• Journal of IKEEE
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• v.22 no.3
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• pp.539-547
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• 2018

Grid-connected inverter is required to cut off the power supplied to the grid at the islanding condition, immediately. For this reason, an islanding detection is an indispensable function for grid-connected distributed generation system. Slip-Mode frequency Shift (SMS) islanding detection method is very popular method to determine the grid state. SMS method supplies the reactive power to the load according to the grid frequency. In the islanding condition of grid, this injected reactive power pulls out the grid frequency from the allowable range, then the inverter system can detect the islanding condition of the grid. The SMS method can detect the islanding state well and does not generate any harmonics of the grid current. However, the reactive power would be generated and the power quality is reduced even though the grid is not islanding condition, but normal condition. In this paper, a modified SMS method is proposed to remove the reactive power in the normal condition. The performance of the proposed method is evaluated by 600W single phase inverter experimental results.

• Journal of the Korean Society for Railway
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• v.11 no.5
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• pp.477-481
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• 2008

This paper dealt with a detection method of series arc existence which is a symptom of electric fires in low-voltage system. The proposed detection circuit consists of a high-pass filter with a low cut-off frequency of 3kHz to attenuate power frequency voltage by 80 dB and an active band-pass filter with a center frequency of 4kHz to detect only the series arc signals. The performance of the circuit was evaluated in a phase-controlled incandescent lamp as a non-linear load and an inverted-fed induction motor as a high frequency load by using the arc generator specified in UL1699. From the experimental results, it was confirmed that the proposed method solved the detection error, which is being the most problem, by discriminating the series arc signal even in non-linear and high frequency loads.

• Journal of Microbiology and Biotechnology
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• v.27 no.2
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• pp.219-225
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• 2017

An aqueous chlorine dioxide ($ClO_2$) treatment combined with highly activated calcium oxide (CaO) and mild heat was tested for inactivating naturally existing bacteria and Escherichia coli O157:H7 inoculated on fresh-cut kale. Kale samples were treated with different concentrations of $ClO_2$ (10, 30, and 50 ppm), CaO (0.01%, 0.05%, 0.1%, and 0.2%), and mild heat ($25^{\circ}C$, $45^{\circ}C$, $55^{\circ}C$, and $65^{\circ}C$) as well with combinations of 30 or 50 ppm $ClO_2$ and 0.2% CaO at $55^{\circ}C$ for 3 min. An increasing concentration of $ClO_2$ and CaO significantly reduced the microbial population compared with the control. In addition, mild heating at $55^{\circ}C$ elicited greater microbial reduction than the other temperatures. A combined treatment of 50 ppm $ClO_2$ and 0.2% CaO at $55^{\circ}C$ reduced the population of naturally existing bacteria on kale by 3.10 log colony forming units (CFU)/g, and the counts of E. coli O157:H7 were below the detection limit (1 log CFU/g). In addition, no significant differences in the Hunter color values were evident in any treatment during storage. Therefore, a combined treatment of $ClO_2$ and active CaO at $55^{\circ}C$ can be an effective sanitizing method to improve the microbiological safety of fresh-cut kale without affecting its quality.

• Parasites, Hosts and Diseases
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• v.50 no.1
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• pp.15-21
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• 2012

In Iran, $Plasmodium$ $vivax$ is responsible for more than 80% of the infected cases of malaria per year. Control interventions for vivax malaria in humans rely mainly on developed diagnostic methods. Recombinant $P.$ $vivax$ apical membrane antigen-1 (rPvAMA-1) has been reported to achieve designing rapid, sensitive, and specific molecular diagnosis. This study aimed to perform isolation and expression of a rPvAMA-1, derived from Iranian patients residing in an endemic area. Then, the diagnostic efficiency of the characterized Iranian PvAMA-1 was assessed using an indirect ELISA method. For this purpose, a partial region of AMA-1 gene was amplified, cloned, and expressed in pET32a plasmid. The recombinant $His-tagged$ protein was purified and used to coat the ELISA plate. Antibody detection was assessed by indirect ELISA using rPvAMA-1. The validity of the ELISA method for detection of anti-$P.$ $vivax$ antibodies in the field was compared to light microscopy on 84 confirmed $P.$ $vivax$ patients and compared to 84 non-$P.$ $vivax$ infected individuals. The ELISA cut-off value was calculated as the mean+2SD of OD values of the people living in malaria endemic areas from a south part of Iran. We found a cut-off point of OD=0.311 that showed the best correlation between the sera confirmed with $P.$ $vivax$ infection and healthy control sera. A sensitivity of 81.0% and specificity of 84.5% were found at this cut off titer. A good degree of statistical agreement was found between ELISA using rPvAMA-1 and light microscopy (0.827) by Kappa analysis.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.2
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• pp.43-52
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• 2017

Pattern Analysis is One of the Most Important Techniques in the Signal and Image Processing and Text Mining Fields. Discrete Fourier Transform (DFT) is Generally Used to Analyzing the Pattern of Signals and Images. We thought DFT could also be used on the Analysis of Text Patterns. In this Paper, DFT is Firstly Adapted in the World to the Sentence Plagiarism Detection Which Detects if Text Patterns of a Document Exist in Other Documents. We Signalize the Texts Converting Texts to ASCII Codes and Apply the Cross-Correlation Method to Detect the Simple Text Plagiarisms such as Cut-and-paste, term Relocations and etc. WordNet is using to find Similarities to Detect the Plagiarism that uses Synonyms, Translations, Summarizations and etc. The Data set, 2013 Corpus, Provided by PAN Which is the One of Well-known Workshops for Text Plagiarism is used in our Experiments. Our Method are Fourth Ranked Among the Eleven most Outstanding Plagiarism Detection Methods.

• Journal of the Korea Computer Graphics Society
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• v.25 no.5
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• pp.11-20
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• 2019

With the development of deep learning technology, research is being actively carried out on user-friendly interfaces that are suitable for use in virtual reality or augmented reality applications. To support the interface using the user's hands, this paper proposes a deep learning-based fingertip detection method to enable the tracking of fingertip coordinates to select virtual objects, or to write or draw in the air. After cutting the approximate part of the corresponding fingertip object from the input image with the Grad-CAM, and perform the convolution neural network with Atrous Convolution for the cut image to detect fingertip location. This method is simpler and easier to implement than existing object detection algorithms without requiring a pre-processing for annotating objects. To verify this method we implemented an air writing application and showed that the recognition rate of 81% and the speed of 76 ms were able to write smoothly without delay in the air, making it possible to utilize the application in real time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1266-1271
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• 2022

Cats have strong wildness so they have a characteristic of hiding diseases well. The disease may have already worsened when the guardian finds out that the cat has a disease. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia, polyuria, and frequent urination more quickly. In this paper, 1) Efficient version of DeepLabCut for pose estimation, 2) YOLO v4 for object detection, 3) LSTM is used for behavior prediction, and 4) BoT-SORT is used for object tracking running on an artificial intelligence device. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the server system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.165-167
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• 2022

The proportion of cat cats among companion animals has been increasing at an average annual rate of 25.4% since 2012. Cats have strong wildness compared to dogs, so they have a characteristic of hiding diseases well. Therefore, when the guardian finds out that the cat has a disease, the disease may have already worsened. Symptoms such as anorexia (eating avoidance), vomiting, diarrhea, polydipsia, and polyuria in cats are some of the symptoms that appear in cat diseases such as diabetes, hyperthyroidism, renal failure, and panleukopenia. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia (drinking a lot of water), polyuria (a large amount of urine), and frequent urination (urinating frequently) more quickly. In this paper, 1) Efficient version of DeepLabCut for posture prediction running on an artificial intelligence server, 2) yolov4 for object detection, and 3) LSTM are used for behavior prediction. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the main server system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.25-31
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• 2014

Korean grammar checkers typically detect context-dependent errors by employing heuristic rules; these rules are formulated by language experts and consisted of lexical items. Such grammar checkers, unfortunately, show low recall which is detection ratio of errors in the document. In order to resolve this shortcoming, a new error-decision rule-generalization method that utilizes the existing KorLex thesaurus, the Korean version of Princeton WordNet, is proposed. The method extracts noun classes from KorLex and generalizes error-decision rules from them using the Tree Cut Model and information-theory-based MDL (minimum description length).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.55-61
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• 2015

Today, IT technology provide convenience to many people. Smartphone era is opened, and market environment is changing rapidly. Pornography market is active by using smartphone use free internet. Many people access mobile harmful site of USA and Japan. App store of the apple has been cut off the porn service, but access block to mobile Web page is an impossible situation. In this paper, we proposed the harmful image detection method of using skin and non skin features to detect harmful image. Our proposed method can provide enough performance than previous method.