• Journal of Korea Multimedia Society
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• v.20 no.5
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• pp.808-826
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• 2017

Most of conventional DSS's(Digital Signage Systems) have been built based on LAMP framework. Recent researches have shown that MEAN or MERN stack framework is simpler, more flexible, faster and more suitable for web-based application than LAMP stack framework. In this paper, we propose a design and implementation of MEARN (ME(A+R)N) stack-based real-time digital signage system, MR-DSS, which supports handing real-time tasks like urgent/instant messaging, system status monitoring and so on, efficiently in addition to conventional digital signage CMS service tasks. MR-DSCMS, CMS of MR-DSS, is designed to provide most of its normal services by REST APIs and real-time services like urgent/instant messaging by Socket.IO base under MEARN stack environment. In addition to architecture description of components composing MR-DSS, design and implementation issues are clarified in more detail. Through experimental testing, it is shown that 1) MR-DSS works functionally well, 2) the networking load performance of MR-DSCMS's REST APIs is better compared to a well-known open source Xibo CMS, and 3) real-time messaging via Socket.IO works much faster than REST APIs.

• Land and Housing Review
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• v.8 no.3
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• pp.181-187
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• 2017

To proactively respond to internal and external changes such as the recent demographic change and rising demand for diversified housing types, this study investigated the framed-structure free plan public house model proposed by the LH to look at the seismic performance of framed-structure apartment according to damper system use through non-linear analysis. The effectiveness thereof was also examined in terms of performance and economy. As a result, the proposed damper system application method to framed-structure free plan public house model was found to meet the performance requirements of the present earthquake-resistant design (KBC2016) and effective to apply to designs. The max response displacement and max response acceleration were compared based on the nonlinear analysis. As a result, the building with damper system showed better earthquake resistance performance than earthquake-resistant structure thanks to the damper system, although the base shear of earthquake-resistant system was reduced by 20% in design. The damper system is expected to help reduce building damage while ensuring excellent earthquake resistance performance. In addition, the framework quantities of earthquake-resistant structure and structure with damping system were compared. As a result, columns were found to reduce concrete amount by about 3.9% and rebar, by about 7.3%. Walls showed about 12.6% reduction in concrete and about 10.7% in rebar. In terms of cost, framework construction cost including formwork and foundation expenses was expected to drop by about 5~6%.

• Journal of Technology Innovation
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• v.9 no.1
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• pp.149-165
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• 2001

This paper analyses characteristics of the numerical controller industry in market formation and the flow of information between users and producers and the characteristic of knowledge base of the industry and discuses the difficulties derived, from the characteristics, in accumulation of technological capability. In market formation between users and producers, the multi-layered market is not favorable to domestic producers in that lower end market is not large enough to provide cradle market to them which produce inferior quality and lower price than imported products. The credibility of the performance of a product is different to prove until a critical mass of products are sold. Therefore gaining market share is deterred by unproven credibility of the performance of the product. The flow of information between users and producers is limited. The flow of information on users environment through mass market to producers is essential for improving credibility of a product. The nature of knowledge base is tacit and the means of knowledge transmission is limited. Technological licensing and reverse engineering, which have been conventional means of knowledge transmission, are not useful in the numerical controller industry. These characteristics provide conditions of vicious circle in accumulation of technological capability of the numerical controller industry. This paper argues that these characteristics of the industry challenge existing approach to R&D management and framework of science and technology policy.

• Earthquakes and Structures
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• v.10 no.6
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• pp.1451-1465
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• 2016

The effectiveness of base isolation (BI) systems for mitigation of seismic vibration of bridges have been extensively studied in the past. It is well established in those studies that the performance of BI system is largely dependent on the characteristics of isolator yield strength. For optimum design of such systems, normally a standard nonlinear optimization problem is formulated to minimize the maximum response of the structure, referred as Stochastic Structural Optimization (SSO). The SSO of BI system is usually performed with reference to a problem of unconstrained optimization without imposing any restriction on the maximum isolator displacement. In this regard it is important to note that the isolator displacement should not be arbitrarily large to fulfil the serviceability requirements and to avoid the possibility of pounding to the adjacent units. The present study is intended to incorporate the effect of excessive isolator displacement in optimizing BI system to control seismic vibration effect of bridges. In doing so, the necessary stochastic response of the isolated bridge needs to be optimized is obtained in the framework of statistical linearization of the related nonlinear random vibration problem. A simply supported bridge is taken up to elucidate the effect of constraint condition on optimum design and overall performance of the isolated bridge compared to that of obtained by the conventional unconstrained optimization approach.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2001.05a
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• pp.411-430
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• 2001

This Paper analyses characteristics of the numerical controller industry in market formation and the flow of information between users and producers and the characteristic of knowledge base of the industry and discusses the difficulties derived, from the characteristics, in accumulation of technological capability In market formation between users and producers, the multi-layered market is not favorable to domestic producers in that lower end market is not large enough to provide cradle market to them which produce inferior quality and lower price than imported products. The credibility of the performance of a product is difficult to prove until a critical mass of products are sold. Therefore gaining market share is deterred by unproven credibility of the performance of the product. The flow of information between users and producers is limited. The flow of information on users environment through mass market to producers is essential for improving credibility of a product. The nature of knowledge base is tacit and the means of knowledge transmission is limited. Technological licensing and reverse engineering, which have been conventional means of knowledge transmission, are not useful in the numerical controller industry. These characteristics provide conditions of vicious circle in accumulation of technological capability of the numerical controller industry. It is conjectured that these characteristics are derived from the fact that the numerical controller is the result of IT based technological convergence in controlling machining process. This paper argues that these characteristics of the industry challenges existing approach to R&D management and framework of science and technology Policy.

• Earthquakes and Structures
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• v.22 no.3
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• pp.219-230
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• 2022

Knowing that the variability of soil properties is an important source of uncertainty in geotechnical analyses, we will study in this paper the effect of this variability on the seismic response of a structure within the framework of Soil Structure Interaction (SSI). We use the proposed and developed model (N2-ISS, Mekki et al., 2014). This approach is based on an extension of the N2 method by determining the capacity curve of the fixed base system oscillating mainly in the first mode, then modified to obtain the capacity curve of the system on a flexible basis using the concept of the equivalent nonlinear oscillator. The properties of the soil that we are interested in this paper will be the shear wave velocity and the soil damping. These parameters will be modeled at first, as independent random fields, then, the two parameters will be correlated. The results obtained showed the importance of the use of random field in the study of SSI systems. The variability of soil damping and shear wave velocity introduces significant uncertainty not only in the evaluation of the damping of the soil-structure system but also in the estimation of the displacement of the structure and the base-shear force.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.132-139
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• 2019

We address the problem about forecasting the direction of stock price movement in the Korea market. Recently, the deep neural network is popularly applied in this area of research. In deep neural network systems, proper parameter initialization reduces training time and improves the performance of the model. Therefore, in our study, we propose a novel parameter initialization technique and apply this technique for the stock price movement prediction model. Specifically, we design a framework which consists of two models: a base model and a main prediction model. The base model constructed with LSTM is trained by using the large data which is generated by a large amount of the stock data to achieve optimal parameters. The main prediction model with the same architecture as the base model uses the optimal parameter initialization. Thus, the main prediction model is trained by only using the data of the given stock. Moreover, the stock price movements can be affected by other related information in the stock market. For this reason, we conducted our research with two types of inputs. The first type is the stock features, and the second type is a combination of the stock features and the Korea Composite Stock Price Index (KOSPI) features. Empirical results conducted on the top five stocks in the KOSPI list in terms of market capitalization indicate that our approaches achieve better predictive accuracy and F1-score comparing to other baseline models.

• Nuclear Engineering and Technology
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• v.46 no.6
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• pp.737-752
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• 2014

As condition-based maintenance (CBM) has risen as a new trend, there has been an active movement to apply information technology for effective implementation of CBM in power plants. This motivation is widespread in operations and maintenance, including monitoring, diagnosis, prognosis, and decision-making on asset management. Thermal efficiency analysis in nuclear power plants (NPPs) is a longstanding concern being updated with new methodologies in an advanced IT environment. It is also a prominent way to differentiate competitiveness in terms of operations and maintenance costs. Although thermal performance tests implemented using industrial codes and standards can provide officially trustworthy results, they are essentially resource-consuming and maybe even a hind-sighted technique rather than a foresighted one, considering their periodicity. Therefore, if more accurate performance monitoring can be achieved using advanced data analysis techniques, we can expect more optimized operations and maintenance. This paper proposes a framework and describes associated methodologies for in-situ thermal performance analysis, which differs from conventional performance monitoring. The methodologies are effective for monitoring, diagnosis, and prognosis in pursuit of CBM. Our enabling techniques cover the intelligent removal of random and systematic errors, deviation detection between a best condition and a currently measured condition, degradation diagnosis using a structured knowledge base, and prognosis for decision-making about maintenance tasks. We also discuss how our new methods can be incorporated with existing performance tests. We provide guidance and directions for developers and end-users interested in in-situ thermal performance management, particularly in NPPs with large steam turbines.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.227-241
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• 2021

Object detection techniques based on deep learning such as YOLO have high detection performance and precision in a single channel video stream. In order to expand to multiple channel object detection in real-time, however, high-performance hardware is required. In this paper, we propose a novel back-end server framework, a real-time AI vision platform (RAVIP), which can extend the object detection function from single channel to simultaneous multi-channels, which can work well even in low-end server hardware. RAVIP assembles appropriate component modules from the RODEM (real-time object detection module) Base to create per-channel instances for each channel, enabling efficient parallelization of object detection instances on limited hardware resources through continuous monitoring with respect to resource utilization. Through practical experiments, RAVIP shows that it is possible to optimize CPU, GPU, and memory utilization while performing object detection service in a multi-channel situation. In addition, it has been proven that RAVIP can provide object detection services with 25 FPS for all 16 channels at the same time.

• ETRI Journal
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• v.46 no.1
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• pp.59-70
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• 2024

We introduce a high-performance named entity recognition (NER) model for written and spoken language. To overcome challenges related to labeled data scarcity and domain shifts, we use transfer learning to leverage our previously developed KorBERT as the base model. We also adopt a meta-pseudo-label method using a teacher/student framework with labeled and unlabeled data. Our model presents two modifications. First, the student model is updated with an average loss from both human- and pseudo-labeled data. Second, the influence of noisy pseudo-labeled data is mitigated by considering feedback scores and updating the teacher model only when below a threshold (0.0005). We achieve the target NER performance in the spoken language domain and improve that in the written language domain by proposing a straightforward rollback method that reverts to the best model based on scarce human-labeled data. Further improvement is achieved by adjusting the label vector weights in the named entity dictionary.