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1

BCK-codes Based on a Parity Check Matrix

Keshavarzian Nazanin, Borumand Saeid Arsham, Tehranian Abolfazl

Fundamenta Informaticae

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2020

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Vol. 174, nr 2

137--165

EN

Hamming codes are of primary concern in information theory and its applications. Despite a number of researches that have been conducted on such codes and their characterizations, dealing with the properties of previously introduced codes in a BCK-algebraic framework has not been considered in earlier works. This paper investigates a code constructed based on BCK-algebraic models and proposes an algorithm corresponding to the presented code. It is noticeable that the suggested rendered algorithm is also established on the basis of the elements of a BCK-algebra. In fact, both the Hamming distance and dimension, associated with the presented code, can be estimated through a BCK-algebra structure due to the mechanism of its algorithm which is heavily dependent on the parity check matrix. In addition, the way in which the codes are designed contributes substantially to classification of them and to extract greater number of their attributes compared to the previous works. The highlight of the proposed method is that the number of atoms of the BCK-algebra plays a key role in calculation of the Hamming distance and dimension of these codes. Moreover, the obtained codes possess specified and recognizable Hamming distance which are essential in performing error-correcting, error-detecting and decoding tasks.

2

Yarn-Dyed Fabric Image Retrieval Using Colour Moments and the Perceptual Hash Algorithm

Li Zhongjian, Xiang Jun, Wang Lei, Zhang Ning, Pan Ruru, Gao Weidong

Fibres & Textiles in Eastern Europe

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2019

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Vol. 27, no. 5 (137)

39--46

EN

Due to the variety of yarn colours and arrangement, it is a challenging problem to retrieve a yarn-dyed fabric image. In this paper, yarn-dyed fabric samples are captured by the DigiEye system first, and then pattern images of the fabric images captured are simulated by pattern design software based on extracted structure parameters of the yarn-dyed fabric. For the simulated pattern image, an effective algorithm is proposed to retrieve these kinds of images by combining the colour moments method and perceptual hash algorithm. Then the pattern images retrieved are mapped back to the yarn-dyed fabric image so as to realise the yarn-dyed fabric image retrieval. In the algorithm proposed, the colour moments method is adopted to extract the colour features, and the perceptual hash algorithm is utilised to calculate the spatial features of the simulated pattern images. Then the two kinds of image features are used to compute the similarity between the input original image and each target image based on the Euclidean distance and Hamming distance. Relevant images can be retrieved in dependence on the similarity value, which is determined by calculating the optimum weighted value of the colour features’ similarity and spatial features’ similarity. In order to measure the retrieval efficiency of the method proposed, the accuracy rate and retrieval rate of image retrieval were computed in experiments using a PATTERN image database with 300 images. The experimental results show that the average accuracy rate of the method proposed is 85.30% and the retrieval rate - 53.51% when the weighted value of the colour feature similarity is fixed at 0.45 and the spatial feature similarity is 0.55. It is shown that the method presented is effective to retrieve pattern images of yarn-dyed fabric.

PL

Ze względu na różnorodność kolorów i rozmieszczenia przędz otrzymanie obrazu tkaniny wytworzonej z barwionych przędz jest trudnym zadaniem. W artykule próbki tkanin z barwionych przędz były najpierw analizowane przez system DigiEye, a następnie wykonane zostały symulacje obrazów z zastosowaniem oprogramowania do projektowania wzorów oparte na wyodrębnionych parametrach struktury tkaniny. W przypadku symulacji obrazu wzoru zaproponowano skuteczny algorytm do odzyskiwania tego rodzaju obrazów poprzez połączenie metody momentów koloru i percepcyjnego algorytmu z mieszaniem. W zaproponowanym algorytmie do wyodrębniania cech kolorów zastosowano metodę momentów barwnych, a do obliczenia cech przestrzennych symulowanych obrazów został wykorzystywany percepcyjny algorytm mieszania. Następnie użyto dwóch rodzajów cech obrazu do obliczenia podobieństwa między oryginalnym obrazem wejściowym a każdym obrazem docelowym w oparciu o odległość euklidesową i odległość Hamminga. Odpowiednie obrazy można odzyskać w zależności od wartości podobieństwa, która jest określana przez obliczenie optymalnej ważonej wartości podobieństwa cech koloru i podobieństwa cech przestrzennych. Aby zmierzyć skuteczność proponowanej metody w eksperymentach obliczono wskaźnik dokładności i szybkość pobierania obrazów, wykorzystując bazę danych obrazów PATTERN z 300 obrazami. Wyniki eksperymentalne pokazały, że średni współczynnik dokładności proponowanej metody wynosi 85,30%, a szybkość pobierania 53,51%, wartość podobieństwa cech kolorów wynosiła 0,45, a podobieństwo cech przestrzennych wynosiło 0,55. Wykazano, że prezentowana metoda jest skuteczna w przypadku otrzymywania obrazów wzorów tkanin z przędz barwionych.

3

Temporal alarm pattern discovery in mobile telecommunication networks based on binary series analysis

Mazdziarz A.

Control and Cybernetics

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2018

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Vol. 47, no. 2

191--213

EN

Highly-advanced systems, such as mobile telecommunication networks, characterized by increased complexity, make maintenance routines diﬃcult. Amount of data to be analyzed in a short time during fault diagnosis of the mobile telecommunication networks strongly justiﬁes the need to automate alarm correlation and root cause analysis. A major challenge in the establishment of alarm correlation is to determine how to reﬂect the alarm ﬂow inertia. Thus, adequate temporal alarm pattern discovery methods should be used in fault diagnosis for correlation-related purposes. Automatic temporal alarm pattern discovery allows fast generation of root cause analysis hypotheses and supports eﬀective troubleshooting of network problems. The process for fault propagation throughout the network is manifested by the time lag between the root-cause alarm and potentially linked symptoms, as well as weakening correlation strength with time. The paper presents a novel method for alarm correlation analysis in mobile telecommunication networks, based on binary series analysis. The method allows for discovery of causal relationship between alarms with dynamic alarm correlation window size estimation.