• Title/Summary/Keyword: series model

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Analyzing the Effect of Management Strategies on Gum Talha Yield from Acacia Seyal, South Kordofan, Sudan

  • Mohammed, M.H.;Roehle, H.
    • Journal of Forest and Environmental Science
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    • v.27 no.3
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    • pp.135-141
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    • 2011
  • The present study was carried out from September 2007 to February 2008 in Umfakarin natural forest reserve, South Kordofan, Sudan. The objective was to analyze the effect of different management strategies on yield of gum talha from Acacia seyal. A total of 493 single target trees were selected, based on their diameters, and assigned to tapping treatments in three different stand densities (making a total of nine treatments per stand density). The treatments are as follows: tapping date with three levels (first of October, 15 October and first of November) and two levels of local tapping tools (sonki, and makmak). Untapped trees were used as control. The first picking of gum was started fifteen days after tapping while the subsequent pickings were done in intervals of fifteen days. Yield per tree throughout the season was obtained by summing up the gum yield from all pickings. Yield throughout the season (from first to the last picking) were analyzed. General linear model (GLM) was used to test the effect of different tapping treatments on the yield of gum talha. Post hoc test after analysis of variance (ANOVA) based on Scheffe test was performed to examine the differences in gum yield as a result of different management strategies. The results showed that tapping has a significant influence on gum yield. Analysis of pick-to-pick yield indicated that only three treatments in dense stand density showed a decreasing pattern while the rest of treatments either have constant or unclear patterns. The results of the present study were based on a single season data and that may underscore the real effect of Acacia seyal stands' management strategies on gum talha yield. Conducting gum yield experiments in permanent trial plots are highly recommended in order to analyze gum yield of seasonal time series.

Optimize TOD Time-Division with Dynamic Time Warping Distance-based Non-Hierarchical Cluster Analysis (동적 타임 워핑 거리 기반 비 계층적 군집분석을 활용한 TOD 시간분할 최적화)

  • Hwang, Jae-Yeon;Park, Minju;Kim, Yongho;Kang, Woojin
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.5
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    • pp.113-129
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    • 2021
  • Recently, traffic congestion in the city is continuously increasing due to the expansion of the living area centered in the metropolitan area and the concentration of population in large cities. New road construction has become impossible due to the increase in land prices in downtown areas and limited sites, and the importance of efficient data-based road operation is increasingly emerging. For efficient road operation, it is essential to classify appropriate scenarios according to changes in traffic conditions and to operate optimal signals for each scenario. In this study, the Dynamic Time Warping model for cluster analysis of time series data was applied to traffic volume and speed data collected at continuous intersections for optimal scenario classification. We propose a methodology for composing an optimal signal operation scenario by analyzing the characteristics of the scenarios for each data used for classification.

Vulnerability Assessment for Fine Particulate Matter (PM2.5) in the Schools of the Seoul Metropolitan Area, Korea: Part II - Vulnerability Assessment for PM2.5 in the Schools (인공지능을 이용한 수도권 학교 미세먼지 취약성 평가: Part II - 학교 미세먼지 범주화)

  • Son, Sanghun;Kim, Jinsoo
    • Korean Journal of Remote Sensing
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    • v.37 no.6_2
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    • pp.1891-1900
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    • 2021
  • Fine particulate matter (FPM; diameter ≤ 2.5 ㎛) is frequently found in metropolitan areas due to activities associated with rapid urbanization and population growth. Many adolescents spend a substantial amount of time at school where, for various reasons, FPM generated outdoors may flow into indoor areas. The aims of this study were to estimate FPM concentrations and categorize types of FPM in schools. Meteorological and chemical variables as well as satellite-based aerosol optical depth were analyzed as input data in a random forest model, which applied 10-fold cross validation and a grid-search method, to estimate school FPM concentrations, with four statistical indicators used to evaluate accuracy. Loose and strict standards were established to categorize types of FPM in schools. Under the former classification scheme, FPM in most schools was classified as type 2 or 3, whereas under strict standards, school FPM was mostly classified as type 3 or 4.

A Study on the Influencing Factors of Fashion Beauty Magazine Curation Service Usage Intention: Focused on the Extended Technology Acceptance Model (패션뷰티 매거진 큐레이션 서비스 이용의도 영향요인: 확장된 기술수용모델을 중심으로)

  • Lee, JongSook
    • Journal of Digital Convergence
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    • v.19 no.4
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    • pp.373-381
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    • 2021
  • This study attempted to present a strategic direction that helps in vitalizing the domestic fashion and beauty magazine industry by examining the factors that influence the intention to use the fashion beauty magazine curation service. A survey was conducted on 314 college students in Korea, and the results were derived through a series of analysis processes using the SPSS 21.0 and AMOS 21.0 programs. Technology self-efficacy had a positive effect on perceived ease of use and perceived usefulness, perceived value had a positive effect on perceived usefulness. Technology self-efficacy and perceived value had a positive effect on intention to use, perceived ease of use had a positive effect on perceived usefulness. Perceived ease of use did not have a significant effect on intention to use, but perceived usefulness had a positive effect on intention to use. In order to increase the intention of using the mobile-based fashion beauty magazine curation service for college students, it is necessary to clearly understand the value and usefulness of the curation service.

The Relationship between Korea Agricultural Productions and Greenhouse Gas Emissions Using Environmental Kuznets Curve (환경쿠즈네츠곡선을 이용한 한국의 농업 생산과 온실가스 배출의 관계 분석)

  • Kang, Hyun-Soo
    • Asia-Pacific Journal of Business
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    • v.12 no.1
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    • pp.209-223
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    • 2021
  • Purpose - The purpose of this study was to investigate the relationship between Korea agricultural productions and Greenhouse Gas (GHG) emissions based on Environmental Kuznets Curve (EKC) hypothesis. Design/methodology/approach - This study utilized time series data of economic growth, greenhouse gas, agricultural productions, trade dependency, and energy usages. In order to econometric procedure of EKC hypothesis, this study utilized unit root test and cointegration test to check staionarity of each variable and also adopted Vector Error Correction Model (VECM) and Ordinary Least Square (OLS) to analyze the short and long run relationships. Findings - In the short run, greenhouse gas emissions resulting from economic growth show an inverse U-shape relationship, and an increase in agricultural production and energy consumption led to increase in greenhouse gas emission. In the long run, total GHG emissions and CO2 emissions show an N-shaped relationship with economic growth, and an increase in agricultural production has resulted in a decrease in total GHG and CO2 emissions. However, methane (CH4) and nitrous oxide (N2O) emissions showed an inverse U-shape relationship with economic growth, which indicated the environment and production process of agricultural production. Research implications or Originality - Korea agricultural production has different effects on the GHG emission sources, and in particular, methane (CH4) and nitrous oxide (N2O) emissions show to increase as the agricultural production expansions, so policy or technological development in related sector is required. Especially, in the context of the 2030 GHG reduction road-map, if GHG-related reduction technologies or policies are spread, national GHG emission reduction targets can be achieved and this is possible to predict the decline in production in the sector and damage to the related industries.

Parallelization and application of SACOS for whole core thermal-hydraulic analysis

  • Gui, Minyang;Tian, Wenxi;Wu, Di;Chen, Ronghua;Wang, Mingjun;Su, G.H.
    • Nuclear Engineering and Technology
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    • v.53 no.12
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    • pp.3902-3909
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    • 2021
  • SACOS series of subchannel analysis codes have been developed by XJTU-NuTheL for many years and are being used for the thermal-hydraulic safety analysis of various reactor cores. To achieve fine whole core pin-level analysis, the input preprocessing and parallel capabilities of the code have been developed in this study. Preprocessing is suitable for modeling rectangular and hexagonal assemblies with less error-prone input; parallelization is established based on the domain decomposition method with the hybrid of MPI and OpenMP. For domain decomposition, a more flexible method has been proposed which can determine the appropriate task division of the core domain according to the number of processors of the server. By performing the calculation time evaluation for the several PWR assembly problems, the code parallelization has been successfully verified with different number of processors. Subsequent analysis results for rectangular- and hexagonal-assembly core imply that the code can be used to model and perform pin-level core safety analysis with acceptable computational efficiency.

An Empirical Study on the Causalities and Effects between Inbound Tourism and Service Industry GDP in China (국제 인바운드 관광과 중국내 서비스 산업 GDP간의 인과관계 및 효과에 관한 실증연구)

  • Kim, Jong-Sup
    • International Area Studies Review
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    • v.14 no.3
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    • pp.363-387
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    • 2010
  • This papers studies the causalities and effects on the relationship between inbound tourism(TOU) and the production amount of service industry in China, using the unit root test, the Granger causality test, the cointegration test, and VECM. we take their natural logarithm and define them as TOU and SGDP: these represent the distributed variable based the lagged values of the number of international tourists by continent and real production amount in service industry of China, respectively. The results of empirical study of this papers are as follows: Firstly, in the unit root test, we found that each time series was unstable one that has unit root. This result made me use 1st differenced data for this empirical study. Secondly, in the Granger casuality test, the study results show that there is unilateral casuality relation between DLSGDP-$DLTOU_i$ except DLSGDP-DLTOUL model for the same time, while no casuality relation between DLTOU-DLSGDP for all models of China. Thirdly, there is cointegration relation between all models for the period of 1980-2008.

A Study on Korean FDI in China by Industries and Intra Industry Trade between Two Countries (한국의 대 중국 업종별 FDI와 산업내무역에 관한 연구)

  • Kim, Seong Ki;Kang, Han Gyoun
    • International Area Studies Review
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    • v.13 no.3
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    • pp.759-780
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    • 2009
  • The purpose of this paper is to analyse the effect of Korean FDI(1990-2008) in China by industries on exports and imports between two countries. We use time series regression, Vector Error Correction Model and Impulse Response Function as methodologies. Our findings through empirical tests are as follows. First Korean FDI in China increases Korean exports with China but shows a tendency to decrease due to the local content of China. Second Korean FDI in China increases Korean imports in SITC 8 with China. Finally Korean trade surplus caused by Korean FDI in China shrinks due to the decreasing of exports and increasing of imports in Korea. Korean FDI in China should be oriented host country's market oriented rather than production efficiency oriented because of unfriendly foreign investment environments in China.

Research on the Surface Improvement of High Soft Ground Using Calibration Chamber Test (모형토조실험에 의한 초연약지반의 표층개량에 관한 연구)

  • Bang, Seongtaek;Yeon, Yongheum
    • Journal of the Korean GEO-environmental Society
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    • v.20 no.5
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    • pp.39-46
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    • 2019
  • Most of the soil used for reclamation is marine clay generated from dredging construction.The soft ground made of dredged clay has high water content and high compressibility, so the bearing capacity of the ground is very weak and it is difficult to enter the ground improvement equipment. Therefore, surface hardening treatment method is used to enter equipment prior to full-scale civil engineering work, and stabilizer is mainly used for cement series. Cement-based stabilizers have the advantage of improving the ground in a short period of time and have excellent economic efficiency, but they are disadvantageous in that they cause environmental problems due to leaching of heavy metals such as hexavalent chromium. In this study, environmental effects evaluation of dredged clay mixed with normal portland cement and environmentally friendly stabilizer was evaluated, and uniaxial compressive strength test and indoor model test were conducted to confirm the bearing capacity characteristics of the solidified layer.

Machine Learning Based Prediction of Bitcoin Mining Difficulty (기계학습 기반 비트코인 채굴 난이도 예측 연구)

  • Lee, Joon-won;Kwon, Taekyoung
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.29 no.1
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    • pp.225-234
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    • 2019
  • Bitcoin is a cryptocurrency with characteristics such as de-centralization and distributed ledger, and these features are maintained through a mining system called "proof of work". In the mining system, mining difficulty is adjusted to keep the block generation time constant. However, Bitcoin's current method to update mining difficulty does not reflect the future hash power, so the block generation time can not be kept constant and the error occurs between designed time and real time. This increases the inconsistency between block generation and real world and causes problems such as not meeting deadlines of transaction and exposing the vulnerability to coin-hopping attack. Previous studies to keep the block generation time constant still have the error. In this paper, we propose a machine-learning based method to reduce the error. By training with the previous hash power, we predict the future hash power and adjust the mining difficulty. Our experimental result shows that the error rate can be reduced by about 36% compared with the current method.