• Journal of Korean Society of Environmental Engineers
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• v.36 no.6
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• pp.421-428
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• 2014

For the analysis of water supply network, demand-driven and pressure-driven analysis methods have been proposed. Of the two methods, demand-driven analysis (DDA) can only be used in a normal operation condition to evaluate hydraulic status of a pipe network. Under abnormal conditions, i.e., unexpected pipe destruction, or abnormal low pressure conditions, pressure-driven analysis (PDA) method should be used to estimate the suppliable flowrate at each node in a network. In order to carry out the pressure-driven analysis, head-outflow relationship (HOR), which estimates flowrate at a certain pressure at each node, should be first determined. Most previous studies empirically suggested that each node possesses its own characteristic head-outflow relationship, which, therefore, requires verification by using actual field data for proper application in PDA modeling. In this study, a model pipe network was constructed, and various operation scenarios of normal and abnormal conditions, which cannot be realized in real pipe networks, were established. Using the model network, data on pressure and flowrate at each node were obtained at each operation condition. Using the data obtained, previously proposed HOR equations were evaluated. In addition, head-outflow relationship at each node was analyzed especially under multiple pipe destruction events. By analyzing the experimental data obtained from the model network, it was found that flowrate reduction corresponding to a certain pressure drop (by pipe destruction at one or multiple points on the network) followed intrinsic head-outflow relationship of each node. By comparing the experimentally obtained head-outflow relationship with various HOR equations proposed by previous studies, the one proposed by Wagner et al. showed the best agreement with the exponential parameter, m of 3.0.

• Journal of the Korean Society of Radiology
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• v.17 no.4
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• pp.489-495
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• 2023

Radiation shielding facilities are constructed in locations where diagnostic radiation generators are installed, with the aim of preventing exposure for patients and radiation workers. The purpose of this study is seek to compare and validate the trend of attenuation thickness of lead, the primary material in these radiation shielding facilities, at different maximum tube voltages by Monte Carlo simulations and measurement. We employed the Monte Carlo N-Particle 6 simulation code. Within this simulation, we set a lead shielding arrangement, where the distance between the source and the lead sheet was set at 100 cm and the field of view was set at 10 × 10 cm². Additionally, we varied the tube voltages to encompass 80, 100, 120, and 140 kVp. We calculated energy spectra for each respective tube voltage and applied them in the simulations. Lead thicknesses corresponding to attenuation rates of 50, 70, 90, and 95% were determined for tube voltages of 80, 100, 120, and 140 kVp. For 80 kVp, the calculated thicknesses for these attenuation rates were 0.03, 0.08, 0.21, and 0.33 mm, respectively. For 100 kVp, the values were 0.05, 0.12, 0.30, and 0.50 mm. Similarly, for 120 kVp, they were 0.06, 0.14, 0.38, and 0.56 mm. Lastly, at 140 kVp, the corresponding thicknesses were 0.08, 0.16, 0.42, and 0.61 mm. Measurements were conducted to validate the calculated lead thicknesses. The radiation generator employed was the GE Healthcare Discovery XR 656, and the dosimeter used was the IBA MagicMax. The experimental results showed that at 80 kVp, the attenuation rates for different thicknesses were 43.56, 70.33, 89.85, and 93.05%, respectively. Similarly, at 100 kVp, the rates were 52.49, 72.26, 86.31, and 92.17%. For 120 kVp, the attenuation rates were 48.26, 71.18, 87.30, and 91.56%. Lastly, at 140 kVp, they were measured 50.45, 68.75, 89.95, and 91.65%. Upon comparing the simulation and experimental results, it was confirmed that the differences between the two values were within an average of approximately 3%. These research findings serve to validate the reliability of Monte Carlo simulations and could be employed as fundamental data for future radiation shielding facility construction.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Journal of Food Hygiene and Safety
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• v.28 no.1
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• pp.50-55
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• 2013

Since 1 June 2012, it is prohibited to sell oilfish as a food material but there are still many illegal cases of selling oilfish as if it is tuna or grilled Patagonian toothfish. So it is absolutely crucial to construct the system to distinguish the real food material from oilfish. There are two sorts of oil fish called Ruvettus pretiosus and Lepidocybirium flavobrunneum involved in Percifomes order and Gempylidae class. 16S DNA gene region in mitochondria was selected to design the specific primers. For design species-specific primer, the theoretical experiment were performed for the sequences of R. pretiosus, L. flavobrunneum, Thunnus thynnus, Thunnus albacores, Makaira mitsukurii and Xiphias gladius, registered at the Gene bank from the National Centre for Biotechnology Information, using BioEdit 7.0.9.0. program. Through the analysis of the result from experiments, it was possible to design the 4 kinds of primers to distinguish R. pretiosus and L. flavobrunneum. As a comparison group, 3 kinds of tuna and 4 kinds of billfishes were selected and experimental verification was performed. As a result, for R. pretiosus and L. flavobrunneum, R.P-16S-006-F/R.P-16S-008-R and L.F-16S-004-F/L.F-16S-006-R primers were selected eventually and PCR condition was established. In addition, 178bp and 238bp of PCR products were confirmed from the established condition and non-specific band was not amplified among similar species. Therefore, the species-specific primers developed in this study would be very useful and used in various ways such as internet shopping mall and illegal distributions with fast and scientific results.

• Progress in Medical Physics
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• v.25 no.3
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• pp.128-138
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• 2014

In gated radiation therapy (gRT), due to residual motion, beam delivery is intended to irradiate not only the true extent of disease, but also neighboring normal tissues. It is desired that the delivery covers the true extent (i.e. clinical target volume or CTV) as a minimum, although target moves under dose delivery. The objectives of our study are to validate if the intended dose is surely delivered to the true target in gRT and to quantitatively understand the trend of dose delivery on it and neighboring normal tissues when gating window (GW), motion amplitude (MA), and CTV size changes. To fulfill the objectives, experimental and computational studies have been designed and performed. A custom-made phantom with rectangle- and pyramid-shaped targets (CTVs) on a moving platform was scanned for four-dimensional imaging. Various GWs were selected and image integration was performed to generate targets (internal target volume or ITV) for planning that included the CTVs and internal margins (IM). The planning was done conventionally for the rectangle target and IMRT optimization was done for the pyramid target. Dose evaluation was then performed on a diode array aligned perpendicularly to the gated beams through measurements and computational modeling of dose delivery under motion. This study has quantitatively demonstrated and analytically interpreted the impact of residual motion including penumbral broadening for both targets, perturbed but secured dose coverage on the CTV, and significant doses delivered in the neighboring normal tissues. Dose volume histogram analyses also demonstrated and interpreted the trend of dose coverage: for ITV, it increased as GW or MA decreased or CTV size increased; for IM, it increased as GW or MA decreased; for the neighboring normal tissue, opposite trend to that of IM was observed. This study has provided a clear understanding on the impact of the residual motion and proved that if breathing is reproducible gRT is secure despite discontinuous delivery and target motion. The procedures and computational model can be used for commissioning, routine quality assurance, and patient-specific validation of gRT. More work needs to be done for patient-specific dose reconstruction on CT images.

• Journal of the Korean Geotechnical Society
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• v.20 no.5
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• pp.145-159
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• 2004

The conventional method for assessment of liquefaction potential proposed by Seed and Idriss has been widely used in most countries because of simplicity of tests. Even though various data such as stress, strain, stress path, and excess pore water pressure can be obtained from the dynamic test, especially, two simple experimental data such as the maximum deviatoric stress and the number of cycles at liquefaction have been used in the conventional assessment. In this study, a new detailed assessment for liquefaction potential to reflect both characteristics of real earthquake motion and dynamic soil resistance is proposed and verified. In the assessment, the safety factor of the liquefaction potential at a given depth of a site can be obtained by the ratio of a resistible cumulative plastic shear strain determined through the performance of the conventional cyclic test and a driving cumulative plastic shear strain calculated from the shear strain time history through the ground response analysis. The last point to cumulate the driving plastic shear strain to initiate soil liquefaction is important for this assessment. From the result of cyclic triaxial test using real earthquake motions, it was concluded that liquefaction under the impact-type earthquake loads would initiate as soon as a peak loading signal was reached. The driving cumulative plastic shear strain, therefore, can be determined by adding all plastic shear strains obtained from the ground response analysis up to the peak point. Through the verification of the proposed assessment, it can be concluded that the proposed assessment for liquefaction potential can be a progressive method to reflect both characteristics of the unique soil resistance and earthquake parameters such as peak earthquake signal, significant duration time, earthquake loading type, and magnitude.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.27 no.1
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• pp.1-12
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• 1991

An experiment has been carefully designed and performed to verify the theory for the echointergration technique of estimating the density of fish school by the use of steel spheres in a laboratory tank. The spheres used to simulate a fish school were randomly distributed throughout the insonified volume to produce the acoustic echoes similar to those scattered from real fish schools. The backscattered echoes were measured as a function of target density at tow frequencies of 50kHz and 200kHz. Data acquisition, processing and analysis were performed by means of the microcomputer-based sonar-echo processor including a FFT analyzer. Acoustic scattering characteristics of a 36cm mackerel was investigated by measuring fish echoes with frequencies ranging from 47.8kHz to 52.0kHz. The fluctuation of bottom echoes caused by the effects of fish-school attenuation and multiple scattering which occurred in dense aggregations of fishes was also examined by analyzing the echograms of sardine schools obtained by a 50kHz telesounder in the set-net's bagnet, and the echograms obtained by a scientific echo sounder of 50kHz in the East China Sea, respectively. The results obtained can be summarized as follows: 1. The measured and the calculated echo shapes on the steel sphere used to simulate a fish school were in close agreement. 2. The waveform and amplitude of echo signals by a mackerel without swimbladder fluctuated irregularly with the measuring frequency. 3. When a collection of 30 targets/m super(3) lied the shadow region behind another collection of 5 targets/m super(3), the mean losses in echo energy for the 30 targets/m super(3) were about -0.4dB at 50kHz and about -0.2dB at 200kHz, respectively. 4. In the echograms obtained in the East China Sea, the bottom echoes fluctuated remarkably when the dense aggregations of fish appeared between transducer and seabed. Especially, in the case of the echograms of sardine school obtained in a set-net's bagnet, the disappearance of bottom echoes and the lengthening of the echo trace by fish aggregations were observed. Then the mean density of the sardine school was estimated as 36 fish/m super(3). It suggests that when the distribution density of fishes in oceans is greater than this density, the effects of fish-school attenuation and multiple scattering must be taken into account as a possible source of error in fish abundance estimates. 5. The relationship between mean backscattering strength (, dB) and target density ($\rho$, No./m super(3)) were expressed by the equations: =-46.2+13.7 Log($\rho$) at 50kHz and =-43.9+13.4 Log($\rho$) at 200kHz. 6. The difference between the experimentally derived number and the actual number of targets gradually decreased with an increase in the target density and was within 20% when the density was 30 targets/m super(3). From these results, we concluded that when the number of targets in the insonified volume is large, the validity of the echo-integration technique of estimating the density of fish schools could be expected.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.27 no.1
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• pp.13-20
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• 1991

This paper describes the fish-density dependence of the mean backscattering strength with aggregations of encaged, free-swimming fish of known density in relation to the experimental verification of echo-integration technique for estimating the density of fish shoals. In this experiment, various numbers of gold crussian, Carassius burgeri burgeri, with a mean length of 18.5cm and a mean weight of 205.9g, were introduced into a net cage of approximately 0.76m super(3). During the backscattering measurements. the cage was suspended on the sound axis of the 50kHz transducer having a beam width of 33 degrees at -3dB downpoints. The volume backscattering strengths from fish aggregations were measured as a function of fish density. Data acquisition, processing and analysis were performed by means of the microcomputer-based sonar-echo processor including a FFT analyzer. The calibration of echo-sounder system was carried out at field with a steel ball bearing of 38mm in diameter having the target strength of -40.8dB. The dorsal-aspect target strengths on anesthetized specimens of gold crussian used in the cage experiment were measured and compared with the target strength predicted by the fish density-echo energy relationship for aggregations of free-swimming gold crussian in the cage. The results obtained can be summarized as follows: 1. The target strengths in the dorsal aspect on anesthetized specimens of gold crussian, with the mean length of 19.1cm and the mean weight of 210.5g, varied from -40.9dB to -44.8dB with a mean of -42.6dB. This mean target strength did not differ significantly from that predicted by the regression of echo energy on fish density of free-swimming gold crussian in the cage. It suggests that the target-strength measurements on anesthetized fish was valid and can be representative for live, free-swimming fish. 2. The relationship between mean backscattering strength(, dB) and distribution density of gold $crussian(\rho, $ fish/m super(3)) was expressed by the following equation; =-41.9+11 $Log(\rho)$ with a correlation coefficient of 0.97. This result support the existence of a linear relationship between fish density and echo energy, but suggest that this line has steeper slope than the regression by the theory of estimating the density of fish schools.

• Journal of the Korean Geotechnical Society
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• v.19 no.6
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• pp.71-84
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• 2003

The metallic shell of soil-steel structures are so weak in bending moment that it should sustain the applied load by the interaction of the backfill soil around the structures. The shell can be subjected to excessive bending moment during side backfilling or under live-load when the soil cover is less than the minimum value. The current design code specifies the allowable deformation and Duncan(1979) and McGrath et al.(2001) suggested the strength analysis methods to limit the moments by the plastic capacity of the shell. However, the allowable deformation is an empirically determined value and the strength analysis methods are based on the results of FE analysis, hence the experimental verification is necessary. In this study, the full-scale tests were conducted on the high-profile arch to investigate its behaviors during backfilling and under static live-loads. Based on the measurements, the allowable deformation of the tested structure could be estimated to be 1.45% of rise, which is smaller than the specified allowable deformation. The comparison between the measurements and the results of two strength analyses indicate that Duncan underestimates the earth-load moment and overestimates the live-load moment, while McGrath et al. predicts both values close to the actual values. However, as the predicted factors of safeties using two methods coincide with the actual factor of safety, it can be concluded that both methods can predict the structural stability under live-loads adequately when the cover is less than the minimum.

• Journal of the Korean Society of Radiology
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• v.14 no.6
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• pp.773-780
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• 2020

With the development of the 4th industrial, research is being conducted to prevent diseases and reduce damage in various fields of science and technology such as medicine, health, and bio. As a result, artificial intelligence technology has been introduced and researched for image analysis of radiological examinations. In this paper, we will directly apply a deep learning model for classification and detection of pneumonia using chest X-ray images, and evaluate whether the deep learning model of the Inception series is a useful model for detecting pneumonia. As the experimental material, a chest X-ray image data set provided and shared free of charge by Kaggle was used, and out of the total 3,470 chest X-ray image data, it was classified into 1,870 training data sets, 1,100 validation data sets, and 500 test data sets. I did. As a result of the experiment, the result of metric evaluation of the Inception V3 deep learning model was 94.80% for accuracy, 97.24% for precision, 94.00% for recall, and 95.59 for F1 score. In addition, the accuracy of the final epoch for Inception V3 deep learning modeling was 94.91% for learning modeling and 89.68% for verification modeling for pneumonia detection and classification of chest X-ray images. For the evaluation of the loss function value, the learning modeling was 1.127% and the validation modeling was 4.603%. As a result, it was evaluated that the Inception V3 deep learning model is a very excellent deep learning model in extracting and classifying features of chest image data, and its learning state is also very good. As a result of matrix accuracy evaluation for test modeling, the accuracy of 96% for normal chest X-ray image data and 97% for pneumonia chest X-ray image data was proven. The deep learning model of the Inception series is considered to be a useful deep learning model for classification of chest diseases, and it is expected that it can also play an auxiliary role of human resources, so it is considered that it will be a solution to the problem of insufficient medical personnel. In the future, this study is expected to be presented as basic data for similar studies in the case of similar studies on the diagnosis of pneumonia using deep learning.