• KIPS Transactions on Software and Data Engineering
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• v.4 no.8
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• pp.315-320
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• 2015

The purposed of this research is to develop multimedia content usage analysis service platform. In the proposed platform, the content gazing behaviors of the users are monitored and profiled in real-time and a set of quantifiable metrics is provided. These metrics are used to determine the closeness of the users' behavior from the intent set by the provider. Based on the evaluation, it is possible to assess the effectiveness of the contents themselves as well. The content usage assessment is accomplished by utilizing the intention flow and the intent weight, which are embedded into the content by the content provider. Proposed methodology can be effectively applied and used in various application domains such as in education and in commercial advertisements.

• Atmosphere
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• v.22 no.2
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• pp.267-277
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• 2012

The objectives of this study are to develop a real-time drought monitoring and prediction system on the East Asia domain and to evaluate the performance of the system by using past historical drought records. The system is mainly composed of two parts: drought monitoring for providing current drought indices with meteorological and hydrological conditions; drought outlooks for suggesting future drought indices and future hydrometeorological conditions. Both parts represent the drought conditions on the East Asia domain (latitude $21.15{\sim}50.15^{\circ}$, longitude $104.40{\sim}149.65^{\circ}$), Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$) and South Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$), respectively. The observed meteorological data from ASOS (Automated Surface Observing System) and AWS (Automatic Weather System) of KMA (Korean Meteorological Administration) and model-driven hydrological data from LSM (Land Surface model) are used for the real-time drought monitoring, while the monthly and seasonal weather forecast information from UM (Unified Model) of KMA are utilized for drought outlooks. For the evaluation of the system, past historical drought records occurred in Korea are surveyed and are compared with the application results of the system. The results demonstrated that the selected drought indices such as KMA drought index, SPI (3), SPI (6), PDSI, SRI and SSI are reasonable, especially, the performance of SRI and SSI provides higher accuracy that the others.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.7-12
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• 2016

DRAM is commonly used as a smartphone memory medium, but extending its capacity is challenging due to DRAM's large battery consumption and density limit. Meanwhile, smartphone applications such as social network services need increasingly large memory, resulting in long latency due to additional storage accesses. To alleviate this situation, we adopt emerging nonvolatile memory (NVRAM) as smartphone's buffer cache and propose an efficient management scheme. The proposed scheme stores all dirty data in NVRAM, thereby reducing the number of storage accesses. Moreover, it separately exploits read and write histories of data accesses, leading to more efficient management of volatile and nonvolatile buffer caches, respectively. Trace-driven simulations show that the proposed scheme improves I/O performances significantly.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.8
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• pp.343-348
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• 2019

In recent years, extractive summarization systems based on end-to-end deep learning models have become popular. These systems do not require human-crafted features and adopt data-driven approaches. However, previous related studies have shown that linguistic analysis features such as part-of-speeches, named entities and word's frequencies are useful for extracting important sentences from a document to generate a summary. In this paper, we propose an extractive summarization system based on deep neural networks using conventional linguistic analysis features. In order to prove the usefulness of the linguistic analysis features, we compare the models with and without those features. The experimental results show that the model with the linguistic analysis features improves the Rouge-2 F1 score by 0.5 points compared to the model without those features.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.261-270
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• 2020

In this study, we identify promising technologies for Piggyback transportation system by analyzing the relevant patent information. In order for this, we first develop the patent database by extracting relevant technology keywords from the pioneering research papers for the Piggyback flactcar system. We then employed textmining to identify the frequently referred words from the patent database, and using these words, we applied the LDA (Latent Dirichlet Allocation) algorithm in order to identify "topics" that are corresponding to "key" technologies for the Piggyback system. Finally, we employ the ARIMA model to forecast the trends of these "key" technologies for technology forecasting, and identify the promising technologies for the Piggyback system. with keyword search method the patent analysis. The results show that data-driven integrated management system, operation planning system and special cargo (especially fluid and gas) handling/storage technologies are identified to be the "key" promising technolgies for the future of the Piggyback system, and data reception/analysis techniques must be developed in order to improve the system performance. The proposed procedure and analysis method provides useful insights to develop the R&D strategy and the technology roadmap for the Piggyback system.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.55-65
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• 2022

As Internet and mobile technology is developing, the educational environment is changing from the traditional passive way into an active one driven by learners. It is important to construct the proper learner's profile for personalized education where learners are able to study according to their learning levels. The existing studies on ICT-based personalized education have mostly focused on vocabulary and learning contents. In this paper, learning profile is constructed with not only vocabulary but grammar to define a learner's learning status in more detailed way. A proficiency metric is defined which shows how a learner is accustomed to the learning contents. The simulational results present the suggested approach is effective to the evaluation essay data with each learner's proficiency that is determined after pre-learning process. Additionally, the proposed analysis technique enables to provide statistics or graphs of the learner's status and necessary data for the learner's learning contents.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.181-183
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• 2007

Copyright infringement and data piracy are pervasive problems of digital era and Electronic Navigational Charts(ENC) are not free from these issues. Aside from the economic impact, the unofficial distribution of nautical information has sign띠cant safeη concerns. Therefore, official distributors of nautical information have sought appropriate methods to protect their data and to provide the mariner with a certificate of authenticity through the adoption of security schema. However, a plethora of different security schema provided by independent distributors markedly complicates the software development of Electronic Chart Display and Information Systems (ECDIS) manufacturers and makes it more difficult to achieve the goal of seamless world-wide electronic navigational database easily accessible to the mariner. A fundamental concern of IHO is that adoption of a single, centrally administered security scheme for all ENCs could improve the ease of use of ENCs and enhance safety of navigation. IHO have driven protection scheme as S-63, S-63x. NORI(National Oceanographic Research Institute) necessarily need protection scheme and supporting system for nautical information. This paper presents protection scheme for NORI and proposes support system for ENC protection.

• Smart Structures and Systems
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• v.20 no.3
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• pp.385-396
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• 2017

The recent advancements in sensing technologies allow us to record measurements from target structures at multiple locations and with relatively high spatial resolution. Such measurements can be used to develop data-driven methodologies for condition assessment, control, and health monitoring of target structures. One of the state-of-the-art technologies, Fiber Optic Strain Sensors (FOSS), is developed at NASA Armstrong Flight Research Center, and is based on Fiber Bragg Grating (FBG) sensors. These strain sensors are accurate, lightweight, and can provide almost continuous strain-field measurements along the length of the fiber. The strain measurements can then be used for real-time shape-sensing and operational load-estimation of complex structural systems. While several works have demonstrated the successful implementation of FOSS on large-scale real-life aerospace structures (i.e., airplane wings), there is paucity of studies in the literature that have investigated the potential of extending the application of FOSS into civil structures (e.g., tall buildings, bridges, etc.). This work assesses the feasibility of using FOSS to predict operational loads (e.g., wind loads) on chain-like structures. A thorough investigation is performed using analytical, computational, and experimental models of a 4-story steel building test specimen, developed at the University of Southern California. This study provides guidelines on the implementation of the FOSS technology on building-like structures, addresses the associated technical challenges, and suggests potential modifications to a load-estimation algorithm, to achieve a robust methodology for predicting operational loads using strain-field measurements.

• International Journal of Safety
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• v.6 no.2
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• pp.1-7
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• 2007

In this study mechanical strength of A53B carbon steel was analyzed using several types of test specimens directly machined from oil recycling pipe experienced a failure due to hydrogen attack in chemical plants. High temperature hydrogen attack (HTHA) is the damage process of grain boundary facets due to a chemical reaction of carbides with hydrogen, thus forming cavities with high pressure methane gas. Driven by the methane gas pressure, the cavities grow on grain boundaries forming intergranular micro cracks. Microscopic optical examination, tensile test, Charpy impact test, hardness measurement, and small punch (SP) test were performed. Carbon content of the hydrogen attacked specimens was dramatically reduced compared with that of standard specification of A53B. Traces of decarburization and micro-cracks were observed by optical and scanning electron microscopy. Charpy impact energy in hydrogen attacked part of the pipe exhibited very low values due to the decarburization and micro fissure formation by HTHA, on the other hand, data tested from the sound part of the pipe showed high and scattered impact energy. Maximum reaction forces and ductility in SP test were decreased at hydrogen attacked part of the pipe compared with sound part of the pipe. Finite element analyses for SP test were performed to estimate tensile properties for untested part of the pipe in tensile test. And fracture toughness was calculated using an equivalent strain concept with SP test and finite element analysis results.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.271-280
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• 2019

Smart factory, a critical part of digital transformation, enables data-driven decision making using monitoring, analysis and prediction. Predictive maintenance is a key element of smart factory and the need is increasing. The purpose of this study is to analyze the degradation characteristics of a galvanizing kettle for the steel plating process and to predict the remaining useful life(RUL) for predictive maintenance. Correlation analysis, multiple regression, principal component regression were used for analyzing factors of the process. To identify the trend of degradation, a proposed rolling window was used. It was observed the degradation trend was dependent on environmental temperature as well as production factors. It is expected that the proposed method in this study will be an example to identify the trend of degradation of the facility and enable more consistent predictive maintenance.