• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.11
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• pp.1042-1049
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• 2014

In Military MicroWave communication, the distance of link, availability, transmission capacity is the important point in order to design the circuit. Currently, operated by fixed modulation, in the future it will be evolved to the modulation techniques enabled to increase the transmission capacity. It would be hard to consistently guarantee the transmission quality of the high-availability because the occurrence probability of fading increase in terms of the link distance for the case of the long distance. In the case of the modulation techniques for the transmission of high-capacity, as the distance is long, a falling-off in the fade margin from the link budget analysis cause the decrease in the availability. It is difficult to provide QoS guaranteed connection. In this paper, we propose the performance improvement technique of transmission by the variable allocation of the bandwidth and the higher priority transmission technique using setting the ratio of the higher priority capacity in association with the distance of link. Also we suggest the alternative of the calculation for channel transmission capacity to design the circuit.

• Journal of the Korea Institute of Building Construction
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• v.21 no.5
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• pp.507-518
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• 2021

The application of an adhesive calcium carbonate-based hybrid insulation board with quasi-combustibility in the external thermal insulation composite system(ETICS) ensures effective thermal performance and fire safety. This study aimed to conduct a mechanical test of the quasi-non-combustible hybrid insulation board as well as its constituent materials to obtain the basic data for the structural design of the adhesive ETICS. Test specimens were fabricated based on domestic and foreign test standards to examine and evaluate their tensile, compressive, flexural, and shear strengths. The strength characteristics of the quasi-non-combustible hybrid insulation board were identified from the test results, which verified that the minimum required physical properties suggested by the current KS M ISO 4898 were met. Furthermore, the quasi-non-combustible ETICS used in this study was found to be suitable for use as an external insulation system for walls unless subjected to continuous gravity load, such as a heavy exterior finish.

• Journal of the Korean GEO-environmental Society
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• v.22 no.10
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• pp.13-19
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• 2021

Cracks in asphalt pavement occur due to changes in weather or impact from vehicles, and if cracks are left unattended, the life of the pavement may be shortened, and various accidents may occur. Therefore, studies have been conducted to detect cracks through images in order to quickly detect cracks in the asphalt pavement automatically and perform maintenance activity. Recent studies adopt machine-learning models for detecting cracks in asphalt road pavement using a Convolutional Neural Network. However, their practical use is limited because they require high-performance computing power. Therefore, this paper proposes a framework for detecting cracks in asphalt road pavement by applying a small deep learning model applicable to mobile devices. The small deep learning model proposed through the case study was compared with general deep learning models, and although it was a model with relatively few parameters, it showed similar performance to general deep learning models. The developed model is expected to be embedded and used in mobile devices or IoT for crack detection in asphalt pavement.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.2
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• pp.35-40
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• 2019

Traditional Malware Detection is susceptible for detecting malware which is modified by polymorphism or obfuscation technology. By learning patterns that are embedded in malware code, machine learning algorithms can detect similar behaviors and replace the current detection methods. Data must collected continuously in order to learn malicious code patterns that change over time. However, the process of storing and processing a large amount of malware files is accompanied by high space and time complexity. In this paper, an HDFS-based distributed processing system is designed to reduce space complexity and accelerate feature extraction time. Using a distributed processing system, we extract two API features based on filtering basis, 2-gram feature and APICFG feature and the generalization performance of ensemble learning models is compared. In experiments, the time complexity of the feature extraction was improved about 3.75 times faster than the processing time of a single computer, and the space complexity was about 5 times more efficient. The 2-gram feature was the best when comparing the classification performance by feature, but the learning time was long due to high dimensionality.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.1-9
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• 2022

As various services are linked to IoT(Internet of Things) and portable communication terminals, cyber attacks that exploit security vulnerabilities of the devices are rapidly increasing. In particular, cyber attacks targeting heterogeneous devices in large-scale network environments through advanced persistent threat (APT) attacks are on the rise. Therefore, in order to improve the effectiveness of the response system in the event of a breach, it is necessary to apply a data enrichment mechanism for the collected artifact data to improve threat analysis and detection performance. Therefore, in this study, by analyzing the data supplementation common elements performed in the existing incident management framework for the artifacts collected for the analysis of intrusion accidents, characteristic elements applicable to the actual system were derived, and based on this, an improved accident analysis framework The prototype structure was presented and the suitability of the derived data supplementary extension elements was verified. Through this, it is expected to improve the detection performance when analyzing cyber incidents targeting artifacts collected from heterogeneous devices.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.121-129
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• 2022

the Naval Combat Management System(CMS) has been installed and used in various ships since its localization, and has been developed by continuously introducing the latest technology. Recently, surface ship CMS have applied server virtualization and desktop virtualization(Virtual Desktop Infra, VDI) technologies among virtualization technologies to increase system stability and limitations on the limited space and weight of ships. On the other hand, submarine CMS do not have virtualization technology applied, so there are limitations in space and weight limitations and CMS efficiency improvement. To this end, this paper proposes a next-generation submarine CMS using Docker-based server virtualization. Through performance analysis between the processor of the existing CMS and the processor to which Docker-based server virtualization was applied, it was confirmed that the method proposed in this paper is applicable to the next-generation submarine CMS.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.43-49
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• 2023

Object tracking is being studied with various techniques such as Kalman filter and Luenberger tracker. Even in situations, such as the one in which the system model is not well specified, to which existing signal processing techniques are not successfully applicable, it is possible to design artificial neural networks to track objects. In this paper, we propose an artificial neural network, which we call 'maximum-likelihood weighted-average neural network', to continuously track unpredictably moving objects. This neural network does not directly estimate the locations of an object but obtains location estimates by making weighted average combining various results of maximum likelihood tracking with different data lengths. We compare the performance of the proposed system with those of Kalman filter and maximum likelihood object trackers and show that the proposed scheme exhibits excellent performance well adapting the change of object moving characteristics.

• Membrane Journal
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• v.33 no.4
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• pp.158-167
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• 2023

The increasing concerns for environmental pollution and depletion of natural resources have prompted the development of environmentally sustainable technologies. Pervaporation has garnered attention in recent decades due to its low energy consumption, environmental impact, and performance efficiency. This method has been used to separate chemical species and dehydrate organic solvents, as the membranes can be fine-tuned to fulfill the desired selectivity. Several separation processes, such as reverse osmosis and distillation, are being utilized in both experimental settings and industrial applications. However, pervaporation has several advantages, such as low operating pressure and temperature and a higher rejection rate. Nonetheless, the current state of membrane technology alone can't suffice the demands of practical applications. Composite membranes, on the other hand, can leverage the benefits of both organic and inorganic materials. Many studies have effectively incorporated inorganic nanomaterials such as graphene oxide (GO) and MXene (MX) in polymeric membranes to tackle the current limitations. This review investigates the recent development of 2D composite membranes in pervaporation and evaluates performance enhancement.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.2
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• pp.117-135
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• 2023

The National Archives of Korea (NAK) operates the NAK Portal as a record search system. However, user search satisfaction is too low, and the number of visitors to the portal is gradually decreasing. This study identifies the portal's issues, proposes feasible improvements, and constructs a pilot system to validate the solutions. The preliminary assessment revealed six major issues, such as poor search tool performance and the lack of consistency in search results. After clarifying the improvement measures, a pilot system was established and compared with the National Records Portal. The evaluation showed significant performance improvements in the pilot system, such as Precision, Recall, and Mean Reciprocal Rank (MRR).

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.441-447
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• 2022

In this paper, we propose a FLL-assisted-PLL based time synchronization algorithm for telemetry systems where frequency and phase errors exist in time synchronization pulse. The telemetry system may analyze the flight state by acquiring the state information in the distributed system. Therefor, in order to collect each state information without errors, precise time synchronization between the master and the slave is required. At this time, the master's time pulse have frequency and phase changes that can be caused by external and internal factors, so a method to maintain precision time synchronization is essential to provide telemetry data continuously. We propose the FLL-assisted-PLL based algorithm that is capable of high-speed synchronization and has high time synchronization accuracy. The proposed algorithm is verified through python simulation, and the VHDL Logic has been implemented in FPGA to check the performance according to the frequency errors and phase errors.