The Internet has become an important source of information for physicians seeking immediate data for the management of patients and for those developing decision-making methodologies and guidelines for clinical practice. In this study, components and subsystems of a medical decision support system are presented. An artificial neural network model, which is one of the subsystems of the differential diagnosis component, has been proposed as a reasoning tool to support medical diagnosis. The input data of artificial neural network models used in different medical diagnosis can be obtained via the Internet. The present study is concerned with the application of artificial neural network model to diabetes prediction. Demographic and medical data of diabetics and non-diabetics obtained via the Internet were used as the artificial neural network inputs. The accuracy of the neural network's results has shown that the diabetes prediction is feasible by the neural network described in this study.
The article analyses the extent to which the UNIDROIT Principles of International Commercial Contracts (UPICC) are used to interpret and supplement Czech contract law. Under Czech legal doctrine the UPICC are part of lex mercatoria and not considered as a generally binding set of legal rules. However, contracting parties are free to make them part of their contract. The authors carry out a comparative analysis of selected UPICC rules and their counterparts in the Czech national law (Czech Civil Code) relating to negotiations in bad fairh, surprising terms, currency of payment, right to terminate the contract and interest for failure to pay money., Monika Pauknerová, Magdalena Pfeiffer., and Obsahuje bibliografické odkazy
John MacFarlane argues against objectivism about ''tasty''/''not tasty'' in the following way. If objectivism were true then, given that speakers use ''tasty''/''not tasty'' in accordance with a rule, TP, speakers would be using an evidently unreliable method to form judgements and make claims about what is tasty. Since this is implausible, objectivism must be false. In this paper, I describe a context in which speakers deviate from TP. I argue that MacFarlane’s argument against objectivism fails when applied to uses of ''not tasty'' within this context. So objectivism about ''not tasty'' is still a viable position within this context., John MacFarlane argumentuje proti objektivismu o ''chutném'' / ''ne chutném'' následujícím způsobem. Pokud by objektivismus byl pravdivý, vzhledem k tomu, že reproduktory používají ''chutné'' / ''ne chutné'' v souladu s pravidly TP, mluvčí by používali zjevně nespolehlivou metodu k tomu, aby vytvořili soudy a prohlásili, co je chutné. Protože to je nepravděpodobné, objektivismus musí být falešný. V tomto článku popisuji kontext, ve kterém se mluvčí odchýlí od TP. Argumentuji, že argument MacFarlane proti objektivismu selhal, když se v tomto kontextu vztahuje k použití ''ne chutných''. Tak objektivismus ''ne chutné'' je stále životaschopný postoj v tomto kontextu., and Alexi Davies
The N250r is a face-sensitive event-related potential (ERP) deflection whose long-term memory sensitivity remains uncertain. We investigated the possibility that long-term memory-related voltage changes are represented in the early ERP's to faces but methodological considerations could affect how these changes appear to be manifested. We examined the effects of two peak analysis procedures in the assessment of the memory-sensitivity of the N250r elicited in an old/new recognition paradigm using analysis of variance (ANOVA) and artificial neural networks (ANN's). When latency was kept constant within subjects, ANOVA was unable to detect differences between ERP's to remembered and new faces; however, an ANN was. Network interpretation suggested that the ANN was detecting amplitude differences at occipitotemporal and frontocentral sites corresponding to the N250r. When peak latency was taken into account, ANOVA detected a significant decrease in onset latency of the N250r to remembered faces and amplitude differences were not detectable, even with an ANN. Results suggest that the N250r is sensitive to long-term memory. This effect may be a priming phenomenon that is attenuated at long lags between faces. Choice of peak analysis procedures is critical to the interpretation of phasic memory effects in ERP data.
In bare soils of semi-arid areas, surface crusting is a rather common phenomenon due to the impact of raindrops. Water infiltration measurements under ponding conditions are becoming largely applied techniques for an approximate characterization of crusted soils. In this study, the impact of crusting on soil hydraulic conductivity was assessed in a Mediterranean vineyard (western Sicily, Italy) under conventional tillage. The BEST (Beerkan Estimation of Soil Transfer parameters) algorithm was applied to the infiltration data to obtain the hydraulic conductivity of crusted and uncrusted soils. Soil hydraulic conductivity was found to vary during the year and also spatially (i.e., rows vs. interrows) due to crusting, tillage and vegetation cover. A 55 mm rainfall event resulted in a decrease of the saturated soil hydraulic conductivity, Ks, by a factor of 1.6 in the inter-row areas, due to the formation of a crusted layer at the surface. The same rainfall event did not determine a Ks reduction in the row areas (i.e., Ks decreased by a non-significant factor of 1.05) because the vegetation cover intercepted the raindrops and therefore prevented alteration of the soil surface. The
developed ring insertion methodology on crusted soil, implying pre-moistening through the periphery of the sampled surface, together with the very small insertion depth of the ring (0.01 m), prevented visible fractures. Consequently, Beerkan tests carried out along and between the vine-rows and data analysis by the BEST algorithm allowed to assess crusting-dependent reductions in hydraulic conductivity with extemporaneous measurements alone. The reliability of the tested technique was also confirmed by the results of the numerical simulation of the infiltration process in a crusted soil. Testing the Beerkan infiltration run in other crusted soils and establishing comparisons with other experimental methodologies
appear advisable to increase confidence on the reliability of the method that seems suitable for simple characterization of crusted soils.
Relations between two Boolean attributes derived from data can be
quantified by truth functions defined on four-fold tables corresponding to pairs of the attributes. Several classes of such quantifiers (implicational, double implicational, equivalence ones) with truth values in the unit interval were investigated in the frame of the theory of data mining methods. In the fuzzy logic theory, there are well-defined classes of fuzzy operators, namely t-norms representing various types of evaluations of fuzzy conjunction (and t-conorms representing fuzzy disjunction), and operators of fuzzy implications.
In the contribution, several types of constructions of quantifiers using fuzzy operators are described. Definitions and theorems presented by the author in previous contributions to WUPES workshops are summarized and illustrated by examples of well-known quantifiers and operators.
There is growing interest to analyze electroencephalogram (EEG) signals with the objective of classifying schizophrenic patients from the control subjects. In this study, EEG signals of 15 schizophrenic patients and 19 age-matched control subjects are recorded using twenty surface electrodes. After the preprocessing phase, several features including autoregressive (AR) model coefficients, band power and fractal dimension were extracted from their recorded signals. Three classifiers including Linear Discriminant Analysis (LDA), Multi-LDA (MLDA) and Adaptive Boosting (Adaboost) were implemented to classify the EEG features of schizophrenic and normal subjects. Leave-one (participant)-out cross validation is performed in the training phase and finally in the test phase; the results of applying the LDA, MLDA and Adaboost respectively provided 78%, 81% and 82% classification accuracies between the two groups. For further improvement, Genetic Programming (GP) is employed to select more informative features and remove the redundant ones. After applying GP on the feature vectors, the results are remarkably improved so that the classification rate of the two groups with LDA, MLDA and Adaboost classifiers yielded 82%, 84% and 93% accuracies, respectively.
Several algorithms have been developed for time series forecasting. In this paper, we develop a type of algorithm that makes use of the numerical methods for optimizing on objective function that is the Kullbak-Leibler divergence between the joint probability density function of a time series xi, X2, Xn and the product of their marginal distributions. The Grani-charlier expansion is ušed for estimating these distributions.
Using the weights that have been obtained by the neural network, and adding to them the Kullback-Leibler divergence of these weights, we obtain new weights that are ušed for forecasting the new value of Xn+k.
The paper deals with application of MF-ARTMAP neural network on
financial fraud data. The focus was on classification of data into 5 types of fraud based on expert knowledge with the aim to achieve the tool with highest classification accuracy. The fraud was characterized by 22 features and the verbal features were encoded into numerical values to be able to use them in the classification proceduře. The results show that in the čase of sufficient data (fraud) representation neural networks could be used with success; in case there are rather small examples, expert generated rules are preferred.
Hospitals must index each case of inpatient medical care with codes from the International Classification of Diseases, 9th Revision (ICD-9), under regulations from the Bureau of National Health Insurance. This paper aims to investigate the analysis of free-textual clinical medical diagnosis documents with ICD-9 codes using state-of-the-art techniques from text and visual mining fields. In this paper, ViSOM and SOM approaches inspire several analyses of clinical diagnosis records with ICD-9 codes. ViSOM and SOM are also used to obtain interesting patterns that have not been discovered with traditional, nonvisual approaches. Furthermore, we addressed three principles that can be used to help clinical doctors analyze diagnosis records effectively using the ViSOM and SOM approaches. The experiments were conducted using real diagnosis records and show that ViSOM and SOM are helpful for organizational decision-making activities.