• Smart Structures and Systems
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• v.1 no.2
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• pp.141-158
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• 2005

A new design of distributed crack sensors based on the topological change of transmission line cables is presented for the condition assessment of reinforced concrete (RC) structures during and immediately after an earthquake event. This study is primarily focused on the performance of cable sensors under dynamic loading, particularly a feature that allows for some "memory" of the crack history of an RC member. This feature enables the post-earthquake condition assessment of structural members such as RC columns, in which the earthquake-induced cracks are closed immediately after an earthquake event due to gravity loads, and are visually undetectable. Factors affecting the onset of the feature were investigated experimentally with small-scale RC beams under cyclic loading. Test results indicated that both crack width and the number of loading cycles were instrumental in the onset of the memory feature of cable sensors. Practical issues related to dynamic acquisition with the sensors are discussed. The sensors were proven to be fatigue resistant from shake table tests of RC columns. The sensors continued to show useful performance after the columns can no longer support additional loads.

• International Journal of Quality Innovation
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• v.3 no.2
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• pp.113-131
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• 2002

The relationships among multi-dimensional data (such as medical examination data) with ambiguity and variation are difficult to explore. The traditional approach to building a data classification system requires the formulation of rules by which the input data can be analyzed. The formulation of such rules is very difficult with large sets of input data. This paper first describes two classification approaches using back-propagation (BP) neural network and Mahalanobis distance (MD) classifier, and then proposes two classification approaches for multi-dimensional feature selection. The first one proposed is a feature selection procedure from the trained back-propagation (BP) neural network. The basic idea of this procedure is to compare the multiplication weights between input and hidden layer and hidden and output layer. In order to simplify the structure, only the multiplication weights of large absolute values are used. The second approach is Mahalanobis-Taguchi system (MTS) originally suggested by Dr. Taguchi. The MTS performs Taguchi's fractional factorial design based on the Mahalanobis distance as a performance metric. We combine the automatic thresholding with MD: it can deal with a reduced model, which is the focus of this paper In this work, two case studies will be used as examples to compare and discuss the complete and reduced models employing BP neural network and MD classifier. The implementation results show that proposed approaches are effective and powerful for the classification.

• Language and Information
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• v.18 no.2
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• pp.59-79
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• 2014

This paper aims at exploring the processing mechanism of filler-gap dependency resolution and feature checking in Korean wh-constructions. Based on their findings on Japanese sentence processing, Aoshima et al. (2004) have argued that the parser posits a gap in the embedded clause in head-final languages, unlike in head-initial languages, where the parser posits a gap in the matrix clause. In order to verify their findings in the Korean context, and to further explore the mechanisms involved in processing Korean wh-constructions, the present study replicated the study done by Aoshima et al., with some modifications of problematic areas in their original design. Sixty-four Korean native speakers were presented Korean sentences containing a wh-phrase in four conditions, with word order and complementizer type as the two main factors. The participants read sentences segment-by-segment, and the reading times at each segment were measured. The reading time analysis showed that there was no such slowdown at the embedded verb in the scrambled conditions as observed in Aoshima et al. Instead, there was a clear indication of the wh-feature checking process in terms of a major slowdown at the relevant region.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.197-207
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• 2022

The Naval Combat System operates in multiple software components for efficient functional processing. Data transmission and reception between components is performed in real time using DDS(Data Distribution Service). Reliable Post-Analysis requires the collection of all DDS messages. However, Software workload and development costs increase because common functions for all messages must be developed directly. In the paper, We propose an improved Post-Analysis based on the Feature Model and a new development system using it. Functions for the modified message were applied as variable domains of the Feature Model. When Build Center updates Post-Analysis, it automatically processes all software tasks associated with Post-Analysis. The proposed development system simplified the overall work procedure, and work time was significantly reduced compared to the existing development system.

• Earthquakes and Structures
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• v.27 no.3
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• pp.177-189
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• 2024

Accurately predicting the failure modes of reinforced concrete (RC) columns is essential for structural design and assessment. In this study, the challenges of imbalanced datasets and complex feature selection in machine learning (ML) methods were addressed through an optimized ML approach. By combining feature selection and oversampling techniques, the prediction of seismic failure modes in rectangular RC columns was improved. Two feature selection methods were used to identify six input parameters. To tackle class imbalance, the Borderline-SMOTE1 algorithm was employed, enhancing the learning capabilities of the models for minority classes. Eight ML algorithms were trained and fine-tuned using k-fold shuffle split cross-validation and grid search. The results showed that the artificial neural network model achieved 96.77% accuracy, while k-nearest neighbor, support vector machine, and random forest models each achieved 95.16% accuracy. The balanced dataset led to significant improvements, particularly in predicting the flexure-shear failure mode, with accuracy increasing by 6%, recall by 8%, and F1 scores by 7%. The use of the Borderline-SMOTE1 algorithm significantly improved the recognition of samples at failure mode boundaries, enhancing the classification performance of models like k-nearest neighbor and decision tree, which are highly sensitive to data distribution and decision boundaries. This method effectively addressed class imbalance and selected relevant features without requiring complex simulations like traditional methods, proving applicable for discerning failure modes in various concrete members under seismic action.

• Advances in Computational Design
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• v.8 no.4
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• pp.327-351
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• 2023

This article explores how multi-objective optimization techniques can be used to design cost-effective and structurally optimal spatial steel structures, highlighting that optimizing performance can be as important as minimizing costs in real-world engineering problems. The study includes the minimization of maximum horizontal displacement, the maximization of the first natural frequency of vibration, the maximization of the critical load factor concerning the first global buckling mode of the structure, and weight minimization as the objectives. Additionally, it outlines a systematic approach to selecting the best design by employing four different evolutionary algorithms based on differential evolution and a multi-criteria decision-making methodology. The paper's contribution lies in its comprehensive consideration of multiple conflicting objectives and its novel approach to simultaneous consideration of bracing system, column orientation, and commercial profiles as design variables.

• Spatial Information Research
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• v.19 no.3
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• pp.73-81
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• 2011

A study about UFID for the management and administration of digital map has achieved much progress through the Korea National Geographic Information Institute. But it is ture that the content and process is too complicated to be applied. For overcoming this and to make harmonious management of the object based seamless digital map, we need to develop the method which has the unique feature identifier on the digital map for management and administration. So, we introduce OSID(Object-based Seamless digital map IDentifier) on the object based seamless digital map and apply OSID in the system to manage the digital map. This study is based on the OSID basic structure which is applied in object based seamless digital map and design the structure of OSID system to maintain and manage each feature of the object based seamless digital map.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.707-712
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• 1991

In machining a part in CAD/CAM system, it is required that the drawing information should be automatically generated, modified, deleted, and thus be used as an general information throughout the entire manufacturing process. This research addresses basic entities(point, line, circle, arc) for design feature and combination of this features, based on GT concepts, with minimum user's manual input. This paper deals with the generalization of operating system which can cover the s parts which appears in mechanical part handbook and the basic constitutional part of sold base. The system developed shows a strong application impact on automatic process planning system of medium - size injection sold companies.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.4
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• pp.153-180
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• 1994

The assemblability is determined by the structure of product and the relationship between composing parts and machining parts. In this paper, the bolt was divided into bolt-head, -shaft, -thread and -end. For higher assemblability in bolting process, it was analyzed the geometric and technological characteristics of bolts were analysed regarding pre- and in-assembly process. And this paper presents the knowledge-based expert system to assist for designer in the processor of designing bolt for easier assembly. The developed expert system for supporting bolt design assemblability which is named as BDFA SYSTEM consists of two system such as "BOLT DESIGN SYSTEM" which provide feasible assembly bolt design to designer and "EVALUATION SYSTEM" which provide assembly evaluation to alternative of bolt design.

• Korean Journal of Computational Design and Engineering
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• v.5 no.4
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• pp.312-318
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• 2000

In this study, an exclusive CAD/CAM system is developed for enhancing the effectiveness and productivity of CNC universal cylindrical grinding machines on which the external/facing/internal grinding cycles and the wheel dressing cycles are integratively carried out. The CAD/CAM system can manage the various processes such as geometry design, NC code generation, NC code verification, DNC operation, and so on. Especially, the feature-based modeling concept is introduced to improve the geometry design efficiency. And the NC code verification is realized by virtual manufacturing technique based on the real-time analysis of NC codes and the boolean operation between workpiece and wheel.