• Journal of the Korea Society for Simulation
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• v.28 no.1
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• pp.23-39
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• 2019

The use of drone-bots is demanded in times regarding the reduction of military force, the spread of the life-oriented thought, and the use of innovative technology in the defense through the fourth industrial revolution. Especially, the drone's surveillance and reconnaissance are expected to play a big role in the future battlefield. However, there are not many cases in which the concept of operation is studied scientifically. In this study, We propose search algorithms for reconnaissance drone through simulation analysis. In the simulation, the drone and target move linearly in continuous space, and the target is moving adopting the Random-walk concept to reflect the uncertainty of the battlefield. The research investigates the effectiveness of existing search methods such as Parallel and Spiral Search. We analyze the probabilistic analysis for detector radius and the speed on the detection probability. In particular, the new detection algorithms those can be used when an enemy moves toward a specific goal, PS (Probability Search) and HS (Hamiltonian Search), are introduced. The results of this study will have applicability on planning the path for the reconnaissance operations using drone-bots.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.9-14
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• 2011

This paper presents a new fast motion estimation method where search ranges are determined by the probabilities of motion vector differences (MVDs), which is an adaptive/dynamic search range (ASR) method. The MVDs' distribution is investigated and its parameter is estimated by the maximum likelihood estimator. With the estimated distribution, we show that the search ranges can be efficiently restricted by a prefixed probability for MVDs. Experimental results showed that the performance of the proposed method is very similar to that of the full search algorithm in PSNR but it enables significant reduction in the computational complexity. In addition, they revealed that the proposed method determine the search ranges much more efficiently than the conventional ASR methods.

• The Korean Journal of Applied Statistics
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• v.14 no.2
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• pp.401-413
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• 2001

이차원 분할자료에 대해서 행과 열의 관계를 저차원상에 시각적으로 표현하는 탐색적대응분석에 대하여 붓스트랩방법의 사용가능성을 살펴보았다. 기존의 탐색적 면만이 강조되어 왔던 대응분석에서 좌표점의 변이와 좌표점간의 거리에 대한 통계적 추론을 붓스트랩방법으로 해결할 수 있음을 보이고 또한 좌표축의 설명력에 대하여 붓스트랩신뢰구간의 포함확률의 일치성을 모의실험을 통해 제시하였다.

• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.43-49
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• 2015

Maximum lock-on distance in tactical guidance missile using seeker image is estimated by seeker's FOV, resolution and performance of tracking algorithm. In case, a missile is launched beyond the maximum lock-on distance, the missile is guided by INS pure navigation until it enters the lock-on possible zone. However, the probability of a target's existence within seekers images decreases as flight time goes by. Therefore, it is crucial to determine the distance that satisfies a certain target existence probability (TEP) and the maximum lock-on distance in order for an operator to take over the navigation role between two distances. In this paper, simulation which can analyse TEP in tactical guided missile seeker image is designed.

• Journal of KIISE:Information Networking
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• v.37 no.2
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• pp.162-165
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• 2010

In the paper, we propose an algorithm that significantly reduces unnecessary computations, while keeping prediction quality almost similar to that of the full search. In the proposed algorithm, we can reduces only unnecessary computations efficiently by taking different search patterns and error criteria of block matching according to distribution probability of motion vectors. Our algorithm takes only 20~30% in computational amount and has decreased prediction quality about 0~0.02dB compared with the fast full search of the H.264 reference software. Our algorithm will be useful to real-time video coding applications using MPEG-2/4 AVC standards.

• Journal of the Korea Society for Simulation
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• v.21 no.3
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• pp.71-78
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• 2012

This research discusses the application of the control variables to achieve a more precise estimation for the target response in queueing network simulation. The efficiency of control variable method in estimating the response depends upon how we choose a set of control variables strongly correlated with the response and how we construct a function of selected control variables. For a class of queuing network simulations, the random variables that drive the simulation are basically the service-time and routing probability random variables. Most of applications of control variable method focus on utilization of the service time random variables for constructing a controlled estimator. This research attempts to suggest a controlled estimator which uses these two kinds of random variables and explore the efficiency of these estimators in estimating the reponses for computer network system. Simulation experiments on this model show the promising results for application of routing probability control variables. We consider the applications of the routing probability control variables to various simulation models and combined control variables using information of service time and routing probability together in constructing a control variable as future researches.

• Proceedings of the Korean Society for Information Management Conference
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• 1994.12a
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• pp.15-18
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• 1994

본 연구에서는 불논리검색의 단점을 보완하기 위한 가장 강력한 검색 모형인 퍼지검색과 확률검색의 효율을 불논리검색과 상호비교하였다. 실험데이터로 정보학 분야의 한국어 test collection인 KT Test Set을 이용하였고 색인어와 색인어의 문헌내 출현빈도를 바탕으로 퍼지시소러스를 생성하여 시소러스의 NT, BT로 탐색식을 확장한 다음 각각에 대해 3가지 검색을 행하고 검색효율을 평균재현율과 평균정확률로 측정하였다. 실험결과 검색효율은 재현율에서는 확률검색, 불논리검색, 퍼지검색 순으로. 정확률에서는 퍼지검색, 확률검색, 불논리검색 순으로 나타났다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.800-802
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• 2003

이 논문에서는 웹 기반의 하이퍼미디어 교육시스템에서 이산 확률 분포 함수와 사용자 프로파일 기반의 동적 적응 모델을 제안하였다. 이 모델은 응용 영역을 동적 적응 객체의 가중치 방향성 그래프로 표현하며 사용자 행위를 이산 확률 함수를 동적으로 구축하는 접근 방식을 이용하여 모델링 한다. 제안한 확률적 해석은 웹 미디어 구조에서 사용자의 탐색 행위를 추적하여 사용자 행위에 대한 잠재적 속성을 나타내는데 사용될 수 있다. 이러한 접근 방식은 사용자에게 가장 알맞은 프로파일을 동적으로 할당할 수 있다.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1539-1545
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• 2017

In this paper, we analyze and discuss the trend of the probability and statistics problems that have been made in the public secondary school teacher employment exam for mathematics teachers. In order to properly teach the national mathematics curriculum in 2015 in terms of content and function, we investigate the probability and statistics contents that a mathematics teachers should know. We also analyze the contents and trends of the items that have been submitted for 15 years in public secondary school teacher employment exam, and discuss the contents, scope, level and direction of the future contents. In conclusion, considering the significance of the Big Data in the 4th industrial revolution, the problems of statistical thinking of data and probability, exploratory data analysis, sample survey, and statistical inference are needed more.

• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.23-34
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• 2023

The purpose of this paper is to review global stochastic optimization algorithms(GSOA) in case binary response experimentation is used and to compare the performances of them. GSOAs utilise estimator of probability of success $\^p$ instead of population probability of success p, since p is unknown and only known by its estimator which has stochastic characteristics. Hill climbing algorithm algorithm, simple random search, random search with random restart, random optimization, simulated annealing and particle swarm algorithm as a population based algorithm are considered as global stochastic optimization algorithms. For the purpose of comparing the algorithms, two types of test functions(one is simple uni-modal the other is complex multi-modal) are proposed and Monte Carlo simulation study is done to measure the performances of the algorithms. All algorithms show similar performances for simple test function. Less greedy algorithms such as Random optimization with Random Restart and Simulated Annealing, Particle Swarm Optimization(PSO) based on population show much better performances for complex multi-modal function.