• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.540-557
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• 2021

Privacy vulnerability of social networks is one of the major concerns for social science research and business analysis. Most existing studies which mainly focus on un-weighted network graph, have designed various privacy models similar to k-anonymity to prevent data disclosure of vertex attributes or relationships, but they may be suffered from serious problems of huge information loss and significant modification of key properties of the network structure. Furthermore, there still lacks further considerations of privacy protection for important sensitive edges in weighted social networks. To address this problem, this paper proposes a privacy preserving method to protect sensitive weighted edges. Firstly, the sensitive edges are differentiated from weighted edges according to the edge betweenness centrality, which evaluates the importance of entities in social network. Then, the perturbation operations are used to preserve the privacy of weighted social network by adding some pseudo-edges or modifying specific edge weights, so that the bottleneck problem of information flow can be well resolved in key area of the social network. Experimental results show that the proposed method can not only effectively preserve the sensitive edges with lower computation cost, but also maintain the stability of the network structures. Further, the capability of defending against malicious attacks to important sensitive edges has been greatly improved.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.57-65
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• 2019

In this paper, we study on finding the rail space in elevators by analyzing each image captured with CCD camera. We propose a method that applies one-dimensional matched filter to the pixels of a selected search space in the vertical line at a horizontal position and decides the position with the thickness of the space being represented by a black thick line in captured images. The pattern similarity representing how strongly the associated image pixels resemble with the thick line is defined and calculated with respect to each position along the vertical line of pixels. The position and thickness of the line are decided from the point having the maximum in pattern similarity graph. In the experiments of the proposed method under different illuminational conditions, it is observed that all the pattern similarity graphs show similar shape around door area independent of the conditions and the method can effectively detect the rail space if the rails are illuminated with even weak light. The method can be used for real-time embedded systems because of its simple algorithm, in which it is implemented in simple structure of program with small amount of operations in comparison with the conventional approaches using Canny edge detection and Hough transform.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.32 no.2
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• pp.93-99
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• 2019

A pressure sensor is a device that converts an applied physical pressure into an electrical signal. Such sensors have a range of applications depending on the pressure level, from low to high pressure. Sensors that use physical pressure, when compared to those operating under air pressure, are not widely applied as they are inefficient. To solve this problem, graphene oxide, which exhibits good mechanical and electrical characteristics, was used to increase the efficiency of these pressure sensors. Graphene oxide has properties that control the movement of charges within the dielectric. Exploiting these properties, we evaluated the change in electrical characteristics when pressure was applied according to the ratio and thickness of the oxidation graph added to the pressure sensor.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.22-27
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• 2020

In this paper, a generalized efficiency equation was proposed to estimate the internal loss of the SMPS (switched-mode power supply) with 3 variables. The first variable was an internal loss not related to the load current such as auxiliary power, the second was a loss proportional to the current such as diode loss, and the third was a loss proportional to square of the current such as conduction loss. Especially, theoretical internal losses of the totem pole bridgeless PFC which is widely used for high efficiency SMPS were expressed as output function to compare generalized efficiency equation. In addition, in order to reduce the conduction loss of the switch, when a multiple switch were paralleled, the correlation with the efficiency was analyzed and shown as a graph. In order to confirm the degree of the parallel switch structure on the efficiency improvement, a 2kW class totem pole bridgeless PFC was constructed and the effectiveness of the analysis was confirmed by comparing the generalized efficiency equation and theoretical loss analysis results with experimental data.

• Communications of the Korean Mathematical Society
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• v.36 no.2
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• pp.197-207
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• 2021

The main purpose of this paper is to study the zero-divisor properties of the zero-symmetric near-ring of skew formal power series R₀[[x; α]], where R is a symmetric, α-compatible and right Noetherian ring. It is shown that if R is reduced, then the set of all zero-divisor elements of R₀[[x; α]] forms an ideal of R₀[[x; α]] if and only if Z(R) is an ideal of R. Also, if R is a non-reduced ring and annR(a - b) ∩ Nil(R) ≠ 0 for each a, b ∈ Z(R), then Z(R₀[[x; α]]) is an ideal of R₀[[x; α]]. Moreover, if R is a non-reduced right Noetherian ring and Z(R₀[[x; α]]) forms an ideal, then ann_R(a - b) ∩ Nil(R) ≠ 0 for each a, b ∈ Z(R). Also, it is proved that the only possible diameters of the zero-divisor graph of R₀[[x; α]] is 2 and 3.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.188-196
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• 2022

Recently, neural architecture search (NAS) has received increasing attention as it can replace human experts in designing the architecture of neural networks for different tasks and has achieved remarkable results in many challenging tasks. In this study, a path-based computation neural architecture encoder (PCE) was proposed. Our PCE first encodes the computation of information on each path in a neural network, and then aggregates the encodings on all paths together through an attention mechanism, simulating the process of information computation along paths in a neural network and encoding the computation on the neural network instead of the structure of the graph, which is more consistent with the computational properties of neural networks. We performed an extensive comparison with eight encoding methods on two commonly used NAS search spaces (NAS-Bench-101 and NAS-Bench-201), which included a comparison of the predictive capabilities of performance predictors and search capabilities based on two search strategies (reinforcement learning-based and Bayesian optimization-based) when equipped with different encoders. Experimental evaluation shows that PCE is an efficient encoding method that effectively ranks and predicts neural architecture performance, thereby improving the search efficiency of neural architectures.

• Progress in Superconductivity and Cryogenics
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• v.25 no.4
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• pp.75-80
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• 2023

Rare earth barium copper oxide (REBCO) materials have shown the possibility of high-temperature superconductor (HTS) magnetic resonance imaging (MRI) magnets due to their elevated transition temperature. While numerous MRI magnet designs have emerged, there is a growing emphasis on estimating the cost before manufacturing. In this paper, we propose two designs of REBCO whole-body MRI magnets: (1) 1.5 T and (2) 3.0 T, the standard center field choices for hospital use, and compare their costs based on conductor usage. The basis topology of the design method is based on discretized solenoids to enhance field homogeneity. Magnetic stress calculation is done to further prove the mechanical feasibility of their construction. Multi-width winding technique and outer notch structure are used to improve critical current characteristic. We apply consistent constraints for current margins, sizes, and field homogeneities to ensure an equal cost comparison. A graph is plotted to show the cost increase with magnetic flux growth. Additionally, we compare our designs to two additional MRI magnet designs from other publications with respect to the cost and magnetic flux, and present the linear relationship between them.

• East Asian mathematical journal
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• v.40 no.2
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• pp.209-229
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• 2024

In this study, we design a teaching unit that constructs Pascal graphs and extended Pascal triangles to explore number patterns inherent in them. This teaching unit is designed to consider the diachronic process of teaching-learning by combining Dörfler's theoretical generalization model with Wittmann's design science ideas, which are applied to the didactical practice of mathematization. In the teaching unit, considering the teaching-learning level of prospective teachers who studied discrete mathematics, we generalize the well-known Pascal triangle and its number patterns to extended Pascal triangles which have directed graphs(called Pascal graphs) as geometric models. In this process, the use of symbols and the introduction of variables are exhibited as important means of generalization. It provides practical experiences of mathematization to prospective teachers by going through various steps of the generalization process targeting symbols. This study reflects Wittmann's intention in that well-understood mathematics and the context of the first type of empirical research as structure-genetic didactical analysis are considered in the design of the learning environment.

• Structural Engineering and Mechanics
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• v.89 no.1
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• pp.23-31
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• 2024

Ratcheting is the cyclic buildup of inelastic strain on a structure resulting from a combination of primary and secondary cyclic stress. It can lead to excessive plastic deformation, incremental collapse, or fatigue. Ratcheting has been numerically investigated on a cantilever beam, considering the current study's primary and secondary bending loads. In addition, the effect of input frequency on the onset of ratcheting has been investigated. The non-linear dynamic elastic-plastic approach has been utilized. Analogous to Yamashita's bending-bending ratchet diagram, a non-dimensional ratchet diagram with a frequency effect is proposed. The result presents that the secondary stress values fall sequentially with the increase of primary stress values. Moreover, a displacement amplification factor graph is also established to explain the effect of frequency on ratchet occurrence conditions. In terms of frequency effect, it has been observed that the lower frequency (0.25 times the natural frequency) was more detrimental for ratchet occurrence conditions than the higher frequency (2 times the natural frequency) due to the effect of dynamic displacement. Finally, the effect of material modeling of ratcheting behavior on a beam is shown using different hardening coefficients of kinematic hardening material modeling.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.10-17
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• 2012

In general, image-based 3D scenes can now be found in many popular vision systems, computer games and virtual reality tours. In this paper, we propose a method for creating 3D virtual scenes based on 2D image that is completely automatic and requires only a single scene as input data. The proposed method is similar to the creation of a pop-up illustration in a children's book. In particular, to estimate geometric structure information for 3D scene from a single outdoor image, we apply the tensor voting to an image segmentation. The tensor voting is used based on the fact that homogeneous region in an image is usually close together on a smooth region and therefore the tokens corresponding to centers of these regions have high saliency values. And then, our algorithm labels regions of the input image into coarse categories: "ground", "sky", and "vertical". These labels are then used to "cut and fold" the image into a pop-up model using a set of simple assumptions. The experimental results show that our method successfully segments coarse regions in many complex natural scene images and can create a 3D pop-up model to infer the structure information based on the segmented region information.