• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.49-57
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• 2013

As 'Big data' has been one of challenging issues, development of new services using Social Network Service (SNS) which is its typical example became active. SNS has developed as a media where everyone communicates at real time and the number of SNS opinion analyzing services is increasing. Meanwhile, new approach to acquire and analyze twitter data becomes necessary in TV advertisement system. This paper proposes LiveAD system, which store and analyze big data such as twitter data as well as analyze TV advertising effect based on twitter data. As a proof of concept, the proposed system has been implemented collecting and analyzing twitter data using Hadoop. The result of collected information over the system increases the chance of analyzing TV advertising effect on twitter in real-time.

• Child Health Nursing Research
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• v.8 no.4
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• pp.381-390
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• 2002

This study examines the factors that are associated with accidents from riding on inline skates and/or kick boards among students in the elementary schools. Data were collected from 902 students in 3 elementary schools in Seoul. Data were analyzed based on descriptive statistics and chi-square test. The results were as follows: 1. Thirty-eight percent of the students investigated were found to have kick boards while sixty-one percent of the students had inline skates. 2. The age of mothers who answered the questionnaires showed a statistically significant association with injuries of their children on inline skates and/or kick boards. Children whose mothers are younger had a lower percentage of injuries on inline skates and/or kick boards. 3. Children with a lower score on K-CBCL had a higher chance of having an accident from riding on inline skates and/or kick boards. That is, children with lack of attention were more likely to be involved in an accident. First-born children were less likely to have an accident. 4. While mothers' attitudes toward the safety of inline skates and kick boards appeared not to be associated with accidents of their children, their preventive actions for the safety related to riding on inline skates and kick boards reduced the chance to be involved in an accident of their children. In conclusion, this study shows that mothers with children going to the elementary schools should be more action-oriented to prevent their children's accidents from riding on inline skates and/or kick boards than merely recognizing the safety of inline skates and/or kick boards on their own. Implication of these findings and major findings of this study were discussed.

• Korean Journal of Social Welfare
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• v.58 no.1
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• pp.115-141
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• 2006

The purpose of this study is to understand the changes from adopting daily two-shift roster in child care institutions. To accomplish this purpose, we collected data mainly from depth interview with managers, child care workers, and children in child care institutions adopting daily two-shift roster, and analysed these data through qualitative case study approach. The results of this study are as follows. First, child care workers take the chance of recreation, their working conditions improved, they were participated in self-development activity, and they could make relationship with persons in social network. But, some participants worried about decrease of responsibility of workers. Second, one hand, possibility of high-quality care for child is increased, on the other hand, possibility of improving attachment relationship between workers and children is decreased. some children is confused by shift. But, most important strength is that partners have complementary parenting roles through discussion about parenting skills. They have developed communication skills by trial and error, and growed with children through sharing. Third, many qualified persons have applied for institution because of improvement of working conditions, thus institutions had the chance of adopting qualified workers. These workers have various abilities and resources, could mobilize resources from community, and could progress various programs and intervene for children. But, institutions had many difficulties in process adopting daily two-shift roster because of unstable financial support and previous structure. Most of participants worried about that local government may cut down a subsidy.

• Spatial Information Research
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• v.19 no.5
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• pp.13-25
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• 2011

Until now, most of the Web GIS system has been developed with one-sided service type that provides pre-built spatial information to users. Recently, however, interactive web system is getting attention because users can create directly spatial information contents that meet their needs. In line with this trend, this study had a aim to develop a UGC(User Generated Contents) support system for marine science researchers who can generate spatial data by themselves on the web. The main advantage of this system is that it provides marine survey data and marine spatial information that needed to work for marine science research. Furthermore, it provides the functions of extracting of coastline as point data for their marine study area, and making of the spatial planning map for marine field survey work and marine science thematic maps for exploratory analysis after research survey. Such kinds of interactive UGC support system gives researchers a chance for utilizing marine spatial information more easily. Therefore, it is expected that the improving of the efficiency of research works, as well as increasing of the utilization of marine spatial data.

• Neurospine
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• v.15 no.4
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• pp.329-337
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• 2018

Objective: Machine learning algorithms excel at leveraging big data to identify complex patterns that can be used to aid in clinical decision-making. The objective of this study is to demonstrate the performance of machine learning models in predicting postoperative complications following anterior cervical discectomy and fusion (ACDF). Methods: Artificial neural network (ANN), logistic regression (LR), support vector machine (SVM), and random forest decision tree (RF) models were trained on a multicenter data set of patients undergoing ACDF to predict surgical complications based on readily available patient data. Following training, these models were compared to the predictive capability of American Society of Anesthesiologists (ASA) physical status classification. Results: A total of 20,879 patients were identified as having undergone ACDF. Following exclusion criteria, patients were divided into 14,615 patients for training and 6,264 for testing data sets. ANN and LR consistently outperformed ASA physical status classification in predicting every complication (p < 0.05). The ANN outperformed LR in predicting venous thromboembolism, wound complication, and mortality (p < 0.05). The SVM and RF models were no better than random chance at predicting any of the postoperative complications (p < 0.05). Conclusion: ANN and LR algorithms outperform ASA physical status classification for predicting individual postoperative complications. Additionally, neural networks have greater sensitivity than LR when predicting mortality and wound complications. With the growing size of medical data, the training of machine learning on these large datasets promises to improve risk prognostication, with the ability of continuously learning making them excellent tools in complex clinical scenarios.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1086-1096
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• 2004

In case of a multimedia application which deals with streaming data, in terms of cache management, cache loses its efficiency due to weak temporal locality of the data. This means that when data have been brought into cache, much of the data are supposed to be replaced without being accessed again during its service. However, there is a good chance that such multimedia data has a commanding locality in it. In this paper, to take advantage of the memory reference regularity which typically innates even in the multimedia data showing up its weak temporal locality, a method is suggested. The suggested method with the feature of dynamic regular-stride reference prefetching can identify for 2-dimensional array format(block pattern). The suggested method is named as block-reference-prediction-technique (BRPT) since it identifies a block pattern and place an address to be prefetched by the regulation of the block format. BRPT proved to be reassuring to reduce memory reference time significantly for applications having abundant block patterns although new rule has complicated the prefetching system even further.

• The Journal of Bigdata
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• v.5 no.1
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• pp.41-54
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• 2020

With the recent expansion of Internet channels and the development of financial technology and information and communication technology, direct overseas purchases have expanded. Although direct overseas purchases dominate consumers in terms of price and scarcity by providing relatively low-priced products and products that are difficult to obtain in Korea, there is a higher chance of consumer dissatisfaction in terms of delivery, product, A/S and refund than domestic purchases. Therefore, this study analyzed consumer dissatisfaction caused by active overseas direct purchase and studied ways to improve problems with overseas direct purchase. As a research method, Several statistical data were collected from the Korea Consumer Agency(KCA), the Korea Customs Service(KCS) and the Korea International Trade Association(KITA) and analyzed using the Exploratory Data Analysis Technique (EDA). The analysis confirmed that consumers were not well aware of information about direct overseas purchases and that the type or degree of consumer complaints varied depending on the type of purchase. Therefore, this study suggests a direction for the revitalization of overseas direct purchases by using EDA to identify the overall status of overseas direct purchases and consumer dissatisfaction and to improve them.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.3
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• pp.493-507
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• 2018

Due to high spatio-temporal variability of amount and optical/microphysical properties of atmospheric aerosols, satellite-based observations have been demanded for spatiotemporal monitoring the major aerosols. Observations of the heavy aerosol episodes and determination on the dominant aerosol types from a geostationary satellite can provide a chance to prepare in advance for harmful aerosol episodes as it can repeatedly monitor the temporal evolution. A new geostationary observation sensor, namely the Advanced Himawari Imager (AHI), onboard the Himawari-8 platform, has been observing high spatial and temporal images at sixteen wavelengths from 2016. Using observed spectral visible reflectance and infrared brightness temperature (BT), the algorithm to find major aerosol type such as volcanic ash (VA), desert dust (DD), polluted aerosol (PA), and clean aerosol (CA), was developed. RGB color composite image shows dusty, hazy, and cloudy area then it can be applied for comparing aerosol detection product (ADP). The CALIPSO level 2 vertical feature mask (VFM) data and MODIS level 2 aerosol product are used to be compared with the Himawari-8/AHI ADP. The VFM products can deliver nearly coincident dataset, but not many match-ups can be returned due to presence of clouds and very narrow swath. From the case study, the percent correct (PC) values acquired from this comparisons are 0.76 for DD, 0.99 for PA, 0.87 for CA, respectively. The MODIS L2 Aerosol products can deliver nearly coincident dataset with many collocated locations over ocean and land. Increased accuracy values were acquired in Asian region as POD=0.96 over land and 0.69 over ocean, which were comparable to full disc region as POD=0.93 over land and 0.48 over ocean. The Himawari-8/AHI ADP algorithm is going to be improved continuously as well as the validation efforts will be processed by comparing the larger number of collocation data with another satellite or ground based observation data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.186-189
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• 2019

The technique named CORD is an algorithm that optimizes resources of Data Service Platform(DSP) in real time, and it has been developed for enhancing operability of DSP of Korean e-Navigation Project performed by Hanwha Systems and Ministry of Oceans and Fisheries(MOF) since 2016. It plays a critical role to recognize the state of DSP in early time and handling problems immediately when it occurs logical, physical error in order to make DSP steady state condition, which has something in common with maximizing operability of DSP and seamless maritime service to various ships in the sea. Therefore, as developing a noble technique that makes DSP steady state by diagnosing resource and operation status of DSP as well as by reconfiguring service queue optimally in real time, DSP can have shorter response time and higher chance of providing proper maritime service to ships in voyage.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.247-250
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• 2018

The remote diagnostic system has been developed for enhancing operability of Data Service Platform(DSP) of Korean e-Navigation Project performed by Ministry of Oceans and Fisheries(MOF) since 2016. It plays a critical role to find and handling logical, physical error in early time in order to maximize operability of DSP, which makes DSP to provide seamless service to various ships voyaging in the sea. Therefore, as developing a system to diagnose resource and operation status of DSP immediately in a remote place, and a system to feed it back to operator or to recover it on its own, DSP can have short period of MTTR as well as high chance of providing proper service to ships in voyage.