• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.15-40
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• 2020

Due to the explosive growth of mobile application services, categorizing mobile application services is in need in practice from both customers' and developers' perspectives. Despite the fact, however, there have been limited studies regarding systematic categorization of mobile application services. In response, this study proposed a method for categorizing mobile application services, and suggested a service taxonomy based on the network clustering results. Total of 1,607 mobile healthcare services are collected through the Google Play store. The network analysis is conducted based on the similarity of descriptions in each application service. Modularity detection analysis is conducted to detects communities in the network, and service taxonomy is derived based on each cluster. This study is expected to provide a systematic approach to the service categorization, which is helpful to both customers who want to navigate mobile application service in a systematic manner and developers who desire to analyze the trend of mobile application services.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1175-1182
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• 2017

Recent trend in the manufacturing industry is focused on the convergence with IoT and Big Data, by emergence of the 4th Industrial Revolution. To realize a smart factory, the proposed system based on MTConnect technology collects and integrates various status information of machines from many production facilities including heterogeneous devices. Also it can distribute the acquisited status of heterogeneous manufacturing machines to the remote devices. As a key technology of a flexible automated production line, the proposed system can provide much possibility to manage important information such as error detection and processing state management in the unmanned automation line.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.1-9
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• 2016

In accordance with the increased political and social utilization of social media, demands on online trend analysis and monitoring technologies based on social bigdata are also increasing rapidly. In this paper, we define 'risk' as issues which have probability of turn to negative public opinion among big social issues and classify their types in details. To define risk types, we conduct a complete survey on news documents and analyzed characteristics according to issue domains. We also investigate cross-medias analysis to find out how different public media and personalized social media. At the result, we define 58 risk types for 6 domains and developed automatic classification model based on machine learning algorithm. Based on empirical experiments, we prove the possibility of automatic detection for social issue risk in social media.

• Strategy21
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• s.34
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• pp.178-206
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• 2014

The battlefield environment in the maritime has been changed by advanced IT technology, variation of naval warfare condition, and developed military science and technology. In addition, state-of-the-art surface combatants has become to multi-purpose battleship that is heavily armed in order to meet actively in composed future sea battlefield condition and perform multi-purpose missions as well as having capability of strategic strike. To maximize the combat strength and survivability of ship, it is not only possible for Zumwalt(DDG-1000) class combatant to conduct multi-purpose mission with advanced weapon system installation, innovative hull form and upper structure such as deckhouse, shipboard high-powered sensor, total ship computing environment, and integrated power control but it was designed so that can be installed with energy based weapon systems in immediate future. Zumwalt class combatant has been set a high value with enormous threatening surface battleship in the present, it seems to be expected that this ship will be restraint means during operation in the littoral. The advent of Zumwalt class battleship in the US Navy can be constructed as a powerful intention of naval strength building for preparing future warfare. It is required surface ship that can be perform multi-purpose mission when the trend of constructed surface combatants was analyzed. In addition, shipboard system has been continuously modernized to keep the optimized ship and maximize the survivability with high-powered detection and surveillance sensor as well as modularity of combat system to efficient operation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.6
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• pp.523-530
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• 2017

Laser-Induced Breakdown Spectroscopy (LIBS) which a plasma is irradiated at a specific wavelength depending on the material when a high-energy laser is irradiated, and a Raman spectroscopy which measures rotation and vibration in molecules as light-scattering phenomenon occurs, are attracting attention as a space exploration technology because of the advantages of high accuracy and real-time analysis, and the ability to perform long-range detection. In this study, the tendency of the laser spectrum according to the change of the soil component was analyzed by laser spectroscopy and the two - dimensional chemical distribution was conducted based on the trend of laser spectrum. We have also established the environment of Mars (4-7 torr) and lunar atmosphere (<1 torr) in experimental setup, to prove that it is possible to measure by difference of soil chemical composition using LIBS and Raman spectroscopy even in artificial space environment.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.637-651
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• 2011

This study presents a rule-based urban image classification method for time series analysis of changes in the vicinity of Asan-si and Cheonan-si in Chungcheongnam-do, using Landsat satellite images (1991-2006). The area has been highly developed through the relocation of industrial facilities, land development, construction of a high-speed railroad, and an extension of the subway. To determine the yearly changing pattern of the urban area, eleven classes were made depending on the trend of development. An algorithm was generalized for the rules to be applied as an unsupervised classification, without the need of training area. The analysis results show that the urban zone of the research area has increased by about 1.53 times, and each correlation graph confirmed the distribution of the Built Up Index (BUI) values for each class. To evaluate the rule-based classification, coverage and accuracy were assessed. When Optimal allowable factor=0.36, the coverage of the rule was 98.4%, and for the test using ground data from 1991 to 2006, overall accuracy was 99.49%. It was confirmed that the method suggested to determine the maximum allowable factor correlates to the accuracy test results using ground data. Among the multiple images, available data was used as best as possible and classification accuracy could be improved since optimal classification to suit objectives was possible. The rule-based urban image classification method is expected to be applied to time series image analyses such as thematic mapping for urban development, urban development, and monitoring of environmental changes.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.5
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• pp.496-502
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• 2016

In this study, we investigated the comparative NHPP software model based on learning techniques that operators in the process of software testing and development of software products that can be applied to software test tool. The life distribution was applied Makeham distribution based on finite fault NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is larger than automatic error that is usually well-organized model could be established. This paper, a trust characterization of applying using time among failures and parameter approximation using maximum likelihood estimation, after the effectiveness of the data through trend examination model selection were well-organized using the mean square error and $R^2$. From this paper, the software operators must be considered life distribution by the basic knowledge of the software to confirm failure modes which may be helped.

• Journal of the Korean Society for information Management
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• v.32 no.1
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• pp.153-169
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• 2015

The combined approach of using ego-centric network analysis and dynamic citation network analysis for refining the result of LDA-based topic modeling was suggested and examined in this study. Tow datasets were constructed by collecting Web of Science bibliographic records of White LED and topic modeling was performed by setting a different number of topics on each dataset. The multi-assigned top keywords of each topic were re-assigned to one specific topic by applying an ego-centric network analysis algorithm. It was found that the topical cohesion of the result of topic modeling with the number of topic corresponding to the lowest value of perplexity to the dataset extracted by SPLC network analysis was the strongest with the best values of internal clustering evaluation indices. Furthermore, it demonstrates the possibility of developing the suggested approach as a method of multi-faceted research trend detection.

• Smart Structures and Systems
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• v.3 no.3
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• pp.341-356
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• 2007

A good understanding of normal modal variability of civil structures due to varying environmental conditions such as temperature and wind is important for reliable performance of vibration-based damage detection methods. This paper addresses the quantification of wind-induced modal variability of a cable-stayed bridge making use of one-year monitoring data. In order to discriminate the wind-induced modal variability from the temperature-induced modal variability, the one-year monitoring data are divided into two sets: the first set includes the data obtained under weak wind conditions (hourly-average wind speed less than 2 m/s) during all four seasons, and the second set includes the data obtained under both weak and strong (typhoon) wind conditions during the summer only. The measured modal frequencies and temperatures of the bridge obtained from the first set of data are used to formulate temperature-frequency correlation models by means of artificial neural network technique. Before the second set of data is utilized to quantify the wind-induced modal variability, the effect of temperature on the measured modal frequencies is first eliminated by normalizing these modal frequencies to a reference temperature with the use of the temperature-frequency correlation models. Then the wind-induced modal variability is quantitatively evaluated by correlating the normalized modal frequencies for each mode with the wind speed measurement data. It is revealed that in contrast to the dependence of modal frequencies on temperature, there is no explicit correlation between the modal frequencies and wind intensity. For most of the measured modes, the modal frequencies exhibit a slightly increasing trend with the increase of wind speed in statistical sense. The relative variation of the modal frequencies arising from wind effect (with the maximum hourly-average wind speed up to 17.6 m/s) is estimated to range from 1.61% to 7.87% for the measured 8 modes of the bridge, being notably less than the modal variability caused by temperature effect.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.22
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• pp.9899-9903
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• 2014

Nasopharyngeal carcinoma (NPC) is an uncommon disease in most countries but occurs with much greater frequency in southern China. This study aimed to examine the secular trends of NPC in urban Guangzhou over the time period of 2000-2011 using data from the Guangzhou Cancer Registry. Age-adjusted annual incidence rates of NPC were calculated by the direct method using the WHO World Standard Population (1960) as the reference. The average annual percentage change (AAPC) was used as an estimate of the trend. A total of 7,532 new cases of NPC and 3,449 related deaths were registered. In both genders, the peak incidence occurred in the 50- to 59-year age group, and this age distribution pattern remained similar throughout. The AAPC in NPC incidence rates was -3.26% (95% CI: -5.4%--1.1) for males and -5.74% (95% CI: -8.9%--2.5) for females, resulting in a total decrease of 39.3% (from 22.14 to 13.44 per 100,000 population) for males and 48.6% (from 10.1 to 5.18 per 100,000 population) for females over this 12-year period. The AAPCs in NPC mortality rates were -4.62% (95%CI: -3.5%--5.7) for males and -6.75% (95% CI: -5.2%--8.3) for females, resulting in a total decrease of -46.1% (from 12.1 to 6.54 per 100,000 population) for males and 51.7% (from 4.14 to 2.00 per 100,000 population) for females. The age-adjusted incidence and mortality rates of NPC declined during 2000-2011 in urban Guangzhou but remained high. Future efforts to improve prevention, early detection and treatment strategies are needed.