• Journal of Broadcast Engineering
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• v.12 no.6
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• pp.565-573
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• 2007

In this paper, we propose a method to select motion vector predictor by considering prediction structure of a multi view content for coding efficiency of multi view coding which is being standardized in JVT. Motion vector of a different tendency is happened while carrying out temporal and view reference prediction of multi-view video coding. Also, due to the phenomena of motion vectors being searched in both temporal and view order, the motion vectors do not agree with each other resulting a decline in coding efficiency. This paper is about how the motion vector predictor are selected with information of prediction structure. By using the proposed method, a compression ratio of the proposed method in multi-view video coding is increased, and finally $0.03{\sim}0.1$ dB PSNR(Peak Signal-to-Noise Ratio) improvement was obtained compared with the case of JMVM 3.6 method.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.2
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• pp.101-113
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• 2013

The concern on environmental quality makes the landscape analysis more important than before ever. For the landscape analysis, selection of viewpoint is one of most important stage. Because of its subjectiveness, the conventional viewpoint selection method often missed some viewpoints of importance. The purpose of this study is to develop a viewpoint selection method for landscape analysis using GIS data and techniques. During the viewpoint selection process, spatial and attribute data from several GIS systems were hired. Query and overlay methods were mainly adapted for analysis to find out meaningful viewpoints. The 3D simulation analysis on DEM(Digital Elevation Model) was used for every selected viewpoint to examine wether the view target is screened out or not. Application study at a sample site showed some omissions of good viewpoints without any screening. It also exhibited the possibility to reduce time and cost for the viewpoint selection process of landscape analysis. For the progress of applicability, GIS data analysis process have to be improved and more modules such as automatic screening analysis system on selected viewpoint have to be developed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7534-7540
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• 2015

In this paper, we set up a vista point overlooking the focus of new research center placed on the existing research literature and point to the selection of books, reports or studies actually suggested focusing on topics such as for landscape simulation evaluation. To re-organize and classify a number of items were presented to spill the evaluation items of this view point selection via the SPSS Statistics. Evaluation items 16 through a professional survey to establish a concrete and systematic plan with selected research results leaked technical characteristics of the view that detailed questions to the factors of technical characteristics and population-specific comparisons through factor analysis in the first, landscapes simulation The views were set out. Second, if you set 16 classified by type of view that considering a similar nature or characteristics depending on the properties of the view that publicity, overlooking castle, the castle was divided into three types of places. Third, the views point for the public good are three items, vista point at which the gender perspective has six items that gender point of view places is set to seven items, was set up to view the most appropriate place to point gender. These results provide a framework for analysis and future system reliability and landscape simulation evaluation study is expected to be used as reference material.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.47-53
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• 2001

In this paper, we compare the classification performances of both ensemble and clustering algorithms (Data Bagging, Variable Selection Bagging, Parameter Combining, Clustering) to logistic regression in consideration of various characteristics of input data. Four factors used to simulate the logistic model are (1) correlation among input variables (2) variance of observation (3) training data size and (4) input-output function. In view of the unknown relationship between input and output function, we use a Taguchi design to improve the practicality of our study results by letting it as a noise factor. Experimental study results indicate the following: When the level of the variance is medium, Bagging & Parameter Combining performs worse than Logistic Regression, Variable Selection Bagging and Clustering. However, classification performances of Logistic Regression, Variable Selection Bagging, Bagging and Clustering are not significantly different when the variance of input data is either small or large. When there is strong correlation in input variables, Variable Selection Bagging outperforms both Logistic Regression and Parameter combining. In general, Parameter Combining algorithm appears to be the worst at our disappointment.

• Journal of the Korean Society for Library and Information Science
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• v.38 no.2
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• pp.213-238
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• 2004

Book review Is a mean that provides Qualitative evaluation and at the same time it plays a role as selection tools for libraries. Therefore, this study Identified various media providing reviews on children's books, evaluated whether the reviews in the media were useful as selection tools of current books, and a desirable model for the book review media that would reform the existing problems was suggested. The efforts to make up for the above suggestions are needed, so that the current children's book review media can properly play a role as selection tools. Above all, at this point in time, it is necessary to publish review media made in the view of libraries and librarians.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4269-4292
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• 2014

Currently, increasing numbers of access points (AP) are being deployed in enterprise offices, campuses and municipal downtowns for flexible Internet connectivity, but most of these access points are idle or redundant most of the time, which causes significant energy waste. Therefore, with respect to power conservation, applying energy efficient strategies in WIFI networks is strongly advocated. One feasible method is dynamically managing network resources, particularly APs, by powering devices on or off. However, when an AP is powered on, the device is initialized through a long boot time, during which period clients cannot be associated with it; therefore, the network performance would be greatly impacted. In this paper, based on a global view of an entire WLAN, we propose an AP selection technology, known as Temporary Access Selection (TAS). The criterion of TAS is a fusion metric consisting of two evaluation indexes which are based on throughput and battery life, respectively. TAS is both service and clients' preference specific through balancing the data rate, battery life and packet size. TAS also works well independently in traditional WLANs in which no energy efficient strategy is deployed. Moreover, this paper demonstrates the feasibility and performance of TAS through experiments and simulations with Network Simulator version 3 (NS3).

• MALSORI
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• no.63
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• pp.125-137
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• 2007

Recently, many techniques have been proposed to improve the noise robustness for speaker verification. In this paper, we consider the feature recombination technique in multi-band approach. In the conventional feature recombination for speaker verification, to compute the likelihoods of speaker models or universal background model, whole feature components are used. This computation method is not effective in a view point of multi-band approach. To deal with non-effectiveness of the conventional feature recombination technique, we introduce a subband likelihood computation, and propose a modified feature recombination using subband likelihoods. In decision step of speaker verification system in noise environments, a few very low likelihood scores of a speaker model or universal background model cause speaker verification system to make wrong decision. To overcome this problem, a reliable feature selection method is proposed. The low likelihood scores of unreliable feature are substituted by likelihood scores of the adaptive noise model. In here, this adaptive noise model is estimated by maximum a posteriori adaptation technique using noise features directly obtained from noisy test speech. The proposed method using subband-based reliable feature selection obtains better performance than conventional feature recombination system. The error reduction rate is more than 31 % compared with the feature recombination-based speaker verification system.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.737-746
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• 2009

The appearance of SOA affects business and IT environment and many studies on SOA is progressed in academics and industries. Service will increase extremely and make business opportunity by composing service. In addition, It will support it. However, studies on selection of a service composition target are insufficient. In this study, we propose a framework that select a service composition target so we use Analytic Hierarchy Process methodology. As a result of this study, we enabled service selection to apply functional/non-functional attributes of services, various stakeholder's view and some selection criteria with service composition.

• Journal of Technology Innovation
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• v.21 no.2
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• pp.225-254
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• 2013

This paper examines an explanatory power of primary alliance motivation theories, such as 'Transaction-Cost Economics (TCE)' and 'Resource-Based View (RBV)', on the technological alliance partner selection criteria, governance and performance. Adopting perspectives of integration provided by TCE and RBV, this work examines the impact of both theories on the alliance processes such as alliance partner selection, governance and performance. Empirical findings show that both TCE and RBV are effective in explaining the choice of technological alliance partners. In addition, TCE appears to be more effective in providing explanation of technological alliance governance structure. Also, both TCE and RBV are effective in evaluating the technological alliance performance phase, though RBV appears to be slightly more effective.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.98-105
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• 2024

This paper proposes a new approach with a distance-based regularization to the entropy applied to the NBV (Next-Best-View) selection with NeRF (Neural Radiance Fields). 3D reconstruction requires images from various viewpoints, and selecting where to capture these images is a highly complex problem. In a recent work, image acquisition was derived using NeRF's ray-based uncertainty. While this work was effective for evaluating candidate viewpoints at fixed distances from a camera to an object, it is limited when dealing with a range of candidate viewpoints at various distances, because it tends to favor selecting viewpoints at closer distances. Acquiring images from nearby viewpoints is beneficial for capturing surface details. However, with the limited number of images, its image selection is less overlapped and less frequently observed, so its reconstructed result is sensitive to noise and contains undesired artifacts. We propose a method that incorporates distance-based regularization into entropy, allowing us to acquire images at distances conducive to capturing both surface details without undesired noise and artifacts. Our experiments with synthetic images demonstrated that NeRF models with the proposed distance and entropy-based criteria achieved around 50 percent fewer reconstruction errors than the recent work.