• Journal of the Korean Society of Marine Environment & Safety
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• v.14 no.3
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• pp.211-217
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• 2008

Natural environment, topographical conditions and marine traffic flows were investigated and questionnaire surveys were performed for the purpose of understanding the cause of marine accidents. The frequent cases of ships' dragging have happened at the anchorages of E-1, E-2 and E-3. The anchorage area is insufficient for the accommodation of a number of ships, the dolphins at the nearby piers are located near a narrow fairway. SBMs' are positioned too close to the fairway. It shows that many crossing marine traffic flows occur in all areas of the port. Marine casualties are concentrated mainly at No. 1 fairway, M1-M7 waters close to the dolphins and Gwanjeolgot, "E" anchorage and the waters close to the fairway "come and go" areas. The marine traffic flow is mainly caused by the ships' movement at the inter-port and most of the ships are the dangerous cargo carriers. And small ships like the tug-barge are moving disorderly in the ports. Furthermore, the fairway‘s layout is crossing each other. Questionnaire surveys of the users and experts shows that the LANBY that can distinguish the fairway of "come and go" ports is required.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• Smart Media Journal
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• v.9 no.4
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• pp.66-72
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• 2020

As the online education market expands, educational contents with various presentation methods are being developed and released. In addition, it is imperative to develop content that reflects the usability and user environment of users who use this educational content. However, for qualitative growth of contents that will support quantitative expansion of markets, existing model analysis methods are urgently needed at a time when development direction of newly developed contents is secured. In this process of content development, a typical model for setting development goals is needed, as the rules of the prototype affect the entire development process and the final development outcome. It can also provide a positive benefit that screens the issue of performance dualization between processes due to the absence of communication between a single entity or between a number of entities. In the case of AR-based educational content which is effective to secure data necessary for development by securing samples of similar categories because there are not enough ready-made samples released. Therefore, a big data statistical analysis service is needed that can easily collect data and make decisions using big data. In this paper, we would like to design analysis services that enable the selection and detection of intuitive multidimensional factors and attributes, and propose big data-based statistical analysis services that can assist cooperative activities within an organization or among many companies.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.1
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• pp.247-265
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• 2021

Recently, public libraries have increased in quantity, while various problems have arisen regarding the operation of public libraries, such as lack of librarian manpower and facilities. Additionally, an increase in the number of public libraries does not correlate to an increase in the utilization of public libraries, and thus developing various services is needed to maintain the continued use of public libraries. This study examined which types of use motivations affect the intention of knowledge exchange in public libraries when using public libraries based on the self-determination theory. It also looked at how the use motivations and the intention of knowledge exchange vary depending on the frequency of public library use. According to an online survey of 230 users of public libraries, extrinsic motivation, intrinsic motivation, autonomy, competence, and relatedness as independent variables had a positive impact on the level of knowledge exchange. In addition, the higher the frequency of public library use, the higher the needs for autonomy and relatedness were. Based on the results, it was suggested that the knowledge exchange needs to be established as a new service of public libraries by offsetting extrinsic motivation that emerged from by negative influences and promoting intrinsic motivation, autonomy and competence.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.45-51
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• 2022

Fear of contact exists due to the prevention of the spread of infectious diseases such as COVID-19. When using the common entrance door of an apartment, access is possible only if the resident enters a password or obtains the resident's permission. There is the inconvenience of having to manually enter the number and password for the common entrance door to enter. Also, contactless entry is required due to COVID-19. Due to the development of ICT, users can be easily identified through the development of face recognition and voice recognition technology. The proposed method detects a visitor's face through a CCTV or camera attached to the common entrance door, recognizes the face, and identifies it as a registered resident. Then, based on the registered information of the resident, it is possible to operate without contact by interworking with the elevator on the server. In particular, if face recognition fails with a hat or mask, the visitor is identified by voice or additional authentication of the visitor is performed based on the voice message. It is possible to block the spread of contagiousness without leaving any contactless function and fingerprint information when entering and exiting the front door of an apartment house, and without the inconvenience of access.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.155-163
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• 2022

In order to avoid the spread of Covid-19, outdoor activities are decreasing worldwide and the time spent at home is increasing. As physical activity declines, the number of people who feel bored, restless and immune deficient is increasing. As indoor life becomes more permanent, multiple approaches to home workout are becoming active. This paper examines how the Covid blue (boredom and social anxiety) produced in the no-touch era affects quality of life through the use of home training applications. Questionnaires were collected from Chinese people using a website dedicated to Chinese questionnaires, and finally 383 appropriate data were analyzed using SPSS24.0 and AMOS24.0. The research results showed that the actual experience of using home workout had a positive impact on quality of life. The higher the user's sense of social unease about being late in the untact, It was found that the higher the social anxiety perceived by users about the untact era, the higher the interactivity and exercise satisfaction with the home workout app. Home workout application can improve exercise satisfaction and quality of life, which are more positive effects beyond the result of resolving consumers' boredom. Therefore, it can be used as a channel for digital services.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.91-101
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• 2024

The utilization of container virtualization technology ensures the consistency and portability of data-intensive and memory volatile workflows. Kubernetes serves as the de facto standard for orchestrating these container applications. Cloud users often overprovision container applications to avoid container restarts caused by resource shortages. However, overprovisioning results in decreased CPU and memory resource utilization. To address this issue, oversubscription of container resources is commonly employed, although excessive oversubscription of memory resources can lead to a cascade of container restarts due to node memory scarcity. Container restarts can reset operations and impose substantial overhead on containers with high memory volatility that include numerous stateful applications. This paper proposes a technique to mitigate container restarts in a memory oversubscription environment based on Kubernetes. The proposed technique involves identifying containers that are likely to request memory allocation on nodes experiencing high memory usage and temporarily pausing these containers. By significantly reducing the CPU usage of containers, an effect similar to a paused state is achieved. The suspension of the identified containers is released once it is determined that the corresponding node's memory usage has been reduced. The average number of container restarts was reduced by an average of 40% and a maximum of 58% when executing a high memory volatile workflow in a Kubernetes environment with the proposed method compared to its absence. Furthermore, the total execution time of a container workflow is decreased by an average of 7% and a maximum of 13% due to the reduced frequency of container restarts.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.4
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• pp.795-804
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• 1999

The increasing number of users of mobile communication systems and the corresponding need for increased system capacity require the use of a modulation scheme which is both power and spectrally efficient. In this paper, we numerically calculate the BER performance of DS/CDMA-BPSK system in different fading channel (Rayleigh, Rician, Shadow Rician). Also, we calculate BER performance and the channel capacity of DS/CDMA-BPSK system which is constant or nearly constant envelopes in 3-state fading channel model. The Shadow Rician fading model described in this paper apply the parameters of the Canadian Mobile Satellite (MSAT). And we assume that the 3-state fading channel model is consist of Rayleigh fading state, Rician fading state, and shadow Rician fading state. This model can be used as a basis for the simulation of the land mobile satellite channel. The dynamic 3-state fading channel model is considered corresponding to different environments and the transitions between these environments. From the numerically calculate results, the DS/CDMA-BPSK system with MUI-20, PG-511 can not achieve the BER performance ($P_b\leq10^{-5}$). And the channel capacity did not meet the system requirement. Also, we know that the BER performance is depend m the occupancy probability of radio channel and the degree of shadow. From the results, we how that during shadowed time intervals it is necessary to use some form of error control coding and receiver diversity in order to support reliable data communication.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.2
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• pp.201-208
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• 2011

With the increase in the number of smartphone users, precise 3D positional information is required by various applications. The positioning accuracy using civilian single-frequency pseudoranges is at the level of 10 m or so, but most applications these days are asking for a sub-meter level Therefore, instead of an absolute positioning technique, the VRS-based differential approach is applied along with the correction of the double-differenced (DD) residual errors using FKP (Flachen-Korrektur-Parameter). The VRS (Virual Reference Station) is located close to the rover, and the measurements are generated by correcting the geometrical distance to those of the master reference station. Since the unmodeled errors are generally proportional to the length of the baselines, the correction parameters are estimated by fitting a plane to the DD pseudorange errors of the CORS network. The DD positioning accuracy using 24 hours of C/A code measurements provides the RMS errors of 37 cm, 28 cm for latitudinal and longitudinal direction, respectively, and 76 cm for height. The accuracy of the horizontal components is within ${\pm}0.5m$ for about 90% of total epochs, and in particular the biases are significantly decreased to the level of 2-3 cm due to the network-based error modeling. Consequently, it is possible to consistently achieve a sub-meter level accuracy from the single-frequency pseudoranges using the VRS and double-differenced error modeling.

• Convergence Security Journal
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• v.12 no.6
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• pp.11-17
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• 2012

Network security performance evaluation is a complex and diverse system environments, a single, specific performance measurements alone performance evaluation measure itself and the meaning of the reliability of the evaluation results do not limit the number of days only. In this paper, we propose a method to measure the security features of security, QoS measurement techniques using MOS satisfaction. MOS(Mean Opinion Score) Rating specifications for network security, QoS satisfaction and how to operate the development and operational model for future customer's satisfaction for information systems that can be used to evaluate the QoS measurement/analysis be utilized in the field. Objectified in the form of standards and performance measurement system provider (supplier development) and consumers(users) all the results available so that how to develop a system. Development is the development of information security features, the performance of these two features networking capabilities and a comprehensive evaluation of a three-gaeyoungyeok Correlating performance measurement methodology. Systematic measurement environment designed using the proposed methodology of this study, when the operating system is on the satisfaction of the security, QoS can be calculated. Forward In addition, a variety of performance metrics and performance measurement methods by extending the network security system satisfaction rating upgrade by the way will be.