• Journal of Environmental Impact Assessment
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• v.21 no.6
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• pp.859-877
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• 2012

In this study, Echo-sounder($E_s$) monitoring methodology was applied to test environmental impacts of artificial weirs(SCW and JSW) in the Yeongsan River on fish community and habitat structures at first time, and was compared with conventional fish sampling methodologies($C_s$). For the Es monitoring in the fields, parallel transect methods was employed in determining the survey distance interval with every 125 m within the upper-lower 2 km of the weirs. Four different fish sampling gears such as casting nets, kick nets, fyke nets, and gill nets were used for applications of $C_s$ monitoring methodology. According to the Echo-sounder monitoring, fish density, expressed as a number of individuals per square meter, along the longitudinal axis of the weir was significantly greater(JSW, t = 3.506, n = 30, p < 0.001) in the down-river reach of the weir than in the up-river reach. Also, fish density along the vertical water column was highest at mid-depths of Seungchon weir, which has simple habitat substrates, while fish density was highest at hypolimnetic depth of Juksan weir. According to fish sampling by the $C_s$ methodology, the fish compositions decreased as the river goes upward, and significant differences(JSW, t = 0.248, n = 30, p < 0.05) in the compositions of fish species occurred between up-reach and down-reach of the weirs. The dominant species near the two weirs were Opsarichthys uncirostris amurensis, Hemiculter eigenmanni and Coilia nasus. Overall, our fish and habitat data, based on $E_s$ and $C_s$ monitoring methodologies, suggest that the weirs disturbed the rivers due to initial habitat disturbances by the weir constructions as well as the barrier roles of weirs on fish passage and migrations. More long-term scientific and systematic fish impact monitoring and assessments($E_s$ and $C_s$) are required in the future to predict changes of ecological structures and functions on the constructions of the weirs.

• International Journal of Highway Engineering
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• v.3 no.4 s.10
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• pp.127-136
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• 2001

To increase the structural integrity of concrete box culvert good compaction by the dynamic compaction roller with bi9 capacity is as effective as good backfill materials. It is needed for effective compaction that a compaction roller closes to concrete structure with high frequency. However structural distress of the culvert could be occur due to the excessive earth pressure by great dynamic compaction load. To investigate the characteristics of Induced stress by compaction, a box culvert was constructed with changing cushion materials and compaction methods. Two types of cushion material such as tire rubber chip and EPS(Expanded Polystyrene) were used as cushion panels and they are set on the culverts before backfill construction. Laboratory test result of cushion material says that the value of dynamic elastic modulus of rubber is lesser than that of EPS. On the other hand, material damping of rubber material is greater than that of EPS. In most case, dynamic compaction rollers with 10.5 ton weights were used and vibration frequency was applied 30Hz for the great compaction energy. This paper presents the main results on the characteristics of dynamic earth pressures during compaction. The amounts of induced dynamic pressures$(\Delta\sigma\;h)$ by compaction are affected with construction condition such as compaction frequency, depth of pressure cell, distance between roller and the wall of culvert and roller direction. Based on the measured values dynamic lateral pressure on the culverts, it could be said that orthogonal direction of roller to the length of culvert is more effective to compaction efficiency than parallel direction.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.7
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• pp.38-45
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• 2006

The superconducting fault current limiters(SFCLs) provide the effect such as enhancement in power system reliability due to limiting the fault current within a few miliseconds. Among various SFCLs we have developed a flux-lock type SFCL and exploited a special design to effectively reduce the fault current according to properly adjustable magnetic field after the short-circuit test. This SFCL consists of two copper coils wound in parallel on the same iron core and a component using the YBCO thin film connected in series to the secondary copper coil. Meanwhile, operating characteristics can be controlled by adjusting the inductances and the winding directions of the coils. To analyze the operational characteristics, we compared closed-loop with open-loop iron core. When the applied voltage was 200[Vrms] in the additive polarity winding, the peak values of the line current the increased up to 30.71[A] in the closed-loop and 32.01[A] in the open-loop iron core, respectively. On the other hand, in the voltages generated at current limiting elements were 220.14[V] in the closed-loop and 142.73[V] in the opal-loop iron core during first-half cycle after fault instant under the same conditions. We confirmed that the open-loop iron core had lower power burden than in the closed-loop iron core. Consequently, we found that the structure of iron core enabled the flux-lock type SFCL at power system to have the flexibility.

• Journal of the Korean Geotechnical Society
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• v.31 no.5
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• pp.5-21
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• 2015

An energy pile is a novel type of ground heat exchangers (GHEX's) which sets up heat exchange pipes inside a pile foundation, and allows to circulate a working fluid through the pipe for exchanging thermal energy with the surrounding ground stratum. Using existing foundation structure, the energy pile can function not only as a structural foundation but also as a GHEX. In this paper, six full-scale energy piles were constructed in a test bed with various configurations of the heat exchange pipe inside large-diameter cast-in-place piles, that is, three parallel U-type heat exchangers (5, 8 and 10 pairs), two coil type heat exchangers (with a 500 mm and 200 mm pitch), and one S-type heat exchanger. During constructing the energy piles, the constructability of each energy pile was evaluated with consideration of the installation time, the number of workers and any difficulty for installing. In order to evaluate the thermal performance of energy piles, the thermal performance tests were carried out by applying intermittent (8 hours operating-16 hours pause) artificial cooling operation to simulate a cooling load for commercial buildings. Through the thermal performance tests, the heat exchange rates of the six energy piles were evaluated in terms of the heat exchange amount normalized with the length of energy pile and/or the length of heat exchange pipe. Finally, the economic feasibility of energy pile was evaluated according to the various types of heat exchange pipe by calculating demanded expenses per 1 W/m based on the thermal performance test results along with the market value of heat exchange pipes and labor cost.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.253-259
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• 2004

in this study, we developed a Monte Carlo imaging simulation code written by the visual C$\^$++/ programing language for design optimization of a digital X-ray imaging system. As a digital X-ray imaging system, we considered a Gd$_2$O$_2$S(Tb) scintillator and a photosensor array, and included a 2D parallel grid to simulate general test renditions. The interactions between X-ray beams and the system structure, the behavior of lights generated in the scintillator, and their collection in the photosensor array were simulated by using the Monte Carlo method. The scintillator thickness and the photosensor array pitch were assumed to 66$\mu\textrm{m}$ and 48$\mu\textrm{m}$, respertively, and the pixel format was set to 256 x 256. Using the code, we obtained X-ray images under various simulation conditions, and evaluated their image qualities through the calculations of SNR (signal-to-noise ratio), MTF (modulation transfer function), NPS (noise power spectrum), DQE (detective quantum efficiency). The image simulation code developed in this study can be applied effectively for a variety of digital X-ray imaging systems for their design optimization on various design parameters.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.4
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• pp.295-302
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• 2014

This study demonstrates a double-path CDI as an alternative of advanced wastewater treatment process. While the CDI typically consists of many pairs of electrodes connected in parallel, the new double-path CDI is designed to have series flow path by dividing the module into two stages. The CFD model showed that the double-path had uniform flow distribution with higher velocity and less dead zone compared with the single-path. However, the double-path was predicted to have higher pressure drop(0.7 bar) compared the single-path (0.4 bar). From the unit cell test, the highest TDS removal efficiencies of single- and double-path were up to 88% and 91%, respectively. The rate of increase in pressure drop with an increase of flow rate was higher in double-path than single-path. At 70 mL/min of flow rate, the pressure drop of double-path was 1.67 bar, which was two times higher than single-path. When the electrode spacing was increased from 100 to $200{\mu}m$, the pressure drop of double-path decreased from 1.67 to 0.87 bar, while there was little difference in TDS removal. When proto type double-path CDI was operated using sewage water, TDS, $NH_4{^+}$-N, $NO_3{^-}$-N and $PO_4{^{3-}}$-P removal efficiencies were up to 78%, 50%, 93% and 50%, respectively.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.56-68
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• 2009

Ongoing and extensive urbanisation, which is frequently accompanied with careless construction works, may threaten important archaeological structures that are still buried in the urban areas. Ground Penetrating Radar (GPR) and Electrical Resistivity Tomography (ERT) methods are most promising alternatives for resolving buried archaeological structures in urban territories. In this work, three case studies are presented, each of which involves an integrated geophysical survey employing the surface three-dimensional (3D) ERT and GPR techniques, in order to archaeologically characterise the investigated areas. The test field sites are located at the historical centres of two of the most populated cities of the island of Crete, in Greece. The ERT and GPR data were collected along a dense network of parallel profiles. The subsurface resistivity structure was reconstructed by processing the apparent resistivity data with a 3D inversion algorithm. The GPR sections were processed with a systematic way, applying specific filters to the data in order to enhance their information content. Finally, horizontal depth slices representing the 3D variation of the physical properties were created. The GPR and ERT images significantly contributed in reconstructing the complex subsurface properties in these urban areas. Strong GPR reflections and highresistivity anomalies were correlated with possible archaeological structures. Subsequent excavations in specific places at both sites verified the geophysical results. The specific case studies demonstrated the applicability of ERT and GPR techniques during the design and construction stages of urban infrastructure works, indicating areas of archaeological significance and guiding archaeological excavations before construction work.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.113-126
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• 2022

The tectonic history of the Chukchi Abyssal Plain in the Amerasia Basin, Arctic Ocean, has not been fully explored due to the harsh conditions of sea ice preventing detailed observation. Existing models of the tectonic history of the region provide contrasting interpretation of the timing of formation of the crust (Mesozoic to Cenozoic), crust type (from hyper-extended continental crust to oceanic crust), and formation process (from parallel/fan-shaped rifting to transformation faulting). To help determine the age of the oceanic crust, the geothermal gradient was measured at three stations in the south of abyssal plain at depth of 2,160-2,250 m below sea level. Heat flow measurement stations were located perpendicular to the spreading axis over a 40 km-long transect. In-situ thermal conductivity measurement, corrected by the laboratory test, gave observed marine heat flows of 55 to 61 mW/m². All measurements were taken during Arctic expeditions in 2018 (ARA09C expedition) and 2021 (ARA12C expedition) by the Korean ice-breaking research vessel (IBRV) Araon. Given the assumption of oceanic crust, the results correspond to formation in the Late Cretaceous (Mesozoic). The inferred age supports the hypothesis of formation activated by the opening of the Makarov Basin during the Late Mesozoic-Cenozoic. This would make it contemporaneous with rifting of the Chukchi Border Land immediately east of the abyssal plain. The heat flow data indicate the base of the gas hydrate stability zone is located 332-367 m below the seafloor, this will help to identify the gas hydrate-related bottom simulating reflector in the future seismic survey, as already identified on the Chukchi Plateau. Further geophysical surveys, including heat flow measurements, are required to increase our understanding of the formation process and thermal mantle structure of the abyssal plain.