• Title/Summary/Keyword: grey model

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Field instrumentation and settlement prediction of ground treated with straight-line vacuum preloading

  • Lei, Huayang;Feng, Shuangxi;Wang, Lei;Jin, Yawei
    • Geomechanics and Engineering
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    • v.19 no.5
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    • pp.447-462
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    • 2019
  • The vacuum preloading method has been used in many countries for ground improvement and land reclamation works. A sand cushion is required as a horizontal drainage channel for conventional vacuum preloading. In terms of the dredged-fill foundation soil, the treatment effect of the conventional vacuum preloading method is poor, particularly in Tianjin, China, where a shortage of sand exists. To solve this problem, straight-line vacuum preloading without sand is widely adopted in engineering practice to improve the foundation soil. Based on the engineering properties of dredged fill in Lingang City, Tianjin, this paper presents field instrumentation in five sections and analyzes the effect of a prefabricated vertical drain (PVD) layout and a vacuum pumping method on the soft soil ground treatment. Through the arrangement of pore water pressure gauges, settlement marks and vane shear tests, the settlement, pore water pressure and subsoil bearing capacity are analyzed to evaluate the effect of the ground treatment. This study demonstrates that straight-line vacuum preloading without sand can be suitable for areas with a high water content. Furthermore, the consolidation settlement and consolidation degree system is developed based on the grey model to predict the consolidation settlement and consolidation degree under vacuum preloading; the validity of the system is also verified.

Musculoskeletal Model for Assessing Firefighters' Internal Forces and Occupational Musculoskeletal Disorders During Self-Contained Breathing Apparatus Carriage

  • Wang, Shitan;Wang, Yunyi
    • Safety and Health at Work
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    • v.13 no.3
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    • pp.315-325
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    • 2022
  • Background: Firefighters are required to carry self-contained breathing apparatus (SCBA), which increases the risk of musculoskeletal disorders. This study assessed the newly recruited firefighters' internal forces and potential musculoskeletal disorders when carrying SCBA. The effects of SCBA strap lengths were also evaluated. Methods: Kinematic parameters of twelve male subjects running in a control condition with no SCBA equipped and three varying-strapped SCBAs were measured using 3D inertial motion capture. Subsequently, motion data and predicted ground reaction force were inputted for subject-specific musculoskeletal modeling to estimate joint and muscle forces. Results: The knee was exposed to the highest internal force when carrying SCBA, followed by the rectus femoris and hip, while the shoulder had the lowest force compared to the no-SCBA condition. Our model also revealed that adjusting SCBA straps length was an efficient strategy to influence the force that occurred at the lumbar spine, hip, and knee regions. Grey relation analysis indicated that the deviation of the center of mass, step length, and knee flexion-extension angle could be used as the predictor of musculoskeletal disorders. Conclusion: The finding suggested that the training of the newly recruits focuses on the coordinated movement of muscle and joints in the lower limb. The strap lengths around 98-105 cm were also recommended. The findings are expected to provide injury interventions to enhance the occupational health and safety of the newly recruited firefighters.

Automatically Dynamic Image Annotation Method Based on Multiple Bernoulli Relevance Models Using GLCM Feature (GLCM을 이용한 다중 베르누이 확률 변수 기반 자동 영상 동적 키워드 추출 방법)

  • Park, Tae-Joon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2009.11a
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    • pp.335-336
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    • 2009
  • In this paper, I propose an automatic approach to annotating images dynamically based on MBRM(Multiple Bernoulli Relevance Models) using GLCM(Grey Level Co-occurrence Matrix). MBRM is more appropriate to annotate images compare with multinomial distribution. The model is used in limited test set, MSRC-v2 (Microsoft Research Cambridge Image Database). The results show that this model is significantly outperforms previously reported results on the task of image annotation and retrieval.

Development and application of a floor failure depth prediction system based on the WEKA platform

  • Lu, Yao;Bai, Liyang;Chen, Juntao;Tong, Weixin;Jiang, Zhe
    • Geomechanics and Engineering
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    • v.23 no.1
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    • pp.51-59
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    • 2020
  • In this paper, the WEKA platform was used to mine and analyze measured data of floor failure depth and a prediction system of floor failure depth was developed with Java. Based on the standardization and discretization of 35-set measured data of floor failure depth in China, the grey correlation degree analysis on five factors affecting the floor failure depth was carried out. The correlation order from big to small is: mining depth, working face length, floor failure resistance, mining thickness, dip angle of coal seams. Naive Bayes model, neural network model and decision tree model were used for learning and training, and the accuracy of the confusion matrix, detailed accuracy and node error rate were analyzed. Finally, artificial neural network was concluded to be the optimal model. Based on Java language, a prediction system of floor failure depth was developed. With the easy operation in the system, the prediction from measured data and error analyses were performed for nine sets of data. The results show that the WEKA prediction formula has the smallest relative error and the best prediction effect. Besides, the applicability of WEKA prediction formula was analyzed. The results show that WEKA prediction has a better applicability under the coal seam mining depth of 110 m~550 m, dip angle of coal seams of 0°~15° and working face length of 30 m~135 m.

The Effect of Eyeglasses, Earrings, Hair Length, and Clothing Color on Impression Formation of Woman in Her 20s - Focused on the Evaluation of Female College Students - (안경, 귀걸이, 헤어 길이와 의복 색이 20대 여성의 인상형성에 미치는 영향 - 여대생들의 평가를 중심으로 -)

  • Lee, Myoung-Hee;Song, Won-Young
    • The Research Journal of the Costume Culture
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    • v.19 no.6
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    • pp.1221-1234
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    • 2011
  • The purpose of this study was to investigate the differences and interaction effects in impression formation according to eyeglasses, earrings, hair length, and clothing color worn by woman in Her 20s. A quasi-experimental method was used for this study. The experimental design was a $3{\times}2{\times}2{\times}4$(eyeglasses${\times}$earrings${\times}$hair length${\times}$clothing color) factorial design. The model of stimulus photographs was a woman with an oval shape face in her late twenties. She wore a tailored collared jacket with a white dress shirt. The subjects were 362 female college students. First, the women wearing glasses were found to be more potent but gave more negative impressions in terms of loveliness, politeness, and attractiveness than the women without glasses. Second, the women wearing earrings were perceived to have higher individuality, attractiveness, potency, loveliness, and elegance than the women without earrings. Third, the women with short hair were evaluated to have higher individuality, potency, and elegance, and to have lower loveliness, politeness, and attractiveness than the women with long hair. Fourth, the red clothes were perceived to have the higher individuality, loveliness, and attractiveness than the dark red or grey clothes. The light grey clothes were considered as the most elegant and the dark grey clothes were shown to have low attractiveness. Fifth, the women wearing the horn-rimmed glasses with short hair were evaluated to have high individuality. The women wearing glasses with short hair were evaluated lower in loveliness than those with long hair. The women with short hair, wearing glasses without earrings were evaluated very low in attractiveness.

A computational estimation model for the subgrade reaction modulus of soil improved with DCM columns

  • Dehghanbanadaki, Ali;Rashid, Ahmad Safuan A.;Ahmad, Kamarudin;Yunus, Nor Zurairahetty Mohd;Said, Khairun Nissa Mat
    • Geomechanics and Engineering
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    • v.28 no.4
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    • pp.385-396
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    • 2022
  • The accurate determination of the subgrade reaction modulus (Ks) of soil is an important factor for geotechnical engineers. This study estimated the Ks of soft soil improved with floating deep cement mixing (DCM) columns. A novel prediction model was developed that emphasizes the accuracy of identifying the most significant parameters of Ks. Several multi-layer perceptron (MLP) models that were trained using the Levenberg Marquardt (LM) backpropagation method were developed to estimate Ks. The models were trained using a reliable database containing the results of 36 physical modelling tests. The input parameters were the undrained shear strength of the DCM columns, undrained shear strength of soft soil, area improvement ratio and length-to-diameter ratio of the DCM columns. Grey wolf optimization (GWO) was coupled with the MLPs to improve the performance indices of the MLPs. Sensitivity tests were carried out to determine the importance of the input parameters for prediction of Ks. The results showed that both the MLP-LM and MLP-GWO methods showed high ability to predict Ks. However, it was shown that MLP-GWO (R = 0.9917, MSE = 0.28 (MN/m2/m)) performed better than MLP-LM (R =0.9126, MSE =6.1916 (MN/m2/m)). This proves the greater reliability of the proposed hybrid model of MLP-GWO in approximating the subgrade reaction modulus of soft soil improved with floating DCM columns. The results revealed that the undrained shear strength of the soil was the most effective factor for estimation of Ks.

Color Differences of Standard Samples according to Their Lightness Levels (명도 수준에 다른 목표 샘플의 색차)

  • Kim Jeong Ryeol;Lee Seung Jun;Kim Sam Soo
    • Textile Coloration and Finishing
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    • v.17 no.2 s.81
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    • pp.19-25
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    • 2005
  • A colour-difference formulae would be based on a colour appearance model, but, So far, most colour-difference formulae in common use are based on empirical fits to data. Therefore, of the many proposed, none are completely satisfactory but advances have been made in recent years. A new color-difference data set has been produced with the aims of making a comparison of the advanced CIE Lab formulae as well as confirming the effect of color-difference. 416 low lightness pairs that have only lightness-difference were produced for evaluation of CIE Lab-based formulae on lightness-difference from glossy polyester fabric. The standard color-difference pair was prepared and used. It was neutral grey sample pair that has only lightness difference. The standard pair was used to investigate lightness tolerances. And grey-scale method used to evaluate visual assessment. CIE Lab coordinates of the samples were measured using a X-Rite 8200 spectrophotometer. Visual assessments were carried out using Gretag Macbeth The Judge II Light Booth. A study of color tolerances at low lightness was carried out and get avaliable some results.

Factors Influencing Development and Severity of Grey Leaf Spot of Mulberry (Morus spp.)

  • Kumar, Punathil Meethal Pratheesh;Qadri, Syed Mashayak Hussaini;Pal, Susil Chandra
    • International Journal of Industrial Entomology and Biomaterials
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    • v.22 no.1
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    • pp.11-15
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    • 2011
  • Impact of pruning date, shoot age and weather parameters on the severity and development of grey leaf spot (Pseudocercospora mori) of mulberry was studied. The disease severity (%) increased with increase in shoot age irrespective of pruning date. Maximum disease severity was observed in plants pruned during second week of October and minimum in plants pruned during last week of December. Significant (P<0.05) influence of date of pruning, shoot age and their interaction was observed on the severity of the disease. Apparent infection rate (r) was significantly higher during plant growth period from day-48 to day-55. Average apparent rate was higher in plants pruned during first week of September and least in plants pruned during third and fourth week of December. Multiple regression analysis revealed contribution of various combinations of weather parameters on the disease severity. A linear prediction model [$Y=66.05+(-1.39)x_1+(-0.219)x_4$] with significant $R^2$ was developed for prediction of the disease under natural epiphytotic condition.

A Study on the Optimization of Multiple Injection Strategy for a Diesel Engine using Grey Relational Analysis and Linear Regression Analysis (선형 회귀 분석과 회색 관계 분석을 이용한 디젤엔진의 다단연료분사 제어전략 최적화 연구)

  • Kim, Sookyum;Woo, Seungchul;Kim, Woong Il;Park, Sangki;Lee, Kihyung
    • Journal of ILASS-Korea
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    • v.20 no.4
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    • pp.247-253
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    • 2015
  • Recently, the engine calibration technique has been much more complicated than that of the past engine case in order to satisfy the strict emission regulations. The current calibration method for the diesel engine which has an increasing market is both costly and time-consuming. New engine calibration method is required to develop for high-quality diesel engines with low cost and release it at the appropriate time. This study provides the optimal calibrating technique for complex engine systems using statistical modeling and numerical optimization. Firstly, it design a test plan based on Design of Experiments, a V-optimality methodology which is suitable looking for set-points, and determine the shape of test engine response. Secondly, it uses functions to make linear regression model for data analysis and optimization to fit the models of engines behavior. Finally, it generates the optimal calibrations obtained directly from empirical engine models using Grey Relational Analysis and compares the calibrations with data. This method can develop a process for systematically identifying the optimal balance of engine emissions.

Thermal based adsorption of daily food waste with the test of AI grey calculations

  • ZY Chen;Huakun Wu;Yahui Meng;ZY Gu;Timothy Chen
    • Membrane and Water Treatment
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    • v.15 no.3
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    • pp.107-115
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    • 2024
  • This study proposes the recycling of MVS as a value-added product for the removal of phosphate from aqueous solutions. By comparing the phosphate adsorption capacity of each calcined adsorbent at each temperature of MVS, it was determined that the optimal heat treatment temperature of MVS to improve the phosphate adsorption capacity was 800 ℃. MVS-800 suggests an adsorption mechanism through calcium phosphate precipitation. Subsequent kinetic studies with MVS-800 showed that the PFO model was more appropriate than the PSO model. In the equilibrium adsorption experiment, through the analysis of Langmuir and Freundlich models, Langmuir can provide a more appropriate explanation for the phosphate adsorption of MVS-800. This means that the adsorption of phosphate by MVS-800 is uniform over all surfaces and the adsorption consists of a single layer. Thermodynamic analysis of thermally activated MVS-800 shows that phosphate adsorption is an endothermic and involuntary reaction. MVS-800 has the highest phosphate adsorption capacity under low pH conditions. The presence of anions in phosphate adsorption reduces the phosphate adsorption capacity of MVS-800 in the order of CO 3 2-, SO 4 2-, NO 3- and Cl-. Based on experimental data to date, MVS-800 is an environmentally friendly adsorbent for recycling waste resources and is considered to be an adsorbent with high adsorption capacity for removing phosphates from aqueous solutions. This paper combines the advantages of gray predictor and AI fuzzy. The gray predictor can be used to predict whether the bear point exceeds the allowable deviation range, and then perform appropriate control corrections to accelerate the bear point to return to the boundary layer and achieve.