• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1416-1428
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• 2016

In this paper, we address the channel zapping time problem of video streaming services based on HTTP Live Streaming (HLS) on smart Over-The-Top Set-Top Boxes (OTT STBs). Experimental analysis of the channel zapping time, show that smart OTT STBs inevitably suffer from the accumulated zapping time through channel change request, Internet Group Management Protocol (IGMP) leave/join, synchronization delay, video buffer delay, and STB processing delay when providing HLS services. As a practical solution for the zapping time reduction, an adaptive buffering method is proposed. The proposed method exploits two adaptive buffers added to the basic HLS player. These two adaptive buffers are responsible for constantly buffering previous and next channels relative to the current channel. Implementation and test results show that a stable zapping time less than one second can be achieved even under diverse video bitrate changes and varying network conditions by the proposed adaptive buffering method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.1027-1030
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• 2005

The article introduces developing trends of an adaptive mobile terminal as an interface for use of various network resources, such as public wireless networks and un-licensed wireless networks in ubiquitous sensor network environments, without troublesome settings or operations by users. These adaptive mobile terminals able to provide seamless services that adapt autonomously to the user's movements and changes in the state of wireless resources. Consequently, adaptive mobile terminals should be had respective independent hardware structure of usable wireless networks.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.91-96
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• 2014

This paper proposed an adaptive threshold method for detecting flame candidate regions in a infrared image and it adapts according to the contrast and intensity changes in the image. Conventional flame detection systems uses fixed threshold method since surveillance environment does not change, once the system installed. But it needs a adaptive threshold method as requirements of surveillance system has changed. The proposed adaptive threshold algorithm uses the dynamic behavior of flame as featured parameter. The test result is analysed by comparing test result of proposed adaptive threshold algorithm and conventional fixed threshold method. The analysed data shows, the proposed method has 91.42% of correct detection rate and false detection is reduced by 20% comparing to the conventional method.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.628-632
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• 2005

Remote sensing through atmospheric turbulence had been hard works for a long time, because wavefront distortion due to the Earth's atmospheric turbulence deteriorates image quality. But due to the appearance of adaptive optics, it is no longer difficult things. Adaptive optics is the technology to correct random optical wavefront distortions in real time. For past three decades, research on adaptive optics has been performed actively. Currently, most of newly built telescopes have adaptive optical systems. Adaptive optical system is typically composed of three parts, wavefront sensing, wavefront correction and control. In this work, the wavefront sensing technology for adaptive optical system is treated. More specifically, shearing interferometers and Shack-Hartmann wavefront sensors are considered. Both of them are zonal wavefront sensors and measure the slope of a wavefront. . In this study, the shearing interferometer is made up of four right-angle prisms, whose relative sliding motions provide the lateral shearing and phase shifts necessary for wavefront measurement. Further, a special phase-measuring least-squares algorithm is adopted to compensate for the phase-shifting error caused by the variation in the thickness of the index-matching oil between the prisms. Shack-Hartmann wavefront sensors are widely used in adaptive optics for wavefront sensing. It uses an array of identical positive lenslets. And each lenslet acts as a subaperture and produces spot image. Distortion of an input wavefront changes the location of spot image. And the slope of a wavefront is obtained by measuring this relative deviation of spot image. Structures and measuring algorithms of each sensor will be presented. Also, the results of wavefront measurement will be given. Using these wavefront sensing technology, an adaptive optical system will be built in the future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.12
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• pp.2714-2726
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• 1997

In this paper, adaptive symbol changes-based medical image compression method is presented. First, the differenctial image domain is obtained using the differentiation rules or obaptive predictors applied to original mdeical image. Also, the algorithm determines the context associated with the differential image from the domain. Then prediction symbols which are thought tobe the most probable differential image values are maintained at a high value through the adaptive symbol changes procedure based on estimates of the symbols with polarity coincidence between the differential image values to be coded under to context and differential image values in the model template. At the coding step, the differential image values are encoded as "predicted" or "non-predicted" by the binary adaptive arithmetic encoder, where a binary decision tree is employed. The simlation results indicate that the prediction hit ratios of differential image values using the proposed algorithm improve the coding gain by 25% and 23% than arithmetic coder with ISO JPEG lossless predictor and arithmetic coder with differentiation rules or adaptive predictors, respectively. It can be used in compression part of medical PACS because the proposed method allows the encoder be directly applied to the full bit-planes medical image without a decomposition of the full bit-plane into a series of binary bit-planes as well as lower complexity of encoder through using an additions when sub-dividing recursively unit intervals.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.272-276
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• 2000

Reverse engineering refers to the process that creates a physical part from acquiring the surface data of an existing part using a scanning device. In recent years, as the non-contact type scanning devices become more popular, the huge amount of point data can be obtained with high speed. The point data handling process, therefore, becomes more important since the scan data need to be refined for the efficiency of subsequent tasks such as mesh generation and surface fitting. As one of point handling functions, the cross-sectioning function is still frequently used for extracting the necessary data from the point cloud. The commercial reverse engineering software supports cross-sectioning functions, however, these are only for cross-sectioning the point cloud with the constant spacing and direction. In this paper, adaptive cross-sectioning point cloud which allow the changes of the spacing and directions of cross-sections according to the constant spacing and direction. In this paper, adaptive cross-sectioning algorithms which allow the changes of the spacing and directions of cross-sections according to the curvature difference of the point cloud data are proposed.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.65-75
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• 2019

Non-Functional Requirements (NFR) play a crucial role during the software development process. Currently, NFRs are considered more important than Functional Requirements and can determine the success of a software system. NFRs can be very complicated to understand due to their subjective manner and especially their conflicting nature. Self-adaptive systems (SAS) are operating in dynamically changing environment. Furthermore, the configuration of the SAS systems is dynamically changing according to the current systems context. This means that the configuration that manages the trade-off between NFRs in this context may not be suitable in another. This is because the NFRs satisfaction is based on a per-context basis. Therefore, one context configuration to satisfy one NFR may produce a conflict with another NFR. Furthermore, current approaches managing Non-Functional Requirements trade-off stops managing them during the system runtime which of concern. To solve this, we propose fragmentizing the NFRs and their alternative solutions in form of Multi-entity Bayesian network fragments. Consequently, when changes occur, our system creates a situation specific Bayesian network to measure the impact of the system's conditions and environmental changes on the NFRs satisfaction. Moreover, it dynamically decides which alternative solution is suitable for the current situation.

• Structural Monitoring and Maintenance
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• v.11 no.3
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• pp.219-234
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• 2024

The strength reduction factor spectrum is traditionally obtained from a single-degree-of-freedom (SDOF) system with a constant damping coefficient. However, according to the principle of Rayleigh damping, the damping coefficient matrix of a system changes with the stiffness matrix, and the damping coefficient of an equivalent SDOF system changes with the tangent stiffness coefficient. In view of that, this study proposes an equivalent SDOF system with an adaptive damping coefficient and derives a standardized reaction balance equation. By iteratively adjusting the strength reduction factor, the corresponding spectrum with an equivalent ductility factor is obtained. In addition, the ratio between the strength reduction factor that considers adaptive damping and the traditional strength reduction factor, denoted by η, is determined, and the η-μ-T relationship is obtained. Seismic records of Classes C, D, and E sites are selected as excitations. Moreover, a nonlinear response time-history analysis is performed to establish the relationship between the η and T values for the equivalent ductility factor μ. Further, by exploring the effects of the site class, ductility factor, second-order stiffness coefficient, and period T on the mean value of η, a simplified calculation equation of mean η is derived, and η is used as a modified value for the traditional strength reduction factor R spectrum.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.360-363
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• 1993

Fuzzy Logic Control immitating human decision making process is a novel control strategy based on expert's experience and knowledge and many process designers are developing its applications. But it is difficult to obtain a set of rules from human operator. And there is a limitation on adjusting to environmental changes. In this paper, we proposed adaptive fuzzy algorithm to overcome these difficulties using weights added to the rules. To verify the validity of this control strategy, we have implemented this algorithm for a DC servo motor with PD-type fuzzy controller.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.579-582
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• 1999

In this paper, we propose a human face detection algorithm using adaptive skin color model and neural networks. To attain robustness in the changes of illumination and variability of human skin color, we perform a color segmentation of input image by thresholding adaptively in modified hue-saturation color space (TSV). In order to distinguish faces from other segmented objects, we calculate invariant moments for each face candidate and use the multilayer perceptron neural network of backpropagation algorithm. The simulation results show superior performance for a variety of poses and relatively complex backgrounds, when compared to other existing algorithm.