• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.2
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• pp.172-177
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• 2013

With Brain Computer Interface (BCI) system, a person with disabled limb could use this direct brain signal like electroencephalography (EEG) to control a device such as the artifact arm. The precise force control for the artifact arm is necessary for this artificial limb system. To understand the relationship between control EEG signal and the gripping force of hands, We proposed a study by measuring EEG changes of three grades (25%, 50%, 75%) of hand grip MVC (Maximal Voluntary Contract). The acquired EEG signal was filtered to obtain power of three wave bands (alpha, beta, gamma) by using fast fourier transformation (FFT) and computed power spectrum. Then the power spectrum of three bands (alpha, beta and gamma) of three classes (MVC 25%, 50%, 75%) was classified by using PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis). The result showed that the power spectrum of EEG is increased at MVC 75% more than MVC 25%, and the correct classification rate was 52.03% for left hand and 77.7% for right hand.

• Journal of the Korean Society for Railway
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• v.14 no.6
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• pp.501-506
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• 2011

The study and techniques of system engineering have been applied to various fields including space-air, national defense division in advanced countries. Korea is currently in the early stages of introducing system engineering scheme in railway system and national defense division restrictedly. As theory and application of system engineering covers a wide scope, documents management and requirement analysis technology applied to establishment of standard and core unit development of the research target. The techniques which are historical management and trace among standards for establishment of standard are introduced using SE tools and participating agencies shared the information by constructing of database from all documents which are generated from the project. Through the functional analysis of the requirements for the intelligent station monitoring system in basic design stage, established requirements are verified and will be made official announcement as standard of the intelligent station monitoring system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.121-130
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• 2012

This paper proposes an intuitive real-time robot control system using human body movement. Recently, it has been developed that motion generation for humanoid robots with reflecting human body movement, which is measured by a motion capture. However, in the existing studies about robot control system by human body movement, the detailed structure information of a robot, for example, degrees of freedom, the range of motion and forms, must be examined in order to calculate inverse kinematics. In this study, we have proposed Associative Motion Generation as humanoid robot motion generation method which does not need the detailed structure information. The associative motion generation system is composed of two neural networks: nonlinear principal component analysis and Jordan recurrent neural network, and the associative motion is generated with the following three steps. First, the system learns the correspondence relationship between an indication and a motion using training data. Second, associative values are extracted for associating a new motion from an unfamiliar indication using nonlinear principal component analysis. Last, the robot generates a new motion through calculation by Jordan recurrent neural network using the associative values. In this paper, we propose a real-time humanoid robot control system based on Associative Motion Generation, that enables user to control motion intuitively by human body movement. Through the task processing and subjective evaluation experiments, we confirmed the effective usability and affective evaluations of the proposed system.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.655-660
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• 2009

The context prediction algorithms are not suitable to provide real-time personalized service for users in context-awareness environment. The algorithms have problems like time delay in training data processing and the difficulties of implementation in real-time environment. In this paper, we propose a prediction algorithm with user modeling to shorten of processing time and to improve the prediction accuracy in the context prediction algorithm. The algorithm uses moving path of user contexts for context prediction and generates user model by time-series analysis of user's moving path. And that predicts the user context with the user model by sequence matching method. We compared our algorithms with the prediction algorithms by processing time and prediction accuracy. As the result, the prediction accuracy of our algorithm is similar to the prediction algorithms, and processing time is reduced by 40% in real time service environment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.1
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• pp.31-45
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• 2015

Existing link-based Frank-Wolfe algorithm has been widely used, thanks to its ease of simulation and stable results; however, it comes with low convergence issue towards near the optimum value. Such issue was not considered as a major drawback in the past. However, in the present, some arguments have occurred over the method's stability, analysis time, and other limits as the size and details of the fundamental data for traffic analysis have vastly improved. Therefore, this paper compared the theoretical attributes and the pros and cons between the Frank-Wolfe algorithm and the Origin-based algorithm and Path-based algorithm newly being developed. As a result of this paper, there is possibility that a problem of stability may arise depending on the convergence and exit criteria. Thus, In practice, this effort to derive the appropriate level of convergence is required to secure and stable results.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.57-70
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• 2021

This study aims to investigate the security demand about the traffic policing by analyzing civil complaints. Latent Dirichlet Allocation(LDA) was applied to extract key topics for 2,062 civil complaints data related to traffic policing from e-People. And additional analysis was made of reports of violations, which accounted for a high proportion. In this process, the consistency and convergence of keywords and representative documents were considered together. As a result of the analysis, complaints related to traffic police could be classified into 41 topics, including traffic safety facilities, passing through intersections(signals), provisional impoundment of vehicle plate, and personal mobility. It is necessary to strengthen crackdowns on violations at intersections and violations of motorcycles and take preemptive measures for the installation and operation of unmanned traffic control equipments, crosswalks, and traffic lights. In addition, it is necessary to publicize the recently amended laws a implemented policies, e-fine, procedure after crackdown.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.192-202
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• 2021

In the past, various studies have been conducted on safety facility installation standards and road safety indices. But there are limitations in applying them to the field, such as using many survey items and variables that are difficult to use. Therefore, this study attempted to develop road safety judgment indicators considering the applicability of the research results and to prepare criteria for installing safety facilities. As part of the study, data of related systems were reviewed, and the use of variables already in use was figured out. Furthermore, the road safety judgment indicators reflecting traffic, road, and accident factors were developed through correlation and factor analysis. Later, the criteria score for determining the installation of safety facilities was derived through cluster analysis. The analyses suggested, that the installation judgment criterion score at the intersection was lower than that of the single road(crosswalk), and the road risk at the intersection was higher.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.212-218
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• 2000

The importance and role of pre-/in-service inspection(PSI/ISI) for nuclear power plant(NPP) components are intimately related to plant design, safety, reliability, operation, etc. In this paper, for an effective and efficient management of large amounts of PSI/ISI data in NPPs, an intelligent database program(WS-IDPIN) for PSI/ISI data management of NPP was developed. WS-IDPIN program enables the prompt extraction of previously conducted PSI/ISI conditions and results so that the time-consuming data management, painstaking data processing and analysis in the past are avoided. Furthermore, development of ISI UT auto flaw evaluation and acceptance module based on ASME Code Sec. XI were presented. This module can be used for any angle beam examination from flat plate to spherical shapes as selected by the proper azimuthal angle. This program can be further developed as a unique PSI/ISI data management expert system.

• Structural Engineering and Mechanics
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• v.75 no.5
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• pp.633-642
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• 2020

Artificial neural networks (ANNs) are known as intelligent methods for modeling the behavior of physical phenomena because of it is a soft computing technique and takes data samples rather than entire data sets to arrive at solutions, which saves both time and money. ANN is successfully used in the civil engineering applications which are suitable examining the complicated relations between variables. Functionally graded materials (FGMs) are advanced composites that successfully used in various engineering design. The FGMs are nonhomogeneous materials and made of two different type of materials. In the present study, the bending analysis of functionally graded material (FGM) beams presents on theoretical based on combination of mixed-finite element method, Gâteaux differential and Timoshenko beam theory. The main idea in this study is to build a model using ANN with four parameters that are: Young's modulus ratio (E_t/E_b), a shear correction factor (k_s), power-law exponent (n) and length to thickness ratio (L/h). The output data is the maximum displacement (w). In the experiments: 252 different data are used. The proposed ANN model is evaluated by the correlation of the coefficient (R), MAE and MSE statistical methods. The ANN model is very good and the maximum displacement can be predicted in ANN without attempting any experiments.

• Journal of Intelligence and Information Systems
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• v.10 no.3
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• pp.105-114
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• 2004

In the past year, the increasing concern about the biometric recognition makes the great activities on the security fields, such as the entrance control or user authentication. In particular, although the features of face recognition, such as user friendly and non-contact made it to be used widely, unhappily it has some disadvantages of low accuracy or low Re-attempts Rates. For this reason, I suggest the new approach to re-classify the classified data of recognition result data to solve the problems. For this study, I will use the typical appearance-based, PCA(Principal Component Analysis) algorithm and verify the performance improvement by adopting the re-classification approach using 200 peoples (10 pictures per one person).