• Title/Summary/Keyword: Area Detection

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Container Vulnerability Intruder Detection Framework based on Memory Trap Technique (메모리 트랩기법을 활용한 컨테이너 취약점 침입 탐지 프레임워크)

  • Choi, Sang-Hoon;Jeon, Woo-Jin;Park, Ki-Woong
    • The Journal of Korean Institute of Next Generation Computing
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    • v.13 no.3
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    • pp.26-33
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    • 2017
  • Recently container technologies have been receiving attention for efficient use of the cloud platform. Container virtualization technology has the advantage of a highly portable, high density when compared with the existing hypervisor. Container virtualization technology, however, uses a virtualization technology at the operating system level, which is shared by a single kernel to run multiple instances. For this reason, the feature of container is that the attacker can obtain the root privilege of the host operating system internal the container. Due to the characteristics of the container, the attacker can attack the root privilege of the host operating system in the container utilizing the vulnerability of the kernel. In this paper, we propose a framework for efficiently detecting and responding to root privilege attacks of a host operating system in a container. This framework uses a memory trap technique to detect changes in a specific memory area of a container and to suspend the operation of the container when it is detected.

Estimating vegetation index for outdoor free-range pig production using YOLO

  • Sang-Hyon Oh;Hee-Mun Park;Jin-Hyun Park
    • Journal of Animal Science and Technology
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    • v.65 no.3
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    • pp.638-651
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    • 2023
  • The objective of this study was to quantitatively estimate the level of grazing area damage in outdoor free-range pig production using a Unmanned Aerial Vehicles (UAV) with an RGB image sensor. Ten corn field images were captured by a UAV over approximately two weeks, during which gestating sows were allowed to graze freely on the corn field measuring 100 × 50 m2. The images were corrected to a bird's-eye view, and then divided into 32 segments and sequentially inputted into the YOLOv4 detector to detect the corn images according to their condition. The 43 raw training images selected randomly out of 320 segmented images were flipped to create 86 images, and then these images were further augmented by rotating them in 5-degree increments to create a total of 6,192 images. The increased 6,192 images are further augmented by applying three random color transformations to each image, resulting in 24,768 datasets. The occupancy rate of corn in the field was estimated efficiently using You Only Look Once (YOLO). As of the first day of observation (day 2), it was evident that almost all the corn had disappeared by the ninth day. When grazing 20 sows in a 50 × 100 m2 cornfield (250 m2/sow), it appears that the animals should be rotated to other grazing areas to protect the cover crop after at least five days. In agricultural technology, most of the research using machine and deep learning is related to the detection of fruits and pests, and research on other application fields is needed. In addition, large-scale image data collected by experts in the field are required as training data to apply deep learning. If the data required for deep learning is insufficient, a large number of data augmentation is required.

Current Status and Analysis of Durability for Buildings Long Neglected after Construction Discontinuation in Jeju (제주지역 공사중단 건축물의 현황조사 및 내구성 분석)

  • Han, In-Deok;Kim, Doo-Seong;Jang, Myunghoun
    • Journal of the Korea Institute of Building Construction
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    • v.23 no.4
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    • pp.441-452
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    • 2023
  • Buildings that have been long neglected can suffer severe durability reduction due to factors such as rebar rust and concrete quality deterioration resulting from exposure to outside air. Furthermore, the issues associated with these suspended buildings, including safety accidents, social crimes, and environmental pollution, are becoming increasingly serious. This study investigates the current status of these buildings in the Jeju area, identifies the problems, and examines the durability of the structure in a specific location to assess the possibility of future use. Aesthetic surveys(visual and slope inspections) as well as non-destructive tests(compressive strength tests, neutralization tests, and rebar detection tests) were conducted to assess durability. The analysis revealed that the structure maintained satisfactory durability and the building's condition was good in comparison to the years of neglect.

Comparison of Characteristics of Gamma-Ray Imager Based on Coded Aperture by Varying the Thickness of the BGO Scintillator

  • Seoryeong Park;Mark D. Hammig;Manhee Jeong
    • Journal of Radiation Protection and Research
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    • v.47 no.4
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    • pp.214-225
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    • 2022
  • Background: The conventional cerium-doped Gd2Al2Ga3O12 (GAGG(Ce)) scintillator-based gamma-ray imager has a bulky detector, which can lead to incorrect positioning of the gammaray source if the shielding against background radiation is not appropriately designed. In addition, portability is important in complex environments such as inside nuclear power plants, yet existing gamma-ray imager based on a tungsten mask tends to be weighty and therefore difficult to handle. Motivated by the need to develop a system that is not sensitive to background radiation and is portable, we changed the material of the scintillator and the coded aperture. Materials and Methods: The existing GAGG(Ce) was replaced with Bi4Ge3O12 (BGO), a scintillator with high gamma-ray detection efficiency but low energy resolution, and replaced the tungsten (W) used in the existing coded aperture with lead (Pb). Each BGO scintillator is pixelated with 144 elements (12 × 12), and each pixel has an area of 4 mm × 4 mm and the scintillator thickness ranges from 5 to 20 mm (5, 10, and 20 mm). A coded aperture consisting of Pb with a thickness of 20 mm was applied to the BGO scintillators of all thicknesses. Results and Discussion: Spectroscopic characterization, imaging performance, and image quality evaluation revealed the 10 mm-thick BGO scintillators enabled the portable gamma-ray imager to deliver optimal performance. Although its performance is slightly inferior to that of existing GAGG(Ce)-based gamma-ray imager, the results confirmed that the manufacturing cost and the system's overall weight can be reduced. Conclusion: Despite the spectral characteristics, imaging system performance, and image quality is slightly lower than that of GAGG(Ce), the results show that BGO scintillators are preferable for gamma-ray imaging systems in terms of cost and ease of deployment, and the proposed design is well worth applying to systems intended for use in areas that do not require high precision.

Building Detection Using Edge and Color Information of Color Imagery (컬러영상의 경계정보와 색상정보를 활용한 동일건물인식)

  • Park, Choung Hwan;Sohn, Hong Gyoo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.3D
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    • pp.519-525
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    • 2006
  • The traditional area-based matching or efficient matching methods using epipolar geometry and height restriction of stereo images, which have a confined search space for image matching, have still some disadvantages such as mismatching and timeconsuming, especially in the dense metropolitan city that very high and similar buildings exist. To solve these problems, a new image matching method through building recognition has been presented. This paper described building recognition in color stereo images using edge and color information as a elementary study of new matching scheme. We introduce the modified Hausdorff distance for using edge information, and the modified color indexing with 3-D RGB histogram for using color information. Color information or edge information alone is not enough to find conjugate building pairs. For edge information only, building recognition rate shows 46.5%, for color information only, 7.1%. However, building recognition rate distinctly increase 78.5% when both information are combined.

A method of assisting small intestine capsule endoscopic lesion examination using artificial neural network (인공신경망을 이용한 소장 캡슐 내시경 병변 검사 보조 방법)

  • Wang, Tae-su;Kim, Minyoung;Jang, Jongwook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.2-5
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    • 2022
  • Human organs in the body have a complex structure, and in particular, the small intestine is about 7m long, so endoscopy is not easy and the risk of endoscopy is high. Currently, the test is performed with a capsule endoscope, and the test time is very long. The doctor connects the removed storage device to the computer to store the patient's capsule endoscope image and reads it using a program, but the capsule endoscope test results in a long image length, which takes a lot of time to read. In addition, in the case of the small intestine, there are many curves due to villi, so the occlusion area or light and shade of the image are clearly visible during the examination, and there may be cases where lesions and abnormal signs are missed during the examination. In this paper, we provide a method of assisting small intestine capsule endoscopic lesion examination using artificial neural networks to shorten the doctor's image reading time and improve diagnostic reliability.

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Utilization of UAV Remote Sensing in Small-scale Field Experiment : Case Study in Evaluation of Plat-based LAI for Sweetcorn Production

  • Hyunjin Jung;Rongling Ye;Yang Yi;Naoyuki Hashimoto;Shuhei Yamamoto;Koki Homma
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2022.10a
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    • pp.75-75
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    • 2022
  • Traditional agriculture mostly focused on activity in the field, but current agriculture faces problems such as reduction of agricultural inputs, labor shortage and so on. Accordingly, traditional agricultural experiments generally considered the simple treatment effects, but current agricultural experiments need to consider the several and complicate treatment effects. To analyze such several and complicate treatment effects, data collection has the first priority. Remote sensing is a quite effective tool to collect information in agriculture, and recent easier availability of UAVs (Unmanned Aerial Vehicles) enhances the effectiveness. LAI (Leaf Area Index) is one of the most important information for evaluating the condition of crop growth. In this study, we utilized UAV with multispectral camera to evaluate plant-based LAI of sweetcorn in a small-scale field experiment and discussed the feasibility of a new experimental design to analyze the several and complicate treatment effects. The plant-based SR measured by UAV showed the highest correlation coefficient with LAI measured by a canopy analyzer in 2018 and 2019. Application of linear mix model showed that plant-based SR data had higher detection power due to its huge number of data although SR was inferior to evaluate LAI than the canopy analyzer. The distribution of plant-based data also statistically revealed the border effect in treatment plots in the traditional experimental design. These results suggest that remote sensing with UAVs has the advantage even in a small-scale experimental plot and has a possibility to provide a new experimental design if combined with various analytical applications such as plant size, shape, and color.

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The evaluation of Spectral Vegetation Indices for Classification of Nutritional Deficiency in Rice Using Machine Learning Method

  • Jaekyeong Baek;Wan-Gyu Sang;Dongwon Kwon;Sungyul Chanag;Hyeojin Bak;Ho-young Ban;Jung-Il Cho
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2022.10a
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    • pp.88-88
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    • 2022
  • Detection of stress responses in crops is important to diagnose crop growth and evaluate yield. Also, the multi-spectral sensor is effectively known to evaluate stress caused by nutrient and moisture in crops or biological agents such as weeds or diseases. Therefore, in this experiment, multispectral images were taken by an unmanned aerial vehicle(UAV) under field condition. The experiment was conducted in the long-term fertilizer field in the National Institute of Crop Science, and experiment area was divided into different status of NPK(Control, N-deficiency, P-deficiency, K-deficiency, Non-fertilizer). Total 11 vegetation indices were created with RGB and NIR reflectance values using python. Variations in nutrient content in plants affect the amount of light reflected or absorbed for each wavelength band. Therefore, the objective of this experiment was to evaluate vegetation indices derived from multispectral reflectance data as input into machine learning algorithm for the classification of nutritional deficiency in rice. RandomForest model was used as a representative ensemble model, and parameters were adjusted through hyperparameter tuning such as RandomSearchCV. As a result, training accuracy was 0.95 and test accuracy was 0.80, and IPCA, NDRE, and EVI were included in the top three indices for feature importance. Also, precision, recall, and f1-score, which are indicators for evaluating the performance of the classification model, showed a distribution of 0.7-0.9 for each class.

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Protection provided by a commercial modified-live porcine reproductive and respiratory syndrome virus (PRRSV) 1 vaccine (PRRSV1-MLV) against a Japanese PRRSV2 field strain

  • Joel Miranda;Salvador Romero;Lidia de Lucas;Fumitoshi Saito;Mar Fenech;Ivan Diaz
    • Journal of Veterinary Science
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    • v.24 no.5
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    • pp.54.1-54.13
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    • 2023
  • Background: Porcine reproductive and respiratory syndrome virus (PRRSV) vaccines do not provide full cross-protection, mainly due to the virus genetic variability. Despite this, vaccines based on modified-live PRRSV (PRRSV-MLV) reduce the disease impact. Objectives: To assess the efficacy of two commercial vaccines-one based on PRRSV1 (PRRSV1-MLV) and another on PRRSV2 (PRRSV2-MLV)-against a Japanese PRRSV2 field strain. Methods: Two groups of three-week-old piglets were vaccinated (G1: PRRSV1-MLV; G2: PRRSV2-MLV) and two were kept as non-vaccinated (INF and CTRL). One month later, G1, G2, and INF were challenged with a PRRSV2 field strain. Results: After the challenge, clinical signs were only observed in INF. Moreover, the highest rectal temperatures and values for the area under the curve (AUC) were observed in INF. Regarding viral detection, both AUC and the proportion of positive samples in blood were higher in INF. In G1, viremic animals never reached 100%. At necropsy (21 d after the challenge), differences for titers among groups were only found in tonsils (G1 < G2 and INF). One animal (belonging to G1) was negative in all tissues. Regarding humoral responses, G1 and G2 seroconverted after vaccination, as detected in the corresponding enzyme-linked immunosorbent assay. Specific neutralizing antibodies (NA) against PRRSV1-MLV were already detected at 14 d after vaccination in G1, showing a significant booster after the challenge, while PRRSV2-MLV NA were detected in G2 at the end of the experiment. Conclusions: Despite genetic differences, PRRSV1-MLV has been demonstrated to confer partial protection against a Japanese PRRSV2 strain, at least as good as PRRSV2-MLV.

Clinical and Radiological Characteristics in Patients with Postoperative Maxillary Cyst: A Retrospective Study

  • Hyoung-Cheol Kim;Suk-Ja Yoon;Yeong-Gwan Im;Jae-Seo Lee
    • Journal of Oral Medicine and Pain
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    • v.48 no.3
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    • pp.81-86
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    • 2023
  • Purpose: To evaluate the clinical and radiologic findings of the postoperative maxillary cysts (POMCs) and investigate the relationship between lesion size and clinical symptoms depending on the time elapsed after radical maxillary sinus surgery. Methods: A total of 29 patients who were diagnosed with POMCs at Chonnam National University Dental Hospital were selected. Clinical and radiologic findings were investigated. POMC cases were divided into two groups: those with <24 years between maxillary sinus surgery and POMC diagnosis and those with >24 years. The chi-square test was used to compare the differences between the two groups. Results: The average period from surgery to POMC detection was 24.32 years; however, the period could not be confirmed in four patients. The average patient age was 52.75 years, and 12 (41.3%) patients were in their 50s. POMC-related clinical symptoms were as follows: buccal pain and swelling, dull pain, toothache, abscess, sensory abnormality, and asymptomatic. Twenty (69.0%) cases showed unilocular radiolucency and 9 (31.0%) revealed multilocular radiolucency. Seven cases (35.0%) were misdiagnosed as odontogenic lesions, resulting in the delayed treatment of POMCs. No statistical significance was found between the two groups with respect to symptoms, expansion to the surrounding area, presence of secondary cysts, and mesiodistal length of cyst on cone-beam computed tomography (CBCT) images. However, the buccopalatal length of the cyst on CBCT images was significantly different between the two groups. Conclusions: The buccopalatal length of POMCs observed on CBCT images was related to the time elapsed since surgery. The lack of awareness of POMCs may lead to misdiagnosis as an odontogenic infection and delayed treatment. Therefore, dentists must recognize the clinical and radiologic features of POMCs to differentiate it from dental infections.