• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Journal of Korea Spatial Information System Society
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• v.6 no.1 s.11
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• pp.73-85
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• 2004

Recently, as the growth of the wireless Internet, PDA and HPC, the focus of research and development related with GIS(Geographic Information System) has been changed to the Real-Time Mobile GIS to service LBS. To offer LBS efficiently, there must be the Real-Time GIS platform that can deal with dynamic status of moving objects and a location index which can deal with the characteristics of location data. Location data can use the same data type(e.g., point) of GIS, but the management of location data is very different. Therefore, in this paper, we studied the Real-Time Mobile GIS using the HBR-tree to manage mass of location data efficiently. The Real-Time Mobile GIS which is developed in this paper consists of the HBR-tree and the Real-Time GIS Platform HBR-tree. we proposed in this paper, is a combined index type of the R-tree and the spatial hash Although location data are updated frequently, update operations are done within the same hash table in the HBR-tree, so it costs less than other tree-based indexes Since the HBR-tree uses the same search mechanism of the R-tree, it is possible to search location data quickly. The Real-Time GIS platform consists of a Real-Time GIS engine that is extended from a main memory database system. a middleware which can transfer spatial, aspatial data to clients and receive location data from clients, and a mobile client which operates on the mobile devices. Especially, this paper described the performance evaluation conducted with practical tests if the HBR-tree and the Real-Time GIS engine respectively.

• Journal of the Korea Concrete Institute
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• v.25 no.5
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• pp.485-496
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• 2013

In recent years, frequent terror or military attacks by explosion or impact accidents have occurred. Examplary case of these attacks were World Trade Center collapse and US Department of Defense Pentagon attack on Sept. 11 of 2001. These attacks of the civil infrastructure have induced numerous casualties and property damage, which raised public concerns and anxiety of potential terrorist attacks. However, a existing design procedure for civil infrastructures do not consider a protective design for extreme loading scenario. Also, the extreme loading researches of prestressed concrete (PSC) member, which widely used for nuclear containment vessel, gas tank, bridges, and tunnel, are insufficient due to experimental limitations of loading characteristics. To protect concrete structures against extreme loading such as explosion and impact with high strain rate, understanding of the effect, characteristic, and propagation mechanism of extreme loadings on structures is needed. Therefore, in this paper, to evaluate the impact resistance capacity and its protective performance of bi-directional unbonded prestressed concrete member, impact tests were carried out on $1400mm{\times}1000mm{\times}300mm$ for reinforced concrete (RC), prestressed concrete without rebar (PS), prestressed concrete with rebar (PSR, general PSC) specimens. According to test site conditions, impact tests were performed with 14 kN impactor with drop height of 10 m, 5 m, 4 m for preliminary tests and 3.5 m for main tests. Also, in this study, the procedure, layout, and measurement system of impact tests were established. The impact resistance capacity was measured using crack patterns, damage rates, measuring value such as displacement, acceleration, and residual structural strength. The results can be used as basic research references for related research areas, which include protective design and impact numerical simulation under impact loading.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.7
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• pp.906-913
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• 2019

To evaluate the removal performance of PO₄-P and NH₃-N, laboratory experiments were conducted by filling a container with oyster shells, pyrolyzed at 100℃ (POS100), 600℃ (POS600) and 800℃ (POS800), and passing artificial wastewaters through the container. The pH in the ef luent was found to increase due to CaO eluted from oyster shell. Removal amounts of PO₄-P of ~23.1 mg/kg, 16.1 mg/kg, and 15.9 mg/kg were obtained when POS100, POS600, and POS800, respectively, were used; therefore, the highest PO₄-P removal amount was obtained when POS100 was used. It is considered that Ca and dolomite in the oyster shells adsorbed and precipitated PO₄-P. Removal amounts of NH₃-N were of ~3.56 mg/kg, 5.72 mg/kg, and 3.97 mg/kg were obtained when POS100, POS600, and POS800, respectively, were used The low removal rate for NH₃-N is probably due to unstable nitrification, use of sealed containers, and the effect of NH₃-N being converted to NH₄⁺ upon increasing pH. Based on these results, pyrolyzed oyster shell is expected to promote changes in PO₄-P and NH₃-N concentrations through chemical reactions. These results can also be used for basic research in the development of wastewater treatment.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.117-140
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• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

• Asia pacific journal of information systems
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• v.20 no.2
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• pp.63-86
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• 2010

Personalized services directly and indirectly acquire personal data, in part, to provide customers with higher-value services that are specifically context-relevant (such as place and time). Information technologies continue to mature and develop, providing greatly improved performance. Sensory networks and intelligent software can now obtain context data, and that is the cornerstone for providing personalized, context-specific services. Yet, the danger of overflowing personal information is increasing because the data retrieved by the sensors usually contains privacy information. Various technical characteristics of context-aware applications have more troubling implications for information privacy. In parallel with increasing use of context for service personalization, information privacy concerns have also increased such as an unrestricted availability of context information. Those privacy concerns are consistently regarded as a critical issue facing context-aware personalized service success. The entire field of information privacy is growing as an important area of research, with many new definitions and terminologies, because of a need for a better understanding of information privacy concepts. Especially, it requires that the factors of information privacy should be revised according to the characteristics of new technologies. However, previous information privacy factors of context-aware applications have at least two shortcomings. First, there has been little overview of the technology characteristics of context-aware computing. Existing studies have only focused on a small subset of the technical characteristics of context-aware computing. Therefore, there has not been a mutually exclusive set of factors that uniquely and completely describe information privacy on context-aware applications. Second, user survey has been widely used to identify factors of information privacy in most studies despite the limitation of users' knowledge and experiences about context-aware computing technology. To date, since context-aware services have not been widely deployed on a commercial scale yet, only very few people have prior experiences with context-aware personalized services. It is difficult to build users' knowledge about context-aware technology even by increasing their understanding in various ways: scenarios, pictures, flash animation, etc. Nevertheless, conducting a survey, assuming that the participants have sufficient experience or understanding about the technologies shown in the survey, may not be absolutely valid. Moreover, some surveys are based solely on simplifying and hence unrealistic assumptions (e.g., they only consider location information as a context data). A better understanding of information privacy concern in context-aware personalized services is highly needed. Hence, the purpose of this paper is to identify a generic set of factors for elemental information privacy concern in context-aware personalized services and to develop a rank-order list of information privacy concern factors. We consider overall technology characteristics to establish a mutually exclusive set of factors. A Delphi survey, a rigorous data collection method, was deployed to obtain a reliable opinion from the experts and to produce a rank-order list. It, therefore, lends itself well to obtaining a set of universal factors of information privacy concern and its priority. An international panel of researchers and practitioners who have the expertise in privacy and context-aware system fields were involved in our research. Delphi rounds formatting will faithfully follow the procedure for the Delphi study proposed by Okoli and Pawlowski. This will involve three general rounds: (1) brainstorming for important factors; (2) narrowing down the original list to the most important ones; and (3) ranking the list of important factors. For this round only, experts were treated as individuals, not panels. Adapted from Okoli and Pawlowski, we outlined the process of administrating the study. We performed three rounds. In the first and second rounds of the Delphi questionnaire, we gathered a set of exclusive factors for information privacy concern in context-aware personalized services. The respondents were asked to provide at least five main factors for the most appropriate understanding of the information privacy concern in the first round. To do so, some of the main factors found in the literature were presented to the participants. The second round of the questionnaire discussed the main factor provided in the first round, fleshed out with relevant sub-factors. Respondents were then requested to evaluate each sub factor's suitability against the corresponding main factors to determine the final sub-factors from the candidate factors. The sub-factors were found from the literature survey. Final factors selected by over 50% of experts. In the third round, a list of factors with corresponding questions was provided, and the respondents were requested to assess the importance of each main factor and its corresponding sub factors. Finally, we calculated the mean rank of each item to make a final result. While analyzing the data, we focused on group consensus rather than individual insistence. To do so, a concordance analysis, which measures the consistency of the experts' responses over successive rounds of the Delphi, was adopted during the survey process. As a result, experts reported that context data collection and high identifiable level of identical data are the most important factor in the main factors and sub factors, respectively. Additional important sub-factors included diverse types of context data collected, tracking and recording functionalities, and embedded and disappeared sensor devices. The average score of each factor is very useful for future context-aware personalized service development in the view of the information privacy. The final factors have the following differences comparing to those proposed in other studies. First, the concern factors differ from existing studies, which are based on privacy issues that may occur during the lifecycle of acquired user information. However, our study helped to clarify these sometimes vague issues by determining which privacy concern issues are viable based on specific technical characteristics in context-aware personalized services. Since a context-aware service differs in its technical characteristics compared to other services, we selected specific characteristics that had a higher potential to increase user's privacy concerns. Secondly, this study considered privacy issues in terms of service delivery and display that were almost overlooked in existing studies by introducing IPOS as the factor division. Lastly, in each factor, it correlated the level of importance with professionals' opinions as to what extent users have privacy concerns. The reason that it did not select the traditional method questionnaire at that time is that context-aware personalized service considered the absolute lack in understanding and experience of users with new technology. For understanding users' privacy concerns, professionals in the Delphi questionnaire process selected context data collection, tracking and recording, and sensory network as the most important factors among technological characteristics of context-aware personalized services. In the creation of a context-aware personalized services, this study demonstrates the importance and relevance of determining an optimal methodology, and which technologies and in what sequence are needed, to acquire what types of users' context information. Most studies focus on which services and systems should be provided and developed by utilizing context information on the supposition, along with the development of context-aware technology. However, the results in this study show that, in terms of users' privacy, it is necessary to pay greater attention to the activities that acquire context information. To inspect the results in the evaluation of sub factor, additional studies would be necessary for approaches on reducing users' privacy concerns toward technological characteristics such as highly identifiable level of identical data, diverse types of context data collected, tracking and recording functionality, embedded and disappearing sensor devices. The factor ranked the next highest level of importance after input is a context-aware service delivery that is related to output. The results show that delivery and display showing services to users in a context-aware personalized services toward the anywhere-anytime-any device concept have been regarded as even more important than in previous computing environment. Considering the concern factors to develop context aware personalized services will help to increase service success rate and hopefully user acceptance for those services. Our future work will be to adopt these factors for qualifying context aware service development projects such as u-city development projects in terms of service quality and hence user acceptance.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1615-1633
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• 2023

Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.6
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• pp.453-458
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• 2001

The Rural Development Administration (RDA) of Korea now operates a system called Rice Variety Selection Tests (RVST), which are now being implemented in eight Agricultural Research and Extension Services located in eight province RVST's objective is to provide accurate yield estimates and to select well-adapted varieties to each province. Systematic evaluation of entries included in RVST is a highly important task to select the best-adapted varieties to specific location and to observe the performance of entries across a wide range of test sites within a region. The rice yield data in RVST for ordinary transplanting in Kangwon province during 1997-2000 were analyzed. The experiments were carried out in three replications of a random complete block design with eleven entries across five locations. Additive Main effects and Multiplicative Interaction (AMMI) model was employed to examine the interaction between genotype and environment (G$\times$E) in the biplot form. It was found that genotype variability was as high as 66％, followed by G$\times$E interaction variability, 21％, and variability by environment, 13％. G$\times$E interaction was partitioned into two significant (P＜0.05) principal components. Pattern analysis was used for interpretation on G$\times$E interaction and adaptibility. Major determinants among the meteorological factors on G$\times$E matrix were canopy minimum temperature, minimum relative humidity, sunshine hours, precipitation and mean cloud amount. Odaebyeo, Obongbyeo and Jinbubyeo were relatively stable varieties in all the regions. Furthermore, the most adapted varieties in each region, in terms of productivity, were evaluated.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5A
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• pp.407-415
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• 2010

In Korea, more than 90% of the total number of steel bridges built for 40~70 m span length is a steel box-girder bridge type. A steel box-girder bridge is suitable for long span or curved bridges with outstanding flexural and torsional rigidity as well as good constructability and safety. However, a steel box-girder bridge is uneconomical, requiring many secondary members and workmanship such as stiffeners and ribs requiring welding attachments to flanges or webs. Therefore, in US and Japan, a plate girder bridge, which is relatively cheap and easy to construct is generally used. One type of the plate girder bridge is the two- or three-main girder plate bridge, which is a composite plate girder bridge that minimizes the number of required main girders by increasing the distance between the adjacent girders. Also, for the simplification of girder section, the stiffener which requires attachment to the web is not required. The two-main steel girder plate bridge is a representative type of plate girder bridges, which is suitable for bridges with 10 m effective width and has been developed in the early 1960s in France. To ensure greater safety of two- or three-main girder plate bridges, a larger steel section is used in the bridge domestically than in Europe or Japan. Also, the total number of two- or three-main girder plate bridge constructed in Korea is significantly less than the steel box girder bridge due to a lack of designers' familiarity with more complex design detailing of the bridge compare to that of a steel box girder bridge design. In this study, a new construction method called Turn Over method is proposed to minimize the steel section size used in a two- or three-main girder plate bridge by applying prestressing force to the member using confining concrete section's weight to reduce construction cost. Also, a full scale 20 m Turn Over girder specimen and a Turn Over girder bridge specimen were tested to evaluate constructability and structural safety of the members constructed using Turn Over process.