• Journal of the Korean Home Economics Association
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• v.49 no.6
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• pp.85-94
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• 2011

The purpose of this study was to validate the Korean Family Support & Challenge Questionnaire (K-SCQ), which is designed to assess family complexity in Children. There were 258 pre-test participants in this study and 498 senior students who were in elementary school. Results from the pre-test suggested us to use Likert scale over a dichotomous agree or disagree scale and positively items over negative ones. Results of the confirmatory factor analysis showed that the two factor structure (family support and challenge) of the SCQ fits well for Korean students. The K-SCQ has also good internal consistency. Further analysis was performed to explore the relationships between four family types based on K-SCQ and children's well-being and flow experience. It showed that the children in a high support/high challenge family had the highest emotional well-being, psychological well-being, and flow experience. These results suggest that the complex family characterized by high support and challenge has strong and positive impact on the children's quality of life.

• Smart Structures and Systems
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• v.14 no.4
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• pp.679-697
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• 2014

The strain data acquired from structural health monitoring (SHM) systems play an important role in the state monitoring and damage identification of bridges. Due to the environmental complexity of civil structures, a better understanding of the actual strain data will help filling the gap between theoretical/laboratorial results and practical application. In the study, the multi-scale features of strain response are first revealed after abundant investigations on the actual data from two typical long-span bridges. Results show that, strain types at the three typical temporal scales of $10^5$, $10^2$ and $10^0$ sec are caused by temperature change, trains and heavy trucks, and have their respective cut-off frequency in the order of $10^{-2}$, $10^{-1}$ and $10^0$ Hz. Multi-resolution analysis and wavelet shrinkage are applied for separating and extracting these strain types. During the above process, two methods for determining thresholds are introduced. The excellent ability of wavelet transform on simultaneously time-frequency analysis leads to an effective information extraction. After extraction, the strain data will be compressed at an attractive ratio. This research may contribute to a further understanding of actual strain data of long-span bridges; also, the proposed extracting methodology is applicable on actual SHM systems.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.11
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• pp.1221-1227
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• 2012

As demands on micro-products increase significantly with raising functional integration and increasing complexity, microfoming attracts a lot of attention in the manufacture of micro-products. Since the conventional big forming systems are not adequate to achieve sufficient tolerances of micro-scale parts, it is necessary to reduce the scale of the forming equipment and devices. In addition, understandings on the size effects, which exist in the material behavior and process characterization of microforming processes, need to be expanded. In this study, a miniaturized forming system based on the ball screw and servo motor actuator was developed for the efficient micro-parts production. In addition, tensile tests and cylindrical upsetting experiments were performed to evaluate the performance of the microforming system and to investigate the flow stress and friction size effects in microforming processes.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.69-75
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• 2001

Systems engineering has been utilized in system development primarily for large-scale projects or commercial large-scale systems during the last several decades. We can understand why it would be useful to apply systems engineering to the development of a relatively small system. However, it is difficult to effectively carry out a project due to the complexity in applying the methods of systems engineering. To apply systems engineering to the development of a small system, the system engineering processes should be tailored. We established a requirements driven system design process(RDSDP) that can effectively carry out the system design far a small system. RDSDP is a system design process that treats all the requirements thoroughly and effectively. This is applied by the designer according to a standardized and systematized process during the first phase in design, in which system specifications are made. By using RDSDP, we can affect a reduction of the number of redesign phases in the process of the system design, shorten the period for to make specification, which will then cause the system to succeed in the actual application.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.901-923
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• 2017

Efficient key distribution and management mechanisms as well as lightweight ciphers are the main pillar for establishing secure wireless sensor networks (WSN). Several symmetric based key distribution protocols are already proposed, but most of them are not scalable, yet vulnerable to a small number of compromised nodes. In this paper, we propose an efficient and scalable key management and distribution framework, named KMMR, for large scale WSNs. The KMMR contributions are three fold. First, it performs lightweight local processes orchestrated into upward and downward tiers. Second, it limits the impact of compromised nodes to only local links. Third, KMMR performs efficient secure node addition and revocation. The security analysis shows that KMMR withstands several known attacks. We implemented KMMR using the NesC language and experimented on Telosb motes. Performance evaluation using the TOSSIM simulator shows that KMMR is scalable, provides an excellent key connectivity and allows a good resilience, yet it ensures both forward and backward secrecy. For a WSN comprising 961 sensor nodes monitoring a 60 hectares agriculture field, KMMR requires around 2.5 seconds to distribute all necessary keys, and attains a key connectivity above 96% and a resilience approaching 100%. Quantitative comparisons to earlier work show that KMMR is more efficient in terms of computational complexity, required storage space and communication overhead.

• Journal of the Korea Safety Management & Science
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• v.14 no.3
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• pp.1-10
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• 2012

Recently, we have witnessed the definitely negative impacts of large-scale accidents happened in such areas as atomic power plants and high-speed train systems, which result in increased fear for the potential danger. The problems appear to arise due to the deficiency in the design of large-scale complex systems. One of the causes can be attributed to the design process that does not fully reflect the safety requirements in the early stage of the system development because of the substantially increased complexity. In this paper, to enhance the systems safety an integrated process is studied, which considers simultaneously both the system design process and system safety process from the beginning of the system development. In the conceptual system design phase an integrated process model is constructed by analyzing the activities of both the system design and safety processes. As a case study example, an inner city train system is described with the application of the developed process. The computer simulation of the example case is followed by the result discussed. The results obtained in the paper are expected to be the basis for the future study where a detailed process and its associated activities can be developed.

• Electronics and Telecommunications Trends
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• v.33 no.5
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• pp.111-120
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• 2018

Agent-based modeling and simulation (ABMS) is a computational method for analyzing research targets through observations of agent-to-agent interactions, and can be applied to multidimensional policy experiments in various fields of social sciences to support policy and decision making. Recently, according to increasing complexity of society and the rapid growth of collected data, the need for high-speed processing is considered to be more important in this field. For this reason, in the ABMS research field, a scalable and large-scale computing infrastructure is becoming an essential element, and cloud computing has been considered a promising infrastructure of ABMS. This paper surveys the technology trends of ABMS tools, cloud computing-based modeling, and simulation studies, and forecasts the use of cloud-computing infrastructure for future modeling and simulation tools. Although fundamental studies are underway to apply and operate cloud computing in the areas of modeling and simulation, new and additional studies are required to devise an optimal cloud computing infrastructure to satisfy the needs of large-scale ABMS.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.3
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• pp.300-311
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• 2016

The analog-to-digital-converter-based (ADC-based) backplane receivers that consist of a front-end ADC followed by a digital equalizer are gaining more popularity in recent years, as they support more sophisticated equalization required for high data rates, scale better with fabrication technology, and are more immune to PVT variations. Unfortunately, designing an ADC-based receiver that meets tight power and performance budgets of high-speed backplane link systems is non-trivial as both front-end ADC and digital equalizer can be power consuming and complex when running at high speed. This paper reviews the state of art designs for the front-end ADC and digital equalizers to suggest implementation choices that can achieve high speed while maintaining low power consumption and complexity. Design-space exploration using system-level models of the ADC-based receiver allows through analysis on the impact of design parameters, providing useful information in optimizing the power and performance of the receiver at the early stage of design. The system-level simulation results with newer device parameters reveal that, although the power consumption of the ADC-based receiver may not comparable to the receivers with analog equalizers yet, they will become more attractive as the fabrication technology continues to scale as power consumption of digital equalizer scales well with process.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.48-55
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• 1997

Advances in VLSI technology have brought us completely new design principles for the high-performance switching fabrics including ATM switches. From a practical point of view, port scalability of ATM switches emerges as an important issue while complexity and performance of the switches have been major issues in the switch design. In this paper, we propose a cost-effective approach to modular ATM switch design which provides the good scalability. Taking advantages of both time-division and space-division switch architectures, we propose a practically implementable large scale ATM switch architecture. We present a scalable shared buffer type switch for a building block and its expansion method. In our design, a large scale ATM switch is realized by interconnecting the proposed shared buffer switches in three stages. We also present an efficient control mechanism of the shared buffers, synchronization method for the switches in each stage, and a flow control between stages. It is believed that the proposed approach will have a significant impact on both improving the ATM switch performance and enhancing the scalability of the switch with a new cost-effective scheme for handling the traffic congestion. We show that the proposed ATM switch provides an excellent performance and that its cell delay characteristic is comparable to output queueing which provides the best performance in cell delay among known approaches.

• Advances in robotics research
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• v.2 no.1
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• pp.33-44
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• 2018

This paper presents a novel feature detection algorithm called depth-hybrid speeded-up robust features (DH-SURF) augmented by depth information in the speeded-up robust features (SURF) algorithm. In the keypoint detection part of classical SURF, the standard deviation of the Gaussian kernel is varied for its scale-invariance property, resulting in increased computational complexity. We propose a keypoint detection method with less variation of the standard deviation by using depth data from a red-green-blue depth (RGB-D) sensor. Our approach maintains a scale-invariance property while reducing computation time. An RGB-D simultaneous localization and mapping (SLAM) system uses a feature extraction method and depth data concurrently; thus, the system is well-suited for showing the performance of the DH-SURF method. DH-SURF was implemented on a central processing unit (CPU) and a graphics processing unit (GPU), respectively, and was validated through the real-time RGB-D SLAM.