• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.3
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• pp.332-339
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• 2013

The network nodes in a tactical network moves continuously and due to the physical and electronic obstacles, the connections are not always available. Due to the frequent disconnections, it is hard to discover the path among the nodes in a DTN. According to PROPHET(Probabilistic Routing Protocol using History of Encounters and Transitivity), one of the most well-known DTN routing protocols, a DTN node determines whom to forward a packet according to the packet delivery probability. From the viewpoint of a node, the packet delivery probability of another node is degraded while the nodes are disconnected whereas it is improved when they encounter. In this paper, we enhance the algorithm estimating the packet probability by considering the encounter count as an additional parameter. Our algorithm prefers the node that encounters the destination more frequently in selecting the next hop toward the destination. We evaluated the performance of our algorithm by simulating military operations using a DTN-dedicated simulator. Through the simulations, we show that our proposed algorithm achieve higher packet delivery ratio with similar overhead compared with PROPHET.

• Journal of the Korea Society for Simulation
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• v.30 no.1
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• pp.43-54
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• 2021

Since COVID-19 (Severe acute respiratory syndrome coronavirus type 2, SARS-Cov-2) was first discovered at the end of 2019, it has spread rapidly around the world. This study introduces an agent-based simulation model representing COVID-19 spread in South Korea to investigate the effect of detect level (contact tracing) on the virus spread. To develop the model, related data are aggregated and probability distributions are inferred based on the data. The entire process of infection, quarantine, recovery, and death is schematically described and the interaction of people is modeled based on the traffic data. A composite logistic functions are utilized to represent the compliance of people to the government move control such as social distancing. To demonstrate to effect of detect level on the virus spread, detect level is changed from 0% to 100%. The results indicate active contact tracing inhibits the virus spread and the inhibitory effect increases geometrically as the detect level increases.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.367-370
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• 2017

This paper proposes a method for selecting efficient relay nodes in stochastic DTN model. Delay Tolerant Network (DTN) uses the Carry and Forward method, which creates a bundle layer for efficient communication, selects relay nodes between different networks and heterogeneous networks, and forwards messages. DTN is basically composed of mobile nodes so DTN has no fixed routing route and it has long latency due to intermittent connection. Therefore, the nodes constituting the DTN necessarily have the characteristics to store the messages, and the capacity of the stored messages and nodes affects the performance of the network. Stochastic DTN model proposed a Markov model that changes randomly over time to analyze the performance of DTN. In this paper, we use stochastic message distribution and node contact probabilities using contact time analyzed through message generation and extinction in order to select efficient relay nodes in stochastic DTN model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.41-43
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• 2022

In order to prevent and block infectious diseases caused by the recent COVID-19 pandemic, non-contact biometric information acquisition and analysis technology is attracting attention. The invasive and attached biometric information acquisition method accurately has the advantage of measuring biometric information, but has a risk of increasing contagious diseases due to the close contact. To solve these problems, the non-contact method of extracting biometric information such as human fingerprints, faces, iris, veins, voice, and signatures with automated devices is increasing in various industries as data processing speed increases and recognition accuracy increases. However, although the accuracy of the non-contact biometric data acquisition technology is improved, the non-contact method is greatly influenced by the surrounding environment of the object to be measured, which is resulting in distortion of measurement information and poor accuracy. In this paper, we propose a context-based bio-signal modeling technique for the interpretation of personalized information (image, signal, etc.) for bio-information analysis. Context-based biometric information modeling techniques present a model that considers contextual and user information in biometric information measurement in order to improve performance. The proposed model analyzes signal information based on the feature probability distribution through context-based signal analysis that can maximize the predicted value probability.

• Journal of the Korean Geophysical Society
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• v.4 no.1
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• pp.57-69
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• 2001

We have carried out a nondestructive close examination for the purpose of the structural safety diagnosis of the Three-Story Pagoda(Seokga Pagoda) in Bulkuk temple in the city of Kyungju, Kyungbuk, Korea. Ultrasonic wave velocities were measured at 456 points of the pagoda comprising 44 blocks to estimate the mechanical properties of rock blocks constituting the pagoda. The measured velocities have the range of 1217 to 4403 m/sec with the average of 3227 m/sec. The empirical relationship between the ultrasonic velocity and the uniaxial compressive strength yielded the estimation of strength of each block, ranging from 134 to 844 kg/cm^2 and averaging 463 kg/cm^2. With an assumption that the strength of each block is described as a random variables having a normal distribution, we calculated the probability of failure of rock blocks of the pagoda. Our investigation revealed that the probability of the structural failure due to the weight of higher blocks is very low. However, the probability of partial failure around contact area is substantial, which is consistent with the appearance that edges and the corners of some blocks were broken off. The platform under the body of the pagoda appeared to be structurally weak as the probability of tensile failure of the lower platform is up to 18%, and diagonal fractures are shown where the probability of failure is high.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.135-140
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• 2007

이탈 고객 예측은 데이터 마이닝에서 다루는 주요한 문제 중에 하나이다. 이탈 고객 예측은 일종의 분류(classification) 문제로 의사결정나무추론, 로지스틱 회귀분석, 인공신경망 등의 기법이 많이 활용되어왔다. 일반적으로 이탈 고객 예측을 위한 모델은 고객의 인구통계학적 정보와 계약이나 거래 정보를 입력변수로 하여 이탈 여부를 목표변수로 보는 형태로 분류 모델을 생성하게 된다. 본 연구에서는 고객과의 지속적인 접촉으로 발생되는 추가적인 사건 정보를 활용하여 연관성 규칙을 생성하고 이 결과를 기존의 방식으로 생성된 분류 모델과 결합하는 이탈 고객 예측 방법을 제시한다. 제시한 방법의 유용성을 확인하기 위해서 특정 국내 신용카드사의 실제 데이터를 활용하여 실험을 수행하였다. 실험 결과 제시된 방법이 기존의 전통적인 분류 모델에 비해서 향상된 성능을 보이는 것을 확인할 수 있었다. 제시된 예측 방법의 장점은 기존의 이탈 예측을 위한 입력 변수들 이외에 고객과 회사간의 접촉을 통해서 생성된 동적 정보들을 통합적으로 활용하여 예측 정확도를 높이고 실시간으로 이탈 확률을 갱신할 수 있다는 점이다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.105-106
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• 2015

본 논문에서는 DTN(Delay Tolerant Network) 환경에서 효율적인 메시지 전달을 위해 확률적으로 중계 노드를 선택하는 기법을 제안한다. DTN은 종단 간 연결이 불확실한 네트워크에서의 통신을 Store-Carry-Forward 방식을 사용하여 메시지를 목적 노드에 전달한다. 또한 종단 간 연결이 불확실한 상황에서도 중계 노드를 통해 메시지를 목적 노드에 전달하여 높은 전송률을 보장한다. 하지만 에피데믹(Epidemic) 라우팅이나 Spray and Wait 라우팅과 같은 기존 다중 복사 라우팅 알고리즘은 접촉한 모든 노드에게 메시지를 복사하여 메시지 복사로 인한 오버헤드가 높아진다. 반면에 PROPHET 라우팅과 같은 단일 복사 알고리즘은 적은 오버헤드를 발생시키지만 중계 노드 수 감소로 인한 메시지 전송률 감소 현상이 나타난다. 본 논문에서 제안하는 알고리즘은 기존 DTN 라우팅의 문제점을 보완하기 위해 확률적으로 노드 분포를 분석하여 현재 네트워크에 효율적인 메시지 복사 방식을 선택하여 작동한다. 본 논문에서는 제안하는 알고리즘이 기존 DTN 라우팅 알고리즘과 오버헤드와 전송률을 비교하여 더 효율적임을 증명한다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.3
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• pp.209-219
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• 2013

Epidemiological models on disease spread attempt to simulate disease transmission and associated control processes and such models contribute to greater understanding of disease spatial diffusion through of individual's contacts. The objective of this study is to develop an agent-based modeling(ABM) approach that integrates geographic information systems(GIS) to simulate the spread of FMD in spatial environment. This model considered three elements: population, time and space, and assumed that the disease would be transmitted between farms via vehicle along the roads. The model is implemented using FMD outbreak data in Andong city of South Korea in 2010 as a case study. In the model, FMD is described with the mathematical model of transmission probability, the distance of the two individuals, latent period, and other parameters. The results show that the GIS-agent based model designed for this study can be easily customized to study the spread dynamics of FMD by adjusting the disease parameters. In addition, the proposed model is used to measure the effectiveness of different control strategies to intervene the FMD spread.

• Journal of the Korean Society for Railway
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• v.10 no.6
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• pp.806-811
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• 2007

The derailment is defined as phenomena in which the wheels run off the rail due to inordinate lateral force generated when wheel flange contacts with the rail. Derailment coefficient is typical standard assessing running safety and derailment. The traditional method measuring by strain gage adhered to wheels is very complicated and easy to fail. It also requires too much cost and higher measurement technique. Therefore it can hardly ensure safety because we can't confirm at which time we need to identify safety. In this paper, we principally researched the method measuring easily wheel load generated by contacts between wheel flange and the rail, and lateral force. Correlation of vibration and displacement which was related physical amounts of wheel load and lateral force, was investigated and analyzed through analysis, experiment and measurement. And it is presents new measurement method of derailment coefficient which can estimate derailment possibility only by movement of vibration and displacement, by which we understand the rate for acceleration and displacement to contribute wheel load and lateral force and compare actual data of wheel load and lateral force measured from wheel.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.635-642
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• 2014

In this paper, an efficient technique is developed to predict failure probability of three failure modes(case rupture, fracture and bolt breakage) related to solid rocket motor case due to the inner pressure during the mission flight. The overall procedure consists of the steps: 1) design parameters affecting the case failure are identified and their uncertainties are modelled by probability distribution, 2) combustion analysis in the interior of the case is carried out to obtain maximum expected operating pressure(MEOP), 3) stress and other structural performances are evaluated by finite element analysis(FEA), and 4) failure probabilities are calculated for the above mentioned failure modes. Axi-symmetric assumption for FEA is employed for simplification while contact between bolted joint is accounted for. Efficient procedure is developed to evaluate failure probability which consists of finding first an Most Probable Failure Point(MPP) using First-Order Reliability Method(FORM), next making a response surface model around the MPP using Latin Hypercube Sampling(LHS), and finally calculating failure probability by employing Importance Sampling.