Miracle-dz/UniFAR-FTUs huggingface dataset:
Video coding Technique using 3-D Dual tree Complex Wavelet Transform with Improved Particle Swarm Optimization

—Video compression plays an important role in video signal processing, transmission and storage. Since the available bandwidth for transmission is very limited, Multimedia Applications such as video conferencing, video on demand, video telephony and remote sensing are not possible without compression. A lot of video compression techniques have been developed and the video signal transmission has followed at data rates below 64kbps.Wavelet transform based motion compensated video codec performs better compression in order to meet the rate and distortion constraint in video transmission for the available bandwidth than the block based techniques, which are followed in standard video transmissions such as H.261 and H.263. But the efficiency of those technique's depends on the way in which it estimates and compensates the object motions in the video sequence. Wavelet based embedded image coder is quite attractive in modern multimedia applications. Wavelet transform, bit plane coding and other techniques make embedded image coder practical and also provide efficient compression. In this paper, we have proposed a novel video coding using swarm intelligence in dual tree complex wavelet transform for video coding. The 3-D DDWT is an attractive video representation because it isolates motion along different directions in separate subbands. However, it is an over-complete transform with redundancy, which is going to be eliminated by choosing optimal subbands with the help of Noise shaping followed by an Improved Particle Swarm Optimization (PSO). The proposed video codec does not require motion compensation and provides better performance than the 3D SPIHT (Embedded type) codec, both objectively and subjectively, and the coder allows full scalability in spatial, temporal and quality dimensions.
Adaptive object placement for augmented reality use in driver assistance systems

We present an approach for adaptive object placement for Augmented Reality (AR) use in driver assistance systems. Combined vanishing point and road surface detection enable the real-time adaptive emplacement of AR objects within a drivers’ natural field of view for on-road information display. This work combines both automotive vision and multimedia production aspects of real-time visual engineering.
Measuring the Practices, Philosophies, and Characteristics of Kindergarten Teachers

This product is part of the RAND Education working paper series. RAND working papers are intended to share researchers' latest findings and to solicit additional peer review. This paper has been peer reviewed but not edited. Unless otherwise indicated, working papers can be quoted and cited without permission of the author, provided the source is clearly referred to as a working paper. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors. is a registered trademark.
Learning: A Teaching Philosophy

Learning: A teaching philosophy by Stephen Allen Warren, Master of Second Language Teaching Utah State University, 2012 Major Professor: Dr. Karin de Jonge-Kannan Department: Languages, Philosophy, and Communication Studies This portfolio presents the author’s current understanding of second language teaching. The main section of the portfolio consists of a teaching philosophy that expresses the author’s believe that definitions of learning direct second language teaching. Three artifacts explore language, culture, and literature and express the development of the author’s teaching philosophy. An annotated bibliography covers the essential readings done in the course of study and provides the foundations for the author’s ontological arguments.
The Value of a Real Customer in a Capstone Project

We argue for the importance of a real customer in a capstone project course via reporting experiences from over ten years period at University of Jyvaskyla (JYU), and providing also practical knowledge and theoretical underpinnings for such an arrangement. Based on our experience and empirical data, we underline that this arrangement is a chance for the students to increase their occupational identity. Theoretically our rationalization of the course arrangement proposes self-direction, empowerment, motivation, and deep level learning strategies for the students.
Selection and validation of miRNAs as normalizers for profiling expression of microRNAs isolated from thyroid fine needle aspiration smears

Fine needle aspiration cytology (FNAC) is currently the method of choice for malignancy prediction in thyroid nodules. Nevertheless, in some cases the interpretation of FNAC results may be problematic due to limitations of the method. The expression level of some microRNAs changes with the development of thyroid tumors, and its quantitation can be used to refine the FNAC results. For this quantitation to be reliable, the obtained data must be adequately normalized. Currently, no reference genes are universally recognized for quantitative assessments of microRNAs in thyroid nodules. The aim of the present study was the selection and validation of such reference genes. Expression of 800 microRNAs in 5 paired samples of thyroid surgical material corresponding to different histotypes of tumors was analyzed using NanoString technology and four of these (hsa-miR-151a-3p, -197-3p, -99a-5p and -214-3p) with the relatively low variation coefficient were selected. The possibility of use of the selected microRNAs and their combination as references was estimated by RT-qPCR on a sampling of cytological smears: benign (n=226), atypia of undetermined significance (n=9), suspicious for follicular neoplasm (n=61), suspicious for malignancy (n=19), medullary thyroid carcinoma (MTC) (n=32), papillary thyroid carcinoma (PTC) (n=54) and non-diagnostic material (ND) (n=34). In order to assess the expression stability of the references, geNorm algorithm was used. The maximum stability was observed for the normalization factor obtained by the combination of all 4 microRNAs. Further validation of the complex normalizer and individual selected microRNAs was performed using 5 different classification methods on 3 groups of FNAC smears from the analyzed batch: benign neoplasms, MTC and PTC. In all cases, the use of the complex classifier resulted in the reduced number of errors. On using the complex microRNA normalizer, the decision-tree method C4.5 makes it possible to distinguish between malignant and benign thyroid neoplasms in cytological smears with high overall accuracy (>91%).
Understanding Hierarchical Methods for Differentially Private Histograms

In recent years, many approaches to differentially privately publish histograms have been proposed. Several approaches rely on constructing tree structures in order to decrease the error when answer large range queries. In this paper, we examine the factors affecting the accuracy of hierarchical approaches by studying the mean squared error (MSE) when answering range queries. We start with one-dimensional histograms, and analyze how the MSE changes with different branching factors, after employing constrained inference, and with different methods to allocate the privacy budget among hierarchy levels. Our analysis and experimental results show that combining the choice of a good branching factor with constrained inference outperform the current state of the art. Finally, we extend our analysis to multi-dimensional histograms. We show that the benefits from employing hierarchical methods beyond a single dimension are significantly diminished, and when there are 3 or more dimensions, it is almost always better to use the Flat method instead of a hierarchy.
Fluid Registration of Diffusion Tensor Images Using Information Theory

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or J-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the J-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.
Has Teachers’ Participation in Decision Making Increased in China? Local Responses to the Implementation of Education Decentralization in Guangdong Province

assumption that such a move will make educational content more relevant to local interests and demands by offering more decision-making power to local educational stakeholders. In such a context, teachers who are seen as the linchpins of educational reforms will be able to enhance their professional competency and status by having increased autonomy in deciding school matters. Both the Carnegie Forum on Education and Economy (1986) and Holmes Group (1986) emphasize the need to increase professional autonomy of teachers in school affairs through allowing teacher participation in deciding school matters. Teachers cannot act as intelligent professionals unless a democratic working environment allows them to develop their skills and knowledge. That is, a decentralized educational system aims at transforming schools into self-analyzing, self-reforming institutions where teachers can develop their efficacy through democratized workplaces and improved working conditions (Datnow, 1994; Webb & Ashton, 1987). More important, as Desimone (2002) argues, teachers will be able to modify educational reforms by matching students’ needs and thereby develop senses of ownership and create senses of accountability for themselves. Following this line of reasoning, giving teachers more participative decision-making power will have an impact on their enhancement of professional development. Such discussions, however, seem to ignore local views on and interpretations of the implementation and effects of educational decentralization policies. Bailey (2000) argues that teachers’ perspectives on educational reforms have been a missing aspect that needs to be further explored. In actuality, for teachers engaged in the process of policy change, the way that they interpret policy and translate it into their daily practices will influence the implementation and the effects of a policy shift. Therefore, it is important and necessary to examine educational decentralization policies from the local perspective, for the ways in which teachers understand and interpret the policy changes will have a direct impact on their implementation. China has been implementing educational decentralization for the last 2 decades. However, research on educational decentralization in China has not
ANN (Adaline) Based Harmonic Compensation for Shunt Active Power Filter with Capacitor Voltage Based Predictive Technique

In this paper, a fast and simple technique to generate the current reference to compensate for the harmonics and reactive power in a shunt type active power filter (APF) is developed. A voltage source inverter (VSI) is operated in the current controlled mode for this purpose. For fast generation of the reference current in the APF, the dc link voltage of the VSI is always sensed and an initial estimate is derived through an ANN based PI controller. It has been observed that this method works fine for balanced load. Unbalance in load and also uncertainty/mismatch in the filter parameters, deteriorate the system performance. To overcome this drawback, an Adaline based technique is incorporated. Weights of Adaline are tuned to minimize the total harmonic distortion (THD) of the source current. Extensive simulations have confirmed the validity of the proposed scheme for all kinds of load (balanced and unbalanced) for a three phase three wire system.
Dynamic Non-Linear Enhancement using Gamma Correction and Dynamic Restoration

This paper has proposed a new integrated image enhancement algorithm by integrating non linear image enhancement technique with dynamic restoration. Image processing plays a vital role in visualization application. It improves the visibility of poor images. Different techniques have been proposed so far. To improve image quality image enhancement can selectively enhance and restrain some information about image. It is a method which decreases image noise, eliminate artifacts, and maintain details. Its purpose is to amplify certain image features for analysis, diagnosis and display. The overall objective of this paper is to propose an integrated technique which will integrate the nonlinear enhancement technique with the gamma correction and dynamic restoration technique. The proposed algorithm is implemented in MATLAB. Experimental results have shown quite significant results over the available methods.
The Arctic freshwater system: Changes and impacts

[1] Dramatic changes have been observed in the Arctic over the last century. Many of these involve the storage and cycling of fresh water. On land, precipitation and river discharge, lake abundance and size, glacier area and volume, soil moisture, and a variety of permafrost characteristics have changed. In the ocean, sea ice thickness and areal coverage have decreased and water mass circulation patterns have shifted, changing freshwater pathways and sea ice cover dynamics. Precipitation onto the ocean surface has also changed. Such changes are expected to continue, and perhaps accelerate, in the coming century, enhanced by complex feedbacks between the oceanic, atmospheric, and terrestrial freshwater systems. Change to the arctic freshwater system heralds changes for our global physical and ecological environment as well as human activities in the Arctic. In this paper we review observed changes in the arctic freshwater system over the last century in terrestrial, atmospheric, and oceanic systems.
Applying machine learning algorithms for automatic Persian text classification

Automatic document classification due to its various applications in data mining and information technology is one of the important topics in computer science. Classification plays a vital role in many information management and retrieval tasks. Document classification, also known as document categorization, is the process of assigning a document to one or more predefined category labels. Classification is often posed as a supervised learning problem in which a set of labeled data is used to train a classifier which can be applied to label future examples [1]. Document classification includes different parts such as text processing, feature extraction, feature vector construction and final classification. Thus improvement in each part should lead to better results in document classification. In this paper, we apply machine learning methods for automatic Persian news classification. In this regard, we first try to exert some language preprocess in Hamshahri dataset [2], and then we extract a feature vector for each news text by using feature weighting and feature selection algorithms. After that we train our classifier by support vector machine (SVM) and K-nearest neighbor (KNN) algorithms. In Experiments, although both algorithms show acceptable results for Persian text classification, the performance of KNN is better in comparison to SVM.
Systematic Equity-Based Credit Risk: A CEV Model With Jump to Default

We use equity as the traded primitive for a detailed analysis of systematic default risk. Default is parsimoniously represented by equity value hitting the zero barrier so that, unlike in reduced-form models, the explicit linkage to the firm's capital structure is preserved, but, unlike in structural models, restrictive assumptions on the structure are avoided. Default risk is either jump-like or diffusive. The equity price can jump to default. In line with recent empirical evidence on the jump-to-default risk price, we highlight how reasonable choices of the pricing kernel can imply remarkable differences in the equity-price-dependent status between the objective default intensity and the risk-neutral intensity. As equity returns experience negative diffusive shocks, their CEV-type local variance increases and boosts the objective and risk-neutral probabilities of diffusive default. A parsimonious version of our general model simultaneously enables analytical credit-risk management and analytical pricing of credit-sensitive instruments. Easy cross-asset hedging ensues.
The recollapse problem of closed Friedmann-Robertson-Walker models in higher-order gravity theories

We study the closed universe recollapse conjecture for positively curved Friedmann–Robertson–Walker models with a perfect fluid matter source and a scalar field which arises in the conformal frame of the R+αR2 theory. By including ordinary matter, we extend the analysis of a previous work. We analyze the structure of the resulted four-dimensional dynamical system with the methods of the center manifold theory and the normal form theory. It is shown that an initially expanding closed FRW universe, starting close to the Minkowski space-time, cannot avoid recollapse. We discuss the posibility that potentials with a positive minimum may prevent the recollapse of closed universes.
Dynamic Reconfiguration of Data Parallel Programs

Given the large amount of data from different sources that have become available to researchers in multiple fields, Data Science has emerged as a new paradigm for exploring and getting value from that data. In that context, new parallel processing environments with abstract programming interfaces, like Spark, were proposed to try to simplify the development of distributed programs. Although such solutions have become widely used, achieving the best performance with them is still not always straight-forward, despite the multiple run-time strategies they use. In this work we analyze some of the causes of performance degradation in such systems and, based on that analysis, we propose a tool to improve performance by dynamically adjusting data partitioning and parallelism degree in recurrent applications based on previous executions. Our results applying that methodology show consistent reductions in execution time for the applications considered, with gains of up to 50%.
Sidekick: A Personal agent for the semantic web

The Semantic Web is a vision to simplify and improve knowledge reuse on the Web. It is all set to alter the way humans beneﬁt from the web from active interaction to somewhat passive utilization through the proliferation of software agents and in particular personal assistants that can better function and thrive on the Semantic Web than the conventional web. Agents can parse, understand and reason about information available on Semantic Web pages in an attempt to use it to meet users’ needs. Such personal assistants will be driven by rules , axioms and the internal model or proﬁle that the agents have inside them for the user. An intrinsic and important pre-requisite for a personal assistant or rather any agent is to manipulate information available on the Semantic Web in the form of ontologies, axioms, and rules written in various semantic markup languages. In this paper, a model architecture for such a personal assistant, which we call Sidekick, that deals with real-world semantic markup is described. The agent reasons with semantic markup written in DAML+OIL, using the Java Expert System Shell (JESS) as the reasoning engine. This software assistant views information providers on the Semantic Web as recommender agents that have a limited view of the user’s preferences and provides a improved notion of personalization by collaborating with peer personal assistants (what are referred to as buddy agents) within communities that the user has identiﬁed as trusted parties to exchange information with. Collaboration is achieved through simple
Metabolic crosstalk between the heart and liver impacts familial hypertrophic cardiomyopathy

Familial hypertrophic cardiomyopathy (HCM) is largely caused by dominant mutations in genes encoding cardiac sarcomeric proteins, and it is etiologically distinct from secondary cardiomyopathies resulting from pressure/volume overload and neurohormonal or inflammatory stimuli. Here, we demonstrate that decreased left ventricular contractile function in male, but not female, HCM mice is associated with reduced fatty acid translocase (CD36) and AMP‐activated protein kinase (AMPK) activity. As a result, the levels of myocardial ATP and triglyceride (TG) content are reduced, while the levels of oleic acid and TG in circulating very low density lipoproteins (VLDLs) and liver are increased. With time, these metabolic changes culminate in enhanced glucose production in male HCM mice. Remarkably, restoration of ventricular TG and ATP deficits via AMPK agonism as well as inhibition of gluconeogenesis improves ventricular architecture and function. These data underscore the importance of the systemic effects of a primary genetic heart disease to other organs and provide insight into potentially novel therapeutic interventions for HCM.
NOAH: a tool for argument reduction, serial and parallel decomposition of decision tables

A tool for managing decision tables was developed and presented in this paper. The tool uses a number of algorithms, namely argument reduction, serial and parallel decomposition to perform operations on these tables. With the help of these operations, reduction in size of the tables can be achieved, leading to smaller memory requirements. The tool is a result of extending previously described software packages by adding a convenient GUI.
100 years of Zermelo's axiom of choice: what was the problem with it?

Cantor conceived set theory in a sequence of six papers published in the Mathematische Annalen during the five year period 1879-1884. In the fifth of these papers, published in 1883,1 he stated as a law of thought (Denkgesetz) that every set can be well-ordered or, more precisely, that it is always possible to bring any well-defined set into the form of a well-ordered set. Now to call it a law of thought was implicitly to claim self-evidence for it, but he must have given up that claim at some point, because in the 1890’s he made an unsuccessful attempt at demonstrating the well-ordering principle.2 The first to succeed in doing so was Zermelo,3 although, as a prerequisite of the demonstration, he had to introduce a new principle, which came to be called the principle of choice (Prinzip der Auswahl) respectively the axiom of choice (Axiom der Auswahl) in his two papers from 1908.4,5 His first paper on the subject, published in 1904, consists of merely three pages, excerpted by Hilbert from a letter which he had received from Zermelo. The letter is dated 24 September 1904, and the excerpt begins by saying that the demonstration came out of discussions with Erhard Schmidt during the preceding week, which means that we can safely date the appearance of the axiom of choice and the demonstration of the well-ordering theorem to September 1904. Brief as it was, Zermelo’s paper gave rise to what is presumably the most lively discussion among mathematicians on the validity, or acceptability, of a mathematical axiom that has ever taken place. Within a couple of