• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.229-237
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• 2023

The use of artificial sources such as explosives and mechanical vibrations for seismic exploration in urban areas poses challenges, as the vibrations and noise generated can lead to complaints. As an alternative to artificial sources, the surface waves generated by traffic noise can be used to investigate the subsurface properties of urban areas. However, traffic noise takes the form of plane waves moving continuously at a constant speed. To apply existing surface wave processing/inversion techniques to traffic noise, the recorded data need to be transformed into a virtual shot gather format using seismic interferometry. In this study, various seismic interferometry methods were applied to traffic noise data, and the optimal method was derived by comparing the results in the Radon and F-K domains. Additionally, the data acquired using various receiver arrays were processed using seismic interferometry, and the results were compared and analyzed to determine the most optimal receiver array direction for exploration.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.113-123
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• 2023

This paper introduces the Cherry system, a user-independent blockchain donation system. This is a procedure that is delivered to the beneficiary's bank account through a virtual account when a donor makes a donation, so there is no difference from the existing donation delivery method from the user's point of view However, within the blockchain, Cherry Points, a virtual currency based on the user ID, are issued and delivered to the beneficiary, while all transactions and the beneficiary's usage history are managed on the blockchain. By adopting this method, there was an improvement in blockchain performance, with transaction processing exceeding 1,000 TPS in typical transaction condition and service completion within 21.3 seconds. By applying the automatic influence control algorithm to this system, the influence according to stake, which is an individual donation, is greatly reduced to 0.3 after 2 months, thereby concentrating influence could be controlled automatically. In addition, it was designed to enable micro tracking by adding a tracking function by timestamp to the donation ledger for each individual ID, which greatly improved the transparency in the use of donations. From a service perspective, existing blockchain donation systems were handled as limited donation delivery methods. Since it is a direct service in a user-independent method, convenience has been greatly improved by delivering donations in various forms.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.185-198
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• 2023

In marine seismic surveys, the inevitable occurrence of trace gaps in the near offset resulting from geometrical differences between sources and receivers adversely affects subsequent seismic data processing and imaging. The absence of data in the near-offset region hinders accurate seismic imaging. Therefore, reconstructing the missing near-offset information is crucial for mitigating the influence of seismic multiples, particularly in the case of offshore surveys where the impact of multiple reflections is relatively more pronounced. Conventionally, various interpolation methods based on the Radon transform have been proposed to address the issue of the nearoffset data gap. However, these methods have several limitations, leading to the recent emergence of deep-learning (DL)-based approaches as alternatives. In this study, we conducted an in-depth analysis of two representative DL-based studies to scrutinize the challenges that future studies on near-offset interpolation must address. Furthermore, through field data experiments, we precisely analyze the limitations encountered when applying previous DL-based trace interpolation techniques to near-offset situations. Consequently, we suggest that near-offset data gaps must be approached by extrapolation rather than interpolation.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.135-145
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• 2023

Due to the decrease in the school-age population, the number of freshmen at local college who lack basic learning skills is increasing. Thus, C college has been running a basic learning ability improvement clinic program. This paper is a case study that investigates the effect of basic learning ability improvement clinic programs on major class immersion, efficacy, and major class satisfaction. In 2022, a total of 459 students were surveyed, including 238 students who participated in online and offline classes for basic learning ability improvement clinics and 221 students who did not participate in classes. Data processing was performed using SPSS Ver. 26.0 was used. The results of this study are as follows. First, among the sub-factors of academic self-efficacy, the group participating in the basic learning ability improvement clinic showed significant differences in task difficulty preference and confidence. Second, the class participation group showed a significant difference in learning immersion in major classes. Third, the class participation group showed significant differences in all sub-factors of major satisfaction. In conclusion, it was found that the basic learning ability improvement clinic class had a significant effect on academic self-efficacy, learning immersion, and major satisfaction.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.211-228
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• 2023

Ground-penetrating radar (GPR) surveys are commonly used to monitor embankments, which is a nondestructive geophysical method. The results of GPR surveys can be complex, depending on the situation, and data processing and interpretation are subject to expert experiences, potentially resulting in false detection. Additionally, this process is time-intensive. Consequently, various studies have been undertaken to detect cavities in GPR survey data using deep learning methods. Deep-learning-based approaches require abundant data for training, but GPR field survey data are often scarce due to cost and other factors constaining field studies. Therefore, in this study, a deep- learning-based model was developed for embankment GPR survey cavity detection using data augmentation strategies. A dataset was constructed by collecting survey data over several years from the same embankment. A you look only once (YOLO) model, commonly used in computer vision for object detection, was employed for this purpose. By comparing and analyzing various strategies, the optimal data augmentation approach was determined. After initial model development, a stepwise process was employed, including box clustering, transfer learning, self-ensemble, and model ensemble techniques, to enhance the final model performance. The model performance was evaluated, with the results demonstrating its effectiveness in detecting cavities in embankment GPR survey data.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.73-80
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• 2023

The recent steep increase in the minimum hourly wage has increased the burden of labor costs, and the share of unmanned stores is increasing in the aftermath of COVID-19. As a result, theft crimes targeting unmanned stores are also increasing, and the "Just Walk Out" system is introduced to prevent such thefts, and LiDAR sensors, weight sensors, etc. are used or manually checked through continuous CCTV monitoring. However, the more expensive sensors are used, the higher the initial cost of operating the store and the higher the cost in many ways, and CCTV verification is difficult for managers to monitor around the clock and is limited in use. In this paper, we would like to propose an AI image processing fusion algorithm that can solve these sensors or human-dependent parts and detect customers who perform abnormal behaviors such as theft at low costs that can be used in unmanned stores and provide cloud-based notifications. In addition, this paper verifies the accuracy of each algorithm based on behavior pattern data collected from unmanned stores through motion capture using mediapipe, object detection using YOLO, and fusion algorithm and proves the performance of the convergence algorithm through various scenario designs.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1245-1254
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• 2023

Significant research has been conducted on the W-band synthetic aperture radar (SAR) system that utilizes the 77 GHz frequency modulation continuous wave (FMCW) radar. To reconstruct the high-resolution W-band SAR image, it is necessary to transform the point cloud acquired from the stereo cameras or the LiDAR in the direction of 6 degrees of freedom (DOF) and apply them to the SAR signal processing. However, there are difficulties in matching images due to the different geometric structures of images acquired from different sensors. In this study, we present the method to extract an optimized depth map by obtaining 6 DOF of the point cloud using a gradient descent method based on the entropy of the SAR image. An experiment was conducted to reconstruct a tree, which is a major road environment object, using the constructed W-band SAR system. The SAR image, reconstructed using the entropy-based gradient descent method, showed a decrease of 53.2828 in mean square error and an increase of 0.5529 in the structural similarity index, compared to SAR images reconstructed from radar coordinates.

• Korean Journal of Optics and Photonics
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• v.34 no.6
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• pp.241-247
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• 2023

We examine the spectral characteristics of laser-induced periodic surface structures (LIPSSs) formed on an amorphous silicon film irradiated by a 355-nm nanosecond laser. A Gaussian beam with a diameter of 196 ㎛ is used to perform a two-dimensional raster scan. The laser's pulse number is varied from 190 to 280, and its intensity is adjusted within 100-130 mJ/cm². LIPSSs with a periodicity of approximately 330 nm form on the surface of the Si film, aligned perpendicular to the laser's polarization. Transmission spectra of the samples show dips around 700 nm for transverse electric polarization and around 500 nm for transverse magnetic polarization. The features are investigated with a one-dimensional-grating model using a rigorous coupled-wave analysis. Simulations confirm that the observed dips are due to the resonant modes, depending on the polarization.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.145-154
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• 2022

This study briefly compares the first-cycle certification of nursing hospitals with the second-cycle certification, reviews the changes and achievements of the second-cycle certification and the third-cycle certification, and examples of challenges and solutions in the process of preparing the third-cycle certification. In this study, it is suggested as follows. First, in order to see the practical effect of certification intended by the government, the exhibition is prepared in a short period of time before certification. Second, after the implementation of the nursing hospital certification system, research on the hospital performance of the medical institution certification system is insufficient in terms of quality and quantity. Therefore, in order to see the effect on the certification system, various research support is also required so that research on this can be actively conducted. Third, design certification standard guidelines from a long-term perspective so that the standard guidelines for certification do not change significantly, and certify not only the guidelines but also individual standards and forms that can be used by medical institutions. Fourth, in the four-cycle certification, accurate and realistic guidelines for infection control and quarantine ward operation support should be developed. The importance of managing infectious diseases will be highlighted in the future due to COVID-19. Fifth, medical institutions can improve the quality of medical care in nursing hospitals and have competitiveness if their daily activities, not short-term certification preparation, are carried out in accordance with certification standards, which affects performance. Sixth, when preparing for certification, nursing hospital officials have problems in organizing documents or processing administratively in the short term as in the past. This is also based on the certification criteria for the usual business process.

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