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Automatic summary of databases is an important tool in strategic decision-making. This paper presents the application of linguistic summaries to outlier detection in databases containing both text and numeric attributes. The proposed method applies Yager's standard summary based on interval-valued fuzzy sets. Fuzzy similarity measures are the features which are looked for. Detection of outliers can identify defects, remove impurities from the data, and, most of all, it may provide the basis for decision-making processes. In this paper, we introduce a definition of an outlier based on linguistic summaries. Feasibility of the method is demonstrated on practical examples.

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The main aim of this work is the estimation of health risks arising from exposure to ozone or other air pollutants by different statistical models taking into account delayed health effects. This paper presents the risk of hospitalization due to bronchitis and asthma exacerbation in adult inhabitants of Silesian Voivodeship from 1 January 2016 to 31 August 2017. Data were obtained from the daily register of hospitalizations for acute bronchitis (code J20–J21, International Classification of Diseases, Tenth Revision – ICD-10) and asthma (J45–J46) which is governed by the National Health Fund. Meteorological data and data on tropospheric ozone concentrations were obtained from the regional environmental monitoring database of the Provincial Inspector of Environmental Protection in Katowice. The paper includes descriptive and analytical statistical methods used in the estimation of health risk with a delayed effect: Almon Distributed Lag Model, the Poisson Distributed Lag Model, and Distributed Lag Non-Linear Model (DLNM). A significant relationship has only been confirmed by DLNM for bronchitis and a relatively short period (1–3 days) from exposure above the limit value (120 µg/m3). The relative risk value was RR = 1.15 (95% CI 1.03–1.28) for a 2-day lag. However, conclusive findings require the continuation of the study over longer observation periods.

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