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Wyświetlanie 1-5 z 5
Tytuł:
Діалектний текст як джерело регіональних словників
A dialect text as a source for regional dictionaries
Autorzy:
Мартинова, Ганна
Щербина, Тетяна
Powiązania:
https://bibliotekanauki.pl/articles/26850457.pdf
Data publikacji:
2022-12-22
Wydawca:
Poznańskie Towarzystwo Przyjaciół Nauk
Tematy:
dialect lexicography
regional dictionary
registered unit
regional peculiarity
local feature
dialect text
діалектне словникарство
регіональний словник
реєстрове слово
регіоналізм
локалізм
діалектний текст
Opis:
У статті актуалізоване одне з невідкладних завдань слов᾽янської лінгвістики початку XXI ст. – лексикографічне опрацювання діалектної мови. Представлено доробок українського діалектного словникарства за перші десятиліття XXI ст., акцентувано увагу на важливості діалектного тексту як джерела для укладання регіонального словника. Указано на переваги такого підґрунтя, специфіку представлення народної лексики, її паспортизації за говірками та ареалами поширення в досліджуваному континуумі. Запропонований підхід уможливлює докладний опис реалій, вирізнення їхніх особливостей, репрезентованих у диференціації назв, засвідчує в реєстрових словах специфіку наголошування, регулярні та спорадичні зміни голосних і приголосних звуків. У спонтанних текстах мовці більш повно й об᾽єктивно розкривають семантику лексем, доповнючи їхнє тлумачення новими значеннями в мікротекстах, що перетворює словник в гіпертекст, веде читача від одного реєстрового слова до іншого, містить етнокультурну інформацію, виявляючи своєрідне бачення реалій діалектоносієм.
The article states that in early 21st century, Slavic linguistics lexicographic arrangement of the dialect appeared to preserve the original lexical stock shaped through a national outlook and mentality, as well as cultural values of the creative Ukrainian nation. The article is aimed to represent the dialect stock of the Ukrainian lexicography in the early 21st century, as well as to stress the importance of a dialect text as a source for arranging a regional dictionary. That has accentuated the dialect text proper as a source for arranging a regional dictionary that includes specially represented patois lexical units, their registration according to the dialects and their expansion in the area under consideration. The approach enables a detailed description of the status quo, its peculiar features represented in the differentiated names, as well as peculiar stressed forms, regular and sporadic shifts in vowels and consonants in the registered lexical units. In spontaneous speech, lexical meanings are more complete and more objectively revealed, being largely enforced by new meanings in microtexts. The authors have proved that arranging dictionaries by meaningful texts complete reveals the registered units, as well as regional and local ones in spontaneous speech in various word-building, phonetic and grammatical variants in the dialect aspect. Broad comments provided for the entries are taken from dialect texts and ensure progress to a next narrative fragment promoting a way to learning other linguistic units characteristic of dialects. The dictionary grows into a hypertext, leading the reader from one registered unit to another, providing ethnic linguistic information while revealing a specific status quo interpreted by dialect speakers.
Źródło:
Gwary Dziś; 2022, 15; 71-82
1898-9276
Pojawia się w:
Gwary Dziś
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Locally Regularized Linear Regression in the Valuation of Real Estate
Autorzy:
Kubus, Mariusz
Powiązania:
https://bibliotekanauki.pl/articles/465851.pdf
Data publikacji:
2016
Wydawca:
Główny Urząd Statystyczny
Tematy:
large transactional data
local regression
feature selection
regularization
cross-validation
Opis:
Regression methods are used for the valuation of real estate in the comparative approach. The basis for the valuation is a data set of similar properties, for which sales transactions were concluded within a short period of time. Large and standardized databases, which meet the requirements of the Polish Financial Supervision Authority, are created in Poland and used by the banks involved in mortgage lending, for example. We assume that in the case of large data sets of transactions, it is more advantageous to build local regression models than a global model. Additionally, we propose a local feature selection via regularization. The empirical research carried out on three data sets from real estate market confirmed the effectiveness of this approach. We paid special attention to the model quality assessment using cross-validation for estimation of the residual standard error.
Źródło:
Statistics in Transition new series; 2016, 17, 3; 515-524
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Texture and gene expression analysis of the MRI brain in detection of Alzheimer’s disease
Autorzy:
Bustamam, A.
Sarwinda, D.
Ardenaswari, G.
Powiązania:
https://bibliotekanauki.pl/articles/91834.pdf
Data publikacji:
2018
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
Alzheimer’s disease
MRI
Feature Extraction
Bi-Clustering
Local Binary Pattern
LBP
Opis:
Alzheimer’s disease is a type of dementia that can cause problems with human memory, thinking and behavior. This disease causes cell death and nerve tissue damage in the brain. The brain damage can be detected using brain volume, whole brain form, and genetic testing. In this research, we propose texture analysis of the brain and genomic analysis to detect Alzheimer’s disease. 3D MRI images were chosen to analyze the texture of the brain, and microarray data were chosen to analyze gene expression. We classified Alzheimer’s disease into three types: Alzheimer’s, Mild Cognitive Impairment (MCI), and Normal. In this study, texture analysis was carried out by using the Advanced Local Binary Pattern (ALBP) and the Gray Level Co-occurrence Matrix (GLCM). We also propose the bi-clustering method to analyze microarray data. The experimental results from texture analysis show that ALBP had better performance than GLCM in classification of Alzheimer’s disease. The ALBP method achieved an average value of accuracy of between 75% - 100% for binary classification of the whole brain data. Furthermore, Biclustering method with microarray data shows good performance gene expression, where this information show influence Alzheimer’s disease with total of bi-cluster is 6.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2018, 8, 2; 111-120
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Marine Mammals Classification using Acoustic Binary Patterns
Autorzy:
Nadir, Maheen
Adnan, Syed M.
Aziz, Sumair
Khan, Muhammad Umar
Powiązania:
https://bibliotekanauki.pl/articles/1953520.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
marine mammals
1D Local Binary Patterns
Mel frequency cepstral coefficients
feature extraction
passive acoustic monitoring
Opis:
Marine mammal identification and classification for passive acoustic monitoring remain a challenging task. Mainly the interspecific and intraspecific variations in calls within species and among different individuals of single species make it more challenging. Varieties of species along with geographical diversity induce more complications towards an accurate analysis of marine mammal classification using acoustic signatures. Prior methods for classification focused on spectral features which result in increasing bias for contour base classifiers in automatic detection algorithms. In this study, acoustic marine mammal classification is performed through the fusion of 1D Local Binary Pattern (1D-LBP) and Mel Frequency Cepstral Coefficient (MFCC) based features. Multi-class Support Vector Machines (SVM) classifier is employed to identify different classes of mammal sounds. Classification of six species named Tursiops truncatus, Delphinus delphis, Peponocephala electra, Grampus griseus, Stenella longirostris, and Stenella attenuate are targeted in this research. The proposed model achieved 90.4% accuracy on 70-30% training testing and 89.6% on 5-fold cross-validation experiments.
Źródło:
Archives of Acoustics; 2020, 45, 4; 721-731
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Rgb-D face recognition using LBP-DCT algorithm
Autorzy:
Kumar, Sunil B L
Kumari, Sharmila M
Powiązania:
https://bibliotekanauki.pl/articles/1956066.pdf
Data publikacji:
2021
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
RGB-D
kinect
local binary pattern
pattern recognition
feature extraction
histogram
face recognition
lokalny wzorzec binarny
rozpoznawanie wzorców
wyodrębnianie cech
rozpoznawanie twarzy
Opis:
Face recognition is one of the applications in image processing that recognizes or checks an individual's identity. 2D images are used to identify the face, but the problem is that this kind of image is very sensitive to changes in lighting and various angles of view. The images captured by 3D camera and stereo camera can also be used for recognition, but fairly long processing times is needed. RGB-D images that Kinect produces are used as a new alternative approach to 3D images. Such cameras cost less and can be used in any situation and any environment. This paper shows the face recognition algorithms’ performance using RGB-D images. These algorithms calculate the descriptor which uses RGB and Depth map faces based on local binary pattern. Those images are also tested for the fusion of LBP and DCT methods. The fusion of LBP and DCT approach produces a recognition rate of 97.5% during the experiment
Źródło:
Applied Computer Science; 2021, 17, 3; 73-81
1895-3735
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-5 z 5

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