• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.300-307
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• 2002

Damage estimation methods are classified into two groups according to the dependence on the FE model : signal-based and model-based methods. Signal-based damage estimation methods are generally appropriate for detection of damage location, whereas not effective for estimation of damage severities. Model-based damage estimation methods are difficult to apply directly to the structures with a large number of the probable damaged members. It is difficult to obtain the exact model representing the real bridge behavior due to the modeling errors. The modeling errors even may exceed the modal sensitivity on damage. In this study, Model-based damage detection method which can effectively consider the modeling errors is suggested. Two numerical example analyses on a simple beam and a multi-girder bridge are presented to demonstrate the effectiveness of the presented method.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.96-112
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• 2020

Solving the disclosure problem of sensitive information with the k-nearest neighbor query, location dummy technique, or interfering data in location-based services (LBSs) is a new research topic. Although they reduced security threats, previous studies will be ineffective in the case of sparse users or K-successive privacy, and additional calculations will deteriorate the performance of LBS application systems. Therefore, a model is proposed herein, which is based on geohash-encoding technology instead of latitude and longitude, memcached server cluster, encryption and decryption, and authentication. Simulation results based on PHP and MySQL show that the model offers approximately 10× speedup over the conventional approach. Two problems are solved using the model: sensitive information in LBS application is not disclosed, and the relationship between an individual and a track is not leaked.

• Journal of Multimedia Information System
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• v.9 no.2
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• pp.93-102
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• 2022

Dependency parsing is a decision problem of the syntactic relation between words in a sentence. Recently, deep learning models are used for dependency parsing based on the word representations in a continuous vector space. However, it causes a mislabeled tagging problem for the proper nouns that rarely appear in the training corpus because it is difficult to express out-of-vocabulary (OOV) words in a continuous vector space. To solve the OOV problem in dependency parsing, we explored the proper noun embedding method according to the embedding unit. Before representing words in a continuous vector space, we replace the proper nouns with a special token and train them for the contextual features by using the multi-layer bidirectional LSTM. Two models of the syllable-based and morpheme-based unit are proposed for proper noun embedding and the performance of the dependency parsing is more improved in the ensemble model than each syllable and morpheme embedding model. The experimental results showed that our ensemble model improved 1.69%p in UAS and 2.17%p in LAS than the same arc-eager approach-based Malt parser.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.51-60
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• 2023

This study focuses on the design of a GPT-based system for relatively rapid technology credit assessment of SMEs. This system addresses the limitations of traditional time-consuming evaluation methods and proposes a GPT-based model to comprehensively evaluate the technological capabilities of SMEs. This model fine-tunes the GPT model to perform fast technical credit assessment on SME-specific text data. Also, It presents a system that automates technical credit evaluation of SMEs using GPT and LLM-based chatbot technology. This system relatively shortens the time required for technology credit evaluation of small and medium-sized enterprises compared to existing methods. This model quickly assesses the reliability of the technology in terms of usability of the base model.

• Journal of the Korea Safety Management & Science
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• v.25 no.2
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• pp.1-8
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• 2023

This paper is proposing a novel machine scheduling model for the unrelated parallel machine scheduling problem without setup times to minimize the total completion time, also known as "makespan". This problem is a NP-complete problem, and to date, most approaches for real-life situations are based on the operator's experience or simple heuristics. The new model based on the Memetic Algorithm, which was proposed by P. Moscato in 1989, is a hybrid algorithm that includes genetic algorithm and local search optimization. The new model is tested on randomly generated datasets, and is compared to optimal solution, and four scheduling models; three rule-based heuristic algorithms, and a genetic algorithm based scheduling model from literature; the test results show that the new model performed better than scheduling models from literature.

• Korean Journal of Social Welfare
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• v.61 no.2
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• pp.161-187
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• 2009

Disability Discrimination Act(DDA) is generally recognized as the institutional frame to realize social model of disability. However social model is not automatically realized via the enactment of DDA. The realization of social model is influenced by various factors among which the definition of disability in DDA is very important factor. Paradoxically definitions of disability based on social model may push DDA into contradictory situation. This is caused by the fact that on the one hand definitions of based on social model exclude impairment and on the other hand they mixes characteristics and treatment. Because of these, when definitions of disability based on social model is reflected into definitions of disability in DDA, they may not be helpful to realize social model against original intention of advocates of the model. We can consider two approaches to resolve this paradox; one is to partially reform current definition of disability in DDA, the other is to totally amend current definition of disability. The former may pragmatic and worth to pursue but it cannot solve fundamental problems and may cause some new problems. The most consistent resolution with social model is to amend current definitions of disability into radically new one which excludes substantial limits and definition of disabled person from definition of disability. This new definition may called characteristics based definition or impairment based definition. Some people may think this new definition as one based on medical model but it is not. What we need is not to carve definition of disability based on social model into DDA but to make institutional frame for DDA to operate without contradictions and to develop social model of both impairment and disability. This model which does not exclude impairment could takes part in realization of the social model disability.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1392-1397
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• 2003

This paper deals with a control technique of eliminating the transient vibration of a twin-drive geared mechanical system. This technique is based on a model-based control in order to establish the damping effect at the driven machine part. The control model is composed of reduced-order electrical and mechanical parts. This control model estimates a load speed converted to the motor shaft. The difference between the estimated load speed and the motor speed is calculated dynamically and it is added to the velocity command to suppress the transient vibration generated at the load. This control technique is applied to a twin-drive geared system with backlash. In the previous work, the performance of this control method is examined by simulations. In this paper, the effectiveness of this control technique is verified by experiments. The settling time of the residual vibration generated at the loading inertia can be shortened down to about 1/2 of the uncompensated vibration level.

• Journal of Electrical Engineering and Technology
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• v.7 no.5
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• pp.698-704
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• 2012

This paper proposes a new methodology for evaluating the probabilistic reliability based grid expansion planning of composite power system including the Wind Turbine Generators. The proposed model includes capacity limitations and uncertainties of the generators and transmission lines. It proposes to handle the uncertainties of system elements (generators, lines, transformers and wind resources of WTG, etc.) by a Composite power system Equivalent Load Duration Curve (CMELDC)-based model considering wind turbine generators (WTG). The model is derived from a nodal equivalent load duration curve based on an effective nodal load model including WTGs. Several scenarios are used to choose the optimal solution among various scenarios featuring new candidate lines. The characteristics and effectiveness of this simulation model are illustrated by case study using Jeju power system in South Korea.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.149-158
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• 2009

It is important to derive reliable parameter values in the measurement-based load model development of electric power systems. However parameter estimation tasks, in practice, often face the parameter identifiability issue; whether or not the model parameters can be estimated with a given input-output data set in reliable manner. This paper introduces concepts and practical definitions of the local identifiability of model parameters. A posteriori local identifiability is defined in the sense of nonlinear least squares. As numerical examples, local identifiability of third-order induction motor (IM) model and a Z-induction motor (Z-IM) model is studied. It is shown that parameter ill-conditioning can significantly affect on reliable parameter estimation task. Numerical studies show that local identifiability can be quite sensitive to input data and a given local solution. Finally, several countermeasures are proposed to overcome ill-conditioning problem in measurement-based load modeling.

• Korean Management Science Review
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• v.19 no.2
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• pp.125-137
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• 2002

The telecommunications market is expanding rapidly and becoming more substitutive. In this environment, demand forecasting is very difficult, yet important for both practitioners and researchers. in this paper, we adopt the modeling approach proposed dy Jun and Park ［6］. The basic premise is that demand patterns result from choice behavior, where customers choose a product to maximize their utility. We apply a choice-based substitutive diffusion model to the Korean mobile telecommunication service market where digital service has completely replaced analog service. In comparison with Bass-type multigeneration models. our model provides superior fitting and forecasting performance. The choice-based model is useful in that it enables the description of such complicated environments and provides the flexibility to include marketing mix variables such as price and advertising in the regression analysis.