Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Stratus Cloud Properties Deduced from Surface, GOES, and Aircraft Data during the March 2000 ARM Cloud IOP

Low-level stratus cloud microphysical properties derived from surface and Geostationary Operational Environmental Satellite (GOES) data during the March 2000 cloud intensive observational period (IOP) at the Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site are compared with aircraft in situ measurements. For the surface retrievals, the cloud droplet effective radius and optical depth are retrieved from a d2-stream radiative transfer model with the input of ground-based measurements, and the cloud liquid water path (LWP) is retrieved from ground-based microwave-radiometer-measured brightness temperature. The satellite results, retrieved from GOES visible, solar-infrared, and infrared radiances, are averaged in a 0.5 8 3 0.58 box centered on the ARM SGP site. The forward scattering spectrometer probe (FSSP) on the University of North Dakota Citation aircraft provided in situ measurements of the cloud microphysical properties. During the IOP, four low-level stratus cases were intensively observed by the ground- and satellite-based remote sensors and aircraft in situ instruments resulting in a total of 10 h of simultaneous data from the three platforms. In spite of the large differences in temporal and spatial resolution between surface, GOES, and aircraft, the surface retrievals have excellent agreement with the aircraft data overall for the entire 10-h period, and the GOES results agree reasonably well with the surface and aircraft data and have similar trends and magnitudes except for the GOES-derived effective radii, which are typically larger than the surface- and aircraft-derived values. The means and standard deviations of the differences between the surface and aircraft effective radius, LWP, and optical depth are 24% 6 20.1%, 21% 6 31.2%, and 8% 6 29.3%, respectively; while their correlation coefficients are 0.78, 0.92, and 0.89, respectively, during the 10-h period. The differences and correlations between the GOES-8 and aircraft results are of a similar magnitude, except for the droplet sizes. The averaged GOES-derived effective radius is 23% or 1.8 mm greater than the corresponding aircraft values, resulting in a much smaller correlation coefficient of 0.18. Additional surface‐satellite datasets were analyzed for time periods when the aircraft was unavailable. When these additional results are combined with the retrievals from the four in situ cases, the means and standard deviations of the differences between the satellite-derived cloud droplet effective radius, LWP, and optical depth and their surface-based counterparts are 16% 6 31.2%, 4% 6 31.6%, and 26% 6 39.9%, respectively. The corresponding correlation coefficients are 0.24, 0.88, and 0.73. The frequency distributions of the two datasets are very similar indicating that the satellite retrieval method should be able to produce reliable statistics of boundary layer cloud properties for use in climate and cloud process models.
A novel approach for edge adaptive steganography on LSB insertion technique

Steganography is define as the process of hiding information in a multimedia carrier. Its ultimate objectives are undetectability and robustness of the hidden data. Least significant bit technique is one of the popular techniques in steganography. Least significant bits of cover are altered by the secret data bits. Changing the LSB's of pixels in smooth regions in the cover image at lower embedding rate will forms the poor visual quality and asymmetry into the stegos. Instead of using smooth regions, edge regions from the cover are selected for data embedding purpose. This novel approach of steganography expand the LSB matching revisited image steganography and propose a new scheme which can select the embedding regions according to the size of secret message and the difference between two consecutive pixels in the cover image. In case of lower embedding rates, only sharper edge regions are used while keeping the other smoother regions as they are. This novel scheme can enhance the security significantly compared with typical LSB based approaches as well as their edge adaptive ones, such as pixel value differencing based approaches, while maintaining excellent visual quality of stego images at the same time.
Psweep: Parallel View Maintenance under Concurrent Data Updates of Distributed Sources Psweep: Parallel View Maintenance under Concurrent Data Updates of Distributed Sources

Data warehouses (DW) are built by gathering information from several information sources (ISs) and integrating it into one repository customized to users' needs. Recent work has begun to address the problem of view maintenance of DWs under concurrent data updates of diierent ISs. SWEEP proposed by Agrawal et al. AAS97] is one of the more popular solutions; even though its performance is limited due to enforcing a sequential ordering on the handling of data updates from ISs by the view maintenance module. We have overcome this limitation by developing a parallel algorithm for view maintenance, called PSWEEP, that still incorporates all beneets of SWEEP while ooering substantially improved performance. In order to perform parallel view maintenance, we solve two issues: detecting maintenance-concurrent data updates in a parallel mode, and correcting the problem that the DW commit order may not correspond to the DW update processing order due to parallel maintenance handling. By decomposing SWEEP into an architecture of modular components, we then can insert a local timestamp assignment module for detecting maintenance-concurrent data updates without requiring any global clock synchronization. We introduce the negative counter concept as a simple yet suucient solution to solve the Variant-DW-Commit problem of variant orders of committing eeects of data updates to the DW. We have proven the correctness of PSWEEP to guarantee that our strategy indeed generates the correct nal DW state. An evaluation of both SWEEP and PSWEEP is given that shows that PSWEEP has the potential of multi-fold performance improvement over SWEEP depending on the number of threads supportable in the given DW system implementation.
MASTERS PRESENTATION SPACELIKE FOLIATIONS OF ROBERTSON-WALKER SPACETIME BY FERMI SPACE SLICES By

Explicit Fermi coordinates are given for geodesic observer s comoving with the Hubble flow in expanding Robertson-Walker spacetimes, along with exact e xpressions for the metric tensors in these coordinates. For the case of non inflationary cosmolog ies, we show that Fermi coordinate charts are global, and spacetime is foliated by space slices of constant Fermi (proper) time that have finite extent. A universal upper bound for the proper radius o f any leaf of the foliation is given. A general expression is derived for the geometrically defined Fermi relative velocity of a test particle (e.g. a galaxy cluster) comoving with the Hubble flow away fro m the observer. Least upper bounds of superluminal recessional Fermi velocities are given for spacetimes whose scale factors follow power laws, including matter-dominated and radiation-dom inated cosmologies. Exact expressions for the proper radius of any leaf of the foliation for this sam e class of spacetimes are given. It is shown that the radii increase linearly with proper time of th e observer moving with the Hubble flow. These results are applied to particular cosmological model s. CALIFORNIA STATE UNIVERSITY, NORTHRIDGE SPACELIKE FOLIATIONS OF ROBERTSON-WALKER SPACETIME BY FERMI SPACE SLICES A thesis submitted in partial fulfillment of the requirement s For the degree of Master of Science in Mathematics
Active Bayesian Optimization: Minimizing Minimizer Entropy

The ultimate goal of optimization is to find the minimizer of a target function.However, typical criteria for active optimization often ignore the uncertainty about the minimizer. We propose a novel criterion for global optimization and an associated sequential active learning strategy using Gaussian processes.Our criterion is the reduction of uncertainty in the posterior distribution of the function minimizer. It can also flexibly incorporate multiple global minimizers. We implement a tractable approximation of the criterion and demonstrate that it obtains the global minimizer accurately compared to conventional Bayesian optimization criteria.
Title Similarity-Based Feature Weighting for Text Categorization

In automated text categorization, a system analyzes a natural-language document to decide whether it belongs in one or more of a group of pre-defined categories. The typical approach is to represent the documents using feature vectors, and inductively generate a classifier based on a training set of documents and their manually-assigned categories. Such a process ignores information on word order, syntax, and other heuristics that might aid in identifying good features for categorization. Recently, more attention has been paid to using deeper natural language processing techniques to improve the performance of the standard classifiers. One such approach, which takes advantage of a previously-generated thesaurus of lexical similarities, is studied in this project. This system identifies key-words in the text by looking for terms with high similarity to the terms in the title field. A database of automatically-clustered dependency-based word similarities is used to identify the similar words. Experiments show increased weighting of key terms aids the effectiveness of text categorization for a number of topics in the standard Reuters newswire corpus.
Combining network calculus and scheduling theory to improve delay bounds

Nowadays embedded real-time systems are often large distributed communicating systems, and the need for bounds on worst-case execution times (WCET) now includes the need of bound on worst-case network traversal time (WCTT). Network calculus is one method used to compute such bounds, and has been successfully applied on Airbus A380 [13]. Nevertheless, the computed bounds could be pessimistic. On the other hand, the scheduling theory can often compute tight bounds, but with algorithms of complexity not able to deal with too large systems. In this paper, the scheduling theory is used to compute tight constraints on flows produced by computers, improving the inputs to the network calculus method and consequently compute better (i.e. lower) bounds. To do so, scheduling methods must be adapted to approach the best and worst date of message production, and some results on network calculus must be written to go from the scheduling method on a finite interval to a general long term constraint.
EVALUATING SIMILARITIES BETWEEN HUMAN AND CHIMPANZEE DNA

A preliminary study was performed by Tomkins comparing 40,000 chimpanzee genomic sequences against the human genome which indicated that reported levels of human-chimp DNA similarity were significantly lower than commonly reported. The present, follow-up study was then completed in which chimp chromosomes were sliced into new individual query files of varying string lengths and queried against their human chromosome homolog. This allowed for comparisons to be optimized irrespective of the linear order of genes and sequence features. The definition of similarity was the amount (percent) of optimally aligned chimp DNA. For the chimp autosomes, the amount of optimally aligned DNA sequence provided similarities between 66 and 76 percent, depending on the chromosome. Only 69 percent of the chimpanzee X chromosome was similar to human and only 43 percent of the Y chromosome. Genome-wide, only 70% of the chimpanzee DNA was similar to human under the most optimal alignment conditions. While, chimpanzees and humans share many localized protein-coding regions of high similarity, the overall extreme discontinuity between the two genomes defies evolutionary timescales and dogmatic presuppositions about a common ancestor.
Trust based recommendation systems

It is difficult for the users to reach the most appropriate and reliable item for them among vast number of items and comments on these items. Recommendation systems and trust/reputation systems are one of the solutions to deal with this problem with the help of personalized services. These systems suggest items to the user by estimating the ratings that user would give to them. Use of trust data for giving recommendation has emerged as a new way for giving better recommendations. In the literature, it is shown that trust based recommendation approaches perform better than the ones that are only based on user similarity, or item similarity. In this paper, a comparative review of recommendation systems, trust/reputation systems, and their combined usage is presented. Then, a sample trust based agent oriented recommendation system is proposed and its effectiveness is justified with the help of some experiments.
Emotion Regulation and Emotion Understanding in Preschoolers as a Predictor of the Maternal Socialization of Emotion

In this study, the relationship between emotion regulation and emotion understanding skills of preschool children and emotional socialization behaviour of mothers was investigated. This study was designed as a correlation type relational survey model with a total of 180 participants - 90 children between the ages of 3-6 and 90 mothers – who have low, medium, and high socio-economic levels. The data of the study were collected using the Coping with Negative Emotions of Children Scale, Emotion regulation Scale, and Wally Emotion Test. The analysis of data was made with multiple regression analysis. The results of the study showed that emotional socialization behaviour of mothers was a significant predictor of emotion regulation skills of preschool children. Problem based and punitive reactions of mothers that are included in emotional socialization behaviours was identified as significant predictors of emotion regulation skills of children. Accordingly, as problem based, and punitive reactions increased, emotion regulation skills of children also increased. However, the results of the study showed that emotional socialization behaviour of mothers was not a significant predictor of understanding emotional skills of preschool children. Based on the research findings, it is suggested that policy makers, institutions educating teachers or teachers themselves prepare early intervention programs to be implemented in pre-schools to ensure mothers' emotional socialization behaviors recognize the potential effects on their children and to support children's emotional development.
Modelling Changes in the Cognitive Processing of Grammar in Implicit and Explicit Learning Conditions:Insights from an Eye-Tracking Study

This study used eye-tracking to examine changes in how second language (L2) learners process target grammatical exemplars in written L2 input in implicit and explicit instructional conditions and how these changes relate to learning gains. In three separate sessions, 77 L2 learners of English read a story containing seven examples of a grammatical construction. The results of a growth curve analysis indicated significant main effects for the instructional condition and test sessions on total fixation duration and a significant interaction between these two variables. There was minimal attentional processing and no improvement in processing efficiency of the target construction in the unenhanced condition. Learners’ attentional processing in the textually enhanced conditions decreased and, by the end of the experiment, they engaged in establishing and fine-tuning form-meaning links. In the two explicit instructional conditions, participants’ attention decreased over time and form-meaning representations of the target structure were strengthened.
VLDL Induces Adipocyte Differentiation in ApoE-Dependent Manner

Objective—To clarify the role of very low density lipoprotein (VLDL) and apolipoprotein E (apoE) in adipogenesis, we studied newly developed hyperlipidemic obese (ob/ob;apoE−/−) mice. Because hydrolysis of VLDL is believed to be the major source of adipogenic free fatty acids, a higher plasma level of VLDL in these mice should exaggerate obesity. Methods and Results—When fed a high-fat, high-cholesterol diet, ob/ob;apoE−/− mice did not show increased body weight or an increased amount of adipose tissue in spite of increased plasma VLDL levels, whereas ob/ob mice showed an increased body weight and amount of adipose tissue, suggesting that there is a novel apoE-dependent pathway for adipogenesis. In vitro experiments using bone marrow stromal cells and 3T3-L1 cells confirmed this notion. ApoE-deficient VLDL did not induce adipogenesis, whereas normal VLDL induced adipogenesis in these cells. The incubation of apoE-deficient VLDL with recombinant human apoE restored its adipogenic activity. Tetrahydrolipstatin, a lipoprotein lipase inhibitor, did not affect the adipogenic activity of VLDL, suggesting that hydrolysis of VLDL did not play a major role in its effects. In fact, lipid components of VLDL or free fatty acids induced only partial adipogenesis. Conclusions—Our findings indicate that VLDL induces adipogenesis in an apoE-dependent manner both in vitro and in vivo.
Votes on Twitter: Assessing Candidate Preferences and Topics of Discussion During the 2016 U.S. Presidential Election

Social media offers scholars new and innovative ways of understanding public opinion, including citizens’ prospective votes in elections and referenda. We classify social media users’ preferences over the two U.S. presidential candidates in the 2016 election using Twitter data and explore the topics of conversation among proClinton and proTrump supporters. We take advantage of hashtags that signaled users’ vote preferences to train our machine learning model which employs a novel classifier—a Topic-Based Naive Bayes model—that we demonstrate improves on existing classifiers. Our findings demonstrate that we are able to classify users with a high degree of accuracy and precision. We further explore the similarities and divergences among what proClinton and proTrump users discussed on Twitter.
An introspective on the Retrospective-Approximation paradigm

Retrospective Approximation (RA) is a solution paradigm introduced in the early 1990s by Chen and Schmeiser for solving one-dimensional stochastic root finding problems (SRFPs). The RA paradigm can be thought of as a refined and implementable version of sample average approximation, where a sequence of approximate problems are strategically generated and solved to identify iterates that progressively approach the desired solution. While originally aimed at one-dimensional SRFPs, the paradigm's broader utility, particularly within general simulation optimization algorithms, is becoming increasingly evident. We discuss the RA paradigm, demonstrate its usefulness, present the key results and papers on the topic over the last fifteen years, and speculate fruitful future directions.
DCU-ADAPT: Learning Edit Operations for Microblog Normalisation with the Generalised Perceptron

We describe the work carried out by the DCU-ADAPT team on the Lexical Normalisation shared task at W-NUT 2015. We train a generalised perceptron to annotate noisy text with edit operations that normalise the text when executed. Features are charactern-grams, recurrent neural network language model hidden layer activations, character class and eligibility for editing according to the task rules. We combine predictions from 25 models trained on subsets of the training data by selecting the most-likely normalisation according to a character language model. We compare the use of a generalised perceptron to the use of conditional random fields restricted to smaller amounts of training data due to memory constraints. Furthermore, we make a first attempt to ver
MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes

Genome‐wide association studies (GWAS) can identify common alleles that contribute to complex disease susceptibility. Despite the large number of SNPs assessed in each study, the effects of most common SNPs must be evaluated indirectly using either genotyped markers or haplotypes thereof as proxies. We have previously implemented a computationally efficient Markov Chain framework for genotype imputation and haplotyping in the freely available MaCH software package. The approach describes sampled chromosomes as mosaics of each other and uses available genotype and shotgun sequence data to estimate unobserved genotypes and haplotypes, together with useful measures of the quality of these estimates. Our approach is already widely used to facilitate comparison of results across studies as well as meta‐analyses of GWAS. Here, we use simulations and experimental genotypes to evaluate its accuracy and utility, considering choices of genotyping panels, reference panel configurations, and designs where genotyping is replaced with shotgun sequencing. Importantly, we show that genotype imputation not only facilitates cross study analyses but also increases power of genetic association studies. We show that genotype imputation of common variants using HapMap haplotypes as a reference is very accurate using either genome‐wide SNP data or smaller amounts of data typical in fine‐mapping studies. Furthermore, we show the approach is applicable in a variety of populations. Finally, we illustrate how association analyses of unobserved variants will benefit from ongoing advances such as larger HapMap reference panels and whole genome shotgun sequencing technologies. Genet. Epidemiol. 34: 816‐834, 2010. © 2010 Wiley‐Liss, Inc.
A Library for Explicit Dynamic Code Generation and Optimisation in C + +

The TaskGraph Library is a C++ library for dynamic code generation, which combines specialisation with dependence analysis and loop restructuring. A TaskGraph represents a fragment of code which is constructed and manipulated at run-time, then compiled, dynamically linked and executed. TaskGraphs are initialised using macros and overloading, which forms a simplified, C-like sub-language with first-class arrays and no pointer arithmetic. Once a TaskGraph has been constructed, we can analyse dependence structure and perform optimisations. In this paper, we present the design of the TaskGraph library, present several sample applications for this library which demonstrate its use for runtime code specialisation and optimisation and discuss related work and future applications and developments of the library.
Minimizing Nonsubmodular Functions with Graph Cuts-A Review

Optimization techniques based on graph cuts have become a standard tool for many vision applications. These techniques allow to minimize efficiently certain energy functions corresponding to pairwise Markov random fields (MRFs). Currently, there is an accepted view within the computer vision community that graph cuts can only be used for optimizing a limited class of MRF energies (e.g., submodular functions). In this survey, we review some results that show that graph cuts can be applied to a much larger class of energy functions (in particular, nonsubmodular functions). While these results are well-known in the optimization community, to our knowledge they were not used in the context of computer vision and MRF optimization. We demonstrate the relevance of these results to vision on the problem of binary texture restoration.
On the addition of quantum matrices

An addition law is introduced for the usual quantum matrices A(R) by means of a coaddition Δ_t=t⊗1+1⊗t. It supplements the usual comultiplication Δt=t⊗t and together they obey a codistributivity condition. The coaddition does not form a usual Hopf algebra but a braided one. The same remarks apply for rectangular m×n quantum matrices. As an application, left‐invariant vector fields are constructed on A(R) and other quantum spaces. They close in the form of a braided Lie algebra. As another application, the wave functions in the lattice approximation of Kac–Moody algebras and other lattice fields can be added and functionally differentiated.