• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.759-766
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• 2013

The paper examines several classes of probability distributions with heavy tails. An (asymptotic) expression for tail probability needs to be known to understand which class a given probability distribution belongs to. It is usually not easy to get expressions for tail probabilities since most absolutely continuous probability distributions are specified by probability density functions and not by distribution functions. The paper proposes a method to obtain asymptotic expressions for tail probabilities using only probability density functions. Some examples are given to illustrate the proposed method.

• Journal of Broadcast Engineering
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• v.3 no.1
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• pp.1-12
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• 1998

8VSB transmission system of American standard and OFDM system of European standard are to be international standards for the transmission of digital terrestrial television. When countries using PAL standard adopt the American 8VSB system which is designed under the circumstance of NTSC system, one of strong interference is the co-channel PAL interference coming from analog PAL signal. In this paper, in order to solve this problem, we classified seven types of PAL system into three groups according to the bandwidth and a new PAL-8VSB system is proposed to reject the co-channel PAL interference by using modified comb filters suitable for each group. By computer simulations of the proposed PAL-8VSB system with the co-channel PAL interference it is confirmed that the proposed comb filter results in the improvement of DIU ratio by about 9 dB.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.3
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• pp.158-170
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• 2009

In this paper, we propose the new torus network which has the hypercube Q3 as the basic module. The proposed Hyper-torus has the degree 4, and is the network which has the scalability, and the fine diameter. If we compare the class of the torus in the viewpoint of network cost, the hyper-torus with $1.4{\sqrt{N}}$+ 16 is proved to be approximately 65% than the torus with $4{\sqrt{N}}$ and 50% than the honeycomb with $2.45{\sqrt{N}}$. This result means that hyper-torus is better for the class of the existing mesh in the viewpoint of network cost.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.155-161
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• 2017

This paper suggests polynomial time solution algorithm for Sudoku puzzle problem. This problem has been known NP (non-deterministic polynomial time)-complete. The proposed algorithm set the initial value of blank cells to value range of [$1,2,{\cdots},9$]. Then the candidate set values in blank cells deleted by preassigned clue in row, column, and block. We apply the basic rules of Stuart, and proposes two additional rules. Finally we apply binary backtracking(BBT) technique. For the experimental Sudoku puzzle with various categories of solution, the BBT algorithm can be obtain all of given Sudoku puzzle regardless of any types of solution.

• Language and Information
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• v.14 no.1
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• pp.165-196
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• 2010

The primary goal of this paper is to propose methods of enriching two heterogeneous ontologies: Sejong Semantic Classes (SJSC) and KorLexNoun 1.5 (KLN). In order to achieve this goal, this study introduces the pros and cons of two ontologies, and analyzes the error patterns found during the fine-grained manual mapping processes between them. Error patterns can be classified into four types: (1) structural defectives involved in node branching, (2) errors in assigning the semantic classes, (3) deficiency in providing linguistic information, and (4) lack of the lexical units representing specific concepts. According to these error patterns, we propose different solutions in order to correct the node branching defectives and the semantic class assignment, to complement the deficiency of linguistic information, and to increase the number of lexical units suitably allotted to their corresponding concepts. Using the results of this study, we can obtain more enriched ontologies by correcting the defects and errors in each ontology, which will lead to the enhancement of practicality for syntactic and semantic analysis.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.10-18
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• 2010

Due to a large number of classes in Hangul character recognition, it is usual to use the six-type preclassification stage. After the preclassification, the first consonent, vowel, and last consonent can be classified separately. Though each of three components has a few of classes, classification errors occurs often due to shape similarity such as 'ㅔ' and 'ㅖ'. So this paper proposes a hierarchical recognition method which adopts multi-stage tree structures for each of 6-types. In addition, to reduce the interference among three components, the method uses the recognition results of first consonents and vowel as features of vowel classifier. The recognition accuracy for the test set of PHD08 database was 98.96%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.555-556
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• 2021

In this paper, we propose a malware family classification scheme using malware visualization and transfer learning. The malware can be easily reused or modified. However, traditional malware detection techniques are vulnerable to detecting variants of malware. Malware belonging to the same class are converted into images that are similar to each other. Therefore, the proposed method can classify malware with a deep learning model that has been verified in the field of image classification. As a result of an experiment using the VGG-16 model on the Malimg dataset, the classification accuracy was over 98%.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3874-3884
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• 2000

An information retrieval system has to retrieve all and only documents which are relevant to a user query, even if index terms and query terms are not matched exactly. However, term mismatches between index terms and qucry terms have been a serious obstacle to the enhancement of retrieval performance. In this paper, we discuss automatic term normalization between words in text corpora and their application to a Korean information retrieval system. We perform two types of term normalizations to alleviate semantic term mismatches: equivalence class and co-occurrence cluster. First, transliterations, spelling errors, and synonyms are normalized into equivalence classes bv using contextual similarity. Second, context-based terms are normalized by using a combination of mutual information and word context to establish word similarities. Next, unsupervised clustering is done by using K-means algorithm and co-occurrence clusters are identified. In this paper, these normalized term products are used in the query expansion to alleviate semantic tem1 mismatches. In other words, we utilize two kinds of tcrm normalizations, equivalence class and co-occurrence cluster, to expand user's queries with new tcrms, in an attempt to make user's queries more comprehensive (adding transliterations) or more specific (adding spc'Cializationsl. For query expansion, we employ two complementary methods: term suggestion and term relevance feedback. The experimental results show that our proposed system can alleviatl' semantic term mismatches and can also provide the appropriate similarity measurements. As a result, we know that our system can improve the rctrieval efficiency of the information retrieval system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.5 s.311
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• pp.29-37
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• 2006

Thresholding is a fundamental approach to segmentation that utilizes a significant degree of pixel popularity or intensity. Otsu's thresholding employed the normalized histogram as a discrete probability density function. Also it utilized a criterion that minimizes the between-class variance of pixel intensity to choose a threshold value for segmentation. However, the Otsu's method has a disadvantage of repeatedly searching optimal thresholds for the entire range. In this paper, a simple but fast multi-level thresholding approach is proposed by means of extending the Otsu's method. Rather than invoke the Otsu's method for the entire gray range, we advocate that the gray-level range of an image be first divided into smaller sub-ranges, and that the multi-level thresholds be achieved by iteratively invoking this dividing process. Initially, in the proposed method, the gray range of the object image is divided into 2 classes with a threshold value. Here, the threshold value for segmentation is selected by invoking the Otsu's method for the entire range. Following this, the two classes are divided into 4 classes again by applying the Otsu's method to each of the divided sub-ranges. This process is repeatedly performed until the required number of thresholds is obtained. Our experimental results for three benchmark images and fifty faces show a possibility that the proposed method could be used efficiently for pattern matching and face recognition.

• Journal of the korean veterinary medical association
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• v.35 no.2
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• pp.108-109
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• 1999

오늘날 `인공수정`하면 소,돼지는 일반화된 방법이 된 지 오래다. 그런데 `개의 인공수정`하면 아직도 많은 수의사나 번식가들이 회의를 가지고 있다. 필자 역시 KCRC 울산 지회로 가입하기 전까지는 그런 부류에 속했다. 그러나 KCRC의 수차례의 Canine Reproduction(AL)에 대한 세미나와 실습을 통하여 냉동 정액을 이용하여 인공수정을 할 수 있구나 하는 생각을 가지게 되었고 필자가 인공수정의 전 과정을 스르로 해 본 결과 나름대로 확신을 가질 수 있게 되었다. 물론 다음의 한 예가 인공수정에 대한 의문을 모두 제거하리라는 기대는 무리가 있겠지만 최소한 개의 인공 수정에 대한 이해의 폭은 넓히리라 확신한다.