• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.616-619
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• 1995

This paper describes developement of on-line system for vibration signal analysis. In the power system, the main reason of transformer fault is due to a large amount of current by a short-circuit and a ground-fault. The electromagnetic force caused by fault-current deforms transformer windings and results in vibration pattern change. Therefore if the continuous on-line vibration monitoring on transformer is performed, an incipient failure can be detected. The developed system is composed of data acquisition devices, user interface program, signal processing program, diagnosis and trend analysis program, self diagnosis program and communication program.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.4
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• pp.559-564
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• 1999

A particle image velocimetry is the representative technique for measuring flow velocities at whole field simultaneously. The present study adopted the PTV method for velocity acquisition in a square enclosure with initially isothermal fluid by using a general lamp-based sheet light source. The enclosure was composed of hot and cold vertical wall and was confined by two horizon-tal adiabatic walls. The drift velocities were measured and the drift was visualized by PTV for a rayleigh number of 5.28{\times}10^8.$ Obtained instant simulataneous velocity vectors show flow pattern and the result of horizontal velocity profile agree well with the numerical result.

• International Journal of Railway
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• v.1 no.4
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• pp.169-174
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• 2008

Experimental study has been conducted to clarify the internal and external pressure variation characteristics for KTX(Korea Train eXpress) passing through tunnel. Abrupt pressure variation gives rise to the ear-discomfort for passenger and fatigue for car body. In this study, the internal and external pressure variation are measured by using KTX real train experiment and on-board portable data acquisition system in Gyeongbu high speed commercial line. The tunnels from 200 m to 4000 m in length are chosen for the investigation of tunnel length effects. From the results of experiment, the internal pressure variation rate for all the test tunnels is lower than the standard criteria of 200 Pa/s. And, the critical tunnel lengths for pressure wave pattern are classified into 7 groups by using the theoretical L-t diagram analysis.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2000.11a
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• pp.29-33
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• 2000

The classical image reconstruction for stripmap SAR is based on the Fresnel approximation which utilizes deramping or chirp deconvolution in the synthetic aperture(slow-time) domain. Another approach in formulating stripmap SAR processing and imaging is based on the SAR wavefront reconsturction theory, and analysis of the SAR signal in the slow-time via the spherical wave Fourier decomposition of the radar radiation pattern. In this paper, we compare the Fresnel approximation and the wavefrong reconstruction methods using simulated stripmap SAR dada.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1478-1499
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• 2024

Coronavirus disease (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. COVID-19 become an active epidemic disease due to its spread around the globe. The main causes of the spread are through interaction and transmission of the droplets through coughing and sneezing. The spread can be minimized by isolating the susceptible patients. However, it necessitates remote monitoring to check the breathing issues of the patient remotely to minimize the interactions for spread minimization. Thus, in this article, we offer a wearable-IoTs-centered framework for remote monitoring and recognition of the breathing pattern and abnormal breath detection for timely providing the proper oxygen level required. We propose wearable sensors accelerometer and gyroscope-based breathing time-series data acquisition, temporal features extraction, and machine learning algorithms for pattern detection and abnormality identification. The sensors provide the data through Bluetooth and receive it at the server for further processing and recognition. We collect the six breathing patterns from the twenty subjects and each pattern is recorded for about five minutes. We match prediction accuracies of all machine learning models under study (i.e. Random forest, Gradient boosting tree, Decision tree, and K-nearest neighbor. Our results show that normal breathing and Bradypnea are the most correctly recognized breathing patterns. However, in some cases, algorithm recognizes kussmaul well also. Collectively, the classification outcomes of Random Forest and Gradient Boost Trees are better than the other two algorithms.

• Fashion & Textile Research Journal
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• v.22 no.5
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• pp.650-659
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• 2020

The present study provides reference data required for the design of clothing for the elderly by analyzing the body surface area during fitness motion based on 3D scan data of Korean elderly women. This study was conducted with the procedures of (1) survey of motions and main muscles for fitness, (2) acquisition of 3D scan data, and (3) analysis of rate of change for body surface area during fitness motion. Acquisition of 3D body scan data was obtained from seven elderly females (age: 64-77). We selected 66 anatomical landmarks (40 upper body and 22 lower body) by referring to previous studies. Body surface was segmented by connecting the landmarks marked on the 3D scan data acquired. Analysis of body surface area was conducted in terms of the change rate of surface area in 9 postures of elbow 0°, 90° and 180° for flexion, shoulder 90°, 180° for flexion, shoulder 0°, 180° for abduction, hip 90° for flexion, and knee 90° for flexion compared to the those in the standing posture. The amount of changes in body surface area were 12%-62% in the upper body, 15%-77% in the arm, and 10%-51% in the lower body. A future study on the rate of change of body surface length is needed; in addition, a study on how to apply the results of body surface area and body surface length analysis to clothing pattern design is also necessary.

• Journal of the Korean Society for Nondestructive Testing
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• v.13 no.4
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• pp.25-31
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• 1994

A system for EMAT, which generates ultrasound by electro-magnectic forces and performs nondestructive testing in noncontact, was established. By linking it with a 3 axis scanning system and a data acquisition and processing system the automation of EMAT testing was attempted. A EMAT sensor was fabricated and the directivity pattern of it was measured. To be suitable automation, it has a transmitter and a receiver in one case and the main beam direction of it can be controlled by the frequency of driving signal. A program which controls the EMAT system, the 3 axis scanner and the data acquisition and processing system was developed. It also processes acquired data and displays the processing results. IBM-PC/AT compatible PC was used as main controller and the stratage of the program is emulation of real devices on the PC monitor. To provide the performance of the established EMAT system, two aluminium blocks containing artificial flaws and a welded aluminium block were tested. The result of the tests were satisfactory.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.156-166
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• 2014

As of 2014, KARI (Korea Aerospace Research Institute) operates two high-resolution satellites such as Kompsat-2 and Kompsat-3. Kompsat-3 has capability of in-track stereo images acquisition but it is quite limited because the stereo mode lowers the spatial coverage in a trajectory. In this paper we analyze the epipolar geometry from the heterogeneous Kompsat-2 and Kompsat-3 image combination to epipolar resample them for 3D spatial data acquisition. The analysis was carried out using the piecewise approach with RPCs (Rational Polynomial Coefficients) and the result showed the parabolic epipolar curve pattern. We also concluded that the third order polynomial transformation is required for epipolar image resampling. The resampled image pair showed 1 pixel level of y-parallax and can be used for 3D display and digitizing.

• Industrial Engineering and Management Systems
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• v.15 no.3
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• pp.224-230
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• 2016

The use of new words, numerous spoken languages, and abbreviations on the Internet is extensive. As such, automatically acquiring words for the purpose of analyzing Internet content is very difficult. In a previous study, we proposed a method for Japanese word segmentation using character N-grams. The previously proposed method is based on a simple state-transition model that is established under the assumption that the input document is described based on four states (denoted as A, B, C, and D) specified beforehand: state A represents words (nouns, verbs, etc.); state B represents statement separators (punctuation marks, conjunctions, etc.); state C represents postpositions (namely, words that follow nouns); and state D represents prepositions (namely, words that precede nouns). According to this state-transition model, based on the states applied to each pseudo-word, we search the document from beginning to end for an accessible pattern. In other words, the process of this transition detects some words during the search. In the present paper, we perform experiments based on the proposed word acquisition algorithm using Japanese and Chinese newspaper articles. These articles were obtained from Japan's Kyoto University and the Chinese People's Daily. The proposed method does not depend on the language structure. If text documents are expressed in Unicode the proposed method can, using the same algorithm, obtain words in Japanese and Chinese, which do not contain spaces between words. Hence, we demonstrate that the proposed method is language independent.

• Journal of IKEEE
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• v.24 no.2
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• pp.632-637
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• 2020

The non-intrusive load monitoring (NILM) is an important way to cost-effective real-time monitoring the energy consumption and time of use for each appliance in a home or business using aggregated energy from a single recording meter. In this paper, we collect from the smart farm's power consumption data acquisition system to the server via an LTE modem, converted the total power consumption, and the power of individual electric devices into HDF5 format and performed NILM analysis. We perform NILM analysis using open source denoising autoencoder (DAE), long short-term memory (LSTM), gated recurrent unit (GRU), and sequence-to-point (seq2point) learning methods.