• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3458-3481
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• 2021

Existing methods for blind identification of linear block codes without a candidate set are mainly built on the Gauss elimination process. However, the fault tolerance will fall short when the intercepted bit error rate (BER) is too high. To address this issue, we apply the reverse algebra approach and propose a novel "two-step-screening" algorithm by solving the linear error equations on the binary Galois field, or GF(2). In the first step, a recursive matrix partition is implemented to solve the system linear error equations where the coefficient matrix is constructed by the full codewords which come from the intercepted noisy bitstream. This process is repeated to derive all those possible parity-checks. In the second step, a check matrix constructed by the intercepted codewords is applied to find the correct parity-checks out of all possible parity-checks solutions. This novel "two-step-screening" algorithm can be used in different codes like Hamming codes, BCH codes, LDPC codes, and quasi-cyclic LDPC codes. The simulation results have shown that it can highly improve the fault tolerance ability compared to the existing Gauss elimination process-based algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.367-371
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• 1989

A linear form of reduced-order distillation model is proposed, which contains the physical properties of distillation process and can be used in real time applications. The proposed model is linear in terms of liquid mole fraction and contains some tuning parameters. To verify the applicability of the proposed model, the model identification using nonlinear filtering techniques was applied. As a result, it was found that this model represented the simulated distillation process very closely as the parameters were converged.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.899-902
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• 1993

A neural model predictive control strategy combining a neural network for plant identification and a nonlinear programming algorithm for solving nonlinear control problems is proposed. A constrained nonlinear optimization approach using successive quadratic programming combined with neural identification network is used to generate the optimum control law for complex continuous chemical reactor systems that have inherent nonlinear dynamics. The neural model predictive controller (MNPC) shows good performances and robustness. To whom all correspondence should be addressed.

• 대한음성학회지:말소리
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• 제54호
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• pp.73-83
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• 2005

The goal of our research is to build a text-independent speaker identification system that can be used in any condition without any additional adaptation process. The performance of speaker recognition systems can be severely degraded in some unknown mismatched microphone and noise conditions. In this paper, we show that PCA(principal component analysis) can improve the performance in the situation. We also propose an augmented PCA process, which augments class discriminative information to the original feature vectors before PCA transformation and selects the best direction for each pair of highly confusable speakers. The proposed method reduced the relative recognition error by 21%.

• 대한한의진단학회지
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• 제19권2호
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• pp.109-113
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• 2015

Byunzheng(辨證), 'Identification of Patterns' implies the process of identifying the original cause from symptoms and signs. Each symptom and sign has a meaning that manifests. But in Clinic, it is difficult to recognize the main cause through symptoms and signs by itself, because the patients complaint their symptoms differently. When considering Byunzheng, not only one symptom of one cause but relationship of manifested symptoms and causes are necessary. The object of Byunzheng is to diagnose Illness and disease through symptoms and signs and to coordinate Therapeutic Methods by Byunzheng. In Byunzheng, there are patterns according to the function of Internal Organs(臟腑), the Channels, the Eight Principles, the Five Elements and etc. Process to Diagnose Byunzheng is the most important. Until present, it is not clear to conclude the Byunzheng process or criteria. In certain case of Byunzheng is recognized by doctor's intuition, but most case is needed for conscious reasoning. Therefore, in this statement, process of conclude Byunzheng is reviewed rather than describing each character of Byunzheng.

• 한국정밀공학회지
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• 제16권11호
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• pp.122-132
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• 1999

This study describes a dynamic model of the hydroforming process which is used for precision forming of sheet metals. To help the controller design for the control of the forming pressure needed for this process as well as to investigate the effect of system parameters on the dynamic behavior, dynamic modeling is performed with emphasis on hydraulic servo system which actuates the forming machine. Since the model contains several unknown parameters, these were estimated via a least square parameter identification method. Based upon the identified model, a series of simulations were performed for various operating conditions. The results were compared with those of the experiments to verify the validity of the proposed model. The comparison study shows that the proposed dynamic model can describe dynamic behavior of the forming pressure of the hydroforming process to desirable accuracy.

• Smart Structures and Systems
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• 제11권1호
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• pp.123-134
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• 2013

Identifying structural modal parameters, especially those modes within high frequency range, from ambient data is still a challenging problem due to various kinds of uncertainty involved in vibration measurements. A procedure applying an ensemble empirical mode decomposition (EEMD) method is proposed for accurate and robust structural modal identification. In the proposed method, the EEMD process is first implemented to decompose the original ambient data to a set of intrinsic mode functions (IMFs), which are zero-mean time series with energy in narrow frequency bands. Subsequently, a Sub-PolyMAX method is performed in narrow frequency bands by using IMFs as primary data for structural modal identification. The merit of the proposed method is that it performs structural identification in narrow frequency bands (take IMFs as primary data), unlike the traditional method in the whole frequency space (take original measurements as primary data), thus it produces more accurate identification results. A numerical example and a multiple-span continuous steel bridge have been investigated to verify the effectiveness of the proposed method.

• Journal of applied mathematics & informatics
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• 제4권1호
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• pp.135-135
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• 1997

Times series modeling plays an important role in the field of engineering, Statistics, Biomedicine etc. Model identification is one of crucial steps in the modeling of an AutoRegreesive Moving Average(ARMA(p, q)) process for real world problems. Many techniques have been developed in the literature (Salas et al., McLeod et al. etc.) for the identification of an ARMA(p, q) Model. In this paper, a new technique called The Generalised Parameters Technique is formulated for seasonal and non-seasonal ARMA model identification. This technique is very simple and can e applied to any given time series. Initial estimates of the AR parameters of the ARMA model are also obtained by this method. This model identification technique is validated through many theoretical and simulated examples.

• Structural Engineering and Mechanics
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• 제70권2호
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• pp.209-219
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• 2019

By normalizing the internal hysteresis variable and eliminating the redundant parameter, the normalized Bouc-Wen model is considered to be an improved and more reasonable form of the Bouc-Wen model. In order to facilitate application and further research of the normalized Bouc-Wen model, some key aspects of the model need to be uncovered. In this paper, hysteresis characterization of the normalized Bouc-Wen model is first studied with respect to the model parameters, which reveals the influence of each model parameter to the shape of the hysteresis loops. The parameter identification scheme is then proposed based on an improved genetic algorithm (IGA), and verified by experimental test data. It is proved that the proposed method can be an efficacious tool for identification of the model parameters by matching the reconstructed hysteresis loops with the target hysteresis loops. Meanwhile, the IGA is shown to outperform the standard GA. Finally, a simplified identification method is proposed based on parameter sensitivity, which indicates that the efficiency of the identification process can be greatly enhanced while maintaining comparable accuracy if the low-sensitivity parameters are reasonably restricted to narrower ranges.

• Asia Marketing Journal
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• 제9권3호
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• pp.117-149
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• 2007

기업의 충성도 높은 고객 유치 및 기업 몰입을 위한 하나의 방안으로 대두되고 있는 온라인 개인 커뮤니티의 경우 개인이 미니홈피를 창조하여, 자신을 표현하고 관리하여 커뮤니티를 구축하고, 커뮤니티와 상호작용하면서 자신을 표현하기 때문에 온라인 개인 커뮤니티와 자아간의 연결인 동일시에 대한 연구가 중요함에도 불구하고 아직까지 이에 대한 연구가 이루어지지 않고 있다. 따라서 본 연구에서는 온라인 개인 커뮤니티 몰입에 대한 동일시의 역할과 동일시에 영향을 미치는 자아표현의 효과를 살펴보는데 연구 목적이 있다. 개인 미니홈피를 싸이월드에서 이용하는 소비자들을 대상으로 검증한 결과 첫째, 개인적 실제자아 표현과 개인적 이상자아 표현은 개인적 동일시에 영향을 미치고, 사회적 실제자아 표현과 사회적 이상자아 표현은 사회적 동일시에 영향을 미치는 것을 알 수 있었다. 둘째, 개인적 동일시와 사회적 동일시는 모두 온라인 개인 커뮤니티 몰입에 긍정적인 영향을 미치는 것을 알 수 있으며, 온라인 개인 커뮤니티 몰입 수준이 높을수록 원천 기업에 대한 반응은 좋게 나타나는 것을 알 수 있었다. 따라서 소비자들의 개인적 동일시와 사회적 동일시를 높여주기 위해서 온라인 개인 커뮤니티내의 상호작용 활동 및 정보제공의 용이성과 개인의 표현력을 높여줄 아이템의 개발이 있어야만 할 것이다.