Miracle-dz/UniFAR-FTUs huggingface dataset:
Web service discovery and integration with QOS parameter using SOA based repository

Any Organization needs to manage and analyze its information. The source of this information may not be the same, organizations use different information system to support their different area of work. Different departments of organization use their specific information system and platform to maintain their own data. But some information is needed by different departments for co-ordination between these departments. The distributed Web Service is managed by registries is issue in the circumstances of a Web Services which is on distributed system. The recent registry is managed and offer for distributed service registries are explained. By this explanation, it was created that none of any given offer that the requirements of flexibility, availability and scalability is proved in terms of the management of the registries. Therefore, a QoS based registry is introduced in current paper. The system uses tmodel(technical model) for storing of the service registries. In this paper involves design and implementation of a UDDI with QoS parameter. It helps to find quality web services using SOAP (Simple Object Access Protocol) message. It serves two fold purposes; first to register quality web services. Second, find that service. A Software for the implementation of these aspects is contributed in this work.
Design considerations of inductor for 500 kVA PV inverter based on Euro efficiency

Inductors are very critical for the size, weight, and the efficiency in PV inverter system. The loss models of high frequency eddy current loss and the core loss of laminated silicon steel were built for both line frequency and high frequencies excitations. Then the total losses were analyzed which have complex relationship with winding turn numbers, foil thicknesses and the power ratings. Finally, the equivalent European efficiency considering the inductor's effect itself was analyzed to get the maximum EU efficiency for inductor winding design. The analysis and the results were based on a 500kVA 3-phase PV inverter.
Dynamic Detection of Process-Hiding Kernel Rootkits

Stealth rootkits that hide themselves on victim systems pose a major threat to computer systems. They are usually evasive as they use sophisticated stealth techniques to conceal files, processes, kernel modules, and other types of objects, making it extremely challenging to detect their presence in the victim system. However, current detection techniques are mostly system-specific and ineffective for unknown rootkits. In this paper, we present the design, implementation and evaluation of XView, a dynamic cross-view based approach to detect rootkits by identifying hidden processes. To this end, we continuously maintain a list of active processes outside the monitored system, and compare it with the list reported by the guest system. XView overcomes the semantic gap by intercepting and interpreting system call events of the guest operating system in a non-intrusive manner. It dynamically monitors the guest system and reconstructs semantic-level process information. Since it is not directed against any specific hiding techniques, it is able to detect unknown rootkits. We have developed an XView prototype and conducted experiments using eleven rootkit samples. Our evaluation results show that XView is able to identify processhiding behaviors of all samples with modest performance
Infinite Horizon LQ Optimal Control for Discrete-Time Stochastic Systems

This paper is concerned with the infinite horizon linear quadratic (LQ) optimal control for discrete-time stochastic systems with both state and control-dependent noise. Under assumptions of stabilization and exact observability, it is shown that the optimal control law and optimal value exist, and the properties of the associated discrete algebraic Riccati equation (ARE) are also discussed
Means and Meanings in Health Psychology

Developments in European Health Psychology over the last 20 years can be characterised by changes in the theoretical frameworks and methods used. Two developments are noted. First, we are increasingly focussed on a smaller set of theories, which makes the discipline more cohesive and potentially more successful as a cumulative science. Second, our research is gaining a greater degree of emphasis on intervention rather than simply observation, with resulting changes to the research designs and methods we use.
Epidemiology of Staphylococcus aureus colonization in nursing home residents.

BACKGROUND We sought to characterize the clinical and molecular epidemiologic characteristics of Staphylococcus aureus colonization (especially extranasal colonization) and to determine the extent to which community-associated methicillin-resistant S. aureus (MRSA) has emerged in community nursing homes. METHODS The study enrolled a total of 213 residents, with or without an indwelling device, from 14 nursing homes in southeastern Michigan. Samples were obtained from the nares, oropharynx, groin, perianal area, wounds, and enteral feeding tube site. Standard microbiologic methods were used to identify methicillin-susceptible S. aureus and MRSA. Molecular epidemiologic methods included pulsed-field gel electrophoresis, PCR detection of Panton-Valentine leukocidin, and SCCmec and agr typing. RESULTS One hundred thirty-one residents (62%) were colonized with S. aureus (MRSA colonization in 86). S. aureus colonization occurred in 80 (76%) of 105 residents with indwelling devices and in 51 (47%) of 108 residents without indwelling devices (P<.001). Of the 86 residents who were colonized with MRSA, nares culture results were positive for only 56 (65%). Residents with devices in place were more likely to be colonized at multiple sites. Eleven different strains of MRSA were identified by pulsed-field gel electrophoresis. Seventy-three residents (85%) were colonized with hospital-associated SCCmec II strains, and 8 (9%) were colonized with community-associated SCCmec IV strains, 2 of which carried Panton-Valentine leukocidin. CONCLUSIONS Extranasal colonization with MRSA is common among nursing home residents-particularly among residents with an indwelling device. We documented the emergence of community-associated SCCmec IV MRSA strains in the community nursing home setting in southeastern Michigan.
Analysis of Medical Treatments Using Data Mining Techniques

Since in health care systems the amount of data is continuously growing, data mining techniques can be applied to analyse these large collections and gain interesting insights. However, some critical issues should be properly addressed. For example, data collections on patient treatments are usually characterized by an inherent sparseness and variable distribu- tion, due to the large variety of possible treatments performed by patients affected by a given disease. To effectively extract interesting knowledge from such collections, we present a frame- work coupling a clustering and a classification algorithm. The clustering approach is named multiple-level because we apply the clustering algorithm in a multiple-level fashion, by focusing on different dataset portions and locally identifying groups of patients with similar profile and examination history. The classification algorithm is used to characterize the discovered clusters. This paper also describes future research issues and possible developments of the proposed framework. Index Terms—Data mining, cluster analysis, classification anal- ysis, medical records, patient examination history.
Triangular-Patch Based Texture Synthesis over Arbitrary Surfaces

We present an improved texture synthesis algorithm over arbitrary surfaces in this paper. The algorithm adopt the searching strategy of restriction degree to compute the texture coordinates of each triangular patch. It reduces the restrictive conditions as searching for the best matching patches and debases the complexity of the algorithm at the same time. Then aiming at the local boundary unmatching phenomenon, we find the best cut path between the overlap regions through extending graph cut technique. In particular, we combine the texture synthesis algorithm with illumination model to gain more natural effect. The results show that our solution fits to a wide range of sample textures and arbitrary surfaces.
A Pseudo-Sequential Choice Model for Valuing Multi-Attribute Environmental Policies or Programs in Contingent Valuation Applications

The assumption of independence of irrelevant alternatives in a sequential contingent valuation format should be questioned. Statistically, most valuation studies treat nonindependence as a consequence of unobserved individual effects. Another approach is to consider an inferential process in which any particular choice is part of a general choosing strategy of a survey respondent. A stochastic model is suggested, consistent with the reflexivity, transitivity, and continuity axioms of utility analysis. An application of this theoretical model to the valuation of watershed ecosystem restoration demonstrates that an empirical model recognizing reflexivity and transitivity, and also allowing for continuity, shows the highest in-sample predictive ability.
Universally Consistent Latent Position Estimation and Vertex Classification for Random Dot Product Graphs

Abstract In this work we show that, using the eigen-decomposition of the adjacencymatrix, we can consistently estimate latent positions for random dot productgraphs provided the latent positions are i.i. d. from some distribution. If classlabels are observed for a number of vertices tending to inﬁnity, then we showthat the remaining vertices can be classiﬁed with error converging to Bayes opti-mal using the k -nearest-neighbors classiﬁcation rule. We evaluate the proposedmethods on simulated data and a graph derived from Wikipedia. 1 Introduction The classical statistical pattern recognition setting involves( X , Y ),( X 1 , Y 1 ),. ,( X n , Y n ) i . i˘ . d . F X , Y ,where the X i : 7! R d are observed feature vectors and the Y i : 7! f0,1gare ob-served class labels for some probability space . We deﬁne D=f( X i , Y i )gas the train-ing set. The goal is to learn a classiﬁer h (;D): R d ! f0,1gsuch that the probability oferror P[ h ( X ;D)6= Y jD]approaches Bayes optimal as n ! 1for all distributions
A combination approach for Web Page Classification using Page Rank and Feature Selection Technique

With the rapid increase in the number of Internet users, there is a constantly increasing requirement for automatic classification techniques with greater classification accuracy. Existing algorithms are based on the text content of the web pages for classification. However, the web pages classified using text content may not yield desired results if the keywords are irrelevantly specified. This provides scope for implementing feature reduction techniques with page ranking on web pages so as to get desired results within less time and greater accuracy. Only then information on the web can be used effectively by the users. In this paper, we propose a unique method for classification of web pages by applying feature selection technique along with page rank. The aim is to improve the classification and search time of web contents so as to provide accurate and speedy results to the users.
Gendered Satisfaction about Quality of Life of Indian Elderly: An Inspection

Gender and aging have been the topic of primary interest for researchers of social sciences in recent period of time due to their growing importance, dynamism and diversified aspects. In this context, this study tries to bring in a new dimension in light through understanding of the difference about perception of quality of life of among male and female elderly in relevance to various socioeconomic backgrounds. An inspection at national level is being done using the WHO-SAGE, 2007 elderly data to understand how gender and economic status simultaneously plays a role determining the level of satisfaction about life in elderly. Bivariate analysis along with some multinomial logistic regression is carried out for this purpose. The study finds that overall satisfaction about the quality of life in higher in female elderly as compared to male. Interestingly, poor elderly women are more unsatisfied compared to their counterparts. Thus, there is a need for deeper introspection to understand this scenario in context of the extent of economic deprivation along with other social discrimination faced my poor female elderly, which may lead to genuine help in changing policy measure and enhance the welfare of elderly women in the country.
Bayesian Network based sequential collision avoidance action execution for an Ocean Navigational System

This paper focuses on a study of the sequential action execution module for a collision avoidance system in ocean navigation. The overall decision-action process of collision avoidance consists on a Fuzzy logic based parallel decision making module and those decisions are formulated into collision avoidance actions by a Bayesian network based sequential action execution module. The presented collision avoidance system is capable of making multiple sequential actions to avoid complicated collision situations involving multiple vessels in ocean navigation while still respecting the COLREGs rules and regulations.
Evaluation of the affective valence of speech using pitch substructure

In order to study the relationship between emotion and intonation, a new technique is introduced for the extraction of the dominant pitches within speech utterances and the quasi-musical analysis of the multipitch structure. After the distribution of fundamental frequencies over the entire utterance has been obtained, the underlying pitch structure is determined using an unsupervised "cluster" (Gaussian mixtures) algorithm. The technique normally results in 3-6 pitch clusters per utterance that can then be evaluated in terms of their inherent dissonance, harmonic "tension", and "major or minor modality". Stronger dissonance and tension were found in utterances with negative affect, relative to utterances with positive affect. Most importantly, utterances that were evaluated as having positive or negative affect had significantly different modality values. Factor analysis showed that the measures involving multiple pitches were distinct from other acoustical measures, indicating that the pitch substructure is an independent factor contributing to the affective valence of speech prosody.
The Dynamics of Boundary Layer Jets within the Tropical Cyclone Core. Part II: Nonlinear Enhancement

Abstract Observations of wind profiles within the tropical cyclone boundary layer until recently have been quite rare. However, the recent spate of observations from the GPS dropsonde have confirmed that a low-level wind speed maximum is a common feature of the tropical cyclone boundary layer. In Part I, a mechanism for producing such a maximum was proposed, whereby strong inward advection of angular momentum generates the supergradient flow. The processes that maintain the necessary inflow against the outward acceleration due to gradient wind imbalance were identified as being (i) vertical diffusion, (ii) vertical advection, and (iii) horizontal advection, and a linear analytical model of the boundary layer flow in a translating tropical cyclone was presented and used to diagnose the properties of the jet and the near-surface flow. A significant shortcoming was that the jet was too weak, which was argued to be due to the neglect of vertical advection. Here, a high-resolution, dry, hydrostatic, numerical .
STP: In-network aggregation through proximity queries in a Sensor Network

Event detection and notification is a common task in a Wireless Sensor Networks (WSN). Efficient data aggregation and minimization of energy consumption are the great research challenges in WSN. In WSN, aggregated event information is more important than individual event information for energy saving and reliability. Proximity queries or query approximation can be used to reduce the complexity of data aggregation and energy consumption. This paper presents an efficient and scalable hybrid framework for processing spatial and temporal proximity queries in WSN which we call STP. STP builds tree structure with less overhead, and reduces the event propagation cost through proximity queries. STP reduces energy consumption by reducing the number of aggregator nodes, which ultimately increases the network life time. STP eliminates the unnecessary aggregation of events using a tunable temporal proximity threshold. We compare STP's performance with another spatial query processing method and we show that, STP performs better.
Mutated Human SOD1 Causes Dysfunction of Oxidative Phosphorylation in Mitochondria of Transgenic Mice*

A growing body of evidence suggests that impaired mitochondrial energy production and increased oxidative radical damage to the mitochondria could be causally involved in motor neuron death in amyotrophic lateral sclerosis (ALS) and in familial ALS associated with mutations of Cu,Zn superoxide dismutase (SOD1). For example, morphologically abnormal mitochondria and impaired mitochondrial histoenzymatic respiratory chain activities have been described in motor neurons of patients with sporadic ALS. To investigate further the role of mitochondrial alterations in the pathogenesis of ALS, we studied mitochondria from transgenic mice expressing wild type and G93A mutated hSOD1. We found that a significant proportion of enzymatically active SOD1 was localized in the intermembrane space of mitochondria. Mitochondrial respiration, electron transfer chain, and ATP synthesis were severely defective in G93A mice at the time of onset of the disease. We also found evidence of oxidative damage to mitochondrial proteins and lipids. On the other hand, presymptomatic G93A transgenic mice and mice expressing the wild type form of hSOD1 did not show significant mitochondrial abnormalities. Our findings suggest that G93A-mutated hSOD1 in mitochondria may cause mitochondrial defects, which contribute to precipitating the neurodegenerative process in motor neurons.
An improved four-component decomposition with distributed double-bounce scattering model

This paper proposes an improved four-component scattering decomposition scheme with modified double-bounce scattering model for the analysis of polarimetric synthetic aperture radar (POLSAR) data. In the Yamaguchi decomposition, it occurs occasionally for some pixels with negative surface scattering power Ps and/or negative diplane scattering power Pd because the whole HV cross-polarized component is assigned to volume scattering due to vegetation; and it is also difficult to discriminate man-made buildings not orthogonal to the radar LOS from vegetation. In advance the conditions of the emergence of negative powers in the Yamaguchi decomposition are given out, and three corresponding processing methods adopted in many improved four-component target decompositions are reviewed in the paper. Then the expression of the coherency matrix of distributed dielectric dihedral corner reflectors is derived. The expression demonstrates that distributed dielectric dihedral corner reflectors also will generate HV cross-polarized component. The new target decomposition utilizes the new double bounce model of distributed dielectric dihedral corner reflectors instead of the original one adopted by the Freeman and Yamaguchi decompositions. In order to solve the new decomposition, we introduce normalize circular-pol correlation coefficients to characterize the percentage of HV scattering component generated by distributed dielectric dihedral corner reflectors. An airborne L band quad-pol data acquired by DLR ESAR sensor over Oberpfaffenhoffen in German are applied to the improved decomposition scheme. Experimental results demonstrate that the new decomposition method can reduce the pixels with negative powers and obtain correct scattering mechanisms of non-reflection structures not paralleled to the flight path.
Nuclear magnetic resonance: A quantum technology for computation and spectroscopy

In this article we consider nuclear magnetic resonance (NMR) as an example of a quantum technology; we consider in particular detail the implementation of quantum computers using NMR. We begin by outlining the physical principles underlying NMR, and give an introduction to the quantum mechanics involved. We next discuss the general characteristics of quantum technologies and the ways and extent to which these characteristics are expressed in NMR. We then give an introduction to the subject of quantum computation and its implementation using NMR. Finally, we describe some spectroscopy techniques which also exploit the quantum nature of NMR.
Solution for Search Result Clustering by Using Singular Value Decomposition

There are many search engines in the Web, but they return a long list of search results, ranked by the irrelevancies to the given query. Web users have to go through the list and examine the titles and (short)snippets sequentially to identify their required results.In this paper we present how usage of Singular Value Decomposition (SVD) as a very good solution for search results clustering.
GAIT RECOGNITION BASED ON PAL AND PAL ENTROPY WITH CBIR USING SVM

Recognition of any individual is a task to identify people. The recognition techniques like face, finger prints, and iris scan mainly require a co-operation by subject, physical contact or near proximity. Such methods were not able to identify an individual at distance hence recognition by using gait biometric is comparatively new biometric technique beyond such disadvantages. Human identification by using Gait is method for identifying a person by the walking or way of moving on foot. This paper aims to recognize a person by using the gait features. Still the most of current approaches are model free which is easy and fast although in this paper PAL and PAL ENTROPY approach is used for feature extraction with CBIR for performing matching of parameters with database sequences. After matching of parameters CCR will be obtained using Support Vector Machine technique. Some experimental results will show the effectiveness of
Promotion of Reprogramming to Ground State Pluripotency by Signal Inhibition

Induced pluripotent stem (iPS) cells are generated from somatic cells by genetic manipulation. Reprogramming entails multiple transgene integrations and occurs apparently stochastically in rare cells over many days. Tissue stem cells may be subject to less-stringent epigenetic restrictions than other cells and might therefore be more amenable to deprogramming. We report that brain-derived neural stem (NS) cells acquire undifferentiated morphology rapidly and at high frequency after a single round of transduction with reprogramming factors. However, critical attributes of true pluripotency—including stable expression of endogenous Oct4 and Nanog, epigenetic erasure of X chromosome silencing in female cells, and ability to colonise chimaeras—were not attained. We therefore applied molecularly defined conditions for the derivation and propagation of authentic pluripotent stem cells from embryos. We combined dual inhibition (2i) of mitogen-activated protein kinase signalling and glycogen synthase kinase-3 (GSK3) with the self-renewal cytokine leukaemia inhibitory factor (LIF). The 2i/LIF condition induced stable up-regulation of Oct4 and Nanog, reactivation of the X chromosome, transgene silencing, and competence for somatic and germline chimaerism. Using 2i /LIF, NS cell reprogramming required only 1–2 integrations of each transgene. Furthermore, transduction with Sox2 and c-Myc is dispensable, and Oct4 and Klf4 are sufficient to convert NS cells into chimaera-forming iPS cells. These findings demonstrate that somatic cell state influences requirements for reprogramming and delineate two phases in the process. The ability to capture pre-pluripotent cells that can advance to ground state pluripotency simply and with high efficiency opens a door to molecular dissection of this remarkable phenomenon.