• Journal of the Korean Institute of Gas
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• v.18 no.3
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• pp.53-59
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• 2014

In this study, we suggest a system to build the monitoring model for compressed natural gas (CNG) stations, operated in only non-stationary modes, and perform the real-time monitoring and the abnormality diagnosis using principal component analysis (PCA) that is suitable for processing large amounts of multi-dimensional data among multivariate statistical analysis methods. We build the model by the calculation of the new characteristic variables, called as the major components, finding the factors representing the trend of process operation, or a combination of variables among 7 pressure sensor data and 5 temperature sensor data collected from a CNG station at every second. The real-time monitoring is performed reflecting the data of process operation measured in real-time against the built model. As a result of conducting the test of monitoring in order to improve the accuracy of the system and verification, all data in the normal operation were distinguished as normal. The cause of abnormality could be refined, when abnormality was detected successfully, by tracking the variables out of the score plot.

• Journal of the Korean Society of Marine Environment & Safety
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• v.18 no.5
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• pp.488-495
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• 2012

The real-time indoor location technology using radio waves has been studied in a variety of environments. One of them, a ship which consists of steel structure has high reception rate but causes significant ranging error due to the reflection of radio waves. In order to reduce location measurement errors that occurs in such a environment, this paper, based on CSS of IEEE 802.15.4a, presents compensation algorithm for localization using modified bilateration and pyroelectric sensor in a ship. The proposed system reduces the number of fixed nodes by estimating the appropriate reception distance between mobile node and fixed node through the analysis of CSS characteristic in a narrow passage such as ship corridors. Also, in the corner section which the ranging errors are significantly fluctuated due to the reflection and diffraction of radio waves, we recognize the location by tracking the a moving section using modified bilateration technique and pyroelectric sensor. The experimental results show that the location accuracy and efficiency of the proposed algorithm are improved 86.2 % compared to general method.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.49 no.1
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• pp.15-24
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• 2012

In this paper, we suggest the dynamic-response-free SMPS using a new high-resolution DPWM generator based on switched-capacitor delay technique. In the proposed system, duty ratio of DPWM is controlled by voltage slope of an internal capacitor using switched-capacitor delay technique. In the proposed circuit, it is possible to track output voltage by controlling current of the internal capacitor of the DPWM generator through comparison between the feedback voltage and the reference voltage. Therefore the proposed circuit is not restricted by the dynamic-response characteristic which is a problem in the existing SMPS using the closed-loop control method. In addition, it has great advantage that ringing phenomenon due to overshoot/undershoot does not appear on output voltage. The proposed circuit can operate at switching frequencies of 1MHz~10MHz using internal operating frequency of 100 MHz. The maximum current of the core circuit is 2.7 mA and the total current of the entire circuit including output buffer is 15 mA at the switching frequency of 10 MHz. The proposed circuit has DPWM duty ratio resolution of 0.125 %. It can accommodate load current up to 1 A. The maximum ripple of output voltage is 8 mV. To verify operation of the proposed circuit, we carried out simulation with Dongbu Hitek BCD $0.35{\mu}m$ technology parameter.

• Journal of the Korea Society of Computer and Information
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• v.16 no.9
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• pp.69-76
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• 2011

According to the related reports, about 60 percents of ship collisions have resulted from operating mistake caused by human factor. Specially, the report said that negligence of observation caused 66.8 percents of the accidents due to a human factor. Hence automatic detection and tracking of an object from an IR images are crucial for safety navigation because it can relieve officer's burden and remedies imperfections of human visual system. In this paper, we present a method to detect an object such as ship, rock and buoy from a sea IR image. Most edge directions of the sea image are horizontal and most vertical edges come out from the object areas. The presented method uses them as a characteristic for the object detection. Vertical edges are extracted from the input image and isolated edges are eliminated. Then morphological closing operation is performed on the vertical edges. This caused vertical edges that actually compose an object be connected and become an object candidate region. Next, reference object regions are extracted using horizontal edges, which appear on the boundaries between surface of the sea and the objects. Finally, object regions are acquired by sequentially integrating reference region and object candidate regions.

• Composites Research
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• v.26 no.6
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• pp.363-372
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• 2013

Numerical simulation for Resin Transfer Molding manufacturing process is attempted by using the eXtended Finite Element Method (XFEM) combined with the level set method. XFEM allows to obtaining a good numerical precision of the pressure near the resin flow front, where its gradient is discontinuous. The enriched shape functions of XFEM are derived by using the level set values so as to correctly describe the interpolation with the resin flow front. In addition, the level set method is used to transport the resin flow front at each time step during the mold filling. The level set values are calculated by an implicit characteristic Galerkin FEM. The multi-frontal solver of IPSAP is adopted to solve the system. This work is validated by comparing the obtained results with analytic solutions. Moreover, a localization method of XFEM and level set method is proposed to increase the computing efficiency. The computation domain is reduced to the small region near the resin flow front. Therefore, the total computing time is strongly reduced by it. The efficiency test is made with a simple channel flow model. Several application examples are analyzed to demonstrate ability of this method.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.12
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• pp.1087-1092
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• 2010

A micro 3D-PTV system has been constructed using a single camera system. Two viewing holes were created behind the object lens of the microscopic system to construct a stereoscopic viewing image. A hybrid recursive PTV algorithm was used. A concept of epipolar line was adopted to eliminate many spurious candidates. Three-dimensional velocity vector fields were obtained by calculating the three-dimensional displacements of particles that were identified as being identical. The system consists of a laser light source (Ar-ion, 500 mW), one high-definition camera ($1028{\times}1024$ pixels, 500 fps), a circular plate with two viewing holes, and a host computer. The performance of the developed algorithm was tested using artificial images. The characteristic of the vector recovery ratio was investigated for the particle numbers. A micro backward-facing step channel ($H{\times}h{\times}W:\;36{\mu}m{\times}70{\mu}m{\times}3000{\mu}m$) was measured using the developed measurement system. The results were in good qualitative agreement with other results.

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.1-10
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• 2009

One of major purposes of a RFID system is to track moving objects using tags attached to the objects. Because a tagged object has both location and time information expressed as the location of the reader, we can index the trajectory of the object like existing spatiotemporal objects. More efficient tracking may be possible if a spatiotemporal trajectory can be formed of a tag, but there has not been much research on tag trajectory indexes. A characteristic that distinguishes tags from existing spatiotemporal objects is that a tag creates a separate trajectory in each reader by entering and then leaving the reader. As a result, there is a trajectory interruption interval between readers, in which the tag cannot be located, and this makes it difficult to track the tag. In addition, the point tags that only enter and don't leave readers do not create trajectories, so cannot be tracked. To solve this problem, we propose a tag trajectory index called TR-tree (tag trajectory R-tree in RFID system) that can track a tag by combining separate trajectories among readers into one trajectory. The results show that TR-tree, which overcomes the trajectory interruption superior performance than TPIR-tree and R-tree.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.51-56
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• 2019

This paper related with the performance comparison of CCA and RMMA blind adaptive equalization in order to reduce the intersymbol interference which is occurred in channel when transmitting the 16-QAM signal, high spectrum efficiencies of nonconstant modulus characteristic. The CCA possible to improve the misadustment and initial convergence by compacting the every signal constellation of 16 by using the sliced symbol of the decision device output, namely statistical symbol, but incresing the computational cost. The RMMA possible to minimize the fast convergence speed and misadjustment and channel tracking capability without increasing the computational cost by obtain the error signal after transform to 4 constant modulus signal based on the region of signal constellation located. In this paper, these algorithm were implemented in the same channel, and the blind adaptive equalization performance were compared using the equalizer output signal constellation, residual isi, MSE, SER. As a result of simulation, the RMMA has better performance in output signal constellation, residual isi and MSE compared to the CCA, but has slow convergence speed about 1.3 times. And the SER performance presenting the robustness to the noise signal, the CCA has more beeter in less SNR, but the RMMA has better in greater than 6dB in SNR.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1266-1271
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• 2022

Cats have strong wildness so they have a characteristic of hiding diseases well. The disease may have already worsened when the guardian finds out that the cat has a disease. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia, polyuria, and frequent urination more quickly. In this paper, 1) Efficient version of DeepLabCut for pose estimation, 2) YOLO v4 for object detection, 3) LSTM is used for behavior prediction, and 4) BoT-SORT is used for object tracking running on an artificial intelligence device. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the server system.

• Education of Primary School Mathematics
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• v.26 no.4
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• pp.333-348
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• 2023

Clear analysis and diagnosis of various characteristic factors of individual students is the most important in order to realize individual customized teaching and learning, which is considered the most essential function of math artificial intelligence-based digital textbooks. In this study, analysis factors and tools for individual customized learning diagnosis and construction models for data collection and analysis were derived from mathematical AI digital textbooks. To this end, according to the Ministry of Education's recent plan to apply AI digital textbooks, the demand for AI digital textbooks in mathematics, personalized learning and prior research on data for it, and factors for learner analysis in mathematics digital platforms were reviewed. As a result of the study, the researcher summarized the factors for learning analysis as factors for learning readiness, process and performance, achievement, weakness, and propensity analysis as factors for learning duration, problem solving time, concentration, math learning habits, and emotional analysis as factors for confidence, interest, anxiety, learning motivation, value perception, and attitude analysis as factors for learning analysis. In addition, the researcher proposed noon data on the problem, learning progress rate, screen recording data on student activities, event data, eye tracking device, and self-response questionnaires as data collection tools for these factors. Finally, a data collection model was proposed that time-series these factors before, during, and after learning.