Miracle-dz/UniFAR-FTUs huggingface dataset:
Image Fusion for Underwater images using Curvelet Transform

1,2,3 Department of Electronics and Communication Engineering 1,2 Hasmukh Goswami College of Engineering 3 Indus Institute of Technology& Engineering Ahmadabad, India Abstract— In the real world noise is often presented in the signal. Noise in the image is inserted during the process of image acquisition or the transmission process of image. Many parameters or factors like light levels and sensor temperature are there which are responsible the for the amount of noise present in the image. Acquiring clear images in underwater environments is an important issue in ocean engineering. Generally underwater images are affected by severe blur and haze caused by light that is reflected from surface and scattered by water particles and color change due to varying degrees of light attenuation for different wavelengths. So there is contrast losses and color deviation in images. In general underwater images are polluted by noises like Gaussian, and Speckle noise. So it is necessary that to denoise the image before further process. There are different filters to denoise the image like Gaussian Filter,Mean Filter, Weiner Filter and Curvelet Transform can be used. After that Fusion is performed of best filtering method and curvelet transform using Simple Average and Average using CVT. Performance can be calculated on the basis of parameter like PSNR (peak signal-to-noise ratio)& MSE (mean square error),MAE (Mean Absolute Error), Correlation. MATLAB is used for implementation of coding and to calculate the output parameter.
Publication Date Prediction through Reverse Engineering of the Web

In this paper, we focus on one of the most challenging tasks in temporal information retrieval: detection of a web page publication date. The natural approach to this problem is to find the publication date in the HTML body of a page. However, there are two fundamental problems with this approach. First, not all web pages contain the publication dates in their texts. Second, it is hard to distinguish the publication date among all the dates found in the page's text. The approach we suggest in this paper supplements methods of date extraction from the page's text with novel link-based methods of dating. Some of our link-based methods are based on a probabilistic model of the Web graph structure evolution, which relies on the publication dates of web pages as on its parameters. We use this model to estimate the publication dates of web pages: based only on the link structure currently observed, we perform a ``reverse engineering'' to reveal the whole process of the Web's evolution.
Estimating the azimuth and elevation of a sound source from the output of a cochlear model

Interaural intensity differences (IIDs) and interaural time differences (ITDs) give important information for estimating the elevation as well as the azimuth of a sound source. The authors extract this information from a filter-bank model of the cochlea using straightforward short-time autocorrelation and crosscorrelation operations. With the appropriate coordinate system, the resulting ITD varies primarily with azimuth, while the IID varies with azimuth and elevation. For a single sound source in an anechoic environment, a maximum-likelihood estimation procedure is shown capable of recovering azimuth to within 1 degree and elevation to within 16 degrees. <<ETX>>
Multiple-Output Resonant Matrix Converter for Multiple Induction Heaters

Most of the ac-ac converters used in home appliances are based on single-output dc-link inverters, which provide a cost-effective and straightforward solution. However, a two-stage power conversion decreases power density and efficiency. A direct ac-ac conversion has been thoroughly studied in the past. Nevertheless, the complex control scheme and higher cost have prevented it from being used in cost-oriented applications, such as home appliances. This paper proposes a direct ac-ac conversion scheme by means of a multiple-output resonant matrix converter applied to multiple inductive load systems. The proposed topology reduces significantly the number of devices and complexity, leading to an efficient, versatile, and cost-effective solution. The analytical and simulation results have been verified by means of a prototype applied to a novel total-active-surface induction-heating appliance.
Delimiting Species Using Single-Locus Data and the Generalized Mixed Yule Coalescent Approach: A Revised Method and Evaluation on Simulated Data Sets

DNA barcoding-type studies assemble single-locus data from large samples of individuals and species, and have provided new kinds of data for evolutionary surveys of diversity. An important goal of many such studies is to delimit evolutionarily significant species units, especially in biodiversity surveys from environmental DNA samples. The Generalized Mixed Yule Coalescent (GMYC) method is a likelihood method for delimiting species by fitting within- and between-species branching models to reconstructed gene trees. Although the method has been widely used, it has not previously been described in detail or evaluated fully against simulations of alternative scenarios of true patterns of population variation and divergence between species. Here, we present important reformulations to the GMYC method as originally specified, and demonstrate its robustness to a range of departures from its simplifying assumptions. The main factor affecting the accuracy of delimitation is the mean population size of species relative to divergence times between them. Other departures from the model assumptions, such as varying population sizes among species, alternative scenarios for speciation and extinction, and population growth or subdivision within species, have relatively smaller effects. Our simulations demonstrate that support measures derived from the likelihood function provide a robust indication of when the model performs well and when it leads to inaccurate delimitations. Finally, the so-called single-threshold version of the method outperforms the multiple-threshold version of the method on simulated data: we argue that this might represent a fundamental limit due to the nature of evidence used to delimit species in this approach. Together with other studies comparing its performance relative to other methods, our findings support the robustness of GMYC as a tool for delimiting species when only single-locus information is available. [Clusters; coalescent; DNA; genealogical; neutral; speciation; species. ]
SOME ASPECTS OF THE NON-PERTURBATIVE RENORMALIZATION OF THE φ4 MODEL

A non-perturbative renormalization of the φ4 model is considered. First, we integrate out only a single pair of conjugated modes with wave vectors ±q. Then, we are looking for the RG equation which would describe the transformation of the Hamiltonian under the integration over a shell Λ - d Λ < k < Λ, where dΛ → 0. We show that the known Wegner–Houghton equation is consistent with the assumption of a simple superposition of the integration results for ±q. The renormalized action can be expanded in powers of the φ4 coupling constant u in the high temperature phase at u → 0. We compare the expansion coefficients with those exactly calculated by the diagrammatic perturbative method and find some inconsistency. It causes a question in which sense the Wegner–Houghton equation is really exact.
ageOpt-RMT: Compiler-driven variation-aware aging optimization for redundant multithreading

Reliability optimization in the nano-era needs to account for multiple reliability concerns. Redundant Multithreading (RMT) has emerged as a promising technique to mitigate soft-errors in multi-cores. Since variation- and aging-unawareness during RMT may increase aging of slow cores due to high utilization or lead to unbalanced aging under varying workload scenarios, we propose to leverage variations in vulnerability and duty cycle by means of multiple compiled versions. We perform variation-aware task mapping to proactively reduce the aging of slower cores and thereby maintaining the minimum processing capabilities. Afterwards, we perform an aging-aware activation/deactivation of RMT considering tasks' variable resilience properties and select appropriate reliable versions for the mapped tasks. Experimental results demonstrate that compared to state-of-the-art aging-unaware RMT techniques, our ageOpt-RMT provides improved and balanced aging profiles by 2x on average.
Between Expectancy and Experience: Testing a Model of Childbirth Satisfaction

Childbirth is a pivotal event for many women, and evidence suggests that women possess strong expectations regarding this experience. In a longitudinal study of 330 Israeli first-time mothers, we distinguished between physical, emotional, and cognitive factors and used them to assess the underlying mechanism of satisfaction, based on theoretical frameworks of stress and control. Women completed questionnaires during pregnancy and two months postpartum. The negative association between a more medicalized birth and birth satisfaction was partially mediated by perceived control. In turn, specific emotions mediated the association between perceived control and satisfaction: Greater perceived control over the birth environment predicted more positive emotions, less fear, and better perceived care; while greater perceived control over the birth process predicted more positive emotions, less fear, and less guilt. Greater incongruence between the planned and actual birth experience predicted lower satisfaction, mediated by perceived care and feelings of guilt. This investigation unraveled the association between women’s lived birth experience and their birth satisfaction. The findings underscore the value of helping women achieve satisfying births by discussing their expectations with them, providing them with experiences that meet their needs, and supporting those with a gap between their expectations and experience. Respecting individual preferences while lowering blame may improve women’s health and well-being. Additional online materials for this article are available on PWQ’s website at http://journals.sagepub. com/doi/suppl/10.1177/0361684318779537.
The kinase inhibitor PKC412 suppresses epiretinal membrane formation and retinal detachment in mice with proliferative retinopathies.

PURPOSE Platelet-derived growth factor (PDGF) is an important stimulatory factor for proliferative retinopathies. Expression of PDGF-B in the retinas of transgenic mice (hemizygous rho/PDGF-B mice) results in rapid-onset retinal detachment caused by proliferation of glial cells, endothelial cells, and pericytes, whereas expression of PDGF-AA (homozygous rho/PDGF-A or PDGF-AA mice) causes slowly progressive retinal detachment from proliferation of glial cells. In this study, we investigated the effect in rho/PDGF-B and rho/PDGF-AA mice of several different receptor kinase inhibitors. METHODS Hemizygous rhoPDGF-B or homozygous rho/PDGF-A mice were treated orally with PKC412 (an inhibitor of PDGF, VEGF, and c-kit receptor kinases and several isoforms of PKC), PTK787 (an inhibitor of PDGF, VEGF, and c-kit receptor kinases), SU1498 (an inhibitor of VEGF receptor kinases), imatinib mesylate (an inhibitor of PDGF, c-kit, and v-abl receptor kinases), or vehicle, and at appropriate time points epiretinal membrane (ERM) formation and retinal detachment were quantified. RESULTS In either rho/PDGF-B or rho/PDGF-A mice, oral administration of PKC412 or PTK787, but not SU1498 or imatinib mesylate, significantly reduced ERM formation. PKC412 reduced the incidence of severe retinal detachments in both models and PTK787 did so in homozygous rho/PDGF-A mice. CONCLUSIONS These data indicate that PKC412 (and possibly PTK787) has appropriate activity and sufficient intraocular bioavailability after oral administration to prevent retinal detachment in models of proliferative retinopathy. PKC412 should be considered for treatment of vascular and nonvascular proliferative retinopathies in humans.
Spatial-semantics: How users derive shape from information space

User problems with large information spaces multiply in complexity when we enter the digital domain. Virtual information environments can offer 3D representations, reconfigurations, and access to large databases that may overwhelm many users' abilities to filter and represent. As a result, users frequently experience disorientation in navigating large digital spaces to locate and use information. To date, the research response has been predominantly based on the analysis of visual navigational aids that might support users' bottom-up processing of the spatial display. In the present paper, an emerging alternative is considered that places greater emphasis on the top-down application of semantic knowledge by the user gleaned from their experiences within the sociocognitive context of information production and consumption. A distinction between spatial and semantic cues is introduced, and existing empirical data are reviewed that highlight the differential reliance on spatial or semantic information as the domain expertise of the user increases. The conclusion is reached that interfaces for shaping information should be built on an increasing analysis of users' semantic processing.
Considering Rendering Algorithms for In Situ Visualization

A diverse set of goals drive rendering algorithm research. The gaming industry, hardware manufacturers, and the film industry all contribute to this research. The field of scientific visualization uses methods from both as well developing its own. However, a portion of these algorithms may no longer be applicable as we move to exascale. The I/O gap is forcing scientific visualization to in situ based systems, and the in situ environment, at scale, is one of limited resources (i.e., time and memory). As a result, design decisions for different rendering algorithm implementations that were appropriate today may not be for in situ systems. In this paper, we survey the current research in rendering, then present a qualitative analysis based on in situ exascale use cases.
Variational Unsupervised Segmentation of Multi-Look Complex Polarimetric Images using a Wishart Observation Model

We address unsupervised variational segmentation of multi-look complex polarimetric images using a Wishart observation model via level sets. The methods consists of minimizing a functional containing an original data term derived from maximum likelihood Wishart approximation and a classical boundary length prior. The minimization is carried out efficiently by first order expansion of the data term and a new multiphase method which embeds a simple partition constraint directly in curve evolution. Results are shown on both synthetic and real images. Quantitative performance evaluation and comparisons with another method are also given.
47 v 2 2 0 O ct 1 99 7 Conserved Currents in Supersymmetric Quantum Cosmology ? ∗ †

In this paper we investigate whether conserved currents can be sensibly defined in su-persymmetric minisuperspaces. Our analysis deals with k = +1 FRW and Bianchi class–A models. Supermatter in the form of scalar supermultiplets is included in the former. Moreover , we restrict ourselves to the first-order differential equations derived from the Lorentz and supersymmetry constraints. The " square-root " structure of N=1 supergravity was our motivation to contemplate this interesting research. We show that conserved currents cannot be adequately established except for some very simple scenarios. Otherwise, equations of the type ∇ a J a = 0 may only be obtained from Wheeler-DeWitt–like equations, which are derived from the supersymmetric algebra of constraints. Two appendices are included. In appendix A we describe some interesting features of quantum FRW cosmologies with complex scalar fields when supersymmetry is present. In particular, we explain how the Hartle-Hawking state can now be satisfactorily identified. In appendix B we initiate a discussion about the retrieval of classical properties from supersymmetric quantum cosmologies.
An Agent-Based Simulation on the Market for Offenses

The equilibrium of the market for offenses using agentbased simulation is studied. One of the potential applications of it is to seek optimal policy in governing an open multi-agent system, especially when heterogeneous agents may behave maliciously. A theoretical work by Fender (1999) is chosen as the basic framework for the simulation. The simulation results show more detailed properties of the market equilibrium compared to those taken from theoretical analysis.
mproved classification of mammograms following idealized training

People often make decisions by stochastically retrieving a small set of relevant memories. This limited retrieval implies that human performance can be improved by training on idealized category distributions (Giguère & Love, 2013). Here, we evaluate whether the benefits of idealized training extend to categorization of real-world stimuli, namely classifying mammograms as normal or tumorous. Participants in the idealized condition were trained exclusively on items that, according to a norming study, were relatively unambiguous. Participants in the actual condition were trained on a representative range of items. Despite being exclusively trained on easy items, idealized-condition participants were more emory retrieval ecision making
Bayesian learning in neural networks for sequence processing

The Bayesian modelli ng framework, first applied to neural networks in [Buntine and Weigend, 1991], [MacKay, 1992] and [Neal, 1992], is appealing for several reasons. First, instead of obtaining an estimate for the mean prediction of the model, one gets an estimate for the entire distribution of model predictions. This estimate takes into account both the noise in the data and the variance of the models. Knowledge of this distribution can prove very useful in situations where the modeller needs to evaluate the risk associated to the prediction. Risk has many different causes and can be evaluated by various means, a survey of which is beyond the scope of this report. Second, Bayesian modelli ng relies heavily on the use of explicit priors defined over the space of models. Depending on one's prior knowledge of the problem, one can make use of a rather general, uninformative prior, or a very specific, highly informative prior. Unfortunately, it is not always easy to express the prior knowledge concerning the problem as a prior distribution over the space of available models. We suggest here a general, albeit computationally expensive procedure. We are mainly interested in modelli ng time-dependent non-linear processes. Because of their universal approximation properties, neural networks (see e.g. [Hornik et al., 1989], [Doya, 1993]) are a valuable tool for solving this kind of problems. However, the more general the tool, the more important is the proper use of priors. We propose here an extension of the Bayesian framework to the modelli ng of multivariate time-dependent data with feedforward and recurrent neural networks. Related experimental results will be presented elsewhere.
Semantics of Multimodal Network Models

A multimodal network (MMN) is a novel graph-theoretic formalism designed to capture the structure of biological networks and to represent relationships derived from multiple biological databases. MMNs generalize the standard notions of graphs and hypergraphs, which are the bases of current diagrammatic representations of biological phenomena, and incorporate the concept of mode. Each vertex of an MMN is a biological entity, a biot, while each modal hyperedge is a typed relationship, where the type is given by the mode of the hyperedge. The semantics of each modal hyperedge e is given through denotational semantics, where a valuation function f_{e} defines the relationship among the values of the vertices incident on e. The meaning of an MMN is denoted in terms of the semantics of a hyperedge sequence. A companion paper defines MMNs and concentrates on the structural aspects of MMNs. This paper develops MMN denotational semantics when used as a representation of the semantics of biological networks and discusses applications of MMNs in managing complex biological data.
Enhancement of GABA-activated membrane currents in aged Fischer 344 rat basal forebrain neurons [published erratum appears in J Neurosci 1995 Jul;15(7):following table of contents]

Changes in GABAergic systems have been widely documented during development. Similar changes might also occur during aging, but little information is currently available. Whole-cell and single-channel GABAA- activated currents were studied in acutely dissociated basal forebrain neurons. An age-related increase in whole-cell GABA currents was observed in cells from aged (19–25 month) Fischer 344 rats. The GABA current from aged animals displayed a greater maximum response, with no change in EC50 or slope of the GABA response curve. A reduction in use- dependent slow receptor desensitization was also observed in aged cells. Single-channel conductance and channel open time were unchanged with age, suggesting no alteration in the properties of single GABA channels. The benzodiazepine, midazolam, potentiated GABA currents to a greater degree in aged animals, consistent with previous reports of enhanced benzodiazepine activity with age. Ontogeny of the GABAA receptor/ion channel complex may continue through the stages of development, maturation, and aging.
Framing Resistance: Identifying Frames That Guide Resistance Interpretations at Work

Programs aimed at implementing change in organizations regularly experience high failure rates. Exploring resistance to change is one promising way to better understand what might be done to improve these rates. Resistance to change has often been envisioned as employee noncompliance with one-way change messages. This study instead conceptualizes resistance as an interpretive system between implementers and employees. The project developed a grounded typology of the interpretive structures that employees and implementers used to interpret others’ behaviors as resistance or not. Four frames (or cognitive schema) that guide resistance interpretations were identified: (a) disagreeability, (b) protecting role performance, (c) conflicting stakes, and (d) habitual environment. Analyses examined patterns in these frames. This work develops a map of resistance frames that researchers studying resistance to change, communication campaigns, and implementation communication will find useful.
Flow Editor: Semantic Web Service Composition Tool

Semantic web service is proposed to support the automation of service discovery, composition and invocation. However, it is still difficult for common users to compose semantic web services or generate them from web services. In order to alleviate such pains, in this paper we present Flow Editor: a visual semantic web service composition tool based on OWL-S specification. It has several advantages, including visual service composition by drag-and-drop, semi-automatic semantic web service generation, visual control construct supports and so on. In practice, the tool is already applied to help users solve realistic problems by creating and exporting new on-demand services.
Classification of human parasite eggs based on enhanced multitexton histogram

The Content-based image retrieval (CBIR) systems and their application in different areas of development, are current research topics, for that reason in this study content-based image retrieval is applied to classificate eight different human parasite eggs: Ascarias, Uncinarias, Trichuris, Dyphillobothrium-Pacificum, Taenia-Solium, Fasciola Hepática and Enterobius-Vermicularis, which are into the class of Helminthes, from their microscopic images. This proposed system includes two stages. In first stage, a feature extraction mechanism that is based on multitexton histogram descriptor (MTH) which has been improved and called `Enhanced MTH'. In second stage, an CBIR system has been implemented in orden to classificate the differents microscopic images to identify their correct species. Finally, simulation result shows overall success rates of 92,16% in the classification.