• Journal of the Korean Society for information Management
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• v.23 no.4 s.62
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• pp.277-294
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• 2006

This paper examines a level of categorization performance in a real-life collection of abstract articles in the fields of science and technology, and tests the optimal size of documents per category in a training set using a kNN classifier. The corpus is built by choosing categories that hold more than 2,556 documents first, and then 2,556 documents per category are randomly selected. It is further divided into eight subsets of different size of training documents : each set is randomly selected to build training documents ranging from 20 documents (Tr-20) to 2,000 documents (Tr-2000) per category. The categorization performances of the 8 subsets are compared. The average performance of the eight subsets is 30% in $F_1$ measure which is relatively poor compared to the findings of previous studies. The experimental results suggest that among the eight subsets the Tr-100 appears to be the most optimal size for training a km classifier In addition, the correctness of subject categories assigned to the training sets is probed by manually reclassifying the training sets in order to support the above conclusion by establishing a relation between and the correctness and categorization performance.

• Journal of KIISE
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• v.42 no.6
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• pp.723-733
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• 2015

The OTT service that provides multimedia video has spread over the Internet for terminals with a variety of resolutions. The terminals are in communication via a networks such as 3G, LTE, VDSL, ADSL. The service of the network has been increased for a variety of terminals giving rise to the need for a new way of encoding multimedia is increasing. SVC is an encoding technique optimized for OTT services. We proposed an efficient multimedia management system for the SVC encoded multimedia data. The I/O trace was generated using a zipf distribution, and were comparatively evaluated for performance with the existing system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.11a
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• pp.11-14
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• 2009

기존의 반이중방식 단방향 중계 네트워크는 하나의 정보를 두 개의 시간 슬롯 동안에 보내므로 주파수 효율에서 감소가 생기게 된다. 이러한 주파수 효율의 감소를 막기 위해 제안된 양방향 중계 네트워크는 중계기에 중첩 부호화 또는 네트워크 부호화를 적용함으로써 단방향 중계 네트워크에 비해 향상된 주파수 효율을 제공한다. 한편, OFDMA 네트워크는 사용자에게 부반송파, 전력 등의 자원을 적응적으로 할당하여 네트워크의 성능 향상을 얻을 수 있다. 본 논문에서는 다중사용자 다중중계기 양방향 OFDMA 중계 네트워크를 위한 새로운 적응적 부반송파 할당 알고리듬을 제안한다. 먼저 모든 사용자 쌍에 대한 달성 합 전송속도(achievable sum-rate over all user pairs)를 최대화하기 위한 최적화 문제를 정형화한다. 시스템의 수명을 늘이고 각 사용자의 최소 전송속도를 보장하기 위해 공정성 제한을 고려한다. 그리고 이로부터 새로운 적응적 부반송파 할당 알고리듬을 제안한다. 모의실험을 통해 제안된 알고리듬이 정적 알고리듬과 그리디 알고리듬, 두 알고리듬 모두 보다 훨씬 낮은 불능확률을 얻음을 확인한다.

• KIISE Transactions on Computing Practices
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• v.24 no.3
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• pp.105-112
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• 2018

As data size increase, a single database is not enough to serve current volume of tasks. Since data is partitioned and stored into multiple databases, analysis should also support parallelism in order to increase efficiency. However, traditional analysis requires data to be transferred out of database into nodes where analytic service is performed and user is required to know both database and analytic framework. In this paper, we propose an efficient way to perform K-means clustering algorithm inside the distributed column-based database and relational database. We also suggest an efficient way to optimize K-means algorithm within relational database.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.199-208
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• 2005

In this thesis, we have proposed an extended resource management mechanism that optimizes the QoS of multimedia service by complementing the existing resource management mechanism used in IP networks. The proposed resource management mechanism is composed of traffic Scheduler which was designed based on statistic analysis of the distribution of user traffic occurrence, Traffic Monitor Unit, Bandwidth Allocation Unit, queue Controller, and Traffic Classifier In order to confirm the validity of the proposed resource management mechanism, its performance was analyzed by using computer simulation. As a result of performance analysis, its availability was proved.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.81-86
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• 2012

In this paper, we proposed a new design methodology of a pattern classification rule based on the local linear discriminant analysis expanded from the generic linear discriminant analysis which is used in the local area divided from the whole input space. There are two ways such as k-Means clustering method and the differential evolutionary algorithm to partition the whole input space into the several local areas. K-Means clustering method is the one of the unsupervised clustering methods and the differential evolutionary algorithm is the one of the optimization algorithms. In addition, the experimental application covers a comparative analysis including several previously commonly encountered methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.196-199
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• 2010

The human eyes are important facial landmarks for image normalization due to their relatively constant interocular distance. This paper introduces a novel approach for the eye detection task using optimal segmentation method for eye representation. The method consists of three steps: (1)edge extraction method that can be used to accurately extract eye region from the gray-scale face image, (2)extraction of eye region using labeling method, (3)eye localization based on intensity information. Experimental results show that a correct eye detection rate of 98.9% can be achieved on 2408 FERET images with variations in lighting condition and facial expressions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8C
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• pp.661-666
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• 2010

In this paper, we apply a likelihood ratio test (LRT) to a non-negative matrix factorization (NMF) based voice activity detection (VAD) to find optimal threshold. In our approach, the NMF based VAD is expressed as Euclidean distance between noise basis vector and input basis vector which are extracted through NMF. The optimal threshold each of noise environments depend on NMF results distribution in noise region which is estimated statistical model-based VAD. According to the experimental results, the proposed approach is found to be effective for statistical model-based VAD using LRT.

• Transactions of the Korean hydrogen and new energy society
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• v.24 no.4
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• pp.326-333
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• 2013

This paper presents the performance enhancement of a double-inlet centrifugal blower by the shape optimization of an inlet duct. Two design variables, a length of anti circulation vane and an angles of inlet guide, are introduced to improve the inlet flow uniformity leading to the blower performance. Three-dimensional Navier-Stokes equations are used to analyze the blower performance and the internal flow of the blower. From the shape optimization of the inlet duct of the double-inlet centrifugal blower, the optimal positions of each design variable are determined. Throughout the analysis of sensitivity, it is found that the angle of the inlet guide is more effective than the length of the anti-circulation vane to increase flow uniformity at the outlet of the duct. Efficiency and pressure for the optimal inlet duct shape are successfully increased up to 3.55% and 3.2% compared to those of reference blower at the design flow condition, respectively. Detailed flow field inside the blower is also analyzed and compared.

• Journal of IKEEE
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• v.22 no.2
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• pp.440-445
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• 2018

The work presented in this paper deals with a navigation problem for a multiple mobile robots in unknown dynamic environments. The environments are completely unknown to the robots; thus, proximity sensors installed on the robots' bodies must be used to detect information about the surroundings. In order to guide the robots along collision-free paths to reach their goal positions, a navigation method based on a combination of primary strategies has been developed. Most of these strategies are achieved by means of fuzzy logic controllers, and are uniformly applied in every robot. In order to improve the performance of the proposed fuzzy logic, the genetic algorithms were used to evolve the membership functions and rules set of the fuzzy controller. The simulation experiments verified that the proposed method effectively addresses the navigation problem.