• Journal of applied mathematics & informatics
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• v.3 no.2
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• pp.157-168
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• 1996

This paper describes an efficient coding method for Ko-rean characters (alphabet) using a three-state transition graph. Par-allel hangul Dynamic Coding Method (PHDCM) compresses about 3.5 bits per Korean character compared with other coding techinques. When we ran the method on a MasPar machine it achieved a 49.314-fold speedup with 64 processors having 10 million orean characters

• KIPS Transactions on Software and Data Engineering
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• v.9 no.3
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• pp.91-100
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• 2020

Unlike the existing Visual Question Answering(VQA) problems, the new Visual Commonsense Reasoning(VCR) problems require deep common sense reasoning for answering questions: recognizing specific relationship between two objects in the image, presenting the rationale of the answer. In this paper, we propose a novel deep neural network model, KG_VCR, for VCR problems. In addition to make use of visual relations and contextual information between objects extracted from input data (images, natural language questions, and response lists), the KG_VCR also utilizes commonsense knowledge embedding extracted from an external knowledge base called ConceptNet. Specifically the proposed model employs a Graph Convolutional Neural Network(GCN) module to obtain commonsense knowledge embedding from the retrieved ConceptNet knowledge graph. By conducting a series of experiments with the VCR benchmark dataset, we show that the proposed KG_VCR model outperforms both the state of the art(SOTA) VQA model and the R2C VCR model.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.57-66
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• 2023

In this paper, a research trend of attack graph studies for Cyber-Physical System (CPS) environments is surveyed, and we analyse the limitations of previous works and prospect the future directions. 35 among around 150 attack graph studies conducted within 5 years target CPS, and we inspect key features of CPS environment in the security aspect. Also, we categorize and analyze target studies in the aspect of modelling physical systems and considering air gaps, which are derived as key features of the security aspects of CPS. Half of 20 research that we surveyed do not reflect those two features, and other studies only consider one of the two features. In this circumstance, we examine challenges that attack graph studies on CPS environment face. Finally, we expect state-led studies or studies targeting open-spec commercial CPS will dominate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1712-1731
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• 2016

In this paper, we propose a novel saliency detection framework via multiple random walks (MRW) which simulate multiple agents on a graph simultaneously. In the MRW system, two agents, which represent the seeds of background and foreground, traverse the graph according to a transition matrix, and interact with each other to achieve a state of equilibrium. The proposed algorithm is divided into three steps. First, an initial segmentation is performed to partition an input image into homogeneous regions (i.e., superpixels) for saliency computation. Based on the regions of image, we construct a graph that the nodes correspond to the superpixels in the image, and the edges between neighboring nodes represent the similarities of the corresponding superpixels. Second, to generate the seeds of background, we first filter out one of the four boundaries that most unlikely belong to the background. The superpixels on each of the three remaining sides of the image will be labeled as the seeds of background. To generate the seeds of foreground, we utilize the center prior that foreground objects tend to appear near the image center. In last step, the seeds of foreground and background are treated as two different agents in multiple random walkers to complete the process of salient object detection. Experimental results on three benchmark databases demonstrate the proposed method performs well when it against the state-of-the-art methods in terms of accuracy and robustness.

• Journal of the Korean Geotechnical Society
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• v.26 no.5
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• pp.37-48
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• 2010

In this study, the seepage flow monitoring method by the hydraulic head loss rate was developed for the purpose of application to offshore construction site enclosed by cofferdams in which seepage force varies periodically. The amount of the hydraulic head loss rate newly defined in this graph was in a range between 0 and 1. The zero of the rate means the existence of flow with no seepage resistance. The 1 of the rate means no seepage flow through the ground. The closer to 1 the coefficient of determinant in the hydraulic head loss graph is, the more the ground through which seepage water flows is stable. The closer to 0 the coefficient of determinant in the hydraulic head loss graph is, the more the ground through which seepage water flows was unstable and the higher the possibilities of existence of empty space or of occurrence of piping on the seepage flow pass in the ground is. The hydraulic head loss graph makes it possible to monitor sensitively the situation of seepage flow state, and the graph helps to understand easily the seepage flow state at the specific section on the whole cofferdam.

• Journal of KIISE:Software and Applications
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• v.34 no.4
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• pp.368-376
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• 2007

How to represent the search space is as important as which search algorithm to use for finding natural-looking paths for moving NPC (non-player character) in computer games. Recently, various state space representation methods which have been developed for computer games are being used while A* algorithm dominates as the preferred search algorithm. These representation methods show some drawbacks such as the size of state space is too large, there is no guarantee for optimality, the path found is not natural-looking, and the generation of nodes and links is not automatic by depending on a level designer. In this paper the requirements for natural-looking paths are introduced and to find paths satisfying these requirements, the use of the generalized visibility graphs which is the extended version of the visibility graph in Robotics is proposed.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.80-86
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• 2022

In this paper, the optimal design and circuit simulation verification results of an LLC resonant half-bridge dc-dc converter using a steady-state model with internal loss resistance are reported. Above all, the input/output voltage gain and frequency characteristic equations in the steady-state were derived by reflecting the internal loss resistance in the equivalent circuit. Based on the results, an LLC resonant half-bridge dc-dc converter with an input voltage of 360-420V, an output voltage of 54V, and a maximum power of 3kW was designed, and to verify the design, the PSIM circuit simulation was executed to compare and analyze the result. In particular, the operating range of the converter could be drawn from the frequency characteristic graph of the voltage gain, and when the converter was operated under light and maximum load conditions, it was confirmed that similar results were obtained by comparing simulation results and calculation results in the switching frequency characteristic graph. In addition, the change of the switching frequency with respect to the load current at each input voltage was compared with the calculated value and the simulation result. As a result, it was possible to confirm the usefulness of the analysis result reflecting the internal loss resistance proposed in this paper and the process of the optimal design.

• Communications of the Korean Mathematical Society
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• v.27 no.4
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• pp.665-668
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• 2012

For a given graph G we consider a set S(G) of all symmetric matrices A = [$a_{ij}$] whose nonzero entries are placed according to the location of the edges of the graph, i.e., for $i{\neq}j$, $a_{ij}{\neq}0$ if and only if vertex $i$ is adjacent to vertex $j$. The minimum rank mr(G) of the graph G is defined to be the smallest rank of a matrix in S(G). In general the computation of mr(G) is complicated, and so is that of the maximum multiplicity MaxMult(G) of an eigenvalue of a matrix in S(G) which is equal to $n$ - mr(G) where n is the number of vertices in G. However, for trees T, there is a recursive formula to compute MaxMult(T). In this note we show that this recursive formula for MaxMult(T) also computes the path cover number $p$(T) of the tree T. This gives an alternative proof of the interesting result, MaxMult(T) = $p$(T).

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.9
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• pp.413-422
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• 2002

In a power plant, disturbance detection and diagnosis are massive and complex problems. Once a disturbance occurs, it can be either persistent, self cleared, cleared by the automatic controllers or propagated into another disturbance until it subsides in a new equilibrium or a stable state. In addition to the Physical complexity of the power plant structure itself, these dynamic behaviors of the disturbances further complicate the fault monitoring and diagnosis tasks. A data structure called a disturbance interrelation analysis graph(DIAG) is proposed in this paper, trying to capture, organize and better utilize the vast and interrelated knowledge required for power plant disturbance detection and diagnosis. The DIAG is a multi-layer directed AND/OR graph composed of 4 layers. Each layer includes vertices that represent components, disturbances, conditions and sensors respectively With the implementation of the DIAG, disturbances and their relationships can be conveniently represented and traced with modularized operations. All the cascaded disturbances following an initial triggering disturbance can be diagnosed in the context of that initial disturbance instead of diagnosing each of them as an individual disturbance. DIAG is applied to a typical cooling water system of a thermal power plant and its effectiveness is also demonstrated.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.238-246
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• 2011

This paper proposes a new semantic representation and its associated similarity measure. The representation expresses textual context observed in a context of a certain term as a network where nodes are terms and edges are the number of cooccurrences between connected terms. To compare terms represented in networks, a graph kernel is adopted as a similarity measure. The proposed representation has two notable merits compared with previous semantic representations. First, it can process polysemous words in a better way than a vector representation. A network of a polysemous term is regarded as a combination of sub-networks that represent senses and the appropriate sub-network is identified by context before compared by the kernel. Second, the representation permits not only words but also senses or contexts to be represented directly from corresponding set of terms. The validity of the representation and its similarity measure is evaluated with two tasks: synonym test and unsupervised word sense disambiguation. The method performed well and could compete with the state-of-the-art unsupervised methods.