• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.221-230
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• 1999

The important issue for intra-city truck dispatching system is to measure and store actual travel speeds between customer locations. Travel speeds(and times) in nearly all metropolitan areas change drastically during the day because of congestion in certain parts of the city road network. We propose a back-propagation neural network model to recognize the pattern of intra-city vehicle travel speeds between locations that relieve much burden for the data collection and computer storage requirements. On a real-world study using the travel speed data[1] collected in Seoul, we evaluate performance of neural network model and compare with Park & Song model[2] that employs the least square method.

• Journal of Korean Society of Transportation
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• v.7 no.2
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• pp.29-43
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• 1989

The purpose of this study is to construct a forecasting model involved in a diverted traffic volume of the 2nd intra-urban expressway in construction presently, in the case of the future prediction of traffic demand for the intra-urban expressway in Pusan. In this study, the model involved in a diverted traffic volume is constructed trustworthy. And the future traffic demand of intra-urban expressway by this model was forecasted 114,005 volume/daily in 1996 and 147,090 volume/daily in 2001. However, it will made a study more and more concretely for practicality and limitation as well as construction of the forecasting model considered an intrinsic problem of an observational error and necessity of survey for much more socio-economic data, the traffic volume on all orad and OD pairs in Pusan.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.385-395
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• 2005

Long sentence analysis has been a critical problem in machine translation because of high complexity. The methods of intra-sentence segmentation have been proposed to reduce parsing complexity. This paper presents the intra-sentence segmentation method based on maximum entropy probability model to increase the coverage and accuracy of the segmentation. We construct the rules for choosing candidate segmentation positions by a teaming method using the lexical context of the words tagged as segmentation position. We also generate the model that gives probability value to each candidate segmentation positions. The lexical contexts are extracted from the corpus tagged with segmentation positions and are incorporated into the probability model. We construct training data using the sentences from Wall Street Journal and experiment the intra-sentence segmentation on the sentences from four different domains. The experiments show about $88\%$ accuracy and about $98\%$ coverage of the segmentation. Also, the proposed method results in parsing efficiency improvement by 4.8 times in speed and 3.6 times in space.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.991-998
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• 2009

This paper deals with directivity forecasting of time series which is useful for futures trading in stock market. Directivity forecasting of time series is to forecast whether a given time series will rise or fall at next observation time point. For directional forecasting, we consider time regression model and ARIMA model. In particular, we study two statistics, intra-model and extra-model deviation and then show usefulness of intra-model deviation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.1
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• pp.53-65
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• 2012

Recently wireless intra-vehicle communication has received a great interest from the automotive industry and ultra wideband (UWB) technology is considered as one of the potential candidate for this system. Many research works have been done on the measurement and modeling of intra-vehicle communication channel. However, very little work has been reported for the performance analysis of various PHY layer methods under the intra-vehicle communication environment. This paper is to study IEEE 802.15.4a standard in intra-vehicle channel and to evaluate its performance. Channel model in chassis and engine compartment is considered for evaluation. Through simulation BER performance of system with different receiver structures is analyzed.

• Asian Journal of Business Environment
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• v.6 no.1
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• pp.19-24
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• 2016

Purpose - This paper aims to find and analyze factors that determine the flows of bilateral foreign direct investment in intra-ASEAN. It specifically focuses on the dimension of macro-economic, natural resources, human resources, and the quality of governance. Research design, data, and methodology - Data were collected from 64 bilateral relations between ASEAN nations from 2002 to 2013. Panel gravity model was utilized to find factors that determine the flows of bilateral foreign direct investment. Results - Significant factors were identified that determine the flows of bilateral foreign direct investment: GDP home country, GDP host country, real interest rate, distance, and total natural resources rent. Unexpectedly, natural resources have a negative effect. Conclusions - In a situation of increasing the flow of FDI among the countries of ASEAN, the government should control the interest rates and maintain good relations with nearby countries. The negative effect of total natural resource rents implies that ASEAN countries should not depend on their natural resources to attract foreign investments.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.107-122
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• 2016

This study aims to develop a framework to estimate mobile source emissions with the macroscopic travel demand model including enhanced estimates of intra-zonal travel emissions using Space Syntax analysis. It is acknowledged that "the land-use and transportation interaction model explains the influence of urban structure on accessibility and mobility pattern". Based upon this theory, the estimation model of intra-zonal travel emissions is presented with the models of total travel distance, total travel demand, and average travel speed of intra-zonal trips. Thess statistical models include several spatial indices derived from the Space Syntax analysis. It explains that urban spatial structure is a critical factor for intra-zonal travel emissions, which is lower in compact zone with smaller portion of land area, lower sprawl indicator, and more grid-type of road network. Also the suggested framework is applied in the evaluation of the effectiveness of bicycle lane project in Suwon, Korea. The estimated emissions including intra-zonal travel is as double as the results only with inter-zonal demands, which shows better performance of the suggested framework for more realistic outcomes. This framework is applicable to the estimation of mobile source emissions in nation-wide and the assessment of transportation-environment policies in regional level.

• ETRI Journal
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• v.35 no.2
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• pp.270-280
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• 2013

A fast intra-prediction method is proposed for High Efficiency Video Coding (HEVC) using a fast intra-mode decision and fast coding unit (CU) size decision. HEVC supports very sophisticated intra modes and a recursive quadtree-based CU structure. To provide a high coding efficiency, the mode and CU size are selected in a rate-distortion optimized manner. This causes a high computational complexity in the encoder, and, for practical applications, the complexity should be significantly reduced. In this paper, among the many predefined modes, the intra-prediction mode is chosen without rate-distortion optimization processes, instead using the difference between the minimum and second minimum of the rate-distortion cost estimation based on the Hadamard transform. The experiment results show that the proposed method achieves a 49.04% reduction in the intra-prediction time and a 32.74% reduction in the total encoding time with a nearly similar coding performance to that of HEVC test model 2.1.

• The Journal of Advanced Prosthodontics
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• v.14 no.2
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• pp.63-69
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• 2022

PURPOSE. The aim of this in vitro study was to investigate the accuracy (trueness and precision) of five intraoral scanners (IOS) using a novel reference model for standardized performance evaluation. MATERIALS AND METHODS. Five IOSs (Medit i500, Omnicam, Primescan, Trios 3, Trios 4) were used to digitize the reference model, which represented a simplified full-arch situation with four abutment teeth. Each IOS was used five times by an experienced operator, resulting in 25 STL (Standard Tessellation Language) files. STL data were imported into 3D software (Final Surface^®) and examined for inter- and intra-group analyses. Deviations in the parameter matching error were calculated. ANOVA F-test and Kruskal-Wallis test were applied for inter-group comparisons (α = .05); and the coefficient of variation (CV) was calculated for intra-group comparisons (in % ± SD). RESULTS. Primescan (matching error value: 0.015), Trios 3 (0.016), and Trios 4 (0.018) revealed comparable results with significantly higher accuracy compared to Medit i500 (0.035) and Omnicam (0.028) (P < .001). For intra-group comparison, Trios 4 demonstrated the most homogenous results (CV 15.8%). CONCLUSION. The novel reference model investigated in this study can be used to assess the performance of dental scanning technologies in the daily routine setting and in research settings.

• Investigative Magnetic Resonance Imaging
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• v.19 no.3
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• pp.168-177
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• 2015

Purpose: Brain surface intensity model (BSIM)-based cortical thickness analysis does not require complicated 3D segmentation of brain gray/white matters. Instead, this technique uses the local intensity profile to compute cortical thickness. The aim of the present study was to evaluate intra-rater and inter-rater reliability of BSIM-based cortical thickness analysis using images from elderly participants. Materials and Methods: Fifteen healthy elderly participants (ages, 55-84 years) were included in this study. High-resolution 3D T1-spoiled gradient recalled-echo (SPGR) images were obtained using 3T MRI. BSIM-based processing steps included an inhomogeneity correction, intensity normalization, skull stripping, atlas registration, extraction of intensity profiles, and calculation of cortical thickness. Processing steps were automatic, with the exception of semiautomatic skull stripping. Individual cortical thicknesses were compared to a database indicating mean cortical thickness of healthy adults, in order to produce Z-score thinning maps. Intra-class correlation coefficients (ICCs) were calculated in order to evaluate inter-rater and intra-rater reliabilities. Results: ICCs for intra-rater reliability were excellent, ranging from 0.751-0.940 in brain regions except the right occipital, left anterior cingulate, and left and right cerebellum (ICCs = 0.65-0.741). Although ICCs for inter-rater reliability were fair to excellent in most regions, poor inter-rater correlations were observed for the cingulate and occipital regions. Processing time, including manual skull stripping, was $17.07{\pm}3.43min$. Z-score maps for all participants indicated that cortical thicknesses were not significantly different from those in the comparison databases of healthy adults. Conclusion: BSIM-based cortical thickness measurements provide acceptable intra-rater and inter-rater reliability. We therefore suggest BSIM-based cortical thickness analysis as an adjunct clinical tool to detect cortical atrophy.