• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.73-80
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• 2016

This study focuses on the formation of input release lots in a semiconductor wafer fabrication facility. After the order-lot pegging process assigns lots in the fab to orders and calculates the required quantity of wafers for each product type to meet customers' orders, the decisions on the formation of input release lots should be made to minimize the production costs of the release lots. Since the number of lots being processed in the wafer fab directly is related to the productivity of the wafer fab, the input lot formation is crucial process to reduce the production costs as well as to improve the efficiency of the wafer fab. Here, the input lot formation occurs before every shift begins in the semiconductor wafer fab. When input quantities (of wafers) for product types are given from results of the order-lot pegging process, lots to be released into the wafer fab should be formed satisfying the lot size requirements. Here, the production cost of a homogeneous lot of the same type of product is less than that of a heterogeneous lot that will be split into the number of lots according to their product types after passing the branch point during the wafer fabrication process. Also, more production cost occurs if a lot becomes more heterogeneous. We developed a multi-dimensional dynamic programming algorithm for the input lot formation problem and showed how to apply the algorithm to solve the problem optimally with an example problem instance. It is necessary to reduce the number of states at each stage in the DP algorithm for practical use. Also, we can apply the proposed DP algorithm together with lot release rules such as CONWIP and UNIFORM.

• Journal of the Korean Society of Safety
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• v.21 no.6 s.78
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• pp.116-121
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• 2006

In metal cutting processes, cutting conditions have an influence on reducing the production cost and deciding the quality of a final product. Process planners usually make modification to recommended cutting parameters obtained from machining data handbooks in order to satisfy requirements for individual operation. The modified cutting parameters also need to be examined for the safe machining. In this paper, a new operation planning system that allows the generation and check of modified cutting parameters is proposed for the milling process. A neural network methodology is introduced to identify mathematical models for generation of the modified cutting parameters, and several simplified rules and equations are presented for the check of the cutting parameters. Finally, the results are demonstrated with an example part.

• Journal of Korea Game Society
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• v.11 no.6
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• pp.33-42
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• 2011

In this study, game-aided human life type game design method is suggested. It mainly deals with the permissiveness of the game rules and coenesthesia of the game that are fitted with the agility of the elders such as the performance of a selective response. And 'Rolling hoops Balance Game' has been implemented by applying the game-aided human life type game. Since the pressure sensors are installed on each parts of the chair type game controller, to play the game, a gamer simply uses her hands and feet to press the sensors without requirements of the complex movements. The goal of the game are the leg muscles strength and improvement of the body balancing ability. In addition, the game graphics consists of sensory stimuli package(Namazi, Haynes, reminiscence therapy, 1994) to make friendly mood for elders. We have tested 50 elders who were more than 65 years old. 74% of them answered they were satisfied totally for the game play. It is a meaningful result that 88% of participants replied they would like to play the game again.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.7
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• pp.265-274
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• 2019

The reliability test performed when developing the weapon system software is classified into static test and dynamic test. In static test, checking the coding rules, vulnerabilities and source code metric are performed without executing the software. In dynamic test, its functions are verified by executing the actual software based on requirements and the code coverage is measured. The purpose of this static/dynamic test is to find out defects that exist in the software. However, there still exist defects that can't be detected only by the current reliability test on the weapon system software. In this paper, whether defects that may occur in the software can be detected by static test and dynamic test of the current reliability test on the weapon system is analyzed through experiments. As a result, we provide guidance on improving the reliability test of weapon system software, especially the dynamic test.

• Convergence Security Journal
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• v.20 no.5
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• pp.3-10
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• 2020

Recently, the Internet and networks are regarded as essential infrastructures that constitute society, and security threats have been constantly increased. However, the network switch that actually transmits packets in the network can cope with security threats only through firewall or network access control based on fixed rules, so the effective defense for the security threats is extremely limited in the network itself and not actively responding as well. In this paper, we propose an in-network security framework using the high-level data plane programming language, P4 (Programming Protocol-independent Packet Processor), to deal with DDoS attacks and IP spoofing attacks at the network level by monitoring all flows in the network in real time and processing specific security attack packets at the P4 switch. In addition, by allowing the P4 switch to apply the network user's or administrator's policy through the SDN (Software-Defined Network) controller, various security requirements in the network application environment can be reflected.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.1
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• pp.25-38
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• 2017

Many security threats are occurring around the world due to the characteristics of industrial control systems that can cause serious damage in the event of a security incident including major national infrastructure. Therefore, the industrial control system network traffic should be analyzed so that it can identify the attack in advance or perform incident response after the accident. In this paper, we research the visualization technique as network forensics to enable reasonable suspicion of all possible attacks on DNP3 control system protocol, and define normal action based rules and derive visualization requirements. As a result, we developed a visualization tool that can detect sudden network traffic changes such as DDoS and attacks that contain anormal behavior from captured packet files on industrial control system network. The suspicious behavior in the industrial control system network can be found using visualization tool with Digital Bond packet.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.5
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• pp.125-131
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• 2015

In order to vitalize the Rich Communication Service-e(RCS-e) service, RCS-e users need various ways to use RCS including RCS-e apps. A RCS standards organization has suggested Application Program Interface(API). Since it only dealt with functional requirements, it was not enough to implement the API. This paper suggests an open API framework that can utilize RCS-e through a web interface. By using the framework, web developers can implement various RCS-e-enabled web applications. A system architecture is defined for the framework. Call flows for establishing a RCS-e session between the framework and other nodes are defined. Also, rules and examples for translating protocols between them are provided. Finally, performance evaluation proves that the proposed framework does not add loads to the existing network infrastructure.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.49-62
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• 2022

Online customer review data can be easily collected on the Internet and also they describe sentimental evaluation of a product in different aspects. Previous sentiment analysis studies evaluate the degree of sentiment with review data, which may have multiple sentences describing different product aspects. Since different aspects of a product can be described in a sentence, the proposed method suggested analyzing a sentence to build a pair of a product aspect terms and sentimental terms. Bidirectional LSTM and CRF algorithms were used in this paper. A pair of aspect terms and sentimental terms are evaluated by pre-defined evaluation rules. The paper suggested using the result of evaulation as inputs of QFD, so that the quantified customer voices effect on the requirements of a new product. Online reviews for a hair dryer were used as an example showing that the proposed approach can derive reasonable sentiment analysis results.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.149-155
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• 2011

This paper presents simulations of advance evacuation analysis using a cellular automata model for passenger behavior in an emergency of passenger ship. The proposed cellular automata model divides the space in a uniform grid called "cell." Each passenger is located in a cell and moves to another cell according to a set of local rules assumed to be associated with the individual and crowd behaviors of the passengers. To verify the usefulness of the proposed cellular automata model, 11 tests, all of which are specified in International Maritime Organization Maritime Safety Committee/ Circulation 1238 (IMO MSC/Circ. 1238), were implemented, and it was confirmed that all the requirements of these tests had been met.

• Convergence Security Journal
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• v.17 no.1
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• pp.31-38
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• 2017

As the cyber-attacks through the networks advance, it is difficult for the intrusion detection system based on the simple rules to detect the novel type of attacks such as Advanced Persistent Threat(APT) attack. At present, many types of research have been focused on the application of machine learning techniques to the intrusion detection system in order to detect previously unknown attacks. In the case of using the machine learning techniques, the performance of the intrusion detection system largely depends on the feature set which is used as an input to the system. Generally, more features increase the accuracy of the intrusion detection system whereas they cause a problem when fast responses are required owing to their large elapsed time. In this paper, we present a network intrusion detection system based on artificial neural network, which adopts a multi-objective genetic algorithm to satisfy the both requirements: accuracy, and fast response. The comparison between the proposing approach and previously proposed other approaches is conducted against NSL_KDD data set for the evaluation of the performance of the proposing approach.