• Title/Summary/Keyword: power optimization

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Research on Minimizing Output Degradation in HJT Cell Separation Using IR Laser Scribing (IR 레이저 스크라이빙에 의한 HJT 셀 분할 시 출력 감소율 최소화에 대한 연구)

  • Eunbi Lee;Sungmin Youn;Minseob Kim;Jinho Shin;Yu Jin Kim;Jeonghun Kim;Min-Joon Park;Chaehwan Jeong
    • Current Photovoltaic Research
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    • v.12 no.2
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    • pp.37-40
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    • 2024
  • One of the current innovation trends in the solar industry is the increase in the size of silicon wafers. As the wafer size increases, the series resistance of the module rises, highlighting the need for research on methods for cutting and bonding solar cells. Among these, the Infrared (IR) laser scribing technique has been extensively researched. However, there is still insufficient optimization research regarding the thermal damage caused by lasers on the Transparent Conductive Oxide (TCO) layer of Heterojunction (HJT) solar cells. Therefore, in this study, we systematically varied conditions such as IR laser scribing speed, frequency, power, and the number of scribes to investigate their impact on the performance of cut cells under each condition. Additionally, we conducted a comparative analysis of thermal damage effects on the TCO layer based on varying scribing depths.

Visual Model of Pattern Design Based on Deep Convolutional Neural Network

  • Jingjing Ye;Jun Wang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.2
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    • pp.311-326
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    • 2024
  • The rapid development of neural network technology promotes the neural network model driven by big data to overcome the texture effect of complex objects. Due to the limitations in complex scenes, it is necessary to establish custom template matching and apply it to the research of many fields of computational vision technology. The dependence on high-quality small label sample database data is not very strong, and the machine learning system of deep feature connection to complete the task of texture effect inference and speculation is relatively poor. The style transfer algorithm based on neural network collects and preserves the data of patterns, extracts and modernizes their features. Through the algorithm model, it is easier to present the texture color of patterns and display them digitally. In this paper, according to the texture effect reasoning of custom template matching, the 3D visualization of the target is transformed into a 3D model. The high similarity between the scene to be inferred and the user-defined template is calculated by the user-defined template of the multi-dimensional external feature label. The convolutional neural network is adopted to optimize the external area of the object to improve the sampling quality and computational performance of the sample pyramid structure. The results indicate that the proposed algorithm can accurately capture the significant target, achieve more ablation noise, and improve the visualization results. The proposed deep convolutional neural network optimization algorithm has good rapidity, data accuracy and robustness. The proposed algorithm can adapt to the calculation of more task scenes, display the redundant vision-related information of image conversion, enhance the powerful computing power, and further improve the computational efficiency and accuracy of convolutional networks, which has a high research significance for the study of image information conversion.

Research Trends in Domestic and International Al chips (국내외 인공지능 반도체에 대한 연구 동향 )

  • Hyun Ji Kim;Se Young Yoon;Hwa Jeong Seo
    • Smart Media Journal
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    • v.13 no.3
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    • pp.36-44
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    • 2024
  • Recently, large-scale artificial intelligence (AI) such as ChatGPT have been developed, and as AI is used across various industrial fields, attention is focused on AI chips (semiconductors). AI chips refer to chips designed for calculations for AI algorithms, and many companies at domestic and abroad, such as NVIDIA, Tesla, and ETRI, are developing AI chips. In this paper, we survey research trends on nine types of AI chips. Currently, many attempts have been made to improve the computational performance of most AI chips, and semiconductors for specific purposes are also being designed. In order to compare various AI semiconductors, each chip is analyzed in terms of operation unit, speed, power, and energy efficiency. We introduce currently existing optimization methodologies for AI computation. Based on this, future research directions for AI semiconductors are presented in this paper.

Evaluation of Edge-Based Data Collection System through Time Series Data Optimization Techniques and Universal Benchmark Development (수집 데이터 기반 경량 이상 데이터 감지 알림 시스템 개발)

  • Woojin Cho;Jae-hoi Gu
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.1
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    • pp.453-458
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    • 2024
  • Due to global issues such as climate crisis and rising energy costs, there is an increasing focus on energy conservation and management. In the case of South Korea, approximately 53.5% of the total energy consumption comes from industrial complexes. In order to address this, we aimed to improve issues through the 'Shared Network Utility Plant' among companies using similar energy utilities to find energy-saving points. For effective energy conservation, various techniques are utilized, and stable data supply is crucial for the reliable operation of factories. Many anomaly detection and alert systems for checking the stability of data supply were dependent on Energy Management Systems (EMS), which had limitations. The construction of an EMS involves large-scale systems, making it difficult to implement in small factories with spatial and energy constraints. In this paper, we aim to overcome these challenges by constructing a data collection system and anomaly detection alert system on embedded devices that consume minimal space and power. We explore the possibilities of utilizing anomaly detection alert systems in typical institutions for data collection and study the construction process.

Density map estimation based on deep-learning for pest control drone optimization (드론 방제의 최적화를 위한 딥러닝 기반의 밀도맵 추정)

  • Baek-gyeom Seong;Xiongzhe Han;Seung-hwa Yu;Chun-gu Lee;Yeongho Kang;Hyun Ho Woo;Hunsuk Lee;Dae-Hyun Lee
    • Journal of Drive and Control
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    • v.21 no.2
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    • pp.53-64
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    • 2024
  • Global population growth has resulted in an increased demand for food production. Simultaneously, aging rural communities have led to a decrease in the workforce, thereby increasing the demand for automation in agriculture. Drones are particularly useful for unmanned pest control fields. However, the current method of uniform spraying leads to environmental damage due to overuse of pesticides and drift by wind. To address this issue, it is necessary to enhance spraying performance through precise performance evaluation. Therefore, as a foundational study aimed at optimizing drone-based pest control technologies, this research evaluated water-sensitive paper (WSP) via density map estimation using convolutional neural networks (CNN) with a encoder-decoder structure. To achieve more accurate estimation, this study implemented multi-task learning, incorporating an additional classifier for image segmentation alongside the density map estimation classifier. The proposed model in this study resulted in a R-squared (R2) of 0.976 for coverage area in the evaluation data set, demonstrating satisfactory performance in evaluating WSP at various density levels. Further research is needed to improve the accuracy of spray result estimations and develop a real-time assessment technology in the field.

Operating Optimization and Economic Evaluation of Multicomponent Gas Separation Process using Pressure Swing Adsorption and Membrane Process (압력 순환 흡착과 막 분리공정을 이용한 다성분 기체의 분리공정 조업 최적화 및 경제성 평가)

  • Kim, Hansol;Lee, Jaewook;Lee, Soobin;Han, Jeehoon;Lee, In-Beum
    • Korean Chemical Engineering Research
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    • v.53 no.1
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    • pp.31-38
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    • 2015
  • At present, carbon dioxide ($CO_2$) emission, which causes global warming, is a major issue all over the world. To reduce $CO_2$ emission directly, commercial deployment of $CO_2$ separation processes has been attempted in industrial plants, such as power plant, oil refinery and steelmaking plant. Besides, several studies have been done on indirect reduction of $CO_2$ emission from recycle of reducing gas (carbon monoxide or hydrogen containing gas) in the plants. Unlike many competing gas separation technologies, pressure swing adsorption (PSA) and membrane filtration are commercially used together or individually to separate a single component from the gas mixture. However, there are few studies on operation of sequential separation process of multi-component gas which has more than two target gas products. In this paper, process simulation model is first developed for two available configurations: $CO_2$ PSA-CO PSA-$H_2$ PSA and $CO_2$ PSA-CO PSA-$H_2$ membrane. Operation optimization and economic evaluation of the processes are also performed. As a result, feed gas contains about 14% of $H_2$ should be used as fuel than separating $H_2$, and $CO_2$ separation should be separated earlier than CO separation when feed gas contains about 30% of $CO_2$ and CO. The simulation results can help us to find an optimal process configuration and operation condition for separation of multicomponent gas with $CO_2$, CO, $H_2$ and other gases.

Evaluation of Image Qualities for a Digital X-ray Imaging System Based on Gd$_2$O$_2$S(Tb) Scintillator and Photosensor Array by Using a Monte Carlo Imaging Simulation Code (몬테카를로 영상모의실험 코드를 이용한 Gd$_2$O$_2$S(Tb) 섬광체 및 광센서 어레이 기반 디지털 X-선 영상시스템의 화질평가)

  • Jung, Man-Hee;Jung, In-Bum;Park, Ju-Hee;Oh, Ji-Eun;Cho, Hyo-Sung;Han, Bong-Soo;Kim, Sin;Lee, Bong-Soo;Kim, Ho-Kyung
    • Journal of Biomedical Engineering Research
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    • v.25 no.4
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    • pp.253-259
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    • 2004
  • in this study, we developed a Monte Carlo imaging simulation code written by the visual C$\^$++/ programing language for design optimization of a digital X-ray imaging system. As a digital X-ray imaging system, we considered a Gd$_2$O$_2$S(Tb) scintillator and a photosensor array, and included a 2D parallel grid to simulate general test renditions. The interactions between X-ray beams and the system structure, the behavior of lights generated in the scintillator, and their collection in the photosensor array were simulated by using the Monte Carlo method. The scintillator thickness and the photosensor array pitch were assumed to 66$\mu\textrm{m}$ and 48$\mu\textrm{m}$, respertively, and the pixel format was set to 256 x 256. Using the code, we obtained X-ray images under various simulation conditions, and evaluated their image qualities through the calculations of SNR (signal-to-noise ratio), MTF (modulation transfer function), NPS (noise power spectrum), DQE (detective quantum efficiency). The image simulation code developed in this study can be applied effectively for a variety of digital X-ray imaging systems for their design optimization on various design parameters.

Optimization of Microalgae-Based Biodiesel Supply Chain Network Under the Uncertainty in Supplying Carbon Dioxide (이산화탄소 원료 공급의 불확실성을 고려한 미세조류 기반 바이오 디젤 공급 네트워크 최적화)

  • Ahn, Yuchan;Kim, Junghwan;Han, Jeehoon
    • Korean Chemical Engineering Research
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    • v.58 no.3
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    • pp.396-407
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    • 2020
  • As fossil fuels are depleted worldwide, alternative resources is required to replace fossil fuels, and biofuels are in the spotlight as alternative resources. Biofuels are produced from biomass, which is a renewable resource to produce biofuels or bio-chemicals. Especially, in order to substitute fossil fuels, the research focusing the biofuel (biodiesel) production based on CO2 and biomass achieves more attention recently. To produce biomass-based biodiesel, the development of a supply chain network is required considering the amounts of feedstocks (ex, CO2 and water) required producing biodiesel, potential locations and capacities of bio-refineries, and transportations of biodiesel produced at biorefineries to demand cities. Although many studies of the biomass-based biodiesel supply chain network are performed, there are few types of research handled the uncertainty in CO2 supply which influences the optimal strategies of microalgae-based biodiesel production. Because CO2, which is used in the production of microalgae-based biodiesel as one of important resources, is captured from the off-gases emitted in power plants, the uncertainty in CO2 supply from power plants has big impacts on the optimal configuration of the biodiesel supply chain network. Therefore, in this study, to handle those issues, we develop the two-stage stochastic model to determine the optimal strategies of the biodiesel supply chain network considering the uncertainty in CO2 supply. The goal of the proposed model is to minimize the expected total cost of the biodiesel supply chain network considering the uncertain CO2 supply as well as satisfy diesel demands at each city. This model conducted a case study satisfying 10% diesel demand in the Republic of Korea. The overall cost of the stochastic model (US$ 12.9/gallon·y) is slightly higher (23%) than that of the deterministic model (US$ 10.5/gallon·y). Fluctuations in CO2 supply (stochastic model) had a significant impact on the optimal strategies of the biodiesel supply network.

Recent Progress in Air-Conditioning and Refrigeration Research : A Review of Papers Published in the Korean Journal of Air-Conditioning and Refrigeration Engineering in 2013 (설비공학 분야의 최근 연구 동향 : 2013년 학회지 논문에 대한 종합적 고찰)

  • Lee, Dae-Young;Kim, Sa Ryang;Kim, Hyun-Jung;Kim, Dong-Seon;Park, Jun-Seok;Ihm, Pyeong Chan
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.26 no.12
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    • pp.605-619
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    • 2014
  • This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during 2013. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. Conclusions are as follows. (1) The research works on the thermal and fluid engineering have been reviewed as groups of fluid machinery, pipes and relative parts including orifices, dampers and ducts, fuel cells and power plants, cooling and air-conditioning, heat and mass transfer, two phase flow, and the flow around buildings and structures. Research issues dealing with home appliances, flows around buildings, nuclear power plant, and manufacturing processes are newly added in thermal and fluid engineering research area. (2) Research works on heat transfer area have been reviewed in the categories of heat transfer characteristics, pool boiling and condensing heat transfer and industrial heat exchangers. Researches on heat transfer characteristics included the results for general analytical model for desiccant wheels, the effects of water absorption on the thermal conductivity of insulation materials, thermal properties of Octadecane/xGnP shape-stabilized phase change materials and $CO_2$ and $CO_2$-Hydrate mixture, effect of ground source heat pump system, the heat flux meter location for the performance test of a refrigerator vacuum insulation panel, a parallel flow evaporator for a heat pump dryer, the condensation risk assessment of vacuum multi-layer glass and triple glass, optimization of a forced convection type PCM refrigeration module, surface temperature sensor using fluorescent nanoporous thin film. In the area of pool boiling and condensing heat transfer, researches on ammonia inside horizontal smooth small tube, R1234yf on various enhanced surfaces, HFC32/HFC152a on a plain surface, spray cooling up to critical heat flux on a low-fin enhanced surface were actively carried out. In the area of industrial heat exchangers, researches on a fin tube type adsorber, the mass-transfer kinetics of a fin-tube-type adsorption bed, fin-and-tube heat exchangers having sine wave fins and oval tubes, louvered fin heat exchanger were performed. (3) In the field of refrigeration, studies are categorized into three groups namely refrigeration cycle, refrigerant and modeling and control. In the category of refrigeration cycle, studies were focused on the enhancement or optimization of experimental or commercial systems including a R410a VRF(Various Refrigerant Flow) heat pump, a R134a 2-stage screw heat pump and a R134a double-heat source automotive air-conditioner system. In the category of refrigerant, studies were carried out for the application of alternative refrigerants or refrigeration technologies including $CO_2$ water heaters, a R1234yf automotive air-conditioner, a R436b water cooler and a thermoelectric refrigerator. In the category of modeling and control, theoretical and experimental studies were carried out to predict the performance of various thermal and control systems including the long-term energy analysis of a geo-thermal heat pump system coupled to cast-in-place energy piles, the dynamic simulation of a water heater-coupled hybrid heat pump and the numerical simulation of an integral optimum regulating controller for a system heat pump. (4) In building mechanical system research fields, twenty one studies were conducted to achieve effective design of the mechanical systems, and also to maximize the energy efficiency of buildings. The topics of the studies included heating and cooling, HVAC system, ventilation, and renewable energies in the buildings. Proposed designs, performance tests using numerical methods and experiments provide useful information and key data which can improve the energy efficiency of the buildings. (5) The field of architectural environment is mostly focused on indoor environment and building energy. The main researches of indoor environment are related to infiltration, ventilation, leak flow and airtightness performance in residential building. The subjects of building energy are worked on energy saving, operation method and optimum operation of building energy systems. The remained studies are related to the special facility such as cleanroom, internet data center and biosafety laboratory. water supply and drain system, defining standard input variables of BIM (Building Information Modeling) for facility management system, estimating capability and providing operation guidelines of subway station as shelter for refuge and evaluation of pollutant emissions from furniture-like products.

Depiction of Acute Stroke Using 3-Tesla Clinical Amide Proton Transfer Imaging: Saturation Time Optimization Using an in vivo Rat Stroke Model, and a Preliminary Study in Human

  • Park, Ji Eun;Kim, Ho Sung;Jung, Seung Chai;Keupp, Jochen;Jeong, Ha-Kyu;Kim, Sang Joon
    • Investigative Magnetic Resonance Imaging
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    • v.21 no.2
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    • pp.65-70
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    • 2017
  • Purpose: To optimize the saturation time and maximizing the pH-weighted difference between the normal and ischemic brain regions, on 3-tesla amide proton transfer (APT) imaging using an in vivo rat model. Materials and Methods: Three male Wistar rats underwent middle cerebral artery occlusion, and were examined in a 3-tesla magnetic resonance imaging (MRI) scanner. APT imaging acquisition was performed with 3-dimensional turbo spin-echo imaging, using a 32-channel head coil and 2-channel parallel radiofrequency transmission. An off-resonance radiofrequency pulse was applied with a Sinc-Gauss pulse at a $B_{1,rms}$ amplitude of $1.2{\mu}T$ using a 2-channel parallel transmission. Saturation times of 3, 4, or 5 s were tested. The APT effect was quantified using the magnetization-transfer-ratio asymmetry at 3.5 ppm with respect to the water resonance (APT-weighted signal), and compared with the normal and ischemic regions. The result was then applied to an acute stroke patient to evaluate feasibility. Results: Visual detection of ischemic regions was achieved with the 3-, 4-, and 5-s protocols. Among the different saturation times at $1.2{\mu}T$ power, 4 s showed the maximum difference between the ischemic and normal regions (-0.95%, P = 0.029). The APTw signal difference for 3 and 5 s was -0.9% and -0.7%, respectively. The 4-s saturation time protocol also successfully depicted the pH-weighted differences in an acute stroke patient. Conclusion: For 3-tesla turbo spin-echo APT imaging, the maximal pH-weighted difference achieved when using the $1.2{\mu}T$ power, was with the 4 s saturation time. This protocol will be helpful to depict pH-weighted difference in stroke patients in clinical settings.