In this study, a new detection algorithm for yarn-dyed fabric defect based on autocorrelation function and grey level co-occurrence matrix (GLCM) is put forward. First, autocorrelation function is used to determine the pattern period of yarn-dyed fabric and according to this, the size of detection window can be obtained. Second, GLCMs are calculated with the specified parameters to characterise the original image. Third, Euclidean distances of GLCMs between being detected images and template image, which is selected from the defect-free fabric, are computed and then the threshold value is given to realise the defect detection. Experimental results show that the algorithm proposed in this study can achieve accurate detection of common defects of yarn-dyed fabric, such as the wrong weft, weft crackiness, stretched warp, oil stain and holes.
The concept of antifragility has received much attention from researchers in recent years. Contrary to fragile systems which fail when exposed to stressors, antifragile systems prosper and improve in response to unpredictability, volatility, randomness, chaos and disturbance. The implications of antifragility goes beyond resilience or robustness. A resilient system resists stress and remains the same; while an antifragile system improves. Taleb argues that antifragility is required for dealing with events that he called black swans or X-events, which are scarce, unpredictable, and extreme events. Such events come as a surprise and have major consequences. The concept of antifragility was developed by Taleb in a socioeconomic context, not in industrial production. However, the authors think that this concept may have its greatest practical utilization when applied to industrial environments. Thus, they focused on this concept in the article aiming to investigate the level of antifragility in an organization. In order to perform this, the authors used a case study based on an Iranian manufacturer of banknotes and security paper (TAKAB). Firstly, a questionnaire was designed based on 7 criteria related to antifragility using the five-point Likert scale and a triangular fuzzy number for each linguistic term is defined. In the next phase, the weight of each component was obtained using the entropy technique. In the final stage, the Euclidean distance between the aggregated fuzzy antifragility index (FAI) and each linguistic term used during this case study was calculated. Finally, based on these results, the level of the organization’s antifragility was assessed as satisfactorily antifragile, based on the minimum Euclidean distance.
Celem badania omawianego w artykule jest ocena zróżnicowania przestrzennego województw pod względem wybranych wskaźników opisujących sytuację osób starszych (65 lat i więcej). Badanie dotyczyło lat 2005, 2010, 2015 i 2019; wykorzystano w nim dane publikowane w Banku Danych Lokalnych Głównego Urzędu Statystycznego. Z uzyskanego zestawu zmiennych wybrano do ostatecznych analiz pięć, w tym zmienną demograficzną oraz zmienne związane z zabezpieczeniem emerytalnym i infrastrukturą zdrowotną. Badanie empiryczne przeprowadzono z wykorzystaniem miary odległości euklidesowej oraz analizy skupień metodą Warda. Przeprowadzone analizy wykazały zróżnicowanie województw, co odzwierciedlają zarówno wyliczone odległości, jak i skład wyodrębnionych skupień. Wyniki wskazują na przestrzenne zróżnicowanie województw, które jest zgodne z przestrzennym zróżnicowaniem demograficznego starzenia się ludności w Polsce. Zaobserwowana odrębność woj. śląskiego może ponadto wynikać z uwzględnienia zmiennych dotyczących systemu zabezpieczenia emerytalnego.
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The aim of the study is the assessment of the spatial variation of voivodships (the largest administrative units in Poland) in terms of selected indicators describing the situation of people aged 65 and over. The study used data from the Local Data Bank of Statistics Poland (Główny Urząd Statystyczny) for the years 2005, 2010, 2015 and 2019. From the obtained set of diagnostic variables, five were used for the final analysis, including those relating to demographics, the pension security system and health infrastructure. The applied empirical method was based on the Euclidean metric as well as cluster analysis with Ward’s method. The performed analyses indicated a variation of voivodships which is reflected by the computed distances and components of the created clusters. The results revealed a spatial variation of voivodships which is consistent with the demographic ageing in Poland. Moreover, the observed distinction of Śląskie Voivodship may have been affected by the fact that variables related to the pension security system were also considered.
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In this paper, we propose a novel approach to distance measurement for rankings, introducing a new metric that exhibits exceptional properties. Our proposed distance metric is defined within the interval of 0 to 1, ensuring a compact and standardized representation. Importantly, we demonstrate that this distance metric satisfies all the essential criteria to be classified as a true metric. By adhering to properties such as non-negativity, identity of indiscernibles, symmetry, and the crucial triangle inequality, our proposed distance metric provides a robust and reliable approach for comparing rankings in a rigorous and mathematically sound manner. Finally, we compare our new metric with distances such as Hamming distance, Canberra distance, Bray-Curtis distance, Euclidean distance, Manhattan distance, and Chebyshev distance. By conducting simple experiments, we assess the performance and advantages of our proposed metric in comparison to these established distance measures. Through these comparisons, we demonstrate the superior properties and capabilities of our new drastic weighted similarity distance for accurately capturing the dissimilarities and similarities between rankings in the decision-making domain.
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