• Korean Journal of Remote Sensing
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• v.16 no.1
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• pp.1-11
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• 2000

Multi-temporal data have been used frequently for analyzing dynamic characteristics of ecological environment. Little research, however, shows the characteristics and problems of the analysis of continental- or global-scale, multi-temporal satellite data. This research investigated the characteristics of large-area, multi-temporal data analysis and the problems of phenological difference of ground vegetation and scarcity of training data for a long term period. This research suggested a latitudinal image segmentation method and an invariant pixel method. As an application, the image segmentation and invariant pixel methods were applied to a set of AVHRR data covering most part of Asia from 1982 to 1993. Fuzzy classification results showed the decrease of forests and the increase of croplands at densely populated areas, however an opposite trend was detected at sparsely populated or depopulated areas.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.04a
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• pp.26-26
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• 2019

DMZ 일원은 정전협정으로 비무장지대(DMZ: Demilitarized Zone)가 설정된 이래 민간인의 출입이 엄격히 금지된 채로 외부의 간섭에서 벗어난 독보적 공간으로 보전되어 오고 있다. 하지만 일부 지역은 자연재해 및 군사적 목적으로 훼손되어 생태적으로 교란된 지역이 발생하여 생태적 건강성이 저하되고 있다. 무엇보다 군사분계선 남쪽 2km에 설치된 남방한계선은 군사적 목적에 따라 시계확보를 위해 불모지작전을 수행하여 생태적 교란 및 토양침식에 의해 생태계가 열악한 실정이다. DMZ 내 생태교란지 식물복원 연구는 DMZ내 생태교란지를 하나의 특수한 생태계로 간주하여, 향후 DMZ내 생태교란지에 특화된 식생복원 체계를 마련하는데 그 목적이 있다. 이에 본 연구에서는 DMZ 155마일(248km)에 대해서 위성영상분석을 수행하여 생태교란지 유형화분류 연구를 수행하여 7개 유형(저지대초지, 서부저지대산지, 저습지 및 수공간 지역 등)으로 분류하였다. 또한 DMZ 생태교란지에 적합한 식물종 선정을 위하여 DMZ 전역을 대상으로 식물상 조사를 실시하여, 분포가 확인된 종을 대상으로 도입 가능종의 검토, 종자 수집 및 채종원 조성을 실시하였다. 추후 DMZ 생태교란지 식물복원에 적합한 공법연구를 수행하고자 한다. 시계확보를 위해 수행되는 불모지 작전에 적합한 종의 선정, 선정된 종을 대상으로 유사환경 조성에 따른 공법 적용, 적용된 공법에 따른 관리 방안 연구를 함께 수행하고자 한다. 본 연구를 통해 DMZ 일원에 특화된 공법개발이 이루어진다면 불모지 작전 및 관리 최소화가 이루어지고, 무엇보다 우리나라 종자 및 야생화 산업의 활성화와 현재 파편화 되어 있는 생태축이 하나의 축으로 연결 될 것이라고 기대해 본다.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.596-599
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• 2023

본 연구는 브랜드가 시장 트렌드를 파악하고 이를 활용하여 경쟁 우위를 확보하고 성장하는 방법을 탐구하고 있다. 이를 위해 세 가지 핵심 요소를 고려하였다. 첫째, 시장의 트렌드 정보를 파악하기 위해 검색 포털 사이트의 검색어 랭킹 정보를 활용하였다. 둘째, 브랜드 상품과 트렌드의 연관성을 분석하기 위해 상품 타이틀과 리뷰 데이터를 활용하였다. 셋째, 각 상품의 브랜드 중요성을 추정하기 위해 리뷰 수, 리뷰 길이, 표현의 다양성 등을 고려했다. 연구 결과, 브랜드는 시장 트렌드를 더욱 정확하게 이해하고 파악함으로써 경쟁 우위를 확보하고 성장할 수 있는 기회를 제공함을 확인하였다. 더불어, 이를 통해 브랜드는 소비자의 요구를 더욱 효과적으로 충족시키고 고객 경험을 개선하는데 기여할 수 있을 것으로 기대된다.

• Korean Journal of Construction Engineering and Management
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• v.10 no.4
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• pp.50-57
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• 2009

The Korea Standard of Estimate which has been used as the only basis of Cost estimate of public construction projects is failed to reflect the fluctuation of current construction cost. Therefore, the government decided to gradually introduce historical construction cost into cost estimate of public construction projects from 2004 and to reduce the use of Korean Standard of Estimate. This paper presents a series of process and the methodology for computing Actual Cost and analyzing the fluctuation patterns based on not only previous contract prices which made a successful bid but also all of the other bid prices. Also, this paper mainly handles a device for extracting strategic bid price such as low price bid for assuring reliable data and for predicting the construction cost which is built by Wavelet Analysis of Time series Analysis data and Neural Network. It is anticipated that the effective use of the proposed process for estimating actual unit cost would make the cost estimation more current and reasonable.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.5
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• pp.505-511
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• 2023

In the present study, a deep learning model was established to predict the motion response of small fishing vessels. Hydrodynamic performances were evaluated for two small fishing vessels for the dataset of deep learning model. The deep learning model of the Long Short-Term Memory (LSTM) which is one of the recurrent neural network was utilized. The input data of LSTM model consisted of time series of six(6) degrees of freedom motions and wave height and the output label was selected as the time series data of six(6) degrees of freedom motions. The hyperparameter and input window length studies were performed to optimize LSTM model. The time series motion response according to different wave direction was predicted by establised LSTM. The predicted time series motion response showed good overall agreement with the analysis results. As the length of the time series increased, differences between the predicted values and analysis results were increased, which is due to the reduced influence of long-term data in the training process. The overall error of the predicted data indicated that more than 85% of the data showed an error within 10%. The established LSTM model is expected to be utilized in monitoring and alarm systems for small fishing vessels.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.165-174
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• 2018

The model using time series data can be considered as a flood forecasting model of a small river due to its efficiency for model development and the advantage of rapid simulation for securing predicted time when reliable data are obtained. Transfer Function Noise (TFN) model has been applied hourly flood forecast in Italy, and UK since 1970s, while it has mainly been used for long-term simulations in daily or monthly basis in Korea. Recently, accumulating hydrological data with good quality have made it possible to simulate hourly flood prediction. The purpose of this study is to assess the TFN model applicability that can reflect exogenous variables by combining dynamic system and error term to reduce prediction error for tributary rivers. TFN model with hourly data had better results than result from Storage Function Model (SFM), according to the flood events. And it is expected to expand to similar sized streams in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.225-231
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• 2013

A bird's-eye view is an elevated view of an object from above, with a perspective as though the observer were a bird, often used in the making of blueprints, floor plans and maps. It can be used under severe weather conditions when visibility is poor. Under low visibility environments, drivers can communicate each other using V2V communication to get each vehicle's status to prevent collision and other accidents. Ubiquitous transportation sensor networks(u-TSN) and its application are emerging rapidly as an exciting new paradigm to provide reliable and comfortable transportatione services. The ever-growing u-TSN and its application will provide an intelligent and ubiquitous communication and network technology for traffic safety area.

• Journal of the Korea Convergence Society
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• v.8 no.9
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• pp.277-283
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• 2017

This paper deals with a longitudinal time series study on the viewing behavior of digital media service. After holdback of terrestrial broadcasting VOD service was extended in 2013, viewers' terrestrial broadcasting VOD viewing went down sharply. Researcher assumed that there was driven by watching alternative products such as movies, kids, etc. as the cause of the decline of the terrestrial broadcasting VOD viewing. In addition, researcher assumed that the decline of terrestrial broadcasting VOD viewing had an influence on the viewing rate of the terrestrial real-time broadcasting, and confirmed the cause of the decreasing of the terrestrial real-time broadcasting viewing rate. In order for terrestrial broadcasters to retrieve real-time broadcasting and VOD viewing, it is necessary to shorten the VOD holdback and reacquire viewers away from terrestrial broadcasting.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8889-8895
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• 2015

It is necessary to secure the underwater visibility in order to perform underwater works such as rubble mound leveling or inspection and management of underwater structures. In this study, turbidity data for typical port area in Korea were measured and analyzed according to the region. Underwater monitoring system including underwater camera and sonar system, which can be effectively attached to underwater equipment for various turbidity conditions, was also investigated.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.27-39
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• 2016

This paper considers variable selection in the sparse vector autoregressive (sVAR) model where sparsity comes from setting small coefficients to exact zeros. In the estimation perspective, Davis et al. (2015) showed that the lasso type of regularization method is successful because it provides a simultaneous variable selection and parameter estimation even for time series data. However, their simulations study reports that the regular lasso overestimates the number of non-zero coefficients, hence its finite sample performance needs improvements. In this article, we show that the adaptive lasso significantly improves the performance where the adaptive lasso finds the sparsity patterns superior to the regular lasso. Some tuning parameter selections in the adaptive lasso are also discussed from the simulations study.