• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1186-1191
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• 1991

This paper represents a new edge relaxation algorithm that enhances the noisy boundary informations in images. The proposed algorithm employes relaxation process that reduces or eliminates ambiguities of derivative operator response via contextual informations. The contextual informations are the neighborhood patterns of a central edge which are estimated using fuzzy pattern matching technique. The algorithm is developed on crack edges. Experimental results show that the proposed scheme is effective even for noisy images or low contrast images.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.12
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• pp.124-131
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• 1994

In this paper, we propose a new approach of solving the stereopsis problem with a discrete-time cellular neural network(DTCNN) where each node has connections only with its local neithbors. Because the matching process of stereo correspondence depends on its geometrically local characteristics, the DTCNN is suitable for the stereo correspondence. Moreover, it can be easily implemented in VLSI. Therefore, we employed a two-layer DTCNN with dual templates, which are determined with the back propagation learning rule. Based on evaluation of the proposed approach for several random-dot stereograms, its performance is better than that of the Marr-Poggio algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9B
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• pp.577-588
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• 2007

The rapid growth of the Internet has stimulated the development of various new applications and services, and the service providers and the Internet users now require different levels of service qualities rather than current best-effort service which treats all incoming packet equally. Therefore, next generation routers should provide the various levels of services. In order to provide the quality of services, incoming packets should be classified into flows according to pre-defined rules, and this should be performed for all incoming packets in wire-speed. Packet classification not only involves multi-dimensional search but also finds the highest priority rule among all matching rules. Area-based quad-trie is a very good algorithm that constructs a two-dimensional trie using source and destination prefix fields. However, it performs the linear search for the prefix length, and hence it does not show very good search performance. In this paper, we propose to apply binary search on length to the area-based quad-trie algorithm. In improving the search performance, we also propose two new algorithms considering the priority of rules in building the trie.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.3
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• pp.87-96
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• 2014

Hackers try to achieve their purpose in a variety of ways, such as operating own website and hacking a website. Hackers seize a large amount of private information after they have made a zombie PC by using malicious code to upload the website and it would be used another hacking. Almost detection technique is the use Snort rule. When unknown code and the patterns in IDS/IPS devices are matching on network, it detects unknown code as malicious code. However, if unknown code is not matching, unknown code would be normal and it would attack system. Hackers try to find patterns and make shellcode to avoid patterns. So, new method is needed to detect that kinds of shellcode. In this paper, we proposed a noble method to detect the shellcode by using Shannon's information entropy.

• Journal for History of Mathematics
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• v.23 no.3
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• pp.45-56
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• 2010

Sequent Calculus is a symmetrical version of the Natural Deduction which Gentzen restructured in 1934, where he presents 'Hauptsatz'. In this thesis, we will examine why the Cut-Elimination Theorem has such an important status in Proof Theory despite of the efficiency of the Cut Rule. Subsequently, the dynamic side of Curry-Howard correspondence which interprets the system of Natural Deduction as 'Simply typed $\lambda$-calculus', so to speak the correspondence of Cut-Elimination and $\beta$-reduction in $\lambda$-calculus, will also be studied. The importance of this correspondence lies in matching the world of program and the world of mathematical proof. Also it guarantees the accuracy of program.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.584-591
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• 2014

This article discussed emotion and communication at the film editing theory. By editing as a form of communication, audiences response to the new facts of the story or the new shot as its details and then it uses their ability to induce. Lev Kuleshov, by the famous Mozhukin experiment, intended to show that montage draw spectator's inferences on emotion and association beyond content of the individual shots. The continuous editing technologies such as 180-degree rule, matching eye-view and behavior, 30-degree rule, and continuity of sound, light and color, enhance emotion. Point-of-view editing is the main device to maximize the film's emotion. Point-of-view editing serving the purpose of the film narration is a powerful means to practice and to persuade emotion communication.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.795-802
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• 2002

We propose a fast and powerful Question-answering (QA) system in Korean, which uses a predictive answer indexer based on 2-pass scoring method. The indexing process is as follows. The predictive answer indexer first extracts all answer candidates in a document. Then, using 2-pass scoring method, it gives scores to the adjacent content words that are closely related with each answer candidate. Next, it stores the weighted content words with each candidate into a database. Using this technique, along with a complementary analysis of questions which is based on lexico-syntactic pattern matching method, the proposed QA system saves response time and enhances the precision.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.31-40
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• 2021

The increasing number of credit card fraud cases has become a considerable problem since the past decades. This phenomenon is due to the expansion of new technologies, including the increased popularity and volume of online banking transactions and e-commerce. In order to address the problem of credit card fraud detection, a rule-based approach has been widely utilized to detect and guard against fraudulent activities. However, it requires huge computational power and high complexity in defining and building the rule base for pattern matching, in order to precisely identifying the fraud patterns. In addition, it does not come with intelligence and ability in predicting or analysing transaction data in looking for new fraud patterns and strategies. As such, Data Mining and Machine Learning algorithms are proposed to overcome the shortcomings in this paper. The aim of this paper is to highlight the important techniques and methodologies that are employed in fraud detection, while at the same time focusing on the existing literature. Methods such as Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), naïve Bayesian, k-Nearest Neighbour (k-NN), Decision Tree and Frequent Pattern Mining algorithms are reviewed and evaluated for their performance in detecting fraudulent transaction.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.176-184
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• 2023

Points of interest (POIs) are widely used in tourism recommendations and to provide information about areas of interest. Currently, situation judgement using POI and GPS data is mainly rule-based. However, this approach has the limitation that inferences can only be made using predefined POI information. In this study, we propose an algorithm that uses POI data, GPS data, and schedule information to calculate the current speed, location, schedule matching, movement trajectory, and POI coverage, and uses machine learning to determine whether to stay or go. Based on the input data, the clustered information is labelled by k-means algorithm as unsupervised learning. This result is trained as the input vector of the SVM model to calculate the probability of moving and staying. Therefore, in this study, we implemented an algorithm that can adjust the schedule using the travel schedule, POI data, and GPS information. The results show that the algorithm does not rely on predefined information, but can make judgements using GPS data and POI data in real time, which is more flexible and reliable than traditional rule-based approaches. Therefore, this study can optimize tourism scheduling. Therefore, the stay detection algorithm using GPS movement trajectories and POIs developed in this study provides important information for tourism schedule planning and is expected to provide much value for tourism services.

• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.885-892
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• 2004

In this paper, we propose a multi-modal biometrics system based on face and signature recognition system. Here, the face recognition system is designed by fuzzy LDA, and the signature recognition system is implemented with the LDA and segment matching methods. To effectively aggregate two systems, we obtain statistical distribution models based on matching values for genuine and impostor, respectively. And then, the final verification is Performed by the support vector machine. From the various experiments, we find that the proposed method shows high recognition rates comparing with the conventional methods.