• Clean Technology
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• v.9 no.4
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• pp.197-206
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• 2003

We performed removal of aromatic compounds, benzene and toluene, from soil and zeolite using supercritical carbon dioxide. Extraction was performed at $50^{\circ}C$ and 27.7 MPa with changing the extent of pollutant concentration and the results were compared and analyzed. Experiments were carried out using flow method and high pressure extractor of 1.27 cm in diameter and 25cm in length was used. The pollutants were sampled every ten minutes and their concentrations were analyzed with GC/FID. As a result, highly contaminated sample followed solubility/elution model and slightly contaminated sample followed desorption/kinetics model. At the same condition benzene was extracted faster than toluene. In the case of zeolite, more time is required to extract pollutants than soil. This phenomena was due to high adsorption capacity of zeolite. In the case of highly contaminated soil, we could correlate experimental data using simple Brady's fixed bed extractor model. But in the case of slightly contaminated soil, that was governed with desorption/kinetics model, there was some errors.

• Journal of Animal Science and Technology
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• v.63 no.2
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• pp.367-379
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• 2021

The objectives of this study were to evaluate convolutional neural network models and computer vision techniques for the classification of swine posture with high accuracy and to use the derived result in the investigation of the effect of dietary fiber level on the behavioral characteristics of the pregnant sow under low and high ambient temperatures during the last stage of gestation. A total of 27 crossbred sows (Yorkshire × Landrace; average body weight, 192.2 ± 4.8 kg) were assigned to three treatments in a randomized complete block design during the last stage of gestation (days 90 to 114). The sows in group 1 were fed a 3% fiber diet under neutral ambient temperature; the sows in group 2 were fed a diet with 3% fiber under high ambient temperature (HT); the sows in group 3 were fed a 6% fiber diet under HT. Eight popular deep learning-based feature extraction frameworks (DenseNet121, DenseNet201, InceptionResNetV2, InceptionV3, MobileNet, VGG16, VGG19, and Xception) used for automatic swine posture classification were selected and compared using the swine posture image dataset that was constructed under real swine farm conditions. The neural network models showed excellent performance on previously unseen data (ability to generalize). The DenseNet121 feature extractor achieved the best performance with 99.83% accuracy, and both DenseNet201 and MobileNet showed an accuracy of 99.77% for the classification of the image dataset. The behavior of sows classified by the DenseNet121 feature extractor showed that the HT in our study reduced (p < 0.05) the standing behavior of sows and also has a tendency to increase (p = 0.082) lying behavior. High dietary fiber treatment tended to increase (p = 0.064) lying and decrease (p < 0.05) the standing behavior of sows, but there was no change in sitting under HT conditions.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.7 no.6
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• pp.39-48
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• 2004

The purpose of this paper was to confirm the application of the equation of the soil-water characteristic curve on an unsaturated soil. To this ends, a series of suction test was conducted on the selected 4 kinds of soil which is located in Korea, using the modified pressure extractor apparatus. And it was carried out to analyze the experimental parameters which can describe the soil-water characteristics, were determined by using the data obtained from the experiment. From the results, it was found that the matric suction was varied according to the grain size distribution, amount of fine grain particle and void ratio. Also it was found that the residual volumetric water content was decreased with the void ratio, but the index related air entry value, the soil parameter related water content and the parameter with residual water content were increased with the void ratio. And the application of equation of the soil-water characteristic curve was confirmed for the various conditions and the various state by the comparison between the volumetric water content measured by the experiment and the predicted values.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.53.1-53.1
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• 2013

We compiled a near-infrared photometric and polarimetric catalog of $5{\times}9$ fields (${\sim}39^{\prime}{\times}69^{\prime}$) in the eastern side of the Large Magellanic Cloud (LMC). This catalog contains 9067 sources brighter than 16 mag in the J, H, and Ks bands, the polarization degree and position angle of each source. The photometric and polarimetric data were simultaneously obtained in J, H, and Ks bands using SIRPOL, an imaging polarimeter of the InfraRed Survey Facility (IRSF), in 2008 December and 2011 December. In this poster, we present a comparison between our results and those of Nakajima et al. (2007, PASJ, 59, 519) on the same sources in the 30 Doradus region in the LMC. We also discuss possible uncertainties in our polarimetric results when the Source Extractor is used to measure aperture photometry.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.6
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• pp.61-69
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• 2004

The aim of the work described in this paper was to confirm the application of the equation of the soil-water characteristic curves on an unsaturated soil. A series of suction test for unsaturated soils was conducted on the selected 4 kinds of soil using modified pressure extractor apparatus. And it was carried out to analyse The experimental parameters which can be describe the soil-water characteristics, were determined by using the data obtained from the experiment. From the results, it was found that The matric suction varied according to the grain size distribution, amount of fine grain particles and void ratio. Also it was found that the residual degree of saturation was decreased with in crease of the void ratio, but the pore size distribution index and air entry value were increased with in crease of the void ratio. And The application of the soil-water characteristic curve equation was confirmed for the various conditions and the various state by the comparison between the measured degree of saturation and the predicted degree of saturation.

• ETRI Journal
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• v.37 no.6
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• pp.1220-1230
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• 2015

An autonomous valet parking (AVP) system is designed to locate a vacant parking space and park the vehicle in which it resides on behalf of the driver, once the driver has left the vehicle. In addition, the AVP is able to direct the vehicle to a location desired by the driver when requested. In this paper, for an AVP system, we introduce technology to recognize a parking space using image sensors. The proposed technology is mainly divided into three parts. First, spatial analysis is carried out using a height map that is based on dense motion stereo. Second, modelling of road markings is conducted using a probability map with a new salient-line feature extractor. Finally, parking space recognition is based on a Bayesian classifier. The experimental results show an execution time of up to 10 ms and a recognition rate of over 99%. Also, the performance and properties of the proposed technology were evaluated with a variety of data. Our algorithms, which are part of the proposed technology, are expected to apply to various research areas regarding autonomous vehicles, such as map generation, road marking recognition, localization, and environment recognition.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.4
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• pp.189-203
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• 2018

In this paper, a Software Defined Radio (SDR) architecture was designed and implemented for rapid prototyping of GNSS receiver. The proposed SDR can receive various GNSS and direct sequence spread spectrum (DSSS) signals without software modification by expanded input parameters containing information of the desired signal. Input parameters include code information, center frequency, message format, etc. To receive various signal by parameter controlling, a correlator, a data bit extractor and a receiver channel were designed considering the expanded input parameters. In navigation signal processing, pseudorange was measured based on Coordinated Universal Time (UTC) and appropriate navigation message decoder was selected by message format of input parameter so that receiver position can be calculated even if SDR is set up various GNSS combination. To validate the proposed SDR, the software was implemented using C++, CUDA C based on GPU and USRP. Experimentation has confirmed that changing the input parameters allows GPS, GLONASS, and BDS satellite signals to be received. The precision of the position from implemented SDR were measured below 5 m (Circular Error Probability; CEP) for all scenarios. This means that the implemented SDR operated normally. The implemented SDR will be used in a variety of fields by allowing prototyping of various GNSS signal only by changing input parameters.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.845-850
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• 2023

In this paper, we propose a method for diagnosing ball bearing vibration using transfer learning. STFT, which can analyze vibration signals in time-frequency, was used as input to CNN to diagnose failures. In order to rapidly learn CNN-based deep artificial neural networks and improve diagnostic performance, we proposed a transfer learning-based deep learning learning technique. For transfer learning, the feature extractor and classifier were selectively learned using a VGG-based image classification model, the data set for learning was publicly available ball bearing vibration data provided by Case Western Reserve University, and performance was evaluated by comparing the proposed method with the existing CNN model. Experimental results not only prove that transfer learning is useful for condition diagnosis in ball bearing vibration data, but also allow other industries to use transfer learning to improve condition diagnosis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2627-2642
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• 2023

Parkinson's disease (PD) is a typical, chronic neurodegenerative disease involving the concentration of dopamine, which can disrupt motor activity and cause different degrees of gait disturbance relevant to PD severity in patients. As current clinical PD diagnosis is a complex, time-consuming, and challenging task that relays on physicians' subjective evaluation of visual observations, gait disturbance has been extensively explored to make automatic detection of PD diagnosis and severity rating and provides auxiliary information for physicians' decisions using gait data from various acquisition devices. Among them, wearable sensors have the advantage of flexibility since they do not limit the wearers' activity sphere in this application scenario. In this paper, an attention-based temporal network (ATN) is designed for the time series structure of gait data (vertical ground reaction force signals) from foot sensor systems, to learn the discriminative differences related to PD severity levels hidden in sequential data. The structure of the proposed method is illuminated by Transformer Network for its success in excavating temporal information, containing three modules: a preprocessing module to map intra-moment features, a feature extractor computing complicated gait characteristic of the whole signal sequence in the temporal dimension, and a classifier for the final decision-making about PD severity assessment. The experiment is conducted on the public dataset PDgait of VGRF signals to verify the proposed model's validity and show promising classification performance compared with several existing methods.

• Journal of the Korean Society of Marine Environment & Safety
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• v.14 no.4
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• pp.257-266
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• 2008

PAHs are of mainly anthropogenic origin from urban runoff, oil spill and combustion of fossil fuels. Some PAHs are potentially carcinogenic and mutagenic to aquatic organisms. This study was carried out to survey the contamination of PAHs in the column sediments around Gwangyang bay. Yeosu petrochemical industrial complex, POSCO(Pohang steel compony) and Gwangyang container harbor are located near the bay. The column sediments were collected at 4 stations(A, B, C and D) and fractionated at intervals of two-centimeter depth on July 29, 1999. PAHs in colmn sediment samples were extracted in soxhlet extractor and were identified and quantified by GC-MS. PAHs compounds were analyzed and found to be 13 species. Total PAHs concentrations in the column sediments ranged from 275.04 to 2,838.64${\mu}g/kg$ dry wt. Naphthalene had the highest concentration in the range of 40.60 to 2,294.06${\mu}g/kg$ dry wt. and Anthracene had the lowest concentration in the range of 2.63 to 11.30${\mu}g/kg$ dry wt. The correlation coefficients between individual PAHs and total PAHs in the column sediments were relatively higher in the low molecular compounds such as Naphthalene, Acenaphthylene and Phenanthrene. The relationship between the P/A(Phenanthrene/Anthracene)ratio and F/P(Fluoranthene/Pyrene)ratio showed that P/A ratio was generally above 10 and F/P ratio was above 1 in all sediment samples. These data indicate that PAHs in the column sediments around Gwangyang bay seem to be of both pyrolytic and petrogenic origin The values of PAHs in the column sediments were lower than the biological effect guidelines.