• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.47-55
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• 2016

As one of recent issues in the information and communication industry, internet of things has attracted attention to provide intelligent infrastructure services which connect and share data and information between real and virtual world. According to the development of these internet of things technologies, types of machines, telecommunication devices, and terminals are increasing tremendously. In this situation, connectivity and interoperability between internet of things components are important issues to build a hyper connected society. To visualize this society, it is important to set up and develop information and communication technology (ICT) standards among stakeholders. However, under limited budget and human resources, it is essential to rank standardization work items for setting standards with respect to efficiency. The purpose of this study is to provide a method for setting standardization strategies within group decision making. As a multi-criteria group decision making tool, analytic hierarchy process (AHP) is adopted and applied to determine the priorities of setting work items. The proposed method first defines decision making problem with objective, criteria, and alternatives which produces a hierarchy consisting of upper and lower criteria. Then, pairwise comparisons of academy and public sector experts are performed with respect to their relative meaning and importance. Individual surveys of expert groups are collected and summarized to determine relative criteria importance measures. Furthermore, to deliver reliable importance criteria measures, differences between academy and public sector expert groups are compared and tested using Mann-Whitney non-parametric test. The results are illustrated for useful guidelines to practical group decision making in standardization strategy establishments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1938-1962
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• 2015

Security of information during transmission is a major issue in this modern era. All of the communicating bodies want confidentiality, integrity, and authenticity of their secret information. Researchers have presented various schemes to cope with these Internet security issues. In this context, both steganography and cryptography can be used effectively. However, major limitation in the existing steganographic methods is the low-quality output stego images, which consequently results in the lack of security. To cope with these issues, we present an efficient method for RGB images based on gray level modification (GLM) and multi-level encryption (MLE). The secret key and secret data is encrypted using MLE algorithm before mapping it to the grey-levels of the cover image. Then, a transposition function is applied on cover image prior to data hiding. The usage of transpose, secret key, MLE, and GLM adds four different levels of security to the proposed algorithm, making it very difficult for a malicious user to extract the original secret information. The proposed method is evaluated both quantitatively and qualitatively. The experimental results, compared with several state-of-the-art algorithms, show that the proposed algorithm not only enhances the quality of stego images but also provides multiple levels of security, which can significantly misguide image steganalysis and makes the attack on this algorithm more challenging.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.107-118
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• 2021

The deployment of 5G is in full swing, with a significant yearly growth in the data traffic expected to reach 26% by the year and data consumption to reach 122 EB per month by 2022 [10]. In parallel, the idea of smart cities has been implemented by various governments and private organizations. One of the main objectives of 5G deployment is to help develop and realize smart cities. 5G can support the enhanced data delivery requirements and the mass connection requirements of a smart city environment. However, for specific high-demanding applications like tactile Internet, transportation, and augmented reality, the cloud-based 5G infrastructure cannot deliver the required quality of services. We suggest using multi-access edge computing (MEC) technology for smart cities' environments to provide the necessary support. In cloud computing, the dependency on a central server for computation and storage adds extra cost in terms of higher latency. We present a few scenarios to demonstrate how the MEC, with its distributed architecture and closer proximity to the end nodes can significantly improve the quality of services by reducing the latency. This paper has surveyed the existing work in MEC for 5G and highlights various challenges and opportunities. Moreover, we propose a unique framework based on the use of MEC for 5G in a smart city environment. This framework works at multiple levels, where each level has its own defined functionalities. The proposed framework uses the MEC and introduces edge-sub levels to keep the computing infrastructure much closer to the end nodes.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.1
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• pp.5-7
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• 2022

KEPCO's plan is undergoing a trial operation to replace the open-loop section with ring main units configuration where underground distribution lines are installed, by linking the multi-way circuit breakers auto (MCA) on the power side of each pad-mounted transformer. However, ring main units application mentioned above may cause the ripple effects, when implementing the configuration without a study of protection coordination. Because ring main units with classical pre-set protection devices contribution in fault condition didn't consider yet. For the reliable ring main units operation, it is necessary to resolve several protection issues such as the protection coordination with substation side, prevention of the transformer inrush current. These issues can radically deteriorate the distribution system reliability Hence, it is essential to design proper protection coordination to reduce these types of problems. This paper presents a scheme of ring main units' configuration and MCA's settings of time-current curves to preserve the performance of protection coordination among the switchgears considering constraints, e.g. prevention of the ripple effects (on the branch section when a transformer failure occurs and the mainline when a branch line failure occurs). It was confirmed that the propagation of the failure for each interrupter segment could be minimized by applying the proposed TCC and the interrupter settings for the MCAs (branch, transformer). Further, it was verified that the undetected area of the distribution automation system (DAS) could be supplemented by having the MCA configurated ring main units operate first, instead of the internal protection equipment in the transformer such as the fuse, STP when a transformer failure occurs.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.111-119
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• 2024

In this paper, we propose a big data platform that can collect information from various sources collected at ocean. Currently operating ocean-related big data platforms are focused on storing and sharing created data, and each data provider is responsible for data collection and preprocessing. There are high costs and inefficiencies in collecting and integrating data in a marine environment using communication networks that are poor compared to those on land, making it difficult to implement related infrastructure. In particular, in fields that require real-time data collection and analysis, such as weather information, radar and sensor data, a number of issues must be considered compared to land-based systems, such as data security, characteristics of organizations and ships, and data collection costs, in addition to communication network issues. First, this paper defines these problems and presents solutions. In order to design a big data platform that reflects this, we first propose a data source, hierarchical MEC, and data flow structure, and then present an overall platform structure that integrates them all.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.478-478
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• 2012

Recently, there are many researches in order to increase the deposition rate (D/R) and improve film uniformity and quality in the deposition of microcrystalline silicon thin film. These two factors are the most important issues in the fabrication of the thin film solar cell, and for the purpose of that, several process conditions, including the large area electrode (more than 1.1 X 1.3 (m2)), higher pressure (1 ~ 10 (Torr)), and very high frequency regime (VHF, 40 ~ 100 (MHz)), have been needed. But, in the case of large-area capacitively coupled discharges (CCP) driven at frequencies higher than the usual RF (13.56 (MHz)) frequency, the standing wave and skin effects should be the critical problems for obtaining the good plasma uniformity, and the ion damage on the thin film layer due to the high voltage between the substrate and the bulk plasma might cause the defects which degrade the film quality. In this study, we will propose the new concept of the large-area multi-electrode (a new multi-electrode concept for the large-area plasma source), which consists of a series of electrodes and grounds arranged by turns. The experimental results with this new electrode showed the processing performances of high D/R (1 ~ 2 (nm/sec)), controllable crystallinity (~70% and controllable), and good uniformity (less than 10%) at the conditions of the relatively high frequency of 40 MHz in the large-area electrode of 280 X 540 mm2. And, we also observed the SEM images of the deposited thin film at the conditions of peeling, normal microcrystalline, and powder formation, and discussed the mechanisms of the crystal formation and voids generation in the film in order to try the enhancement of the film quality compared to the cases of normal VHF capacitive discharges. Also, we will discuss the relation between the processing parameters (including gap length between electrode and substrate, operating pressure) and the processing results (D/R and crystallinity) with the process condition map for ${\mu}c$-Si:H formation at a fixed input power and gas flow rate. Finally, we will discuss the potential of the multi-electrode of the 3.5G-class large-area plasma processing (650 X 550 (mm2) to the possibility of the expansion of the new electrode concept to 8G class large-area plasma processing and the additional issues in order to improve the process efficiency.

• Korean Journal of Culture and Social Issue
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• v.14 no.4
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• pp.39-69
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• 2008

The present study examined the overall receptivity of community members to migrant wives in Korea. A total of 23 community members from two regions, Ansan, an urban area and Youngam, a rural area, were selected for the interview based on their prior experience with migrant wives. Data were collected via a semi-structured interview method. The participants provided their personal feelings and thoughts on a variety of issues involving migrant wives, such as how they perceive migrant wives' original culture and lifestyles, the nature of their interaction experience with migrant wives, their overall evaluation of migrant wives, their opinions about migrant wives' cultural adaptation, and their opinions about the on-going transformation of the Korean society into a multi-racial, multi-cultural society. Interview results indicated that, although the participants' attitude toward migrant wives was positive, the overall receptivity to migrant wives was largely based on the traditional sex-role stereotypes typically found in the Korean society. Moreover, the vast majority of the participants endorsed a narrow-minded, uni-directional perspective on cultural adaptation which puts far greater emphasis on migrant wives' assimilation into the host culture than reciprocal influence process between the two cultures. Implications of the study and directions for future research were discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.49-55
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• 2017

Most motor cases adopt deep drawing products, which are excellent in waterproof functions, concentricity, right angle, and quality. In addition, the blower motor and seat motor, which are installed in the car interior and do not require waterproof function, adopts a multi-forming manufacturing method. The deep drawing process requires an expensive transfer press that can digest approximately 12 processes, such as drawing, trimming and piercing. On the other hand, products can be produced with low investment because the multi-forming method is composed of one multi-forming machine or one multi-forming machine and one press. The multi-forming machine is a high-priced facility that is mostly imported and a bending / shearing process multi-foaming machine, which was developed by domestic small and medium-sized enterprises, is not enough to reduce the production cost. An integral multi - forming machine is used as a limited working method for thin material and small products. A large product and thick material has a high shear load. A large product and thick material has a high shear load and uses a single crank press. After blanking, the worker manually feeds the material to a multi-forming machine. When the bending operation is performed in the multi-forming machine, it is transferred to the press again to calibrate the dimensions. This variance in work processes has resulted in lower cost competitiveness due to the lower productivity, quality issues, and excessive operator input. The aim of this study was to establish a stable and cost - effective production system through bending / shearing process separation and facility automation.