Tunnel-lining Back Analysis Based on Artificial Neural Network for Characterizing Seepage and Rock Mass Load (투수 및 이완하중 파악을 위한 터널 라이닝의 인공신경망 역해석)
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- Journal of the Korean Geotechnical Society
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- v.22 no.8
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- pp.107-118
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- 2006
Among a variety of influencing components, time-variant seepage and long-term underground motion are important to understand the abnormal behavior of tunnels. Excessiveness of these two components could be the direct cause of severe damage on tunnels, however, it is not easy to quantify the effect of these on the behavior of tunnels. These parameters can be estimated by using inverse methods once the appropriate relationship between inputs and results is clarified. Various inverse methods or parameter estimation techniques such as artificial neural network and least square method can be used depending on the characteristics of given problems. Numerical analyses, experiments, or monitoring results are frequently used to prepare a set of inputs and results to establish the back analysis models. In this study, a back analysis method has been developed to estimate geotechnically hard-to-known parameters such as permeability of tunnel filter, underground water table, long-term rock mass load, size of damaged zone associated with seepage and long-term underground motion. The artificial neural network technique is adopted and the numerical models developed in the first part are used to prepare a set of data for learning process. Tunnel behavior, especially the displacements of the lining, has been exclusively investigated for the back analysis.
The present study investigates the non-linear soil-pile interaction using three-dimensional (3D) non-linear finite element models. The numerical models were validated by using the results of extensive pile load and shaking table tests. The pile performance in liquefiable and non-liquefiable soil has been studied by analyzing the liquefaction ratio, pile lateral displacement (LD), pile bending moment (BM), and frictional resistance (FR) results. The pile models have been developed for the different ground conditions. The study reveals that the results obtained during the pile load test and shaking cycles have good agreement with the predicted pile and soil response. The soil density, peak ground acceleration (PGA), slenderness ratio (L/D), and soil condition (i.e., dry and saturated) are considered during modeling. Four ground motions are used for the non-linear time history analyses. Consequently, design charts are proposed depended on the analysis results to be used for design practice. Eleven models have been used to validate the capability of these charts to capture the soil-pile response under different seismic intensities. The results of the present study demonstrate that L/D ratio slightly affects the lateral displacement when compared with other parameters. Also, it has been observed that the increasing in PGA and decreasing L/D decreases the excess pore water pressure ratio; i.e., increasing PGA from 0.1 g to 0.82 g of loose sand model, decrease the liquefaction ratio by about 50%, and increasing L/D from 15 to 75 of the similar models (under Kobe earthquake), increase this ratio by about 30%. This study reveals that the lateral displacement increases nonlinearly under both dry and saturated conditions as the PGA increases. Similarly, it is observed that the BM increases under both dry and saturated states as the L/D ratio increases. Regarding the acceleration histories, the pile BM was reduced by reducing the acceleration intensity. Hence, the pile BM decreased to about 31% when the applied ground motion switched from Kobe (PGA=0.82 g) to Ali Algharbi (PGA=0.10 g). This study reveals that the soil conditions affect the relationship pattern between the FR and the PGA. Also, this research could be helpful in understanding the threat of earthquakes in different ground characteristics.
Purpose - This study investigates the effect of service quality of coffee shop on store attitude and store loyalty. It demonstrates that the individual's behavior identification level plays a moderating role when the service quality of coffee shop affects store attitude. Conceptually drawing on Brady & Cronin's three-dimensional model of service quality, this study examines the effect of service quality of coffee specialty store on customer's attitudes and loyalty. Also, according to construal level theory, it examines the individual's propensity difference whether the individual's behavior identification level on service quality and store attitude has a moderating effect Research design, data, and methodology - This study used Brady & Cronin's three-dimensional service quality model, and 183 valid cases collected through the questionnaire survey were used for data analyses. For hypothesis testing, regression analysis, multiple regression analysis, and covariance analysis were conducted. Result- As a result of this study, first, it is confirmed that service quality has a positive effect on store attitude toward coffee shop. Second, the difference of an individual's construal level did not have a moderating effect on the influential relationship of service quality on the store attitude of coffee shop. This is because the influence of the service quality is greater than the difference between groups at the construal level. Therefore, there was no moderating influence according to construal level. Third, the store attitude of coffee specialty store has a positive effect on store loyalty. Conclusions - It is confirmed that there is a difference in the effect of service quality and store attitude on general and college students. This suggests that it can be used to establish marketing strategies by segment. And, the college students were found to be more influenced by physical environment quality factor among three dimensions of service quality. Therefore, it is necessary to further improve efforts to raise the level of service quality perception through physical environmental factors such as clean and pleasant environment including the interior of a coffee shop, and internal table arrangement. The empirical study on the moderating effects of customer's tendency of difference is meaningful in the absence of empirical studies.
Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we propose a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. First, we attempt to find the relationship between documents and topics by using the result of topic analysis for single-categorized documents. Second, we construct a correspondence table between topics and categories by investigating the relationship between them. Finally, we calculate the matching scores for each document to multiple categories. The results imply that a document can be classified into a certain category if and only if the matching score is higher than the predefined threshold. For example, we can classify a certain document into three categories that have larger matching scores than the predefined threshold. The main contribution of our study is that our methodology can improve the applicability of traditional multi-category classifiers by generating multi-categorized documents from single-categorized documents. Additionally, we propose a module for verifying the accuracy of the proposed methodology. For performance evaluation, we performed intensive experiments with news articles. News articles are clearly categorized based on the theme, whereas the use of vulgar language and slang is smaller than other usual text document. We collected news articles from July 2012 to June 2013. The articles exhibit large variations in terms of the number of types of categories. This is because readers have different levels of interest in each category. Additionally, the result is also attributed to the differences in the frequency of the events in each category. In order to minimize the distortion of the result from the number of articles in different categories, we extracted 3,000 articles equally from each of the eight categories. Therefore, the total number of articles used in our experiments was 24,000. The eight categories were "IT Science," "Economy," "Society," "Life and Culture," "World," "Sports," "Entertainment," and "Politics." By using the news articles that we collected, we calculated the document/category correspondence scores by utilizing topic/category and document/topics correspondence scores. The document/category correspondence score can be said to indicate the degree of correspondence of each document to a certain category. As a result, we could present two additional categories for each of the 23,089 documents. Precision, recall, and F-score were revealed to be 0.605, 0.629, and 0.617 respectively when only the top 1 predicted category was evaluated, whereas they were revealed to be 0.838, 0.290, and 0.431 when the top 1 - 3 predicted categories were considered. It was very interesting to find a large variation between the scores of the eight categories on precision, recall, and F-score.
This experiment was conducted, making use of the 'NONG-RIM No, 6' a recommended variety of rice plant for the year of 1969. Main purpose of the experiment are to explore possibilities of; a) ways and means of saving irrigation water and, b) overcoming drought at the same time so that an increaded yield in rice production could be resulted in Specifically, it was tried to determine the effects of the Rotation Irrigation method combined with differentiated thickess of Lining upon the growth and Yield of rice production. Some of the major finding are summarized in the follows. 1) The Different thicknesses show a significant relationship with the weight of 1000 grains. In the case of 3cm Lined plot, the grain weight is 39.0 Grams, the heaviest. Next in order is 6 cm lined plnt, 5 day control plot, 6 day control plot. 2) In rice yield, it is found that there is a considerably moderate signicant relationship with both the different thickness of lining and the number of irrgation, as shown in the table No,7. 3) There is little or no difference among different plot in terms of; a) physical and chemical properties of soil, b) quality of irrgation water, c) climatic condition, and rainfalls. 4) It is found that there is no significant relationship between differences in the method of rotation irrgation and the number of ears per hill because of too much rainydays and low temperature during irrigation season. 5) In uyny1-treated plots, it is shown that there is on difference among different plots, but the irrigation water requirement saved as much as 1/2 to actual irrigation water compare to uncontroled plot. 6) The irrigation water requirement for 48 days is saved as much 67% compared to uncontroled plot, the order are; the 9cm lined plot, the plot of vinyl with no hole, the plot with a hole of
Nowadays, it is common that most consumers are purchasing goods in e-stores. The e-stores eager to attract, revisit, retain, and finally convert them into loyal customers. The e-store marketers have planned and executed numerous marketing efforts. As one of the marketing activities, e-store managers attempt to build web sites that meet customers' functional and psychological needs. A wide array of studies has been done to identify factors that could affect customers' response of web sites. Majority of studies were conducted to verify technology-related and functional variables of the website which facilitate transactions and enhance customer responses such as purchase intention and website loyalty. However, there has been little research on the external cues of website and psychological variables of consumer that could have positive influences on customer response. The purpose of this study is to investigate the influence of e-store personality on e-store loyalty through mediating variables such as e-store identification, e-store trust, and e-store engagement. The authors of this study develop the model and set up the six main hypotheses and a set of sub-hypotheses based on a literature review, shown in
Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center.
In this study, we suggest an empirical forecast of CIR (Corotating Interaction Regions) and geomagnetic storm based on the information of coronal holes (CH). For this we used CH data obtained from He I
The dose re-calculation process using Megavoltage cone-beam CT images is inevitable process to perform the Adaptive Radiation Therapy (ART). The purpose of this study is to improve dose re-calculation accuracy using MVCBCT images by applying intensity calibration method and three dimensional rigid body transform and filtering process. The three dimensional rigid body transform and Gaussian smoothing filtering process to MVCBCT Rando phantom images was applied to reduce image orientation error and the noise of the MVCBCT images. Then, to obtain the predefined modification level for intensity calibration, the cheese phantom images from kilo-voltage CT (kV CT), MVCBCT was acquired. From these cheese phantom images, the calibration table for MVCBCT images was defined from the relationship between Hounsfield Units (HUs) of kV CT and MVCBCT images at the same electron density plugs. The intensity of MVCBCT images from Rando phantom was calibrated using the predefined modification level as discussed above to have the intensity of the kV CT images to make the two images have the same intensity range as if they were obtained from the same modality. Finally, the dose calculation using kV CT, MVCBCT with/without intensity calibration was applied using radiation treatment planning system. As a result, the percentage difference of dose distributions between dose calculation based on kVCT and MVCBCT with intensity calibration was reduced comparing to the percentage difference of dose distribution between dose calculation based on kVCT and MVCBCT without intensity calibration. For head and neck, lung images, the percentage difference between kV CT and non-calibrated MVCBCT images was 1.08%, 2.44%, respectively. In summary, our method has quantitatively improved the accuracy of dose calculation and could be a useful solution to enhance the dose calculation accuracy using MVCBCT images.
This study has a purpose to look into the effect of the relationship between the Tube current (mA) and SOD(Source to Object Distance), which is a parameter of lower limb angiography examination, and the dilution rate of the contrast medium concentration (300, 320, 350) on the image. To that end, using 3 mm vessel model water phantom, a vessel model custom made in the size of peripheral vessel diameter, this study measured relationships between change of parameters, such as tube current (mA), SOD and varying concentrations (300, 320, 350) of contrast medium dilution into SNR and CNR values while analyzing the coefficients of variance(cv<10). The software used to measure SNR and CNR values was Image J 1.50i from NIH (National Institutes of Health, USA). MPV (mean pixel value) and SD (standard deviation) were used after verifying numerically the image signal for region of interest (ROI) and background on phantom from the DICOM (digital imaging and communications in medicine) 3.0 file transmitted to PACS. As to contrast medium dilution by the change of tube current, when 146 mA and 102 mA were compared, For both SNR and CNR, the coefficient of variation value was less than 10 until the section of CM: N/S dilution (100% ~ 30% : 70%) but CM: N/S dilution rate (20%: 80% ~ 10% : 90%) the coefficient of variation was 10 or more. As to contrast medium dilution by concentration for SOD change, when SOD's (32.5 cm and 22.5 cm) were compared,For both SNR and CNR, the coefficient of variation value was less than 10 until the section of CM: N/S dilution (100% ~ 30% : 70%) but CM: N/S dilution rate (20%: 80% ~ 10% : 90%) the coefficient of variation was 10 or more. As to contrast medium dilution by concentration for SOD change, when SOD's (32.5 cm and 12.5 cm) were compared,For both SNR and CNR, the coefficient of variation value was less than 10 until the section of CM: N/S dilution (100% ~ 30% : 70%) but CM: N/S dilution rate (20%: 80% ~ 10% : 90%) the coefficient of variation was 10 or more. As a result, set a low tube current value in other tests or procedures including peripheral angiography of the lower extremities in the intervention, and make the table as close as possible to the image receiver, and adjust the contrast agent concentration (300) to CM: N/S dilution (30%: 70%). ) Is suggested as the most efficient way to obtain images with an appropriate concentration while simultaneously reducing the burden on the kidney and the burden on exposure.
. This model is composed of four paths such as dimensions of e-store personality. First of all, hypothesis 1 is partially supported because sub-hypothesis 1-1 and 1-2 are supported, whereas sub-hypothesis 1-3, 1-4, and 1-5 are rejected. Specifically, it reveals that warmth and sophistication dimensions in e-store personality have positive influence on e-store identification, however, activity, progressiveness, and strictness does not have any significant relationship on e-store identification. Secondly, hypothesis 2 was supported. Therefore, it can be said that e-store identification has a positive impact on e-store trust. Thirdly, hypothesis 3 is also supported. Hence, there is a positive relationship between e-store identification and e-store engagement. Fourthly, hypothesis 4 is supported too. e-store identification has a positive influence on e-store loyalty. Fifthly, hypothesis 5 is also accepted. This indicates that e-store trust is a precedent variable which positively affects e-store loyalty. Lastly, it reveals that e-store engagement has a positive impact on e-store loyalty. Therefore, hypothesis 6 is supported. The findings of the study imply that some dimensions of e-store personality have a positive influence on e-store identification, and that e-store identification has direct and indirect influence on e-store loyalty through e-store trust and e-store engagement positively. These results also suggest that the e-store identification in e-store personality is a precedent variable which positively affects e-store loyalty directly and indirectly through e-store trust and engagement as a mediating variable. Therefore, e-store marketers need to implement website strategy based on e-store personality, e-store identification, e-store trust, and e-store engagement to meet customers' psychological needs and enhance e-store loyalty. Finally, the limitations and future study directions based on this study are discussed.
Spatial effect on the diffusion of discount stores
(대형할인점 확산에 대한 공간적 영향)
. In a result of the Bass model(I), the estimates of innovation coefficient(p) and imitation coefficient(q) are 0.017 and 0.323 respectively. While the estimate of market potential is 384. A result of the Bass model(II) for each district shows the estimates of innovation coefficient(p) in SG is 0.019 and the lowest among 5 areas. This is because SG is the diffusion center. The estimates of imitation coefficient(q) in BG is 0.353 and the highest. The imitation coefficient in the vicinity of the diffusing center such as BG is higher than that in the diffusing center because much information flows through various paths more as diffusion is progressing. A result of the Bass model(II) shows the estimates of innovation coefficient(p) in SG is 0.019 and the lowest among 5 areas. This is because SG is the diffusion center. The estimates of imitation coefficient(q) in BG is 0.353 and the highest. The imitation coefficient in the vicinity of the diffusing center such as BG is higher than that in the diffusing center because much information flows through various paths more as diffusion is progressing. In a result of spatial diffusion model(IV), we can notice the changes between coefficients of the bass model and those of the spatial diffusion model. Except for GJ, the estimates of innovation and imitation coefficients in Model IV are lower than those in Model II. The changes of innovation and imitation coefficients are reflected to spatial coefficient(
Empirical Forecast of Corotating Interacting Regions and Geomagnetic Storms Based on Coronal Hole Information
(코로나 홀을 이용한 CIR과 지자기 폭풍의 경험적 예보 연구)
Improvement of the Dose Calculation Accuracy Using MVCBCT Image Processing
(Megavoltage Cone-Beam CT 영상의 변환을 이용한 선량 계산의 정확성 향상)
Analysis of Contrast Medium Dilution Rate for changes in Tube Current and SOD, which are Parameters of Lower Limb Angiography Examination
(하지 혈관조영검사 시 매개변수인 관전류와 SOD에 변화에 대한 조영제 희석률 분석)
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