• Title/Summary/Keyword: AICC

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Design and Implementation of SCORM conformance testing (SCORM conformance testing의 설계 및 구현)

  • Choi, Ji-Yeon;Min, Su-Hong;Cho, Dong-Sub
    • Proceedings of the Korea Information Processing Society Conference
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    • 2004.05a
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    • pp.1681-1684
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    • 2004
  • 90 년대 후반부터 웹 기반 수업(Web-based instruction)이라 하여 인터넷을 이용한 새로운 교육방법이 시도되었다. WBI에 필요한 각종 프로그래밍을 수작업으로 진행하여야 한다는 문제점을 극복하기 위해 개발된 학습운영체제(Learning Management System)가 개발되면서 인터넷을 통한 교육은 급속히 확산되고 있다. 무선 인터넷 기술까지 수용하는 개념인 소위 e-Learning 체제로 발전되면서 e-Learning의 수요는 급속히 증가하게 되었다. e-Learning 기술 표준 개발을 실질적으로 주도하는 기관들인 IEEE, AICC, IMS가 제안하는 개별 표준안들을 ADL에서 SCORM(Sharable Content Object Reference Model)이라는 종합적인 표준안으로 수렴하게 되면서 SCORM을 기준으로 만든 다양한 컨텐츠가 개발되고있다.

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Analysis of Global Shipping Market Status and Forecasting the Container Freight Volume of Busan New port using Time-series Model (글로벌 해운시장 현황 분석 및 시계열 모형을 이용한 부산 신항 컨테이너 물동량 예측에 관한 연구)

  • JO, Jun-Ho;Byon, Je-Seop;Kim, Hee-Cheul
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.10 no.4
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    • pp.295-303
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    • 2017
  • In this paper, we analyze the trends of the international shipping market and the domestic and foreign factors of the crisis of the domestic shipping market, and identify the characteristics of the recovery of the Busan New Port trade volume which has decreased since the crisis of the domestic shipping market We quantitatively analyzed the future volume of Busan New Port and analyzed the trends of the prediction and recovery trends. As a result of analyzing Busan New Port container cargo volume by using big data analysis tool R, the variation of Busan New Cargo container cargo volume was estimated by ARIMA model (1,0,1) (1,0,1)[12] Estimation error, AICc and BIC were the most optimal ARIMA models. Therefore, we estimated the estimated value of Busan New Port trade for 36 months by using ARIMA (1, 0, 1)[12], which is the optimal model of Busan New Port trade, and estimated 13,157,184 TEU, 13,418,123 TEU, 13,539,884 TEU, and 4,526,406 TEU, respectively, indicating that it increased by about 2%, 2%, and 1%.

Development of Prediction Model on Fruit Width Using Climatic Environmental Factors in 'Fuji' Apple (기후 환경 요인을 이용한 사과 '후지'의 과실 횡경 예측 모델 개발)

  • Han, Hyun Hee;Han, Jeom Hwa;Jeong, Jae Hoon;Ryu, Suhyun;Kwon, YongHee
    • Journal of Bio-Environment Control
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    • v.26 no.4
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    • pp.346-352
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    • 2017
  • In this study, we analyzed environmental factors including annual fruit growth and meteorological conditions in Suwon area from 2000 to 2014 to develop and verify a fruit width prediction model in 'Fuji' apple. The 15-year average of full bloom data was April 28 and that of fruit development period was 181 days. The fruit growth until 36 days after full bloom followed single sigmoid curve. The environmental factors affecting fruit width were BIO2, precipitation in September, the average of daily maximum and minimum temperature in April, minimum temperature in August, and growing degree days (GDD) in April. Among them, the model was constructed by combining BIO2 and precipitation in September, which are not cross-correlated with each other or, with other factors. And then, the final model was selected as 19.33095 + (5.76242 ${\times}$ BIO2) - (0.01891 ${\times}$ September precipitation) + (2.63046 ${\times}$ minimum temperature in April) which was the most suitable model with AICc of 92.61 and the adjusted $R^2$ value of 0.53. The model was compared with the observed values f rom 2000 to 2014. As a result, the mean difference between the measured and predicted values of 'Fuji' apple fruit width was ${\pm}2.9mm$ and the standard deviation was 3.54.

Habitat Connectivity Assessment of Tits Using a Statistical Modeling: Focused on Biotop Map of Seoul, South Korea (통계모형을 활용한 박새류의 서식지 연결성 평가: 서울시 도시생태현황도 자료를 중심으로)

  • Song, Wonkyong;Kim, Eunyoung;Lee, Dongkun
    • Journal of Environmental Impact Assessment
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    • v.22 no.3
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    • pp.219-230
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    • 2013
  • Species distribution modeling is one of the most effective habitat analysis methods for wildlife conservation. This study was for evaluating the suitability of species distribution to distance between forest patches in Seoul city using tits. We analyzed the distribution of the four species of tits: varied tit (Parus varius), marsh tit (P. palustris), great tit (P. major) and coal tit (P. ater), using the landscape indexes and connectivity indexes, and compared the resulting suitability indexes from 100m to 1,000m. As factors affecting to the distribution of tits, we calculated landscape indices by separating them into intra-patch indices (i.e. logged patch area (PA), area-weighted mean patch shape index (PSI), tree rate (TR)) and inter-patch indices (i.e. patch degree (PD), patch betweenness (PB), difference probability of connectivity (DPC)), to analyze the internal properties of the patches and their connectivity by tits occurrence data using logistic regression modeling. The models were evaluated by AICc (Akaike Information Criteria with a correction for finite sample sizes) and AUC (Area Under Curve of ROC). The results of AICc and AUC showed DPC, PA, PSI, and TR were important factors of the habitat models for great tit and marsh tit at the level of distance 500~800m. In contrast, habitat models for coal tit and varied tit, which are known as forest interior species, reflected PA, PSI, and TR as intra-patch indices rather than connectivity. These mean that coal tit and varied tit are more likely to find a large circular forest patch than a small and long-shaped forest patch, which are higher rate of forest. Therefore, different strategies are required in order to enhance the habitats of the forest birds, tits, in a region that has fragmented forest patches such as Seoul city. It is important to manage forest interior areas for coal tit and varied tit, which are known as forest interior species and to manage not only forest interior areas but also connectivity of the forest patches in the threshold distance for great tit and marsh tit as adapted species to the urban ecosystem for sustainable ecosystem management.

An Analysis of the Effects of Customer Characteristics on Sales of Alley Market Area Using Geographically Weighted Regression (지리가중회귀분석을 이용한 고객특성별 골목상권 매출액 영향 연구)

  • Kang, Hyun Mo;Lee, Sang-Kyeong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.6
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    • pp.611-620
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    • 2018
  • With the revitalization of alley market area becoming a major goal of the urban regeneration project, an understanding on customer characteristics that affect the sales of alley market areas is needed. As spatial heterogeneity appears to exist in alley market areas, the use of GWR (Geographically Weighted Regression) is required as an alternative to OLS (Ordinary Least Squares) regression. This study analyzes effects of customer characteristics on sales of 1007 alley market areas in Seoul. Comparing R squared and AICc, results show that GWR is better than OLS regression. According to OLS regression, the ratio of female, the ratio of 40's and 50's, the number of employees, the opening rate of establishment, the density of building and the size of alley market area have positive effects on sales, while the ratio of 20's and 30's, the distance of bus stop and that of subway station have negative effects. As a result of comparing local regression coefficients of geographically weighted regression analysis, the ratio of female customers has the greatest effect on the northwestern region, followed by the southwestern region, the central region and the northeastern region. The ratio of 20's and 30's and that of 40's and 50's effect on the southeastern and northeastern regions, and then the southwestern region. It is expected that this study will help to identify marketing target for each alley market area.

Process for Development of Query-Answer Learning Tool (질의 응답 학습 도구 개발을 위한 프로세스)

  • 김정수;신호준;한은주;김행곤
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10d
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    • pp.391-393
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    • 2002
  • 최근 가상교육에서 학습 기술의 상호 운용성을 기반으로 한 표준화의 필요성을 인식하고 여러 국제표준기관을 통해서 기반 환경과 컨텐트 명세 및 활용에 대한 표준화 작업이 이루어지고 있다. 이로 인해 e-learning 분야에서는 국제표준을 소개하고 체제적으로 AICC(Aviation Industry CBT Committee), IMS(Instructional Management Systems) Global Learning Consortium, ADL(Advanced Distributed Learning)을 중심으로 진행되어 오고 있다. 특히, 미래의 진보적인 e-learning 환경 개발로, 기능별 5계층으로 구성된 LTSA(Learning Technology Standard Architecture)를 제정하고 이를 통한 개발을 지원하고 있다. 하지만, 이는 시스템 구성요소를 정의한 계층 3의 경우 데이터 흐름 모델로 작성되어 현재 개발 수준과 일치하지 않는 문제점을 가지는 모델로 인정한다. 본 논문에서는 표준 모델링 언어인 UML(Unified Modeling Language)을 통해 모델을 재정의하고, 각 프로세스별 단계를 메타모델로 제시하여 개발과 아키텍처의 이해에 대한 문제점을 해결하고자 한다. 또한, 재정의된 모델을 기반으로 e-learning 지원을 위한 분석, 설계 프로세스를 정의하여 이에 대한 사례를 제시한다. 이는 아키텍처를 기반으로 한 메타모델과 프로세스를 통한 교육영역의 질의 응답 학습 도구인 QALT(Query-Answer Learning Tool)에 적용한다. 모델의 재정의로 아키텍처의 이해성 및 이를 기반으로 하는 교육용 애플리케이션 개발의 용이성의 증대를 기대할 수 있으며, 모델의 재사용성을 보장할 수 있다.

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A Segmented Model with Upside-Down Bathtub Shaped Failure Intensity (Upside-Down 욕조 곡선 형태의 고장 강도를 가지는 세분화 모형)

  • Park, Woo-Jae;Kim, Sang-Boo
    • Journal of the Korean Society of Industry Convergence
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    • v.23 no.6_2
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    • pp.1103-1110
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    • 2020
  • In this study, a segmented model with Upside-Down bathtub shaped failure intensity for a repairable system are proposed under the assumption that the occurrences of the failures of a repairable system follow the Non-Homogeneous Poisson Process. The proposed segmented model is the compound model of S-PLP and LIP (Segmented Power Law Process and Logistic Intensity Process), that fits the separate failure intensity functions on each segment of time interval. The maximum likelihood estimation is used for estimating the parameters of the S-PLP and LIP model. The case study of system A shows that the S-PLP and LIP model fits better than the other models when compared by AICc (Akaike Information Criterion corrected) and MSE (Mean Squared Error). And it also implies that the S-PLP and LIP model can be useful for explaining the failure intensities of similar systems.

Prediction of Energy Consumption in a Smart Home Using Coherent Weighted K-Means Clustering ARIMA Model

  • Magdalene, J. Jasmine Christina;Zoraida, B.S.E.
    • International Journal of Computer Science & Network Security
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    • v.22 no.10
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    • pp.177-182
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    • 2022
  • Technology is progressing with every passing day and the enormous usage of electricity is becoming a necessity. One of the techniques to enjoy the assistances in a smart home is the efficiency to manage the electric energy. When electric energy is managed in an appropriate way, it drastically saves sufficient power even to be spent during hard time as when hit by natural calamities. To accomplish this, prediction of energy consumption plays a very important role. This proposed prediction model Coherent Weighted K-Means Clustering ARIMA (CWKMCA) enhances the weighted k-means clustering technique by adding weights to the cluster points. Forecasting is done using the ARIMA model based on the centroid of the clusters produced. The dataset for this proposed work is taken from the Pecan Project in Texas, USA. The level of accuracy of this model is compared with the traditional ARIMA model and the Weighted K-Means Clustering ARIMA Model. When predicting,errors such as RMSE, MAPE, AIC and AICC are analysed, the results of this suggested work reveal lower values than the ARIMA and Weighted K-Means Clustering ARIMA models. This model also has a greater loglikelihood, demonstrating that this model outperforms the ARIMA model for time series forecasting.

Exploring Spatial Patterns of Theft Crimes Using Geographically Weighted Regression

  • Yoo, Youngwoo;Baek, Taekyung;Kim, Jinsoo;Park, Soyoung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.1
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    • pp.31-39
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    • 2017
  • The goal of this study was to efficiently analyze the relationships of the number of thefts with related factors, considering the spatial patterns of theft crimes. Theft crime data for a 5-year period (2009-2013) were collected from Haeundae Police Station. A logarithmic transformation was performed to ensure an effective statistical analysis and the number of theft crimes was used as the dependent variable. Related factors were selected through a literature review and divided into social, environmental, and defensive factors. Seven factors, were selected as independent variables: the numbers of foreigners, aged persons, single households, companies, entertainment venues, community security centers, and CCTV (Closed-Circuit Television) systems. OLS (Ordinary Least Squares) and GWR (Geographically Weighted Regression) were used to analyze the relationship between the dependent variable and independent variables. In the GWR results, each independent variable had regression coefficients that differed by location over the study area. The GWR model calculated local values for, and could explain the relationships between, variables more efficiently than the OLS model. Additionally, the adjusted R square value of the GWR model was 10% higher than that of the OLS model, and the GWR model produced a AICc (Corrected Akaike Information Criterion) value that was lower by 230, as well as lower Moran's I values. From these results, it was concluded that the GWR model was more robust in explaining the relationship between the number of thefts and the factors related to theft crime.

Testing Non-Stationary Relationship between the Proportion of Green Areas in Watersheds and Water Quality using Geographically Weighted Regression Model (공간지리 가중회귀모형(GWR)을 이용한 유역 녹지비율과 하천수질의 비균질적 관계 검증)

  • Lee, Sang-Woo
    • Journal of the Korean Institute of Landscape Architecture
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    • v.41 no.6
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    • pp.43-51
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    • 2013
  • This study aims to examine the presence of non-stationary relationship between water quality and land use in watersheds. In investigating the relationships between land use and water quality, most previous studies adopted OLS method which is assumed stationarity. However, this approach is difficult to capture the local variation of the relationships. We used 146 sampling data and land cover data of Korean Ministry of Environment to build conventional regressions and GWR models for BOD, TN and TP. Regression model and GWR models of BOD, TN, TP were compared with $R^2$, AICc and Moran's I. The results of comparisons and descriptive statistics of GWR models strongly indicated the presence of Non-Stationarity between water quality and land use.