• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.89-96
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• 2010

In this paper, we proposed a method about improving face tracking efficiency of face detection for AF system using the faces to the ROI. The conventional face detection system detecting faces based skin color uses the ratio of skin pixels of the present frame to detected face regions of the past frame to track the faces. The tracking method is superior in the stability of the regions but it is inferior in the face tracking efficiency. We proposed a face tracking method using the area of the overlapping region in the detected face regions of the past frame and the present frame to improve the tracking efficiency. The proposed face tracking efficiency demonstration was performed by making a film of face detection with face tracking in real-time and using the moving traces of the detected faces.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.321-325
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• 2009

The detection process of defective tags in most of Korean domestic RFID manufacturing companies is handled or treated by on-hand processing after the job of chip bonding, so it has been requesting to reduce the time and cost for manufacturing of RFID tags. Therefore, in this paper, we design and implement the system to perform the functionality of detection of defective tags after the process of chip bonding, and so provide the basis of a related software to establish the foundation of a automation system for the detection of defected RFID tags which is requested in the related Korean domestic industrial field. The developed system in this paper shows the enhancement of 700% in processing speed and 100% in detection rate of defective tags, comparing to the method of on-hand processing.

• Korean Chemical Engineering Research
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• v.58 no.3
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• pp.408-415
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• 2020

In this study, the AE-SOM method, which combines auto-encoder and self-organizing map, is used to detect and diagnose faults in EVA production process. Then, the fault propagation pathways are identified using Granger causality test. One year and seven months of operation data were obtained to detect faults of the process, and the process variables of the autoclave reactor are mainly analyzed. In the data pretreatment process, the data are standardized and 200 samples of each grade are randomly chosen to obtain a fault detection model. After that, the best matching unit (BMU) of each grade is confirmed by applying AE-SOM. The faults are determined based on each BMU. When a fault is found, the most causative variable of the fault is identified by using a contribution plot, and the fault propagation pathway is identified by Granger causality test. The prognostic of the two shutdowns is detected, and the fault propagation pathway caused by the faulty variable was analyzed.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.31-38
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• 2022

This paper applies an expert independent unsupervised neural network learning-based multivariate time series data analysis model, MSCRED(Multi-Scale Convolutional Recurrent Encoder-Decoder), and to overcome the limitation, because the MCRED is based on Auto-encoder model, that train data must not to be contaminated, by using learning data sampling technique, called Subset Sampling Validation. By using the vibration data of power plant equipment that has been labeled, the classification performance of MSCRED is evaluated with the Anomaly Score in many cases, 1) the abnormal data is mixed with the training data 2) when the abnormal data is removed from the training data in case 1. Through this, this paper presents an expert-independent anomaly diagnosis framework that is strong against error data, and presents a concise and accurate solution in various fields of multivariate time series data.

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.13-22
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• 2020

This paper presents an adaptive feedback based actuator fault detection and tolerant control algorithms for longitudinal functional safety of autonomous driving. In order to ensure the functional safety of autonomous vehicles, fault detection and tolerant control algorithms are needed for sensors and actuators used for autonomous driving. In this study, adaptive feedback control algorithm to compute the longitudinal acceleration for autonomous driving has been developed based on relationship function using states. The relationship function has been designed using feedback gains and error states for adaptation rule design. The coefficients in the relationship function have been estimated using recursive least square with multiple forgetting factors. The MIT rule has been adopted to design the adaptation rule for feedback gains online. The stability analysis has been conducted based on Lyapunov direct method. The longitudinal acceleration computed by adaptive control algorithm has been compared to the actual acceleration for fault detection of actuators used for longitudinal autonomous driving.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1276-1279
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• 1996

Reclaimer in the raw material yard is being used to dig iron and coal so that they transfer to main blast furnace. A newly automatic system was developed and tested in the raw yard of Kwangyang iron making. The concept of the proposed system is based on the 3-dimensional detection of pile and auto-landing on the surface it.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.133-142
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• 2012

This paper presents a salient region detection algorithm for auto-focusing based on the characteristics of a human's visual attention. To describe the saliency at the local, regional, and global levels, this paper proposes a set of novel features including multi-scale local contrast, variance, center-surround entropy, and closeness to the center. Those features are then prioritized to produce a saliency map. The major advantage of the proposed approach is twofold; i) robustness to changes in focus and ii) low computational complexity. The experimental results showed that the proposed method outperforms the existing low-level feature-based methods in the sense of both robustness and accuracy for auto-focusing.

• Journal of Convergence Society for SMB
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• v.4 no.1
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• pp.31-39
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• 2014

PID auto-tuning controller was designed via fuzzy logic. Typical values such as error and error derivative feedback were changed as heuristic expressions, and they determine PID gain through fuzzy logic and defuzzification process. Fuzzy procedure and PID controller design were considered separately, and they are combined and analyzed. Obtained auto-tuning PID controller by Fuzzy Logic showed the ability for less than 3rd order plant control. We also applied to reference tracking problem with the designed auto-tuning scheme.

• Journal of Biomedical Engineering Research
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• v.30 no.2
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• pp.113-121
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• 2009

This study aims at designing and evaluating light source devices that can stably generate light with various wavelengths in order to make possible PDD using a photosensitizer and diagnosis using auto-fluorescence. The light source was a Xenon lamp and filter wheel, composed of an optical output control through Iris and filters with several wavelength bands. It also makes the inducement of auto-fluorescence possible because it is designed to generate a wavelength band of 380-420nm, 430-480nm, and 480-560nm. The transmission part of the light source was developed to enhance the efficiency of light transmission. To evaluate this light source, the characteristics of light output and wavelength band were verified. To validate the capability of this device as PDD, the detection of auto-fluorescence using mouse models was performed.

• Journal of information and communication convergence engineering
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• v.13 no.3
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• pp.189-196
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• 2015

In this paper, we present a rotating auto-zeroing offset cancellation technique, which can improve the performance of touch screen sensing circuits. Our target touch screen detection method employs multiple continuous sine waves to achieve a high speed for large touch screens. While conventional auto-zeroing schemes cannot handle such continuous signals properly, the proposed scheme does not suffer from switching noise and provides effective offset cancellation for continuous signals. Experimental results show that the proposed technique improves the signal-to-noise ratio by 14 dB compared to a conventional offset cancellation scheme. For the realistic simulation results, we used Cadence SPECTRE with an accurate TSP model and noise source. We also applied an asymmetric device size (10% MOS size mismatch) to the OP Amp design in order to measure the effectiveness of offset cancellation. We implemented the proposed circuit as part of a touch screen controller system-on-chip by using a Magnachip/SK Hynix 0.18-µm complementary metal-oxide semiconductor (CMOS) process.