• Journal of Korean Society of Steel Construction
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• v.27 no.6
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• pp.513-523
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• 2015

In steel moment frames constructed of H-shapes, strong-axis moment connections should be used for maximum structural efficiency if possible. And most of cyclic seismic testing, domestic and international, has been conducted for strong-axis moment connections and cyclic test data for weak-axis connections is quite limited. However, when perpendicular moment frames meet, weak-axis moment connections are also needed at the intersecting locations. Especially, both strong- and weak-axis moment connections have been frequently used in domestic practice. In this study, cyclic seismic performance of RBS (reduced beam section) weak-axis welded moment connections was experimentally investigated. Test specimens, designed according to the procedure proposed by Gilton and Uang (2002), performed well and developed an excellent plastic rotation capacity of 0.03 rad or higher, although a simplified sizing procedure for attaching the beam web to the shear plate in the form of C-shaped fillet weld was used. The test results of this study showed that the sharp corner of C-shaped fillet weld tends to be the origin of crack propagation due to stress concentration there and needs to be trimmed for the better weld shape. Different from strong-axis moment connections, due to the presence of weld access hole, a kind of CJP butt joint is formed between the beam flange and the horizontal continuity plate in weak-axis moment connections. When weld access hole is large, this butt joint can experience cyclic local buckling and subsequent low cycle fatigue fracture as observed in this testing program. Thus the size of web access hole at the butt joint should be minimized if possible. The recommended seismic detailing such as stickout, trimming, and thicker continuity plate for construction tolerance should be followed for design and fabrication of weak-axis welded moment connections.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.179-192
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• 2014

Keeping in line with the recent changes in the information technology environment, the online learning environment that supports multiple users' participation such as MOOC (Massive Open Online Courses) has become important. One of the largest professional associations in Information Technology, IEEE Computer Society, announced that "Supporting New Learning Styles" is a crucial trend in 2014. Popular MOOC services, CourseRa and edX, have continued to build active learning environment with a large number of lectures accessible anywhere using smart devices, and have been used by an increasing number of users. In addition, collaborative web services (e.g., blogs and Wikipedia) also support the creation of various user-uploaded learning materials, resulting in a vast amount of new lectures and learning materials being created every day in the online space. However, it is difficult for an online educational system to keep a learner' motivation as learning occurs remotely, with limited capability to share knowledge among the learners. Thus, it is essential to understand which materials are needed for each learner and how to motivate learners to actively participate in online learning system. To overcome these issues, leveraging the constructivism theory and collective intelligence, we have developed a social bookmarking system called WeStudy, which supports learning material sharing among the users and provides personalized learning material recommendations. Constructivism theory argues that knowledge is being constructed while learners interact with the world. Collective intelligence can be separated into two types: (1) collaborative collective intelligence, which can be built on the basis of direct collaboration among the participants (e.g., Wikipedia), and (2) integrative collective intelligence, which produces new forms of knowledge by combining independent and distributed information through highly advanced technologies and algorithms (e.g., Google PageRank, Recommender systems). Recommender system, one of the examples of integrative collective intelligence, is to utilize online activities of the users and recommend what users may be interested in. Our system included both collaborative collective intelligence functions and integrative collective intelligence functions. We analyzed well-known Web services based on collective intelligence such as Wikipedia, Slideshare, and Videolectures to identify main design factors that support collective intelligence. Based on this analysis, in addition to sharing online resources through social bookmarking, we selected three essential functions for our system: 1) multimodal visualization of learning materials through two forms (e.g., list and graph), 2) personalized recommendation of learning materials, and 3) explicit designation of learners of their interest. After developing web-based WeStudy system, we conducted usability testing through the heuristic evaluation method that included seven heuristic indices: features and functionality, cognitive page, navigation, search and filtering, control and feedback, forms, context and text. We recruited 10 experts who majored in Human Computer Interaction and worked in the same field, and requested both quantitative and qualitative evaluation of the system. The evaluation results show that, relative to the other functions evaluated, the list/graph page produced higher scores on all indices except for contexts & text. In case of contexts & text, learning material page produced the best score, compared with the other functions. In general, the explicit designation of learners of their interests, one of the distinctive functions, received lower scores on all usability indices because of its unfamiliar functionality to the users. In summary, the evaluation results show that our system has achieved high usability with good performance with some minor issues, which need to be fully addressed before the public release of the system to large-scale users. The study findings provide practical guidelines for the design and development of various systems that utilize collective intelligence.

• THE JOURNAL OF KOREAN ORIENTAL ONCOLOGY
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• v.7 no.1
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• pp.77-97
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• 2001

Anti-angiogenesis is one of therapies which have been high-lightened on the research of cancer treatment. Anti-angiogenesis means that new blood vessels are created from a existing capillary tube and it is a important process on metastasis and permeation when cancer is created or formed. Since angiogenesis have been under research, a complete recovery oriented treatment against cancer have been suggested blocking metastasis, delaying the growth of cancer cell, and blocking the supply of oxygen and nutritive substance through the web of blood vessels. Until now, there are several anti-angiogenesis, which have been known to the public, such as thalidomide, angiostatin, endostatin, 2-methoxyestradiol, TNP-470, and marimastat, etc. Additionally, 17 clinical testing projects about anti-angiogenesis are on the process in NCI(National Cancer Institute). Especially, TNP-470 showed effectiveness against cancer on clinical testing after finishing animal testing. Based on existing researches showing that Yinsamyangwui-tang is effective to strengthening body resistance and Whallakhyolenyng-dan effects cells on the inside of blood vessel because Whallakhyolenyng- dan restrains cell adhesion during the restraining period of a blood vessel, I tried to research the effect of Whalakhyolenyng-dan plus Yinsamyangwui-tang on angiogenesis. I made a conclusion putting into operation through using SK-Hep-1 (KCLB 30052), A549(KCLB 10185), AGS(KCLB 21739), and BCE(Bovine Capillary Endothelial Cell). Followings are the results of my experimental research: 1. According to the researching results of anti-cancer activation against cancer cell, Whallkhyoleyng dan plus Yinsamyangwui-tang decreased the number of cancer cells -- While injecting $600{\mu}g/ml$, injected groups decreased 3.1% more comparing with the contrastive group of SK-Hep-1, 49.7% more comparing with the contrastive group of A549, and 31.0% more comparing with the contrastive group of AGS. 2. According to the researching results of DNA composition effect between BCE and cancer cell, Whallakhyoleyng-dan plus Yinsamyangwui-tang reduced the rate of SK-Hep-1 synthesis inhibition by 59.1% at $600{\mu}g/ml$ intensity comparing with contrastive group; for A549, 72.6%; for AGS, 6.1%, for BCE, 28.9%. 3. According to the researching results about the effect of BCE cell to angiogenesis, angiogenesis was restrained at $400{\mu}g/ml$ intensity during 18 hours observation. 4. In the case of aortic ring assay, the half level of angiogenesis was reduced comparing with the contrastive group while injecting with $400{\mu}g/ml$ intensity; with $800{\mu}g/ml$, under 10% comparing with contrastive group; and with $1600{\mu}g/ml$, complete restrain. According to the above results, Whallakhyoleyng-dan plus Yinsamyangwui-tang was proved to have an anti-angiogenetic effects.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.151-171
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• 2014

Firms today have sought management effectiveness and efficiency utilizing information technologies (IT). Numerous firms are outsourcing specific information systems functions to cope with their short of information resources or IT experts, or to reduce their capital cost. Recently, Software-as-a-Service (SaaS) as a new type of information system has become one of the powerful outsourcing alternatives. SaaS is software deployed as a hosted and accessed over the internet. It is regarded as the idea of on-demand, pay-per-use, and utility computing and is now being applied to support the core competencies of clients in areas ranging from the individual productivity area to the vertical industry and e-commerce area. In this study, therefore, we seek to quantify the value that SaaS has on business performance by examining the relationships among firm strategies, SaaS technology maturity, and business performance of SaaS providers. We begin by drawing from prior literature on SaaS, technology maturity and firm strategy. SaaS technology maturity is classified into three different phases such as application service providing (ASP), Web-native application, and Web-service application. Firm strategies are manipulated by the low-cost strategy and differentiation strategy. Finally, we considered customer acquisition as a business performance. In this sense, specific objectives of this study are as follows. First, we examine the relationships between customer acquisition performance and both low-cost strategy and differentiation strategy of SaaS providers. Secondly, we investigate the mediating and moderating effects of SaaS technology maturity on those relationships. For this purpose, study collects data from the SaaS providers, and their line of applications registered in the database in CNK (Commerce net Korea) in Korea using a questionnaire method by the professional research institution. The unit of analysis in this study is the SBUs (strategic business unit) in the software provider. A total of 199 SBUs is used for analyzing and testing our hypotheses. With regards to the measurement of firm strategy, we take three measurement items for differentiation strategy such as the application uniqueness (referring an application aims to differentiate within just one or a small number of target industry), supply channel diversification (regarding whether SaaS vendor had diversified supply chain) as well as the number of specialized expertise and take two items for low cost strategy like subscription fee and initial set-up fee. We employ a hierarchical regression analysis technique for testing moderation effects of SaaS technology maturity and follow the Baron and Kenny's procedure for determining if firm strategies affect customer acquisition through technology maturity. Empirical results revealed that, firstly, when differentiation strategy is applied to attain business performance like customer acquisition, the effects of the strategy is moderated by the technology maturity level of SaaS providers. In other words, securing higher level of SaaS technology maturity is essential for higher business performance. For instance, given that firms implement application uniqueness or a distribution channel diversification as a differentiation strategy, they can acquire more customers when their level of SaaS technology maturity is higher rather than lower. Secondly, results indicate that pursuing differentiation strategy or low cost strategy effectively works for SaaS providers' obtaining customer, which means that continuously differentiating their service from others or making their service fee (subscription fee or initial set-up fee) lower are helpful for their business success in terms of acquiring their customers. Lastly, results show that the level of SaaS technology maturity mediates the relationships between low cost strategy and customer acquisition. That is, based on our research design, customers usually perceive the real value of the low subscription fee or initial set-up fee only through the SaaS service provide by vender and, in turn, this will affect their decision making whether subscribe or not.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.448-454
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• 2020

This study aims to determine the cause of structural defects occurring during aircraft operations and to verify the structural integrity of the improved features. The fracture plane was analyzed to verify the characteristics of the cracks and the fatigue failure leading to the final fracture was determined by the progress of the cracks by the repeated load. During aircraft operations, the comparative analysis of the load measurement data at the cracks with the aircraft design load determined that the measured load was not at the level of 30% of the design to be capable of being damaged. A gap analysis resulted in a significant stress of approximately 32 ksi at the crack site. Pre-Load testing also confirmed that the M.S. was reduced by more than 50% from +0.71 to +0.43, resulting in a sharp increase in aircraft load and the possibility of cracking when combined. Thus, structural reinforcement and the removal of the gap for aircraft cracking sites improved the defect. Based on the structural strength analysis of the improvement features, the bulkhead has a margin of about +0.88 and the fitting feature is about +0.48 versus allowable stress. In addition, the life analysis results revealed an improvement of approximately 84000 hours.

• Korean Journal of Soil Science and Fertilizer
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• v.47 no.6
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• pp.457-463
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• 2014

This study was carried out to find out major factors to mitigate carbon emission using Life Cycle Assessment (LCA). System boundary of LCA was confined from sowing to packaging during vegetable production. Input amount of agri-materials was calculated on 2007 Income reference of white radish, chinese cabbage and chive produced at open field and film house published by Rural Development Administration. Domestic data and Ecoinvent data were used for emission factors of each agri-material based on the 1996 IPCC guideline. Carbon footprint of white radish was 0.19 kg $CO_2kg^{-1}$ at open fields, 0.133 kg $CO_2kg^{-1}$ at film house, that of chinese cabbage was 0.22 kg $CO_2kg^{-1}$ at open fields, 0.19 kg $CO_2kg^{-1}$ at film house, and that of chive was 0.66 kg $CO_2kg^{-1}$ at open fields and 1.04 kg $CO_2kg^{-1}$ at film house. The high carbon footprint of chive was related to lower vegetable production and higher fuel usage as compared to white radish and Chinese cabbage. The mean proportion of carbon emission was 35.7% during the manufacturing byproduct fertilizer; white radish at open fields was 50.6%, white radish at film house 13.1%, Chinese cabbage at outdoor 38.4%, Chinese cabbage at film house 34.0%, chive at outdoor 50.6%, and chive at film house 36.0%. Carbon emission, on average, for the step of manufacturing and combustion accounted for 16.1% of the total emission; white radish at open fields was 4.3%, white radish at film house 15.6%, Chinese cabbage at open fields 6.9%, Chinese cabbage at film house 19.0%, chive at open fields 12.5%, and chive at film house 29.1%. On the while, mean proportion of carbon footprint for the step of $N_2O$ emission was 29.2%; white radish at open fields was 39.2%, white radish at film house 41.9%, Chinese cabbage at open fields 34.4%, Chinese cabbage at film house 23.1%, chive at open fields 28.8%, and chive at film house 17.1%. Fertilizer was the primary factor and fuel was the secondary factor for carbon emission among the vegetables of this study. It was suggested to use Heug-To-Ram web-service system, http://soil.rda.go.kr, for the scientific fertilization based on soil testing, and for increase of energy efficiency to produce low carbon vegetable.

• Journal of the Korea Concrete Institute
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• v.15 no.6
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• pp.820-828
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• 2003

Recent research has indicated that the current ACI shear provision provides unconservative predictions for large slender beams and beams with low level of longitudinal reinforcement, and conservative results for deep beams. To modify some problems of ACI shear provision, ultimate shear strength equation considering size effect and arch action to compute shear strength in high-strength concrete beams without stirrups is presented in this research. Three basic equations, namely size reduction factor, rho factor, and arch action factor, are derived from crack band model of fracture mechanics, analysis of previous some shear equations for longitudinal reinforcement ratio, and concrete strut described as linear prism in strut-tie model deep beams. Constants of basic equations are determined using statistical analysis of previous shear testing data. To verify proposed shear equation for each variable, effective depth, longitudinal reinforcement ratio, concrete compressive strength and shear span-to-depth ratio, about 300 experimental data are used and proposed shear equation is compared with ACI 318-99 code, CEB-FIP Model code, Kim &Park's equation and Zsutty's equation. The proposed shear equation is not only simpler than other shear equations, it is but also shown to be economical predictions and reasonable safety margin. Hence proposed shear strength equation is expected to be applied to practical shear design.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.489-498
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• 2012

This paper consists of two parts: In the first part, we describe our work to build hierarchical knowledge base of digital library patron's research interests and learning topics in various scholarly areas through analyzing well classified Electronic Theses and Dissertations (ETDs) of NDLTD Union catalog. Journal articles from ACM Transactions and conference web sites of computing areas also are added in the analysis to specialize computing fields. This hierarchical knowledge base would be a useful tool for many social computing and information service applications, such as personalization, recommender system, text mining, technology opportunity mining, information visualization, and so on. In the second part, we compare four grouping algorithms to select best one for our data mining researches by testing each one with the hierarchical knowledge base we described in the first part. From these two studies, we intent to show traditional verification methods for social community miming researches, based on interviewing and answering questionnaires, which are expensive, slow, and privacy threatening, can be replaced with systematic, consistent, fast, and privacy protecting methods by using our suggested hierarchical knowledge base.

• Journal of IKEEE
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• v.24 no.2
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• pp.673-676
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• 2020

In this paper, we propose a whole-body management system using ultra-low temperature cyclical cooling method combined with IT technology. The proposed system has the following characteristics. First, it minimizes maintenance costs by circulating nitrogen gas cooled by ultra-low temperature inside the controller. Secondly, based on the information measured by the temperature sensor and oxygen concentration sensor, nitrogen gas is supplied to provide safe ultra-low temperature whole-body management. Thirdly, after entering the user's height, it provides convenient, ultra-low temperature whole-body care that can be controlled using an automatic lift. Fourth, it provides an easy-to-access, easy-to-manage GUI and a manager-only web program for whole-body management system operation. The results tested by the authorized testing agency to assess the performance of the proposed system were measured in the range of ±5%, the world's highest temperature sensor accuracy, and a range of -110℃ to -150℃ greater than the world's highest whole-body management temperature range(-110℃ ~ -140℃). In addition, humidity was measured at less than 40%, the world's highest, and oxygen concentration was more than 18%, the world's highest. Therefore, the effectiveness of the methods proposed in this paper was demonstrated because they produced the same results as the world's highest levels.