• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1916-1924
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• 2017

Fossil oil, as the main energy of transportation, is destined to be exhausted. The electrification of transportation is a sustainable solution to the energy crisis, since electric power could be acquired from the inexhaustible sun, wind and water. Among all the problems that hinder the development of Electric Vehicle (EV) industry, charging issue might be the most prominent one. In this paper, the service process of a charging station with Battery Energy Storage System (BESS) is analyzed by means of $Cram{\acute{e}}r$ - Lundberg model which has been intensively utilized in ruin theory. The service quality is proposed in two dimensions: the service efficiency and the service reliability. The arrival rate and State of Charge (SOC) upon arrival are derived from 2009 National Household Travel Survey (NHTS). The simulations are performed to show how the service quality is determined by the system parameters such as the number of servers, the service rate, the initial capacity, the charge rate and the maximum waiting time. At last, the economic analysis of the system is conducted and the best combination of the system parameters are given.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2086-2098
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• 2018

Security plays a vital role and is the key challenge in Mobile Ad-hoc Networks (MANET). Infrastructure-less nature of MANET makes it arduous to envisage the genre of topology. Due to its inexhaustible access, information disseminated by roaming nodes to other nodes is susceptible to many hazardous attacks. Intrusion Detection and Prevention System (IDPS) is undoubtedly a defense structure to address threats in MANET. Many IDPS methods have been developed to ascertain the exceptional behavior in these networks. Key issue in such IDPS is lack of fast self-organized learning engine that facilitates comprehensive situation awareness for optimum decision making. Proposed "Intelligent Behavioral Hybridized Intrusion Detection and Prevention System (IBH_IDPS)" is built with computational intelligence to detect complex multistage attacks making the system robust and reliable. The System comprises of an Intelligent Client Agent and a Smart Server empowered with fuzzy inference rule-based service engine to ensure confidentiality and integrity of network. Distributed Intelligent Client Agents incorporated with centralized Smart Server makes it capable of analyzing and categorizing unethical incidents appropriately through unsupervised learning mechanism. Experimental analysis proves the proposed model is highly attack resistant, reliable and secure on devices and shows promising gains with assured delivery ratio, low end-to-end delay compared to existing approach.

• ETRI Journal
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• v.36 no.5
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• pp.730-740
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• 2014

The rapid increase in the number of patients with chronic diseases is an important public healthcare issue in many countries, which accelerates many studies on a healthcare system that can, whenever and wherever, extract and process patient data. A patient with a chronic disease conducts self-management in an out-of-hospital environment, particularly in an at-home environment, so it is important to provide integrated and personalized healthcare services for effective care. To help provide effective care for chronic disease patients, we propose a service flow and a new cloud-based personalized healthcare system architecture supporting both at-home and at-hospital environments. The system considers the different characteristics of at-hospital and at-home environments, and it provides various chronic disease care services. A prototype implementation and a predicted cost model are provided to show the effectiveness of the system. The proposed personalized healthcare system can support cost-effective disease care in an at-hospital environment and personalized self-management of chronic disease in an at-home environment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.526-533
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• 2014

In this study, we introduce design methodology to develop a guidance for issuing heavy rainfall warning by using both RBFNNs(Radial basis function neural networks) and SVR(Support vector regression) model, and then carry out the comparative studies between two pattern classifiers. Individual classifiers are designed as architecture realized with the aid of optimization and pre-processing algorithm. Because the predictive performance of the existing heavy rainfall forecast system is commonly affected from diverse processing techniques of meteorological data, under-sampling method as the pre-processing method of input data is used, and also data discretization and feature extraction method for SVR and FCM clustering and PSO method for RBFNNs are exploited respectively. The observed data, AWS(Automatic weather wtation), supplied from KMA(korea meteorological administration), is used for training and testing of the proposed classifiers. The proposed classifiers offer the related information to issue a heavy rain warning in advance before 1 to 3 hours by using the selected meteorological data and the cumulated precipitation amount accumulated for 1 to 12 hours from AWS data. For performance evaluation of each classifier, ETS(Equitable Threat Score) method is used as standard verification method for predictive ability. Through the comparative studies of two classifiers, neuro-fuzzy method is effectively used for improved performance and to show stable predictive result of guidance to issue heavy rainfall warning.

• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.46-47
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• 2007

SCADA (Supervisory Control and Data Acquisition) system has been used fur remote measurement and control on the critical infrastructures as well as modem industrial facilities. As cyber attacks increase on communication networks. SCADA network has been also exposed to cyber security problems. Especially, SCADA systems of energy industry such as electric power, gas and oil are vulnerable to targeted cyber attack and terrorism. Recently, many research efforts to solve the problems have made progress on SCADA network security. In this paper, we introduce recent security issue of SCADA network and propose the application of encryption method to Korea SCADA network.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.425-427
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• 2006

In this paper, an automatic side-view inspection algorithm for LCD modules is proposed. Until now, most parts of inspection is performed by human inspectors, which means very high product costs. So inspection automation is the very hot issue in the LCD industries. However, it is not easy problem to replace the human by computer vision system. In the many inspections which are based on the human eyes, side-view inspection is most hard problem to solve. In this paper, an image morphing algorithm is developed, which will help to enable the automation of the side-view inspection process.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1597-1598
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• 2015

Regenerative power utilization is one of the most interesting issue in electric railway systems. Generally, technologies to utilize regenerative power from railway vehicles are railway substation with regenerative inverter, on-station energy storage systems, and on-board energy storage systems. In this paper, the electric power loss for those technologies is calculated and compared using DC electric railway system analysis algorithm.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.30 no.9
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• pp.596-601
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• 2017

The advancement and diversification of urban functions has caused an increasing need to improve the reliability of power supplies. The diversification of urban areas causes social disruptions by paralyzing urban functions during power outages. A large power outage occurs in the event of an accident, owing to the subduction of distribution lines. Therefore, in recent years, for the sake of the environment and safety, the safety diagnosis of electric power facilities has become an important issue. In this system, because thermal information changes rapidly during unattended monitoring owing to heat concentration phenomenon due to abnormal load or deterioration, studies have been conducted on the development of a device that can notify the manager at all times.

• Journal of Electrical Engineering and Technology
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• v.2 no.3
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• pp.386-390
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• 2007

At recent times, an essential issue in the replacement of the old analogue I&C to computer-based digital systems in nuclear power plants becomes the quantitative software reliability assessment. Software reliability models have been successfully applied to many industrial applications, but have the unfortunate drawback of requiring data from which one can formulate a model. Software that is developed for safety critical applications is frequently unable to produce such data for at least two reasons. First, the software is frequently one-of-a-kind, and second, it rarely fails. Safety critical software is normally expected to pass every unit test producing precious little failure data. The basic premise of the rare events approach is that well-tested software does not fail under normal routine and input signals, which means that failures must be triggered by unusual input data and computer states. The failure data found under the reasonable testing cases and testing time for these conditions should be considered for the quantitative reliability assessment. We presented the quantitative reliability assessment methodology of safety critical software for rare failure cases in this paper.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.4
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• pp.240-245
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• 2014

How well the self-interference cancellation (SIC) technique performs is a primary issue in realizing an in-band full-duplex (FD) wireless communication system. One factor affecting its performance is channel estimation error on the self-interference channel. We propose a new analog SIC scheme which is robust to channel estimation error. It uses phase rotators in the radio frequency (RF) chain. We also derive closed-form equations for the residual self-interference of the proposed and the conventional schemes. The analytical and numerical results show that the residual self-interference under the proposed SIC scheme is less than that using the conventional scheme, even though channel estimation error is present.