• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.187-193
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• 2015

The ICT healing platform sets a couple of goals including preventing chronic diseases and sending out early disease warnings based on personal information such as bio-signals and life habits. The 2-step open system(TOS) had a relay designed between the healing platform and the storage of personal health data. It also took into account a publish/subscribe(pub/sub) service based on large-scale connections to transmit(monitor) the data processing process in real time. In the early design of TOS pub/sub, however, the same buffers were allocated regardless of connection idling and type of message in order to encode connection messages into a deflate algorithm. Proposed in this study, the dynamic buffer allocation was performed as follows: the message transmission type of each connection was first put to queuing; each queue was extracted for its feature, computed, and converted into vector through tf-idf, then being entered into a k-means cluster and forming a cluster; connections categorized under a certain cluster would re-allocate the resources according to the resource table of the cluster; the centroid of each cluster would select a queuing pattern to represent the cluster in advance and present it as a resource reference table(encoding efficiency by the buffer sizes); and the proposed design would perform trade-off between the calculation resources and the network bandwidth for cluster and feature calculations to efficiently allocate the encoding buffer resources of TOS to the network connections, thus contributing to the increased tps(number of real-time data processing and monitoring connections per unit hour) of TOS.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.65-77
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• 2013

Recent advanced sensors and communication technologies have been widely applied to advanced safety vehicle (ASV) for reducing traffic accident and injury severity. To apply the advanced safety vehicle technologies, it is important to quantify the safety benefits, which is a fundamental for justifying application. This study proposed a methodology for quantifying the effectiveness of the advanced driver assistant system (ADAS), and applied the methodology to lane departure warning system (LDWS) and automatic emergency braking system (AEBS) which are typical advanced driver assistant systems. When the proposed methodology is applied to 2008-2010 gyeonggi-province crash data, LDWS would reduce about 10~14% of relevant crashes such as head-on, run-off-the road, rollover and fixed-object collisions on the road. In addition, AEBS could potentially prevent about 50% of total rear-end crashes. The outcomes of this study support decision making for developing not only vehicular technology but also relevant safety policies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1602-1608
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• 2019

In this study, we developed a "Zetton Children's Traffic Safety Education" application using mixed reality to help children experience a variety of traffic situations indirectly and to help them defend themselves from accidents. We analyze the types of high mortality child traffic accidents to set learning goal. And we developed the experience-oriented contents that players could acquire signal systems and traffic information naturally and funny in the course of playing scenarios according to designed various traffic situations. In order to verify the educational effectiveness of the developed application, children were given traffic safety education through after-school education activities. The result shows that the frequency of right answers to questions related to traffic safety awareness and learning objectives is increased.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.130-139
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• 2024

Artificial intelligence models are being used to detect facility anomalies using physics data such as vibration, current, and temperature for predictive maintenance in the manufacturing industry. Since the types of facility anomalies, such as facility defects and failures, anomaly detection methods using autoencoder-based unsupervised learning models have been mainly applied. Normal or abnormal facility conditions can be effectively classified using the reconstruction error of the autoencoder, but there is a limit to identifying facility anomalies specifically. When facility anomalies such as unbalance, misalignment, and looseness occur, the facility vibration frequency shows a pattern different from the normal state in a specific frequency range. This paper presents an N-segmentation anomaly detection method that performs anomaly detection by dividing the entire vibration frequency range into N regions. Experiments on nine kinds of anomaly data with different frequencies and amplitudes using vibration data from a compressor showed better performance when N-segmentation was applied. The proposed method helps materialize them after detecting facility anomalies.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.47-54
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• 2024

The importance of cultural arts education utilizing digital tools is increasing in terms of enhancing tech literacy, self-expression, and developing convergent capabilities. The creation process and evaluation of innovative multi-modal AI, provides expanded creative audio-visual experiences in users. In particular, the process of creating music with AI provides innovative experiences in all areas, from musical ideas to improving lyrics, editing and variations. In this study, we attempted to empirically analyze the process of performing tasks using an Audio and Music Generative AI platform and discussing with fellow learners. As a result, 12 services and 10 types of evaluation criteria were collected through voluntary participation, and divided into usage patterns and purposes. The academic, technological, and policy implications were presented for AI-powered liberal arts education with learners' perspectives.

• Spatial Information Research
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• v.23 no.1
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• pp.41-48
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• 2015

BIM Technology contains data from the life cycle of facility through 3D modeling. For these, one building products the huge file because of massive data. One of them is IFC which is the standard format, and there are issues that large scale data processing based on geometry and property information of object. It increases the rendering speed and constitutes the graphic card, so large scale data is inefficient for screen visualization to user. The light weighting of large scale BIM data has to solve for process and quality of program essentially. This paper has been searched and confirmed about light weight techniques from domestic and abroad researches. To control and visualize the large scale BIM data effectively, we proposed and verified the technique which is able to optimize the BIM character. For operating the large scale data of facility on web based GIS platform, the quality of screen switch from user phase and the effective memory operation were secured.

• Journal of Platform Technology
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• v.10 no.4
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• pp.47-55
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• 2022

Recently, diverse devices using different wireless technologies are gradually increasing in the IoT environment. In particular, it is essential to design an efficient feature extraction approach and detect the exact types of radio signals in order to accurately identify various radio signal modulation techniques. However, it is difficult to gather labeled wireless signal in a real environment due to the complexity of the process. In addition, various learning techniques based on deep learning have been proposed for wireless signal classification. In the case of deep learning, if the training dataset is not enough, it frequently meets the overfitting problem, which causes performance degradation of wireless signal classification techniques using deep learning models. In this paper, we propose a generative adversarial network(GAN) based on data augmentation techniques to improve classification performance when various wireless signals exist. When there are various types of wireless signals to be classified, if the amount of data representing a specific radio signal is small or unbalanced, the proposed solution is used to increase the amount of data related to the required wireless signal. In order to verify the validity of the proposed data augmentation algorithm, we generated the additional data for the specific wireless signal and implemented a CNN and LSTM-based wireless signal classifier based on the result of balancing. The experimental results show that the classification accuracy of the proposed solution is higher than when the data is unbalanced.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.51-68
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• 2014

Today's public sector information is considered an important national asset that has social and economic value. Hence, developed countries are competitively promoting various policies to actively promote access to public sector information and the use of such information for private purposes. The Korean government is also boosting the Government 3.0 policy as a new governmental management paradigm that supports the creative economy. Despite these governmental efforts, since open public sector information is only classified from the supplier's perspective, it is difficult to have access to information for private application from the consumer's perspective and expand private applications because of the problems in identifying the information source. In this study, the concept of data from the user's perspective for the activation of private applications was defined by focusing on public sector information obtained by affiliated organizations of the Ministry of Science, ICT and Future Planning(MSIP). The new classification system was designed by analyzing the classification system of conventional open services of public sector information through investigation.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.29-43
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• 2022

With the advent of the Internet and the development of mobile digital devices such as smartphones and tablet PCs, the communication service paradigm began to shift from existing voice services to data services. Recently, as social network services (SNS) are activated and 4th industrial revolution technologies centered on ICT (Information and Communication Technologies) such as Big Data, Blockchain, Cloud, and 5G/6G are rapidly developed, the amount of shared data type and the amount of data are increasing rapidly. As the transition to a digital society begins actively, the importance of using data information, as well as the economic and social values of personal information are becoming increasingly important. As a result, they are actively discussing policies to revitalize the data information industry around the world and ways to efficiently obtain, analyze, and utilize increasingly diverse and vast data, as well as to protect/guarantee the rights of information subjects (providers) in various fields such as society, culture, economy, and politics.. In this paper, in order to improve the self-determination right of personal information on data produced by information subjects, and further expand the use of safe data and the data economy, a differentiated data trusts system was considered and suggested. In addition, the components and data trusts procedures necessary to efficiently operate the data trusts system in Korea were considered, and the non-profit data trusts system and the for-profit data trusts system were considered as a way to flexibly operate the data trusts system. Furthermore, the legal items necessary for the implementation of the data trusts system were investigated and considered. In this paper, in order to propose a domestic data trusts system, cases related to existing data trusts systems such as the United States, Japan, and Korea were reviewed and analyzed. In addition, in order to prepare legislation necessary for the data trusts system, data-related laws in major countries and domestic legal and policy trends were reviewed to study the rights that conflict or overlap with existing laws, and differences were investigated and considered. The Data trusts system proposed in this paper is a reasonable system that is expected to recognize the asset value of data in the capitalist market economy system, to provide legitimate compensation for data produced by data subjects, and further to contribute greatly to the use of safe data and creation of a new service market.

• Journal of Korean Society of Forest Science
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• v.110 no.3
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• pp.355-368
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• 2021

This study aims to identify appropriate tree species and crops for agroforestry target sites in North Korea based on ecological geography and site properties. To this end, an ecological geographic map (13 regions and 4 zones) of North Korea was made using satellite images and North Korean academic journal articles. The target agroforestry sites were selected and mapped according to 18 site conditions depending on 3 site characteristics, and the sites were divided into short-term and long-term target sites depending on the agroforestry management period. Finally, optimal combinations of 30 tree species and 19 crops were selected by overlapping the ecological geographic map and agroforestry target site map. For regions within the same zone, tree species and crops were almost similar; however, compared to regions in other zones, they differed. This is likely because the geographical climatic characteristics reflected in the ecological geographic map vary greatly from zone to zone. These results will be used to propose a combination of suitable tree species and crops that takes into account both management purposes and management types for inter-Korean forest cooperation in the agroforestry sector.