Erosion of a river bed has important implications with respect to scour around river structures such as bridges, transport of contaminants attached to the sediment, and disruption or destruction of aquatic habitats. Erosion occurs when the resistive strength of the sediment is overcome by the hydrodynamic forces produced by the flow of water. This resistance to erosion in a sediment originates from gravity or interparticle forces for coarse sediment (sand and gravel) and fine sediment (silt and clay), respectively. Since the erosion of fine sediment depends on the combination of many interparticle forces, and this combination fluctuates widely amongst different fine sediments, past studies have had difficulty finding a consistent method to estimate fine sediment erosion. This study analyzes sediments that fall in the transition size range between fine and coarse sediments and compares the findings with those from fine sediments (Wang 2013) and sandy coarse sediments (Navarro 2004, Hobson 2008), in order to correlate the erosion rates of both sediment types to their physical characteristics. In this study, kaolin-sand mixtures were prepared by mixing various percentages of Georgia kaolin by weight ranging from 30% to 100% with industrial fine sand and tap water. Geotechnical and other tests of sediment properties were performed to measure water content, bulk density, grain size distribution, temperature, pH, and conductivity of these mixtures. Hydraulic flume experiments measured the erosion rates of each sediment and these rates were used to estimate the critical shear stress correlating to that mixture. Relationships between the physical properties of the sediment and critical shear stress were developed by multiple regression analysis. An alternative option of estimating the critical shear stress by a weighted equation, which uses the combination of fine sediment erosion and coarse sediment erosion equations separately, was explored and found to be a viable and accurate option to estimating both coarse and fine sediment erosion from the same parameters and equation. The results from this study can be used to estimate sediment erodibility and thus river bed stability based on simple tests of physical properties of the river bed sediment and will help predict scour around bridges and other flow obstructions.

Sediment transport at the watershed scale in the Bluegrass Region of Kentucky is dominated by surface fine grained laminae, streambed, and streambank erosion; high instream sediment storage; and surface erosion processes. All these processes can be impacted by agricultural, urban, and suburban land-uses as well as hydrologic forcing. Understanding sediment transport processes at the watershed scale is a need for budgeting and controlling sediment pollution, and watershed modeling enables investigation of the cumulative effect of sediment processes and the parameters controlling these processes upon the entire sediment budget for a watershed. Sediment transport is being modeled by coupling the hydrologic model Hydrologic Simulations Program-FORTRAN (HSPF) with an in-house conceptually based hydraulic and sediment transport model. The total yield at the watershed outlet as well as the source fractions from surface fine grained lamina, streambed, and streambank sources; deposition; and biological generation within the streambed are predicted with the sediment transport model. Urbanization scenarios are then run on the calibrated model so as to predict the sediment budget for the South Elkhorn watershed for present and future conditions.

Fine-grained access control is a conceptual approach to addressing database security requirements. In relational database management systems, fine-grained access control refers to access restrictions enforced at the row, column, or cell level. While a number of commercial implementations of database fine-grained access control are available, there are presently no generalized approaches to implementing fine-grained access control for relational database management systems. Fine-grained access control is potentially a good solution for database professionals and system architects charged with designing database applications that implement granular security or privacy protection features. However, in the oral tradition of the database community, fine-grained access control is spoken of as imposing significant performance penalties, and is therefore best avoided. Regardless, there are current and emerging social, legal, and economic forces that mandate the need for efficient fine-grained access control in relational database management systems. In the study undertaken, the author was able to quantify the performance costs associated with four common implementations of fine-grained access control for relational database management systems. Security benchmarking was employed as the methodology to quantify performance costs. Synthetic data from the TPC-W benchmark as well as representative data from a real-world application were utilized in the benchmarking process. A simple graph-base performance model for Fine-grained Access Control Evaluation (FACE) was developed from benchmark data collected during the study. The FACE model is intended for use in predicting throughput and response times for relational database management systems that implement fine-grained access control using one of the common fine-grained access control mechanisms - authorization views, the Hippocratic Database, label-based access control, and transparent query rewrite. The author also addresses the issue of scalability for fine-grained access control mechanisms that were evaluated in the study.

"Secondary teachers across the United States are being asked to use formative assessment data to inform their classroom instruction. At the same time, critics of US government’s No Child Left Behind legislation are calling the bill “No Child Left Untested”. Among other things, critics point out that every hour spent assessing students is an hour lost from instruction. But, does it have to be? What if we better integrated assessment into classroom instruction and allowed students to learn during the test? This dissertation emphasizes using the intelligent tutoring system as an assessment system that just so happens to provide instructional assistance during the test. Usually it is believed that assessment get harder if students are allowed to learn during the test, as it’s then like trying to hit a moving target. So, my results are somewhat shocking that by providing tutoring to students while they are assessed I actually improve the assessment of students’ knowledge. Most traditional assessments treat all questions on the test as sampling a single underlying knowledge component. Yet, teachers want detailed, diagnostic reports to inform their instruction. Can we have our cake and eat it, too? In this dissertation, I provide solid evidence that a fine-grained skill model is able to predict state test scores better than coarser-rained models, as well as being used to give teachers more informative feedback that they can reflect on to improve their instruction. The contribution of the dissertation lies in that it established novel assessment methods to better assess students in intelligent tutoring systems. Through analyzing data of more than 1,000 students across two years, it provides strong evidence implying that it is possible to develop a continuous assessment system that can do all three of these things at the same time: 1) accurately and longitudinally assesses students, 2) gives fine grained feedback that is more cognitively diagnostic, and 3) saves classroom instruction time by assessing students while they are getting tutoring. "

Recent ground failure case histories after 1994 Northridge, 1999 Kocaeli and 1999 Chi-Chi earthquakes revealed that low-plasticity silt-clay mixtures generate significant cyclic pore pressures and can exhibit a strain-softening response, which may cause significant damage to overlying structural systems. These observations accelerated research studies on liquefaction susceptibility of fine-grained soils. Alternative approaches to Chinese Criteria were proposed by several researchers (Seed et al. 2003, Bray and Sancio 2006, Boulanger and Idriss 2006) most of which assess liquefaction triggering potential based on cyclic test results compared on the basis of index properties of soils (such as LL, PI, LI, wc/LL). Although these new methodologies are judged to be major improvements over Chinese Criteria, still there exist unclear issues regarding if and how reliably these methods can be used for the assessment of liquefaction triggering potential of fine grained soils. In this study, results of cyclic tests performed on undisturbed specimens (ML, CL, MH and CH) were used to study cyclic shear strain and excess pore water pressure generation response of fine-grained soils. Based on comparisons with the cyclic response of saturated clean sands, a shift in pore pressure ratio (ru) vs. shear strain response is observed, which is identified to be a function of PI, LL and (wc/LL). Within the confines of this study, i) probabilistically based boundary curves identifying liquefaction triggering potential in the ru vs. shear strain domain were proposed as a function of PI, LL and (wc/LL), ii) these boundaries were then mapped on to the normalized net tip resistance (qt,1,net) vs. friction ratio (FR) domain, consistent with the work of Cetin and Ozan (2009). The proposed framework enabled both Atterberg limits and CPT based assessment of liquefaction triggering potential of fine grained low plasticity soils, differentiating clearly both cyclic mobility and liquefaction responses.

The move into deeper waters in the Gulf of Mexico has produced new opportunities for petroleum production, but it also has produced new challenges as different reservoir problems are encountered. This integrated reservoir characterization effort has provided useful information about the behavior and characteristics of a typical unconsolidated, overpressured, fine-grained, turbidite reservoir, which constitutes the majority of the reservoirs present in the Outer Continental Shelf of the Gulf of Mexico. Reservoirs in the Green Canyon 18 (GC 18) field constitute part of a turbidite package with reservoir quality typically increasing with depth. Characterization of the relatively shallow 8 reservoir had hitherto been hindered by the difficulty in resolving its complex architecture and stratigraphy. Furthermore, the combination of its unconsolidated rock matrix and abnormal pore pressure has resulted in severe production-induced compaction. The reservoir's complex geology had previously obfuscated the delineation of its hydrocarbon accumulation and determination of its different resource volumes. Geological and architectural alterations caused by post-accumulation salt tectonic activities had previously undermined the determination of the reservoir's active drive mechanisms and their chronology. Seismic interpretation has provided the reservoir geometry and topography. The reservoir stratigraphy has been defined using log, core and seismic data. With well data as pilot points, the spatial distribution of the reservoir properties has been defined using geostatistics. The resulting geological model was used to construct a dynamic flow model that matched historical production and pressure data.. The reservoir's pressure and production behavior indicates a dominant compaction drive mechanism. The results of this work show that the reservoir performance is influenced not only by the available drive energy, but also by the spatial distribution of the different facies relative to well locations. The study has delineated the hydrocarbon bearing reservoir, quantified the different resource categories as STOIIP/GIIP = 19.8/26.2 mmstb/Bscf, ultimate recovery = 9.92/16.01 mmstb/Bscf, and reserves (as of 9/2001) = 1.74/5.99 mmstb/Bscf of oil and gas, respectively. There does not appear to be significant benefit to infill drilling or enhanced recovery operations.

This dissertation investigated the impact of the Surficial Fine-Grained Laminae (SFGL) upon stream biogeochemical cycles to constrain stream C and N budgets. Collection and analysis of 8 years of transported sediment elemental and isotopic signatures, weekly, from a SFGL dominated stream, a novel dissolved C and N dataset, statistical and time-series analysis of sediment and dissolved data, and development of a comprehensive modeling framework that couples hydrodynamics, sediment, C and N biogeochemistry, and stable isotope sub-models to simulate fluvial C and N budgets was used. SFGL C modeling suggests benthic particulate C stocks and transport vary seasonally and annually but are in a state of long-term equilibrium which is governed by negative feedback mechanisms whereby high POC export due to extreme hydrologic events and high frequency hydrologic events reduces benthic particulate C stocks and inhibits benthic particulate C growth. Model distribution fitting suggests transported particulate C in SFGL streams is Gamma distributed; in which statistical moments are governed by variability of the SFGL. Stable isotope un-mixing of the bed source suggests that the SFGL has varying levels of carbon quality seasonally and annually, in which non-equilibrium conditions stem from extreme depositional events. Coupling stable isotope mass balance and SFGL fractionation processes into water quality modeling frameworks, reduced uncertainty of the C budget by nearly 60%, suggesting algal sloughing constitutes nearly 40% of the total organic C budget, shifting the balance from dissolved C to particulate C dominated. Time series analysis of the eight year dataset suggest nitrogen dynamics in the SFGL dominated stream were consistent with existing conceptual models when algal biomass is the prominent organic matter source in the SFGL, but contradicts conventional wisdom in winter through late spring when abiotic sorption appears prominent. The development of a new numerical model to simulate the fluvial N budget couples this new conceptual model of SFGL stream N dynamics to isotope mass-balances and C dynamics in order to provide a comprehensive management tool for restoration engineers. Meta-analysis and upscaling of results for regional to global scales will enable researchers to place the role of the SFGL in a broader context.

Small lowland agricultural systems promote conditions where benthic biological communities can thrive. These biogeochemical processes have significant impacts on terrestrial ecosystem processes including POC flux and fate, nutrient balances, water quality budges, and aquatic biological functioning. Limited information is available on coupled biological and hydrologic processes in fluvial systems. This study investigates the mixture of biological and hydrologic processes in the benthic layer in order to understand POC cycling in the South Elkhorn system. Further, comprehensive modeling of POC flux in lowland systems has not been performed previously and the behavior of potentially controlling variables, such as hydrologic forcing and seasonal temperature regimes, is not well understood. Conceptual hydraulic and sediment transport models were simulated for the South Elkhorn. Based on data and model results it was concluded that during a hydrologic event, upland and bank sources produce high variability of POC sources. Likewise, over time, the density of hydrologic events influenced accrual of benthic algal biomass in the POC pool. Environmental variables such as temperature and light availability drove seasonal variations of POC in the streambed. Based on model estimates, around 0.29 metric tCkm-2yr-1 of POC is flushed from the system annually with 13 % coming from autochthonous algae.

Background: Traditionally text mention normalization corpora have normalized concepts to single ontology identifiers ("pre-coordinated concepts"). Less frequently, normalization corpora have used concepts with multiple identifiers ("post-coordinated concepts") but the additional identifiers have been restricted to a defined set of relationships to the core concept. This approach limits the ability of the normalization process to express semantic meaning. We generated a freely available corpus using post-coordinated concepts without a defined set of relationships that we term "compositional concepts" to evaluate their use in clinical text. Methods: We annotated 5397 disorder mentions from the ShARe corpus to SNOMED CT that were previously normalized as "CUI-less" in the "SemEval-2015 Task 14" shared task because they lacked a pre-coordinated mapping. Unlike the previous normalization method, we do not restrict concept mappings to a particular set of the Unified Medical Language System (UMLS) semantic types and allow normalization to occur to multiple UMLS Concept Unique Identifiers (CUIs). We computed annotator agreement and assessed semantic coverage with this method. Results: We generated the largest clinical text normalization corpus to date with mappings to multiple identifiers and made it freely available. All but 8 of the 5397 disorder mentions were normalized using this methodology. Annotator agreement ranged from 52.4% using the strictest metric (exact matching) to 78.2% using a hierarchical agreement that measures the overlap of shared ancestral nodes. Conclusion: Our results provide evidence that compositional concepts can increase semantic coverage in clinical text. To our knowledge we provide the first freely available corpus of compositional concept annotation in clinical text.

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