• Journal of the Korea Society of Computer and Information
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• v.4 no.4
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• pp.1-8
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• 1999

In the logic where we study the principle and method of human, the binary logic with the proposition which has one-valued property that it can be assigned the truth value 'truth'or 'false'. Although most of the traditional binary logic which was drawn by human includes fuzziness hard to deal with, the knowledge for expressing it is not precise and has less degree of credit. This study uses multi-valued logic in order to slove the problem above that .When compared with the data processing ability of the binary logic, Multi-valued logic has an at a high speed. Therefore the Inference can be possible by minimization multi-valued logic in stead of using the information stead of using the information system based on the symbolic binary logic.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1569-1574
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• 2005

In this paper, I propose an intelligent credit rating system using a bankruptcy prediction model based on support vector machines (SVMs). SVMs are promising methods because they use a risk function consisting of the empirical error and a regularized term which is derived from the structural risk minimization principle. This study examines the feasibility of applying SVM in Predicting corporate bankruptcies by comparing it with other data mining techniques. In addition. this study presents architecture and prototype of intelligeht credit rating systems based on SVM models.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.12
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• pp.391-398
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• 2015

This paper devises a performance improvement and evaluation process of circuit minimization algorithms for mentorship education of distinguished informatics gifted secondary students. In the process, students learn that there are several alternative equivalent circuits for a target function and recognize the necessity for formalized circuit minimization methods. Firstly, they come at the concept of circuit minimization principle from Karnaugh Map which is a manual methodology. Secondly, they explore Quine-McCluskey algorithm which is a computational methodology. Quine-McCluskey algorithm's time complexity is high because it uses set operations. To improve the performance of Quine-McCluskey algorithm, we encourage them to adopt a bit-wise data structure instead of integer array for sets. They will eventually see that the performance achievement is about 36%. The ultimate goal of the process is to enlarge gifted students' interest and integrated knowledge about computer science encompassing electronic switches, logic gates, logic circuits, programming languages, data structures and algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.4062-4080
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• 2022

COVID-19, a highly infectious disease, has affected the globe tremendously since its outbreak during late 2019 in Wuhan, China. In order to respond to the pandemic, governments around the world introduced a variety of public health measures including contact-tracing, a method to identify individuals who may have come into contact with a confirmed COVID-19 patient, which usually leads to quarantine of certain individuals. Like many other governments, the South Korean health authorities adopted public health measures using latest data technologies. Key data technology-based quarantine measures include:(1) Electronic Entry Log; (2) Self-check App; and (3) COVID-19 Wristband, and heavily relied on individual's personal information for contact-tracing and self-isolation. In fact, during the early stages of the pandemic, South Korea's strategy proved to be highly effective in containing the spread of coronavirus while other countries suffered significantly from the surge of COVID-19 patients. However, while the South Korean COVID-19 policy was hailed as a success, it must be noted that the government achieved this by collecting and processing a wide range of personal information. In collecting and processing personal information, the data minimum principle - one of the widely recognized common data principles between different data protection laws - should be applied. Public health measures have no exceptions, and it is even more crucial when government activities are involved. In this study, we provide an analysis of how the governments around the world reacted to the COVID-19 pandemic and evaluate whether the South Korean government's digital quarantine measures ensured the protection of its citizen's right to privacy.

• Steel and Composite Structures
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• v.42 no.3
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• pp.375-388
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• 2022

In this work, limit elastic speed analysis of functionally graded porous rotating disks has been reported. The work proposes an effective approach for modeling the mechanical properties of a porous functionally graded rotating disk. Four different types of porosity models namely: uniform, symmetric, inner maximum, and outer maximum distribution are considered. The approach used is the variational principle, and the solution has been achieved using Galerkin's error minimization theory. The study aims to investigate the effect of grading indices, aspect ratio, porosity volume fraction, and porosity types on limit angular speed for uniform and variable disk geometries of constant mass. To validate the current study, finite element analysis has been used, and there is good agreement between the two methods. The study yielded a decrease in limit speed as grading indices and aspect ratio increase. The porosity volume fraction is found to be more significant than the aspect ratio effect. The research demonstrates a range of operable speeds for porous and non-porous disk profiles that can be used in industries as design data. The results show a significant increase in limit speed for an exponential disk when compared to other disk profiles, and thus, the study demonstrates a range of FG-based structures for applications in industries that will not only save material (lightweight structures) but also improve overall performance.

• Structural Engineering and Mechanics
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• v.39 no.6
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• pp.751-765
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• 2011

The present paper deals with the identification of a concentrated damage in an elastic parabolic arch through the minimization of an objective function which measures the differences between numerical and experimental values of static displacements. The damage consists in a notch that reduces the height of the cross section at a given abscissa and therefore causes a variation in the flexural stiffness of the structure. The analytical values of static displacements due to applied loads are calculated by means of the principle of virtual work for both the undamaged and damaged arch. First, pseudo-experimental data are used to study the inverse problem and investigate whether a unique solution can occur or not. Various damage intensities are considered to assess the reliability of the identification procedure. Then, the identification procedure is applied to an experimental case, where displacements are measured on a prototype arch. The identified values of damage parameters, i.e., location and intensity, are compared to those obtained by means of a dynamic identification technique performed on the same structure.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2337-2341
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• 2005

This paper presents the target detection method using Support Vector Machines(SVMs) and the navigation system using behavior-based fuzzy controller. SVM is a machine-learning method based on the principle of structural risk minimization, which performs well when applied to data outside the training set. We formulate detection of target objects as a supervised-learning problem and apply SVM to detect at each location in the image whether a target object is present or not. The behavior-based fuzzy controller is implemented as an individual priority behavior: the highest level behavior is target-seeking, the middle level behavior is obstacle-avoidance, the lowest level is an emergency behavior. We have implemented and tested the proposed method in our mobile robot "Pioneer2-AT". Comparing with a neural-network based detection method, a SVM illustrate the excellence of the proposed method.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.217-223
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• 2024

The current study aimed to evaluate the effectiveness of using Support Vector Machine (SVM) for political affiliation classification. The system was designed to analyze the political tweets collected from Twitter and classify them as positive, negative, and neutral. The performance analysis of the SVM classifier was based on the calculation of metrics such as accuracy, precision, recall, and f1-score. The results showed that the classifier had high accuracy and f1-score, indicating its effectiveness in classifying the political tweets. The implementation of SVM in this study is based on the principle of Structural Risk Minimization (SRM), which endeavors to identify the maximum margin hyperplane between two classes of data. The results indicate that SVM can be a reliable classification approach for the analysis of political affiliations, possessing the capability to accurately categorize both linear and non-linear information using linear, polynomial or radial basis kernels. This paper provides a comprehensive overview of using SVM for political affiliation analysis and highlights the importance of using accurate classification methods in the field of political analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.700-705
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• 2012

This paper addresses an intelligent digital redesign (IDR) technique for observer-based output-feedback control systems, in order to efficiently convert a pre-designed Takagi-Sugeno fuzzy model-based analog controller into a sampled-data one in the sense of state matching. A delta operator is used to get an asymptotic relation between the analog and the sampled-data control systems. The IDR problem is viewed as a minimization problem of the norm distances between linear operator to be matched. The condition is represented as linear matrix inequalities, and the separation principle on the IDR is shown.

• Korean Journal of Community Nutrition
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• v.16 no.1
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• pp.98-112
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• 2011

This study aimed to suggest a 1300 scale of a middle school foodservice facility floor plan which was compliant to the principle of HACCP, as well as ensuring food and work safety, and the flow of personnel and food materials. which consisted of 46 nutrition teachers and 6 experts, responded with a questionnaire on the relationship of functional area and space. Using their opinions, key principles for the design of the facility were single direction movement of food materials, customers and workers; minimization of the cross-contamination through the separation of functional space; and securement of customer-focused efficiency; staff-centered convenience and efficiency; and work and food safety. After the completion of an adjacency diagram, bubble diagram and program statement, the functional areas of a 1300 scale middle school food-service facility were allocated as follows: $9.9\;m^2$ for the receiving area, $56.1\;m^2$ for the pre-preparation area, $10.5\;m^2$ for the food storage area, $6.0\;m^2$ for the supplies storage area, $97.8\;m^2$ for the cooking area, $33.6\;m^2$ for the service area, $52.5\;m^2$ for dish washing area, cafeteria $410.5\;m^2$, $4.5\;m^2$ for the front room, for a total of $725.8\;m^2$. Expert groups have pointed to limitations within this model as there are no windows in the office for the influx of fresh outside air and a need for the straight line installation of steam-jacket and frying kettles on the sides of windows. This study can be useful as the guidelines for estimating the investment cost of the facility and placing the placement of functional areas and equipment in the renovation of the facility. It can be also useful data for a methodology of foodservice facility design.