• Journal of Dental Anesthesia and Pain Medicine
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• v.21 no.2
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• pp.155-165
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• 2021

Background: This study aimed to assess the course of anxiety and pain during lower third molar (LTMo) surgery and explore the role of mobile and single-channel electroencephalography under clinical and surgical conditions. Methods: The State-Trait Anxiety Inventory (STAI), Corah's Dental Anxiety Scale (DAS), and Interval Scale of Anxiety Response (ISAR) were used. The patient self-rated anxiety (PSA), the pain felt during and after surgery, EEG, heart rate (HR), and blood pressure (BP) were assessed. Results: The Attention (ATT) and Meditation (MED) algorithms and indicators evaluated in this study showed several associations. ATT showed interactions and an association with STAI-S, pain during surgery, PSA level, HR, and surgical duration. MED showed an interaction and association with DAS, STAI-S, and pain due to anesthesia. Preclinical anxiety parameters may influence clinical perceptions and biological parameters during LTMo surgeries. High STAI-Trait and PSA scores were associated with postoperative pain, whereas high STAI-State scores were associated with more pain during anesthesia and surgery, as well as DAS, which was also associated with patient interference during surgery due to anxiety. Conclusions: The findings suggest that single-channel EEG is promising for evaluating brain responses associated with systemic reactions related to anxiety, surgical stress, and pain during oral surgery.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.619-627
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• 2021

Recent advance in low cost and light-weight drones has extended their application areas in both military and private sectors. Accordingly surveillance program against unfriendly drones has become an important issue. Drone detection and classification technique has long been emphasized in order to prevent attacks or accidents by commercial drones in urban areas. Most commercial drones have small sizes and low reflection and hence typical sensors that use acoustic, infrared, or radar signals exhibit limited performances. Recently, artificial intelligence algorithm has been actively exploited to enhance radar image identification performance. In this paper, we adopt machined learning algorithm for high resolution radar imaging in drone detection and classification applications. For this purpose, simulation is carried out against commercial drone models and compared with experimental data obtained through high resolution radar field test.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.3
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• pp.252-259
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• 2019

Jet engine modulation(JEM) signals are widely used in the field of target recognition along with high-range resolution profile and inverse synthetic aperture radar because they provide specific information of the jet engine. To obtain the number of blades of the jet engine, the chopping frequency proportional to the number of blades must be extracted. In the conventional chopping frequency extraction method, an initial threshold value is defined and a method of detecting the chopping peak is used. However, this detection method takes time depending on the signal due to repetitive detection. Thus, in this study, we proposed to extract the chopping frequency using MUltiple SIgnal Classification(MUSIC) algorithm. We applied the MUSIC algorithm to a given JEM signal to find the chopping frequency and determine the blade number candidates. We also applied the MUSIC algorithm to other chopping frequency extractions to determine the score of the candidate groups. Unlike the conventional detection algorithm, which requires repetitive frequency detection, MUSIC algorithm quickly detects the accurate chopping frequency and reduces the calculation time.

• Journal of Gastric Cancer
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• v.13 no.3
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• pp.164-171
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• 2013

Purpose: Laparoscopy-assisted distal gastrectomy for early gastric cancer has gained acceptance and popularity worldwide. However, laparoscopy-assisted distal gastrectomy for advanced gastric cancer is still controversial. Therefore, we propose this prospective randomized controlled multi-center trial in order to evaluate the safety and feasibility of laparoscopy assisted D2-gastrectomy for advanced stage gastric cancer. Materials and Methods: Patients undergoing distal gastrectomy for advanced gastric cancer staged cT2/3/4 cN0/1/2/3a cM0 by endoscopy and computed tomography are eligible for enrollment after giving their informed consent. Patients will be randomized either to laparoscopyassisted distal gastrectomy or open distal gastrectomy. Sample size calculation revealed that 102 patients are to be included per treatment arm. The primary endpoint is the non-compliance rate of D2 dissection; relevant secondary endpoints are three-year disease free survival, surgical and postoperative complications, hospital stay and unanimity rate of D2 dissection evaluated by reviewing the intraoperative video documentation. Discussion: Oncologic safety is the major concern regarding laparoscopy-assisted distal gastrectomy for advanced gastric cancer. Therefore, the non-compliance rate of clearing the N2 area was chosen as the most important parameter for the technical feasibility of the laparoscopic procedure. Furthermore, surgical quality will be carefully reviewed, that is, three independent experts will review the video records and score with a check list. For a long-term result, disease free survival is considered a secondary endpoint for this trial. This study will offer promising evidence of the feasibility and safety of Laparoscopy-assisted distal gastrectomy for advanced gastric cancer. Trial Registration: NCT01088204 (international), NCCCTS-09-448 (Korea).

• Journal of the Korean earth science society
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• v.41 no.6
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• pp.617-629
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• 2020

Sea surface temperature (SST), which plays an important role in climate change and global environmental change, can be divided into skin sea surface temperature (SSST) observed by satellite infrared sensors and the bulk temperature of sea water (BSST) measured by instruments. As sea surface temperature products distributed by many overseas institutions represent temperatures at different depths, it is essential to understand the relationship between the SSST and the BSST. In this study, we constructed an observation system of infrared radiometer onboard a marine research vessel for the first time in Korea to measure the SSST. The calibration coefficients were prepared by performing the calibration procedure of the radiometer device in the laboratory prior to the shipborne observation. A series of processes were applied to calculate the temperature of the layer of radiance emitted from the sea surface as well as that from the sky. The differences in skin-bulk temperatures were investigated quantitatively and the characteristics of the vertical structure of temperatures in the upper ocean were understood through comparison with Himawari-8 geostationary satellite SSTs. Comparison of the skin-bulk temperature differences illustrated overall differences of about 0.76℃ at Jangmok port in the southern coast and the offshore region of the eastern coast of the Korean Peninsula from 21 April to May 6, 2020. In addition, the root-mean-square error of the skin-bulk temperature differences showed daily variation from 0.6℃ to 0.9℃, with the largest difference of 0.83-0.89℃ at 1-3 KST during the daytime and the smallest difference of 0.59℃ at 15 KST. The bias also revealed clear diurnal variation at a range of 0.47-0.75℃. The difference between the observed skin sea surface temperature and the satellite sea surface temperature showed a mean square error of approximately 0.74℃ and a bias of 0.37℃. The analysis of this study confirmed the difference in the skin-bulk temperatures according to the observation depth. This suggests that further ocean shipborne infrared radiometer observations should be carried out continuously in the offshore regions to understand diurnal variation as well as seasonal variations of the skin-bulk SSTs and their relations to potential causes.