• Journal of IKEEE
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• v.22 no.4
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• pp.1006-1011
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• 2018

This paper proposes a three level buck converter utilizing multi-bit flying capacitor voltage control. The conventional three-level buck converter can not control the flying capacitor voltage, so that the operation is unstable or the circuit for controlling the flying capacitor voltage can not be applied to the PWM mode. Also when the load current is increased, an error occurs in the inductor voltage. The proposed structure can control the flying capacitor voltage in PWM mode by using differential difference amplifier and common mode feedback circuit. In addition, this paper proposes a 3bit flying capacitor voltage control circuit to optimize the operation of the three level buck converter depending on the load current, and a triangular wave generation circuit using the schmitt trigger circuit. The proposed 3-level buck converter is designed in $0.18{\mu}m$ CMOS process and has an input voltage range of 2.7V~3.6V and an output voltage range of 0.7V~2.4V. The operating frequency is 2MHz, the load current range is 30mA to 500mA, and the output voltage ripple is measured up to 32.5mV. The measurement results show a maximum power conversion efficiency of 85% at a load current of 130 mA.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.701-709
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• 2019

Recently, heart rate signal, which is one of biological signals, have been used in various fields related to healthcare. Conventionally, most of the proposed heart rate signal detection methods are contact type methods, but there is a problem of discomfort that the subject have to contact with the device. In order to solve the problem, detection study by non-contact method has been progressed recently. The detected heart rate signal can be used for finger vein liveness detection and various application using heart rate. In this paper, we propose a method to obtain heart rate signal by using finger vein imaging system. The proposed method detected the signal from the changes of the brightness value in the time domain of the infrared finger vein images and converted it into the frequency domain using the image processing algorithm. After the conversion, we removed the noise not related to the heart rate signal through band-pass filtering. In order to evaluate the accuracy of the signal, we analyzed the correlation with the signal obtained simultaneously with the finger vein acquisition device and contact type PPG sensor approved by KFDA. As a result, it was possible to confirm that the heart rate signal detected in non-contact method through the finger vein image coincides with the waveform of actual heart rate signal.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.68-77
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• 2021

In this paper, a GPS/MEMS IMU integrated navigation receiver module capable of operating in a high dynamic environment is designed and fabricated, and the results is confirmed. The designed module is composed of RF receiver unit, inertial measurement unit, signal processing unit, correlator, and navigation S/W. The RF receiver performs the functions of low noise amplification, frequency conversion, filtering, and automatic gain control. The inertial measurement unit collects measurement data from a MEMS class IMU applied with a 3-axis gyroscope, accelerometer, and geomagnetic sensor. In addition, it provides an interface to transmit to the navigation S/W. The signal processing unit and the correlator is implemented with FPGA logic to perform filtering and corrrelation value calculation. Navigation S/W is implemented using the internal CPU of the FPGA. The size of the manufactured module is 95.0×85.0×.12.5mm, the weight is 110g, and the navigation accuracy performance within the specification is confirmed in an environment of 1200m/s and acceleration of 10g.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.33-40
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• 2021

Automatic Speech Recognition(ASR) is a technology that analyzes human speech sound into speech signals and then automatically converts them into character strings that can be understandable by human. Speech recognition technology has evolved from the basic level of recognizing a single word to the advanced level of recognizing sentences consisting of multiple words. In real-time voice conversation, the high recognition rate improves the convenience of natural information delivery and expands the scope of voice-based applications. On the other hand, with the active application of speech recognition technology, concerns about related cyber attacks and threats are also increasing. According to the existing studies, researches on the technology development itself, such as the design of the Automatic Speaker Verification(ASV) technique and improvement of accuracy, are being actively conducted. However, there are not many analysis studies of attacks and threats in depth and variety. In this study, we propose a cyber attack model that bypasses voice authentication by simply manipulating voice frequency and voice speed for AI voice recognition service equipped with automated identification technology and analyze cyber threats by conducting extensive experiments on the automated identification system of commercial smartphones. Through this, we intend to inform the seriousness of the related cyber threats and raise interests in research on effective countermeasures.

• The Korea Journal of Herbology
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• v.27 no.6
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• pp.29-35
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• 2012

Objectives : To observe the effect of 4 kinds of Korean medicine and complex extracts on the anti-stress of chronic mild stress Rat model, so as to find out the machanism of its pharmacological effects. Methods : 64 healthy SD Rats were randomly divided into 8 groups. Model Design by chronic stress(CSM), and carried out the forced swimming test. We investigated the body weight, feed and water intake, feed conversion ratio and measured parameters to changes in swimming time, immobility time, 2 and 24 hours of feces, corticosterone hormone and blood glucose level. Results : In this experiments, body weight gain and feed intake were higher in all korean medicinal herb group. Swimming time were increased by Zizyphus jujuba and Gagamsanzointang(SZT) groups and immobility time was significantly lower by Zizyphus jujuba and Fluoxetine(FLX) groups. The result of corticosterone hormone level were significantly lower in Fluoxetine(FLX) and Gagamsanzointang(SZT) but blood glucose was not significantly difference. In 2 hours after fecal frequency result were significantly lower in Zizyphus jujuba group. but SZT group were increased. This result caused by acute stress but 24 hours of feces were restored to normal. Conclusions : 5 kind of Korean Medicinal Herbs extracts has good anti-stress effects, and also to clear the circulatory system and regulate blood glucose and improve bowel function. We suggest that use a single Korean medicine rather than the combination to relieve stress.

• Journal of Korean Home Economics Education Association
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• v.35 no.1
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• pp.105-124
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• 2023

The purpose of this study was to identify the characteristics of the contents included in the curriculum and 382 syllabi of the department of home economics education of College of Education in Korea and analyze the correlation by detailed area through the keyword network method. In order to analyze the home economics education curriculum and 382 syllabuses of a total of 11 universities, the frequency of keyword occurrence was analyzed using the KrKwic program, also the degree of connection between keywords and various centrality scales were calculated and visualized. The results of this study were as follows. First, as a result of analyzing the entire syllabi, keywords representing various fields such as family, secondary school, clothing, food, consumer, and design appeared evenly, and keywords related to teaching methods such as 'method', 'practice', 'change', and 'principle' were appeared. Those keywords showed high degree of connection and centrality. Second, in the detailed sectoral analysis, core keywords for each area appeared, and each subject were found to reflect the core keywords of the academic base. This study contributes to the conversion of curriculum of the department of home economics education to future-oriented and convergent curriculum.

• The Transactions of the Korea Information Processing Society
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• v.13 no.10
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• pp.481-491
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• 2024

Digital watermarking is a technique for embedding information into digital content. Digital watermarking has attracted attention as a technique to combat piracy and identify artificially generated content, but it is still not robust in various situations. In this paper, we propose a frequency conversion-based hierarchical watermarking technique capable of attack detection, error correction, and owner identification. By embedding attack detection and error correction signatures in hierarchical watermarking, the proposed scheme maintains invisibility and outperforms the existing methods in capacity and robustness. We also proposed a framework to evaluate the performance of the image quality and error correction according to the type of error correction signature and the number of signature embeddings. We compared the visual quality and error correction performance of the conventional model without error correction signature and the conventional model with hamming and BCH signatures. We compared the quality by the number of signature embeddings and found that the quality deteriorates as the number of embeddings increases but is robust to attacks. By analyzing the quality and error correction ability by error correction signature type, we found that hamming codes showed better error correction performance than BCH codes and 41.31% better signature restoration performance than conventional methods.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.

• Journal of Chest Surgery
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• v.42 no.1
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• pp.14-21
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• 2009

Background: Postoperative atrial fibrillation (AF) is a common complication after coronary artery bypass graft (CABG) surgery. Although postoperative AF is regarded as benign, transient and self-limited, it has been associated with increased morbidity, thromboembolic events and an increased duration and cost of hospitalization. Material and Method: From January 1994 to December 2007, 190 patients that had isolated CABG surgery were divided into two groups. Group 1 (n=139) involved those who had postoperative atrial fibrillation, and group 2 (n=51) did not have any such events. We reviewed the medical records retrospectively including the incidence of postoperative AF, patient characteristics, surgery related factors and the outcome of the patients with postoperative AF. Result: The frequency of postoperative AF was 26.8%, the conversion rate to regular sinus rhythm before discharge was 82.4%; 82.4% of the AF developed within the first three postoperative days. Although the postoperative AF group was significantly older and had a prolonged postoperative Intensive care unit (ICU) stay, there was no difference in the aortic crossclamp time or duration of hospitalization. No spontaneous defibrillation at declamping, and longer duration of cardiopulmonary bypass were significantly related to the development of postoperative AF. However, postoperative treatment with a beta blocker was associated with a decreased incidence of postoperative AF. The multivariate analysis showed that age and ICU stay were significantly associated with the development of POAF. Spontaneous defibrillation and postoperative beta blocker treatment were significantly associated with a decreased frequency of POAF. Conclusion: AF after CABG surgery is a common complication associated with increased morbidity and a longer ICU stay. Therefore, various strategies aimed at reducing AF, and its complications, such as postoperative treatment with a beta blocker should be considered.

• Journal of Animal Science and Technology
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• v.55 no.5
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• pp.381-388
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• 2013

This study examined the effects of sex in different group sizes of Hanwoo calves. The growth performance including the mean daily gain, feed conversion rate, behavioral characteristics, and blood parameters in Hanwoo calves were investigated. A total of 54 heads of Hanwoo calves were housed separately at 4 heads per group, 3 heads per group, and 2 heads per group per pen. In the heifer calves, except for those 10 months of age, the growth performance was improved by increasing the group size, which was similar to steer calves (p<0.05). The heifer calves housed in 3 heads group spent more time lying down (p<0.05). The steer calves spent more time standing in the 3 heads group, lying down (2 heads group), and walking (4 heads group). The heifer calves housed in 2 heads group had a lower frequency of drinking, self-grooming, pairwise grooming, and fighting (p<0.05). On the other hand, the steer calves in the 4 heads group had a higher frequency of drinking, rubbing, and fighting (p<0.05). The white blood cell and cortisol were highest in the heifer calves in the 2 heads group (p<0.05).