• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1493-1507
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• 2020

The LEOP Cal/Val (Launch and Early Operation Phase Calibration/Validation) was carried out during 6 months after KOMPSAT-3A (KOMPSAT-3A Korea Multi-Purpose Satellite-3A) was launched in March 2015. After LEOP Cal/Val was successfully completed, high resolution KOMPSAT-3A has been successfully distributing to users over the past 8 years. The sub-meter high-resolution satellite image data obtained from KOMPSAT-3A is used as basic data for qualitative and quantitative information extraction in various fields such as mapping, GIS (Geographic Information System), and national land management, etc. The KARI (Korea Aerospace Research Institute) periodically checks and manages the quality of KOMPSAT-3A's product and the characteristics of satellite hardware to ensure the accuracy and reliability of information extracted from satellite data of KOMPSAT-3A. To minimize the deterioration of image quality due to aging of satellite hardware, payload and attitude sensors of KOMPSAT-3A, continuous improvement of image quality has been carried out. In this paper, the Cal/Val work-flow defined in the KOMPSAT-3A development phase was illustrated for the period of before and after the launch. The MTF, SNR, and location accuracy are the key parameters to estimate image quality and the methods of the measurements of each parameter are also described in this work. On the basis of defined quality parameters, the performance was evaluated and measured during the period of after LEOP Cal/Val. The current status and characteristics of MTF, SNR, and location accuracy of KOMPSAT-3A from 2016 to May 2020 were described as well.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.101-125
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• 2022

Recently, with the development of computing technology and the improvement of the cloud environment, deep learning technology has developed, and attempts to apply deep learning to various fields are increasing. A typical example is anomaly detection, which is a technique for identifying values or patterns that deviate from normal data. Among the representative types of anomaly detection, it is very difficult to detect a contextual anomaly that requires understanding of the overall situation. In general, detection of anomalies in image data is performed using a pre-trained model trained on large data. However, since this pre-trained model was created by focusing on object classification of images, there is a limit to be applied to anomaly detection that needs to understand complex situations created by various objects. Therefore, in this study, we newly propose a two-step pre-trained model for detecting abnormal situation. Our methodology performs additional learning from image captioning to understand not only mere objects but also the complicated situation created by them. Specifically, the proposed methodology transfers knowledge of the pre-trained model that has learned object classification with ImageNet data to the image captioning model, and uses the caption that describes the situation represented by the image. Afterwards, the weight obtained by learning the situational characteristics through images and captions is extracted and fine-tuning is performed to generate an anomaly detection model. To evaluate the performance of the proposed methodology, an anomaly detection experiment was performed on 400 situational images and the experimental results showed that the proposed methodology was superior in terms of anomaly detection accuracy and F1-score compared to the existing traditional pre-trained model.

• Korean journal of aerospace and environmental medicine
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• v.31 no.1
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• pp.24-30
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• 2021

Purpose: The purpose of this study is to consider ways to strengthen it through comparison and curriculum while recognizing the importance of global competencies in liberal arts education in universities. Methods: In order to explore ways to reinforce the sub-competence of global competencies, this study was conducted at a four-year university in Chungcheong-do for one year in 2019, such as 'Global Culture Talk', 'Global Travel', 'Global Nanta', and 'Making Global Friends'. Cases of comparison and application of educational programs were analyzed. The program was attended by the Department of Business Administration, Department of Aviation Service, Department of Design, Department of Manga Animation, Department of Broadcasting and Film, and foreign exchange students. The competency-centered curriculum not only has clear educational goals, but is also very advantageous in establishing a feedback system by measuring its performance. This study will assess the effectiveness of the education plan by diagnosing the change in competencies before and after the comparison and curriculum is operated. Results: The overall global competency has increased by 0.2 points compared to 2017. By subsector, it was found that the flexibility increased by 1.4 points. In the field of cross-cultural understanding, it rose 0.6 points, and in the field of global understanding, it rose 2.2 points, showing the largest increase in the sub-fields. Nevertheless, the field of global interest remains at a low level. This is considerably low compared to flexibility and ability to understand other cultures, and it is expected that measures for improvement should be continuously sought. Since the understanding of other cultures has already exceeded 60 points, it is expected that the global competency of the university will be strengthened if the level is consistently maintained and the emphasis is placed on enhancing flexibility and improving global understanding. Conclusion: The importance of strengthening global capabilities is steadily rising. Universities are also reorganizing the curriculum by analyzing the needs and satisfaction of education consumers to respond to this. The programs operated and analyzed in this study were also made as part of this effort. However, since there are various factors that affect global competency, it cannot be but admitted that it is not easy to gauge the change in competency with only a few programs and short-term efforts. However, if the efforts pursued by this study are accumulated and supplemented through feedback from a long-term perspective, it can be expected that there are not a lot of contributions to strengthening global competencies in liberal arts education.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.25-36
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• 2023

Today, as AI (Artificial Intelligence) technology is introduced in various fields, including security, the development of technology is accelerating. However, with the development of AI technology, attack techniques that cleverly bypass malicious behavior detection are also developing. In the classification process of AI models, an Adversarial attack has emerged that induces misclassification and a decrease in reliability through fine adjustment of input values. The attacks that will appear in the future are not new attacks created by an attacker but rather a method of avoiding the detection system by slightly modifying existing attacks, such as Adversarial attacks. Developing a robust model that can respond to these malware variants is necessary. In this paper, we propose two methods of generating Adversarial attacks as efficient Adversarial attack generation techniques for improving Robustness in AI models. The proposed technique is the XAI-based attack technique using the XAI technique and the Reference based attack through the model's decision boundary search. After that, a classification model was constructed through a malicious code dataset to compare performance with the PGD attack, one of the existing Adversarial attacks. In terms of generation speed, XAI-based attack, and reference-based attack take 0.35 seconds and 0.47 seconds, respectively, compared to the existing PGD attack, which takes 20 minutes, showing a very high speed, especially in the case of reference-based attack, 97.7%, which is higher than the existing PGD attack's generation rate of 75.5%. Therefore, the proposed technique enables more efficient Adversarial attacks and is expected to contribute to research to build a robust AI model in the future.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.1-10
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• 2023

This paper proposes a method to extend Inter-Carrier Interference (ICI) canceling Orthogonal Frequency Division Multiplexing (OFDM) receivers for 5G mobile systems to spatial multiplexing 2×2 MIMO (Multiple Input Multiple Output) systems to support high-speed ground transportation services by linear motor cars traveling at 500 km/h. In Japan, linear-motor high-speed ground transportation service is scheduled to begin in 2027. To expand the coverage area of base stations, 5G mobile systems in high-speed moving trains will have multiple base station antennas transmitting the same downlink (DL) signal, forming an expanded cell size along the train rails. 5G terminals in a fast-moving train can cause the forward and backward antenna signals to be Doppler-shifted in opposite directions, so the receiver in the train may have trouble estimating the exact channel transfer function (CTF) for demodulation. A receiver in such high-speed train sees the transmission channel which is composed of multiple Doppler-shifted propagation paths. Then, a loss of sub-carrier orthogonality due to Doppler-spread channels causes ICI. The ICI Canceller is realized by the following three steps. First, using the Demodulation Reference Symbol (DMRS) pilot signals, it analyzes three parameters such as attenuation, relative delay, and Doppler-shift of each multi-path component. Secondly, based on the sets of three parameters, Channel Transfer Function (CTF) of sender sub-carrier number n to receiver sub-carrier number l is generated. In case of n≠l, the CTF corresponds to ICI factor. Thirdly, since ICI factor is obtained, by applying ICI reverse operation by Multi-Tap Equalizer, ICI canceling can be realized. ICI canceling performance has been simulated assuming severe channel condition such as 500 km/h, 8 path reverse Doppler Shift for QPSK, 16QAM, 64QAM and 256QAM modulations. In particular, 2×2MIMO QPSK and 16QAM modulation schemes, BER (Bit Error Rate) improvement was observed when the number of taps in the multi-tap equalizer was set to 31 or more taps, at a moving speed of 500 km/h and in an 8-pass reverse doppler shift environment.

• Journal of the International Relations & Interdisciplinary Education
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• v.4 no.1
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• pp.1-18
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• 2024

This study is a qualitative case study on the experience of an on-site, audience-participatory educational play conducted by four college students majoring in theater under the title 'Hooni and Choroki' for 7-year-old kindergarten students about to enter elementary school. The core theme of the play is to help relieve anxiety about school life before entering elementary school and to communicate smoothly with peers. To this end, college students participate in scenario planning, kindergarten recruitment, and 40-minute training at three kindergartens. He even conducted theatrical performances. As a result of the study, the key components of 'another growth in my life', 'improvement of happiness through meeting children', and 'new challenge toward dreams' were derived. The greatest significance of this study is that the audience-participatory educational theater experience allowed college students to practice sharing the results of their learning with someone else, and through this practice of sharing learning, they were able to realize their somewhat vague career paths and dreams. It was an opportunity that allowed me to experience 'improved confidence' and 'a resonance in my heart' so that I could set a direction. We hope that future educational theater with audience participation will be widely implemented in various aspects.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.48-66
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• 2024

According to the three amended Laws of the Data Economy and the Data Industry Act of Korea, systems for pseudonymous data integration and Data Safe Zones have been operated separately by selected agencies, eventually causing a burden of use in SMEs, startups, and general users because of complicated and ineffective procedures. An over-stringent pseudonymization policy to prevent data breaches has also compromised data quality. Such trials should be improved to ensure the convenience of use and data quality. This paper proposes a prototype system of the Integrated Data Safe Zone based on redesigned and optimized pseudonymization workflows. Conventional workflows of pseudonymization were redesigned by applying the amended guidelines and selectively revising existing guidelines for business process redesign. The proposed prototype has been shown quantitatively to outperform the conventional one: 6-fold increase in time efficiency, 1.28-fold in cost reduction, and 1.3-fold improvement in data quality.

• Research in Plant Disease
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• v.8 no.2
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• pp.84-91
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• 2002

Disease forecasting in Korea was first studied in the Department of Fundamental Research, in the Central Agricultural Technology Institute in Suwon in 1947, where the dispersal of air-borne conidia of blast and brown spot pathogens in rice was examined. Disease forecasting system in Korea is operated based on information obtained from 200 main forecasting plots scattered around country (rice 150, economic crops 50) and 1,403 supplementary observational plots (rice 1,050, others 353) maintained by Korean government. Total number of target crops and diseases in both forecasting plots amount to 30 crops and 104 diseases. Disease development in the forecasting plots is examined by two extension agents specialized in disease forecasting, working in the national Agricul-tural Technology Service Center(ATSC) founded in each city and prefecture. The data obtained by the extension agents are transferred to a central organization, Rural Development Administration (RDA) through an internet-web system for analysis in a nation-wide forecasting program, and forwarded far the Central Forecasting Council consisted of 12 members from administration, university, research institution, meteorology station, and mass media to discuss present situation of disease development and subsequent progress. The council issues a forecasting information message, as a result of analysis, that is announced in public via mass media to 245 agencies including ATSC, who informs to local administration, the related agencies and farmers for implementation of disease control activity. However, in future successful performance of plant disease forecasting system is thought to be securing of excellent extension agents specialized in disease forecasting, elevation of their forecasting ability through continuous trainings, and furnishing of prominent forecasting equipments. Researches in plant disease forecasting in Korea have been concentrated on rice blast, where much information is available, but are substan-tially limited in other diseases. Most of the forecasting researches failed to achieve the continuity of researches on specialized topic, ignoring steady improvement towards practical use. Since disease forecasting loses its value without practicality, more efforts are needed to improve the practicality of the forecasting method in both spatial and temporal aspects. Since significance of disease forecasting is directly related to economic profit, further fore-casting researches should be planned and propelled in relation to fungicide spray scheduling or decision-making of control activities.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.307-319
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• 2016

A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.

• Asia pacific journal of information systems
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• v.17 no.3
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• pp.105-130
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• 2007

Recently, there is a substantial interest in implementing Business Process Management System(BPMS) among enterprises with the purpose of business process innovation. BPMS redesigns and coordinates business processes in terms of both automated steps and human involvement in order to maximize the value of both involved people and systems. The reason why BPMS is getting attention from top managers is that it has the possibility to optimize the business processes by cycling the process of modeling, execution, monitoring, evaluation, and redesigning work processes. Thus, it has created high expectations about not only productivity improvement but also business process innovation. However. having an innovative nature, which is used for process innovation, BPMS implementation has great potential to stir up employee resistance. The analysis and the discussion about the prevention of the resistance against IS(Information Systems) is important because IS change the way people work and also alter the power structure within the organization, in general. The purpose of this study is to investigate factors that have an impact on the effective adoption of BPMS at the enterprise level. To find out these factors, this study considers two characteristics of BPMS: First. BPMS shares some characteristics with other enterprise-wide IS such as ERP. Second, it has special BPMS-specific characteristics. Due to the lack of previous research on BPMS adoption, interviews were carried out with IT-consultants and CIOs who conducted BPMS projects previously to find out BPMS-specific features that would make BPMS unique when compared to other enterprise-wide IS. As a result, the monitoring function was chosen as the main BPMS-specific factor. Thus, this paper reviewed studies both on enterprise-wide IS adoptions, which applied Technology Acceptance Model (TAM) and secondly on computer based monitoring to find out factors that would influence the employees' perception on the monitoring function of BPMS. Based on the literature review, the study suggested three factors that would have an impact on the employee's perception of the monitoring function: fairness of enterprise evaluation system, fairness of the boss, and self-efficacy of their work. Three factors that would impact the enterprise-wide IS adoption were also set: the shared belief in the benefit of BPMS, training, and communication. Then, these factors were integrated with TAM. Structural equation modeling was used to test hypotheses, out factors that would impact the employees' perception on the monitoring function of BPMS. Based on the literature review the study suggested three factors that would have an impact on the employee's perception of the monitoring function: fairness of enterprise evaluation system, fairness of the boss, and self-efficacy of their work. Three factors that would impact the enterprise-wide IS adoption were also set: the shared belief in the benefit of BPMS, training, and communication. Then, these factors were integrated with TAM. Structural equation modeling was used to test hypotheses. The data analysis results showed that two among three monitoring function related factors - enterprise evaluation system and fairness of the boss - were significant. This implies that employees would worry less about the BPMS implementation as long as they perceive the monitoring results will be used fairly for their performance evaluation. However, employees' high self-efficacy on their job was not a significant factor in their perception of the usefulness of BPMS. This is related to cases that showed employees resisted against the information systems because they automated their works (Markus, 1983). One specific case was an electronic company, where the accounting department workers were requested to redefine their job because their working processes were automated due to BPMS implementation.