• Journal of Information Science Theory and Practice
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• 제9권2호
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• pp.47-65
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• 2021

This study aims to identify specific topics, trends, and structural characteristics of scholarly communication research, based on 1,435 articles published from 1970 to 2018 in the Scopus database through Latent Dirichlet Allocation topic modeling, serial analysis, and network analysis. Topic modeling, time series analysis, and network analysis were used to analyze specific topics, trends, and structures, respectively. The results were summarized into three sets as follows. First, the specific topics of scholarly communication research were nineteen in number, including research resource management and research data, and their research proportion is even. Second, as a result of the time series analysis, there are three upward trending topics: Topic 6: Open Access Publishing, Topic 7: Green Open Access, Topic 19: Informal Communication, and two downward trending topics: Topic 11: Researcher Network and Topic 12: Electronic Journal. Third, the network analysis results indicated that high mean profile association topics were related to the institution, and topics with high triangle betweenness centrality, such as Topic 14: Research Resource Management, shared the citation context. Also, through cluster analysis using parallel nearest neighbor clustering, six clusters connected with different concepts were identified.

• 한국ITS학회 논문지
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• 제20권5호
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• pp.113-129
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• 2021

최근 수도권 중심의 생활권역 확장과 대도시로의 인구 집중으로 도시 내의 교통 혼잡이 지속적으로 증가하고 있다. 도심지의 땅값 상승과 한정된 부지로 인해 새로운 도로 건설은 불가능하게 되었고, 데이터 기반의 효율적인 도로 운영의 중요성이 점점 부각되고 있다. 효율적인 도로 운영을 위해서는 교통상황의 변화에 따른 적절한 TOD 시간분할과 TOD 시간분할을 통한 최적의 신호 운영 방안이 필수적이다. 본 연구에서는 최적의 TOD 시간 분할을 위해 연속된 교차로에서 수집된 교통량과 속도 데이터에 시계열 데이터의 군집 분석을 위한 동적 타임 워핑 모델을 적용하였다. 시간 분할을 위해 활용된 데이터별 군집의 특성을 분석하여 최적의 신호 운영 시나리오를 구성하기 위한 시간 분할 방법론을 제안하고자 한다.

• 한국물환경학회지
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• 제37권6호
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• pp.520-530
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• 2021

Multivariate statistical analysis and an environmental hydrological model were applied for investigating the causes of water pollution and providing best management practices for water quality improvement in urban and agricultural watersheds. Principal component analysis (PCA) and cluster analysis (CA) for water quality time series data show that chemical oxygen demand (COD), total organic carbon (TOC), suspended solids (SS) and total phosphorus (T-P) are classified as non-point source pollutants that are highly correlated with river discharge. Total nitrogen (T-N), which has no correlation with river discharge and inverse relationship with water temperature, behaves like a point source with slow and consistent release. Biochemical oxygen demand (BOD) shows intermediate characteristics between point and non-point source pollutants. The results of the PCA and CA for the spatial water quality data indicate that the cluster 1 of the watersheds was characterized as upstream watersheds with good water quality and high proportion of forest. The cluster 3 shows however indicates the most polluted watersheds with substantial discharge of BOD and nutrients from urban sewage, agricultural and industrial activities. The cluster 2 shows intermediate characteristics between the clusters 1 and 3. The results of hydrological simulation program-Fortran (HSPF) model simulation indicated that the seasonal patterns of BOD, T-N and T-P are affected substantially by agricultural and livestock farming activities, untreated wastewater, and environmental flow. The spatial analysis on the model results indicates that the highly-populated watersheds are the prior contributors to the water quality degradation of the river.

• 농촌계획
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• 제26권4호
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• pp.107-116
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• 2020

The purpose of this study is to analyze the characteristics of the 11 southeastern states in the United States by using regional characteristics variables and to classify the regions. First, 19 variables from four categories of population, society, industry-economy and urban service were selected and factor analysis were conducted, and the result showed five major factors of population, economic condition, job and commuting. Based on the following factor scores, a cluster analysis was conducted, and eight types of big city, medium-sized city, bed town, small town, urban hinterland, retirement town, and rural village were derived. These types of spatial distribution characteristics showed big cities were by different types of regions and they formed metropolitan areas. Each types of classified regions were located along the road network with hierarchy. The study focused on cases in the southeastern regions of the United States and can be used as a comparison with Korean cases. If the same research method is applied to Korea in the future, or if the time series of changes is tracked by analyzing different time points, it will greatly help identify the characteristics of urban and rural mixed areas.

• 한국환경과학회지
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• 제19권10호
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• pp.1229-1235
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• 2010

Three meteor-statistical forecasting models - the transfer function model, the time-series autoregressive model and the neural networks model - were tested to develop a daily forecasting model for Jejudo, where the need and demand for wind power forecasting has increased. All the meteorological observation sites in Jejudo have been classified into 6 groups using a cluster analysis. Four pairs of observation sites among them, all having strong wind speed correlation within the same meteorological group, were chosen for a model test. In the development of the wind speed forecasting model for Jejudo, it was confirmed that not only the use a wind dataset at the objective site itself, but the introduction of another wind dataset at the nearest site having a strong wind speed correlation within the same group, would enhance the goodness to fit of the forecasting. A transfer function model and a neural network model were also confirmed to offer reliable predictions, with the similar goodness to fit level.

• 한국환경과학회:학술대회논문집
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• 한국환경과학회 2003년도 International Symposium on Clean Environment
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• pp.73-78
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• 2003

In this research, we implement Realtime Air Diffusion Prediction System which is a parallel Fortran model running on distributed-memory parallel computers. The system is designed for air diffusion simulations with four-dimensional data assimilation. For regional air quality forecasting a series of dynamic downscaling technique is adopted using the NCAR/Penn. State MM5 model which is an atmospheric model. The realtime initial data have been provided daily from the KMA (Korean Meteorological Administration) global spectral model output. It takes huge resources of computation to get 24 hour air quality forecast with this four step dynamic downscaling (27km, 9km, 3km, and lkm). Parallel implementation of the realtime system is imperative to achieve increased throughput since the realtime system have to be performed which correct timing behavior and the sequential code requires a large amount of CPU time for typical simulations. The parallel system uses MPI (Message Passing Interface), a standard library to support high-level routines for message passing. We validate the parallel model by comparing it with the sequential model. For realtime running, we implement a cluster computer which is a distributed-memory parallel computer that links high-performance PCs with high-speed interconnection networks. We use 32 2-CPU nodes and a Myrinet network for the cluster. Since cluster computers more cost effective than conventional distributed parallel computers, we can build a dedicated realtime computer. The system also includes web based Gill (Graphic User Interface) for convenient system management and performance monitoring so that end-users can restart the system easily when the system faults. Performance of the parallel model is analyzed by comparing its execution time with the sequential model, and by calculating communication overhead and load imbalance, which are common problems in parallel processing. Performance analysis is carried out on our cluster which has 32 2-CPU nodes.

• 천문학논총
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• 제31권3호
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• pp.43-56
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• 2016

Through time-series BV CCD photometry of the open cluster NGC 225 region, we have detected 30 variable stars including 22 new ones. They are five ${\delta}$ Scuti-type variable stars, a slowly pulsating B star, six eclipsing binary stars and 18 semi-long periodic or slow irregular variables, respectively. We have performed multiple-frequency analysis to determine pulsation frequencies of the ${\delta}$ Scuti-type stars and a slowly pulsating B star, using the discrete Fourier transform and linear least-square fitting methods. We also have derived the periods and amplitudes of 6 eclipsing binaries and a long-period variable star from the phase fitting method, and presented the light curves of all variable stars. A slowly pulsating B star is a member of NGC 225, but ${\delta}$ Scuti-type stars are not members from the positions in the color-magnitude diagram and the radial distancies from the center of the cluster. From Dias et al. (2014, A&A, 564, 79), only three variable stars including the slowly pulsating B star are members of clusters: two are in NGC 225 and one is in Stock 24. But a variable star in Stock 24 is not a member of the cluster because of its position of color-magnitude diagarm.

• 천문학논총
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• 제25권2호
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• pp.31-49
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• 2010

Next to Paper I (Jeon 2009a), time-series BV CCD images of the open cluster M38 were taken for 4 nights on December, 2009. The observations have been carried out for total 27 nights. In addition to the 20 variable stars in the Paper I, the discovery of 44 new variable stars has been presented in this paper: $6{\delta}$ Scuti stars, $2{\gamma}$ Doradus stars, 18 eclipsing binaries and 18 semi-long periodic and/or slow irregular type variable stars. For the V photometry of the ${\delta}$ Scuti and ${\gamma}$ Doradus stars, multi-frequency analysis was performed using the Discrete Fourier Transform and linear least-square fitting. The period search for the eclipsing binaries and the semi-long periodic and/or slow irregular type variable stars was performed by phase fitting method. As a result, the periods for 23 variable stars among the 44 ones were defined.

• 천문학논총
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• 제25권4호
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• pp.167-176
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• 2010

In the region of the intermediate open cluster M35 (NGC 2168), the time-series of V CCD images was taken for 12 nights from December 18, 2007 to September 25, 2010. From this observation, we detected 22 variable stars including 15 new ones. They are 6 $\delta$ Scuti, a Cepheid, an RR Lyrae, 9 eclipsing binaries and 5 semi-long periodic and/or slow irregular type variable stars. For the V photometry of the $\delta$2 Scuti stars, the multi-frequency analysis was performed using the Discrete Fourier Transform and the linear least-square fitting.

• 응용통계연구
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• 제33권6호
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• pp.791-804
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• 2020

스마트그리드 환경하에서 ICT 기술의 발달로 AMI 기기를 통해 가정의 실시간 전력사용량을 수집할 수 있게 됨에 따라 이러한 자료들을 활용하여 보다 더 정확한 가정용 전력사용량 예측을 할 수 있게 되었다. 본 논문에서는 1시간 단위 가정용 전력사용량 자료를 바탕으로 ARIMA, TBATS, NNAR 모형을 사용하여 전력수요를 예측하는 모형을 연구하였는데, 기존과 달리 가구 전체 사용량을 한 번에 예측하는 것이 아닌 유사한 전력사용패턴을 나타내는 가구들을 군집하여 군집별로 예측 모형을 수립하고 각 모형별 예측치를 합산하여 예상 전력사용량을 산출하였다. 특히 전력사용량 자료는 전형적인 시계얼 자료로서 군집분석 방법으로 시계열에 적절한 방법을 선택하였으며 본 논문에서는 동적타임워핑(dynamic time warping)과 Periodogram 기반의 방법을 사용하였다. 연구 결과 사용량이 유사한 가구들을 군집하여 전력사용량을 예측하는 것이 한 번에 예측하는 것보다 예측 성능이 더 우수한 것으로 나타났으며 예측 모형 중에서는 여름철의 경우 NNAR 모형이, 겨울철의 경우 TBATS 모형의 성능이 가장 좋았으며 군집분석 방법은 군집 간 패턴의 차이가 명확히 나타난 동적타임워핑 방법을 사용했을 때 예측 성능의 향상이 가장 많았다.