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Search results for: DATA CLUSTERING ANALYSIS
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Enhanced susceptibility of SARS-CoV-2 spike RBD protein assay targeted by cellular receptors ACE2 and CD147: Multivariate data analysis of multisine impedimetric response
PublicationSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters the cells through the binding of spike protein to the host cell surface-expressing angiotensin-converting enzyme 2 (ACE2) or by endocytosis mediated by extracellular matrix metalloproteinase inducer (CD147). We present extended statistical studies of the multisine dynamic electrochemical impedance spectroscopy (DEIS) revealing interactions between Spike RBD and...
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30-day morbidity and mortality of sleeve gastrectomy, Roux-en-Y gastric bypass and one anastomosis gastric bypass: a propensity score-matched analysis of the GENEVA data
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Cytokine TGFβ Gene Polymorphism in Asthma: TGF-Related SNP Analysis Enhances the Prediction of Disease Diagnosis (A Case-Control Study With Multivariable Data-Mining Model Development)
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Przegląd badań dotyczących efektywności i produktywności oświaty (szkół podstawowych i ponadpodstawowych) w Polsce, prowadzonych za pomocą metody Data Envelopment Analysis i indeksu Malmquista
PublicationCelem artykułu jest przedstawienie i ocena prowadzonych za pomocą metody Data Envelopment Analysis (DEA) i indeksu Malmquista badań dotyczących polskich placówek oświatowych. Wykorzystano systematyczny i krytyczny przegląd literatury przedmiotu do zobrazowania postępu badań nad edukacją podstawową i ponadpodstawową. Badania zostały przeanalizowane ze względu na różne kryteria, biorąc pod uwagę: 1) metodę DEA i indeksu Malmquista,...
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Algorithms for processing and visualization of Critical Infrastructure security data as well as simulation and analysis of threats = Algorytmy przetwarzania i wizualizacji danych dotyczących bezpieczeństwa infrastruktur krytycznych oraz symulacji i analizy zagrożeń
PublicationRozprawa traktuje o algorytmach przetwarzania danych dotyczących różnego rodzaju zagrożeń, w szczególności wyników analiz ryzyka infrastruktur krytycznych, pozwalających na przestrzenną analizę tych danych w kontekście geograficznym za pomocą dedykowanego Systemu Informacji Przestrzennej. Prezentowane metody analizy zgrupowań Infrastruktur Krytycznych oraz propagacji ich zagrożeń wykorzystują wyniki syntetycznej analizy podatności...
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Self-Organizing Map representation for clustering Wikipedia search results
PublicationThe article presents an approach to automated organization of textual data. The experiments have been performed on selected sub-set of Wikipedia. The Vector Space Model representation based on terms has been used to build groups of similar articles extracted from Kohonen Self-Organizing Maps with DBSCAN clustering. To warrant efficiency of the data processing, we performed linear dimensionality reduction of raw data using Principal...
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Self–Organizing Map representation for clustering Wikipedia search results
PublicationThe article presents an approach to automated organization of textual data. The experiments have been performed on selected sub-set of Wikipedia. The Vector Space Model representation based on terms has been used to build groups of similar articles extracted from Kohonen Self-Organizing Maps with DBSCAN clustering. To warrant efficiency of the data processing, we performed linear dimensionality reduction of raw data using Principal...
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Categorization of Wikipedia articles with spectral clustering
PublicationAbstract. The article reports application of clustering algorithms for creating hierarchical groups withinWikipedia articles.We evaluate three spectral clustering algorithms based on datasets constructed with usage ofWikipedia categories. Selected algorithm has been implemented in the system that categorize Wikipedia search results in the fly.
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Development and Research of the Text Messages Semantic Clustering Methodology
PublicationThe methodology of semantic clustering analysis of customer’s text-opinions collection is developed. The author's version of the mathematical models of formalization and practical realization of short textual messages semantic clustering procedure is proposed, based on the customer’s text-opinions collection Latent Semantic Analysis knowledge extracting method. An algorithm for semantic clustering of the text-opinions is developed,...
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Categorization of Cloud Workload Types with Clustering
PublicationThe paper presents a new classification schema of IaaS cloud workloads types, based on the functional characteristics. We show the results of an experiment of automatic categorization performed with different benchmarks that represent particular workload types. Monitoring of resource utilization allowed us to construct workload models that can be processed with machine learning algorithms. The direct connection between the functional...
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Spectral Clustering Wikipedia Keyword-Based search Results
PublicationThe paper summarizes our research in the area of unsupervised categorization of Wikipedia articles. As a practical result of our research, we present an application of spectral clustering algorithm used for grouping Wikipedia search results. The main contribution of the paper is a representation method for Wikipedia articles that has been based on combination of words and links and used for categoriation of search results in this...
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Weighted Clustering for Bees Detection on Video Images
PublicationThis work describes a bee detection system to monitor bee colony conditions. The detection process on video images has been divided into 3 stages: determining the regions of interest (ROI) for a given frame, scanning the frame in ROI areas using the DNN-CNN classifier, in order to obtain a confidence of bee occurrence in each window in any position and any scale, and form one detection window from a cloud of windows provided by...
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Clustering Context Items into User Trust Levels
PublicationAn innovative trust-based security model for Internet systems is proposed. The TCoRBAC model operates on user profiles built on the history of user with system interaction in conjunction with multi-dimensional context information. There is proposed a method of transforming the high number of possible context value variants into several user trust levels. The transformation implements Hierarchical Agglomerative Clustering strategy....
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External Validation Measures for Nested Clustering of Text Documents
PublicationAbstract. This article handles the problem of validating the results of nested (as opposed to "flat") clusterings. It shows that standard external validation indices used for partitioning clustering validation, like Rand statistics, Hubert Γ statistic or F-measure are not applicable in nested clustering cases. Additionally to the work, where F-measure was adopted to hierarchical classification as hF-measure, here some methods to...
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Information Retrieval with the Use of Music Clustering by Directions Algorithm
PublicationThis paper introduces the Music Clustering by Directions (MCBD) algorithm. The algorithm is designed to support users of query by humming systems in formulating queries. This kind of systems makes it possible to retrieve songs and tunes on the basis of a melody recorded by the user. The Music Clustering by Directions algorithm is a kind of an interactive query expansion method. On the basis of query, the algorithm provides suggestions...
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Interactive Query Expansion with the Use of Clustering by Directions Algorithm
PublicationThis paper concerns Clustering by Directions algorithm. The algorithm introduces a novel approach to interactive query expansion. It is designed to support users of search engines in forming web search queries. When a user executes a query, the algorithm shows potential directions in which the search can be continued. This paper describes the algorithm and it presents an enhancement which reduces the computational complexity of...
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Fragmentation of Hydrographic Big Data Into Subsets During Reduction Process
PublicationThe article presented problems of fragmentation of hydrographic big data into smaller subsets during reduction process. Data reduction is a processing of reduce the value of the data set, in order to make them easier and more effective for the goals of the analysis. The main aim of authors is to create new reduction method. The article presented the first stage of this method – fragmentation of bathymetric data into subsets. It...
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A Clustering-Based Methodology for Selection of Fault Tolerance Techniques
PublicationDevelopment of dependable applications requires selection of appropriate fault tolerance techniques that balance efficiency in fault handling and resulting consequences, such as increased development cost or performance degradation. This paper describes an advisory system that recommends fault tolerance techniques considering specified development and runtime application attributes. In the selection process, we use the K-means...
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Ontology clustering by directions algorithm to expand ontology queries
PublicationThis paper concerns formulating ontology queries. It describes existing languages in which ontologies can be queried. It focuses on languages which are intended to be easily understood by users who are willing to retrieve information from ontologies. Such a language can be, for example, a type of controlled natural language (CNL). In this paper a novel algorithm called Ontology Clustering by Directions is presented. The algorithm...
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Wyszukiwanie informacji z wykorzystaniem algorytmu Ontology Clustering by Directions
PublicationArtykuł opisuje algorytm Ontology Clustering by Directions. Algorytm ten ma na celu wspieranie użytkowników w formułowaniu ontologicznych zapytań. Ontologiczne zapytania służą do wydobywania informacji sformułowanych za pomocą ontologii opisanych np. językiem OWL. Artykuł przedstawia rodzaje języków wykorzystywanych do formułowania ontologicznych zapytań. W szczególności opisuje języki, które mają być przyjazne użytkownikom. Na...
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0-step K-means for clustering Wikipedia search results
PublicationThis article describes an improvement for K-means algorithm and its application in the form of a system that clusters search results retrieved from Wikipedia. The proposed algorithm eliminates K-means isadvantages and allows one to create a cluster hierarchy. The main contributions of this paper include the ollowing: (1) The concept of an improved K-means algorithm and its application for hierarchical clustering....
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Agent-Based Non-distributed and Distributed Clustering
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Fuzzy Divisive Hierarchical Clustering of Solvents According to Their Experimentally and Theoretically Predicted Descriptors
PublicationThe present study describes a simple procedure to separate into patterns of similarity a large group of solvents, 259 in total, presented by 15 specific descriptors (experimentally found and theoretically predicted physicochemical parameters). Solvent data is usually characterized by its high variability, dierent molecular symmetry, and spatial orientation. Methods of chemometrics can usefully be used to extract and explore accurately...
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APPLICATION OF CHEMOMETRIC ANALYSIS TO THE STUDY OF SNOW AT THE SUDETY MOUNTAINS, POLAND
PublicationSnow samples were collected during winter 2011/2012 in three posts in the Western Sudety Mountains (Poland) in 3 consecutive phases of snow cover development, i.e. stabilisation (Feb 1st), growth (Mar 15th) and its ablation (Mar 27th). To maintain a fixed number of samples, each snow profile has been divided into six layers, but hydrochemical indications were made for each 10 cm section of core. The complete data set was subjected...
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The adaptive spatio-temporal clustering method in classifying direct labor costs for the manufacturing industry
PublicationEmployee productivity is critical to the profitability of not only the manufacturing industry. By capturing employee locations using recent advanced tracking devices, one can analyze and evaluate the time spent during a workday of each individual. However, over time, the quantity of the collected data becomes a burden, and decreases the capabilities of efficient classification of direct labor costs. However, the results obtained...
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Fiscal decentralization in the European Countries: a cluster analysis approach
PublicationThe scope of public authority depend on many factors. One of them is a declaration, usually expressed in the constitution of a given country (Sferlea, 2014, Libman, 2010, Nehmelman, Vetzo, 2016) of the application of the decentralisation principle in the performance of public tasks. Despite this declaration, the structure of the public sector and the tasks carried out at different levels in particular countries are not identical....
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The image of the City on social media: A comparative study using “Big Data” and “Small Data” methods in the Tri-City Region in Poland
Publication“The Image of the City” by Kevin Lynch is a landmark planning theory of lasting influence; its scientific rigor and relevance in the digital age were in dispute. The rise of social media and other digital technologies offers new opportunities to study the perception of urban environments. Questions remain as to whether social media analytics can provide a reliable measure of perceived city images? If yes, what implication does...
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Qualitative and Quantitative Analysis of Selected Tonic Waters by Potentiometric Taste Sensor With All-Solid-State Electrodes
PublicationTaste sensor with five all-solid-state electrodes (ASSE) III (third version) was used for qualitative and quantitative analysis of selected tonic waters (J.Gasco, Kinley, Jurajski, Jurajski with citrus flavor, Carrefour, Schweppes Indian Tonic, and Schweppes Bitter Lemon). The results obtained by this taste sensor analyzed with principal component analysis, agglomerative hierarchical clustering methods show that this sensor can...
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Molecular-dynamics simulation of clustering processes in sea-ice floes
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Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublicationHigher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...
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Increasing K-Means Clustering Algorithm Effectivity for Using in Source Code Plagiarism Detection
PublicationThe problem of plagiarism is becoming increasingly more significant with the growth of Internet technologies and the availability of information resources. Many tools have been successfully developed to detect plagiarisms in textual documents, but the situation is more complicated in the field of plagiarism of source codes, where the problem is equally serious. At present, there are no complex tools available to detect plagiarism...
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Real estate investment trusts in Turkey: Structure, analysis, and strategy
PublicationPurpose-Aim of this study is to make the determinations related to the problems mentioned in the REIT sector in Turkey, to offer a solution for this issue, and to ensure the classification in the sector by adhering to the financial data of the REITsMethodology-Financial data set of the REITs was firstly standardized by using median instead of mean. Then, the scoring was performed according to defined coefficients....
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Interfejs do algorytmu Clustering by Directions ułatwiający formułowanie zapytań w wyszukiwarkach internetowych
PublicationRozdział dotyczy tworzenia zapytań w wyszukiwarkach internetowych. Opisuje sposoby wspierania użytkowników wyszukiwarek w formułowaniu zapytań. Ponadto opisuje zasadę działania opracowanego przez autora algorytmu Clustering by Directions. Algorytm ten przeznaczony jest do wskazywania użytkownikom potencjalnych kierunków, w których mogą kontynuować wyszukiwanie. Kierunki są reprezentowane przez wyrazy, które użytkownik może dodawać...
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An Approach for Journal Summarization Using Clustering Based Micro-Summary Generation
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Breast Cancer Heterogeneity Investigation: Multiple k-Means Clustering Approach
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Pre-selection and assessment of green organic solvents by clustering chemometric tools
PublicationThe study presents the result of the application of chemometric tools for selection of physicochemical parameters of solvents for predicting missing variables – bioconcentration factors, water-octanol and octanol-air partitioning constants. EPI Suite software was successfully applied to predict missing values for solvents commonly considered as “green”. Values for logBCF, logKOW and logKOA were modelled for 43 rather nonpolar solvents...
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Kernel-Based Fuzzy C-Means Clustering Algorithm for RBF Network Initialization
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublicationMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
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Dynamic Re-Clustering Leach-Based (Dr-Leach) Protocol for Wireless Sensor Networks
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Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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Designing RBFNs Structure Using Similarity-Based and Kernel-Based Fuzzy C-Means Clustering Algorithms
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Multimodal system for diagnosis and polysensory stimulation of subjects with communication disorders
PublicationAn experimental multimodal system, designed for polysensory diagnosis and stimulation of persons with impaired communication skills or even non-communicative subjects is presented. The user interface includes an eye tracking device and the EEG monitoring of the subject. Furthermore, the system consists of a device for objective hearing testing and an autostereoscopic projection system designed to stimulate subjects through their...
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Multifactor consciousness level assessment of participants with acquired brain injuries employing human–computer interfaces
PublicationBackground A lack of communication with people suffering from acquired brain injuries may lead to drawing erroneous conclusions regarding the diagnosis or therapy of patients. Information technology and neuroscience make it possible to enhance the diagnostic and rehabilitation process of patients with traumatic brain injury or post-hypoxia. In this paper, we present a new method for evaluation possibility of communication and the...
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Selection of Visual Descriptors for the Purpose of Multi-camera Object Re-identification
PublicationA comparative analysis of various visual descriptors is presented in this chapter. The descriptors utilize many aspects of image data: colour, texture, gradient, and statistical moments. The descriptor list is supplemented with local features calculated in close vicinity of key points found automatically in the image. The goal of the analysis is to find descriptors that are best suited for particular task, i.e. re-identification...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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General concept of reduction process for big data obtained by interferometric methods
PublicationInterferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data – datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main...
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Process layout planning and optimised product range selection in manufacture of wooden construction sets
PublicationThis paper introduces a systematic deterministic framework for planning and the analysis of facility layouts aimed at manufacturing a variety of parts, as components of specific end products. The essence of the proposed approach lies in the decomposition of a traditional job-shop into layout modules of generic material flow patterns, that inherently yields improved efficiency of the entire system. It entails the use of a relevant...
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Microbial diversity of inflamed and noninflamed gut biopsy tissues in inflammatory bowel disease.
PublicationBACKGROUND: Inflammatory bowel disease (IBD) is a chronic gastrointestinal condition without any known cause or cure. An imbalance in normal gut biota has been identified as an important factor in the inflammatory process. METHODS: Fifty-eight biopsies from Crohn's disease (CD, n = 10), ulcerative colitis (UC, n = 15), and healthy controls (n = 16) were taken from a population-based case-control study. Automated ribosomal intergenic...
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Sustainability of Cluster Organizations as Open Innovation Intermediaries
PublicationThe purpose of the paper is to identify the most important open innovation practices used by cluster organizations (COs). To reflect these practices, the paper uses the concept of the trajectory of relationship development in COs, applied in the Interizon cluster organization. Additionally, this paper introduces the potential sustainability-related implications of open innovation adoption in cluster organizations. An in-depth direct...