• Title/Summary/Keyword: 모듈 시스템

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A Comparative Study of the Vocational Education Training in Germany, Switzerland and Austria (독어권 국가의 도제훈련제도 비교연구)

  • Choi, Sujung;Bae, Suhyun;Jeong, SeongJi
    • Journal of vocational education research
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    • v.35 no.6
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    • pp.113-141
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    • 2016
  • The apprenticeship training is given as a solution of the youth unemployment problem. The apprenticeship is a system that companies hire and instruct trainees and is implemented in various countries. In Korea, there is a Korean work-learning dual system which is managed by the government rather than the company itself. This Study analyzed Germany, Switzerland and Austria's apprenticeship training system and compared common factors of apprenticeship system, a trainer in company and cost-benefit analysis. The result of the study can be shown as follows. First, Germany operates practical training, meanwhile Switzerland and Austria provide a pre-education course before students enter the upper-secondary VET course. Second, Germany and Switzerland give a single type apprenticeship training, whereas Austria runs a modularization system, which enables students to specify their skills and improves clarity. Third, social partners as well as the government, states, companies/schools actively participate in apprenticeship. Fourth, there is a suitable trainer's qualification system in all countries. Finally, Germany and Austria's companies cause larger cost than benefit in apprenticeship. On the other hand, Switzerland gets larger net-benefit than cost. We can give implications to the Korean work-learning dual system based on this study.

The Development of Productivity Prediction Model for Interior Finishes of Apartment using Deep Learning Techniques (Deep Learning 기반 공동주택 마감공사 단위작업별 생산성 예측모델 개발 - 내장공사를 중심으로 -)

  • Lee, Giryun;Han, Choong-Hee;Lee, Junbok
    • Korean Journal of Construction Engineering and Management
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    • v.20 no.2
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    • pp.3-12
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    • 2019
  • Despite the importance and function of productivity information, in the Korean construction industry, the method of collecting and analyzing productivity data has not been organized. Also, in most cases, productivity management is reliant on the experience and intuitions of field managers, and productivity data are rarely being utilized in planning and management. Accordingly, this study intends to develop a prediction model for interior finishes of apartment using deep learning techniques, so as to provide a foundation for analyzing the productivity impacting factors and predicting productivity. The result of the study, productivity prediction model for interior finishes of apartment using deep learning techniques, can be a basic module of apartment project management system by applying deep learning to reliable productivity data and developing as data is accumulated in the future. It can also be used in project engineering processes such as estimating work, calculating work days for process planning, and calculating input labor based on productivity data from similar projects in the past. Further, when productivity diverging from predicted productivity is discovered during construction, it is expected that it will be possible to analyze the cause(s) thereof and implement prompt response and preventive measures.

A Study on Heat Transfer and Pressure Drop Characteristics according to Block Size and Turbulence Generator's Placement in a Horizontal Channel (블록 크기 및 난류발생기 배치에 따른 수평채널내의 열전달 및 압력강하 특성에 관한 연구)

  • Seo, Kyu-Won;Lim, Jong-Han;Yoon, Jun-Kyu
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.4
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    • pp.639-647
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    • 2019
  • Recently, as the semiconductor integration technology due to miniaturization and high density of electronic equipment have developed, it is importantly recognized the application of thermal control system in order to release inner heat generated from chips, modules, In this study, we considered the heat transfer and pressure drop characteristics in a horizontal channel with four blocks using k-${\omega}$ SST turbulence model During CFD (Computational Fluid Dynamics) analysis, the parameters applied block width, block height, heat source and turbulence generator placement etc. As the boundary conditions of analysis, the channel inlet temperature and flow velocity were respectively 300 K and 3.84 m/s, the heat flux was $358W/m^2$. As a result, the heat transfer performance was decreased as the block width ratio (w/h) was increased, while it was increased as the block height ratio (h/w) was increased. In addition, as the arrangement of heat source size was increased to high heat flux from low heat flux, it was influenced by heat source size and the heat transfer coefficient showed a tendency to increase, When the turbulence generator was installed in the upper part of block No. 1 position the closely to the channel entrance, the heat transfer characteristics was greatly influenced on the whole of four heating blocks. and in oder to consider the pressure drop characteristics, we are able to select the most appropriate turbulence generator's position.

A Security Nonce Generation Algorithm Scheme Research for Improving Data Reliability and Anomaly Pattern Detection of Smart City Platform Data Management (스마트시티 플랫폼 데이터 운영의 이상패턴 탐지 및 데이터 신뢰성 향상을 위한 보안 난수 생성 알고리즘 방안 연구)

  • Lee, Jaekwan;Shin, Jinho;Joo, Yongjae;Noh, Jaekoo;Kim, Jae Do;Kim, Yongjoon;Jung, Namjoon
    • KEPCO Journal on Electric Power and Energy
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    • v.4 no.2
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    • pp.75-80
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    • 2018
  • The smart city is developing an energy system efficiently through a common management of the city resource for the growth and a low carbon social. However, the smart city doesn't counter a verification effectively about a anomaly pattern detection when existing security technology (authentication, integrity, confidentiality) is used by fixed security key and key deodorization according to generated big data. This paper is proposed the "security nonce generation based on security nonce generation" for anomaly pattern detection of the adversary and a safety of the key is high through the key generation of the KDC (Key Distribution Center; KDC) for improvement. The proposed scheme distributes the generated security nonce and authentication keys to each facilities system by the KDC. This proposed scheme can be enhanced to the security by doing the external pattern detection and changed new security key through distributed security nonce with keys. Therefore, this paper can do improving the security and a responsibility of the smart city platform management data through the anomaly pattern detection and the safety of the keys.

$AB^2$ Semi-systolic Architecture over GF$GF(2^m)$ ($GF(2^m)$상에서 $AB^2$ 연산을 위한 세미시스톨릭 구조)

  • 이형목;전준철;유기영;김현성
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.12 no.2
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    • pp.45-52
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    • 2002
  • In this contributions, we propose a new MSB(most significant bit) algorithm based on AOP(All One Polynomial) and two parallel semi-systolic architectures to computes $AB^2$over finite field $GF(2^m)$. The proposed architectures are based on standard basis and use the property of irreducible AOP(All One Polynomial) which is all coefficients of 1. The proposed parallel semi-systolic architecture(PSM) has the critical path of $D_{AND2^+}D_{XOR2}$ per cell and the latency of m+1. The modified parallel semi-systolic architecture(WPSM) has the critical path of $D_{XOR2}$ per cell and has the same latency with PSM. The proposed two architectures, PSM and MPSM, have a low latency and a small hardware complexity compared to the previous architectures. They can be used as a basic architecture for exponentiation, division, and inversion. Since the proposed architectures have regularity, modularity and concurrency, they are suitable for VLSI implementation. They can be used as a basic architecture for algorithms, such as the Diffie-Hellman key exchange scheme, the Digital Signature Algorithm(DSA), and the ElGamal encryption scheme which are needed exponentiation operation. The application of the algorithms can be used cryptosystem implementation based on elliptic curve.

A Study on the Maximization of Scintillation Pixel Array According to the Size of the Photosensor (광센서 크기에 따른 섬광 픽셀 배열의 최대화 연구)

  • Lee, Seung-Jae
    • Journal of the Korean Society of Radiology
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    • v.16 no.2
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    • pp.157-162
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    • 2022
  • Since preclinical positron emission tomography imaging is performed on small animals that are very small compared to the human body, a detector with excellent spatial resolution is required. For this purpose, a system was constructed using a detector using small scintillation pixels. Since the size of the currently developed and used photosensors is limited, excellent spatial resolution can be obtained when the minimum scintillation pixel and maximum array are used. In this study, the size of the photosensor is fixed and various scintillation pixel arrays are configured to match the size of the scintillation pixels, so that no overlap occurs in the flood image and the maximum scintillation pixel array in which all scintillation pixels are distinguished. For this purpose, DETECT2000, which can simulate a detector module composed of a scintillator and an photosensor, was used. A photosensor consisting of a 4 × 4 array of 3 mm × 3 mm pixels was used, and the scintillation pixel array was configured from 8 × 8 to 13 × 13, and simulations were performed. A flood image was constructed using the data obtained from the photosensor pixel, and the maximum scintillation pixel array that does not overlap the image was found through the flood image and the profile. As a result, the size of the scintillation pixel array in which all scintillation pixels are imaged without overlapping each other in the flood image was 11 × 11.

Quantitative Analysis of Damage Impacts in case of Bunkering NH3 from Tank Lorry to Fishing Vessel (어선-탱크로리 간의 NH3 이적 시 누출에 따른 정량적 피해영향분석)

  • Lim, Sang-Jin;Choi, Bu-Hong;Lee, Yoon-Ho
    • Journal of the Korean Institute of Gas
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    • v.26 no.3
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    • pp.10-20
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    • 2022
  • About 21% of domestic chemical accidents are caused by transport vehicles for the past 10 years in Korea. Also, ammonia is a chemical substance with the largest number of accidents, 82 out of 672. In this study, supposed seasonal alternative scenario and worst scenario in case of releasing ammonia during bunkering it from tank lorry to fishing vessel and interpreted seasonal impact and range through Python, ALOHA, Probit analysis. Radiation impact range of possibility for 2nd burn and for maximum radiation in winter scenario, which is one of the alternative scenarios, was the highest(range: 41m, radiation: 5.01kW/m2) while overpressure impact was less than minimum standard of impact. And toxicity impact range(EPRG-2) of the summer scenario was the widest(5.0km) and took a very high death rate near accident area(port area, tourist area) according to Probit analysis. the wort scenario had a similar impact and range of summer scenario.

Development of Portable Multi-function Sensor (Mini CPT Cone + VWC Sensor) to Improve the Efficiency of Slope Inspection (비탈면 점검 효율화를 위한 휴대형 복합센서 개발)

  • Kim, Jong-Woo;Jho, Youn-Beom
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.26 no.1
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    • pp.49-57
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    • 2022
  • In order to efficiently analysis the stability of a slope, measuring the shear strength of soil is needed. The Standard Penetration Test (SPT) is not appropriate for a slope inspection due to cost and weights. One of the ways to effectively measure the N-value is the Dynamic Cone Penetration Test (DCPT). This study was performed to develop a minimized multi-function sensors that can easily estimate CPT values and Volumetric Water Content. N value with multi-fuction sensor DCPT showed -2.5 ~ +3.9% error compared with the SPT N value (reference value) in the field tests. Also, the developed multi-fuction sensor system was tested the correlation between the CPT test and the portable tester with indoor test. The test result showed 0.85 R2 value in soil, 0.83 in weathered soil, and 0.98 in mixed soil. As a result of the field test, the multi-function sensor shows the excellent field applicability of the proposed sensor system. After further research, it is expected that the portable multi-function sensor will be useful for general slope inspection.

A Study on Secure Encoding for Visible Light Communication Without Performance Degradation (가시광 통신에서 성능 저하 없는 보안 인코딩 연구)

  • Kim, Minchul;Suh, Taeweon
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.1
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    • pp.35-42
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    • 2022
  • Visible light communication (VLC) is a method of transmitting data through LED blinking and is vulnerable to eavesdropping because the illumination affects the wide range of area. IEEE standard 802.15.7 defines On-Off Keying (OOK), Variable Pulse Position Modulation (VPPM), and Color Shift Keying (CSK) as modulation. In this paper, we propose an encryption method in VPPM for secure communication. The VPPM uses an encoding method called 4B6B where 16 different outputs are represented with 6-bit. This paper extends the number of outputs to 20, to add complexity while not violating the 4B6B generation conditions. Then each entry in the extended 4B6B table is scrambled using vigenère cipher. The probability of decrypting each 6-bit data is $\frac{1}{20}$. Eavesdropper should perform $\sum\limits_{k=1}^{n}20^k$ number of different trials to decrypt the message if the number of keys is n. The proposed method can be applied to OOK of PHY II and CSK of PHY III. We further discuss the secure encoding that can be used in OOK and CSK without performance degradation.

Improved Anatomical Landmark Detection Using Attention Modules and Geometric Data Augmentation in X-ray Images (어텐션 모듈과 기하학적 데이터 증강을 통한 X-ray 영상 내 해부학적 랜드마크 검출 성능 향상)

  • Lee, Hyo-Jeong;Ma, Se-Rie;Choi, Jang-Hwan
    • Journal of the Korea Computer Graphics Society
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    • v.28 no.3
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    • pp.55-65
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    • 2022
  • Recently, deep learning-based automated systems for identifying and detecting landmarks have been proposed. In order to train such a deep learning-based model without overfitting, a large amount of image and labeling data is required. Conventionally, an experienced reader manually identifies and labels landmarks in a patient's image. However, such measurement is not only expensive, but also has poor reproducibility, so the need for an automated labeling method has been raised. In addition, in the X-ray image, since various human tissues on the path through which the photons pass are displayed, it is difficult to identify the landmark compared to a general natural image or a 3D image modality image. In this study, we propose a geometric data augmentation technique that enables the generation of a large amount of labeling data in X-ray images. In addition, the optimal attention mechanism for landmark detection was presented through the implementation and application of various attention techniques to improve the detection performance of 16 major landmarks in the skull. Finally, among the major cranial landmarks, markers that ensure stable detection are derived, and these markers are expected to have high clinical application potential.