• Korean Journal of Heritage: History & Science
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• v.56 no.2
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• pp.124-133
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• 2023

Preservation processing for two combat boots was executed through application of 3-dimensional digital technology and with use of preservation materials providing outstanding reversibility and stability. The aim of this was to establish a method to preserve the relics of fallen Korean War soldiers that had been excavated by the soldiers remains excavation corps of the Ministry of National Defense. It was possible to estimate the foot size of the soldiers who would have worn the combat boots via 3-dimensional digital scanning and modeling of the boots. In this process, the original form of the combat boots was restored through the use of 3D-printed structures. The original form was restored through a process of removing contaminants from the excavated relics and performing a conditioning treatment, and through use of an antique-color treatment after bonding and filling in the sections that had been ripped or deteriorated. Following the aforementioned preservation processes, it was possible to confirm that both of the combat boots had soles and top sections made of rubber, and portions of the top section and ankle section of the boots were made of synthetic rubber. As such, it was confirmed that these were similar to the Shoe Pac(M-1944, 12-inch) winter boots that had been manufactured for the purposes of waterproofing and/or protection against cold, and introduced in 1944. Such results confirmed that it is possible to discover the manufacturing techniques, materials, and uses of relics excavated through application of preservation processing, thereby illustrating the importance of the convergent research of scientific preservation processing and 3-dimensional digital technology.

• Composites Research
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• v.36 no.3
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• pp.199-204
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• 2023

A combination of a metallic mesh and an adhesive layer of metallic particle/epoxy composite was introduced as an intermediate layer to enhance the adhesion between cold-sprayed particles and fiber-reinforced composites (FRCs). Aluminum was considered for both the metallic particles in the adhesive and the metallic mesh. To predict the mechanical characteristics of the intermediate bond layer under a high strain rate, the properties of the adhesive layer needed to be calculated or measured. Therefore, in this study, the Al particle/epoxy adhesive was homogenized by using a rule of mixture. To verify the homogenization, the penetration depth, and the thickness decrease after the cold spray deposition from the undeformed surface, was monitored with FE analysis and compared with experimental observation. The comparison displayed that the penetration depth was comparable to the diameters of one cold spray particle, and thus the homogenization approach can be reasonable for the prediction of the stress level of particulate polymer composite interlayer under a high strain rate for cold spray processing.

• Convergence Security Journal
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• v.22 no.2
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• pp.131-141
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• 2022

Future battlefield domains are expanding to ground, sea, air, space, and cyber, so future military operations are expected to be carried out simultaneously and complexly in various battlefield domains. In addition, the application of convergence technologies that create innovations in all fields of economy, society, and defense, such as artificial intelligence, IoT, and big data, is being promoted. However, since the current Korean military C4I system manages warfighting function DBs in one DB server, the efficiency of combat performance is reduced utilization and distribution speed of data and operation response time. To solve this problem, research is needed on how to apply the 4th industrial revolution technologies such as AI, IoT, 5G, big data, and cloud to the Korean military C4I system, but research on this is insufficient. Therefore, this paper analyzes the problems of the current Korean military C4I system and proposes to apply the 4th industrial revolution technology in terms of operational mission, network and data link, computing environment, cyber operation, interoperability and interlocking capabilities.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.329-344
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• 2023

In this study, we comprehensively analyze the generalization performance of various deep learning-based active sonar target classifiers when applied to small and imbalanced active sonar datasets. To generate the active sonar datasets, we use data from two different oceanic experiments conducted at different times and ocean. Each sample in the active sonar datasets is a time-frequency domain image, which is extracted from audio signal of contact after the detection process. For the comprehensive analysis, we utilize 22 Convolutional Neural Networks (CNN) models. Two datasets are used as train/validation datasets and test datasets, alternatively. To calculate the variance in the output of the target classifiers, the train/validation/test datasets are repeated 10 times. Hyperparameters for training are optimized using Bayesian optimization. The results demonstrate that shallow CNN models show superior robustness and generalization performance compared to most of deep CNN models. The results from this paper can serve as a valuable reference for future research directions in deep learning-based active sonar target classification.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.320-328
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• 2023

Underwater active target detection is vital for defense systems, requiring accurate detection and estimation of distance and velocity. Sequential transmission is necessary at each beam angle, but divided pulse length leads to range ambiguity. Multi-frequency transmission results in time-bandwidth product losses when bandwidth is divided. To overcome these problem, we propose a novel method using Generalized Sinusoidal Frequency Modulation (GSFM) for rapid target detection, enabling low-correlation pulses between subpulses without bandwidth division. The proposed method allows for rapid updates of the distance and velocity of target by employing GSFM with minimized pulse length. To evaluate our method, we simulated an underwater environment with reverberation. In the simulation, a linear frequency modulation of 0.05 s caused an average distance estimation error of 50 % and a velocity estimation error of 103 % due to limited frequency band. In contrast, GSFM accurately and quickly tracked targets with distance and velocity estimation errors of 10 % and 14 %, respectively, even with pulses of the same length. Furthermore, GSFM provided approximate azimuth information by transmitting highly orthogonal subpulses for each azimuth.

• Analytical Science and Technology
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• v.21 no.3
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• pp.222-228
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• 2008

On living skin the chances of a successfully developing latent fingerprint are very limited. This is due to the fact that continual perspiration and rapid absorption diffuse into the lipophillic layer on skin. A study was conducted to investigate effectively developing method of latent fingerprints on human skin surfaces and pig skin likely corpse's skin. We used commercial fingerprint powder, black powders, black magnetic powder, fluorescence magnetic powder, Cyanoacrylate fuming (CA) and direct lifting methods (lifting paper, glasses and photo glossy paper). Developing of fresh fingerprints on living skin was achieved with S-powderblack, CA fuming and CA fuming following S-powder, fluorescence powder. The other powder tends to overwhelm the latent print and the background. But, latent fingerprint residue was disappeared with time after deposit on a living surface. In case of pig skin likely corpse's skin, latent fingerprint detection was achieved with CA fuming following S-powder and deposited print during 6 hr at $25^{\circ}C$, 40% relative moisture yielded excellent fingerprints with clear ridge details using 1 min CA fuming. And enhancement of fingerprint detection image using forensic light source was achieved.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.257-266
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• 2022

Inundation damage is increasing every year due to localized heavy rain and an increase of rainfall exceeding the design frequency. Accordingly, the importance of hydraulic structures for flood control and defense is also increasing. The hydraulic structures are designed according to its purpose and performance, and the amount of flood is an important calculation factor. However, in Korea, design rainfall is used as input data for hydrological analysis for the design of hydraulic structures due to the lack of sufficient data and the lack of reliability of observation data. Accurate probability rainfall and its temporal distribution are important factors to estimate the design rainfall. In practice, the regression equation of temporal distribution for the design rainfall is calculated using the cumulative rainfall percentage of Huff's quartile method. In addition, the 6^th order polynomial regression equation which shows high overall accuracy, is uniformly used. In this study, the optimized regression equation of temporal distribution is derived using the variable selection method according to the principle of parsimony in statistical modeling. The derived regression equation of temporal distribution is verified through the significance test. As a result of this study, it is most appropriate to derive the regression equation of temporal distribution using the stepwise selection method, which has the advantages of both forward selection and backward elimination.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.202-202
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• 2022

Recently days, soybean production in paddy field is increasing, from 4,422 ha in 2016 to 10,658 ha in 2021 in Korea. It is easy for Phytophthora stem and root rot (PSR) occurring in paddy field condition, when it is poorly drained soils with a high clay content, and temporary flooding and ponding. Therefore PSR resistant soybean cultivar is required. The objective of this study is to identify QTL region and candidate genes relating to PSR resistance of the race in main soybean cultivation area in Korea. 210 soybean materials including cultivars and germplasm were used for inoculation and genome-wide association study (GWAS). Inoculation was conducted using stem-scar method with 2 replications in 2-year for the race 3053 from Kimje and 3617 from Andong. 210 materials were genotyped with Soya SNP 180K chip, and structure analysis and association mapping were conducted with QTLMAX V2. The results of inoculation showed that survival ratio ranged from 0% to 96.7% and mean 9.7% for 3053 and ranged from 0% to 100% and mean 7.6% for 3617. Structure analysis showed linkage disequillibrium (LD) was decayed below r²=0.5 at 335kb of SNP distance. Significant SNPs (LOD>7.0) were identified in Chr 1, 2, 3, 4, 5, 11, 14, 15 for 3053 and Chr 1, 2, 3, 7, 10, 14 for 3617. Especially, LD blocks (AX-90455181;15,056,628bp~AX-90475572;15,298,872bp) in Chr 2 for 3053 and 3067 were duplicated. 29 genes were identified on these genetic regions including Glyma.02gl47000 relating to ribosome recycling factor and defense response to fungus in Soybase.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.67-76
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• 2023

Although deep learning models are making innovative achievements in the field of computer vision, the problem of vulnerability to adversarial examples continues to be raised. Adversarial examples are attack methods that inject fine noise into images to induce misclassification, which can pose a serious threat to the application of deep learning models in the real world. In this paper, we propose a model that detects adversarial examples using differences in predictive values between edge-learned classification models and underlying classification models. The simple process of extracting the edges of the objects and reflecting them in learning can increase the robustness of the classification model, and economical and efficient detection is possible by detecting adversarial examples through differences in predictions between models. In our experiments, the general model showed accuracy of {49.9%, 29.84%, 18.46%, 4.95%, 3.36%} for adversarial examples (eps={0.02, 0.05, 0.1, 0.2, 0.3}), whereas the Canny edge model showed accuracy of {82.58%, 65.96%, 46.71%, 24.94%, 13.41%} and other edge models showed a similar level of accuracy also, indicating that the edge model was more robust against adversarial examples. In addition, adversarial example detection using differences in predictions between models revealed detection rates of {85.47%, 84.64%, 91.44%, 95.47%, and 87.61%} for each epsilon-specific adversarial example. It is expected that this study will contribute to improving the reliability of deep learning models in related research and application industries such as medical, autonomous driving, security, and national defense.

• The Journal of Korean Medical History
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• v.35 no.2
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• pp.69-82
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• 2022

Shin Hong-gyun was born on August 20, 1881. The second son of Shin Tae-geom (申泰儉) in Sangsang-ri, Sinbukcheong-myeon, Bukcheong-gun,Hamgyeongnam-do. His family had been practicing East Asian medicine as a family business. At that time, the families of East Asian doctors who passed the general examination of the Joseon Dynasty had been continuing the East Asian medicine business from generation to generation. Starting with exile in North Gando in 1911, he was located in Wangga-dong, 17 Doo-gu, Changbaek-hyeon. In 1915, he met General Choi Un-san in Bongo-dong, treated the soldiers suffering from cellulitis, and participated in the training process to prepare for the upcoming anti-Japanese war. However, because of a growing difference of opinion with General Choi Woon-san, Shin Hong-gyun left Bono-dong after a year and mets Sorae Kim Jung-geon and joined the founding of Wonjonggyo and Daejindan, an anti-Japanese armed group. It is said that Shin Hong-gyun established many schools in Korean villages destroyed by the Gyeongshin disaster and 14 schools were established under the names of Wonjonggyo and Daejin. After the Japanese established the puppet Manchukuo in 1931, the Manchurian Defense Forces were formed. Koreans and Chinese immigrants to Manchuria worked together to carry out a joint Korean-Chinese anti-Japanese operation towards the Japanese Empire. In 1933, 50 of the Daejindan members joined the Korean Independence Army, and among them, Shin Hong-gyun began to work as a medical doctor in earnest. During an ambush in Daejeonryeong Valley, he could not get a proper meal and, to make matters worse, got wet in the rainy season, so the situation was a challenge in various ways. At this time, Shin Hong-gyun showed his knowledge of herbal medicine, picked black wood ear mushrooms that grew wild in the mountains, washed them in rain water, and provided food to the independence fighters and relieved them of hunger. After the Battle of Daejeon-ryeong, the Japanese army's suppression of the independence forces intensified, and most of the independence fighters escaped from the Chinese army's encirclement and were scattered. Ahn Tae-jin and others led the remaining units and continued the anti-Japanese armed struggle in the forest areas of Yeongan, Aekmok, Mokneung, and Milsan.