• Title/Summary/Keyword: statistical grading

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Examination of Aggregate Quality Using Image Processing Based on Deep-Learning (딥러닝 기반 영상처리를 이용한 골재 품질 검사)

  • Kim, Seong Kyu;Choi, Woo Bin;Lee, Jong Se;Lee, Won Gok;Choi, Gun Oh;Bae, You Suk
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.6
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    • pp.255-266
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    • 2022
  • The quality control of coarse aggregate among aggregates, which are the main ingredients of concrete, is currently carried out by SPC(Statistical Process Control) method through sampling. We construct a smart factory for manufacturing innovation by changing the quality control of coarse aggregates to inspect the coarse aggregates based on this image by acquired images through the camera instead of the current sieve analysis. First, obtained images were preprocessed, and HED(Hollistically-nested Edge Detection) which is the filter learned by deep learning segment each object. After analyzing each aggregate by image processing the segmentation result, fineness modulus and the aggregate shape rate are determined by analyzing result. The quality of aggregate obtained through the video was examined by calculate fineness modulus and aggregate shape rate and the accuracy of the algorithm was more than 90% accurate compared to that of aggregates through the sieve analysis. Furthermore, the aggregate shape rate could not be examined by conventional methods, but the content of this paper also allowed the measurement of the aggregate shape rate. For the aggregate shape rate, it was verified with the length of models, which showed a difference of ±4.5%. In the case of measuring the length of the aggregate, the algorithm result and actual length of the aggregate showed a ±6% difference. Analyzing the actual three-dimensional data in a two-dimensional video made a difference from the actual data, which requires further research.

Comparison of Monoexponential, Biexponential, Stretched-Exponential, and Kurtosis Models of Diffusion-Weighted Imaging in Differentiation of Renal Solid Masses

  • Jianjian Zhang;Shiteng Suo;Guiqin Liu;Shan Zhang;Zizhou Zhao;Jianrong Xu;Guangyu Wu
    • Korean Journal of Radiology
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    • v.20 no.5
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    • pp.791-800
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    • 2019
  • Objective: To compare various models of diffusion-weighted imaging including monoexponential apparent diffusion coefficient (ADC), biexponential (fast diffusion coefficient [Df], slow diffusion coefficient [Ds], and fraction of fast diffusion), stretched-exponential (distributed diffusion coefficient and anomalous exponent term [α]), and kurtosis (mean diffusivity and mean kurtosis [MK]) models in the differentiation of renal solid masses. Materials and Methods: A total of 81 patients (56 men and 25 women; mean age, 57 years; age range, 30-69 years) with 18 benign and 63 malignant lesions were imaged using 3T diffusion-weighted MRI. Diffusion model selection was investigated in each lesion using the Akaike information criteria. Mann-Whitney U test and receiver operating characteristic (ROC) analysis were used for statistical evaluations. Results: Goodness-of-fit analysis showed that the stretched-exponential model had the highest voxel percentages in benign and malignant lesions (90.7% and 51.4%, respectively). ADC, Ds, and MK showed significant differences between benign and malignant lesions (p < 0.05) and between low- and high-grade clear cell renal cell carcinoma (ccRCC) (p < 0.05). α was significantly lower in the benign group than in the malignant group (p < 0.05). All diffusion measures showed significant differences between ccRCC and non-ccRCC (p < 0.05) except Df and α (p = 0.143 and 0.112, respectively). α showed the highest diagnostic accuracy in differentiating benign and malignant lesions with an area under the ROC curve of 0.923, but none of the parameters from these advanced models revealed significantly better performance over ADC in discriminating subtypes or grades of renal cell carcinoma (RCC) (p > 0.05). Conclusion: Compared with conventional diffusion parameters, α may provide additional information for differentiating benign and malignant renal masses, while ADC remains the most valuable parameter for differentiation of RCC subtypes and for ccRCC grading.

A Study for Strategy of On-line Shopping Mall: Based on Customer Purchasing and Re-purchasing Pattern (시스템 다이내믹스 기법을 활용한 온라인 쇼핑몰의 전략에 관한 연구 : 소비자의 구매 및 재구매 행동을 중심으로)

  • Lee, Sang-Gun;Min, Suk-Ki;Kang, Min-Cheol
    • Asia pacific journal of information systems
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    • v.18 no.3
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    • pp.91-121
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    • 2008
  • Electronic commerce, commonly known as e-commerce or eCommerce, has become a major business trend in these days. The amount of trade conducted electronically has grown extraordinarily by developing the Internet technology. Most electronic commerce has being conducted between businesses to customers; therefore, the researches with respect to e-commerce are to find customer's needs, behaviors through statistical methods. However, the statistical researches, mostly based on a questionnaire, are the static researches, They can tell us the dynamic relationships between initial purchasing and repurchasing. Therefore, this study proposes dynamic research model for analyzing the cause of initial purchasing and repurchasing. This paper is based on the System-Dynamic theory, using the powerful simulation model with some restriction, The restrictions are based on the theory TAM(Technology Acceptance Model), PAM, and TPB(Theory of Planned Behavior). This article investigates not only the customer's purchasing and repurchasing behavior by passing of time but also the interactive effects to one another. This research model has six scenarios and three steps for analyzing customer behaviors. The first step is the research of purchasing situations. The second step is the research of repurchasing situations. Finally, the third step is to study the relationship between initial purchasing and repurchasing. The purpose of six scenarios is to find the customer's purchasing patterns according to the environmental changes. We set six variables in these scenarios by (1) changing the number of products; (2) changing the number of contents in on-line shopping malls; (3) having multimedia files or not in the shopping mall web sites; (4) grading on-line communities; (5) changing the qualities of products; (6) changing the customer's degree of confidence on products. First three variables are applied to study customer's purchasing behavior, and the other variables are applied to repurchasing behavior study. Through the simulation study, this paper presents some inter-relational result about customer purchasing behaviors, For example, Active community actions are not the increasing factor of purchasing but the increasing factor of word of mouth effect, Additionally. The higher products' quality, the more word of mouth effects increase. The number of products and contents on the web sites have same influence on people's buying behaviors. All simulation methods in this paper is not only display the result of each scenario but also find how to affect each other. Hence, electronic commerce firm can make more realistic marketing strategy about consumer behavior through this dynamic simulation research. Moreover, dynamic analysis method can predict the results which help the decision of marketing strategy by using the time-line graph. Consequently, this dynamic simulation analysis could be a useful research model to make firm's competitive advantage. However, this simulation model needs more further study. With respect to reality, this simulation model has some limitations. There are some missing factors which affect customer's buying behaviors in this model. The first missing factor is the customer's degree of recognition of brands. The second factor is the degree of customer satisfaction. The third factor is the power of word of mouth in the specific region. Generally, word of mouth affects significantly on a region's culture, even people's buying behaviors. The last missing factor is the user interface environment in the internet or other on-line shopping tools. In order to get more realistic result, these factors might be essential matters to make better research in the future studies.

The Effects of Object Size and Reaching Distance on Upper Extremity Movement (물체 크기와 뻗기 거리가 상지 움직임에 미치는 영향)

  • Bae, Su-Young;Kim, Tae-Hoon
    • The Journal of Korean society of community based occupational therapy
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    • v.10 no.1
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    • pp.51-61
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    • 2020
  • Objectives : The purpose of this study is to investigate the effect of object size and reaching distance on kinematic factors of the upper limb while performing arm reaching for normal subjects. Methods : The subjects of this study were 30 university students who were in D university in Busan, and the measuring tool was CMS-70P(Zebris Medizintechnik Gmbh, Germany), a three-dimensional motion analyzer. The task had six conditions. The average velocity of motion, average acceleration, maximum velocity, and the velocity definite number of movements were measured according to changes in object size(2cm, 10cm) and reaching distance(15%, 37.5%, 60%) when they performed arm reaching. The general characteristics of the subject were technical statistics. One-way ANOVA measurement was used to compare variables when the arm reaching task was performed from two object sizes to three reaching distance, and the post-test was conducted with Tukey test. In addition, an independent t-test was used to analyze the kinematic differences according to the two object sizes at three reaching distances. A two-way ANOVA measurement (3×2 Two-way ANOVA measurement) was performed to identify the interaction of the reaching distance(15%, 37.5%, 60%) and the object size(2cm, 10cm). The statistical significance level α was set to .05. Results : When the size of the object increased, the velocity and maximum velocity also increased, but the definite number of velocity decreased. When the reaching distance increased, the velocity and maximum velocity increased, whereas the definite number of velocity decreased. Conclusion : The clinical significance of this study could be utilized as the baseline data for grading object size and reaching distances when the reaching training is implemented for patients whose central nervous system was damaged.

Genetic Parameter Estimation of Carcass Traits of Hanwoo Steers (한우 거세우의 도체형질에 대한 유전모수 추정)

  • Hwang, Jeong-Mi;Kim, Sidong;Choy, Yun-Ho;Yoon, Ho-Baek;Park, Cheol-Jin
    • Journal of Animal Science and Technology
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    • v.50 no.5
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    • pp.613-620
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    • 2008
  • The genetic parameters used in National Hanwoo Genetic Evaluation(NHGE) were needed to be monitored and updated periodically for accounting any possible changes in population parameters due to selection and environmental changes. Genetic parameters were estimated with single and two-trait models with MTDFREML package using 2,791 carcass records of steers collected from Hanwoo Progeny Test Program(HPTP). Single and two-trait models gave similar parameter estimates for all traits. The heritability estimates from single and two-trait models for carcass weight(CW), dressing percentage(DP), eye muscle area(EMA), back fat thickness(BFT) and marbling score(MS) were 0.30, 0.30, 0.37, 0.44 and 0.44, respectively. The heritability estimates for all the traits except BFT were slightly lower than those used in NHGE but seemed to be within the acceptable ranges. However, further monitoring is needed because the data might not have fully reflected the changes such as carcass grading standards in performance testing program. In order to shift statistical model of NHGE from single trait model to multiple-trait model, the genetic correlations between carcass traits were estimated with pairwise two-trait models. The genetic correlation coefficients between CW and DP, between CW and EMA, between CW and BFT and between CW and MS were 0.44, 0.63, 0.17 and 0.06, respectively. Those between DP and EMA, between DP and BFT and between DP and MS were 0.29, 0.40 and 0.20. Those between EMA and BFT and between EMA and MS were -0.24 and 0.15, respectively. The genetic correlation coefficient between BFT and MS was 0.03.

Awareness of Zoonoses among Cattle Slaughterhouse Workers in Korea (소 도축 관련 종사자의 인수공통감염증 인지도 조사)

  • Lim, Hyun-Sul;Yoo, Seok-Ju;Lee, Kwan
    • Journal of agricultural medicine and community health
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    • v.34 no.1
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    • pp.101-112
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    • 2009
  • Objectives: Cattle slaughterhouse workers are known as the high risk group for the zoonoses. We surveyed the awareness of zoonoses among cattle slaughterhouse workers to suggest direction of education and public relations. Methods: We evaluated the epidemiological characteristics of zoonoses and the process of cattle slaughtering. We designed different questionnaires for the workers involved in slaughtering, the handlers of residual products, the inspectors and their assistants, and the grading testers and their assistants respectively. We visited 73 cattle slaughterhouses and 62 residual products handle houses across the country and conducted a questionnaire survey of the general characteristics and the awareness of zoonoses. The data collected was evaluated using the SPSS 17.0 statistical package. Results: The awareness rate of brucellosis, Q fever and Enterohemorrhagic Escherichia coli (EHEC) were 83.9%, 18.5%, 62.7% among cattle slaughterhouse workers. The awareness rate of zoonoses among the workers involved in slaughtering and the handlers of residual products was lower than other workers. The awareness rate of zoonoses tended to increase as the school career. In the correct awareness rate of the transmission of zoonoses, 'transmission by tick bite', 'person to person' and 'air transmission' were lower than other transmission items. The most common reason why cattle slaughterhouse workers think that it is difficult to prevent zoonoses was the ignorance of how to prevent. Conclusions: An educational program is needed for the cattle slaughterhouse workers on zoonoses especially Q fever. And publicity activities about prevention of infection are needed for high risk groups.