• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.7-15
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• 2022

Since the direct and indirect damage caused by the fire in the underground utility tunnel will cause great damage to society as a whole, it is necessary to make efforts to prevent and control it in advance. The most of the fires that occur in cables are caused by short circuits, earth leakage, ignition due to over-current, overheating of conductor connections, and ignition due to sparks caused by breakdown of insulators. In order to find the cause of fire at an early stage due to the characteristics of the underground utility tunnel and to prevent disasters and safety accidents, we are constantly managing it with a detection system using image analysis and making efforts. Among them, a case of developing a fire detection system using CCTV-based deep learning image analysis technology has been reported. However, CCTV needs to be supplemented because there are blind spots. Therefore, we would like to develop a high-performance acoustic-based deep learning model that can prevent fire by detecting the spark sound before spark occurs. In this study, we propose a method that can collect sound in underground utility tunnel environments using microphone sensor through development and experiment of prototype module. After arranging an acoustic sensor in the underground utility tunnel with a lot of condensation, it verifies whether data can be collected in real time without malfunction.

• Journal of the Korean Society of Radiology
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• v.12 no.4
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• pp.481-489
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• 2018

In MRI examination, when irradiating the human body with RF Pulse to acquire images, the portion of the irradiated RF Pulse energy is absorded into the human body, and this will affect the temperature of the human body. If a metal is inserted into the human body even if the same RF Pulse energy is applied, the SAR value increases and the body temperature changes due to the increase in the electromagnetic wave conductivity of the metal. So we measure and compared with the change in the SAR and temperature in the implant material of the dental implant in Brain MRI examinations. Experiments were performed on a human head model using a 64MHz and 128 MHz RF Pulse frequency generated by a 3.0 Tesla MRI apparatus. And then changed material of dental implants to Titanium and $Al_2O_3$. Using the XFDTD program, the changes in SAR and body temperature around the head were examined. When with Titanium the SAR value and temperature of Brain increased, but with $Al_2O_3$ showed lower SAR and temperature as compared with Titanium. The dental implants were low in SAR and temperature of the head in $Al_2O_3$, which are electrical insulators with low electrical conductivity, compared to Titanium, which is an electrical conductor. It is necessary to study the biologic effect of patient with brain MRI when titanium dental implant material is inserted in the future. Because the maximum value of SAR is much higher than the limit when dental implant material is Titanium. In addition, it is necessary to use an implant of $Al_2O_3$ material to reduce the SAR value and temperature of the Brain in Brain MRI examination.