• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.34-44
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• 2016

This study was initiated to evaluate the performance of methodologies to estimate the space mean speed(SMS) using the time mean speed(TMS) which was collected from the vehicle detection system(VDS) in expressways. To this end, the methodologies presented in prior studies were firstly summarized. It is very hard to achieve exact SMSs and TMSs due to mechanical and communication errors in the field. Thus, a microscopic traffic simulation model was utilized to evaluated the performance. As a result, the harmonic mean and volume-distance weighted harmonic mean were close to the SMS in the case in which the TMSs of individual vehicles were used. However, when the 30-second-interval aggregated TMS were used, the volume-distance weighted harmonic mean was outstanding. In this study, a radar detector was installed in the Joongbu expressway to collect the SMS. The trajectory of individual vehicles collected from the detector were used to calculate the SMS, which was compared with the estimates using other methodologies selected in this study. As a result, the volume-distance weighted mean was turned out to be close to the SMS. However, as the congestion becomes severe. the deviation between the two speed becomes bigger.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.1
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• pp.16-21
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• 2002

Repetitive strings have been studied in such diverse fields as molecular biology data compression etc. Some important regularities that have been studied are perods, covers seeds and squares. A natural extension of the repetition problems is to allow errors. Among the four notions above aproximate squares and approximate periodes have been studied. In this paper, we introduce the notion of approximate covers which is an approximate version of covers. Given two strings P(｜P｜=m) and T(｜T｜=n) we propose and algorithm with finds the minimum distance t such that P is a t-approximate cover of T. The algorithm take O(m,n) time for the edit distance and $O(mn^2)$ time of finding a string which is an approximate cover of T is minimum distance is NP-complete.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2570-2572
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• 2005

본 논문에서는 다중 경로 오차 제거를 위해, 4개의 상관값을 제공하는 가중 협대역 상관기(Weighted Narrow Correlator) 구조에 대해 제안한다. 가중 협대역 상관기는 서로 다른 칩 간격을 가지는 여러 상관값 출력에 가중치를 주어 다중경로 신호에 의한 코드 위상 측정 오차를 줄이는 방법이다. 우선 다양한 지연시간 및 신호 감쇄를 가지는 다중 경로 신호에 대하여, 가중치에 대한 수신기의 성능 변화를 분석하고 이를 통해 최적의 가중치를 선택하였다. 제안한 상관기는 일반 수신기와 동일한 신호 획득능력을 가지며, 협대역 상관기보다 개선된 다중경로 오차 제거 능력을 보인다. 가중 협대역 상관기의 성능은 시뮬레이션을 통한 의사거리 측정치의 비교를 통해 검증하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.3
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• pp.554-559
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• 2009

This paper proposes a new method of weighted template matching fur machine-printed numeral recognition. The proposed weighted template matching, which emphasizes the feature of a pattern using adaptive Hamming distance on local feature areas, improves the recognition rate while template matching processes an input image as one global feature. The experiment compares confusion matrices of the template matching, error back propagation neural network classifier, and the proposed weighted template matching respectively. The result shows that the proposed method improves fairly the recognition rate of the machine-printed numerals.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.43-50
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• 2013

This paper aims to determine the optimal location of expressway patrol vehicle stations that minimizes additional troubles caused by the delay of crash treatments. To do this, we formulate a maximum covering problem and a p-center problem weighted by crash frequency, using the shortest distance as the criteria for allocating service district, and we employ the Lagrangian relaxation algorithm to solve the former and Daskin's heuristic algorithm to solve the latter, respectively. Based on crash data of Korean expressways, the results from the proposed models are compared with the current location of patrol vehicle stations by using several indices as the level of service for crash treatment, such as maximum crash-weighted distance, average crash-weighted distance, and average access distance. The results show that the proposed models improve average access distance and time by about 10km and 10min, respectively. When allocation for service district is changed only with the fixed current location, the level of service can be also improved. The models and results proposed in this paper can contribute to improving the level of service for crash treatment on expressways. They can also provide the theoretical basis on the location decision for other various emergency facilities, and the allocation decision for floating service districts according to time-period crash data.

• The Journal of the Acoustical Society of Korea
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• v.31 no.4
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• pp.266-272
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• 2012

Speaker segmentation is a process of automatically detecting the speaker boundary points in the audio data. Speaker segmentation methods are divided into two categories depending on whether they use a prior knowledge or not: One is the model-based segmentation and the other is the metric-based segmentation. In this paper, we introduce the eigenvoice-based speaker weight distance method and compare it with the representative metric-based methods. Also, we employ and compare the Euclidean and cosine similarity functions to calculate the distance between speaker weight vectors. And we verify that the speaker weight distance method is computationally very efficient compared with the method directly using the distance between the speaker adapted models constructed by the eigenvoice technique.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.366-373
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• 2017

In this paper, we propose a variable weighted average (VWA) learning method in order to improve the performance of the fuzzy ART neural network that has been developed by Grossberg. In a conventional method, the Fast Commit Slow Recode (FCSR), when an input pattern falls in a category, the representative pattern of the category is updated at a fixed learning rate regardless of the degree of similarity of the input pattern. To resolve this issue, a variable learning method proposes reflecting the distance between the input pattern and the representative pattern to reduce the FCSR's category proliferation issue and improve the pattern recognition rate. However, these methods still suffer from the category proliferation issue and limited pattern recognition rate due to inevitable excessive learning created by use of fuzzy AND. The proposed method applies a weighted average learning scheme that reflects the distance between the input pattern and the representative pattern when updating the representative pattern of a category suppressing excessive learning for a representative pattern. Our simulation results show that the newly proposed variable weighted average learning method (VWA) mitigates the category proliferation problem of a fuzzy ART neural network by suppressing excessive learning of a representative pattern in a noisy environment and significantly improves the pattern recognition rates.

• Journal of the Korea Organic Resources Recycling Association
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• v.23 no.3
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• pp.78-84
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• 2015

The aim of this study was to evaluate methane emission flux based on spatial methane concentration using laser methane detector, and geospatial methodology (Inverse distance weighting) at a landfill. The obtained results showed that the spatial methane concentrations were in good agreement with the methane emission fluxes. Thus, it was concluded that the methane emission flux could be derived from spatial methane concentrations. In addition, the results of the geospatial calculations showed that 12.85% of the total area contributed more than 42.21% of total flux. This suggested that the geospatial methodology might be essential in chamber method to determine accurate methane emission fluxes from landfills.

• Journal of the Korean Solar Energy Society
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• v.37 no.6
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• pp.79-91
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• 2017

The meteorological data of 1 hour interval are required to write a typical weather data for building energy simulation. However, many meterological data are missing and the interpolation method to recover the missing data is required. Especially, lots of meterological data are replicated by linear interpolation method because the changes are not significant. While, the wind velocity fluctuates with the time or locations, so linear interpolation method is not appropriate in interpolation of the wind velocity data. In this study, three interpolation methods, using surrounding wind velocity data, Inverse Distance Weighting (IDW), Revised Inverse Distance Weighting (IDW-r), were analyzed considering the characteristics of wind velocity. The Revised Inverse Distance Weighting method, proposed in this study, showed the highest reliability in restoration of the wind velocity data among the analyzed methods.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.104-104
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• 2019

기후 관측자료의 경우 관측, 가공, 전송 중에 오류가 발생할 수 있으며, 특히 글로벌 기후자료는 다양한 조건을 가지고 있는 자료를 수집하였기 때문에 일반적으로 해당 국가 관측자료보다 품질이 낮다. 본 연구에서는 글로벌 기후 관측자료의 품질을 개선할 수 있는 품질관리 기법을 개발하고 국내 지역에 적용해보고자 한다. 연구대상지역으로 국내 대표도시 7 곳을 선정하였으며, 글로벌 기후자료는 NCDC (National Climatic Data Center)의 일 단위 GSOD (Global Surface Summary of the Day) 자료를 수집하였다. 품질관리는 강수와 기온에 대해서 실시하였으며 과정은 크게 이상치 검사, 이상치 및 결측치 보정, 연, 월 단위 기후 자료 산정으로 구분된다. 이상치 검사는 중복성 검사, 내적일치성 검사, 기후범위 검사, 공간동질성 검사를 기반으로 구성되어 있다. 이상치 및 결측치 보정은 인접 관측소의 자료를 보간하여 수행하였으며, 보간기법은 4 방향 역거리 가중법을 활용하였다. 연, 월 단위 자료 산정은 자료의 결측률을 고려하여 일 단위 자료를 연, 월 단위 자료로 변환하는 과정이다. 이상치 검사 결과 대부분의 이상치는 기후범위와 공간동질성 검사에서 발견되는 것으로 나타났으며, 중복성 및 내적일치성 검사는 이상치 검출 효과가 적은 것으로 나타났다. 결측치 및 이상치 보간 결과 추정된 자료와 관측값 간의 상관관계가 있는 것으로 나타나 활용성이 있었다. 본 연구는 글로벌 자료의 품질관리 기법을 제시하였다는 점에서 활용성이 있으며, 향후 품질관리 기법의 검증에 관한 연구를 수행할 필요가 있다.