Effects of Combined Treatments of Electron-Beam Irradiation and Addition of Leek (<i>Allium tuberosum</i>) Extract on Reduction of Pathogens in Pork Jerky

Kang, Mingu,Kim, Hyun-Joo,Jayasena, Dinesh D.,Bae, Young Sik,Yong, Hae In,Lee, Mooha,Jo, Cheorun Mary Ann Liebert 2012 Foodborne Pathogens and Disease Vol.9 No.12

Universal Mechanism of Band-Gap Engineering in Transition-Metal Dichalcogenides

Kang, Mingu,Kim, Beomyoung,Ryu, Sae Hee,Jung, Sung Won,Kim, Jimin,Moreschini, Luca,Jozwiak, Chris,Rotenberg, Eli,Bostwick, Aaron,Kim, Keun Su American Chemical Society 2017 NANO LETTERS Vol.17 No.3

<P>van der Waals two-dimensional (2D) semiconductors have emerged as a class of materials with promising device characteristics owing to the intrinsic band gap. For realistic applications, the ideal is to modify the band gap in a controlled manner by a mechanism that can be generally applied to this class of materials. Here, we report the observation of a universally tunable band gap in the family of bulk 2H transition metal dichalcogenides (TMDs) by in situ surface doping of Rb atoms. A series of angle-resolved photoemission spectra unexceptionally shows that the band gap of TMDs at the zone corners is modulated in the range of 0.8-2.0 eV, which covers a wide spectral range from visible to near-infrared, with a tendency from indirect to direct band gap. A key clue to understanding the mechanism of this band-gap engineering is provided by the spectroscopic signature of symmetry breaking and resultant spin-splitting, which can be explained by the formation of 2D electric dipole layers within the surface bilayer of TMDs. Our results establish the surface Stark effect as a universal mechanism of band-gap engineering on the basis of the strong 2D nature of van der Waals semiconductors.</P>

Real-time selective gas detection by gas sensor array and deep learning

Mingu Kang(강민구),Incheol Cho(조인철),Inkyu Park(박인규) 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.11

The demand for gas sensors is increasing because of the growing interest in monitoring indoor/outdoor air pollutions. In particular, semiconductor metal oxide (SMO) gas sensors are attracting attention as the next-generation gas sensors. However, there are limitations in the actual applications of SMO gas sensors due to their low selectivity. In this study, the selectivity problem could be solved by fabricating a gas sensor array and using the deep learning network. The fabricated gas sensor array used nanocolumnar films of metal oxides (SnO₂, In₂O₃, WO₃, and CuO) deposited through the glancing angle deposition (GLAD) as the sensing materials, and the convolutional neural network (CNN) was selected as the deep learning network for gas identification. Finally, a real-time selective gas detection for CO, NH₃, NO₂, Methane, and Acetone gas was achieved with an accuracy of 98% by applying preprocessed sensing data collected from the gas sensor arrays to the CNN.

Modeling Electrical Characteristics for Multi-Finger MOSFETs Based on Drain Voltage Variation

Mingu Kang,윤일구 한국전기전자재료학회 2011 Transactions on Electrical and Electronic Material Vol.12 No.6

The scaling down of metal oxide semiconductor field-effect transistors (MOSFETs) for the last several years has contributed to the reduction of the scaling variables and device parameters as well as the operating voltage of the MOSFET. At the same time, the variation in the electrical characteristics of MOSFETs is one of the major issues that need to be solved. Especially because the issue with variation is magnified as the drive voltage is decreased. Therefore,this paper will focus on the variations between electrical characteristics and drain voltage. In order to do this, the test patterned multi-finger MOSFETs using 90-nm process is used to investigate the characteristic variations, such as the threshold voltage, DIBL, subthreshold swing, transconductance and mobility via parasitic resistance extraction method. These characteristics can be analyzed by varying the gate width and length, and the number of fingers. Through this modeling scheme, the characteristic variations of multi-finger MOSFETs can be analyzed.

Sign Inversion of Anomalous Hall Effect in heavy metal/permalloy bilayer structures

Mingu Kang,Seung-heon Chris Baek,Kab-Jin Kim,Byong-Guk Park 한국자기학회 2017 한국자기학회 학술연구발표회 논문개요집 Vol.2017 No.5

Serial-Parallel Content Addressable Memory with a Conditional Driver (SPCwCD)

KANG, Mingu,JUNG, Seong-Ook The Institute of Electronics, Information and Comm 2009 IEICE transactions on fundamentals of electronics, Vol.92 No.1

<P>In this paper, a novel content addressable memory (CAM) structure is proposed to improve the performance of a static divided word matching (SDWM) CAM. In the SDWM CAM, a small pmos has to be used to keep a noise margin, but it degrades performance significantly. To resolve this problem, a conditional driver is introduced in the proposed serial-parallel CAM. Performance is improved by 28.0% without additional power consumption at a cost of about 5.6% increased area when the total bit number is 32 with four series bits and 30% of VDD is allowed as noise.</P>

Holstein polaron in a valley-degenerate two-dimensional semiconductor

Kang, Mingu,Jung, Sung Won,Shin, Woo Jong,Sohn, Yeongsup,Ryu, Sae Hee,Kim, Timur K.,Hoesch, Moritz,Kim, Keun Su Nature Publishing Group UK 2018 NATURE MATERIALS Vol.17 No.8

<P>Two-dimensional (2D) crystals have emerged as a class of materials with tunable carrier density(1). Carrier doping to 2D semiconductors can be used to modulate many-body interactions(2) and to explore novel composite particles. The Holstein polaron is a small composite particle of an electron that carries a cloud of self-induced lattice deformation (or phonons)(3-5), which has been proposed to play a key role in high-temperature superconductivity(6) and carrier mobility in devices(7). Here we report the discovery of Holstein polarons in a surfacedoped layered semiconductor, MoS2, in which a puzzling 2D superconducting dome with the critical temperature of 12 K was found recently(8-11). Using a high-resolution band mapping of charge carriers, we found strong band renormalizations collectively identified as a hitherto unobserved spectral function of Holstein polarons(12-18). The short-range nature of electronphonon(e-ph) coupling in MoS2 can be explained by its valley degeneracy, which enables strong intervalley coupling mediated by acoustic phonons. The coupling strength is found to increase gradually along the superconducting dome up to the intermediate regime, which suggests a bipolaronic pairing in the 2D superconductivity.</P>

Resilience against Adversarial Examples: Data-Augmentation Exploiting Generative Adversarial Networks

( Mingu Kang ),( Hyeungkyeom Kim ),( Suchul Lee ),( Seokmin Han ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.11

Recently, malware classification based on Deep Neural Networks (DNN) has gained significant attention due to the rise in popularity of artificial intelligence (AI). DNN-based malware classifiers are a novel solution to combat never-before-seen malware families because this approach is able to classify malwares based on structural characteristics rather than requiring particular signatures like traditional malware classifiers. However, these DNN-based classifiers have been found to lack robustness against malwares that are carefully crafted to evade detection. These specially crafted pieces of malware are referred to as adversarial examples. We consider a clever adversary who has a thorough knowledge of DNN-based malware classifiers and will exploit it to generate a crafty malware to fool DNN-based classifiers. In this paper, we propose a DNN-based malware classifier that becomes resilient to these kinds of attacks by exploiting Generative Adversarial Network (GAN) based data augmentation. The experimental results show that the proposed scheme classifies malware, including AEs, with a false positive rate (FPR) of 3.0% and a balanced accuracy of 70.16%. These are respective 26.1% and 18.5% enhancements when compared to a traditional DNN-based classifier that does not exploit GAN.

Asymmetric Independent-Gate MOSFET SRAM for High Stability

Mingu Kang,Park, H. K.,Wang, J.,Yeap, G.,Jung, S. O. IEEE 2011 IEEE transactions on electron devices Vol.58 No.9

<P>In this paper, the application of an asymmetric independent-gate MOSFET (IG-MOSFET) to the bit-cell structures of the SRAM schemes that were previously proposed using the symmetric IG-MOSFET is analyzed. In addition, a novel SRAM scheme with the asymmetric IG-MOSFET is proposed to improve read stability and writeability by controlling the back gates of pass-gate and pull-up transistors. New array architecture is also suggested to prevent read stability degradation in the half-selected cell, where word line is selected but bit line is unselected. The previous SRAMs with IG-MOSFET (IG-SRAMs) fail to simultaneously improve read stability and writeability compared to the SRAM with the tied-gate MOSFET. The proposed IG-SRAM significantly improves both read stability and writeability at the cost of slightly increased bit-cell area and read delay, as compared to the previous IG-SRAMs.</P>

Comparison of Toxicity and Deposition of Nano-Sized Carbon Black Aerosol Prepared With or Without Dispersing Sonication

Kang, Mingu,Lim, Cheol-Hong,Han, Jeong-Hee Korean Society of ToxicologyKorea Environmental Mu 2013 Toxicological Research Vol.29 No.2

Nanotoxicological research has shown toxicity of nanomaterials to be inversely related to particle size. However, the contribution of agglomeration to the toxicity of nanomaterials has not been sufficiently studied, although it is known that agglomeration is associated with increased nanomaterial size. In this study, we prepared aerosols of nano-sized carbon black by 2 different ways to verify the effects of agglomeration on the toxicity and deposition of nano-sized carbon black. The 2 methods of preparation included the carbon black dispersion method that facilitated clustering without sonication and the carbon black dispersion method involving sonication to achieve scattering and deagglomeration. Male Sprague-Dawley rats were exposed to carbon black aerosols 6 hr a day for 3 days or for 2 weeks. The median mass aerodynamic diameter of carbon black aerosols averaged $2.08{\mu}m$ (for aerosol prepared without sonication; group N) and $1.79{\mu}m$ (for aerosol prepared without sonication; group S). The average concentration of carbon black during the exposure period for group N and group S was $13.08{\pm}3.18mg/m^3$ and $13.67{\pm}3.54mg/m^3$, respectively, in the 3-day experiment. The average concentration during the 2-week experiment was $9.83{\pm}3.42mg/m^3$ and $9.08{\pm}4.49mg/m^3$ for group N and group S, respectively. The amount of carbon black deposition in the lungs was significantly higher in group S than in group N in both 3-day and 2-week experiments. The number of total cells, macrophages and polymorphonuclear leukocytes in the bronchoalveolar lavage (BAL) fluid, and the number of total white blood cells and neutrophils in the blood in the 2-week experiment were significantly higher in group S than in normal control. However, differences were not found in the inflammatory cytokine levels (IL-$1{\beta}$, TNF-${\alpha}$, IL-6, etc.) and protein indicators of cell damage (albumin and lactate dehydrogenase) in the BAL fluid of both group N and group S as compared to the normal control. In conclusion, carbon black aerosol generated by sonication possesses smaller nanoparticles that are deposited to a greater extent in the lungs than is aerosol formulated without sonication. Additionally, rats were narrowly more affected when exposed to carbon black aerosol generated by sonication as compared to that produced without sonication.