• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2149-2170
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• 2017

Application-layer Distributed Denial-of-Service (DDoS) attack is one of the leading security problems in the Internet. In recent years, the attack strategies of application-layer DDoS have rapidly developed. This paper introduces a new attack strategy named Path Vulnerabilities-Based (PVB) attack. In this attack strategy, an attacker first analyzes the contents of web pages and subsequently measures the actual response time of each webpage to build a web-resource-weighted-directed graph. The attacker uses a Top M Longest Path algorithm to find M DDoS vulnerable paths that consume considerable resources when sequentially accessing the pages following any of those paths. A detection mechanism for such attack is also proposed and discussed. A finite-state machine is used to model the dynamical processes for the state of the user's session and monitor the PVB attacks. Numerical results based on real-traffic simulations reveal the efficiency of the attack strategy and the detection mechanism.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.45.2-45.2
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• 2014

To measure the mass distribution of galaxy systems weak-lensing analysis has been widely used because it directly measures the total mass of a system regardless of its baryon content and dynamical state. However, the weak-lensing only provides a map of projected surface mass density. On the other hand, galaxy redshift surveys provide a map of the three-dimensional galaxy distribution. It thus can resolve the structures along the line of sight projected in the weak-lensing map. Therefore, the comparison of structures identified in the weak-lensing maps and in the redshift surveys is an important test of the issues limiting applications of weak-lensing to the identification of galaxy clusters. Geller et al. (2010) and Kurtz et al. (2012) compared massive clusters identified in a dense redshift survey with significant weak-lensing map convergence peaks. Both assessments of the efficiency of weak-lensing map for cluster identification did not draw a general conclusion, because the sample is so small. Thus, we additionally perform deep imaging observations of fields in a dense galaxy redshift survey that contain galaxy clusters at z~0.2-0.5, using CFHT Megacam.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1130-1137
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• 1996

Every neural network has some kind of feedback. For the sake of analyzing fundamental aspects of information processing in neural nets, a net without feedbacks is an important theoretical model. But here we focus on a recurrent neural net which delay synapses as a realistic dynamical model of nervous systems. Synaptic connections are determined by a version of the Hebb rule (correlation type rule). We use a statistical neurodynamic method to explain the retrieval dynamics of the network. The result of the analysis for the sequential associativ e memory with delay synapses is compared with computer simulation. We have succeeded in explaining the dynamics of this network by theoretical analyses.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.37
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• pp.233-240
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• 1996

Julia set, Fatou set와 Mandelbrot set 가 컴퓨터에 의하여 도형화된 후부터 혼돈 역학체계 (chaotic dynamical system)에 대한 연구가 모든 학계에 비상한 관심을 모으고 있으며 특히 수학자들에 의하여 많은 연구가 이루어지고 있다. 또한 혼돈 역학체계를 기초로 하여 컴퓨터 그래픽스를 이용한 후랙탈(fractal)들의 매혹적인 시각적 표현으로 인하여 최근들어 과학자들 뿐 아니라 일반대중의 후랙탈에 대한 관심이 매우 높아지고 있다. 후랙탈이란 말은 라틴어 fractus(부서진 상태를 뜻함)에서 유래되었으며 1975년 Mandelbrot가 수학 및 자연계의 비정규적 패턴들에 대한 체계적 고찰을 담은 자신의 에세이의 표제를 주기 위해서 만들었다(〔6〕). 후랙탈을 기술하는데 있어서 가장 중요한 양은 차원(dimension)으로, 예컨데 Cantor 1/3 집합은 길이 1인 선분으로부터 시작하야 매 단계마다 모든 선분들의 가운데 1/3을 잘라내는 것을 무한히 반복함으로써 얻어지는데 이 집합의 Lebesgue measure는 0이지만 후랙탈 차원은 log2/log3 로 정수차원이 아닌 실수차원을 갖으며 또한 Cantor 1/3집합은 연속이 아니면서 점도 선도 아닌 집합인 것이다. 이 논문에서는 Box counting dimension 과 Hausdorff dimension에 대한 몇 가지 정의를 하고 정리 2.6, 정리2.7 및 정리 3.3을 증명함으로써 어떤 성질을 갖는 후랙탈의 가장 중요한 양인 후랙탈 차원에 대하여 논의 하고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3041-3063
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• 2018

Community search aims at finding a meaningful community that contains the query node and also maximizes (minimizes) a goodness metric. This problem has recently drawn intense research interest. However, most metric-based algorithms tend to include irrelevant subgraphs in the identified community. Apart from the user-defined metric algorithm, how can we search the natural community that the query node belongs to? In this paper, we propose a novel community search algorithm based on the concept of the k-hop and local distance dynamics model, which can naturally capture a community that contains the query node. The basic idea is to envision the nodes that k-hop away from the query node as an adaptive local dynamical system, where each node only interacts with its local topological structure. Relying on a proposed local distance dynamics model, the distances among nodes change over time, where the nodes sharing the same community with the query node tend to gradually move together, while other nodes stay far away from each other. Such interplay eventually leads to a steady distribution of distances, and a meaningful community is naturally found. Extensive experiments show that our community search algorithm has good performance relative to several state-of-the-art algorithms.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.1
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• pp.35-47
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• 2004

In this paper presents a new approach to the design and real-time implementation of fuzzy control system based-on digital signal processors(DSP:IMS320C80) in order to improve the precision and robustness for system of industrial robot(Dual-Arm with 8 joint Robot). The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The IMS320C80 is used in implementing real time fuzzy control to provide an enhanced motion control for robot manipulators. In this paper, a Self-Organizing Fuzzy Controller(SOFC) for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a FLC(Fuzzy Logic Controller), one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult SOFC is proposed for a hierarchical control structure consisting of basic and high levels that modify control rules. The proposed SOFC scheme is simple in structure, Int in computation, and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for a Dual-Arm robot with eight joints.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.759-763
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4585-4603
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• 2015

Video streaming services make up a large proportion of Internet traffic on both fixed and mobile access throughout the world. Adaptive streaming allows for dynamical adaptation of the bitrate with varying network conditions, to guarantee the best user experience. Adaptive bitrate algorithms face a significant challenge in correctly estimating the throughput as it varies widely over time. In this paper, we first evaluate the throughput estimation techniques and show that the method that we have used offers stable response to throughput fluctuations while maintaining a stable playback buffer. Then, we propose an adaptive bitrate scheme that intelligently selects the video bitrates based on the estimated throughput and buffer occupancy. We show that the proposed scheme improves viewing experience by achieving a high video rate without taking unnecessary risks and by minimizing the frequency of changes in the video quality. Furthermore, we show that it offers a stable response to short-term fluctuations and responds swiftly to large fluctuations. We evaluate our algorithm for both constant bitrate (CBR) and variable bitrate (VBR) video content by taking into account the segment sizes and show that it significantly improves the quality of video streaming.

• International Journal of Automotive Technology
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• v.5 no.1
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• pp.61-67
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• 2004

This paper suggests two simple two-degree-of-freedom models to describe the dynamical interaction between the pad and the disc of a disc brake system. Separate models for in-plane and out -of-plane vibration are described. Although a brake pad and disc have many modes of vibration, the interaction between a single mode of each component is considered as this is thought to be crucial for brake noise. For both models, the pad and the disc are connected by a sliding friction interface having a velocity dependent friction coefficient. In this paper, it is shown that this friction model acts as negative damping in the system that describes the in-plane vibration, and as negative stiffness in system that describes the out-of-plane vibration. Stability analysis is performed to investigate the conditions under which the systems become unstable. The results of the stability analysis show that the damping is the most important parameter for in-plane vibration, whereas the stiffness is the most important parameter for the out-of-plane vibration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4510-4526
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• 2017

Most available methods of facial gender recognition work well under a constrained situation, but the performances of these methods have decreased significantly when they are implemented under unconstrained environments. In this paper, a method via low-rank and collaborative representation is proposed for facial gender recognition in the wild. Firstly, the low-rank decomposition is applied to the face image to minimize the negative effect caused by various corruptions and dynamical illuminations in an unconstrained environment. And, we employ the collaborative representation to be as the classifier, which using the much weaker $l_2-norm$ sparsity constraint to achieve similar classification results but with significantly lower complexity. The proposed method combines the low-rank and collaborative representation to an organic whole to solve the task of facial gender recognition under unconstrained environments. Extensive experiments on three benchmarks including AR, CAS-PERL and YouTube are conducted to show the effectiveness of the proposed method. Compared with several state-of-the-art algorithms, our method has overwhelming superiority in the aspects of accuracy and robustness.