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Tytuł:
Pattern recognition approach to differentiation of disease severity in patients with amyotrophic lateral sclerosis
Autorzy:
Jóźwik, A.
Sokołowska, B.
Niebroj-Dobosz, I.
Janik, P.
Kwieciński, H.
Powiązania:
https://bibliotekanauki.pl/articles/333433.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
rozpoznawanie obrazu
klasyfikacja K-NN
erytropoetyna
pattern recognition
k-NN classifier
amyotropic lateral sclerosis
erythropoietin
Opis:
A possibility of recognition of the clinical status of patients with amyotrophic lateral sclerosis (ALS) in relation to severity of the disease was investigated. Three groups: (i) healthy controls (n=15) and two subgroups of ALS patients (ii) mild (n=15) and (iii) severe (n=15) were considered as classes. Four features of the subjects: (i) their age (AGE) (ii) erythropoietin concentration in serum (SERUM), (iii) in cerebrospinal fluid (CSF), and (iv) duration time of the disease (Tdis) were used for classifier construction based on the k Nearest Neighbours (k-NN) rule, known from pattern recognition theory. The presented results demonstrate that the pattern recognition approach may be useful for the evaluation of the severity of the ALS disease.
Źródło:
Journal of Medical Informatics & Technologies; 2008, 12; 143-147
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Recognition of pathological states in arterial blood by distance based techniques
Autorzy:
Sokołowska, B.
Jóźwik, A.
Powiązania:
https://bibliotekanauki.pl/articles/333231.pdf
Data publikacji:
2003
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
gazometria krwi tętniczej
paraliż przepony
zasada k-NN
klasyfikatory
arterial blood gasometry
paralysis of diaphragm
k-NN rule
classifiers
k-means algorithm
Opis:
The paper presents the application of some distance based pattern recognition algorithms for recognition of pathological states in respiratory system on the basis of the arterial blood gasometry (features pH, pCO2, pO2). In our biological model two experimental situations were considered: 1) the intact animals and 2) the main inspiratory muscles paralyzed (after acute of bilateral phrenicotomy). The comparison of the mentioned three features in the two conditions was the main goal of the present study. The analyzed biological data set contained 38 in class 1 (muscle function preserved) and 36 in class 2 (after diaphragm paralyzed) measurements. It was discovered that a significant part of the measurements could be correctly recognized as the ones coming from the first or the second class according to gasometric measurements.
Źródło:
Journal of Medical Informatics & Technologies; 2003, 5; MI23-30
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Pattern recognition approach for analysis of metabolic response to intermittent hypoxia
Autorzy:
Sokołowska, B.
Jóźwik, A.
Powiązania:
https://bibliotekanauki.pl/articles/333610.pdf
Data publikacji:
2010
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
rozpoznawanie wzorców
zasada k-NN
przerywane niedotlenienie
metaboliczna odpowiedź
pattern recognition
k-NN rule
pair-wise classifier
intermittent hypoxia
metabolic response
Opis:
Intermittent hypoxia (IH) elicits two forms of respiratory plasticity, which are initiated during and after exposure to IH, i.e. a long-term facilitation and a progressive augmentation of respiratory motor output. IH is often used as a model of sleep apnea and/or respiratory plasticity in humans and animals. Procedures of IH are also applied in sport medicine and rehabilitation of respiratory diseases. The aim of the present paper is an analysis of a metabolic response to acute intermittent hypoxia in a rat model. The animals were placed and monitored in a whole body plethysmographic chamber. The rats were exposed to five consecutive cycles consisting of 10-min hypoxic stimulus period separated by 10-min normoxic intervals, and additionally they were monitored up to 1 h after the final hypoxic exposure. The metabolism software analyzer recorded following variables (features): metabolic rate, carbon dioxide production, oxygen consumption and respiratory quotient. The obtained results demonstrated that acute IH causes metabolic effects during and after intermittent stimuli, which may be effectively recognized by an application of the k-NN classifiers.
Źródło:
Journal of Medical Informatics & Technologies; 2010, 15; 177-183
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Recommendation systems with the quantum k-NN and Grover algorithms for data processing
Autorzy:
Sawerwain, Marek
Wróblewski, Marek
Powiązania:
https://bibliotekanauki.pl/articles/330538.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
quantum k-NN algorithm
recommendation system
Grover algorithm
big data
kwantowy algorytm k-NN
system rekomendujący
algorytm Grovera
duży zbiór danych
Opis:
In this article, we discuss the implementation of a quantum recommendation system that uses a quantum variant of the k-nearest neighbours algorithm and the Grover algorithm to search for a specific element in an unstructured database. In addition to the presentation of the recommendation system as an algorithm, the article also shows the main steps in construction of a suitable quantum circuit for realisation of a given recommendation system. The computational complexity of individual calculation steps in the recommendation system is also indicated. The verification of the correctness of the proposed system is analysed as well, indicating an algebraic equation describing the probability of success of the recommendation. The article also shows numerical examples presenting the behaviour of the recommendation system for two selected cases.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2019, 29, 1; 139-150
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Measuring sadness index based on country statistics
Autorzy:
Samojluk, Artur
Nowak, Bartosz
Papiernik, Karolina
Powiązania:
https://bibliotekanauki.pl/articles/2190982.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Warmińsko-Mazurski w Olsztynie
Tematy:
happiness index
sadness index
k-nn
regression
machine learning
Opis:
The article studied topics related to measuring people’s sadness. For this purpose, the question was asked which factor: social, economic or climate, matters most. The paper analyzed, using machine learning, statistical data related to the number of suicides against the factors: level of Internet access, average income, temperature in a country and, in addition, population density. The method used was correlational statistical analysis using the K-nearest neighbor (KNN) method and also Pearson’s correlation. The results were visualized in the form of graphs, then subjected to final analysis and included in the form of final conclusions.
Źródło:
Technical Sciences / University of Warmia and Mazury in Olsztyn; 2022, 25(1); 193--203
1505-4675
2083-4527
Pojawia się w:
Technical Sciences / University of Warmia and Mazury in Olsztyn
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis of matrix metalloproteinases (MMPs) in cerebrospinal fluid of patients with amyotrophic lateral sclerosis (ALS)
Autorzy:
Sokołowska, B.
Jóźwik, A.
Niebroj-Dobosz, I.
Janik, P.
Kwieciński, H.
Powiązania:
https://bibliotekanauki.pl/articles/333116.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
klasyfikacja K-NN
stwardnienie zanikowe boczne
metaloproteinazy macierzy
płyn mózgowo-rdzeniowy
pattern recognition
k-NN classifier
amyotrophic lateral sclerosis
matrix metalloproteinase
cerebrospinal fluid
Opis:
Matrix metalloproteinases (MMPs) are implicated in the pathogenesis of motor neuron degeneration in amyotrophic lateral sclerosis (ALS) and might be potential markers of diagnosis, prognosis and monitoring treatment effects. The aim of the present study was evaluation of the MMPs significance in cerebrospinal fluid (CSF MMPs) of patients with ALS in relation to severity of the disease. Metalloproteinases MT-MMP-1, MMP-2, MMP-9 and additionally age of subjects and disease duration were analyzed. The results demonstrate that the error of differentiation between healthy subjects and ALS patients (for MMP-2 feature) as well as between mild and severe ALS states (for CSF MMPs set) equalled to 0.033. In conclusion, the pattern recognition approach may be useful for differentation of ALS progressing on the basis of CSF MMPs features.
Źródło:
Journal of Medical Informatics & Technologies; 2009, 13; 147-150
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Some problems with construction of the k-NN classifier for recognition of an experimental respiration pathology
Autorzy:
Jóźwik, A.
Sokołowska, B.
Powiązania:
https://bibliotekanauki.pl/articles/332910.pdf
Data publikacji:
2002
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
rozpoznawanie wzorców
klasyfikacja nadzorowana
zasada k-NN
wybór funkcji
oddychanie
wentylacja
paraliż
przepona
pattern recognition
supervised classification
k-NN rule
feature selection
respiration
ventilation
paralysis
diaphragm
Opis:
An objective of the work is to demonstrate some difficulties with construction of a classifier based on the k-NN rule. The standard k-NN classifier and the parallel k-NN classifier have been chosen as the two most powerful approaches. This kind of classifiers has been applied to automatic recognition of diaphragm paralysis degree. The classifier construction consists in determination of the number of nearest neighbors, selection of features and estimation of the classification quality. Three classes of muscle pathology, including the control class, and five ventilatory parameters are taken into account. The data concern a model of the diaphragm pathology in a cat. The animals were forced to breathe in three different experimental situations: air, hypercapnic and hypoxic conditions. A separate classifier is constructed for each kind of the mentioned situations. The calculation of the misclassification rate is based on the leave one out and on the testing set method. Several computational experiments are suggested for the correct feature selection, the classifier type choice and the misclassification probability estimation.
Źródło:
Journal of Medical Informatics & Technologies; 2002, 3; MI89-97
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The pair-wise linear classifier and the k-NN rule in application to ALS progression differentiation
Autorzy:
Sokołowska, B.
Jóźwik, A.
Niebroj-Dobosz, I.
Janik, P.
Powiązania:
https://bibliotekanauki.pl/articles/333011.pdf
Data publikacji:
2012
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
rozpoznawanie wzorców
wybór funkcji
klasyfikator liniowy
zasada k-NN
biomarkery
stwardnienie zanikowe boczne
pattern recognition
feature selection
linear classifier
k-NN rule
pair-wise classifier
biomarkers
amyotrophic lateral sclerosis
Opis:
The two kinds of classifier based on the k-NN rule, the standard and the parallel version, were used for recognition of severity of ALS disease. In case of the second classifier version, feature selection was done separately for each pair of classes. The error rate, estimated by the leave one out method, was used as a criterion as for determination the optimum values of k's as well as for feature selection. All features selected in this manner were used in the standard and in the parallel classifier based on k-NN rule. Furthermore, only for the verification purpose, the linear classifier was applied. For this kind of classifier the error rates were calculated by use the training set also as a testing one. The linear classifier was trained by the error correction algorithm with a modified stop condition. The data set concerned with the healthy subjects and patients with amyotrophic lateral sclerosis (ALS). The set of several biomarkers such as erythropoietin, matrix metalloproteinases and their tissue inhibitors measured in serum and cerebrospinal fluid (CSF) were treated as features. It was shown that CSF biomarkers were very sensitive for the ALS progress.
Źródło:
Journal of Medical Informatics & Technologies; 2012, 20; 79-83
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Nonparametric methods of supervised classification
Autorzy:
Jóźwik, A.
Powiązania:
https://bibliotekanauki.pl/articles/333226.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
pattern recognition
feature selection
k-NN rules
pair-wise classifier
artificial features
linear classifier
reference set size reduction
rozpoznawanie wzorca
wybór funkcji
reguła k-NN
sztuczne cechy
klasyfikator liniowy
Opis:
Selected nonparametric methods of statistical pattern recognition are described. A part of them form modifications of the well known k-NN rule. To this group of the presented methods belong: a fuzzy k-NN rule, a pair-wise k-NN rule and a corrected k-NN rule. They can improve classification quality as compared with the standard k-NN rule. For the cases when these modifications would offer to large error rates an approach based on class areas determination is proposed. The idea of class areas can be also used for construction of the multistage classifier. A separate feature selection can be performed in each stage. The modifications of the k-NN rule and the methods based on determination class areas can be too slow in some applications, therefore algorithms for reference set reduction and condensation, for simple NN rule, are proposed. To construct fast classifiers it is worth to consider also a pair-wise linear classifiers. The presented idea can be used as in the case when the class pairs are linearly separable as well as in the contrary case.
Źródło:
Journal of Medical Informatics & Technologies; 2013, 22; 21-32
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Zastosowanie multimodalnej klasyfikacji w rozpoznawaniu stanów emocjonalnych na podstawie mowy spontanicznej
Spontaneus emotion redognition from speech signal using multimodal classification
Autorzy:
Kamińska, D.
Pelikant, A.
Powiązania:
https://bibliotekanauki.pl/articles/408014.pdf
Data publikacji:
2012
Wydawca:
Politechnika Lubelska. Wydawnictwo Politechniki Lubelskiej
Tematy:
rozpoznawanie emocji
sygnał mowy
algorytm kNN
emotion recognition
speech signal
k-NN algorithm
Opis:
Artykuł prezentuje zagadnienie związane z rozpoznawaniem stanów emocjonalnych na podstawie analizy sygnału mowy. Na potrzeby badań stworzona została polska baza mowy spontanicznej, zawierająca wypowiedzi kilkudziesięciu osób, w różnym wieku i różnej płci. Na podstawie analizy sygnału mowy stworzono przestrzeń cech. Klasyfikację stanowi multimodalny mechanizm rozpoznawania, oparty na algorytmie kNN. Średnia poprawność: rozpoznawania wynosi 83%.
The article presents the issue of emotion recognition from a speech signal. For this study, a Polish spontaneous database, containing speech from people of different age and gender, was created. Features were determined from the speech signal. The process of recognition was based on multimodal classification, related to kNN algorithm. The average of accuracy performance was up to 83%.
Źródło:
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska; 2012, 3; 36-39
2083-0157
2391-6761
Pojawia się w:
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Could k-NN classifier be Useful in tree leaves recognition?
Autorzy:
Horaisová, K.
Powiązania:
https://bibliotekanauki.pl/articles/229900.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
binary image
Fourier transform
affine invariance
harmonic analysis
pattern recognition
k-NN classifier
Opis:
This paper presents a method for affine invariant recognition of two-dimensional binary objects based on 2D Fourier power spectrum. Such function is translation invariant and their moments of second order enable construction of affine invariant spectrum except of the rotation effect. Harmonic analysis of samples on circular paths generates Fourier coefficients whose absolute values are affine invariant descriptors. Affine invariancy is approximately saved also for large digital binary images as demonstrated in the experimental part. The proposed method is tested on artificial data set first and consequently on a large set of 2D binary digital images of tree leaves. High dimensionality of feature vectors is reduced via the kernel PCA technique with Gaussian kernel and the k-NN classifier is used for image classification. The results are summarized as k-NN classifier sensitivity after dimensionality reduction. The resulting descriptors after dimensionality reduction are able to distinguish real contours of tree leaves with acceptable classification error. The general methodology is directly applicable to any set of large binary images. All calculations were performed in the MATLAB environment.
Źródło:
Archives of Control Sciences; 2014, 24, 2; 177-192
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An analysis of a multidimensional dataset of an epidemic study using soft computing tools - a pilot study
Autorzy:
Handri, S.
Nomura, S.
Irfan, A. C.M.
Fukuda, S.
Yamano, E.
Watanabe, Y.
Powiązania:
https://bibliotekanauki.pl/articles/333077.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
epidemiologia
analiza regresji logistycznej
epidemiology
logistic regression analysis
feature set selection
K-NN analysis
Opis:
Two contrasting approaches toward an epidemic study were illustrated as a pilot study; the regression analysis which is rather conventional methodology used in the past/present epidemic studies, and the other is the classifier analysis which is in the soft computing toolbox. The dataset we used for this study is obtained from a part of a cohort study which principally focused on a fatigue syndrome of the elementary and junior high school educates. In the classifier analysis we employed a major supervised machine-learning algorithm, K-Nearest Neighbour (K-NN), coupled with Principal Component Analysis (PCA). As a result, the performance that was found by cross validation method in the classifier analysis provides better results than that of the regression analysis. Finally we discussed the availability of both analyses with referring the technical and conceptual limitation of both approaches.
Źródło:
Journal of Medical Informatics & Technologies; 2009, 13; 107-110
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Age-Type Identification and Classification of Historical Kannada Handwritten Scripts using Line Segmentation with HOG feature Descriptors
Autorzy:
Bannigidad, Parashuram
Gudada, Chandrashekar
Powiązania:
https://bibliotekanauki.pl/articles/1075427.pdf
Data publikacji:
2019
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
HOG
K-NN
Kannada
LDA
Line segmentation
Recognition
Restoration
SVM
Seam carving
document image analysis
handwritten script
historical documents
Opis:
The offline handwritten text recognition is one of the most challenging tasks in document image analysis; our aim is to recreate the cultural importance of the Kannada Language writing tradition through the historical degraded manuscripts. In the present digital era, we need to protect and digitize the resources of our Indian culture and heritage by digitizing those manuscripts which are losing its status; the degraded manuscripts are influenced by weather condition. In this paper, we have attempted to identify and recognise the historical Kannada handwritten scripts of various dynasties; namely, Vijayanagara dynasty (1460 AD), Mysore Wadiyar dynasty (1936 AD), Vijayanagara dynasty (1400 AD) and Hoysala dynasty (1340 AD) by using the improved seam carving text line segmentation method with HOG feature descriptors. The average classification accuracy for different dynasties are computed. The LDA classifier is yielded 93.4%, K-NN classifier has yielded 92% and SVM classifier has 95.5%. Based on the experimentation, the SVM classifier has recorded good classification performance comparatively LDA and K-NN classifiers for historical Kannada handwritten scripts.
Źródło:
World Scientific News; 2019, 126; 23-35
2392-2192
Pojawia się w:
World Scientific News
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Music Playlist Generation using Facial Expression Analysis and Task Extraction
Autorzy:
Sen, A.
Popat, D.
Shah, H.
Kuwor, P.
Johri, E.
Powiązania:
https://bibliotekanauki.pl/articles/908868.pdf
Data publikacji:
2016
Wydawca:
Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Tematy:
facial expression analysis
emotion recognition
feature extraction
viola jones face detection
gabor filter
adaboost
k-NN algorithm
task extraction
music classification
playlist generation
Opis:
In day to day stressful environment of IT Industry, there is a truancy for the appropriate relaxation time for all working professionals. To keep a person stress free, various technical or non-technical stress releasing methods are now being adopted. We can categorize the people working on computers as administrators, programmers, etc. each of whom require varied ways in order to ease themselves. The work pressure and the vexation of any kind for a person can be depicted by their emotions. Facial expressions are the key to analyze the current psychology of the person. In this paper, we discuss a user intuitive smart music player. This player will capture the facial expressions of a person working on the computer and identify the current emotion. Intuitively the music will be played for the user to relax them. The music player will take into account the foreground processes which the person is executing on the computer. Since various sort of music is available to boost one's enthusiasm, taking into consideration the tasks executed on the system by the user and the current emotions they carry, an ideal playlist of songs will be created and played for the person. The person can browse the playlist and modify it to make the system more flexible. This music player will thus allow the working professionals to stay relaxed in spite of their workloads.
Źródło:
Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica; 2016, 16, 2; 1-6
1732-1360
2083-3628
Pojawia się w:
Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A k-Nearest Neighbors Method for Classifying User Sessions in E-Commerce Scenario
Autorzy:
Suchacka, G.
Skolimowska-Kulig, M.
Potempa, A.
Powiązania:
https://bibliotekanauki.pl/articles/308645.pdf
Data publikacji:
2015
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
data mining
e-commerce
k-Nearest Neighbors
k-NN
log file analysis
online store
R-project
supervised classification
web mining
Web store
Web traffic
Web usage mining
Opis:
This paper addresses the problem of classification of user sessions in an online store into two classes: buying sessions (during which a purchase confirmation occurs) and browsing sessions. As interactions connected with a purchase confirmation are typically completed at the end of user sessions, some information describing active sessions may be observed and used to assess the probability of making a purchase. The authors formulate the problem of predicting buying sessions in a Web store as a supervised classification problem where there are two target classes, connected with the fact of finalizing a purchase transaction in session or not, and a feature vector containing some variables describing user sessions. The presented approach uses the k-Nearest Neighbors (k-NN) classification. Based on historical data obtained from online bookstore log files a k-NN classifier was built and its efficiency was verified for different neighborhood sizes. A 11-NN classifier was the most effective both in terms of buying session predictions and overall predictions, achieving sensitivity of 87.5% and accuracy of 99.85%.
Źródło:
Journal of Telecommunications and Information Technology; 2015, 3; 64-69
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
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