Miracle-dz/UniFAR-FTUs huggingface dataset:
Ontological evaluation of enterprise systems interoperability using ebXML

Enterprise systems interoperability (ESI) is an important topic for business currently. This situation is evidenced, at least in part, by the number and extent of potential candidate protocols for such process interoperation, viz., ebXML, BPML, BPEL, and WSCI. Wide-ranging support for each of these candidate standards already exists. However, despite broad acceptance, a sound theoretical evaluation of these approaches has not yet been provided. We use the Bunge-Wand-Weber (BWW) models, in particular, the representation model, to provide the basis for such a theoretical evaluation. We, and other researchers, have shown the usefulness of the representation model for analyzing, evaluating, and engineering techniques in the areas of traditional and structured systems analysis, object-oriented modeling, and process modeling. In this work, we address the question, what are the potential semantic weaknesses of using ebXML alone for process interoperation between enterprise systems? We find that users lack important implementation information because of representational deficiencies; due to ontological redundancy, the complexity of the specification is unnecessarily increased; and, users of the specification have to bring in extra-model knowledge to understand constructs in the specification due to instances of ontological excess.
Emissions of volatile organic compounds inferred from airborne flux measurements over a megacity

Toluene and benzene are used for assessing the ability to measure disjunct eddy covariance (DEC) fluxes of Volatile Organic Compounds (VOC) using Proton Transfer Reaction Mass Spectrometry (PTR-MS) on aircraft. Statistically significant correlation between vertical wind speed and mixing ratios suggests that airborne VOC eddy covariance (EC) flux measurements using PTR-MS are feasible. City-median midday toluene and benzene fluxes are calculated to be on the order of 14.1 +/- 4.0 mg/m(2)/h and 4.7 +/- 2.3 mg/m(2)/h, respectively. For comparison the adjusted CAM2004 emission inventory estimates toluene fluxes of 10 mg/m(2)/h along the footprint of the flight-track. Wavelet analysis of instantaneous toluene and benzene measurements during city overpasses is tested as a tool to assess surface emission heterogeneity. High toluene to benzene flux ratios above an industrial district (e. g. 10-15 g/g) including the International airport (e. g. 3-5 g/g) and a mean flux (concentration) ratio of 3.2 +/- 0.5 g/g (3.9 +/- 0.3 g/g) across Mexico City indicate that evaporative fuel and industrial emissions play an important role for the prevalence of aromatic compounds. Based on a tracer model, which was constrained by BTEX (BTEX Benzene/Toluene/Ethylbenzene/ m, p, o-Xylenes) compound concentration ratios, the fuel marker methyl-tertiary-butylether (MTBE) and the biomass burning marker acetonitrile (CH3CN), we show that a combination of industrial, evaporative fuel, and exhaust emissions account for > 87% of all BTEX sources. Our observations suggest that biomass burning emissions play a minor role for the abundance of BTEX compounds in the MCMA (2-13%).
On Large Scale Peer-To-Peer Live Video Distribution : CoolStreaming and Its Prelimianry Experimental Results

It is an attractive idea to spread media data using a peer-to-peer scheme; however it remains unclear whether this technology can really deliver real-time media to a large number of users in global scale. This paper presents an empirical study on CoolStreaming, a Data-driven Overlay Network for live media streaming. The core operations in CoolStreaming are very simple: every node periodically exchanges data availability information with a set of partners, and retrieves unavailable data from one or more partners, or supplies available data to partners. We have extensively evaluated the performance of CoolStreaming over real Internet environment. Our experiments, involving more than 10,000 distinct users, demonstrate that CoolStreaming can achieve quite good streaming quality with globally distributed users, even under formidable network conditions. Meanwhile, we present several interesting observations from these large-scale tests. Finally, we offer some directions toward the future development of p2p media streaming
Microbial Research : Progress and Potential

Toranzos of NSF provided guidance and logistical support for the workshop. We thank Myrna Watanabe for help with report preparation. Executive Summary Introduction The National Science Foundation (NSF) Microbial Observatory (MO) and Life in Extreme Environments (LExEn) programs have fostered significant advances in microbial ecosystems research in a wide variety of natural environments. The investigators funded by these programs have extended the frontiers of microbial diversity and microbial biogeochemistry research, discovering novel microbial lineages, describing the complexity of natural microbial communities, and linking microbial taxa to critical ecosystem functions. This workshop, the first of its kind, provided a platform for MO and LExEn researchers to discuss recent accomplishments and future directions in microbial ecosystem research. LExEn and MO projects have greatly benefited from the use of new molecular technologies to identify organisms and their activities in natural environments. Molecular methods have provided microbial ecologists with invaluable information about the enormous reservoir of uncultured microbes; 16S rRNA work alone has identified more than 13,000 new prokaryotes. These technologies have also allowed access to functional genes, providing a mechanism to assess both capability for and expression of ecologically important microbial processes in natural environments. The challenges now facing microbial-life researchers are to move beyond the limitations of 16S rRNA-based approaches and characterized functions to access the unknown organisms, functions, and activities of uncultured members of microbial communities. Metagenomics Genomic analysis, now used primarily to observe the structures of genomes of individual organisms, can also be used to study the genetic reservoir of entire communities , i.e., the metagenome (Vergin et al., 1998; Rondon et al., 2000; Béjà et al., 2000b). With this approach, genetic material from a natural community can be analyzed without first culturing all the organisms. Several MO projects are making use of this new technology to describe and discover microbes and microbial products from environments as diverse as soils, the ocean, and the guts of insects. Before metagenomics can take a leading position in microbial-life research, however, technological capabilities must be improved for obtaining sufficient DNA from natural environments ; for cloning, sequencing, and storing metagenomic DNA; and for capturing the dynamics of microbial communities over time and space through gene sequencing approaches. Environmental Microarrays Use of microarray technology represents another potentially valuable, yet challenging , prospect for microbial-life research. A reasonably complete set of functional genes collected from an environment or collection of environments provides a window into …
INCREMENTAL MAINTENANCE OF SCHEMA-BASED XML STATISTICS

Current approaches for estimating the cardinality of XML queries are applicable to a static scenario wherein the underlying XML data does not change subsequent to the collection of statistics on the repository. However, in practice, many XML-based applications are dynamic and involve frequent updates to the data. In this paper, we investigate efficient strategies for incrementally maintaining statistical summaries as and when updates are applied to the data. Specifically, we propose algorithms that handle both the addition of new documents as well as random insertions in the existing document trees. We also show, through a detailed performance evaluation, that our incremental techniques are significantly faster than the naive recomputation approach; and that estimation accuracy can be maintained even with a fixed memory budget.
An energy-efficient reconfigurable public-key cryptography processor

The ever-increasing demand for security in portable energy-constrained environments that lack a coherent security architecture has resulted in the need to provide energy-efficient algorithm-agile cryptographic hardware. Domain-specific reconfigurability is utilized to provide the required flexibility, without incurring the high overhead costs associated with generic reprogrammable logic. The resulting implementation is capable of performing an entire suite of cryptographic primitives over the integers modulo N, binary Galois fields and nonsupersingular elliptic curves over GF(2/sup n/), with fully programmable moduli, field polynomials and curve parameters ranging in size from 8 to 1024 bits. The resulting processor consumes a maximum of 75 mW when operating at a clock rate of 50 MHz and a 2-V supply voltage. In ultralow-power mode (3 MHz at 0.7 V) the processor consumes at most 525 /spl mu/W. Measured performance and energy efficiency indicate a comparable level of performance to previously reported dedicated hardware implementations, while providing all of the flexibility of a software-based implementation. In addition, the processor is two to three orders of magnitude more energy efficient than optimized software and reprogrammable logic-based implementations.
Central Bank Balance Sheet Policies and Inflation Expectations

We analyse the empirical effects of credit easing and quantitative easing on inflation expectations and exchange rates. Both monetary policy strategies are summarised in measures for composition and size of the central bank balance sheet and are included in a VAR model. The results show that changes in balance sheet size had positive, albeit weak effects on inflation expectations in Japan, while the effects were negligible in the euro area. By contrast, an increasing balance sheet size is associated with reduced short-term inflation expectations in the US and UK, pointing at negative signalling effects. Shocks to balance sheet size or composition have no substantial effects on long-term inflation expectations in the euro area, US and UK. An expanding balance sheet size is associated with a depreciation of the euro, pound sterling and Japanese yen.
A PCA-based thresholding strategy for group studies of brain connectivity - with applications to resting state fMRI

Functional brain connectivity can be measured from BOLD fMRI recordings using graph representations incorporating inter-regional similarity of time courses. The resulting binary graphs are commonly constructed using thresholding of correlation values between pairwise time series anchored at their corresponding brain locations, representing the nodes in the graph. In this work we propose a new data driven approach to the challenge of selecting correlation threshold levels in group studies. Our approach addresses a collection of subject-specific graphs, thresholded at different levels. It combines information such that variability is preserved, and detection of sub-groups in the sample, having specific properties, is facilitated. The method is illustrated on simple synthetic graphs, and also tested on data from a resting state fMRI study of healthy elderly people with varying genetic risk of Alzheimers disease.
Flea inspired catapult mechanism with active energy storage and release for small scale jumping robot

Fleas have a unique catapult mechanism with a special muscle configuration. Energy is stored in an elastic material, resilin, and the extensor muscle. Force is applied by the extensor muscle to generate a torque. Energy is released as a small triggering muscle reverses the direction of the aforementioned torque. A flea can jump 150 times its body length using this elastic catapult mechanism. In this paper, a flea-inspired catapult mechanism is presented. This mechanism can be categorized as an active storage and active release elastic catapult. Owing to its unique stiffness change characteristic, a shape-memory-alloy coil spring actuator enables the mimicking of the flea's catapult mechanism. Two types of flea-inspired jumping mechanisms were developed for verifying the feasibility of applying the concept to an efficient jumping robot. The first prototype has a flea-like appearance and the second is simplified to contain just the essential components of the flea-inspired catapult mechanism. The two prototypes are 20-mm- and 30-mm-long and can jump 64 cm and 120 cm, respectively. This unique catapult mechanism can be used not only for jumping robots but also for other small-sized robots to generate fast-releasing motion.
The impact of structured, unstructured and integrated decision support systems on SME economic performance: an empirical study

This study investigates the impact that Information and Enterprise Systems have on economic performance in a sample of Greek SMEs. Furthermore, it analyses whether the adoption of unstructured decision support systems (DSS), structured decision systems (MIS) and enterprise application systems (ERP) are linked to increase the firm's turnover in four economic sectors. The results of the study indicate that the systems which support the unstructured decision making (like DSS) and systems which integrate a related set of functions and business processes (like ERP) are positively associated with firm's turnover. On the other hand, statistical analysis suggested that there was a negative relationship between the systems which support the structured decision making (like MIS) and firm's economic performance. The empirical analysis is based on a joint methodology of fully structured questionnaires and personal interviews in 54 Greek SMEs at four different industrial Sectors (Other Services, Manufacturing, Trade and Hotels).
Surface-common-feature descriptor of point cloud data for deep learning

This paper addresses the problem of feature extraction for 3d point cloud data by using autoencoder. Deep learning is one of the most active fields of artificial intelligence, especially in a variety of visual applications, such as image classification and object recognition. However it has not been successfully applied on 3d point cloud data. In this paper, a new method of analyzing the point cloud data is proposed. The method aims to convert the point cloud data to a surface-condition-feature map, which is very effective and useful in pre-training by autoencoder. The surface-condition-features in this paper are defined as upward inclined, downward inclined, upward curved, downward curved, edge and flat, where those features are converted from surface normal vectors.
Conversion database of the shapes into XML data for shape matching

We present a new approach to the matching of 2D shapes using XML language and dynamic programming. Given a 2D shape, we extract its contour and which is represented by set of points. The contour is divided into curves using corner detection. After, each curve is described by local and global features; these features are coded in a string of symbols and stored in a XML file. Finally, using the dynamic programming, we find the optimal alignment between sequences of symbols. Results are presented and compared with existing methods using MATLAB for KIMIA-25 database and MPEG7 databases.
Salient Posture Modeling Based on Spatio-temporal Interesting Points

An action can be represented as a sequence of salient postures. Effective modeling of the salient postures is critical for robust action recognition. This paper proposes to characterize the salient postures using a set of the spatio-temporal interesting points (STIPs). Local features are extracted at each STIP and the statistical distribution of the features for each salient posture is further modelled by a Gaussian mixture model (GMM). Experimental results have verified the effectiveness of the proposed posture model.
Impact of Market Orientation and ICT on the Performance of Rural Smaller Service Enterprises

Market orientation (MO) is considered as a competitive strategy for the smaller service enterprises based in rural locations. A model is proposed and validated for the rural tourism sector that encompasses the effects of MO and of the use of information and communications technology (ICT) on business activity, taking into account the business's financial results, improvements to the rural location, and the more personal, intangible impact on the local entrepreneur. ICT is found to have a positive impact on MO and outcomes, whereas, similarly, the adoption of MO is found to have a positive effect on outcomes.
Dynamic Sleeping Algorithm Based on AHP for Wireless Sensor Networks

Saving energy is one of the key problems of applying wireless sensor network. Clustering and sleeping scheme have good influence on prolonging of lifetime of network and enhancing of energy efficiency. This paper proposes a dynamic sleeping algorithm basing on analytic hierarchy process (AHP), under the condition of heterogeneous industrial sensor clustered-networks. The simulation result indicates that dynamic sleeping algorithm basing on AHP is feasible. It has notable benefit on prolonging of lifetime of network and enhancing of energy efficiency.
Qualitative Methods Used in Market Research

According to the given data, admittedly, there are two main types of market research: Quantitative Research (questionnaire surveys) and Qualitative Research. Qualitative Research implies getting answers from a small number of respondents and the results of qualitative nature: ideas, perceptions, attitudes, associated values, preferences, suggestions. The Qualitative Research is conducted in the initial phase of studying one issue. The main purpose of Qualitative Research is to define the nature of the issue and to cater qualitative Information. For this paper work, the subject is a Qualitative Research (a focus-group) thinking out, a research where we were moderators. The research was conducted in order to oversee and to analyze the psycho-social influences of a large dismissal, as a consequence of the industrial restructuring programmes in Brasov, as well as the impact of the applied intervention measures. The research was conducted in December 2005.
Distinct Failure Diversity in Multiversion SoftwareDerek Partridge

In earlier studies of multiversion programming, both empirical and analytical, emphasis switched from notions of independence to one of minimization of coincident failure. We show that neither independence of failure, nor lack of coincident failure are the single important properties. Indeed, an N-version system may deliver an optimal performance (under some voting strategy) even when the incidence of coincident failure is arbitrarily high. The key notion that this study contributes is one of distinct diierent failure, and hence distinct-failure diversity. The important property is not whether versions fail on the same input so much as whether they fail in the same way. If the failures of an N-version system (on some input) are dispersed over a set of distinct alternative outcomes, then this (hitherto unacknowledged) aspect of diversity may be exploited to substantially enhance system reliability. We propose measures for the traditional coincident-failure diversity (CFD), for the new distinct failure-diversity (DFD), and for an integrated overall diversity (OD). We show how the DFD property of an N-version system may permit substantial performance enhancement despite maximum coincident failure. We demonstrate the extra practical beneets that accrue from an exploitation of this new treatment of multiversion software systems by application to previously published examples. Finally, we suggest how this new aspect of diversity (as well as several others) can be exploited to cast the potential for multiversion software engineering in a much more positive light than was produced by the previous studies which demonstrated the necessary absence of independent failure behaviour.
Model-based direct policy search

Scaling Reinforcement Learning (RL) to real-world problems with continuous state and action spaces remains a challenge. This is partly due to the reason that the optimal value function can become quite complex in continuous domains. In this paper, we propose to avoid learning the optimal value function at all but to use direct policy search methods in combination with model-based RL instead.
Response to Comment on: Schuit et al. β-Cell–Specific Gene Repression: A Mechanism to Protect Against Inappropriate or Maladjusted Insulin Secretion? Diabetes 2012;61:969–975

Thank you for the invitation to respond to the comment by Rutter and Pullen (1). We are aware of the original work by the Rutter laboratory on LDHA and MCT1 (2,3) and cited it before (4) and in the Perspective (5). However, with the limitation of 50 references in the Perspective, some original research could not be cited, and we apologize for that. We strongly disagree, however, with the claim from Rutter and Pullen to be the first to discover islet-specific gene repression through bioinformatic analysis (1). It should be made clear that until 2006 research on lactate dehydrogenase and moncarboxylate transporter 1 was conducted …
Differential cytokine sensitivities of STAT5-dependent enhancers rely on Stat5 autoregulation

Cytokines utilize the transcription factor STAT5 to control cell-specific genes at a larger scale than universal genes, with a mechanistic explanation yet to be supplied. Genome-wide studies have identified putative STAT5-based mammary-specific and universal enhancers, an opportunity to investigate mechanisms underlying their differential response to cytokines. We have now interrogated the integrity and function of both categories of regulatory elements using biological and genetic approaches. During lactation, STAT5 occupies mammary-specific and universal cytokine-responsive elements. Following lactation, prolactin levels decline and mammary-specific STAT5-dependent enhancers are decommissioned within 24 h, while universal regulatory complexes remain intact. These differential sensitivities are linked to STAT5 concentrations and the mammary-specific Stat5 autoregulatory enhancer. In its absence, mammary-specific enhancers, but not universal elements, fail to be fully established. Upon termination of lactation STAT5 binding to a subset of mammary enhancers is substituted by STAT3. No STAT3 binding was observed at the most sensitive STAT5 enhancers suggesting that upon hormone withdrawal their chromatin becomes inaccessible. Lastly, we demonstrate that the mammary-enriched transcription factors GR, ELF5 and NFIB associate with STAT5 at sites lacking bona fide binding motifs. This study provides, for the first time, molecular insight into the differential sensitivities of mammary-specific and universal cytokine-sensing enhancers.
Explaining Black-White Wage Convergence, 1940-1950: the Role of the Great Compression

The "Great Compression" of the 1940s produced a substantial narrowing in wage differentials in the United States. This paper examines the role of the Great Compression in fostering black-white wage convergence in the 1940s. Using data from the 1940 and 1950 census public use samples, I show that between half and two-thirds of black white wage convergence at the sample means can be attributed to shifts in wage structure associated with the Great Compression. I also demonstrate that, by (temporarily) boosting the incomes of black parents. the Great Compression led to greater increases in schooling levels among black teens between 1940 and 1950 than would have occurred otherwise.