• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.211-214
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• 2000

This paper describes a lateral guidance system of an autonomous vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in simulations. As the neural network controller acquires magnetic field values(B$\sub$x/, B$\sub$y/, B$\sub$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the teaming pattern, learning itself, and the adequacy of the design controller. Also, the performance of the controller can be verified through simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.6
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• pp.855-859
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• 2014

Quality criteria for interaction between a pantograph and overhead contact wire is a most important requirement to assess of the performance for the current collection system. Interaction performance between pantograph and catenary system is subject to approval by the infrastructure manager when a new design and contraction of overhead contact line and pantograph are installed. Among the various performance, percentage of arcing at maximum line speed is a simple test method compared with contact force of pantograph due to direct sensing of pantagraph, calibrations, installations of train, and etc. On the other hand, percentage of arcing is need to reliable arcing detector and general requirements with accordance with EN 50317. In this paper, percentage of arcing are investigated on the function of duration of arc and proposed which is satiable of percentage of arcing. As a results, we proposed which duration of arcs are unsuitable from infrastructures point of view as performance testing for quality of current collection.

• Journal of the Korean Solar Energy Society
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• v.33 no.5
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• pp.69-75
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• 2013

To increase the efficiency of the photovoltaic, almost photovoltaic appliances are controlled by Maximum Power Point Tracking(MPPT). Existing most of the PV MPPT techniques have used power which multiplies sensed output current and voltage of the solar cell. However, these algorithms are unnecessarily complicated and too expensive for small and compact system. The other hand, the proposed MPPT technique is only one sensing of the MPPT converter's output current, so there is no need to insert another sensors of battery side. Therefore, this algorithm is simpler compared to the traditional approach and is suitable for low power solar system. Further, the novel proper charge/discharge algorithm for the battery with PV MPPT is developed. In this algorithm, there is CC battery charge mode and load discharge mode of the PV cell & battery dual. Also we design current control to regulate allowable current during the battery charging. The proposed algorithm will be applicable to battery included solar cell applications like solar lantern and solar remote control car. Finally, the proposed method has been verified with computer simulation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3236-3244
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• 2011

Negligent accidents are often caused by risk factors of working environment at most construction sites and construction schedules are delayed as the workers' work location and construction progress are not figured out accurately, and this leads to a lot of loss. In this paper, with the object of solving the problems at construction sites, RFID portable device, active tag and wireless RFID reader to provide the status of workers which is based on location are designed in order to send information about the location of workers and work progress in real time to a personal RFID device. Also an application system to monitor workers' approaching to prevent accidents from vehicles and danger zones and to manage the real time location of workers is designed.

• Advances in Computational Design
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• v.4 no.2
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• pp.73-90
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• 2019

The growth in the number of single-member households is a critical issue worldwide, especially among the elderly. For those living alone, who may be unaware of their health status or routines that could improve their health, a continuous healthcare monitoring system could provide valuable feedback. Assessing the performance adequacy of activities of daily living (ADL) can serve as a measure of an individual's health status; previous research has focused on determining a person's daily activities and extracting the most frequently performed behavioral patterns using camera recordings or wearable sensing techniques. However, existing methods used to extract common patterns of an occupant's activities in the home fail to address the spatio-temporal dimensions of human activities simultaneously. Though multiple sequence alignment (MSA) offers some advantages - such as inherent containment of the spatio-temporal data in sequence format, and rapid identification of hidden patterns - MSA has rarely been used to extract in-home ADL routines. This research proposes a method to extract a household occupant's ADL routines from a cumulative spatio-temporal data log of occupancy collected using a non-intrusive method (i.e., a tomographic motion detection system). The findings from an occupant's 28-day spatio-temporal activity log demonstrate the capacity of the proposed approach to identify routine patterns of an occupant's daily activities and to reveal the order, duration, and frequency of routine activities. Routine ADL patterns identified from the proposed approach are expected to provide a basis for detecting/evaluating abrupt or gradual changes of an occupant's ADL patterns that result from a physical or mental disorder, and can offer valuable information for home automation applications by enabling the prediction of ADL patterns.

• Journal of Practical Engineering Education
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• v.10 no.2
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• pp.113-118
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• 2018

The most important thing in vocational education and training is to enhance students' interest and understanding of the whole process of the production site. In this paper, we present a case on the implementation of tele-operation robot hand by learning factory based technology convergence education. It also suggests some points to be taken when applying the learning factory in the future curriculum. In order to implement the tele-operation robot hand, it is necessary to support the compulsory subjects of university level courses in domestic curriculum such as mechanic design, motor control, local communication implementation, sensing and feedback control. The educational research presented in this paper guides the students with the skills they need and understands the skills through self-study and practice, and implements the final products. This study will be useful as a base data when introducing the training process of training factory in the future.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.9
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• pp.98-104
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• 2022

Because a robot actuator is directly affected by the external force of the robot and accounts for the largest portion of the robot system weight, developing an optimized actuator suitable for each characteristic of the robot system is essential. Although there have been many developments and studies related to robot actuators in various industrial fields, lightweight and compact actuator designs that can control force are still lacking. In this study, a novel actuator module was developed, and its performance was verified experimentally. The structure and control of various robot systems can be optimized by utilizing the proposed actuator. It can be used for various tasks by sensing external force and through feedback control.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.49-59
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• 2017

Smart sensing plays a key role in a variety of IoT applications, and its importance is growing more and more together with the development of artificial intelligence. Therefore the importance of smart sensors cannot be overemphasized. However, most studies related to smart sensors have been focusing on specific application purposes, for example, security, energy saving, monitoring, and there are not much effort on researches on how to efficiently configure various types of smart sensors to be needed in the future. In this paper, a component-based framework with hierarchical structure for efficient construction of smart sensor is proposed and its application to smart home is designed and implemented. The proposed method shows that various types of smart sensors to be appeared in the near future can be configured through the design and development of necessary components within the proposed software framework. In addition, since it has a layered architecture, the configuration of the smart sensor can be expanded by inserting the internal or external layers. In particular, it is possible to independently design the internal and external modules when designing an IoT application service through connection with the external device layer. A small-scale smart home system is designed and implemented using the proposed method, and a home cloud operating as an external layer, is further designed to accommodate and manage multiple smart homes. By developing and thus adding the components of each layer, it will be possible to efficiently extend the range of applications such as smart cars, smart buildings, smart factories an so on.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.289-307
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• 2010

The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model selection for the general case of arbitrary (random or deterministic) design matrices and arbitrary nonzero entries of the signal. In this regard, it generalizes the notion of incoherence in the existing literature on model selection and introduces two fundamental measures of coherence-termed as the worst-case coherence and the average coherence-among the columns of a design matrix. It utilizes these two measures of coherence to provide an in-depth analysis of a simple, model-order agnostic one-step thresholding (OST) algorithm for model selection and proves that OST is feasible for exact as well as partial model selection as long as the design matrix obeys an easily verifiable property, which is termed as the coherence property. One of the key insights offered by the ensuing analysis in this regard is that OST can successfully carry out model selection even when methods based on convex optimization such as the lasso fail due to the rank deficiency of the submatrices of the design matrix. In addition, the paper establishes that if the design matrix has reasonably small worst-case and average coherence then OST performs near-optimally when either (i) the energy of any nonzero entry of the signal is close to the average signal energy per nonzero entry or (ii) the signal-to-noise ratio in the measurement system is not too high. Finally, two other key contributions of the paper are that (i) it provides bounds on the average coherence of Gaussian matrices and Gabor frames, and (ii) it extends the results on model selection using OST to low-complexity, model-order agnostic recovery of sparse signals with arbitrary nonzero entries. In particular, this part of the analysis in the paper implies that an Alltop Gabor frame together with OST can successfully carry out model selection and recovery of sparse signals irrespective of the phases of the nonzero entries even if the number of nonzero entries scales almost linearly with the number of rows of the Alltop Gabor frame.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12B
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• pp.1708-1721
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• 2011

Recent outbreak of cattle diseases such as foot-and-mouth disease(FMD) requires constant monitoring of burial sites of mass cull of cattles. However, current monitoring system takes environmental samples from burial sites with period of between one and two weeks, which makes it impossible for non-stop management of hazardous bio-waste. Therefore, in this study, we suggest an improved real-time environmental monitoring system for such bio-hazardous sites based on wireless sensor networks, which makes constant surveillance of the FMD burial sites possible. The system consists mainly several wireless environmental monitoring sensors(i.e dust, Co2, VOC, NH3, H2S, temperature, humidity) nodes and GPS location tracking nodes. Through analysis of the relayed of the environmental monitoring data via gateway, the system makes it possible for constant monitoring and quick response for emergency situation of the burial sites. In order to test the effectiveness of the system, we have installed a set of sensor to gas outlets of the burial sites, then collected and analyzed measured bio-sensing data. We have conducted simulated emergency test runs and was able to detect and monitor the foul smell constantly. With our study, we confirm that the preventive measures and quick response of bio environmental accident are possible with the help of a real-time environmental monitoring system.