Miracle-dz/UniFAR-FTUs huggingface dataset:
HANFORD RIVER PROTECTION PROJECT ENHANCED MISSION PLANNING THROUGH INNOVATIVE TOOLS LIFECYCLE COST MODELING AND AQUEOUS THERMODYNAMIC MODELING - 12134

Two notable modeling efforts within the Hanford Tank Waste Operations Simulator (HTWOS) are currently underway to (1) increase the robustness of the underlying chemistry approximations through the development and implementation of an aqueous thermodynamic model, and (2) add enhanced planning capabilities to the HTWOS model through development and incorporation of the lifecycle cost model (LCM). Since even seemingly small changes in apparent waste composition or treatment parameters can result in large changes in quantities of high-level waste (HLW) and low-activity waste (LAW) glass, mission duration or lifecycle cost, a solubility model that more accurately depicts the phases and concentrations of constituents in tank waste is required. The LCM enables evaluation of the interactions of proposed changes on lifecycle mission costs, which is critical for decision makers. The RPP System Plan (1) provides the basis for the alignment of program costs, scope, and schedules from upper-tier contracts to individual operating plans. Updates are made to the RPP System Plan to reflect recent progress, current plans, responses to emergent issues, changes in the regulatory environment, and budgeting constraints. The Hanford Tank Waste Operations Simulator (HTWOS) is the foundation of the RPP system planning process, providing a model that integrates technical parameters with programmatic planning considerations. The HTWOS is a dynamic flowsheet simulator and mass balance model that calculates the flow of both discrete and continuous events occurring during the storage, retrieval, supplemental treatment, pretreatment, and vitrification of Hanford tank waste. By simulating the overall RPP mission, the HTWOS can forecast outcomes of changes to the baseline assumptions, and the sensitivities to alternative retrieval and waste staging strategies, new proposed technologies, and changes to the assumed dates of facility availabilities. The results of HTWOS runs include projections for key mission metrics such as quantities of HLW and LAW glass canisters, total sodium requirements of the system, and dates for completion of retrieval and treatment milestones. These metrics are used in mission analysis applications and are included for the scenarios evaluated in system planning to help guide decisions on how to manage the overall project. Any changes or upgrades made to the HTWOS model that improve the accuracy of the underlying assumptions add fidelity to the model projections, thereby improving its ability to support mission planning. Likewise, any further development to the model that increases the number and kinds of outputs generated provides a broader basis for scenario analysis and gives decision makers a more complete view of mission impacts.
Stationary Transfer Component Analysis for Brain Computer Interfacing

Motion intention can be detected from human Electroencephalography (EEG) signals through BCI, which can facilitate motor motion control for disabled or paralyzed people. However, the continuous use of BCI is hindered by the non-stationarity of the EEG signals. This paper proposes a method to identify the EEG signal components that can be used to train a classifier to address the non-stationarity issue. The proposed method is based on Transfer Component Analysis (TCA). TCA seeks to locate components that can be transferred across domains in a Reproducing Kernel Hilbert Space (RKHS). The distributions associated with data are closer to each other in the subspaces spanned by the identified transfer components. Therefore, typical machine learning techniques can be applied in the subspace spanned by these transfer components. This results in classifiers that can be trained on the source domain and tested on the target domain. The proposed Stationary Transfer Component Analysis (STCA) method is compared with Stationary Sub-space Analysis (SSA) on the BCI competition IV dataset 2a. The results show significant improvements over the baseline case and the results are better than those produced by SSA.
TO IDENTIFY AND EXTRACT INDEPENDENT COMPONENTS FROM AN AUDITORY SCENE By

of a Master’s Research Project at the University of Miami Research project supervised by Professor Ken Pohlmann Number of pages in text: 71 The cocktail party effect, our ability to separate a sound source from a multitude of other sources, has been researched in detail over the past few decades, and many investigators have tried to model this on computers. Two of the major research areas currently being evaluated for the so-called sound source separation problem are Auditory Scene Analysis (Bregman 1990) and a class of statistical analysis techniques known as Independent Component Analysis (Hyvärinen 2001). This paper presents a methodology for combining these two techniques. It suggests a framework that first separates sounds by analyzing the incoming audio for patterns and synthesizing or filtering them accordingly, measures features of the resulting tracks, and finally separates sounds statistically by matching feature sets and making the output streams statistically independent. Artificial and acoustical mixes of sounds are used to evaluate the signal-tonoise ratio where the signal is the desired source and the noise is comprised of all other sources. The proposed system is found to successfully separate audio streams. The amount of separation is inversely proportional to the amount of reverberation present.
S TUDY OF D ATA M INING T ECHNOLOGY IN A IRCRAFT S YSTEM TO PREDICT FAILURE

In this paper the main theme of this paper is to apply Data Mining technology to find out the accurate assessment of the probability of failure of any avionics unit utilizing the known history of abuse from environmental and operational factors. The data contains environmental and operational conditions of a particular avionics unit. For prediction purpose, modern data mining approach is used. In this approach first of all prognostic model is designed using 2 techniques. Clustering is used to select the most informative subspaces and to separate the failure and no failure clusters. After this decision tree is made in parallel whose each node represents the projection of clusters on different subspaces. An interactive line drawing method is designed to separate the clusters. On the basis of this model prediction can be done for the new monitored data and detects whether the system is going to fail and one can take corrective measures. The system developed gives the good classification accuracy as compare to others if the number of records is more during training.
Natural prefabricated vertical drains-structure and geo-hydraulic properties

Over the past decades synthetic prefabricated vertical drains (SPVDs) have been used in many regions around the world to accelerate the consolidation of soil, but because these synthetic polymeric materials last for decades, they are now seen as having adverse effects on the natural environment. Natural prefabricated vertical drains (NPVDs) on the other hand, which are made from agriculture products such as jute, coir, and straw can discharge excess pore pressure effectively and they are also environmentally friendly thanks to their biodegradability. This paper outlines the fundamental characteristics of prefabricated vertical jute drains (PVJDs) such as their structure, tensile strength, and discharge capacity, because they are currently considered to be one of the most common types of NPVDs. Disciplines Engineering | Science and Technology Studies Publication Details Nguyen, T. T. , Indraratna, B. & Rujikiatkamjorn, C. (2016). Natural prefabricated vertical drains-structure and geo-hydraulic properties. In P. Long (Ed.), Geotechnics for Sustainable Infrastructure Development Geotec Hanoi 2016 (pp. 651-658). Vietnam: Construction Publishing House. This conference paper is available at Research Online: https://ro.uow. edu.au/eispapers1/1562 Geotechnics for Sustainable Infrastructure Development Geotec Hanoi 2016, Phung (edt). ISBN 978-604-82-0013-8 1
Global and Local Motion Priors and their Applications by

With the rising popularity and accessibility of cameras as well as the arrival of popular video sharing websites like YouTube.com, Google Video, veoh.com, and many others, large quantities of video are produced and available everyday. With all this data, it becomes necessary to find ways of understanding the content of videos in large data sets for applications in areas like multimedia management, video surveillance, and many others. At the same time, all this amount of information produced everyday can be used for solving problems that can be difficult without a large amount of training data such as scene matching and alignment. This work studies motion properties across different sources of video. Both the global motion (also known as the camera motion) and the local motion are studied, to extract common properties of similar video sequences. As a consequence, several applications using these types of information arise. In the case of global motion, an application for clustering videos based on their genre is examined. For the local motion, this work describes a way to use a database of flow fields together with matching and alignment techniques for inferring an optical flow field from a single image (as opposed to the standard problem of motion estimation using two adjacent video frames) as well as synthesizing video also from a single image. Thesis Supervisor: W. Eric Grimson Title: Bernard Gordon Professor of Medical Engineering Thesis Supervisor: Antonio Torralba Title: Assistant Professor
Genetic diversity among farmer-preferred cassava landraces in Uganda.

Understanding of genetic diversity among a breeding population is an important requirement for crop improvement as it allows for the selection of diverse parental combinations and formation of heterotic pools for genetic gain. This study was carried out to determine genetic diversity within and among 51 farmer-preferred cassava ( Manihot esculenta ) landraces and 15 elite accessions grown in Uganda. Twenty six simple sequence repeat (SSR) markers used for genetic diversity assessment in this study revealed a total of 154 alleles, of which 24% were unique alleles present only in landraces. The genetic diversity and observed herozygosity in landraces were slightly higher than in elite accessions. Elite accessions clustered with some of the landraces indicating that there were some alleles in common. However, 58.8% of the landraces fell into 3 different clusters independent of the elite accessions. Including these landraces with unique alleles in cassava breeding schemes will increase the chances of producing farmer preferred adapted elite cultivars. The study also revealed genetic differentiation among accessions from different regions providing an opportunity for establishment of heterotic pools within a breeding programme. Keywords: Alleles, Manihot esculenta, SSR markers African Crop Science Journal , Vol. 20, Issue Supplement s1, pp. 15 - 30
Integral boundary layer heat transfer prediction on turbine blades

Integral Boundary Layer Heat Transfer Prediction on Turbine Blades by William James Steptoe Submitted to the department of Aeronautics and Astronautics on September 25, 1989 in partial fulfillment of the requirements for the degree of Master of Science in Aeronautics and Astronautics An integral method for predicting heat transfer and losses in the boundary layer of a two dimensional airfoil is developed. Losses and heat transfer are measured by the momentum thickness and enthalpy thickness respectively. These integral parameters are calculated by the forward integration of three simultaneous differential equations using closure relations developed from the Falkner-Skan wedge flows. Local heat transfer measurements are obtained from a new empirical integral formula developed from finite difference solutions. Comparison with finite difference solutions is good. Comparison with experiments is as good as finite difference prediction for the same flows. Further development should lead to integration into an integral boundary layer airfoil analysis and design tool and hence the ability to analyse and design non-adiabatic airfoils such as those in an axial flow turbine. Thesis Supervisor: Dr. Alan Epstein Title: Associate Professor of Aeronautics and Astronautics
Generated using version 3 . 0 of the official AMS L A TEX template The CCSM 4 Ocean Component

The ocean component of the Community Climate System Model version 4 (CCSM4) is described and its solutions from the 20th Century (20C) simulations are documented in comparison with observations and those of CCSM3. The improvements to the ocean model physical processes include new parameterizations to represent previously missing physics and modifications of existing parameterizations to incorporate recent new developments. In comparison with CCSM3, the new solutions show some significant improvements that can be attributed to ocean model improvements. These include a better equatorial current structure, a sharper thermocline, and elimination of the cold bias of the equatorial cold tongue all in the Pacific Ocean; reduced sea surface temperature (SST) and salinity biases along the North Atlantic Current path; and much smaller potential temperature and salinity biases in the near-surface Pacific Ocean. Other improvements include significant reductions in the excessive chlorofluorocarbon (CFC-11) uptake in the Southern Ocean, reduced surface salinity biases at low latitudes resulting from improved precipitation in these regions, and a global-mean SST that is more consistent with the present-day observations due to a different spin-up procedure from that used in CCSM3. Despite these improvements, many of the biases present in CCSM3 still exist in CCSM4. Some examples are warm SST biases in the upwelling regions off the west coasts of North and South America and South Africa and excessive CFC-11 uptake in the northern North Atlantic. A major concern continues to be the substantial heat content loss in the ocean during the pre-industrial control simulation from which the 20C cases start. This heat loss largely reflects the top of the atmospheric model heat loss rate in the coupled system and it essentially determines the abyssal ocean potential temperature biases in the 20C simulations. There is also a deep salty bias in all
Energy lowering of current-carrying single-particle states in open-shell atoms due to an exchange-correlation vector potential

Current density functional theory is used to calculate perturbatively the single-particle energies of open-shell atoms prepared in a current-carrying state. We focus on the highest occupied such energy, because its negative is, in principle, the exact ionization energy. A variety of different density functionals and calculational schemes are compared with each other and with experiment. When the atom is prepared in a current-carrying state, a current-dependent exchange-correlation functional is found to slightly lower the single-particle energy of the current-carrying orbital, as compared with a calculation using standard (current independent) density functionals for the same system. The current-dependent terms in the exchange-correlation functional thus provide additional stabilization of the current-carrying state. © 2005 Wiley Periodicals, Inc. Int J Quantum Chem, 2005
Review on Fuzzy Approach to Sentence Level Text Clustering

Clustering plays vital role in Information retrieval and text mining. The amount of stored data is increasing day by day. In order to make it useful text clustering can be applied. Text clustering has important applications to classify documents, to organize the data and to retrieve useful information from it. Clustering is roughly classified in to two types i.e. hard clustering and soft clustering. In hard clustering data point belongs to exactly one cluster where as in soft clustering data point can belongs to more than one cluster with degree of membership associated with it. Soft or fuzzy clustering technique is useful in sentence clustering as sentence is related to more than one topic within a document. Due to this fuzzy relational clustering algorithm is used for sentence clustering.
Identification of a nonlinear model in syntheticmicrobial systems

To well understand the mechanism of microbial behavior, mathematic models of microbial systems have become a key issue. In particular, it is important for complex microbial systems. Currently, in complex synthetic microbial systems, block oriented nonlinear model can be widely used to represent and approximate many real complex processes. In this paper, the parameter estimation approach for the Hammerstein model is investigated. The basic idea is as follows. Firstly, the nonlinear transfer function of the model can be converted to an intermediate model. Secondly, the estimates of the parameters of the intermediate model are found by using an improved fish swarm optimization algorithm. Thirdly, the relations of the parameters of the intermediate model and those of the Hammerstein model are established. Then, the estimates of the parameters of the Hammerstein model are obtained. Finally, in simulation experiment, compared with other methods, the simulation results show the effectiveness of the proposed algorithm.
EXCLUDING HERBIVORES FROM RUSSIAN TUNDRA 134 We focused on three habitat types : Willow Meadows , Forb Tundra , and Mesic Tundra

Plant-herbivore relationships are important for the functioning of tundra ecosystems. Here, we report the first results from an exclosure experiment that, something very few studies have done, separated the impact of three sizes of herbivores (small, medium and large) on nine functional groups of plants in the low arctic tundra of the Yamal Peninsula (Russia). Herbivore faeces counts in the exclosures and pictures from automatic cameras proved that the experimental setup worked. The majority of plant groups did not respond to exclusion of herbivores, supporting our expectation that vegetation responses in tundra are generally too slow to be measured during one growing season. The plant groups with highest growth rates and palatability (forbs and grasses) increased their biomass in meadows associated to tall willow shrubs when reindeer were excluded. This result was expected based on studies from other arctic regions. Our results also suggested that willow meadows and forb tundra, which are focal habitat for herbivores, are resilient and have the capacity to increase their biomass over a short term. We expect this experiment to provide valuable information on how different plant functional types and habitats with different growing conditions and importance to herbivores respond to relaxed grazing pressure from a variety of tundra herbivores.
What Others Say About This Work ? Scalable Extraction of Citation Contexts from Research Papers Journal Item

This work presents a new, scalable solution to the problem of extracting citation contexts: the textual fragments surrounding citation references. These citation contexts can be used to navigate digital libraries of research papers to help users in deciding what to read. We have developed a prototype system which can retrieve, on-demand, citation contexts from the full text of over 15 million research articles in the Mendeley catalog for a given reference research paper. The evaluation results show that our citation extraction system provides additional functionality over existing tools, has two orders of magnitude faster runtime performance, while providing a 9% improvement in F-measure over the current state-of-the-art.
Development of Spiritual Orientation Scale: The Study Of Validity and

The objective of the study is to develop a Spiritual Orientation Scale, which is to be utilized to evaluate spiritual orientation of individuals. 872 university students (492 females and 380 males) participated in the study to develop the scale. Exploratory and confirmatory factor analyses were conducted to test the structural validity of the spiritual orientation scale. It was determined that the scale was consisted of one factor that explained 47.59 % of the total variance, and the fit indices of the model represented by one dimension were χ2=239.718, sd=100, p= . 000, χ2/ sd= 2.39, RMSEA=0.06, RMR= 0.05, GFI=0.93, AGFI=0.90, CFI=0.95, IFI=0.95, NFI=0.92. Thus, a 7 point Likert-type scale with 16 items was created. 277 university students (172 females and 105 males) participated in content validity and reliability studies for the scale. Similar scales validity, correlation was found as r = . 57 p< . 01. Reliability of the scale was assessed using two methods: The first was Cronbach alpha coefficient (Alpha = .87); and the second was test-retest reliability coefficient (r = .84). These findings demonstrated that the scale was a valid and reliable measurement tool.
BINARY NEUTRON STARS IN QUASI-EQUILIBRIUM

Quasi-equilibrium sequences of binary neutron stars are constructed for a variety of equations of state in general relativity. Einstein's constraint equations in the Isenberg–Wilson–Mathews approximation are solved together with the relativistic equations of hydrostationary equilibrium under the assumption of irrotational flow. We focus on unequal-mass sequences as well as equal-mass sequences, and compare those results. We investigate the behavior of the binding energy and total angular momentum along a quasi-equilibrium sequence, the endpoint of sequences, and the orbital angular velocity as a function of time, changing the mass ratio, the total mass of the binary system, and the equation of state of a neutron star. It is found that the orbital angular velocity at the mass-shedding limit can be determined by an empirical formula derived from an analytic estimation. We also provide tables for 160 sequences, which will be useful as a guideline of numerical simulations for the inspiral and merger performed in the near future.
Tensor microwave anisotropies from a stochastic magnetic field

We derive an expression for the angular power spectrum of cosmic microwave background anisotropies due to gravity waves generated by a stochastic magnetic field and compare the result with current observations; we take into account the non-linear nature of the stress energy tensor of the magnetic field. For almost scale invariant spectra, the amplitude of the magnetic field at galactic scales is constrained to be of order 10-9 G. If we assume that the magnetic field is damped below the Alfven damping scale, we find that its amplitude at 0.1h-1 Mpc, B? , is constrained to be B? -3/2, where n is the spectral index of the magnetic field and H0=100h km s-1 Mpc-1 is the Hubble constant today.