• Smart Media Journal
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• v.2 no.4
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• pp.9-19
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• 2013

This paper gives a review on three illumination issues of face tracking on smart phones: dark scenes, sudden lighting change and backlit effect. First, we propose a fast and robust face tracking method utilizing continuous adaptive mean shift algorithm (CAMSHIFT) and CbCr skin locus. Initially, the skin locus obtained from training video data. After that, a modified CAMSHIFT version based on the skin locus is accordingly provided. Second, we suggest an enhancement method to increase the chance of detecting faces, an important initialization step for face tracking, under dark illumination. The proposed method works comparably with traditional CAMSHIFT or particle filter, and outperforms these methods when dealing with our public video data with the three illumination issues mentioned above.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.10
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• pp.67-76
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• 2008

In this research, a simple technique for designing PID controller, which guarantees robust stability for two-mass systems with parameter uncertainties as well as rigid-body behavior and zero steady-state error,is described. As well, such a PID controller is designed to mate two important frequencies, at which the given system is excited, very close so that an appropriate reference profile generated by using command shaping techniques can cover those two frequencies. Root-locus analysis. which shows traces of closed-loop poles for the given system, is used to design this PID controller. Finally, feedforward controller is added to improve tracking performance of the closed-loop system. Simulation for a system with a flexible mode and parameter uncertainties is executed to prove the feasibility of this technique.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.91-98
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• 2001

In this paper, center detection and motion analysis of a moving object are studied. Kohonen's self-organizing neural network models are used for the moving objects tracking and time delay neural networks are used for dynamic characteristic analysis. Instead of objects brightness, neuron projections by Kohonen Networks are used. The motion of target objects can be analyzed by using the differential neuron image between the two projections. The differential neuron image which is made by two consecutive neuron projections is used for center detection and moving objects tracking. The two differential neuron images which are made by three consecutive neuron projections are used for the moving trajectory estimation. It is possible to distinguish 8 directions of a moving trajectory with two frames and 16 directions with three frames.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.4
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• pp.379-384
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• 1999

In this paper, we present a new time-varying sliding surface to achieve fast and robust tracking of higher-order uncertain systems. The surface passes through an initial error, and afterwards, it moves towards a predetermined target surface by means of a variable named by sliding surface gain and its intercept. Specifically, the sliding surface gain is determined so that its initial value can minimize a shifting distance of the surface and that the system roots in sliding mode can follow certain stable trajectories. The designed sliding mode control forces the system errors to stay always on the proposed surface from the beginning. By this means, the system remains insensitive to system uncertainties and disturbances for the whole time. To illustrate the effectiveness of the proposed method, the comparative study with conventional time-invariant sliding mode control is performed.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.445-447
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• 1998

This paper shows simulation results for stability and performance of two INS/GPS integration systems. First, the code tracking error of GPS receiver is analyzed by spectrum analysis and simulated for the tight and loose INS/GPS integrations. Next, stability of the integrated systems are simulated using root locus method. As loop filter in the GPS receiver, passive filter and active filter are used and compared.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.3
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• pp.403-411
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• 2015

In this paper, we propose a design method for the position and speed controller, current control of a Brushless Direct Current(BLDC) motor using back-stepping design techniques. Further, to stabilize the whole system, and proposes a method for setting the appropriate gain control to improve the tracking performance. By applying the proposed controller to 120W BLDC motors were tested for the ability to follow the position, velocity and current reference. Since the simulation results of the steady state error is within 1%, we were able to show the usefulness of the tracking performance of the proposed controller.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.96-103
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• 2023

This paper presents a robust position tracking controller for a motor used in semiconductor equipment, utilizing the motor angle measurement. Precise position control is challenging due to the presence of uncertainties in various motor applications. The proposed controller consists of a PD (Proportional-Derivative) controller and a PIO (Proportional-Integral Observer) to estimate the system's state and equivalent disturbance compensating for the uncertainties. Since the stability alternates as the observer gain increases, we have investigated it through the closedloop root locus under the system parameters change. The analysis has showed that the inertia of the motor is the main parameter that affects it, and by adjusting the control gain appropriately, the system can be rendered to be stable even when the inertia of the motor changes. The effectiveness of the proposed control algorithm is validated through computer simulations, followed by a comparison of its performance with the results of a previous study.

• Smart Media Journal
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• v.13 no.2
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• pp.85-94
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• 2024

Artificial Intelligence of Things (AIoT), which combines AI and the Internet of Things (IoT), has recently gained popularity. Deep neural networks (DNNs) have achieved great success in many applications. Deploying complex AI models on embedded boards, nevertheless, may be challenging due to computational limitations or intelligent model complexity. This paper focuses on an AIoT-based system for smart sewing automation using edge devices. Our technique included developing a detection model and a decision tree for a sufficient testing scenario. YOLOv5 set the stage for our defective sewing stitches detection model, to detect anomalies and classify the sewing patterns. According to the experimental testing, the proposed approach achieved a perfect score with accuracy and F1score of 1.0, False Positive Rate (FPR), False Negative Rate (FNR) of 0, and a speed of 0.07 seconds with file size 2.43MB.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.952-958
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• 1999

This paper presented the application of GAs as a means of finding optimal solutions over a parameter space in the controller design for a fuzzy control system. The performance can involve a weighted combination of various performance characteristics such as rise-time, settling-time, settling-time, overshoot. The results obtained here are compared with those for a traditional design obtained using the root-locus method. In contrast to traditional methods, the GA-based method does not require the usual mathematical processess or mathematical model of the system. In this paper, the Ga-based Fuzzy control system combining Fuzzy control theory with the GA, that is known to be very effective in the optimization problem, will be proposed The effectiveness of the proposed control system will be demonstrated by computer simulations using task tracking position system in stable and unstable linear systems. It is shown that the GA-based controller is better than the traditional controller used It stable and unstable linear systems.

• Journal of Life Science
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• v.27 no.4
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• pp.464-470
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• 2017

Three Korean native cattle (KNC) and seven exotic breeds (Chikso, Hanwoo, Jeju black, Holstein, Japanese black, Charolais, Angus, Hereford, Simmental, and Cross breed) were characterized by using five microsatellite (MS) markers (INRA30, TGLA325, UMN0803, UMN0905, and UMN0929) from the sex chromosome. Genetic diversity was evaluated across the 10 breeds by using the number of alleles per locus, allele frequency, heterozygosity, and polymorphism information content (PIC) to search for locus and/or breed specific alleles, allowing a rapid and cost-effective identification of cattle samples, avoiding mislabeling of commercial beef. It was divided into two main groups from STRUCTURE analysis, one corresponding to KNC and the other to exotic cattle breeds. These results also showed specific genetic differences between KNC and exotic breeds. Nei's standard genetic distance was calculated and used in the construction of a neighbor-joining tree. Results evidenced a correspondence between genetic distance, breeds' history, and their geographic origin, and a clear separation between KNC and exotic breeds. Overall, this study evidenced that DNA markers can discriminate between domestic and imported beef, contributing to the knowledge on cattle breeds' genetic diversity and relationships by using MS markers of the sex chromosome. These markers would be useful for inhibitory effect about false sales and for building an effective tracking system.