• Ecology and Resilient Infrastructure
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• v.6 no.4
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• pp.250-257
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• 2019

Recently, 357 water-friendly space were established near the main streams of the country through the Four Major Rivers Project, which was used as a resting and leisure space for the citizens, and the river environment and ecological health were improved. We are working hard to reduce the number of points and plan and manage the water-friendly space. In particular, attempts are being made to utilize mobile big data to make more scientific and systematic research on the number of users. However, when using mobile big data compared to the existing method of conducting field surveys, it is possible to easily identify spatial user movement patterns, but it is different from the actual amount of use, so various verifications are required to solve this problem. Therefore, this study evaluated the accuracy of estimating the number of users using mobile big data by comparing the number of visitors using mobile big data and the number of visitors using drone for Samrak ecological park located in the mouth of Nakdong River. As a result, in the river hydrophilic district, it was difficult to accurately estimating the usage pattern of each facility due to the low precision of pCELL, and it was confirmed that the usage patterns in the park could be distorted due to the signals stopped at roads and parking lots. Therefore, it is necessary to improve the number of pCELLs in the water-friendly space and to estimate the number of visitors excluding facilities such as roads and parking lots in future mobile big data processing.

• Proceedings of KOSOMES biannual meeting
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• 2017.11a
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• pp.1-1
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• 2017

• Journal of the Korea Convergence Society
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• v.8 no.5
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• pp.29-35
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• 2017

Korea has been showing a high interest in convergence centered on information and communication technologies for the past 10 years. However, with successful convergence of broadcasting and telecommunication sectors, successful convergence cases such as IPTV have been excluded. In some fields, The performance that citizens can experience is limited. In addition, the combination of the Internet of things and the big data shows that infinite data in the natural and social environment surrounding service users can be created and utilized to create better services. However, the division between departments and departments, And the limitations of policies and systems that can promote convergence of information and communication technologies. Therefore, in order to create new industries through the fusion of the Internet of things and big data, it is necessary to investigate what kind of inhibitory enzymes are present, to investigate the problems, to solve the problems, to develop technologies for activating the Internet and big data, And suggests ways to utilize the policy to promote convergence of related technologies.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.5
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• pp.1117-1127
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• 2017

With the advent of Internet of Things (IoT), the number of devices connected to Internet has rapidly increased, but the security for IoT is still vulnerable. It is difficult to integrate existing security technologies due to generating a large amount of traffic by using different protocols to use various IoT devices according to purposes and to operate in a low power environment. Therefore, in this paper, we propose a normal network behavior profiling method based on big data analysis techniques. The proposed method utilizes a Hadoop/Hive for Big Data analytics and an R for statistical computing. Also we verify the effectiveness of the proposed method through a simulation.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.57-68
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• 2018

This paper presents a smart firefighting appliances monitoring system based on big data analytics platform using GS1 for Smart City. Typical firefighting appliances are fire hydrant, fire extinguisher, fire alarm, sprinkler, fire engine, etc. for the fire of classes A/B/C/D/E. Among them, the dry chemical fire extinguisher have been widely supplied and 6 millions ones were replaced for the aging ones over 10 years in the past year. However, only 5% of them have been collected for recycling of chemical materials included the heavy metals of environment pollution. Therefore, we considered the trace of firefighting appliances from production to disposal for the public open service. In the paper, we suggest 1) a smart firefighting appliances system using GS1, 2) a big data analytics platform and 3) a public open service and visualization with the analyzed information, for fire extinguishers from production to disposal. It can give the information and the visualized diagrams with the analyzed data through the public open service and the free Apps.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.145-154
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• 2024

In order to operate predictive models utilizing administrative big data, it is crucial to consider policy changes and the characteristics of highly volatile data. Considering this scenario, this study proposes the Cut-off Voting Classifier (CVC) algorithm. This proposed algorithm prevents a sharp decline in accuracy by utilizing multiple weak classifiers. The study validates the proposed algorithm's performance through experiments. The performance evaluation demonstrates the ability to maintain stable prediction rates even in situations with a sharp decline in predictive model accuracy.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.688-701
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• 2023

The conventional methods of network intrusion detection system (NIDS) cannot measure the trend of intrusiondetection targets effectively, which lead to low detection accuracy. In this study, a NIDS method which based on a deep neural network in a big-data environment is proposed. Firstly, the entire framework of the NIDS model is constructed in two stages. Feature reduction and anomaly probability output are used at the core of the two stages. Subsequently, a convolutional neural network, which encompasses a down sampling layer and a characteristic extractor consist of a convolution layer, the correlation of inputs is realized by introducing bidirectional long short-term memory. Finally, after the convolution layer, a pooling layer is added to sample the required features according to different sampling rules, which promotes the overall performance of the NIDS model. The proposed NIDS method and three other methods are compared, and it is broken down under the conditions of the two databases through simulation experiments. The results demonstrate that the proposed model is superior to the other three methods of NIDS in two databases, in terms of precision, accuracy, F1- score, and recall, which are 91.64%, 93.35%, 92.25%, and 91.87%, respectively. The proposed algorithm is significant for improving the accuracy of NIDS.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.755-768
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• 2017

As Big Data becomes the core of the fourth industrial revolution, big data-based processing and analysis capabilities are expected to influence the company's future competitiveness. Comparative studies of RHadoop and RHIPE that integrate R and Hadoop environment, have not been discussed by many researchers although RHadoop and RHIPE have been discussed separately. In this paper, we constructed big data platforms such as RHadoop and RHIPE applicable to large scale data and implemented the machine learning algorithms such as multiple regression and logistic regression based on MapReduce framework. We conducted a study on performance and scalability with those implementations for various sample sizes of actual data and simulated data. The experiments demonstrated that our RHadoop and RHIPE can scale well and efficiently process large data sets on commodity hardware. We showed RHIPE is faster than RHadoop in almost all the data generally.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.157-158
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• 2017

There is a method to analyze the big data of the article and text mining by using Python language. And Python is a kind of programming language and it is easy to operating. Reaserch and use Python to creat a Web environment that the research result of the analysis can show directly on the browser. In this thesis, there are 100 article paper frrom Altmetric, Altmetric tracks a range of sources to capture. It is necessary to collect and analyze the big data use an effictive method, After the result coming out, Use Python wordcloud to make a directive image that can show the highest frequency of words.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.65-76
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• 2023

This paper identifies the aspects of living environment elements (PM^2.5, PM¹⁰, Noise) throughout Seoul and the urban characteristics that affect them by utilizing the big data of the S-Dot sensors in Seoul, which has recently become a hot topic. In other words, it proposes a big data based urban computing research methodology and research direction to confirm the relationship between urban characteristics and living environments that directly affect citizens. The temporal range is from 2020 to 2021, which is the available range of time series data for S-Dot sensors, and the spatial range is throughout Seoul by 500mX500m GRID. First of all, as part of analyzing specific living environment patterns, simple trends through EDA are identified, and cluster analysis is conducted based on the trends. After that, in order to derive specific urban planning factors of each cluster, basic statistical analysis such as ANOVA, OLS and MNL analysis were conducted to confirm more specific characteristics. As a result of this study, cluster patterns of environment elements(PM^2.5, PM¹⁰, Noise) and urban factors that affect them are identified, and there are areas with relatively high or low long-term living environment values compared to other regions. The results of this study are believed to be a reference for urban planning management measures for vulnerable areas of living environment, and it is expected to be an exploratory study that can provide directions to urban computing field, especially related to environmental data in the future.