• 대한건축학회논문집:계획계
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• 제34권12호
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• pp.49-54
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• 2018

Applying metric(distance) factor as weighting to spatial syntax is known to not contribute to the explanatory power for the human movement behavior as compared to the geometric(angle) factor according to the negative results of several related studies. However, Kim & Piao (2017) assumed that there is not a problem of the metric factor itself but a problem of the way of applying the metric factor as weighting, and presented a new possibility of the metric factor as weighting by proposing and verifying the methods of applying the metric weighting, which are different from the existing ones. The purpose of this study is to propose advanced methods of applying the metric weighting to space syntax, and to verify whether they contribute to the improvement of explanatory power of space syntax analysis. In this paper, we propose functions for combined depth of distance-step that combine the distance-weighted depth function with the step depth function and apply them to axial segment analysis to check the improvement of explanatory power of them.

• Journal of Positioning, Navigation, and Timing
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• 제4권2호
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• pp.79-85
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• 2015

Existing Differential GPS (DGPS) pseudorange correction (PRC) generation techniques based on a virtual reference station cannot effectively assign a weighting factor if the baseline distance between a user and a reference station is not long enough. In this study, a virtual reference station DGPS PRC generation technique was developed based on an enhanced inverse distance weighting method using an exponential function that can maximize a small baseline distance difference due to the dense arrangement of DGPS reference stations in South Korea, and its positioning performance was validated. For the performance verification, the performance of the model developed in this study (EIDW) was compared with those of typical inverse distance weighting (IDW), first- and second-order multiple linear regression analyses (Planar 1 and 2), the model of Abousalem (1996) (Ab_EXP), and the model of Kim (2013) (Kim_EXP). The model developed in the present study had a horizontal accuracy of 53 cm, and the positioning based on the second-order multiple linear regression analysis that showed the highest positioning accuracy among the existing models had a horizontal accuracy of 51 cm, indicating that they have similar levels of performance. Also, when positioning was performed using five reference stations, the horizontal accuracy of the developed model improved by 8 ~ 42% compared to those of the existing models. In particular, the bias was improved by up to 27 cm.

• 한국태양에너지학회 논문집
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• 제37권6호
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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.

• 한국음향학회지
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• 제4권1호
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• pp.43-54
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• 1985

이 논문에서는 Frequency weighting을 이용하여 선형예측 부호화기의 명료성을 개선하는 방법 을 연구한다. 잡음이 섞이지 않은 음성에 대해서는 음성을 분석하기전에 frequency weighting을 행한다. 또한 잡음이 섞인 음성인 경우에는 잡음성분을 spectral subtraction 방법에 의해서 제거한 다음에 frequency weighting을 준다. 이 때 frequency weighting을 주기 위해서 귀의 특성과 연관되어 잘 알려 진 C- message weighting 함수, flanagan weighting 함수 및 articulation index를 약간 수정한 weighting 함수를 사용했다. 여러 객관적인 distance measure를 사용하여 frequency weighting 방법의 성능을 측정하고 귀로 들어 본 결과, frequency weighting 방법을 사용하여 선형예측 방법에 의한 합성 음의 명료도를 효율적으로 개선할 수 있었다.

• 한국음향학회지
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• 제15권4호
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• pp.36-42
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• 1996

본 연구에서는 견고한 이산형 은닉마르코프모델의 파라미터를 얻기위한 방법으로 CDDN(codeword dependent distance Normalization)과 거리에 기반한 코드워드 가중방법을 제안한다. 제안된 방법에서 FVQ(fuzzy vector quantization)에 기반한 방법에서 코드워드에 대한 출력확률 계산 시, 코드워드의 분포특성과 상태 의존적인 코드워드의 특성을 반영하여 거리를 계산하고, 이 거리값에 퍼지목적함수를 적용하여 코드워드별 기여도를 계산한다. 실험결과, 제안된 방법이 기존의 FVQ기반한 방법에 비해서 4.5%정도의 인식율 향상이 있음을 할 수 있었다. 특히, 거리가중치를 사용하여 출력확률 평활화를 적용한 경우가 단순히 코드워드별 가중을 적용한 경우에 비해서 2.5% 성능향상을 보였다.

• 한국멀티미디어학회논문지
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• 제9권6호
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• pp.762-772
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• 2006

Instance based learning algorithm is the best known lazy learner and has been successfully used in many areas such as pattern analysis, medical analysis, bioinformatics and internet applications. However, its feature weighting scheme is too naive that many other extensions are proposed. Our version of IB3 named as eXtended IBL (XIBL) improves feature weighting scheme by backward stepwise regression and its distance function by VDM family that avoids overestimating discrete valued attributes. Also, XIBL adopts leave-one-out as its noise filtering scheme. Experiments with common artificial domains show that XIBL is better than the original IBL in terms of accuracy and noise tolerance. XIBL is applied to two important applications - intrusion detection and spam mail filtering and the results are promising.

• 스마트미디어저널
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• 제2권1호
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• pp.31-36
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• 2013

A robust and efficient text extraction is very important for an accuracy of Optical Character Recognition (OCR) systems. Natural scene images with degradations such as uneven illumination, perspective distortion, complex background and multi color text give many challenges to computer vision task, especially in text extraction. In this paper, we propose a method for extraction of the text in signboard images based on a combination of mean shift algorithm and weighting scheme of hue and saturation in HSI color space for clustering algorithm. The number of clusters is determined automatically by mean shift-based density estimation, in which local clusters are estimated by repeatedly searching for higher density points in feature vector space. Weighting scheme of hue and saturation is used for formulation a new distance measure in cylindrical coordinate for text extraction. The obtained experimental results through various natural scene images are presented to demonstrate the effectiveness of our approach.

• 대한기계학회논문집A
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• 제34권12호
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• pp.1793-1803
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• 2010

가중치법이나 목표계획법을 이용하여 다목적함수 최적화를 수행할 때 설계자는 각 함수에 적절한 가중치나 목표값을 설정해 주어야 한다. 하지만 파라미터를 잘못 설정하게 되면 파레토 최적해를 얻지못하기 때문에 이는 설계자에게 큰 부담이 된다. 최근에 데이터의 분포특성만을 이용하여 데이터의 평균과 함수 사이의 거리를 표현하는 마하라노비스 거리(MD)를 최소화하는 MTS기법이 개발되었다. 이 방법은 파라미터를 설정하지 않아도 되는 장점이 있지만 최적해가 참고데이터의 평균으로 수렴하는 단점이 있다. 따라서 본 연구에서는 방향성이 없는 기존의 MD에 방향성을 부여한 새로운 거리 척도인 SMD를 제안하였다. 그리고 SMD법이 계산과정에서 각 함수의 가중치를 자동으로 반영하고 평균에서 가장 멀리 위치한 한 점을 항상 파레토 최적해로 제공한다는 것을 2개의 단순예제를 통해 검증하였다.

• 대한임베디드공학회논문지
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• 제6권2호
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• pp.108-116
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• 2011

Non-line-of-sight (NLOS) error is the most common and also a major source of errors in wireless location system. A novel weighting factor (NWF) method is presented in this paper, based on the RSS(Received Signal Strength) measurements, path loss model and Circular Disk of Scatterers Model (CDSM). The proposed positioning method effectively weighted the TOA distance measurements for each Base Station (BS). Simulation results show that the proposed method efficiently weighted the distance measurements and achieve higher localization accuracy than that of Linear Line of Position (LLOP) and Believable Factor Algorithm (BFA).

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.123-126
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• 2000

In this paper, we propose new watermarking technique using weighting factor decision method in the watermark embedding step and adaptive threshold decision method in the watermark extracting step. In our method, we are determined weighting factor in simple by calculating distance between pixel coefficient and neighborhood pixel coefficients and threshold is adaptively determined by searching the minimized extract error value using histogram of difference value.