• Nuclear Engineering and Technology
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• 제55권1호
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• pp.100-108
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• 2023

In this study, a neural network model inspired by a one-dimensional convolution U-net is developed to automatically accelerate edge localized mode (ELM) detection from big diagnostic data of fusion devices and increase the detection accuracy regardless of the hyperparameter setting. This model recognizes the input signal patterns and overcomes the problems of existing detection algorithms, such as the prominence algorithm and those of differential methods with high sensitivity for the threshold and signal intensity. To train the model, 10 sets of discharge radiation data from the KSTAR are used and sliced into 11091 inputs of length 12 ms, of which 20% are used for validation. According to the receiver operating characteristic curves, our model shows a positive prediction rate and a true prediction rate of approximately 90% each, which is comparable to the best detection performance afforded by other algorithms using their optimized hyperparameters. The accurate and automatic ELM-burst detection methodology used in our model can be beneficial for determining plasma properties, such as the ELM frequency from big data measured in multiple experiments using machines from the KSTAR device and ITER. Additionally, it is applicable to feature detection in the time-series data of other engineering fields.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1597-1600
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• 1991

In this paper, we describe a notion of sensor modeling method in multisensor data fusion using fuzzy set theory. Each sensor module is characterized by its fuzzy constraints to specific features of environment. These sensor fuzzy constraints can be imposed on multisensory data to verify their degree of truth and compatibility toward the final decision making. In comparison with other sensor modeling methods, such as probabilistic models or rule-based models, the proposed method is very simple and can be easily implemented in intelligent robot systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권8호
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• pp.2749-2763
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• 2021

The desirable result of infrared (IR) and visible (VIS) image fusion should have textural details from VIS images and salient targets from IR images. However, detail information in the dark regions of VIS image has low contrast and blurry edges, resulting in performance degradation in image fusion. To resolve the troubles of fuzzy details in dark regions of VIS image fusion, we have proposed a method of reflectance estimation for IR and VIS image fusion. In order to maintain and enhance details in these dark regions, dark region approximation (DRA) is proposed to optimize the Retinex model. With the improved Retinex model based on DRA, quasi-Newton method is adopted to estimate the reflectance of a VIS image. The final fusion outcome is obtained by fusing the DRA-based reflectance of VIS image with IR image. Our method could simultaneously retain the low visibility details in VIS images and the high contrast targets in IR images. Experiment statistic shows that compared to some advanced approaches, the proposed method has superiority on detail preservation and visual quality.

• 한국초전도학회:학술대회논문집
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• 한국초전도학회 2005년도 High Temperature Superconductivity Vol.XV
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• pp.45-45
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• 2005

• 한국고분자학회지:고분자과학과기술
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• 제22권5호
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• pp.467-473
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• 2011

• 한국축산시설환경학회지
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• 제18권sup호
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• pp.7-12
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• 2012

To prevent the inappropriate treatment of livestock manure and induce the correct circulation of them into farmland, systematic monitoring and management by the treatment and circulation stage of livestock manure are required. The purpose of this study was to apply ubiquitous information communictation technology (u-ICT) to a livestock waste management system for better treatment by utilizing ubiquitous computing technology in the livestock sector. Elements and levels of applicable u-ICT technology for efficient livestock manure management were derived by analyzing previous researches. In addition, a conceptual diagram of an integrated management system was suggested by analyzing the existing liquid fertilization process.

• International journal of advanced smart convergence
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• 제4권2호
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• pp.69-75
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• 2015

There are several possible places which are accessible in many buildings and facilities, various types of systems have been utilized such as access control or surveillance depending on the purpose. Especially if security is important, it must go through the various authentication procedures when people can access. Until now many access control systems have been proposed and developed, they are applied and utilized to companies which security is needed. However, as time passes the problems with existing access control systems occur or the vulnerabilities related to access control are reported, as technology advances. The solution to this, we propose authentication technology related to access control using LED-QR tag.

• 제어로봇시스템학회논문지
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• 제17권10호
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• pp.995-1005
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• 2011

An efficient outdoor local localization method is suggested using multi-sensor fusion with MU-EKF (Multi-Update Extended Kalman Filter) for car-like mobile robots. In outdoor environments, where mobile robots are used for explorations or military services, accurate localization with multiple sensors is indispensable. In this paper, multi-sensor fusion outdoor local localization algorithm is proposed, which fuses sensor data from LRF (Laser Range Finder), Encoder, and GPS. First, encoder data is used for the prediction stage of MU-EKF. Then the LRF data obtained by scanning the environment is used to extract objects, and estimates the robot position and orientation by mapping with map objects, as the first update stage of MU-EKF. This estimation is finally fused with GPS as the second update stage of MU-EKF. This MU-EKF algorithm can also fuse more than three sensor data efficiently even with different sensor data sampling periods, and ensures high accuracy in localization. The validity of the proposed algorithm is revealed via experiments.

• International Journal of Advanced Culture Technology
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• 제11권4호
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• pp.202-209
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• 2023

In the 21st century, the dualistic worldview of the Cold War era collapsed and we entered an era of new creation and fusion. The fusion of different designs between East and West, the design activities of traditional clothing from the past, the use of new materials that are continuously being developed, and the mixing of unique items are being conducted in various fields. However, research is being conducted by combining fusion characteristics with hair. In addition, the period is short and the amount of research is small. Therefore, this study analyzed hairstyles of fusion images shown in hair collection using data of Juno Hair collection from 2013 to 2022 as analysis data and examined types of fusion images shown in the work of folk images, mixed images, and future images. Oriented images were divided into three categories and analyzed. In this study, we added Results of such research can be used not only as data for predicting future fashion trends, but also as basic data for exploring new design developments. In future research, it is expected that convergent research will be conducted, such as analyzing fusion images from an integrated perspective.

• Bulletin of the Korean Chemical Society
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• 제35권10호
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• pp.2889-2890
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• 2014