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A study of 3D CAD and DLP 3D printing educational course (3D CAD와 DLP 3D 프린팅 교육과정에 관한 연구)

  • Young Hoon Kim;Jeongwon Seok
    • Journal of the Korean Crystal Growth and Crystal Technology
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    • v.33 no.1
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    • pp.22-30
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    • 2023
  • Currently, almost all product development in the jewelry industry utilizes 3D CAD and 3D printing. In this situation, 3D CAD modeling and 3D printing ability units in colleges, Tomorrow Learning Card Education, and Course Evaluation-type jewelry design related education are conducted with developed curriculum based on the standards for training standards, training hours, training equipment, and practice materials presented by NCS. Accordingly, this study analyzes 3D CAD modeling and 3D printing training facilities, training hours, training equipment, etc into three categories of NCS precious metal processing and jewelry design, and studies the development of educational systems such as 3D CAD/3D printing curriculum and various environments that meet these standards. Education using this 3D CAD/3D printing education system will enable us to continuously supply professional talent with practical skills not only in the jewelry industry but also in the entire 3D CAD/3D printing manufacturing industry, which is called as one of the pillars of the 4th Industry. The quality of employment of trainees receiving education and the long-term retention rate after employed can also have a positive effect. In addition, excellent educational performance will help improve the recruitment rate of new students in jewelry jobs or manufacturing-related departments, which are difficult to recruit new students in recent years.

Apartment Price Prediction Using Deep Learning and Machine Learning (딥러닝과 머신러닝을 이용한 아파트 실거래가 예측)

  • Hakhyun Kim;Hwankyu Yoo;Hayoung Oh
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.2
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    • pp.59-76
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    • 2023
  • Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.

Acoustic outputs from clinical extracorporeal shock wave lithotripsy devices (임상에서 사용중인 체외충격파쇄석기의 음향 출력 분포)

  • Jong Min Kim;Oh Bin Kwon;Jin Sik Cho;Sung Joung Jeon;Ki Il Nam;Sung Yong Cho;Min Joo Choi
    • The Journal of the Acoustical Society of Korea
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    • v.42 no.5
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    • pp.469-490
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    • 2023
  • Survey was carried out on the acoustic outputs from 12 shock wave fields produced by the 10 extracorporeal shock wave lithotriptors whose technical documents are available, among the 33 devices approved by the Ministry of Food & Drug Safety (MFDS).The results show that the acoustic outputs (P+, P-, efd, and E), critical to the therapeutic efficacy and the patient safety, are largely different between the devices. The maximum values of P+, P-, efd, and E vary up to 2.08, 3.72, 3.89, and 15.98 times, respectively. The acoustic output parameters are not thoroughly provided in the technical documents, and some of data (eg. efd) are suspected to be abnormal outside usual ranges. The large device to device differences in the shock wave outputs are likely to undermine equivalence between the ESWL devices approved for the same indication. To verify the reliability of the data in the technical documents of the approved devices and to confirm if the acoustic outputs from the devices in clinical use are the same as those in their technical documents, an authorized test laboratory should be available. A postapproval monitoring led by the regulatory agency is suggested to maintain the acoustic outputs from the ESWL devices that suffer from degrading in performance due to aging.

A Study on Machine Learning of the Drivetrain Simulation Model for Development of Wind Turbine Digital Twin (풍력발전기 디지털트윈 개발을 위한 드라이브트레인 시뮬레이션 모델의 기계학습 연구)

  • Yonadan Choi;Tag Gon Kim
    • Journal of the Korea Society for Simulation
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    • v.32 no.3
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    • pp.33-41
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    • 2023
  • As carbon-free has been getting interest, renewable energy sources have been increasing. However, renewable energy is intermittent and variable so it is difficult to predict the produced electrical energy from a renewable energy source. In this study, digital-twin concept is applied to solve difficulties in predicting electrical energy from a renewable energy source. Considering that rotation of wind turbine has high correlation with produced electrical energy, a model which simulates rotation in the drivetrain of a wind turbine is developed. The base of a drivetrain simulation model is set with well-known state equation in mechanical engineering, which simulates the rotating system. Simulation based machine learning is conducted to get unknown parameters which are not provided by manufacturer. The simulation is repeated and parameters in simulation model are corrected after each simulation by optimization algorithm. The trained simulation model is validated with 27 real wind turbine operation data set. The simulation model shows 4.41% error in average compared to real wind turbine operation data set. Finally, it is assessed that the drivetrain simulation model represents the real wind turbine drivetrain system well. It is expected that wind-energy-prediction accuracy would be improved as wind turbine digital twin including the developed drivetrain simulation model is applied.

Analysis of Crushing/Classification Process for Recovery of Black Mass from Li-ion Battery and Mathematical Modeling of Mixed Materials (폐배터리 블랙 매스(black mass) 회수를 위한 파쇄/분급 공정 분석 및 2종 혼합물의 수학적 분쇄 모델링)

  • Kwanho Kim;Hoon Lee
    • Resources Recycling
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    • v.31 no.6
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    • pp.81-91
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    • 2022
  • The use of lithium-ion batteries increases significantly with the rapid spread of electronic devices and electric vehicle and thereby an increase in the amount of waste batteries is expected in the near future. Therefore, studies are continuously being conducted to recover various resources of cathode active material (Ni, Co, Mn, Li) from waste battery. In order to recover the cathode active material, black mass is generally recovered from waste battery. The general process of recovering black mass is a waste battery collection - discharge - dismantling - crushing - classification process. This study focus on the crushing/classification process among the processes. Specifically, the particle size distribution of various samples at each crushing/classification step were evaluated, and the particle shape of each particle fraction was analyzed with a microscope and SEM (Scanning Electron Microscopy)-EDS(Energy Dispersive Spectrometer). As a result, among the black mass particle, fine particle less than 74 ㎛ was the mixture of cathode and anode active material which are properly liberated from the current metals. However, coarse particle larger than 100 ㎛ was present in a form in which the current metal and active material were combined. In addition, this study developed a PBM(Population Balance Model) system that can simulate two-species mixture sample with two different crushing properties. Using developed model, the breakage parameters of two species was derived and predictive performance of breakage distribution was verified.

Development and Application of Penetration Type Field Shear Wave Apparatus (관입형 현장 전단파 측정장치의 개발 및 적용)

  • Lee, Jong-Sub;Lee, Chang-Ho;Yoon, Hyung-Koo;Lee, Woo-Jin;Kim, Hyung-Sub
    • Journal of the Korean Geotechnical Society
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    • v.22 no.12
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    • pp.67-76
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    • 2006
  • The reasonable assessment of the shear stiffness of a dredged soft ground and soft clay is difficult due to the soil disturbance. This study addresses the development and application of a new in-situ shear wave measuring apparatus (field velocity probe: FVP), which overcomes several of the limitations of conventional methods. Design concerns of this new apparatus include the disturbance of soils, cross-talking between transducers, electromagnetic coupling between cables, self acoustic insulation, the constant travel distance of S-wave, the rotation of the transducer, directly transmitted wave through a frame from transducer to transducer, and protection of the transducer and the cable. These concerns are effectively eliminated by continuous improvements through performing field and laboratory tests. The shear wave velocity of the FVP is simply calculated, without any inversion process, by using the travel distance and the first arrival time. The developed FVP Is tested in soil up to 30m in depth. The experimental results show that the FVP can produce every detailed shear wave velocity profiles in sand and clay layers. In addition, the shear wave velocity at the tested site correlates well with the cone tip resistance. This study suggests that the FVP may be an effective technique for measuring the shear wave velocity in the field to assess dynamic soil properties in soft ground.

A Study on Test Set to prevent illegal films searches (불법촬영물 검색 방지를 위한 시험 세트 방안 연구)

  • Yong-Nyuo Shin
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.3
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    • pp.27-33
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    • 2023
  • Countries around the world are calling for stronger law enforcement to combat the production and distribution of child sexual exploitation images, such as child grooming. Given the scale and importance of this social problem, it requires extensive cooperation between law enforcement, government, industry, and government organizations. In the wake of the Nth Room Case, there have been some amendments to the Enforcement Decree of the Telecommunications Business Act regarding additional telecommunications services provided by precautionary operators in Korea. While Naver and others in Korea use Electronics and Telecommunications Research Institute's own technology to filter illegal images, Microsoft uses its own PhotoDNA technology. Microsoft's PhotoDNA is so good at comparing and identifying illegal images that major global operators such as Twitter are using it to detect and filter images. In order to meet the Korean government's testing standards, Microsoft has conducted more than 16 performance tests on "PhotoDNA for Video 2.0A," which is being applied to the Bing service, in cooperation with the Korea Communications Commission and Telecommunications Technology Association. In this paper, we analyze the cases that did not pass the standards and derive improvement measures related to adding logos. In addition, we propose to use three video datasets for the performance test of filtering against illegal videos.

A Study on the Performance Analysis of LINC+ Program (LINC+사업 성과 분석에 관한 연구)

  • Seo, Kyung-Hwa;Kim, Chang-Suk;Lee, Ju-Yeong;Han, Jung-Hee;Kim, Hyun-Soo;Han, Young-Jin;Jung, Young-Jin
    • Journal of Convergence for Information Technology
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    • v.12 no.3
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    • pp.186-192
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    • 2022
  • This study investigated 110 contractual industries to identify the effects of curriculum development and educational environment improvement through Ulsan College LINC+ Program on job education and training. As a result of the study, core competency and job competency were 5.73 points each in field practice and educational environment, and job performance was significant with OJT 5.58 points and 5.74 points for educational environment(p<0.05). The relationship between suitability of the curriculum, educational environment, and recruitment performance was significant with 5.73 points for OJT, 5.74 points for field training during the education and training period, and 5.79 points for educational environment, and job reeducation/training expense was significant with 5.73 points for OJT and 5.79 points for educational environment(p<0.05). Also, students who completed the LINC+business curriculum shortened their job period by 1 to 6 months in 86.3% of the respondents, and responded that the education expense for new employees was reduced. Therefore, it was identified that the LINC+ Program of Ulsan College has the effect of shortening the job adaptation period and reducing education expenses for new employees by operating the curriculum reflecting the needs of the industry and improving the same educational environment as the industrial field.

Hierarchical Circuit Visualization for Large-Scale Quantum Computing (대규모 양자컴퓨팅 회로에 대한 계층적 시각화 기법)

  • Kim, JuHwan;Choi, Byung-Soo;Jo, Dongsik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.611-613
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    • 2021
  • Recently, research and development of quantum computers, which exceed the limits of classical computers, have been actively carried out in various fields. Quantum computers, which use quantum mechanics principles in a way different from the electrical signal processing of classical computers, have various quantum mechanical phenomena such as quantum superposition and quantum entanglement. It goes through a very complicated calculation process compared to the calculation of a classical computer for performing an operation using its characteristics. In order to utilize each element efficiently and accurately, it is necessary to visualize the data before driving the actual quantum computer and perform error verification, optimization, reliability, and verification. However, when visualizing all the data of various elements configured inside the quantum computer, it is difficult to intuitively grasp the necessary data, so it is necessary to visualize the data selectively. In this paper, we visualize the data of various elements that make up a quantum computer, and hierarchically visualize the internal circuit components of a quantum computer that are complicatedly configured so that the data can be observed and utilized intuitively.

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The effect of corporate field teacher and corporate education satisfaction on apprenticeship education satisfaction and student job competency - Focusing on NCS job standards and apprenticeship school project group types - (기업현장교사 및 기업교육의 만족도가 도제교육 만족도와 직무역량 함양에 미치는 영향 - NCS 직무표준과 사업단 유형을 중심으로 - )

  • Yoojeong Kim;Hong Sub-Keun;Kim In-Yeop
    • Industry Promotion Research
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    • v.8 no.1
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    • pp.83-94
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    • 2023
  • This study explored the effect of corporate field teacher and corporate education satisfaction on apprenticeship education satisfaction and student job competency development focusing on NCS job standards and industry-academia-integrated apprenticeship school project group. As a result of the study, satisfaction with corporate field teachers in the electrical, electronic, and food service sectors was found to have a positive influence on improving students' job competency, while satisfaction with corporate education was important in the management, accounting, office, and information and communication sectors. In the analysis by type of project group, the satisfaction of corporate field teachers in the joint practice type and industry-led type had a strong influence on improving job competency, but in the base school type and single school type, corporate education satisfaction had a greater influence on capacity improvement. Therefore, it is necessary to redefine the competencies of corporate field teachers and to establish and implement an industry-academic integrated apprenticeship school operation plan with the relationship between the type of project group and NCS job standard classification.