• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.13-19
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• 2019

After the Fukushima nuclear accident, a new power supply using a lithium polymer battery has been proposed the first time in the world as the safety of the emergency battery facility has been required. It is required to have the safety of the rack system in which the battery device is installed in order to apply the proposed technology to the field. Therefore, the purpose of this study is to evaluate the seismic performance of string and rack frame for lithium-polymer battery devices developed for the first time in the world to satisfy 72 hours capacity. (1) The natural frequency of the unit rack system was 9 Hz, and the natural frequency before and after the earthquake load did not change. This means that the connection between members is secured against the design earthquake load. (2) he vibration reduction effect by string design was about 20%. (3) As a result of the seismic performance test under OBE and SSE conditions, the rack frame system was confirmed to be safe. Therefore, the proposed rack system can be applied to the nuclear power plant because the rack system has been verified structural safety to the required seismic forces.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.1 s.6
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• pp.15-29
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• 2005

Truck Shipment Safety Information, which is a part of the development of NERIS is divided into Optimal Route Guidance System and Emergency Response System. This research is for establishing an advance warning system, which aims for preventing damages(fire, explosion, gas-escape etc.) and detecting incidents that are able to happen during transporting hazardous materials in advance through monitoring the position of moving vehicles and the state of hazardous materials in real-time. This research is peformed to confirm the practical possibility of application of the advance warning system that monitors whether the hazardous materials transport vehicles move the allowed routes, finds the time and the location of incidents of the vehicles promptly and develops the emergency system that is able to respond to the incidents as well by using the technologies of CPS, CDMA and CIS with testing the ability of performance. As the results of the test, communication accuracies are 99$\%$ in freeway, 96$\%$ in arterial, 97$\%$ in hilly sections, 99$\%$ in normal sections, 96$\%$ in local sections, 99$\%$ in urban sections and 98$\%$ in tunnels. According to those results, the system has been recorded a high success rate of communication that enough to apply to the real site. However, the weak point appeared through the testing is that the system has a limitation of communication that is caused in the rural areas and certain areas where are fewer antennas that make communication possible between on-board unit and management server. Consequently, for the practical use of this system, it is essential to develop the exclusive en-board unit for the vehicles and find the method that supplements the receiving limitation of the GPS coordinates inside tunnels. Additionally, this system can be used to regulate illegal acts automatically such as illegal negligence of hazardous materials. And the system can be applied to the study about an application scheme as a guideline for transporting hazardous materials because there is no certain management system and act of toxic substances in Korea.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1827-1836
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• 2022

Disasters that occur unexpectedly are difficult to predict. In addition, the scale and damage are increasing compared to the past. Sometimes one disaster can develop into another disaster. Among the four stages of disaster management, search and rescue are carried out in the response stage when an emergency occurs. Therefore, personnel such as firefighters who are put into the scene are put in at a lot of risk. In this respect, in the initial response process at the disaster site, robots are a technology with high potential to reduce damage to human life and property. In addition, Light Detection And Ranging (LiDAR) can acquire a relatively wide range of 3D information using a laser. Due to its high accuracy and precision, it is a very useful sensor when considering the characteristics of a disaster site. Therefore, in this study, development and experiments were conducted so that the robot could perform real-time monitoring at the disaster site. Multi-sensor module was developed by combining LiDAR, Inertial Measurement Unit (IMU) sensor, and computing board. Then, this module was mounted on the robot, and a customized Simultaneous Localization and Mapping (SLAM) algorithm was developed. A method for stably mounting a multi-sensor module to a robot to maintain optimal accuracy at disaster sites was studied. And to check the performance of the module, SLAM was tested inside the disaster building, and various SLAM algorithms and distance comparisons were performed. As a result, PackSLAM developed in this study showed lower error compared to other algorithms, showing the possibility of application in disaster sites. In the future, in order to further enhance usability at disaster sites, various experiments will be conducted by establishing a rough terrain environment with many obstacles.

• Biomedical Science Letters
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• v.12 no.3
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• pp.289-301
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• 2006

Cardiopulmonary bypass (CPB) for cardiac surgery triggers the production and release of numerous chemotactic substances and cytokines, ensuing systemic inflammatory response that leads to postoperative major organ dysfunction. Traditionally, corticosteroids (steroid) have been administered to patients undergoing cardiac surgery to ward off these detrimental physiologic alterations. However, the majority of the studies have been performed on adult patients with high-dose steroid. We carried out a randomized, prospective, double-blind study to compare the efficacy of low-dose steroid with that of high-dose steroid and to determine the adequate dose of pretreated-steroid for prophylactic effects in pediatric cardiac surgery. Thirty pediatric patients scheduled for elective cardiac surgery were randomly assigned to two groups; fifteen patients received low-dose methylprednisolone (10mg/kg intravenously, n=15, low-dose group) and the others received high-dose methylprednisolone (30mg/kg intravenously, n=15, high-dose group) 1 hour prior to CPB. Arterial blood samples were taken before CPB (Pre-CPB), 10 minutes after start of CPB (CPB-10), and immediately after CPB-end (CPB-OFF) for measuring total leukocyte counts (T-WBC) and diff-counts, platelet counts, interleukin-6 (IL-6), myeloperoxidase (MPO), total antioxidant (TAO), neuron-specific enolase (NSE), troponin I (TNI), aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine, and blood urea nitrogen (BUN) levels. Other parameters such as volumes of urine output, pulmonary index $(PI,\;PaO_2/FiO_2)$, mechanical ventilating period, intensive care unit (ICU)-staying period, postoperative complications (fever, wound problem), postoperative 24 hrs and total volumes in blood loss, and hospitalized days were also assessed. All parameters were compared between two groups. There were no significant differences in T-WBC counts, monocyte fraction, platelet counts, TA levels, NSE levels, creatinine levels, BUN levels, the volumes of total urine output, PI, the incidences of fever and wound problem, postoperative 24hrs- and total-blood loss volumes and ICU-staying period between two groups (P>0.05). At CPB-OFF, neutrophil fraction, MPO level, TNI level, and AST level were higher in the high-dose group than in the low-dose group (P<0.05). IL-6 level at CPB-10 was higher in the high dose-group than in the low-dose group (P<0.05). Furthermore, mechanical ventilating periods and hospitalized days of the high-dose group were significantly longer than those of low-dose group (P<0.05). The high-dose group had significantly low lymphocyte fi-action at CPB-OFF compared with the low-dose group (P<0.001). These findings suggest that pretreatment of high-dose steroid is not superior to that of low-dose steroid regrading its potential benefits in pediatric cardiac surgery. Therefore, the conventional strategy of steroid treatment, high-dose pretreatment, should be modified in the cardiac surgery with CPB. However, further studies must be performed on the larger number of patients in as much as small number of patients in this study.

• 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.