• Carbon letters
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• v.27
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• pp.35-41
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• 2018

Surfactant-wrapped separation methods of metallic and semiconducting single-walled carbon nanotubes (SWCNTs) can result in large changes in intrinsic physical and chemical properties due to electronic interactions between a nanotube and a surfactant. Our approach to synthesize SWCNTs with an electronic feature relied on utilizing carbon nanorings, [n] cycloparaphenylenes ([n]CPPs), which are the fundamental unit of armchair type SWCNTs (a-SWCNTs) that possess a metallic feature without any surfactants. To obtain long tubular structures from [n]CPPs, the host-guest complexes formed with well-aligned [n]CPP hosts and various fullerene guests on a silicon substrate were pyrolyzed under an ethanol gas flow at a high temperature with focused-ultraviolet laser irradiation. The pyrolyzed [n]CPPs were observed to transform from nanorings to tubular structures with 1.5-1.7 nm diameters corresponding to the employed diameter of [n]CPPs. Our approach suggests that [n]CPPs are useful for structure-controlled synthesis of SWCNTs.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.669-684
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• 2012

Discrete wavelet transforms are extensively preferred in biomedical signal processing for denoising, feature extraction, and compression. This paper presents a new denoising method based on the modeling of discrete wavelet coefficients of ECG in selected sub-bands with Kernel density estimation. The modeling provides a statistical distribution of information and noise. A Gaussian kernel with bounded support is used for modeling sub-band coefficients and thresholds and is estimated by placing a sliding window on a normalized cumulative density function. We evaluated this approach on offline noisy ECG records from the Cardiovascular Research Centre of the University of Glasgow and on records from the MIT-BIH Arrythmia database. Results show that our proposed technique has a more reliable physical basis and provides improvement in the Signal-to-Noise Ratio (SNR) and Percentage RMS Difference (PRD). The morphological information of ECG signals is found to be unaffected after employing denoising. This is quantified by calculating the mean square error between the feature vectors of original and denoised signal. MSE values are less than 0.05 for most of the cases.

• Nuclear Engineering and Technology
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• v.30 no.6
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• pp.541-554
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• 1998

A computer code COSMOS has been developed based on the CARO-D5 for the thermal analysis of LWR UO$_2$ and MOX fuel rod under steady-state and transient operating conditions. The main purpose of the COSMOS, which considers high turnup characteristics such as thermal conductivity degradation with turnup and rim formation at the outer part of fuel pellet, is to calculate temperature profile across fuel pellet and fission gas release up to high burnup. A new mechanistic fission gas release model developed based on physical processes has been incorporated into the code. In addition, the features of MOX fuel such as change in themo-mechanical properties and the effect of microscopic heterogeneity on fission gas release have been also taken into account so that it can be applied to MOX fuel. Another important feature of the COSMOS is that it can analyze fuel segment refabricated from base irradiated fuel rods in commercial reactors. This feature makes it possible to analyze database obtained from international projects such as the MALDEN and RISO, many of which were collected from refabricated fuel segments. The capacity of the COSMOS has been tested with some number of experimental results obtained from the HALDEN, RISO and FIGARO programs. Comparison with the measured data indicates that, although the COSMOS gives reasonable agreement, the current models need to be improved. This work is being performed using database available from the OECD/NEA.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4041-4059
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• 2019

Key establishment method based on channel reciprocity for time division duplex (TDD) system has earned a vital consideration in the majority of recent research. While most of the cellular systems rely on frequency division duplex (FDD) systems, especially the 5G network, which is not characterized by the channel reciprocity feature. This paper realizes the generation of a group secret key for multi-terminals communicated through a wireless network in FDD mode, by utilizing the nature of the physical layer for the wireless links between them. I consider a new group key generation approach, which using bitwise XOR with a modified pairwise secret key generation approach not based on the channel reciprocity feature. Precisely, this multi-node secret key agreement technique designed for three wireless network topologies: 1) the triangle topology, 2) the multi-terminal star topology, and 3) the multi-node chain topology. Three multi-node secret key agreement protocols suggest for these wireless communication topologies in FDD mode, respectively. I determine the upper bound for the generation rate of the secret key shared among multi-node, for the three multi-terminals topologies, and give numerical cases to expose the achievement of my offered technique.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.4
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• pp.427-433
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• 2019

This paper propose a fuzzy inference model for map building and navigation for a mobile robot with an active camera, which is intelligently navigating to the goal location in unknown environments using sensor fusion, based on situational command using an active camera sensor. Active cameras provide a mobile robot with the capability to estimate and track feature images over a hallway field of view. In this paper, instead of using "physical sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data. Command fusion method is used to govern the robot navigation. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a command fusion technique is introduced, where the sensory data of active camera sensor for navigation experiments are fused into the identification process. Navigation performance improves on that achieved using fuzzy inference alone and shows significant advantages over command fusion techniques. Experimental evidences are provided, demonstrating that the proposed method can be reliably used over a wide range of relative positions between the active camera and the feature images.

• Smart Structures and Systems
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• v.31 no.4
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• pp.409-419
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• 2023

Structural integrity can be accessed from dynamic deformations of structures. Moreover, dynamic deformations can be acquired from non-contact sensors such as video cameras. Kanade-Lucas-Tomasi (KLT) algorithm is one of the commonly used methods for motion tracking. However, averaging throughout the extracted features would induce bias in the measurement. In addition, pixel-wise measurements can be converted to physical units through camera intrinsic. Still, the depth information is unreachable without prior knowledge of the space information. The assigned homogeneous coordinates would then mismatch manually selected feature points, resulting in measurement errors during coordinate transformation. In this study, a two-stage optimization method for video-based measurements is proposed. The manually selected feature points are first optimized by minimizing the errors compared with the homogeneous coordinate. Then, the optimized points are utilized for the KLT algorithm to extract displacements through inverse projection. Two additional criteria are employed to eliminate outliers from KLT, resulting in more reliable displacement responses. The second-stage optimization subsequently fine-tunes the geometry of the selected coordinates. The optimization process also considers the number of interpolation points at different depths of an image to reduce the effect of out-of-plane motions. As a result, the proposed method is numerically investigated by using a truss bridge as a physics-based graphic model (PBGM) to extract high-accuracy displacements from recorded videos under various capturing angles and structural conditions.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.971-974
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• 2020

Infants express their physical and emotional needs to the outside world mainly through crying. However, most of parents find it challenging to understand the reason behind their babies' cries. Failure to correctly understand the cause of a baby' cry and take appropriate actions can affect the cognitive and motor development of newborns undergoing rapid brain development. In this paper, we propose an infant cry recognition system based on deep transfer learning to help parents identify crying babies' needs the same way a specialist would. The proposed system works by transforming the waveform of the cry signal into log-mel spectrogram, then uses the VGGish model pre-trained on AudioSet to extract a 128-dimensional feature vector from the spectrogram. Finally, a softmax function is used to classify the extracted feature vector and recognize the corresponding type of cry. The experimental results show that our method achieves a good performance exceeding 0.96 in precision and recall, and f1-score.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1657-1673
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• 2023

With the advancement of information technology, criminals employ multiple cyberspaces to promote cybercrime. To combat cybercrime and cyber dangers, banks and financial institutions use artificial intelligence (AI). AI technologies assist the banking sector to develop and grow in many ways. Transparency and explanation of AI's ability are required to preserve trust. Deep learning protects client behavior and interest data. Deep learning techniques may anticipate cyber-attack behavior, allowing for secure banking transactions. This proposed approach is based on a user-centric design that safeguards people's private data over banking. Here, initially, the attack data can be generated over banking transactions. Routing is done for the configuration of the nodes. Then, the obtained data can be preprocessed for removing the errors. Followed by hierarchical network feature extraction can be used to identify the abnormal features related to the attack. Finally, the user data can be protected and the malicious attack in the transmission route can be identified by using the Wrapper stepwise ResNet classifier. The proposed work outperforms other techniques in terms of attack detection and accuracy, and the findings are depicted in the graphical format by employing the Python tool.

• Journal of Industrial Technology
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• v.43 no.1
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• pp.1-6
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• 2023

TiO₂ is a versatile metal oxide material that is frequently used as a photo-catalyst for organic pollutant oxidation and a functional material for ultraviolet-ray protection. To improve its chemical/physical properties and widen the range of industrial application, it is demanded to control the crystalline feature and morphology precisely by applying advanced nano-synthesis methods. In this study, we prepared TiO₂ nanoparticles using the water-in-oil (W/O) microemulsion method and compared them with the particles synthesized by the conventional precipitation method. Also, we tried to find the optimum conditions for obtaining nano-sized, anatase-rich TiO₂ particles by the W/O microemulsion method. We analyzed the crystalline feature and particle size of the prepared samples using X-ray diffraction (XRD) and Transmission electron microscopy (TEM). In summary, we found the W/O microemulsion is more effective than precipitation in obtaining nano-sized TiO₂. The best result was derived when the microemulsion was formed using AOT surfactant, hydrolysis was performed under basic condition and the sample was calcined at 200℃.

• Journal of computational fluids engineering
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• v.19 no.3
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• pp.44-51
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• 2014

Considering the importance of the detailed resolution of the reacting flow field inside a gasifier, the objective of this study lies on to investigate the effect of important variables to influence on the reacting flow and thereby to clarify the physical feature occurring inside the gasifier using a comprehensive gasifier computer program. Thus, in this study the gasification process of a 1.0 ton/day gasifier are numerically modeled using the Fluent code. And parametric investigation has been made in terms of swirl intensity and aspect ratio of the gasifier. Doing this, special attention is given on the detailed change of the reacting flow field inside a gasifier especially with the change of this kind of design and operation parameters. Based on this study, a number of useful conclusions can be drawn in the view of flow pattern inside gasifier together with the consequence of the gasification process caused by the change of the flow pattern. Especially, swirl effect gives rise to a feature of a central delayed recirculation zone, which is different from the typical strong central recirculation appeared near the inlet nozzle. The delayed feature of central recirculation appearance could be explained by the increased axial momentum due to the substantial amount of the presence of the coal slurry occupying over the entire gasifier in gasification process. Further, the changes of flow pattern are explained in detail with the gasifier aspect ratio. In general, the results obtained are physically acceptable in parametric study.