• Journal of Korea Port Economic Association
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• v.39 no.4
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• pp.107-125
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• 2023

The pace of sustainability transition within the maritime industry has been accelerating. This shift primarily necessitates changes in the industry's heavy reliance on fossil fuel-driven ecosystems. Additionally, numerous sustainability laws and regulations, such as the EU's CBAM and IMO's EEXI, have been implemented. This transition is poised to amplify the competitive edge of firms equipped with greater resources, as it introduces substantial operational burdens due to expensive eco-friendly fuel adoption and regulatory compliance. To diverge from the traditional competitive landscape, this paper aims to explore innovative maritime finance models enabling domestic firms to gain competitive advantages on a global scale. Employing analogical reasoning and modeling as a research method, this paper demonstrates that maritime firms can leverage the sustainability transition by aligning sustainable maritime operations with ETS (Emission Trading Schemes). Expanding on this novel approach, the paper delves into potential connections between CCM (Compliance Carbon Market), VCM (Voluntary Carbon Market), and digital asset exchanges. This newly proposed digital/net-zero maritime ecosystem holds the potential to significantly impact the shipping, shipbuilding, and ship finance industries, positioning Busan as a sustainable maritime finance hub. This study holds significance as pioneering research that may stimulate subsequent case-based studies and offer strategic guidance to market participants and policymakers as the maritime industry moves towards a net-zero transition

• Journal of Digital Convergence
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• v.11 no.12
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• pp.479-485
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• 2013

Virtualization is a promising approach to consolidating multiple online services onto a smaller number of computing resources. A virtualized server environment allows computing resources to be shared among multiple performance isolated platforms called virtual machines. Through server virtualization software, applications servers are encapsulated into VMs, and deployed with APIs on top generalized pools of CPU and memory resources. Networking and security have been moved to a software abstraction layer that transformed computing, network virtualization. And it paves the way for enterprise to rapidly deploy networking and security for any application by creating the virtual network. Stochastic reward net (SRN) is an extension of stochastic Petri nets which provides compact modeling facilities for system analysis. In this paper, we develop SRN model of network virtualization based on virtual switch. Measures of interest such as switching delay and throughput are considered. These measures are expressed in terms of the expected values of reward rate functions for SRNs. Numerical results are obtained according to the virtual switch capacity and number of active VMs.

• The KIPS Transactions:PartA
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• v.12A no.5 s.95
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• pp.441-450
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• 2005

As game markets are rapidly growing, the cost and period of game development are both increasing. These imply that the game development projects require more professional management of the project. Game mechanics is an algorithm of the gameplay on a specific game-platform. Game mechanics is concentrated on engineering elements of the game and its quality should be continuously managed from the design phase to the implementation phase. In the design phase, useful methods that can analyze the quality of game mechanics are the simulations. There are several simulation methods of the game mechanics but each method has limited use range because of its characteristics. In this Paper, we survey the game mechanics simulation methods and analyze the characteristics of each method. By the analyzed results, the Petri net model simulation method is good for analyzing total quality of no-error, optimization, and play-balance of the game mechanics but others are not.

• Journal of the Korean Society for information Management
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• v.23 no.4 s.62
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• pp.89-110
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• 2006

Life science is one of the most important fields which have direct influence on human life. Many domestic life scientists in the industries, educational organizations and research institutes have been producing important results in a variety of forms such as papers, research notes, presentation materials, books and teaching materials. Open Archiving Community has been constructed in order to share and exchange research information related to life science between researchers. The domestic life scientists can acquire valuable information through the community quickly and efficiently. In this study, the community system has been designed and implemented to provide free access to all data including metadata registry of the bibliographic information on life science and research results accumulated by researchers of their own accord. The community system also has been designed and implemented based on Web 2.0 and provides users with BBS by subjects.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.586-591
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• 2012

The solution of maintenance decision support system for the gas turbine engine, which is currently operating in GUNSAN combined cycle power plant, was developed and is consist of online monitoring module, periodic performance trending module, optimal compressor washing interval analysis module and hot component management module. Also, GUI platform was applied to this solution for the user to monitoring the analyzed result of engine performance condition and then to make a decision of the consequent maintenance action. In online condition monitoring module, the performance degradation of engine is provided by the analysis of difference between the real time measurement data compared to exist engine performance. The optimal compressor washing interval module produced the washing interval of maximum net profit value by researching the maintenance expense and the loss profit value corresponds to the performance degradation with economic assessment algorithm. Thus, this solution support the user to enable the optimal maintenance and operation of gas turbine engine with overall analysis of engine condition and main information.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.4
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• pp.1-11
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• 2021

In this paper, we explain the purpose of building a mobile app called "ARnetView" that can use the AR(augmented Reality)based calling function and AR based content creation function, and as well as an AR based data center that can share AR based video streaming and AR based contents on smartphones and tablet devices. For the AR(Augmented Reality) based data center implement, we have developed a mobile application and implemented a service system including an AR(augmented Reality) based calling function and AR based content production and AR based video streaming functions for real-time communication to connect a field technician and an expert so that the expert can see and discuss the situation in the field and technician and experts, they can draw digital annotation on mobile screen that accurately stick to 3D physical objects, allowing the expert to guide the technician step by step. In result, it provides a remote technical collaboration environment between field technician and expert. In addition, AR(Augmented Reality) collaboration service Platform was designed and implemented to increase work speed, efficiency, and utilization of advanced technicians, improve continuous productivity of equipment and facilities, maximize equipment and facility utilization, and strengthen industrial competitiveness. Therefore, through this, the AR collaboration service Platform can be applied to the industrial field, the medical field, and the entertainment/education field.

• Informatization Policy
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• v.26 no.2
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• pp.3-23
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• 2019

This review article summarizes the trends and issues around the mobility business and government regulations in Korea. Key issues identified involve unclear government regulations, conflict management between key stakeholders, platform labor, and regional conflicts. The study then offers an overview of the current government regulations on the mobility business and conflict management, along with some policy recommendations in the areas of linking conflict resolution efforts with the welfare safety net, and corporates' social responsibility for the sustainable ecosystem. Ultimately, an ecosystem is required for multiple ministries and stakeholders to participate in the process of improving the regulations, as well as a control tower (government agency) who plays the pivotal role as a coordinator.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.439-445
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• 2022

Due to the development of online media platforms and the COVID-19 incident, the mass production and consumption of digital video content are rapidly increasing. In order to select digital video content, users grasp it in a short time through thumbnails and teaser videos, and select and watch digital video content that suits them. It is very inconvenient to check all digital video contents produced around the world one by one and manually edit teaser videos for users to choose from. In this paper, keyframes are extracted based on YCbCr color models to automatically generate teaser videos, and keyframes extracted through clustering are optimized. Finally, we present a method of producing a teaser video to help users check digital video content by connecting the finally extracted keyframes.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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• pp.89-100
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• 2023

Recently, on-device artificial intelligence (AI) solutions using mobile devices and embedded edge devices have emerged in various fields, such as computer vision, to address network traffic burdens, low-energy operations, and security problems. Although vision transformer deep learning models have outperformed conventional convolutional neural network (CNN) models in computer vision, they require more computations and parameters than CNN models. Thus, they are not directly applicable to embedded edge devices with limited hardware resources. Many researchers have proposed various model compression methods or lightweight architectures for vision transformers; however, there are only a few studies evaluating the effects of model compression techniques of vision transformers on performance. Regarding this problem, this paper presents a performance evaluation of vision transformers on embedded platforms. We investigated the behaviors of three vision transformers: DeiT, LeViT, and MobileViT. Each model performance was evaluated by accuracy and inference time on edge devices using the ImageNet dataset. We assessed the effects of the quantization method applied to the models on latency enhancement and accuracy degradation by profiling the proportion of response time occupied by major operations. In addition, we evaluated the performance of each model on GPU and EdgeTPU-based edge devices. In our experimental results, LeViT showed the best performance in CPU-based edge devices, and DeiT-small showed the highest performance improvement in GPU-based edge devices. In addition, only MobileViT models showed performance improvement on EdgeTPU. Summarizing the analysis results through profiling, the degree of performance improvement of each vision transformer model was highly dependent on the proportion of parts that could be optimized in the target edge device. In summary, to apply vision transformers to on-device AI solutions, either proper operation composition and optimizations specific to target edge devices must be considered.

• The Journal of Bigdata
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• v.6 no.2
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• pp.99-108
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• 2021

Recently, unexpected and more advanced cyber medical treat attacks are on the rise. However, in responding to various patterns of cyber medical threat attack, rule-based security methodologies such as physical blocking and replacement of medical devices have the limitations such as lack of the man-power and high cost. As a way to solve the problems, the medical community is also paying attention to artificial intelligence technology that enables security threat detection and prediction by self-learning the past abnormal behaviors. In this study, there has collecting and learning the medical information data from integrated Medical-Information-Systems of the medical center and introduce the research methodology which is to develop the AI-based Net-Working Behavior Adaptive Information data. By doing this study, we will introduce all technological matters of rule-based security programs and discuss strategies to activate artificial intelligence technology in the medical information business with the various restrictions.