• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.15 no.4
• /
• pp.217-231
• /
• 2015

A novel fuzzy learning framework that employs fuzzy inference to solve the problem of Multiple Instance Learning (MIL) is presented. The framework introduces a new class of fuzzy inference systems called Multiple Instance Mamdani Fuzzy Inference Systems (MI-Mamdani). In multiple instance problems, the training data is ambiguously labeled. Instances are grouped into bags, labels of bags are known but not those of individual instances. MIL deals with learning a classifier at the bag level. Over the years, many solutions to this problem have been proposed. However, no MIL formulation employing fuzzy inference exists in the literature. Fuzzy logic is powerful at modeling knowledge uncertainty and measurements imprecision. It is one of the best frameworks to model vagueness. However, in addition to uncertainty and imprecision, there is a third vagueness concept that fuzzy logic does not address quiet well, yet. This vagueness concept is due to the ambiguity that arises when the data have multiple forms of expression, this is the case for multiple instance problems. In this paper, we introduce multiple instance fuzzy logic that enables fuzzy reasoning with bags of instances. Accordingly, a MI-Mamdani that extends the standard Mamdani inference system to compute with multiple instances is introduced. The proposed framework is tested and validated using a synthetic dataset suitable for MIL problems. Additionally, we apply the proposed multiple instance inference to fuse the output of multiple discrimination algorithms for the purpose of landmine detection using Ground Penetrating Radar.

• Journal for History of Mathematics
• /
• v.14 no.2
• /
• pp.93-100
• /
• 2001

The problem of vagueness has been investigated for a long time by philosophers and mathematicians. There are there approaches in mathematics to the problem, which are probability theory, fuzzy logic, and rough set theory. In this paper I introduce these theories and their meanings.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2013.05a
• /
• pp.457-458
• /
• 2013

• Journal of the Korea Safety Management & Science
• /
• v.13 no.4
• /
• pp.117-124
• /
• 2011

Supplier selection is one of the most important activities of a company. This importance is increased even more by new strategies in a supply chain, because of the key role suppliers perform in terms of quality, costs and services which affect the outcome in the buyer's company. In addition, green production has become an important issue for almost every manufacturer and will determine the sustainability of a manufacturer. Therefore a performance evaluation system for supplier and green suppliers is necessary to determine the suitability of suppliers to cooperate with the company. Supplier and green supplier selection is a multiple criteria decision making problem in which the objectives are not equally important. In practice, vagueness and imprecision of the goals, constraints and parameters in these problems make the decision making complicated. The objective of this study is to construct a decision-making process using fuzzy analytic hierarchy process (FAHP) and balanced scorecard (BSC) for evaluating supplier and green suppliers in the manufacturing industry. The BSC concept is applied to define the hierarchy with four major perspectives and performance indicators are selected for each perspective. FAHP is then proposed in order to tolerate vagueness and ambiguity of information. Finally, FAHP is applied to facilitate the solving process. With the proposed approach, manufacturers can have a better understanding of the capabilities that supplier and green supplier must possess and can evaluate and select the most suitable supplier for cooperation.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.43 no.2
• /
• pp.87-104
• /
• 2015

As the influence of Landscape Urbanism has grown, various criticisms on the discourse also have increased. A study on critical opinions of Landscape Urbanism is necessary to fully comprehend the theoretical structure of the discourse and its limitations. This study introduced the concept of Intension and Extension, which is used in the field of Logics and Semiotic, as an analytical tool to interpret various criticisms based on different views in a more objective and synthetic way. After examining the development of criticisms of Landscape Urbanism, 30 texts with important critiques on the theory were selected and analyzed. Criticisms can be classified as internal criticism and external criticism according to specific topics they are engaged with. The study only covers internal criticism as a research scope. The internal criticisms on Landscape Urbanism are re-categorized into topics of theory, practice and the relation between theory and practice. Vagueness of concepts and error in concepts are two types criticism related to the issue of theory. Lexical Ambiguity and Intensional Vagueness are the main causes of conceptual vagueness in Landscape Urbanism. Conceptual vagueness related with the problem of redefining an existing concept through expanding its meaning reveals a structural dilemma. There are three types of criticism included in the topic of practice: absence of practical results, form-oriented practice, and ambiguous identity in practical results. Ambiguous identity is caused by Extensional Vagueness allowing borderline cases. Because these borderline cases overlap with extensions of landscape architecture, it is hard to differentiate projects of Landscape Urbanism and those of conventional landscape architecture. Most criticisms on the relation between theory and practice raise the question on the practical method. Two types of criticism are engaged with the topic of the practical method: errors in practical methods and absence of practical methods. The absence of practical methods is a fundamental problem of Landscape Urbanism which is hard to solve by the proposed solutions. However, these structural problems are not only the weak point but also the factor that is able to prove the potentials expand the scope of Landscape Urbanism. In addition to the results of the study, internal criticisms on Landscape Urbanism should be examined in the following studies in order to predict the next direction of Landscape Urbanism.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.12a
• /
• pp.279-282
• /
• 2001

This paper presents an image contrast enhancement technique for improving the low contrast images using the improved IAFC(Integrated Adaptive Fuzzy Clustering) Model. The low pictorial information of a low contrast image is due to the vagueness or fuzziness of the multivalued levels of brightness rather than randomness. Fuzzy image processing has three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. Using a new model of automatic crossover point selection, optimal crossover point is selected automatically. The problem of crossover point selection can be considered as the two-category classification problem. The improved MEC can classify the image into two classes with unsupervised teaming rule. The proposed method is applied to some experimental images with 256 gray levels and the results are compared with those of the histogram equalization technique. We utilized the index of fuzziness as a measure of image quality. The results show that the proposed method is better than the histogram equalization technique.

• Journal of the Korea Institute of Building Construction
• /
• v.4 no.2
• /
• pp.119-128
• /
• 2004

Lately construction industry tends to prefer remodeling of existing buildings rather than new construction or reconstruction of buildings due to strengthening of several restriction related to real estates along with prolonged depression. And also, remodeling of building costs less and creates less wastes compared to reconstruction and so it is more profitable in financial and environmental view. However remodeling is process of creating new environment with existing building. Therefor remodeling must follow the procedure realizing problem and fix the problem based on through investigation on existing building and users requirement must be faithfully reflected. Specially in case of apartment houses, since vagueness on ownership and management authority on common parts exists. Hereupon, in this study we are to present the procedure of analyzing apartment house remodeling method through user requirement by approaching to several considerable factors in user request side.

• Architectural research
• /
• v.12 no.2
• /
• pp.85-92
• /
• 2010

In recent years, construction projects have been forced to cope with lack of skilled labor and increasing hazard circumstance of human operations. A construction robotic system has been frequently accomplished as one alterative for overcoming these difficulties in increasing construction quality, enhancing productivity, and improving safety. However, while the complexity of such a system increases, there are few ways to carry out an assessment of the system. This paper introduces a knowledge-based multi-criteria decision-making process to assist decision makers in systematically evaluating an automated system for a given project and quantifying its system performance index. The model employs linguistic terms and fuzzy numbers in attempts to deal with the vagueness inherent in experts' or decision makers' subjective opinions, considering the contribution resulted from their knowledge on a decision problem. As an illustrative case, the system, called Robotic-based Construction Automation, for constructing steel erection of high-rise buildings was applied into this model. The results show the model's capacities and imply the application to other extended types of construction robotic systems.

• Journal of the Korea Society of Computer and Information
• /
• v.23 no.8
• /
• pp.45-50
• /
• 2018

Many of the current successful commercial recommender systems utilize collaborative filtering techniques. This technique recommends products to the active user based on product preference history of the neighbor users. Those users with similar preferences to the active user are typically named his/her neighbors. Hence, finding neighbors is critical to performance of the system. Although much effort for developing similarity measures has been devoted in the literature, there leaves a lot to be improved, especially in the aspect of handling subjectivity or vagueness in user preference ratings. This paper addresses this problem and presents a novel similarity measure using fuzzy logic for selecting neighbors. Experimental studies are conducted to reveal that the proposed measure achieved significant performance improvement.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.05a
• /
• pp.119-122
• /
• 2002

The research Interest of this paper is focused on the efficient clustering task for an arbitrary color data. In order to tackle this problem, we have tiled to model the inherent uncertainty and vagueness of color data using fuzzy color model. By laking a fuzzy approach to color modeling, we could make a soft decision for the vague regions between neighboring colors. The proposed fuzzy color model defined a three dimensional fuzzy color ball and color membership computation method with the two inter-color distance measures. With the fuzzy color model, we developed a new fuzzy clustering algorithm for an efficient partition of color data. Each fuzzy cluster set has a cluster prototype which is represented by fuzzy color centroid.