• KIPS Transactions on Computer and Communication Systems
• /
• v.11 no.1
• /
• pp.23-34
• /
• 2022

With the development of network technology, the application area has also been diversified, and protocols for various purposes have been developed and the amount of traffic has exploded. Therefore, it is difficult for the network administrator to meet the stability and security standards of the network with the existing traditional switching and routing methods. Software Defined Networking (SDN) is a new networking paradigm proposed to solve this problem. SDN enables efficient network management by programming network operations. This has the advantage that network administrators can flexibly respond to various types of attacks. In this paper, we design a threat level management module, an attack detection module, a packet statistics module, and a flow rule generator that collects attack information through the controller and switch, which are components of SDN, and detects attacks based on these attributes of SDN. It proposes a method to block denial of service attacks (DoS) of advanced attackers by programming and applying honeypot. In the proposed system, the attack packet can be quickly delivered to the honeypot according to the modifiable flow rule, and the honeypot that received the attack packets analyzed the intelligent attack pattern based on this. According to the analysis results, the attack detection module and the threat level management module are adjusted to respond to intelligent attacks. The performance and feasibility of the proposed system was shown by actually implementing the proposed system, performing intelligent attacks with various attack patterns and attack levels, and checking the attack detection rate compared to the existing system.

• Journal of the Korean Geotechnical Society
• /
• v.38 no.12
• /
• pp.91-101
• /
• 2022

The 1995 Kobe earthquake caused a massive damage to the Port of Kobe. Therefore, it was pointed out that it was impossible to design port structures for Level II (Mw 6.5) earthquakes with quasi-static analysis and Allowable Stress Design methods. In Japan and the United States, where earthquakes are frequent, the most advanced design standards for port facilities are introduced and applied, and the existing seismic design standards have been converted to performance-based design. Since 1999, the Korean Port Seismic Design Act has established a definition of necessary facilities and seismic grades through research on facilities that require seismic design and their seismic grades. It has also established a performance-based seismic design method based on experimental verification. In the performance-based seismic design method of the breakwater proposed in this study, the acceleration time history on the surface of the original ground was subjected to a fast Fourier transform, followed by a filter processing that corrected the frequency characteristics corresponding to the maximum allowable displacement with respect to performance level of the breakwater and the filtered spectrum. The horizontal seismic coefficient for the equivalent static analysis considering the displacement was calculated by inversely transforming (i.e., subjected to an inverse fast Fourier transform) into the acceleration time history and obtaining the maximum acceleration value. In addition, experiments and numerical analysis were performed to verify the performance-based seismic design method of breakwaters suitable for domestic earthquake levels.

• KIPS Transactions on Computer and Communication Systems
• /
• v.11 no.5
• /
• pp.157-166
• /
• 2022

Exercise is necessary for a healthy life, but it is recommended that it be conducted in a non-face-to-face environment in the context of an epidemic such as COVID-19. However, in the existing non-face-to-face exercise content, it is possible to recognize exercise movements, but the process of interpreting and providing feedback information is not automated. Therefore, in this paper, to solve this problem, we propose a method of creating a formalized rule to track the contents of exercise and the motions that constitute it. To make such a rule, first make a rule for the overall exercise content, and then create a tracking rule for the motions that make up the exercise. A motion tracking rule can be created by dividing the motion into steps and defining a key frame pose that divides the steps, and creating a transition rule between states and states represented by the key frame poses. The rules created in this way are premised on the use of posture and motion recognition technology using motion capture equipment, and are used for logical development for automation of application of these technologies. By using the rules proposed in this paper, not only recognizing the motions appearing in the exercise process, but also automating the interpretation of the entire motion process, making it possible to produce more advanced contents such as an artificial intelligence training system. Accordingly, the quality of feedback on the exercise process can be improved.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.8
• /
• pp.355-364
• /
• 2023

As advanced cyber threats continue to increase in recent years, it is difficult to detect new types of cyber attacks with existing pattern or signature-based intrusion detection method. Therefore, research on anomaly detection methods using data learning-based artificial intelligence technology is increasing. In addition, supervised learning-based anomaly detection methods are difficult to use in real environments because they require sufficient labeled data for learning. Research on an unsupervised learning-based method that learns from normal data and detects an anomaly by finding a pattern in the data itself has been actively conducted. Therefore, this study aims to extract a latent vector that preserves useful sequence information from sequence log data and develop an anomaly detection learning model using the extracted latent vector. Word2Vec was used to create a dense vector representation corresponding to the characteristics of each sequence, and an unsupervised autoencoder was developed to extract latent vectors from sequence data expressed as dense vectors. The developed autoencoder model is a recurrent neural network GRU (Gated Recurrent Unit) based denoising autoencoder suitable for sequence data, a one-dimensional convolutional neural network-based autoencoder to solve the limited short-term memory problem that GRU can have, and an autoencoder combining GRU and one-dimensional convolution was used. The data used in the experiment is time-series-based NGIDS (Next Generation IDS Dataset) data, and as a result of the experiment, an autoencoder that combines GRU and one-dimensional convolution is better than a model using a GRU-based autoencoder or a one-dimensional convolution-based autoencoder. It was efficient in terms of learning time for extracting useful latent patterns from training data, and showed stable performance with smaller fluctuations in anomaly detection performance.

• The Journal of Advanced Prosthodontics
• /
• v.15 no.3
• /
• pp.155-170
• /
• 2023

PURPOSE. This study aims to clinically compare the fitness and trueness of zirconia crowns fabricated by different combinations of open CAD-CAM systems. MATERIALS AND METHODS. Total of 40 patients were enrolled in this study, and 9 different zirconia crowns were prepared per patient. Each crown was made through the cross-application of 3 different design software (EZIS VR, 3Shape Dental System, Exocad) with 3 different processing devices (Aegis HM, Trione Z, Motion 2). The marginal gap, absolute marginal discrepancy, internal gap(axial, line angle, occlusal) by a silicone replica technique were measured to compare the fit of the crown. The scanned inner and outer surfaces of the crowns were compared to CAD data using 3D metrology software to evaluate trueness. RESULTS. There were significant differences in the marginal gap, absolute marginal discrepancy, axial and line angle internal gap among the groups (P < .05) in the comparison of fit. There was no statistically significant difference among the groups in terms of occlusal internal gap. The trueness ranged from 36.19 to 43.78 ㎛ but there was no statistically significant difference within the groups (P > .05). CONCLUSION. All 9 groups showed clinically acceptable level of marginal gaps ranging from 74.26 to 112.20 ㎛ in terms of fit comparison. In the comparison of trueness, no significant difference within each group was spotted. Within the limitation of this study, open CAD-CAM systems used in this study can be assembled properly to fabricate zirconia crown.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.10
• /
• pp.133-153
• /
• 2023

In this paper, we propose a novel approach to investigating brain-signal measurement technology using Electroencephalography (EEG). Traditionally, researchers have combined EEG signals with bio-signals (BSs) to enhance the classification performance of emotional states. Our objective was to explore the synergistic effects of coupling EEG and BSs, and determine whether the combination of EEG+BS improves the classification accuracy of emotional states compared to using EEG alone or combining EEG with pseudo-random signals (PS) generated arbitrarily by random generators. Employing four feature extraction methods, we examined four combinations: EEG alone, EG+BS, EEG+BS+PS, and EEG+PS, utilizing data from two widely-used open datasets. Emotional states (task versus rest states) were classified using Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) classifiers. Our results revealed that when using the highest accuracy SVM-FFT, the average error rates of EEG+BS were 4.7% and 6.5% higher than those of EEG+PS and EEG alone, respectively. We also conducted a thorough analysis of EEG+BS by combining numerous PSs. The error rate of EEG+BS+PS displayed a V-shaped curve, initially decreasing due to the deep double descent phenomenon, followed by an increase attributed to the curse of dimensionality. Consequently, our findings suggest that the combination of EEG+BS may not always yield promising classification performance.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_2
• /
• pp.743-754
• /
• 2023

The global occurrence of myriad natural disasters and incidents, catalyzed by climate change and extreme meteorological conditions, has engendered substantial human and material losses. International organizations such as the International Charter have established an enduring collaborative framework for real-time coordination to provide high-resolution satellite imagery and geospatial information. These resources are instrumental in the management of large-scale disaster scenarios and the expeditious execution of recovery operations. At the national level, the operational deployment of advanced National Earth Observation Satellites, controlled by National Geographic Information Institute, has not only catalyzed the advancement of geospatial data but has also contributed to the provisioning of damage analysis data for significant domestic and international disaster events. This special edition of the National Disaster Management Research Institute delineates the contemporary landscape of major disaster incidents in the year 2023 and elucidates the strategic blueprint of the government's national disaster safety system reform. Additionally, it encapsulates the most recent research accomplishments in the domains of artificial satellite systems, information and communication technology, and spatial information utilization, which are paramount in the institution's disaster situation management and analysis efforts. Furthermore, the publication encompasses the most recent research findings relevant to data collection, processing, and analysis pertaining to disaster cause and damage extent. These findings are especially pertinent to the institute's on-site investigation initiatives and are informed by cutting-edge technologies, including drone-based mapping and LiDAR observation, as evidenced by a case study involving the 2023 landslide damage resulting from concentrated heavy rainfall.

• Applied Chemistry for Engineering
• /
• v.35 no.1
• /
• pp.54-60
• /
• 2024

The present study was aimed to evaluate the removal of the trace pollutants (heavy metals and microplastics) in the sewage treatment plant by using the jellyfish Extract at Immunity reaction (JEI) of Aurelia coerulea. The experiment was conducted on two different scales: the lab scale using a Jar-tester and the Pilot system scale equipped with two newly developed devices in the laboratory, the active tube connection mixed system and the concentration integrated separation device. Compared to anionic polymers currently used in the field, JEI showed similar or higher efficiency to remove the trace pollutants. When JEI was added to the effluent through the Pilot system, the combination of JEI and the trace pollutants was maximized through two mixing processes, and as a result, the removal rate of the trace pollutants was greatly improved. Based on these results, we propose the present technology as an alternative to removing trace pollutants that can reduce ecosystem risk and minimize the generation of inorganic waste, away from the existing method.

• Korean Journal of Radiology
• /
• v.24 no.10
• /
• pp.1006-1016
• /
• 2023

Objective: Computed tomography (CT) is an established method for the diagnosis, staging, and treatment of multiple myeloma. Here, we investigated the potential of photon-counting detector computed tomography (PCD-CT) in terms of image quality, diagnostic confidence, and radiation dose compared with energy-integrating detector CT (EID-CT). Materials and Methods: In this prospective study, patients with known multiple myeloma underwent clinically indicated whole-body PCD-CT. The image quality of PCD-CT was assessed qualitatively by three independent radiologists for overall image quality, edge sharpness, image noise, lesion conspicuity, and diagnostic confidence using a 5-point Likert scale (5 = excellent), and quantitatively for signal homogeneity using the coefficient of variation (CV) of Hounsfield Units (HU) values and modulation transfer function (MTF) via the full width at half maximum (FWHM) in the frequency space. The results were compared with those of the current clinical standard EID-CT protocols as controls. Additionally, the radiation dose (CTDIvol) was determined. Results: We enrolled 35 patients with multiple myeloma (mean age 69.8 ± 9.1 years; 18 [51%] males). Qualitative image analysis revealed superior scores (median [interquartile range]) for PCD-CT regarding overall image quality (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), edge sharpness (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), image noise (4.0 [4.0-4.0] vs. 3.0 [3.0-4.0]), lesion conspicuity (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), and diagnostic confidence (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]) compared with EID-CT (P ≤ 0.004). In quantitative image analyses, PCD-CT compared with EID-CT revealed a substantially lower FWHM (2.89 vs. 25.68 cy/pixel) and a significantly more homogeneous signal (mean CV ± standard deviation [SD], 0.99 ± 0.65 vs. 1.66 ± 0.5; P < 0.001) at a significantly lower radiation dose (mean CTDIvol ± SD, 3.33 ± 0.82 vs. 7.19 ± 3.57 mGy; P < 0.001). Conclusion: Whole-body PCD-CT provides significantly higher subjective and objective image quality at significantly reduced radiation doses than the current clinical standard EID-CT protocols, along with readily available multi-spectral data, facilitating the potential for further advanced post-processing.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.37 no.4
• /
• pp.427-432
• /
• 2024

The polymer crystallization process, promoting the formation of ferroelectric β-phase, is essential for developing polyvinylidene fluoride (PVDF)-based high-performance piezoelectric energy harvesters. However, traditional high-temperature annealing is unsuitable for the manufacture of flexible piezoelectric devices due to the thermal damage to plastic components that occurs during the long processing times. In this study, we investigated the feasibility of introducing a flash lamp annealing that can rapidly induce the β-phase in the PVDF layer while avoiding device damage through selective heating. The flash light-irradiated PVDF films achieved a maximum β-phase content of 76.52% under an applied voltage of 300 V and an on-time of 1.5 ms, a higher fraction than that obtained through thermal annealing. The PVDF-based piezoelectric energy harvester with the optimized irradiation condition generates a stable output voltage of 0.23 V and a current of 102 nA under repeated bendings. These results demonstrate that flash lamp annealing can be an effective process for realizing the mass production of PVDF-based flexible electronics.