• Title/Summary/Keyword: analysis of algorithms

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Application and development of a machine learning based model for identification of apartment building types - Analysis of apartment site characteristics based on main building shape - (머신러닝 기반 아파트 주동형상 자동 판별 모형 개발 및 적용 - 주동형상에 따른 아파트 개발 특성분석을 중심으로 -)

  • Sanguk HAN;Jungseok SEO;Sri Utami Purwaningati;Sri Utami Purwaningati;Jeongseob KIM
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.2
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    • pp.55-67
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    • 2023
  • This study aims to develop a model that can automatically identify the rooftop shape of apartment buildings using GIS and machine learning algorithms, and apply it to analyze the relationship between rooftop shape and characteristics of apartment complexes. A database of rooftop data for each building in an apartment complex was constructed using geospatial data, and individual buildings within each complex were classified into flat type, tower type, and mixed types using the random forest algorithm. In addition, the relationship between the proportion of rooftop shapes, development density, height, and other characteristics of apartment complexes was analyzed to propose the potential application of geospatial information in the real estate field. This study is expected to serve as a basic research on AI-based building type classification and to be utilized in various spatial and real estate analyses.

Analysis of the Impact of Surface Reflectance Error Retrieved from 6SV for KOMPSAT-3A according to MODIS AOD Expected Error (MODIS AOD 기대 오차에 따른 6SV 기반 KOMPSAT-3A 채널별 지표반사도 오차 영향 분석)

  • Daeseong Jung;Suyoung Sim;Jongho Woo;Nayeon Kim;Sungwoo Park;Honghee Kim;Kyung-Soo Han
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1517-1522
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    • 2023
  • This study evaluates the impact of Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) expected error (EE) on the accuracy of surface reflectance (SR) derived from the KOMPSAT-3A satellite, utilizing the Second Simulation of the Satellite Signal in the Solar Spectrum Vector radiative transfer model. By considering a range of ground-based AOD and the resultant MODIS AOD EE, the research identifies significant influences on SR accuracy, particularly under high solar zenith angles(SZA) and shorter wavelengths. The study's simulations reveal that SR errors increase with shorter wavelengths and higher SZAs, highlighting the necessity for further research to improve atmospheric correction algorithms by incorporating wavelength and SZA considerations. Additionally, the study provides foundational data for better understanding the use of AOD data from other satellites in atmospheric correction processes and contributes to advancing atmospheric correction technologies.

A Tunable Transmitter - Tunable Receiver Algorithm for Accessing the Multichannel Slotted-Ring WDM Metropolitan Network under Self-Similar Traffic

  • Sombatsakulkit, Ekanun;Sa-Ngiamsak, Wisitsak;Sittichevapak, Suvepol
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.777-781
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    • 2004
  • This paper presents an algorithm for multichannel slotted-ring topology medium access protocol (MAC) using in wavelength division multiplexing (WDM) networks. In multichannel ring, there are two main previously proposed architectures: Tunable Transmitter - Fixed Receiver (TTFR) and Fixed Transmitter - Tunable Receivers (FTTR). With TTFR, nodes can only receive packets on a fixed wavelength and can send packets on any wavelengths related to destination of packets. Disadvantage of this architecture is required as many wavelengths as there are nodes in the network. This is clearly a scalability limitation. In contrast, FTTR architecture has advantage that the number of nodes can be much larger than the number of wavelength. Source nodes send packet on a fixed channel (or wavelength) and destination nodes can received packets on any wavelength. If there are fewer wavelengths than there are nodes in the network, the nodes will also have to share all the wavelengths available for transmission. However the fixed wavelength approach of TTFR and FTTR bring low network utilization. Because source node with waiting data have to wait for an incoming empty slot on corresponding wavelength. Therefore this paper presents Tunable Transmitter - Tunable Receiver (TTTR) approach, in which the transmitting node can send a packet over any wavelengths and the receiving node can receive a packet from any wavelengths. Moreover, the self-similar distributed input traffic is used for evaluation of the performance of the proposed algorithm. The self-similar traffic performs better performance over long duration than short duration of the Poison distribution. In order to increase bandwidth efficiency, the Destination Stripping approach is used to mark the slot which has already reached the desired destination as an empty slot immediately at the destination node, so the slot does not need to go back to the source node to be marked as an empty slot as in the Source Stripping approach. MATLAB simulator is used to evaluate performance of FTTR, TTFR, and TTTR over 4 and 16 nodes ring network. From the simulation result, it is clear that the proposed algorithm overcomes higher network utilization and average throughput per node, and reduces the average queuing delay. With future works, mathematical analysis of those algorithms will be the main research topic.

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An Analysis of the Factors Affecting User Satisfaction in Computational Science and Engineering Platforms: A Case Study of EDISON (계산과학공학플랫폼 품질 특성이 사용자 만족도에 영향을 미치는 요인에 관한 연구)

  • On, Noori;Kim, Nam-Gyu;Ru, Kimyoung;Jang, Hanbichnale;Lee, Jongsuk Ruth
    • Journal of Internet Computing and Services
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    • v.20 no.6
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    • pp.85-93
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    • 2019
  • Computational Science and Engineering is a convergence study that understands and solves complex problems such as science, engineering, and social phenomena through modeling using computing resources. Computational science and engineering combines algorithms, computational and informatics, and infrastructure. The importance of computational science is increasing with the improvement of computer performance and the development of large data processing technology. In Korea, Korea Institute of Science and Technology Information (KISTI) has been developing national computational science engineering software and utilization technology by combining basic science and computing technology through EDISON project. The EDISON project builds an open EDISON platform and integrates and services information systems in seven areas of computational science and engineering (computational thermal fluids, nanophysics, computational chemistry, structural dynamics, computational design, and computational medicine). Using this, we have established a web-based curriculum to lay the groundwork for fostering scientific talent and commercializing computational science and engineering software. The purpose of this study is to derive the quality characteristic factors of computational science platform and to empirically examine the effect on user satisfaction. This paper examines how the quality characteristics of information systems, the computational science engineering platform, affect the user satisfaction by modifying the research questions according to the propensity of the computational science platform by referring to the success factors of DeLone and McLean's information system. Based on the results of this study, we will suggest strategic implications for platform improvement by searching the priority of quality characteristics of computational science platform.

Design of Classifier for Sorting of Black Plastics by Type Using Intelligent Algorithm (지능형 알고리즘을 이용한 재질별 검정색 플라스틱 분류기 설계)

  • Park, Sang Beom;Roh, Seok Beom;Oh, Sung Kwun;Park, Eun Kyu;Choi, Woo Zin
    • Resources Recycling
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    • v.26 no.2
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    • pp.46-55
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    • 2017
  • In this study, the design methodology of Radial Basis Function Neural Networks is developed with the aid of Laser Induced Breakdown Spectroscopy and also applied to the practical plastics sorting system. To identify black plastics such as ABS, PP, and PS, RBFNNs classifier as a kind of intelligent algorithms is designed. The dimensionality of the obtained input variables are reduced by using PCA and divided into several groups by using K-means clustering which is a kind of clustering techniques. The entire data is split into training data and test data according to the ratio of 4:1. The 5-fold cross validation method is used to evaluate the performance as well as reliability of the proposed classifier. In case of input variables and clusters equal to 5 respectively, the classification performance of the proposed classifier is obtained as 96.78%. Also, the proposed classifier showed superiority in the viewpoint of classification performance where compared to other classifiers.

A Comparative Analysis of 3D Circle Fitting Algorithms for Determination of VLBI Antenna Reference Point (VLBI 안테나 기준점 결정을 위한 3D Circle Fitting 알고리즘의 비교 분석)

  • Hyuk Gil, Kim;Jin Sang, Hwang;Hong Sik, Yun;Tae Jun, Jeong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.4
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    • pp.231-244
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    • 2015
  • The accuracy of reference point of VLBI antenna is mandatory to perform collocation of different space geodetic techniques. In this study, we evaluated the optimal methods for the 3D circle fitting to enhance the accuracy of the reference point of VLBI antenna. Two kinds of methodologies for the orthonormal coordinate system with translation of planar observation point and the unitary coordinate transforamation were suggested and their fitting accuracies were evaluated where the orthogonal distance was calculated by residual between observation point and fitting model and the recursive calculation was performed to improve the accuracy of 3D circle fitting. Finally, we found that the methodology for the unitary coordinate transformation is highly appropriate to determine the optimal equation for azimuth-axis and elevation-axis of VLBI antenna. Therefore, the reference point of VLBI antenna with high accuracy can be determined by the intersection of the above two axises (azimuth-axis and elevation-axis). This result is expected to be utilized for a variety of researches for connection between VLBI observation results and the national control point.

A Study on Factors Influencing the Severity of Autonomous Vehicle Accidents: Combining Accident Data and Transportation Infrastructure Information (자율주행차 사고심각도의 영향요인 분석에 관한 연구: 사고데이터와 교통인프라 정보를 결합하여)

  • Changhun Kim;Junghwa Kim
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.5
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    • pp.200-215
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    • 2023
  • With the rapid advance of autonomous driving technology, the related vehicle market is experiencing explosive growth, and it is anticipated that the era of fully autonomous vehicles will arrive in the near future. However, along with the development of autonomous driving technology, questions regarding its safety and reliability continue to be raised. Concerns among technology adopters are increasing due to media reports of accidents involving autonomous vehicles. To promote the improvement of the safety of autonomous vehicles, it is essential to analyze previous accident cases and identify their causes. Therefore, in this study, we aimed to analyze the factors influencing the severity of autonomous vehicle accidents using previous accident cases and related data. The data used for this research primarily comprised autonomous vehicle accident reports collected and distributed by the California Department of Motor Vehicles (CA DMV). Spatial information on accident locations and additional traffic data were also collected and utilized. Given that the primary data used in this study were accident reports, a Poisson regression analysis was conducted to model the expected number of accidents. The research results indicated that the severity of autonomous vehicle accidents increases in areas with low lighting, the presence of bicycle or bus-exclusive lanes, and a history of pedestrian and bicycle accidents. These findings are expected to serve as foundational data for the development of algorithms to enhance the safety of autonomous vehicles and promote the installation of related transportation infrastructure.

Analysis on the Contribution of FDOA Measurement Accuracy to the Performance of Combined TDOA/FDOA Localization Systems (TDOA/FDOA 복합 위치추정 시스템에서 FDOA 측정 정확도에 따른 추정 성능 기여도 분석)

  • Kim, Dong-Gyu;Kim, Yong-Hee;Han, Jin-Woo;Song, Kyu-Ha;Kim, Hyoung-Nam
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.5
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    • pp.88-96
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    • 2014
  • In modern electronic warfare systems, the necessity of a more accurate estimation method based on non-AOA (arrival of angle) measurement, such as TDOA and FDOA, have been increased. The previous researches using single TDOA have been carried out in terms of not only the development of emitter location algorithms but also the enhancement of measurement accuracy. Recently, however, the combined TDOA/FDOA method is of considerable interest because it is able to estimate the velocity vector of a moving emitter and acquire a pair of TDOA and FDOA measurements from a single sensor pair. In this circumstance, it is needed to derive the required FDOA measurement accuracy in order that the TDOA/FDOA combined localization system outperforms the previous single TDOA localization systems. Therefore, we analyze the contribution of FDOA measurement accuracy to emitter location, then propose the criterion based on CRLB (Cramer-Rao lower bound). Simulations are included to examine the validity of the proposed criterion by using the Gauss-Newton algorithm.

Evaluation of hydrological applicability for rainfall estimation algorithms of dual-polarization radar (이중편파 레이더의 강우 추정 알고리즘별 수문학적 적용성 평가)

  • Lee, Myungjin;Lee, Choongke;Yoo, Younghoon;Kwak, Jaewon;Kim, Hung Soo
    • Journal of Korea Water Resources Association
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    • v.54 no.1
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    • pp.27-38
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    • 2021
  • Recently, many studies have been conducted to use the radar rainfall in hydrology. However, in the case of weather radar, the beam is blocked due to the limitation of the observation such as mountain effect, which causes underestimation of the radar rainfall. In this study, the radar rainfall was estimated using the Hybrid Sacn Reflectivity (HSR) technique for hydrological use of weather radar and the runoff analysis was performed using the GRM model which is a distributed rainfall-runoff model. As a result of performing the radar rainfall correction and runoff simulation for 5 rainfall events, the accuracy of the dual-polarization radar rainfall using the HSR technique (Q_H_KDP) was the highest with an error within 15% of the ground rainfall. In addition, the result of runoff simulation using Q_H_KDP also showed an accuracy of R2 of 0.9 or more, NRMSE of 1.5 or less and NSE of 0.5 or more. From this study, we examined the application of the dual-polarization radar and this results can be useful for studies related to the hydrological application of dual-polarization radar rainfall in the future.

Assessment of Heavy Metal Exposure Levels (Pb, Hg, Cd) among South Koreans and Contribution Rates by Exposure Route - Korean National Environmental Health Survey (KoNEHS) Cycle 4 (2018~2020) - (한국인의 체내 중금속(납, 수은, 카드뮴)의 노출수준 및 노출경로별 기여율 평가 - 제4기 국민환경보건 기초조사(2018~2020) -)

  • Gihong Min;Jihun Shin;Dongjun Kim;Jaemin Woo;Kyeonghwa Sung;Mansu Cho;Wonho Yang
    • Journal of Environmental Health Sciences
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    • v.49 no.5
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    • pp.262-274
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    • 2023
  • Background: Exposure levels for heavy metals such as lead (Pb), mercury (Hg), and cadmium (Cd) have increased due to human activities. They are known to be a public health concern. Objectives: This study aimed to determine the exposure levels to heavy metals in the blood and urine of South Korean adults and to present the contribution rate of exposure pathways using an exposure algorithm for men aged 19~64, women aged 19~64, and all seniors aged 65 or older. Methods: We analyzed data from the Korean National Environmental Health Survey (KoNEHS) Cycle 4 (2018~2020). A total of 2,646 participants aged ≥19 years were included. Multiple regression analysis was performed to determine the factors affecting heavy metal concentrations. The contribution rate was calculated by applying three exposure algorithms for ingestion, inhalation, and dermal exposure. Results: Factors that commonly affect heavy metal concentrations in blood and urine were gender and age. The main influencing factors for Pb and Cd were education level and smoking status, while frequency of fish consumption and of alcohol consumption were indicated to be the main influencing factors for mercury. The contribution rates of lead and cadmium from food ingestion were 78.03~79.62% and 88.39~92.89%, respectively. Additionally, the highest contribution for mercury was accounted for by food at 81.69~85.77%. As a result of the risk assessment, cadmium was found to pose a potential health risk a with total cancer risk (TCR) of more than 1×10-6. Conclusions: The KoNEHS could be an important study for determining the level of exposure to heavy metals and their influencing factors. Integrated exposure to heavy metals could assess the main exposure pathways, and this methodology could be applied to exposure management of heavy metals.