• Proceedings of the Korean Nuclear Society Conference
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• 2004.10a
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• pp.99-100
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• 2004

AMBIDEXTER-NEC의 천이노심은 $^{Nat}Th$과 $^{Nat}U$의 주입만으로 전 출력의 Break-even 노심에 도달하기위한 중간 단계이다. 선행연구에서 수행한 전 출력노심인 평형노심의 핵종수밀도에 도달하기 위해서 평형노심에서의 기저물질, 잠재핵분열성물질, 핵분열물질의 수밀도를 각 SEU-기반, Pu-기반, ADS-기반에서 그대로 유지하여 초기노심을 구성하였다. 또 각 시나리오에 대해 최대첨두출력과 원자로의 안전성을 고려해 Excess Reactivity를 5mk 내에서 초기노심을 결정하였다. 각 노심은 주 핵분열성물질 $^{235}U$, $^{239}Pu$ 및 $^{233}U$의 핵반응단면적 특성에 따라 평균 전환율이 각각 0.95, 0.83 및 1 .21 로서 핵연료물질의 적절한 선택만으로도 전환로, 연소로 및 증식로로 설계할 수 있음을 보여준다. 이러한 $Th/^{233}U$, U/Pu 핵연료주기를 사용하는 AMBIDEXTER-NEC 용융염핵연료 원자로의 초기노심에서 시작한 천이노심은 평형노심에장전할 충분한 $^{233}U$ 양을 확보해야 하므로 천이노심의 목표는 평형노심 $^{233}U$의 요구량에 최소한의 기간에 가장 적은 외부주입을 통해 도달하는 것이다. 천이노심에서 임계가 유지되는 AMBIDEXTER-NEC 원자로시스템의 3군 핵종변환 코드인 HELIOS-SQUID-AMBIBURN 체제를 개발하였고 그림 1.에 나타내었다. 이 알고리즘은 각 초기노심 중원소의 미시단면적, 중원소를 제외한 원소들의 거시단면적, 임계도를 만족하는 중성자속 및 외부주입율을 계산하여 SQUID 및 AMBIBURN 입력자료를 제공한다. 또한 일정시간 중원소의 핵종농도, 외부주입율과 중성자속이 일정하다는 가정 하 에 반복수행 하고 SEU-기반과 Pu-기반의 경우에는 각각 핵변환을 거쳐 재순환되는 $^{233}U$ 및 $^{239}Pu$의 양을 바로 주입하는 최대재순환 경우와 평형노심 요구 장전량에 이를 때까지 시설 내 저장하는 최소재순환 경우로 상황을 모사하였다. 그림 2 는 각 시나리오별 초기노심에서부터 200FPD까지 단위 용융염 체적당 $^{233}U$의 수밀도 시간변화를 나타낸 것이다. 그림을 보면 50일 이후부터는 수밀도의 변화가 일정한 기울기를 보이고 있고 재처리공정에서 $^{233}Pa$를 분리하는 최소재순환의 경우에는 최대재순환보다 2-3%정도에 지나지않아 그림에서 나타내지않았다. SEU-기반 및 Pu-기반에서 $^{233}U$의 증가율이 각각 2.54E+13, 2.81E+13 #/cc/d 로 Pu 기반이 조금 더 큰 증가율을 나타내고 있지만 평형노심 농도 1.04E+20 #/cc/d 에 도달하기 위해서는 두 경우 모두 매우 긴 시간이 걸릴 것을 예상할 수 있다. 요컨대 250MWth AMBIDEXTER-NEC가 평형노심을 이루기 위해 필요로 하는 $^{233}U$을 생산하는데 제안한 SEU-기반, Pu-기반 시나리오는 천이노심주기기간이 전형적인 원자로 수명 3-40년 보다 매우 큰 것으로 나타났다. 따라서 장전될 $^{233}U$의 확보를 위한 최적옵션은 초기노심부터 ADS와 같은 외부생산시설로부터 전량을 공급 받아 운전하는 것이라 판단된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.630-637
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• 2018

Harmony search (HS) is a recently developed metaheuristic optimization algorithm. HS is inspired by the process of musical improvisation and repeatedly searches for the optimal solution using three operations: random selection, memory recall (or harmony memory consideration), and pitch adjustment. HS has been applied by many researchers in various fields. The increasing complexity of real-world optimization problems has created enormous challenges for the current technique, and improved techniques of optimization algorithms and HS are required. We propose an improved clustering harmony search (ICHS) that uses a clustering technique to group solutions in harmony memory based on their objective function values. The proposed ICHS performs modified harmony memory consideration in which decision variables of solutions in a high-ranked cluster have higher probability of being selected than those in a low-ranked cluster. The ICHS is demonstrated in various optimization problems, including mathematical benchmark functions and water distribution system pipe design problems. The results show that the proposed ICHS outperforms other improved versions of HS.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.481-494
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• 2018

The accurate radiative transfer model simulation is essential for an accurate ozone profile retrieval using optimal estimation from backscattered ultraviolet (BUV) measurement. The input parameters of the radiative transfer model are the main factors that determine the model accuracy. In particular, meteorological parameters such as temperature and surface pressure have a direct effect on simulating radiation spectrum as a component for calculating ozone absorption cross section and Rayleigh scattering. Hence, a sensitivity of UV ozone profile retrievals to these parameters has been investigated using radiative transfer model. The surface pressure shows an average error within 100 hPa in the daily / monthly climatological data based on the numerical weather prediction model, and the calculated ozone retrieval error is less than 0.2 DU for each layer. On the other hand, the temperature shows an error of 1-7K depending on the observation station and altitude for the same daily / monthly climatological data, and the calculated ozone retrieval error is about 4 DU for each layer. These results can help to understand the obtained vertical ozone information from satellite. In addition, they are expected to be used effectively in selecting the meteorological input data and establishing the system design direction in the process of applying the algorithm to satellite operation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.12-19
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• 2020

The clustered heterogeneous wireless sensor network is comprised of sensor nodes and cluster heads, which are hierarchically organized for different objectives. In the network, we should especially take care of managing node resources to enhance network performance based on memory and battery capacity constraints. For instances, if some interesting events occur frequently in the vicinity of particular sensor nodes, those nodes might receive massive amounts of data. Data congestion can happen due to a memory bottleneck or link disconnection at cluster heads because the remaining memory space is filled with those data. In this paper, we utilize drones as mobile sinks to resolve data congestion and model the network, sensor nodes, and cluster heads. We also design a cost function and a congestion indicator to calculate the degree of congestion. Then we propose a data congestion map index and a data congestion mapping scheme to deploy drones at optimal points. Using control variable, we explore the relationship between the degree of congestion and the number of drones to be deployed, as well as the number of drones that must be below a certain degree of congestion and within communication range. Furthermore, we show that our algorithm outperforms previous work by a minimum of 20% in terms of memory overflow.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.487-496
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• 2000

In this paper, the Multi-FNN(Fuzzy-Neural Networks) model is identified and optimized using HCM(Hard C-Means) clustering method and genetic algorithms. The proposed Multi-FNN is based on Yamakawa's FNN and uses simplified inference as fuzzy inference method and error back propagation algorithm as learning rules. We use a HCM clustering and Genetic Algorithms(GAs) to identify both the structure and the parameters of a Multi-FNN model. Here, HCM clustering method, which is carried out for the process data preprocessing of system modeling, is utilized to determine the structure of Multi-FNN according to the divisions of input-output space using I/O process data. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. The aggregate performance index stands for an aggregate objective function with a weighting factor to consider a mutual balance and dependency between approximation and predictive abilities. According to the selection and adjustment of a weighting factor of this aggregate abjective function which depends on the number of data and a certain degree of nonlinearity, we show that it is available and effective to design an optimal Multi-FNN model. To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.13-20
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• 2005

In this paper, I recognized Korean isolated words using CVEM which is suggested by M. Bilginer et al. CVEM is an algorithm which is easy to extract the common properties from training voice signals and also doesn't need complex calculation. In addition CVEM shows high accuracy in recognition results. But, CVEM has couple of problems which are impossible to use for many training voices and no discriminant information among extracted common vectors. To get the optimal common vectors from certain voice classes, various voices should be used for training. But CVEM is impossible to get continuous high accuracy in recognition because CVEM has a limitation to use many training voices and the absence of discriminant information among common vectors can be the source of critical errors. To solve above problems and improve recognition rate, k-clustering subspace method and DCVEM suggested. And did various experiments using voice signal database made by ETRI to prove the validity of suggested methods. The result of experiments shows improvements in performance. And with proposed methods, all the CVEM problems can be solved with out calculation problem.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.4
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• pp.426-439
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• 1999

본 논문에서는 웹(World Wide Web)에서 사용자가 손쉽고 편리하게 이용할 수 있는 멀티미디어 대중교통 안내시스템 개발 경험을 소개한다. 개발된 시스템은 클라이언트와 서버 시스템, 경로탐색 시스템, 교통정보 저장 시스템, 노선 및 정류장 관리 시스템으로 구성되어 있다. 클라이언트에서 작동되는 사용자 인터페이스는 직관적으로 이해가 쉽고, 사용이 편리하며 인터액티브한 멀티미디어 대중 교통안내 서비스를 제공한다. 서버 시스템은 교통정보 수집 시스템으로부터 입력되는 데이타와, 경로탐색 시스템, 교통정보 저장 시스템과 연동되어 클라이언트의 요구사항을 처리하고 그 결과를 사용자에게 돌려준다. 수정된 A* 알고리즘을 이용하는 경로탐색 시스템은 최적경로를 탐색하며, 교통정보 저장 시스템은 현재 교통상황, 정류장, 노선, 지도 등의 정보를 저장한다. 노선 및 정류장 관리시스템은 시스템 관리자가 노선 또는 정류장 관리를 서버 화면의 지도상에서 효율적으로 수행할 수 있는 도구이다. 본 논문에서 다루는 대중교통 안내시스템은 Java로 구현하였기 때문에 확장과 이식이 용이하며, 시스템 유지보수 비용이 적게 드는 장점을 가지고 있다. 그리고, 웹 브라우저가 동작되는 환경에서는 어디서나 쉽게 접근이 가능하며 향후 구축될 Intelligent Transportation Systems(ITS)의 한 모듈로써 바로 작동될 수 있을 뿐만 아니라, 현재 인터넷상에서 제공되는 다양한 서비스와도 연동이 가능하다.Abstract This paper introduces our experience for developing a public transportation guidance system, which facilitates the World-Wide Web(WWW) to provide users with easier access and use. The proposed system is composed of four subsystems: client/server system, path search system, traffic data storage system, and traffic raw-data management system. The user interface in clients utilizes Java to furnish users with multimedia data accessibility and interactivity. The server processes clients' requests based on the traffic data coming from remote sensing devices and interacts with the path search system and traffic data storage system to provide users with the results. The path search system, which uses a modified A* algorithm, produces optimal solutions based on dynamic traffic data. The traffic data storage system stores the current traffic information together with the geographical information about the b$us_way routes. The traffic raw-data management system is a graphical user interface which enables the system manager to handle the traffic information easily on the map in the terminal screen. The system has considerable benefits such as portability, scalability, and flexibility since it is implemented using Java. Also, it can be extended to an integrated Intelligent Transportation Systems(ITS) which includes a variety of information on the Internet as well as traffic information.n.

• Journal of Radiation Protection and Research
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• v.42 no.1
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• pp.9-15
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• 2017

Background: The purpose of this study is to assign an appropriate density to virtual phantom for 2D diode array detector with different dose calculation algorithms to guarantee the accuracy of patient-specific QA. Materials and Methods: Ten VMAT plans with 6 MV photon beam and ten VMAT plans with 15 MV photon beam were selected retrospectively. The computed tomography (CT) images of MapCHECK2 with MapPHAN were acquired to design the virtual phantom images. For all plans, dose distributions were calculated for the virtual phantoms with four different materials by AAA and AXB algorithms. The four materials were polystyrene, 455 HU, Jursinic phantom, and PVC. Passing rates for several gamma criteria were calculated by comparing the measured dose distribution with calculated dose distributions of four materials. Results and Discussion: For validation of AXB modeling in clinic, the mean percentages of agreement in the cases of dose difference criteria of 1.0% and 2.0% for 6 MV were $97.2%{\pm}2.3%$, and $99.4%{\pm}1.1%$, respectively while those for 15 MV were $98.5%{\pm}0.85%$ and $99.8%{\pm}0.2%$, respectively. In the case of 2%/2 mm, all mean passing rates were more than 96.0% and 97.2% for 6 MV and 15 MV, respectively, regardless of the virtual phantoms of different materials and dose calculation algorithms. The passing rates in all criteria slightly increased for AXB as well as AAA when using 455 HU rather than polystyrene. Conclusion: The virtual phantom which had a 455 HU values showed high passing rates for all gamma criteria. To guarantee the accuracy of patent-specific VMAT QA, each institution should fine-tune the mass density or HU values of this device.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.437-441
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• 2006

Wireless sensor network consists of sensor nodes which are disseminated closely to each other to collect informations for the various requests of a sensor application applied for sensing phenomenons in real world. Each sensor node delivers sensing informations to an end user by conducting cooperative works such as processing and communicating between sensor nodes. In general, the power supply of a sensor node is depends on a battery so that the power consumption of a sensor node decides the entire life time of a sensor network. To resolve the problem, optimal routing algorithm can be used for prolong the entire life time of a sensor network based on the information on the energy level of each sensor node. In this paper, different from the existing Directed Diffusion and SPTN method, we presents a data dissemination protocol based on lower-power consumption that effectively maximizes the whole life time of a sensor network using the informations on the energy level of a sensor node and shortest-path hops. With the proposed method, a data transfer path is established using the informations on the energy levels and hops, and the collected sensing information from neighboring nodes in the event-occurring area is merged with others and delivered to users through the shortest path.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.143-151
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• 2010

Fingerprint classification is a step to increase the efficiency of an 1:N fingerprint recognition system and plays a role to reduce the matching time of fingerprint and to increase accuracy of recognition. It is difficult to classify fingerprints, because the ridge pattern of each fingerprint class has an overlapping characteristic with more than one class, fingerprint images may include a lot of noise and an input condition is an exceptional case. In this paper, we propose a novel approach to design a stochastic model and to accomplish fingerprint classification using a directional characteristic of fingerprints for an effective classification of various qualities. We compute the directional value by searching a fingerprint ridge pixel by pixel and extract a directional characteristic by merging a computed directional value by fixed pixels unit. The modified Markov model of each fingerprint class is generated using Markov model which is a stochastic information extraction and a recognition method by extracted directional characteristic. The weight list of classification model of each class is decided by analyzing the state transition matrixes of the generated Markov model of each class and the optimized value which improves the performance of fingerprint classification using GA (Genetic Algorithm) is estimated. The performance of the optimized classification model by GA is superior to the model before the optimization by the experiment result of applying the fingerprint database of various qualities to the optimized model by GA. And the proposed method effectively achieved fingerprint classification to exceptional input conditions because this approach is independent of the existence and nonexistence of singular points by the result of analyzing the fingerprint database which is used to the experiments.