• Journal of Mechanical Science and Technology
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• v.19 no.3
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• pp.743-755
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• 2005

Human Sensibility Engineering System (HSES) has been applied to product development for customer's satisfaction based on ergonomic technology. The system is composed of three parts such as human sensibility analysis, inference mechanism, and presentation technologies. Inference mechanism translating human sensibility into design elements plays an important role in the HSES. In this paper, we propose a rule-based inference model for HSES. The rule-based inference model is composed of five rules and two inference approaches. Each of these rules reasons the design elements for selected human sensibility words with the decision variables from regression analysis in terms of forward inference. These results are evaluated by means of backward inference. By comparing the evaluation results, the inference model decides on product design elements which are closer to the customer's feeling and emotion. Finally, simulation results are tested statistically in order to ascertain the validity of the model.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.189-202
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• 2011

It is important issue how to evaluate the economic feasibility of computing factors in the real world when we build ubiquitous spaces. In this paper, we propose a simple model that can evaluate the economic feasibility of mobile RFID-based ubiquitous computing system which enables seamless communication between offline and online via embedded computing factors in the real world. To achieve this, we explore the meaning of mobile RFID system, the difference between our research and extant researches concerning the evaluation of economic feasibility in RFID system, and propose the so-called 'Tag-based Evaluation Model' (TEM) which is an evaluation model to access the economic feasibility of mobile RFID systems. We also analyze the TEM via simulation cases based on proposed model and discuss the future of TEM.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.113-118
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• 2001

In this paper, we develop an optimal intelligent digital redesign method for a class of fuzzy-model-based controllers, effective for stabilization of continuous-time complex nonlinear systems. Takagi-Sugeno (TS) fuzzy model is used to extend the results of the classical digital redesign technique to complex nonlinear systems. Unlike the conventional intelligent digital redesign technique reported in the literature, the proposed method utilized the recently developed LMI optimization technique to obtain a digitally redesigned fuzzy-model-based controller. Precisely speaking, the intelligent digital redesign problem is converted to an equivalent optimization problem, and the LMI optimization method is used to find the digitally redesigned fuzzy-model-based controller. A numerical example is provided to evaluate the feasibility of the proposed approach.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.4
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• pp.292-303
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• 2003

An efficient mobility management for mobile stations plays an important role in mobile communication network. Two basic operations of mobility management are location registration and paging. A zone-based registration (ZBR) is implemented in most of mobile communication systems and we consider the mobility management scheme that combines a zone-based registration and a selective paging (SP). We propose new analytical model that can reflect on the characteristics of the ZBR based on 2-dimensional random walk mobility model and more efficient paging schemes considering the proposed model. We evaluate the performance of the mobility management scheme with our mobility model to determine the optimal size of location area that will result in the minimum signaling traffic on radio channels. Numerical results are provided to demonstrate that our mobility model is useful to evaluate the ZBR more exactly.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.279-284
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• 2005

Knowledge based fault diagnosis has a limitation in determining the cause and scheme for the fault, because it detects faults from signal pattern only Therefore, model-based fault diagnosis is requested to determine the fault by analyzing output of the equipment from its dynamic model. This research shows a method how to devise the automaton of system as a model for normal and faulty condition through the reduction of handling data by quantization of vibration signals and the example which is concerning to the bearing of ATM. The developed model based fault diagnosis was applied to detect the faulty bearing of ATM, which results.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.2
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• pp.8-15
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• 2018

In traditional Document Based Configuration Management(DBCM) environment, changes in a system's configurations are hard to be reflected to existing engineering documents. This nature of DBCM triggers unconformities of system configurations which could become great risks. Model-based Configuration Management(MBCM) has been introduced to solve the problem of DBCM by managing system's configurations through an unified model. Therefore, it is important to model engineering documents in a general modeling language, down to low-level information items to develop traceability and flexibility of a system's engineering information. So, in the research, to explore the possibility of Model-based Approach(MBA) in the field of configuration management, a development of a systems requirement document model using SysML based Views & Viewpoints concept has been studied.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.4
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• pp.164-173
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• 2009

Automotive systems have tended to be equipped with many electronic contents to satisfy safety, comport, convenience, and entertainment services over the past years. As a result, the amount of vehicle embedded software in electrical/electronic(E/E) systems is steadily increasing to manage these requirements. This leads to the traditional, document-based software development in the vehicle embedded systems being increasingly displaced by a model-based development in order to reduce software development time and cost. Due to the application of model-based development, a great evolution is being realized in the aspect of efficiency, but the development is being made without sufficient testing. So, erroneous automotive embedded software may cause serious problems such as car accidents which relate to human safety. Therefore, efficient methods for model-based test and validation are needed to improve software reliability in the stage of embedded software development. This paper presents the model-based development and test method for AUTOSAR embedded software to improve its reliability and safety, and it is demonstrated based on the case study.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.195-202
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• 2011

The study interprets each of three classification models based on Bath-Tub Failure Rate (BTFR), Extreme Value Distribution (EVD) and Conjugate Bayesian Distribution (CBD). The classification model based on BTFR is analyzed by three failure patterns of decreasing, constant, or increasing which utilize systematic management strategies for reliability of time. Distribution model based on BTFR is identified using individual factors for each of three corresponding cases. First, in case of using shape parameter, the distribution based on BTFR is analyzed with a factor of component or part number. In case of using scale parameter, the distribution model based on BTFR is analyzed with a factor of time precision. Meanwhile, in case of using location parameter, the distribution model based on BTFR is analyzed with a factor of guarantee time. The classification model based on EVD is assorted into long-tailed distribution, medium-tailed distribution, and short-tailed distribution by the length of right-tail in distribution, and depended on asymptotic reliability property which signifies skewness and kurtosis of distribution curve. Furthermore, the classification model based on CBD is relied upon conjugate distribution relations between prior function, likelihood function and posterior function for dimension reduction and easy tractability under the occasion of Bayesian posterior updating.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.224-227
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• 2003

The Intrsuion Detecion Systems(IDS) are required the accuracy, the adaptability, and the expansion in the information society to be changed quickly. Also, it is required the more structured, and intelligent IDS to protect the resource which is important and maintains a secret in the complicated network environment. The research has the purpose to build the model for the intelligent IDS, which creates the intrusion patterns. The intrusion pattern has extracted from the vast amount of data. To manage the large size of data accurately and efficiently, the link analysis and sequence analysis among the data mining techniqes are used to build the model creating the intrusion patterns. The model is consist of "Time based Traffic Model", "Host based Traffic Model", and "Content Model", which is produced the different intrusion patterns with each model. The model can be created the stable patterns efficiently. That is, we can build the intrusion detection model based on the intelligent systems. The rules prodeuced by the model become the rule to be represented the intrusion data, and classify the normal and abnormal users. The data to be used are KDD audit data.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.110-110
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• 2001

By the state transformation including independent outputs functions, a nonlinear process model can be decomposed into two subsystems; the one(design model) is described in output variables as new states and used for control system synthesis and the other(disturbance model) is described in the original unavailable states and its couplings with the design model are treated as uncertain time-varying parameters in the design model. Its existence with respect to the design model is ignored. So, the design model is and uncertain time-variant system. Control synthesis based on a reduced design model is a combined form of a time-variant input-output linearization with parameter estimation. The parameter estimation is also based on the design model and it gives the parameter estimates such that the estimated outputs follow the actual outputs in a specified way. The disturbances form disturbance model and as well all the other uncertainties affecting the outputs will be reflected into the estimated parameters used in the linearizing control law.