• Current Optics and Photonics
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• v.6 no.2
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• pp.137-142
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• 2022

Leak detection is one of the most important challenges in condition monitoring of water pipelines. Fiber Bragg grating (FBG) sensors offer an attractive technique to detect leak signals. In this paper, leak measurements were conducted on a water distribution pilot plant with a length of 270 m and a diameter of 100 mm. FBG sensors were installed on the pipeline surface and used to detect leak vibration signals. The leak was demonstrated with 1-, 2-, 3-, and 4-mm diameter leak holes in four different pipe types. The frequency response of leak signals was analyzed by fast Fourier transform analysis in real time. In the experiment, the frequency range of leak signals was approximately 340-440 Hz. The frequency shifts of leak signals according to the pipe type and the size of the leak hole were demonstrated at a pressure of 1.8 bar and a flow rate of 25.51 m³/h. Results show that frequency shifts detected by FBG sensors can be used to detect leaks in pipelines.

• Journal of Pharmacopuncture
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• v.26 no.3
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• pp.276-284
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• 2023

Objectives: Previous studies have shown that anger can lead to frontal lobe α (8-13 Hz) band asymmetry (FAA) in electroencephalogram (EEG), in accordance with motivational direction. This pilot study aimed to investigate the impact of acupuncture on FAA elicited by anger. Methods: Thirty-four right-handed participants scoring above 75 points on the Novaco Anger Scale were included. Baseline EEG signals were recorded for eight minutes using a 32-channel cap under comfortable conditions. Anger was induced through a nine-minute sequence of Articulated Thoughts in Simulated Situations (ATSS) task. Following that, participants received acupuncture at GB20 and GB21 for 10 minutes. Fast Fourier transform was employed for frequency analysis, and repeated measure ANOVA was conducted for statistical analysis. Results: The results revealed that participants exhibited significantly higher FAA (p = 0.026), particularly in the left hemisphere, after the ATSS task sequence compared to the baseline. During acupuncture treatment, the greater left-sided FAA was significantly reduced (p = 0.027) and reversed. Upon the cessation of acupuncture, FAA returned to a value between the baseline and the anger-evoked stage (p = 0.046). Conclusion: The EEG results of this study revealed that anger stimulation induced an increase in left-sided FAA, which was effectively alleviated by acupuncture. This led to an immediate restoration of FAA asymmetry induced by anger. These findings suggest the potential of acupuncture as a treatment option for reducing FAA associated with anger.

• Science of Emotion and Sensibility
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• v.19 no.4
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• pp.119-126
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• 2016

In this study, we investigated the effects of mouth breathing on brain activity through electroencephalogram (EEG). EEG was performed on 12 healthy volunteers of age ranging from 21 to 27 years (male: female = 6:6, non-smoker). Brain waves on resting state (Rest_N/Rest_M) and auditory-language stimuli state (Eng_N/Eng_M) were recorded during mouth and nose breathing. Four different regions (R1~R4) were classified based on the brain functionality. And each channel (e.g., Pf1 and Pf2) and frequency (${\alpha}$, ${\beta}$, ${\gamma}$, and ${\theta}$) were analyzed using their absolute power ratios of fast Fourier transform (FFT). The results showed that there was no significant difference between Rest_N and Rest_M. Eng_N had significantly higher brain activity than Rest_N; on the other hand, there was no significant difference between Rest_M and Eng_M. These results demonstrate that mouth-breathing on resting state does not induce any significant effects on brain activity and/or functionality, even though it causes subtle temporary inconvenience. In addition to the uncomfort, the brain activity can be adversely influenced by mouth-breathing, which could lower the cognitive skills under certain circumstances.

• Nuclear Engineering and Technology
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• v.52 no.6
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• pp.1201-1207
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• 2020

This study explored whether MXene (Ti₃C₂T_x) could remove radioactive Cs⁺ from model nuclear wastewater. Various adsorption tests were performed and the physical aspects of the interaction were investigated. We varied the MXene dosage, Cs⁺ initial concentration, solution pH, solution temperature and exposure time. MXene adsorption exhibited very fast kinetics, based on the fact that equilibrium was achieved within 1 h. MXene exhibited an outstanding adsorption capacity (148 mg g^-1) at adsorbent and adsorbate concentrations of 5 and 2 mg L^-1, respectively, at neutral pH condition (i.e., pH 7). We explored Cs⁺ adsorption by MXene in the presence of four different ions (NaCl, KCl, CaCl₂ and MgCl₂) and three different organic acids (sodium oleate, oxalic acid, and citric acid). The Cs⁺ removal rate changed in the presence of these components; adsorption of Cs⁺ by MXene thus involved ion exchange, supported by both Fourier-transform infrared spectroscopy and X-ray photoelectron spectroscopy. We confirmed that MXene was re-usable for at least four cycles. MXene is cost-effective and practical when used to adsorb radionuclides (e.g., Cs⁺) in nuclear wastewater.

• The Journal of Korea Robotics Society
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• v.7 no.3
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• pp.171-181
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• 2012

Outdoor mobile robots are faced with various terrain types having different characteristics. To run safely and carry out the mission, mobile robot should recognize terrain types, physical and geometric characteristics and so on. It is essential to control appropriate motion for each terrain characteristics. One way to determine the terrain types is to use non-contact sensor data such as vision and laser sensor. Another way is to use contact sensor data such as slope of body, vibration and current of motor that are reaction data from the ground to the tire. In this paper, we presented experimental results on terrain classification using contact sensor data. We made a mobile robot for collecting contact sensor data and collected data from four terrains we chose for experimental terrains. Through analysis of the collecting data, we suggested a new method of terrain feature extraction considering physical characteristics and confirmed that the proposed method can classify the four terrains that we chose for experimental terrains. We can also be confirmed that terrain feature extraction method using Fast Fourier Transform (FFT) typically used in previous studies and the proposed method have similar classification performance through back propagation learning algorithm. However, both methods differ in the amount of data including terrain feature information. So we defined an index determined by the amount of terrain feature information and classification error rate. And the index can evaluate classification efficiency. We compared the results of each method through the index. The comparison showed that our method is more efficient than the existing method.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.675-687
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• 2010

Structural Health Monitoring (SHM) is the science and technology of monitoring and assessing the condition of aerospace, civil and mechanical infrastructures using a sensing system integrated into the structure. Impedance-based SHM measures impedance of a structure using a PZT (Lead Zirconate Titanate) patch. This paper presents a low-power wireless autonomous and active SHM node called Autonomous SHM Sensor 2 (ASN-2), which is based on the impedance method. In this study, we incorporated three methods to save power. First, entire data processing is performed on-board, which minimizes radio transmission time. Considering that the radio of a wireless sensor node consumes the highest power among all modules, reduction of the transmission time saves substantial power. Second, a rectangular pulse train is used to excite a PZT patch instead of a sinusoidal wave. This eliminates a digital-to-analog converter and reduces the memory space. Third, ASN-2 senses the phase of the response signal instead of the magnitude. Sensing the phase of the signal eliminates an analog-to-digital converter and Fast Fourier Transform operation, which not only saves power, but also enables us to use a low-end low-power processor. Our SHM sensor node ASN-2 is implemented using a TI MSP430 microcontroller evaluation board. A cluster of ASN-2 nodes forms a wireless network. Each node wakes up at a predetermined interval, such as once in four hours, performs an SHM operation, reports the result to the central node wirelessly, and returns to sleep. The power consumption of our ASN-2 is 0.15 mW during the inactive mode and 18 mW during the active mode. Each SHM operation takes about 13 seconds to consume 236 mJ. When our ASN-2 operates once in every four hours, it is estimated to run for about 2.5 years with two AAA-size batteries ignoring the internal battery leakage.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1407-1419
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• 2020

Long time-series gridded data is crucial for the analyses of Earth environmental changes. Climate reanalysis and satellite images are now used as global-scale periodical and quantitative information for the atmosphere and land surface. This paper examines the feasibility of DCT-PLS (penalized least square regression based on discrete cosine transform) for the spatial gap filling of gridded data through the experiments for multiple variables. Because gap-free data is required for an objective comparison of original with gap-filled data, we used LDAPS (Local Data Assimilation and Prediction System) daily data and MODIS (Moderate Resolution Imaging Spectroradiometer) monthly products. In the experiments for relative humidity, wind speed, LST (land surface temperature), and NDVI (normalized difference vegetation index), we made sure that randomly generated gaps were retrieved very similar to the original data. The correlation coefficients were over 0.95 for the four variables. Because the DCT-PLS method does not require ancillary data and can refer to both spatial and temporal information with a fast computation, it can be applied to operative systems for satellite data processing.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.6
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• pp.36-45
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• 2005

This paper addresses the application of motor current spectral analysis for the detection of rolling-element bearing damage in induction machines. We set the experimental test bed. They is composed of the normal condition bearing system, the abnormal rolling-element bearing system of 2 type induction motors with shaft deflection system by external force and a hole drilled through the outer race of the shaft end bearing of the four pole test motor. We have developed the embedded distributed fault tolerant and fault diagnosis system for industrial motor. These mechanisms are based on two 32-bit DSPs and each TMS320F2407 DSP module is checking stator current The effects on the stator current spectrum are described and related frequencies are also determined. This is an important result in the formulation of a fault detection scheme that monitors the stator currents. We utilized the FFT(Fast Fourier Transform), Wavelet analysis and averaging signal pattern by inner product tool to analyze stator current components. Especially, the analyzed results by inner product clearly illustrate that the stator signature analysis can be used to identify the presence of a bearing fault.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2271-2280
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• 1999

In this paper, a variable motion estimation scheme based on HBMA(Hierarchical Block Matching Algorithm) to improve the performance and to reduce heavy computational and transmission load, is presented. The proposed algorithm is composed of four steps. First, block activity for each block is defined using the edge information of differential image between two sequential images, and then average block activity of the present image is found by taking the mean of block activity. Secondly, camera pan compensation is carried out, according to the average activity of the image, in the hierarchical pyramid structure constructed by wavelet transform. Next, the LUT classifying each block into one among Moving, No Moving, Semi-Moving Block according to the block activity compensated camera pan is obtained. Finally, as varying the block size and adaptively selecting the initial search layer and the search range referring to LUT, the proposed variable HBMA can effectively carries out fast motion estimation in the hierarchical pyramid structure. The cost function needed above-mentioned each step is only the block activity defined by the edge information of the differential image in the sequential images.

• Journal of Microbiology and Biotechnology
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• v.24 no.4
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• pp.453-464
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• 2014

The current research was focused on the extracellular biosynthesis of bactericidal silver nanoparticles (AgNPs) using cell-free supernatant of a local isolate previously identified as a novel Streptomyces aegyptia NEAE 102. The biosynthesis of silver nanoparticles by Streptomyces aegyptia NEAE 102 was quite fast and required far less time than previously published strains. The produced particles showed a single surface plasmon resonance peak at 400 nm by UV-Vis spectroscopy, which confirmed the presence of AgNPs. Response surface methodology was chosen to evaluate the effects of four process variables ($AgNO_3$ concentration, incubation period, pH levels, and inoculum size) on the biosynthesis of silver nanoparticles by Streptomyces aegyptia NEAE 102. Statistical analysis of the results showed that the linear and quadratic effects of incubation period, initial pH, and inoculum size had a significant effect (p < 0.05) on the biosynthesis of silver nanoparticles by Streptomyces aegyptia NEAE 102. The maximum silver nanoparticles biosynthesis (2.5 OD, at 400 nm ) was achieved in runs number 5 and 14 under the conditions of 1 mM $AgNO_3$ (1-1.5% (v/v)), incubation period (72-96 h), initial pH (9-10), and inoculum size (2-4% (v/v)). An overall 4-fold increase in AgNPs biosynthesis was obtained as compared with that of unoptimized conditions. The biosynthesized silver nanoparticles were characterized using UV-VIS spectrophotometer and Fourier transform infrared spectroscopy analysis, in addition to antimicrobial properties. The biosynthesized AgNPs significantly inhibited the growth of medically important pathogenic gram-positive (Staphylococcus aureus) and gram-negative bacteria (Pseudomonas aeruginosa) and yeast (Candida albicans).