• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.363-368
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• 1993

Hilbert Transform has been used for detection of nonlinearity in modal analysis. HTD(Hilbert Transform Describers) are used to quantify and identify nonlinearity. Mottershead and Stanway method for identification of N-th power velocity nonlinear damping are extended to P-th power displacement stiffness, N-th power velocity damping and dry friction. Time domain and frequency domain data are used and HTD and Mottershead methods are combined for identification of nonlinear parameters in this paper. Computer simulations and experimental results are shown to verify nonlinear structure identification methods.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.77.2-77
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• 2002

Human upright standing posture in the sagittal plane is studied, when it exposed in the antero-posterior vibration. A two link inverted pendulum model is considered and described its functional behavior in terms of ankle and hip joint according to the dominant joints that provides the largest contribution to the corresponding human reactionary motion. The data is analyzed, both in the time domain and the frequency domain. Subjects behave as a non-rigid pendulum with a mass and a spring throughout the whole period of the platform motion. When vision was allowed, each segment of body shows more stabilized.

• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.335-348
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• 2009

Fuzzy regression is used as a complement or an alternative to represent the relation between variables among the forecasting models especially when the data is insufficient to evaluate the relation. Such phenomenon often occurs in seasonal time series data which require large amount of data to describe the underlying pattern. Semiparametric model is useful tool in the case where domain knowledge exists about the function to be estimated or emphasis is put onto understandability of the model. In this paper we propose fuzzy semiparametric support vector regression so that it can provide good performance on forecasting of the seasonal time series by incorporating into fuzzy support vector regression the basis functions which indicate the seasonal variation of time series. In order to indicate the performance of this method, we present two examples of predicting the seasonal time series. Experimental results show that the proposed method is very attractive for the seasonal time series in fuzzy environments.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.841-848
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• 2008

This paper examined dynamic characteristics of high speed trains using a time varying frequency transform. Fourier transform based methods are frequently used for the calculation of the dynamic characteristics of trains in the frequency domain, but they cannot represent the time-varying characteristics. Therefore it is necessary to examine their characteristics using a time-varying frequency transform. For the examination, the non-stationary vibration of wheelset, bogie, and carbody are measured using accelerometers and stored in a data aquisition system. They are processed with localization of the data by modulating with a window function, and Fourier transform is taken to each localized data, called the short-time Fourier transform. From the processed results, time varying auto-spectral density, cross-spectral density, frequency response, and coherence functions have been calculated. From the analysis, it is confirmed that the time varying frequency transform is a useful method for analyzing the dynamic characteristics of high speed trains.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.1
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• pp.5-21
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• 2008

In order to securely transmit multicast data packets in a mobile environment where frequent join/leave events are a characteristic of the environment, there is a need for a new secure and efficient group key management solution. We propose a secure group key generation/distribution solution providing scalability and reliability. Using this solution, when a mobile node, which is in a multicast session, enters a new domain, the agent of the domain joins the multicast session and coordinates its data packets with the mobile node. The agent encrypts and transmits subsequent data packets to the mobile node, using a local one-time pad key. This key is generated with FI sequences, enabling the mobile node to regenerate the same data packet, based on the information sent by the agent. Our performance analysis demonstrates that the proposed solution can significantly reduce the number of key generations and distributions, when it is applied to the hierarchical mobile IPv6 network.

• Wind and Structures
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• v.18 no.4
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• pp.347-373
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• 2014

Since its development in the early 1980's the force balance technique has become a standard method in the efficient determination of structural loads and responses. Its usefulness lies in the simplicity of the physical model, the relatively short records required from the wind tunnel testing and its versatility in the use of the data for different sets of dynamic properties. Its major advantage has been the ability to provide results in a timely manner, assisting the structural engineer to fine-tune their building at an early stage of the structural development. The analysis of the wind tunnel data has evolved from the simple un-coupled system to sophisticated methods that include the correction for non-linear mode shapes, the handling of complex geometry and the handling of simultaneous measurements on multiple force balances for a building group. This paper will review some of the components in the force balance data analysis both in historical perspective and in its current advancement. The basic formulation of the force balance methodology in both frequency and time domains will be presented. This includes all coupling effects and allows the determination of the resultant quantities such as resultant accelerations, as well as various load effects that generally were not considered in earlier force balance analyses. Using a building model test carried out in the wind tunnel as an example case study, the effects of various simplifications and omissions are discussed.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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• pp.1073-1075
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• 2013

Background: In normal cells, activated epidermal growth factor receptor (EGFR) molecules are subjected to ubiquitination-mediated proteasome degradation pathway by c-Cbl, an ubiquitin ligase that checks uncontrolled proliferation. Hence expression of wild type c-Cbl molecule is essential to keep this degradation machinery in a functional state. Loss of expression or function of c-Cbl may consequently lead to sustained activation of EGFR and promote carcinogenesis, loss of function mutations in the c-Cbl gene already being reported in lung and hematopoietic cancers. However, the genetic status of c-Cbl in oral squamous cell carcinoma (OSCC) is not known. Hence in the present study we investigated the genomic DNA isolated from OSCC tissue biopsy samples for mutations in the RING finger domain coding region of c-Cbl gene, which has also been reported to be most frequently mutated in other cancers. Materials and Methods: Total genomic DNA isolated from thirty two post surgical OSCC tissue samples were amplified using primers flanking the exon 8 of c-Cbl gene that codes for the RING finger domain. The PCR amplicons were then resolved in a 1.2% agarose gel, purified and subjected to direct sequencing to screen for mutations. Results: The sequencing data of the thirty two OSCC samples did not identify mutations in the RING finger domain coding region of c-Cbl gene. Conclusions: To the best of our knowledge, this is the first time that the genetic status of c-Cbl gene in OSCC samples has been investigated. The present data indicates that genetic alteration of RING finger domain coding region of c-Cbl gene is relatively infrequent in OSCC samples.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.916-937
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• 2023

Most of the existing Distributed Denial-of-Service mitigation schemes in Software-Defined Networking are only implemented in the network domain managed by a single controller. In fact, the zombies for attackers to launch large-scale DDoS attacks are actually not in the same network domain. Therefore, abnormal traffic of DDoS attack will affect multiple paths and network domains. A single defense method is difficult to deal with large-scale DDoS attacks. The cooperative defense of multiple domains becomes an important means to effectively solve cross-domain DDoS attacks. We propose an efficient multi-domain DDoS cooperative defense mechanism by integrating blockchain and SDN architecture. It includes attack traceability, inter-domain information sharing and attack mitigation. In order to reduce the length of the marking path and shorten the traceability time, we propose an AS-level packet traceability method called ASPM. We propose an information sharing method across multiple domains based on blockchain and smart contract. It effectively solves the impact of DDoS illegal traffic on multiple domains. According to the traceability results, we designed a DDoS attack mitigation method by replacing the ACL list with the IP address black/gray list. The experimental results show that our ASPM traceability method requires less data packets, high traceability precision and low overhead. And blockchain-based inter-domain sharing scheme has low cost, high scalability and high security. Attack mitigation measures can prevent illegal data flow in a timely and efficient manner.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.89-96
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• 2015

In this paper, time-frequency analysis algorithms, empirical mode decomposition and local mean decomposition, are reviewed and their applications to nonlinear and nonstationary real-world data are discussed. In addition, their generic extensions to complex domain are addressed for the analysis of multichannel data. Simulations of these algorithms on synthetic data illustrate the fundamental structure of the algorithms and how they are designed for the analysis of nonlinear and nonstationary data. Applications of the complex version of the algorithms to the synthetic data also demonstrate the benefit of the algorithms for the accurate frequency decomposition of multichannel data.

• The Journal of the Acoustical Society of Korea
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• v.22 no.5
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• pp.375-382
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• 2003

Lip-reading technique based on bimodal is to enhance speech recognition rate in noisy environment. It is most important to detect the correct lip-image. But it is hard to estimate stable performance in dynamic environment, because of many factors to deteriorate Lip-reading's performance. There are illumination change, speaker's pronunciation habit, versatility of lips shape and rotation or size change of lips etc. In this paper, we propose the IIR filtering in time-domain for the stable performance. It is very proper to remove the noise of speech, to enhance performance of recognition by digital filtering in time domain. While the lip-reading technique in whole lip image makes data massive, the Principal Component Analysis of pre-process allows to reduce the data quantify by detection of feature without loss of image information. For the observation performance of speech recognition using only image information, we made an experiment on recognition after choosing 22 words in available car service. We used Hidden Markov Model by speech recognition algorithm to compare this words' recognition performance. As a result, while the recognition rate of lip-reading using PCA is 64%, Time-domain filter applied to lip-reading enhances recognition rate of 72.4%.