• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.251-258
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• 2009

Data mining is a method that extract useful knowledges from huge size of data. Recently, a focussing research part of data mining is to find interesting patterns in graph databases. More efficient methods have been proposed in graph mining. However, graph analysis methods are in NP-hard problem. Graph pattern mining based on pattern growth method is to find complete set of patterns satisfying certain property through extending graph pattern edge by edge with avoiding generation of duplicated patterns. This paper suggests an efficient approach of reducing computing time of pattern growth method through pattern growth's property that similar patterns cause similar tasks. we suggest pruning methods which reduce search space. Based on extensive performance study, we discuss the results and the future works.

• Journal of Microbiology and Biotechnology
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• v.2 no.4
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• pp.293-296
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• 1992

Increased concentrations of yeast extract led to increased growth yields and faster growth rates of the newly isolated Clostridium thermobutyricum. This species produced butyrate as its main fermentation product from glucose as well as from yeast extract. In the presence of peptone or tyrptone and during growth on agar, up to 70% of the cells sporulated. Growth yields were 30 and 55 g per mole glucose in the presence of 0.05 and 2.0% yeast extract, respectively. The Arrhenius graph was biphasic, exhibiting an intermediary plateau around $38^{\circ}C$ with a concomitant change in the Arrhenius energy. The optimum temperature was $55^{\circ}C$. An unusually sharp decline in the growth rate occurred above $59^{\circ}C$ .

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.11
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• pp.634-639
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• 2002

A Shortest Path Algorithm is the method to find the most efficient route among many routes from a start node to an end node. It is based on Labeling methods. In Labeling methods, there are Label-Setting method and Label-Correcting method. Label-Setting method is known as the fastest one among One-to-One shortest path algorithms. But Benjamin[1,2] shows Label-Correcting method is faster than Label-Setting method by the experiments using large road data. Since Graph Growth algorithm which is based on Label-Correcting method is made to find One-to-All shortest path, it is not suitable to find One-to-One shortest path. In this paper, we propose a new One-to-One shortest path algorithm. We show that our algorithm is faster than Graph Growth algorithm by extensive experiments.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.1 no.1
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• pp.31-43
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• 1968

1. Shell height frequencies of the fresh-water cockle, Corbicula elatior, sampled in the period of 1960 to 1963, are analyzed to assess the age composition and average growth pattern. Cumulative frequencies in a sample are traced on a probability scale, and the points of inflection on a probability graph are assumed to dissect age groups. 2. Seasonal growth of Corbicula elatior in the Naktong River ill as follows: Young cockles settle down on river-bed by June and grow rapidly during the summer season, reaching 14mm in shell height by October. From October to April the growth is very slow. The rapid growth in the second year starts around in May. 3. Survival rate per year for Corbicula elatior in the Naktong River is estimated to be $5\~10\%$ by age composition.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.5
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• pp.177-188
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• 2018

The scale of graph data has been increased rapidly because of the growth of mobile Internet applications and the proliferation of social network services. This brings upon the imminent necessity of efficient distributed and parallel graph processing approach since the size of these large-scale graphs are easily over a capacity of a single machine. Currently, there are two popular parallel graph processing approaches, vertex-centric graph processing and block centric processing. While a vertex-centric graph processing approach can easily be applied to the parallel processing system, a block-centric graph processing approach is proposed to compensate the drawbacks of the vertex-centric approach. In these systems, the initial quality of graph partition affects to the overall performance significantly. However, it is a very difficult problem to divide the graph into optimal states at the initial phase. Thus, several dynamic load balancing techniques have been studied that suggest the progressive partitioning during the graph processing time. In this paper, we present a load balancing algorithms for the block-centric graph processing approach where most of dynamic load balancing techniques are focused on vertex-centric systems. Our proposed algorithm focus on an improvement of the graph partition quality by dynamically reassigning blocks in runtime, and suggests block split strategy for escaping local optimum solution.

• ETRI Journal
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• v.31 no.2
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• pp.240-242
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• 2009

A computationally efficient implementation of the progressive edge-growth algorithm is presented. This implementation uses an array of red-black (RB) trees to manage the layered structure of check nodes and adopts a new strategy to expand the Tanner graph. The complexity analysis and the simulation results show that the proposed approach reduces the computational effort effectively. In constructing a low-density parity check code with a length of $10^4$, the RB-tree-array-based implementation takes no more 10% of the time required by the original method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3258-3273
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• 2021

Malware is a severe threat to the computing system and there's a long history of the battle between malware detection and anti-detection. Most traditional detection methods are based on static analysis with signature matching and dynamic analysis methods that are focused on sensitive behaviors. However, the usual detections have only limited effect when meeting the development of malware, so that the manual update for feature sets is essential. Besides, most of these methods match target samples with the usual feature database, which ignored the characteristics of the sample itself. In this paper, we propose a new malware detection method that could combine the features of a single sample and the general features of malware. Firstly, a structure of Directed Cyclic Graph (DCG) is adopted to extract features from samples. Then the sensitivity of each API call is computed with Markov Chain. Afterward, the graph is merged with the chain to get the final features. Finally, the detectors based on machine learning or deep learning are devised for identification. To evaluate the effect and robustness of our approach, several experiments were adopted. The results showed that the proposed method had a good performance in most tests, and the approach also had stability with the development and growth of malware.

• Journal of the HCI Society of Korea
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• v.10 no.1
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• pp.5-17
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• 2015

Nowadays various public data have been serviced to the public. Through the opening of public data, the transparency and effectiveness of public policy developed by governments are increased and users can lead to the growth of industry related to public data. Since end-users of using public data are citizens, it is very important for everyone to figure out the meaning of public data using proper visualization techniques. In this work, to indicate the significance of widespread public data, we consider UN voting record as public data in which many people may be interested. In general, it has high utilization value by diplomatic and educational purposes, and is available in public. If we use proper data mining and visualization algorithms, we can get an insight regarding the voting patterns of UN members. To visualize, it is necessary to measure the voting similarity values among UN members and then a social graph is created by the similarity values. Next, using a graph layout algorithm, the social graph is rendered on the screen. If we use the existing method for visualizing the social graph, it is hard to understand the meaning of the social graph because the graph is usually dense. To improve the weak point of the existing social graph visualization, we propose Friend-Matching, Friend-Rival Matching, and Bubble Heap algorithms in this paper. We also validate that our proposed algorithms can improve the quality of visualizing social graphs displayed by the existing method. Finally, our prototype system has been released in http://datalab.kunsan.ac.kr/politiz/un/. Please, see if it is useful in the aspect of public data utilization.

• Korean Journal of Materials Research
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• v.21 no.3
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• pp.174-179
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• 2011

Ultra-thin aluminum (Al) and tin (Sn) films were grown by dc magnetron sputtering on a glass substrate. The electrical resistance R of films was measured in-situ method during the film growth. Also transmission electron microscopy (TEM) study was carried out to observe the microstructure of the films. In the ultra-thin film study, an exact determination of a coalescence thickness and a continuous film thickness is very important. Therefore, we tried to measure the minimum thickness for continuous film (dmin) by means of a graphical method using a number of different y-values as a function of film thickness. The raw date obtained in this study provides a graph of in-situ resistance of metal film as a function of film thickness. For the Al film, there occurs a maximum value in a graph of in-situ electrical resistance versus film thickness. Using the results in this study, we could define clearly the minimum thickness for continuous film where the position of minimum values in the graph when we put the value of Rd3 to y-axis and the film thickness to x-axis. The measured values for the minimum thickness for continuous film are 21 nm and 16 nm for sputtered Al and Sn films, respectively. The new method for defining the minimum thickness for continuous film in this study can be utilized in a basic data when we design an ultra-thin film for the metallization application in nano-scale devices.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.131-137
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• 2007

I intend to seek the shortest path which an aircraft safely flies to its destination through the shadow volume of three dimensional terrain which propagation does not extend. Herein, I propose a method in which a relatively wide shadow volume is divided with a polygon type of block polygon, a path up to the intermediate destination is sought in the divided block polygons according to the weight, and then, the shortest path up to the final destination is sought by repeating courses for seeking a destination again from the adjacent polygon based on the starting point of the intermediate destination within the divided polygon. The shortest path was searched by using the revised algorithms which apply to a critical angle from graph growth algorithms on the shadow volume which propagation on the actual three dimensional terrain does not extend to. The experiment shows that a method proposed in this paper creates effective flying curves.