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Proposal of An Artificial Intelligence based Temperature Prediction Algorithm for Efficient Agricultural Activities -Focusing on Gyeonggi-do Farm House-

  • Jang, Eun-Jin;Shin, Seung-Jung
    • International journal of advanced smart convergence
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    • v.10 no.4
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    • pp.104-109
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    • 2021
  • In the aftermath of the global pandemic that started in 2019, there have been many changes in the import/export and supply/demand process of agricultural products in each country. Amid these changes, the necessity and importance of each country's food self-sufficiency rate is increasing. There are several conditions that must accompany efficient agricultural activities, but among them, temperature is by far one of the most important conditions. For this reason, the need for high-accuracy climate data for stable agricultural activities is increasing, and various studies on climate prediction are being conducted in Korea, but data that can visually confirm climate prediction data for farmers are insufficient. Therefore, in this paper, we propose an artificial intelligence-based temperature prediction algorithm that can predict future temperature information by collecting and analyzing temperature data of farms in Gyeonggi-do in Korea for the last 10 years. If this algorithm is used, it is expected that it can be used as an auxiliary data for agricultural activities.

Disturbance observer-based robust backstepping load-following control for MHTGRs with actuator saturation and disturbances

  • Hui, Jiuwu;Yuan, Jingqi
    • Nuclear Engineering and Technology
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    • v.53 no.11
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    • pp.3685-3693
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    • 2021
  • This paper presents a disturbance observer-based robust backstepping load-following control (DO-RBLFC) scheme for modular high-temperature gas-cooled reactors (MHTGRs) in the presence of actuator saturation and disturbances. Based on reactor kinetics and temperature reactivity feedback, the mathematical model of the MHTGR is first established. After that, a DO is constructed to estimate the unknown compound disturbances including model uncertainties, external disturbances, and unmeasured states. Besides, the actuator saturation is compensated by employing an auxiliary function in this paper. With the help of the DO, a robust load-following controller is developed via the backstepping technique to improve the load-following performance of the MHTGR subject to disturbances. At last, simulation and comparison results verify that the proposed DO-RBLFC scheme offers higher load-following accuracy, better disturbances rejection capability, and lower control rod speed than a PID controller, a conventional backstepping controller, and a disturbance observer-based adaptive sliding mode controller.

Detection of Art Exhibitions using Augmented Reality Technology (증강현실 기술을 적용한 미술 전시품 검출)

  • Lee, Yong-Hwan;Kim, Youngseop
    • Journal of the Semiconductor & Display Technology
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    • v.17 no.4
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    • pp.101-104
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    • 2018
  • Augmented Reality (AR) is an emerging technology and the applications of technology are still not fully unveiled. This paper explores a new application of augmented reality for new direction in art exhibitions, which aims to bring interactive learning experience to life. The project takes printed images on book or exhibiting arts to the next level by applying AR technology to provide a unique fascinating experience to its readers on mobile devices. AR technology composing with animation brings new digital entertainment experience to the user of art exhibitions. The key feature of this paper uses the technology presents auxiliary information in the field of view of an object on art exhibitions automatically without human intervention.

Genome-Wide Comparison of Carbohydrate-Active Enzymes (CAZymes) Repertoire of Flammulina ononidis

  • Park, Young-Jin;Kong, Won-Sik
    • Mycobiology
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    • v.46 no.4
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    • pp.349-360
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    • 2018
  • Whole-genome sequencing of Flammulina ononidis, a wood-rotting basidiomycete, was performed to identify genes associated with carbohydrate-active enzymes (CAZymes). A total of 12,586 gene structures with an average length of 2009 bp were predicted by the AUGUSTUS tool from a total 35,524,258 bp length of de novo genome assembly (49.76% GC). Orthologous analysis with other fungal species revealed that 7051 groups contained at least one F. ononidis gene. In addition, 11,252 (89.5%) of 12,586 genes for F. ononidis proteins had orthologs among the Dikarya, and F. ononidis contained 8 species-specific genes, of which 5 genes were paralogous. CAZyme prediction revealed 524 CAZyme genes, including 228 for glycoside hydrolases, 21 for polysaccharide lyases, 87 for glycosyltransferases, 61 for carbohydrate esterases, 87 with auxiliary activities, and 40 for carbohydrate-binding modules in the F. ononidis genome. This genome information including CAZyme repertoire will be useful to understand lignocellulolytic machinery of this white rot fungus F. ononidis.

An Overview of Theoretical and Practical Issues in Spatial Downscaling of Coarse Resolution Satellite-derived Products

  • Park, No-Wook;Kim, Yeseul;Kwak, Geun-Ho
    • Korean Journal of Remote Sensing
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    • v.35 no.4
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    • pp.589-607
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    • 2019
  • This paper presents a comprehensive overview of recent model developments and practical issues in spatial downscaling of coarse resolution satellite-derived products. First, theoretical aspects of spatial downscaling models that have been applied when auxiliary variables are available at a finer spatial resolution are outlined and discussed. Based on a thorough literature survey, the spatial downscaling models are classified into two categories, including regression-based and component decomposition-based approaches, and their characteristics and limitations are then discussed. Second, open issues that have not been fully taken into account and future research directions, including quantification of uncertainty, trend component estimation across spatial scales, and an extension to a spatiotemporal downscaling framework, are discussed. If methodological developments pertaining to these issues are done in the near future, spatial downscaling is expected to play an important role in providing rich thematic information at the target spatial resolution.

Transient Alert Message Processing System for the LSST era

  • Shin, Min-Su
    • The Bulletin of The Korean Astronomical Society
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    • v.44 no.1
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    • pp.71.2-71.2
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    • 2019
  • We have developed and tested a prototype system to process transient alert messages from the currently working facilities such as Gaia and GCN notices. Our experiments with the prototype focus on developing a platform that can be used in the LSST era with about 10 million alerts per night and helping Korean community members with the automated processing environment to provide auxiliary information for every alert message. The system consists of a message broker implemented by Redis and multiple message subscribers specialized for specific scientific interests. The current implementation of the entire system allows new Korean members to adopt their own processing chains receiving the messages from our local broker. We welcome experimental ideas and opinions from the Korean community about the current message processing system. We plan to test the current system with the ZTF alerts in the near future.

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Comparative Analysis of Diagnostic Prediction Algorithm Performance for Blood Cancer Factor Validation and Classification (혈액암 인자 유효성 검증과 분류를 위한 진단 예측 알고리즘 성능 비교 분석)

  • Jeong, Jae-Seung;Ju, Hyunsu;Cho, Chi-Hyun
    • Journal of Korea Multimedia Society
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    • v.25 no.10
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    • pp.1512-1523
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    • 2022
  • Artificial intelligence application in digital health care has been increasing with its development of artificial intelligence. The convergence of the healthcare industry and information and communication technology makes the diagnosis of diseases more simple and comprehensible. From the perspective of medical services, its practice as an initial test and a reference indicator may become widely applicable. Therefore, analyzing the factors that are the basis for existing diagnosis protocols also helps suggest directions using artificial intelligence beyond previous regression and statistical analyses. This paper conducts essential diagnostic prediction learning based on the analysis of blood cancer factors reported previously. Blood cancer diagnosis predictions based on artificial intelligence contribute to successfully achieve more than 90% accuracy and validation of blood cancer factors as an alternative auxiliary approach.

Development of f-chart for the Design of Solar Heating Systems (태양열난방장치 설계를 위한 f-chart 개발)

  • Song Dal-Sun;Yoo Seong-Yeon
    • The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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    • v.15 no.3
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    • pp.292-298
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    • 1986
  • The new f-chart capable of estimating long-term thermal performance of solar space and water heating systems was developed. The system comprise a flat plate solar collector, heat exchanger, storage tank filled with water, auxiliary fuel fired heater, and a house structure. The information obtained from many simulations of solar heating systems has been used to develop this f-chart. Actual hourly meteorological data collected in Seoul, Daejeon, Kwangju and Daegu, Korea from 1979 to 1983 have been utilized in these simulations. The new f-equation is as follows: $$f=1.034Y_{-}0.0968X_{-}0.2235Y^2+0.0043X^2+0.0144Y^3$$. The system performance estimates obtained from the developed f-chart are in close agreement with the results of experiment.

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Direct Adaptive Control of Nonminimum Phase Systgems based on PID Structures (PID 구조를 기초로 한 비최소 위상 시스템의 직접적응제어)

  • Kim, Jong-Hwan;Choi, Keh-Kun
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.23 no.6
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    • pp.895-901
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    • 1986
  • This paper presents direct adaptive controllers for single-input single-output nonminimum phase systems based on PID structures. Also, characteristics of these schemes are compared, and convergence properties are considered. In these schemes, controller parameters are estimated from the least-square algorithm and some additional auxiliary parameters are obtained from the proposed polynomial identity which is derived from the pole placement equation and the Bezout identity. The effectiveness of these schemes is demonstrated by computer simulation that has been carried out for a very difficult example.

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Analyzing Preprocessing for Correcting Lighting Effects in Hyperspectral Images (초분광영상의 조명효과 보정 전처리기법 분석)

  • Yeong-Sun Song
    • Journal of the Korean Society of Industry Convergence
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    • v.26 no.5
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    • pp.785-792
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    • 2023
  • Because hyperspectral imaging provides detailed spectral information across a broad range of wavelengths, it can be utilized in numerous applications, including environmental monitoring, food quality inspection, medical diagnosis, material identification, art authentication, and crime scene analysis. However, hyperspectral images often contain various types of distortions due to the environmental conditions during image acquisition, which necessitates the proper removal of these distortions through a data preprocessing process. In this study, a preprocessing method was investigated to effectively correct the distortion caused by artificial light sources used in indoor hyperspectral imaging. For this purpose, a halogen-tungsten artificial light source was installed indoors, and hyperspectral images were acquired. The acquired images were then corrected for distortion using a preprocessing that does not require complex auxiliary equipment. After the corrections were made, the results were analyzed. According to the analysis, a statistical transformation technique using mean and standard deviation with reference to a reference signal was found to be the most effective in correcting distortions caused by artificial light sources.