• Journal of the Korean Society of Industry Convergence
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• v.4 no.4
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• pp.365-369
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• 2001

This paper presented a new model of virtualized CNC milling machine. The model verifies the over cut, the under cut and the surface roughness using NC file generated from CAM and cutting condition. The model uses Z-map model to verify workpiece. In this paper, the model used the velocities of x, y and z direction and obtained a center point of a hall end mill for modeling Z-map of workpiece. To investigate the performance of the model, simulation study was carried out. As the results, the model gave geometry accuracy of workpiece, the surface roughness and the chip loads in finish cutting that can predict tool chipping. The virtualized CNC machine can he used a flat end mill, a ball end mill and a rounded end mill.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.635-640
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• 2000

Thermal deformation of machine tools can be evaluated from the analysis of the whole temperature field. However, it is extremely inefficient and impossible to acquire the whole temperature field by measuring temperatures of every point. So, a temperature estimator, which can estimate the whole temperature field from the temperatures of just a few points, is required. In this paper, 1-dimensional heat transfer problem is modeled with modal analysis and state space equations. and then state observer is designed to estimate the intensity of heat source and the whole temperature field in real-time. The reliability of this estimator is verified by making a comparison between solutions by the proposed method and the exact solutions of examples. The proposed method is applied to the estimation of temperature distribution in a ball screw system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.5
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• pp.529-535
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• 2009

This paper describes a measuring device of glass thickness using machine vision and image processing techniques on real-time. Today, the machine vision enable to inspect fast and exactly than human's eyes. The presented system has advantages of continuous measurement, flexibility and good accuracy. The system consists of a laser diode, a CCD camera with PC. The camera located on the opposite side of the incident beam measures the distance between two reflected laser beams from the glass top and bottom surface. We apply a binary algorithm to convert and analyze the image from camera to PC. Laser point coordination by border tracing algorithm is used to find the center of beam circle. The measured result was compared with micrometer and showed 0.002mm accuracy. Finally, the errors were discussed how to minimize the influence of glass wedge angle and angular error of moving stage.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.911-913
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• 1997

This paper presents a method for optima] placement of series capacitors in order to improve the power system transient stability, using genetic algorithms. For the formulation, this paper considers the objective function which is the energy margin as the difference between transient energy and critical energy. The most important factor in determining an accurate critical energy is the controlling unstable equilibrium point (UEP). This paper proposes the controlling UEP methods, concurrently with the DFP(Davidon-Fletcher-Powell) method, which enables the enhancement of multi-machine analysis. The proposed method is applied to 6-bus, 7-line, 4-machine model system to show its effectiveness in determining the locations to install series capacitors and the it's size to be installed in system, simultaneously.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.18-23
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• 1996

The Job of Milling in the Local Skill Contest in 1996 was to assemble parts into a complete whole of the parts number 1, 3, 4 worded by Milling Machine and the parts number 2 worked by Machining Center. In the parts of Milling Machine, the Job was to work 45$^{\circ}$angle working, T-slot, dovetail, the correct position drilling, rimming, boring, etc. In the Machining Center, there were the way of calculation of point of contact of 'R' contour curved line and lots of working elements. So, it was possible to work the parts and assemble them within the time limit only through the program to be made out in the way to shorten working hours.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.353-358
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• 2002

A feature-based inspection planning system is proposed in this research to develop more efficient measuring methodology for the OMM (On-machine measurement) for complicated workpiece having many primitive form features. This paper focuses on the development of the CAIP (computer-aided inspection system) methodologies. The optimum inspection sequences for the features are determined by analyzing the feature information such as the nested relations and the possible probe approaching directions of the features, and forming feature groups. A series of heuristic rules are developed to accomplish it. Also, each feature is decomposed into its constituent geometric elements, and then the number of sampling points, the locations of the measuring point, the optimum probing path are determined by applying the fuzzy logic, Hammersley's method, and the TSP algorithm. To verify the proposed methodologies, simulations are carried out and the results are analyzed.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.750-752
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• 2003

This paper presents a method of tolerance analysis for a electric machine. Tolerance analysis technique is required to find the tolerance band of design variables and estimate the characteristic distribution of the electric machine, because that manufacturing tolerances as well as measuring errors have a great influence on the electric machine. Therefore, this paper introduces Stochastic Response Surface Methodology to achieve the tolerance analysis. As an example, the tolerance analysis is applied to the analysis of torque characteristics for a BLDC motor from the electric point of view.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2199-2201
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• 2001

The 3-dimensional measuring machine by using an ultrasonic sensor is used one of the NDE(Nondestructive Examination). It is applied to the inspection of pipelines, boreholes, pressure vessel and tank, and so on. In particular when a harsh environment prohibits the use of moving mechanical parts. The 3-dimensional measuring machine by using an ultrasonic sensor, which measure 1-dimensional information and 2-dimensional information simultaneously from a target of inspection, and then reembody 3-dimensional information. So we can find the situation in progress and predict remaining life and corrosion without destructive examination. It's a point of excellence that the 3-dimensional measuring machine is portable.

• ETRI Journal
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• v.43 no.5
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• pp.775-786
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• 2021

To translate in real time, a simultaneous translation system should determine when to stop reading source tokens and generate target tokens corresponding to a partial source sentence read up to that point. However, conventional attention-based neural machine translation (NMT) models cannot produce translations with adequate latency in online scenarios because they wait until a source sentence is completed to compute alignment between the source and target tokens. To address this issue, we propose a reinforced learning (RL)-based attention mechanism, the reinforced attention mechanism, which allows a neural translation model to jointly train the stopping criterion and a partial translation model. The proposed attention mechanism comprises two modules, one to ensure translation quality and the other to address latency. Different from previous RL-based simultaneous translation systems, which learn the stopping criterion from a fixed NMT model, the modules can be trained jointly with a novel reward function. In our experiments, the proposed model has better translation quality and comparable latency compared to previous models.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.272-276
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• 2021

Presently, Online / Offline Users are facing cyber attacks every day. These cyber attacks affect user's performance, resources and various daily activities. Due to this critical situation, attention must be given to prevent such users through cyber attacks. The objective of this research paper is to improve the IDS systems by using machine learning approach to develop a hybrid model which controls the cyber attacks. This Hybrid model uses the available KDD 1999 intrusion detection dataset. In first step, Hybrid Model performs feature optimization by reducing the unimportant features of the dataset through decision tree, support vector machine, genetic algorithm, particle swarm optimization and principal component analysis techniques. In second step, Hybrid Model will find out the minimum number of features to point out accurate detection of cyber attacks. This hybrid model was developed by using machine learning algorithms like PSO, GA and ELM, which trained the system with available data to perform the predictions. The Hybrid Model had an accuracy of 99.94%, which states that it may be highly useful to prevent the users from cyber attacks.