• Journal of Power Electronics
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• v.13 no.5
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• pp.884-895
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• 2013

In this paper, the Fourier-based PLL (Phase-locked Loop) is introduced with a new structure, capable of selective harmonic detection in single and three-phase systems. The application of the FB-PLL to harmonic detection is discussed and a new model applicable to three-phase systems is introduced. An analysis of the convergence of the FB-PLL based on a linear model is presented. Simulation and experimental results are included for performance analysis and to support the theoretical development. The decomposition of an input signal in its harmonic components using the Fourier theory is based on previous knowledge of the signal fundamental frequency, which cannot be easily implemented with input signals with varying frequencies or subjected to phase-angle jumps. In this scenario, the main contribution of this paper is the association of a phase-locked loop system, with a harmonic decomposition and reconstruction method, based on the well-established Fourier theory, to allow for the tracking of the fundamental component and desired harmonics from distorted input signals with a varying frequency, amplitude and phase-angle. The application of the proposed technique in three-phase systems is supported by results obtained under unbalanced and voltage sag conditions.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1125-1136
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• 2010

Lately there exist increasing demands for online abnormality monitoring over trajectory stream, which are obtained from moving object tracking devices. This problem is challenging due to the requirement of high speed data processing within limited space cost. In this paper, we present a FADA (Fuzzy Anomaly Detection Algorithm) which constructs normal profile by computing mobility feature information from the GPS (Global Positioning System) logs of mobile devices in MANETs (Mobile Ad-hoc Networks), computes a fuzzy dissimilarity between the current mobility feature information of the mobile device and the mobility feature information in the normal profile, and detects effectively the anomaly behaviors of mobile devices on the basis of the computed fuzzy dissimilarity. The performance of proposed FADA is evaluated through simulation.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.24 no.4
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• pp.484-491
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• 2014

Objectives: An image processing program for asbestos fibers analyzing the gradient components and partial linearity was developed in order to accurately segment fibers. The objectives were to increase the accuracy of counting through the formulation of the size and shape of fibers and to guarantee robust fiber detection in noisy backgrounds. Methods: We utilized samples mixed with sand and sepiolite, which has a similar structure to asbestos. Sample concentrations of 0.01%, 0.05%, 0.1%, 0.5%, 1%, 2%, and 3%(w/w) were prepared. The sand used was homogenized after being sieved to less than $180{\mu}m$. Airborne samples were collected on MCE filters by utilizing a personal pump with 2 L/min flow rate for 30 minutes. We used the NIOSH 7400 method for pre-treating and counting the fibers on the filters. The results of the NIOSH 7400 method were compared with those of the image processing program. Results: The performance of the developed algorithm, when compared with the target images acquired by PCM, showed that the detection rate was on average 88.67%. The main causes of non-detection were missing fibers with a low degree of contrast and overlapping of faint and thin fibers. Also, some duplicate countings occurred for fibers with breaks in the middle due to overlapping particles. Conclusions: An image detection algorithm that could increase the accuracy of fiber counting was developed by considering the direction of the edge to extract images of fibers. It showed comparable results to PCM analysis and could be used to count fibers through real-time tracking by modeling a branch point to graph. This algorithm can be utilized to measure the concentrations of asbestos in real-time if a suitable optical design is developed.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.731-736
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• 2008

In this paper, we propose the movement detection algorithm by using virtual skeleton model. To do this, first, we eliminate error values by using conventioanl method based on RGB color model and eliminate unnecessary values by using the HSI color model. Second, we construct the virtual skeleton model with skeleton information of 10 peoples. After matching this virtual model to original image, we extract the real head silhouette by using the proposed circle searching method. Third, we extract the object by using the mean-shift algorithm and this head information. Finally, we validate the applicability of the proposed method through the various experiments in a complex environments.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.40 no.1
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• pp.78-85
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• 2004

The new biotelemetry method and system that the installation and the treatment of equipment is convenient and the instantaneously detailed position of the fish attached a pinger is able to track comparatively easily had been developed, an practicality of it were verified in the water tank and the small sea port through the tracking of fish. The biotelemetry method had been gotten the three dimensional locations of fish to the receiving transducer by combining of the super short base line (SSBL) method to detect the direction of pinger and the pinger synchronizing method to measure the range from receiving transducer to pinger. The receiving system had been designed to realize the high precision or wide detection range by application of the basic design method for receiving system of biotelemetry and the hydrophone array configuration. From tracking test of carp in the water tank, the migration course and the velocity of carp was investigated and the observed migration course was compared with measurement. The measured migration course of carp coincided with the observation in the main and the position of carp was able to track three dimensionally. The velocity of carp measured by the moving average method was 11.2cm/s. From tracking test of yellowtail in the small sea port, the migration course and the velocity of yellowtail was investigated at natural condition. The position of yellowtail was able to track three dimensionally and the velocity of it measured by moving average method was 43.9cm/s.

• Journal of KIISE:Software and Applications
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• v.36 no.3
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• pp.236-243
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• 2009

With advances in topic detection and tracking(TDT), automatic trend analysis from a collection of time-stamped documents, like patents, news papers, and blog pages, is a challenging research problem. Past research in this area has mainly focused on showing a trend line over time of a given concept by measuring the strength of trend-associated term frequency information. for detection of emerging trends, either a simple criterion such as frequency change was used, or an overall comparison was made against a training data. We note that in order to show most salient trends detected among many possibilities, it is critical to devise a ranking function. To this end, we define four properties(change, persistency, stability and volume) of trend lines drawn from frequency information, to quantify various aspects of trends, and propose a method by which trend lines can be ranked. The properties are examined individually and in combination in a series of experiments for their validity using the ranking algorithm. The results show that a judicious combination of the four properties is a better indicator for salient trends than any single criterion used in the past for ranking or detecting emerging trends.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.112-118
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• 2009

Skin color segmentation techniques have been widely utilized for face/hand detection and tracking in many applications such as a diagnosis system using facial information, human-robot interaction, an image retrieval system. In case of a video image, it is common that the skin color model for a target is updated every frame for the robust target tracking against illumination change. As for a single image, however, most of studies employ a fixed skin color model which may result in low detection rate or high false positive errors. In this paper, we propose a novel method for effective skin color segmentation in a single image, which modifies the conditions for skin color segmentation iteratively by the image feedback of segmented skin color region in a given image.

• Journal of Energy Engineering
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• v.15 no.3 s.47
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• pp.181-187
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• 2006

This paper is proposed to a solar cell power system used in fire emergency equipment. Also it is designed with a high efficiency power converter in order to increase efficiency of power system. The controlling switches used in DC-DC booster chopper and DC-AC inverter are operated with soft switching, which is applied to resonant circuit method to reduce switching loss. The result is that the system gets to high efficiency. In this paper, A detection circuit of maximum power point of solar cell is described in this paper. And the performance evaluations for the photovoltaic power system of high efficiency are examined by the analysis of a new tracking controller with a maximum power $P_{max}$ detection of solar cell.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1A
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• pp.65-75
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• 2009

In Wireless Sensor Network, the sensor node localization is important issue for information tracking, event detection, routing. Generally, in wireless sensor network localization, the absolute positions of certain anchor nodes are required based on the use of global positioning system, then all the other nodes are approximately localized using various algorithms based on a coordinate system of anchor DV-Hop is a localized, distributed, hop by hop positioning algorithm in wireless sensor network where only a limited fraction of nodes have self positioning capability. However, instead of uniformly distributed network, in anisotropic network with possible holes, DV-Hop's performance is very low. To address this issue, we propose Group based DV-Hop (GDV-Hop) algorithm. Best contribution of GDV-Hop is that it performs localization with reduced error compared with DV-Hop in anisotropic network.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.159-164
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• 2019

Detecting wildfire using only color in image information is a very difficult issue. This paper proposes an algorithm to detect forest fire area by analyzing color and motion of the area in the video including forest fire. The proposed algorithm removes the background region using the Gaussian Mixture based background segmentation algorithm, which does not depend on the lighting conditions. In addition, the RGB channel is changed to an HSV channel to extract flame candidates based on color. The extracted flame candidates judge that it is not a flame if the area moves while labeling and tracking. If the flame candidate areas extracted in this way are in the same position for more than 2 minutes, it is regarded as flame. Experimental results using the implemented algorithm confirmed the validity.