• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.458-465
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• 2020

The purpose of this study is to analyze the effect of policy in Jeju, using a macro-economic forecasting model of Jeju. First, the model's reality explanatory power improved by updating its statistics to 2017 and expanding new policy variables and modules. Also, the industrial structure of the model was further subdivided and extended to be considered simultaneously in the demand side of Keynesian theory. Second, it was determined that the predictive power for the model of this study was better than that of the existing model. However, with some endogenous variables, it was possible to identify implications that should be developed and considered when the model is improved with additional data in the future. Third, when the second airport construction was considered, it was observed that its effect was an increase of 1.25 times for GRDP, 1.2 times for employment, 1.48 times for private consumption, and 2.06 times for investment. Also, the economic growth rate was estimated to be 1.6% point higher than when the second airport was not constructed. Finally, the results of this study are expected to be used for policy decision making of the Jeju Government.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.4
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• pp.811-817
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• 2009

The rapid growth of network based IT systems has resulted in continuous research of security issues. Probe intrusion detection is an area of increasing concerns in the internet community. Recently, a number of probe intrusion detection schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems, are useful only for the existing patterns of probe intrusion. They can not detect new patterns of probe intrusion. Therefore, it is necessary to develop a new Probe Intrusion Detection technology that can find new patterns of probe intrusion. In this paper, we proposed a new network based probe intrusion detector(NePID) using anomaly traffic analysis and fuzzy cognitive maps that can detect intrusion by the denial of services attack detection method utilizing the packet analyses. The probe intrusion detection using fuzzy cognitive maps capture and analyze the packet information to detect syn flooding attack. Using the result of the analysis of decision module, which adopts the fuzzy cognitive maps, the decision module measures the degree of risk of denial of service attack and trains the response module to deal with attacks. For the performance evaluation, the "IDS Evaluation Data Set" created by MIT was used. From the simulation we obtained the max-average true positive rate of 97.094% and the max-average false negative rate of 2.936%. The true positive error rate of the NePID is similar to that of Bernhard's true positive error rate.

• Proceedings of KOSOMES biannual meeting
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• 2004.05b
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• pp.43-48
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• 2004

The development of the traffic system has brought relative reduction in aspect of the cost and time distance on the geographical space. SOC(social overhead capital), an express highway and railroad, has a great and absolute effect on the prosperity of community, As Mokpo is one of the community under the influence q West costal highway express and KTX(Korea Train Express), the number of the tourists visiting city of port like Mokpo has increasing gradually, especially at the high-demand season(in Summer). But the coastal passenger boot can't be capable of customers arriving at the port. As a result of this situation, the 'balking' occurs. No 'balking', means the jam of road. In this thesis, by understanding the concept and property of ARENA and simulating operation of coastal passenger boot at Mokpo port, intends to analyze the truth of 'balking' and finds an effective operation method of coastal passenger boot for the solution to the traffic jam. The solution to the jam in the vicinity of port of Mokpo, which try to develop tourism package commodity now, will present the effect of qualitative analysis in giving an opportunity of economic growth of the community, Mokpo.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.5
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• pp.265-273
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• 2002

With the explosive growth of WWW traffic, there is an increasing demand for the high performance Web servers to provide a stable Web service to users. The cluster-based Web server is a solution to core with the heavy access from users, easily scaling the server according to the loads. In the cluster-based Web sewer, a back-end node may not be able to serve some HTTP requests directly because it does not have the requested contents in its main memory. In this case, the back-end node has to retrieve the requested contents from its local disk or other back-end nodes in the cluster. To reduce service latency, we introduce a new prefetch scheme. The back-end nodes predict the next HTTP requests and prefetch the contents of predicted requests before the next requests arrive. We develop three prefetch algorithms bated on some useful information gathered from many clients'HTTP requests. Through trace-driven simulation, the service latency of the prefetch scheme is reduced by 10 ~ 25% as compared with no prefetch scheme. Among the proposed prefetch algorithms, Time and Access Probability-based Prefetch (TAP2) algorithm, which uses the access probability and the inter-reference time of Web object, shows the best performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1419-1426
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• 2012

The heating and cooling energy load of the KNU plant factory was analyzed using the DesignBuilder. Indoor temperature set-point, LED supplemental lighting schedule, LED heat gain, and type of double skin window were selected as simulation parameters. For the cases without LED supplemental lighting, the proper growth temperature of lettuce $20^{\circ}C$ was selected as indoor temperature set-point together with $15^{\circ}C$ and $25^{\circ}C$. The annual heating and cooling loads which are required to maintain a constant indoor temperature were calculated for all the given temperatures. The cooling load was highest for $15^{\circ}C$ and heating load was highest for $25^{\circ}C$. For the cases with LED supplemental lighting, the heating load was decreased and the cooling load was 6 times higher than the case without LED. In addition, night time lighting schedule gave better result as compared to day time lighting schedule. To investigate the effect of window type on annual energy load, 5 different double skin window types were selected. As the U-value of double skin window decreases, the heating load decreases and the cooling load increases. To optimize the total energy consumption in the plant factory, it is required to set a proper indoor temperature for the selected plantation crop, to select a suitable window type depending on LED heat gain, and to apply passive and active energy saving technology.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.4
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• pp.105-117
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• 2010

The topographical depressions in urban areas, the lack in drainage capability, sewage backward flow, road drainage, etc. cause internal inundation, and the increase in rainfall resulting from recent climate change, the rapid urbanization accompanied by economic development and population growth, and the increase in an impervious area in urban areas deteriorate the risk of internal inundation in the urban areas. In this study, the vulnerability of internal inundation in urban areas is analyzed and SWMM model is applied into Oncheoncheon watershed, which represents urban river of Busan, as a target basin. Based on the results, the representative storm sewers in individual sub-catchments is selected and the risk of vulnerability to internal inundation due to rainfall in urban streams is analyzed. In order to analyze the risk and vulnerability of internal inundation, capacity is applied as an index indicating the volume of a storm sewer in the SWMM model, and the risk of internal inundation is into 4 steps. For the analysis on the risk of internal inundation, simulation results by using a SMMM model are compared with the actual inundation areas resulting from localized heavy rain on July 7, 2009 at Busan and comparison results are analyzed to prove the validity of the designed model. Accordingly, probabilistic rainfall at Busan was input to the model for each frequency (10, 20, 50, 100 years) and duration (6, 12, 18, 24hr) at Busan. In this study, it suggests that the findings can be used to preliminarily alarm the possibility of internal inundation and selecting the vulnerable zones in urban areas.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11B
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• pp.1346-1356
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• 2011

Transportation has been playing important role in our society by providing for people, freight, and information. However, it cuts its own throat by causing car accidents, traffic congestion, and air pollution. The main cause of these problems is a noticeable growth in the number of vehicles. The easiest way to mitigate these problems is to build new road infrastructures unless resources such as time, money, and space are limited. Therefore, there is a need to manage the existing road infrastructures effectively and safely. In this paper, we propose a road reservation scheme that provides fast and safe response for emergency vehicles using ubiquitous sensor network. Our idea is to allow emergency vehicle to reserve a road on a freeway for arriving to the scene of the accident quickly and safely. We evaluate the performance by three reservation method (No, Hop, and Full) to show that emergency vehicles such as ambulances, fire trucks, or police cars can rapidly and safely reach their destination. Simulation results show that the average speed of road reservation is about 1.09 ~ 1.20 times faster than that of non-reservation at various flow rates. However, road reservation should consider the speed of the emergency vehicle and the road density of the emergency vehicle processing direction, as a result of Hop Reservation and Full Reservation performance comparison analysis. We confirm that road reservation can guarantee safe driving of emergency vehicles without reducing their speed and help to mitigate traffic congestion.

• Journal of KIISE:Information Networking
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• v.37 no.3
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• pp.175-186
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• 2010

Due to the emergence of new application programs and the fast growth of Internet users, Internet routers are required to provide the quality of services according to the class of input packets, which is identified by wire-speed packet classification. For a pre-defined rule set, by performing multi-dimensional search using various header fields of an input packet, packet classification determines the highest priority rule matching to the input packet. Efficient packet classification algorithms have been widely studied. Tuple pruning algorithm provides fast classification performance using hash-based search against the candidate tuples that may include matching rules. Bloom filter is an efficient data structure composed of a bit vector which represents the membership information of each element included in a given set. It is used as a pre-filter determining whether a specific input is a member of a set or not. This paper proposes new tuple pruning algorithms using Bloom filters, which effectively remove unnecessary tuples which do not include matching rules. Using the database known to be similar to actual rule sets used in Internet routers, simulation results show that the proposed tuple pruning algorithm provides faster packet classification as well as consumes smaller memory amount compared with the previous tuple pruning algorithm.

• KDI Journal of Economic Policy
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• v.12 no.4
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• pp.3-20
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• 1990

The multisector model is designed to analyze and forecast structural change in industrial output, employment, capital and relative price as well as macroeconomic change in aggregate income, interest rate, etc. This model has 25 industrial sectors, containing about 1,300 equations. Therefore, this model is characterized by detailed structural disaggregation at the sectoral level. Individual industries are based on many of the economic relationships in the model. This is what distinguishes a multisector model from a macroeconomic model. Each industry is a behavioral agent in the model for industrial investment, employment, prices, wages, and intermediate demand. The strength of the model lies in the simulating the interactions between different industries. The result of its simulation will be introduced in the next paper. In this paper, we only introduce the structure of the multisector model and the coefficients of the equations. The multisector model is a dynamic model-that is, it solves year by year into the future using its own solutions for earlier years. The development of a dynamic, year-by-year solution allows us to combine the change in structure with a consideration of the dynamic adjustment required. These dynamics have obvious advantages in the use of the multisector model for industrial planning. The multisector model is a medium-term and long-term model. Whereas a short-term model can taken the labor supply and capital stock as given, a long-term model must acknowledge that these are determined endogenously. Changes in the medium-term can be analyzed in the context of long-term structural changes. The structure of this model can be summarized as follow. The difference in domestic and world prices affects industrial structure and the pattern of international trade; domestic output and factor price affect factor demand; factor demand and factor price affect industrial income; industrial income and relative price affect industrial consumption. Technical progress, as measured in terms of total factor productivity and relative price affect input-output coefficients; input-output coefficients and relative price determine the industrial input cost; input cost and import price determine domestic price. The differences in productivity and wage growth among different industries affect the relative price.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.2
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• pp.9-17
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• 2010

Recently, there has been much interest in orthogonal frequency division multiplexing (OFDM) for next generation wireless wideband communication systems. OFDM is a special case of multicarrier transmission, where a single data stream is transmitted over a number of lower-rate subcarriers. One of the main reasons to use OFDM is to increase robustness against frequency-selective fading or narrowband interference. However, in the radio systems it is also important to distortion introduced by high power amplifiers (HPA's) such as solid state power amplifier (SSPA) considered in this paper. Since the signal amplitude of the OFDM system is Rayleigh-distributed, the performance of the OFDM system is significantly degraded by the nonlinearity of the HPA in the OFDM transmitter. In this paper, we propose a canonical piecewise-linear (PWL) model based digital predistorter to prevent signal distortion and spectral re-growth due to the high peak-to-average power ratio (PAPR) of OFDM signal and the nonlinearity of HPA's. Computer simulation on an OFDM system under additive white Gaussian noise (AWGN) channels with QPSK, 16-QAM and 64-QAM modulation schemes and modulator/demodulator implemented with 1024-point FFT/IFFT, demonstrate that the proposed predistorter achieves significant performance improvement by effectively compensating for the nonlinearity introduced by the SSPA.