• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1021-1031
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• 2023

State-sponsored cyber attacks are highly impactful because they are carried out to achieve pre-planned goals. As a defender, it is difficult to respond to them because of the large scale of the attack and the possibility that unknown vulnerabilities may be exploited. In addition, overreacting can reduce the availability of users and cause business disruption. Therefore, there is a need for a response policy that can effectively defend against attacks while ensuring user availability. To solve this problem, this paper proposes a method to collect the number of processes and sessions of defense assets in real time and use them for learning. Using this method to learn reinforcement learning-based policies on a cyber attack simulator, the attack duration based on 100 time-steps was reduced by 27.9 time-steps and 3.1 time-steps for two attacker models, respectively, and the number of "restore" actions that impede user availability during the defense process was also reduced, resulting in an overall better policy.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.5
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• pp.775-784
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• 2023

Drone images are being used more and more actively in the fields of surveying and spatial information, and are rapidly replacing existing aerial and satellite images. The technology of quickly acquiring real-time data at low cost and processing it is now being applied to actual industries beyond research. However, there are also problems encountered as this progresses. When high-resolution spatial information is acquired using a general 2D flight plan for a terrain with sever undulations, problems arise due to the difference in resolution of the data. In particular, when a low-altitude high-resolution image is taken using a drone in a mountainous or steep terrain, there may be a problem in image matching due to a resolution difference caused by terrain undulations. This problem occurs because a drone acquires data while flying on a 2D plane at a fixed altitude, just like conventional aerial photography. In order to acquire high-quality 3D data using a drone, the scale difference for the shooting distance should be considered. In addition, in order to obtain facade images of large structures, it is necessary to take images in 3D space. In this study, in order to improve the disadvantages of the 2D flight method, a 3D flight plan was established for the study area, and it was confirmed that high-quality 3D spatial information could be obtained in this way.

• Journal of Environmental Science International
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• v.32 no.9
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• pp.659-669
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• 2023

The purpose of this study is to predict the pressure drop due to the installation of venturi under diverse operating conditions such as dust concentration, pulse interval and pressure, and filtration velocity using algebraic-linear regression model and use it as an economic data and efficient operating condition for a pulse air jet bag filter. A pilot scale bag filter with a filter a filter size(Ø140 × 850ℓ, 12) was used, and the filters used in the experiment were the polyester filters most commonly used in real industrial sites. The SAS 9.4 program (SAS Institute, USA) was used to predict and to determine the effects of inlet concentration (C_i), pulse interval (P_i) and pressure (P_p), filtration velocity (V_f), presence or absence of venturi, etc. The results are shown below. The variation in pressure drop with or without venturi installation was 38.8 mmAq when venturi is installed and 47.6 mmAq when venturi is not installed, indicating a difference in pressure drop of 8.8 mmAq depending on venturi installation. It is estimated that the efficiency can be improved by about 18.5% if the venturi is installed.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.79-86
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• 2024

In this paper, a novel visual tracking method which can utilize the context of object regions is presented. Conventional methods have the inherent problem of treating all candidate regions independently, where the tracker could not successfully discriminate regions with similar appearances. This was due to lack of contextual modeling in a given scene, where all candidate object regions should be taken into consideration when choosing a single region. The goal of the proposed method is to encourage feature exchange between candidate regions to improve the discriminability between similar regions. It improves upon conventional methods that only consider a single region, and is implemented by employing the MLP-Mixer model for enhanced feature exchange between regions. By implementing channel-wise, inter-region interaction operation between candidate features, contextual information of regions can be embedded into the individual feature representations. To evaluate the performance of the proposed tracker, the large-scale LaSOT dataset is used, and the experimental results show a competitive AUC performance of 0.560 while running at a real-time speed of 65 fps.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.151-160
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• 2023

Breast cancer is the most dangerous and deadly form of cancer. Initial detection of breast cancer can significantly improve treatment effectiveness. The second most common cancer among Indian women in rural areas. Early detection of symptoms and signs is the most important technique to effectively treat breast cancer, as it enhances the odds of receiving an earlier, more specialist care. As a result, it has the possible to significantly improve survival odds by delaying or entirely eliminating cancer. Mammography is a high-resolution radiography technique that is an important factor in avoiding and diagnosing cancer at an early stage. Automatic segmentation of the breast part using Mammography pictures can help reduce the area available for cancer search while also saving time and effort compared to manual segmentation. Autoencoder-like convolutional and deconvolutional neural networks (CN-DCNN) were utilised in previous studies to automatically segment the breast area in Mammography pictures. We present Automatic SegmenAN, a unique end-to-end adversarial neural network for the job of medical image segmentation, in this paper. Because image segmentation necessitates extensive, pixel-level labelling, a standard GAN's discriminator's single scalar real/fake output may be inefficient in providing steady and appropriate gradient feedback to the networks. Instead of utilising a fully convolutional neural network as the segmentor, we suggested a new adversarial critic network with a multi-scale L1 loss function to force the critic and segmentor to learn both global and local attributes that collect long- and short-range spatial relations among pixels. We demonstrate that an Automatic SegmenAN perspective is more up to date and reliable for segmentation tasks than the state-of-the-art U-net segmentation technique.

• Smart Structures and Systems
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• v.33 no.2
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• pp.119-131
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• 2024

Drift angle is a significant index for diagnosing post-event structures. A common way to estimate this drift response is by using modal parameters identified under natural excitations. Although the modal parameters of shear structures cannot be identified accurately in the real environment, the identification error has little impact on the estimation when measurements from several floors are used. However, the estimation accuracy falls dramatically when there is only one accelerometer. This paper describes the susceptibility of single sensor identification to modelling error and simulations that preliminarily verified this characteristic. To make a robust evaluation from measurements of one floor of shear structures based on imprecisely identified parameters, a novel scheme is devised to approximately correct the mode shapes with respect to fictitious frequencies generated with a genetic algorithm; in particular, the scheme uses constrained minimization to take both the mathematical aspect and the realistic aspect of the mode shapes into account. The algorithm was validated by using a full-scale shear building. The differences between single-sensor and multiple-sensor estimations were analyzed. It was found that, as the number of accelerometers decreases, the error rises due to insufficient data and becomes very high when there is only one sensor. Moreover, when measurements for only one floor are available, the proposed method yields more precise and appropriate mode shapes, leading to a better estimation on the drift angle of the lower floors compared with a method designed for multiple sensors. As well, it is shown that the reduction in space complexity is offset by increasing the computation complexity.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.1
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• pp.63-70
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• 2024

Lithium-ion batteries (LIB) are widely used in various sectors, such as transportation (e.g., electric vehicles (EV)) and energy (e.g., energy storage facilities) due to their high energy density, broad operating temperature (-20 ℃ ~ 60 ℃), and high capacities. LIBs are powerful but fragile on external factors, including pressure, physical damage, overheating, and overcharging, that cause thermal runaway causing fires and explosions. During a LIB fire, a large amount of oxygen is generated from the decomposition of ionogenic materials. A water fire extinguisher that helps with cooling and suffocating must be essentially required at the same time. In fact, however, it is difficult to suppress LIB fires in the case of EVs because a LIB is installed with a battery pack housing that interrupts direct extinguishing by water. Thus, this study aims to investigate effective fire extinguishing measurements for LIB fires by using an EV. Relevant documents, including research articles and reports, were reviewed to identify effective ways of LIBs fire extinguishing. A real-scale fire experiment generating thermal runaway was carried out to figure out the combustion characteristics of EVs. This study revealed that the most effective fire extinguishing measurements for LIB fires are applying fire blankets and water tanks. However, there is still a lack of adequate regulation and guidelines for LIB fire extinguishment. Taking this into account, developing functional fire extinguishment measurements and available regulatory instruments is an urgent issue to secure the safety of firefighters and citizens.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.4
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• pp.77-93
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• 2024

The recent development of data collection technology, which conveys various travel data in real-world such as mobile data and probe vehicle data, facilitates transportation planners identifying specified spatio-temporal travel patterns. In this study, an easily implementable travel mode classification methodology was proposed to classify inter-regional trip-modes without modeling by superimposing trajectories generated from mobile phone signaling and transportation infrastructure points into a polygon scale of a shapefile in a GIS system. Each regional mode trip was classified according to the rules such as the presence of transportation infrastructure in the trip trajectory, travel time, and the presence of access trips. An accuracy test generates Type I and Type II error results table to verify the proposed methodology. As a result, it was found that the methodology developed showed the F1-Score of the air mode 1.00, rail mode 0.95, bus mode 0.73.

• Journal of the Korean earth science society
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• v.45 no.4
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• pp.318-326
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• 2024

Black ice, a thin and nearly invisible ice layer on roads and pavements, poses a significant danger to drivers and pedestrians during winter due to its transparency. We propose an efficient black ice detection system and technique utilizing Global Positioning System (GPS)-reflected signals. This system consists of a GPS antenna and receiver configured to measure the power of GPS L1 band signal strength. The GPS receiver system was designed to measure the signal power of the Right-Handed Circular Polarization (RHCP) and Left-Handed Circular Polarization (LHCP) from direct and reflected signals using two GPS antennas. Field experiments for GPS LHCP and RHCP reflection measurements were conducted at two distinct sites. We present a Normalized Polarized Reflection Index (NPRI) as a methodological approach for determining the presence of black ice on road surfaces. The field experiments at both sites successfully detected black ice on asphalt roads, indicated by NPRI values greater than -0.1 for elevation angles between 45° and 55°. Our findings demonstrate the potential of the proposed GPS-based system as a cost-effective and scalable solution for large-scale black ice detection, significantly enhancing road safety in cold climates. The scientific significance of this study lies in its novel application of GPS reflection signals for environmental monitoring, offering a new approach that can be integrated into existing GPS infrastructure to detect widespread black ice in real-time.

• The Journal of Korean Society for Radiation Therapy
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• v.22 no.1
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• pp.25-32
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• 2010

Purpose: In radiotherapy that takes into account respiration using a RPM (Real time Position Management, Varian, USA) system, which can treat in consideration of the movement of tumor, infrared reflective markers supplied by manufacturers cannot obtain respiratory signal if the couch rotates at a certain angle or larger. In order to solve this problem, the author developed the 3D infrared reflective marker named 'Kw-marker' that can obtain respiratory signal at any angle, and evaluate its usefulness. Materials and Methods: In order to measure the stability of respiratory signal, we put the infrared reflective marker on the 3D moving phantom that can reproduce respiratory movement and acquired respiratory signal for 3 minutes under each of 3 conditions (A: $couch\;0^{\circ}$, a manufacturer's infrared reflective marker B: $couch\;0^{\circ}$, Kw-marker C: $couch\;90^{\circ}$, Kw-marker). By analyzing the respiratory signal using a breath analysis program (Labview Ver. 7.0), we obtained the peak value, valley value, standard deviation, variation value, and amplitude value. In order to examine the rotation error and moving range of the target, we placed a B.B phantom on the 3D moving phantom, and obtained images at a couch angle of $0^{\circ}$ and $90^{\circ}$ using OBI, and then acquired the X, Y and Z values (mm) of the ball bearing at the center of the B.B phantom. Results: According to the results of analyzing the respiratory signal, the standard deviation at the peak value was A: 0.002, B: 0.002 and C: 0.003, and the stability of respiration for amplitude was A: 0.15%, B: 0.14% and C:0.13%, showing that we could get respiratory signal stably by using the Kw-marker. When the couch rotated $couch\;90^{\circ}$, the mean rotation error of the ball bearing, namely, the target was X: -1.25 mm, Y: -0.45 mm and Z: +0.1 mm, which were within 1.3 mm on the average in all directions, and the difference in the moving range of the target was within 0.3 mm. Conclusion: When we obtained respiratory signal using the Kw-marker in non-coplanar treatment where the couch rotated, we could acquire respiratory signal stably and the Kw-marker was effective enough to substitute for the manufacturer's infrared reflective marker. When the rotation error and moving range of the target were measured, there was little difference, indicating that the displacement of the reflector movement in couch rotation is the cause of change in the scale and amplitude of respiratory signal. If the converted value of amplitude height according to couch angle is studied further and applied, it may be possible to perform non-coplanar phase-based gating treatment.