• Title/Summary/Keyword: average case error

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A Conical Indentation Technique Based on FEA Solutions for Property Evaluation (유한요소해에 기초한 원뿔형 압입 물성평가법)

  • Hyun, Hong-Chul;Kim, Min-Soo;Lee, Jin-Haeng;Lee, Hyung-Yil
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.33 no.9
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    • pp.859-869
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    • 2009
  • The sharp indenters such as Berkovich and conical indenters have a geometrical self-similarity in theory, but different materials have the same load-depth curve in case of single indentation. In this study, we analyze the load-depth curves of conical indenter with angles of indenter via finite element method. From FE analyses of dual-conical indentation test, we investigate the relationships between indentation parameters and load-deflection curves. With numerical regressions of obtained data, we finally propose indentation formulae for material properties evaluation. The proposed approach provides stress-strain curve and the values of elastic modulus, yield strength and strain-hardening exponent with an average error of less than 2%. It is also discussed that the method is valid for any elastically deforming indenters made of tungsten carbide and diamond for instance. The proposed indentation approach provides a substantial enhancement in accuracy compared with the prior methods.

Coin Calculation System Using Binarization and Hue Histogram (이진화와 색상 히스토그램을 이용한 동전 계산 시스템)

  • Bae, Jong-Wook;Jung, Sung-Hwan
    • KIISE Transactions on Computing Practices
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    • v.21 no.6
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    • pp.424-429
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    • 2015
  • This research proposes a new system for calculating the total amount of coins in an image. The proposed system identified and classified the coins in the image in realtime. The image was obtained using a USB camera. Most previous coin calculation systems only used size information. If the size of an object was incorrectly detected, it caused a misclassification. Especially, in case of the former 10 won, it had high error rate because it was similar in size to the 50 won and 100 won coin. The proposed system combines hue histogram information with size information to reduce errors in the classification process. When we only used size information in the classification experiment of 2,290 coins, the recognition rate was on average about 88.2%. When we combined hue information with size information the recognition rate increased to about 99.3%.

A Novel OFDM Integer Frequency Offset Estimation Scheme Using Differential Combining (차동 결합을 이용한 새로운 OFDM 정수 주차수 옵셋 추정 기법)

  • Ahn, Sang-Ho;Chong, Da-Hae;Han, Tae-Hee;Kim, Sang-Hyo;Yoon, Seok-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.8C
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    • pp.627-632
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    • 2008
  • The timing offset is one of the main error sources in estimating the frequency offset in orthogonal frequency division multiplexing (OFDM) systems. Although some works have been done to mitigate the influence of the timing offset on the frequency offset estimation, most of the investigations require the knowledge of the timing offset range, which is not generally available in practical systems. In this paper, we propose a new frequency offset estimation scheme using differential combining between two successive correlation samples, which does not require the knowledge of the timing offset range, and thus, is robust to the timing offset variation. The simulation results show that the proposed scheme is not only robust to the timing offset variation, but also generally performs better than the conventional scheme on the average, in the case of the timing offset range being not known exactly.

Design and Evaluation of Neighbor-aware AODV Routing Protocol in Mobile Ad-hoc Network (이동 애드혹 네트워크에서 이웃노드 정보를 이용한 AODV 라우팅 프로토콜의 설계 및 평가)

  • Kim, Cheol-Joong;Park, Seok-Cheon
    • The KIPS Transactions:PartC
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    • v.15C no.3
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    • pp.213-220
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    • 2008
  • A MANET is an autonomous, infrastructureless system that consists of mobile nodes. In MANET, on-demand routing protocols are usually used because network topology changes frequently. The current approach in case of broken routes is to flag an error and re-initiate route discovery either at the source or at the intermediate node. Repairing these broken links is a costly affair in terms of routing overhead and delay involved. Therefore, this paper propose a NAODV(Neighbor-aware AODV) protocol that stands on the basis of an AODV. It sets up the route rapidly if it operates for setting the route directly by using sequence number of neighbor nodes without re-search the route when the route to destination node is broken. Also, it reduces loss of packets. We use NS-2 for the computer simulation and validate that the proposed scheme is better than general AODV in terms of packet delivery ratio and average end-to-end delay. Also, when the proposed protocol is applied to the large ad-hoc network with multiple nodes, the performance is more efficient.

An Improved Face Detection Method Using a Hybrid of Hausdorff and LBP Distance (Hausdorff와 LBP 거리의 융합을 이용한 개선된 얼굴검출)

  • Park, Seong-Chun;Koo, Ja-Young
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.11
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    • pp.67-73
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    • 2010
  • In this paper, a new face detection method that is more accurate than the conventional methods is proposed. This method utilizes a hybrid of Hausdorff distance based on the geometric similarity between the two sets of points and the LBP distance based on the distribution of local micro texture of an image. The parameters for normalization and the optimal blending factor of the two different metrics were calculated from training sample images. Popularly used face database was used to show that the proposed method is more effective and robust to the variation of the pose, illumination, and back ground than the methods based on the Hausdorff distance or LBP distance. In the particular case, the average error distance between the detected and the true face location was reduced to 47.9% of the result of LBP method, and 22.8% of the result of Hausdorff method.

Estimation of the Forest Stand Volumes from Forest Inventory Data Based on Synthetic Estimation Method: A Case of the Economic Forest in Gangwon-do, Republic of Korea

  • Seo, Hwan seok;Park, Jeong mook;Lee, Jung soo
    • Journal of Forest and Environmental Science
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    • v.32 no.2
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    • pp.140-148
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    • 2016
  • This study aims to estimate the forest volumes of the economic forest in Gangwon Province of Republic of Korea (hereinafter referred to as Gangwon) through the synthetic estimation. To estimate the forest volume, Stratified systematic sampling method was used along with the forest type maps and the $5^{th}$ National Forest Inventory data. The synthetic estimation includes sample plots of the expanded areas as well as those of the target area, and the forest volume of economic forest in every city and county throughout Gangwon. Results show that the average forest volume calculated by synthetic estimation was $159.6m^3/ha$ in national economic forest and $129.6m^3/ha$ in private economic forest. The total forest volume of the national economic forest was approximately $59.45million\;m^3$, which was $20.18million\;m^3$ higher than that of the private economic forest. On the other hands, the standard error of the national economic forest was approximately ${\pm}2.21m^3/ha$, which was ${\pm}0.30m^3/ha$ lower than that of the private economic forest. The lowest standard errors was about ${\pm}3.12 m^3/ha$ in broad-leaved forest, followed by ${\pm}4.33m^3/ha$ of mixed forest, and ${\pm}5.78m^3/ha$ of coniferous forest.

Missing Data Imputation Using Permanent Traffic Counts on National Highways (일반국토 상시 교통량자료를 이용한 교통량 결측자료 추정)

  • Ha, Jeong-A;Park, Jae-Hwa;Kim, Seong-Hyeon
    • Journal of Korean Society of Transportation
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    • v.25 no.1 s.94
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    • pp.121-132
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    • 2007
  • Up to now Permanent traffic volumes have been counted by Automatic Vehicle Classification (AVC) on National Highways. When counted data have missing items or errors, the data must be revised to stay statistically reliable This study was carried out to estimate correct data based on outoregression and seasonal AutoRegressive Integrated Moving Average (ARIMA). As a result of verification through seasonal ARIMA, the longer the missed period is, the greater the error. Autoregression results in better verification results than seasonal ARIMA. Traffic data is affected by the present state mote than past patterns. However. autoregression can be applied only to the cases where data include similar neighborhood patterns and even in this case. the data cannot be corrected when data are missing due to low qualify or errors Therefore, these data shoo)d be corrected using past patterns and seasonal ARIMA when the missing data occurs in short periods.

Comparison Study of Rainfall Data Using RDAPS Model and Observed Rainfall Data (RDAPS 모델의 강수량과 실측강수량의 비교를 통한 적용성 검토)

  • Jeong, Chang-Sam;Shin, Ju-Young;Jung, Young-Hun;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.44 no.3
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    • pp.221-230
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    • 2011
  • The climate change has been observed in Korea as well as in the entire world recently. The rainstorm has been gradually increased and then the damage has been grown. It is getting important to predict short-term rainfall. The Korea Meteorological Administration (KMA) generates numerical model outputs which are computed by Global Data Assimilation and Prediction System (GDAPS) and Regional Data Assimilation and Prediction System (RDAPS). The KMA predicts rainfall using RDAPS results. RDAPS model generates 48 hours data which is organized 3 hours data accumulated at 00UTC and 12UTC. RDAPS results which are organized 3 hours time scale are converted into daily rainfall to compare observed daily rainfall. In this study, 9 cases are applied to convert RDAPS results to daily rainfall data. The MAP (mean areal precipitation) in Geum river basin are computed by using KMA which are 2005 are used. Finally, the best case which gives the close value to the observed rainfall data is obtained using the average absolute relative error (AARE) especially for the Geum River basin.

Temperature Compensation and Characteristics of Non-dispersive Infrared Alcohol Sensor According to the Intensity of Light (입사광량의 조절과 이에 따른 비분산 적외선 알코올 센서의 온도 특성과 보정)

  • Kim, JinHo;Cho, HeeChan;Yi, SeungHwan
    • Journal of Sensor Science and Technology
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    • v.27 no.1
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    • pp.47-54
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    • 2018
  • In this paper, we describe the thermal characteristics of the output voltages of ethanol gas sensor according to the amount of radiation incident on the infrared sensors located at each focal point of two elliptical waveguides. In order to verify the output characteristics of the gas sensor according to the amount of incident light on the infrared sensor, two combinations of sensor modules were fabricated. Hydrophobic thin film is deposited on one of the reflectors of sensor modules and one of the two infrared sensors was equipped with a hollow disk (10 Ø), and the temperature characteristics of the infrared sensor equipped with the hollow disk (10 Ø) and the infrared sensor without the disk were tested. The temperature was varied from 253 K to 333 K at 10 K intervals based on 298 K. The properties of ethanol gas sensor have been identified with respect to varying temperature for a range of ethanol concentration from 0 ppm to 500 ppm. In the case of an infrared sensor equipped with a hollow disk (10 Ø), the output voltage of the sensor decreased by 0.8 mV and 1 mV, respectively, as the temperature increased. Conversely, the output voltage of the diskless infrared sensor showed an average increase of 67 mV and 57 mV as the temperature increased. The ethanol concentrations estimated on the basis of results show an error of more than 10 % for less than 100 ppm concentration. However, if the ethanol concentration exceeds 100 ppm, the gas concentration can be estimated within the range of ${\pm}10%$.

An Evaluation of Uncertainty for Reference Standards Solar Radiation Data (참조표준 일사량 데이터에 대한 불확도 평가)

  • Kim, Sang-Yeob;Jo, Dok-Ki;Yun, Chang-Yeol;Kim, Kwang-Deuk
    • Journal of the Korean Solar Energy Society
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    • v.31 no.1
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    • pp.51-58
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    • 2011
  • The energy makes the basic element which improves the quality of life with motive power of industry and life. However, using the fossil fuel resources was restricted through it's abuse and exhaustion, and that cause a global warming resultingly. According to the reason, the world increased the interest that are stability and use of new and renewable energy which is clean energy with environment. Therefore, the property data of new and renewable is needed for developing and supplying the energy. In other words, the data of new and renewable energy becomes the standards for supply and evaluation of new and renewable energy with development of industry and technology. Also, the necessity came to the fore as the reference and standards of new and renewable energy data. Therefore, in this study, we evaluate and collect the solar radiation data as the new and renewable data and process the collected data through the standards for valuation. We evaluate uncertainty with standards which are NREL, WMO, and GUM. Whereby the data becomes reference standards data and gains the credibility. For the reliability data, we correct the measuring instrument with correction period. Using the DQMS and SERI QC, we efficiently manage and evaluate the solar radiation data. As a result, we evaluate uncertainty as 1,120 case about 16 area. we achieve credibility of data from evaluated solar radiation data and provide an accurate information to user. The annual average of horizontal radiation presents between 1,484 and 4,577, then the uncertainty evaluates from 163 to 453. The error of uncertainty presents smaller than the measurement values. So, we judge a credibility of data by expression of reliability quantitatively. In additional, the reference standards data which is possible to approach anywhere will be used for the supporting related industry and policy making.