• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1558-1564
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• 2019

Corporate business clusters create a borderless business network through value chains and value creation activities. Clusters in the IT sector are crossing regional boundaries because of their rapid technological development and short product life cycle. To investigate this phenomenon, we examined the value activities of IT companies. As a result, the global expansion of the case companies was limited, but they had business clusters that exceeded the regional boundaries. However, because the order of business clusters is not advanced, value activities are focused on productivity rather than innovation. Given the rapidly evolving nature of IT, it is necessary to evolve into a business cluster that can create new value. Companies must design and implement value-creating processes to develop new technologies or enter new markets, which can lead to cluster growth. Companies must design and implement value-creating processes to develop new technologies or enter new markets, which can lead to cluster growth.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.593-600
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• 2020

The equipment for marine IoT service have to overcome the effect of seawater. Furthermore, the free floating transmitter in seawater will be less affected by the seawater environment. The results of the design and fabrication of antenna, which is embedded in buoy, are shown in this research. The proposed antenna is used to supervise the states of fishing gears in monitoring system for real-name system of electric fishing gear. The selected frequency band of the proposed antenna is 920 MHz, and PCB pattern type is selected for subminiature and light weight. It is confirmed that RF characteristics is more degraded, however, the radiation is gradually upward as the contact surface of buoy with seawater is more broaden through the simulation results. That is, the RF performance of the proposed antenna is more deteriorated but beam radiation characteristics is more suited the marine IoT, the seawater effect is more increased. It is expected that the proposed antenna will contribute the implementation of IoT network based on low power wide area (LPWA) when the degradation of RF performance will be settled.

• Journal of Korean Library and Information Science Society
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• v.52 no.2
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• pp.65-84
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• 2021

This study aimed to analyze the overall operation status of the Bank of Korea library representing the economic library in Korea, investigate user satisfaction and demand, and to propose a direction for the development of the economic library in the future. To this end, a case study was conducted on changes in the external environment of major libraries at home and abroad, and a user survey was conducted. As a result, the future tasks include introducing smart systems, robotics some library services, non-face-to-face service response spaces that reflect the times, introducing big data analysis services, strengthening user-tailored systems, and activating SNS communication. It proposed developing specialized libraries, online reference and research support services, and providing original DBs for publications to strengthen expertise, maintaining and expanding cloud services, maintaining and expanding cooperative projects, and collecting national knowledge and information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.827-833
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• 2022

This study aims to prevent secondary traffic accidents with high severity by overcoming the limitations of existing traffic information collection systems through analysis of traffic information collection detectors and various algorithms used to detect unexpected situations. In other words, this study is meaningful present that analyzing the 'unexpected situation that causes secondary traffic accidents' and 'Existing traffic information collection system' accordingly presenting a solution that can preemptively prevent secondary traffic accidents, intelligent traffic information collection system that enables accurate information collection on all sections of the road. As a result of the experiment, the reliability of data transmission reached 97% based on 95%, the data transmission speed averaged 209ms based on 1000ms, and the network failover time achieved targets of 50sec based on 120sec.

• Journal of the Korea Society of Computer and Information
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• v.27 no.4
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• pp.19-26
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• 2022

With the recent development of intelligent transportation systems, car license plate recognition systems are being used in various fields. Such systems need to guarantee real-time performance to recognize the license plate of a driving car. Also, they should keep a high recognition rate even in problematic situations such as small license plates in low-resolution and unclear image due to distortion. In this paper, we propose a real-time car license plate recognition system that improved processing speed using object detection algorithm based on anchor-free method and text recognition algorithm based on Convolutional Neural Network(CNN). In addition, we used Spatial Transformer Network to increase the recognition rate on the low resolution or distorted images. We confirm that the proposed system is faster than previously existing car license plate recognition systems and maintains a high recognition rate in a variety of environment and quality images because the proposed system's recognition rate is 93.769% and the processing speed per image is about 0.006 seconds.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.226-234
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• 2022

With advances in autonomous vehicles and networked control, there is a growing interest in the consensus control of a multi-agents system to control multi-agents with distributed control beyond the control of a single agent. Since consensus control is a distributed control, it is bound to have delay in a practical system. In addition, it is often difficult to have a very accurate mathematical model for a system. Even though a reinforcement learning (RL) method was developed to deal with these issues, it often experiences slow convergence in the presence of large uncertainties. Thus, we propose a slide RL which combines the sliding mode control with RL to be robust to the uncertainties. The structure of a sliding mode control is introduced to the action in RL while an auxiliary sliding variable is included in the state information. Numerical simulation results show that the slide RL provides comparable performance to the model-based consensus control in the presence of unknown time-varying delay and disturbance while outperforming existing state-of-the-art RL-based consensus algorithms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.173-178
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• 2022

Recently, a recommendation system using deep learning in social network services has been actively studied. However, in the case of a recommendation system using deep learning, the cold start problem and the increased learning time due to the complex computation exist as the disadvantage. In this paper, the user-tailored exercise routine recommendation algorithm is proposed using the user's metadata. Metadata (the user's height, weight, sex, etc.) set as the input of the model is applied to the designed model in the proposed algorithms. The exercise recommendation system model proposed in this paper is designed based on the neural collaborative filtering (NCF) algorithm using multi-layer perceptron and matrix factorization algorithm. The learning proceeds with proposed model by receiving user metadata and exercise information. The model where learning is completed provides recommendation score to the user when a specific exercise is set as the input of the model. As a result of the experiment, the proposed exercise recommendation system model showed 10% improvement in recommended performance and 50% reduction in learning time compared to the existing NCF model.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.1-9
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• 2022

As various services are linked to IoT(Internet of Things) and portable communication terminals, cyber attacks that exploit security vulnerabilities of the devices are rapidly increasing. In particular, cyber attacks targeting heterogeneous devices in large-scale network environments through advanced persistent threat (APT) attacks are on the rise. Therefore, in order to improve the effectiveness of the response system in the event of a breach, it is necessary to apply a data enrichment mechanism for the collected artifact data to improve threat analysis and detection performance. Therefore, in this study, by analyzing the data supplementation common elements performed in the existing incident management framework for the artifacts collected for the analysis of intrusion accidents, characteristic elements applicable to the actual system were derived, and based on this, an improved accident analysis framework The prototype structure was presented and the suitability of the derived data supplementary extension elements was verified. Through this, it is expected to improve the detection performance when analyzing cyber incidents targeting artifacts collected from heterogeneous devices.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.103-113
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• 2022

As globalization progresses and localization takes place, interest in local culture is increasing. In line with this trend, the Cultural Heritage Administration has been promoting the Cultural Heritage Night Tour Project as a night-type cultural property tourism content since 2016. Cultural property nightlife, part of the regional regeneration project, creates new added value by converging and combining various historical and cultural-related contents centered on local cultural heritage. Although the "cultural nightlife" has been greatly activated, it is judged that changes are needed to continue. This is because fixed nightlife programs are positive in terms of establishing a nationwide network, but there is a limitation in that they cannot be standardized and expanded to various forms. Therefore, in this study, the meaning and limitations of nightlife programs were identified, and cognitive theory applicable to nightlife programs was considered. Through this process, it was confirmed that cognitive poetry's 'circular for dynamic semantic composition', 'surreal foreground', and 'adventures in time and space' can be applied to nightlife programs. As a result of combining cognitive poetry with nightlife programs, it was possible to present a strategy for implementing nightlife programs differentiated from existing nightlife programs.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.738-750
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• 2022

In this study, we reviewed and discussed whether auditory stimuli with short length can evoke emotion-related neurological responses. The findings implicate that if personalized sound tracks are provided to XR users based on machine learning or probability network models, user experiences in XR environment can be enhanced. We also investigated that the arousal-relaxed factor evoked by short auditory sound can make distinct patterns in functional connectivity characterized from background EEG signals. We found that coherence in the right hemisphere increases in sound-evoked arousal state, and vice versa in relaxed state. Our findings can be practically utilized in developing XR sound bio-feedback system which can provide preference sound to users for highly immersive XR experiences.