• Korean Journal of Remote Sensing
• /
• v.39 no.5_2
• /
• pp.755-770
• /
• 2023

Due to recent severe climate change, abnormal weather phenomena, and other factors, the frequency and magnitude of natural disasters are increasing. The need for disaster management using artificial satellites is growing, especially during large-scale disasters due to time and economic constraints. In this study, we have summarized the current status of next-generation medium-sized satellites and microsatellites in operation and under development, as well as trends in satellite imagery analysis techniques using a large volume of satellite imagery driven by the advancement of the space industry. Furthermore, by utilizing satellite imagery, particularly focusing on recent major disasters such as floods, landslides, droughts, and wildfires, we have confirmed how satellite imagery can be employed for damage analysis, thereby establishing its potential for disaster management. Through this study, we have presented satellite development and operational statuses, recent trends in satellite imagery analysis technology, and proposed disaster response strategies that utilize various types of satellite imagery. It was observed that during the stages of disaster progression, the utilization of satellite imagery is more prominent in the response and recovery stages than in the prevention and preparedness stages. In the future, with the availability of diverse imagery, we plan to research the fusion of cutting-edge technologies like artificial intelligence and deep learning, and their applicability for effective disaster management.

• Journal of the Korean Society of Radiology
• /
• v.81 no.1
• /
• pp.21-40
• /
• 2020

Magnetic resonance imaging (MRI) is an essential modality for the diagnosis of musculoskeletal system defects because of its higher soft-tissue contrast and spatial resolution. With the recent development of MRI-related technology, faster imaging and various image plane reconstructions are possible, enabling better assessment of three-dimensional musculoskeletal anatomy and lesions. Furthermore, the image quality, diagnostic accuracy, and acquisition time depend on the MRI protocol used. Moreover, the protocol affects the efficiency of the MRI scanner. Therefore, it is important for a radiologist to optimize the MRI protocol. In this review, we will provide guidance on patient positioning; selection of the radiofrequency coil, pulse sequences, and imaging planes; and control of MRI parameters to help optimize the MRI protocol for the six major joints of the musculoskeletal system.

• Journal of Advanced Navigation Technology
• /
• v.27 no.6
• /
• pp.690-698
• /
• 2023

Information sharing and decision making between airport stakeholders became possible after the introduction of airport cooperative making system (A-CDM). This also resulted in optimizing aircraft handling time and increased the efficiency of aircraft operations. Technological advances have recently led to the development of urban air mobility (UAM) which is a small aircraft taking off and landing vertically. It is emerging as a new air transportation system in the future due to its advantage of saving time and solving congestion problem in the urban area. This study aims to suggest how vertiport cooperative decision making system (V-CDM) should be managed for efficient operation of UAM. By establishing procedure for decision making system based on Vertiport ecosystem of UAM. By establishing procedure for decision making system based on Vertiport ecosystem and UAM aircraft, unnecessary flight delays or cancellations can be minimized and efficiency of UAM operation will be improved as well.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.19 no.1
• /
• pp.95-107
• /
• 2017

In this study, a preliminary study was undertaken for development of a tunnel incident automatic detection system based on a machine learning algorithm which is to detect a number of incidents taking place in tunnel in real time and also to be able to identify the type of incident. Two road sites where CCTVs are operating have been selected and a part of CCTV images are treated to produce sets of training data. The data sets are composed of position and time information of moving objects on CCTV screen which are extracted by initially detecting and tracking of incoming objects into CCTV screen by using a conventional image processing technique available in this study. And the data sets are matched with 6 categories of events such as lane change, stoping, etc which are also involved in the training data sets. The training data are learnt by a resilience neural network where two hidden layers are applied and 9 architectural models are set up for parametric studies, from which the architectural model, 300(first hidden layer)-150(second hidden layer) is found to be optimum in highest accuracy with respect to training data as well as testing data not used for training. From this study, it was shown that the highly variable and complex traffic and incident features could be well identified without any definition of feature regulation by using a concept of machine learning. In addition, detection capability and accuracy of the machine learning based system will be automatically enhanced as much as big data of CCTV images in tunnel becomes rich.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.39 no.6
• /
• pp.920-926
• /
• 2010

Marine alga, Chlorella vulgaris, was extracted by chloroform-methanol (2:1, v/v) solvents for lipid extraction at $35^{\circ}C$ for five hours (HCM-35) and its process was compared with conventional lipid extraction condition such as chloroform-methanol (2:1, v/v) at $65^{\circ}C$ for one hour (CM-65). This low temperature extraction process showed that 80% of total lipid was extracted and its residues contained relatively unchanged amounts of intact proteins and other minerals as well as amino acid profiles. Interestingly enough, the weight fraction of carbohydrate in the residues slightly increased due to less denaturation at low process temperature. The biological activities of the residues such as cytotoxicity and immune cell growth activation were not much changed after being extracted. The sensory evaluation were found to be very favorable for being used as a food additive and/or food supplement. This result could also help to maintain the economic feasibility of utilizing marine resources in food and other relevant industries.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.12 no.1
• /
• pp.19-26
• /
• 2008

Purpose: In general, We discharged radioactive wastewater and sewages less than $8.1{\times}10^{-13}$ Ci/ml in a exclusive water-purifier tank. Our hospital operating three exclusive water-purifier tank for radioactive wastewater and sewages of 60 tons capacity respectively. In order to meet the criteria it need a enough decay more than 125 days per each exclusive tank. However, recently we fell into the serious situation that decay period was decreased remarkably, owing to the wastewater amount increased rapidly by enlarge the therapy ward. For that reason, in this article, I'd like to say the way that reducing of radioactive wastewater and sewages rationally. Materials and Methods: From January, 2006 to October, four hundred and two cases were analyzed. They were all hospitalized during 3 days and 2 nights. We calculated the average amount of water used (include toilet water used, shower water used, washstand water used, $\cdots$), each exclusive water-purifier tank's decay period, as well as try to search the increased factors about water-purifier tank inflow flux by re-analysis of the procedure of radioisotope therapy step by step. Results: We could increase each exclusive water-purifier tank's decay period from 84 days to 130 days through the improvement about following cause: (1) Improvement of conventional toilet stool for excessive water waste $\rightarrow$ Replacement of water saving style toilet stool (2) Prevention of unnecessary shower and wash (3) Stop the diuretics taking during hospitalization (4) Analysis of relationship between water intakes and residual dose of body (5) Education about outside toilet utilization before the administration (6) Changed each water-purifier tank's maximum level from85% to 90% Conclusion: The originality of our efforts are not only software but hardware performance improvements. Incidentally the side of software's are change of therapy procedures and protocols, the side of hardware's are replacement of water saving style toilet stool and change of each water-purifier tank's maximum level. Thus even if a long lapse of time, problem such as return to the former conditions may not happen. Besides, We expect that our trials become a new reasonable model in similar situation.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.14 no.2
• /
• pp.164-170
• /
• 1985

Yellowish modified wool, dithiocarbamate(DTC) wool, was synthesized by partial hydrolysis in 0.2 N-NaOH reacting with carbon disulfide to use as ${\alpha}-amylase$ immobilization matrix. ${\alpha}-amylase$ was immobilized reacting with sulfide group of DTC-wool by covalent binding within 1 hour. 0.5 gram of this preparation, $DTC-wool-{\alpha}-amylase$, contained 150 ug of enzyme protein and its specific activity was about 90% of the native one. General properties of $DTC-wool-{\alpha}-amylase$ were a little different from optimum temperature, optimum pH, heat stability, kinetic constants and activation energy. An apparent Michaelis constant and maximum velocity of $DTC-wool-{\alpha}-amylase$ were 5.56 mg/ml and 0.37 mg/ml. $min^{-1}$ respectively, while activation energy was 16.6 kcal/mole.

• Journal of Korea Water Resources Association
• /
• v.55 no.8
• /
• pp.623-634
• /
• 2022

Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.

• Journal of Practical Agriculture & Fisheries Research
• /
• v.17 no.1
• /
• pp.57-71
• /
• 2015

This study was conducted to develop the fertigation system with a peristaltic hose pump and brushless DC motor. The fertigation system was consisted of sensor, main controller, motor control unit, peristaltic pump, water supply pump, control panel, and filter. The peristaltic pump discharges liquid by squeezing the tube with rollers. Rollers attached to the external circumference of the rotor compresses the flexible tube. The fluid is contained within a flexible tube fitted inside a circular pump casing. The developed fertigation system has no mixing tank but instead injects directly a concentrated nutrient solution into a water supply pipe. The revolution speed of the peristaltic pump is controlled by PWM (Pulse width modulation) method. When the revolution speed of the peristaltic pump was 300rpm, the flow rate of the 3.2, 4.8, 6.3mm diameter tube was 202, 530, 857mL/min, respectively. As increasing revolution speed, the flow rate of the peristaltic pump linearly increased. As the inner diameter of a tube larger, a slope of graph is more steep. Flow rate of three roller was more than that of four roller. Flow rate of a norprene tube with good restoring force was more than that of a pharmed tube. As EC sensor probe was installed in direct piping in comparison with bypass piping showed good performance. After starting the system, it took 16~17 seconds to stabilize EC. The maximum value of EC was 1.44~1.7dS/m at a setting value of 1.4dS/m. The developed fertigation system showed ±0.06dS/m deviation from the setting value of EC. In field test, Cucumber plants generally showed good growth. From these findings, this fertigation system can be appropriately suitable for fertigation culture for crops.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_3
• /
• pp.1779-1790
• /
• 2023

Satellite-based fog detection algorithms are being developed to detect fog in real-time over a wide area, with a focus on the Korean Peninsula (KorPen). The GEO-KOMPSAT-2A/Advanced Meteorological Imager (GK2A/AMI, GK2A) satellite offers an excellent temporal resolution (10 min) and a spatial resolution (500 m), while GEO-KOMPSAT-2B/Geostationary Ocean Color Imager-II (GK2B/GOCI-II, GK2B) provides an excellent spatial resolution (250 m) but poor temporal resolution (1 h) with only visible channels. To enhance the fog detection level (10 min, 250 m), we developed a fused GK2AB fog detection algorithm (FDA) of GK2A and GK2B. The GK2AB FDA comprises three main steps. First, the Korea Meteorological Satellite Center's GK2A daytime fog detection algorithm is utilized to detect fog, considering various optical and physical characteristics. In the second step, GK2B data is extrapolated to 10-min intervals by matching GK2A pixels based on the closest time and location when GK2B observes the KorPen. For reflectance, GK2B normalized visible (NVIS) is corrected using GK2A NVIS of the same time, considering the difference in wavelength range and observation geometry. GK2B NVIS is extrapolated at 10-min intervals using the 10-min changes in GK2A NVIS. In the final step, the extrapolated GK2B NVIS, solar zenith angle, and outputs of GK2A FDA are utilized as input data for machine learning (decision tree) to develop the GK2AB FDA, which detects fog at a resolution of 250 m and a 10-min interval based on geographical locations. Six and four cases were used for the training and validation of GK2AB FDA, respectively. Quantitative verification of GK2AB FDA utilized ground observation data on visibility, wind speed, and relative humidity. Compared to GK2A FDA, GK2AB FDA exhibited a fourfold increase in spatial resolution, resulting in more detailed discrimination between fog and non-fog pixels. In general, irrespective of the validation method, the probability of detection (POD) and the Hanssen-Kuiper Skill score (KSS) are high or similar, indicating that it better detects previously undetected fog pixels. However, GK2AB FDA, compared to GK2A FDA, tends to over-detect fog with a higher false alarm ratio and bias.