• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.559-560
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• 2013

• 한국CDE학회논문집
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• 제5권2호
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• pp.136-143
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• 2000

The appearance of new machine tools with higher flexibility is in need of a basic structure design system for establishing the systematic and rationalized design and manufacturing procedures. In this study. the basic structure design system for machine tools is realized based on the modular construction method. Machine tools are represented as a whole and modular complex with the directed graph, and all possible structural configurations and codes of machine tools for satisfying the machining requirement are derived from the DNA data and connecting patterns of basic structural elements. Especially the structural configurations of machine tools are visualized by the solid modeling techniques and 3-D graphics techniques.

• 한국정밀공학회지
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• 제16권9호
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• pp.75-81
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• 1999

In order to remain competitive, a manufacturing company needs to maintain the optimal condition of its manufacturing system. Machine tools as an important element of a manufacturing system consist of complex mechanical as well as electronic components. Therefore, diagnosing the troubles of machine tools is a tricky process which requires a lot of experience and knowledge. Since providing machine tool users with necessary services at the right time is very difficult and expensive, a remote diagnosis system is to be regarded as a good alternative, with which users can diagnose and fix the machine troubles. This paper presents a framework for a remote machine tools diagnosis system by combining the world wide web technology and backward reasoning expert system.

• 한국해양공학회지
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• 제36권3호
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• pp.194-210
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• 2022

Recently, an analysis method using machine learning for solving problems in coastal and ocean engineering has been highlighted. Machine learning models are effective modeling tools for predicting specific parameters by learning complex relationships based on a specified dataset. In coastal and ocean engineering, various studies have been conducted to predict dependent variables such as wave parameters, tides, storm surges, design parameters, and shoreline fluctuations. Herein, we introduce and describe the application trend of machine learning models in coastal and ocean engineering. Based on the results of various studies, machine learning models are an effective alternative to approaches involving data requirements, time-consuming fluid dynamics, and numerical models. In addition, machine learning can be successfully applied for solving various problems in coastal and ocean engineering. However, to achieve accurate predictions, model development should be conducted in addition to data preprocessing and cost calculation. Furthermore, applicability to various systems and quantifiable evaluations of uncertainty should be considered.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 봄 학술논문 발표대회
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• pp.151-152
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• 2021

The sale price of apartment buildings is a key factor in the success or failure of apartment projects, and the factors that affect the sale price of apartments vary widely, including location, environmental factors, and economic conditions. Existing methods of predicting the sale price do not reflect the nonlinear characteristics of apartment prices, which are determined by the complex impact factors of reality, because statistical analysis is conducted under the assumption of a linear model. To improve these problems, a new analysis technique is needed to predict apartment sales prices by complex nonlinear influencing factors. Using machine learning techniques that have recently attracted attention in the field of engineering, it is possible to predict the sale price reflecting the complexity of various factors. Therefore, this study aims to conduct a basic study for the development of a machine learning-based prediction model for apartment sale prices.

• International Journal of Computer Science & Network Security
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• 제23권5호
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• pp.21-32
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• 2023

The design of complex man-made systems mostly involves a conceptual modeling phase; therefore, it is important to ensure an appropriate analysis method for these models. A key concept for such analysis is the development of a diagramming technique (e.g., UML) because diagrams can describe entities and processes and emphasize important aspects of the systems being described. The analysis also includes an examination of ontological concepts such as states and events, which are used as a basis for the modeling process. Studying fundamental concepts allows us to understand more deeply the relationship between these concepts and modeling frameworks. In this paper, we critically analyze the classic definition of a state utilizing the Thinging machine (TM) model. States in state machine diagrams are considered the appropriate basis for modeling system behavioral aspects. Despite its wide application in hardware design, the integration of a state machine model into a software system's modeling requirements increased the difficulty of graphical representation (e.g., integration between structural and behavioral diagrams). To understand such a problem, in this paper, we project (create an equivalent representation of) states in TM machines. As a case study, we re-modeled a state machine of an assembly line system in a TM. Additionally, we added possible triggers (transitions) of the given states to the TM representation. The outcome is a complicated picture of assembly line behavior. Therefore, as an alternative solution, we re-modeled the assembly line based solely on the TM. This new model presents a clear contrast between state-based modeling of assembly line behavior and the TM approach. The TM modeling seems more systematic than its counterpart, the state machine, and its notions are well defined. In a TM, states are just compound events. A model of a more complex system than the one in the assembly line has strengthened such a conclusion.

• 한국균학회지
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• 제11권1호
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• pp.27-32
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• 1983

Five species of the genus Pythium were identified from 91 isolates which were collected from rice seedlings in machine transplanting nursery boxes and paddy fields in Korea. They included P. graminicola complex, P. monospermum complex, P. rostratum complex, and P. ultimum complex. The most frequently found species of the genus Pythium was P. graminicola complex followed by P. monospermum complex. Rice seed germinability was greatly decreased by being infested with P. graminicola complex at nursery box. P. graminicola complex was the most virulent in terms of prohibiting germinations and stunting plants in nursery boxes.

• Journal of international Conference on Electrical Machines and Systems
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• 제1권4호
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• pp.505-508
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• 2012

A permanent magnet flux switching (PMFS) machine has a simple rotor, whilst both magnets and coils are set in the stator, resulting in easy removal of heat due to both copper loss and eddy current loss in magnets. However, the volume of magnets used in PMFS machines is usually larger than in conventional PM machines, and leakage flux does exist at the non-airgap side. To make full use of the magnets and gain higher power density, a novel 3-dimensional (3D) field PMFS machine is developed. It combines merits of the tubular linear machine, external-rotor rotary machine and axial-flux rotary machine, hence, offers high power density and peak torque capability, as well as efficient utility of magnets owing to the unique configuration of triple airgap fields.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.32-36
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• 2002

This paper presents the structural characteristic analysis of a centerless grinding machine with concrete bed. The centerless grinding machine is composed of grinding wheel head, regulating wheel head, concrete bed, wheel dresser and so on. Especially, the concrete bed is introduced to improve the static, dynamic and thermal characteristics of the centerless grinding machine. The structural analysis model of centerless grinding machine is constructed by the finite element method, and the structural characteristics in the design stage are estimated based on the structural deformation and harmonic response under the various testing conditions related to gravity force and directional farces

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.868-871
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• 1995

In order to remain competitive, a manufacturing company needs to maintain the optimal condition of its manufacturing system. Machine tools as an important element of a manufacturing system comprises complex mechanical as well as electronic components. Therefore, diagnosing the troubles of machine tools is a tricky process which requires a lot of experience and knowledge. Since providing machine tool users with necessary services at the right time is very difficult and expensive, a remote diagnosis system is to be regarded as a good alternative,with which users can diagnose and fix the machine troubles. This paper presents a framework for a remote machine tool diagnosis system using the world wide web technology and backward reasoning expert system.