Evaluation de la dépendance spatiale locale pour la caractérisation de la texture

- Nous proposons une modélisation des distributions locales de la proximité de niveaux de gris entre un pixel et ses voisins sous hypothèses d'indépendance des pixels du voisinage. Le modèle proposé permet, au moyen du test du Chi-deux, de caractériser les aspects aléatoire et isotrope de la texture. Nous considérons le cas de l'indépendance stricte des pixels voisins et celui de l'indépendance conditionnelle relativement au pixel central

Artificial intelligence methods in diagnostics of coal-biomass blends co-combustion in pulverised coal burners

The paper presents technologies being developed in the Institute of Electronics and Information Technologies at Lublin University of Technology. They use optical sensors and artificial intelligence methods for process supervision and diagnostics. Research is aimed to develop a system allowing a parametric evaluation of the quality of pulverized coal burner operation. Due to the highly nonlinear nature of dependencies and lack of an analytical model, the artificial intelligence methods were used to estimate and classify the selected parameter, including a relatively new class of classification methods – artificial immunology algorithms. The article shows results for coal-shredded straw blends, yet the methodology may be applied for other types of blends.У роботі представлені технології, розроблені в Інституті електроніки та інформаційних технологій Люблінського технологічного університету. Вони використовують оптичні датчики та методи штучного інтелекту для контролю та діагностики процесу. Дослідження спрямовано на розробку системи, що дозволяє провести параметричну оцінку якості роботи пиловугільного пальника. Через високу нелінійну природу залежностей та відсутність аналітичної моделі для оцінки та класифікації обраного параметра були використані методи штучного інтелекту, включаючи відносно новий клас методів класифікації - алгоритми штучної імунології. У статті наведені результати для солом'яно-вугільних сумішей, але методологія може застосовуватися і для інших типів сумішей

Détection de contours par Transformation Quasi-Mixing

é - Nous présentons dans cet article une nouvelle approche pour l'extraction de contours. Cette approche est basée sur l'utilisation d'une transformation dite "quasi-mixing", c'est-à-dire, sur l'utilisation d'une permutation spécifique des pixels de l'image vérifiant certaines propriétés de nature statistique. Pour cette méthode, nous donnons des exemples variés et des éléments relatifs aux performances de l'algorithme proposé

Development and analysis of symmetric encryption algorithm Qamal based on a substitution-permutation network

This paper represents a developed cryptographic information protection algorithm based on an substitution-permutation network. We describe the cryptographic transformations used in the developed algorithm. One of the features of the algorithm is the simplicity of its modification with regard to different security levels. The algorithm uses a pre-developed S-box tested against differential and linear cryptanalysis. The S-box is consistent with the one of known standards AES and GOST R 34.12-2015. We provide the findings of an avalanche-effect investigation and statistical properties of cipher texts. The algorithm actually meets the avalanche-effect criterion even after the first round

Laser photoplethysmography in integrated evaluation of collateral circulation of lower extremities

The paper evaluated the diagnostic value of laser photoplethysmography when examining patients with chronic lower limb ischemia. A statistical analysis of the research results was made, and diagrams of relationship between the degrees of ischemia and blood flow are presente

Association between the c.*229C>T polymorphism of the topoisomerase IIb binding protein 1 (TopBP1) gene and breast cancer

Topoisomerase IIb binding protein 1 (TopBP1) is involved in cell survival, DNA replication, DNA damage repair and cell cycle checkpoint control. The biological function of TopBP1 and its close relation with BRCA1 prompted us to investigate whether alterations in the TopBP1 gene can influence the risk of breast cancer. The aim of this study was to examine the association between five polymorphisms (rs185903567, rs116645643, rs115160714, rs116195487, and rs112843513) located in the 30UTR region of the TopBP1 gene and breast cancer risk as well as allele-specific gene expression. Five hundred thirty-four breast cancer patients and 556 population controls were genotyped for these SNPs. Allele-specific Top- BP1 mRNA and protein expressions were determined by using real time PCR and western blotting methods, respectively. Only one SNP (rs115160714) showed an association with breast cancer. Compared to homozygous common allele carriers, heterozygous and homozygous for the T variant had significantly increased risk of breast cancer (adjusted odds ratio = 3.81, 95 % confidence interval: 1.63–8.34, p = 0.001). Mean TopBP1 mRNA and protein expression were higher in the individuals with the CT or TT genotype. There was a significant association between the rs115160714 and tumor grade and stage. Most carriers of minor allele had a high grade (G3) tumors classified as T2-T4N1M0. Our study raises a possibility that a genetic variation of TopBP1 may be implicated in the etiology of breast cancer

Low computational complexity algorithm for recognition highly corrupted QR codes based on Hamming-Lippmann neural network

This article describes the architecture of the Hamming-Lippmann neural network and the math of the modified learning-recognition algorithm and presents some practical aspects for using it for solving an image recognition task. We have created software using C# programming language, that utilized this network as an additional error-correcting procedure, and have solved the task of recognition highly corrupted QR codes (with a connection to the database). Experimental results, of finding the optimal parameters for this algorithm, are presented. This neural network doesn’t require time-consuming computational procedures and large amounts of memory, even for high-resolution and big size images.W tym artykule opisano architekturę sieci neuronowej Hamminga-Lippmanna oraz matematykę zmodyfikowanego algorytmu rozpoznawania uczenia się, a także przedstawiono kilka praktycznych aspektów korzystania z niej w celu rozwiązania zadania rozpoznawania obrazu. Stworzyliśmy oprogramowanie wykorzystujące język programowania C #, który wykorzystał tę sieć jako dodatkową procedurę korekty błędów i rozwiązaliśmy zadanie rozpoznawania wysoce uszkodzonych kodów QR (w połączeniu z bazą danych). Przedstawiono wyniki eksperymentalne poszukiwania optymalnych parametrów dla tego algorytmu. Opisywana neuronowa nie wymaga czasochłonnych procedur obliczeniowych i dużej ilości pamięci, nawet w przypadku obrazów o wysokiej rozdzielczości i dużych rozmiarach. (Algorytm o niskiej złożoności obliczeniowej do rozpoznawania wysoce uszkodzonych kodów QR w oparciu o sieć neuronową Hamminga-Lippmanna)