• Journal of KSNVE
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• v.9 no.2
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• pp.265-272
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• 1999

A LMS algorithms has been widely used for an adaptive filter algorithm in active noise control systems. But this algorithm has poor convergence and it is very difficult to select optimal convergence parameters in this algorithm. In this paper, a fuzzy LMS algorithm where the convergence parameters are computed using a fuzzy logic controller was proposed. A proposed algorithm was applied to active noise control system in HVAC(central Heating Ventilation and Air Conditioning) ducts. The experimental ducts and experimental apparatus were designed and manufactured for experiments, and the modelling of the experimental ducts was also performed for computer simulations. Computer simulations and experiments were performed to show the effectiveness of a proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.11-17
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• 2019

In this paper, we propose a method to recognize the moving direction in the indoor environment by using the sensing system equipped with passive infrared (PIR) sensors and a deep learning algorithm. A PIR sensor generates a signal that can be distinguished according to the direction of movement of the user. A sensing system with four PIR sensors deployed by $45^{\circ}$ increments is developed and installed in the ceiling of the room. The PIR sensor signals from 6 users with 10-time experiments for 8 directions were collected. We extracted the raw data sets and performed experiments varying the number of sensors fed into the deep learning algorithm. The proposed sensing system using deep learning algorithm can recognize the users' moving direction by 99.2 %. In addition, with only one PIR senor, the recognition accuracy reaches 98.4%.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.267-270
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• 2019

Through this research, the rating data of shops were analyzed. The model was designed for discrete multiple classification as to the corresponding data, and the following experiments were initiated to observe the learned machine. By comparing each benchmarks in the experiments, which contains different setting variables for the machine model, the hit ratio was measured which indicates how much it is matched with the expected label. By analyzing those results from each benchmarks, the model was redesigned one time during the research and the effects of each setting variables on this machine were clarified. Furthermore, the research result left the future works, which are related with how the learning could be improved and what should be designed in the further research.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.65-72
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• 2022

With the mark of the fourth industrial revolution, the smart factory is evolving into a new future manufacturing plant. As a human-machine-interactive tool, augmented reality (AR) helps workers acquire the proficiency needed in smart factories. The valuable data displayed on the AR device must be delivered intuitively to users. Current AR applications used in smart factories lack user movement calibration, and visual fiducial markers for position correction are detected only nearby. This paper demonstrates a marker-based object detection using perspective projection to adjust augmented content while maintaining the user's original perspective with displacement. A new angle, location, and scaling values for the AR content can be calculated by comparing equivalent marker positions in two images. Two experiments were conducted to verify the implementation of the algorithm and its practicality in the smart factory. The markers were well-detected in both experiments, and the applicability in smart factories was verified by presenting appropriate displacement values for AR contents according to various movements.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.40-48
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• 2023

Speech Emotions recognition has become the active research theme in speech processing and in applications based on human-machine interaction. In this work, our system is a two-stage approach, namely feature extraction and classification engine. Firstly, two sets of feature are investigated which are: the first one is extracting only 13 Mel-frequency Cepstral Coefficient (MFCC) from emotional speech samples and the second one is applying features fusions between the three features: Zero Crossing Rate (ZCR), Teager Energy Operator (TEO), and Harmonic to Noise Rate (HNR) and MFCC features. Secondly, we use two types of classification techniques which are: the Support Vector Machines (SVM) and the k-Nearest Neighbor (k-NN) to show the performance between them. Besides that, we investigate the importance of the recent advances in machine learning including the deep kernel learning. A large set of experiments are conducted on Surrey Audio-Visual Expressed Emotion (SAVEE) dataset for seven emotions. The results of our experiments showed given good accuracy compared with the previous studies.

• Journal of The Korean Association of Information Education
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• v.14 no.2
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• pp.165-174
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• 2010

The digital textbook project which embarked by the Ministry of Education, Science and Technology has focused on experiments and practices from the school designated by the government. However the previous research about digital textbook provides static interaction models and teaching-learning models analogous to web-based learning based desktop PC even the framework of the digital textbook is based of Tablet PC. This paper provides learning and teaching models for next generation digital textbook which based digital inking techinques for sketcth interface and AR(augmented reality) interactions between teacher and learner. The proposed method of this paper is applied to educational contents and we found positive effect which is supported by statistical experiments. The results of this study in the future and the future development of digital textbooks in effect will be an effective development plan.

• Journal of Power Electronics
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• v.12 no.1
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• pp.223-231
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• 2012

In this paper, criteria for better selection of a supercapacitor through EIS (Electrochemical Impedance Spectroscopy) experiments are presented. The performance characteristics of a supercapacitor are thoroughly analyzed in terms of losses and available energy to select the optimal product. The validity of the proposed criteria is demonstrated through the computer simulations and experiments on a fuel cell vehicle using a supercapacitor module with the FTP-72 urban dynamometer driving schedule.

• Journal of applied mathematics & informatics
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• v.6 no.2
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• pp.631-638
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• 1999

Sensitive testing has been widely employed for many years in connection with the development and evaluation explosives detonation devices and propellants. Perhaps its earliest and possibly most important implementation was in biological studies of dosage mortality and response to drugs. Recently sensitivity experiments has been employed in the evaluation of new materials subject to stress in various environments and in delineanation of unstable combustion regions in chemical propulsion systems. This paper discussed a sta-tistical development of sensitivity testing.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.623-626
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• 1998

NLMS algorithm is degraded by the ambient noises and the near-end speech signals. In this paper, a robust acoustic echo cancellation algorithm is proposed. To enhance the echo cancellation performance, the step size of the proposed algorithm is normalized by the sum o fthe power of the reference signals and the primary signals. as results of comparing the excess mean square errors, it is shown that the proosed algorithm can enhance the performance of cancelling the echo signals. Some experiments, which is used multimedia personal computer, are carried out. As results of experiments, the proposed algorithm shows better performance than conventional ones.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.28-33
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• 1996

This paper presents a position control of ultra-precision machine tool post using piezoelectric material. A stack-type piezoelectric actuator is employed in a hinge-type tool holder. An assumed linear transfer function of the practical nonlinear plant is established through the comparison of transfer functions and step responses in the experiments and the simulations. Several types of feedforward/feedback controllers are designed via computer simulations using the assumed linear transfer function, The position tracking control experiments are undertaken to show the control efficiency of each controller.