• Korean Journal of Geomatics
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• v.3 no.1
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• pp.33-41
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• 2003

Every year, several typhoons hit the Korean peninsula and cause severe damage. For the prevention and accurate estimation of these damages, real time or almost real time flood information is essential. Because of weather conditions, images taken by optic sensors or LIDAR are sometimes not appropriate for an accurate estimation of water areas during typhoon. In this case SAR (Synthetic Aperture Radar) images which are independent of weather condition can be useful for the estimation of flood areas. To get detailed information about floods from satellite imagery, accurate classification of water areas is the most important step. A commonly- and widely-used classification methods is the ML(Maximum Likelihood) method which assumes that the distribution of brightness values of the images follows a Gaussian distribution. The distribution of brightness values of the SAR image, however, usually does not follow a Gaussian distribution. For this reason, in this study the ANN (Artificial Neural Networks) method independent of the statistical characteristics of images is applied to the SAR imagery. RADARS A TSAR images are primarily used for extraction of water areas, and DEM (Digital Elevation Model) is used as supplementary data to evaluate the ground undulation effect. Water areas are also extracted from KOMPSAT image achieved by optic sensors for comparison purpose. Both ANN and ML methods are applied to flat and mountainous areas to extract water areas. The estimated areas from satellite imagery are compared with those of manually extracted results. As a result, the ANN classifier performs better than the ML method when only the SAR image was used as input data, except for mountainous areas. When DEM was used as supplementary data for classification of SAR images, there was a 5.64% accuracy improvement for mountainous area, and a similar result of 0.24% accuracy improvement for flat areas using artificial neural networks.

• The Journal of Industrial Distribution & Business
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• v.11 no.6
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• pp.41-53
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• 2020

Purpose: The purpose of this study is to review the previous studies on the characteristics of the image search service provided by using artificial intelligence, the social impact characteristics, and the moderating effect of perceived anthropomorphism, and conduct empirical analysis to identify the constituent factors affecting purchase intention. To clarify. Through this, I tried to present theoretical and practical implications. Research design, data, and methodology: Research design was that characteristics of image search service (ubiquity and information quality) and social impact characteristics (subjective norms, electronic word of mouth marketing) are affected by mediation of satisfaction and flow, therefore, control of perceived anthropomorphism have an effect on purchase intention to increase. For analysis, research conducted literature review, and developed questionnaires, so that EM firm which is a specialized research institute has collected data. This was conducted on 410 people between the 20s and 50s who have mobile shopping experiences. SPSS Statistics 23 and AMOS 23 had been used to perform necessary analysis such as exploratory factor analysis, reliability analysis, feasibility analysis, and structural equation modeling based on this data. Results: first, ubiquity, information quality and subjective norms were found to have a positive effect on purchase intention through satisfaction and flow parameters. Second, satisfaction and flow were found to have a mediating effect between ubiquity, information quality, and subjective norms and purchase intentions. However, there was no mediating effect between eWOM information and purchase intention. Third, perceived anthropomorphism was found to have a moderating effect between information quality and satisfaction, and it was found that there was no moderating effect on the relationship between information quality and flow. Conclusions: The information quality of image search services using artificial intelligence has a positive effect on satisfaction, and it has been found that there is a positive moderate effect of perceived anthropomorphism in this relationship, which may be an academic contribution to the distribution science utilizing artificial intelligence. Therefore, it is possible to propose a distribution strategy that improves purchase intention by utilizing image search service and anthropomorphism in practical business and providing a more enjoyable immersive experience to customers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.625-626
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• 2015

The optimal distribution pattern for the compensation for the distorted WDM signals due to the group velocity dispersion (GVD) and the nonlinear Kerr effects is induced in $80km{\times}50spans$ optical link with an artificial distributions of single mode fiber (SMF) lengths and residual dispersion per span (RDPS).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.348-350
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• 2018

In this paper, dispersion-managed optimal link configuration with the repetitively artificial-distributed single mode fiber lengths and residual dispersion per span, in which optical phase conjugator placed at midway, is proposed. It is confirmed that the proposed optical link configuration is suitable for expanding transmission length capable to obtain the good performance.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.441-451
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• 2014

This article addresses an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using the artificial bee colony algorithm. The objective function is adapted to enhance the overall system static voltage stability index and to achieve maximum net yearly savings. Load variations have been considered to optimally scope the fixed and switched capacitors required. The numerical results are compared with those obtained using recent heuristic methods and show that the proposed approach is capable of generating high-grade solutions and validated viability.

• Asian Journal of Business Environment
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• v.8 no.4
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• pp.37-44
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• 2018

Purpose - The artificial intelligence industry plays an increasingly significant role in stimulating the development of United States of America's economy. On account of this background, this paper attempts to explore the impact of artificial intelligence industry on United States of America's macroeconomy. Research design, data, and methodology - This paper mainly focuses on the impact of artificial intelligence industry on GDP, employment, real income, import, export and foreign direct investment. Furthermore, the Phillips-Perron test and Canonical cointegrating regression will be employed to examine the impact of artificial intelligence industry on United States of America's macroeconomy with a sample form 2010-Q1 to 2017-Q4. Results - Via the empirical analysis, the results reveal that the artificial intelligence industry has a positive effect on United States of America's GDP, employment, real income, export and foreign direct investment. Conversely, the artificial intelligence industry has a negative effect on United States of America's import. Conclusions - In summary, the impact of artificial intelligence industry on United States of America's macroeconomy is positive and significant in statistics. Therefore, the government of United States of America should put more input into artificial intelligence industry.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.3
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• pp.41-48
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• 2014

This paper proposes a new sensor circuit using a 32 nm carbon nanotube FET (CNFET) technology for artificial skin. For future robotic and prosthetic applications, it is essential to develop a robust and low power artificial skin for detecting the environment through touch. Therefore, a sensor circuit for the artificial skin also has to be developed to detect the sensor signals and convert them into digital bits. The artificial skin sensor is based on a mesh of sensors consisting of a nxn matrix using CNFET, and the sensor outputs are connected to a current monitoring circuit proposed as the sensor circuit. The proposed sensor provides pressure measurements and shape information about pressure distribution.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1042-1047
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• 2004

Voltage control is an essential part of the electric energy transmission and distribution system to maintain proper voltage limit at the consumer's terminal. Besides the generating units that provide the basic voltage control, there are many additional voltage-controlling agents e.g., shunt capacitors, shunt reactors, static VAr compensators, regulating transformers mentioned in [1], [2]. The most popular one, among all those agents for controlling voltage levels at the distribution and transmission system, is the on-load tap changer transformer. It serves two functions-energy transformation in different voltage levels and the voltage control. Artificial Neural Network (ANN) has been realized as a convenient tool that can be used in controlling the on load tap changer in the distribution transformers. Usage of the ANN in this area needs suitable training and testing data for performance analysis before the practical application. This paper briefly describes a procedure of processing the data to train an Artificial Neural Network (ANN) to control the tap changer operating decision of parallel transformers for a closed primary bus. The data set are used to train a two layer ANN using three different neural net learning algorithms, namely, Standard Backpropagation [3], Bayesian Regularization [4] and Scaled Conjugate Gradient [5]. The experimental results are presented including performance analysis.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.676-683
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• 2003

A laboratory experiment using artificial fracture rocks was used to understand the 3-dimensional dispersion of a tracer and the mixing process in a fractured network. In this experiment, 12cm polystyrene foam cubes with two electrodes for monitoring electric conductivity (EC) were used as artificial fractured rocks. Distilled water with 0.5mS/m was used as a tracer in water with 35mS/m and the difference of EC between the tracer and the water was monitored by a multipoint simultaneous measurement system of electrical resistance. The results showed that even if the fracture arrangement pattern was not straight in the direction of the flow, the tracer did not diffuse along individual fractures and an oval tracer plume, which was the distribution of tracer concentrations, tended to be form in the direction of the flow. The vertical cross section of the tracer distribution showed small diffusivity in the vertical direction. The calculated total tracer volume passing through each measurement point in the horizontal cross section showed while that the solute passed through measurement points near the direction of hydraulic gradient and in other directions, the passed tracer volumes were small. Using Peclet number as a criterion, it was found that the mass distribution at the fracture intersection was controlled in the stage of transition between the complete mixing model and the streamline routing model.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.50 no.1
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• pp.30-38
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• 2014

Hydro-acoustic survey was carried out to investigate the spatial characteristics of fish distribution near two artificial reefs (AO: large octagonal semi-sphere and AC: combined custom built) having different types in Jeju marine ranching area. The survey system consisted of scientific echo sounder (EK60), DGPS system, and ECDIS (Mecys). Field survey was conducted on August and October 2012 with star survey and line transect survey line method, and species composition was investigated from gill net fishing survey. The acoustic signals from individual fishes and small fish schools were mainly recorded around AO, but large and strong signals from large fish school were mainly detected in the top layer of and the water column near AC. The echogram suggest that the fish aggregation for the two types of AO and AC exist the significant difference in fish species and spatial distribution pattern.