• Title/Summary/Keyword: Large Dataset

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Spatial Hedonic Modeling using Geographically Weighted LASSO Model (GWL을 적용한 공간 헤도닉 모델링)

  • Jin, Chanwoo;Lee, Gunhak
    • Journal of the Korean Geographical Society
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    • v.49 no.6
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    • pp.917-934
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    • 2014
  • Geographically weighted regression(GWR) model has been widely used to estimate spatially heterogeneous real estate prices. The GWR model, however, has some limitations of the selection of different price determinants over space and the restricted number of observations for local estimation. Alternatively, the geographically weighted LASSO(GWL) model has been recently introduced and received a growing interest. In this paper, we attempt to explore various local price determinants for the real estate by utilizing the GWL and its applicability to forecasting the real estate price. To do this, we developed the three hedonic models of OLS, GWR, and GWL focusing on the sales price of apartments in Seoul and compared those models in terms of model fit, prediction, and multicollinearity. As a result, local models appeared to be better than the global OLS on the whole, and in particular, the GWL appeared to be more explanatory and predictable than other models. Moreover, the GWL enabled to provide spatially different sets of price determinants which no multicollinearity exists. The GWL helps select the significant sets of independent variables from a high dimensional dataset, and hence will be a useful technique for large and complex spatial big data.

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Characterization of Nutritional Value for Twenty-one Pork Muscles

  • Kim, J.H.;Seong, P.N.;Cho, S.H.;Park, B.Y.;Hah, K.H.;Yu, L. H.;Lim, D.G.;Hwang, I.H.;Kim, D.H.;Lee, J.M.;Ahn, C.N.
    • Asian-Australasian Journal of Animal Sciences
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    • v.21 no.1
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    • pp.138-143
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    • 2008
  • A study was conducted to evaluate nutritional value for twenty-one pork muscles. Ten market-weight crossbred pigs (five gilts and five barrows) were used for evaluating proximate chemical composition, cholesterol, total iron, calorie and fatty acid contents. As preliminary analysis revealed no noticeable sex effect, pooled data from both sexes were used for the final analysis. M. rectus femoris had the highest moisture content, while m. latissimus dorsi was lowest in moisture content (p<0.05). Protein content was highest for m. longissimus dorsi and lowest for m. supraspinatus (p<0.05). The tensor fasciae and latissimus dorsi muscles contained the highest intramuscular fat (p<0.05), while rectus femoris, adductor and vastus lateralis were lowest in intramuscular fat content. When simple correlations between chemical values were computed for the pooled dataset from all muscles, intramuscular fat had significant (p<0.05) negative linear relationships with moisture (r = -0.85) and protein (r = -0.51) contents. Calorie levels were not significantly affected by fat content, while rectus femoris and latissimus dorsi muscles showed lowest and highest calorie contents, respectively (p<0.05). Polyunsaturated fatty acid content was highest (p<0.05) for both m. adductor and m. rectus femoris, while it was lowest for m. longissimus dorsi. Collectively, the current study identified a large amount of variation in nutritional characteristics between pork muscles, and the data can be used for the development of muscle-specific strategies to improve eating quality of meats and meat products.

Clinical crown angulation and inclination of normal occlusion in a large Korean sample (정상교합자의 치관경사도에 관한 연구)

  • Lee, Shin-Jae;Ahn, Sug-Joon;Kim, Tae-Woo
    • The korean journal of orthodontics
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    • v.35 no.5 s.112
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    • pp.331-340
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    • 2005
  • Angulation and inclination of clinical crown is important for diagnosing, treatment planning and developing convenient orthodontic attachments. The aim of the study was to establish normative data with higher reliability on the angulation and inclination of clinical crown of Koreans with normal occlusion This study employed the dental casts of 307 (male. 187: female. 120) adult normal occlusion samples. The angulation and inclination of clinical crown were measured by set-up model checker In order to ensure reliability, intra- and inter-rater error were evaluated 3 times The resultant data obtained had excellent reliability however when compared with the previous data as well as with gender difference, clinically significant interpretation was impossible because the whithin-dataset normal variation was High which was common pattern of angulation and inclination measuring data of previous research The result of this biometric study seemed 4o suggest more substantive design of the multivariate. high-dimensional interpretation methodology of these normal variation is required if more compatible orthodontic appliance could be developed.

Projecting Future Paddy Irrigation Demands in Korea Using High-resolution Climate Simulations (고해상도 기후자료를 이용한 우리나라의 논 관개요구량 예측)

  • Chung, Sang-Ok
    • Journal of Korea Water Resources Association
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    • v.44 no.3
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    • pp.169-177
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    • 2011
  • The impacts of climate change on paddy irrigation water demands in Korea have been analyzed. High-resolution ($27{\times}27\;km$) climate data for the SRES A2 scenario produced by the Korean Meteorological Research Institute (METRI) and the observed baseline climatology dataset were used. The outputs from the ECHO-G GCM model were dynamically downscaled using the MM5 regional model by the METRI. The Geographic information system (GIS) was used to produce maps showing the spatial changes in irrigation water requirements for rice paddies. The results showed that the growing season mean temperature for future scenarios was projected to increase by $1.5^{\circ}C$ (2020s), $3.3^{\circ}C$ (2050s) and $5.3^{\circ}C$ (2080s) as compared with the baseline value (1971~2000). The growing season rainfall for future scenarios was projected to increase by 0.1% (2020s), 4.9% (2050s) and 19.3% (2080s). Assuming cropping area and farming practices remain unchanged, the total volumetric irrigation demand was projected to increase by 2.8% (2020s), 4.9% (2050s) and 4.5% (2080s). These projections are contrary to the previous study that used HadCM3 outputs and projected decreasing irrigation demand. The main reason for this discrepancy is the difference with the projected climate of the GCMs used. The temporal and spatial variations were large and should be considered in the irrigation water resource planning and management in the future.

Correlation Analysis of Signal to Noise Ratio (SNR) and Suspended Sediment Concentration (SSC) in Laboratory Conditions (실험수로에서 신호대잡음비와 부유사농도의 상관관계 분석)

  • Seo, Kanghyeon;Kim, Dongsu;Son, Geunsoo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.37 no.5
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    • pp.775-786
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    • 2017
  • Monitoring sediment flux is crucial especially for maintaining river systems to understand morphological behaviors. Recently, hydroacoustic backscatter (or SNR) as a surrogate to empirically estimate suspended sediment concentration has been increasingly highlighted for more efficient acquisition of sediment dataset, which is difficult throughout direct sediment sampling. However, relevant contemporary researches have focused on wide range solution applicable for large natural rivers where H-ADCPs with relatively low acoustic frequency have been widely utilized to seamlessly measure streamflow discharge. In this regard, this study aimed at investigating hydroacoustical characteristics based on a very recently released H-ADCP (SonTek SL-3000) with high acoustic frequency of 3 MHz in order to capitalize its capacity to be applied for suspended sediment monitoring in laboratory conditions. SL-3000 was tested in a laboratory flume to collect SNR in conjunction with LISST-100X for actual sediment concentration and particle distribution in both sand and silt sediment injection in various amount. Conventional algorithms to correct signal attenuations for water and sediment were carefully tested to validate whether they can be applied for SL-3000. As result of analyzing the SNR-SSC correlation trand, through further study in the future, it is confirmed that SSC can be observed indirectly by using the SNR.

Real-Time Stereoscopic Visualization of Very Large Volume Data on CAVE (CAVE상에서의 방대한 볼륨 데이타의 실시간 입체 영상 가시화)

  • 임무진;이중연;조민수;이상산;임인성
    • Journal of KIISE:Computing Practices and Letters
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    • v.8 no.6
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    • pp.679-691
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    • 2002
  • Volume visualization is an important subarea of scientific visualization, and is concerned with techniques that are effectively used in generating meaningful and visual information from abstract and complex volume datasets, defined in three- or higher-dimensional space. It has been increasingly important in various fields including meteorology, medical science, and computational fluid dynamics, and so on. On the other hand, virtual reality is a research field focusing on various techniques that aid gaining experiences in virtual worlds with visual, auditory and tactile senses. In this paper, we have developed a visualization system for CAVE, an immersive 3D virtual environment system, which generates stereoscopic images from huge human volume datasets in real-time using an improved volume visualization technique. In order to complement the 3D texture-mapping based volume rendering methods, that easily slow down as data sizes increase, our system utilizes an image-based rendering technique to guarantee real-time performance. The system has been designed to offer a variety of user interface functionality for effective visualization. In this article, we present detailed description on our real-time stereoscopic visualization system, and show how the Visible Korean Human dataset is effectively visualized on CAVE.

An Efficient BotNet Detection Scheme Exploiting Word2Vec and Accelerated Hierarchical Density-based Clustering (Word2Vec과 가속화 계층적 밀집도 기반 클러스터링을 활용한 효율적 봇넷 탐지 기법)

  • Lee, Taeil;Kim, Kwanhyun;Lee, Jihyun;Lee, Suchul
    • Journal of Internet Computing and Services
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    • v.20 no.6
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    • pp.11-20
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    • 2019
  • Numerous enterprises, organizations and individual users are exposed to large DDoS (Distributed Denial of Service) attacks. DDoS attacks are performed through a BotNet, which is composed of a number of computers infected with a malware, e.g., zombie PCs and a special computer that controls the zombie PCs within a hierarchical chain of a command system. In order to detect a malware, a malware detection software or a vaccine program must identify the malware signature through an in-depth analysis, and these signatures need to be updated in priori. This is time consuming and costly. In this paper, we propose a botnet detection scheme that does not require a periodic signature update using an artificial neural network model. The proposed scheme exploits Word2Vec and accelerated hierarchical density-based clustering. Botnet detection performance of the proposed method was evaluated using the CTU-13 dataset. The experimental result shows that the detection rate is 99.9%, which outperforms the conventional method.

Creative Project and Reward Based Crowdfunding:Determinants of Success (창의적 프로젝트와 후원형 크라우드펀딩: 성공요인)

  • Chun, Hesuk
    • The Journal of the Korea Contents Association
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    • v.15 no.5
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    • pp.560-569
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    • 2015
  • Crowd funding is the method of raising money for a project, companies from a large group of people via the Internet, in return for future products or equity. Kickstarter is the largest and most successful crowdfunding site where creative projects raise reward based funding. Drawing on dataset of 80,267 projects with combined funding over $1.3b from 8.1m people, this paper suggest that backer select project based on their preference on the project, instead profitability of the project. It suggests that well-established platform and big size of network increases the chance of success of the project due to a ripple effect and blockbuster effects. Clear communication about the project's idea and goal is highly correlated with success. Regular communication on the project site, such as by constant progress updates, helps the success of the project. Equity-based crowdfunding is emerging as an innovative means of raising capital for businesses, so it has been receiving a lot of attention and expectation from the government and the market. The findings of this paper and others will help to get some understanding and insight into equity-based crowdfunding. However, Kickstarter differs from equity-based crowdfunding in the goals of the backers. Kickstarter's backers are not investors, they are contributors. To understand equity-based crowdfunding, the subject will need further study.

Characteristics of the Point-source Spectral Model for Odaesan Earthquake (M=4.8, '07. 1. 20) (오대산지진(M=4.8, '07. 1. 20)의 점지진원 스펙트럼 모델 특성)

  • Yun, Kwan-Hee;Park, Dong-Hee
    • Geophysics and Geophysical Exploration
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    • v.10 no.4
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    • pp.241-251
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    • 2007
  • The observed spectra from Odaesan earthquake were fitted to a point-source spectral model to evaluate the source spectrum and spatial features of the modelling error. The source spectrum was calculated by removing from the observed spectra the path and site dependent responses (Yun, 2007) that were previously revealed through an inversion process applied to a large accumulated spectral dataset. The stress drop parameter of one-corner Brune's ${\omega}^2$ source model fitted to the estimated source spectrum was well predicted by the scaling relation between magnitude and stress drop developed by Yun et al. (2006). In particular, the estimated spectrum was quite comparable to the two-corner source model that was empirically developed for recent moderate earthquakes occurring around the Korean Peninsula, which indicates that Odaesan earthquake is one of typical moderate earthquakes representative of Korean Peninsula. Other features of the observed spectra from Odaesan earthquake were also evaluated based on the commonly treated random error between the observed data and the estimated point-source spectral model. Radiation pattern of the error according to azimuth angle was found to be similar to the theoretical estimate. It was also observed that the spatial distribution of the errors was correlated with the geological map and the $Q_0$ map which are indicatives of seismic boundaries.

Clustering Analysis by Customer Feature based on SOM for Predicting Purchase Pattern in Recommendation System (추천시스템에서 구매 패턴 예측을 위한 SOM기반 고객 특성에 의한 군집 분석)

  • Cho, Young Sung;Moon, Song Chul;Ryu, Keun Ho
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.2
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    • pp.193-200
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    • 2014
  • Due to the advent of ubiquitous computing environment, it is becoming a part of our common life style. And tremendous information is cumulated rapidly. In these trends, it is becoming a very important technology to find out exact information in a large data to present users. Collaborative filtering is the method based on other users' preferences, can not only reflect exact attributes of user but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, we propose clustering method by user's features based on SOM for predicting purchase pattern in u-Commerce. it is necessary for us to make the cluster with similarity by user's features to be able to reflect attributes of the customer information in order to find the items with same propensity in the cluster rapidly. The proposed makes the task of clustering to apply the variable of featured vector for the user's information and RFM factors based on purchase history data. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.