• Proceedings of the KSPS conference
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• 2005.04a
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• pp.99-102
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• 2005

Research efforts have been made for out-of-vocabulary word rejection to improve the confidence of speech recognition systems. However, little attention has been paid to non-recognition sentence rejection. According to the appearance of pronunciation correction systems using speech recognition technology, it is needed to reject non-recognition sentences to provide users with more accurate and robust results. In this paper, we introduce standard phoneme based sentence rejection system with no need of special filler models. Instead we used word spotting ratio to determine whether input sentences would be accepted or rejected. Experimental results show that we can achieve comparable performance using only standard phoneme based recognition network in terms of the average of FRR and FAR.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.407-408
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• 2007

Robust pitch estimation is an important study in many areas of speech processing. In voice pathology, diverse statistics extracted form pitch were commonly used to test voice quality. In this study, we compared several established pitch detection algorithms (PDAs) for verification of adequacy of the PDAs. In the database of total pathological voices of 99 and normal voices of 30, an analysis of errors related with pitch detection was evaluated between pathological and normal voices, or among the types of pathological voices such as benign vocal fold lesions; polyp, nodule, and cysts. Consequently, it is required to survey the severity of tested voice in order to obtain accurate pitch estimates.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1191-1191
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• 2001

Generation of precise, accurate, and robust calibration models for spectroscopic methods of analysis can be time-consuming, expensive, and sometimes difficult to achieve. For these reasons, efforts have been made to find ways in which the calibration from one instrument can be moved to another with minimal performance reduction. A slight shift in nomenclature from the common term calibration transfer to the term calibration transport is used here to help resolve the subtle difference between two means of moving a calibration from one instrument to another. The former term denotes a transfer procedure that includes mathematical manipulation of the calibration data via some determined transfer function, whereas the latter term does not. Todays generation of process and laboratory FTNIR analyzers is capable of not only achieving calibration transfer, but also calibration transport often without the need of slope or bias adjustments. Several studies are used to examine the boundaries of the extent to which calibration transport is achieved in the refining industry. Data collected on multiple on-line and laboratory FTNIR analyzers located in multiple countries are considered, and the ultimate limitations discussed.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.95-107
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• 2022

With the rapid development of Internet of Things sensor devices and big data processing techniques, Internet of Things sensor-based information systems have been applied in various industries. Depending on the industry in which the information systems are applied, the accuracy of the information derived can affect the industry's efficiency and safety. Therefore, security techniques that protect sensing data from security attacks and enable information systems to derive accurate information are essential. In this paper, we examine security threats targeting each processing step of an Internet of Things sensor-based information system and propose security mechanisms for each security threat. Furthermore, we present an Internet of Things sensor-based information system structure that is robust to security attacks by integrating the proposed security mechanisms. In the proposed system, by applying lightweight security techniques such as a lightweight encryption algorithm and obfuscation-based data validation, security can be secured with minimal processing delay even in low-power and low-performance IoT sensor devices. Finally, we demonstrate the feasibility of the proposed system by implementing and performance evaluating each security mechanism.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.472-477
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• 1996

This paper presents a new approachtothe design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The prpposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1107-1110
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• 1999

In speech signal processing, the accurate decision of the voiced/unvoiced sound is important for robust word recognition and analysis and a high coding efficiency. In this paper, we propose the mehod of the voiced/unvoiced decision using the LSP parameter which represents the spectrum characteristics of the speech signal. The voiced sound has many more LSP parameters in low frequency region. To the contrary, the unvoiced sound has many more LSP parameters in high frequency region. That is, the LSP parameter distribution of the voiced sound is different to that of the unvoiced sound. Also, the voiced sound has the minimun value of sequantial intervals of the LSP parameters in low frequency region. The unvoiced sound has it in high frequency region. we decide the voiced/unvoiced sound by using this charateristics. We used the proposed method to some continuous speech and then achieved good performance.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.216-218
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• 1995

In this article a neural network adaptive observer is proposed and applied to the case of induction motor control. The high performance vector control drives require exact knowledge of rotor flux. Because rotor time constant is needed to observe rotor flux, the accurate estimation of rotor time constant is important. For these problems, proposed observer which comprises neural network flux observer and neural network torque observer is trained to learn the flux dynamics and torque dynamics and subject to further on-line training by means of a backpropagation algorithem. Therefore it has been shown that the robust control of induction motor neglects the rotor time constant variations.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.99-107
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• 2022

Urban Air Mobility (UAM) such as a drone taxi is one of the future transportations that have recently been attracting attention. Along with the construction of an urban terminal, an accurate landing system for UAM is also essential. However, in urban environments, reliable Global Navigation Satellite Systems (GNSS) signals cannot be received due to obstacles such as high-rise buildings which causes multipath and non-line of sight signal. Thus, the positioning result in urban environments from the GNSS signal is unreliable. Consequently, we propose the Ultra-Wideband (UWB) network to assist the soft landing of UAM on a vertiport. Since the positioning performance of UWB network depends on the layout of UWB anchors, it is necessary to optimize the layout of UWB anchors. In this paper, we propose a two-steps genetic algorithm that consists of binary genetic algorithm involved multi objectives fitness function and integer genetic algorithm involved robust solution searching fitness function in order to optimize taking into account Fresnel hole effects.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.51-53
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• 2009

In wireless sensor networks(WSNs), geographic routing algorithms can enhance the network capacity. However, in the real WSNs, it is difficult for each node to know its accurate physical location. Geographic routing with location error may have serious problems such as disconnected links and delayed data transmission. In this letter, we present an efficient location error detection scheme for geographic routing. The proposed algorithm can efficiently update its incorrect location without additional procedure and finally enhance the performance on the geographic routing with the location errors.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.25-34
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• 2008

By comparing two images, which are captured with the same scene at different time, we can detect a set of outliers, such as occluding objects due to moving vehicles. To reduce the influence from the different intensity properties of the images, an intensity compensation scheme, which is based on the polynomial regression model, is employed. For an accurate detection of outliers alleviating the influence from a set of outliers, a simple technique that reruns the regression is employed. In this paper, an algorithm that iteratively reruns the regression is theoretically analyzed by observing the convergence property of the estimates of the noise variance. Using a correction constant for the estimate of the noise variance is proposed. The correction enables the detection algorithm robust to the choice of thresholds for selecting outliers. Numerical analysis using both synthetic and Teal images are also shown in this paper to show the robust performance of the detection algorithm.