• Fisheries and Aquatic Sciences
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• v.20 no.1
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• pp.1.1-1.7
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• 2017

A survey was conducted to investigate the presence of epiphytic organisms in four kelp Saccharina japonica farms in the coastal area of Korea from 2014 to 2015. Of 740 kelp samples that were taken, 208 exhibited six kinds of epiphytic organisms, including hydroid (detection rate: 11.6%), bryozoan (6.4%), polychaete (3.4%), algae (3.2%), caprellid (3%), and oyster (0.5%). The infestation rate for hydroid, bryozoan, and polychaete was significantly higher in the Wando farm, Busan farm, and Pohang farm, respectively. Epiphytic organisms were generally observed during May to September and not January to April, indicating that their infestation was significantly higher when the water had a higher temperature. The histopathogical examination revealed that hydroid and bryozoan organisms were attached on the cuticula of the thallus while some algae were attached on the cuticula of the thallus or had penetrated the epidermis. These results indicate that hydroid and bryozoan were the most predominant epiphytic organisms in Korean kelp farms, even though the infested thallus had not been broken.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.149-157
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• 2019

In case of reading passport using a smart phone in contrast with a dedicated passport reading system, MRZ(Machine Readable Zone) character recognition can be hard when the character strokes were broken, touched or blurred according to the lighting condition, and the position and size of MRZ character lines were varied due to the camera distance and angle. In this paper, the effective recognition algorithm of the passport MRZ information using a combined neural network recognizer of CNN(Convolutional Neural Network) and ANN( Artificial Neural Network), is proposed under the various sized and skewed passport images. The MRZ line detection using connected component analysis algorithm and the skew correction using perspective transform algorithm are also designed in order to achieve effective character segmentation results. Each of the MRZ field recognition results is verified by using five check digits for deciding whether retrying the recognition process of passport MRZ information or not. After we implement the proposed recognition algorithm of passport MRZ information, the excellent recognition performance of the passport MRZ information was obtained in the experimental results for PC off-line mode and smart phone on-line mode.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1A
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• pp.44-50
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• 2007

In typical MC-CDMA systems, different frequency-domain scrambling codes are randomly chosen from a given code set and then assigned to different subscriber stations using the same subcarrier set. When orthogonal codes are employed for the frequency-domain scrambling, the choice of the scrambling code does not affect the detection performance if the timing and frequency synchronizations are perfect and the channel characteristic is flat. However, in practical cases, inter-code interference often appears due to the broken code orthogonality. In this paper, the optimal order of allocating the orthogonal frequency-domain scrambling codes to new subscriber stations is derived under non-negligible timing offsets in MC-CDMA system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.2
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• pp.75-84
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• 2008

Recently, the straightforward CRT-RSA was shown to be broken by fault attacks through many experimental results. In this paper, we analyze the fault attacks against CRT-RSA and their countermeasures, and then propose a new fault infective method resistant to the various fault attacks on CRT-RSA. In our CRT-RSA algorithm, if an error is injected in exponentiation with modulo p or q, then the error is spreaded by fault infective computation in CRT recombination operation. Our countermeasure doesn't have extra error detection procedure based on decision tests and doesn't use public parameter such as e. Also, the computational cost is effective compared to the previous secure countermeasures.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.23-31
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• 2020

This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

• Parasites, Hosts and Diseases
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• v.56 no.1
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• pp.87-91
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• 2018

Morphological and molecular characteristics of spirometrid tapeworms, Spirometra decipiens, were studied, which were recovered from a heavily infected stray cat road-killed in Eumseong-gun, Chungcheongbuk-do (Province), the Republic of Korea (=Korea). A total of 134 scolices and many broken immature and mature proglottids of Spirometra tapeworms were collected from the small intestine of the cat. Morphological observations were based on 116 specimens. The scolex was 22.8-32.6 mm (27.4 mm in average) in length and small spoon-shape with 2 distinct bothria. The uterus was coiled 3-4 times, the end of the uterus was ball-shaped, and the vaginal aperture shaped as a crescent moon was closer to the cirrus aperture than to the uterine aperture. PCR amplification and direct sequencing of the cox1 target fragment (377 bp in length and corresponding to positions 769-1,146 bp of the cox1 gene) were performed using total genomic DNA extracted from 134 specimens. The cox1 sequences (377 bp) of the specimens showed 99.0% similarity to the reference sequence of S. decipiens and 89.3% similarity to the reference sequence of S. erinaceieuropaei. In the present study, we report a stray cat heavily infected with S. decipiens identified by mitochondrial cox1 sequence analysis and morphological examinations of the adult worms.

• Korean Journal of Materials Research
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• v.21 no.2
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• pp.89-94
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• 2011

In this work, fabrication and electrochemical analysis of an individual multi-walled carbon nanotube (MWNT) electrode are carried out to confirm the applicability of electrochemical sensing. The reactive ion etching (RIE) process is performed to obtain sensitive MWNT electrodes. In order to characterize the electrochemical properties, an individual MWNT is cut by RIE under oxygen atmosphere into two segments with a small gap: one segment is applied to the working electrode and the other is used as a counter electrode. Electrical contacts are provided by nanolithography to the two MWNT electrodes. Dopamine is specially selected as an analytical molecule for electrochemical detection using the MWNT electrode. Using a quasi-Ag/AgCl reference electrode, which was fabricated by us, the nanoelectrodes are subjected to cyclic voltammetry inside a $2{\mu}L$ droplet of dopamine solution. In the experiment, RIE power is found to be a more effective parameter to cut an individual MWNT and to generate "broken" open state, which shows good electrochemical performance, at the end of the MWNT segments. It is found that the pico-molar level concentration of analytical molecules can be determined by an MWNT electrode. We believe that the MWNT electrode fabricated and treated by RIE has the potential for use in high-sensitivity electrochemical measurement and that the proposed scheme can contribute to device miniaturization.

• Journal of the Korean Society of Safety
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• v.12 no.3
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• pp.166-172
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• 1997

The BEF on the radial distribution line refers to a class of ground faults in which the load-side power line only is grounded, with the distribution line broken into two parts, the source-side and the load-side. Because its mechanism is remarkably different from that of other earth faults, the fault current is very low, and then difficult to detect the BEF. Thus, it is necessary to analyze its properties and to find an appropriate method that can economically protect the BEF of nonautomation area in the substation. As a result of analyzing the BEF data obtained by the RTDS, EMTP simulation, and the field test data of ETSA, we believe that it is the dominant factor in distinguishing the BEF from normal conditions by a criterion value that is appropriately handled from the zero-sequence current. Thus, with this criterion value, a BEF detecting algorithm is constructed which measures the variations of the zero-sequence current and processes then properly so as to make the fault decision. To prove the accuracy of this algorithm, it is compared with the field test data of ETSA under various conditions. The results show that the proposed algorithm is accurate.

• Journal of IKEEE
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• v.2 no.1 s.2
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• pp.34-41
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• 1998

An integrated circuit for magnetic stripe storage system is implemented. All the analog and digital circuits are integrated in one chip. The analog block contains preamplifier, peak detecter, comparator and reference generater. And digital block includes reference window signal generater, up/down counter for F/2F signal measurement, bit-error detection logic, and control logic. Both the encoding and decoding functions for F/2F signal processing are provided. An AGC(automatic gain control) circuit which was included in conventional circuits is eliminated due to optimized circuit design. Misreading prevention circuits are also proposed by fixing up new reference bit when broken bits are detected. The prototype chip is implemented using $0.8{\mu}m$ N-well CMOS technology and operates from 3.3 V to 7.5 V of supply voltage. It occupies a die area of $3.04mm^2(1.6mm{\times}1.9mm)$ and dissipates 8 mW with a 5 V supply voltage.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.23-30
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• 2012

This paper proposes an improved steganalysis method to detect the existence of secret message. Firstly, we magnify the small stego noise by multiplying the speckle noise to a given image and then we estimate the denoised image by using the soft thresholding method. Because the noises are not perfectly eliminated, some noises exist in the estimated cover image. If the given image is the cover image, then the remained noise will be very small, but if it is the stego image, the remained noise will be relatively large. The parent-child relationship in the wavelet domain will be slighty broken in the stego image. From this characteristic, we extract the joint statistical moments from the difference image between the given image and the denoised image. Additionally, four statistical moments are extracted from the denoised image for the proposed steganalysis method. All extracted features are used as the input of MLP(multilayer perceptron) classifier. Experimental results show that the proposed scheme outperforms previous methods in terms of detection rates and accuracy.