• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.455-456
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• 2002

Wear is one of the main factors causing breakdown and fault of machine, so ferrography technique analyzing wear particles can be an effective way for condition monitoring and fault diagnosis. On the base of the forward multilayer neural network, a nodes self-deleting neural network model is provided in this paper. This network can itself deletes the nodes to optimize its construction. On the basis of the nodes self-deleting neural network, an intelligent ferrography diagnosis expert system (IFDES) for wear particles recognition and wear diagnosis is described. This intelligent expert system can automatically slim lip knowledge by learning from samples and realize basically the entirely automatic processing from wear particles recognition to wear diagnosis.

• ETRI Journal
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• v.35 no.1
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• pp.173-176
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• 2013

Existing symmetric cryptography-based solutions against pollution attacks for network coding systems suffer various drawbacks, such as highly complicated key distribution and vulnerable security against collusion. This letter presents a novel homomorphic subspace message authentication code (MAC) scheme that can thwart pollution attacks in an efficient way. The basic idea is to exploit the combination of the symmetric cryptography and linear subspace properties of network coding. The proposed scheme can tolerate the compromise of up to r-1 intermediate nodes when r source keys are used. Compared to previous MAC solutions, less secret keys are needed for the source and only one secret key is distributed to each intermediate node.

• Proceedings of the Technology Innovation Conference
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• 2005.06a
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• pp.116-139
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• 2005

ICT(information and communication technology) has played a pivotal role in the world economy, and the out look for ICT has improved markedly. One of the noticeable characteristics in the ICT sector Is the global rationalization of its technology and service. Specialization on the specific ICT capability is a pressing problem for many countries. Along the line of classical innovation cluster and network studies, this paper suggests a way to find and analyze the role of core technologies on the ICT network First, technology network is constructed by using patent citation data from USPTO. Then, a couple of cluster is generated by K-means clustering technique. Finally, brokerage analysis is applied to manifest the role of principal technologies. The network visualization and some stylized facts on dynamics are briefly given altogether Based on the role and relationship of technologies across clusters, it is expected that this research could contribute to the ICT cluster formation and the vision-making for ICT specialization at the viewpoint of technology Policy.

• 한국정보통신설비학회:학술대회논문집
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• 2006.08a
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• pp.43-46
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• 2006

IEEE 802.16 WirelessMAN aiming to broadband wireless access (BWA) is evolving to 4G mobile communication system through the standardization of IEEE 802.16e supporting mobility on existing fixed WirelessMAN system. It is necessary for hand-over to provide seamless data service while MS (Mobile Station) moves to another BS (Base Station). Because the performance of handover affects packet loss or delay of any communications, it must consider low latency handover mechanism in packet based network. In this paper, we describes handover scheme of IEEE 802.16e with the cell edge interference problem and shows the way to solve the problem in frequency reuse one deployment. Our scheme reduces the handover latency and packet loss probability.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2000.11a
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• pp.69-87
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• 2000

Models and Strategies for Network Operator's B2B Ecommerce The B2B ecommerce market is one of the fastest growing areas in the telecom industry. However network operators have been slow to enter the arena, Network operator have been held back by their general unsurety about the Internet business. Network operators'core business(the supply of connectivity and transport service) is becoming unprofitable. As a result they are looking to diversify into areas where margins are higher. B2B ecommerce offers them a major way to achieve this. It is possible to identify various business models for offering ecommerce services to end user, ranging from the provision of complete packaged applications to the implementation and management of customized ecommerce solution. In this study the three main approaches available to network operators are the traditional IT outsourcing model, the ASP model and the community builder model.

• IE interfaces
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• v.13 no.4
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• pp.627-638
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• 2000

During last ten years, logistics network management has become one of the most important sources of competitive advantage regarding logistics cost and customer service in numerous business segments. The key to success in this dynamic and severe business environment is the ability to design and plan the logistics network optimally in an integrated way. Network design and planning involves many issues relating to strategic, tactical, and operational decisions. To assist a logistics designer or planner, many computer-based decision support systems (DSS) have been developed. In this paper, the issues related to design, development, and implementation of the DSS for logistics network design and planning are discussed, and an ideal framework of the DSS is proposed with some ideas on the future development. Finally, DLNET, the DSS developed by author, is briefly introduced.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.147-154
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• 2023

Network intrusion refers to any unauthorized penetration or activity on a computer network. This upsets the confidentiality, integrity, and availability of the network system. One of the major threats to any system's availability is a Denial-of-Service (DoS) attack, which is intended to deny a legitimate user access to resources. Therefore, due to the complexity of DoS attacks, it is increasingly important to abstract and describe these attacks in a way that will be effectively detected. The automaton theory is used in this paper to implement a SYN Flood detection system based on Time-Dependent Finite Automata (TDFA).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1368-1375
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• 2013

The Smart Grid, which can monitor or diagnose the power grid in real time to operate efficiently, has been pushed ahead systematically as one of alternatives to solve these issues by combining the advanced Information Communication Technology and the electrical network. Hence, the electric company which introduces smart grid technology can read remotely the electrical meter readings by means of two-way communication between the meter and the central system. This enabled the customer and the utility to take part in reasonable electrical energy utilization. AMI became one of the core foundations in realizing the Smart Grid. It is hard to test the entire process of AMI system before the full deployment because it covers the broad objects from the customer to the utility operation system and requires mass data handling and management. Therefore, we design an efficient AMI network model and a simulator for performance evaluation required to simulate the network model similar to the real environment. This tool supports to evaluate the efficiency of the AMI network equipments and deployment. Additionally, it estimates the appropriate number of deployments and the proper capabilities.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.641-646
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• 1998

In order to enhance the dynamic and interactive simulation capability of a system thermal hydraulic code for nuclear power plant, applicability of flow network models in SINDA/FLUIN $T^{™}$ has been tested by modeling feedwater system and coupling to DSNP which is one of a system thermal hydraulic simulation code for a pressurized heavy water reactor. The feedwater system is selected since it is one of the most important balance of plant systems with a potential to greatly affect the behavior of nuclear steam supply system. The flow network model of this feedwater system consists of condenser, condensate pumps, low and high pressure heaters, deaerator, feedwater pumps, and control valves. This complicated flow network is modeled and coupled to DSNP and it is tested for several normal and abnormal transient conditions such turbine load maneuvering, turbine trip, and loss of class IV power. The results show reasonable behavior of the coupled code and also gives a good dynamic and interactive simulation capabilities for the several mild transient conditions. It has been found that coupling system thermal hydraulic code with a flow network code is a proper way of upgrading simulation capability of DSNP to mature nuclear plant analyzer (NPA).

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.6
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• pp.289-296
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• 2018

Drone detection in FMCW radar system needs complex techniques because a drone beat frequency is highly dynamic and unpredictable. Therefore, the current static signal processing algorithms cannot show appropriate detection accuracy. With dynamic signal fluctuation and environmental clutters, it can fail to detect a drone or make false detection. It affects to the radar system integrity and safety. Constant false alarm rate (CFAR), one of famous static signal process algorithm is effective for static environment. But for drone detection, it shows low detection accuracy. In this paper, we suggest neural network based FMCW radar system for detecting a drone. We use recurrent neural network (RNN) because it is the effective neural network for signal processing. In our FMCW radar system, one transmitter emits FMCW signal and four-way fixed receivers detect reflected drone beat frequency. The coordinate of the drone can be calculated with four receivers information by triangulation. Therefore, RNN only learns and inferences reflected drone beat frequency. It helps higher learning and detection accuracy. With several drone flight experiments, RNN shows false detection rate and detection accuracy as 21.1% and 96.4%, respectively.