• Journal of Urban Science
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• v.10 no.1
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• pp.11-20
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• 2021

In this study, the vibration characteristics were theoretically analyzed by modeling a free isotropic rotating disk with an outer periphery with a fixed inner periphery, paying attention to disks used as storage devices for information devices, especially magnetic disks, magneto-optical disks, and compact disks in which the head and disk are non-contact. Iluminate with Composite materials represented by fiber-reinforced plastics (FRP) have high specific strength (strength/density) and specific stiffness (narrowness/density). It is used in the elements, and its use is rapidly expanding. Under this circumstance, the disk currently manufactured using an isotropic material made of various plastic materials such as aluminum or polycarbonate as a base material is an extremely anisotropic material made of a composite material, and the circumferential stiffness of the disk is made of reinforcing fibers in the circumferential direction. It is modeled as an anisotropic rotating disk with increased, and its influence on the vibration characteristics is revealed.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.136-141
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• 2023

The continuous shrinking of transistors in integrated circuits leads to difficulties in improving performance, resulting in the emerging transistors such as nanosheet field-effect transistors. In this paper, we propose a TCAD-machine learning framework of nanosheet FETs to model the current-voltage characteristics. Sentaurus TCAD simulations of nanosheet FETs are performed to obtain a large amount of device data. A machine learning model of I-V characteristics is trained using the multi-layer perceptron from these TCAD data. The weights and biases obtained from multi-layer perceptron are implemented in a PSPICE netlist to verify the accuracy of I-V and the DC transfer characteristics of a CMOS inverter. It is found that the proposed machine learning model is applicable to the prediction of nanosheet field-effect transistors device and circuit performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.30-37
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• 2014

In this paper, the compact model for FinFET gate resistance is developed. Based on the FinFET geometry and material, the value of the gate resistance is extracted by Y-parameter analysis using 3D device simulator, Sentaurus. By dividing the gate resistance into horizontal and vertical components, the proposed gate resistance model captures the non-linear characteristics. The proposed compact model reflects the realistic gate structure which has two different materials (Tungsten, TiN) stacked. Using the proposed model, the number of fins for the minimum gate resistance can be proposed based on the variation of gate geometrical parameters. The proposed gate resistance model is implemented in BSIM-CMG. A ring-oscillator is designed, and its delay performance is compared with and without gate resistance.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.67-75
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• 2013

In this paper, an analytical model is presented for the source/drain parasitic resistance of FinFET. The parasitic resistance is a important part of a total resistance in FinFET because of current flow through the narrow fin. The model incorporates the contribution of contact and spreading resistances considering three-dimensional current flow. The contact resistance is modeled taking into account the current flow and parallel connection of dividing parts. The spreading resistance is modeled by difference between wide and narrow and using integral. We show excellent agreement between our model and simulation which is conducted by Raphael, 3D numerical field solver. It is possible to improve the accuracy of compact model such as BSIM-CMG using the proposed model.

• Journal of Astronomy and Space Sciences
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• v.29 no.1
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• pp.51-55
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• 2012

A few high-mass X-ray binaries-consisting of an OB star plus compact companion-have been observed by Fermi and ground-based Cerenkov telescopes like High Energy Stereoscopic System (HESS) to be sources of very high energy (VHE; up to 30 TeV) ${\gamma}$-rays. This paper focuses on the prominent ${\gamma}$-ray source, LS 5039, which consists of a massive O6.5V star in a 3.9-day-period, mildly elliptical ($e{\approx}0.24$) orbit with its companion, assumed here to be an unmagnetized compact object (e.g., black hole). Using three dimensional smoothed particle hydrodynamics simulations of the Bondi-Hoyle accretion of the O-star wind onto the companion, we find that the orbital phase variation of the accretion follows very closely the simple Bondi-Hoyle-Lyttleton (BHL) rate for the local radius and wind speed. Moreover, a simple model, wherein intrinsic emission of ${\gamma}$-rays is assumed to track this accretion rate, reproduces quite well Fermi observations of the phase variation of ${\gamma}$-rays in the energy range 0.1-10 GeV. However for the VHE (0.1-30 TeV) radiation observed by the HESS Cerenkov telescope, it is important to account also for photon-photon interactions between the ${\gamma}$-rays and the stellar optical/UV radiation, which effectively attenuates much of the strong emission near periastron. When this is included, we find that this simple BHL accretion model also quite naturally fits the HESS light curve, thus making it a strong alternative to the pulsar-wind-shock models commonly invoked to explain such VHE ${\gamma}$-ray emission in massive-star binaries.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.891-907
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• 2023

Compact Advanced Satellite 500-4 (CAS500-4) is scheduled to be launched to collect high spatial resolution data focusing on vegetation applications. To achieve this goal, accurate surface reflectance retrieval through atmospheric correction is crucial. Therefore, a machine learning-based atmospheric correction algorithm was developed to simulate atmospheric correction from a radiative transfer model using Sentinel-2 data that have similarspectral characteristics as CAS500-4. The algorithm was then evaluated mainly for forest areas. Utilizing the atmospheric correction parameters extracted from Sentinel-2 and GEOKOMPSAT-2A (GK-2A), the atmospheric correction algorithm was developed based on Random Forest and Light Gradient Boosting Machine (LGBM). Between the two machine learning techniques, LGBM performed better when considering both accuracy and efficiency. Except for one station, the results had a correlation coefficient of more than 0.91 and well-reflected temporal variations of the Normalized Difference Vegetation Index (i.e., vegetation phenology). GK-2A provides Aerosol Optical Depth (AOD) and water vapor, which are essential parameters for atmospheric correction, but additional processing should be required in the future to mitigate the problem caused by their many missing values. This study provided the basis for the atmospheric correction of CAS500-4 by developing a machine learning-based atmospheric correction simulation algorithm.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.5
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• pp.389-396
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• 2017

Peridynamics has been widely used in the dynamic fracture analysis of brittle materials. Recently, various crack patterns(compact region, floret, Hertz-type crack, etc.) of multilayered glass structures in experiments(Bless et al. 2010) were implemented with a bond-based peridynamic simulation(Bobaru et al.. 2012). The actual glass layers are bound with thin elastic interlayer material while the interlayer is missing from the peridynamic model used in the previous numerical study. In this study, the peridynamic interlayer modeling for the multilayered structures is proposed. It requires enormous computational time and memory to explicitly model very thin interlayer materials. Instead of explicit modeling, fictitious peridynamic particles are introduced for modeling interlayer materials. The computational efficiency and accuracy of the proposed peridynamic interlayer model are verified through numerical tests. Furthermore, preventing penetration scheme based on short-range interaction force is employed for the multilayered structure under compression and verified through parametric tests.

• Korean Journal of Optics and Photonics
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• v.23 no.4
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• pp.167-171
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• 2012

This paper reports on the stray light analysis results of a compact imaging spectrometer (COMIS) for a microsatellite STSAT-3. COMIS images Earth's surface and atmosphere with ground sampling distances of 27 m at the 18~62 spectral bands (0.4 ~ 1.05 ${\mu}m$) for the nadir looking at an altitude of 700 km. COMIS has an imaging telescope and an imaging spectrometer box into which three electronics PCBs are embedded. The telescope images a $27m{\times}28km$ area of Earth surface onto a slit of dimensions $11.8{\mu}m{\times}12.1mm$. This corresponds to a ground sampling distance of 27 m and a swath width of 28 km for nadir looking posture at an altitude of 700 km. Then the optics relays and disperses the slit image onto the detector thereby producing a monochrome image of the entrance slit formed on each row of detector elements. The spectrum of each point in the row is imaged along a detector column. The optical mounts and housing structures are designed in order to prevent stray light from arriving onto the image and so deteriorating the signal to noise ratio (SNR). The stray light analysis, performed by a non-sequential ray tracing software (LightTools) with three dimensional housing and lens modeling, confirms that the ghost and stray light arriving at the detector plane has the relative intensity of ${\sim}10^{-5}$ and furthermore it locates outside the concerned image size i.e. the field of view of the optics.

• Korean Journal of Optics and Photonics
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• v.12 no.3
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• pp.240-249
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• 2001

A high speed ultra-compact lens with a diffractive optical element (DOE) is designed, which can be applied to mobile communication devices such as IMT2000, PDA, notebook computer, etc. The designed hybrid lens has sufficiently high performance of less than f/2.2, compact size of 3.3 mm (1st surf. to image), and wide field angle of more than 30 deg. compared with the specifications of a single lens. By proper choice of the aspheric and DOE surface which has very large negative dispersion, we can correct chromatic and high order aberrations through the optimization technique. From Seidel third order aberration theory and Sweatt modeling, the initial data and surface configurations, that is, the combination condition of the DOE and the aspherical surface are obtained. However, due to the consideration of diffraction efficiency of a DOE, we can choose only four cases as the optimization input, and present the best solution after evaluating and comparing those four cases. On the other hand, we also report dramatic improvement in optical performance by inserting another refractive lens (so-called, field flattener), that keeps the refractive power of an original DOE lens and makes the petzval sum zero in the original DOE lens system. ystem.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.479-485
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• 2013

Virtualization is a promising approach to consolidating multiple online services onto a smaller number of computing resources. A virtualized server environment allows computing resources to be shared among multiple performance isolated platforms called virtual machines. Through server virtualization software, applications servers are encapsulated into VMs, and deployed with APIs on top generalized pools of CPU and memory resources. Networking and security have been moved to a software abstraction layer that transformed computing, network virtualization. And it paves the way for enterprise to rapidly deploy networking and security for any application by creating the virtual network. Stochastic reward net (SRN) is an extension of stochastic Petri nets which provides compact modeling facilities for system analysis. In this paper, we develop SRN model of network virtualization based on virtual switch. Measures of interest such as switching delay and throughput are considered. These measures are expressed in terms of the expected values of reward rate functions for SRNs. Numerical results are obtained according to the virtual switch capacity and number of active VMs.