• Journal of Veterinary Clinics
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• v.34 no.6
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• pp.420-424
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• 2017

Cystic endometrial hyperplasia (CEH) and uterine dilation (hydro-, muco-, hemato- and pyometra) are common uterine diseases in intact female dogs. The aim of the present study was to assess the usefulness of digital abdominal radiography in diagnosing uterine disease in intact female dogs. Two hundred and thirteen intact female dogs were included, and were classified into four groups on the basis of radiographic uterine visibility (visible/invisible) and ultrasonographic findings (normal uterus/abnormal uterine condition including CEH and uterine dilation). For each dog, the ratio of the maximum uterine diameter to the height of the fifth lumbar vertebral body (U/L5 ratio) was calculated on radiographs. There were 78 and 135 dogs in the normal and abnormal groups, respectively; 34.6% normal and 53.5% abnormal uteri were visible on abdominal radiographs. Our results suggested that a mean U/L5 ratio of $1.18{\pm}0.53$ ($mean{\pm}2SD$) indicated a normal radiographic uterus diameter, and that a value of > 1.60 should be used as an indicator of uterine disease in clinical practice. However, because false negative results were noted, radiography cannot replace ultrasonography for assessment of the uterus.

• Fire Science and Engineering
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• v.30 no.5
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• pp.100-107
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• 2016

Today, high-rise buildings expected to meet various needs and improve the quality of frequency of fire and the potential risks are increasing. In particular, the fire spread risk in the vertical direction is increasing. As a result there is a problem with delays in the evacuation time of occupants. To overcome this problem, there is a need to consider the structure of the building and develop a system for the early detection of fire by applying a fire alarm system according to the risk ranking. Therefore, this paper describes the vertical fire spread characteristics of a multistory double-skin and stairs structure with risk. The data were compared with that from the national and international fire alarms as well as with. smoke density, smoke detectors, visibility, and CO concentration using FDS. A fire alarm system for each structure is proposed.

• Clinical Endoscopy
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• v.51 no.6
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• pp.513-526
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• 2018

White light imaging (WLI) may not reveal early upper gastrointestinal cancers. Linked color imaging (LCI) produces bright images in the distant view and is performed for the same screening indications as WLI. LCI and blue laser imaging (BLI) provide excellent visibility of gastric cancers in high color contrast with respect to the surrounding tissue. The characteristic purple and green color of metaplasias on LCI and BLI, respectively, serve to increase the contrast while visualizing gastric cancers regardless of a history of Helicobacter pylori eradication. LCI facilitates color-based recognition of early gastric cancers of all morphological types, including flat lesions or those in an H. pylori-negative normal background mucosa as well as the diagnosis of inflamed mucosae including erosions. LCI reveals changes in mucosal color before the appearance of morphological changes in various gastric lesions. BLI is superior to LCI in the detection of early esophageal cancers and abnormal findings of microstructure and microvasculature in close-up views of upper gastrointestinal cancers. Excellent images can also be obtained with transnasal endoscopy. Using a combination of these modalities allows one to obtain images useful for establishing a diagnosis. It is important to observe esophageal cancers (brown) using BLI and gastric cancers (orange) surrounded by intestinal metaplasia (purple) and duodenal cancers (orange) by LCI.

• Journal of The Korean Astronomical Society
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• v.51 no.6
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• pp.197-206
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• 2018

We present the analysis of KMT-2016-BLG-0212, a low flux-variation ($I_{flux-var}{\sim}20mag$) microlensing event, which is in a high-cadence (${\Gamma}=4hr^{-1}$) field of the three-telescope Korea Microlensing Telescope Network (KMTNet) survey. The event shows a short anomaly that is incompletely covered due to the brief visibility intervals that characterize the early microlensing season when the anomaly occurred. We show that the data are consistent with two classes of solutions, characterized respectively by low-mass brown-dwarf (q = 0.037) and sub-Neptune (q < $10^{-4}$) companions. Future high-resolution imaging should easily distinguish between these solutions.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1081-1088
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• 2020

In this paper, the method of detecting sea fog through CCTV image is proposed based on convolutional neural networks. The study data randomly extracted 1,0004 images, sea-fog and not sea-fog, from a total of 11 ports or beaches (Busan Port, Busan New Port, Pyeongtaek Port, Incheon Port, Gunsan Port, Daesan Port, Mokpo Port, Yeosu Gwangyang Port, Ulsan Port, Pohang Port, and Haeundae Beach) based on 1km of visibility. 80% of the total 1,0004 datasets were extracted and used for learning the convolutional neural network model. The model has 16 convolutional layers and 3 fully connected layers, and a convolutional neural network that performs Softmax classification in the last fully connected layer is used. Model accuracy evaluation was performed using the remaining 20%, and the accuracy evaluation result showed a classification accuracy of about 96%.

• Safety and Health at Work
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• v.11 no.4
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• pp.537-542
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• 2020

Background: Personal protective equipment (PPE) has been designed in such a way to reduce accident rates. Unfortunately, existing PPE is rather ineffective as it is not able to provide warning signals when hazard is around. The integration of intelligent systems is envisaged to increase the efficiency of existing PPE. Methods: This project designed a safety vest incorporated with metal detectors which can provide immediate warning to the field workers when there is metal hazard around. This product has greater freedom of design via smart manufacturing as it involves the assembly of few commercially available parts into a single entity. Briefly, the metal detector is a do it yourself (DIY) kit, and the safety vest is purchasable from any local market. The DIY kit was connected to a copper coil and being sewed into the safety vest. Results: The metal detector induces beeping sound when there is metal hazard around. A total of 121 engineering students were introduced to the prototype before being requested to answer a survey associated with the design. Respondents have rated >3.00/5.00 for the design simplicity, ease of usage, and light weight. Meanwhile, respondents suggested that the design should be further improved by increasing the metal detection range. Conclusion: It is envisaged that the introduction of this smart safety vest will allow the workers to carry out their duties securely by reducing the accident rates. Particularly, such design is expected to reduce workplace accident especially during night time at construction sites where the visibility is low.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.83-90
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• 2023

Blurred image is an important factor in lowering image recognition rates in Computer vision. This mainly occurs when the camera is unstablely out of focus or the object in the scene moves quickly during the exposure time. Blurred images greatly degrade visual quality, weakening visibility, and this phenomenon occurs frequently despite the continuous development digital camera technology. In this paper, it replace the modified building module based on the Deep multi-patch neural network designed with convolution neural networks to capture details of input images and Attention techniques to focus on objects in blurred images in many ways and strengthen the image. It measures and assigns each weight at different scales to differentiate the blurring of change and restores from rough to fine levels of the image to adjust both global and local region sequentially. Through this method, it show excellent results that recover degraded image quality, extract efficient object detection and features, and complement color constancy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.557-564
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• 2017

The purpose of the thermal imaging observation device mounted on the K's tank in the Republic of Korea military is to convert infrared rays into visual information to provide information about the environment under conditions of restricted visibility. Among the various performance indicators of thermal observation devices, such as the view, magnification, resolution, MTF, NETD, and Minimum Resolvable Temperature Difference (MRTD), the MRTD is the most important, because it can indicate both the spatial frequency and temperature resolvable. However, the standard method of measuring the MRTD in NATO contains many subjective factors. As the measurement result can vary depending on subjective factors such as the human eye, metal condition and measurement conditions, the MRTD obtained is not stable. In this study, these qualitative MRTD measurement systems are converted into quantitative indicators based on a gray scale using imaging processing. By converting the average of the gray scale differences of the black and white images into the MRTD, the mean values can be used to determine whether the performance requirements required by the defense specification are met. The (mean) value can also be used to discriminate between detection, recognition and identification and the detectable distance of the thermal equipment can be analyzed under various environmental conditions, such as altostratus, heavy rain and fog.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6C
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• pp.349-354
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• 2011

Passive millimeter wave imaging has the capability of detecting concealed objects under clothing. Also, passive millimeter imaging can obtain interpretable images under low visibility conditions like rain, fog, smoke, and dust. However, the image quality is often degraded due to low spatial resolution, low signal level, and low temperature resolution. This paper addresses image registration and fusion between passive millimeter images and visual images. The goal of this study is to combine and visualize two different types of information together: human subject's identity and concealed objects. The image registration process is composed of body boundary detection and an affine transform maximizing cross-correlation coefficients of two edge images. The image fusion process comprises three stages: discrete wavelet transform for image decomposition, a fusion rule for merging the coefficients, and the inverse transform for image synthesis. In the experiments, various types of metallic and non-metallic objects such as a knife, gel or liquid type beauty aids and a phone are detected by passive millimeter wave imaging. The registration and fusion process can visualize the meaningful information from two different types of sensors.

• 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.