• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.7
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• pp.45-51
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• 2009

We have presented a routing mechanism that selects a route by considering channel statuses in order to fast transfer delay-sensitive data in WSNs (Wireless Sensor Networks). The existing methods for real-time data transfer select a path whose latency is the shortest or the number of hops is the smallest. An algorithm to select a real-time transfer path based on link error rates according to the characteristic of wireless medium was also suggested. However, the propagation delay and retransmission timeout affected by link error rates are shorter than channel assessment time and backoff time. Therefore, the mechanism proposed in this paper estimated the time spent in using a clear channel and sending out a packet, which is based on channel backoff rates. A source node comes to select a route with the shortest end-to-end delay as a fast transfer path for real-time traffic, and sends data along the path chosen. We found that this proposed mechanism improves the speed of event-to-sink data transfer by performing experiments under different link error and channel backoff rates.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1998.10a
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• pp.157-162
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• 1998

Dynamic loads may arise from rotating parte of pump if they are insufficiently balanced. The magnitude of pump induced vibrations varies according to the weight, eccentricity, and unbalanced mass of pump. This is a study to estimate the pump induced vibration in time and frequency domain by transfer function. The transfer function has real and imaginary information of signals, and response function has also real and imaginary information. So the vibration force can be obtained from the response and transfer function by complex calculation. The amplitudes and components of 50Hp pump vibration force are suggested.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.245-251
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• 2023

Facial expression recognition plays a significant role in understanding human emotional states. With the advancement of AI and computer vision technologies, extensive research has been conducted in various fields, including improving customer service, medical diagnosis, and assessing learners' understanding in education. In this study, we develop a model that can infer emotions in real-time from a webcam using transfer learning with TensorFlow.js and MobileNet. While existing studies focus on achieving high accuracy using deep learning models, these models often require substantial resources due to their complex structure and computational demands. Consequently, there is a growing interest in developing lightweight deep learning models and transfer learning methods for restricted environments such as web browsers and edge devices. By employing MobileNet as the base model and performing transfer learning, our study develops a deep learning transfer model utilizing JavaScript-based TensorFlow.js, which can predict emotions in real-time using facial input from a webcam. This transfer model provides a foundation for implementing facial expression recognition in resource-constrained environments such as web and mobile applications, enabling its application in various industries.

• Journal of Hydrogen and New Energy
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• v.26 no.2
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• pp.184-191
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• 2015

As the power electronics system increases the frequency, the power loss and thermal management are paid more attention. This research presents a real time model of dissipation power with junction temperature response for 120kw IGBT inverter which is applied to the thermal management of high power IGBT inverter. Since the computational time is critical for real time simulation, look-up tables of IGBT module characteristic curve are implemented. The power loss from IGBT provides a clue to calculate the temperature of each module of IGBT. In this study, temperature of each layer in IGBT is predicted by lumped capacitance analysis of layers with convective heat transfer. The power loss and temperature of layers in IGBT is then communicated due to mutual dependence. In the dynamic model, PWM pulses are employed to calculation real time IGBT and diode power loss. Under Matlab/Simulink$^{(R)}$ environment, the dynamic model is validated with experiment. Results showed that the dynamic response of power loss is closely coupled with effective thermal management. The convective heat transfer is enough to achieve proper thermal management under guideline temperature.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.534-538
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• 1995

In this paper, a realization of a real-time train information system(TIS) is discussed. The requirements of TIS which satisfy real-time constraints are analyzed in view of data transfer. For efficient data communication in TIS, a new network system is suggested and its real-time characteristics are analyzed and compared with the standard network system. A local unit is designed based on VMEbus system.

• Composites Research
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• v.18 no.4
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• pp.35-43
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• 2005

In resin transfer molding(RTM), race-track effects and non-uniform fiber volume fraction may cause undesirable resin flow patterns and thus result in dry spots, which affect the mechanical properties of the finished parts. In this study, a real time RTM control strategy to reduce these unfavorable effects is proposed. This control rule is accomplished by means of the permeability mapping and pressure regulation. Through numerical simulations, the validity of the proposed scheme is demonstrated.

• Journal of the Korean Solar Energy Society
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• v.30 no.3
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• pp.25-32
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• 2010

A real-time monitoring system was developed for transfer, receive, backup and analysis of wind power data at three wind farm(Hang won, Hankyung and Sung san) in Jeju. For this monitoring system a communication system analysis, a collection of data and transmission module development, data base construction and data analysis and management module was developed, respectively. These modules deal with mechanical, electrical and environmental problem. Especially, time series graphic is supported by the data analysis and management module automatically. The time series graphic make easier to raw data analysis. Also, the real-time monitoring system is connected with wind power forecasting system through internet web for data transfer to wind power forecasting system's data base.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.6
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• pp.295-301
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• 2013

In this paper, we propose a real-time centralized soft motion control system for high speed and precision robot control. The system engages EtherCAT as high speed industrial motion network to enable force based motion control in real-time and is composed of software-based master controller with PC and slave interface modules. Hard real-time control capacity is essential for high speed and precision robot control. To implement soft based real time control, The soft based master controller is designed using a real time kernel (RTX) and EtherCAT network, and servo processes are located in the master controller for centralized motion control. In the proposed system, slave interface modules just collect and transfer all sensor information of robot to the master controller via the EtherCAT network. It is proven by experimental results that the proposed soft motion control system has real time controllability enough to apply for various robot control systems.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1722-1729
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• 2011

This paper presents an optimization model for revising train timetable based on an existing timetable to improve transfer time at each station. The transfer time consists of walking and waiting time. The model is formulated as a mixed integer programming. The objective function is to minimize the transfer time from one train to another train at each station. To reflect real situations, range of revising departure time is considered as major condition in the model. To validate the effectiveness of the model, rudimentary computational results are included, and the results are analyzed in terms of transfer time.

• Journal of Electrical Engineering and Technology
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• v.5 no.2
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• pp.209-219
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• 2010

In this paper, a novel dynamic available transfer capability (DATC) has been computed for real time applications using three different intelligent techniques viz. i) back propagation algorithm (BPA), ii) radial basis function (RBF), and iii) adaptive neuro fuzzy inference system (ANFIS) for the first time. The conventional method of DATC is tedious and time consuming. DATC is concerned with calculating the maximum increase in point to point transfer such that the transient response remains stable and viable. The ATC information is to be continuously updated in real time and made available to market participants through an internet based Open Access Same time Information System (OASIS). The independent system operator (ISO) evaluates the transaction in real time on the basis of DATC information. The dynamic contingency screening method [1] has been utilized and critical contingencies are selected for the computation of DATC using the energy function based potential energy boundary surface (PEBS) method. The PEBS based DATC has been utilized to generate patterns for the intelligent techniques. The three different intelligent methods are tested on New England 68-bus 16 machine and 39-bus 10 machine systems and results are compared with the conventional PEBS method.