• Title/Summary/Keyword: 융합적 운영

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NCS-based Education & Training and Qualification Proposal for Work-Learning Parallel Companies Introducing Smart Manufacturing Technology (스마트 제조기술을 도입하는 일학습병행 학습기업을 위한 NCS 기반 교육훈련 및 자격 제안)

  • Choi, Hwan Young
    • Journal of Practical Engineering Education
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    • v.12 no.1
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    • pp.117-125
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    • 2020
  • According to the government's smart factory promotion project for small and medium-sized enterprises, more than 10,000 intelligent factories are scheduled or already built in the country and the government-led goal is to nurture 100,000 skilled workers by 2022. Smart Factory introduces numerous types of education and training courses from the supplier's point of view, such as training institutions belonging to local governments, some universities, and public organizations, in the form of an efficient resource management system and ICT technology convergence in the automated manufacturing equipment. The lack of linkage with the NCS, the standard for training, seems to have room for rethinking and direction. Results of survey is provided for the family companies of K-University in the metropolitan area and Chungnam area, and analyzes job demands by identifying whether or not they want to introduce smart factories. Defining the practitioners who will serve as a window for the introduction of smart factory technology within the company, setting up a training goal in consideration of the career path, and including the level of training required competency units, optional competency units, and training time suitable for introducing and operating smart factories. Author would like to present an NCS-based qualification design plan.

Implementation of the Unborrowed Book Recommendation System for Public Libraries: Based on Daegu D Library (공공도서관 미대출 도서 추천시스템 구현 : 대구 D도서관을 중심으로)

  • Jin, Min-Ha;Jeong, Seung-Yeon;Cho, Eun-Ji;Lee, Myoung-Hun;Kim, Keun-Wook
    • Journal of Digital Convergence
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    • v.19 no.5
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    • pp.175-186
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    • 2021
  • The roles and functions of domestic public libraries are diversifying, but various problems have emerged due to internally biased book lending. In addition, due to the 4th Industrial Revolution, public libraries have introduced a book recommendation system focusing on popular books, but the variety of books that users can access is limited. Therefore, in this study, the public library unborrowed book recommendation system was implemented limiting its spatial scope to Duryu Library in Daegu City to enhance the satisfaction of public library users, by using the loan records data (213,093 cases), user information (35,561 people), etc. and utilizing methods like cluster analysis, topic modeling, content-based filtering recommendation algorithm, and conducted a survey on actual users' satisfaction to present the possibility and implications of the unborrowed book recommendation system. As a result of the analysis, the majority of users responded with high satisfaction, and was able to find the satisfaction was relatively high in the class classified by specific gender, age, occupation, and usual reading. Through the results of this study, it is expected that some problems such as biased book lending and reduced operational efficiency of public libraries can be improved, and limitations of the study was also presented.

A Study on the Internal Validity of Korean Medicine Education Evaluation and Accreditation (한의학교육평가인증 내적타당화에 대한 고찰)

  • Lee, Hyeong-Ju
    • Journal of the International Relations & Interdisciplinary Education
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    • v.1 no.2
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    • pp.31-47
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    • 2021
  • This study intends to examine the indicators of Korean medicine education that are directly required in the field, in the process of developing and rationalizing the second cycle of evaluation and accreditation standards for the Colleges of Korean medicine and present indicators to the Korean medicine education community. To this end, we conducted the Delphi survey on six Korean medicine education experts, and the second cycle evaluation and accreditation standards were developed after verifying the validity of the contents and through a public hearing on three experts. Based on the research results of this study, we make the following suggestions: First, the support of Korean medical education institutions should be considered. The Korean medical education institution operates the Korean medicine hospital under each institution's name. Thus, criteria for evaluation shall be considered according to the number of beds and the support of schools. Second, for the second cycle of evaluation, all six members of the evaluation committee were professors of Korean medicine; however, in the future, each group of the evaluation committee needs to be composed of an external curriculum and evaluation experts to seek the evaluation focusing on education. Third, it is necessary to include curriculum and evaluation experts in the development stage of education programs and institutional evaluation and accreditation standards. Fourth, the experts of the curriculum should be included as the members of the curriculum development team of the College of Korean Medicine. This study is meaningful as a study to improve the quality of Korean medicine education.

Application of recurrent neural network for inflow prediction into multi-purpose dam basin (다목적댐 유입량 예측을 위한 Recurrent Neural Network 모형의 적용 및 평가)

  • Park, Myung Ky;Yoon, Yung Suk;Lee, Hyun Ho;Kim, Ju Hwan
    • Journal of Korea Water Resources Association
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    • v.51 no.12
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    • pp.1217-1227
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    • 2018
  • This paper aims to evaluate the applicability of dam inflow prediction model using recurrent neural network theory. To achieve this goal, the Artificial Neural Network (ANN) model and the Elman Recurrent Neural Network(RNN) model were applied to hydro-meteorological data sets for the Soyanggang dam and the Chungju dam basin during dam operation period. For the model training, inflow, rainfall, temperature, sunshine duration, wind speed were used as input data and daily inflow of dam for 10 days were used for output data. The verification was carried out through dam inflow prediction between July, 2016 and June, 2018. The results showed that there was no significant difference in prediction performance between ANN model and the Elman RNN model in the Soyanggang dam basin but the prediction results of the Elman RNN model are comparatively superior to those of the ANN model in the Chungju dam basin. Consequently, the Elman RNN prediction performance is expected to be similar to or better than the ANN model. The prediction performance of Elman RNN was notable during the low dam inflow period. The performance of the multiple hidden layer structure of Elman RNN looks more effective in prediction than that of a single hidden layer structure.

Development of AI-based Real Time Agent Advisor System on Call Center - Focused on N Bank Call Center (AI기반 콜센터 실시간 상담 도우미 시스템 개발 - N은행 콜센터 사례를 중심으로)

  • Ryu, Ki-Dong;Park, Jong-Pil;Kim, Young-min;Lee, Dong-Hoon;Kim, Woo-Je
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.2
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    • pp.750-762
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    • 2019
  • The importance of the call center as a contact point for the enterprise is growing. However, call centers have difficulty with their operating agents due to the agents' lack of knowledge and owing to frequent agent turnover due to downturns in the business, which causes deterioration in the quality of customer service. Therefore, through an N-bank call center case study, we developed a system to reduce the burden of keeping up business knowledge and to improve customer service quality. It is a "real-time agent advisor" system that provides agents with answers to customer questions in real time by combining AI technology for speech recognition, natural language processing, and questions & answers for existing call center information systems, such as a private branch exchange (PBX) and computer telephony integration (CTI). As a result of the case study, we confirmed that the speech recognition system for real-time call analysis and the corpus construction method improves the natural speech processing performance of the query response system. Especially with name entity recognition (NER), the accuracy of the corpus learning improved by 31%. Also, after applying the agent advisor system, the positive feedback rate of agents about the answers from the agent advisor was 93.1%, which proved the system is helpful to the agents.

Vizrt Engine-Based Virtual Reality Graphics Algorithm A Study on the Basic Practical Training Method (Vizrt 엔진 기반 가상현실 그래픽 알고리즘과 기초 실습 교육 방식의 연구)

  • Cho, Hyun Kyung
    • The Journal of the Convergence on Culture Technology
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    • v.5 no.3
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    • pp.197-202
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    • 2019
  • In the era of the fourth revolution, interest in content production using proven engines in the broadcasting sector, such as Vizrt, is growing. The new visual effects required in the 5G era are critical to content production training. Vizrt has a good production time utility and affordability for broadcast and media content. In this paper, we are going to use this to present a practical case of the theorem and application of the basic training course in the production of virtual content, and to present the basic training direction. In the introduction, the graphic algorithm analyzed and studied the characteristics and environmental factors of the Vizrt engine. In this paper, the production process was studied separately, and the work carried out through engine implementation was presented. The VS Studio Foundation was provided as a practical production case at each stage. The Vizrt engine operator process is important in graphic approach and application, and through the results of the lecture, the method of understanding and implementing algorithms for virtual reality perspective suitable for basic learning was studied. Based on practice, the research method of main theory was to create Vizrt contents specialized in 5G contents work in each sector and to implement graphic production in new areas from contents image. Through this study, we came to the conclusion of the basic training method through virtual reality content work based on Vizrt by practicing content creation according to the subject. It also proposes the effect of creating Vizrt content and the direction of building Vizrt basic training courses.

Field Applications of Non-powered Downward Water Circulation System to Improve Reservoir Water Quality (저수지 수질개선을 위한 무동력 하향류 수류순환시스템의 현장적용성)

  • Jang, YeoJu;Lim, HyunMan;Jung, JinHong;Park, JaeRho;Kim, WeonJae
    • Ecology and Resilient Infrastructure
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    • v.6 no.2
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    • pp.109-119
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    • 2019
  • Eutrophication has occurred due to the inflow of various water pollutants in many Korean reservoirs with low depth, and algal blooms of surface layer and low oxygenation of deep layer have repeated every year. There are several existing technologies to alleviate the stratification of reservoirs, but it is difficult to apply them in field sites due to the necessity of electric power and low economic efficiency. In this study, a non-powered water circulation system using natural energy of wind and water flow has been developed, and two test-beds constructed in the reservoirs with different conditions and examined its field applicability. Through computational fluid dynamics (CFD) simulation, it has been shown that the water circulation system could induce the downward flow to mitigate the stratification between surface and deep layers, and its influence radius could reach about 30 m. As a result of long-term monitoring of the test-beds, various water quality improvement effects have been observed such as moderation of DO fluctuation by water circulation, reduction of DO supersaturation and prevention of excessive pH rising. In order to improve the applicability of the water circulation system, it is considered necessary to review countermeasures against flood and depth conditions of each reservoir.

Pre-service Elementary School Teachers' Perceptions on Instructional Design: Based on Lesson Plan Analysis (예비초등교사의 교수설계에 대한 인식: 수업지도안 분석을 중심으로)

  • Kwon, Hyuk-il
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.4
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    • pp.421-428
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    • 2021
  • This study intended to identify the differences of pre-service elementary school teachers' perceptions on instructional design between face-to-face and online instruction. Lesson plans for face-to-face and online instruction were analyzed by 84 participants who were seniors at C university of education. Results of content analysis indicate that 'Providing Learning Guidance' domain is the biggest domain in terms of the frequency gap between face-to-face and online instruction. Frequency differences by domains between face-to-face and online instruction were found to be significant as a result of Chi-square test. Frequency differences by instructional elements in the 'Providing Learning Guidance' domain between face-to-face and online instruction were found to be statistically significant as well. In conclusion, this study indicates the differences of pre-service elementary school teachers' perceptions on instructional design between face-to-face and online instruction, which implies the necessity for the development and implementation of professional development programs focusing on the perceptions on instructional design of online instruction for pre-service elementary school teachers.

A Study on Analysis and Utilization of Public Sharing Bike Data - By applying the data of Ouling, Public Sharing Bike System in Sejong City (공유자전거 데이터 분석 및 활용방안 연구 세종특별자치시 공유자전거 어울링의 데이터를 적용하여)

  • An, Se-Yun;Ju, Hannah;Kim, So-Yeon;Jo, Min-Jun;Kim, Sungwhan
    • The Journal of the Korea Contents Association
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    • v.21 no.7
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    • pp.259-270
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    • 2021
  • Recently, interests in the use of Sharing Bike is increasing in consideration of eco-friendly transportation and safety from viruses. As the technology for collecting and storing data is improved with the development of ICTs, research on mobility using the Sharing Bike Data is also actively progressing. Therefore, this paper analyzes the properties of Sharing Bike Data and cases of researches on it through literature review, and based on the results of the review, data of Eoulling, the Sharing Bike System of Sejong City is analyzed as a way to utilize Sharing Bike Data. Most of the selected literature used structured data, and analyzed it through statistical methods or data mining. Through data analysis, it identified the current status, found out problems of the Sharing Bike System, proposed a solution to solve them, developed plans to activate the use of Sharing Bike. This provides basic data for efficient management and operation plans for Sharing Bike System. Ultimately, it will be possible to explore ways to improve mobility in urban spaces by utilizing Sharing Bike Data.

EC-RPL to Enhance Node Connectivity in Low-Power and Lossy Networks (저전력 손실 네트워크에서 노드 연결성 향상을 위한 EC-RPL)

  • Jeadam, Jung;Seokwon, Hong;Youngsoo, Kim;Seong-eun, Yoo
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.6
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    • pp.41-49
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    • 2022
  • The Internet Engineering Task Force (IETF) has standardized RPL (IPv6 Routing Protocol for Low-power Lossy Network) as a routing protocol for Low Power and Lossy Networks (LLNs), a low power loss network environment. RPL creates a route through an Objective Function (OF) suitable for the service required by LLNs and builds a Destination Oriented Directed Acyclic Graph (DODAG). Existing studies check the residual energy of each node and select a parent with the highest residual energy to build a DODAG, but the energy exhaustion of the parent can not avoid the network disconnection of the children nodes. Therefore, this paper proposes EC-RPL (Enhanced Connectivity-RPL), in which ta node leaves DODAG in advance when the remaining energy of the node falls below the specified energy threshold. The proposed protocol is implemented in Contiki, an open-source IoT operating system, and its performance is evaluated in Cooja simulator, and the number of control messages is compared using Foren6. Experimental results show that EC-RPL has 6.9% lower latency and 5.8% fewer control messages than the existing RPL, and the packet delivery rate is 1.7% higher.