• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.2052-2053
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• 2007

Recently, the importance of supplying the reliable electric power is increasing. Breaking insulation of stator winding is major cause of fault in rotator machine. On-line PD detecting is useful technique to diagnose rotator machine. However, interpretation of its results in time domain is very complex because of the mixed results with PD(Partial Discharge) and noise signal. Therefore, the results were analyzed in frequency domain by FFT (Fast Fourier Transform) to detect precise PD signals. The purpose of this paper is to describe the optimal frequency range to discriminate the PD and noise signal.

• Journal of Yeungnam Medical Science
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• v.35 no.1
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• pp.1-6
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• 2018

Alzheimer's disease (AD) is a neurodegenerative disorder associated with extracellular plaques, composed of amyloid-beta ($A{\beta}$), in the brain. Although the precise mechanism underlying the neurotoxicity of $A{\beta}$ has not been established, $A{\beta}$ accumulation is the primary event in a cascade of events that lead to neurofibrillary degeneration and dementia. In particular, the $A{\beta}$ burden, as assessed by neuroimaging, has proved to be an excellent predictive biomarker. Positron emission tomography, using ligands such as $^{11}C$-labeled Pittsburgh Compound B or $^{18}F$-labeled tracers, such as $^{18}F$-florbetaben, $^{18}F$-florbetapir, and $^{18}F$-flutemetamol, which bind to $A{\beta}$ deposits in the brain, has been a valuable technique for visualizing and quantifying the deposition of $A{\beta}$ throughout the brain in living subjects. $A{\beta}$ imaging has very high sensitivity for detecting AD pathology. In addition, it can predict the progression from mild cognitive impairment to AD, and contribute to the development of disease-specific therapies.

• Journal of the Semiconductor & Display Technology
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• v.9 no.2
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• pp.79-85
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• 2010

In this paper, we propose a web inspection system (WIS) for real-time detection of paper defects which can cause critical fractures during papermaking process. Our system incorporates high speed line-scan camera, lighting system, and detection algorithm to provide robust and precise detection of paper defects in real-time. Since edge defects are very crucial to the paper fractures, our system focuses on the edge region of the paper instead of inspecting the whole paper area. In our algorithm, image projection and sub-pixel operation are utilized to detect the edge defects precisely and connected component labeling and shape analysis techniques are adopted to extract various kinds of the region defects. Experimental results revealed that our web inspection system is very efficient for detecting paper defects during papermaking processes.

• Journal of Platform Technology
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• v.10 no.3
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• pp.21-29
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• 2022

Recently, the scope of the smart factory has been expanded, and process research to minimize the part that requires manpower in many processes is increasing. In the case of detecting defects in the appearance of small products, precise verification using a vision system is required. Reliability and speed of inspection are inefficient for human inspection. In this paper, we propose an algorithm for inspecting product appearance defects using a machine vision system. In the case of the remote control targeted in this paper, the appearance is different for each product. Due to the characteristics of the remote control product, the data obtained using two cameras is compared with the master data after denoising and stitching steps are completed. When the algorithm presented in this paper is used, it is possible to detect defects in a shorter time and more accurately compared to the existing human inspection.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.97-105
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• 2022

Web services show a rapid evolution and integration to meet the increased users' requirements. Thus, web services undergo updates and may have performance degradation due to undetected faults in the updated versions. Due to these faults, many performances and regression anomalies in web services may occur in real-world scenarios. This paper proposed applying the deep learning model and innovative explainable framework to detect performance and regression anomalies in web services. This study indicated that upper bound and lower bound values in performance metrics provide us with the simple means to detect the performance and regression anomalies in updated versions of web services. The explainable deep learning method enabled us to decide the precise use of deep learning to detect performance and anomalies in web services. The evaluation results of the proposed approach showed us the detection of unusual behavior of web service. The proposed approach is efficient and straightforward in detecting regression anomalies in web services compared with the existing approaches.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.2_1
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• pp.225-230
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• 2023

This research addresses sound command based human tracking problems for autonomous cleaning mobile robot in a networked AI space. To solve the problem, the difference among the traveling times of the sound command to each of three microphones has been used to calculate the distance and orientation of the sound from the cleaning mobile robot, which carries the microphone array. The cross-correlation between two signals has been applied for detecting the time difference between two signals, which provides reliable and precise value of the time difference compared to the conventional methods. To generate the tracking direction to the sound command, fuzzy rules are applied and the results are used to control the cleaning mobile robot in a real-time. Finally the experiment results show that the proposed algorithm works well, even though the mobile robot knows little about the environment.

• Analytical Science and Technology
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• v.36 no.4
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• pp.161-169
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• 2023

In this study, a straightforward and precise nitrogen/sulphur-codoped carbon dots (N/S-CD) was produced using a microwave irradiation approach. The N/S-CD was formulated from succinic acid (SA), bis-(3-aminopropyl)-amine (BAPA), and sodium thiosulphate (STS) as sources of carbon, nitrogen, and sulphur, respectively. The synthesized N/S-CD established a valuable quantum yield (QY) of 70 % and was sensitive to aluminium ion (Al³⁺) with a detection limit of 0.21 µM and a linear concentration range of 0-100 µM. When detecting Al³⁺ in real water samples, the N/S-CD resulted in a satisfactory recovery in the range of 91.14 %-103.37 %. Thus, the proposed study is very promising for Al³⁺ detection in environmental water samples.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.97-98
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• 2023

Recently, the use of digital technology in architectural technology is gradually increasing with the development of various industrial technologies. There are artificial intelligence and drones in the field of architecture, and among them, deep learning technology has been introduced to conduct research in areas such as precise inspection of buildings, and it is expressed in a highly reliable way. When a building is deteriorated, various defects such as cracks in the surface and subsidence of the structure may occur. Since these cracks can represent serious structural damage in the future, the detection of cracks was conducted using artificial intelligence that can detect and identify surface defects by detecting cracks and aging of buildings.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.1
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• pp.7-14
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• 2013

Presently, there are many different technologies used for position detection. However, as signal-receiving devices operating in different locations must detect the precise position of objects located at long distances, it is essential to know the precise time at which an object's or a user's terminal device sends a signal. For this purpose, the existing time of arrival (ToA) technology is not sufficiently reliable, and the existing time difference of arrival (TDoA) technology is more suitable. If a TDoA-based electric surveillance system and other tracking devices fail to achieve precise time-synchronization between devices with separation distance operation, it is impossible to obtain correct TDoA values from the signals sent by the signal-receiving devices; this failure to obtain the correct values directly affects the location estimation error. For this reason, the technology for achieving precise time synchronization between signal-receiving devices in separation distance operation, among the technologies previously mentioned, is a core technology for detecting TDoA-based locations. In this paper, the accuracy of the proposed time synchronization and the measurement error in the TDoA-based location detection technology is evaluated. The TDoA-based location measurement error is significantly improved when using the proposed method for time-synchronization error reduction.

• The KIPS Transactions:PartD
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• v.15D no.6
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• pp.825-840
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• 2008

Refactoring is a kind of software modification process that improves system qualities internally but maintains system functions externally. What should be improved on the existing source codes should take precedence over the others in such a modification process using this refactoring. Martin Fowler and Kent Beck proposed a method that identifies code smells for this purpose. Also, some studies on determining what refactoring will be applied to which targets through detecting code smells in codes were presented. However, these studies have a lot of disadvantages that show a lack of precise description for such code smells and detect limited code smells only. In addition, these studies showed other disadvantages that generate ambiguity in behavior preservation due to the fact that a description method of pre-conditions for the behavior preservation is included in a refactoring process or unformalized. Thus, our study represents a precise specification of code smells using OCL and proposes a framework that performs a refactoring process through the automatic detection of code smells using an OCL interpreter. Furthermore, we perform the automatic detection in which the code smells are be specified by using OCL to the java program and verify its applicability and effectivity through applying a refactoring process.