• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.152-152
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• 2022

Only employing historical data limits the estimation of the full distribution of probable Tropical Cyclone (TC) risk due to the insufficiency of samples. Addressing this limitation, this study introduces a semi-physical TC rainfall model that produces spatially and temporally resolved TC rainfall data to improve TC risk assessments. The model combines a statistical-based track model based on the Markov renewal process to produce synthetic TC tracks, with a physics-based model that considers the interaction between TC and the atmospheric environment to estimate TC rainfall. The simulated data from the combined model are then fitted to a probability distribution function to compute the spatially heterogeneous risk brought by landfalling TCs. The methodology is employed in South Korea as a case study to be able to implement a country-scale-based vulnerability inspection from damaging TC impacts. Results show that the proposed model can produce TC tracks that do not only follow the spatial distribution of past TCs but also reveal new paths that could be utilized to consider events outside of what has been historically observed. The model is also found to be suitable for properly estimating the total rainfall induced by landfalling TCs across various points of interest within the study area. The simulated TC rainfall data enable us to reliably estimate extreme rainfall from higher return periods that are often overlooked when only the historical data is employed. In addition, the model can properly describe the distribution of rainfall extremes that show a heterogeneous pattern throughout the study area and that vary per return period. Overall, results show that the proposed approach can be a valuable tool in providing sufficient TC rainfall samples that could be an aid in improving TC risk assessment.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.45-55
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• 2008

The impact on streamflow and groundwater recharge considering future potential climate and land use change was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for a $260.4km^2$ which has been continuously urbanized during the past couple of decades. The model was calibrated and validated with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.8 to 0.7 and 0.7 to 0.5, respectively. The CCCma CGCM2 data by two SRES (Special Report on Emissions Scenarios) climate change scenarios (A2 and B2) of the IPCC (Intergovemmental Panel on Climate Change) were adopted and the future weather data was downscaled by Delta Change Method using 30 years (1977 - 2006, baseline period) weather data. The future land uses were predicted by CA (Cellular Automata)-Markov technique using the time series land use data of Landsat images. The future land uses showed that the forest and paddy area decreased 10.8 % and 6.2 % respectively while the urban area increased 14.2 %. For the future vegetation cover information, a linear regression between monthly NDVI (Normalized Difference Vegetation Index) from NOAA/AVHRR images and monthly mean temperature using five years (1998 - 2002) data was derived for each land use class. The future highest NDVI value was 0.61 while the current highest NDVI value was 0.52. The model results showed that the future predicted runoff ratio ranged from 46 % to 48 % while the present runoff ratio was 59 %. On the other hand, the impact on runoff ratio by land use change showed about 3 % increase comparing with the present land use condition. The streamflow and groundwater recharge was big decrease in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.107-120
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• 2010

The effect of potential future climate change on the inflow of agricultural reservoir and its impact to downstream streamflow by reservoir operation for paddy irrigation water was assessed using the SLURP (semi-distributed land use-based runoff process), a physically based hydrological model. The fundamental input data (elevation, meteorological data, land use, soil, vegetation) was collected to calibrate and validate of the SLURP model for a 366.5 $km^2$ watershed including two agricultural reservoirs (Geumgwang and Gosam) located in Anseongcheon watershed. Then, the CCCma CGCM2 data by SRES (special report on emissions scenarios) A2 and B2 scenarios of the IPCC (intergovernmental panel on climate change) was used to assess the future potential climate change. The future weather data for the year, m ms, m5ms and 2amms was downscaled by Change Factor method through bias-correction using 3m years (1977-2006) weather data of 3 meteorological stations of the watershed. In addition, the future land uses were predicted by modified CA (cellular automata)-Markov technique using the time series land use data fromFactosat images. Also the future vegetation cover information was predicted and considered by the linear regression between monthly NDVI (normalized difference vegetation index) from NOAA AVHRR images and monthly mean temperature using eight years (1998-2006) data.

• ETRI Journal
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• v.20 no.3
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• pp.251-271
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• 1998

It is well known that if usage parameter control/network parameter control (UPC/NPC) functions are used together with a cell loss priority control scheme in ATM networks, the measurement phasing problem can occur. This makes it difficult for a network provider to define and commit the cell loss ratio as a QoS parameter. To solve the problem, we propose a new UPC/NPC algorithm. By using the proposed UPC/NPC algorithm, we can define the cell loss ratios for CLP = 0 and CLP = 0+1 cell streams without the measurement phasing problem under any conditions. We analyzed the performance of the proposed UPC/NPC algorithm. Using a discrete time model for the UPC/NPC architecture with a discrete-time semi-Markov process (DSMP) input model, we obtained the cell discarding probabilities of CLP = 0 and CLP = 0+1 cells streams and showed that more CLP = 0 cells are accepted compared to what was proposed in ITU-T.

• IE interfaces
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• v.25 no.4
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• pp.450-457
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• 2012

This study addresses the call admission control(CAC) problem for OFDMA wireless communication systems in which both subcarriers and power should be considered together as the system resources. To lessen the exccessive allocation of radio resources for protecting handoff calls, the proposed CAC allows the less data rate than their requirements to handoff calls. The CAC problem is formulated as a semi-Markov decision process(SMDP) with constraints on the blocking probabilities of handoff calls. Some extensive experiments are conducted to show the usefulness of the proposed CAC model.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.181-183
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• 2006

This paper proposes an intelligent decision framework for update of the environment model using GSPN(generalized stochastic petri nets). The GSPN has several advantages over direct use of the Markov Process. The modeling, analysis, and performance evaluation are conducted on the mathematical basis. By adopting the probabilistic approach, our decision framework helps the robot to decide the time to update the map. The robot navigates autonomously for a long time in dynamic environments. Experimental results show that the proposed scheme is useful for service robots which work semi-permanently and improves dependability of navigation in dynamic environments.

• The Journal of the Acoustical Society of Korea
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• v.18 no.1
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• pp.53-60
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• 1999

This paper is a study on the korean broadcasting speech recognition. Here we present the methods for the large vocabuary continuous speech recognition. Our main concerns are the language modeling and the search algorithm. The used acoustic model is the uni-phone semi-continuous hidden markov model and the used linguistic model is the N-gram model. The search algorithm consist of three phases in order to utilize all available acoustic and linguistic information. First, we use the forward Viterbi beam search to find word end frames and to estimate related scores. Second, we use the backword Viterbi beam search to find word begin frames and to estimate related scores. Finally, we use A/sup */ search to combine the above two results with the N-grams language model and to get recognition results. Using these methods maximum 96.0% word recognition rate and 99.2% syllable recognition rate are achieved for the speaker-independent continuous speech recognition problem with about 12,000 vocabulary size.

• Journal of Korea Water Resources Association
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• v.43 no.3
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• pp.309-323
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• 2010

As climate changes and abnormal climates have drawn research interest recently, many countries utilize the GCM, which is based on SRES suggested by IPCC, to obtain more accurate forecast for future climate changes. Especially, many research attempts have been made to simulate localized geographical characteristics by using RCM with the high resolution data globally. To evaluate the impacts of climate and landuse change on water resources in the Han-river basin, we carried out the procedure consisting of the CA-Markov Chain, the Multi-Regression equation using two independent variables of temperature and rainfall, the downscaling technique based on the RegCM3 RCM, and SLURP. From the CA-Markov Chain, the future landuse change is forecasted and the future NDVI is predicted by the Multi-Regression equation. Also, RegCM3 RCM 50 sets were generated by the downscaling technique based on the RegCM3 RCM provided by KMA. With them, 90 year runoff scenarios whose period is from 2001 to 2090 are simulated for the Han-river basin by SLURP. Finally, the 90-year simulated monthly runoffs are compared with the historical monthly runoffs for each dam in the basin. At Paldang dam, the runoffs in September show higher increase than the ones in August which is due to the change of rainfall pattern in future. Additionally, after exploring the impact of the climate change on the structure of water circulation, we find that water management will become more difficult by the changes in the water circulation factors such as precipitation, evaporation, transpiration, and runoff in the Han-river basin.

• The KIPS Transactions:PartC
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• v.8C no.2
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• pp.173-181
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• 2001

하드웨어 기술의 발전으로 인해 컴퓨터 하드웨어의 결함 발생률은 상수 값이거나 점차 작아지는 경향이 있다. 반면에 하드웨어에 탑재된 소프트웨어의 복잡성 및 크기는 이전에는 상상할 수 없을 정도로 방대해져가고 있기 때문에, 소프트웨어의 결함 발생으로 인한 컴퓨터 시스템의 장애 발생 가능성은 점차 더 높아지고 있다. 본 논문에서는 Active/Active 클러스터 시스템의 가용도 개선을 위해서 소프트웨어적인 결함 발생을 미연에 방지할 수 있는 능동적 결함허용 기법인 소프트웨어 재활(rejuvenation) 방법에 대하여 연구하였다. 소프트웨어 재활 과정 및 여분서버로 작업전이(switchover) 과정을 semi-Markov 프로세스로 모델링 한 후, 수학적 분석을 통해 구한 Active/Active 클러스터 시스템의 bud형 상태 확률을 이용하여, 다양한 운영 조건하의 가용도 및 손실비용을 계산하였으며, 이를 통하여 소프트웨어 재활을 통한 Active/Active 클러스터 시스템의 가용도 개선 가능성을 확인하였다.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2003.12a
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• pp.141-145
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• 2003

We propose the model of Software Rejuvenation methodology, which is applicable for survivability. Software rejuvenation is a proactive fault management technique and being used in fault tolerant systems as a cost effective technique for dealing with software faults. Survivability focuses on delivery of essential services and preservation of essential assets, even systems are penetrated and compromised. Thus, our objective is to detect the intrusions in a real time and survive in face of such attacks. As we deterrent against an attack in a system level, the Intrusion tolerance could be maximized at the target environment. We address the optimal time to execute ad hoc software rejuvenation and we compute it by using the semi Markov process. This is one way that could be really frustrated and deterred the attacks, as the attacker can't make their progress. This Software Rejuvenation method can be very effective under the assumption of unknown attacks. In this paper, we compute the optimum time to perform an ad hoc Software Rejuvenation through intrusions.