• Nuclear Engineering and Technology
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• 제52권11호
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• pp.2442-2451
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• 2020

The safety level of Sodium Fast Reactors is directly related with the sodium void reactivity. A low-void effect design has been proposed within the Horizon2020 ESFR-SMART project thanks to the introduction of a sodium plenum above the active core. In order to assess the impact of this core conception on transient analysis, a map with the spatial distribution of sodium void worth can be computed and fed into a point-kinetics-based transient code. Due to the spatial correlations between neighboring zones, the global effect of voiding two different axial or radial regions is not necessarily the sum of both individual contributions. Neglecting those correlations in the void worth map and consequently in the transient analysis may lead to an unrealistic prediction of the transient sequences. In this work, a method based on sensitivity analysis and similarity assessment is proposed for predicting those correlations. The method proved to be able to establish correlations between axial slices of a sub-assembly and was checked against realistic sodium void propagation patterns.

• ETRI Journal
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• 제44권2호
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• pp.208-219
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• 2022

Crime amount prediction is crucial for optimizing the police patrols' arrangement in each region of a city. First, we analyzed spatiotemporal correlations of the crime data and the relationships between crime and related auxiliary data, including points-of-interest (POI), public service complaints, and demographics. Then, we proposed a crime amount prediction model based on 2D convolution and long short-term memory neural network (2DCONV-LSTM). The proposed model captures the spatiotemporal correlations in the crime data, and the crime-related auxiliary data are used to enhance the regional spatial features. Extensive experiments on real-world datasets are conducted. Results demonstrated that capturing both temporal and spatial correlations in crime data and using auxiliary data to extract regional spatial features improve the prediction performance. In the best case scenario, the proposed model reduces the prediction error by at least 17.8% and 8.2% compared with support vector regression (SVR) and LSTM, respectively. Moreover, excessive auxiliary data reduce model performance because of the presence of redundant information.

• 아태비즈니스연구
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• 제13권1호
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• pp.277-288
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• 2022

Purpose - This study analyzed the determinants of local unemployment rate in Korea using panel data from 16 metropolitan cities and provinces from 2000 to 2018. Design/methodology/approach - We use a dynamic spatial panel model that considers characteristics of the regional unemployment rate such as the common factors effect, spatial dependence, and serial correlations. Findings - The local unemployment rate is affected by the past and present values of the national unemployment rate. And it is significantly affected by the past local unemployment rate and the past neighboring unemployment rate because spatial dependence and serial correlations are clearly present. In addition, when the industrial structure diversity and labor productivity were high, the regional unemployment rate decreased, and when the education level was high, the regional unemployment rate increased. Research implications or Originality - In order to reduce regional unemployment rate, it is necessary to plan and establish regional customized industrial structure policies under the stance of diversification rather than specializing the regional industrial structure and accompany improvement of the quality of education with the number of years of education. In addition, the redistribution of labor from low labor productivity sectors to high labor productivity sectors through technology development will help to reduce the local unemployment rate.

• Journal of Communications and Networks
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• 제5권2호
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• pp.104-115
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• 2003

It is well known that Multiple Input Multiple Output (MIMO) systems offer the promise of achieving very high spectrum efficiencies (many tens of bit/s/Hz) in a mobile environment. The gains in MIMO capacity are sensitive to the presence of spatial and temporal correlation introduced by the radio environment. In this paper, we examine how MIMO capacity is influenced by a number of factors e.g., a) temporal correlation b) various combinations of low/high spatial correlations at either end, c) combined spatial and temporal correlations. In all cases, we compare the channel capacity that would be achievable under independent fading. We investigate the behaviour of "capacity fades," examine how often the capacity experiences the fades, develop a method to determine level crossing rates and average fade durations and relate these to antenna numbers. We also evaluate the influence of channel correlation on the capacity autocorrelation and assess the fit of a Gaussian random process to the temporal capacity sequence. Finally we note that the particular spatial correlation structure of the MIMO channel is influenced by a large number of factors. For simplicity, it is desirable to use a single overall correlation measure which parameterizes the effect of correlation on capacity. We verify this single parameter concept by simulating a large number of different spatially correlated channels.

• 대한임베디드공학회논문지
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• 제5권4호
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• pp.206-216
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• 2010

Wireless sensor networks (WSNs) are used to collect various data in environment monitoring applications. A spatial clustering may reduce energy consumption of data collection by partitioning the WSN into a set of spatial clusters with similar sensing data. For each cluster, only a few sensor nodes (samplers) report their sensing data to a base station (BS). The BS may predict the missed data of non-samplers using the spatial correlations between sensor nodes. ASAP is a representative data collection algorithm using the spatial clustering. It periodically reconstructs the entire network into new clusters to accommodate to the change of spatial correlations, which results in high message overhead. In this paper, we propose a new data collection algorithm, name EPDC (Energy-efficient Periodic Data Collection). Unlike ASAP, EPDC identifies a specific cluster consisting of many dissimilar sensor nodes. Then it reconstructs only the cluster into subclusters each of which includes strongly correlated sensor nodes. EPDC also tries to reduce the message overhead by incorporating a judicious probabilistic model transfer method. We evaluate the performance of EPDC and ASAP using a simulation model. The experiment results show that the performance improvement of EPDC is up to 84% compared to ASAP.

• 대기
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• 제20권3호
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• pp.343-353
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• 2010

A regional wind network with complex surface conditions must be designed with sufficient space and time resolution to resolve the local circulations. In this study, the spatial variations of the wind field observed in the Seoul and Jeju regional networks were evaluated in terms of annual, seasons, and months to assess the spatial homogeneity of wind fields within the regional networks. The coherency of the wind field as a function of separation distance between stations indicated that significant coherency was sometimes not captured by the network, as inferred by low correlations between adjacent stations. A meso-velocity scale was defined in terms of the spatial variability of the wind within the network. This problem is predictably most significant with weak winds, dull prevailing wind, clear skies and significant topography. The relatively small correlations between stations imply that the wind at a given point cannot be estimated by interpolating winds from the nearest stations. For the Seoul and Jeju regional network, the meso-velocity scale has typically a same order of magnitude as the speed of the network averaged wind, revealing the large spatial variability of the Jeju network station imply topography and weather. Significant scatter in the relationship between spatial variability of the wind field and the wind speed is thought to be related to thermally-generated flows. The magnitude of the mesovelocity scale was significantly different along separation distance between stations, wind speed, intensity of prevailing wind, clear and cloudy conditions, topography. Resultant wind vectors indicate much different flow patterns along condition of contributing factors. As a result, the careful considerations on contributing factors such as prevailing wind in season, weather, and complex surface conditions with topography and land/sea contrast are required to assess the spatial variations of wind field on a regional network. The results in the spatial variation from the mesovelocity scale are useful to represent the characteristics of regional wind speed including lower surface conditions over the grid scale of large scale atmospheric model.

• 대한공간정보학회지
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• 제19권2호
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• pp.29-37
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• 2011

우리나라 산불관리의 주체는 관할시도 행정자치 단체이므로, 산불을 효율적으로 관리하기 위해서는 지역별 산불 발생 특성에 대한 이해가 필요하다. 본 연구에서는 지역별 산불 발생패턴을 분석하기 위해서, 행정구역도를 기반으로 전국을 9개로 분할하고, 각 권역에서 1991년부터 2008년까지 발생한 산불의 위치 data를 사용해서 공간통계적 분석을 실시하였다. 산불 발생 자료의 공간 분포는 베리오그램을 통해 분석하였고, 도출된 공간자기상관성을 가지고 Kriging 기법을 통해 산불발생위험을 예측하였다. 분석결과, 대도시를 포함하는 권역에서는 산불이 강한 공간상관성을 가지고 있었지만, 강원도, 제주도, 충청북도 등의 대도시를 포함하지 않는 지역에서는 산불의 공간상관성이 낮은 것으로 나타났다.

• 대한건축학회논문집:계획계
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• 제36권5호
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• pp.53-58
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• 2020

The purpose of this study is to build a database of Spatial information Bigdata of cities using satellite images and spatial information, and to examine the correlations with the surface temperature. Using architectural structure and usage in building information, DEM and Slope topographical information for constructed with 300 × 300 mesh grids for Busan. The satellite image is used to prepare the Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Bare Soil Index (BI), and Land Surface Temperature (LST). In addition, the building area in the grid was calculated and the building ratio was constructed to build the urban environment DB. In architectural structure, positive correlation was found in masonry and concrete structures. On the terrain, negative correlations were observed between DEM and slope. NDBI and BI were positively correlated, and NDVI was negatively correlated. The higher the Building ratio, the higher the surface temperature. It was found that the urban environment DB could be used as a basic data for urban environment analysis, and it was possible to quantitatively grasp the impact on the architecture and urban environment by adding local meteorological factors. This result is expected to be used as basic data for future urban environment planning and disaster prevention data construction.

• 방송공학회논문지
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• 제1권1호
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• pp.44-54
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• 1996

In this paper, we propose a new 3-D deinterlacing algorithm based on wide sparse vector correlations and a vertical edge based motion detection algorithm. which is an extension of the deinterlacing algorithm proposed in [10. llJ by the authors. The prooised algorithm is developed mainly for the format conversion problem encountered in current HDTV system, but can also be aplicable to the double scan conversion problesm frequently encountered in ths NTSC systems. By exploiting the edge oriented spatial interpolation based on the wide vector correlations, visually annoying artifiacts caused by interlacing such as a serrate line. line crawling, a line flicker, and a large area flicker can be remarkably reduced since the use of the wide vectors increases the range of the edge orientations that can be detected, and by exploiting sparse vectors correlations the HjW complexity for realizing the algorithm in applications cam be significantly simplified. Simulations are provided indicating thet the proposed algorithm results in a high performance comparable to the performance of the deinterlacing algorithm. based on the wide vector correlations.

• 공학교육연구
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• 제18권4호
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• pp.34-44
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• 2015

Mathematical, spatial, and verbal abilities are important for future engineers to succeed in the STEM disciplines. The purpose of the study is to assess engineering students' spatial abilities and analyse the relationship with mathematical achievement, verbal achievement, and gender. On the mental rotation tests, 65% of male students demonstrated a substantial level of spatial abilities. But only 30% of female students exhibited spatial skills at the same level as their male colleagues. The correlations between mathematical - spatial - verbal abilities are found to be negligible. When spatial visualization ability was plotted according to the mathematical achievement level, there was no difference in the mean spatial abilities score. But when mathematical achievement score was plotted according to the spatial abilities, there was a noticeable difference. Regression analysis confirmed that female students' mathematical achievement increased as spatial abilities improved. This phenomenon was not observed for male students. It's because male students' spatial ability already contributed to their mathematics achievement. So spatial ability can be regarded as one factor for the gender differences in mathematics achievement. The gender gap on spatial abilities and math achievement is large among high achieving students. For example, there was a 4.3 to 1 male - female ratio and 3.4 to 1 male - female ratio among students scoring 99th percentile in spatial visualization test and scholastic aptitude test-math.