Materials and Methods of the Study of Influence of Agrotechnical Methods on Sensory Characteristics of Technical Sorts of Grape

The topicality of using the sensory analysis of berries in enological practice at planning of agrotechnical complex at vineyard to receive the certain style and quality of production was grounded. For study of the influence of agrotechnical methods on sensory characteristics of technical sorts of grape Zagrey and Fragrant, selected by NSC “IVaW named after V.E. Tairov” (Ukraine), there was elaborated the algorithm of research, including field experiment and laboratory sensory analysis. The method of organoleptic analysis of berries, consisted of 20 parameters for assessment of visual, tactile and gustatory properties of pulp, peel and seeds, was approbated. Mathematical processing of experimental data was carried out by the methods of one- and two-factor analysis of variance and analysis of main components in the environment of package of applied programs MS Excell 2010, Statistica Statsoft ver. 7. 0 (Tulsa, USA).The sensory descriptors, characterizing the quality of studied sorts of grape, were determined. It was established, that agrotechnical methods of planting grape bushes influenced the sensory characteristics of berries of studied sorts

Unity in diversity : integrating differing linguistic data in TUSNELDA

This paper describes the creation and preparation of TUSNELDA, a collection of corpus data built for linguistic research. This collection contains a number of linguistically annotated corpora which differ in various aspects such as language, text sorts / data types, encoded annotation levels, and linguistic theories underlying the annotation. The paper focuses on this variation on the one hand and the way how these heterogeneous data are integrated into one resource on the other hand

Wavelet versus Detrended Fluctuation Analysis of multifractal structures

We perform a comparative study of applicability of the Multifractal Detrended Fluctuation Analysis (MFDFA) and the Wavelet Transform Modulus Maxima (WTMM) method in proper detecting of mono- and multifractal character of data. We quantify the performance of both methods by using different sorts of artificial signals generated according to a few well-known exactly soluble mathematical models: monofractal fractional Brownian motion, bifractal Levy flights, and different sorts of multifractal binomial cascades. Our results show that in majority of situations in which one does not know a priori the fractal properties of a process, choosing MFDFA should be recommended. In particular, WTMM gives biased outcomes for the fractional Brownian motion with different values of Hurst exponent, indicating spurious multifractality. In some cases WTMM can also give different results if one applies different wavelets. We do not exclude using WTMM in real data analysis, but it occurs that while one may apply MFDFA in a more automatic fashion, WTMM has to be applied with care. In the second part of our work, we perform an analogous analysis on empirical data coming from the American and from the German stock market. For this data both methods detect rich multifractality in terms of broad f(alpha), but MFDFA suggests that this multifractality is poorer than in the case of WTMM.Comment: substantially extended version, to appear in Phys.Rev.

Traffic Analysis for the Calibration of Risk Assessment Methods

In order to provide some measure of the uncertainty inherent in the sorts of charting data that are provided to the end-user, we have previously proposed risk models that measure the magnitude of the uncertainty for a ship operating in a particular area. Calibration of these models is essential, but the complexity of the models means that we require detailed information on the sorts of ships, traffic patterns and density within the model area to make a reliable assessment. In theory, the ais system should provide this information for a suitably instrumented area. We consider the problem of converting, filtering and analysing the raw ais traffic to provide statistical characterizations of the traffic in a particular area, and illustrate the method with data from 2008-10-01 through 2008-11-30 around Norfolk, VA. We show that it is possible to automatically construct aggregate statistical characteristics of the port, resulting in distributions of transit location, termination and duration by vessel category, as well as type of traffic, physical dimensions, and intensity of activity. We also observe that although 60 days give us suffi- cient data for our immediate purposes, a large proportion of it—up to 52% by message volume—must be considered dubious due to difficulties in configuration, maintenance and operation of ais transceivers

Speech acts and medical records: The ontological nexus

Despite the recent advances in information and communication technology that have increased our ability to store and circulate information, the task of ensuring that the right sorts of information gets to the right sorts of people remains. We argue that the many efforts underway to develop efficient means for sharing information across healthcare systems and organizations would benefit from a careful analysis of human action in healthcare organizations. This in turn requires that the management of information and knowledge within healthcare organizations be combined with models of resources and processes of patient care that are based on a general ontology of social interaction. The Health Level 7 (HL7) is one of several ANSI-accredited Standards Developing Organizations operating in the healthcare arena. HL7 has advanced a widely used messaging standard that enables healthcare applications to exchange clinical and administrative data in digital form. HL7 focuses on the interface requirements of the entire healthcare system and not exclusively on the requirements of one area of healthcare such as pharmacy, medical devices, imaging or insurance transactions. This has inspired the development of a powerful abstract model of patient care called the Reference Information Model (RIM). The present paper begins with an overview of the core classes of the HL7 (Version 3) RIM and a brief discussion of its “actcentered” view of healthcare. Central to this account is what is called the life cycle of events. A clinical action may progress from defined, through planned and ordered, to executed. These modalities of an action are represented as the mood of the act. We then outline the basis of an ontology of organizations, starting from the theory of speech Acts, and apply this ontology to the HL7 RIM. Special attention is given to the sorts of preconditions that must be satisfied for the successful performance of a speech act and to the sorts of entities to which speech acts give rise (e.g. obligations, claims, commitments, etc.). Finally we draw conclusions for the efficient communication and management of medical information and knowledge within and between healthcare organizations, paying special attention to the role that medical documents play in such organizations

Natural Language Ontology

The aim of natural language ontology is to uncover the ontological categories and structures that are implicit in the use of natural language, that is, that a speaker accepts when using a language. This article aims to clarify what exactly the subject matter of natural language ontology is, what sorts of linguistic data it should take into account, how natural language ontology relates to other branches of metaphysics, in what ways natural language ontology is important, and what may be distinctive of the ontological categories and structures reflected in natural language

Modified Linear Projection for Large Spatial Data Sets

Recent developments in engineering techniques for spatial data collection such as geographic information systems have resulted in an increasing need for methods to analyze large spatial data sets. These sorts of data sets can be found in various fields of the natural and social sciences. However, model fitting and spatial prediction using these large spatial data sets are impractically time-consuming, because of the necessary matrix inversions. Various methods have been developed to deal with this problem, including a reduced rank approach and a sparse matrix approximation. In this paper, we propose a modification to an existing reduced rank approach to capture both the large- and small-scale spatial variations effectively. We have used simulated examples and an empirical data analysis to demonstrate that our proposed approach consistently performs well when compared with other methods. In particular, the performance of our new method does not depend on the dependence properties of the spatial covariance functions.Comment: 29 pages, 5 figures, 4 table