• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.79-81
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• 2014

Recently, It is built various information systems evolve IT skills. But When you build the information system, Difficult to determine whether the appropriate scale and problems that rely heavily on SI companies and professionals. To solve this problem, Korea Information Security Agency, etc., based on the primary objective was to develop H/W Capacity Equation formally to each system type. But the problems are to present H/W capacity equation by discussion of the expert group of suppliers and relatively long that it is difficult to formally apply in the situation now so it is no longer the limit. In this study, we proposes proper capacity planning techniques, which can guarantee the best performance compared to the budget invested. For this purpose, we derived the proper H/W capacity equation by regression analysis to gather performance metrics and cost of various cases by simulation of a virtual environment in the cloud. Through this study, when capacity planning, It is possible to reduce costs that It is possible to build an information system based on the digitized data and build information system in an environment that does not rely on the SI business or professional.

• Journal of the Korean Society for information Management
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• v.36 no.3
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• pp.149-174
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• 2019

This study analyzes the actual use data of the websites of university libraries, analyzes the users' usage behavior, and proposes improvement measures for the websites. The study analyzed users' traffic and analyzed their usage behavior from January 2018 to December 2018 on the C University website. The website's analysis tool used 'Google Analytics'. The web traffic variables were analyzed in five categories: user general characteristics, user environment analysis, visit analysis, inflow analysis, site analysis, and site analysis based on the metrics of sessions, users, page views, pages per session, average session time, and bounce rate. As a result, 1) In the analysis results of general characteristics of users, there was some access to the website not only in Korea but also in China. 2) In the user experience analysis, the main browser type appeared as Internet Explorer. The next place was Chrome, with a bounce rate of Safari, third and fourth, double that of the Explore or Chrome. In terms of screen resolution, 1920x1080 resolution accounted for the largest percentage, with access in a variety of other environments. 3) Direct inflow was the highest in the inflow media analysis. 4) The site analysis showed the most page views out of 4,534,084 pages, followed by the main page, followed by the lending/extension/history/booking page, the academic DB page, and the collection page.

• Journal of Pharmacopuncture
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• v.22 no.3
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• pp.166-170
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• 2019

Objectives: Attentional and memory functions are important aspects of neural plasticity that, theoretically, should be amenable to pharmacopuncture treatments. A previous study from our laboratory suggested that quantitative electroencephalographic (qEEG) measurements of theta/beta ratio (TBR), an index of attentional control, may be indicative of academic performance in a first-semester medical school course. The present study expands our prior report by extracting and analyzing data on frontal theta and beta asymmetries. We test the hypothesis that the amount of frontal theta and beta asymmetries (fTA, fBA), are correlated with TBR and academic performance, thereby providing novel targets for pharmacopuncture treatments to improve cognitive performance. Methods: Ten healthy male volunteers were subjected to 5-10 min of qEEG measurements under eyes-closed conditions. The qEEG measurements were performed 3 days before each of first two block examinations in anatomy-physiology, separated by five weeks. Amplitudes of the theta and beta waveforms, expressed in ${\mu}V$, were used to compute TBR, fTA and fBA. Significance of changes in theta and beta EEG wave amplitude was assessed by ANOVA with post-hoc t-testing. Correlations between TBR, fTA, fBA and the raw examination scores were evaluated by Pearson's product-moment coefficients and linear regression analysis. Results: fTA and fBA were found to be negatively correlated with TBR (P<0.03, P<0.05, respectively) and were positively correlated with the second examination score (P<0.03, P=0.1, respectively). Conclusion: Smaller fTA and fBA were associated with lower academic performance in the second of two first-semester medical school anatomy-physiology block examination. Future studies should determine whether these qEEG metrics are useful for monitoring changes associated with the brain's cognitive adaptations to academic challenges, for predicting academic performance and for targeting phamacopuncture treatments to improve cognitive performance.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.1-18
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• 2019

Due to the great advances in e-Marketplace and changes in type of items purchased from the online market, it has been dramatically increased the demand of the storage and transportation under the special conditions such as restricted temperature. Especially, the cold chain needs the way to transparently measure and monitor the entire network in realtime because it has a very complicated structure and requires totally different criteria at the every different steps and items. In this research, it has been presented the performance evaluation metrics to make contract using service level agreement (SLA), the way to apply the smart contract based on blockchain, the structure of blocks, service platform and application in order to build cold chain which can prevent the risk factors by measuring and sharing information in realtime using block chain technology. In addition, we have proposed the way to store the measured performance and reputation of each player in the block using smart contract based on SLA. With the presented framework, all players including service providers as well as users can secure the information for making the rational decisions. When the service platform is actually built and operated, it seems possible to secure the information in transparently and realtime. Also, it is possible to prevent the risk factors or prepare the preemptive plans to react on them.

• Journal of Wetlands Research
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• v.21 no.2
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• pp.181-190
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• 2019

Recently, Low impact development techniques, a form of nature-based solutions (NBS), were seen cost-efficient alternatives that can be utilized as alternatives for conventional stormwater management practices. This study evaluated the effectiveness of an infiltration trench (IT) and a small constructed wetland (SCW) in treating urban stormwater runoff. Long-term monitoring data were observed to assess the seasonal performance and cite the advantages and disadvantages of utilizing the facilities. Analyses revealed that the IT has reduced performance during the summer season due to higher runoff volumes that exceeded the facility's storage volume capacity and caused the facility to overflow. On the other hand, the pollutant removal efficiency of the SCW was impacted by the winter season as a result of dormant biological activities. Sediment data also indicated that fine and medium sand particles mostly constituted the trapped sediments in the pretreatment and media zones. Sediments in SCW exhibited a lower COD and TN load due to the phytoremediation and microbiological degradation capabilities of the system. This study presented brief comparison LID facilities equipped with pre-treatment zones. The identified factors that can potentially affect the performance of the systems were also beneficial in establishing metrics on the utilization of similar types of nature-based stormwater management practices.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.239-247
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• 2019

An accurate prediction of emotion is a very important issue for the sake of patient-centered medical device development and emotion-related psychology fields. Although there have been many studies on emotion prediction, no studies have applied the heart rate variability and neuro-fuzzy approach to emotion prediction. We propose ANFEP(Adaptive Neuro Fuzzy System for Emotion Prediction) HRV. The ANFEP bases its core functions on an ANFIS(Adaptive Neuro-Fuzzy Inference System) which integrates neural networks with fuzzy systems as a vehicle for training predictive models. To prove the proposed model, 50 participants were invited to join the experiment and Heart rate variability was obtained and used to input the ANFEP model. The ANFEP model with STDRR and RMSSD as inputs and two membership functions per input variable showed the best results. The result out of applying the ANFEP to the HRV metrics proved to be significantly robust when compared with benchmarking methods like linear regression, support vector regression, neural network, and random forest. The results show that reliable prediction of emotion is possible with less input and it is necessary to develop a more accurate and reliable emotion recognition system.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.91-99
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• 2018

Sketch-based 3D object retrieval is a convenient way to search for various 3D data using human-drawn sketches as query. In this paper, we propose a new method of using Sketch CNN, Wasserstein CNN and Wasserstein center loss for sketch-based 3D object search. Specifically, Wasserstein center loss is a method of learning the center of each object category and reducing the Wasserstein distance between center and features of the same category. To do this, the proposed 3D object retrieval is performed as follows. Firstly, Wasserstein CNN extracts 2D images taken from various directions of 3D object using CNN, and extracts features of 3D data by computing the Wasserstein barycenters of features of each image. Secondly, the features of the sketch are extracted using a separate Sketch CNN. Finally, we learn the features of the extracted 3D object and the features of the sketch using the proposed Wasserstein center loss. In order to demonstrate the superiority of the proposed method, we evaluated two sets of benchmark data sets, SHREC 13 and SHREC 14, and the proposed method shows better performance in all conventional metrics compared to the state of the art methods.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.10
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• pp.285-290
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• 2021

In the medical field, disease diagnosis and prediction research using artificial intelligence technology is being actively conducted. It is being released as a variety of products for disease diagnosis and prediction, which are most widely used in the application of artificial intelligence technology based on medical images. Artificial intelligence is being applied to diagnose diseases, to classify diseases into benign and malignant, and to separate disease regions for use in identification or reading according to the risk of disease. Recently, in connection with cloud technology, its utility as a service product is increasing. Among the diseases dealt with in this paper, liver disease is a disease with very high risk because it is difficult to diagnose early due to the lack of pain. Artificial intelligence technology was introduced based on medical images as a non-invasive diagnostic method for diagnosing these diseases. We describe the development of a web service to help the most meaningful clinical reading of liver cirrhosis patients. Then, it shows the web service process and shows the operation screen of each process and the final result screen. It is expected that the proposed service will be able to diagnose liver cirrhosis at an early stage and help patients recover through rapid treatment.

• Journal of Environmental Impact Assessment
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• v.30 no.3
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• pp.164-174
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• 2021

Information on biodiversity plays an important role in conservation planning for ecosystem. As existing biodiversity indices are calculated and predicted only based on the number of individuals and species, it is difficult to explain aspects of genetic and ecological diversity. Phylogenetic diversity can indirectly evaluate ecological diversity as well as genetic diversity overlooked by existing biodiversity assessments. In this study, typical metrics of biodiversity (e.g., species diversity, species richness, etc.) and phylogenetic diversity were evaluated together using a long-term monitoring data of winter birds in Jungrang, Cheonggye and Anyang stream where are designated as Seoul migratory bird reserves. Then discussed the meaning of each assessmentresult. In Jungrang and Anyang stream, the number of individuals generally decreased overtime, whereas in Cheonggye stream, there was no significant change. In addition, species abundance increased over time slightly in Cheonggye stream, while there was no significant change in Jungrang and Anyang stream. Species diversity temporally increased in Jungrang and Cheonggye stream, excluding Anyang stream, but phylogenetic diversity showed a tendency to increase only in Cheonggye stream. These changes in the biodiversity assessment indices are thought to be due to anthropogenic disturbances such as construction that occurred within each site, and it was shown that species diversity and phylogenetic diversity do not always lead to the same assessment results. Therefore, this study suggests that biodiversity assessment needs to be considered from various contexts such as genetic and ecological perspectives.

• The Journal of Industrial Distribution & Business
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• v.12 no.1
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• pp.47-62
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• 2021

Purpose: Our purpose in this study was to examine the strategies for the development of watermelon industry using unstructured big data analysis. That is, this study was to look the change of issues and consumer's perception about watermelon using big data and social network analysis and to investigate ways to strengthen the competitiveness of watermelon industry based on that. Methodology: For this purpose, the data was collected from Naver (blog, news) and Daum (blog, news) by TEXTOM 4.5 and the analysis period was set from 2015 to 2016 and from 2017-2018 and from 2019-2020 in order to understand change of issues and consumer's perception about watermelon or watermelon industry. For the data analysis, TEXTOM 4.5 was used to conduct key word frequency analysis, word cloud analysis and extraction of metrics data. UCINET 6.0 and NetDraw function of UCINET 6.0 were utilized to find the connection structure of words and to visualize the network relations, and to make a cluster of words. Results: The keywords related to the watermelon extracted such as 'the stalk end of a watermelon', 'E-mart', 'Haman', 'Gochang', and 'Lotte Mart' (news: 015-2016), 'apple watermelon', 'Haman', 'E-mart', 'Gochang', and' Mudeungsan watermelon' (news: 2017-2018), 'E-mart', 'apple watermelon', 'household', 'chobok', and 'donation' (news: 2019-2020), 'watermelon salad', 'taste', 'the heat', 'baby', and 'effect' (blog: 2015-2016), 'taste', 'watermelon juice', 'method', 'watermelon salad', and 'baby' (blog: 2017-2018), 'taste', 'effect', 'watermelon juice', 'method', and 'apple watermelon' (blog: 2019-2020) and the results from frequency and TF-IDF analysis presented. And in CONCOR analysis, appeared as four types, respectively. Conclusions: Based on the results, the authors discussed the strategies and policies for boosting the watermelon industry and limitations of this study and future research directions. The results of this study will help prioritize strategies and policies for boosting the consumption of the watermelon and contribute to improving the competitiveness of watermelon industry in Korea. Also, it is expected that this study will be used as a very important basis for agricultural big data studies to be conducted in the future and this study will offer watermelon producers and policy-makers practical points helpful in crafting tailor-made marketing strategies.