• Korean Journal of Logic
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• v.16 no.3
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• pp.437-452
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• 2013

This paper verifies the following two: First, I verify the standard completeness proof for the system $ULw_t$ is not correct in the sense that t-weakening uninorms are t-norms, but not weakening-free uninorms. Second, I verify that the proof for $ULw_t$ can be used for the system MTL. That is, I provide a new standard completeness proof for it.

• Journal of applied mathematics & informatics
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• v.39 no.5_6
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• pp.769-783
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• 2021

Demirci ((1999) Vague groups. J. Math. Anal. Appl. 230, 142-156) introduced the concept of vague groups as one of uncertain reasoning structures where indistinguishable operators separate points. In this paper, we consider vague groups in which an indistinguishable operator does not need to separate points because it seems more appropriate to handle ambiguous situations. For our purposes we generalize or redefine some notions such as: vague closed subset, vague subgroup, vague kernel and vague injectiveness. Consequently we generalize most of the known results and obtain some new additional fundamental properties of vague groups, some of which are similar to ones of ordinary groups.

• Korean Journal of Logic
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• v.17 no.2
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• pp.323-349
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• 2014

In this paper, we show that the standard completeness for the extension of UL with compensation-free reinforcement (cfr) $(({\phi}&{\psi}){\rightarrow}({\phi}{\wedge}{\psi})){\vee}(({\phi}{\vee}{\psi}){\rightarrow}({\phi}&{\psi}))$ can be established. More exactly, first, the compensation-freely reinforced uninorm logic $UL_{cfr}$ (the UL with (cfr)) is introduced. The algebraic structures of $UL_{cfr}$ are then defined, and its algebraic completeness is established. Next, standard completeness (i.e. completeness on [0, 1]) is established for $UL_{cfr}$ by using the method introduced in Yang (2009).

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.60-65
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• 2008

In this paper, we concern the stability of smart space by using the robust digital controller. The proposed methodologies are based on the intelligent digital redesign (IDR). More precisely, we represent the nonlinear and uncertain analog system as the Takaki-Sugeno (T-S) fuzzy model. Then the IDR problem can be reduced to find the digital gains minimizing the norm distance between the closed-loop states of the analog and digital control. Its constructive conditions are expressed as the linear matrix inequalities (LMIs). At last, a numerical example, HVAC system, is demonstrated to visualize the feasibility of the proposed methodology.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.7
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• pp.1015-1026
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• 2019

Objective: The objective of this study was to evaluate three different degrees of white striping (WS) addressing their automatic assessment and customer acceptance. The WS classification was performed based on a computer vision system (CVS), exploring different machine learning (ML) algorithms and the most important image features. Moreover, it was verified by consumer acceptance and purchase intent. Methods: The samples for image analysis were classified by trained specialists, according to severity degrees regarding visual and firmness aspects. Samples were obtained with a digital camera, and 25 features were extracted from these images. ML algorithms were applied aiming to induce a model capable of classifying the samples into three severity degrees. In addition, two sensory analyses were performed: 75 samples properly grilled were used for the first sensory test, and 9 photos for the second. All tests were performed using a 10-cm hybrid hedonic scale (acceptance test) and a 5-point scale (purchase intention). Results: The information gain metric ranked 13 attributes. However, just one type of image feature was not enough to describe the phenomenon. The classification models support vector machine, fuzzy-W, and random forest showed the best results with similar general accuracy (86.4%). The worst performance was obtained by multilayer perceptron (70.9%) with the high error rate in normal (NORM) sample predictions. The sensory analysis of acceptance verified that WS myopathy negatively affects the texture of the broiler breast fillets when grilled and the appearance attribute of the raw samples, which influenced the purchase intention scores of raw samples. Conclusion: The proposed system has proved to be adequate (fast and accurate) for the classification of WS samples. The sensory analysis of acceptance showed that WS myopathy negatively affects the tenderness of the broiler breast fillets when grilled, while the appearance attribute of the raw samples eventually influenced purchase intentions.