• Journal of the military operations research society of Korea
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• v.25 no.1
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• pp.160-168
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• 1999

This research focussed on developing a hit probability model for polygonal target to increase the survivability of weapon systems by its shape design. First, we defined the delivery errors and derived functions for these errors based on the assumption of bivariate normal distribution, and the derived functions for probability of shot hitting of various shapes of polygonal target. Also, we developed computer program for computation of the probability of hitting a general n-sided polygon and we have shown a sample run output. The model could be used to improve the survivability from design phase by designing optimal polygonal shape of weapon system.

• Journal of the Korea Society of Computer and Information
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• v.20 no.8
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• pp.1-6
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• 2015

The MapReduce Program of Hadoop Distributed File System operates on any unspecified nodes due to distributed-parallel process and block replicate for data stability. Since it is difficult to guarantee the cache locality when a Solid State Drive is used as a cache in hadoop, cache hit-rate is decreased. In this paper, we suggest a method to improve cache hit rate by pre-loading the input data of the MapReduce onto the SSD cache. To perform this method, we estimated the blocks that are used on each node by using capacity scheduler and block metadata. Eventually we could increase the performance of SSD cache by loading the blocks onto SSD cache before the Map Task run.

• Journal of Environmental Science International
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• v.28 no.1
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• pp.19-35
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• 2019

This study investigates the performance of four Bayesian methods, Random Walk Metropolis (RWM), Hit-And-Run Metropolis (HARM), Adaptive Mixture Metropolis (AMM), and Population Monte Carlo (PMC), for estimating the parameters and uncertainties of probability rainfall distribution, and the results are compared with those of conventional parameter estimation methods; namely, the Method Of Moment (MOM), Maximum Likelihood Method (MLM), and Probability Weighted Method (PWM). As a result, Bayesian methods yield similar or slightly better results in parameter estimations compared with conventional methods. In particular, PMC can reduce parameter uncertainty greatly compared with RWM, HARM, and AMM methods although the Bayesian methods produce similar results in parameter estimations. Overall, the Bayesian methods produce better accuracy for scale parameters compared with the conventional methods and this characteristic improves the accuracy of probability rainfall. Therefore, Bayesian methods can be effective tools for estimating the parameters and uncertainties of probability rainfall distribution in hydrological practices, flood risk assessment, and decision-making support.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.420-425
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• 2009

In this paper, image detection and recognition algorithms are studied with respect to embedded carrier system. There are many suggested techniques to detect and recognize objects. But they have the propensity to need much calculation for high hit rate. Advanced and modified method needs to study for embedded systems that low power consumption and real time response are requested. The proposed methods were implemented using Intel(R) Open Source Computer Vision Library provided by Intel Corporation. And they run and tested on embedded system using a ARM920T processor by cross-compiling. They showed 1.6sec response time and 95% hit rate and supported the automated moving carrier system smoothly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.629-631
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• 2010

Using carefully assembled sets of IDs based on the cryptographic principle of secret shares, we can create RFID tags that yield virtually no information to casual "hit-and-run" attackers, but only reveal their true ID after continuous and undisturbed reading from up-close something that can hardly go unnoticed by an item's owner. In this paper, we analyses the practical issues of cryptography for RFID privacy with lightweight method.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.218-233
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• 2022

The long-term (1986~2020) predictability of the number of days of heat and cold damages for each growth stage of soybean is evaluated using the daily maximum and minimum temperature (Tmax and Tmin) data produced by Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF). The Predictability evaluation methods for the number of days of damages are Normalized Standard Deviations (NSD), Root Mean Square Error (RMSE), Hit Rate (HR), and Heidke Skill Score (HSS). First, we verified the simulation performance of the Tmax and Tmin, which are the variables that define the heat and cold damages of soybean. As a result, although there are some differences depending on the month starting with initial conditions from January (01RUN) to May (05RUN), the result after a systematic bias correction by the Variance Scaling method is similar to the observation compared to the bias-uncorrected one. The simulation performance for correction Tmax and Tmin from March to October is overall high in the results (ENS) averaged by applying the Simple Composite Method (SCM) from 01RUN to 05RUN. In addition, the model well simulates the regional patterns and characteristics of the number of days of heat and cold damages by according to the growth stages of soybean, compared with observations. In ENS, HR and HSS for heat damage (cold damage) of soybean have ranged from 0.45~0.75, 0.02~0.10 (0.49~0.76, -0.04~0.11) during each growth stage. In conclusion, 01RUN~05RUN and ENS of PNU CGCM-WRF Chain have the reasonable performance to predict heat and cold damages for each growth stage of soybean in South Korea.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.11a
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• pp.90-95
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• 2004

During the past 50 years methods for predicting wave overtopping of coastal structures have coastal structures have continuously been developed Wave overtopping is one of the most important processes for the design of seawalls. The term 'wave overtopping' is used here to refer to the processes where waves hit a sloping structure run up the slope and, if the crest level of the slope is lower than the highest run up level, overtop the structure. Wave overtopping is dependent on the processes associated with breaking wave. The Numerical model is based on Navier-Stokes equation and Marker-Density Function of method for nonlinear free-surface flow by Miyata & Park(1995). The influence of how the slopes of seawalls, wave type and crest freeboard affect overtopping discharges has been investigated. The research of study using the new development nonlinear free-surface flow numerical model SOLA-VOF are presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.224-240
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• 1996

It is common sense for at least one or more levels of cache memory to be used in these day's computer systems. In this paper, the impact of the internal cache memory organization on the performance of the computer is investigated by using a simulator program, which is wirtten by authors and run on SUN SPARC workstation, with several real execution, with several real execution trace files. 280 cache organizations have been simulated using n-way set associative mapping and LRU(Least Recently Used) replacement algorithm with write allocation policy. As a result, 16-way setassociative cache is the best configuration, and when we select 256KB cache memory and 64 byte line size, the bus traffic ratio was decreased compared to that of the noncache system so that a single bus could support almost 7 processors without any delay and degradationof high ratio(hit ratio was 99.21%). The smaller the line size we choose, the little lower hit ratio we can get, but the more processors can be supported by a single bus(maximum 18 processors). Therefore, using a proper cache memory organization can make a single bus structure be able to support multiple processors without any performance degradation.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.3
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• pp.170-177
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• 2007

In this study, the long-term predictability of El Nino and La Nina events of Pusan National University Coupled General Circulation Model(PNU/CME CGCM) developed from a Research and Development Grant funded by Korea Meteorology Administration(KMA) was examined in terms of the correlation coefficients of the sea surface temperature between the model and observation and skill scores at the tropical Pacific. For the purpose, long-term global climate was hindcasted using PNU/CME CGCM for 12 months starting from April, July, October and January(APR RUN, JUL RUN, OCT RUN and JAN RUN, respectively) of each and every years between 1979 and 2004. Each 12-month hindcast consisted of 5 ensemble members. Relatively high correlation was maintained throughout the 12-month lead hindcasts at the equatorial Pacific for the four RUNs starting at different months. It is found that the predictability of our CGCM in forecasting equatorial SST anomalies is more pronounced within 6-month of lead time, in particular. For the assessment of model capability in predicting El Nino and La Nina, various skill scores such as Hit rates and False Alarm rate are calculated. According to the results, PNU/CME CGCM has a good predictability in forecasting warm and cold events, in spite of relatively poor capability in predicting normal state of equatorial Pacific. The predictability of our CGCM was also compared with those of other CGCMs participating DEMETER project. The comparative analysis also illustrated that our CGCM has reasonable long-term predictability comparable to the DEMETER participating CGCMs. As a conclusion, PNU/CME CGCM can predict El Nino and La Nina events at least 12 months ahead in terms of NIino 3.4 SST anomaly, showing much better predictability within 6-month of leading time.

• Journal of Ocean Engineering and Technology
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• v.19 no.3
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• pp.18-24
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• 2005

Wave overtopping is one of the most important processes for the design of seawalls. The term "wave overtopping" is used here to refer to the processes where waves hit a sloping structure run up the slope and, if the crest level of the slope is lower than the highest run up level, overtop the structure. Wave overtopping is dependent on the processes associated with breaking wave. A numerical model based on Navier-Stokes equation and the Marker-density function for predicting wave overtopping of coastal structures is developed in this paper. In order to evaluate the present model, two simulations are tested. One is overflow without waves at vertical seawall, and the other is wave overtopping at sloping seawalls.