• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.163-171
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• 2022

This study was conducted to understand the research trends and central concepts of middle-aged women' health in Korea. For the analysis of this study, target papers published from 2012 to 2021 were collected by entering the keywords of 'middle-aged woman' or 'menopausal woman'. 1,116 papers were used for analysis. The co-occurrence network of key words was developed and analyzed, and the research trends were analyzed through topic modeling of the LSD by dividing it into five-year units (2012-2016, 2017-2021), and visualized word cloud and sociogram were used. The keywords that appeared the most during the last 10 years were obesity, depression, body composition, stress, and menopause symptom. Five topics analyzed in the thesis data for 5 years from 2012 to 2016 were 'postmenopausal self-efficacy and satisfaction enhancement strategy', 'exercise to manage obesity and risk factors', 'intervention for obesity and stress', 'promotion of happiness and life management' and 'menopausal depression and quality of life' were confirmed. Five topics of research conducted for the next five years (2017-2021) were 'menopausal depression and quality of life', 'management of obesity and cardiovascular risk factors', 'life experience as a middle-aged woman', and 'life satisfaction and psychological well-being' and 'menopausal symptom relief strategy'. Through the results, the trend of research topics related to middle-aged women's health over the past 10 years have been identified, and research on health of middle-aged women that reflects the trend of the future should be continued.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6B
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• pp.551-560
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• 2009

This paper describes a newly developed pollutant transport model named ARPTM which was designed to simulate the transport and characteristics of pollutant materials after an accidental spill in upstream of river system up to a given position in the downstream. In particular, the ARPTM incorporated ADCP data to compute longitudinal dispersion coefficient and advection velocity which are necessary to apply one-dimensional advection-dispersion equation. ARPTM was built on top of the geographic information system platforms to take advantage of the technology's capabilities to track geo-referenced processes and visualize the simulated results in conjunction with associated geographic layers such as digital maps. The ARPTM computes travel distance, time, and concentration of the pollutant cloud in the given flow path from the river network, after quickly finding path between the spill of the pollutant material and any concerned points in the downstream. ARPTM is closely connected with a recently developed GIS-based Arc River database that stores inputs and outputs of ARPTM. ARPTM thereby assembles measurements, modeling, and cyberinfrastructure components to create a useful cyber-tool for determining and visualizing the dynamics of the clouds of pollutants while dispersing in space and time. ARPTM is expected to be potentially used for building warning system for the transport of pollutant materials in a large basin.

• Information Systems Review
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• v.26 no.2
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• pp.155-167
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• 2024

This study recognized the importance of joint research in the field of artificial intelligence and analyzed the characteristics of the industry-academic-research technological cooperation ecosystem focusing on patents from the perspective of the Techno-Economic Segment (TES). To this end, economic entities such as companies, universities, and research institutes within the ecosystem were identified for 7,062 joint research projects out of 113,289 artificial intelligence patents over the past 10 years filed in IP5 countries since 2012. Next, this study identified the topics of technological cooperation and the characteristics of cooperation. As a result of the analysis, technological cooperation is increasing, and the frequency of all types of cooperation was high in industry-to-industry (40%) and industry-to-university (25.2%) relationships. Here, this study confirmed that the role of universities is being strengthened, with an increase in the ratio of companies with strengths in funding and analytical data, industry and universities with excellent research personnel (9.8%), and cooperation between universities (1.9%). In addition, as a result of identifying collaborative patent research areas of interest and collaborative relationships through topic modeling and network analysis, overall similar research interests were derived regardless of the type of cooperation, and applications such as autonomous driving, edge computing, cloud, marketing, and consumer behavior analysis were derived. It was confirmed that the scope of research was expanding, collaborating entities were becoming more diverse, and a large-scale network including Chinese-centered universities was emerging.

• Journal of the Korean Applied Science and Technology
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• v.37 no.3
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• pp.473-483
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• 2020

This paper proposes a tourism recommendation system in intelligent cloud environment using information of tourist behavior applied with perceived value. This proposed system applied tourist information and empirical analysis information that reflected the perceptual value of tourists in their behavior to the tourism recommendation system using wide and deep learning technology. This proposal system was applied to the tourism recommendation system by collecting and analyzing various tourist information that can be collected and analyzing the values that tourists were usually aware of and the intentions of people's behavior. It provides empirical information by analyzing and mapping the association of tourism information, perceived value and behavior to tourism platforms in various fields that have been used. In addition, the tourism recommendation system using wide and deep learning technology, which can achieve both memorization and generalization in one model by learning linear model components and neural only components together, and the method of pipeline operation was presented. As a result of applying wide and deep learning model, the recommendation system presented in this paper showed that the app subscription rate on the visiting page of the tourism-related app store increased by 3.9% compared to the control group, and the other 1% group applied a model using only the same variables and only the deep side of the neural network structure, resulting in a 1% increase in subscription rate compared to the model using only the deep side. In addition, by measuring the area (AUC) below the receiver operating characteristic curve for the dataset, offline AUC was also derived that the wide-and-deep learning model was somewhat higher, but more influential in online traffic.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.61.2-61.2
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• 2015

15P/Finlay is one of the Jupiter-Family Comets that has long been known since the late 19 century. The comet maintains the perihelion around 1.0 AU over a century, without showing any prominent activities (i.e. fragmentation or eruption) since the discovery. According to reports in unpublished observations, the comet exhibited an outburst in the middle of 2014 December. We conducted a imaging observation of 15P/Finlay just after the report, from 2014 December 23 to 2015 February 18 using three telescopes (the Okayama Astrophysical Observatory 50-cm telescope, the Ishigakijima Astronomical Observatory 105-cm telescope, and the Nishi-Harima Astronomical Observatory 2-m telescope), which constitute a portion of the OISTER (an inter-university observation network in the optical and infrared wavelengths). As a result of the frequent observations, we witnesses the second outburst around UT 2015 January 16. Such cometary outbursts draw the attention to researchers on ground that they could offer insight into the internal structure of comets, following a historical outburst occurred at 17P/Holmes on 2007 October 23. Although cometary outbursts have been often reported mostly in unpublished observations or unreviewed reports, it should be emphasized that there are not a sufficient number of astrophysical research which characterizes the physical properties by observing the aftermaths. This presentation provides a new observational result of 15P/Finlay outburst. Based on the morphological development of the dust cloud as well as the near-nuclear magnitude, we will derive the kinetic energy of the outburst. Finally we plan to compare the results of 15P/Finlay with those of analogical events at 17P/Holmes and P/2010 V1 (Ikeya-Murakami).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.87-97
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• 2018

The traffic accident reports that are generated by the Traffic Broadcasting Networks(TBN) are unstructured data. It, however, has the value as some sort of real-time traffic information generated by the viewpoint of the drives and/or pedestrians that were on the roads, the time and spots, not the offender or the victim who caused the traffic accidents. However, the traffic accident reports, which are big data, were not applied to traffic accident analysis and traffic related research commonly. This study adopting text-mining technique was able to provide a clue for utilizing it for the impacts of traffic accidents. Seven years of traffic reports were grasped by this analysis. By analyzing the reports, it was possible to identify the road names, accident spot names, time, and to identify factors that have the greatest influence on other drivers due to traffic accidents. Authors plan to combine unstructured accident data with traffic reports for further study.

• Journal of The Korean Astronomical Society
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• v.36 no.spc1
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• pp.83-91
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• 2003

There are terrestrial signatures of the solar activity cycle in ice core data (Ram & Stoltz 1999), but the variations in the sun's irradiance over the cycle seem too small to account for the signature (Lean 1997; Goode & Dziembowski 2003). Thus, one would expect that the signature must arise from an indirect effect(s) of solar activity. Such an indirect effect would be expected to manifest itself in the earth's reflectance. Further, the earth's climate depends directly on the albedo. Continuous observations of the earthshine have been carried out from Big Bear Solar Observatory since December 1998, with some more sporadic measurements made during the years 1994 and 1995. We have determined the annual albedos both from our observations and from simulations utilizing the Earth Radiation Budget Experiment (ERBE) scene model and various datasets for the cloud cover, as well as snow and ice cover. With these, we look for inter-annual and longer-term changes in the earth's total reflectance, or Bond albedo. We find that both our observations and simulations indicate that the albedo was significantly higher during 1994-1995 (activity minimum) than for the more recent period covering 1999-2001 (activity maximum). However, the sizes of the changes seem somewhat discrepant. Possible indirect solar influences on the earth's Bond albedo are discussed to emphasize that our earthshine data are already sufficiently precise to detect, if they occur, any meaningful changes in the earth's reflectance. Still greater precision will occur as we expand our single site observations to a global network.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.309-315
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• 2012

The dissemination of smartphones is being spread and supplementary services using smartphones are increasing and various as the Mobile network and device are developing rapidly, so smartphones that enables to provide a wide range of services is expected to receive the most attention. It makes users listen to music anytime, anywhere in real-time, use useful applications, and access to Internet to search for information. The service environment is changing on PC into Mobile due to the change of the circumstance mentioned above. these services are done by using just location information rather than other context, and users have to search services and use them. It is essential to have Context-aware technology for personalization recommendation services and the appropriate representation and definition of Context information for context-aware. Ontology is possible to represent knowledge freely and knowledge can be extended by inferring. In addition, design of the ontology model is needed according to the purposes of utilization. This paper used context-aware technologies to implement a user personalization recommendation service. It also defined the context through OWL modeling for user personalization recommendation service and used inference rules and inference engine for context reasoning.

• Journal of Information Technology and Architecture
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• v.11 no.4
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• pp.449-462
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• 2014

In big data era, there are a number of considerable parts in processing systems for capturing, storing, and analyzing stored or streaming data. Unlike traditional data handling systems, a big data processing system needs to concern the characteristics (format, velocity, and volume) of being handled data in the system. In this situation, virtualized computing platform is an emerging platform for handling big data effectively, since virtualization technology enables to manage computing resources dynamically and elastically with minimum efforts. In this paper, we analyze resource utilization of virtualized computing resources to discover suitable deployment models in Apache Hadoop and HBase-based big data processing environment. Consequently, Task Tracker service shows high CPU utilization and high Disk I/O overhead during MapReduce phases. Moreover, HRegion service indicates high network resource consumption for transfer the traffic data from DataNode to Task Tracker. DataNode shows high memory resource utilization and Disk I/O overhead for reading stored data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2087-2102
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• 2011

The purpose of this study is to develop and present a strategic framework for mobile Internet marketing in the $Web^2$ environment. The $Web^2$ mobile Internet marketing is characterized by services, such as augmented reality and social network services. Considering the changes in the effects and types of advertisements in the mobile Internet, few studies of mobile advertisements have been conducted thus far in the $Web^2$ environment, including the cloud computing environment. Accordingly, this research aims to identify the relationships between importance and satisfaction and to uncover the characteristics of mobile advertisements through smart phones using the IPA (Importance-performance Analysis) methodology in the $Web^2$ environment. To induce the minimum required characteristics of a mobile advertisement in terms of the importance and satisfaction of IPA, Kano's model is applied to this analysis. The study also probes the relationships between the overall satisfaction and factors of each dimension of IPA through a regression analysis. As a result, this study presents four types of $Web^2$ mobile Internet marketing strategies. It was also confirmed that the maintenance reinforcement factors of the IPA dimension affect the degree of overall satisfaction. This study has implications for businesses and researchers preparing $Web^2$ mobile services and marketing.