• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.1037-1048
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• 2022

A radioactive isotope identification algorithm is a prerequisite for a low-resolution scintillation detector applied to an unmanned radiation monitoring system. In this paper, a sparse representation with dictionary learning approach is proposed and applied to plastic gamma-ray spectra. Label-consistent K-SVD was used to learn a discriminative dictionary for the spectra corresponding to a mixture of four isotopes (¹³³Ba, ²²Na, ¹³⁷Cs, and ⁶⁰Co). A Monte Carlo simulation was employed to produce the simulated data as learning samples. Experimental measurement was conducted to obtain practical spectra. After determining the hyper parameters, two dictionaries tailored to the learning samples were tested by varying with the source position and the measurement time. They achieved average accuracies of 97.6% and 98.0% for all testing spectra. The average accuracy of each dictionary was above 96% for spectra measured over 2 s. They also showed acceptable performance when the spectra were artificially shifted. Thus, the proposed method could be useful for identifying radioisotopes in gamma-ray spectra from a plastic scintillation detector even when a dictionary is adapted to only simulated data. Furthermore, owing to the outstanding properties of sparse representation, the proposed approach can easily be built into an insitu monitoring system.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.71-78
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• 2022

This paper proposes an algorithm for 3D object detection by processing point cloud data of 3D LiDAR. Unlike 2D LiDAR, 3D LiDAR-based data was too vast and difficult to process in three dimensions. This paper introduces various studies based on 3D LiDAR and describes 3D LiDAR data processing. In this study, we propose a method of processing data of 3D LiDAR using clustering techniques for object detection and design an algorithm that fuses with cameras for clear and accurate 3D object detection. In addition, we study models for clustering 3D LiDAR-based data and study hyperparameter values according to models. When clustering 3D LiDAR-based data, the DBSCAN algorithm showed the most accurate results, and the hyperparameter values of DBSCAN were compared and analyzed. This study will be helpful for object detection research using 3D LiDAR in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.6
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• pp.189-196
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• 2023

Today, in the era of the 4th industrial revolution based on the paradigm of hyper-connectivity, super-intelligence, and superconvergence, the remote work environment is becoming central based on technologies such as mobile, cloud, and big data. This remote work environment has been accelerated by the demand for non-face-to-face due to COVID-19. Since the remote work environment can perform various tasks by accessing services and resources anytime and anywhere, it has increased work efficiency, but has caused a problem of incapacitating the traditional boundary-based network security model by making the internal and external boundaries ambiguous. In this paper, we propse a method to improve the limitations of the traditional boundary-oriented security strategy by building a security model centered on core components and their relationships based on the zero trust idea that all actions that occur in the network beyond the concept of the boundary are not trusted.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.33.1-33.1
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• 2021

The overprediction of the number of satellite galaxies in the LCDM paradigm compared to that of the Milky Way (MW) and M31 (the "missing satellites" problem) has been a long-standing issue. Recently, a large host-to-host scatter of satellite populations has been recognized both from an observational perspective with a larger sample and from a theoretical perspective including baryons, and it is crucial to collect diverse and complete samples with a large survey coverage to investigate underlying factors contributing to the diversity. In this study, we discuss the diversity in terms of galaxy assembly history, using satellite populations of both observed systems and simulated systems from IllustrisTNG. In addition to previously studied satellite systems, we identify satellite candidates from 25deg2 of Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) Wide layer around NGC 4437, a spiral galaxy of about one-fourth of the MW mass, paired with a ~2 magnitude fainter dwarf spiral galaxy NGC 4592. Using the surface brightness fluctuations (SBF) method, we confirm five dwarf galaxies as members of the NGC 4437 group, resulting in a total of seven members. The group consists of two distinct subgroups, the NGC 4437 subgroup and the NGC 4592 subgroup, which resembles the relationship between the MW and M31. The number of satellites is larger than that of other observed and simulated galaxy groups in the same host stellar mass range. However, the discrepancy decreases if compared with galaxy groups with similar magnitude gaps (V12 ~ 2), defined as the V-band magnitude difference between the two brightest galaxies in the group. Using simulated galaxy groups in IllustrisTNG, we find that groups with smaller V12 have richer satellite systems, host more massive dark matter halos, and have assembled more recently. These results show that the host-to-host scatter of satellite populations can be attributed to the diversity in galaxy assembly history and be probed by V12 to some degree and that NGC 4437 group is likely a recently assembled galaxy group with a large halo mass compared to galaxy groups of similar luminosity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.277-280
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• 2021

Recently as various contents are mass produced based on high accessibility, the media contents market is more active. Users want to find content that suits their taste, and each platform is competing for personalized recommendations for content. For an efficient recommendation system, high-quality metadata is required. Existing platforms take a method in which the user directly inputs the metadata of an image. This will waste time and money processing large amounts of data. In this paper, for media hyperpersonalization recommendation, keyframes are extracted based on the YCrCb color model of the video based on movie trailers, movie genres are distinguished through supervised learning of artificial intelligence and In the future, we would like to propose a utilization plan for generating metadata.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.47-55
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• 2023

This paper presents a method for predicting the threat index of combat systems using Gradient Boosting Regressors and Support Vector Regressors among machine learning models. Currently, combat systems are software that emphasizes safety and reliability, so the application of AI technology that is not guaranteed to be reliable is restricted by policy, and as a result, the electrified domestic combat systems are not equipped with AI technology. However, in order to respond to the policy direction of the Ministry of National Defense, which aims to electrify AI, we conducted a study to secure the basic technology required for the application of machine learning in combat systems. After collecting the data required for threat index evaluation, the study determined the prediction accuracy of the trained model by processing and refining the data, selecting the machine learning model, and selecting the optimal hyper-parameters. As a result, the model score for the test data was over 99 points, confirming the applicability of machine learning models to combat systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.296-299
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• 2022

The rapid urban expansion and the increase in natural disasters due to the increase of population after industrialization and climate change are causing numerous urban management problems. The IP based hyper-connectivity caused by the initiation of the 4th industrial revolution enables a variety of technologies and services that produce vast amounts of data and solve urban management problems based on this. Especially, the quality of life is improved by providing the necessary information for life that are produced through a sensor network on wired and wireless communication. In this study, we intend to propose the method of optimal communcation network composition for innovative and futuristic city management technology through the case of K-water Smart Village Communication System

• Smart Structures and Systems
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• v.32 no.5
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• pp.319-338
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• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.939-946
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• 2023

In the hyper-connected network, which network equipment is diverse and network structure is complex, the attack surface has also increased. In this environment, MTD(Moving Target Defense) technology is being researched as a method to fundamentally defend against cyber attacks by actively changing the attack surface. network-based MTD technologies are being widely studied. However, in order for network address mutation technology to be applied within the existing fixed IP-based system, research is needed to determine what impact it will have. In this paper, we studied the impact of applying network address mutation technology to the existing network protection system. As a result of the study, factors to be considered when firewall, NAC, IPS, and network address mutation technologies are operated together were derived, and elements that must be managed in network address mutation technology for interoperability with the network analysis system were suggested.

• Journal of Venture Innovation
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• v.4 no.1
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• pp.87-99
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• 2021

The importance of "personalization technology" has recently been highlighted due to the Covid-19 and the development of IT technology such as AI and big data, which is soon coming beyond personalization into the "super-personalization era." Therefore, in terms of the music streaming service market, it has formed a service supply trend in which individual tastes are respected and companies are seeking to establish a realistic analysis and development direction considering the external market environment. From this perspective, this paper sought to analyze the strengths and weaknesses of the Genie Music's and provide a direction for development based on Genie Music's customer interactive strategy. In particular, it was intended to analyze the advantages and disadvantages of customer interactive strategies with the 'live music service platform' that moves with customers and to provide directions for future corporate development. As an analysis method, we looked at strengths and weaknesses, opportunities and threat requirements based on SWOT analysis. Afterwards, the company attempted to present specific corporate development strategies through TOWS analysis.