• Journal of Environmental Health Sciences
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• v.40 no.3
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• pp.178-186
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• 2014

Background: This study was conducted to assess health risks in regard to exposure by children to volatile organic compounds (VOCs) in children's products. Methods: Ten VOCs were measured by head-space gas chromatography in children's products, including toys, oil pastels, sign pens, furniture, ball pools, and playmats. We estimated the average daily dose (ADD) via inhalation during the use of these children's products and calculated hazard quotient (HQ) by dividing ADD by reference dose of VOCs. Results: Among the measured VOCs, five compounds were identified in children's products: benzene, ethylbenzene, styrene, toluene, and xylene. The detection rates of VOCs in toys, ball pools, furniture, playmats, sign pens, and oil pastels were 85%, 100%, 100%, 30%, 100%, and 60%, respectively. The maximum levels of VOCs were 0.18 mg benzene/kg in toys, 5.92 mg toluene/kg in playmats, 10.37 mg ethylbenzene/kg in ball pools, 24.85 mg xylene/kg in toys, and 118.29 mg styrene/kg in ball pools. From exposure levels of VOCs in the children's products HQs were calculated within a range of $5.71{\times}10^{-10}$ to $4.77{\times}10^{-4}$. The HQ of xylene was the highest for children aged 0-6 playing on the playmats. However, the HQ via inhalation exposure to VOCs in individual products did not exceed 1.00. Conclusion: Based on the results, it was concluded that the use of these children's products do not pose health risks to children.

• Journal of Embryo Transfer
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• v.24 no.3
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• pp.131-137
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• 2009

In dogs, correct diagnosis of estrus is important and the exact time of ovulation can be determined by variouse methods. Vaginal cytology has commonly used in conjunction with the physical examination, clinical history, vaginoscopy, and hormonal assays to determine the stage of the reproductive cycle. This study was therefore investigated the effectiveness of direct ovulation detector designed by changes of electrical resistance in vaginal mucus following different estrus cycles with several methods; vaginal cytology, concentration of plasma estrogen and progesterone, and direct examination by laparotomy. A total of 12 bitches was selected for the study and observed estrus signs. The bitches were evaluated clinical sign (vulvar swelling and bleeding), cytological examination (keratocyte and RBC), electrical resistance, plasma estrogen and progesterone concentration for estrus assessment. Accuracy of ovulation detection by vaginal cytology was significantly (p<0.05) lower than those by electrical resistance and plasma progesterone concentration, based on the confirmation by laparotomy. Vaginal smear is not confidential method compared to detection of electrical resistance and plasma progesterone concentration at ovulation. Although the value of electrical resistance was varied at the same points of estrus in individuals, ovulation was occurred at the first day which shown the peak of electrical resistance and mating time was third day after peak. In conclusion, ovulation detector designed by changes of electrical resistance is an effective and economic instrument for predicting estrus and ovulation in bitches.

• Journal of Animal Science and Technology
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• v.59 no.10
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• pp.21.1-21.6
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• 2017

Background: The aim of the study is to evaluate the effectiveness of thermographic monitoring, using the temperature changes of perianal and perivulvar areas for the determination of estrus in Anatolian Shepherd bitches. Fifteen bitches were used in the study. Blood and vaginal smear samples were collected and thermographic monitoring of perianal and perivulvar areas were carried out starting from proestrus to early diestrus. Also, external signs of estrus were investigated. Smear samples were evaluated by light microscopy after Diff-Quik staining method and superficial and keratinized superficial cells were determined as percentage (S + KS%). Progesterone and luteinizing hormone measurements were done by radioimmunoassay. The difference in temperature between perianal and perivulvar areas was evaluated through thermographic images by FLIR ResearchIR Software. Results: According to the results obtained from the study, differences between progesterone and S + KS% were statistically significant (P < 0,05). Although temperature showed increase and decrease with progesterone and S + KS%, the differences were not important statistically (P > 0,05). Serum luteinizing hormone levels did not sign any difference (P > 0,05). Conclusions: As a result, thermographic monitoring alone is not enough for estrus detection in Anatolian Shepherd bitches. However, it can be used to assist the actual estrus detection technique in terms of providing some foreknowledge by evaluating the differences in temperature.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.107-114
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• 2017

Iris diagnosis is an alternative medicine to diagnose the disease of the patient by using different of the iris pattern, color and other characteristics. This paper proposed a disease prediction algorithm that using the iris regions that analyze iris change to using differential image of iris image. this method utilize as patient's health examination according to iris change. Because most of previous studies only find a sign pattern in a iris image, it's not enough to be used for a iris diagnosis system. We're developed an iris diagnosis system based on a iris images processing approach, It's presents the extraction algorithms of 8 major iris signs and correction manually for improving the accuracy of analysis. As a result, PNSR of applied edge detection image is about 132, and pattern matching area recognition presented practical use possibility by automatic diagnostic that presume situation of human body by iris about 91%.

• Convergence Security Journal
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• v.13 no.2
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• pp.155-163
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• 2013

Connection hijacking attack using the vulnerability of the TCP protocol to redirect TCP stream goes through your machine actively (Active Attack). The SKEY such as one-time password protection mechanisms that are provided by a ticket-based authentication system such as Kerberos or redirection, the attacker can bypass.Someone TCP connection if you have access on TCP packet sniffer or packet generator is very vulnerable. Sniffer to defend against attacks such as one-time passwords and token-based authentication and user identification scheme has been used. Active protection, but these methods does not sign or encrypt the data stream from sniffing passwords over insecure networks, they are still vulnerable from attacks. For many people, an active attack is very difficult and so I think the threat is low, but here to help break the illusion successful intrusion on the UNIX host, a very aggressive attack is presented. The tools available on the Internet that attempt to exploit this vulnerability, known as the recent theoretical measures is required. In this paper, we propose analysis techniques on a wireless network intruder detection.

• 한국지형공간정보학회:학술대회논문집
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• 2002.11a
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• pp.117-122
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• 2002

Change detection is a useful technology that can be applied to various fields, taking temporal change information with the comparison and analysis among multi-temporal satellite images. Especially, change detection that utilizes high-resolution satellite imagery can be implemented to extract useful change information for many purposes, such as the environmental inspection, the circumstantial analysis of disaster damage, the inspection of illegal building, and the military use, which cannot be achieved by lower middle-resolution satellite imagery. However, because of the special characteristics that result from high-resolution satellite imagery, it cannot use a pixel-based method that is used for low-resolution satellite imagery. Therefore, it must be used a feature-based algorithm based on the geographical and morphological feature. This paper presents the system that builds the change map by digitizing the boundary of the changed object. In this system, we can make the change map using manual or semi-automatic digitizing through the user interface implemented with a floating window that enables to detect the sign of the change, such as the construction or dismantlement, more efficiently.

• Korean Journal of Veterinary Service
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• v.45 no.2
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• pp.101-110
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• 2022

This study was performed to investigate infectious gastrointestinal diseases in 115 Korean cats (83 indoors and 32 outdoors) with digestive signs such as diarrhea, anorexia or abdominal distention. Detection of infectious pathogens was analyzed using real-time PCR. As a result, 85 of 115 Korean cats were detected with feline corona virus (FCoV), feline parvo virus, Group A rotavirus, Clostridium perfringens (C. perfringens), Campylobacter coli (C. coli), Campylobacter jejuni, enterotoxigenic Escherichia coli, enteropathogenic Escherichia coli, Salmonella spp., Tritrichomonas foetus, Cyclospora cayetanensis, and Giardia lamblia. The most frequently detected pathogen was C. perfringens (52 cats, 61.2%), followed by FCoV (43 cats, 50.6%) and C. coli (16 cats, 18.8%). Also, single infection was the most common (43 cats), followed by double infection in 31 cats, triple infection in 7 cats, and quadruple infection in 4 cats. There was no significant relationship between pathogen detection and age, gender, living environment, weather, and diarrhea. However, there was a significant difference between the age group under 1 year and the age group 1~7 (P value<0.05). In this study, cats with suspected gastrointestinal infection were randomly evaluated, and other factors that could affect pathogen detection were insufficiently considered. For this reason, additional epidemiological investigations with a larger number of cats and sufficient consideration of the causes that may affect the results are needed. Nevertheless, it is thought that this study can also provide valuable information on gastrointestinal pathogens in Korean cats.

• Korean Journal of Radiology
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• v.1 no.4
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• pp.198-207
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• 2000

Uterine cervical carcinoma is one of the most common malignant tumors occurring in females. After primary treatment, patients are usually followed up with CT or MRI and the findings of these modalities may be the first sign of recurrent disease. Because earlier additional treatment by chemotherapy or radiation therapy may improve the prognosis, the early detection of recurrent cervical carcinoma is clinically important. In this article, we review the CT and MR imaging findings of recurrent uterine cervical carcinoma, and assign them to one of four groups: a) recurrence at the primary site, involving the intrapelvic organs, b) extension to the pelvic side-wall, c) metastases to pelvic and extrapelvic lymph nodes, or d) metastases to distant organs. A further contribution of CT and MR imaging is the detection of hydronephrosis due to ureteral obstruction. The cases in each group are illustrated and discussed, and since an awareness of the spectrum of imaging findings of recurrent cervical carcinoma is likely to lead to its early detection, radiologists should be familiar with the information presented.

• Convergence Security Journal
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• v.21 no.2
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• pp.57-66
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• 2021

Deep neural networks (DNNs) provide excellent performance for image, speech, and pattern recognition. However, DNNs sometimes misrecognize certain adversarial examples. An adversarial example is a sample that adds optimized noise to the original data, which makes the DNN erroneously misclassified, although there is nothing wrong with the human eye. Therefore studies on defense against adversarial example attacks are required. In this paper, we have experimentally analyzed the success rate of detection for adversarial examples by adjusting various parameters. The performance of the ensemble defense method was analyzed using fast gradient sign method, DeepFool method, Carlini & Wanger method, which are adversarial example attack methods. Moreover, we used MNIST as experimental data and Tensorflow as a machine learning library. As an experimental method, we carried out performance analysis based on three adversarial example attack methods, threshold, number of models, and random noise. As a result, when there were 7 models and a threshold of 1, the detection rate for adversarial example is 98.3%, and the accuracy of 99.2% of the original sample is maintained.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.160-174
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• 2023

LiDAR plays a key role in autonomous vehicles, and to improve its visibility, it is necessary to improve its performance and the detection objects. Accordingly, this study proposes a shape for traffic safety signs that is advantageous for self-driving vehicles to recognize. Improvement plans are also proposed using a shape-recognition algorithm based on point cloud data collected through LiDAR sensors. For the experiment, a DBSCAN-based road-sign recognition and classification algorithm, which is commonly used in point cloud research, was developed, and a 32ch LiDAR was used in an actual road environment to conduct recognition performance tests for 5 types of road signs. As a result of the study, it was possible to detect a smaller number of point clouds with a regular triangle or rectangular shape that has vertical asymmetry than a square or circle. The results showed a high classification accuracy of 83% or more. In addition, when the size of the square mark was enlarged by 1.5 times, it was possible to classify it as a square despite an increase in the measurement distance. These results are expected to be used to improve dedicated roads and traffic safety facilities for sensors in the future autonomous driving era and to develop new facilities.