• Food Science and Preservation
• /
• v.24 no.7
• /
• pp.1017-1024
• /
• 2017

The objective of this study was to investigate the inhibitory effects of Litsea japonica fruit flesh extract (LJF-HE) on gastritis in an indomethacin-induced SD rat model. Rats were randomly divided into six groups: G1 (normal group), G2 (control group, indomethacin-induced gastritis), G3 (positive group, indomethacin-induced gastritis and ranitidine 50 mg/kg), G4 (LJF-HE-L group, indomethacin-induced gastritis and L. japonica fruit flesh extract at 30 mg/kg), G5 (LJF-HE-M group, indomethacin-induced gastritis and L. japonica fruit flesh extract at 60 mg/kg), G6 (LJF-HE-H group, indomethacin-induced gastritis and L. japonica fruit flesh extract at 120 mg/kg). In the group treated with LJF-HE (G4, G5, and G6), gastric mucosal damage, gastric juice secretion and pepsin activity were significantly decreased compared to the control group. Additionally, there were decreases in the expression of cholecystokinin 2 receptor (CCK-2r), histamine receptor H2 (H2r) and H+/K+ ATPase in the gastric lesions. The plasma levels of TNF-${\alpha}$ and IL-$1{\beta}$ significantly decreased in LJF-HE (G4, G5, and G6) treated groups compared with control. The plasma level of PGE2 was also significantly increased by LJF-HE (G5 and G6). These results suggest that LJF-HE (G4, G5, and G6) has the ability to inhibit on indomethacin-induced gastritis.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.2
• /
• pp.901-908
• /
• 2011

For the available grid environmental realization, the resource supply PC must have to provide an appropriate security function of their operation environments. SKY@HOME is a kind of the grid computing environments. If this has not supervised by administrator handling smoothly, it is inherently vulnerable state to the security level of the grid environments, because the resource supply PC is not update a security function without delay. It is also have the troublesome problems which have to install of an additional security program for support the appropriate security. This paper proposes an integration security model on the policy-based that provides an update each level according to the situation of the resource supply PC for improving its problems as a security aspect of the SKY@HOME. This model analyzes the security state of the resource supply PC respectively, and then the result is available to provide an appropriate security of the resource supply PC using an integration security model. The proposed model is not need additionally to buy and install the software, because it is provided the security management server oriented service. It is also able to set up the suit security function of a characteristic of the each resource supply PC. As a result, this paper clearly show the participation of resource supply PC improved about 20%.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.3
• /
• pp.629-643
• /
• 2019

In the era of the 4th industrial revolution, countries around the world are conducting projects to rapidly expand smart factory to secure competitiveness in manufacturing industries. However, unlike existing factories where the network environment was closed, smart factories can be vulnerable because internal and external objects are interconnected and various ICT technologies are used. And smart factories are likely to be the subject of cyber-attacks that are designed to cause monetary damage to certain targets because economic damage is so serious when an accident occurs. Therefore, it is necessary to study and apply security for smart factories, but there is no specific smart factory system architecture, so there is no establish for smart factory security requirements. In order to solve these problems, this paper derives the smart factory architecture that can extract and reflect the main characteristics of a smart factory based on the domestic and foreign reference model of smart factories. And this paper identifies the security threats based on the derived smart factory architecture and present the security requirements to cope with them for contributing to the improvement of the security of the smart factory.

• Journal of IKEEE
• /
• v.23 no.2
• /
• pp.438-447
• /
• 2019

As the IoT-based hyper-connected society grows, public-key cryptosystem such as RSA is frequently used for encryption, authentication, and digital signature. Public-key cryptosystem use very large (safe) prime numbers to ensure security against malicious attacks. Even though the performance of the device has greatly improved, the generation of a large (safe)prime is time-consuming or memory-intensive. In this paper, we propose ET-MR and ET-MR-MR using Euler sieve so it runs faster while using less memory. We present a running time prediction model by probabilistic analysis and compare time and memory of our method with conventional methods. Experimental results show that the difference between the expected running time and the measured running time is less than 4%. In addition, the fastest running time of ET-MR is 36% faster than that of TD-MR, 8.5% faster than that of DT-MR and the fastest running time of ET-MR-MR is 65.3% faster than that of TD-MR-MR and similar to that of DT-MR-MR. When k=12,381, the memory usage of ET-MR is 2.7 times more than that of DT-MR but 98.5% less than that of TD-MR and when k=65,536, the memory usage of ET-MR-MR is 98.48% less than that of TD-MR-MR and 92.8% less than that of DT-MR-MR.

• The Journal of the Convergence on Culture Technology
• /
• v.7 no.1
• /
• pp.291-299
• /
• 2021

In 2019, SUV sales surpassed sedans in the domestic sales market with phenomenal domestic sales. The strength of SUVs around the world is expected to continue in the future. South Korea's K-company aggressively launched small SUVs in the SUV market. Its simple lineup is recognized as a brand image, not as a SUV. It is time to evaluate this. Therefore, it influences the purchasing decisions of potential customers and buyers of small SUVs through the evaluation of design images of small SUVs in Korea. Rather than the functional properties of the SUV model, it is purchased by emotional characteristics, brand symbolism, and image. Subconsciousness of the purchasing psychology of the end consumer was used by metaphor extraction techniques. Customers wanted to study the evaluation of small SUV design images that fit their needs. We wanted to see if consumers who intend to purchase or purchase small SUVs in Korea had a connection with the image of design of small SUVs in Korea. The conclusion of the study was extracted through ZMET, a metaphor extraction technique, with the latent consciousness of the primary ambiguous message from the consumer's feeling and representation of the image. Therefore, based on the results of this study, we hope that the images presented in SUVs in the future will be used as a design guide in the development of small SUVs to influence customer thinking and behavior.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.15 no.3
• /
• pp.3-12
• /
• 2005

This paper introduces a 3D perceptual model based on JND(Just Noticeable Difference) and proposes a video watermarking scheme which is perceptual approach of adaptive embedding in 3D-DCT domain. Videos are composed of consecutive frames with many similar adjacent frames. If a watermark is embedded in the period of similar frames with little motion, it can be easily noticed by human eyes. Therefore, for the transparency the watermark should be embedded into some places where motions exist and for the robustness its magnitude needs to be adjusted properly. For the transparency and the robustness, watermark based on 3D perceptual model is utilized. That is. the sensitivities from the 3D-DCT quantization are derived based on 3D perceptual model, and the sensitivities of the regions having more local motion than global motion are adjusted. Then the watermark is embedded into visually significant coefficients in proportion to the strength of motion in 3D-DCT domain. Experimental results show that the proposed scheme improves the robustness to MPEG compression and temporal attacks by about $3{\sim}9\%$, compared to the existing 3D-DCT based method. In terms of PSNR, the proposed method is similar to the existing method, but JND guarantees the transparency of watermark.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.11
• /
• pp.449-456
• /
• 2021

An intrusion detection system is a technology that detects abnormal behaviors that violate security, and detects abnormal operations and prevents system attacks. Existing intrusion detection systems have been designed using statistical analysis or anomaly detection techniques for traffic patterns, but modern systems generate a variety of traffic different from existing systems due to rapidly growing technologies, so the existing methods have limitations. In order to overcome this limitation, study on intrusion detection methods applying various machine learning techniques is being actively conducted. In this study, a comparative study was conducted on data preprocessing techniques that can improve the accuracy of anomaly detection using NGIDS-DS (Next Generation IDS Database) generated by simulation equipment for traffic in various network environments. Padding and sliding window were used as data preprocessing, and an oversampling technique with Adversarial Auto-Encoder (AAE) was applied to solve the problem of imbalance between the normal data rate and the abnormal data rate. In addition, the performance improvement of detection accuracy was confirmed by using Skip-gram among the Word2Vec techniques that can extract feature vectors of preprocessed sequence data. PCA-SVM and GRU were used as models for comparative experiments, and the experimental results showed better performance when sliding window, skip-gram, AAE, and GRU were applied.

• Journal of the Korea Society for Simulation
• /
• v.19 no.1
• /
• pp.63-71
• /
• 2010

In modern war, Intercept Performance of SAM(Surface to Air Missile) is gaining importance as range and precision of Missile and Guided Weapon on information warfare have been improved. An aerial defence system using Surface-to-air Radar and Guided Missile is needed to be built for prediction and defense from threatening aerial attack. When developing SAM, M&S is used to free from a time limit and a space restriction. M&S is widely applied to education, training, and design of newest Weapon System. This study was conducted to develop simulator for evaluation of Intercept Performance of SAM. In this study, architecture of Intercept Performance of SAM analysis simulator for estimation of Intercept Performance of various SAM was suggested and developed. The developed Intercept Performance of SAM analysis simulator was developed by C++ and Direct3D, and through 3D visualization using the Direct3D, it shows procedures of the simulation on a user animation window. Information about design and operation of Fighting model is entered through input window of the simulator, and simulation engine consisted of Object Manager, Operation Manager, and Integrated Manager conducts modeling and simulation automatically using the information, so the simulator gives user feedback in a short time.

• Korean Journal of Culture and Social Issue
• /
• v.17 no.2
• /
• pp.175-197
• /
• 2011

This study aimed to expand and reconstruct the Driving Behavior Determinants' factors in order to confirm the relationship between Driving Behavior Determinants(DBD) and drivers' reckless driving behavior level. To expand the structure of DBD, drivers anger, introversion and type A characteristics were added, which were never considered as related factors in existing DBD studies before. The correlations between the new factors of DBD and reckless driving behavior(includes driver's personal records of driving experiences for the last three years) were verified. A factor analysis result showed us that new DBD questionnaire consists of five factors such as, 'Problem Evading', 'Benefits/Sensation Seeking', 'Anti-personal Anxiety', 'Anti-personal Anger', and 'Aggression'. Also, reckless driving behavior consists of 'Speeding', 'Inexperienced Coping', 'Wild Driving', 'Drunken Driving', and 'Distraction'. The result of correlation between the DBD and reckless driving behavior indicates that inappropriate level of DBD is highly correlated with dangerous driving behavior and strong possibilities of traffic accidents. Based on these results, we might be able to discriminate drivers according to DBD level and predict their reckless driving behavior through a standardization procedure. Futhermore, this will make us to provide drivers differentiated safety education service.

• Journal of Internet Computing and Services
• /
• v.24 no.6
• /
• pp.119-125
• /
• 2023

Through the Ukraine-Russia war, the military importance of drones is being reassessed, and North Korea has completed actual verification through a drone provocation towards South Korea at 2022. Furthermore, North Korea is actively integrating artificial intelligence (AI) technology into drones, highlighting the increasing threat posed by drones. In response, the Republic of Korea military has established Drone Operations Command(DOC) and implemented various drone defense systems. However, there is a concern that the efforts to enhance capabilities are disproportionately focused on striking systems, making it challenging to effectively counter swarm drone attacks. Particularly, Air Force bases located adjacent to urban areas face significant limitations in the use of traditional air defense weapons due to concerns about civilian casualties. Therefore, this study proposes a new passive air defense method that aims at disrupting the object detection capabilities of AI models to enhance the survivability of friendly aircraft against the threat posed by AI based swarm drones. Using laser-based adversarial examples, the study seeks to degrade the recognition accuracy of object recognition AI installed on enemy drones. Experimental results using synthetic images and precision-reduced models confirmed that the proposed method decreased the recognition accuracy of object recognition AI, which was initially approximately 95%, to around 0-15% after the application of the proposed method, thereby validating the effectiveness of the proposed method.