• Title/Summary/Keyword: Optimization.

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Optimization of 1.2 kV 4H-SiC MOSFETs with Vertical Variation Doping Structure (Vertical Variation Doping 구조를 도입한 1.2 kV 4H-SiC MOSFET 최적화)

  • Ye-Jin Kim;Seung-Hyun Park;Tae-Hee Lee;Ji-Soo Choi;Se-Rim Park;Geon-Hee Lee;Jong-Min Oh;Weon Ho Shin;Sang-Mo Koo
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.37 no.3
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    • pp.332-336
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    • 2024
  • High-energy bandgap material silicon carbide (SiC) is gaining attention as a next-generation power semiconductor material, and in particular, SiC-based MOSFETs are developed as representative power semiconductors to increase the breakdown voltage (BV) of conventional planar structures. However, as the size of SJ (Super Junction) MOSFET devices decreases and the depth of pillars increases, it becomes challenging to uniformly form the doping concentration of pillars. Therefore, a structure with different doping concentrations segmented within the pillar is being researched. Using Silvaco TCAD simulation, a SJ VVD (vertical variation doping profile) MOSFET with three different doping concentrations in the pillar was studied. Simulations were conducted for the width of the pillar and the doping concentration of N-epi, revealing that as the width of the pillar increases, the depletion region widens, leading to an increase in on-specific resistance (Ron,sp) and breakdown voltage (BV). Additionally, as the doping concentration of N-epi increases, the number of carriers increases, and the depletion region narrows, resulting in a decrease in Ron,sp and BV. The optimized SJ VVD MOSFET exhibits a very high figure of merit (BFOM) of 13,400 KW/cm2, indicating excellent performance characteristics and suggesting its potential as a next-generation highperformance power device suitable for practical applications.

Analysis of the Effectiveness of Big Data-Based Six Sigma Methodology: Focus on DX SS (빅데이터 기반 6시그마 방법론의 유효성 분석: DX SS를 중심으로)

  • Kim Jung Hyuk;Kim Yoon Ki
    • KIPS Transactions on Software and Data Engineering
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    • v.13 no.1
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    • pp.1-16
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    • 2024
  • Over recent years, 6 Sigma has become a key methodology in manufacturing for quality improvement and cost reduction. However, challenges have arisen due to the difficulty in analyzing large-scale data generated by smart factories and its traditional, formal application. To address these limitations, a big data-based 6 Sigma approach has been developed, integrating the strengths of 6 Sigma and big data analysis, including statistical verification, mathematical optimization, interpretability, and machine learning. Despite its potential, the practical impact of this big data-based 6 Sigma on manufacturing processes and management performance has not been adequately verified, leading to its limited reliability and underutilization in practice. This study investigates the efficiency impact of DX SS, a big data-based 6 Sigma, on manufacturing processes, and identifies key success policies for its effective introduction and implementation in enterprises. The study highlights the importance of involving all executives and employees and researching key success policies, as demonstrated by cases where methodology implementation failed due to incorrect policies. This research aims to assist manufacturing companies in achieving successful outcomes by actively adopting and utilizing the methodologies presented.

Performance Evaluation and Analysis on Single and Multi-Network Virtualization Systems with Virtio and SR-IOV (가상화 시스템에서 Virtio와 SR-IOV 적용에 대한 단일 및 다중 네트워크 성능 평가 및 분석)

  • Jaehak Lee;Jongbeom Lim;Heonchang Yu
    • The Transactions of the Korea Information Processing Society
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    • v.13 no.2
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    • pp.48-59
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    • 2024
  • As functions that support virtualization on their own in hardware are developed, user applications having various workloads are operating efficiently in the virtualization system. SR-IOV is a virtualization support function that takes direct access to PCI devices, thus giving a high I/O performance by minimizing the need for hypervisor or operating system interventions. With SR-IOV, network I/O acceleration can be realized in virtualization systems that have relatively long I/O paths compared to bare-metal systems and frequent context switches between the user area and kernel area. To take performance advantages of SR-IOV, network resource management policies that can derive optimal network performance when SR-IOV is applied to an instance such as a virtual machine(VM) or container are being actively studied.This paper evaluates and analyzes the network performance of SR-IOV implementing I/O acceleration is compared with Virtio in terms of 1) network delay, 2) network throughput, 3) network fairness, 4) performance interference, and 5) multi-network. The contributions of this paper are as follows. First, the network I/O process of Virtio and SR-IOV was clearly explained in the virtualization system, and second, the evaluation results of the network performance of Virtio and SR-IOV were analyzed based on various performance metrics. Third, the system overhead and the possibility of optimization for the SR-IOV network in a virtualization system with high VM density were experimentally confirmed. The experimental results and analysis of the paper are expected to be referenced in the network resource management policy for virtualization systems that operate network-intensive services such as smart factories, connected cars, deep learning inference models, and crowdsourcing.

Recent Developments in Quantum Dot Patterning Technology for Quantum Dot Display (양자점 디스플레이 제작을 위한 양자점 패터닝 기술발전 동향)

  • Yeong Jun Jin;Kyung Jun Jung;Jaehan Jung
    • Journal of Powder Materials
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    • v.31 no.2
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    • pp.169-179
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    • 2024
  • Colloidal quantum dot (QDs) have emerged as a crucial building block for LEDs due to their size-tunable emission wavelength, narrow spectral line width, and high quantum efficiency. Tremendous efforts have been dedicated to improving the performance of quantum dot light-emitting diodes (QLEDs) in the past decade, primarily focusing on optimization of device architectures and synthetic procedures for high quality QDs. However, despite these efforts, the commercialization of QLEDs has yet to be realized due to the absence of suitable large-scale patterning technologies for high-resolution devices., This review will focus on the development trends associated with transfer printing, photolithography, and inkjet printing, and aims to provide a brief overview of the fabricated QLED devices. The advancement of various quantum dot patterning methods will lead to the development of not only QLED devices but also solar cells, quantum communication, and quantum computers.

Optimal Sensor Placement for Improved Prediction Accuracy of Structural Responses in Model Test of Multi-Linked Floating Offshore Systems Using Genetic Algorithms (다중연결 해양부유체의 모형시험 구조응답 예측정확도 향상을 위한 유전알고리즘을 이용한 센서배치 최적화)

  • Kichan Sim;Kangsu Lee
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.37 no.3
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    • pp.163-171
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    • 2024
  • Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.

A Study on the Optimization Period of Light Buoy Location Patterns Using the Convex Hull Algorithm (볼록 껍질 알고리즘을 이용한 등부표 위치패턴 최적화 기간 연구)

  • Wonjin Choi;Beom-Sik Moon;Chae-Uk Song;Young-Jin Kim
    • Journal of Navigation and Port Research
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    • v.48 no.3
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    • pp.164-170
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    • 2024
  • The light buoy, a floating structure at sea, is prone to drifting due to external factors such as oceanic weather. This makes it imperative to monitor for any loss or displacement of buoys. In order to address this issue, the Ministry of Oceans and Fisheries aims to issue alerts for buoy displacement by analyzing historical buoy position data to detect patterns. However, periodic lifting inspections, which are conducted every two years, disrupt the buoy's location pattern. As a result, new patterns need to be analyzed after each inspection for location monitoring. In this study, buoy position data from various periods were analyzed using convex hull and distance-based clustering algorithms. In addition, the optimal data collection period was identified in order to accurately recognize buoy location patterns. The findings suggest that a nine-week data collection period established stable location patterns, explaining approximately 89.8% of the variance in location data. These results can improve the management of light buoys based on location patterns and aid in the effective monitoring and early detection of buoy displacement.

Optimization of MRI Protocol for the Musculoskeletal System (근골격계 자기공명영상 프로토콜의 최적화)

  • Hong Seon Lee;Young Han Lee;Inha Jung;Ok Kyu Song;Sungjun Kim;Ho-Taek Song;Jin-Suck Suh
    • Journal of the Korean Society of Radiology
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    • v.81 no.1
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    • pp.21-40
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    • 2020
  • Magnetic resonance imaging (MRI) is an essential modality for the diagnosis of musculoskeletal system defects because of its higher soft-tissue contrast and spatial resolution. With the recent development of MRI-related technology, faster imaging and various image plane reconstructions are possible, enabling better assessment of three-dimensional musculoskeletal anatomy and lesions. Furthermore, the image quality, diagnostic accuracy, and acquisition time depend on the MRI protocol used. Moreover, the protocol affects the efficiency of the MRI scanner. Therefore, it is important for a radiologist to optimize the MRI protocol. In this review, we will provide guidance on patient positioning; selection of the radiofrequency coil, pulse sequences, and imaging planes; and control of MRI parameters to help optimize the MRI protocol for the six major joints of the musculoskeletal system.

Algorithm for Maximum Degree Vertex Partition of Cutwidth Minimization Problem (절단 폭 최소화 문제의 최대차수 정점 분할 알고리즘)

  • Sang-Un Lee
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.24 no.1
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    • pp.37-42
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    • 2024
  • This paper suggests polynomial time algorithm for cutwidth minimization problem that classified as NP-complete because the polynomial time algorithm to find the optimal solution has been unknown yet. To find the minimum cutwidth CWf(G)=max𝜈VCWf(𝜈)for given graph G=(V,E),m=|V|, n=|E|, the proposed algorithm divides neighborhood NG[𝜈i] of the maximum degree vertex 𝜈i in graph G into left and right and decides the vertical cut plane with minimum number of edges pass through the vertex 𝜈i firstly. Then, we split the left and right NG[𝜈i] into horizontal sections with minimum pass through edges. Secondly, the inner-section vertices are connected into line graph and the inter-section lines are connected by one line layout. Finally, we perform the optimization process in order to obtain the minimum cutwidth using vertex moving method. Though the proposed algorithm requires O(n2) time complexity, that can be obtains the optimal solutions for all of various experimental data

Optimization of Automated Solid Phase Extraction-based Synthesis of [18F]Fluorocholine (고체상 추출법을 기반으로 한 [18F]Fluorocholine 합성법의 최적화 연구)

  • Jun Young PARK;Jeongmin SON;Won Jun KANG
    • Korean Journal of Clinical Laboratory Science
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    • v.55 no.4
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    • pp.261-268
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    • 2023
  • [18F]Fluorocholine is a radiopharmaceutical used non-invasively in positron emission tomography to diagnose parathyroid adenoma, prostate cancer, and hepatocellular carcinoma by evaluating the choline metabolism. In this study, a radiolabeling method for [18F]fluorocholine was optimized using a solid phase extraction (SPE) cartridge. [18F]Fluorocholine was labeled in two steps using an automated synthesizer. In the first step, dibromomethane was reacted with [18F]KF/K2.2.2/K2CO3 to obtain the intermediate [18F]fluorobromomethane. In the second step, [18F]fluorobromomethane was passed through a Sep-Pak Silica SPE cartridge to remove the impurities and then reacted with N,N-dimethylaminoethanol (DMAE) in a Sep-Pak C18 SPE cartridge to label [18F]fluorocholine. The reaction conditions of [18F]fluorocholine were optimized. The synthesis yield was confirmed according to the number of silica cartridges and DMAE concentration. No statistically significant difference in the synthesis yield of [18F]fluorocholine was observed when using four or three silica cartridges (P>0.05). The labeling yield was 11.5±0.5% (N=4) when DMAE was used as its original solution. On the other hand, when diluted to 10% with dimethyl sulfoxide, the radiochemical yield increased significantly to 30.1±5.2% (N=20). In conclusion, [18F]Fluorocholine for clinical use can be synthesized stably in high yield by applying an optimized synthesis method.

Method to Derive the Optimal Vent Position when Flammable Liquid Leaks Based on CFD (CFD 기반 인화성 액체 누출 시 최적의 환기구 배치 도출 방안)

  • Eun-Hee Kim;Seung-Hyo An;Jun-Seo Lee;Byung-Chol Ma
    • Journal of the Korean Institute of Gas
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    • v.28 no.1
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    • pp.11-18
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    • 2024
  • If flammable liquid leaks, vapor evaporated from the pool can cause poisoning or suffocation to workers, leading to secondary accidents such as fires and explosions. To prevent such damage, ventilation facilities shall be installed when designing indoor workplaces. At this time, the behavior varies depending on the characteristics of the leaked chemical, so it is necessary to select a suitable vent location according to the material. Therefore, 3D CFD simulations were introduced to derive optimal vent position and ventilation efficiency was quantitatively evaluated by vent position. At this time, assuming a situation in which flammable liquids leak at indoor workplaces to form pools, the concentration of vapor evaporated from pools was compared to derive the optimal vent position. As a result of research on toluene with high vapor density, ventilation efficiency was confirmed to be the highest at the upper supply-lower exhaust, and it is judged that introducing it can achieve about 3.7 times ventilation effect at the same maintenance cost. Through this study, it is expected that the workplace will be able to secure workers' safety by applying simulation results and installing ventilation ports.