• Fire Science and Engineering
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• v.33 no.6
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• pp.72-79
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• 2019

Through this study, we developed a model for predicting chemical accidents lead to casualties. The model was derived from the logistic regression analysis model and applied to the variables affecting the accident. The accident data used in the model was analyzed by studying the statistics of past chemical accidents, and applying independent variables that were statistically significant through data analysis, such as the type of accident, cause, place of occurrence, status of casualties, and type of chemical accident that caused the casualties. A significance of p < 0.05 was applied. The model developed in this study is meaningful for the prevention of casualties caused by chemical accidents and the establishment of safety systems in the workplace. The analysis using the model found that the most influential factor in the occurrence of casualty in accidents was chemical explosions. Therefore, there is an urgent need to prepare countermeasures to prevent chemical accidents, specifically explosions, from occurring in the workplace.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.4
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• pp.629-638
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• 2013

Recently the interest in the information privacy has been growing. Digital data can be easily transferred via Internet. Service providers ask users for private data to give customized services. Users believe that their shared data are protected as they deliver their private data securely. However, their private data may be leaked if service providers do not delete or initialize them when they expire. The possibility of information leak may lower if the service providers deal with users' private data properly. In this paper, we study the self-destruction of private data for information privacy and propose the glass-box model.

• Journal of Advanced Navigation Technology
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• v.13 no.3
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• pp.438-447
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• 2009

Digital home devices aims at providing the multimedia service which is not limited at time and space in home network environment. However, it is incapable of the fair use of consumers who legally buys contents, and causes damage to the contents providers owing to the indiscriminate distribution and use of illegal contents. DRM system appeared to solve this problem cannot protect the license stored on digital home devices and manage license by redistribution. This paper proposes a license audit model which makes an inspection of illegal access, modification and redistribution and reports alert logs to server.

• Journal of Korea Multimedia Society
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• v.12 no.10
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• pp.1450-1456
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• 2009

By the explosive growth of IT technologies, mobile phones have embedded a lot of functions and everyone can use them with facility. But there are various cybercrimes as invasions of one's privacy or thefts of company's sensitive information using a built-in digital camera function in a mobile phone. In this paper, we propose a scheme for analyzing evidences by digital pictures on mobile phones. Therefore we analyze the features of digital pictures on mobile phones and make databases of characteristic patterns based on the vendor and the model of mobile phone. The proposed scheme will help to acquire digital evidences by providing a better decision of the vendor and/or the model of mobile phone by cybercrime suspects.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.20 no.2
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• pp.171-183
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• 2022

The parent and daughter nuclides in a radioactive decay chain arrive at secular equilibrium once they have a large half-life difference. The characteristics of this equilibrium state can be used to estimate the production time of nuclear materials. In this study, a mathematical model and algorithm that can be applied to radio-chronometry using the radioactive equilibrium relationship were investigated, reviewed, and implemented. A Bateman equation that can analyze the decay of radioactive materials over time was used for the mathematical model. To obtain a differential-based solution of the Bateman equation, an algebraic numerical solution approach and two different matrix exponential functions (Moral and Levy) were implemented. The obtained result was compared with those of commonly used algorithms, such as the Chebyshev rational approximation method and WISE Uranium. The experimental analysis confirmed the similarity of the results. However, the Moral method led to an increasing calculation uncertainty once there was a branching decay, so this aspect must be improved. The time period corresponding to the production of nuclear materials or nuclear activity can be estimated using the proposed algorithm when uranium or its daughter nuclides are included in the target materials for nuclear forensics.

• The Journal of Korean Institute of Information Technology
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• v.17 no.8
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• pp.11-19
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• 2019

Against advanced image-related crimes, a high level of digital forensic methods is required. However, feature-based methods are difficult to respond to new device features by utilizing human-designed features, and deep learning-based methods should improve accuracy. This paper proposes a deep learning model to identify camera models based on DenseNet, the recent technology in the deep learning model field. To extract camera sensor features, a HPF feature extraction filter was applied. For camera model identification, we modified the number of hierarchical iterations and eliminated the Bottleneck layer and compression processing used to reduce computation. The proposed model was analyzed using the Dresden database and achieved an accuracy of 99.65% for 14 camera models. We achieved higher accuracy than previous studies and overcome their disadvantages with low accuracy for the same manufacturer.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1281-1281
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• 2001

Near-infrared (NIR) spectra have bean measured for high-density (HDPE), linear low-density (LLDPE), and low-density (LDPE) polyethylene in pellet or thin films. The obtained spectra have been analyzed by conventional spectroscopic analysis methods and chemometrics. By using the second derivative, principal component analysis (PCA), and two-dimensional (2D) correlation analysis, we could separate many overlapped bands in the NIR. It was found that the intensities of some bands are sensitive to density and crystallinity of PE. This may be the first time that such bands in the NIR region have ever been discussed. Correlations of such marker bands among the NIR spectra have also been investigated. This sort of investigation is very important not only for further understanding of vibration spectra of various of PE but also for quality control of PE by vibrational spectroscopy. Figure 1 (a) and (b) shows a NIR reflectance spectrum of one of the LLDPE samples and that of PE, respectively. Figure 2 shows a PC weight loadings plot of factor 1 for a score plot of PCA for the 16 kinds of LLDPE and PE based upon their 51 NIR spectra in the 1100-1900 nm region. The PC loadings plot separates the bands due to the $CH_3$ groups and those arising form the $CH_2$ groups, allowing one to make band assignments. The 2D correlation analysis is also powerful in band enhancement, and the band assignments based upon PCA are in good agreement with those by the 2D correlation analysis.(Figure omitted). We have made a calibration model, which predicts the density of LLDPE by use of partial least square (PLS) regression. From the loadings plot of regression coefficients for the model , we suggest that the band at 1542, 1728, and 1764 nm very sensitive to the changes in density and crystalinity.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.7
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• pp.2713-2717
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• 2015

Background: Possible associations between the single nucleotide polymorphism (SNP) rs8034191 in the aminoglycosidephosphotransferase domain containing 1 (AGPHD1) gene and lung cancer risk have been studied by many researchers but the results have been contradictory. Materials and Methods: A computerized search for publications on rs8034191 and lung cancer risk was performed. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to assess the association between rs8034191 and lung cancer risk with 13 selected case-control studies. Sensitivity analysis, test of heterogeneity, cumulative meta-analysis, and assessment of bias were also performed. Results: A significant association between rs8034191 and lung cancer susceptibility was found using the dominant genetic model (OR=1.344, 95% CI: 1.285-1.406), the additive genetic model (OR=1.613, 95% CI: 1.503-1.730), and the recessive genetic model (OR=1.408, 95% CI: 1.319-1.503). Moreover, an increased lung cancer risk was found with all genetic models after stratification of ethnicity. Conclusions: The association between rs8034191 and lung cancer risk was significant using multiple genetic models, suggesting that rs8034191 is a risk factor for lung cancer. Further functional studies of this polymorphism and lung cancer risk are warranted.

• Computers and Concrete
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• v.31 no.5
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• pp.405-417
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• 2023

The submerged floating tunnel (SFT) is tethered by mooring lines anchored to the seabed, therefore, the structural integrity of the anchor should be sensitively managed. Despite their importance, reaction forces cannot be simply measured by attaching sensors or load cells because of the structural and environmental characteristics of the submerged structure. Therefore, we propose an effective method for estimating the reaction forces at the seabed anchor of a submerged floating tunnel using a structural pattern model. First, a structural pattern model is established to use the correlation between tunnel motion and anchor reactions via a deep learning algorithm. Once the pattern model is established, it is directly used to estimate the reaction forces by inputting the tunnel motion data, which can be directly measured inside the tunnel. Because the sequential characteristics of responses in the time domain should be considered, the long short-term memory (LSTM) algorithm is mainly used to recognize structural behavioral patterns. Using hydrodynamics-based simulations, big data on the structural behavior of the SFT under various waves were generated, and the prepared datasets were used to validate the proposed method. The simulation-based validation results clearly show that the proposed method can precisely estimate time-series reactions using only acceleration data. In addition to real-time structural health monitoring, the proposed method can be useful for forensics when an unexpected accident or failure is related to the seabed anchors of the SFT.

• Biomedical Science Letters
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• v.12 no.3
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• pp.191-196
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• 2006

Cardiovascular disease (CVD) risk factors may be acting several decades before CVD becomes manifest. Data from young subjects may be valuable in further elucidating at this issue. We evaluated the association between baPWV (brachial-ankle pulse wave velocity) and cardiovascular risk factors in apparently healthy young adults. A total of 46 male and 91 female adolescents aged $18{\sim}25 years$ were studied. baPWV increased in a dose-responsive manner as the number of metabolic syndrome components. In both gender groups, baPWV was positively correlated with age. In males, waist, circumference total cholesterol, and LDL-cholesterol were positively correlated with baPWV, and in females, blood pressure (BP) was positively correlated with baPWV. Age, gender, mean BP, and Homeostasis model assessment insulin resistance (HOMA-IR) were found to be independent factors associated with baPWV levels. In conclusion, mean BP, age, gender, and HOMA-IR were associated with baPWV in young adults. This result suggests that multiple cardiovascular risk factors may be associated with an increased risk of arterial stiffness in young adults.