Miracle-dz/UniFAR-FTUs huggingface dataset:
Advantages of thesaurus representation using the Simple Knowledge Organization System (SKOS) compared with proposed alternatives

espanolIntroduccion. Se muestra un analisis comparativo de SKOS frente a otras alternativas para la representacion de tesauros en la Web Semantica. Metodologia. Partiendo de los cambios funcionales y estructurales de los tesauros, se ofrece una vision actual abandonando el paradigma lexico en favor del paradigma conceptual, describiendose diversas iniciativas de representacion de tesauros usando vocabularios RDF para su aplicacion en la Web Semantica, dedicando especial atencion a SKOS. Analisis y resultados. La comparacion nos permite conocer los aspectos trascendentales en un modelo de representacion de tesauros. SKOS incorpora las principales organizando los conceptos en esquemas y colecciones. Las nociones de terminos descriptores y no-descriptores se sustituyen por la asociacion a conceptos de etiquetas preferentes y alternativas y es posible definir relaciones jerarquicas o asociativas entre conceptos. SKOS tambien contempla establecer correspondencias entre conceptos de esquemas conceptuales diferentes. Conclusiones. Se justifica la opcion de SKOS como mejor alternativa para el desarrollo de aplicaciones de gestion de tesauros en sistemas de informacion Web en especial si se considera el punto de vista del usuario. EnglishIntroduction. This paper presents an analysis of the Simple Knowledge Organization System (SKOS) compared with other alternatives for thesaurus representation in the Semantic Web. Method. Based on functional and structural changes of thesauri, provides an overview of the current context in which lexical paradigm is abandoned in favour of the conceptual paradigm. Likewise are described briefly various initiatives for the representation of thesauri using RDF vocabularies and hence for application to the Semantic Web, with particular attention to SKOS. Analysis and Results. This brief comparison will allow us to know some highlights of these proposals to raise those transcendental aspects in a model representing thesauri. SKOS includes the main proposal of this model, which organizes the concepts into diagrams and libraries. The notions of descriptors and non-descriptors terms are replaced by the association to the concepts of preferred and alternative labels and may be defined hierarchical or associative relationships between concepts. SKOS also provides for the establishment of correspondence relations between concepts belonging to different conceptual schemes. Conclusions. In accordance with the extent to which this series of requirements is fulfilled, we propose and defend the SKOS option as the best alternative for the development of multiple applications focusing on the use of thesauri in Web-based information services and systems, highlighting the advantages of this model over others proposed and in consideration of the user perspective in management, search and information query operations.
SQL-SA for big data discovery polymorphic and parallelizable SQL user-defined scalar and aggregate infrastructure in Teradata Aster 6.20

There is increasing demand to integrate big data analytic systems using SQL. Given the vast ecosystem of SQL applications, enabling SQL capabilities allows big data platforms to expose their analytic potential to a wide variety of end users, accelerating discovery processes and providing significant business value. Most existing big data frameworks are based on one particular programming model such as MapReduce or Graph. However, data scientists are often forced to manually create adhoc data pipelines to connect various big data tools and platforms to serve their analytic needs. When the analytic tasks change, these data pipelines may be costly to modify and maintain. In this paper we present SQL-SA, a polymorphic and parallelizable SQL scalar and aggregate infrastructure in Aster 6.20. This infrastructure extends Aster 6's MapReduce and Graph capabilities to support polymorphic user-defined scalar and aggregate functions using flexible SQL syntax. The implementation enhances main Aster components including query syntax, API, planning and execution extensively. Integrating these new user-defined scalar and aggregate functions with Aster MapReduce and Graph functions, Aster 6.20 enables data scientists to integrate diverse programming models in a single SQL statement. The statement is automatically converted to an optimal data pipeline and executed in parallel. Using a real world business problem and data, Aster 6.20 demonstrates a significant performance advantage (25%+) over Hadoop Pig and Hive.
Semantic Relatedness in Folksonomy

Social networking sites like Flickr , Youtube and Del.icio. us have been rapidly gaining popularity on the Internet, underscoring a transformation of the Web to a participatory medium in which users are actively creating, evaluating and distributing information. With this process, social tagging systems, which allow users to interactively annotate a pool of shared resources using descriptive tags, have enjoyed phenomenal success in recent years. Folksonomy are data created in social tagging. Tags in folksonomy reflect users’ collaborative cognition on information. They can reveal both the users’ behavior and resources’ properties. In this paper, we will study the vocabulary of users’ tagging and the relationship between words. We connect tags by users collaborative tagging to form a network of folksonomy, and investigate the semantic relatedness between tags within it. The result shows that the links within this network have relatively strong semantic relatedness, which is useful for designing future folksonomy-based systems.
Predictable Design of Network-Based Covert Communication Systems

This paper presents a predictable and quantifiable approach to designing a covert communication system capable of effectively exploiting covert channels found in the various layers of network protocols. Two metrics are developed that characterize the overall system. A measure of probability of detection is derived using statistical inference techniques. A measure of reliability is developed as the bit error rate of the combined noisy channel and an appropriate error-correcting code. To support reliable communication, a family of error-correcting codes are developed that handle the high symbol insertion rates found in these covert channels. The system metrics are each shown to be a function of the covert channel signal-to-noise ratio, and as such the two can be used to perform system level design trade-offs. Validation of the system design methodology is provided by means of an experiment using real network traffic data.
A general parameterized mathematical food web model that predicts a stable green world in the terrestrial ecosystem

Terrestrial ecosystems are generally green with vegetation and only a small part ( Pcc > 0); plants are less nutritive than animals (np < nh, nc); and carnivore searches huge volume daily while eating speed of herbivore is limited (S _ eh). These conditions are well-realized in aboveground terrestrial ecosystems where plant-rich “green worlds” are common, vs. animal-rich belowground and aquatic ecosystems where some conditions are not realized. The h and c calculated from our model agreed well with those from empirical observations in forest ecosystems, where both h and c are within an order of magnitude of 100 mg (fresh biomass/m2 forest), and in savannah ecosystems. The model predicts that plant nutritive value np, digestibility of plants by herbivores αh, and herbivore eating speed eh are positively correlated with h and the intensity of herbivory, which theoretically explains the outdoor defensive effects of plant anti-nutritive or quantitative defenses (e.g., tannins, protease inhibitors), and predicts that c and the carnivore/herbivore ratio c/h are positively correlated with the relative growth rate of herbivores Gh. The present model introduced parameterized realities into food web theory that previous models lack.
A Threshold Signature Scheme with a Weakened Trusted Party

In the (t, n) threshold signature schemes with the assistance of a trusted party, the trusted party easily becomes the targets of attack. And an authority which can be trusted by all players doesn't exist. So the schemes without a trusted party were proposed to solve those security problems. But all of the conventional schemes without a trusted party cannot withstand conspiracy attacks. A novel (t, n) threshold signature scheme with a weakened trusted party is proposed, in which the group secret key is composed of two parts. Any t or more group players cannot cooperate to reveal the group secret key and the weakened trusted party only knows a part of player’s secret key. So the new scheme can effectively withstand conspiracy attacks and as the power of the trusted party is limited, it meets the purpose of designing a threshold signature scheme without a trusted party.
Low-frequency constraints on the spectra of the lobes of the microquasar GRS 1758–258

I present low-frequency observations of the lobes of the microquasar GRS 1758−258, which, together with earlier radio observations, provide the best constraints yet on the lobe spectra, and show that they are consistent with the electron energy indices expected from standard shock acceleration models. There is no statistically significant evidence for synchrotron ageing along the length of the lobes, which is consistent with expectation if the magnetic field strength is close to the minimum-energy value. If the environment of the lobes has typical ISM properties, the lobes will dissipate on timescales of thousands of years or less, long before synchrotron ageing can become significant.
Prevalence of lysosomal storage disorders.

CONTEXT Lysosomal storage disorders represent a group of at least 41 genetically distinct, biochemically related, inherited diseases. Individually, these disorders are considered rare, although high prevalence values have been reported in some populations. These disorders are devastating for individuals and their families and result in considerable use of resources from health care systems; however, the magnitude of the problem is not well defined. To date, no comprehensive study has been performed on the prevalence of these disorders as a group. OBJECTIVE To determine the prevalence of lysosomal storage disorders individually and as a group in the Australian population. DESIGN Retrospective case studies. SETTING Australia, from January 1, 1980, through December 31, 1996. MAIN OUTCOME MEASURE Enzymatic diagnosis of a lysosomal storage disorder. RESULTS Twenty-seven different lysosomal storage disorders were diagnosed in 545 individuals. The prevalence ranged from 1 per 57000 live births for Gaucher disease to 1 per 4.2 million live births for sialidosis. Eighteen of 27 disorders had more than 10 diagnosed cases. As a group of disorders, the combined prevalence was 1 per 7700 live births. There was no significant increase in the rate of either clinical diagnoses or prenatal diagnoses of lysosomal storage disorders during the study period. CONCLUSIONS Individually, lysosomal storage disorders are rare genetic diseases. However, as a group, they are relatively common and represent an important health problem in Australia.
Cross-cultural generalization: Using meta-analysis to test hypotheses about cultural variability

Researchers conducting multinational organizational studies face considerable challenges. They must not only understand psychological variables, but also translate measures across several languages and administer those measures across several countries and organizational settings. Furthermore, once the data are collected, the researchers must determine whether the measures operate in a similar statistical manner across cultures in terms of their factor structure, reliability, and predictive validity. The entire process can be daunting. This book presents accessible models and real-world examples of large-scale, multinational research within organizations. The contributors describe their own successful research projects, highlighting the challenges they have faced and how they have overcome them. Psychometric, ethical, and methodological concerns are explored, as well as the personal and professional rewards of conducting this type of research. This book will help organizational researchers ensure that their studies are both generalizable and relevant to today's global and diverse work force. It will also help consumers of multicultural research in organizations (e.g., managers, practitioners, and policymakers) obtain a multicultural perspective on important research problems. (PsycINFO Database Record (c) 2014 APA, all rights reserved)
A New Era for Cities with Fog Computing

In this article, the authors dissect the technical challenges that cities face when implementing smart city plans and outlines the design principles and lessons learned after they carried out a flagship initiative on fog computing in Barcelona. In particular, they analyze what they call the Quadruple Silo (QS) problem -- that is, four categories of silos that cities confront after deploying commercially available solutions. Those silo categories are: physical (hardware) silos, data silos, and service management silos, and the implications of the three silos in administrative silos. The authors show how their converged cloud/fog paradigm not only helps solve the QS problem, but also meets the requirements of a growing number of decentralized services -- an area in which traditional cloud models fall short. The article exposes cases in which fog computing is a must, and shows that the reasons for deploying fog are centered much more on operational requirements than on performance issues related to the cloud.
Analysing recall loss in named entity slot filling

State-of-the-art fact extraction is heavily constrained by recall, as demonstrated by recent performance in TAC Slot Filling. We isolate this recall loss for NE slots by systematically analysing each stage of the slot filling pipeline as a filter over correct answers. Recall is critical as candidates never generated can never be recovered, whereas precision can always be increased in downstream processing. We provide precise, empirical confirmation of previously hypothesised sources of recall loss in slot filling. While NE type constraints substantially reduce the search space with only a minor recall penalty, we find that 10% to 39% of slot fills will be entirely ignored by most systems. One in six correct answers are lost if coreference is not used, but this can be mostly retained by simple name matching rules.
Automatic circuit adjustment technique for process sensitivity reduction and yield improvement

In deep submicron process, parametric yield loss due to process variations has become a critical issue, especially for sensitive analog circuits. Design centering is one of the popular techniques to find the nominal design that leads to the maximum yield. However, in critical cases, it is possible that some parts of the performance distribution are still outside the feasible region and has no way to further improve the yield. Therefore, a process sensitivity reduction flow for analog circuits is proposed in this paper. Without moving the given nominal point, a new set of device sizes that lead to smaller performance distribution range can be obtained in the proposed sizing flow, which helps to further improve the yield of that design.
A single-system signal-detection theory of repetition priming and recognition memory.

A dominant view in current memory research is that there are distinct implicit (unconscious) and explicit (conscious) memory systems. The present thesis proposes an alternative, single-system signal-detection model of priming (a traditional implicit memory phenomenon) and recognition (a traditional explicit memory phenomenon). The model has two core assumptions: 1) priming and recognition are driven by the same memory strength signal, and 2) this signal is subjected to independent sources of random noise for priming and recognition tasks (the variance of which is typically greater for priming tasks). The model is shown to account for numerous results: 1) the sensitivity of priming tasks does not typically exceed that of recognition tasks, and priming therefore does not occur when recognition is at chance (Experiments 1-8) 2) the magnitude of the effect produced by manipulations of attention at encoding is greater on recognition than priming (Experiments 5-8), and this can give rise to single dissociations (Appendix 1) 3) priming and recognition can be very weakly correlated, even though they are driven by the same memory signal 4) priming can occur for items that are not recognised (Experiment 9 Simulation Study 2) 5) the relationship between the identification latencies to misses and false alarms can change as a function of overall memory strength (Simulation Study 3) 6) priming and fluency are relatively intact in amnesics, despite severe impairments in recognition (Simulation Study 4). Thus, contrary to previous interpretation, (2)-(6) are not inconsistent with a single-system view (1) suggests that the contents of the memory driving priming are accessible to consciousness. Finally, the predictions of the model were tested in a novel paradigm, the CID-2AFC task (Experiments 10-12 Simulation Study 5). Limitations of the model (and a dual-system version) were revealed, suggesting directions for future research.
A robust timing and frequency synchronization for OFDM systems

A robust symbol-timing and carrier-frequency synchronization scheme applicable to orthogonal frequency-division-multiplexing systems is presented. The proposed method is based on a training symbol specifically designed to have a steep rolloff timing metric. The proposed timing metric also provides a robust sync detection capability. Both time domain training and frequency domain (FD) training are investigated. For FD training, maintaining a low peak-to-average power ratio of the training symbol was taken into consideration. The channel estimation scheme based on the designed training symbol was also incorporated in the system in order to give both fine-timing and frequency-offset estimates. For fine frequency estimation, two approaches are presented. The first one is based on the suppression of the interference introduced in the frequency estimation process by the training symbol pattern in the context of multipath dispersive channels. The second one is based on the maximum likelihood principle and does not suffer from any interference. A new performance measure is introduced for timing estimation, which is based on the plot of signal to timing-error-induced average interference power ratio against the timing estimate shift. A simple approach for finding the optimal setting of the timing estimator is presented. Finally, the sync detection, timing estimation, frequency estimation, and bit-error-rate performance of the proposed method are presented in a multipath Rayleigh fading channel.
Using statistical decision theory and relevance models for query-performance prediction

We present a novel framework for the query-performance prediction task. That is, estimating the effectiveness of a search performed in response to a query in lack of relevance judgments. Our approach is based on using statistical decision theory for estimating the utility that a document ranking provides with respect to an information need expressed by the query. To address the uncertainty in inferring the information need, we estimate utility by the expected similarity between the given ranking and those induced by relevance models; the impact of a relevance model is based on its presumed representativeness of the information need. Specific query-performance predictors instantiated from the framework substantially outperform state-of-the-art predictors over five TREC corpora.
Adjusting batch effects in microarray expression data using empirical Bayes methods.

Non-biological experimental variation or "batch effects" are commonly observed across multiple batches of microarray experiments, often rendering the task of combining data from these batches difficult. The ability to combine microarray data sets is advantageous to researchers to increase statistical power to detect biological phenomena from studies where logistical considerations restrict sample size or in studies that require the sequential hybridization of arrays. In general, it is inappropriate to combine data sets without adjusting for batch effects. Methods have been proposed to filter batch effects from data, but these are often complicated and require large batch sizes ( > 25) to implement. Because the majority of microarray studies are conducted using much smaller sample sizes, existing methods are not sufficient. We propose parametric and non-parametric empirical Bayes frameworks for adjusting data for batch effects that is robust to outliers in small sample sizes and performs comparable to existing methods for large samples. We illustrate our methods using two example data sets and show that our methods are justifiable, easy to apply, and useful in practice. Software for our method is freely available at: http://biosun1.harvard. edu/complab/batch/.
1 3 Ja n 20 05 Possible charge ordered states in BN ( BCN ) nanotubes and nanoribbons

Electronic states in boron-nitride and boron-carbon-nitride nanoribbons with zigzag edges are studied using the extended Hubbard model with nearest neighbor Coulomb interactions. The charge and spin polarized states are considered, and the phase diagram between two states is obtained. Next, the electric capacitance is calculated in order to examine the nano-functionalities of the system. Due to the presence of the strong site energies, the charge polarized state overcomes the spin polarized states, giving the large difference of the phase diagram in comparison with that of graphite system. The electronic structures are always like of semiconductors. The capacitance calculated for the charge polarized state with the realistic values of the Coulomb interactions is inversely proportional to the ribbon width, owing to the presence of the charge excitation energy gap. PACS numbers: 71.10. Hf, 73.22. -f, 73.20. At, 77.22. Ej E-mail address: k.harigaya@aist.go.jp; URL: http://staff.aist.go.jp/k.harigaya/ Corresponding address
Introduction to Single Chip Microwave PLLs

Synthesizer and Phase Locked Loop (PLL) figures of merit including phase noise, spurious output and lock time, at microwave frequencies, are examined. Measurement methods for these parameters and supporting software are discussed in detail. The requirements for the loop filler, the charge pump, the dual modulus prescaler and their effects on PLL performance are analyzed.
A new integrative approach to evaluate pathological gait: locomotor rehabilitation index

This article reviews the concept of locomotor rehabilitation index (LRI) from the principle of dynamical similarities and the theory of mechanism minimizing the energy expenditure in pathological walking. This index is defined as the percentage ratio between self-selected speed and optimum speed (algebraically LRI = 100 × self-selected speed/optimum walking speed). First, we analyze the mechanical foundations of human walking especially focusing on general size effects. Then, we discuss the descriptive physiology of pendular mechanism, evidencing the path that leads to the view of reductionist and extremely descriptive view of pathological gait. Integrative models, generated by the first evidence presented in our previous papers around the LRI, represent a crucial change of perspective. This model is discussed in details and criticized concerning the ensuing experimental findings. Finally, we discuss the case of Parkinson's disease using the Nordic walking as a neat example of application of LRI on pathological locomotion. To conclude , the concept of LRI is reinforced by the substantial evidence, showing that this new proposal for assessing the gait functionality is extremely promising and should be stimulated in studies that examine the effects of therapies on gait functionality in degenerative diseases.