• Journal of The Korean Astronomical Society
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• v.52 no.3
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• pp.71-82
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• 2019

We derive the geometric albedo of a near-Earth asteroid, (4179) Toutatis, to investigate its surface physical conditions. The asteroid has been studied rigorously not only via ground-based photometric, spectrometric, polarimetric, and radar observations but also via in situ observation by the Chinese Chang'e-2 space probe; however, its geometric albedo is not well understood. We conducted V-band photometric observations when the asteroid was at opposition in April 2018 using the three telescopes in the southern hemisphere that compose the Korea Microlensing Telescope Network (KMTNet). The observed time-variable cross section was corrected using the radar shape model. We find that Toutatis has a geometric albedo $p_V=0.185^{+0.045}_{-0.039}$, which is typical of S-type asteroids. We compare the geometric albedo with archival polarimetric data and further find that the polarimetric slope-albedo law provides a reliable estimate for the albedo of this S-type asteroid. The thermal infrared observation also produced similar results if the size of the asteroid is updated to match the results from Chang'e-2. We conjecture that the surface of Toutatis is covered with grains smaller than that of the near-Sun asteroids including (1566) Icarus and (3200) Phaethon.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.80.1-80.1
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• 2019

Photometric investigations of asteroids allow us to determine their rotation states and shape models (Apostolovska et al. 2014). Our main target, asteroid (2078) Nanking's perihelion distance (q) is 1.480 AU, which belongs to the Mars-crossing asteroid (1.3 < q < 1.66 AU). Mars-crossing asteroids are objects that cross the orbit of Mars and regarded as one of the primary sources of near-Earth asteroids due to the unstable nature of their orbits. We present the analysis of the spin parameters and 3D shape model of (2078) Nanking. We conducted Cousins_R-band time-series photometry of this asteroid from November 26, 2014 to January 17, 2015 at the Sobaeksan Optical Astronomy Observatory (SOAO) and for 25 nights from March to April 2016 using the Korea Microlensing Telescope Network (KMTNet) to reconstruct its physical model with our dense photometric datasets. Using the lightcurve inversion method (Kaasalainen & Torppa 2001; Kaasalainen et al. 2001), we determine the pole orientation and shape model of this object based on our lightcurves along with the archival data obtained from the literatures. We derived rotational period of 6.461 h, the preliminary ecliptic longitude (${\lambda}_p$) and latitude (${\beta}_p$) of its pole as ${\lambda}_p{\sim}8^{\circ}$ and ${\beta}_p{\sim}-52^{\circ}$ which indicates a retrograde rotation of the body. From the apparent W UMa-shaped lightcurve and its location in the rotation frequency-amplitude plot of Sheppard and Jewitt (2004), we suspect the contact binary nature of the body (Choi 2016).

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.61.3-61.3
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• 2019

We report the status of KMTNet (Korea Microlensing Telescope Network) microlensing. From KMTNet event-finder, we are annually detecting over 2500 microlensing events. In 2018, we have carried out a real-time alert for only the Northern bulge fields. It was very helpful to select Spitzer targets. Thanks to the real-time alert, KMT-only events for which OGLE and MOA could not detect have been largely increased. The KMTNet event-finder and alert-finder algorithms are being upgraded every year. From these, we found 18 exoplanets and various interesting events, such as an exomoon-candidate, a free-floating candidate, and brown dwarfs, which are very difficult to be detected by other techniques including radial velocity and transit. In 2019, the KMTNet alert will be available in real-time for all bulge fields. As before, we will continue to collaborate with Spitzer team to measure the microlens parallaxes, which are required for estimating physical parameters of the lens. Thus, the KMTNet alert will be helpful to select Spitzer targets again. Also we plan to do follow-up observations for high-magnification events to study the planet multiplicity function. The KMTNet alert will play an important role to do follow-up observations for high-magnification events. Also, we will search for free-floating planets with short timescale (< 3 days) to study the planet frequency in our Galaxy.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.6
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• pp.3-14
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• 2018

The aim of this study is to propose a method for calculating the weight of walking energy in ERAM model by calculating it for the analysis of vertical and horizontal spaces in a building. Conventional theories on the space analysis in the field of architectural planning predict the pedestrian volume of network spaces in urban street or in two-dimensional plane within a building, however, for vertical and horizontal spaces in a building, estimates of the pedestrian volume by those theories are limited. Because in the spatial syntax and ERAM model have been applied weights such as the spatial depth, adjacent angles, and physical distances available only to the two-dimensional same layer or plane. Therefore, the following basic assumptions and analysis conditions in this study were established for deriving a predictor of pedestrian volume in vertical and horizontal spaces of a building. The basic premise of space analysis is not to address the relationship between the pedestrian volume and the spatial structure itself but to the properties of spatial structure connection that human beings experience. The analysis conditions in three-dimensional spaces are as follows : 1) Measurement units should be standardized on the same scale, and 2) The connection characteristics between spaces should influence the accessibility of human beings. In this regard, a factor of walking energy has the attributes to analyze the connection of vertical and horizontal spaces and satisfies the analysis conditions presented in this study. This study has two implications. First, this study has shown how to quantitatively calculate the walking energy after a factor of walking energy was derived to predict the pedestrian volume in vertical and horizontal spaces. Second, the method of calculating the walking energy can be applied to the weights of the ERAM model, which provided the theoretical basis for future studies to predict the pedestrian volume of vertical and horizontal spaces in a building.

• Journal of Marine Bioscience and Biotechnology
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• v.12 no.2
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• pp.81-90
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• 2020

Sialic acid, which is contained in about 60-160 mg/kg in the edible bird's nest (EBN), is known to facilitate in the proper formation of synapses and improve memory function. The objective of this study is to extract effectively the sialic acid from edible bird's nest using affinity bead technology (ABT). After preparing the non-polar polymeric bead "KJM-278-28A" having a porous network structure, and then desorbed sialic acid was concentrated and dried. The analysis of the physicochemical properties of bead "KJM-278-28A" showed that the particle size was 400-700 ㎛, the moisture holding capacity was 67-70%, the surface area (BET) was 705-900 ㎡/g, and the average pore diameter 70-87 Å. The adsorption capacity of the bead "KJM-278-28A" for sialic acid was shown a strong physical force to bind sialic acid to the bead surface of 400 mg/L. In addition, as a result of analyzing the adsorption and desorption effects of sialic acid on water, ethanol, and 10% ethanol on the bead, it was confirmed that desorption effectively occurs from the beads when only ethanol is used. As a result of HPLC measurement of the separated sialic acid solution, a total of four sialic acid peaks of N-acetyl-neuraminic acid (Neu5Ac), α,β-anomer of Neu5Ac and N-glycoly-neuraminic acid were identified. Through these results, it was confirmed that it is possible to separate sialic acid from EBN extract with efficient and high yield when using ABT.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2168-2187
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• 2021

The smart grid replaces the traditional power structure with information inventiveness that contributes to a new physical structure. In such a field, malicious information injection can potentially lead to extreme results. Incorrect, FDI attacks will never be identified by typical residual techniques for false data identification. Most of the work on the detection of FDI attacks is based on the linearized power system model DC and does not detect attacks from the AC model. Also, the overwhelming majority of current FDIA recognition approaches focus on FDIA, whilst significant injection location data cannot be achieved. Building on the continuous developments in deep learning, we propose a Deep Learning based Locational Detection technique to continuously recognize the specific areas of FDIA. In the development area solver gap happiness is a False Data Detector (FDD) that incorporates a Convolutional Neural Network (CNN). The FDD is established enough to catch the fake information. As a multi-label classifier, the following CNN is utilized to evaluate the irregularity and cooccurrence dependency of power flow calculations due to the possible attacks. There are no earlier statistical assumptions in the architecture proposed, as they are "model-free." It is also "cost-accommodating" since it does not alter the current FDD framework and it is only several microseconds on a household computer during the identification procedure. We have shown that ANN-MLP, SVM-RBF, and CNN can conduct locational detection under different noise and attack circumstances through broad experience in IEEE 14, 30, 57, and 118 bus systems. Moreover, the multi-name classification method used successfully improves the precision of the present identification.

• New Physics: Sae Mulli
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• v.68 no.11
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• pp.1173-1182
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• 2018

Mesoporous silica allows proper hydration of an ion exchange membrane under low relative humidity due to its strong hydrophilicity and structural characteristic. A mesoporous silica and Nafion composite membrane shows good proton conductivity under low relative humidity. An understanding of ion-channel formation and proton transfer through an ion-channel network in mesoporous silica and Nafion composite membranes is essential for the development and the optimization of ion exchange membranes. In this study, a mesoporous cellular foam $SiO_2/Nafion$ composite membrane is fabricated, and its proton conductivity and performance are measured. Also, the ion-channel distribution is analyzed by using electrostatic force microscopy to measure the surface charge density of the mesoporous cellular foam $SiO_2/Nafion$ composite membrane. The research reveals a few remarkable results. First, the composite membrane shows excellent proton conductivity and performance under low relative humidity. Second, the composite membrane is observed to form ion-channel-rich and ion-channel-poor region locally.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.5
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• pp.3-11
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• 2005

This paper presents a performance analysis model based on an M/M/1 queue and Poisson distribution of input data traffic. The simulation on a pipelined AES system with processing rate of 10 rounds per clock shows $4.0\%$ higher performance than a non-pipelined version consuming 10 clocks per transaction. Physical implementation of pipelined AES with FPGA takes 3.5 times bigger gate counts than the non-pipelined version whereas the pipelined version yields only $3.5\%$ performance enhancement. The proposed analysis model can be used to optimize cost-performance of AES hardware designs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.4
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• pp.47-60
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• 2011

With the increase in the use of mobile banking service, mobile banking has become an attractive target to attackers. Even though many security measures are applied to the current mobile banking service, some threats such as physical theft or penetration to a mobile device from remote side are still remained as unsolved. With aiming to fill this void, we propose a novel approach to prevent e-financial incidents by analyzing mobile device user's input patterns. This approach helps us to distinguish between original user's usage and attacker's usage through analyzing personal input patterns such as input time-interval, finger pressure level on the touch screen. Our proposed method shows high accuracy, and is effective to prevent the e-finance incidents proactively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1317-1341
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• 2021

Nowadays, the Internet of Things (IoT) is adopted to enable effective and smooth communication among different networks. In some specific application, the Wireless Sensor Networks (WSN) are used in IoT to gather peculiar data without the interaction of human. The WSNs are self-organizing in nature, so it mostly prefer multi-hop data forwarding. Thus to achieve better communication, a cross-layer routing strategy is preferred. In the cross-layer routing strategy, the routing processed through three layers such as transport, data link, and physical layer. Even though effective communication achieved via a cross-layer routing strategy, energy is another constraint in WSN assisted IoT. Cluster-based communication is one of the most used strategies for effectively preserving energy in WSN routing. This paper proposes a Bio-inspired cross-layer routing (BiHCLR) protocol to achieve effective and energy preserving routing in WSN assisted IoT. Initially, the deployed sensor nodes are arranged in the form of a grid as per the grid-based routing strategy. Then to enable energy preservation in BiHCLR, the fuzzy logic approach is executed to select the Cluster Head (CH) for every cell of the grid. Then a hybrid bio-inspired algorithm is used to select the routing path. The hybrid algorithm combines moth search and Salp Swarm optimization techniques. The performance of the proposed BiHCLR is evaluated based on the Quality of Service (QoS) analysis in terms of Packet loss, error bit rate, transmission delay, lifetime of network, buffer occupancy and throughput. Then these performances are validated based on comparison with conventional routing strategies like Fuzzy-rule-based Energy Efficient Clustering and Immune-Inspired Routing (FEEC-IIR), Neuro-Fuzzy- Emperor Penguin Optimization (NF-EPO), Fuzzy Reinforcement Learning-based Data Gathering (FRLDG) and Hierarchical Energy Efficient Data gathering (HEED). Ultimately the performance of the proposed BiHCLR outperforms all other conventional techniques.