Wyniki wyszukiwania - BazTech

1

Similarity analysis of dynamic temperature measurements

Cui Zhiwen, Li Wenjun, Yu Sisi, Jin Minjun

Metrology and Measurement Systems

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2022

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Vol. 29, nr 2

283--300

EN

Different temperature sensors show different measurement values when excited by the same dynamic temperature source. Therefore, a method is needed to determine the difference between dynamic temperature measurements. This paper proposes a novelty approach to treating dynamic temperature measurements over a period of time as a temperature time series, and derives the formula for the distance between the measurement values using uniform sampling within the time series analysis. The similarity is defined in terms of distance to measure the difference. The distance measures were studied on the analog measurement datasets. The results show that the discrete Fréchet distance has stronger robustness and higher sensitivity. The two methods have also been applied to an experimental dataset. The experimental results also confirm that the discrete Fréchet distance performs better.

2

An application of the Pythagorean fuzzy sets in the fault diagnosis

Nguyen Hoang

Journal of KONBiN

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2022

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Vol. 52, iss. 4

63--74

EN

In this paper, a comprehensive review and critical analyses of methods based on the ordinary fuzzy set, Atanassov’s intuitionistic fuzzy set, and its extensions have been conducted to show their limitations and defects. Then, a novel similarity measure based on the generalized score function has been introduced that incorporates the significance (importance) of information, making it more intuitive to compare them. The proposed method is employed for the fault diagnosis of steam turbine generator unit under Pythagorean fuzzy environment. Ten fault types of rotating machines are established as failure patterns in nine different vibration frequency ranges, expressed in terms of Pythagorean fuzzy numbers. The superiority of the proposed method in dealing with uncertain and vague information is shown by comparing it with some existing measures in numerical examples.

PL

W artykule dokonano kompleksowego przeglądu i analiz krytycznych metod opartych na klasycznym zbiorze rozmytym lub intuicjonistycznym zbiorze rozmytym Atanassova i ich rozszerzeniach w celu wykazania ich ograniczeń i wad. Następnie wprowadzono na podstawie miary wiedzy, nową miarę podobieństwa, która uwzględnia znaczenie (ważność) informacji, czyniąc je bardziej intuicyjnymi przy ich porównywaniu. Zaproponowaną metodę weryfikuje się w przypadku diagnozowania uszkodzeń zespołu turbogeneratora w rozmytym środowisku. Dziesięć typów uszkodzeń turbogeneratora jest określanych jako wzorce uszkodzeń wyrażonych za pomocą liczb rozmytych Pitagorasa opisujących ich symptomy w dziewięciu różnych zakresach częstotliwości drgań. Poprzez porównanie z niektórymi istniejącymi miarami w kilku przykładach liczbowych pokazano przewagę proponowanej metody w opisaniu niedokładnych i niepewnych informacji.

3

A simple multi-feature based stereoscopic medical image retrieval system

Shaheer Abubacker K. A., Sutha J., Shahul Hameed K. A.

Polish Journal of Medical Physics and Engineering

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2019

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Vol. 25, Iss. 2

127--130

EN

This paper describes a method of retrieving stereoscopic medical images from the database that consists of feature extraction, similarity measure, and re-ranking of retrieved images. This method retrieves similar images of the query image from the database and re-ranks them according to the disparity map. The performance is evaluated using the metrics namely average retrieval precision (APR) and average retrieval rate (ARR). According to the performance outcomes, the multi-feature based image retrieval using Mahalanobis distance measure has produced better result compared to other distance measures namely Euclidean, Minkowski, the sum of absolute difference (SAD) and the sum of squared absolute difference (SSAD). Therefore, the stereo image retrieval systems presented has high potential in biomedical image storage and retrieval systems.

4

Niewiarowski Artur

Computer Assisted Methods in Engineering and Science

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2019

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vol. 26, no. 3-4

163--175

EN

This paper presents a new algorithm with an objective of analyzing the similarity measure between two text documents. Specifically, the main idea of the implemented method is based on the structure of the so-called “edit distance matrix” (similarity matrix). Elements of this matrix are filled with a formula based on Levenshtein distances between sequences of sentences. The Levenshtein distance algorithm (LDA) is used as a replacement for various implementations of stemming or lemmatization methods. Additionally, the proposed algorithm is fast, precise, and may be implemented for analyzing very large documents (e.g., books, diploma works, newspapers, etc.). Moreover, it seems to be versatile for the most common European languages such as Polish, English, German, French and Russian. The presented tool is intended for all employees and students of the university to detect the level of similarity regarding analyzed documents. Results obtained in the paper were confirmed in the tests shown in the article.

5

Ďuračiová R., Rášová A., Lieskovský T.

Reports on Geodesy and Geoinformatics

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2017

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Vol. 104

115--130

EN

When combining spatial data from various sources, it is often important to determine similarity or identity of spatial objects. Besides the differences in geometry, representations of spatial objects are inevitably more or less uncertain. Fuzzy set theory can be used to address both modelling of the spatial objects uncertainty and determining the identity, similarity, and inclusion of two sets as fuzzy identity, fuzzy similarity, and fuzzy inclusion. In this paper, we propose to use fuzzy measures to determine the similarity or identity of two uncertain spatial object representations in geographic information systems. Labelling the spatial objects by the degree of their similarity or inclusion measure makes the process of their identification more efficient. It reduces the need for a manual control. This leads to a more simple process of spatial datasets update from external data sources. We use this approach to get an accurate and correct representation of historical streams, which is derived from contemporary digital elevation model, i.e. we identify the segments that are similar to the streams depicted on historical maps.

6

Interval-valued Fuzzy Soft Decision Making Methods Based on MABAC, Similarity Measure and EDAS

Peng X., Dai J., Yuan H.

Fundamenta Informaticae

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2017

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Vol. 152, nr 4

373--396

EN

Interval-valued fuzzy soft decision making problems have obtained great popularity recently. Most of the current methods depend on level soft set that provide choice value of alternatives to be ranked. Such choice value always encounter the equal condition that the optimal alternative can't be gained. Most important of all, the current decision making procedure is not in accordance with the way that the decision makers think about the decision making problems. In this paper, we initiate a new axiomatic definition of interval-valued fuzzy distance measure and similarity measure, which is expressed by interval-valued fuzzy number (IVFN) that will reduce the information loss and keep more original information. Later, the objective weights of various parameters are determined via grey system theory, meanwhile, we develop the combined weights, which can show both the subjective information and the objective information. Then, we present three algorithms to solve interval-valued fuzzy soft decision making problems by Multi- Attributive Border Approximation area Comparison (MABAC), Evaluation based on Distance from Average Solution (EDAS) and new similarity measure. Three approaches solve some unreasonable conditions and promote the development of decision making methods. Finally, the effectiveness and feasibility of approaches are demonstrated by some numerical examples.

7

Varish N., Kumar S., Pal A. K.

Fundamenta Informaticae

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2017

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Vol. 156, nr 2

209--235

EN

Content-based image retrieval (CBIR) scheme has gained popularity in the field of information retrieval for retrieving some relevant images from the image database based on the visual descriptors such as color, texture and/or shape of a given query image. In this paper, color features have been exploited from each color component of an RGB color image by using multiresolution approach since most of the information of an image is undetected at one resolution level while some other undetectable information is visualized in other multi-resolution levels. Initially, Gaussian image pyramid is employed on each color component of the color image and subsequent DCT is computed directly on the obtained multi-resolution image planes. Then some significant DCT coefficients are selected according to the zigzag scanning order. For formation of the feature vector, we have derived some statistical values from AC coefficients and all other DC coefficients are included entirely. Finally, a similarity measure is suggested during image retrieval process and it is found that the overall computation overhead is reduced due to consideration of the proposed similarity measure. The proposed CBIR scheme is validated on a two standard Corel-1K and GHIM-10K image databases and satisfactory results are achieved in terms of precision, recall and F-score. The retrieved results show that the proposed scheme outperforms significantly over other related CBIR schemes.

8

Content-based image retrieval using a signature graph and a self-organizing map

Van T. T., Le T. M.

International Journal of Applied Mathematics and Computer Science

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2016

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Vol. 26, no. 2

423--438

EN

In order to effectively retrieve a large database of images, a method of creating an image retrieval system CBIR (content-based image retrieval) is applied based on a binary index which aims to describe features of an image object of interest. This index is called the binary signature and builds input data for the problem of matching similar images. To extract the object of interest, we propose an image segmentation method on the basis of low-level visual features including the color and texture of the image. These features are extracted at each block of the image by the discrete wavelet frame transform and the appropriate color space. On the basis of a segmented image, we create a binary signature to describe the location, color and shape of the objects of interest. In order to match similar images, we provide a similarity measure between the images based on binary signatures. Then, we present a CBIR model which combines a signature graph and a self-organizing map to cluster and store similar images. To illustrate the proposed method, experiments on image databases are reported, including COREL, Wang and MSRDI.

9

Method for identification of fragments of lip prints images on the basis of the generalized hough transform

Wrobel K., Doroz R.

Journal of Medical Informatics & Technologies

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2013

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Vol. 22

189--193

EN

The paper presents a new method for identification of fragments of lip print images on the basis of the Generalized Hough Transform (GHT). The effectiveness of this method was verified in practice. The maximum value obtained from the accumulator array after the Hough transform has been assumed as the measure of similarity between a lip print image and a reference object. The advantage of this method is the possibility of use in forensic science to identify persons who left lip prints at crime scenes.

10

Miary podobieństwa w wyznaczaniu dysparycji obrazu stereowizyjnego

Szpytko J., Hyla P.

Logistyka

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2012

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nr 3

PL

Przedmiot artykułu stanowi test ośmiu metod obliczania miary podobieństwa zaimplementowanych w postaci algorytmu porównującego blokami dla potrzeb obliczania mapy dysparycji ze wzorcowej stereopary. Przyjęte przez autorów kryteria oceny uzyskanych wyników pod względem ich przydatności w głównej mierze uwzględniają zarówno kryteria jakościowe wygenerowanej mapy dysparycji oraz kryteria ilościowe uwzględniające czas przetwarzania przyjętej za wzorzec stereopary.

EN

The article focus on the eight methods of the similarity measures, implementing in the region matching algorithms for the needs of disparity calculation. The authors establishes quality and quantitative criteria for the final results examine. Each posses dense disparity map was tested under her outward appearance and computing time. All tests was realized on the example stereo pair photos.

11

Hydraulic model based method for leaks location in urban water distribution network

Tomasik P.

Diagnostyka

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2012

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nr 1(61)

45-50

EN

The paper describes the use one of the methods for locating leaks based on an accurate model of the network. The paper presents the results of this approach for the active experiment which was carried out on the water supply. The experiment consisted of releasing water with the varying intensity of the fire hydrants located on the test area. Based on the readings of flow meters located in the district, the aim was to identify pre-defined areas in which the simulated leaks occurred. The results are summarized in conclusions.

12

A Method for Nucleotide Sequence Analysis

Kozarzewski B.

Computational Methods in Science and Technology

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2012

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Vol. 18, No. 1

5-10

EN

Symbolic sequence decomposition into a set of consecutive, distinct subsequences (mers) is presented. Several statistical distributions of nucleotide subsequences are defined and analysed. Sequence entropy and similarity between sequences in terms of mer lengths distribution are defined. An alignment-free method of phylogenetic tree construction is proposed.

13

Zastosowanie modeli dokładnych sieci do detekcji i lokalizacji wycieków

Tomasik P.

Problemy Eksploatacji

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2011

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nr 2

223-230

PL

W referacie opisano metodę wykorzystującą dokładne modele sieci wodociągowej do detekcji i lokalizacji wycieków. Metoda ta bazuje na prostej mierze podobieństwa pomiędzy rzeczywistymi i modelowymi danymi o przepływach w sieci wodociągowej.

EN

The paper describes a method of using accurate models of the water supply system for detecting and locating leaks. This method is based on a simple measure of similarity between real and simulated data on water flows in the water supply.

14

Efficient face recognition based on weighted matrix distance metrics and 2DPCA algorithm

Rouabhia C., Tebbikh H.

Archives of Control Sciences

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2011

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Vol. 21, no. 2

207-221

EN

In this paper, a new similarity measure is developed for human face recognition, namely, weighted matrix distance. The key difference between this metric and the standard distances is the use of matrices and weights rather than the vectors only. The two feature matrices are obtained by two-dimensional principal component analysis (2DPCA). The weights are the inverse of the eigenvalues sorted in decreasing order of the covariance matrix of all training face matrices. Experiments are performed under illumination and facial expression variations using four face image databases: ORL, Yale, PF01 and a subset of FERET. The results demonstrate the effectiveness of the proposed weighted matrix distances in 2DPCA face recognition over the standard matrix distance metrics: Yang, Frobenius and assembled matrix distance (AMD).

15

Wybór miary podobieństwa a efektywność grupowania reguł w złożonych bazach wiedzy

Nowak-Brzezińska A., Wakulicz-Deja A.

Studia Informatica

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2010

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Vol. 31, nr 2A

189-201

PL

Praca przedstawia wyniki eksperymentów analizujących wpływ wybranej metryki podobieństwa na efektywność grupowania reguł w złożonych bazach wiedzy. Inna metryka podobieństwa to inna struktura skupień reguł, a co za tym idzie, inny przebieg procesów wnioskowania dla takich struktur.

EN

The paper presents the results of the experiments analyzing an influence choosed similarity measure on the efficiency of rules (from composited knowledge bases) clustering. In authors oppinion. Each time when we use different measure we achieving different structure of rules' clusters and the results of inference process.

16

Tensor Framework and Combined Symmetry for Hypertext Mining

Saha S., Murthy C.A., Pal S.K.

Fundamenta Informaticae

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2009

|

Vol. 97, nr 1/2

215-234

EN

We have made a case here for utilizing tensor framework for hypertext mining. Tensor is a generalization of vector and tensor framework discussed here is a generalization of vector space model which is widely used in the information retrieval and web mining literature. Most hypertext documents have an inherent internal tag structure and external link structure that render the desirable use of multidimensional representations such as those offered by tensor objects. We have focused on the advantages of Tensor Space Model, in which documents are represented using sixth-order tensors. We have exploited the local-structure and neighborhood recommendation encapsulated by the proposed representation. We have defined a similarity measure for tensor objects corresponding to hypertext documents, and evaluated the proposed measure for mining tasks. The superior performance of the proposed methodology for clustering and classification tasks of hypertext documents have been demonstrated here. The experiment using different types of similarity measure in the different components of hypertext documents provides the main advantage of the proposed model. It has been shown theoretically that, the computational complexity of an algorithm performing on tensor framework using tensor similarity measure as distance is at most the computational complexity of the same algorithmperforming on vector space model using vector similarity measure as distance.

17

A Similarity Measure for Cyclic Unary Regular Languages

Dassow J., Martin G.M., Vico F.J.

Fundamenta Informaticae

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2009

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Vol. 96, nr 1/2

71-88

EN

A cyclic unary regular language is a regular language over a unary alphabet that is represented by a cyclic automaton. We propose a similarity measure for cyclic unary regular languages by modifying the Jaccard similarity coefficient and the Sorensen coefficient to measure the level of overlap between such languages. This measure computes the proportion of strings that are shared by two or more cyclic unary regular languages and is an upper bound of the Jaccard coefficient and the Sorensen coefficient. By using such similarity measure, we define a dissimilarity measure for cyclic unary regular languages that is a semimetric distance. Moreover, it can be used for the non-cyclic case.

18

New signature similarity measure based on average differences

Wróbel K., Doroz R.

Journal of Medical Informatics & Technologies

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2008

|

Vol. 12

51--56

EN

This paper presents a new method of recognizing handwritten signatures. Signature was treated as a collection of features of specific values. As features the values of x, y coordinates of signature points and the pressure p in its consecutive points have been used. Additionally, before comparing them, the signatures were properly prepared. The method discussed in the paper is a modification of the method based on average differences. This modification consists in dividing signatures into windows of the preset size and measuring the value of similarity between the windows according to their position in the signature. The paper shows the construction of a new similarity measure taking into consideration the modifications introduced and the results of the research obtained by means of this similarity measure.

19

Analysis of Cotton Maturity Degree on Microstructure Level by Fuzzy Set Conception

Sarna E., Rabiej M., Sarna M., Włochowicz A.

Fibres & Textiles in Eastern Europe

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2008

|

Vol. 16, no. 1 (66)

13--18

EN

This paper is a continuation and generalisation of an earlier study of cotton maturity degree determination in the earlier paper. Up till now the maturity degree of cotton has been determined by the analysis of longitudinal outside views of cotton fibres. Early, we proposed a method of cotton maturity determination based on SEM images of cotton fractures. Fuzzy set conception was adopted to analyse each image, considering the fracture category. In this paper have emphasized the fuzzy aspects of cotton maturity determination by analysing the longitudinal outside views of cotton in accordance with the “Russian-standard”, and by using a new method for determination, which is based on analysing SEM images of cotton fractures proposed by as.

PL

Przedstawiona praca stanowi kontynuację wcześniejszych badań nad wyznaczaniem stopnia dojrzałości bawełny do tej pory wyznaczanego na podstawie analizy wzdłużnego, zewnętrznego widoku włókna bawełny. W wcześniejszej pracy zaproponowano metodę wyznaczania dojrzałości bawełny na podstawie analizy obrazów SEM przełomów włókien bawełny. Do analizy cech obrazów przełomów włókien została zastosowana koncepcja zbiorów rozmytych. W prezentowanym opracowaniu zastosowano elementy zbiorów rozmytych również do oceny wzdłużnego widoku włókna. Utworzono „wzorzec rozmyty” bazując na tzw. „Standardach Radzieckich”. Miara „zbliżenia” zbioru rozmytego jest użytecznym narzędziem do wyznaczania stopnia dojrzałości bawełny.

20

Fitness-distance analysis of a car sequencing problem

Kubiak M., Jaszkiewicz A., Kominek P.

Foundations of Computing and Decision Sciences

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2006

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Vol. 31, No. 3-4

263-276

EN

The paper describes a fitness-distance analysis of a car sequencing problem. It defines 5 similarity measures for solutions of the problem, describes computational experiments and provides values of determination coefficients between fitness and similarity, which are an indicator of fitness-distance correlation (or 'big valley'). The analysis reveals certain correlations of fitness and two types of similarity for 4 of 5 types of available instances. This results might motivate such designs of metaheuristics for these types of instances which would exploit the structure in fitness landscapes.