• Korean Management Science Review
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• v.30 no.3
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• pp.81-97
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• 2013

This paper considers a parallel-machine scheduling problem with dedicated and common processing machines. Non-identical setup and processing times are assumed for each machine. A genetic algorithm is proposed to minimize the makespan objective measure. In this paper, a lowerbound and some heuristic algorithms are derived and tested through computational experiments.

• Journal of the Society of Disaster Information
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• v.2 no.1
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• pp.39-52
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• 2006

In this paper, an analytical and experimental study was performed in order to determine the effects of interaction between vehicle and structure. Results presented in the paper show that analytical method including moving load effect can investigate the trend of structural response due to dynamic interaction between vehicle and structure. The wheel tracking machine fitted with 2-axle test vehicle can demonstrate more accurate dynamic interaction between vehicle and structure than the wheel tracking machine fitted without 2-axle test vehicle.

• Korean Management Science Review
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• v.12 no.3
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• pp.177-185
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• 1995

This paper presents a Tabu Search method to minimize a number of tardy jobs in the nonidentical parallel machine scheduling. The Tabu Search method employs a restricted neighborhood for the reduction of computation time. In this paper, we use two different types of method for a single machine scheduling. One is Moore's algorithm and the other is insertion method. We discuss computational experiments on more than 1000 test problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.6 no.9
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• pp.39-44
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• 1983

The main issue of his paper is to quantify the compatability between man and machine in a system. This paper offers an evaluation model derived from transfer function of control system, and shows a methodology of applying efficiency for man and machine to the model to quantify the compatability of a system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.30
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• pp.107-116
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• 1994

This paper formulates a dynamic monitoring and control model with a machine state by quality variations in a single lot production system. A monitoring model is based on estimate of machine state obtained using control theory. The model studied in this paper has a great advance from a point of view the combination between quality control (Sampling, Control Chart) and automatic control theory, and can be extended in a several ways.

• Proceedings of the KIPE Conference
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• 2002.11a
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• pp.12-16
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• 2002

This paper deals with the measurement of machine parameters of inverter-fed induction motors for an accurate torque control applications such as machine tools and tension control machines. After discussing nonlinearities of both inverter and motor, this paper suggests appropriate compensation and measurement methods. The experimental results show the validity of the proposed method in the operating conditions.

• Journal of KIISE:Software and Applications
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• v.27 no.7
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• pp.759-768
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• 2000

The ZG-machine is a space-efficient G-machine, which exploits a simple encoding method, called tag-forwarding, to compress the heap structure of graphs. Experiments on the ZG-machine without garbage collection shows that the ZG-machine saves 30% of heap space and the run-time overhead is no more than 6% than the G-machine. This paper presents the results of further experiments on the ZG-machine with the garbage collector. As a result, the heap-residency of the ZG-machine decreases by 34% on average although the run-time increases by 34% compared to the G-machine. The high rate of the run-time overhead of the ZG-machine is incurred by the garbage collector. However, when the heap size is 7 times the heap-residency, the run-time overhead of the ZG-machine is no more than 12% compared to the G-machine. With the aspect of reduced heap-residency, the ZG-machine may be useful in memory-restricted environments such as embedded systems. Also, with the development of a more efficient garbage collector, the run-time is expected to decrease significantly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3966-3991
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• 2018

Due to the lack of visualization services and organic combinations between public and private buildings data, the usability of the basic map has remained low. To address this issue, this paper reports on a solution that organically combines public and private data while providing visualization services to general users. For this purpose, factors that can affect building prices first were examined in order to define the related data attributes. To extract the relevant data attributes, this paper presents a method of acquiring public information data and real estate-related information, as provided by private real estate portal sites. The paper also proposes a pretreatment process required for intelligent machine learning. This report goes on to suggest an intelligent machine learning algorithm that predicts buildings' value pricing and future value by using big data regarding buildings' spatial information, as acquired from a database containing building value attributes. The algorithm's availability was tested by establishing a prototype targeting pilot areas, including Suwon, Anyang, and Gunpo in South Korea. Finally, a prototype visualization solution was developed in order to allow general users to effectively use buildings' value ranking and value pricing, as predicted by intelligent machine learning.

• The KIPS Transactions:PartA
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• v.14A no.2
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• pp.91-98
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• 2007

Generally, virtual machine platform is composed of a compiler, an assembler, and VM(Virtual Machine). To develop it, the design of VMC(Virtual Machine Code) is an essential task. And it is very important to verify the virtual machine platform. To do this and furthermore to execute VMC, it needs to implement VMC execution system using compiling method, interpreting method, or decompiling method. In this paper, we suggested and implemented the executing system of VMC using decompiling method out of three methods to execute the VMC. In our implementation, the VMC is SIL(Standard Intermediate Language) that is an intermediate code of EVM(Embedded Virtual Machine). Actually, we verified the usefulness of the decompiling method. And the decompiling method suggested in this paper can be used to minimize the mistake in developing Virtual machine platform.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.245-258
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• 2016

This paper aims to present the way to bring about significant results through performance improvement of learning algorithm in the research applying to machine learning. Research papers showing the results from machine learning methods were collected as data for this case study. In addition, suitable machine learning methods for each field were selected and suggested in this paper. As a result, SVM for engineering, decision-making tree algorithm for medical science, and SVM for other fields showed their efficiency in terms of their frequent use cases and classification/prediction. By analyzing cases of machine learning application, general characterization of application plans is drawn. Machine learning application has three steps: (1) data collection; (2) data learning through algorithm; and (3) significance test on algorithm. Performance is improved in each step by combining algorithm. Ways of performance improvement are classified as multiple machine learning structure modeling, $+{\alpha}$ machine learning structure modeling, and so forth.