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1

Fuzzy failure mode and effect analysis model for operational supply chain risks assessment: an application in canned tuna manufacturer in Thailand

Sumrit Detcharat, Srisawad Sirima

LogForum

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2022

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Vol. 18, no. 1

77--96

EN

Background: This study proposes a multi-criterion decision-making (MCDM) framework for operational supply chain risks assessment based on fuzzy failure mode effect analysis model. The proposed framework attempts to overcome some weaknesses and disadvantages of the traditional FMEA in many aspects such as (i) considering “degree of difficulty to eliminate risks” in the assessment process, (ii) using MCDM ranking methodology instead of a risk priority number, (iii) taking both subjective and objective weights of risk criteria into account. Application of the proposed framework used canned tuna production in Thailand as a case study. Methods: In this study, the operational supply chain risks assessment is treated as fuzzy MCDM problem. Subjective weights of risk criteria are determined by experts’ judgements. Objective weights are derived by Shannon entropy method. VIKOR approach is employed to prioritize the failure modes. A sensitivity analysis is performed to examine the robustness of the proposed framework. Results and conclusions: The findings from this study indicates that the most three critical FMs are “risk of product deterioration” followed by “risk of volatility raw materials supplied” and “risk of variabilities in production processes”, respectively. It recommends that the practitioners in canned tuna industry should give the priority to mitigate these risks. Although the present study focuses on canned tuna industry, the other similar industries can apply this proposed framework to assess their operational supply chain risks in the same way.

2

Automatic identification of respiratory diseases from stethoscopic lung sound signals using ensemble classifiers

Fraiwan Luay, Hassanin Omnia, Fraiwan Mohammad, Khassawneh Basheer, Ibnian Ali M., Alkhodari Mohanad

Biocybernetics and Biomedical Engineering

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2021

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Vol. 41, no. 1

1--14

EN

This paper investigates the application of different homogeneous ensemble learning methods to perform multi-class classification of respiratory diseases. The case sample involved a total of 215 subjects and consisted of 308 clinically acquired lung sound recordings and 1176 recordings obtained from the ICBHI Challenge database. These recordings corresponded to a wide range of conditions including healthy, asthma, pneumonia, heart failure, bronchiectasis or bronchitis, and chronic obstructive pulmonary disease. Feature representation of the lung sound signals was based on Shannon entropy, logarithmic energy entropy, and spectrogram-based spectral entropy. Decision trees and discriminant classifiers were employed as base learners to build bootstrap aggregation and adaptive boosting ensembles. The optimal structure of the investigated ensemble models was identified through Bayesian hyperparameter optimization and was then compared to typical classifiers in literature. Experimental results showed that boosted decision trees provided the best overall accuracy, sensitivity, specificity, F1-score, and Cohen's kappa coefficient of 98.27%, 95.28%, 98.9%, 93.61%, and 92.28%, respectively. Among the baseline methods, SVM provided the best yet a slightly poorer performance, as demonstrated by its average accuracy (98.20%), sensitivity (91.5%), and specificity (98.55%). Despite their simplicity, the investigated ensemble classification methods exhibited a promising performance for detecting a wide range of respiratory disease conditions. The data fusion approach provides a promising insight into an alternative and more suitable solution to reduce the effect of imbalanced data for clinical applications in general and respiratory sound analysis studies in specific.

3

Fundamental heart sounds analysis using improved complete ensemble EMD with adaptive noise

Altuve Miguel, Suárez Luis, Ardila Jeyson

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 1

426--439

EN

Phonocardiogram (PCG) recordings contain valuable information about the functioning and state of the heart that is useful in the diagnosis of cardiovascular diseases. The first heart sound (S1) and the second heart sound (S2), produced by the closing of the atrioventricular valves and the closing of the semilunar valves, respectively, are the fundamental sounds of the heart. The similarity in morphology and duration of these heart sounds and their superposition in the frequency domain makes it difficult to use them in computer systems to provide an automatic diagnosis. Therefore, in this paper, we analyzed these heart sounds in the intrinsic mode functions (IMF) domain, which were issued from two time-frequency decomposition techniques, the empirical mode decomposition (EMD) and the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), with the aim of retrieving useful information on an expanded basis. The decomposition of PCG recordings into IMF allows representing the fundamental cardiac sounds in many oscillating components, increasing thus the observability of the system. Moreover, the time-frequency representation of PCG recordings could provide valuable information to automatically detect heart sounds and diagnose pathologies from characteristic patterns of these heart sounds in the IMF. The analysis was made through the variance and Shannon's entropy of the heart sounds, observed in time windows located among different IMF. In addition, we determined the frequencies ranges of the IMF from the decomposition of the PCG recordings using both techniques. Given that the frequency content of S1 and S2 is different but overlap each other, and the duration of these sounds are also different, these heart sounds were represented in different IMF with different variances and entropies, in both techniques, but the ICEEMDAN offers a more consistent decomposition of S1 and S2 (they were concentrated in IMF 4-6). The decomposition of PCG signals into IMF has allowed us to identify the frequency components of the IMF in which these sounds are found.

4

Social-Group-Optimization based tumor evaluation tool for clinical brain MRI of Flair/diffusion-weighted modality

Dey Nilanjan, Rajinikanth V., Shi Fuqian, Tavares João Manuel R.S., Moraru Luminita, Arvind Karthik K., Lin Hong, Kamalanand K., Emmanuel C.

Biocybernetics and Biomedical Engineering

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2019

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Vol. 39, no. 3

843--856

EN

Brain tumor is one of the harsh diseases among human community and is usually diagnosed with medical imaging procedures. Computed-Tomography (CT) and Magnetic-Resonance- Image (MRI) are the regularly used non-invasive methods to acquire brain abnormalities for medical study. Due to its importance, a significant quantity of image assessment and decision-making procedures exist in literature. This article proposes a two-stage image assessment tool to examine brain MR images acquired using the Flair and DW modalities. The combination of the Social-Group-Optimization (SGO) and Shannon's-Entropy (SE) supported multi-thresholding is implemented to pre-processing the input images. The image post-processing includes several procedures, such as Active Contour (AC), Watershed and region-growing segmentation, to extract the tumor section. Finally, a classifier system is implemented using ANFIS to categorize the tumor under analysis into benign and malignant. Experimental investigation was executed using benchmark datasets, like ISLES and BRATS, and also clinical MR images obtained with Flair/DW modality. The outcome of this study confirms that AC offers enhanced results compared with other segmentation.

5

New bounds for Shannon, Relative and Mandelbrot entropies via Hermite interpolating polynomial

Mehmood N., Butt S. I., Pečarić D., Pečarić J.

Demonstratio Mathematica

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2018

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Vol. 51, nr 1

112--130

EN

To procure inequalities for divergences between probability distributions, Jensen’s inequality is the key to success. Shannon, Relative and Zipf-Mandelbrot entropies have many applications in many applied sciences, such as, in information theory, biology and economics, etc. We consider discrete and continuous cyclic refinements of Jensen’s inequality and extend them from convex function to higher order convex function by means of different new Green functions by employing Hermite interpolating polynomial whose error term is approximated by Peano’s kernal. As an application of our obtained results, we give new bounds for Shannon, Relative and Zipf-Mandelbrot entropies.

6

Fault diagnosis for electromagnetic relay using discrete wavelet transform and wavelet packet entropy

Havryliuk V.

Zeszyty Naukowe Wyższej Szkoły Technicznej w Katowicach

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2017

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nr 9

31--40

EN

In order to fault features extraction for neutral electromagnetic relays of railway automatics, the time dependences of the relays transient currents during relays switching have been measured. The results of measurements, performed for the relay in operable condition and for relays with artificially created defects, were analyzed in the time and frequency domains. The discrete wavelet transform (DWT), discrete wavelet packet transform (DWPT) and wavelet packet energy Shannon entropy (WPESE) were used for relay fault feature extraction. Increased values of the WPESE of the transient current for electromagnetic relay with armature defects as compared with the value for the relay in operable condition, provides an integrated assessment of the relay fault existence. Analysis of relay transient currents by using DWT and WPT allows to identify the defects of the relay contacts and armature. Defects of the relay electromagnetic system can be revealed by measuring the time constants of the transient current when the relay is energized but the anchor does not move yet, because it is in one of the two end positions.

PL

Aby wykryć oznaki wad neutralnych przekaźników elektromagnetycznych automatyki kolejowej, zmierzono zależności prądów przejściowych, przekaźników w czasie ich przełączania. Wyniki pomiarów, wykonanych w stanie roboczym przekaźnika i dla przekaźników ze sztucznie stworzonymi wadami, przeanalizowano w zależności od czasu i częstotliwości. Do wykrycia wady przekaźnika użyto dyskretnej transformaty fali elementarnej (DWT), dyskretnej transformaty paczki fal elementarnych (DWPT) oraz entropii Shannona energii paczki fal elementarnych (WPESE). Zwiększona WPESE prądu przejściowego dla przekaźnika elektromagnetycznego w porównaniu do wartości w stanie roboczym zapewnia kompleksową ocenę występowania wady przekaźnika. Analiza prądu przejściowego przy użyciu DWT i DWPT pozwala na identyfikację i lokalizację w czasie wad kontaktów i zwory przekaźnika. Wady układu przekaźnika można ujawnić mierząc stałe czasowe prądu przejściowego, kiedy przekaźnik jest włączony, ale zwora się nie porusza, ponieważ znajduje się w jednym z dwóch położeń końcowych.

7

Estimation of information entropy based on its visualization

Cholewa M., Palys M.

Journal of Medical Informatics & Technologies

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2017

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Vol. 26

18--25

EN

This paper describes the method which allows an estimation of information entropy in the meaning of Shannon. The method is suitable to an estimation which sample has a higher value of information entropy. Several algorithms have been used to estimate entropy, assuming that they do it faster. Each algorithm has calculated this value for several text samples. Then analysis has verified which comparisons of the two samples were correct. It has been found that the probabilistic algorithm is the fastest and most effective in returning the estimated value of entropy.

8

Discriminating Between Different Streamflow Regimes by Using the Fisher-Shannon Method : An Application to the Colombia Rivers

Pierini J. O., Restrepo J. C., Lovallo M., Telesca L.

Acta Geophysica

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2015

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Vol. 63, no. 2

533--546

EN

The Fisher-Shannon (FS) information plane, defined by the Fisher information measure (FIM) and the Shannon entropy power (NX), was robustly used to investigate the complex dynamics of eight monthly streamflow time series in Colombia. In the FS plane the streamflow series seem to aggregate into two different clusters corresponding to two different climatological regimes in Colombia. Our findings suggest the use of the statistical quantity defined by the FS information plane as a tool to discriminate among different hydrological regimes.

9

Miary entropijne w kontroli ruchu internetowego

Pawelec J., Bereziński P., Piotrowski R., Chamela W.

TTS Technika Transportu Szynowego

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2013

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R. 20, nr 10

2309--2318, CD

PL

Trzy miary entropijne - Shannona, Tsallisa i tzw. T-entropia - są przedmiotem analizy pod kątem wykrywania anomalii w ruchu internetowym. Szczególną uwagę zwrócono na entropię Tsallisa, którą wykorzystano w detektorze demonstratora Traffic Entropy Spectrum - pruned (widmo entropijne ruchu internetowego - znormalizowane). Wyniki eksploatacji są zachęcające.

EN

Three entropy measures - Shannon, Tsallis and T-entropy - are studied in viewpoint of internet traffic anomaly detection. The main attention is placed on the Tsallis entropy and its application in the test-bed called Traffic Entropy Spectrum - pruned. Obtained results are encouraging.

10

Złożoność danych pomiarowych i metody jej określania

Czajka A., Polak A.

Przegląd Elektrotechniczny

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2010

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R. 86, nr 9

9-12

PL

W referacie przedstawiono problematykę określania złożoności danych pomiarowych oraz przegląd pewnej klasy algorytmów wyznaczających złożoność. Omówiono złożoność Kołmogorowa, entropię Shannona oraz entropię próbek. Celem przeprowadzonych prac była analiza wybranych algorytmów zastosowanych do określania złożoności sygnałów generowanych przez coraz bardziej złożony system. Badania miały charakter eksperymentów symulacyjnych. Ich wyniki pokazują, że miara złożoności danych generowanych przez badany system może być powiązana ze złożonością jego struktury i procesów zachodzących w samym systemie. Jest to krok wstępny do opracowania metody monitorowania zmian zachodzących w systemach złożonych poprzez oceny złożoności generowanych przez nie sygnałów. Do systemów takich należy m.in. układ oddechowy monitorowany podczas bezdechu sennego.

EN

In this paper the problem of assessment of measurement data complexity is presented together with a review of a certain class of algorithms for complexity calculation. The Kolmogorov complexity, Shannon entropy and sample entropy are discussed. The aim of this work was to analyse the chosen algorithms used in the assessment of complexity of signals generated by a more and more complex system. The investigations were performed as simulation experiments. Their results show that the measure of complexity of data generated by the system under investigation can be related to the complexity of both the system’s structure and internal processes. This is a preliminary step towards the elaboration of a method for monitoring changes in complex systems by assessment of the complexity of generated by them signals. Such systems include e.g. the respiratory system monitored during sleep apnoea.

11

On a sum form functional equation related to entropies and some moments of a discrete random variable

Nath P., Singh D.

Demonstratio Mathematica

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2009

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Vol. 42, nr 1

83-96

EN

The general solutions of a sum form functional equation have been obtained. The importance of its solutions in relation to the entropies and some moments of a discrete random variable has been discussed.

12

Entropy and Gibbs distribution in image processing : an historical perspective

Battiato S.

Image Processing & Communications

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2001

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Vol. 7, no 3-4

35-50

EN

This paper presents an historical overview about the entropy and its applications for the solution of inferential statistical problems in image processing. This survey covers some of the more important entropy-based research approaches. A brief introduction to the mathematical details and foundations about the basic concepts of Markov Random Fields (MRF} and related Gibbs sampling is also given. The information entropy is a mathematical measure of information or uncertainty derived from a probabilistic model. The paper starting from the seminal works of C. Shannon and of E.T. Javnes and of S. Geman and D. German discusses results obtained using different related techniques in image restoration, analysis and synthesis of textures and saliency maps construction. The paper moreover gives useful suggestions about the trend of development in future research