• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.185-194
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• 2022

The software industry makes it possible to converge science and Information and Communication Technologies (ICT), create new markets, and create jobs. It is a key industry in the 21^st century knowledge and information age, which is growing very rapidly. This study uses Input-output analysis to derive Linkage effect of the software industry in Korea and the United States (US), and compares the result with CO₂ inducement effect to verify whether the industry meets the low carbon emission development strategy. As the result of this study, first, the software industries in Korea and the US are confirmed to have large influences on the national economy. Second, the Korean software industry has a low Forward linkage effect, so it is less affected by the output of other industries. On the other hand, in the US, it has a high Forward linkage effect and can induce a lot of output in others. Third, CO₂ inducement effects of the industry in Korea and the US are both low, confirming that the industry is suitable for a sustainable future.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.91-101
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• 2022

This study started with the awareness that the review of the historical origins of Korean broadcasting will be of great significance in exploring the future of Korean broadcasting, and examined the various "origins" of Korean broadcasting - colonial, Cold War, totalitarian, neoliberal. Based on the theoretical background of "media archaeology", the historical 'origin' of Korean broadcasting was applied to track the origin of Hallyu(the Korean Wave) in the 21st century by comprehensively examining the political and economic motives of the time, the state's situational awareness of problems, major broadcasting policies and broadcasting realities. As a result of the study, it came to the tentative conclusion that the historical origin of the Hallyu, which began to be formed in the 1980s, originated from the three origins of Korean broadcasting and the "synthetic mixture" in the subsequent development process.

• Analyses & Alternatives
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• v.6 no.2
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• pp.5-36
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• 2022

The Russia-Ukraine War was a "three-layer compounded war" between the US and Russia, Russia and Ukraine, and Ukrainian government forces and rebels. First, the war is a phenomenon that occurred when the western sphere of influence seeking to maintain and strengthen the liberal international order and the Sino-Russian sphere of influence seeking a new alternative order collided in Ukraine, a geopolitical fault zone. Second, this war is the result of a typical 'security dilemma' phenomenon caused by the 'chain reaction' game of NATO's continuous expansion and Russia's response. Third, the Russia-Ukraine war was caused by the Russian military projection to prevent the military restoration of Donbas region by Ukraine. Until now, the Western world, led by the US, showed unexpected solidarity after the war despite subtle differences in positions. However, the non-Western world, including China, is not participating in the condemnation and sanctions against Russia. This war will be an important turning point in the existence and change of the current international order that has been formed and is operating since the end of the Cold War. The direction of maintenance/restoration, revision/change, and end/transformation of the current international order is highly likely to be determined depending on the development pattern and method of ending the war.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.103-111
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• 2023

This paper proposes a new data correction technique that transforms anomalies in time series data into normal values. With the recent development of IT technology, a vast amount of time-series data is being collected through sensors. However, due to sensor failures and abnormal environments, most of time-series data contain a lot of anomalies. If we build a predictive model using original data containing anomalies as it is, we cannot expect highly reliable predictive performance. Therefore, we utilizes the LSTM-GAN model to detect anomalies in the original time series data, and combines DTW (Dynamic Time Warping) and GAN techniques to replace the anomaly data with normal data in partitioned window units. The basic idea is to construct a GAN model serially by applying the statistical information of the window with normal distribution data adjacent to the window containing the detected anomalies to the DTW so as to generate normal time-series data. Through experiments using open NAB data, we empirically prove that our proposed method outperforms the conventional two correction methods.

• The Korean Journal of Applied Statistics
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• v.36 no.2
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• pp.115-127
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• 2023

Multinomial probit model is a popular model for multiclass classification and choice model. Markov chain Monte Carlo (MCMC) method is widely used for estimating multinomial probit model, but its computational cost is high. However, it is well known that variational Bayesian approximation is more computationally efficient than MCMC, because it uses subsets of samples. In this study, we describe multinomial probit model with Gaussian process classification and how to employ variational Bayesian approximation on the model. This study also compares the results of variational Bayesian multinomial probit model to the results of naive Bayes, K-nearest neighbors and support vector machine for the UCI mice protein expression level data.

• Journal of Advanced Navigation Technology
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• v.27 no.3
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• pp.247-254
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• 2023

GAIN in the US explained in its Pilot/Controller Collaboration Initiatives report that "pilots and air traffic controllers talk to each other all day long, but they rarely communicate." The starting point for the study was the question of whether differences in flight safety perceptions and culture between pilots and air traffic controllers, or other factors, could lead to mutual misunderstandings of procedures and instructions. Digest with The many processes that must be solved within tight deadlines increase the likelihood of accidents through cascading risk factors such as James Reason's Swiss Cheese Theory. Despite the fact that the pilot-air traffic controller complex, which is the subject of flight, occupies a considerable part, there is no integrated management for safe operation between the two groups. Therefore, this research aims to achieve integrated management of safety and education for safe operation between pilots and air traffic controllers through JCRM..

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.5-5
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• 2021

최근 기후변화로 인해 예측이 어려운 국지성 호우가 빈번하게 발생하고 있다. 국지성 호우는 대량의 홍수를 일으키고 산사태와 유송잡물을 동반한 흐름을 야기할 수 있으며 이로 말미암아 인근의 초목과 식생들로부터 유목(driftwood)이 발생하기도 한다. 유목이 흐름과 함께 떠내려 오게 되면 그로 인한 운동에너지가 크게 발생하게 되며, 수공구조물과 주택가옥 등에 충돌시, 순수한 수류의 충돌보다 훨씬 큰 손상을 주기도 한다. 또한 유목이 수공구조물 인근 하상에 군집하면 통수능을 저하시키기도 하며 식생효과와 마찬가지로 유목주변으로 유속이 증가하면서 세굴현상이 발생하게 되는데, 이는 하상저하를 일으키며 수공구조물의 안정성에 지속적으로 피해를 줄 수 있다. 특히 군집된 유목들이 교각에 충격을 주면 흐름방향으로 교각에 작용하는 외력을 증가시키게 되고 군집된 유목들이 다른 유목들을 연쇄적으로 포착하는 동시에 흐름을 지속적으로 방해하여 수위상승을 야기하게 된다. 이는 유목주변으로 세굴을 발생시켜 교량의 붕괴를 촉진시킬 수 있다. 일본의 경우에는 대부분의 하천유역의 경사가 매우 급하기 때문에 홍수발생시 산사태와 유송잡물들이 빈번하게 발생하고 있다. 그에 따라 대량의 유목들이 하천으로 유입되어 하천의 수공구조물과 주거지역에 심각한 피해를 주는 경우도 많다. 따라서 유목의 거동과 군집현상을 이해하여 사전에 유목거동의 예측과 유목과 하상변동의 상호작용 분석을 통해 유목에 의한 수리구조물 피해를 예측하는 연구들이 필요할 것으로 판단된다. 본 연구는 유목의 거동과 군집양상을 예측분석하기 위해 유목과 흐름의 이동상 실내실험과 수치해석을 수행하여 유목유입량에 따른 하상변동과 유목의 하상퇴적양상 및 다양한 거동을 관측분석 하였다. 특히, 유목간의 상호충돌과 측벽충돌을 고려하는 수치모듈을 유목동역학모형에 적용하여 수치해석을 수행하였다. 이를 통해 이동상 하상에서의 유목의 군집과정을 분석하고 수치해석의 한계와 개선사항들을 논의하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1794-1799
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• 2022

Recently, the increasing number of overloaded vehicles on the road poses a risk to traffic safety, such as falling objects, road damage, and chain collisions due to the abnormal weight distribution, and can cause great damage once an accident occurs. therefore we propose to build an object detection-based AI model to identify overloaded vehicles that cause such social problems. In addition, we present a simple yet effective method to construct an object detection model for the large-scale vehicle images. In particular, we utilize the large-scale of vehicle image sets provided by open AI-Hub, which include the overloaded vehicles. We inspected the specific features of sizes of vehicles and types of image sources, and pre-processed these images to train a deep learning-based object detection model. Also, we propose an integrated system for tracking the detected vehicles. Finally, we demonstrated that the detection performance of the overloaded vehicle was improved by about 23% compared to the one using raw data.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.326-326
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• 2021

장기간에 걸쳐 넓은 지역에 대해 발생하는 가뭄을 예측하기위해 많은 학자들의 기술적, 학술적 시도가 있어왔다. 본 연구에서는 복잡한 시계열을 가진 가뭄을 전망하는 방법 중 시나리오에 기반을 둔 가뭄전망 방법과 실시간으로 가뭄을 예측하는 비시나리오 기반의 방법 등을 이용하여 미래 가뭄전망을 실시했다. 시나리오에 기반을 둔 가뭄전망 방법으로는, 3개월 GCM(General Circulation Model) 예측 결과를 바탕으로 2009년도 PDSI(Palmer Drought Severity Index) 가뭄지수를 산정하여 가뭄심도에 대한 단기예측을 실시하였다. 또, 통계학적 방법과 물리적 모델(Physical model)에 기반을 둔 확정론적 수치해석 방법을 이용하여 비시나리오 기반 가뭄을 예측했다. 기존 가뭄을 통계학적 방법으로 예측하기 위해서 시도된 대표적인 방법으로 ARIMA(Autoregressive Integrated Moving Average) 모델의 예측에 대한 한계를 극복하기위해 서포트 벡터 회귀(support vector regression, SVR)와 웨이블릿(wavelet neural network) 신경망을 이용해 SPI를 측정하였다. 최적모델구조는 RMSE(root mean square error), MAE(mean absolute error) 및 R(correlation Coefficient)를 통해 선정하였고, 1-6개월의 선행예보 시간을 갖고 가뭄을 전망하였다. 그리고 SPI를 이용하여, 마코프 연쇄(Markov chain) 및 대수선형모델(log-linear model)을 적용하여 SPI기반 가뭄예측의 정확도를 검증하였으며, 터키의 아나톨리아(Anatolia) 지역을 대상으로 뉴로퍼지모델(Neuro-Fuzzy)을 적용하여 1964-2006년 기간의 월평균 강수량과 SPI를 바탕으로 가뭄을 예측하였다. 가뭄 빈도와 패턴이 불규칙적으로 변하며 지역별 강수량의 양극화가 심화됨에 따라 가뭄예측의 정확도를 높여야 하는 요구가 커지고 있다. 본 연구에서는 복잡하고 비선형성으로 이루어진 가뭄 패턴을 기상학적 가뭄의 정도를 나타내는 표준강수증발지수(SPEI, Standardized Precipitation Evapotranspiration Index)인 월SPEI와 일SPEI를 기계학습모델에 적용하여 예측개선 모형을 개발하고자 한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.849-859
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• 2006

Earnings of domestic enterprises are expected a serious damage because the lowest cost bid system and the current cost estimate system. In 2005 average successful bid rate for the lowest cost bid project is below 60%, this is not reach at the operating budget of enterprise. Many problems such as illegal construction, low price subcontract, chain enterprise loss com in to practice because of low successful bid rate. In addition earnings of the enterprises expected to be the minimum, because of enlarge execution of the current cost estimate system. This study tries to lend assistance by giving alternative for the construction enterprise by presenting the bid system, investigate and compare foreign system with domestic and analyze correlation of the lowest cost bid and the current cost estimate system.