• The KIPS Transactions:PartC
• /
• v.11C no.7 s.96
• /
• pp.917-922
• /
• 2004

Mobile ad hoc networks (MANETs) are networks of mobile nodes that have no fixed network infrastructure. Since the mobile node's location changes frequently, it is an attractive area to maintain the node's location efficiently. In this paper, we present an adaptive randomized database group (ARDG) scheme to manage the mobile nodes mobility in MHANETs. The proposed scheme stores the network nodes' location in location databases to manage the nodes' mobility. When a mobile node changes its location or needs a node's location, the node randomly select some databases to update or que교 the location information. The number of the selected databases is fixed in the case of querying while the number of the databases is determined according to the node's popularity in the case of updating. We evaluated the performance of the proposed scheme using an analytical model, and compared the performance with that of the conventional randomized database group (RDG) scheme.

• Journal of Broadcast Engineering
• /
• v.8 no.4
• /
• pp.325-338
• /
• 2003

Video adaptation in response to dynamic resource conditions and user preferences is required as a key technology to enable universal multimedia access (UMA) through heterogeneous networks by a multitude of devices In a seamless way. Although many adaptation techniques exist, selections of appropriate adaptations among multiple choices that would satisfy given constraints are often ad hoc. To provide a systematic solution, we present a general conceptual framework to model video entity, adaptation, resource, utility, and relations among them. It allows for formulation of various adaptation problems as resource-constrained utility maximization. We apply the framework to a practical case of dynamic bit rate adaptation of MPEG-4 video streams by employing combination of frame dropping and DCT coefficient dropping. Furthermore, we present a descriptor, which has been accepted as a part of MPEG-21 Digital Item Adaptation (DIA), for supporting terminal and network quality of service (QoS) in an interoperable manner. Experiments are presented to demonstrate the feasibility of the presented framework using the descriptor.

• The KIPS Transactions:PartD
• /
• v.15D no.6
• /
• pp.841-856
• /
• 2008

The priority of requirement is important because the priority is a critical activity of release plan especially in software development which has an open market customer. Also, it is important for stakeholders to select a method and aspects to prioritize requirements. The selection is based on the organizational experience of a priority process, the process model of the product, goals and a type of products, and dependencies between requirements. But, the current researches considered only static dependency between requirements and did not suggest a systematic priority process. In addition, the current researches only suggest limited aspects to prioritize requirements, such as cost and value. Therefore, this paper proposes an adjustable priority process based on a priority model to select a method and aspects for the suitable priority for product and organization. Especially, this paper enhances the completeness of a release plan by a definition of static and dynamic dependency types between requirements. This paper suggests a priority model, which considers the dependencies between requirement and various viewpoint of software development. Based on the priority model, the paper suggests a systematic priority process to promote reasonable decisions to the priority and release plan of requirement.

• Korean Journal of Social Welfare Studies
• /
• no.37
• /
• pp.429-455
• /
• 2008

The purpose of this study is to generate a substantive theory that accounts for the social readaptation of the women who have engaged in prostitution and propose a practical program for them. We used the grounded theory developed by Strauss and Corbin(1990). Raw data were collected through the in-depth interview, documents and observation. We used constant comparative method for the data analysis. The nine women who had the exprience of prostitution have participated in this study. As a result of the data analysis, in open coding were generated 116 concepts, 29 subcategories and 12 categories, In axial coding the outcomes of a paradigm model were as follows. The causal conditions were named 'hostile environment' and 'the self endowed stigma'. The phenomenon turned out to be 'living as an anonymous being'. The contextual conditions were named 'cohesion of family', 'being pushed' and 'shrinked emotion'. The intervening conditions were presented to be 'desire of self restoration as a social being', 'reactionary reconstruction'. The action/interaction strategies turned out to be 'shifting of social status', 'neighbor alliance'. The consequences were presented to be 'psychological wayfarer' and 'tentacular living'. In selective coding we found a core category, 'repetition of leaving and returning from the life world'. Based on the phenomenon, two types of participants life attitudes were found as follows : present hesitating type, self concealing type. Following the adove results, We finally suggested the need to develope a community oriented case management model.

• Journal of KIISE:Information Networking
• /
• v.37 no.6
• /
• pp.489-493
• /
• 2010

In an indoor localization method taking the lateration-based approach, the distance between a target and an AP (Anchor Point) is estimated using RSS (Received Signal Strength) measurements. Since the characteristics of a radio signal randomly vary in time and space, errors are unavoidable in distance estimation with measured RSS. Since the accuracy of distance estimation affects the localization accuracy of a lateration-based method, additional APs hearing a target have been used for localization in the literature. However, lots of experimental results show that the accuracy of a lateration-based method is improved by using carefully selected APs measuring the high quality RSSs which the distances estimated is close to the actual distances between nodes as reference APs, not using merely more APs. In this paper, we focus on selection method of reference AP and distance estimation method reflecting on environmental dynamics. We validate our method by implementing an indoor localization system and evaluating the accuracy of our method in the various experimental environments.

• Journal of KIISE:Computer Systems and Theory
• /
• v.32 no.10
• /
• pp.520-529
• /
• 2005

A feature-based 3D modeling algorithm is presented in this paper. Since conventional methods use depth-based techniques, they need much time for the image matching to extract depth information. Even feature-based methods have less computation load than that of depth-based ones, the calculation of modeling error about whole pixels within a triangle is needed in feature-based algorithms. It also increase the computation time. Therefore, the proposed algorithm consists of three phases, which are an initial 3D model generation, model evaluation, and model refinement phases, in order to acquire an efficient 3D model. Intensity gradients and incremental Delaunay triangulation are used in the Initial model generation. In this phase, a morphological edge operator is adopted for a fast edge filtering, and the incremental Delaunay triangulation is modified to decrease the computation time by avoiding the calculation errors of whole pixels and selecting a vertex at the near of the centroid within the previous triangle. After the model generation, sparse vertices are matched, then the faces are evaluated with the size, approximation error, and disparity fluctuation of the face in evaluation stage. Thereafter, the faces which have a large error are selectively refined into smaller faces. Experimental results showed that the proposed algorithm could acquire an adaptive model with less modeling errors for both smooth and abrupt areas and could remarkably reduce the model acquisition time.

• Journal of KIISE:Computer Systems and Theory
• /
• v.31 no.1_2
• /
• pp.59-66
• /
• 2004

In this paper, a fast 3D model extraction algorithm with an enhanced PBIL of preserving depth consistency is proposed for the extraction of 3D depth information from 2D images. Evolutionary computation algorithms are efficient search methods based on natural selection and population genetics. 2D disparity maps acquired by conventional matching algorithms do not match well with the original image profile in disparity edge regions because of the loss of fine and precise information in the regions. Therefore, in order to decrease the imprecision of disparity values and increase the quality of matching, a compact genetic algorithm is adapted for matching environments, and the adaptive window, which is controlled by the complexity of neighbor disparities in an abrupt disparity point is used. As the result, the proposed algorithm showed more correct and precise disparities were obtained than those by conventional matching methods with relaxation scheme.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.9 no.5
• /
• pp.543-548
• /
• 2014

Multiple-model based speech recognition framework (MMSR) has been known to be very successful in speech recognition. Since it uses multiple hidden Markov modes (HMMs) that corresponds to various noise types and signal-to-noise ratio (SNR) values, the selected acoustic model can have a close match with the test noisy speech. However, since the number of HMM sets is limited in practical use, the acoustic mismatch still remains as a problem. In this study, we experimentally determined the optimal SNR mapping between the test noisy speech and the HMM set to mitigate the mismatch between them. Improved performance was obtained by employing the SNR mapping instead of using the estimated SNR from the test noisy speech. When we applied the proposed method to the MMSR, the experimental results on the Aurora 2 database show that the relative word error rate reduction of 6.3% and 9.4% was achieved compared to a conventional MMSR and multi-condition training (MTR), respectively.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.06d
• /
• pp.55-57
• /
• 2006

최근 국내 표준의 확정과 함께 새로운 수익모델로써 다양한 분야에서 활용이 기대가 되는 RFID 무선인식 시스템은 국내의 많은 업체와 기관들이 현재 다양한 솔루션을 개발함으로써 다가오는 유비쿼터스 환경에 적극 대응하고 있다. RFID 시스템의 중요한 기술요소 중 하나는 다중 태그로 인한 충돌을 처리하는 Anti-collision 알고리즘이다. 본 논문에서는 먼저 충돌방지기법의 종류와 최근에 900MHz대역의 RFID 표준으로 확정된 ISO/IEC 18000-6 Type C 표준문서에서 소개한 Slotted random 충돌방지 알고리즘을 분석하고, 충돌 정도에 따라 적응적으로 다음 프레임의 크기를 조정하는 기법을 제안한다. 모든 태그를 완전히 읽어내는데 걸리는 시간을 계산하기 위해서 Type C 표준을 적용한 모의실험을 통해 성능평가를 하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.04a
• /
• pp.303-306
• /
• 2004

기존의 퍼지 규칙에 기반을 둔 퍼지 다항식 뉴론(FPN)들로 구성된 SOFPNN은 데이터 수가 적고 비선형 요소가 많은 시스템에 대한 체계적이고 효율적인 최적 모델 을 구축할 수 있었으며 각 층 노드의 선택 입력을 변화시킴으로써 네트워크 구조 전체의 적응능력을 향상 시켰다. 유전자 알고리즘을 이용하여 자기구성 퍼지 다항식 뉴럴 네트워크의 입력변수의 수와 이에 해당되는 입력변수 그리고 규칙 후반부 다항식의 차수를 탐색하여 최적 의 자기구성 퍼지 다항식 뉴럴 네트워크를 구축한다. 그러나, SOFPNN의 기본 뉴론인 퍼지 규칙 기반 다항식 뉴론의 경우 입력변수가 많아질수록 규칙수가 기하급수적으로 증가한다는 단점을 가지고 있으나 본 노문에서 제안한 퍼지 집합 기반 다항식 뉴론(FSPN)의 규칙수는 입력 변수들이 서로 독립적이므로 규칙의 증가가 퍼지 규칙 기반 다항식 뉴런보다는 적다는 장점을 가지고 있다. 이러한 특성을 기반으로 기존의 SOFPNN의 노드에 퍼지 규칙 기반 다항식 뉴런 대신에 퍼지 집합 기반 다항식 뉴런을 적용한 SOFPNN을 제안하여 기존의 SOFPNN과 성능을 비교하였다. 최적의 자기 구성 퍼지 집합기반 다항식 뉴럴 네트워크를 구축하기 위하여 SOFPNN에서처럼 유전자 알고리즘을 이용하여 네트워크의 입력변수의 수와 이에 해당되는 입력변수 그리고 규칙 후반부 다항식의 차수를 탐색하였다.