• Title/Summary/Keyword: BIG 6 모형

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Application of a Topic Model on the Korea Expressway Corporation's VOC Data (한국도로공사 VOC 데이터를 이용한 토픽 모형 적용 방안)

  • Kim, Ji Won;Park, Sang Min;Park, Sungho;Jeong, Harim;Yun, Ilsoo
    • Journal of Information Technology Services
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    • v.19 no.6
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    • pp.1-13
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    • 2020
  • Recently, 80% of big data consists of unstructured text data. In particular, various types of documents are stored in the form of large-scale unstructured documents through social network services (SNS), blogs, news, etc., and the importance of unstructured data is highlighted. As the possibility of using unstructured data increases, various analysis techniques such as text mining have recently appeared. Therefore, in this study, topic modeling technique was applied to the Korea Highway Corporation's voice of customer (VOC) data that includes customer opinions and complaints. Currently, VOC data is divided into the business areas of Korea Expressway Corporation. However, the classified categories are often not accurate, and the ambiguous ones are classified as "other". Therefore, in order to use VOC data for efficient service improvement and the like, a more systematic and efficient classification method of VOC data is required. To this end, this study proposed two approaches, including method using only the latent dirichlet allocation (LDA), the most representative topic modeling technique, and a new method combining the LDA and the word embedding technique, Word2vec. As a result, it was confirmed that the categories of VOC data are relatively well classified when using the new method. Through these results, it is judged that it will be possible to derive the implications of the Korea Expressway Corporation and utilize it for service improvement.

Experimental Studies of the Short-Term Fluctuations of Net Photosynthesis Rate of Norway Spruce Needles under Field Conditions (야외조건하(野外條件下)에서 독일가문비(Picea abies Karst) 침엽(針葉)의 순(純) 광합성률(光合成率)의 단기(短期) 변화(變化)에 대한 실험적(實驗的) 연구(硏究))

  • Bolondinsky, V.;Oltchev, A.;Jin, Hyun O.;Joo, Yeong Teuk;Chung, Dong Jun
    • Journal of Korean Society of Forest Science
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    • v.88 no.1
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    • pp.38-46
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    • 1999
  • Canopy structure conductances of a Norway spruce forest in the Solling Hills(Central Germany) and Central Forest Biosphere Reserve(320km to the north-west from Moscow) were derived from LE(latent heat flux) and H(sensible heat flux) fluxes measured(by Eddy correlation technique and energy balance method) and modelled(by one dimensional non-steady-state) SVAT(soil-vegetation-atmosphere-transfer) model(SLODSVAT) using a rearranged Penman-Monteith equation("Big-leaf" approximation) during June 1996. They were compared with canopy stomatal conductances estimated by consecutive intergrating the stomatal conductance of individual needles over the whole canopy("bottom-up" approach) using SLODSVAT model. The result indicate a significant difference between the canopy surface conductances derived from measured and modelled fluxes("top-down" approach) and the stomatal conductances modelled by the SLODSVAT("bottom-up" approach). This difference was influenced by some nonphysiological factors within the forest canopy(e.g. aerodynamic and boundary layer resistances, radiation budget, evapotranspiration from the forest understorey). In general, canopy surface conductances derived from measured and modelled fluxes exceeded canopy stomatal conductance during the whole modelled period, The contribution of the understorey's evapotranspiration to the total forest evapotranspiration was small (up to 5-9% of the total LE flux) and was not depended on total radiation balance of forest canopy. Ignoring contribution of the understorey's evapotranspiration resulted in an overestimation of the canopy surface conductance for a spruce forest up to 2mm/s(about 10-15%).

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Sewer overflow simulation evaluation of urban runoff model according to detailed terrain scale (상세지형스케일에 따른 도시유출모형의 관거월류 모의성능평가)

  • Tak, Yong Hun;Kim, Young Do;Kang, Boosik;Park, Mun Hyun
    • Journal of Korea Water Resources Association
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    • v.49 no.6
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    • pp.519-528
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    • 2016
  • Frequently torrential rain is occurred by climate change and urbanization. Urban is formed with road, residential and underground area. Without detailed topographic flooded analysis consideration can take a result which are wrong flooded depth and flooded area. Especially, flood analysis error of population and assets in dense downtown is causing a big problem for establishments and disaster response of flood measures. It can lead to casualties and property damage. Urban flood analysis is divided into sewer flow analysis and surface inundation analysis. Accuracy is very important point of these analysis. In this study, to confirm the effects of the elevation data precision in the process of flooded analysis were studied using 10m DEM, LiDAR data and 1:1,000 digital map. Study area is Dorim-stream basin in the Darim drainage basin, Sinrim 3 drainage basin, Sinrim 4 drainage basin. Flooding simulation through 2010's heavy rain by using XP-SWMM. Result, from 10m DEM, shows wrong flood depth which is more than 1m. In particular, some of the overflow manhole is not seen occurrence. Accordingly, detailed surface data is very important factor and it should be very careful when using the 10m DEM.

Arrival Time Estimation for Bus Information System Using Hidden Markov Model (은닉 마르코프 모델을 이용한 버스 정보 시스템의 도착 시간 예측)

  • Park, Chul Young;Kim, Hong Geun;Shin, Chang Sun;Cho, Yong Yun;Park, Jang Woo
    • KIPS Transactions on Computer and Communication Systems
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    • v.6 no.4
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    • pp.189-196
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    • 2017
  • BIS(Bus Information System) provides the different information related to buses including predictions of arriving times at stations. BIS have been deployed almost all cities in our country and played active roles to improve the convenience of public transportation systems. Moving average filters, Kalman filter and regression models have been representative in forecasting the arriving times of buses in current BIS. The accuracy in prediction of arriving times depends largely on the forecasting algorithms and traffic conditions considered when forecasting in BIS. In present BIS, the simple prediction algorithms are used only considering the passage times and distances between stations. The forecasting of arrivals, however, have been influenced by the traffic conditions such as traffic signals, traffic accidents and pedestrians ets., and missing data. To improve the accuracy of bus arriving estimates, there are big troubles in building models including the above problems. Hidden Markov Models have been effective algorithms considering various restrictions above. So, we have built the HMM forecasting models for bus arriving times in the current BIS. When building models, the data collected from Sunchean City at 2015 have been utilized. There are about 2298 stations and 217 routes in Suncheon city. The models are developed differently week days and weekend. And then the models are conformed with the data from different districts and times. We find that our HMM models can provide more accurate forecasting than other existing methods like moving average filters, Kalmam filters, or regression models. In this paper, we propose Hidden Markov Model to obtain more precise and accurate model better than Moving Average Filter, Kalman Filter and regression model. With the help of Hidden Markov Model, two different sections were used to find the pattern and verified using Bootstrap process.

The Study for Estimating Traffic Volumes on Urban Roads Using Spatial Statistic and Navigation Data (공간통계기법과 내비게이션 자료를 활용한 도시부 도로 교통량 추정연구)

  • HONG, Dahee;KIM, Jinho;JANG, Doogik;LEE, Taewoo
    • Journal of Korean Society of Transportation
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    • v.35 no.3
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    • pp.220-233
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    • 2017
  • Traffic volumes are fundamental data widely used in various traffic analysis, such as origin-and-destination establishment, total traveled kilometer distance calculation, congestion evaluation, and so on. The low number of links collecting the traffic-volume data in a large urban highway network has weakened the quality of the analyses in practice. This study proposes a method to estimate the traffic volume data on a highway link where no collection device is available by introducing a spatial statistic technique with (1) the traffic-volume data from TOPIS, and National Transport Information Center in the Ministry of Land, Infrastructure, and (2) the navigation data from private navigation. Two different component models were prepared for the interrupted and the uninterrupted flows respectively, due to their different traffic-flow characteristics: the piecewise constant function and the regression kriging. The comparison of the traffic volumes estimated by the proposed method against the ones counted in the field showed that the level of error includes 6.26% in MAPE and 5,410 in RMSE, and thus the prediction error is 20.3% in MAPE.

An Analysis on Determinants of the Capesize Freight Rate and Forecasting Models (케이프선 시장 운임의 결정요인 및 운임예측 모형 분석)

  • Lim, Sang-Seop;Yun, Hee-Sung
    • Journal of Navigation and Port Research
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    • v.42 no.6
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    • pp.539-545
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    • 2018
  • In recent years, research on shipping market forecasting with the employment of non-linear AI models has attracted significant interest. In previous studies, input variables were selected with reference to past papers or by relying on the intuitions of the researchers. This paper attempts to address this issue by applying the stepwise regression model and the random forest model to the Cape-size bulk carrier market. The Cape market was selected due to the simplicity of its supply and demand structure. The preliminary selection of the determinants resulted in 16 variables. In the next stage, 8 features from the stepwise regression model and 10 features from the random forest model were screened as important determinants. The chosen variables were used to test both models. Based on the analysis of the models, it was observed that the random forest model outperforms the stepwise regression model. This research is significant because it provides a scientific basis which can be used to find the determinants in shipping market forecasting, and utilize a machine-learning model in the process. The results of this research can be used to enhance the decisions of chartering desks by offering a guideline for market analysis.

Water shortage assessment by applying future climate change for boryeong dam using SWAT (SWAT을 이용한 기후변화에 따른 보령댐의 물부족 평가)

  • Kim, Won Jin;Jung, Chung Gil;Kim, Jin Uk;Kim, Seong Joon
    • Journal of Korea Water Resources Association
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    • v.51 no.12
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    • pp.1195-1205
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    • 2018
  • In the study, the water shortage of Boryeong Dam watershed ($163.6km^2$) was evaluated under future climate change scenario. The Soil and Water Assessment Tool (SWAT) was used considering future dam release derived from multiple linear regression (MLR) analysis. The SWAT was calibrated and verified by using daily observed dam inflow and storage for 12 years (2005 to 2016) with average Nash-Sutcliffe efficiency of 0.59 and 0.91 respectively. The monthly dam release by 12 years MLR showed coefficient of determination ($R^2$) of above 0.57. Among the 27 RCP 4.5 scenarios and 26 RCP 8.5 scenarios of GCM (General Circulation Model), the RCP 8.5 BCC-CSM1-1-M scenario was selected as future extreme drought scenario by analyzing SPI severity, duration, and the longest dry period. The scenario showed -23.6% change of yearly dam storage, and big changes of -34.0% and -24.1% for spring and winter dam storage during 2037~2047 period comparing with 2007~2016 period. Based on Runs theory of analyzing severity and magnitude, the future frequency of 5 to 10 years increased from 3 in 2007~2016 to 5 in 2037~2046 period. When considering the future shortened water shortage return period and the big decreases of winter and spring dam storage, a new dam operation rule from autumn is necessary for future possible water shortage condition.

An Empirical Study on the Spatial Effect of Distribution Patterns between Small Business and Social-environmental factors (소상공인 점포의 분포와 환경요인의 공간적 영향관계에 관한 실증연구)

  • YOO, Mu-Sang;CHOI, Don-Jeong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.1
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    • pp.1-18
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    • 2019
  • This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.

The Study of Characteristics of Consumer Purchasing Private Brand Products at Large-Scale Mart (국내 대형마트의 유통업체 브랜드 상품 구매 소비자의 특성 분석에 관한 연구)

  • Hwang, Seong-Huyk;Lee, Jung-Hee;Roh, Eun-Jung
    • Journal of Distribution Research
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    • v.15 no.4
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    • pp.1-19
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    • 2010
  • As having the movement of developing private brand (PB) goods, domestic big retailers are facing up with new problems. Thus, it is required studies of PB products, and how consumers recognize PB products as a consideration commodity set. Also, it is worthy in order that it gives us the important meaning on the marketing strategy with focusing on evaluating the differences between customers buying PB grocery goods with respect to demographic characteristics and purchasing behaviors. PB has some advantages for customers and retailers. However, according to AC Nielson's report (2005), Asian and emerging market has 1/5 sales relatively to Western countries. But we can assume that the emerging market has the most potential growth through this result. As a result from several other studies, it becomes necessary to not only increase the rate of selling composition of PB product temporarily, but also analyze the characteristics of customers using big retailers and segmenting customer groups to make PB product as a consideration commodity set for them. In addition, it is needed to have a variety of acts of marketing. From studies related to PB, there is a prejudice - cheap products have low quality - but, evaluation by customers who have used those products shows neutral stand, and there is a study representing that it is the most important to accumulate the belief between the retailers selling PB products and consumers using those for the accurate evaluation and intention on purchasing. Also, by the result from analyzing the characteristics of customers buying PB products, we could assume that higher income and higher education level, more preference on PB products. Especially, according to TNS's research, the primary targets of PB product are 30's who seeks value for money and planned spending habits, and 40's who have teenager children, and are interested in encouraging themselves. This paper used Probit model to analyze the characteristics of consumers. This model helps us to analyze with the variables representing the demographic characteristics of consumers (gender, age, educational level, occupation, income level, living area), and variables related to purchasing behavior (visiting frequency on big retailers, the average amount that they pay for goods in there, and check-up which brand made those goods). The method we used in this study is by man to man interview and survey on-line with the rate of 89% and 11% in Seoul and Gyunggi Province, respectively, for about one month from the beginning of February, 2008. As a result of this, under the assumption that people buy PB products more as long as they go shopping more, it was not meaningful for target groups which we pointed out as frequently visiting customers to be. Although, we have expected women buy more PB products than men do, gender doesn't mean anything for the result. And, it has inferred that married people buy more PB goods than singles do. It was also meaningless with variables related to occupation. Because housewives are often exposed to any kind of supermarket than workers are, we could not get any relatives. Moreover, we couldn't proof that younger generation prefer big retailers more than older people who 50~60's. Education levels doesn't affect on the purchase of PB product as well. Related to living area, the result is statistically not similar as we expected whether living in Seoul or not. It shows there is no relationship with the preference on retail brands and PB products, and it is similar with the study researched by TNS(2008) that customers tend to buy PB product impulsively no matter which brand it is and where they are even though their shopping place is the big market where customers are often using. Variables on which we had meaningful results are income level and living place. That is, customers who have 3,000,000~6,000,000 WON every month on average are more willing to buy PB products than other customers whose income is over 6,000,000 WON, and residents not living in Seoul prefer PB goods than those who are living in Seoul. To explain more about what we got, if there is only one condition about customer's visiting frequency on big retails, we could come up with this result that more exposed to PB products, more purchasing frequency. Consequently, it brings the important insight that large retailers have to prepare something to make customers visit them often to increase selling rate of PB products. To demonstrate the result of analyzing more, what is more efficient variables are demographically including marital status, income level, and residential area to buy items that affect the PB products and could include the frequency of visiting large markets by the purchase habits. Specifically, then, married couples rather than singles, middle-income customers than high-income customers, and local residents not living in Seoul than customers in Seoul are more likely to purchase PB goods. In addition, as long as a customer visits two times more, then the purchasing rate of PB products is to increase over 5.3%. Therefore, it seems that retailers are better to make a shopping place as fun and comfortable places. With overwhelming the idea that PB products are just cheap, one-time purchase goods, it is needed to increase the loyalty on those goods like NB products, try to make PB products as a consideration products set, and occur to sustainable sales. Especially, as suggested by this paper, it seems like it strongly needs to identify the characteristics of customers who prefer PB, to segment those customers, and to select the main target, and to do positioning with well-planned marketing strategies. Then, it is able to give us a meaningful point on marketing strategy by developing the field of PB study, identifying the difference of life style and shopping habits of customers.

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Effects of Time Perspectives and Smart Phone Addiction on Abstract Thinking and Growth Mindset of Adolescent (시간관과 스마트폰 중독이 청소년의 추상적 사고와 성장 마인드세트에 미치는 영향)

  • Park, Chan Jung;Hyun, Jung Suk
    • The Journal of Korean Association of Computer Education
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    • v.16 no.6
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    • pp.21-32
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    • 2013
  • Since creativity has been emphasized and creative problem solving has also been a big topic recently, various kinds of research works have proceeded. Among them, this paper focuses on abstract thinking and growth mindset, which affect on problem solving. Also, this paper analyzes what kinds of relationships time perspectives and smart-phone addiction have with the two factors and how they influence on them. In order to do so, we survey on 441 primary, middle, high school, and college students. Our analysis results cover the relationships among the two factors, smart-phone addiction level, present-hedonic perspective, and future time perspective. In addition, we analyze the relationship among the factors with a structural equation model. By doing these, we propose educational alternatives in terms of time and plan to improve our adolescent's abstract thinking level, which helps their problem solving skills and their academic achievement.

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