• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.381-388
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• 2014

In this paper, we deal with implementation issues of an unknown word classifier for middle-school level English writing test. We define the type of unknown words occurred in English text and discuss the detection process for unknown words. Also, we define the type of swear words occurred in students's English writings, and suggest how to handle this type of words. We implement an unknown word classifier with a swear detection module for developing an automatic English writing scoring system. By experiments with actual test data, we evaluate the accuracy of the unknown word classifier as well as the swear detection module.

• Smart Structures and Systems
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• v.15 no.1
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• pp.169-189
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• 2015

Convergence difficulty and available complete measurement information have been considered as two primary challenges for the identification of large-scale engineering structures. In this paper, a time domain substructural identification approach by combining a weighted adaptive iteration (WAI) algorithm and an extended Kalman filter method with a weighted global iteration (EFK-WGI) algorithm was proposed for simultaneous identification of physical parameters of concerned substructures and unknown external excitations applied on it with limited response measurements. In the proposed approach, according to the location of the unknown dynamic loadings and the partially available structural response measurements, part of structural parameters of the concerned substructure and the unknown loadings were first identified with the WAI approach. The remaining physical parameters of the concerned substructure were then determined by EFK-WGI basing on the previously identified loadings and substructural parameters. The efficiency and accuracy of the proposed approach was demonstrated via a 20-story shear building structure and 23 degrees of freedom (DOFs) planar truss model with unknown external excitation and limited observations. Results show that the proposed approach is capable of satisfactorily identifying both the substructural parameters and unknown loading within limited iterations when both the excitation and dynamic response are partially unknown.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.251-255
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• 2019

On today, Protocol reverse-engineering technique can be used to extract the specification of an unknown protocol. However, there is no standardized method, and in most cases, the extracting process is executed manually or semi-automatically. If the information about the structure of an unknown protocol could be acquired in advance, it would be easy to conduct reverse engineering. the feature extraction is an important step in unknown protocol classification. However, in this paper, we present a comparison several feature extraction techniques and suggests a method of feature extraction algorithm for recognizing unknown protocol. In order to verify the performance of the proposed system, we performed the training using eight open protocols to evaluate the performance using unknown data.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.560-563
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• 1997

The conventional impedance control has been known to have the following problems: it has lack of specifying force directly and unknown environment stiffness has to be known priori in order to specify the reference trajectory. In this paper, new impedance force control that can control a desired force directly under unknown stiffness is proposed. A new nonlinear impedance function is developed based on estimation of unknown stiffness from force and position measurements. The nonlinear characteristics of the proposed impedance function are analyzed based on unknown environment position. Simulation studies with robot manipulator are carried out to test analytical results.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.3
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• pp.205-211
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• 2002

Unknown inputs observer(UIO) which is achieved by the coordinate transformation method has the differential of system outputs in the observer and the equation for unknown inputs estimation. Generally, the differential of system outputs in the observer can be eliminated by defining a new variable. But it brings about the partition of the observer into two subsystems and need of an additional differential of system outputs still remained to estimate the unknown inputs. Therefore, the block pulse function expansions and its differential operation which is a newly derived in this paper are presented to alleviate such problems from an algebraic form.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.76-78
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• 2009

This paper considers the problem of global adaptive regulation for a class of nonlinear systems which have multiple unknown virtual control coefficient. By using a new parameter estimator and backstepping technique, we design a smooth state feedback control law, parameter update laws that estimate the unknown virtual control coefficients, and a continuously differentiable Lyapunov function which is positive definite and proper.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.26.4-26
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• 2001

This paper proposes a dynamic observer that is applicable to linear time-invariant systems subject to unknown inputs. The proposed method utilizes the output feedback control structure to design an unknown input observer. We name it as the dynamic unknown input observer(UIO). The dynamic UIO can be designed easily compared to the usual static UIO, and the system response could be improved.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2086-2088
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• 2002

This paper deals with an algebraic approach for unknown inputs observer by using Haar functions. In the algebraic UIO(unknown input observer) design procedure, coordinate transformation method is adopted to derive the reduced order dynamic system which is decoupled unknown inputs and Haar function and its integral operational matrix is applied to avoid additional differentiation of system outputs.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.39-46
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• 1994

In this paper a state reconstruction filter for linear discrete-time stochastic systems with unknown inputs and noises is presented. The suggested filter can estimate the system state vector and the unknown inputs simultaneously As an extension of the filter a fault diagnosis filter for linear discrete-time stochastic systems with unknown inputs and noises is presented for each filters the optimal gain determination methods which minimize the variance of the state reconstruction errorare presented. Finally the usability of the filtersis shown via numerical examples.

• The Journal of the Korea Contents Association
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• v.17 no.4
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• pp.576-584
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• 2017

Unknown nouns which are not in a dictionary make problems not only morphological analysis but also almost all natural language processing area. This paper describes a recognition method for Korean unknown nouns using strings following nouns such as postposition, suffix and postposition, suffix and eomi, etc. We collect and sort words including nouns from documents and divide a word including unknown noun into two parts, candidate noun and string following the noun, by finding same prefix morphemes from more than two unknown words. We use information of strings following nouns extracted from Sejong corpus and decide unknown noun finally. We obtain 99.64% precision and 99.46% recall for unknown nouns occurred more than two forms in news of two portal sites.