• Title/Summary/Keyword: $A^*$ search algorithm

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Optimized Simulation Framework for the Analysis in Battle systems (전투실험 분석을 위한 최적화 시뮬레이션 프레임워크)

  • Kang, Jong-Gu;Lee, Minkyu;Kim, Sunbum;Hwang, Kun-Chul;Lee, Donghoon
    • Journal of the Korea Society for Simulation
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    • v.24 no.2
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    • pp.1-9
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    • 2015
  • The tactical employment is a critical factor to win the war in the modern battlefield. To apply optimized tactics, it needs analyses related to a battle system. Normally, M&S (Modeling & Simulation) has been studied to analyze data in general problems. However, this method is not suitable for military simulations because there are many variables which make complex interaction in the system. For this reason, we suggested the optimized simulation framework based on the M&S by using DPSO (Discrete binary version of PSO) algorithm. This optimized simulation framework makes the best tactical employment to reduce the searching time compared with the normal M&S used by Monte Carlo search method. This paper shows an example to find the best combination of anti-torpedo scenario in a short searching time. From the simulation example, the optimized simulation framework presents the effectiveness.

Texture Image Database Retrieval Using JPEG-2000 Partial Entropy Decoding (JPEG-2000 부분 엔트로피 복호화에 의향 질감 영상 데이터베이스 검색)

  • Park, Ha-Joong;Jung, Ho-Youl
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.5C
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    • pp.496-512
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    • 2007
  • In this paper, we propose a novel JPEG-2000 compressed image retrieval system using feature vector extracted through partial entropy decoding. Main idea of the proposed method is to utilize the context information that is generated during entropy encoding/decoding. In the framework of JPEG-2000, the context of a current coefficient is determined depending on the pattern of the significance and/or the sign of its neighbors in three bit-plane coding passes and four coding modes. The contexts provide a model for estimating the probability of each symbol to be coded. And they can efficiently describe texture images which have different pattern because they represent the local property of images. In addition, our system can directly search the images in the JPEG-2000 compressed domain without full decompression. Therefore, our proposed scheme can accelerate the work of retrieving images. We create various distortion and similarity image databases using MIT VisTex texture images for simulation. we evaluate the proposed algorithm comparing with the previous ones. Through simulations, we demonstrate that our method achieves good performance in terms of the retrieval accuracy as well as the computational complexity.

Adaptive Scene Classification based on Semantic Concepts and Edge Detection (시멘틱개념과 에지탐지 기반의 적응형 이미지 분류기법)

  • Jamil, Nuraini;Ahmed, Shohel;Kim, Kang-Seok;Kang, Sang-Jil
    • Journal of Intelligence and Information Systems
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    • v.15 no.2
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    • pp.1-13
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    • 2009
  • Scene classification and concept-based procedures have been the great interest for image categorization applications for large database. Knowing the category to which scene belongs, we can filter out uninterested images when we try to search a specific scene category such as beach, mountain, forest and field from database. In this paper, we propose an adaptive segmentation method for real-world natural scene classification based on a semantic modeling. Semantic modeling stands for the classification of sub-regions into semantic concepts such as grass, water and sky. Our adaptive segmentation method utilizes the edge detection to split an image into sub-regions. Frequency of occurrences of these semantic concepts represents the information of the image and classifies it to the scene categories. K-Nearest Neighbor (k-NN) algorithm is also applied as a classifier. The empirical results demonstrate that the proposed adaptive segmentation method outperforms the Vogel and Schiele's method in terms of accuracy.

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Mutual Information-based Circular Template Matching for Image Registration (영상등록을 위한 Mutual Information 기반의 원형 템플릿 정합)

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.30 no.5
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    • pp.547-557
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    • 2014
  • This paper presents a method for designing circular template used in similarity measurement for image registration. Circular template has translation and rotation invariant property, which results in correct matching of control points for image registration under the condition of translation and rotation between reference and sensed images. Circular template consisting of the pixels located on the multiple circumferences of the circles whose radii vary from zero to a certain distance, is converted to two-dimensional Discrete Polar Coordinate Matrix (DPCM), whose elements are the pixels of the circular template. For sensed image, the same type of circular template and DPCM are created by rotating the circular template repeatedly by a certain degree in the range between 0 and 360 degrees and then similarity is calculated using mutual information of the two DPCMs. The best match is determined when the mutual information for each rotation angle at each pixel in search area is maximum. The proposed algorithm was tested using KOMPSAT-2 images acquired at two different times and the results indicate high accurate matching performance under image rotation.

A Study on the Methodology of Acupuncture Clinical Trial on the Postmenopausal and Perimenopausal Hot Flashes (갱년기 안면홍조에 대한 침 임상시험 방법론 연구)

  • Roh, Jin-Ju;Kim, Dong-Il
    • The Journal of Korean Obstetrics and Gynecology
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    • v.21 no.4
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    • pp.193-206
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    • 2008
  • Purpose: In spite of many arguments on the result of WHI (Women's Health Initiative) study, no one can deny the necessity for researches on the alternative treatment to HRT (hormone replacement therapy). In this study, the author wanted to investigate the method of precedent acupuncture RCTs (randomized controlled trials) to make out the appropriate acupuncture study design on postmenopausal and perimenopausal hot flashes in Korea. Methods: Precedent studies were investigated using Pubmed search and key-words "acupuncture and hot flash", "acupuncture and menopause", "acupuncture and vasomotor", limited to RCT, from 2000 to 2008 April. Results: As a result. 10 studies were searched. In the hereafter studies, multi-center clinical trials which consist of population group of postmenopausal and perimenopausal women that would be pre-stratified and more than 50 patients per treatment arm seem adequate. Sham control study can make out the proper consequence because many people are get used to acupuncture in Korea. Flexible choice of acupoints addressed an individual's symptoms using standardized algorithm is recommended. Treatment consist of 4 weeks' observation, 11 acupuncture sessions during 7 weeks, follow-up of 3 months or more after treatment and hot flash score as a primary outcome measure seem appropriate. After all, higher level of description according to global standard must be obtained in the study report and publishing. Conclusion: The researchers should develope the methodology of acupuncture clinical trial on the postmenopausal and perimenopausal hot flashes.

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A machine learning model for the derivation of major molecular descriptor using candidate drug information of diabetes treatment (당뇨병 치료제 후보약물 정보를 이용한 기계 학습 모델과 주요 분자표현자 도출)

  • Namgoong, Youn;Kim, Chang Ouk;Lee, Chang Joon
    • Journal of the Korea Convergence Society
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    • v.10 no.3
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    • pp.23-30
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    • 2019
  • The purpose of this study is to find out the structure of the substance that affects antidiabetic using the candidate drug information for diabetes treatment. A quantitative structure activity relationship model based on machine learning method was constructed and major molecular descriptors were determined for each experimental data variables from coefficient values using a partial least squares algorithm. The results of the analysis of the molecular access system fingerprint data reflecting the candidate drug structure information were higher than those of the in vitro data analysis in terms of goodness-of-fit, and the major molecular expression factors affecting the antidiabetic effect were also variously derived. If the proposed method is applied to the new drug development environment, it is possible to reduce the cost for conducting candidate screening experiment and to shorten the search time for new drug development.

An Index-Building Method for Boundary Matching that Supports Arbitrary Partial Denoising (임의의 부분 노이즈제거를 지원하는 윤곽선 매칭의 색인 구축 방법)

  • Kim, Bum-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.11
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    • pp.1343-1350
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    • 2019
  • Converting boundary images to time-series makes it feasible to perform boundary matching even on a very large image database, which is very important for interactive and fast matching. In recent research, there has been an attempt to perform fast matching considering partial denoising by converting the boundary image into time series. In this paper, to improve performance, we propose an index-building method considering all possible arbitrary denoising parameters for removing arbitrary partial noises. This is a challenging problem since the partial denoising boundary matching must be considered for all possible denoising parameters. We propose an efficient single index-building algorithm by constructing a minimum bounding rectangle(MBR) according to all possible denoising parameters. The results of extensive experiments conducted show that our index-based matching method improves the search performance up to 46.6 ~ 4023.6 times.

Time-aware Collaborative Filtering with User- and Item-based Similarity Integration

  • Lee, Soojung
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.9
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    • pp.149-155
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    • 2022
  • The popularity of e-commerce systems on the Internet is increasing day by day, and the recommendation system, as a core function of these systems, greatly reduces the effort to search for desired products by recommending products that customers may prefer. The collaborative filtering technique is a recommendation algorithm that has been successfully implemented in many commercial systems, but despite its popularity and usefulness in academia, the memory-based implementation has inaccuracies in its reference neighbor. To solve this problem, this study proposes a new time-aware collaborative filtering technique that integrates and utilizes the neighbors of each item and each user, weighting the recent similarity more than the past similarity with them, and reflecting it in the recommendation list decision. Through the experimental evaluation, it was confirmed that the proposed method showed superior performance in terms of prediction accuracy than other existing methods.

The evaluation of Spectral Vegetation Indices for Classification of Nutritional Deficiency in Rice Using Machine Learning Method

  • Jaekyeong Baek;Wan-Gyu Sang;Dongwon Kwon;Sungyul Chanag;Hyeojin Bak;Ho-young Ban;Jung-Il Cho
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2022.10a
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    • pp.88-88
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    • 2022
  • Detection of stress responses in crops is important to diagnose crop growth and evaluate yield. Also, the multi-spectral sensor is effectively known to evaluate stress caused by nutrient and moisture in crops or biological agents such as weeds or diseases. Therefore, in this experiment, multispectral images were taken by an unmanned aerial vehicle(UAV) under field condition. The experiment was conducted in the long-term fertilizer field in the National Institute of Crop Science, and experiment area was divided into different status of NPK(Control, N-deficiency, P-deficiency, K-deficiency, Non-fertilizer). Total 11 vegetation indices were created with RGB and NIR reflectance values using python. Variations in nutrient content in plants affect the amount of light reflected or absorbed for each wavelength band. Therefore, the objective of this experiment was to evaluate vegetation indices derived from multispectral reflectance data as input into machine learning algorithm for the classification of nutritional deficiency in rice. RandomForest model was used as a representative ensemble model, and parameters were adjusted through hyperparameter tuning such as RandomSearchCV. As a result, training accuracy was 0.95 and test accuracy was 0.80, and IPCA, NDRE, and EVI were included in the top three indices for feature importance. Also, precision, recall, and f1-score, which are indicators for evaluating the performance of the classification model, showed a distribution of 0.7-0.9 for each class.

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Development of Simulation Technology Based on 3D Indoor Map for Analyzing Pedestrian Convenience (보행 편의성 분석을 위한 3차원 실내지도 기반의 시뮬레이션 기술 개발)

  • KIM, Byung-Ju;KANG, Byoung-Ju;YOU, So-Young;KWON, Jay-Hyoun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.20 no.3
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    • pp.67-79
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    • 2017
  • Increasing transportation dependence on the metro system has lead to the convenience of passengers becoming as important as the transportation capacity. In this study, a pedestrian simulator has been developed that can quantitatively assess the pedestrian environment in terms of attributes such as speed and distance. The simulator consists of modules designed for 3D indoor map authoring and algorithmic pedestrian modeling. Module functions for 3D indoor map authoring include 3D spatial modeling, network generation, and evaluation of obtained results. The pedestrian modeling algorithm executes functions such as conducting a path search, allocation of users, and evaluation of level of service (LOS). The primary objective behind developing the said functions is to apply and analyze various scenarios repeatedly, such as before and after the improvement of the pedestrian environment, and to integrate the spatial information database with the dynamic information database. Furthermore, to demonstrate the practical applicability of the proposed simulator in the future, a test-bed was constructed for a currently operational metro station and the quantitative index of the proposed improvement effect was calculated by analyzing the walking speed of pedestrians before and after the improvement of the passage. The possibility of database extension for further analysis has also been discussed in this study.