• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.7
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• pp.89-101
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• 1997

A technical method of noise modeling and adaptive filtering reducing of speckle noise in ultrasonic medical images is presented. By adjusting the characteristics of the filer according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in diagnosis. Homogeneous factor(HF) from the noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the diagnostic systems with various inner statistical properties is proposed. We show by the experimented that the performance of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region.

• Clinical and Experimental Pediatrics
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• v.49 no.10
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• pp.1026-1030
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• 2006

Mental retardation(MR) is one of the most common developmental disabilities, which is characterized by deficits in intellectual and adaptive functions. Most children with MR have cognitive limitation in the mild range. With respect to the etiology, it is believed that genetic and environmental factors are interrelated and show variable pictures. Most children with MR present with speech and language delay during the early years. The diagnosis can be made by clinical features and neuropsychological tests of intelligence and adaptive functioning. The treatment is limited, but many associated problems are amenable to multidisciplinary interventions. The article will review the recent advances in the management of MR and other neurodevelopmental disorders in children.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.2
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• pp.33-49
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• 2002

CBM (Condition-Based Maintenance) has increasingly drawn attention in industry because of its many benefits. CBM Problem Is characterized as a state-dependent scheduling model that demands simultaneous maintenance actions, each for an attribute that influences on machine condition. This problem is very hard to solve within conventional Markov decision process framework. In this paper, we present an intelligent machine maintenance scheduler, for which a new incremental decision tree learning method as evolutionary system identification model and shortest path problem as schedule generation model are developed. Although our approach does not guarantee an optimal scheduling policy in mathematical viewpoint, we verified through simulation based experiment that the intelligent scheduler is capable of providing good scheduling policy that can be used in practice.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.6
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• pp.241-251
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• 2002

The effect of sensor faults in direct torque control(DTC) based induction motor drives is analyzed and a new Instrument fault detection isolation scheme(IFDIS) is proposed. The proposed IFDIS, which operated in real-time, detects and isolates the incipient fault(s) of speed sensor and current sensors that provide the feedback information. The scheme consists of an adaptive gain scheduling observer as a residual generator and a special sequential test logic unit. The observer provides not only the estimate of stator flux, a key variable in DTC system, but also the estimates of stator current and rotor speed that are useful for fault detection. With the test logic, the IFDIS has the functionality of fault isolation that only multiple estimator based IFDIS schemes can have. Simulation results for various type of sensor faults show the detection and isolation performance of the IFDIS and the applicability of this scheme to fault tolerant control system design.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.12
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• pp.8-14
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• 2015

An effective way to ensure that LEDs produce wanted light output is to use a current driving topology, because the brightness of LEDs is directly related to their current. However, this topology may lead to the lifetime shortening of a illumination system because over-currents may flow through non-damaged LEDs in case some LEDs are damaged. This paper presents an adaptive current control circuits for LEDs, which protect LEDs in a good state by limiting the driving currents according to the number of damaged ones. The proposed control circuits consist of a simple constant-current driver and a micro-controller which monitors the voltage of LED array without any auxiliary current sensors for fault diagnosis. And the driving current is automatically controlled into 6-levels according to the number of failures.

• Journal of Biomedical Engineering Research
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• v.27 no.1
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• pp.6-13
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• 2006

Ultrasound visualization is a typical diagnosis method to examine organs, soft tissues and fetus data. It is difficult to visualize ultrasound data because the quality of the data might be degraded by artifact and speckle noise, and gathered with non-linear sampling. Rendering speed is too slow since we can not use additional data structures or procedures in rendering stage. In this paper, we use several visualization methods for fast rendering of ultrasound data. First method, denoted as adaptive ray sampling, is to reduce the number of samples by adjusting sampling interval in empty space. Secondly, we use early ray termination scheme with sufficiently wide sampling interval and low threshold value of opacity during color compositing. Lastly, we use bilinear interpolation instead of trilinear interpolation for sampling in transparent region. We conclude that our method reduces the rendering time without loss of image quality in comparison to the conventional methods.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.165-170
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• 2021

Discrete event systems interact with the external environment to decide which action plan is adequate. Some of these interactions are not predictable in the modelling phase and require consequently an adaptation of the system to the metamorphosed behavior of the environment. One of the challenging issues is to guarantee safety behavior when failures tend to derive the system from normal status. In this paper we propose a framework to combine diagnose technique with adaptive control to avoid unsafe sate an maintain the normal behavior as long as possible.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.153-159
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• 2022

Plain radiographic analysis is the initial imaging modality for suspected small bowel obstruction. Among the many features that affect the diagnosis of small bowel obstruction (SBO), the presence of gas-filled or fluid-filled small bowel loops is the most salient feature that can be automatized by computer vision algorithms. In this study, we compare three frequently applied pixel-clustering algorithms for extracting gas-filled areas without human intervention. In a comparison involving 40 suspected SBO cases, the Possibilistic C-Means and Fuzzy C-Means algorithms exhibited initialization-sensitivity problems and difficulties coping with low intensity contrast, achieving low 72.5% and 85% success rates in extraction. The Adaptive Resonance Theory 2 algorithm is the most suitable algorithm for gas-filled region detection, achieving a 100% success rate on 40 tested images, largely owing to its dynamic control of the number of clusters.

• Electrical & Electronic Materials
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• v.11 no.11
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• pp.1-8
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• 1998

This paper presents an arificial neuro-fuzzy technique based prtial discharge (PD) pattern classifier to power system application. This may require a complicated analysis method employ -ing an experts system due to very complex progressing discharge form under exter-nal stress. After referring briefly to the developments of artificical neural network based PD measurements, the paper outlines how the introduction of new emerging technology has resulted in the design of a number of PD diagnostic systems for practical applicaton of residual lifetime prediction. The appropriate PD data base structure and selection of learning data size of PD pattern based on fractal dimentsional and 3-D PD-normalization, extraction of relevant characteristic fea-ture of PD recognition are discussed. Some practical aspects encountered with unknown stress in the neuro-fuzzy techniques based real time PD recognition are also addressed.

• Current Optics and Photonics
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• v.8 no.2
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• pp.183-191
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• 2024

High-resolution retinal imaging based on adaptive optics (AO) is important for early diagnosis related to retinal diseases. However, in practical applications, closed-loop AO correction takes a relatively long time, and traditional open-loop correction methods have low accuracy in correction, leading to unsatisfactory imaging results. In this paper, a SH-U-net-based open-loop AO wavefront correction method is presented for a retinal AO imaging system. The SH-U-net builds a mathematical model of the entire AO system through data training, and the Root mean square (RMS) of the distorted wavefront is 0.08λ after correction in the simulation. Furthermore, it has been validated in experiments. The method improves the accuracy of wavefront correction and shortens the correction time.