• Title/Summary/Keyword: Mean value model

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Comparison of machine learning algorithms to evaluate strength of concrete with marble powder

  • Sharma, Nitisha;Upadhya, Ankita;Thakur, Mohindra S.;Sihag, Parveen
    • Advances in materials Research
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    • v.11 no.1
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    • pp.75-90
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    • 2022
  • In this paper, functionality of soft computing algorithms such as Group method of data handling (GMDH), Random forest (RF), Random tree (RT), Linear regression (LR), M5P, and artificial neural network (ANN) have been looked out to predict the compressive strength of concrete mixed with marble powder. Assessment of result suggests that, the overall performance of ANN based model gives preferable results over the different applied algorithms for the estimate of compressive strength of concrete. The results of coefficient of correlation were maximum in ANN model (0.9139) accompanied through RT with coefficient of correlation (CC) value 0.8241 and minimum root mean square error (RMSE) value of ANN (4.5611) followed by RT with RMSE (5.4246). Similarly, other evaluating parameters like, Willmott's index and Nash-sutcliffe coefficient value of ANN was 0.9458 and 0.7502 followed by RT model (0.8763 and 0.6628). The end result showed that, for both subsets i.e., training and testing subset, ANN has the potential to estimate the compressive strength of concrete. Also, the results of sensitivity suggest that the water-cement ratio has a massive impact in estimating the compressive strength of concrete with marble powder with ANN based model in evaluation with the different parameters for this data set.

THE DISTANCE BETWEEN THE UPPER CANINE AND THE ORBITAL PLANE IN GNATHOSTATIC MODEL OF KOREANS WITH NORMAL OCCLUSION (한국인 정상교합자의 악태모형위에서의 안와평면과 상악견치 사이의 거리)

  • Lee, Soo-In;Choi, Mok-Kyun;Kim, Kwang-Hyun
    • The korean journal of orthodontics
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    • v.5 no.1
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    • pp.51-56
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    • 1975
  • In orthodontic field, the study on gnathostatic model is very important to the diagnosis and analysis of malocclusion. The purpose of this study is to observe that relation of orbital plane and upper canine in Koreans. We selected 230 cases with normal occlusion, 124 male and 106 female cases aged from 12 years to 25 years, to prepare 230 gnathostatic models, and measured the distance from midpoint of mesio-distal distance of upper canine to orbital plane in gnathostatic model. The results obtained were as follows: 1) The mean value of the distance from upper canine to orbital plane showed no significant change with age. 2) The mean value of the distance from the upper canine to orbital plane was -3.11mm in male and -3.84mm in female. 3) The orbital plane passed through the upper canine in normal occlusion of Koreans.

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Measurement of Joint Aperture Using 3-D Laser Profilometer (3차원 레이저 측정기를 이용한 절리 간극의 측정)

  • 이희석;이연규;이희근
    • Economic and Environmental Geology
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    • v.33 no.4
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    • pp.309-320
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    • 2000
  • Aperture is an important parameter for determining the hydraulic characteristics of fractured media. In this study the topography of artificial rock joint surface was measured using 3D laser profilometer to analyze the aperture distribution. The initial aperture distribution was determined when the contact area became one percent of total joint surface. The initial aperture distribution of granite joint, with the mean value of 0.78 mm and the standard deviation of 0.34 mm was much different from that of the marble joint, with the mean value of 0.57 mm and the standard deviation of 0.26 mm. Apertures of both granite and marble showed normal distributions. Aperture distribution with the contact area of 25% was also analyzed. Mean value was decreased to one third compared to the initial aperture, but the standard deviation was decreased slightly. To determine the spatial correlation of the aperture distribution variogram analysis was carried out on the initial aperture data. Most experimental variograms were fitted well with exponential model. It is expected that the measured aperture characteristics can be used for stochastic analysis of fluid flow through rock joints.

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Development of Real-Time Simulator for a Heavy Duty Diesel Engine (건설기계 디젤엔진용 실시간 시뮬레이터 개발)

  • Noh, Young Chang;Park, Kyung Min;Oh, Byoung Gul;Ko, Min Seok;Kim, Nag In
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.39 no.2
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    • pp.203-209
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    • 2015
  • Recently, the portion of electronic control in an engine system has been increasing with the aim of meeting the requirements of emissions and fuel efficiency of the engine system in the construction machinery industry. Correspondingly, the complexity of the engine management system (EMS) has increased. This study developed an engine HiLS system for reducing the cost and time required for function development for the EMS. The engine model for HiLS is composed of air, fuel, torque, and dynamometer models. Further, the mean value method is applied to the developed HiLS engine model. This model is validated by its application to a heavy-duty diesel engine equipped with an exhaust gas recirculation system and a turbocharger. Test results demonstrate that the model has accuracy greater than 90 and also verify the feasibility of the virtual calibration process.

Development of a new explicit soft computing model to predict the blast-induced ground vibration

  • Alzabeebee, Saif;Jamei, Mehdi;Hasanipanah, Mahdi;Amnieh, Hassan Bakhshandeh;Karbasi, Masoud;Keawsawasvong, Suraparb
    • Geomechanics and Engineering
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    • v.30 no.6
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    • pp.551-564
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    • 2022
  • Fragmenting the rock mass is considered as the most important work in open-pit mines. Ground vibration is the most hazardous issue of blasting which can cause critical damage to the surrounding structures. This paper focuses on developing an explicit model to predict the ground vibration through an multi objective evolutionary polynomial regression (MOGA-EPR). To this end, a database including 79 sets of data related to a quarry site in Malaysia were used. In addition, a gene expression programming (GEP) model and several empirical equations were employed to predict ground vibration, and their performances were then compared with the MOGA-EPR model using the mean absolute error (MAE), root mean square error (RMSE), mean (𝜇), standard deviation of the mean (𝜎), coefficient of determination (R2) and a20-index. Comparing the results, it was found that the MOGA-EPR model predicted the ground vibration more precisely than the GEP model and the empirical equations, where the MOGA-EPR scored lower MAE and RMSE, 𝜇 and 𝜎 closer to the optimum value, and higher R2 and a20-index. Accordingly, the proposed MOGA-EPR model can be introduced as a useful method to predict ground vibration and has the capacity to be generalized to predict other blasting effects.

A Maintenance Model Applying Loss Function Based on the Cpm+ in the Process Mean Shift Problem in Which the Production Volume Decreases (생산량이 감소하는 공정평균이동 문제에서 Cpm+ 기준의 손실함수를 적용한 보전모형)

  • Lee, Do-Kyung
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.44 no.1
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    • pp.45-50
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    • 2021
  • Machines and facilities are physically or chemically degenerated by continuous usage. The representative type of the degeneration is the wearing of tools, which results in the process mean shift. According to the increasing wear level, non-conforming products cost and quality loss cost are increasing simultaneously. Therefore, a preventive maintenance is necessary at some point. The problem of determining the maintenance period (or wear limit) which minimizes the total cost is called the 'process mean shift problem'. The total cost includes three items: maintenance cost (or adjustment cost), non-conforming cost due to the non-conforming products, and quality loss cost due to the difference between the process target value and the product characteristic value among the conforming products. In this study, we set the production volume as a decreasing function rather than a constant. Also we treat the process variance as a function to the increasing wear rather than a constant. To the quality loss function, we adopted the Cpm+, which is the left and right asymmetric process capability index based on the process target value. These can more reflect the production site. In this study, we presented a more extensive maintenance model compared to previous studies, by integrating the items mentioned above. The objective equation of this model is the total cost per unit wear. The determining variables are the wear limit and the initial process setting position that minimize the objective equation.

Adaptive Shot Change Detection using Mean of Feature Value on Variable Reference Blocks and Implementation on PMP

  • Kim, Jong-Nam;Kim, Won-Hee
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.229-232
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    • 2009
  • Shot change detection is an important technique for effective management of video data, so detection scheme requires adaptive detection techniques to be used actually in various video. In this paper, we propose an adaptive shot change detection algorithm using the mean of feature value on variable reference blocks. Our algorithm determines shot change detection by defining adaptive threshold values with the feature value extracted from video frames and comparing the feature value and the threshold value. We obtained better detection ratio than the conventional methods maximally by 15% in the experiment with the same test sequence. We also had good detection ratio for other several methods of feature extraction and could see real-time operation of shot change detection in the hardware platform with low performance was possible by implementing it in TVUS model of HOMECAST Company. Thus, our algorithm in the paper can be useful in PMP or other portable players.

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Target Modeling with Color Arrangement for Region-Based Object Tracking (영역 기반 물체 추적에서 색상 배치를 고려한 표적 모델링)

  • Kim, Dae-Hwan;Lee, Seung-Jun;Ko, Sung-Jea
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.1
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    • pp.1-10
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    • 2012
  • In this paper, we propose a new class of color histogram model suitable for object tracking. In addition to the pixel count, each bin of the proposed model also contains the spatial mean and the average value of the pixels located at a certain distance from the mean location of the bin. Using the proposed color histogram model, we derive a mean shift procedure using the modified Bhattacharyya distance. Unlike most mean shift based methods, our algorithm performs well even when the object being tracked shares similar colors with the background. Experimental results demonstrate improved tracking performance over existing methods.

Image Dehazing Enhancement Algorithm Based on Mean Guided Filtering

  • Weimin Zhou
    • Journal of Information Processing Systems
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    • v.19 no.4
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    • pp.417-426
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    • 2023
  • To improve the effect of image restoration and solve the image detail loss, an image dehazing enhancement algorithm based on mean guided filtering is proposed. The superpixel calculation method is used to pre-segment the original foggy image to obtain different sub-regions. The Ncut algorithm is used to segment the original image, and it outputs the segmented image until there is no more region merging in the image. By means of the mean-guided filtering method, the minimum value is selected as the value of the current pixel point in the local small block of the dark image, and the dark primary color image is obtained, and its transmittance is calculated to obtain the image edge detection result. According to the prior law of dark channel, a classic image dehazing enhancement model is established, and the model is combined with a median filter with low computational complexity to denoise the image in real time and maintain the jump of the mutation area to achieve image dehazing enhancement. The experimental results show that the image dehazing and enhancement effect of the proposed algorithm has obvious advantages, can retain a large amount of image detail information, and the values of information entropy, peak signal-to-noise ratio, and structural similarity are high. The research innovatively combines a variety of methods to achieve image dehazing and improve the quality effect. Through segmentation, filtering, denoising and other operations, the image quality is effectively improved, which provides an important reference for the improvement of image processing technology.

A Study on a Comparison of Sky View Factors and a Correlation with Air Temperature in the City (하늘시계지수 비교 및 도시기온 상관성 연구: 강남 선정릉지역을 중심으로)

  • Yi, Chaeyeon;Shin, Yire;An, Seung Man
    • Atmosphere
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    • v.27 no.4
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    • pp.483-498
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    • 2017
  • Sky view factor can quantify the influence of complex obstructions. This study aims to evaluate the best available SVF method that represents an urban thermal condition with land cover in complex city of Korea and also to quantify a correlation between SVF and mean air temperature; the results are as follows. First, three SVF methods comparison result shows that urban thermal study should consider forest canopy induced effects because the forest canopy test (on/off) on SVF reveals significant difference range (0.8, between maximum value and minimum value) in comparison with the range (0.1~0.3) of SVFs (Fisheye, SOLWEIG and 3DPC) difference. The significance is bigger as a forest cover proportion become larger. Second, R-square between SVF methods and urban local mean air temperature seems more reliable at night than a day. And as the value of SVF increased, it showed a positive slope in summer day and a negative slope in winter night. In the SVF calculation method, Fisheye SVF, which is the observed value, is close to the 3DPC SVF, but the grid-based SWG SVF is higher in correlation with the temperature. However, both urban climate monitoring and model/analysis study need more development because of the different between SVF and mean air temperature correlation results in the summer night period, which imply other major factors such as cooling air by the forest canopy, warming air by anthropogenic heat emitted from fuel oil combustion and so forth.