• Bulletin of the Korean Space Science Society
• /
• 2009.10a
• /
• pp.48.1-48.1
• /
• 2009

In recent years, many candidates for extra-solar planet have been discovered from various measurement techniques. Fueled by such discoveries, new space missions for direct detection of earth-like planets have been proposed and actively studied. TPF instrument is a fair example of such scientific endeavors. One of the many technical problems that space missions such as TPF would need to solve is deconvolution of the collapsed (i.e. spatially and temporally) spectral signal arriving at the detector surface and the deconvolution computation may fall into a local minimum solution, instead of the global minimum solution, in the optimization process, yielding mis-interpretation of the spectral signal from the potential earth-like planets. To this extend, observational and theoretical understanding on the spectral bio-signal from the Earth serves as the key reference datum for the accurate interpretation of the planetary bio-signatures from other star systems. In this study, we present ray tracing computational model for the on-going simulation study on the Earth bio-signatures. A multi-layered atmospheric model and sea ice variation model were added to the existing target Earth model and a hypothetical space instrument (called AmonRa) observed the spectral bio-signals of the model Earth from the L1 halo orbit. The resulting spectrums of the Earth show well known "red-edge" spectrums as well as key molecular absorption lines important to harbor life forms. The model details, computational process and the resulting bio-signatures are presented together with implications to the future study direction.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.4
• /
• pp.73-79
• /
• 2020

Due to the rapidly ageing population and low birth rates, most countries have faced with the problems of an ageing population. As a result, research into aging and the means to support an aging population has therefore become a priority for many governments around the world. Ambient Assisted Living(AAL) approach is the way to guarantee better life conditions for the aged and for monitoring their health conditions by the development of innovative technologies and services. AAL technologies can provide more safety for the elderly, offering emergency response mechanisms and fall detection solutions. Since the information transmitted in AAL systems is very personal, however, the security and privacy of such data are becoming important issues that must be dealt with. In this paper, we propose a Chameleon hash-based secure authentication protocol for AAL systems. The proposed authentication protocol not only supports several important security requirements needed by the AAL systems, but can also withstand various types of attacks. In addition, the security analysis results show that the proposed authentication protocol is more efficient and secure than the existing authentication protocols.

• Journal of Environmental Health Sciences
• /
• v.39 no.1
• /
• pp.32-42
• /
• 2013

Objectives: Cryptosporidium, a protozoan parasite, has been recognized as a frequent cause of waterborne disease due to its extremely strong resistance against chlorine disinfection. Although there has as yet been no report of a Cryptosporidium outbreak through drinking water in Korea, it is important to estimate the health risk of Cryptosporidium in water supply systems because of the various infection cases in human and domestic animals and frequent detection reports on their oocysts in water environments. Methods: This study evaluated the annual infection risk of Cryptosporidium in tap water using the quantitative microbial risk assessment technique. Exposure assessment was performed upon the results of a national survey on Cryptosporidium on the water sources of 97 large-scale water purification plants in Korea, water treatment efficacy, and daily unboiled tap water consumption. The estimates of the US Environmental Protection Agency on the mean likelihood of infection from ingesting one oocyst were applied for effect assessment. Results: Using probabilistic methods, mean annual infection risk of Cryptosporidiosis by the intake of tap water was estimated to fall within the range of $2.3{\times}10^{-4}$ to $1.0{\times}10^{-3}$ (median $5.7{\times}10^{-4}$). The risk in using river sources was predicted to be four times higher than with lake sources. With 0.5-log higher removal efficacy, the risk was estimated to be $1.8{\times}10^{-4}$, and could then be lowered by one-third. Conclusions: These estimations can be compared with acceptable risk and then used to determine the adequacy and priority of various drinking water quality strategies such as the establishment of new treatment technology.

• Korean Journal of Veterinary Service
• /
• v.39 no.4
• /
• pp.231-237
• /
• 2016

The present study was conducted to investigate the lesion of red internal organs in slaughtered pigs and provided assistant data for pig farms. During March to December 2015, a total of 1,160 lung samples out of 58 herds were collected randomly from pigs slaughtered in Jeonbuk province. In addition, 290 hilar lymph nodes from pig with pneumonic lung lesion (5 samples per herd) were screened for selected viral and bacterial pathogens. Gross lesions of lungs such as swine enzootic pneumonia (SEP), pleuritis, pleuropneumonia, pericarditis and liver white spots were examined. The overall prevalence of SEP was 64.3% (746/1,160). In the analysis of seasonal prevalence, there was an increase of occurrence during the spring months (287/400, 71.8%) and decrease during the fall months (93/200, 46.5%) among the whole herds. The mean number of SEP score per pig was $1.20{\pm}1.28$. The prevalence of pleuropneumonia, pleuritis, pericarditis, and milk spot was 25.5% (296/1,160), 44.1% (512/1,160), 3.8% (44/1,160) and 17.6% (204/1,160), respectively. The most frequent region with lung lesion was diaphragmatic lobes (left 17.1%, right 17.3%). In the detection of viral pathogens by PCR, porcine circovirus type2 (PCV2) was positive in 86.9% (252/290), while porcine reproductive and respiratory syndrome virus (PRRSV) was not detected, In the case of bacterial pathogens, 50 microorganisms were isolated by PCR and/or microbiological test. The most frequently isolated bacteria was Streptococcus suis (20, 34.4%), followed by Pasteurella multocida (17, 29.3%), Streptococcus spp. (11, 3.4%), Actinobacillus pleuropneumoniae (2, 8.9%).

• Archives of Pharmacal Research
• /
• v.25 no.4
• /
• pp.505-510
• /
• 2002

An improved kinetic assay for prekallikrein activator (PKA), a potential vasodilator, has been developed to be used as an indicator for quality control during production of human albumin preparations. It consists of two reaction stages. In the first stage, PKA and prekallikrein are incubated at $37^{\circ}C$ for 45 min to allow the transformation into kallikrein. Kallikrein, a serine protease, catalyzes the splitting of p-nitroaniline (pNA) from its substrate H-D-Pro-Phe-Arg-pNA(S-2302). The rate at which pNA is released was measured spectrophotometrically at 405 nm. Prekallikrein, a substrate of PKA was purified by DEAE ion-exchange chromatography and the major potential variations in the assay were optimized; pH 8.0 and 150 mM sodium chloride were chosen to give a proper ionic strength. Reaction times in the range of 10 to 360 min provided linear dose-response curves. The concentration of prekallikrein was adjusted to fall between 1:1 and 1:3 dilutions to generate a linear standard calibration curve. Under the optimized conditions, reproducibility was checked. In a precision test, the coefficient of variation (CV) stayed within ${\pm}4%$ and the dose-response curve showed a good correlation (${r^2}=0.999$). An accuracy test with an international standard of PKA afforded a mean recovery of 97.5%.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.5
• /
• pp.969-976
• /
• 2019

A lightweight artificial intelligence hardware has made great strides in many application areas. In general, a lightweight artificial intelligence system consist of lightweight artificial intelligence engine and preprocessor including feature selection, generation, extraction, and normalization. In order to achieve optimal performance in broad range of applications, lightweight artificial intelligence system needs to choose a good preprocessing function and set their respective hyper-parameters. This paper proposes a unified framework for a lightweight artificial intelligence system and utilization method for finding models with optimal performance to use on a given dataset. The proposed unified framework can easily generate a model combined with preprocessing functions and lightweight artificial intelligence engine. In performance evaluation using handwritten image dataset and fall detection dataset measured with inertial sensor, the proposed unified framework showed building optimal artificial intelligence models with over 90% test accuracy.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.49 no.9
• /
• pp.771-780
• /
• 2021

The space Debris laser ranging system is called to be a definite type of satellite laser ranging system that measures the distance to satellites. It is a system that performs POD (Precise Orbit Determination) by measuring time of flight by firing a laser. Distance precision can be measured in mm-level units, and it is the most precise system among existing systems. Currently, KASI has built SLR in Sejong and Geochang, and utilized SLR data to verify the precise orbits of the STSAT-2C and KOMASAT-5. In recent years, due to the fall or collision of space debris, its satellites have been threatened, and in terms of security, laser tracking of space objects is receiving great interest in order to protect their own space assets and protect the safety of the people. In this paper, a 1.5m-class main mirror was applied for the system design of a multipurpose laser tracking system that considers satellite laser ranging and space object laser tracking. System preliminary performance analysis was performed based on Link Budget analysis considering specifications of major components.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.353-360
• /
• 2022

Due to the dense and complicated working environment, the construction industry is susceptible to many accidents. Worker's fall is a severe problem at the construction site, including falling into holes or openings because of the inadequate coverings as per the safety rules. During the construction or demolition of a building, openings and holes are formed in the floors and roofs. Many workers neglect to cover openings for ease of work while being aware of the risks of holes, openings, and gaps at heights. However, there are safety rules for worker safety; the holes and openings must be covered to prevent falls. The safety inspector typically examines it by visiting the construction site, which is time-consuming and requires safety manager efforts. Therefore, this study presented a worker-driven approach (the worker is involved in the reporting process) to facilitate safety managers by developing integrated computer vision and inertia sensors-based mobile applications to identify openings. The TensorFlow framework is used to design Convolutional Neural Network (CNN); the designed CNN is trained on a custom dataset for binary class openings and covered and deployed on an android smartphone. When an application captures an image, the device also extracts the accelerometer values to determine the inclination in parallel with the classification task of the device to predict the final output as floor (openings/ covered), wall (openings/covered), and roof (openings / covered). The proposed worker-driven approach will be extended with other case scenarios at the construction site.

• Korean Journal of Veterinary Service
• /
• v.35 no.4
• /
• pp.339-342
• /
• 2012

The objective of this study was to determine the infection patterns of etiological agents causing calf diarrhea in the Gyeongnam province, Korea. In this study, from January 2011 to December 2011, feces and necropsy specimens from 249 calves diagnosed with diarrhea (<7 months old) were examined by reverse transcriptase-polymerase chain reaction assay and bacteria & coccidium isolation for detection pathogenic organism. The results of this study showed that 78 cases (31.3%) in spring, 71 cases (28.5) in summer, 62 cases (24.9%) in fall and 38 cases (15.3%) in winter were diagnosed with calf diarrhea, respectively. Calf diarrhea-causing pathogens were diagnosed as bacteria 113 (45.4%), viruses 97 (39.0%), coccidium 1 (0.4%), unknown cases 13 (5.2%), and mixed infections 25 (10.0%). We isolated three virus types from fecal samples (97), which were classified as BVD 64 (66.0%), BRV 21 (21.6%), and BCV 12 (12.4%). Moreover, co-infected pathogens were 25 cases, consisting with BVD & BRV 11 (44%), BVD & BCV& BRV 7 (28.0%), E. coli & BCV 3 (12%), and BVD & IBR 1 (4.0%). In summary, we demonstrated that the enteropathogens of bacteria, viruses, and parasite were detected in samples from cattle with diarrhea, principally in young calves less than 7 months of age. Future studies of infectious diarrhea in cattle should include assays for this etiologic agent.

• Journal of the Korea Computer Graphics Society
• /
• v.28 no.2
• /
• pp.1-9
• /
• 2022

In this paper, we propose a vector-based augmentation technique that can generate data required for crack detection and a ConvNet(Convolutional Neural Network) technique that can learn it. Detecting cracks quickly and accurately is an important technology to prevent building collapse and fall accidents in advance. In order to solve this problem with artificial intelligence, it is essential to obtain a large amount of data, but it is difficult to obtain a large amount of crack data because the situation for obtaining an actual crack image is mostly dangerous. This problem of database construction can be alleviated with elastic distortion, which increases the amount of data by applying deformation to a specific artificial part. In this paper, the improved crack pattern results are modeled using ConvNet. Rather than elastic distortion, our method can obtain results similar to the actual crack pattern. By designing the crack data augmentation based on a vector, rather than the pixel unit used in general data augmentation, excellent results can be obtained in terms of the amount of crack change. As a result, in this paper, even though a small number of crack data were used as input, a crack database can be efficiently constructed by generating various crack directions and patterns.