Evolutionarily Tuned Generalized Pseudo-Inverse in Linear Discriminant Analysis

Linear Discriminant Analysis (LDA) and the related Fisher's linear discriminant are very important techniques used for classification and for dimensionality reduction. A certain complication occurs in applying these methods to real data. We have to estimate the class means and common covariance matrix, which are not known. A problem arises if the number of features exceeds the number of observations. In this case the estimate of the covariance matrix does not have full rank, and so cannot be inverted. There are a number of ways to deal with this problem. In our previous paper, we proposed improving LDA in this area, and we presented a new approach which uses a generalization of the Moore-Penrose (MP) pseudo-inverse to remove this weakness. However, for data sets with a larger number of features, our method was computationally too slow to achieve good results. Now we propose a model selection method with a genetic algorithm to solve this problem. Experimental results on different data sets demonstrate that the improvement is efficient

STACKED REGRESSION WITH A GENERALIZATION OF THE MOORE-PENROSE PSEUDOINVERSE

In practice, it often happens that there are a number of classification methods. We are not able to clearly determine which method is optimal. We propose a combined method that allows us to consolidate information from multiple sources in a better classifier. Stacked regression (SR) is a method for forming linear combinations of different classifiers to give improved classification accuracy. The Moore-Penrose (MP) pseudoinverse is a general way to find the solution to a system of linear equations. This paper presents the use of a generalization of the MP pseudoinverse of a matrix in SR. However, for data sets with a greater number of features our exact method is computationally too slow to achieve good results: we propose a genetic approach to solve the problem. Experimental results on various real data sets demonstrate that the improvements are efficient and that this approach outperforms the classical SR method, providing a significant reduction in the mean classification error rate

An Experimental Evaluation of Time Series Classification Using Various Distance Measures

In recent years a vast number of distance measures for time series classification has been proposed. Obviously, the definition of a distance measure is crucial to further data mining tasks, thus there is a need to decide which measure should we choose for a particular dataset. The objective of this study is to provide a comprehensive comparison of 26 distance measures enriched with extensive statistical analysis. We compare different kinds of distance measures: shape-based, edit-based, feature-based and structure-based. Experimental results carried out on 34 benchmark datasets from UCR Time Series Classification Archive are provided. We use an one nearest neighbour (1NN) classifier to compare the efficiency of the examined measures. Computation times were taken into consideration as well

Zielone Inteligentne Miasta jako nowy paradygmat lokalnego rozwoju

The idea of a smart city is widely discussed in literature but is associated to a lesser extent with the idea of moving towards a green smart city. Authors debate the critique of this type of approach and are of the opinion that climate change forces the construction of green models Like businesses, municipalities must be systematically assessed to identify assistance in terms of specialist advice or financial aid. The aim of this article is to develop the concept of a green smart city model, which may become a new development paradigm for municipalities. The article introduces the term eco-transformation in relation to the evolution of changes in the green smart city idea and proposes a tool to measure the action taken by municipalities in their pursuit of ecological maturity. The proposed models are universal in nature, i.e. they can be used to study other areas of a municipality’s activity. Many areas in the model are debatable and difficult for municipalities to incorporate without a critical approach to many areas of knowledge, for example, of municipality management processes, technology, macroeconomic and mesoeconomic specificity, and behavioural analyses.Idea smart city należy do szeroko dyskutowanych w literaturze, ale w mniejszym stopniu wiąże się ją z ideą dążenia do green smart city. Autorzy polemizują z krytyką tego typu ujęcia i są zdania, że zmiany klimatyczne wymuszają budowanie zielonych modeli. Podobnie jak przedsiębiorstwa gminy, muszą podlegać systematycznej ocenie służącej określenia poomocy w zakresie specjalistycznego doradztwa lub pomocy finansowej. Celem artykułu jest opracowanie koncepcji modelu green smart city, która może stać się nowym paradygmatem rozwoju dla gmin.  W artykule wprowadzono termin eko-transformacji w odniesieniu do ewolucji zmian green smart city oraz zaproponowano narzędzie do pomiaru aktywności gmin w dążeniu do dojrzałości ekologicznej. Zaproponowane modele mają uniwersalny charakter tzn. mogą zostać zaproponowane do badania innych obszarów aktywności gminy. Wiele obszarów w modelu jest dyskusyjnych i trudnych do wcielenia przez gminy bez krytycznego podejścia do wielu obszarów wiedzy np. procesów zarządzania gminą, technologii, specyfiki makroekonomicznej i mezoekonomicznej, behawioralnych analiz

AN EXTENSION OF THE CLASSICAL DISTANCE CORRELATION COEFFICIENT FOR MULTIVARIATE FUNCTIONAL DATA WITH APPLICATIONS

The relationship between two sets of real variables defined for the same individuals can be evaluated by a few different correlation coefficients. For the functional data we have one important tool: canonical correlations. It is not immediately straightforward to extend other similar measures to the context of functional data analysis. In this work we show how to use the distance correlation coefficient for a multivariate functional case. The approaches discussed are illustrated with an application to some socio-economic data

The potential for locating hydrocarbon traps in the Rotliegend formation, based on the results of experimental seismic surveys

Within the framework of the Operational Programme Innovative Economy 2007-2013, studies were carried out for improving the effectiveness of using seismic surveys in the prospecting and exploration of gas fields in the Rotliegend formation. The completed experimental seismic surveys provided new, very interesting data on the geological structure of the deeper part of the Rotliegend basin (>4000 m), which is practically very important for prospecting for new gas fields. The interesting results were obtained along virtually the entire cross-section, particularly in two segments: the southern segment – in front of and within the Człopa-Szamotuły tectonic zone (the Szczecin-Gorzów segment) and the northern segment – in the area of the Zabartowo-1 and Zabartowo-2 wells (the Pomeranian segment). In the northern segment, for the first time in the history of studies of the Lower Permian Basin, it was possible to record reflections from the horizon of the aeolian sandstones occurring within the playa silty-clayey deposits (543 m below the top of the Rotliegend formation), which represents a significant achievement from the point of view of prospecting for hydrocarbon resources. This horizon, characterized by favourable reservoir properties, pinches out northward. It is a very important piece of information because systems of lithologic traps may be related to such pinchouts. In the central part of the Obrzycko-Zabartowo profile, in the Chodzież area, a vast structural elevation occurs, approximately 10–12 km wide and with the amplitude of 250–300 m, which may be a potential large structural or structural and lithologic trap. These newly discovered zones of occurrence of gas traps in the seismic profiles made by the AGH University of Science and Technology within the framework of the research project, will be implemented in a detailed seismic exploration during the exploratory work of Polish Oil and Gas Company (PGNiG SA)

Front-face fluorescence spectroscopy and chemometrics for quality control of cold-pressed rapeseed oil during storage

The aim of this study was to test the usability of fluorescence spectroscopy to evaluate the stability of cold-pressed rapeseed oil during storage. Freshly-pressed rapeseed oil was stored in colorless and green glass bottles exposed to light, and in darkness for a period of 6 months. The quality deterioration of oils was evaluated on the basis of several chemical parameters (peroxide value, acid value, K232 and K270, polar compounds, tocopherols, carotenoids, pheophytins, oxygen concentration) and fluorescence. Parallel factor analysis (PARAFAC) of oil excitation-emission matrices revealed the presence of four fluorophores that showed different evolution throughout the storage period. The fluorescence study provided direct information about tocopherol and pheophytin degradation and revealed formation of a new fluorescent product. Principal component analysis (PCA) performed on analytical and fluorescence data showed that oxidation was more advanced in samples exposed to light due to the photo-induced processes; only a very minor effect of the bottle color was observed. Multiple linear regression (MLR) and partial least squares regression (PLSR) on the PARAFAC scores revealed a quantitative relationship between fluorescence and some of the chemical parameters.Funding Agency Ministry of Science and Higher Education, Poland NN312428239 Poznan University of Economics and Businessinfo:eu-repo/semantics/publishedVersio

Long-term quality of life and clinical outcomes in patients with resistant hypertension treated with renal denervation

Introduction: Pharmacological treatment combined with lifestyle modifications is an effective treatment for arterial hypertension. However, there are still patients who do not respond to standard treatments. Patients with pharmacologically resistant hypertension may benefit from renal denervation (RDN). Aim: To assess long-term quality of life (QoL) after RDN and effectiveness in reduction of blood pressure (BP) in patients with resistant hypertension. Material and methods: From 2011 to 2014, 12 patients with previously diagnosed resistant hypertension, treated by RDN, were included in this study. The QoL was assessed using a standardized Polish version of the Nottingham Health Profile questionnaire (NHP). Results: The median age was 54 (IQR: 51–57.5) years. Mean baseline ambulatory pre-procedural systolic/diastolic BP was 188/115 ±29.7/18 mm Hg. The mean values of systolic/diastolic BP measured perioperatively and 3, 6, 12 and 24 months postoperatively were 138/86, 138/85, 146/82, 152/86, and 157/91. All p-values for mean systolic and diastolic BP before versus successive time points after RDN were statistically significant; p-value for all comparisons < 0.05. Improvement of QoL was only observed in two sections of the NHP questionnaire: emotional reaction and sleep disturbance. The analysis of the NHP index of Distress (NHP-D) showed a lower distress level perioperatively and 3, 6, 12 and 24 months after RDN as compared to baseline. The RDN was not associated with any significant adverse events. Conclusions: Patients with pharmacologically resistant hypertension treated with RDN achieved significant reduction in BP during 24-month follow-up. Furthermore, a significant improvement in the QoL was observed in those patients