• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3867-3886
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• 2015

This article investigates the problem of opportunistic spectrum access in dynamic environment, in which the signal-to-noise ratio (SNR) is time-varying. Different from existing work on continuous feedback, we consider more practical scenarios in which the transmitter receives an Acknowledgment (ACK) if the received SNR is larger than the required threshold, and otherwise a Non-Acknowledgment (NACK). That is, the feedback is discrete. Several applications with different threshold values are also considered in this work. The channel selection problem is formulated as a non-cooperative game, and subsequently it is proved to be a potential game, which has at least one pure strategy Nash equilibrium. Following this, a multi-agent Q-learning algorithm is proposed to converge to Nash equilibria of the game. Furthermore, opportunistic spectrum access with multiple discrete feedbacks is also investigated. Finally, the simulation results verify that the proposed multi-agent Q-learning algorithm is applicable to both situations with binary feedback and multiple discrete feedbacks.

• Journal of Hydrogen and New Energy
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• v.30 no.2
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• pp.155-162
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• 2019

The energy management technology for an independent fuel cell-battery hybrid system is developed for a household usage. To develop an efficient energy management technology, a simulation model is first developed. After the model is verified with experimental results, three energy management schemes are developed. Three control techniques are a fuzzy logic control (FLC), a state machine control (SMC), and a hybrid method of FLC and SMC. As the fuel cell-battery hybrid system is used for a house, battery state of charge (SOC) regulation is the most important factor for an energy management because SOC should be kept constant every day for continuous usage. Three management schemes are compared to see SOC, power split, and fuel cell power variations effects. Experimental results are also presented and the most favorable strategy is the state machine combined fuzzy control method.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.17 no.2
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• pp.90-100
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• 2021

Molten corium-concrete interaction (MCCI) is one of the most important phenomena that can lead to the potential hazard of late containment failure due to basemat penetration during a severe accident. In this study, MCCI analytical models of the CORQUENCH code were prepared through verification calculations of several experiments, which had been performed using concrete types similar to those of the calandria vault floor in CANDU-6 plants. The behaviors of thermal-hydraulic variables related to MCCI phenomena were analyzed under the conditions of dry floor and water flooding during the severe accident stemming from a hypothetic station blackout. Uncertainty analyses on the ablation depth were also carried out. It was estimated that the concrete ablation was not interrupted due to the continuous MCCI process under the dry condition but was terminated within 24 hours under the water flooding condition. It was confirmed that the water flooding as a mitigating action was effective to achieve the quenching and thermal stabilization of the melt discharged from the calandria vessel, showing that the present models are capable of reasonably simulating MCCI phenomena in CANDU-6 plants. This study is expected to provide the technical bases to the accident management strategy during the late-phase severe accidents.

• Transactions of Materials Processing
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• v.32 no.2
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• pp.74-80
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• 2023

A deformation behavior of commercially pure titanium (CP-Ti) is highly dependent on material and processing parameters, such as deformation temperature, deformation direction, and strain rate. This study aims to predict the multivariable and nonlinear tensile behavior of CP-Ti using machine learning based on three algorithms: artificial neural network (ANN), light gradient boosting machine (LGBM), and long short-term memory (LSTM). The predictivity for tensile behaviors at the cryogenic temperature was lower than those in the room temperature due to the larger data scattering in the train dataset used in the machine learning. Although LGBM showed the lowest value of root mean squared error, it was not the best strategy owing to the overfitting and step-function morphology different from the actual data. LSTM performed the best as it effectively learned the continuous characteristics of a flow curve as well as it spent the reduced time for machine learning, even without sufficient database and hyperparameter tuning.

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3262-3271
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• 2000

Continuous media objects, due to large volume and real-time consiraints in their delivery,are likely to consume much network andwidth Generally, proxy servers are used to hold the fiequently requested objects so as to reduce the network traffic to the central server but most of them are designed for text and image dae that they do not go well with continuous media data. So, in this paper, we propose a two-layered network cache management policy for continuous media object delivery on the wide area networks. With the proposed cache management scheme,in cach LAN, there exists one LAN cache and each LAN is further devided into a group of sub-LANs, each of which also has its own sub-LAN eache. Further, each object is also partitioned into two parts the front-end and rear-end partition. they can be loaded in the same cache or separately in different network caches according to their access frequencics. By doing so, cache replacement overhead could be educed as compared to the case of the full size daa allocation and replacement , this eventually reduces the backbone network traffic to the origin server.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.1-23
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• 2019

Big data refers to data that is difficult to store, manage, and analyze by existing software. As the lifestyle changes of consumers increase the size and types of needs that consumers desire, they are investing a lot of time and money to understand the needs of consumers. Companies in various industries utilize Big Data to improve their products and services to meet their needs, analyze unstructured data, and respond to real-time responses to products and services. The financial industry operates a decision support system that uses financial data to develop financial products and manage customer risks. The use of big data by financial institutions can effectively create added value of the value chain, and it is possible to develop a more advanced customer relationship management strategy. Financial institutions can utilize the purchase data and unstructured data generated by the credit card, and it becomes possible to confirm and satisfy the customer's desire. CRM has a granular process that can be measured in real time as it grows with information knowledge systems. With the development of information service and CRM, the platform has change and it has become possible to meet consumer needs in various environments. Recently, as the needs of consumers have diversified, more companies are providing systematic marketing services using data mining and advanced CRM (Customer Relationship Management) techniques. KB Kookmin Card, which started as a credit card business in 1980, introduced early stabilization of processes and computer systems, and actively participated in introducing new technologies and systems. In 2011, the bank and credit card companies separated, leading the 'Hye-dam Card' and 'One Card' markets, which were deviated from the existing concept. In 2017, the total use of domestic credit cards and check cards grew by 5.6% year-on-year to 886 trillion won. In 2018, we received a long-term rating of AA + as a result of our credit card evaluation. We confirmed that our credit rating was at the top of the list through effective marketing strategies and services. At present, Kookmin Card emphasizes strategies to meet the individual needs of customers and to maximize the lifetime value of consumers by utilizing payment data of customers. KB Kookmin Card combines internal and external big data and conducts marketing in real time or builds a system for monitoring. KB Kookmin Card has built a marketing system that detects realtime behavior using big data such as visiting the homepage and purchasing history by using the customer card information. It is designed to enable customers to capture action events in real time and execute marketing by utilizing the stores, locations, amounts, usage pattern, etc. of the card transactions. We have created more than 280 different scenarios based on the customer's life cycle and are conducting marketing plans to accommodate various customer groups in real time. We operate a smart offering system, which is a highly efficient marketing management system that detects customers' card usage, customer behavior, and location information in real time, and provides further refinement services by combining with various apps. This study aims to identify the traditional CRM to the current CRM strategy through the process of changing the CRM strategy. Finally, I will confirm the current CRM strategy through KB Kookmin card's big data utilization strategy and marketing activities and propose a marketing plan for KB Kookmin card's future CRM strategy. KB Kookmin Card should invest in securing ICT technology and human resources, which are becoming more sophisticated for the success and continuous growth of smart offering system. It is necessary to establish a strategy for securing profit from a long-term perspective and systematically proceed. Especially, in the current situation where privacy violation and personal information leakage issues are being addressed, efforts should be made to induce customers' recognition of marketing using customer information and to form corporate image emphasizing security.

• Transactions on Electrical and Electronic Materials
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• v.3 no.1
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• pp.30-37
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• 2002

A focusing grating coupler (FGC) was not fabricated by the 'Continuous Path Control'writing strategy but by an electron-beam lithography system of more general exposure mode, which matches not only the address grid with the grating period but also an integer multiple of the address grid resolution (5 nm). To more simplify the fabrication, we are able to reduce a process step without large decrease of pattern quality by excluding a conducting material or layer such as metal (Al, Cr, Au), which are deposited on top or bottom of an e-beam resist to prevent charge build-up during e-beam exposure. A grating pitch period and an aperture feature size of the FGC designed and fabricated by e-beam lithography and reactive ion etching were ranged over 384.3 nm to 448.2 nm, and 0.5 $\times$ 0.5 mm$^2$area, respectively. This fabrication method presented will reduce processing time and improve the grating quality by means of a consideration of the address grid resolution, grating direction, pitch size and shapes when exposing. Here our investigations concentrate on the design and efficient fabrication results of the FGC for coupling from slab waveguide to a spot in free space.

• The KIPS Transactions:PartD
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• v.13D no.5 s.108
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• pp.691-698
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• 2006

The companies need the enterprise-wide support environment to build the competency to gather VOM(Voice of Market) in the process of preparing and implementing the strategy and to help establishing and managing the business process in order to secure the continuous competitive edge The enterprise-wide support environment to establish, operate, improve and evaluate the business process must be carried out. In this paper we define the method to define process and business rule in order to enable accurate execution of the process. Furthermore, collection and refection of accurate data concerning the competency of individuals, the subjects of the process execution, allows prevention of weakness of the process execution result and is the basis for identifying the areas of improvement. Therefore, high visibility can be attained through the work knowledge and processes presented in rules, and it can help firmly establish the process centered work culture (or system) in the organization by process improvement strictly based on data.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.17 no.1
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• pp.18-27
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• 2021

This study aims to develop an improved evaluation technology for assessing CANDU-6 safety. For this purpose, the multiple steam generator tube rupture (mSGTR) followed by an unmitigated station blackout (SBO) in a CANDU-6 plant was selected as a hypothetical event scenario and the analysis model to evaluate the plant responses was envisioned into the MARS-KS input model. The model includes logic models for controlling the pressure and inventory of the primary heat transport system (PHTS) decreasing due to the u-tubes' rupture, as well as the main features of PHTS with a simplified model for the horizontal fuel channels, the secondary heat transport system including the shell side of steam generators, feedwater and main steam line, and moderator system. A steady state condition was successfully achieved to confirm the stable convergence of the key parameters. Until the turbine trip, the fuel channels were adequately cooled by forced circulation of coolant and supply of main feedwater. However, due to the continuous reduction of PHTS pressure and inventory, the reactor and turbine were shut down and the thermal-hydraulic behaviors between intact and broken loops got asymmetric. Furthermore, as the conditions of low-flow coolant and high void fraction in the broken loop persisted, leading to degradation of decay heat removal, it was evaluated that the peak cladding temperature (PCT) exceeded the limit criteria for ensuring nuclear fuel integrity. This study is expected to provide the technical bases to the accident management strategy for transient conditions with multiple events.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.9
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• pp.2665-2691
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• 2024

The philosophy of Zero Trust in cybersecurity lies in the notion that nothing assumes to be trustworthy by default. This drives defense organizations to modernize their cybersecurity architecture through integrating with the zero-trust principles. The enhanced architecture is expected to shift protection strategy from static and perimeter-centric protection to dynamic and proactive measures depending on the logical contexts of users, assets, and infrastructure. Given the domain context of defense environment, we aim three challenge problems to tackle and identify four technical approaches by the security capabilities defined in the Zero Trust Architecture. First approach, dynamic access control manages visibility and accessibility to resources or services with Multi Factor Authentication and Software Defined Perimeter. Logical network separation approach divides networks on a functional basis by using Software Defined Network and Micro-segmentation. Data-driven analysis approach enables machine-aided judgement by utilizing Artificial Intelligence, User and Entity Behavior Analytics. Lastly, Security Awareness approach observes fluid security context of all resources through Continuous Monitoring and Visualization. Based on these approaches, a comprehensive study of modern technologies is presented to materialize the concept that each approach intends to achieve. We expect this study to provide a guidance for defense organizations to take a step on the implementation of their own zero-trust architecture.