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The Effect of Intracoronary Nicorandil on Coronary Myocardial Bridging
Jung, Jae-Hun,Min, Pil-Ki,Sung, Chong Won,Lee, Sang-Hak,Choi, Seonghoon,Cho, Jung Rae,Lee, Namho,Park, Kyoung-Ha,Kim, Min-Kyu,Park, Woo Jung,Jang, Yangsoo SAGE Publications 2009 Journal of cardiovascular pharmacology and therape Vol.14 No.3
<P>Medical treatments of coronary myocardial bridging (CMB) generally include β-blockers and calcium channel blockers. Nitrates are avoided because symptoms may worsen. Nicorandil is a hybrid of a nitrate and a potassium channel opener. However, the effect of nicorandil on CMB is unknown. We analyzed nicorandil reactivity at the site with CMB in 51 patients. Maximal and minimal diameters of CMB were measured by quantitative angiography at baseline and at 60 seconds after intracoronary administration of 200 mg nicorandil. The maximal diameter during diastole increased from 2.15 + 0.42 mm to 2.34 + 0.44 mm after administration of nicorandil (P < .001), and the minimal diameter during systole increased from 1.24 + 0.63 mm to 1.67 + 0.64 mm (P < .001). Thus, nicorandil reduced the percentage vessel narrowing from 44.0 + 26.1% to 30.3 + 21.2% (P < .001). In 22 patients, we also evaluated the effect of nitroglycerin. The maximal diameter during diastole increased from 2.25 + 0.47 mm to 2.51 + 0.44 mm after administration of nitroglycerin (P < .019), and the minimal diameter during systole decreased from 1.28 + 0.64 mm to 1.14 + 0.60 mm (P = .276). Thus, nitroglycerin augmented the percentage vessel narrowing from 44.9% + 25.0% to 56.0% + 23.5% (P = .023). These results indicate that intracoronary administration of nicorandil could dilate coronary arteries during diastole as well as systole in patients with CMB during coronary angiography.</P>
Machine Learning-Based Programming Analysis Model Proposal : Based on User Behavioral Analysis
Seonghoon Jang,Seung-Jung Shin 한국인터넷방송통신학회 2020 Journal of Advanced Smart Convergence Vol.9 No.4
The online education platform market is developing rapidly after the coronavirus infection-19 pandemic. As school classes at various levels are converted to non-face-to-face classes, interest in non-face-to-face online education is increasing more than ever. However, the majority of online platforms currently used are limited to the fragmentary functions of simply delivering images, voice and messages, and there are limitations to online hands-on training. Indeed, digital transformation is a traditional business method for increasing coding education and a corporate approach to service operation innovation strategy computing thinking power and platform model. There are many ways to evaluate a computer programmer's ability. Generally, piecemeal evaluation methods are used to evaluate results in time through coding tests. In this study, the purpose of this study is to propose a comprehensive evaluation of not only the results of writing, but also the execution process of the results, etc., and to evaluate the programmer's propensity habits based on the programmer's coding experience to evaluate the programmer's ability and productivity.
Jung, Eunjin,Jeong, Seonghoon,Ryou, Jae-Hyun,Kim, Hyunsoo American Scientific Publishers 2017 Journal of Nanoscience and Nanotechnology Vol.17 No.10
<P>The deep-trap states of light-emitting diodes (LED) fabricated with GaN/InGaN multiple-quantum-well active region were analyzed using the space charge limited (SCL) conduction model. Based on the Power-law relationship of the forward leakage current at a low voltage, it was revealed that the presence of two deep-trap states located 0.37 and 0.51 eV below the conduction-band edge of the active region, each with a density of 1.34x10(17) and 2.36x10(17) cm(-3), respectively, resulted in an evolution of forward leakage current. At a higher reverse bias, the reverse leakage current was also shown to follow the Power law instead of Poole-Frenkel emission model, indicating that the SCL conduction model is appropriate to use for the analysis of reverse leakage currents.</P>
Deep Learning-Based Smart Meter Wattage Prediction Analysis Platform
Seonghoon Jang,Seung-Jung Shin 한국인터넷방송통신학회 2020 Journal of Advanced Smart Convergence Vol.9 No.4
As the fourth industrial revolution, in which people, objects, and information are connected as one, various fields such as smart energy, smart cities, artificial intelligence, the Internet of Things, unmanned cars, and robot industries are becoming the mainstream, drawing attention to big data. Among them, Smart Grid is a technology that maximizes energy efficiency by converging information and communication technologies into the power grid to establish a smart grid that can know electricity usage, supply volume, and power line conditions. Smart meters are equient that monitors and communicates power usage. We start with the goal of building a virtual smart grid and constructing a virtual environment in which real-time data is generated to accommodate large volumes of data that are small in capacity but regularly generated. A major role is given in creating a software/hardware architecture deployment environment suitable for the system for test operations. It is necessary to identify the advantages and disadvantages of the software according to the characteristics of the collected data and select sub-projects suitable for the purpose. The collected data was collected/loaded/processed/analyzed by the Hadoop ecosystem-based big data platform, and used to predict power demand through deep learning.
동역학 모델을 활용한 서비스용 지능형 로봇의 현가시스템 설계 최적화
최성훈(Seonghoon Choi),박태원(Taewon Park),이수호(Sooho Lee),정성필(Sungpil Jung) 대한기계학회 2008 대한기계학회 춘추학술대회 Vol.2008 No.11
Recently, the intelligent service robot is applied for the purpose of guiding the building or providing information to the visitors of the public institution. The intelligent robot which is on development has a sensor to recognize its location at the bottom of it. Four wheels which are arranged in the form of a lozenge support the weight of the components and structures of the robot. The operating environment of this robot is restricted at the uneven place because the driving part and internal structure is designed in one united body. The impact from the ground is transferred to the internal equipments and structures of the robot. This continuous impact can cause the unusual state of the precise components and weaken the connection between each structural part. In this paper, a suspension system which can be applied to the intelligent robot is designed. The dynamic model of the robot is created, and the driving characteristics of the actual robot and the robot with suspension are compared. The road condition which the robot can operate is expanded by the application of the suspension system. Additionally, the suspension system is optimized to reduce the impact to the robot components.
6.7nm 리소그래피용 브래그 반사형 거울과 흡수체 물질 연구
정성훈 ( Seonghoon Jeong ),홍성철 ( Seongchul Hong ),김정식 ( Jung Sik Kim ),안진호 ( Jinho Ahn ) 대한금속재료학회(구 대한금속학회) 2016 대한금속·재료학회지 Vol.54 No.5
Beyond extreme ultraviolet lithography (BEUVL) is considered to be a future patterning technology using light source with wavelength of 6.7 nm. However, it is difficult to optimize the material system for BEUV mask consisting of reflector and absorber design with an optimized multilayer mirror and absorber layer of the reflective mask. In this study, we propose a lanthanum nitride/boron (LaN-/B) Bragg reflector for 6.7nm through optical simulation. Instead of BEUV absorber, we propose 6% attenuated phase shifting absorber stack to utilize 180 degrees phase shift effect at the edge of pattern. For the absorber stack, we used tantalum nitride (TaN)/ palladium (Pd) and tantalum nitride (TaN)/ ruthenium (Ru). As a result, the BEUV mask with optimized reflector and attenuated phase shifting absorber is expected to exhibit a better imaging performance (i.e., higher normalized image log slope and reduced mask shadowing effect) under 6.7nm illumination compared to the conventional binary intensity mask. †(Received March 24, 2016)
Deep Learning-Based Smart Meter Wattage Prediction Analysis Platform
Jang, Seonghoon,Shin, Seung-Jung The Institute of Internet 2020 International journal of advanced smart convergenc Vol.9 No.4
As the fourth industrial revolution, in which people, objects, and information are connected as one, various fields such as smart energy, smart cities, artificial intelligence, the Internet of Things, unmanned cars, and robot industries are becoming the mainstream, drawing attention to big data. Among them, Smart Grid is a technology that maximizes energy efficiency by converging information and communication technologies into the power grid to establish a smart grid that can know electricity usage, supply volume, and power line conditions. Smart meters are equient that monitors and communicates power usage. We start with the goal of building a virtual smart grid and constructing a virtual environment in which real-time data is generated to accommodate large volumes of data that are small in capacity but regularly generated. A major role is given in creating a software/hardware architecture deployment environment suitable for the system for test operations. It is necessary to identify the advantages and disadvantages of the software according to the characteristics of the collected data and select sub-projects suitable for the purpose. The collected data was collected/loaded/processed/analyzed by the Hadoop ecosystem-based big data platform, and used to predict power demand through deep learning.