• The Journal of the Korea Contents Association
• /
• v.18 no.2
• /
• pp.438-449
• /
• 2018

Recently, various graph data have been utilized in various fields such as social networks and citation networks. As the graph changes dynamically over time, it is necessary to manage the graph historical data for tracking changes and retrieving point-in-time graphs. Most historical data changes partially according to time, so unchanged data is stored redundantly when data is stored in units of time. In this paper, we propose a graph history storage management method to minimize the redundant storage of time graphs. The proposed method continuously detects the change of the graph and stores the overlapping subgraph in intersection snapshot. Intersection snapshots are connected by a number of delta snapshots to maintain change data over time. It improves space efficiency by collectively managing overlapping data stored in intersection snapshots. We also linked intersection snapshots and delta snapshots to retrieval the graph at that point in time. Various performance evaluations are performed to show the superiority of the proposed scheme.

• Proceedings of the KIEE Conference
• /
• 2004.05a
• /
• pp.65-67
• /
• 2004

Change of state of Channel between two wireless terminals which is caused by noise and multiple environmental conditions for happens frequently from the Wireles Network. So, When it is like that planning a wireless network protocol or performance analysis, it follows to change of state of time-varying channel and packet the analysis against a transmission efficiency is necessary. In this paper, analyzes transmission time of a packet and a packet in a time-varying and packet based Wireless Network. To reflecte the feature of the time-varying channel, we use a Signal Flow Graph model. From the model the mean of transmission time and the mean of queue length of the packet are analyzed in terms of the packet distribution function, the packet transmission service time, and the PER of the time-varying channel.

• Environmental and Resource Economics Review
• /
• v.12 no.4
• /
• pp.687-708
• /
• 2003

The purpose of this paper is to introduce time-series causality analysis by combining time-series technique with graph theory. Vector autoregressive (VAR) models can provide reasonable interpretation only when the contemporaneous variables stand in a well-defined causal order. We show that how graph theory can be applied to search for the causal structure In VAR analysis. Using Maryland crop cash prices and CBOT futures price data, we estimate a VAR model with directed acyclic graph analysis. This expands our understanding the degree of interconnectivity between the employed time-series variables.

• Journal of applied mathematics & informatics
• /
• v.5 no.1
• /
• pp.141-152
• /
• 1998

Based on the geometric representation an efficient al-gorithm is designed to find all articulation points of a permutation graph. The proposed algorithm takes only O(n log n) time and O(n) space where n represents the number of vertices. The proposed se-quential algorithm can easily be implemented in parallel which takes O(log n) time and O(n) processors on an EREW PRAM. These are the first known algorithms for the problem on this class of graph.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.3
• /
• pp.111-117
• /
• 2021

The delivery problem on a graph is that of minimizing the object delivery time from one vertex to another vertex on a graph with m vertices using n various speed robot agents. In this paper, we propose two optimal solution algorithms for the delivery problem on a graph with time complexity of O(㎥n) and O(㎥). After preprocessing to obtain the shortest path for all pairs of the graph, our algorithm processed by obtaining the shortest delivery path in the order of the vertices with the least delivery time. Assuming that the graph reflects the terrain on which to solve the problem, our O(㎥) algorithm actually has a time complexity of O(㎡n) as only one preprocessing is required for the various deployment of n robot agents.

• International Journal of Advanced Culture Technology
• /
• v.4 no.1
• /
• pp.19-27
• /
• 2016

Technology in the animation industry has evolved significantly over the past decade. The tools to create animation are becoming more intuitive to use. Animators now spend more time on the artistic quality of their work than wasting time figuring out how to use the software that they rely on. However, one particular tool that is still unintuitive for animators is the motion graph editor. A motion graph editor is a tool to manipulate the interpolation of the movements generated by the software. Although the motion graph editor contains a lot of options to control the outcome of the animation, the emotional rhythm of the movements desired by the animator still depends on the animator's skill, which requires a very steep learning curve. More often than not, animators had to resort to trial and error methods to achieve good results. This inevitably leads to slow productivity, susceptible to mistakes, and waste of resources. This research will study the connection between the motion graph profile and the emotions they portray in movements. The findings will hopefully be able to provide animators reference materials to achieve the emotional animation they need with less effort.

• KIISE Transactions on Computing Practices
• /
• v.23 no.3
• /
• pp.156-164
• /
• 2017

Measuring the similarity of two graphs is a basic tool to solve graph problems in various applications. Most graph algorithms have a high time complexity according to the number of vertices and edges. Because Graphics Processing Units (GPUs) have a high computational power and can be obtained at a low cost, these have been widely used in graph applications to improve execution time. This paper proposes an efficient parallel algorithm to measure graph similarity using the CUDA on a GPU environment. The experimental results show that the proposed approach brings a considerable improvement in performance and efficiency when compared to CPU-based results. Our results also show that the performance is improved significantly as the size of the graph increases.

• Journal of applied mathematics & informatics
• /
• v.28 no.5_6
• /
• pp.1347-1358
• /
• 2010

An upright drawing of a planar graph G on k layers is a planar straight-line drawing of G, where the vertices of G are placed on a set of k horizontal lines, called layers and no two adjacent vertices are placed on the same layer. There is a previously known algorithm that decides in linear time whether a planar graph admits an upright drawing on k layers for a fixed value of k. However, the constant factor in the running time of the algorithm increases exponentially with k and makes it impractical even for k = 3. In this paper, we give a linear-time algorithm to examine whether a biconnected planar graph G admits an upright drawing on three layers and to obtain such a drawing if it exists. We also give a necessary and sufficient condition for a tree to have an upright drawing on three layers. Our algorithms in both the cases are much simpler and easier to implement than the previously known algorithms.

• Journal of the Korean Society of Safety
• /
• v.13 no.2
• /
• pp.136-144
• /
• 1998

FTA is the most commonly used method among quantitative safety assessment. In case that the observing system become larger, a lot of terms should be calculated to accomplish FTA through complicated process. Many methods have been tried to reduce time, one of tries is How to calculate the reliability using graph theory after changing W to graph. This paper suggests an algorithm that can calculate more rapidly reliability and outset of system expressed by non-linear graph as like as FTA or CCA.

• Journal of KIISE
• /
• v.44 no.7
• /
• pp.710-718
• /
• 2017

As graphs are becoming increasingly large, the costs for storing and managing data are increasing continuously. Shortest path discovery over a large graph requires long running time due to frequent disk I/Os and high complexity of the graph data. Recently, graph summarization techniques have been studied, which reduce the size of graph data and disk I/Os by representing highly dense subgraphs as a single super-node. Decompressing should be minimized for efficient shortest path discovery over the summarized graph. In this paper, we analyze the decompression performance of a summarized graph and propose an approximate technique that discovers the shortest path quickly with a minimum error ratio. We also propose an exact technique that efficiently discovered the shortest path by exploiting an index built on paths containing super-nodes. In our experiments, we showed that the proposed technique based on the summarized graph can reduce the running time by up to 70% compared with the existing techniques performed on the original graph.