• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.246-253
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• 2013

Based on the conventional 2-6GHz digital frequency discriminator (DFD) using the phase unwrapping and least-squares techniques, we propose a new 2-18GHz DFD. To compensate for lowered-precision frequency estimation due to the expanded bandwidth, the proposed DFD design employs more delay lines, accordingly accompanying high complexity. Thus, a new computationally efficient frequency estimation algorithm is also presented to overcome such high computational burden. More specifically, the proposed frequency estimation algorithm is basically based on the conventional phase unwrapping technique, along with a new candidates selection for the unwrapped phases under the condition that the phase margin is known. As a result, the computational burden required for the least-squares technique can be reduced. Finally, simulation results are provided to demonstrate the effectiveness of the proposed approach, compared with those of the conventional DFD's.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1049-1056
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• 2010

Recently RFID system has been adopted in various fields rapidly. However, we should solve the problem of privacy invasion that can be occurred by obtaining information of RFID Tag without any permission for popularization of RFID system. To solve these problems, There is the Ohkubo et al.'s Hash-Chain Scheme which is the safest method. However, this method has a problem that requesting lots of computing process because of creasing numbers of Tag. Therefore We, suggest SP-Division algorithm satisfied with all necessary security of Privacy Protection Scheme and decreased in Tag Identification Time in this paper. And this paper implemented it in time standard finding the first key among the data devided into each nodes. The length of Hash-Chain holds 1000, and the total number of SPs increases 1000, 2000, 3000, and 4000. Comparing tag identification time by the total number of SPs and the number of Nodes with single node, extending the number of nodes to 1, 2, 3 and 4, when the number of nodes is 2, 40% of Performance, when the number of nodes is 3, 56%, and when the number of nodes is 4, 71% is improved.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.1
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• pp.81-87
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• 2009

Recently RFID system has been adopted in various fields rapidly. However, we ought to solve the problem of privacy invasion that can be occurred by obtaining information of RFID Tag without any permission for popularization of RFID system To solve the problems, it is Ohkubo et al.'s Hash-Chain Scheme which is the safest method. However, this method has a problem that requesting lots of computing process because of increasing numbers of Tag. Therefore, in this paper we apply the previous method into the grid environment by analyzing Hash-Chain scheme in order to reduce processing time when Tags are identified. We'll implement the process by offering Tag Identification Process Model to divide SPs evenly by node.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.35-36
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• 2016

소셜 네트워크가 발전함에 따라 인맥형성과 정보공유 의 목적뿐만 아니라 마케팅, 추천 등 여러 분야에 활용됨에 따라 정보를 단시간 내에 더 많은 사용자들이 공유하기 위해 영향력이 높은 사용자를 필요로 하고 이를 위해 정확한 사용자 영향력 판별이 요구된다. 그러나 누구나 정보를 공유할 수 있고 그 양이 너무 방대하기 때문에 신뢰성 없는 정보를 공유하는 문제가 발생한다. 이에 본 논문에서는 소셜 네트워크에서 신뢰성을 고려한 사용자 영향력 판별 기법을 제안한다. 제안하는 기법에서는 신뢰성에 의한 네트워크 간소화와 사용자의 직-간접적인 영향력을 고려하여 영향력을 판별함으로써 정확성을 향상시킨다.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.401-410
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• 2021

Popular in discriminant classification analysis, k-nearest neighbor classification methods have limitations that do not reflect the local characteristic of the data, considering only the number of fixed neighbors. Considering the local structure of the data, the adaptive nearest neighbor method has been developed to select the number of neighbors. In the analysis of high-dimensional data, it is common to perform dimension reduction such as random projection techniques before using k-nearest neighbor classification. Recently, an ensemble technique has been developed that carefully combines the results of such random classifiers and makes final assignments by voting. In this paper, we propose a novel discriminant classification technique that combines adaptive nearest neighbor methods with random projection ensemble techniques for analysis on high-dimensional data. Through simulation and real-world data analyses, we confirm that the proposed method outperforms in terms of classification accuracy compared to the previously developed methods.

• Journal of Navigation and Port Research
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• v.33 no.10
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• pp.671-678
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• 2009

Recently, there have been some researches in the equipment fault detection based on shock and vibration information. Most research of them is based on shock and vibration monitoring to determine the equipment fault or not. Different with engine fault detection based on shock and vibration information we focus on detection of engine for boat and system control. First, it use the duplicated-checking method for shock and vibration information to determine the engine fault or not. If there is a fault happened, we use the integral to determine the error engine shock wave width and detect the fault area. On the other hand, we use the engine trend analysis and standard of safety engine to implement the shock and vibration information database. Our simulation results show that the probability of engine fault determination is 98% and the probability of engine fault detection is 72%

• Journal of KIISE:Information Networking
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• v.36 no.3
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• pp.153-162
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• 2009

It is a challenging work for service operators to accurately classify different services, which runs on various wireless networks based upon numerous platforms. This works focuses on design and implementation of a classifier, which accurately classifies applications, which are captured horn WiBro Network. Notion of session is introduced for the classifier, instead of commonly used Flow to develop a classifier. Based on session information of given traffic, two classification algorithms are presented, Classification and Regression Tree and Support Vector Machine. Both algorithms are capable of classifying accurately and effectively with misclassification rate of 0.85%, and 0.94%, respectively. This work shows that classifier using CART provides ease of interpreting the result and implementation.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.636-646
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• 2015

In information society, the need to detect document duplication and plagiarism is increasing. Many studies have progressed to meet such need, but there are limitations in increasing document duplication detection quality due to technological problem of natural language processing. Recently, some studies tried to increase the quality by applying syntatic-semantic analysis technique. But, the studies have the problem comparing syntactic-semantic trees. This paper develops a syntactic-semantic tree comparator, designs and implements a discriminator of similar documents using the comparator. To evaluate the system, we analyze the correlation between human discrimination and system discrimination with the comparator. This analysis shows that the proposed discrimination has good performance. We need to define the document type and improve the processing technique appropriate for each type.

• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.840-848
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• 2004

Garbage collecting objects in Java makes memory management easier for the programmer, but it is time consuming. Stack allocation may be an alternative which identifies stack-allocatable objects before the execution, without performance degradation. We suggest an escaping analysis recording the interprocedural movement of the method, to detect an object the method of whose creation may have been already deactivated during the access. Our approach is different from prior works, enables us to handle some cases that are missed in the previous variable - oriented approach.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.01a
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• pp.5-7
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• 2016

본 논문에서는 블록 생성 번호를 활용한 동적 마모도 평준화 기법을 제안한다. 지금까지 제안된 동적 마모도 평준화 기법들은 콜드 블록을 판별하기 위해 경과 시간을 사용하고 있다. 하지만 저장장치의 데이터 접근은 일정한 시간 간격으로 이루어지는 것이 아니기 때문에 이와 같은 경과 시간을 사용하는 방식은 데이터에 대한 블록 접근 정보가 왜곡될 수 있는 단점이 있다. 이러한 단점을 해결하기 위해, 본 논문에서 제안하는 기법은 블록을 할당할 때 블록 순차 번호를 테이블에 저장하고 이를 이용하여 블록의 접근 빈도를 판별한다. 실험에서 제한하는 기법은 기존의 CB, CAT 기법과 비교하여 최대 11% 수명이 향상됨을 확인하였다.