• Title/Summary/Keyword: Feature weight

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Content- based Image Retrieval using Fuzzy Integral (퍼지 적분을 이용한 내용기반 영상 검색)

  • Kim, Dong-Woo;Song, Young-Jun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.2
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    • pp.203-208
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    • 2006
  • The management of image information settles as an important field with the advent of multimedia age and we are in need of the effective retrieval method to manage systematically image information. This paper has complemented the problem caused by the absence of space information that is a weak point of the existing color histogram method by assigning regions of features, and raised accuracy by adding texture and shape information. And existing methods using multiple features have problems that the retrieval process is embarrassed because each weight is set up manually. So we has solved these problems by assignment of weight applying fuzzy integral. As a result of experimenting with 1,000 color images, the proposed method showed better precision and recall than the existing method.

A Theory on Phase Behaviors of Diblock Copolymer/Homopolymer Blends

  • 윤경섭;박형석
    • Bulletin of the Korean Chemical Society
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    • v.16 no.9
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    • pp.873-885
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    • 1995
  • The local structural and thermodynamical properties of blends A-B/H of a diblock copolymer A-B and a homopolymer H are studied using the polymer reference interaction site model (RISM) integral equation theory with the mean-spherical approximation closure. The random phase approximation (RPA)-like static scattering function is derived and the interaction parameter is obtained to investigate the phase transition behaviors in A-B/H blends effectively. The dependences of the microscopic interaction parameter and the macrophase-microphase separation on temperature, molecular weight, block composition and segment size ratio of the diblock copolymer, density, and concentration of the added homopolymer, are investigated numerically within the framework of Gaussian chain statistics. The numerical calculations of site-site interchain pair correlation functions are performed to see the local structures for the model blends. The calculated phase diagrams for A-B/H blends from the polymer RISM theory are compared with results by the RPA model and transmission electron microscopy (TEM). Our extended formal version shows the different feature from RPA in the microscopic phase separation behavior, but shows the consistency with TEM qualitatively. Scaling relationships of scattering peak, interaction parameter, and temperature at the microphase separation are obtained for the molecular weight of diblock copolymer. They are compared with the recent data by small-angle neutron scattering measurements.

Lifting Lug by the Change of form Using Multivariate Functions: An Optimal Design Study (다변수 함수를 이용한 형상 변화에 따른 리프팅 러그의 최적 설계에 관한 연구)

  • Choi, Kyung-Shin;Kim, Ji-Jun;Lee, Ji-Han;Chan, Gwang-Woo
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.20 no.4
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    • pp.31-38
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    • 2021
  • In this paper, we proposed an optimal design for determining the shape of a lifting lug freely by applying a multivariate function to the D-type lug, which is commonly used in shipyards. We derived the optimal aspect ratio of the lug through structural analysis and analyzed the safety and behavior of the lug aspect ratio. As a result, two types of final candidates, both lighter than the existing lug weight, were suitable for the ratio. They were found to have the greatest force at an angle of 45 degrees when a load of 100 tons was imposed. When the horizontal and vertical feature ratio of the lug was 1:3, it showed excellent results in terms of safety rates while maintaining weight reduction and functional aspects.

Forecasting Volatility of Stocks Return: A Smooth Transition Combining Forecasts

  • HO, Jen Sim;CHOO, Wei Chong;LAU, Wei Theng;YEE, Choy Leng;ZHANG, Yuruixian;WAN, Cheong Kin
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.10
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    • pp.1-13
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    • 2022
  • This paper empirically explores the predicting ability of the newly proposed smooth transition (ST) time-varying combining forecast methods. The proposed method allows the "weight" of combining forecasts to change gradually over time through its unique feature of transition variables. Stock market returns from 7 countries were applied to Ad Hoc models, the well-known Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family models, and the Smooth Transition Exponential Smoothing (STES) models. Of the individual models, GJRGARCH and STES-E&AE emerged as the best models and thereby were chosen for constructing the combined forecast models where a total of nine ST combining methods were developed. The robustness of the ST combining forecasts is also validated by the Diebold-Mariano (DM) test. The post-sample forecasting performance shows that ST combining forecast methods outperformed all the individual models and fixed weight combining models. This study contributes in two ways: 1) the ST combining methods statistically outperformed all the individual forecast methods and the existing traditional combining methods using simple averaging and Bates & Granger method. 2) trading volume as a transition variable in ST methods was superior to other individual models as well as the ST models with single sign or size of past shocks as transition variables.

Fast Fingerprint Alignment Method and Weighted Feature Vector Extraction Method in Filterbank-Based Fingerprint Matching (필터뱅크 기반 지문정합에서 빠른 지문 정렬 방법 및 가중치를 부여한 특징 벡터 추출 방법)

  • 정석재;김동윤
    • Journal of KIISE:Software and Applications
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    • v.31 no.1
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    • pp.71-81
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    • 2004
  • Minutiae-based fingerprint identification systems use minutiae points, which cannot completely characterize local ridge structures. Further, this method requires many methods for matching two fingerprint images containing different number of minutiae points. Therefore, to represent the fired length information for one fingerprint image, the filterbank-based method was proposed as an alternative to minutiae-based fingerprint representation. However, it has two shortcomings. One shortcoming is that similar feature vectors are extracted from the different fingerprints which have the same fingerprint type. Another shortcoming is that this method has overload to reduce the rotation error in the fingerprint image acquisition. In this paper, we propose the minutia-weighted feature vector extraction method that gives more weight in extracting feature value, if the region has minutiae points. Also, we Propose new fingerprint alignment method that uses the average local orientations around the reference point. These methods improve the fingerprint system's Performance and speed, respectively. Experimental results indicate that the proposed methods can reduce the FRR of the filterbank-based fingerprint matcher by approximately 0.524% at a FAR of 0.967%, and improve the matching performance by 5% in ERR. The system speed is over 1.28 times faster.

Forming Weighting Adjustment Cells for Unit-Nonresponse in Sample Surveys (표본조사에서 무응답 가중치 조정층 구성방법에 따른 효과)

  • Kim, Young-Won;Nam, Si-Ju
    • Communications for Statistical Applications and Methods
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    • v.16 no.1
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    • pp.103-113
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    • 2009
  • Weighting is a common form of unit nonresponse adjustment in sample surveys where entire questionnaires are missing due to noncontact or refusal to participate. A common approach computes the response weight as the inverse of the response rate within adjustment cells based on covariate information. In this paper, we consider the efficiency and robustness of nonresponse weight adjustment bated on the response propensity and predictive mean. In the simulation study based on 2000 Fishry Census in Korea, the root mean squared errors for assessing the various ways of forming nonresponse adjustment cell s are investigated. The simulation result suggest that the most important feature of variables for inclusion in weighting adjustment is that they are predictive of survey outcomes. Though useful, prediction of the propensity to response is a secondary. Also the result suggest that adjustment cells based on joint classification by the response propensity and predictor of the outcomes is productive.

Error Calibration of Initial Value of Weight Measuring Sensors with Different Feature of Forklift (특성이 다른 지게차 적재 중량 센서의 초기 값 오차 보정)

  • Han, Chi-moon;Yim, Choon-Sik;Lee, Seong-Real
    • Journal of Advanced Navigation Technology
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    • v.23 no.2
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    • pp.214-220
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    • 2019
  • The calibration method of the initial value error obtained in the weight measurement through anchor bolt type strain gauge sensor is proposed. The strain gauge sensor is developed for preventing the overturning of forklift, which is the most frequent type of safety-accident in industry. It was confirmed that the initial value error is caused from the physical and mechanical error of anchor bolt, and the environmental problem. Since the elimination of these causes falls outside the realm of this research, we find out the calibrated values based on all the causes, and we adjust the initial values of analog-to-digital convertor (ADC) module consisted of strain gauge sensor block using the calibrated values. We use the linear interpolation method for our calibration. We confirm that four sensor modules have the different under 5% between the real weight and the measured value in the experiment applied with the calibration of initial values. The low correlation between the real weights and ADC values is also improved through the proposed calibration.

Schematic Cost Estimation Method using Case-Based Reasoning: Focusing on Determining Attribute Weight (사례기반추론을 이용한 초기단계 공사비 예측 방법: 속성 가중치 산정을 중심으로)

  • Park, Moon-Seo;Seong, Ki-Hoon;Lee, Hyun-Soo;Ji, Sae-Hyun;Kim, Soo-Young
    • Korean Journal of Construction Engineering and Management
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    • v.11 no.4
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    • pp.22-31
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    • 2010
  • Because the estimated cost at early stage has great influence on decisions of project owner, the importance of early cost estimation is increasing. However, it depends on experience and knowledge of the estimator mainly due to shortage of information. Those tendency developed into case-based reasoning(CBR) method which solves new problems by adapting previous solution to similar past problems. The performance of CBR model is affected by attribute weight, so that its accurate determination is necessary. Previous research utilizes mathematical method or subjective judgement of estimator. In order to improve the problem of previous research, this suggests CBR schematic cost estimation method using genetic algorithm to determine attribute weight. The cost model employs nearest neighbor retrieval for selecting past case. And it estimates the cost of new cases based on cost information of extracted cases. As the result of validation for 17 testing cases, 3.57% of error rate is calculated. This rate is superior to accuracy rate proposed by AACE and the method to determine attribute weight using multiple regression analysis and feature counting. The CBR cost estimation method improve the accuracy by introducing genetic algorithm for attribute weight. Moreover, this makes user understand the problem-solving process easier than other artificial intelligence method, and find solution within short time through case retrieval algorithm.

The Pupil Motion Tracking Based on Active Shape Model Using Feature Weight Vector (특징 가중치 벡터를 적용한 능동 형태 모델 기반의 눈동자 움직임 추적)

  • Kim, Soon-Beak;Lee, Soo-Heum
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2005.11a
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    • pp.205-208
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    • 2005
  • 본 논문은 특징 가중치 벡터를 적용하여 능동형태 모델(Active Shape Model)기반에서 눈동자의 움직임 추적 속도를 향상시키는 방법을 제안한다. 일반적인 능동형태 모델에서는 객체 추적을 위한 PDM 구성을 위해 각 특징점 구성 벡터의 유클리디안 거리의 최소 값으로 Training Set정렬 과정을 수행한다. 이 과정에서 적절하지 못한 샘플 영상으로 인해 안정된 PDM을 구성하지 못하는 문제점이 발생한다. 이러한 문제점을 해결하기 위하여 본 논문에 서는 형태를 구성하는 특징점마다 가중치를 부여하는 벡터를 작성하고, 최소자승근사법으로 최유사 특징점 벡터를 산출하기 위한 선형방정식을 구상하였다. 이로 인해 안정된 PDM을 구성할 수 있었으며, 눈동자 추적실험을 통해 형태적 움직임을 보정하는 실험을 수행하였다. 실험결과 기존의 능동형태 모델에 비해 반복연산의 횟수가 줄어들고, 다양한 형태로 나타나는 눈동자의 움직임 추적에 보다 안정적인 결과를 얻을 수 있었다.

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Visceral Leishmaniasis without Fever in an 11-Month-Old Infant: a Rare Clinical Feature of Kala-azar

  • Sayyahfar, Shirin;Ansari, Shahla;Mohebali, Mehdi;Behnam, Babak
    • Parasites, Hosts and Diseases
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    • v.52 no.2
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    • pp.189-191
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    • 2014
  • Visceral leishmaniasis or kala-azar is an endemic parasitic disease in some parts of the world which is characterized by fever, splenomegaly, and pancytopenia in most of the cases. Herein we report an 11 month-old male infant with diagnosis of kala-azar who presented with pallor, hepatosplenomegaly, failure to gain weight, and no history of fever. Surprisingly, fever started after beginning of meglumine antimoniate treatment in this patient. As far as we are aware of, this is a rare presentation of visceral leishmaniasis. Therefore, clinicians especially in endemic areas are highly recommended to include kala-azar among differential diagnosis of unexplained anemia without fever to prevent misdiagnosis of this potentially fatal, but treatable condition.