• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.311-318
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• 2016

Recent vehicles are using car internal network for various purposes such as vehicle control, diagnostic functions, and ECU program upgrade. Currently CAN and FlexRay are the most representative networks. In the next-generation network, the use of CAN FD and car ethernet is actively studied. In this paper, we aimed to compare and evaluate the diagnostic function and the program of the ECU from the upgrade view on characteristics related to download time for each network when CAN, CAN FD, and FlexRay network are applied. As a result of the simulation, it was possible to determine that the CAN FD network is currently the most suitable for the next-generation network by suppressing other networks in terms of cost performance even under conditions of 500 Kbps and 2 Mbps which are practically usable speeds.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.4
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• pp.20-29
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• 2014

This research aims to study the new paradigm of NDE measurement which allows the identification of defect locations and sizes of a certain structure by measuring its surface temperature after applying heat. STS which has a certain defect is applied by the heat of 70000W by a heater. Its difference of STS surface temperature is measured by using Infrared thermography. The estimated result of STS experiment and that of theoretical analysis of Flex-PDE are compared and analyzed to diagnose STS defect. Moreover, this study can save time and money and improve accuracy in contrast to the existing ultrasonic NDE experiment. In addition, the new paradigm of NDT/NDE by reverse-engineering will be valid if the data of thermal analysis and temperature distribution from the specifications of many materials is accumulated and verified.

• Advances in aircraft and spacecraft science
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• v.5 no.6
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• pp.653-669
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• 2018

This work has the objective to analyze multibody mechanisms of inflatable structures for manned space applications. The focus is on the evaluation of the main characteristics of MaxFlex, a new module of MSC Adams including the effect of nonlinear flexible bodies. MaxFlex integrates the nonlinear Finite Element Analysis (FEA) of Nastran-SOL400-and the Adams multibody capabilities in one unique solver, providing an improvement concerning the concept and technology based on the co-simulation among solvers. MaxFlex converts the equations of motion of the nonlinear FEA into phase-space form and discretizes them according to the multibody system integrator framework. The numerical results deal with an inflatable manned space module having rigid components and a flexible coating made of Kevlar. This paper is a preliminary assessment of the computational capabilities of the software and does not provide realistic guidelines for the actual design of the structure. The analysis leads to some recommendations related to the main issues to consider in a nonlinear simulation including both rigid and flexible components. The results underline the importance of realistic deployment times and applied forces. Also, a proper structural modeling is necessary, but can lead to excessive computational overheads.

• Proceedings of the Materials Research Society of Korea Conference
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• 2009.05a
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• pp.3.2-3.2
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• 2009

Development of printed electronics, which is occasionally referred to as 'flexible' or 'polymer' electronics, has attracted considerable world wide attention in recent years. Printed (or flexible) electronics is currently expected to represent a new form of electronics and open up wide ranging applications in displays, electron devices for medical use, sensors, and other areas. This presentation aims to provide a strategy for scalable and viable paths to accomplish flexible, printable, large area circuits displaying high performance. Novel approaches evolving from system on package (SoP) to system on flex (SoF) technology will allow the integration of heterogeneous materials platforms into a system which is needed to enhance the functionality of the system. The talk also includes speculations about areas on which future advances in printed electronics could have a substantial impact along with a brief introduction of the Korea Printed Electronics Association (KoPEA).

• Journal of Multimedia Information System
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• v.4 no.2
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• pp.93-98
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• 2017

A new cultivation diary system based on environment sensor data and Web 2.0 with Flex is suggested, to improve the previous system using the subjective data of cultivators. The proposed system is designed by applying an object-oriented model called mini-architecture, in order to enhance the reliability of software as well as promote stability to overall system design. The environment sensor data such as temperature and humidity are used to develop the new reliable diary. Also, an active interface based on Web 2.0 and Android as the user GUI are implemented to maximize the convenience while recording the cultivation diary. The result of the performance evaluation shows that the data from sensors has 99.1% of correlation with that of analogue.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.560-563
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• 2008

The early web technology was 2D type and exchange of information was passive generally. AS the time had passed, users wanted to participate in the 3D environment which is similar to real world actively. However VRML which is expected to bring big changes of the web environment has not been expanded owing to various circumstances. At a recent Web 2.0 is the most popular topic in the Internet business. Basic concept of Web 2.0 is implementation of comfortable UI(User Interface) and implementation of more active web than previous web. Concept of RIA(Rich Internet Application) is one of the Web 2.0 important technologies. In this paper, we designed and implemented Web Environmental Sensor Data System which has fantastic UI and various functions by using Flex.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.287-288
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• 2007

This paper is for a Real-time Active Control System to operate a boiler. By sensing of flame we wanted to get status of a furnace as many as possible, like load, efficiency, and/or amount of pollutant. These data can be used to make optimal running point by controlling the ratio of air and fuel. So the last object is to make a closed actual control loop from optical head to valve controllers. The first job was to design and to develop a optical data acquisition system. including optical sensor module. And we gathered flame data in variable situations for taking the trend of flame against burning environment. Currently we are developing a general system model, designing some control strategy and testing this active control system.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.311-320
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• 2021

This study aims to explore the applicability of the HyFlex Learning Model as a new form of early childhood education in the post-COVID-19 era. In order to achieve the purpose of this study, first, the current challenges of early childhood education and the form of early childhood distance education in Korea were examined. Second, after examining the outline and characteristics of the HyFlex Learning Model(HLM) and the application cases of overseas institutions, in particular, the cases of applying the HLM in overseas early childhood education institutions were reviewed. Third, things to consider when applying the HLM in the field of early childhood education in Korea were derived. As a result, the HLM was investigated to be applicable not only in higher education but also in early childhood education as a model that emphasizes the learner's choice, learner-centered/directed, and activity. In order to apply the HLM to the early childhood education field in Korea, several points to be considered were proposed. Finally, the contribution of this study and further study were suggested.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.738-743
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• 2007

In this paper, a muscle motion sensing system and an artificial arm control system are studied. The artificial arm is for the people who lost one's forearm. The muscle motion sensing system detect the intention of motion from the upper arm's muscle. In sensing system we use flex sensors which is electrical resistance type sensor. The sensor is attached on the biceps brachii muscle and coracobrachialis muscle of the upper arm. We propose an algorithm to classify the one's intention of motions from the sensor signal. Using this algorithm, we extract the 4 motions which are flexion and extension of the forearm, pronation and supination of the arm. To verify the validity of the proposed algorithms we made experiments with two d.o.f. artificial arm. To reduce the control errors of the artificial arm we also proposed a fuzzy PID control algorithm which based on the errors and error rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2377-2398
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• 2023

In our daily lives, we engage in a variety of tasks that rely on our senses, such as seeing. Blindness is the absence of the sense of vision. According to the World Health Organization, 2.2 billion people worldwide suffer from various forms of vision impairment. Unfortunately, blind people face a variety of indoor and outdoor challenges on a daily basis, limiting their mobility and preventing them from engaging in other activities. Blind people are very vulnerable to a variety of hazards, including falls. Various barriers, such as stairs, can cause a fall. The Internet of Things (IoT) is used to track falls and send a warning message to the blind caretakers. One of the gaps in the previous works is that they were unable to differentiate between falls true and false. Treating false falls as true falls results in many false alarms being sent to the blind caretakers and thus, they may reject the IoT system. As a means of bridging this chasm, this paper proposes an intelligent shoe that is able to precisely distinguish between false and true falls based on three sensors, namely, the load scale sensor, the light sensor, and the Flex sensor. The proposed IoT system is tested in an indoor environment for various scenarios of falls using four models of machine learning. The results from our system showed an accuracy of 0.96%. Compared to the state-of-the-art, our system is simpler and more accurate since it avoids sending false alarms to the blind caretakers.