• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.1-7
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• 2023

Recently, the technology of device-to-device(D2D) communication has been receiving big attention to improve the system performance since the amount of high quality/large capacity data traffic from smart phones and various devices of Internet of Things increase rapidly in 5G/6G based next generation cellular networks. However, even though the system performance of macro cells increase by reusing the frequency, the performance of macro user equipments(MUEs) decrease because of the strong interference from D2D user equipments(DUEs). Therefore, this paper proposes a dynamic channel management(DCM) scheme for DUEs to guarantee the performance of MUEs as the number of DUEs increases in next generation downlink cellular networks. In the proposed D2D DCM scheme, macro base stations dynamically assign subchannels to DUEs based on the interference information and signal to interference and noise ratio(SINR) of MUEs. Simulation results show that the proposed D2D DCM scheme outperforms other schemes in terms of the mean MUE capacity as the threshold of the SINR of MUEs incareases.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.57-64
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• 2023

The ROK military faces a significant challenge in its vigilance mission due to demographic problems, particularly the current aging population and population cliff. This study demonstrates the crucial role of the 4th industrial revolution and its core artificial intelligence algorithm in maximizing work efficiency within the Command&Control room by mechanizing simple tasks. To achieve a fully developed military surveillance system, we have chosen multi-object tracking (MOT) technology as an essential artificial intelligence component, aligning with our goal of an intelligent and automated surveillance system. Additionally, we have prioritized data visualization and user interface to ensure system accessibility and efficiency. These complementary elements come together to form a cohesive software application. The CCTV video data for this study was collected from the CCTV cameras installed at the 1st and 2nd main gates of the 00 unit, with the cooperation by Command&Control room. Experimental results indicate that an intelligent and automated surveillance system enables the delivery of more information to the operators in the room. However, it is important to acknowledge the limitations of the developed software system in this study. By highlighting these limitations, we can present the future direction for the development of military surveillance systems.

• Journal of Advanced Navigation Technology
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• v.27 no.3
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• pp.306-313
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• 2023

Realistic and graphics-based virtual reality content is based on 360-degree videos, and viewport extraction through the viewer's intention or automatic recommendation function is essential. This paper designs a viewport extraction system based on multiple object tracking in 360-degree videos and proposes a parallel computing structure necessary for multiple viewport extraction. The viewport extraction process in 360-degree videos is parallelized by composing pixel-wise threads, through 3D spherical surface coordinate transformation from ERP coordinates and 2D coordinate transformation of 3D spherical surface coordinates within the viewport. The proposed structure evaluated the computation time for up to 30 viewport extraction processes in aerial 360-degree video sequences and confirmed up to 5240 times acceleration compared to the CPU-based computation time proportional to the number of viewports. When using high-speed I/O or memory buffers that can reduce ERP frame I/O time, viewport extraction time can be further accelerated by 7.82 times. The proposed parallelized viewport extraction structure can be applied to simultaneous multi-access services for 360-degree videos or virtual reality contents and video summarization services for individual users.

• Nuclear Engineering and Technology
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• v.27 no.6
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• pp.859-869
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• 1995

The present study is to understand the physical phenomena anticipated during the accident with RHR loss under mid-loop operation in a PWR and, at the same time, to examine the prediction capability of RELAP5/MOD3.1 on such an accident, by simulating an integral test relevant to this accident for reliable analysis in an actual PWR. The selected experiment, i.g. BETHSY Test 6.9a, represents the configuration with the pressurizer manway open and steam generators unavailable during the accident. Accordingly, the results of this ok are sure to contribute to understanding both the key events as well as the sensitive parameters, anticipated in the accident, for validity of the actual analysis. In the simulation result overall behavior as well as major phenomena observed in the experiment have been predicted reasonably by RELAP5/MOD3.1, however, the problem associated with enormous computing time .due to small time step size has been encountered. Besides, the code prediction of higher swollen level in the pressure vessel has given rise to overestimation of both pressurizer level and RCS pressure. Subsequently, overprediction of the break flow through the manway has led to earlier core uncovery than that in the experiment by about 400 seconds. As a whole, it is demonstrated from both the experiment and the analysis that gravity feed has not been sufficient to recover the core level and thus additional forced feed has been necessary in this configuration.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.3
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• pp.73-82
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• 2022

Auto-scaling is one of the most important functions for cloud computing technology. Even if the number of users or service requests is explosively increased or decreased, system resources and service instances can be appropriately expanded or reduced to provide services suitable for the situation and it can improves stability and cost-effectiveness. However, since the policy is performed based on a single metric data at the time of monitoring a specific system resource, there is a problem that the service is already affected or the service instance that is actually needed cannot be managed in detail. To solve this problem, in this paper, we propose a method to predict system resource and service response time using a multivariate time series analysis model and establish an auto-scaling policy based on this. To verify this, implement it as a custom scheduler in the Kubernetes environment and compare it with the Kubernetes default auto-scaling method through experiments. The proposed method utilizes predictive data based on the impact between system resources and response time to preemptively execute auto-scaling for expected situations, thereby securing system stability and providing as much as necessary within the scope of not degrading service quality. It shows results that allow you to manage instances in detail.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.1061-1070
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• 2023

Over the last few years, lead-free inorganic metal perovskites have gained impressive ground in empowering satellites in space exploration owing to their material stability and performance evolution under extreme space environments. The present work has examined the versatility of eight such perovskites as space radiation shielding materials by computing their photon, charged particles and neutron interaction parameters. Photon interaction parameters were calculated for a wide energy range using PAGEX software. The ranges of heavy charged particles (H, He, C, N, O, Ne, Mg, Si and Fe ions) in these perovskites were estimated using SRIM software in the energy range 1 keV-10 GeV, and that of electrons was computed using ESTAR NIST software in the energy range 0.01 MeV-1 GeV. Further, the macroscopic fast neutron removal cross-sections were also calculated to estimate the neutron shielding efficiencies. The examined shielding parameters of the perovskites varied depending on the radiation type and energy. Among the selected perovskites, Cs₂TiI₆ and Ba₂AgIO₆ displayed superior photon attenuation properties. A 3.5 cm thick Ba₂AgIO₆-based shield could reduce the incident radiation intensity to half its initial value, a thickness even lesser than that of Pb-glass. Besides, CsSnBr₃ and La_0.8Ca_0.2Ni_0.5Ti_0.5O₃ displayed the highest and lowest range values, respectively, for all heavy charged particles. Ba₂AgIO₆ showed electron stopping power (on par with Kovar) better than that of other examined materials. Interestingly, La_0.8Ca_0.2Ni_0.5Ti_0.5O₃ demonstrated neutron removal cross-section values greater than that of standard neutron shielding materials - aluminium and polyethylene. On the whole, the present study not only demonstrates the employment prospects of eco-friendly perovskites for shielding space radiations but also suggests future prospects for research in this direction.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.119-125
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• 2023

IT infrastructure operation has advanced, and the methods for managing systems have become widely adopted. Recently, research has focused on improving system management using Syslog. However, utilizing log data collected through these methods presents challenges, as logs are extracted in various formats that require expert analysis. This paper proposes a system that utilizes edge computing to distribute the collection of Syslog data and preprocesses duplicate data before storing it in a central database. Additionally, the system constructs a data dictionary to classify and count data in real-time, with restrictions on transmitting registered data to the central database. This approach ensures the maintenance of predefined patterns in the data dictionary, controls duplicate data and temporal duplicates, and enables the storage of refined data in the central database, thereby securing fundamental data for big data analysis. The proposed algorithms and procedures are demonstrated through simulations and examples. Real syslog data, including extracted examples, is used to accurately extract necessary information from log data and verify the successful execution of the classification and storage processes. This system can serve as an efficient solution for collecting and managing log data in edge environments, offering potential benefits in terms of technology diffusion.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1D
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• pp.129-136
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• 2008

Along with the development in cutting-edge digital technology, the street space is also being changed. Mobile telecommunication units and internet give a big change in a human being's lifestyle. And the ubiquitous computing is proceeding with expanding its application range from the indoor space to the street space. As the street furniture is the convenient facility that allows a human being's life in street space to be abundant, it is getting advanced. First of all, in terms of such phenomenon, this study analyzed the cases of a research on application of street space and the actual condition of a change in the number of individuals for the street furniture, through a literature research of ubiquitous. Also, it researched into the realities of using the street furniture of the walking-desired streets at Daehac-ro and Hongdae district, where are two representative places related to digital generation. The next was carried out FGI (Focus Group Interview) with users of the street space in front of Hongik University and managers of the street furniture, and was researched into the use & management behavior, and recognition level on the street furniture. Thus, the key elements were extracted such as interchange of information for cultural activities, automation for interaction variability in function. Finally the core elements for future vision of street furniture in this digital era were extracted in 3I, namely, Information, Intellectualization, and Integration. This is considered to be applied to the establishment of direction in the process of high-tech digitalization in street furniture related to information hereafter.

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

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.127-135
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• 2023

With the development of information and communication technology, the amount of information produced and shared in the battlefield and stored and managed in the system dramatically increased. This means that the amount of information which cansupport situational awareness and decision making of the commanders has increased, but on the other hand, it is also a factor that hinders rapid decision making by increasing the information overload on the commanders. To overcome this limitation, this study proposes a method to automatically search, select, and summarize documents that can help the commanders to understand the battlefield situation reports that he or she received. First, named entities are discovered from the battlefield situation report using a named entity recognition method. Second, the documents related to each named entity are discovered. Third, a language model and collaborative filtering are used to select the documents. At this time, the language model is used to calculate the similarity between the received report and the discovered documents, and collaborative filtering is used to reflect the commander's document reading history. Finally, sentences containing each named entity are selected from the documents and sorted. The experiment was carried out using academic papers since their characteristics are similar to military documents, and the validity of the proposed method was verified.