• Title/Summary/Keyword: static uses

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Behavior of Hollow Box Girder Using Unbonded Compressive Pre-stressing (비부착 압축 프리스트레싱을 도입한 중공박스 거더의 거동)

  • Kim, Sung Bae;Kim, Jang-Ho Jay;Kim, Tae Kyun;Eoh, Cheol Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.3A
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    • pp.201-209
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    • 2010
  • Generally, PSC girder bridge uses total gross cross section to resist applied loads unlike reinforced concrete member. Also, it is used as short and middle span (less than 30 m) bridges due to advantages such as ease of design and construction, reduction of cost, and convenience of maintenance. But, due to recent increased public interests for environmental friendly and appearance appealing bridges all over the world, the demands for longer span bridges have been continuously increasing. This trend is shown not only in ordinary long span bridge types such as cable supported bridges but also in PSC girder bridges. In order to meet the increasing demands for new type of long span bridges, PSC hollow box girder with H-type steel as compression reinforcements is developed for bridge with a single span of more than 50 m. The developed PSC girder applies compressive prestressing at H-type compression reinforcements using unbonded PS tendon. The purpose of compressive prestressing is to recover plastic displacement of PSC girder after long term service by releasing the prestressing. The static test composed of 4 different stages in 3-point bending test is performed to verify safety of the bridge. First stage loading is applied until tensile cracks form. Then in second stage, the load is removed and the girder is unloaded. In third stage, after removal of loading, recovery of remaining plastic deformation is verified as the compressive prestressing is removed at H-type reinforcements. Then, in fourth stage, loading is continued until the girder fails. The experimental results showed that the first crack occurs at 1,615 kN with a corresponding displacement of 187.0 mm. The introduction of the additional compressive stress in the lower part of the girder from the removal of unbonded compressive prestressing of the H-type steel showed a capacity improvement of about 60% (7.7 mm) recovery of the residual deformation (18.7 mm) that occurred from load increase. By using prestressed H-type steel as compression reinforcements in the upper part of cross section, repair and rehabilitation of PSC girders are relatively easy, and the cost of maintenance is expected to decrease.

Medical Information Dynamic Access System in Smart Mobile Environments (스마트 모바일 환경에서 의료정보 동적접근 시스템)

  • Jeong, Chang Won;Kim, Woo Hong;Yoon, Kwon Ha;Joo, Su Chong
    • Journal of Internet Computing and Services
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    • v.16 no.1
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    • pp.47-55
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    • 2015
  • Recently, the environment of a hospital information system is a trend to combine various SMART technologies. Accordingly, various smart devices, such as a smart phone, Tablet PC is utilized in the medical information system. Also, these environments consist of various applications executing on heterogeneous sensors, devices, systems and networks. In these hospital information system environment, applying a security service by traditional access control method cause a problems. Most of the existing security system uses the access control list structure. It is only permitted access defined by an access control matrix such as client name, service object method name. The major problem with the static approach cannot quickly adapt to changed situations. Hence, we needs to new security mechanisms which provides more flexible and can be easily adapted to various environments with very different security requirements. In addition, for addressing the changing of service medical treatment of the patient, the researching is needed. In this paper, we suggest a dynamic approach to medical information systems in smart mobile environments. We focus on how to access medical information systems according to dynamic access control methods based on the existence of the hospital's information system environments. The physical environments consist of a mobile x-ray imaging devices, dedicated mobile/general smart devices, PACS, EMR server and authorization server. The software environment was developed based on the .Net Framework for synchronization and monitoring services based on mobile X-ray imaging equipment Windows7 OS. And dedicated a smart device application, we implemented a dynamic access services through JSP and Java SDK is based on the Android OS. PACS and mobile X-ray image devices in hospital, medical information between the dedicated smart devices are based on the DICOM medical image standard information. In addition, EMR information is based on H7. In order to providing dynamic access control service, we classify the context of the patients according to conditions of bio-information such as oxygen saturation, heart rate, BP and body temperature etc. It shows event trace diagrams which divided into two parts like general situation, emergency situation. And, we designed the dynamic approach of the medical care information by authentication method. The authentication Information are contained ID/PWD, the roles, position and working hours, emergency certification codes for emergency patients. General situations of dynamic access control method may have access to medical information by the value of the authentication information. In the case of an emergency, was to have access to medical information by an emergency code, without the authentication information. And, we constructed the medical information integration database scheme that is consist medical information, patient, medical staff and medical image information according to medical information standards.y Finally, we show the usefulness of the dynamic access application service based on the smart devices for execution results of the proposed system according to patient contexts such as general and emergency situation. Especially, the proposed systems are providing effective medical information services with smart devices in emergency situation by dynamic access control methods. As results, we expect the proposed systems to be useful for u-hospital information systems and services.

The Research on Recommender for New Customers Using Collaborative Filtering and Social Network Analysis (협력필터링과 사회연결망을 이용한 신규고객 추천방법에 대한 연구)

  • Shin, Chang-Hoon;Lee, Ji-Won;Yang, Han-Na;Choi, Il Young
    • Journal of Intelligence and Information Systems
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    • v.18 no.4
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    • pp.19-42
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    • 2012
  • Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.