• KNOM Review
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• v.23 no.2
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• pp.29-41
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• 2020

Networks are growing faster than ever before causing a multi-domain complexity. The diversity, variety and dynamic nature of network traffic and services require enhanced orchestration and management approaches. While many standard orchestrators and network operators are resulting in an increase of complexity for handling E2E slice orchestration. Besides, there are multiple domains involved in E2E slice orchestration including access, edge, transport and core network each having their specific challenges. Hence, handling of multi-domain, multi-platform and multi-operator based networking environments manually requires specified experts and using this approach it is impossible to handle the dynamic changes in the network at runtime. Also, the manual approaches towards handling such complexity is always error-prone and tedious. Hence, this work proposes an automated and abstracted solution for handling E2E slice orchestration using an intent-based approach. It abstracts the domains from the operators and enable them to provide their orchestration intention in the form of high-level intents. Besides, it actively monitors the orchestrated resources and based on current monitoring stats using the machine learning it predicts future utilization of resources for updating the system states. Resulting in a closed-loop automated E2E network orchestration and management system.

• Journal of the Korean Society of Safety
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• v.37 no.4
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• pp.20-27
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• 2022

This article aims to develop an algorithm that detects fire pump defects by analyzing the current signals of an induction motor, which are triggered by changes in the flow rate and pressure of multistage volute pumps that are used for fire services. The operational status of the pumps was categorized into three: first, normal operation; second, a defect that is caused by a change in the current value; and third, a defect occasioned by a change in current, pressure, and flow rate. When a fire pump was in normal operation, the motor's operating current was measured between 5.06 A and 6.9 A, the flow rate was estimated at 0-0.27 m³/min, and the pressure ranged from 0 to 0.47 MPa. In the event that a defect was caused by an abnormal current value in the motor, it was attributed to the pump's adherence. Furthermore, if there was no source of water, the defect was considered to have been induced by phase-loss operation, no-load operation, or run-stop operation, with the current value of each scenario being measured at > 52.8 A, < 4.13 A, > 45.15 A, and < 3.8 A, respectively, placing its overall range between 0 and 50 A. The sources of defects were detected based on an analysis of the flow rate, pressure, and current, which represent the following causes: air inflow into the casing, inadequate suction of water, and reverse-phase operation, respectively. Each cause entailed the following values: when air seeped into the casing, the pressure was measured at 0.24 MPa irrespective of changes in the flow rate; when there was inadequate suction of water, the pressure was recorded between 0 and 0.05 MPa despite changes in the flow rate; and when the power line's reverse-phase loss was the cause of the defect, the pressure was measured at 0.33 MPa for a flow rate of 0 L/min, and a higher flow rate decreased the pressure to nearly 0 MPa. The results of this study will enable engineers to develop a pump defect detection algorithm that is based on an analysis of current, and this algorithm will facilitate the execution of a program that will control a fire pump defect detection system.

• Journal of Physiology & Pathology in Korean Medicine
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• v.36 no.4
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• pp.138-142
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• 2022

This study aimed to evaluate the effectiveness of Korean rehabilitation treatement for patients with post-TKR. The medical records of inpatients undergoing Korean rehabilitation treatment after TKR from 2016.01.01. to 2021.12.31. during the admission, were analyzed retrospectively. The effect of treatment was evaluated by using a numeric rating scale(NRS) and range of motion(ROM) of knee. Statistical analysis was done using the IBM SPSS statistics 26 program. If the period of hospitalization was within 7 days or change of NRS and ROM was not recorded properly, the case was excluded. All inpatients received acupuncture treatment, Electro-acupuncture. Soyeom pharmaco-acupuncture were used at a high rate. Blood letting cupping therapy, dry cupping therapy, Interferential Current Therapy(ICT) continuous passive motion(CPM), cryotherapy were used at a high rate. A significant improvement was noted when comparing the NRS and knee ROM results at the time of admission and discharge. Korean medical rehabilitation can be effectively used for patients who have undergone TKR, to relieve pain and enable returning to daily activities. It is expected to be helpful in future studies of post-TKR in Korean Medicine. Also It can be used for medical treatment of post-TKR in Korean Medicine Hospital and clinic. However, further research with a high level of evidence is necessary to support this finding.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.119-137
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• 2022

Recent recommendation system studies apply various deep learning models to represent user and item interactions better. One of the noteworthy studies is ONCF(Outer product-based Neural Collaborative Filtering) which builds a two-dimensional interaction map via outer product and employs CNN (Convolutional Neural Networks) to learn high-order correlations from the map. However, ONCF has limitations in recommendation performance due to the problems with CNN and the absence of side information. ONCF using CNN has an inductive bias problem that causes poor performances for data with a distribution that does not appear in the training data. This paper proposes to employ a Vision Transformer (ViT) instead of the vanilla CNN used in ONCF. The reason is that ViT showed better results than state-of-the-art CNN in many image classification cases. In addition, we propose a new architecture to reflect side information that ONCF did not consider. Unlike previous studies that reflect side information in a neural network using simple input combination methods, this study uses an independent auxiliary classifier to reflect side information more effectively in the recommender system. ONCF used a single latent vector for user and item, but in this study, a channel is constructed using multiple vectors to enable the model to learn more diverse expressions and to obtain an ensemble effect. The experiments showed our deep learning model improved performance in recommendation compared to ONCF.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.667-677
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• 2022

The purpose of this study is to analyze the structural relationship among the usefulness, ease of use, use intention, and learning utilization of smart learning devices recognized by college students. In order to achieve this, the following problems were addressed: first, how do college students' recognition of ease and usefulness of smart learning devices? second, how do college students' recognition of ease and learning utilization? third, what mediating effects od use of smart learning devices and learning utilization? As for the research method, a survey of 350 students who participated in smart learning was conducted to conduct a home review, confirmatory factor analysis, and bootsrapping for structural equation estimation and mediating analysis. As a result of the analysis on this, first, it was found that the usefulness and ease of smart learning devices recognized by college students had an effect on the intention of use. Second, it was found that the perception of the usefulness and ease of smart devices perceived by college students had an effect on the use of smart learning device learning. Third, it was found that the intention to use smart devices perceived by college students mediated the relationship between usefulness and learning utilization, and it was found that it mediated the relationship between ease and learning utilization. The implications are that instructors can recognize and utilize the intention of using smart learning devices properly by allowing college students to recognize the usefulness and ease of using smart learning devices in the classroom, thereby increasing the learning utilization of smart learning devices in class. In addition, efforts are needed to enable college students to recognize the usefulness of smart devices and to expand the use of learning.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.139-147
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• 2022

In this study, we designed a high-strength, low-alkali type cement composite for artificial reef by mixing various binders and evaluated whether it is possible to manufacture it with an ME method 3D printer. As a result of the tests, it is found that it is important to control the water-binder ratio, the silica sand-binder ratio, and the type of silica sand in order to control the fluidity of the cement composites to enable 3D printing. The surface quality of 3D printer output can be achieved by adjusting the amount of viscosity agent added while obtaining printable fluidity. In the cement composites mixing proportion using the alpha-type hemihydrate gypsum, a setting control agent needs to be used to control the quick setting effect. It is also necessary to derive the time to maintain the fluidity, and to apply it when printing. To obtain the required strength, the mix proportion needs to be modified while satisfying the fluidity level of 3D-printable cement composites. In the present study, 3D-printable mix proportions were designed by the use of multi-component binders including alpha-type hemihydrate gypsum a for low-alkali type artificial reefs, and the printability was confirmed. A further study needs to be performed to quantitatively evaluate the alkali reduction effect.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.555-562
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• 2021

Recently, in the field of geospatial information construction, unmanned aerial vehicles have been increasingly used because they enable rapid data acquisition and utilization. In this study, photogrammetry was performed using fixed-wing, rotary-wing, and VTOL (Vertical Take-Off and Landing) unmanned aerial vehicles, and geospatial information was constructed using two types of unmanned aerial vehicle LiDAR (Light Detection And Ranging) sensors. In addition, the accuracy was evaluated to present the utility of spatial information constructed through unmanned aerial photogrammetry and LiDAR. As a result of the accuracy evaluation, the orthographic image constructed through unmanned aerial photogrammetry showed accuracy within 2 cm. Considering that the GSD (Ground Sample Distance) of the constructed orthographic image is about 2 cm, the accuracy of the unmanned aerial photogrammetry results is judged to be within the GSD. The spatial information constructed through the unmanned aerial vehicle LiDAR showed accuracy within 6 cm in the height direction, and data on the ground was obtained in the vegetation area. DEM (Digital Elevation Model) using LiDAR data will be able to be used in various ways, such as construction work, urban planning, disaster prevention, and topographic analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.491-496
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• 2021

In line with the modern era in which the safety of underground facilities and the use of underground information are increasingly emphasized, the state is pushing for more precise and accurate underground spatial information to be secured and utilized. Therefore, we need to pay more attention to subsurface geospatial data. In the future, the Ministry of Land, Infrastructure and Transport will actively utilize the 15 types of Integrated Underground Geospatial Information Map(6 types of underground facilities, 6 types of underground structures, 3 types of ground) that the Ministry of Land, Infrastructure and Transport is building as three-dimensional underground spatial information, and contribute greatly to improving national safety and convenience in underground construction. expected to do However, when a site manager requests an Integrated Underground Geospatial Information Map with a mobile device, if the large-capacity integrated underground space map is not quickly transmitted over the wireless section and is not serviced, it causes inconvenience to the site manager and delays work. In this paper, the goal of this paper is to enable field managers to quickly receive a tiled Integrated Underground Geospatial Information Map with minimal information exchange. Therefore, the tiling system is configured according to the dataset for high-speed Mobile Integrated Underground Geospatial Information Map transmission. In addition, a transmission system for the Mobile Integrated Underground Geospatial Information Map is established, and a TCP/IP (Transmission Control Protocol/Internet Protocol)-based spatial information tiling transmission protocol dedicated to the on-site Integrated Underground Geospatial Information Map is developed.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.313-323
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• 2021

The purpose of this study is to propose rules that can identify the speaker referred by the speaker directive in the text for the realization of a machine learning-based virtual character using a literary text. Through previous studies, we found that when applying literary texts to machine learning, the machine did not properly discriminate the speaker without any specific rules for the analysis of speaker directives such as other names, nicknames, pronouns, and so on. As a way to solve this problem, this study proposes 'nine rules for finding a speaker indicated by speaker directives (including pronouns)': location, distance, pronouns, preparatory subject/preparatory object, quotations, number of speakers, non-characters directives, word compound form, dispersion of speaker names. In order to utilize characters within a literary text as virtual ones, the learning text must be presented in a machine-comprehensible way. We expect that the rules suggested in this study will reduce trial and error that may occur when using literary texts for machine learning, and enable smooth learning to produce qualitatively excellent learning results.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.683-691
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• 2021

The purpose of this study is to measure the yield and to evaluate the physiological activity of Cannabis sativa seed(Hemp seed) extracts extracted using a density fluctuation supercritical carbon dioxide for each temperature condition-30℃(HSSE30), 45℃(HSSE45), 60℃(HSSE60), and to enable dissolution of the poorly water-soluble extracts by liposome formulation and to enhance the skin permeability. As a result of the yield measurement, HSSE60 showed the highest yield, and in the antioxidant activities, HSSE45 had the highest total polyphenol content, and showed the highest DPPH, ABTS+ radical scavenging activities at the highest concentration of the extracts. As a result of the antimicrobial susceptibility testing, a clear zone appeared only in the Propionibateium acnes strain. It was confirmed that particle size was reduced and the absolute value of the zeta potential increased in the case of the formulation in which the extracts were in liposomes than in the formulation in which the extracts were dissolved in deionized water, and the skin permeability was improved. Based on these experimental results, we confirmed the possibility of using the hemp seed supercritical carbon dioxide extracts, a poorly water-soluble extract, can be applied as a functional natural material for cosmetics.