Methodologies that are employed when a specific Data Mining algorithm is utilized within a KDD (Knowledge Discovery in Databases) process. This study will employ certain Knowledge Discovery processes that are widely accepted in both the academic and commercial worlds. Several Knowledge Discovery models will be developed utilizing secondary data containing known correct values. Tests will be conducted on the secondary data both before and after storing data instances with known results and then identifying imprecise data values. One of the integral stages in the accomplishment of successful Knowledge Discovery is the Data Mining phase. The actual Data Mining process deals significantly with prediction, estimation, classification, pattern recognition and the development of association rules. Neural Networks are the most commonly selected tools for Data Mining classification and prediction. Neural Networks employ various types of Transfer Functions when outputting data. The most commonly employed Transfer Function is the s-Sigmoid Function. Various Knowledge Discovery Models from various research and business disciplines were tested using this framework. However, missing and inconsistent data has been pervasive problems in the history of data analysis since the origin of data collection. Due to advancements in the capacities of data storage and the proliferation of computer software, more historical data is being collected and analyzed today than ever before. The issue of missing data must be addressed, since ignoring this problem can introduce bias into the models being evaluated and lead to inaccurate data mining conclusions. The objective of this research is to address the impact of Missing Data and Data Imputation on the Data Mining phase of Knowledge Discovery when Neural Networks are utilized when employing an s-Sigmoid Transfer function, and are confronted with Missing Data and Data Imputation methodologie

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http://archive.org/details/performanceindic00prigNAN

Wind and water work

The following series of kinetic works was designed to use moving air (wind) and moving water as power sources and to establish limits of control over them, ranging from programmed movement to random movement. Balance is naturally a crucial factor in all of these pieces as they each make use of one or more counterweight systems to assure a reaction from the piece to the action of the particular power source. "Wind Piece #1" was designed to operate with even the slightest breeze. This was accomplished by using light materials (wood and sheet steel) and applying some of the basic laws of physics in its design, namely the ones covering the moment of the force. Thus when a light breeze engages the blade, the movable portion of the piece, it is easily set into motion as the force of the breeze, is multiplied many times by the long perpendicular distance from the top of the blade to the axis. This piece utilizes the knife type pivot which is virtually friction-proof, but at the same time limiting as to the amount of swing possible. In this case it is less than 100 degrees

Resolving a paradox—high mercury deposition, but low bioaccumulation in northeastern Puerto Rico

At a “clean air” trade winds site in northeastern Puerto Rico, we found an apparent paradox: atmospheric total mercury (THg) deposition was highest of any site in the USA Mercury Deposition Network, but assimilation into the local food web was quite low. Avian blood THg concentrations (n = 31, from eight species in five foraging guilds) ranged widely from 0.2 to 32 ng g−1 (median of 4.3 ng g−1). Within this population, THg was significantly greater at a low-elevation site near a wetland compared to an upland montane site, even when the comparison was limited to a single species. Overall, however, THg concentrations were approximately an order of magnitude lower than comparable populations in the continental U.S. In surface soil and sediment, potential rates of demethylation were 3 to 9-fold greater than those for Hg(II)-methylation (based on six radiotracer amendment incubations), but rates of change of ambient MeHg pools showed a slight net positive Hg(II)-methylation. Thus, the resolution of the paradox is that MeHg degradation approximately keeps pace with MeHg production in this landscape. Further, any net production of MeHg is subject to frequent flushing by high rainfall on chronically wet soils. The interplay of these microbial processes and hydrology appears to shield the local food web from adverse effects of high atmospheric mercury loading. This scenario may play out in other humid tropical ecosystems as well, but it is difficult to evaluate because coordinated studies of Hg deposition, methylation, and trophic uptake have not been conducted at other tropical sites

Representations of Utopian Urbanism and the Feminist Geopolitics of ‘New City’ Development

Increasingly over the past few years the building of new cities “from scratch” has become a key strategy to promote development across much of the Global South. While several projects are currently under construction, many others exist primarily as proposals awaiting adequate investment or government action. This paper builds on previous literature that considers representations of such projects – promotional materials, digitally-produced video simulations, and master plans – as key components in the production of imagined urban futures. Through an exploration of the proposed Zone for Economic Development and Employment (ZEDE) in Honduras, this article demonstrates a feminist geopolitical approach focused on how such representations of utopian urbanism circulate through the local communities slated for new city development. I examine how representations of future urban spaces and future urban governance regimes become appropriated by local residents in organizing opposition or otherwise making sense of the proposed project’s potential impact on their lives.12 month embargo; published online: 30 Dec 2018This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Mercury in Nelson's Sparrow Subspecies at Breeding Sites

Background: Mercury is a persistent, biomagnifying contaminant that can cause negative effects on ecosystems. Marshes are often areas of relatively high mercury methylation and bioaccumulation. Nelson’s Sparrows (Ammodramus nelsoni) use marsh habitats year-round and have been documented to exhibit tissue mercury concentrations that exceed negative effects thresholds. We sought to further characterize the potential risk of Nelson’s Sparrows to mercury exposure by sampling individuals from sites within the range of each of its subspecies

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

The social meaning of social indicators

While new modes of data processing have provided reams of data, there has been relatively less effort in seeking to comprehend the social meaning of results of empirical work. A set of previously developed indicators of urban social structure is here examined for its link to theory, and to the social structure of the city itself. The original indicators (size, social class, racial composition and community maturity) were empirically derived. In this paper, each is taken in turn, and explored with respect to several possible social meanings. Size, for example, is considered to be itself an indicator, and an imperfect one, for system complexity; percent non-white is seen to be itself an indicator for a slowdown in the mobility process, or a slower social metabolism. These and other results are suggestions, with illustrations, but not conclusive support, from other than the original data. While it is hoped that the theoretical suggestions may themselves be of interest, it is also hoped that approach itself can indicate the fertility and usefulness of going back to theory once empirical measures have been developed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43687/1/11205_2004_Article_BF00304121.pd