• Journal of the Korean Geotechnical Society
• /
• v.22 no.6
• /
• pp.71-82
• /
• 2006

One of the most popular pre-reinforcement methods of tunnel heading in cohesionless soils would be the fore-polling of grouted pipes, known as RPUM (reinforced protective umbrella method) or UAM (umbrella arch method). This technique allows safe excavation even in poor ground conditions by creating longitudinal arch parallel to the tunnel axis as the tunnel advances. Some previous studies on the reinforcing effects have been performed using numerical methods and/or laboratory-based small scale model tests. The complexity of boundary conditions imposes difficulties in representing the tunnelling procedure in laboratory tests and theoretical approaches. Full-scale study to identify reinforcing effects of the tunnel heading has rarely been carried out so far. In this study, a large scale model testing for a tunnel in granular soils was performed. Reinforcing patterns considered are four cases, Non-Reinforced, Crown-Reinforced, Crown & Face-Reinforced, and Face-Reinforced. The behavior of ground and pipes as reinforcing member were fully measured as the surcharge pressure applied. The influences of reinforcing pattern, pipe length, and face reinforcement were investigated in terms of stress and displacement. It is revealed that only the Face-Reinforced has decreased sufficiently both vertical settlement in tunnel heading and horizontal displacement on the face. Vertical stresses along the tunnel axis were concentrated in tunnel heading from the test results, so the heading should be reinforced before tunnel advancing. Most of maximum axial forces and bending moments for Crown-reinforced were measured at 0.75D from the face. Also it should be recommended that the minimum length of the pipe is more than l.0D for crown reinforcement.

• The Journal of Engineering Geology
• /
• v.20 no.1
• /
• pp.47-60
• /
• 2010

This study is focused on the analysis of tunnel behavior to estimate the stability on tunnel design. An estimation method was proposed as a hybrid consideration, which contains the displacement analysis by 3D numerical simulation, the maximum displacement obtained after field measurement, and an assessment of tunnel stability using a deformation analysis proposed by Sakurai(1988, 1997). The points of case study by Sakurai(1988, 1997) were replotted considering his analysis. From the new analysis of the tunnel case study, the trend line for analyzed points is analogized, which curve is divided into stable, unstable and failure zone. To evaluate the estimation method, a special shape of railway tunnel was selected, which are the Inchon international airport rail way connected to subway line 9 in Gimpo, Korea. The point s of upper and below track on the Inchon international airport rail way were satisfied to the stability of tunnel after reinforcing. Also the points shows the higher apparent Young's modulus, which resulted from improvement on shear strength by the micro silica grouting and the supporting of umbrella method. Therefore, if new analysis used, proper tunnel reinforcing method could be selected according to tunnel strain and geological property.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.9 no.2
• /
• pp.109-120
• /
• 2007

Auxiliary support systems such as the reinforced protective umbrella method have been applied before tunnel excavation to increase ground stiffness and to prevent the large deformation. However, determination procedure of geotechnical parameters along the construction sequence contains various errors. This study suggests a method to characterize the time-dependent behavior of pre-reinforced zones around the tunnel using elastic waves. Experimental results show that shear strength as well as elastic wave velocities increase with the curing time. Shear strength and strength parameters can be uniquely correlated to elastic wave velocities. Obtained results from the laboratory tests are applied to numerical simulation of tunnel considering its construction sequences. Based on numerical analysis, initial installation part of pre-reinforcement and portal of tunnel are critical for tunnel stability. Result of the time-dependent condition is similar to the results of for $1{\sim}2$ days of the constant time conditions. Finally, suggested simple analysis method combining experimental and numerical procedure which considering time-dependent behavior of pre-reinforced zone on tunnel would provide reliable and reasonable design and analysis for tunnel.

• Journal of Korean Public Health Nursing
• /
• v.12 no.2
• /
• pp.1-11
• /
• 1998

This study was performed to analyze the occupational health nursing of support-project of health management skill for small-scale industries. The 2 subject centers were under the umbrella of Korean Industrial Health Association and data collection period was 2weeks from September 1 to 13. 1997 and time and motion study method was used. Data was handled by SPSS win 7.5 program. results were worked out number. percentage. F-value. (1) The weekly time spending of occupational health nurses was distributed into indoor service 46.9%, outdoor service 26.6%, movement 26.5%. The mean visiting times were 2-3 times per week. and spending time was about 1 hour per industry. (2) There are statistically significant difference among the distribution of time spending according to industrial works(F=23.08. p=.000). and the special education for occupational disease prevention takes the most mean time. (3) There were statistically significant difference among the spending time for the health coach of occupational health nurses(F=188.79. p=.000). and the activity time for workers (58.4%) was more than that of for monitors(41.6%). The frequency of health coachs were 155 times for monitors during two weeks. but health coach for worker was 87 times. As a results. the contents of health coach for workers was proved to take more time than that for monitors. Perhaps we think that monitors has limitation for health management. therefore we should be consider flexible management of visiting time and health coach guidelines for occupational health nurses. (4) There were statistically significant differences among the distribution of time spending according to health coach methods for industrial health nurses(F=66.31. p=.000). The most frequent method of all was guide transmission. 159 times(65.7%), and the mean spending time for instruction was 19.78 min. the longest time. Our suggestion for occupational health nursing of support-project of health management skill for small-scale industry is that the need of each industry is very complex because of various conditions. therefore need assessment for industries should be conducted professionally. And occupational health nurses should apply occupational health nursing process autonomously. and their activities be guaranted by the guideline

• Journal of the Korean GEO-environmental Society
• /
• v.12 no.5
• /
• pp.59-63
• /
• 2011

Ground dynamic parameter such as shear elastic modulus and damping ratio is a very important variable in design of ground-structure with repeated load and dynamic load. Shear elastic modulus and damping ratio on small strain below linear limit strain is constant regardless of strain. Shear elastic modulus as the maximum shear elastic modulus and damping ratio as the minimum damping ratio were considered. As a lot of experiment related to the maximum shear elastic modulus, which is in dynamic deformation characteristics, have been conducted, many factors including voiding ratio, over consolidation ratio(OCR), confining pressure, geology time, PI, and the number of load cycle affect to dynamic soil characteristic. However, the research of ground dynamic characteristic improved with grout is absent such as underground continuous wall construction, deep mixing method, umbrella arch method. In order to investigate the dynamic soil characteristics improved with grout, in this study, resonant column tests were performed with changing water content(20%, 25%, 30%) and injection ratio of grout(5%, 10%, 15%), cure time(7th day, 28th day) As a result, shear elastic modulus and damping ratio, which are ground dynamic parameter, are affected by the injection ratio of milk grout, cure time and water content.

• Horticultural Science & Technology
• /
• v.17 no.6
• /
• pp.737-741
• /
• 1999

We surveyed the physiological disorders of fruit vegetables grown in the greenhouse in Kyungbuk province in 1998. Greenhouses used for cultivation were mostly single or multi-span iron pipe houses covered with polyethylene film. Single span greenhouses were used for strawberry, oriental melon and watermelon. Fifty six percent of the surveyed farms was a mono-cropping system for oriental melon and tomato. There were greenhouses used for successive cultivation for 10 years or more for strawberry and oriental melon in Koryeong and Seongju. Varieties of fruit vegetables cultivated were diverse, especially in cucumber and watermelon. In strawberry, malformed fruits were observed most frequently in March and the small fruits at late harvest period. Leaf chlorosis, stunt plants and runner outbreak were also found during the growing season. In tomato, occurrence of malformed fruits was severe from March to May, and occurrence of cracked fruits and blossom- end rot was also severe in October and November. The self topping and abnormal stem in tomato were problem in hydroponic cultures in August and November, respectively. Malformed cucumber fruits, such as curved, club shaped, irregular shaped and narrow necked, occurred at late season. Umbrella-shaped leaf in cucumber in summer were caused by calcium deficiency. Most serious disorders were fermented and malformed fruits occurring from March to May in oriental melon, and cracked fruits occurring from April to May in watermelon. At late growing stage of melons the leaf chlorosis occurred with complex symptoms of leaf disease. Growers had little knowledge on physiological disorders, and also on diagnose and measures to cure the disorders. Most growers pointed out that poor soil environment and temperature management in the greenhouse as the main causes of physiological disorders.

• Journal of Intelligence and Information Systems
• /
• v.19 no.2
• /
• pp.39-54
• /
• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.