• Journal of Genetic Medicine
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• v.13 no.2
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• pp.65-71
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• 2016

Cell-free nucleic acids (cf-NAs) originate in trophoblasts and are detected in the maternal plasma. Using innovative bioinformatic technologies such as next-generation sequencing, cf-NAs in the maternal plasma have been rapidly applied in prenatal genetic screening for fetal aneuploidy. Amniotic fluid is a complex and dynamic fluid that provides growth factors and protection to the fetus. In 2001, the presence of cf-NA in amniotic fluid was reported. Amniotic fluid is in direct contact with the fetus and is derived from fetal urine and maternal and fetal plasma. Therefore, these genetic materials have been suggested to reflect fetal health and provide real-time genetic information regarding fetal development. Recently, several studies evaluated the global gene expression changes of amniotic fluid cell-free RNA according to gestational age. In addition, by analyzing the transcriptome in the amniotic fluid of fetal aneuploidy, potential key pathways and novel biomarkers for fetal chromosomal aneuploidy were identified. Here, we review the current knowledge of cell-free RNA in amniotic fluid and suggest future research directions.

• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.2
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• pp.153-160
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• 2010

The widespread deterioration of concrete structures has required the development of new and innovative materials and technologies for strengthening and repair. Recently Fiber reinforced polymer(FRP) composites have received widespread attention as materials for the strengthening and repair of the deteriorated concrete structures. This paper presents the results of Fire-performance of RC beams strengthened with FRP-Aluminum composit hollow beams. Test results show that the higher-damaged FRP strengthened RC beams are more vulnerable to the fire and decrease the effect of FRP strenthening.

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.211-232
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• 2007

In this paper we investigate some issues and solutions related to the design of a Data Warehouse (DW), storing several aggregate measures about trajectories of moving objects. First we discuss the loading phase of our DW which has to deal with overwhelming streams of trajectory observations, possibly produced at different rates, and arriving in an unpredictable and unbounded way. Then, we focus on the measure presence, the most complex measure stored in our DW. Such a measure returns the number of distinct trajectories that lie in a spatial region during a given temporal interval. We devise a novel way to compute an approximate, but very accurate, presence aggregate function, which algebraically combines a bounded amount of measures stored in the base cells of the data cube. We conducted many experiments to show the effectiveness of our method to compute such an aggregate function. In addition, the feasibility of our innovative trajectory DW was validated with an implementation based on Oracle. We investigated the most challenging issues in realizing our trajectory DW using standard DW technologies: namely, the preprocessing and loading phase, and the aggregation functions to support OLAP operations.

• Smart Structures and Systems
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• v.2 no.2
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• pp.189-208
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• 2006

Monitoring large-scale civil engineering structures such as offshore platforms and high-large buildings requires a large number of sensors of different types. Innovative sensor data information technologies are very extremely important for data transmission, storage and retrieval of large volume sensor data generated from large sensor networks. How to obtain the optimal sensor set and placement is more and more concerned by researchers in vibration-based SHM. In this paper, a method of determining the sensor location which aims to extract the dynamic parameter effectively is presented. The method selects the number and place of sensor being installed on or in structure by through the tolerance domain statistical inference algorithm combined with second order sensitivity technology. The method proposal first finds and determines the sub-set sensors from the theoretic measure point derived from analytical model by the statistical tolerance domain procedure under the principle of modal effective independence. The second step is to judge whether the sorted out measured point set has sensitive to the dynamic change of structure by utilizing second order characteristic value sensitivity analysis. A 76-high-building benchmark mode and an offshore platform structure sensor optimal selection are demonstrated and result shows that the method is available and feasible.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.4
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• pp.43-50
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• 2006

The objective of this research is to select the most effective technique from AMT (Advanced Manufacturing Technologies) and IMP (Innovative Management Practices) for improving manufacturing performance in shipbuilding enterprises. The research consists of several principal steps. The first step is to design critical criteria in evaluating manufacturing performance in shipbuilding enterprises. The second step is to develop sub-criteria of the critical criteria. The third step is to develop a four level AHP (Analytic Hierarchy Process) structure using the critical criteria, sub-criteria and techniques from AMT and IMP. The fourth step is to develope the pairwise comparison matrix by each level of AHP structure, which was based on survey data collected at the H heavy industry. And the last step is to select the most effective technique from AMT and IMP by using AHP analysis. The results of AHP analysis did not show clear difference in priority between techniques of AMT and IMP in terms of manufacturing performance of the shipbuilding enterprise. Thus, each critical criterion was assigned modified weights and examined the priority change of techniques by conducting performance sensitivity analysis.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.475-487
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• 2020

The paper aims to facilitate a discussion around how big data technologies and data from citizens can be used to help public administration, society, and policy-making to improve community's lives. This paper discusses opportunities and challenges of big data strategies for government, society, and policy-making. It employs the presentation of numerous practical examples from different parts of the world, where public-service delivery has seen transformation and where initiatives have been taken forward that have revolutionized the way governments at different levels engage with the citizens, and how governments and civil society have adopted evidence-driven policy-making through innovative and efficient use of big data analytics. The examples include the governments of the United States, China, the United Kingdom, and India, and different levels of government agencies in the public services of fraud detection, financial market analysis, healthcare and public health, government oversight, education, crime fighting, environmental protection, energy exploration, agriculture, weather forecasting, and ecosystem management. The examples also include smart cities in Korea, China, Japan, India, Canada, Singapore, the United Kingdom, and the European Union. This paper makes some recommendations about how big data strategies transform the government and public services to become more citizen-centric, responsive, accountable and transparent.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.240-247
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• 2021

As competition among companies has intensified and the life cycle of products has been shortened, strong innovation is needed to meet consumers' needs. In addition, it is necessary to shorten the life cycle of the product and reduce the time required for technology development for the competitive advantage of the product. In particular, venture companies where new technologies and ideas are important require more innovative capabilities than others companies. Therefore, this study analyzed the impact of technology innovation capabilities (product development process capability, human resource capability and financial capability) on sales by technology development for small and medium venture companies and analyzed moderating effect of technology development period on the relationship between technology innovation capabilities and sales by technology development. The data of 'Small and Medium Business Technology Statistics' collected by the government every year were used for analysis. Technology-intensive ventures were extracted from this data. In addition, the moderating effect was analyzed through hierarchical regression analysis. This study shows that product planning capability, test capability, and R&D expenditure have a positive impact on sales by technology development. In this study, the product development period showed a positive moderating effect on product development capability and sales performance. On the other hand, the product development period showed a negative moderating effect on R&D expenditure and sales by technology development.

• Clinical Endoscopy
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• v.51 no.6
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• pp.527-533
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• 2018

There have been many advances in endoscopic imaging technologies. Magnifying endoscopy with narrow-band imaging is an innovative optical technology that enables the precise discrimination of structural changes on the mucosal surface. Several studies have demonstrated its usefulness and superiority for tumor detection and differential diagnosis in the stomach as compared with conventional endoscopy. Furthermore, magnifying endoscopy with narrow-band imaging has the potential to predict the invasion depth and tumor margins during gastric endoscopic submucosal dissection. Classifications of the findings of magnifying endoscopy with narrow-band imaging based on microvascular and pit patterns have been proposed and have shown excellent correlations with invasion depth confirmed by microscopy. In terms of tumor margin prediction, magnifying endoscopy with narrow-band imaging offers superior delineation of gastric tumor margins compared with traditional chromoendoscopy with indigo carmine. The limitations of narrow-band imaging, such as the need for considerable training, long procedure time, and lack of studies about its usefulness in undifferentiated cancer, should be resolved to confirm its value as a complementary method to endoscopic submucosal dissection. However, the role of magnifying endoscopy with narrow-band imaging is expected to increase steadily with the increasing use of endoscopic submucosal dissection for the treatment of gastric tumors.

• Journal of the Korean Electrochemical Society
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• v.21 no.4
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• pp.68-79
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• 2018

Currently, hybridization of energy generator and storage devices is considered to be one of the most important energy-related technologies due to the possibility of replacing batteries or extending the lifetime of a batteries in accordance with increasing battery demand. This review aims to describe current progress on the mechanical energy generator and hybridization of energy generator and energy storage devices for self-powered electronics. First, the research trends related to energy generation devices using piezoelectric and triboelectric effect that convert physical energy into electric energy is introduced. In addition, integration of energy generators and energy storage devices is introduced. In particular, self-charging energy cells provide an innovative approach to the direct conversion of mechanical energy into electrochemical energy to decrease energy conversion loss.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.3
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• pp.349-360
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• 2019

This study analyzes the trends of recommendation services for customized fashion styles in relation to artificial intelligence. To achieve this goal, the study examined filtering technologies of collaborative, content based, and deep-learning as well as analyzed the characteristics of recommendation services in the users' purchasing process. The results of this study showed that the most universal recommendation technology is collaborative filtering. Collaborative filtering was shown to allow intuitive searching of similar fashion styles in the cognition of need stage, and appeared to be useful in comparing prices but not suitable for innovative customers who pursue early trends. Second, content based filtering was shown to utilize body shape as a key personal profile item in order to reduce the possibility of failure when selecting sizes online, which has limits to being able to wear the product beforehand. Third, fashion style recommendations applied with deep-learning intervene with all user processes of buying products online that was also confirmed to penetrate into the creative area of image tag services, virtual reality services, clothes wearing fit evaluation services, and individually customized design services.