• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1397-1399
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• 2003

When and Where, What kind of agricultural products will be produced and provided for the market? It is a commercial requirement, and also an academic questions to remote sensing technology. Crop physiology analysis and growth monitoring are important elements for precision agriculture management. Remote sensing technology supplies us more selections and available spaces in this dynamic change study by producing images of different spatial, spectral and temporal resolutions. Especially, the hyperspectral remote sensing should do play a key role in crop growth investigation at national, regional and global scales. In the past five years, Chinese academy of sciences and Japan NTT-DATA have made great efforts to establish a prototype information service system to dynamically survey the vegetable planting situation in Nagano area of Japan mainly based on remote sensing data. For such concern, a flexible and light-duty flight system and some practical data processing system and some necessary background information should be rationally made together. In addition, some studies are also important, such as quick pre-processing for hyperspectral data, Multi-temporal vegetation index analysis, hyperspectral image classification in support of GIS data, etc. In this paper, several spectral data analysis models and a designed airborne platform are provided and discussed here.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1433-1435
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• 2003

Very decisive progress was made in advancing fundamental POL-IN-SAR theory and algorithm development during the past decade. This was accomplished with the aid of airborne & shuttle platforms supporting single -to-multi-band multi-modal POL-SAR and also some POL-IN-SAR sensor systems, which will be compared and assessed with the aim of establishing the hitherto not completed but required missions such as tomographic and holographic imaging. Because the operation of airborne test-beds is extremely expensive, aircraft platforms are not suited for routine monitoring missions which is better accomplished with the use drones or UAVs. Such unmanned aerial vehicles were developed for defense applications, however lacking the sophistic ation of implementing advanced forefront POL-IN-SAR technology. This shortcoming will be thoroughly scrutinized resulting in the finding that we do now need to develop most rapidly POL-IN-SAR drone-platform technology especially for environmental stress-change monitoring with a great variance of applications beginning with flood, bush/forest-fire to tectonic-stress (earth-quake to volcanic eruptions) for real-short-time hazard mitigation. However, for routine global monitoring purposes of the terrestrial covers neither airborne sensor implementation - aircraft and/or drones - are sufficient; and there -fore multi-modal and multi-band space-borne POL-IN-SAR space-shuttle and satellite sensor technology needs to be further advanced at a much more rapid phase. The existing ENVISAT with the forthcoming ALOSPALSAR, RADARSAT-2, and the TERRASAT will be compared, demonstrating that at this phase of development the fully polarimetric and polarimetric-interferometric modes of operation must be viewed and treated as preliminary algorithm verification support modes and at this phase of development are still not to be viewed as routine modes.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.579-593
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• 2010

Low-power radio frequency (RF) chip transceiver technology and the associated structural health monitoring platforms have matured recently to enable high-rate, lossless transmission of measurement data across large-scale sensor networks. The intrinsic value of these advanced capabilities is the allowance for high-quality, rapid operational modal analysis of in-service structures using distributed accelerometers to experimentally characterize the dynamic response. From the analysis afforded through these dynamic data sets, structural identification techniques can then be utilized to develop a well calibrated finite element (FE) model of the structure for baseline development, extended analytical structural evaluation, and load response assessment. This paper presents a case study in which operational modal analysis is performed on a three-span prestressed reinforced concrete bridge using a wireless sensor network. The low-power wireless platform deployed supported a high-rate, lossless transmission protocol enabling real-time remote acquisition of the vibration response as recorded by twenty-nine accelerometers at a 256 Sps sampling rate. Several instrumentation layouts were utilized to assess the global multi-span response using a stationary sensor array as well as the spatially refined response of a single span using roving sensors and reference-based techniques. Subsequent structural identification using FE modeling and iterative updating through comparison with the experimental analysis is then documented to demonstrate the inherent value in dynamic response measurement across structural systems using high-rate wireless sensor networks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.4
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• pp.469-475
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• 2021

In order to effectively maintain and manage river facilities, on going data collection of associated objects is important. However, the existing data acquisition methods of using a total station, a global navigation satellite system, or a terrestrial laser scanner have limitations in terms of cost/time/manpower when acquiring spatial information data on river facilities distributed over a wide and long area, unlike general facilities. In contrast, a mobile mapping system (MMS), which acquires data while moving its platform, acquires precise spatial information data for a large area in a short time, so it is suitable for use in the maintenance of linear facilities around rivers. As a result of applying a MMS to a research area of 4 km, 184,646,099 points were acquired during a 20-minute data acquisition period, and 378 cross-sections were extracted. By comparing this with computer-drawn river plans, it was confirmed that efficient levee management using a MMS is possible.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.1-9
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• 2021

Although interest in the metaverse increases due to the pandemic, the understanding of the metaverse interest factor, which is an essential element for the sustainability of any metaverse platform, is lacking. This study aims to reveal the interest factors of metaverse services by analyzing user community discourse. We collected user community discourses from and applied LDA to extract topics. Further, we categorize the factors into growth and verifiable indicators, various levels of interaction, self-expression and freedom, and connection with the real world. The content planning direction of the game-based metaverse of utilization was derived. This study is meaningful in that it analyzes the interest factors of the metaverse based on the empirical evidence of user discourse data.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.71-78
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• 2019

This study aims to identify good borrowers within the context of P2P lending. P2P lending is a growing platform that allows individuals to lend and borrow money from each other. Inherent in any loans is credit risk of borrowers and needs to be considered before any lending. Specifically in the context of P2P lending, traditional models fall short and thus this study aimed to rectify this as well as explore the problem of class imbalances seen within credit risk data sets. This study implemented an over-sampling technique known as Synthetic Minority Over-sampling Technique (SMOTE). To test our approach, we implemented five benchmarking classifiers such as support vector machines, logistic regression, k-nearest neighbor, random forest, and deep neural network. The data sample used was retrieved from the publicly available LendingClub dataset. The proposed SMOTE revealed significantly improved results in comparison with the benchmarking classifiers. These results should help actors engaged within P2P lending to make better informed decisions when selecting potential borrowers eliminating the higher risks present in P2P lending.

• Steel and Composite Structures
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• v.30 no.3
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• pp.201-215
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• 2019

In this research, the behavior of tube-in-tube BRBs (TiTBRBs) has been investigated. In a typical TiTBRB, the yielding core tube is located inside the outer restraining one to dissipate energy through extensive plastic deformation, while the outer restraining tube remains essentially elastic. With the aid of FE analyses, the monotonic and cyclic behavior of the proposed TiTBRBs have been studied as individual brace elements. Subsequently, a detailed finite element model of a representative single span-single story frame equipped with such a TiTBRB has been constructed and both monotonic and cyclic behavior of the proposed TiTBRBs have been explored under the application of the AISC loading protocol at the braced frame level. With the aid of backbone curves derived from the FE analyses, a simplified frame model has been developed and verified through comparison with the results of the detailed FE model. It has been shown that, the simplified model is capable of predicting closely the cyclic behavior of the TiTBRB frame and hence can be used for design purposes. Considering type of connection detail used in a frame, the TiTBRB member which behave satisfactorily at the brace element level under cyclic loading conditions, may suffer global buckling due to the flexural demand exerted from the frame to the brace member at its ends. The proposed TiTBRB suit tubular members of offshore structures and the application of such TiTBRB in a typical offshore platform has been introduced and studied in a single frame level using detailed FE model.

• Smart Media Journal
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• v.8 no.3
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• pp.95-103
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• 2019

The global manufacturing industry has reached the limit to growth due to a long-term recession, the rise of labor cost and raw material. As a solution to these difficulties, we promote the 4th Industry Revolution based on ICT and sensor technology. Following this trend, this paper proposes the design of a model using manufacturing data in the protection film process for smart manufacturing innovation. In the protective film process, the manufacturing data of temperature, pressure, humidity, and motion and thermal image are acquired by various sensors for the raw material blending, stirring, extrusion, and inspection processes. While the acquired manufacturing data is stored in mass storage, A.I. platform provides time-series image analysis and its visualization.

• Electronics and Telecommunications Trends
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• v.34 no.5
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• pp.14-25
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• 2019

As the Internet of Things, artificial intelligence and big data have received a lot of attention as key growth engines in the era of the fourth industrial revolution, data acquisition and utilization in mobile, automotive, robotics, manufacturing, agriculture, health care and national defense are becoming more important. Due to numerous data-based industrial changes, demand for sensor technologies is exploding, especially for intelligent sensor technologies that combine control, judgement, storage and communication functions with the sensors's own functions. Intelligent sensor technology can be defined as a convergence component technology that combines intelligent sensor units, intelligent algorithms, modules with signal processing circuits, and integrated plaform technologies. Intelligent sensor technology, which can be applied to variety of smart IT convergence services such as smart devices, smart homes, smart cars, smart factory, smart cities, and others, is evolving towards intelligent and convergence technologies that produce new high-value information through recognition, reasoning, and judgement based on artificial intelligence. As a result, development of intelligent sensor units is accelerating with strategies for miniaturization, low-power consumption and convergence, new form factor such as flexible and stretchable form, and integration of high-resolution sensor arrays. In the future, these intelligent sensor technologies will lead explosive sensor industries in the era of data-based artificial intelligence and will greatly contribute to enhancing nation's competitiveness in the global sensor market. In this report, we analyze and summarize the recent trends in intelligent sensor technologies, especially those for four core technologies.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.05a
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• pp.127-128
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• 2019

After the financial crisis in 2008, Korean ship-parts manufacturing companies faced the survival of companies due to the difficulty in securing the volume of orders by sharp dropping in orders from big-three Korean shipbuilders. In ship-parts industry, product diversification and overseas market entry are important targets. Based on the expert Delphi survey and SWOT analysis, this study analyzes the key factors of overseas advancement by the growth stage of ship-parts companies and suggests a systematic and efficient overseas marketing strategy. Also, we propose a systematic and efficient advancement into overseas market by suggesting the traditional offline marketing strategy of exporting materials, marketing and marketing, and suggesting the need to build an integrated online and offline platform.