• 한국정보과학회논문지:시스템및이론
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• 제34권10호
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• pp.502-510
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• 2007

Private Matching은 각기 다른 두 참여자가 가진 데이타의 교집합을 구하는 문제이다. Private matching은 보험사기 방지시스템, 항공기 탑승 금지자 목록 검색, 의료 정보 검색 등에 이용될 수 있으며 다자간의 계산으로 확장하면 전자투표, 온라인 게임 등에도 이용될 수 있다. 2004년 Freedman 등 [1]은 이 문제를 확률적으로 해결하는 프로토콜을 제안하고 악의적인 공격자 모델과 다자간 계산으로 확장하였다. 이 논문에서는 기존의 프로토콜을 결정적(deterministic) 방법으로 개선하여 Semi-Honest 모델에서 결과의 정확성을 보장하는 한편, 이를 악의적인 공격자 모델에 확장하여 신뢰도와 연산속도를 향상 시키는 새로운 프로토콜을 제안한다.

• Structural Engineering and Mechanics
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• 제34권1호
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• pp.15-38
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• 2010

In order to predict the shear strengths of reinforced concrete beams, many deterministic models have been developed based on rules of mechanics and on experimental test results. While the constant and variable angle truss models are known to provide reliable bases and to give reasonable predictions for the shear strengths of members with shear reinforcement, in the case of members without shear reinforcement, even advanced models with complicated procedures may show lack of accuracy or lead to fairly different predictions from other similar models. For this reason, many research efforts have been made for more accurate predictions, which resulted in important recent publications. This paper develops probabilistic shear strength models for reinforced concrete beams without shear reinforcement based on deterministic shear strength models, understanding of shear transfer mechanisms and influential parameters, and experimental test results reported in the literature. Using a Bayesian parameter estimation method, the biases of base deterministic models are identified as algebraic functions of input parameters and the errors of the developed models remaining after the bias-correction are quantified in a stochastic manner. The proposed probabilistic models predict the shear strengths with improved accuracy and help incorporate the model uncertainties into vulnerability estimations and risk-quantified designs.

• 대한전자공학회논문지
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• 제27권4호
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• pp.571-579
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• 1990

A dynamic relocation algorithm for non-deterministic process graph in distributed computer systems is proposed. A method is represented for determining the optimal policy for processing a process tree. A general database query request is modelled by a process tree which represent a set of subprocesses together with their precedence relationship. The process allocation model is based on operating cost which is a function fo selection of site for processing operation, data reduction function and file size. By using expected values of parameters for non-deterministic process tree, the process graph and optimal policy that yield minimum operating cost are determined. As process is relocated according to threshold value and new information of parameters after the execution of low level process for non-deterministic process graph, the assigned state that approximate to optiaml solution is obtained. The proposed algorihtm is heuristic By performing algorithm for sample problems, it is shown that the proposed algorithm is good in obtaining optimal solution.

• 산업경영시스템학회지
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• 제14권23호
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• pp.57-64
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• 1991

The preliminary, advanced and final evaluation of R&D project is essential in order to reduce loss of resource and opportunity and to minimize uncertainty resulting from optimal selection and efficient progress of R&D project. This thesis examined characteristics of deterministic evaluation, economical evaluation, and OR-approach evaluation as theoretical methodology of evaluation of R&D project applicable to food industry in Korea by using scoring method, one of deterministic evaluations. In addition, this thesis divided the evaluation factors for preliminary evaluation of R&D project into 5 groups and 30 factors on basis of the environment of domestic companies and set up the standard of each evaluation factors and contains marking-selecting way. But, generally, the evaluation model by this thesis, as the conditions of the business company environment are different to each other, contents to be set up evaluation factors, evaluation standard and decision method conforming to each the environment of the business companies with referring to as one standard of evaluation project for selecting R&D project.

• ETRI Journal
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• 제45권4호
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• pp.627-635
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• 2023

In vehicular edge computing (VEC) networks, the rapid expansion of intelligent transportation and the corresponding enormous numbers of tasks bring stringent requirements on timely task offloading. However, many tasks typically appear within a short period rather than arriving simultaneously, which makes it difficult to realize effective and efficient resource scheduling. In addition, some key information about tasks could be learned due to the regular data collection and uploading processes of sensors, which may contribute to developing effective offloading strategies. Thus, in this paper, we propose a model that considers the deterministic demand of multiple tasks. It is possible to generate effective resource reservations or early preparation decisions in offloading strategies if some feature information of the deterministic demand can be obtained in advance. We formulate our scenario as a 0-1 programming problem to minimize the average delay of tasks and transform it into a convex form. Finally, we proposed an efficient optimal offloading algorithm that uses the interior point method. Simulation results demonstrate that the proposed algorithm has great advantages in optimizing offloading utility.

• 한국군사과학기술학회지
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• 제24권5호
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• pp.558-568
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• 2021

The existing underwater vehicle controller design is applied by linearizing the nonlinear dynamics model to a specific motion section. Since the linear controller has unstable control performance in a transient state, various studies have been conducted to overcome this problem. Recently, there have been studies to improve the control performance in the transient state by using reinforcement learning. Reinforcement learning can be largely divided into value-based reinforcement learning and policy-based reinforcement learning. In this paper, we propose the roll controller of underwater vehicle based on Deep Deterministic Policy Gradient(DDPG) that learns the control policy and can show stable control performance in various situations and environments. The performance of the proposed DDPG based roll controller was verified through simulation and compared with the existing PID and DQN with Normalized Advantage Functions based roll controllers.

• 한국물환경학회지
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• 제24권2호
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• pp.239-246
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• 2008

In this study, an optimized deterministic water-quality model was constructed to estimate water quality of a river and lake in the upstream basin of a dam. A stochastic water-quality analysis using reliability analysis technique was applied to the model. The model was tested in the 13.9 km reach from Maeil stage station of Kyechun to Hoengsung Dam of Sum River. After finding hydraulic characteristics from nonuniform flow analysis, Broyden-Fletcher-Goldfarb-Shanno (BFGS) optimization technique for model calibration was applied to determine optimum reaction parameters, and model verification was performed based on these. The stochastic model, using Mean First­Order Second­-Moment (MFOSM) and Monte-Carlo methods, was applied to the same reach as the deterministic study. Variations of discharge and water quality in headwater were considered, as well as variations of hydraulic coefficients and reaction coefficients. The statistical results of output variables from MFOSM were similar to those from the Monte-Carlo method. Risk analysis using MFOSM and Monte-Carlo methods presented the probabilities of some locations in the Hoengsung Lake violating existing water-quality standards in terms of DO and BOD.

• 한국농공학회지
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• 제32권E호
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• pp.33-46
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• 1990

Abstract Over 700/0 of the rural land area in Korea is mountainous and small watersheds provide most of the water resources for agricutural use. To provide an appropriate tool for the agricultural water resource development project, SNUA2, a mathematical model for simulating the physical processes governing the precipitation-runoff relationships and predicting the storm and long-term runoff quantities from the small mountainous watersheds was developed. The hydrological characteristics of small mountainous watersheds were reviewed to select appropriate theories for the simulation of the runoff processes, and a deterministic and distributed model was developed. In this, subsurface flows are routed by solving Richard's two dimensional equation, the dynamics of soil moisture contents are simulated by the consideration of phenological factors of canopy plants and surface flows are routed by solving the kinematic wave theory by numerical analysis. As a result of an application test of the model to the Sanglim watershed, peak flow rates of storm runoff were over-estimated by up to 184.2%. The occurence time of peak flow and total runoff volume of storm runoffs simulated were consistent with observed values and the annual runoff volumes were simulated in the error range of less than 5.8%.

• 한국경영과학회지
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• 제41권3호
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• pp.23-36
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• 2016

We consider a model that minimizes the total cost incurred by assigning available weapons to existing targets in order to reduce enemy threats, which is called the weapon target assignment problem (WTAP). This study addresses the stochastic versions of WTAP, in which data, such as the probability of destroying a target, are given randomly (i.e., data are identified with certain probability distributions). For each type of random data or parameter, we provide a stochastic optimization model on the basis of the expected value or scenario enumeration. In particular, when the probabilities of destroying targets depending on weapons are stochastic, we present a stochastic programming formulation with a simple recourse. We show that the stochastic model can be transformed into a deterministic equivalent mixed integer programming model under a certain discrete probability distribution of randomness. We solve the stochastic model to obtain an optimal solution via the mixed integer programming model and compare this solution with that of the deterministic model.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.213-216
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• 1996

R'||'&'||'D project management is a process of decisions concerned with the achievement of goals of objectives. Especially, defense R'||'&'||'D project planning is the key in the successfull management of defense development. The defense project managers are constantly having to perform "what if\ulcorner" exercise, such as what if the project is extended out for an additional cost\ulcorner In this reserch, we developed a schedule-cost analysis model based upon Critical Path Method(CPM) and Venture Evaluation and Review Technique(VERT) for schedule-cost trade off analysis defense R'||'&'||'D projects. In the first step, a deterministic model is developed as a heuristic which deterministic model is developed as a heuristic which determines the schedule extension and reduction cost as a function desired schedule. In the second step, a stochastic network simulation model is developed to analyse the project risk (sucess and failure). The expected time and cost can be determined for desired schedule under the assumptions of stochastic arc data (time and cost) with a various precedence relationships. This model provides the defense R'||'&'||'D managers with an estimated and expected cost for curtailing or extending a project a given amount of time. The effectiveness and efficiency of the proposed methods, a heuristic and stochastic networks simulations, have been demonstrated through examples.