• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.135-140
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• 2009

In this paper, we synthesized active sonar target signals based on highlights model, and then carried out target classification using the synthesized signals. If the target aspect angle is changed, the different signals are synthesized. To know the result, two different experiments are done. First, The classification results with respect to each aspect angle are shown. Second, the results in two group in aspect angle are acquired. Time domain feature extraction is done using matched filter and envelope detection. It shows the pattern of each highlights. Artificial neural networks and multi-class SVM are used for classifying target signals.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.569-575
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• 2020

The serial arc is one of factors causing electrical fires. Over past decades, various researches have been carried out to detect arc occurrences. Even though frequency analysis, wavelet, and statistical features have been used, additional steps such as transformation and feature extraction are required. On the contrary, deep learning models directly use the raw data without any feature extraction processes. Therefore, the usage of time-domain data is preferred, but the performance is not satisfactory. To solve this problem, subsequent 1-D signals are transformed into 2-D data that can feed into a convolutional neural network (CNN). Experiments validated that CNN model outperforms deep neural network (DNN) by the classification accuracy of 8.6%. In addition, data augmentation is utilized, resulting in the accuracy improvement by 14%.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.494-499
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• 2012

In this paper, a new method for detecting various objects that can be risks to safety navigation in sea environment is proposed. By analysing Infrared(IR) images obtained from various sea environments, we could find out that object regions include both horizontal and vertical direction edges while background regions of sea surface mainly include vertical direction edges. Therefore, we present an approach to detecting object regions considering horizontal and vertical edges. To this end, in the first step, image enhancement is performed by suppressing noises such as sea glint and complex clutters using a statistical filter. In the second step, a horizontal edge map and a vertical edge map are generated by 1-D Discrete Cosine Transform technique. Then, a combined map integrating the horizontal and the vertical edge maps is generated. In the third step, candidate object regions are detected by a adaptive thresholding method. Finally, exact object regions are extracted by eliminating background and clutter regions based on morphological operation.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.638-642
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• 2005

For gas hydrate exploration, long offset multichannel seismic data acquired using by the 4km streamer length in Ulleung basin of the East Sea. The dataset was processed to define the BSRs (Bottom Simulating Reflectors) and to estimate the amount of gas hydrates. Confirmation of the presence of Bottom Simulating reflectors (BSR) and investigation of its physical properties from seismic section are important for gas hydrate detection. Specially, faster interval velocity overlying slower interval velocity indicates the likely presences of gas hydrate above BSR and free gas underneath BSR. In consequence, estimation of correct interval velocities and analysis of their spatial variations are critical processes for gas hydrate detection using seismic reflection data. Using Dix's equation, Root Mean Square (RMS) velocities can be converted into interval velocities. However, it is not a proper way to investigate interval velocities above and below BSR considering the fact that RMS velocities have poor resolution and correctness and the assumption that interval velocities increase along the depth. Therefore, we incorporated Migration Velocity Analysis (MVA) software produced by Landmark CO. to estimate correct interval velocities in detail. MVA is a process to yield velocities of sediments between layers using Common Mid Point (CMP) gathered seismic data. The CMP gathered data for MVA should be produced after basic processing steps to enhance the signal to noise ratio of the first reflections. Prestack depth migrated section is produced using interval velocities and interval velocities are key parameters governing qualities of prestack depth migration section. Correctness of interval velocities can be examined by the presence of Residual Move Out (RMO) on CMP gathered data. If there is no RMO, peaks of primary reflection events are flat in horizontal direction for all offsets of Common Reflection Point (CRP) gathers and it proves that prestack depth migration is done with correct velocity field. Used method in this study, Tomographic inversion needs two initial input data. One is the dataset obtained from the results of preprocessing by removing multiples and noise and stacked partially. The other is the depth domain velocity model build by smoothing and editing the interval velocity converted from RMS velocity. After the three times iteration of tomography inversion, Optimum interval velocity field can be fixed. The conclusion of this study as follow, the final Interval velocity around the BSR decreased to 1400 m/s from 2500 m/s abruptly. BSR is showed about 200m depth under the seabottom

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.151-157
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• 2019

Recently, monitoring respiration of people has been of interest using non-invasive method. Among the vital signals usually used for indicating health status, non-invasive and portable device based monitoring respiratory status is practically useful and enable one to promptly deal with abnormal physical status. This paper proposes the approach to real-time detection of apnea signal based on Short-Time-Fourier-Transform(STFT). Contrary to the analysis of a signal in frequency domain using Fast-Fourier Transform, this paper employs Short-time-Fourier-Transform so that frequency response can be analyzed in short time interval. The respiratory signal is acquired using UWB radar sensor that enables one to obtain respiration signal in contactless way. Detection of respiratory status is carried out by analyzing frequency response, and classification of respiratory status can be provided. In particular, STFT is employed to analyze respiratory signal in real-time, leading to effective analysis of the respiratory status in practice. In the case of existence of noise in the signal, appropriate filtering process is employed as well. The proposed method is straightforward and is workable in practice to analyze the respiratory status of people. To evaluate the proposed method, experimental results are provided.

• Journal of Plant Biotechnology
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• v.50
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• pp.190-199
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• 2023

Date palm (Phoenix dactylifera L.: Arecaceae) is a dioecious species where only female trees bear fruits. In their natural state, date palms produce dates once a year. However, in Thailand, some trees were observed to produce dates during the off-season, despite no variations in morphology. The availability of such off-season fruits can significantly increase their market value. Interestingly, most female off-season date palms investigated in this study were obtained through micropropagation. Hence, there is an urgent need for genetic markers to distinguish female offseason flowering plantlets within tissue culture systems. In this study, we aimed to develop random amplification of polymorphic DNA-sequence characterized amplified region (RAPD-SCAR) markers for the identification of female off-season flowering date palms cultivated in Thailand. A total of 160 random decamer primers were employed to screen for specific RAPD markers in off-season flowering male and female populations. Out of these, only one primer, OPN-02, generated distinct genomic DNA patterns in female off-season flowering (FOFdp) individuals compared to female seasonal flowering genotypes. Based on the RAPD-specific sequence, specific SCAR primers denoted as FOFdpF and FOFdpR were developed. These SCAR primers amplified a single 517-bp DNA fragment, predominantly found in off-season flowering populations, with an accuracy rate of 60%. These findings underscore the potential of SCAR marker technology for tracking offseason flowering in date palms. Notably, a BLAST analysis revealed a substantial similarity between the SCAR marker sequence and the transcript variant mRNA from Phoenix dactylifera encoding the SET DOMAIN GROUP 40 protein. In Arabidopsis, this protein is involved in the epigenetic regulation of flowering time. The genetic potential of the off-season flowering traits warrants further elucidation.

• Journal of Ocean Engineering and Technology
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• v.27 no.3
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• pp.61-66
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• 2013

This paper presents the results of finite element simulations of elastic wave propagation in an underwater steel plate and the verification of a proposed method utilizing elastic wave-based damage detection. For the simulation and verification, we carried out the following procedures. First, three-dimensional finite element models were constructed using a general purpose finite element program. Second, two types of damages (mechanical defects and deteriorations) were applied to the underwater steel plate and three parameters (defect location, defect width, and depth) were considered to adjust the severity of the applied damages. Third, elastic waves were generated using the oblique incident method with a Gaussian tone burst, and the response signals were obtained at the receiving point for each defect or deterioration case. In addition, the received time domain signals were analyzed, particularly by measuring the magnitudes of the maximum amplitudes. Finally, the presence and severity of each type of damage were identified by the decreasing ratios of the maximum amplitudes. The results showed that the received signals for the models had the same global pattern with minor changes in the amplitudes and phases, and the decreasing ratio generally increased as the damage area increased. In addition, we found that the defect depth was more critical than the width in the decrease of the amplitude. This mainly occurred because the layout of the depth interfered with the elastic wave propagation in a more severe manner than the layout of the width. An inverse analysis showed that the proposed method is applicable for detecting mechanical defects and quantifying their severity.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.220-226
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• 2003

This paper presents the result of an investigation on the application of the acoustic emission method to the monitoring of fatigue crack initiation, growth and track location in welded joints. Fatigue test was carried out for a typical fillet welded joint of ship structure. AE parameter such as ring down count was analyzed in time domain and crack locations were examined by source location and cluster option which is one of the functions of AE signal processor The usability of AE mettled was confirmed for the detection of the initiation and location of through crack.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.281-286
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• 2004

The wear process of end mill is a so complicated process that a more reliable technique is required for the monitoring and controling the tool life and its performance. This research presents a new tool wear monitoring method based on the sound signal generated on the machining. The experiment carried out continuous-side-milling for using the high-speed steel end mill under wet condition. The sound pressure was measured at 0.5m from the cutting zone by a dynamic microphone, and was analyzed at frequency domain. The tooth passing frequency appears as a harmonics form, and end mill wear is related with the first harmonic. It can be concluded from the result that the tool wear is correlate with the intensity of the measured sound at tooth passing frequency estimation of end mill wear using sound is possible through frequency analysis at tooth passing frequency under the given circumstances.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.435-439
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• 2022

ROK has a lot to benchmark from how Ukraine is fighting Russia back with its tactical wins. They have taken a targeted strategy to strike Russia's top generals with high precision. To carry out this strategy, Ukraine is operating a Special Operations Force, which utilizes US/NATO forces, civilian and own resources for maximum impact. Of note, they utilize Starlink for seamless connection from detection, decision-making to strike to maximize operational efficiency. As ROK faces security threat of weapons of mass destruction, Ukraine's military intelligence organization set-up, weapons system and operations can provide some guidance on how to leverage its various SOF as well.