• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2167-2175
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• 2017

In recent years, an IoT is dramatically developing according to the enhancement of AI, the increase of connected devices, and the high-performance cloud systems. Huge data produced by many devices and sensors is expanding the scope of services, such as an intelligent diagnostics, a recommendation service, as well as a smart monitoring service. The studies of edge computing are limited as a role of small server system with high quality HW resources. However, there are specialized requirements in a smart factory domain needed edge computing. The edges are needed to pre-process containing tiny filtering, pre-formatting, as well as merging of group contexts and manage the regional rules. So, in this paper, we extract the features and requirements in a scope of efficiency and robustness. Our edge offers to decrease a network resource consumption and update rules and learning models. Moreover, we propose architecture of edge computing based on learning factors sharing with a cloud system in a smart factory.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.7
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• pp.378-388
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• 2000

In this paper, we propose Fuzzy Polynomial Neural Networks(FPNN) based on Polynomial Neural Networks(PNN) and Fuzzy Neural Networks(FNN) for model identification of complex and nonlinear systems. The proposed FPNN is generated from the mutually combined structure of both FNN and PNN. The one and the other are considered as the premise part and consequence part of FPNN structure respectively. As the consequence part of FPNN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. FPNN is available effectively for multi-input variables and high-order polynomial according to the combination of FNN with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. As the premise part of FPNN, FNN uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. And we use two kinds of FNN structure according to the division method of fuzzy space of input variables. One is basic FNN structure and uses fuzzy input space divided by each separated input variable, the other is modified FNN structure and uses fuzzy input space divided by mutually combined input variables. In order to evaluate the performance of proposed models, we use the nonlinear function and traffic route choice process. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously. And also performance index related to the approximation and prediction capabilities of model is evaluated and discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12B
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• pp.758-766
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• 2007

IStreaming services with a client-server architecture have scalability problem because a server cannot accomodate clients more than its processing capability. This paper introduces a case study for implementing H.264 streaming system based on P2P architecture in order to provide scalable and stable broadcast streaming services over the internet. The prototype system called OmniCast264 consists of the H.264 encoding server, the streaming server, the proxy server, and peer nodes. The proxy server dynamically manages placement of the peer nodes on the P2P network. Omnicast264 has the concepts of distributed streaming loads, real-time playback, error-robustness and modularity. Thus, it can provide large-scale broadcast streaming services. Finally, we have built P2P streaming systems with 12 PCs connected serially or in parallel. The experiment shows that OmniCast264 can provide real-time playback.

• The Journal of the Korea Contents Association
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• v.11 no.9
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• pp.17-25
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• 2011

The wireless mesh networks are recently getting much attention for commercial applications. In such networks, the service should be uninterrupted when roaming from one domain to another while the authentication for a secure access should be maintained. The challenge is to consider the authentic coordination between the home domain and foreign domains and the maintenance of local authenticity between foreign domains. In this paper, a novel authentication method is presented so that a mobile mesh node can be effectively authenticated and obtain an secure connection in foreign domains. In the proposed method, the authentication process does not rely on an end-to-end connection between the foreign domain and the home domain. Even without a connectivity to the home domain, the foreign domain can provide an effective authentication of a mesh node by consulting one of the neighboring foreign domains that has been visited by the mobile mesh node. In order to verify the performance of our proposed method, a qualitative analysis has been performed and compared to those of conventional methods. The results show that our method is superior to the conventional ones in terms of authentication response time and authentication service robustness.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.6
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• pp.10-21
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• 2000

The Cellular Noninear Networks structure for Distance Transform(DT) and the robust optical flow detection algorithm based on the DT are proposed. For some applications of optical flows such as target tracking and camera ego-motion computation, correct optical flows at a few feature points are more useful than unreliable one at every pixel point. The proposed algorithm is for detecting the optical flows on the trajectories only of the feature points. The translation lengths and the directions of feature movements are detected on the trajectories of feature points on which Distance Transform Field is developed. The robustness caused from the use of the Distance Transform and the easiness of hardware implementation with local analog circuits are the properties of the proposed structure. To verify the performance of the proposed structure and the algorithm, simulation has been done about various images under different noisy environment.

• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.861-869
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• 2003

The rapid growth of multimedia network systems has caused overflowing illegal copies of digital contents. Among digital contents, watermarking technique can be used to protect ownership about the image. Copyright protection involves the authentication of image ownership and the identification of illegal copies of image. In this paper, a new digital watermarking technique using HVS and adaptive scale factor based on the wavelet transform is proposed to use the binary image watermark. The original image is decomposed by 3-level wavelet transform. It is embedded to baseband and high frequency band. The embedding in the baseband is considered robustness, the embedding in the high frequency band is concerned about HVS and invisibility. The watermarking of a visually recognizable binary image used the HVS and random permutation to protect the copyright. From the experimental results, we confirm that the proposed technique is strong to various attacks such as joint photographic experts ground(JPEG) compression, cropping, collusion, and inversion of lines.

• Journal of Korea Multimedia Society
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• v.8 no.9
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• pp.1227-1238
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• 2005

Recently, with the advance of network and internet technologies, it is appeared the Problem that the digital contents such as image, voice and video are illegally pirated and distributed. To protect the copyright of the digital contents, the digital watermarking technology of inserting the provider's information into the contents has been widely used. In this paper, we propose the method of applying the digital watermarking into biometric information such as fingerprint and iris in order to prevent the problem caused by steal and misuse. For that, we propose the method of inserting watermark in frequency domain, compare the recognition performance before and aster watermark inserting. Also, we experiment the robustness of proposed method against blurring attack, which is conventionally taken on biometrics data. Experimental results show that our proposed method can be used for protecting iris and fingerprint data, efficiently.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.479-486
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• 2013

There exist two major difficulties in developing flight control system: nonlinear dynamic characteristics and time-varying properties of parameters of aircraft. Instead of the difficulties, many high reliable and efficient control methodologies have been developed. But, most of the developed control systems are based on the exact mathematical modelling of aircraft and, in the absence of such a model, it is very difficult to derive performance, robustness and nominal stability. From these aspects, recently, some approaches to utilizing the intelligent control theories such as fuzzy logic control, neural network and genetic algorithm have appeared. In this paper, one advanced intelligent lateral control system of a high speed fight has been developed utilizing type-2 fuzzy logic, which can deduce the uncertainty problem of the conventional fuzzy logic. The results will be verified through computer simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.10
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• pp.1323-1328
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• 2011

In the current design process for the lower arm used in automobile parts, an optimal solution of its various design variables should be found through exploration of the design space approximated using the response surface model formulated with a first- or second-order polynomial equation. In this study, a multi-level computational DOE (design of experiment) was carried out to explore the design space showing nonlinear behavior, in terms of factors such as the total weight and applied stress of the lower arm, where a fractional-factorial orthogonal array based on the artificial neural network model was introduced. In addition, the tolerance robustness of the optimal solution was estimated using a tolerance optimization with six sigma constraints, taking into account the tolerances occurring in the design variables.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2938-2956
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• 2020

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.