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1

Segmentation algorithm of coal slurry foam with double-point directional extension based on the improved FCM clustering algorithm

Wu ZiHao, Huang XianWu, Shang HaiLi, Zhao YuHong

Physicochemical Problems of Mineral Processing

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2023

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Vol. 59, iss. 1

art. no. 158850

EN

In flotation production, the visual surface information of the flotation foam reflects the flotation effects, which are closely related to the flotation conditions and directly reflect the degree of mineralization of the foam layer. In this study, it was proposed a novel and efficient segmentation algorithm to extract the edge information of slime bubbles, as the boundaries are typically blurred and difficult to segment, due to the slime bubbles sticking to each other in the slime flotation foam image. First, the improved clustering algorithm and image morphology operation were used to extract the edges of the foam spots. Second, the image morphological operations were used as a starting point to look around the foam edge points. The pseudo-edge points were then removed using a region and spatial removal algorithm. Finally, the foam edges were extracted using the double-point directed expansion algorithm. A new criterion was proposed for segmentation effect determination based on the particularity of the segmented object. The feasibility and effectiveness of the foam segmentation method were investigated by comparative experiments. The experimental results showed that the proposed algorithm could obtain the foam surface properties more accurately and provide effective guidance for flotation production.

2

Ozonation in Wastewater Disinfection

Zamorska Justyna, Kiełb-Sotkiewicz Izabela

Civil and Environmental Engineering Reports

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2023

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Vol. 33, no. 3

63--75

EN

Due to the potential microbiological hazard associated with discharging treated sewage into the receiving body, its disinfection is a key issue to protect ecological safety and human health. Water scarcity and drinking water supply, irrigation, rapid industrialization, use of treated water, protection of water sources, overpopulation and environmental protection force us to look for solutions to ensure safe reuse of wastewater, and this depends primarily on the quality of wastewater disinfection. Many wastewater disinfection methods are commonly used. One of the chemical processes of disinfection sludge is ozonation. Ozonation is widely used in wastewater treatment by oxidation, because ozone is a very strong and effective oxidizing agent. Studies have shown that the effectiveness of ozone in disinfecting water and sewage is up to 50% greater than that of chlorine . An additional advantage of this method is that it also eliminates odors that may be unavailable. The article presents the results of research on the effectiveness of ozonation treatment in the disinfection of treated sewage, based on indicator bacteria such as coliforms, including Escherichia coli, mesophiles, psychrophiles, and spores. The study took into account various effects of time (dose) and temperature. For the purpose of this study, both traditional and modern methods of assessing microbiological quality of wastewater were used. The first one is represented by conventional culture measurements and the second one by using a luminometer (ATP) and flow cytometer (FCM).

3

Image retrieval of MRI brain tumour images based on SVM and FCM approaches

Bansal Sonia, Mehan Vineet

Bio-Algorithms and Med-Systems

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2021

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Vol. 17, no. 3

173--179

EN

Objectives: The key test in Content-Based Medical Image Retrieval (CBMIR) frameworks for MRI (Magnetic Resonance Imaging) pictures is the semantic hole between the low-level visual data caught by the MRI machine and the elevated level data seen by the human evaluator. Methods: The conventional component extraction strategies centre just on low-level or significant level highlights and utilize some handmade highlights to diminish this hole. It is important to plan an element extraction structure to diminish this hole without utilizing handmade highlights by encoding/consolidating low-level and elevated level highlights. The Fleecy gathering is another packing technique, which is applied in plan depiction here and SVM (Support Vector Machine) is applied. Remembering the predefinition of bunching amount and enlistment cross-section is until now a significant theme, a new predefinition advance is extended in this paper, in like manner, and another CBMIR procedure is suggested and endorsed. It is essential to design a part extraction framework to diminish this opening without using painstakingly gathered features by encoding/joining low-level and critical level features. Results: SVM and FCM (Fuzzy C Means) are applied to the power structures. Consequently, the incorporate vector contains all the objectives of the image. Recuperation of the image relies upon the detachment among request and database pictures called closeness measure. Conclusions: Tests are performed on the 200 Image Database. Finally, exploratory results are evaluated by the audit and precision.

4

Materiały opakowaniowe do kontaktu z żywnością

Lenartowicz-Klik Marta

Przemysł Spożywczy

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2020

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T. 74, nr 12

30--33

PL

Metal, drewno, szkło, papier i ceramika to tradycyjne materiały opakowaniowe do żywności, które już dawno ustąpiły miejsca innowacyjnym opakowaniom z tworzyw polimerowych. Branża materiałów opakowaniowych przeznaczonych do kontaktu z żywnością coraz częściej dostarcza innowacyjne produkty, które z punktu widzenia konsumentów mają niezmiernie ważny wpływ zarówno na bezpieczeństwo żywności, jak i jej atrakcyjność użytkową. Materiały przeznaczone do kontaktu z żywnością powinny być wystarczająco obojętne, żeby ich składniki nie wpływały niekorzystnie na zdrowie konsumentów ani na jakość żywności. Aby zapewnić bezpieczeństwo materiałów przeznaczonych do kontaktu z żywnością i ułatwić swobodny przepływ towarów, prawo UE przewiduje wiążące zasady, których muszą przestrzegać podmioty gospodarcze. W artykule scharakteryzowano podstawowe materiały stosowane do kontaktu z żywnością, głównie tworzywa polimerowe, oraz przedstawiono zasadnicze wymogi prawne dotyczące materiałów przeznaczonych do kontaktu z żywnością.

EN

Metal, wood, glass, paper and ceramics are the traditional food packaging materials (FCMs), which are increasingly giving way to innovative packaging from polymer plastics. The industry of packaging materials intended for contact with food more and more often provides innovated products that, from the point of view of consumers, have a significant impact on both food safety and its attractiveness. FCMs should be sufficiently inert so that their constituents neither adversely affect consumer health nor influence the quality of the food. To ensure the safety of FCMs, and to facilitate the free movement of goods, EU law provides for binding rules that business operators must comply with. The article describes the basic materials used in FCMs, mainly polymeric materials, and presents the basic requirements for these materials.

5

Fuzzy Logic Method for Predicting the Effect of Main Fabric Parameters Influencing Drape Phenomenon

Thouraya Hamdi, Adel Ghith, Faten Fayala

Autex Research Journal

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2020

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Vol. 20, no. 3

220--227

EN

The main aspect of this research was to predict the drape parameters and describe clearly the drape phenomenon using fuzzy logic method. Forecasting features allow manufacturers to save time and improve their productivity. The bending rigidity, (in warp, weft, and skew direction), shear rigidity, and weight of fabric samples were used as the key input variables for the model, whereas drape coefficient, drape distance ratio, folds depth index, and node number were used as output/response variables. The results show that changing the values of fabric parameters significantly affected the fabric drape and a representative correlation values were found between the experimental values and those calculated by the fuzzy system.

6

Wykorzystanie rozmytych map kognitywnych FCM, jako narzędzia wspomagającego proces podejmowania decyzji w planowaniu przestrzennym

Skiba M.

Teka Komisji Urbanistyki i Architektury Oddział PAN w Krakowie

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2018

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T. 46

557--564

PL

W artykule przedstawiono narzędzie – rozmyte mapy kognitywne FCM, które może być wykorzystane do modelowania percepcji krajobrazu. Metodologia pozostawia szanse na wprowadzenie uzupełniających lub alternatywnych zasad oceny, źródeł danych i zastosowań. Narzędzie FCM nadaje się do określania różnych scenariuszy działań, w zależności od np.: przewidywanych trendów użytkowania gruntów lub celów przyjętych w strategii planowania przestrzennego. Zarządzanie krajobrazem kulturowym wymaga uczestnictwa społeczności (zwłaszcza lokalnych) w procesie kształtowania krajobrazu tak, aby możliwy był wzrost jego jakości i akceptacji przy jednoczesnym minimalizowaniu konfliktów przestrzennych. Włączenie budowy map kognitywnych FCM jako narzędzia wspomagającego proces podejmowania decyzji na jednym z etapów (np. partycypacji społeczności lokalnej) w planowaniu przestrzennym umożliwia spełnienie tych wymagań.

EN

The paper presents an instrument – fuzzy cognitive maps (FCM), which can be used to model landscape perception. The methodology provides the possibility of introducing complementary or alternative assessments, data sources and applications. The FCM instrument can be used to define different scenarios, depending on, for example, anticipated land use trends or objectives adopted in the spatial planning strategy. Managing a cultural landscape requires the participation of communities (especially local ones) in the process of landscape formation to increase the quality of the landscape and its acceptance while minimizing spatial conflicts. The incorporation of fuzzy cognitive maps (FCM) as an instrument facilitating the process of decision-making at one stage (e.g. local community participation) in spatial planning makes it possible to meet these requirements.

7

Modelowanie systemu prognozowania natężenia ruchu z zastosowaniem rozmytej mapy kognitywnej i wielokrokowych algorytmów uczenia

Jastriebow A., Poczęta K.

Logistyka

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2014

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nr 3

2590--2597

PL

Rozmyta mapa kognitywna (ang. fuzzy cognitive map FCM) stanowi efektywne narzędzie modelowania dynamicznych systemów wspomagania decyzyjnego. Kluczowym zagadnieniem związanym z FCM jest możliwość uczenia macierzy relacji na podstawie rzeczywistych danych. Niniejsza praca prezentuje zastosowanie rozmytej mapy kognitywnej oraz wielokrokowych algorytmów uczenia w modelowaniu systemu prognozowania natężenia ruchu. Opisano FCM oraz wielokrokowe algorytmy uczenia nadzorowanego opartego na metodzie gradientowej. Przedstawiono wybrane wyniki analizy symulacyjnej opracowanego modelowania kognitywnego na przykładzie systemu prognozowania natężenia ruchu. Uczenie oraz testowanie FCM przeprowadzono z zastosowaniem rzeczywistych znormalizowanych danych. Dokonano analizy porównawczej wielokrokowej metody gradientowej z jednokrokową, pod kątem wpływu na działanie modelowanego systemu. Uzyskane wyniki pokazują dostateczną efektywność zastosowania rozmytej mapy kognitywnej i wielokrokowych algorytmów uczenia w prognozowaniu natężenia ruchu.

EN

Fuzzy cognitive map (FCM) is an effective tool for modeling of dynamic decision support systems. The crucial issue connected with the FCM is the ability to learn the relations matrix based on real data. This paper presents the use of fuzzy cognitive map and multi-step learning algorithms in modeling of decision support system for traffic forecasting. FCM and multi-step supervised learning algorithms based on gradient method are described. Selected results of simulation analysis of the cognitive modeling on the example of traffic forecasting are shown. FCM learning and testing were performed with the use of real normalized data. Comparative analysis of multi-step gradient method to one-step algorithm, from the point of view of the influence on the modeled system was done. The results show the sufficient effectiveness of the use of fuzzy cognitive map and multi-step learning algorithms in traffic forecasting.

8

Segmentacja sekwencji obrazów metodą korelacyjną

Świta R., Suszyński Z.

Pomiary Automatyka Kontrola

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2013

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R. 59, nr 7

680--683

PL

Artykuł przedstawia nową metodę segmentacji sekwencji obrazów termicznych wyodrębniającą obszary o różnych właściwościach cieplnych. Metoda oparta jest na korelacji położenia i kształtu segmentów w poszczególnych kadrach sekwencji. Segmentacja pozwala zmniejszyć liczbę analizowanych obszarów do kilku tysięcy razy, co stwarza realne możliwości praktycznego wykorzystania tomografii termicznej. Opisana metoda jest porównana z algorytmami klasteryzacji K-Means i FCM. Zaletą algorytmu korelacyjnego jest automatyczne wyznaczanie liczby segmentów wyjściowych.

EN

This paper presents a new method for segmentation of thermal image sequences. Its aim is to divide the sequence into segments with different thermal properties. The described algorithm is based on measurements of the position and shape correlation of the segments in successive frames of the sequence. It is composed of several stages. The first stage consists of segmenting consecutive frames of the sequence (Fig. 2). The second step is analysis of the similarity of each segment in each frame with respect to all other segments of all frames and synthesis of the intermediate segments (Fig. 4). The intermediate segments form the segmented output image using the depth buffer technique to resolve multiple pixel-to-segment assignments (Fig. 6). This method is a basis for the thermal analysis of solids, which results in discovering depth profiles of thermal properties for each area. The segmentation reduces the number of the analyzed areas down to a few thousand times, which creates real opportunities for practical application of thermal tomography. The new algorithm has been compared with the K means algorithm [2], and FCM [6], which minimizes the sum of pixel value deviations from the centers of the segments they are assigned to, for all frames of the sequence (Tab. 1). The advantage of the correlation method is automatic determination of the number of output segments in the image and maintaining the constant segmentation error when increasing the number of the processed frames.

9

Fast FCM with spatial neighborhood information for brain MR image segmentation

Biniaz A., Abbasi A.

Journal of Artificial Intelligence and Soft Computing Research

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2013

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Vol. 3, No. 1

15--25

EN

Among different segmentation approaches Fuzzy c-Means clustering (FCM) is a welldeveloped algorithm for medical image segmentation. In emergency medical applications quick convergence of FCM is necessary. On the other hand spatial information is seldom exploited in standard FCM; therefore nuisance factors can simply affect it and cause misclassification. This paper aims to introduce a Fast FCM (FFCM) technique by incorporation of spatial neighborhood information which is exploited by a linear function on fuzzy membership. Applying proposed spatial Fast FCM (sFFCM), elapsed time is decreased and neighborhood spatial information is exploited in FFCM. Moreover, iteration numbers by proposed FFCM/sFFCM techniques are decreased efficiently. The FCM/FFCM techniques are examined on both simulated and real MR images. Furthermore, to considerably decrease of convergence time and iterations number, cluster centroids are initialized by an algorithm. Accuracy of the new approach is same as standard FCM. The quantitative assessments of presented FCM/FFCM techniques are evaluated by conventional validity functions. Experimental results demonstrate that sFFCM techniques efficiently handle noise interference and significantly decrease elapsed time.

10

Cuda Based Fuzzy C-Means Acceleration for the Segmentation of Images with Fungus Grown in Foam Matrices

Rowińska Z., Gocławski J

Image Processing & Communications

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2012

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Vol. 17, no. 4

191--200

EN

In the paper authors verify the advantages of GPU computing applied to fuzzy c-means segmentation. Three different algorithms implementing FCM method have been compared by their execution times. All tests refer to the images of polyurethane foam matrices filled with fungus (mould). They are aimed at separating mould regions from the matrix base. The authors proposed a method using CUDA programming tools, which significantly speedsup FCM computations with multiple cores built in a graphic card.

11

Crisp and Fuzzy Classifiers in the Two-Phase Gas-Liquid Flow Diagnostics

Fiderek P., Jaworski T., Banasiak R., Kucharski J.

Image Processing & Communications

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2012

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Vol. 17, no. 4

385--394

EN

The following paper presents results of common clustering algorithms use, both crisp and fuzzy, for flow pattern recognition of two-phase gas-liquid flows observed in horizontal pipeline. Obtained results of HCM, FCM, and kNN clustering algorithms were presented in a form of confusion matrix and compared via its prediction performance.

12

Learning style recognition based on an adjustable three-layer fuzzy cognitive map

Georgiou D. A., Botsios S., Mitropoulou V., Papaioannou M., Schizas C., Tsoulouhas G.

Journal of Artificial Intelligence and Soft Computing Research

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2011

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Vol. 1, No. 4

333--347

EN

Identification of learning styles supports Adaptive Educational Hypermedia Systems compiling and presenting tutorials custom in cognitive characteristics of each individual learner. This work addresses the issue: identifying the learning style of students, following the Kolb’s learning cycle. To this purpose, we propose a three-layers Fuzzy Cognitive Map (FCM) in conjunction with a dynamic Hebbian rule for learning styles recognition. The form of FCMs is designed by humans who determine its weighted interconnections among concepts. But the human factor may not be as reliable as it should be. Thus, a FCM model of the system allowing the adjustment of its weights using additional learners’ characteristics such as the Learning Ability Factors. In this article, two consecutively interconnected FCM (in the form of a three layer FCM) are presented. The schema’s efficiency has been tested and compared to known results after a fine-tuning of the weights of the causal interconnections among concepts. The simulations results of training the process system verify the effectiveness, validity and advantageous characteristics of those learning techniques for FCMs. The online recognition of learning styles by using threelayer Fuzzy Cognitive Map improves the accuracy of recognition obtained using Bayesian Networks that uses quantitative measurements of learning style taken from statistical samples. This improvement is due to the fuzzy nature of qualitative characterizations (such as learning styles), and the presence of intermediate level nodes representing Learning Ability Factors. Such factors are easily recognizable characteristics of a learner to improve adjustment of weights in edges with one end in the middle-level nodes. This leads to the establishment of a more reliable model, as shown by the results given by the application to a test group of students.

13

Assessment of the didactic measurement results using FCM type networks

Gumińska M., Madejski J.

Archives of Materials Science and Engineering

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2009

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Vol. 39, nr 1

45-52

EN

Purpose: The paper presents students egzamination system developer for the scaleable e-learning system. Organisation of the teaching and examination processes, as well as the implementation details are described. An intelligent system based on one of the Artificial Intelligence methods - FCM (Fuzzy Cognitive Maps) type network is being developed within the framework of current work on the e-learning process topic, to model the behaviour and functioning the system as a whole. Design/methodology/approach: The intelligent examination system for students was developed based on mechanism derived from HotPotatoes system. Programming languages like PHP and JavaScript were also used. Fuzzy Cognitive Maps were used to model the e-learning process and an example of the system use is presented. Findings: The project effect is the intelligent examination system supporting the statistical analysis of the difficulty level of test problems, generating comments and materials individually for every user. The didactic process was modelled using FCM method. Practical implications: Reduction of test checking time consumption, individual attitude to every student, score advised to the students along with the comments pertaining to the wrong answers and recommended study topics - all immediately after the test, sent to the student's mailbox. Originality/value: Employment of FCM AI tool for evaluation of the teaching process effectiveness.

14

Relations of granular worlds

Pedrycz W., Vukovich G.

International Journal of Applied Mathematics and Computer Science

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2002

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Vol. 12, no 3

347-357

EN

In this study, we are concerned with a two-objective development of information granules completed on a basis of numeric data. The first goal of this design concerns revealing and representing a structure in a data set. As such it is very much oriented towards coping with the underlying relational aspects of the experimental data. The second goal deals with a formation of a mapping between information granules constructed in two spaces (thus it concentrates on the directional aspect of information granulation). The quality of the mapping is directly affected by the information granules over which it operates, so in essence we are interested in the granules that not only reflect the data but also contribute to the performance of such a mapping. The optimization of information granules is realized through a collaboration occurring at the level of the data and the mapping between the data sets. The operational facet of the problem is cast in the realm of fuzzy clustering. As the standard techniques of fuzzy clustering (including a well-known approach of FCM) are aimed exclusively at the first objective identified above, we augment them in order to accomplish sound mapping properties between the granules. This leads to a generalized version of the FCM (and any other clustering technique for this matter). We propose a generalized version of the objective function that includes an additional collaboration component to make the formed information granules in rapport with the mapping requirements (that comes with a directional component captured by the information granules). The additive form of the objective function with a modifiable component of collaborative activities makes it possible to express a suitable level of collaboration and to avoid a phenomenon of potential competition in the case of incompatible structures and the associated mapping. The logic-based type of the mapping (that invokes the use of fuzzy relational equations) comes ...