• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.11
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• pp.95-104
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• 2018

Healthcare technology has been growing and fostering cooperation between industry, university and hospitals as growth engines in korea. So, the medibio research institutes in hospital have been constructed to promote research and industrialization centering on healthcare technology. The purpose of this study is to investigate the cases of research institutes in hospitals, and search the characteristics of building organization of medibio research laboratory facilities. Case study is investigated by floor plan, homepage and site visits about five research institutes selected in research-driven hospitals. The facility title and size of research laboratory is originated from site area and research building location. The building function include not only the research lab and business office reflecting on the development platform, and but assembly and meeting room in the ground level. Laboratory floor plans have three types, rectangular, rectangular+linear and linear type, one is traditional and efficient, the others are people and friendly. And building core types are correlated with lab space unit modules, single and double side core are shown in rectangular type. All the laboratories are open lab, composed with laboratory bench and research note writing desk facing the lab service and enclosed lab-support area. And they have communication space looking as warm and cozy common area for the innovation, convergence and collaboration. As the high risk of contamination and high standard for safety and security, equipment and facilities are well managed with biological environment including BSC, fume hood, PCR classification, eye washing and emergency shower.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.116-126
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• 2011

In this paper, we present a multi-media processor which can decode multiple-format video standards. The designed processor is evaluated with optimized MPEG-2, MPEG-4, and AVS (Audio video standard). There are two approaches for developing of real-time video decoders. First, hardware-based system is much superior to a processor-based one in execution time. However, it takes long time to implement and modify hardware systems. On the contrary, the software-based video codecs can be easily implemented and flexible, however, their performance is not so good for real-time applications. In this paper, in order to exploit benefits related to two approaches, we designed a processor called ASIP(Application specific instruction-set processor) for video decoding. In our work, we extracted eight common modules from various video decoders, and added several multimedia instructions to the processor. The developed processor for video decoders is evaluated with the Synopsys platform simulator and a FPGA board. In our experiment, we can achieve about 37% time saving in total decoding time.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.177-189
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• 2013

In Smart Education, the roles of digital textbook is very important as face-to-face media to learners. The standardization of digital textbook will promote the industrialization of digital textbook for contents providers and distributers as well as learner and instructors. In this study, the following three objectives-oriented digital textbooks are looking for ways to standardize. (1) digital textbooks should undertake the role of the media for blended learning which supports on-off classes, should be operating on common EPUB viewer without special dedicated viewer, should utilize the existing framework of the e-learning learning contents and learning management. The reason to consider the EPUB as the standard for digital textbooks is that digital textbooks don't need to specify antoher standard for the form of books, and can take advantage od industrial base with EPUB standards-rich content and distribution structure (2) digital textbooks should provide a low-cost open market service that are currently available as the standard open software (3) To provide appropriate learning feedback information to students, digital textbooks should provide a foundation which accumulates and manages all the learning activity information according to standard infrastructure for educational Big Data processing. In this study, the digital textbook in a smart education environment was referred to open digital textbook. The components of open digital textbooks service framework are (1) digital textbook terminals such as smart pad, smart TVs, smart phones, PC, etc., (2) digital textbooks platform to show and perform digital contents on digital textbook terminals, (3) learning contents repository, which exist on the cloud, maintains accredited learning, (4) App Store providing and distributing secondary learning contents and learning tools by learning contents developing companies, and (5) LMS as a learning support/management tool which on-site class teacher use for creating classroom instruction materials. In addition, locating all of the hardware and software implement a smart education service within the cloud must have take advantage of the cloud computing for efficient management and reducing expense. The open digital textbooks of smart education is consdered as providing e-book style interface of LMS to learners. In open digital textbooks, the representation of text, image, audio, video, equations, etc. is basic function. But painting, writing, problem solving, etc are beyond the capabilities of a simple e-book. The Communication of teacher-to-student, learner-to-learnert, tems-to-team is required by using the open digital textbook. To represent student demographics, portfolio information, and class information, the standard used in e-learning is desirable. To process learner tracking information about the activities of the learner for LMS(Learning Management System), open digital textbook must have the recording function and the commnincating function with LMS. DRM is a function for protecting various copyright. Currently DRMs of e-boook are controlled by the corresponding book viewer. If open digital textbook admitt DRM that is used in a variety of different DRM standards of various e-book viewer, the implementation of redundant features can be avoided. Security/privacy functions are required to protect information about the study or instruction from a third party UDL (Universal Design for Learning) is learning support function for those with disabilities have difficulty in learning courses. The open digital textbook, which is based on E-book standard EPUB 3.0, must (1) record the learning activity log information, and (2) communicate with the server to support the learning activity. While the recording function and the communication function, which is not determined on current standards, is implemented as a JavaScript and is utilized in the current EPUB 3.0 viewer, ths strategy of proposing such recording and communication functions as the next generation of e-book standard, or special standard (EPUB 3.0 for education) is needed. Future research in this study will implement open source program with the proposed open digital textbook standard and present a new educational services including Big Data analysis.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.11
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• pp.5637-5642
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• 2012

Objective: Gastric cancer (GC) is one of the most common malignancies and its mortality ranks third among all cancers in China. We previously noted that XRCC1 Arg194Trp was associated with GC risk in Western China in a study on XRCC1 Arg194Trp and ADPRT Val762Ala. We aimed to further explore the association of these polymorphisms with risk of the noncardia subtype. Methods: We enrolled 176 noncardia GC patients and 308 controls from four hospitals and a community between October 2010 and August 2011. Genotyping was performed in a 384-well plate format on the Sequenom MassARRAY platform. A self-designed questionnaire was utilized to collect epidemiological data from the subjects regarding demographic factors and potential risk factors. Results: Subjects were aged $56.8{\pm}11.8$ (mean ${\pm}$ standard deviation) and $57.6{\pm}11.1$ years in the case and control groups, respectively. Individuals carrying the XRCC1 Trp/Trp or Arg/Trp variant genotype were at significantly increased risk of noncardia GC (adjusted OR, 1.48; 95% CI, 1.00-2.17), after adjustment for family history of cancer, drinking, and smoking. The increased risk of XRCC1 Arg194Trp variant genotype was more pronounced among subjects below 60 years old (adjusted OR, 1.78; 95% CI, 1.07-2.96), compared to older individuals. ADPRT Val762Ala variants (Ala/Ala or Val/Ala) were not associated with noncardia GC (adjusted OR, 1.03; 95% CI, 0.69-1.54). Conclusions: Our study suggests that XRCC1 Arg194Trp is a genetic susceptibility factor for developing noncardia GC in Han Chinese in Western China. In particular, individuals with the XRCC1 Arg194Trp variant genotype are at increased risk for GC below 60 years old.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.12a
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• pp.169-181
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• 2004

SK Telecom has already constructed GIMS system as the base common framework of LBS/GIS service system based on OGC(OpenGIS Consortium)'s international standard for the first mobile vector map service in 2002, But as service content appears more complex, renovation has been needed to satisfy multi-purpose, multi-function and maximum efficiency as requirements have been increased. This research is for preparation ion of GML3-based platform to upgrade service from GML2 based GIMS system. And with this, it will be possible for variety of application services to provide location and geographic data easily and freely. In GML 3.0, it has been selected animation, event handling, resource for style mapping, topology specification for 3D and telematics services for mobile LBS multimedia service. And the schema and transfer protocol has been developed and organized to optimize data transfer to MS(Mobile Stat ion) Upgrade to GML 3.0-based GIMS system has provided innovative framework in the view of not only construction but also service which has been implemented and applied to previous research and system. Also GIMS channel interface has been implemented to simplify access to GIMS system, and service component of GIMS internals, WFS and WMS, has gotten enhanded and expanded function.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.