Miracle-dz/UniFAR-FTUs huggingface dataset:
Service-oriented computing

Service-oriented Architectures (SOA) facilitate the dynamic and seamless integration of services offered by different service providers which in addition can be located in different trust domains. Especially for business integration scenarios, Federated Identity Management emerged as a possibility to propagate identity information as security assertions across company borders in order to secure the interaction between different services. Although this approach guarantees scalability regarding the integration of identity-based services, it exposes a service provider to new security risks. These security risks result from the complex trust relationships within a federation. In a federation the authentication of a user is not necessarily performed within the service provider’s domain, but can be performed in the user’s local domain. Consequently, the service provider has to rely on authentication results received from a federation partner to enforce access control. This implies that the quality of the authentication process is out of control by the service provider and therefore becomes a factor which needs to be considered in the access control step. In order to guarantee a designated level of security, the quality of the authentication process should be part of the access control decision. To ease this process, we propose in this paper a method to rate authentication information by a level of trust which describes the strength of an authentication method. Additionally, in order to support the concept of a two-factor authentication, we also present a mathematical model to calculate the trust level when combining two authentication methods. Quantitative Trust Management (QTM) provides a dynamic interpretation of authorization policies for access control decisions based on upon evolving reputations of the entities involved. QuanTM, a QTM system, selectively combines elements from trust management and reputation management to create a novel method for policy evaluation. Trust management, while effective in managing access with delegated credentials (as in PolicyMaker and KeyNote), needs greater flexibility in handling situations of partial trust. Reputation management provides a means to quantify trust, but lacks delegation and policy enforcement. This paper reports on QuanTM’s design decisions and novel policy evaluation procedure. A representation of quantified trust relationships, the trustdependency graph, and a sample QuanTM application specific to the KeyNote trust management language, are also proposed.
ul 2 00 4 NEAR-IR SUB-ARCSECOND OBSERVATIONS OF ULTRACOMPACT H ii REGIONS 1

We present adaptive-optics (AO) assisted J , H and K/K ′ images of 8 ultra-compact H ii regions (UC H iis) taken with the ALFA and ADONIS AO systems at Calar Alto and La Silla observatories. The images show details of the stellar population and the near-IR morphology of UC H iis with unprecedented resolution. We have searched for the ionizing sources of the regions using near-IR photometry. The spectral type of the ionizing and most luminous stars inferred from our photometry has been compared with spectral type estimates from IRAS and published radio-continuum measurements. We find that the photometric near-IR spectral types are earlier than estimates from radio and IRAS data. This difference is alleviated when stellar spherical models including line blanketing and stellar winds instead of non-LTE plane-parallel models are used to derive the radioand IRAS-based spectral types. We also made an attempt to correlate the properties of the near-IR ionizing population with MSX data and published CS measurements. No correlation was found. We note that in two of the regions (G309.92+0.48 and G61.48+0.09B1), the best candidate to ionize the region is possibly a super-giant. Subject headings: H II regions: general — infrared: ISM — instrumentation: adaptive optics, high angular resolution — catalogs
The SinBiota 2.0 Biodiversity Information System

For the last 10 years, Sin Biota, the information system of the Biota-FAPESP Program, has served the community storing and displaying data in maps, and providing a common base for researchers in different areas to communicate and exchange biodiversity data. State administration has also used the system to support new laws and regulations. Now it is time to rethink the system, which has grown in an ad-hoc, unstructured way, aiming at the support that will be needed for the next 10 years. In a project jointly funded by Microsoft Research and FAPESP, we aim at the creation of a specification for the new Sin Biota 2.0 system, including cutting-edge services and technologies on information technology, in order to achieve a number of goals, namely: guarantee the use and expansion of the system for the next ten years, support the availability of a larger volume of higher quality environmental data, oriented also to the educational and public administration sectors, provide more efficient sharing of data among BIOTA researchers, inter-operate with international initiatives, provide effective tools to assist researchers in finding relevant information amongst a large amount of environment data. The expected results at the end of this project are the composition of a specification (Reference Document) of the Sin Biota 2.0 system, and the implementation of a prototype that will gradually replace the current system. We propose in this work the system architecture and our vision of the main features that would allow Sin Biota 2.0 to meet the expectations of the biodiversity research community and other stakeholders. We also describe a prototype application that implements most of the features present in the current Sin Biota 1.0 system, as well as some of the new features envisaged for the new version.
Characterizing the Machine Learning Capabilities of General-Purpose CPUs

Machine learning is a ever-growing field, with many people interested in trying it out on their own. While there is specialized hardware to run machine learning algorithms, it costs a considerable amount to invest into even the low-end devices. Those who are merely curious will find themselves using what hardware they have their laptops, desktops, and tablets to run machine learning applications. There exist test benches and published results for most processors, but machine learning operations are not part of the widespread tests. There also exist machine learning test benches, but they are specialized for more powerful hardware. This thesis finds the intersection of the two, characterizing the machine learning capabilities of general-purpose CPU’s using DeepBench, Baidu’s machine learning test bench, and VTune Amplifier, Intel’s hardware analysis tool, in order to inform people what they should expect when running machine learning algorithms on their generalpurpose devices. We find that of the two main machine learning operations, matrix multiply and convolution, matrix multiplication performs well on most machines, while convolution has mixed results.
ECF Estimation of Markov Models Where the Transition Density is Unknown

In this paper, we consider the estimation of Markov models where the transition density is unknown. The approach we propose is based on the empirical characteristic function estimation procedure with an approximate optimal weight function. The approximate optimal weight function is obtained through an EdgeworthsGram--Charlier expansion of the logarithmic transition density of the Markov process. We derive the estimating equations and demonstrate that they are similar to the approximate maximum likelihood estimation (AMLE). However, in contrast to the conventional AMLE our approach ensures the consistency of the estimator even with the approximate likelihood function. We illustrate our approach with examples of various Markov processes. Monte Carlo simulations are performed to investigate the finite sample properties of the proposed estimator in comparison with other methods. Copyright The Author(s). Journal compilation Royal Economic Society 2010.
Cellular senescence in aging and osteoarthritis

Abstract — It is well accepted that age is an important contributing factor to poor cartilage repair following injury, and to the development of osteoarthritis. Cellular senescence, the loss of the ability of cells to divide, has been noted as the major factor contributing to age-related changes in cartilage homeostasis, function, and response to injury. The underlying mechanisms of cellular senescence, while not fully understood, have been associated with telomere erosion, DNA damage, oxidative stress, and inflammation. In this review, we discuss the causes and consequences of cellular senescence, and the associated biological challenges in cartilage repair. In addition, we present novel strategies for modulation of cellular senescence that may help to improve cartilage regeneration in an aging population.
Students' Attitudes toward Teacher Use of Technology in Classrooms.

Malia M. Hoffmann is an assistant professor in the Department of Bilingual and Elementary Education in the College of Education at California State University, Fullerton. A. Y. “Fred” Ramirez is a professor in the School of Education at Concordia University Irvine, Irvine, California. Alavi, 2016). And again, in English Language Arts courses, it has been shown there is a need for teacher professional development in student-focused technology use since the learning of English increases greatly with the integration of technology in academic classes (Davidson, Richardson, & Jones, 2014). Student-centered technologies have not only increased student motivation and academic performance, but interactive technologies can lead to differentiated instruction through which students have again shown higher motivation. Interactive technology is changing the philosophy of technological and pedagogical instruction by allowing teachers to adapt their lessons to the differing needs of students (Levin & Wadmany, 2006). Due to this development of student-centered technologies, pre-service teacher education is able to adapt to meet the needs of 21st century students and teachers (Mulholland, 2006; Janssen & Lozaonder, 2015). Along with technology training, research is needed to analyze whether teachers are integrating the technology that they they are learning in their professional development sessions or other technology trainings in their classrooms (Rehmat, & Bailey, 2014). However, it has been found that the number of technology trainings held and attended by teachers is not an accurate indicator of actual application within teachers’ classrooms. It has been demonstrated that attendance at technology workshops given by school districts does not predict technology use within teachers’ classrooms (Brzycki & Dudt, 2005), even when Introduction
Segmentation of On-line Handwritten Japanese Characters of Arbitrary Line Direction Using SVM(Internationa Session 6)

Bilan Zhu and Masaki Nakagawa Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei, Tokyo 184-8588, Japan E-mail: {zhubilan, nakagawa}@cc.tuat. ac.jp Abstract This paper describes a method of producing segmentation point candidates for on-line handwritten Japanese text by a support vector machine (SVM) to improve text recognition. This method extracts multi-dimensional features from on-line strokes of handwritten text and applies the SVM to the extracted features to produces segmentation point candidates. This paper also shows the details of generating segmentation point candidates in order to achieve high discrimination rate by finding the optimal combination of the segmentation threshold and the concatenation threshold. We compare the method for segmentation by the SVM with that by a neural network (NN) and show the result that the method by the SVM bring about a better segmentation rate and character recognition rate.
A Two-Step Knowledge Extraction Framework for Improving Disease Diagnosis

In the last decades, various methodologies have been proposed by the researchers for developing effective disease diagnosis support systems (DDSSs). The present research proposes a two-step framework in which an entropy-based feature-selection approach is introduced in the first step and a rule-base hybrid model using Perfect Rule Induction by Sequential Method (PRISM) is explored in the subsequent step for effective diagnosis of diseases. The suggested feature-selection technique is validated using five state-of-the-art classifiers namely C4.5 (a decision tree-based classifier), naïve Bayes (NB), Repeated Incremental Pruning to Produce Error Reduction (RIPPER), neural network (NN) and support vector machine (SVM) over fourteen benchmark diseases that are very common and the leading causes of deaths. Next, on the basis of top three performance metrics, viz., prediction accuracy, sensitivity and false positive rate, the performance of the hybrid model over the datasets is compared with its base learner: PRISM, two other competent learners namely C4.5 and NN, and some specialized models. The empirical outcomes positively demonstrate that the hybrid model with application of feature-selection method is a generic model and effective in diagnosing diseases. More importantly, the model not only is able to produce good results but also to elucidate its knowledge in understandable: IF-THEN form (convenient for medical practitioners).
Towards standardisation of the Sensory Profile Checklist Revisited: Perceptual and Sensory Sensitivities in Autism Spectrum Conditions

Although sensory and perceptual symptoms have been associated with ASC from the time that autism was first defined as a diagnosis (Kanner, 1943), and despite many personal accounts from individuals, there is a long lasting debate whether sensory symptoms are a component of core ASC deficits or a co-morbid phenomenon. The current research aimed to explore the pattern of sensory and perceptual experiences in ASC using the Sensory Profile Checklist Revisted (SPCR; Bogdashina, 2003). The measure has been useful for guiding clinical intervention, but the structure, reliability and validity is yet to be analysed. The SPCR was completed by support workers based on their observations of 38 individuals with clinical diagnosis of ASC. 40 individuals from the general population also completed the measure based on their observations of someone they knew for more than 6 months. Reporting A principle components factor analysis using promax rotation was conducted for the SPCR, with 4 factors explaining 30.82% of the variance. Internal consistency was high with alphas ranging from . 90 to . 95. Principle axis factoring was used to analyse the factor structure of ASC traits underlying the AQ. The 3 factor solution, which explained 48.31 % of the variance, was chosen. Internal consistency was moderate to high, with alphas ranging from . 56 to . 92. Individuals with an ASC were found to score significantly higher on the SPCR than healthy controls (b=78.496, t(77)=4.577, p=. 05). AQ scores were found to have a significant effect on SPCR scores with a single score increase in AQ scores predictive of 3.49 point increase in SPCR scores (b=3.49, t(76)=4.795, p<. 05). ASP scores were found to have a significant effect on SPCR scores, with a single score increase in ASP scores predictive of 2.78 point increase in SPCR scores (b=2.78, t(36)=8.885, p<0.05). The results suggest that sensory and perceptual processing styles of individuals with ASC are significantly different to those of healthy controls. The extracted constructs differ from those originally suggested by Bogdashina (2003), however, it could be argued that wih tighter controls and a larger sample size, the extracted factors would be separated further. The high correlation between items of the SPCR and the AQ suggest that the SPCR is useful tool for evaluating the sensory and perceptual experiences of individuals with ASC. Whilst it cannot be claimed to aid diagnosis, the structure of the measure is such that it would be a useful tool for parents, carers and …
A Precise Distance Indicator: Type Ia Supernova Multicolor Light-Curve Shapes

We present an empirical method that uses multicolor light-curve shapes (MLCSs) to estimate the luminosity, distance, and total line-of-sight extinction of Type Ia supernovae (SNe Ia). The empirical correlation between the MLCSs and the luminosity is derived from a “ training set” of nine SN Ia light curves with independent distance and reddening estimates. We find that intrinsically dim SN Ia's are redder and have faster light curves than the bright ones, which are slow and blue. By 35 days after maximum, the intrinsic color variations become negligible. A formal treatment of extinction employing Bayes's theorem is used to estimate the best value and its uncertainty. Applying the MLCS method to both light curves and to color curves provides enough information to determine which supernovae are dim because they are distant, which are intrinsically dim, and which are dim because of extinction by dust. The precision of the MLCS distances is examined by constructing a Hubble diagram with an independent set of 20 SN Ia's. The dispersion of 0.12 mag indicates a typical distance accuracy of 5% for a single object, and the intercept yields a Hubble constant on the Sandage et al. Cepheid distance scale of H0 = 64 ± 3 (statistical) km s–1 Mpc–1 (±6 total error). The slope of 0.2010 ± 0.0035 mag over the distance interval 32.2 < μ < 38.3 yields the most precise confirmation of the linearity of the Hubble law.
Linguistic Diversity in the very Long Run

This paper presents an endogenous growth model in which language is an engine of growth. Language is an input into production and exchange: agents who can communicate easily are able to produce and consume more. At the same time, economic interaction among agents aects the evolution of language. The model can match a key stylized fact of historical linguistics|a global increase, followed by decline, in linguistic diversity. In addition, the model generates the endogenous creation and destruction of distinct linguistic groups.
Physical properties and culture-specific factors as principles of semantic categorisation of the Gújjolaay Eegimaa noun class system

1 This paper investigates the semantic bases of class membership in the noun class system of Gújjolaay Eegimaa (Eegimaa henceforth), a Niger-Congo and Atlantic language of the BAK group spoken in Southern Senegal. The question of whether semantic principles underlie the overt classification of nouns in Niger-Congo languages is a controversial one. There is a common perception of Niger-Congo noun class systems as being mainly semantically arbitrary. The goal of the present paper is to show that physical properties and culture-specific factors are central principles of semantic categorisation in the Eegimaa noun class system. I argue that the Eegimaa overt grammatical classification of nouns into classes is a semantic categorisation system whereby categories are structured according to prototypicality, family resemblance, metaphorical and metonymic extensions and chaining processes, as argued within the framework of Cognitive Linguistics. I show that the categorisation of entities in the Eegimaa nominal classification system productively makes use of physical properties such as shape as well as using culture-specific, less productive parameters for the semantic categorisation of entities denoted by nouns. The analysis proposed here also shows that the cases of multiple morphosyntactic classifications of nouns reflect multiple conceptual categorisation strategies. A detailed examination of 1 This paper is the result of research funded by the University of London Central Research Fund and the SOAS-Endangered Languages Documentation Programme (FTG0021 & IPF-0141). I am very grateful to the Associate Editor and the anonymous reviewers for their thorough comments and suggestions. I also wish to express my gratitude to Professor Eva Schultze-Berndt for her invaluable comments on different versions of this paper. Finally, I owe a debt of thanks to Mrs Hannah Gibson, Dr Yuni Kim, Mr Samuel A. Atintono and Dr Jonh Löwenadler for reading and commenting on this paper. The above readers are not responsible for any residual errors or strong claims made in this article.
Investigation of Station Service Transformer Ferroresonance in Manitoba Hydro's 230-kV Dorsey Converter Station

An investigation of ferroresonance in a 230-kV transformer is undertaken. Correct modelling of the iron-core losses and the direct magnetic coupling between phases are shown to be important in duplicating field observations. A brute-force time-domain method and an analytical method for displaying margins to fer- roresonance on a parameter plane are compared. Fol- lowing proposed bus modifications, it is shown that loading resistors may now be made switchable.
Simulation Exercises as a Patient Safety Strategy

Simulation is a versatile technique used in a variety of health care settings for a variety of purposes, but the extent to which simulation may improve patient safety remains unknown. This systematic review examined evidence on the effects of simulation techniques on patient safety outcomes. PubMed and the Cochrane Library were searched from their beginning to 31 October 2012 to identify relevant studies. A single reviewer screened 913 abstracts and selected and abstracted data from 38 studies that reported outcomes during care of real patients after patient-, team-, or system-level simulation interventions. Studies varied widely in the quality of methodological design and description of simulation activities, but in general, simulation interventions improved the technical performance of individual clinicians and teams during critical events and complex procedures. Limited evidence suggested improvements in patient outcomes attributable to simulation exercises at the health system level. Future studies would benefit from standardized reporting of simulation components and identification of robust patient safety targets.