• Nuclear Engineering and Technology
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• 제53권6호
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• pp.1979-1990
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• 2021

Evacuation Time Estimate (ETE) can provide decision-makers with a likelihood to implement evacuation of a population with radiation exposure risk by a nuclear power plant. Thus, the ETE is essential for developing an emergency response preparedness. However, studies on ETE have not been conducted adequately in Korea to date. In this study, different cohorts were selected based on assumptions. Existing local data were collected to construct a multi-model network by TSIS-CORSIM code. Furthermore, several links were aggregated to make simple calculations, and post-processing was conducted for dealing with the stochastic property of TSIS-CORSIM. The average speed of each cohort was calculated by the link aggregation and post-processing, and the evacuation time was estimated. As a result, the average cohort-based evacuation time was estimated as 2.4-6.8 h, and the average clearance time from ten simulations in 26 km was calculated as 27.3 h. Through this study, uncertainty factors to ETE results, such as classifying cohorts, degree of model complexity, traffic volume outside of the network, were identified. Various studies related to these factors will be needed to improve ETE's methodology and obtain the reliability of ETE results.

• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.304-310
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• 2021

The paper presents problems of optimization of the synthesis of embedded systems, in particular Pareto optimization. The model of such a system for its design for high-level of abstract is based on the classic approach known from the theory of task scheduling, but it is significantly extended, among others, by the characteristics of tasks and resources as well as additional criteria of optimal system in scope structure and operation. The metaheuristic algorithm operating according to this model introduces a new approach to system synthesis, in which parallelism of task scheduling and resources partition is applied. An algorithm based on a genetic approach with simulated annealing and Boltzmann tournaments, avoids local minima and generates optimized solutions. Such a synthesis is based on the implementation of task scheduling, resources identification and partition, allocation of tasks and resources and ultimately on the optimization of the designed system in accordance with the optimization criteria regarding cost of implementation, execution speed of processes and energy consumption by the system during operation. This paper presents examples and results for multi-criteria optimization, based on calculations for specifying non-dominated solutions and indicating a subset of Pareto solutions in the space of all solutions.

• 한국IT서비스학회지
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• 제13권4호
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• pp.205-230
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• 2014

In recent years, the social network service (SNS) and the location-based social network service (LBSNS) industry is expanding and the competition within the field is increasing much more. Since 2010, the full-scaled studies of SNS and LBSNS have begun. With the growth of SNS and LBSNS markets, SoLoMo (Social-Local-Mobile) is also becoming the trend for applications in different fields. However, despite the importance of SoLoMo, there have been little studies on the characteristics of SoLoMo applications. The purpose of this research is to investigate the effect of characteristics and perceived privacy risk of mobile location-based SNS on intention to use SoLoMo applications. For the purpose, we proposed a SoLoMo service acceptance model with TAM (Technology Acceptance Model) and the characteristics of SoLoMo applications. The characteristics consist of three factors, i.e. SNS, location, and mobile-related factors. This study also considered a gamification and a perceived privacy risk factor influencing on SoLoMo service usage in our proposed research model. The results of our empirical analysis using partial least squares (PLS) method show that the characteristics of SoLoMo applications including SNS, location, and mobile-related features, gamification, and perceived privacy risk have partially an effect on intention to use SoLoMo applications. Based on these results, SoLoMo-related companies will be able to increase the usage of SoLoMo services by differentiating their own strategies with these factors influencing on SoLoMo services.

• 산업진흥연구
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• 제2권2호
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• pp.1-6
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• 2017

한국전력의 전력을 생산, 수송, 공급하는 3가지 업무분야 중 수송부분을 관리하는 서울전력관리처에 SCADA (Supervisery Control And Data Acquisition) System이 1980년 처음 도입된 후 중앙급전소, 지역급전소, 변전소 업무를 EMS, SCADA, RTU 컴퓨터 설비 3계층의 1:N 식 방사상 형태로 구성하여 HARRIS 6000, BSC, HDLC, L&N, 도시바 등 5개 Protocol로 1200 bps와 9600 bps로 Data Link를 이용하여 왔다. 본 연구는 OSI표준네트워크패킷흐름을 도시하여 DataLink와 Network Layer를 분석하고, 네트워크 3계층을 사용하는 X.25 고속 통신망으로 구성된 한국전력 SCADA 네트워크 모델을 제시하였으며, 통신망을 시험 평가하였다. 현재의 스카다 통신구조를 개선한 미래 스카다 통신구조를 제시하고, SCADA DB 구조를 정의하고, 스카다 기능 구조에 원격 SCADA 게이트웨이 개념을 도입 표준 통신프로토콜을 적용 하였다. 따라서 데이터 전송시간 제약완화, 타지역 타 설비에서의 감시 및 제어의 다중화 및 통신 개방성을 확보하도록 하였다.

• 대한전자공학회논문지TC
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• 제44권8호
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• pp.23-32
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• 2007

본 논문에서는 계층적 무선 센서 네트워크를 위한 그룹기반 보안 메커니즘을 제안한다. 이를 위해 세 가지 형태의 노드(베이스 스테이션 그룹 관리 노드 센서 노드)로 구성된 3계층 센서네트워크에서 안전한 라우팅을 위한 구조를 설계한다. 그룹기반 배치는 가우시안(Gaussian) 분산을 이용하여 수행되며, 제안된 모델을 사용해 85% 이상의 네트워크 연결이 가능하다. 이미 보안 기능을 공유하고 있는 작은 그룹들은 안전한 그룹을 형성하고, 그룹 관리 노드들은 전체 네트워크의 백본을 형성한다. 본 논문의 보안 메커니즘은 배치된 센서 그룹에서 수집된 데이터를 처리하기 위해 제안되었으며, 관리노드에 의해 수집된 센싱 데이터는 다른 관리노드를 거쳐 베이스 스테이션에 전달된다. 제안된 메커니즘은 경량화 되었고, 노드 캡쳐 공격에 강력하게 대응할 수 있으며 분석 자료와 시뮬레이션을 결과를 통해 이러한 특징을 확인할 수 있다. 또한, 분석 자료를 통해 그룹 관리노드와 센서 노드가 조밀하게 배치되었을 때 안전성이 크게 향상됨을 알 수 있다.

• 대한토목학회논문집
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• 제31권1B호
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• pp.1-11
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• 2011

DEM을 이용한 수로망의 생성은 수문해석모형의 적용을 위한 전처리 과정으로써 실제 유역시스템의 배수구조를 결정하는 중요한 인자로 활용된다. 본 연구에서는 DEM으로부터 합리적인 수로망 추출과정 수립을 목적으로 보편적으로 사용되고 있는 면적한계기준과 국부경사와 기여면적사이의 특성에 근거한 경사-면적한계기준 기법을 이용하여 수로망을 생성하고 지형법칙에 의거하여 각 기법에 따른 소규모 유역(진안천 유역; $18.28km^2$) 배수구조의 신뢰성을 평가하였다. 그 결과, 면적한계 기준 기법은 수원유역의 크기의 인위적 결정에 의해 지형법칙을 만족시키지 못하고 유역전체의 배수구조를 왜곡되게 묘사한 반면, 경사-면적한계기준 기법의 경우 물리적인 지형법칙을 만족시키는 우수한 결과를 나타냈다. 따라서 경사-면적한계기준 기법은 DEM 기반의 수문모형을 적용 시 효율적이고 객관적인 수로망 생성을 위한 방법론으로서 활용이 가능하리라 판단된다.

• Korean Journal of Radiology
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• 제22권3호
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• pp.344-353
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• 2021

Objective: The mitotic count of gastrointestinal stromal tumors (GIST) is closely associated with the risk of planting and metastasis. The purpose of this study was to develop a predictive model for the mitotic index of local primary GIST, based on deep learning algorithm. Materials and Methods: Abdominal contrast-enhanced CT images of 148 pathologically confirmed GIST cases were retrospectively collected for the development of a deep learning classification algorithm. The areas of GIST masses on the CT images were retrospectively labelled by an experienced radiologist. The postoperative pathological mitotic count was considered as the gold standard (high mitotic count, > 5/50 high-power fields [HPFs]; low mitotic count, ≤ 5/50 HPFs). A binary classification model was trained on the basis of the VGG16 convolutional neural network, using the CT images with the training set (n = 108), validation set (n = 20), and the test set (n = 20). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated at both, the image level and the patient level. The receiver operating characteristic curves were generated on the basis of the model prediction results and the area under curves (AUCs) were calculated. The risk categories of the tumors were predicted according to the Armed Forces Institute of Pathology criteria. Results: At the image level, the classification prediction results of the mitotic counts in the test cohort were as follows: sensitivity 85.7% (95% confidence interval [CI]: 0.834-0.877), specificity 67.5% (95% CI: 0.636-0.712), PPV 82.1% (95% CI: 0.797-0.843), NPV 73.0% (95% CI: 0.691-0.766), and AUC 0.771 (95% CI: 0.750-0.791). At the patient level, the classification prediction results in the test cohort were as follows: sensitivity 90.0% (95% CI: 0.541-0.995), specificity 70.0% (95% CI: 0.354-0.919), PPV 75.0% (95% CI: 0.428-0.933), NPV 87.5% (95% CI: 0.467-0.993), and AUC 0.800 (95% CI: 0.563-0.943). Conclusion: We developed and preliminarily verified the GIST mitotic count binary prediction model, based on the VGG convolutional neural network. The model displayed a good predictive performance.

• 한국CDE학회논문집
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• 제13권2호
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• pp.131-138
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• 2008

With the advancements of the Internet and CAD data translation techniques, more CAD models are transferred from a CAD system to another through the network and interoperability is getting a common word in the CAD industry. However, when a CAD model is translated for an incompatible system into a neutral format such as STEP or IGES, its precious feature information is lost. When this feature information is lost, the advantage of feature based modeling is not valid any longer, and modification for the model is purely dependent on geometric and topological manipulations. However, the capabilities of the existing methods to modify these feature-independent models are limited as the modification involves a topological change in the model. To address this issue, we present a volumetric method to modify the solid models in neutral format. First, this method selectively decomposes the solid model to separate the portion of interest called feature volume. Next, the designer modifies the feature volume without concerning a topological change. Finally, the feature volume is united with the original solid model to complete the modification process. The results of test cases are presented to attest the usefulness of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권1호
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• pp.39-46
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• 2006

We propose an global color model based method for tracking motions of multiple human using a networked multiple-camera system in intelligent space as a human-robot coexistent system. An intelligent space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of intelligent space as well. One of the main goals of intelligent space is to assist humans and to do different services for them. In order to be capable of doing that, intelligent space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and intelligent space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• 한국통신학회논문지
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• 제29권12A호
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• pp.1309-1318
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• 2004

무선 인터넷의 급속한 성장에 따라 사용영역과 그 범위가 점차 확대되고 있으며, 사용자들은 멀티미디어 $.$ 동화상 등 점차 많은 대역폭을 요구하는 서비스를 원하고 있다. 현재 사용 중인 이동통신 단말기로 다양한 멀티미디어 서비스를 지원하기에는 한계가 있다. 다양한 컨텐츠를 지원할 수 있는 유선 인터넷 서비스와 유사한 IEEE 802.11 무선 LAM (Local Area Network)에 핸드오프까지 고려하여 설계한 광대역 무선 접속 (Broadband Wireless Access) 시스템인 IEEE 802.16 무선 MAN (Metropolitan Area Network)시스템이 제안되었다. 특히 IEEE 802.16의 TG (Task Group)e 에서는 BS (Base Station) 혹은 섹터(sector) 단위의 상위 계층 핸드오프의 지원과 MAC에서의 핸드오프를 지원하는 것에 대한 논의가 진행중이지만, 세부적인 방안은 나오지 않고 있다. 본 논문은 이동 통신 망인 cdma2000 Ix EV-DO (Evolution Data only) 네트워크를 이용하여 IEEE 802.16e에서 BS간의 소프트 핸드오프를 지원하기 위한 네트워크 모델을 제안한다. 이 모델에서는 MC(Mobility Controller)에 각 BS의 MA를 관리하는 기능을 추가하여 소프트 핸드오프를 지원하고자 한다. 제안하는 네트워크 모델은 기존의 시스템을 그대로 활용할 수 있고, 다양한 무선 인터넷 멀티미디어 서비스를 이용할 수 있다.