• Journal of the Ergonomics Society of Korea
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• v.25 no.2
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• pp.135-146
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• 2006

Multimodal interfaces are recognition-based technologies that interpret and encode hand gestures, eye-gaze, movement pattern, speech, physical location and other natural human behaviors. Modality is the type of communication channel used for interaction. It also covers the way an idea is expressed or perceived, or the manner in which an action is performed. Multimodal Interfaces are the technologies that constitute multimodal interaction processes which occur consciously or unconsciously while communicating between human and computer. So input/output forms of multimodal interfaces assume different aspects from existing ones. Moreover, different people show different cognitive styles and individual preferences play a role in the selection of one input mode over another. Therefore to develop an effective design of multimodal user interfaces, input/output structure need to be formulated through the research of human cognition. This paper analyzes the characteristics of each human modality and suggests combination types of modalities, dual-coding for formulating multimodal interaction. Then it designs multimodal language and input synchronization method according to the granularity of input synchronization. To effectively guide the development of next-generation multimodal interfaces, substantially cognitive modeling will be needed to understand the temporal and semantic relations between different modalities, their joint functionality, and their overall potential for supporting computation in different forms. This paper is expected that it can show multimodal interface designers how to organize and integrate human input modalities while interacting with multimodal interfaces.

• Journal of the Ergonomics Society of Korea
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• v.27 no.4
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• pp.73-83
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• 2008

With a rapid extension of functions in mobile phones, text input method has become very important for mobile phone users. Previous studies for text input methods were focused on Fitts' law, emphasizing expert's behaviors with one-handed text input method. However, it was observed that 97% of Korean mobile phone users input texts with two-hands. Therefore, this study was designed to develop a prediction model of two-handed Hangul text entry method including novice users as well as experts for mobile phone. For this study, Fitts' law was hypothesized to predict experts' movement time(MT) whereas Hick-Hyman law for visual search time was hypothesized to be added to MT for novices. The results showed that the prediction model was well fitted with the empirical data for both experts and novices with less than 3% error rates. In conclusion, this prediction model of two-handed Hangul text entry including novice users was proven to be a very effective model for modeling two-handed Hangul text input behavior for both experts.

• IE interfaces
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• v.12 no.3
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• pp.437-447
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• 1999

Modeling and system development for the fabrication process in the semiconductor manufacturing is presented in this paper. Maximization of wafer production can be achieved by the wafer flow balance under high utilization of bottleneck machines. Relatively simpler model is developed for the fabrication line by considering main characteristics of logistics. Simulation system is developed to evaluate the line performance such as balance rate, utilization, WIP amount and wafer production. Scheduling rules and input rules are suggested, and tested on the simulation system. We have shown that there exists good combination of scheduling and input rules.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.533-537
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• 2002

A fast time domain modeling and simulation is performed for the input-series-output-parallel connected 2-switch forward converter Steady-state and large-signal transient responses due to a step load change are simulated. The simulation results are verified through experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.239-239
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• 2000

This paper present experimental results on temperature trajectory tracking. The benefits of precalculated feedforward input together with PID feedback control are demonstrated by experimental results. To find the feedforward input, the plant (autoregresiive) model is first identified and convex optimization procedure is applied. PID controller is then implemented based on Ziegler-Nickels tuning rule to reduce effects of disturbances and modeling errors. Experimental results show an improvement in slope tracking performance over the fully PID controller.

• Proceedings of the Safety Management and Science Conference
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• 2003.11a
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• pp.271-284
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• 2003

We developing for Gate-Container Yard model to execute the Input & Output process of containers which are waiting in container yard effectively and fast. The optimal model is developed to manage and trace the containers in yard. We developed the put-away strategies which considered the storage time for volume of transportation and the distance between blocks and gates using the MICRO-CRAFT (Computerized Relative Allocation Facilities Technique).

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.7
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• pp.82-88
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• 1992

This paper presents one of the first comprehensive studies of how hot electron degradation impacts the input offset voltage of a CMOS differential amplifiers. This study utilizes the concept of a virtual source-coupled MOSFET pair in order to evaluate offset voltaged egradation directly from individual device measurement. Next, analytical models are developed to describe the offset voltage degradation. These models are used to examine how hot electron induced offset voltage is affected with the device parameters.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.443-447
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• 2001

In this paper, a robust sensorless vector control system for induction motors with a speed estimator and an uncertainty observer is presented. At first, the proposed speed estimator is based on the MRAS(Mode Reference Adaptive System) scheme and constructed with a simple fuzzy logic(FL) approach. The structure of the proposed FL estimator is very simple. The input of the FL is the rotor flux error difference between reference and adjustable model, and the output is the estimated incremental rotor speed Secondly, the unmodeled uncertainties such as parametric uncertainties and external load disturbances are modeled by a radial basis function network(RBFN). In the overal speed control system, the control inputs are composed with a norminal control input and a compensated control input, which are from RBFN observer output and the modeling error of the RBFN, repectively. The compensated control input is derived from Lyapunov unction approach. The simulation results are presented to show the validity of the proposed system.

• Journal of Power System Engineering
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• v.7 no.1
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• pp.74-81
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• 2003

A system identification is to estimate the mathematical model on the base of input output data and to measure the output in the presence of adequate input for the controlled system. In the traditional system control field, most identification problems have been thought as estimating the unknown modeling parameters on the assumption that the model structures are fixed. In the system identification, it is possible to estimate the true parameter values by the adjusted least squares method in the input output case of no observed noise, and it is possible to estimate the true parameter values by the total least squares method in the input output case with the observed noise. We suggest the adjusted least squares method as a consistent estimation method in the system identification in the case where there is observed noise only in the output. In this paper the adjusted least squares method has been developed from the least squares method and the efficiency of the estimating results was confirmed by the generating data with the computer simulations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1223-1229
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• 2009

The performance of Radial Basis Function Neural Networks depends on setting up the Radial Basis Functions over the input space which are the important design procedure of Radial Basis Function Neural Networks. The existing method to initialize the location of the radial basis functions over the input space is to use the conditional fuzzy C-means clustering. However, the researchers which are interested in the conditional fuzzy C-means clustering cannot get as good modeling performance as they expect because the conditional fuzzy C-means clustering cannot project the information which is extracted over the output space into the input space. To compensate the above mentioned drawback of the conditional fuzzy C-means clustering, we apply a fuzzy K-nearest neighbors approach to project the auxiliary information defined over the output space into the input space without lose of the information.