• 국제학술발표논문집
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• The 1th International Conference on Construction Engineering and Project Management
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• pp.383-388
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• 2005

In the construction industry, complex works are carried out with significant resources under non-linear circumstances where clear concepts of project management could be of benefit to all parties and personnel involved. In this paper, we define the optimum project management configuration for construction management by using DSM (Design Structure Matrix). Furthermore DSM can be visualized as a network model, and then Graph Theory provides us the numerical results.

• Nuclear Engineering and Technology
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• 제48권1호
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• pp.64-71
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• 2016

Void fraction is an important parameter in the oil industry. This quantity is necessary for volume rate measurement in multiphase flows. In this study, the void fraction percentage was estimated precisely, independent of the flow regime in gas-liquid two-phase flows by using ${\gamma}-ray$ attenuation and a multilayer perceptron neural network. In all previous studies that implemented a multibeam ${\gamma}-ray$ attenuation technique to determine void fraction independent of the flow regime in two-phase flows, three or more detectors were used while in this study just two NaI detectors were used. Using fewer detectors is of advantage in industrial nuclear gauges because of reduced expense and improved simplicity. In this work, an artificial neural network is also implemented to predict the void fraction percentage independent of the flow regime. To do this, a multilayer perceptron neural network is used for developing the artificial neural network model in MATLAB. The required data for training and testing the network in three different regimes (annular, stratified, and bubbly) were obtained using an experimental setup. Using the technique developed in this work, void fraction percentages were predicted with mean relative error of <1.4%.

• 한국항해항만학회지
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• 제41권5호
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• pp.287-296
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• 2017

The Formal Safety Assessment (FSA) is a structured and systematic methodology developed by the IMO, aimed at assessing the risk of vessels and recommending the method to control intolerable risks, thereby enhancing maritime safety, including protection of life, health, the marine environment and property, by using risk analysis and cost-benefit assessment. While the FSA has mostly been applied to merchant vessels, it has rarely been applied to a DP vessel, which is one of the special purpose vessels in the offshore industry. Furthermore, most of the FSA has been conducted so far by using the Fault Tree Analysis tool, even though there are many other risk analysis tools. This study carried out the FSA for safe operation of DP vessels by using the Bayesian network, under which conditional probability was examined. This study determined the frequency and severity of DP LOP incidents reported to the IMCA from 2001 to 2010, and obtained the Risk Index by applying the Bayesian network. Then, the Risk Control Options (RCOs) were identified through an expert brainstorming and DP vessel simulations. This study recommends duplication of PRS, regardless of the DP class and PRS type and DP system specific training. Finally, this study verified that the Bayesian network and DP simulator can also serve as an effective tool for FSA implementation.

• 한국경제지리학회지
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• 제16권1호
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• pp.17-36
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• 2013

본 연구는 지역산업 네트워크의 변화를 통해 지역과 산업의 관계를 살펴보고자 하였다. 순창 지역 산업의 변화과정을 지역 내부에서 출현한 전통장류제조업체와, 지역외부에서 유입된 기업인 양조장류제조업체로 구분하여, 순창 장류산업의 발전과정과 지역과의 관계를 살펴보았다. 지역산업 네트워크를 통해 조직, 기술, 영역 공간의 지역 내외의 변화를 살펴보기 위해, 2장에서는 순창 장류산업의 지역 내외의 확장과 변화를 살펴본다. 3장에서는 순창장류산업을 행위자 측면과 제도적 측면에서 장류산업을 살펴본다. 행위자 측면에서는 전통장류제조업체의 기업활동 네트워크를 생산네트워크, 판매네트워크, 연구개발 및 지원 네트워크로 구분하여, 순창 장류산업에서 나타난 네트워크와 이들의 조정과정을 살펴본다. 그리고 제도적 측면에서는 행위자를 둘러싼 조직, 기술, 영역 공간의 변화가 어떻게 이루어져왔고 조정되어 왔는지를 살펴본다. 4장에서는 논의를 종합하고 결론짓는다. 본 연구는 지역산업을 분석하는 관점을 제시한다는 측면에서 의의가 있다.

• 산업공학
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• 제16권spc호
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• pp.87-92
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• 2003

Progressive mesh representation and generation have become one of the most important issues in network-based computer graphics. However, current researches are mostly focused on triangular mesh models. On the other hand, solid models are widely used in industry and are applied to advanced applications such as product design and virtual assembly. Moreover, as the demand to share and transmit these solid models over the network is emerging, the generation and the transmission of progressive solid models depending on specific engineering needs and purpose are essential. In this paper, we present a Cellular Topology-based approach to generating and transmitting progressive solid models from a feature-based solid model for internet-based design and collaboration. The proposed approach introduces a new scheme for storing and transmitting solid models over the network. The Cellular Topology (CT) approach makes it possible to effectively generate progressive solid models and to efficiently transmit the models over the network with compact model size.

• Journal of information and communication convergence engineering
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• 제20권1호
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• pp.8-15
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• 2022

The new 5G radio technology (NR) can provide ultra-reliable low latency communications. The supporting 5G network infrastructure will move away from the previous point-to-point network architecture to a service-based architecture. 5G can provide three new things, i.e., wider channels, lower latency and more bandwidth. These will allow 5G to support three main types of connected services, including enhanced mobile broadband, mission-critical communications, and the massive Internet of Things (IoT). In 2015, the 5th generation (5G) mobile communication was officially approved by the International Telecommunication Union (ITU) as IMT-2020. Since then, 3GPP, the international organization responsible for 5G standards, is actively developing specifications for 5G technologies. 3GPP Release 15 provides the first full set of 5G standards, and the evolution and expansion of 5G are now being standardized in Release 16 and 17, respectively. This paper provides an overview of 3GPP 5G technologies and key services.

• 방사선산업학회지
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• 제17권1호
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• pp.19-32
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• 2023

The amount of radioactive waste is expected to dramatically increase with decommissioning of nuclear power plants such as Kori-1, the first nuclear power plant in South Korea. Accurate nuclide analysis is necessary to manage the radioactive wastes safely, but research on verification of radionuclide analysis has yet to be well established. This study aimed to develop the technology that can verify the results of radionuclide analysis based on artificial intelligence. In this study, we propose an anomaly detection algorithm for inspecting the analysis error of radionuclide. We used the data from 'Updated Scaling Factors in Low-Level Radwaste' (NP-5077) published by EPRI (Electric Power Research Institute), and resampling was performed using SMOTE (Synthetic Minority Oversampling Technique) algorithm to augment data. 149,676 augmented data with SMOTE algorithm was used to train the artificial neural networks (classification and anomaly detection networks). 324 NP-5077 report data verified the performance of networks. The anomaly detection algorithm of radionuclide analysis was divided into two modules that detect a case where radioactive waste was incorrectly classified or discriminate an abnormal data such as loss of data or incorrectly written data. The classification network was constructed using the fully connected layer, and the anomaly detection network was composed of the encoder and decoder. The latter was operated by loading the latent vector from the end layer of the classification network. This study conducted exploratory data analysis (i.e., statistics, histogram, correlation, covariance, PCA, k-mean clustering, DBSCAN). As a result of analyzing the data, it is complicated to distinguish the type of radioactive waste because data distribution overlapped each other. In spite of these complexities, our algorithm based on deep learning can distinguish abnormal data from normal data. Radionuclide analysis was verified using our anomaly detection algorithm, and meaningful results were obtained.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제10권1호
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• pp.37-42
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• 2010

Final year students are normally encountering high pressing in their study. In view of this fact, this research focuses on determining mental states condition of college student in final year based on the psycho-physiological information. The experiments were conducted in two times, i.e., prior- and post- graduation seminar examination. The early results indicated that the student profile of mood states (POMS) in prior final graduation seminar showed higher scores than students in post final graduation seminar. Thus, in this research, relation between biosignal representing by heart rate variability (HRV) and questionnaire responses were evaluated by hidden Markov model (HMM) and neural networks (NN).

• 대한간호학회지
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• 제54권1호
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• pp.1-17
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• 2024

Purpose: The significance of the healthcare industry has grown exponentially in recent years due to the impact of the fourth industrial revolution and the ongoing pandemic. Accordingly, this study aimed to examine domestic healthcare-related patents comprehensively. Big data analysis was used to present the trend and status of patents filed in nursing. Methods: The descriptive review was conducted based on Grant and Booth's descriptive review framework. Patents related to nursing was searched in the Korea Intellectual Property Rights Information Service between January 2016 to December 2020. Data analysis included descriptive statistics, phi-coefficient for correlations, and network analysis using the R program (version 4.2.2). Results: Among 37,824 patents initially searched, 1,574 were selected based on the inclusion criteria. Nursing-related patents did not specify subjects, and many patents (41.4%) were related to treatment in the healthcare delivery phase. Furthermore, most patents (56.1%) were designed to increase effectiveness. The words frequently used in the titles of nursing-related patents were, in order, "artificial intelligence," "health management," and "medical information," and the main terms with high connection centrality were "artificial intelligence" and "therapeutic system." Conclusion: The industrialization of nursing is the best solution for developing the healthcare industry and national health promotion. Collaborations in education, research, and policy will help the nursing industry become a healthcare industry of the future. This will prime the enhancement of the national economy and public health.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2010년도 춘계학술대회
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• pp.753-755
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• 2010

현재 자동차 산업은 인포테인먼트 시스템에 대한 수요 증가와 요구에 부응하기 위하여 MOST(Media Oriented Systems Transport)라는 차량용 멀티미디어 네트워크 기술을 적용하게 되었고, MOST25 네트워크의 경우 현재 일부 차종에 제한적으로 장착되어 사용되고 있으나, 대역폭과 호환성 등의 문제가 발생하였으며, 이를 해결하고자 MOST150 기술의 개발과 이를 차량에 적용하고자 많은 연구가 진행되고 있다. 따라서 본 연구에서는 차량용 MOST150/Ethernet Gateway 구현에 있어서 효과적인 이더넷 트래픽 처리를 위해 MOST150의 등시채널(Isochronous channel), MOST 이더넷 패킷 채널(Ethernet Packet channel) 등의 Management Mapping 방법에 대해 분석하고 효율적인 알고리즘에 대하여 연구하고자 한다.