• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.2
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• pp.129-151
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• 1994

Recently, Decision Support Systems (DSS) research has seen a more to combine Artificial Intelligence (AI) including neural network techniques with traditional DSS concepts and technologies to build an intelligent DSS or a knowledge-based DSS. This article proposes a Management Evaluation and its Support System (MESS) as a knowledge-based DSS. The management evaluation of a firm means the performance of all managerial operations is appraised by considering the situations of the firm. A neural network is used to represent the management evaluation structure as a suitable means of management knowledge representation. Finally a case study in a telecommunication corporation is presented.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.12
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• pp.3236-3245
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• 1994

The nesting of two-dimensional patterns onto a given raw sheet has applications in a number industries. It is a common problem often faced by designers in the shipbuilding, garment making, blanking die design, glass and wood industries. This paper presents a multi-stage layout approach for nesting two-dimensional patterns by using artificial intelligence techniques with a relatively short computation time. The raw material with irregular boundaries and internal defects which must be considered in various cases of nesting was also investigated in this study. The proposed nesting approach consists of two stages : initial layout stage and layout improvement stage. The initial layout configuration is achieved by the self-organizing assisted layout(SOAL) algorithm while in the layout improvement stage, the simulated annealing(SA) is adopted for a finer optimization.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.183-186
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• 1996

The relational database management systems sometimes require extremely long and complicated queries for a certain retreval. In this case, recursive retirevals are more efficient approach than the usual queries. Many researchers have tried to incorporate semantics in the traditional relational models using artificial intelligence techniques. This new concept becomes a deductive database and sometimes it is also called as a logic programming. However, the designer of a deductive database did not overcome the short of relational database. In this paper, we propose a new way of designing queries for the deductive database. We also provide relations for recursive retrieval in the deductive database. These approaches are applied for the material requirement planning.

• Computers and Concrete
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• v.9 no.5
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• pp.375-387
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• 2012

The objective of this investigation was to develop rules for automatic categorization of concrete quality using selected artificial intelligence methods based on machine learning. The range of tested materials included concrete containing a new waste material - solid residue from coal combustion in fluidized bed boilers (CFBC fly ash) used as additive. The rapid chloride permeability test - Nordtest Method BUILD 492 method was used for determining chloride ions penetration in concrete. Performed experimental tests on obtained chloride migration provided data for learning and testing of rules discovered by machine learning techniques. It has been found that machine learning is a tool which can be applied to determine concrete durability. The rules generated by computer programs AQ21 and WEKA using J48 algorithm provided means for adequate categorization of plain concrete and concrete modified with CFBC fly ash as materials of good and acceptable resistance to chloride penetration.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.771-778
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• 2004

Recently, various applications of robot system become more popular in accordance with rapid development of computer hardware/software, artificial intelligence, and automatic control technology. Formerly robots mainly have been used in industrial field, however, nowadays it is said that the robot will do an important role in the home service application. To make the robot more useful, we require further researches on implementation of natural communication method between the human and the robot system, and autonomous behavior generation. The gesture recognition technique is one of the most convenient methods for natural human-robot interaction, so it is to be solved for implementation of intelligent robot system. In this paper, we describe the state-of-the-art of advanced gesture recognition technologies for intelligent robots according to three methods; sensor based method, feature based method, appearance based method, and 3D model based method. And we also discuss some problems and real applications in the research field.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.579-583
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• 1988

As the power facilities grow up, the optimal operation and the best maintenance of power plant can not be overestimated too much, which can enhance the plant availability and reliability much further. In this respect, fault diagnosis methodologies of dynamic system which is time-varing and strongly nonlinear have been studied. On of them is to use algorithm which is based on time-invariant, linear system, but this is not so nice a method for applying to power Plant. Therefore, the study on other techniques using Artificial Intelligence (AI) is under way. In this paper, the existing ways of fault detection are surveyed and their problems are also discussed.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.1
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• pp.52-57
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• 2005

In the foe of global competition, the requirements for the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a mai or change on steel manufacturing industries. Indeed, one of the keys to achieve this goal is the automation of the steel-making process using AI(Artificial Intelligence) techniques. The automation of hot rolling process requires the developments of several mathematical models for simulation and quantitative description of the industrial operations involved. In this paper, an on-line training neural network for both long-term teaming and short-term teaming was developed in order to improve the prediction of rolling force in hot rolling mill. This analysis shows that the predicted rolling force is very closed to the actual rolling force, and the thickness error of the strip is considerably reduced.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.124-129
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• 2003

In the face of global competitor the requirements flor the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a major change on steel manufacturing industries. Indeed, one of the keys to achieve this goal is the automation of the steel-making process using AI(Artificial Intelligence) techniques. The automation of hot rolling process requires the developments of several mathematical models fir simulation and quantitative description of the industrial operations involved. In this paper, a on-line training neural network for both long-term teaming and short-term teaming was developed in order to improve the prediction of rolling force in hot rolling mill. This analysis shows that the predicted rolling force is very closed to the actual rolling force, and the thickness error of the strip is considerably reduced.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.3
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• pp.173-180
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• 2015

In this paper, we propose a new precise control technology of robotic gripper for assembling and handling of part. When a robot manipulator interacts mechanically with its environment to perform tasks such as assembly or edge-finishing, the end-effector is thereby constrained by the environment. Therefore grasping force control is very important, since it increases safety due to monitoring of contact force. A comparison of various force control architecture is reported. Different force control methods can often be configured to achieve similar results for a given task, and the choice of control algorithm depends strongly on the application or on the characteristics of a particular robot. In the research, the adjustable gripping force can be controlled and improved the accuracy using the artificial intelligence techniques.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.41-48
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• 2007

Latest advances in network sensor technology and state of the art of mobile robot, and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. In this study, as the preliminary step for developing a multi-purpose "Intelligent Space" platform to implement advanced technologies easily to realize smart services to human. We will give an explanation for the ISpace system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. Instead we will focus on the main results with relevance to the DIND data fusion with CI of Intelligent Space. We will conclude by discussing some possible future extensions of ISpace. It is first dealt with the general principle of the navigation and guidance architecture, then the detailed functions tracking multiple objects, human detection and motion assessment, with the results from the simulations run.