• Title/Summary/Keyword: optimizing

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Deep Neural Network Analysis System by Visualizing Accumulated Weight Changes (누적 가중치 변화의 시각화를 통한 심층 신경망 분석시스템)

  • Taelin Yang;Jinho Park
    • Journal of the Korea Computer Graphics Society
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    • v.29 no.3
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    • pp.85-92
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    • 2023
  • Recently, interest in artificial intelligence has increased due to the development of artificial intelligence fields such as ChatGPT and self-driving cars. However, there are still many unknown elements in training process of artificial intelligence, so that optimizing the model requires more time and effort than it needs. Therefore, there is a need for a tool or methodology that can analyze the weight changes during the training process of artificial intelligence and help out understatnding those changes. In this research, I propose a visualization system which helps people to understand the accumulated weight changes. The system calculates the weights for each training period to accumulates weight changes and stores accumulated weight changes to plot them in 3D space. This research will allow us to explore different aspect of artificial intelligence learning process, such as understanding how the model get trained and providing us an indicator on which hyperparameters should be changed for better performance. These attempts are expected to explore better in artificial intelligence learning process that is still considered as unknown and contribute to the development and application of artificial intelligence models.

Design and Implementation of IEC62541-based Industry-Internet of Things Simulator for Meta-Factory (메타팩토리를 위한 IEC62541기반 IIoT·시뮬레이터 설계 및 구현)

  • Chae-Young Lim;Chae-Eun Yeo;Woo-jin Cho;Jae-Hoi Gu;Sang-Hyun Lee
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.789-795
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    • 2023
  • Digital-Twin are recognized as an important core technology for the realization of Smart Factories by simulating and optimizing the monitoring and predictive maintenance of manufacturing equipment and the operation of production lines in a digital space. To implement this system, we adopt the IEC62541-based OPC-UA (Open Platform Communications Unified-Architecture) Protocol, which has strengths in interoperability and connectivity between heterogeneous platforms. Therefore, In this paper, We designed and implemented an IIoT(Industry Internet of Things) system that connects heterogeneous platforms, and developed an OPC-UA simulator based on IEC 62541. We will present whether the data will be applied to the Digital-Twin Platform and whether it will work, and proceed with performance tests and evaluations. We evaluate the operation performance and OPC-UA performance of the Digital-Twin platform lightened by the proposed device, and present the optimal IEC62514-based simulator system. We proceeded with the performance evaluation of sending and receiving data with OPC-UA wrapping with the proposed simulator, and found that a lightweight Digital-Twin platform can be operated. This research can apply the OPC-UA protocol for implementing smart factory and meta-factory in the manufacturing shop floor with limited resources, avoiding the waste of time and space on the shop floor through the OPC-UA simulator. We expect that this will contribute to a significant improvement in efficiency by minimizing.

Residual Pesticide Analysis Method of Edible Oil via Heat Distillation Methods (가열증류법에 의한 식용유지의 잔류농약 분석법 개발)

  • Mi-Hui Son;Jae-Kwan Kim;Young-Seon Cho;Na-Eun Han;Byeong-Tae Kim;Myoung-Ki Park;Yong-Bae Park
    • Journal of Food Hygiene and Safety
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    • v.38 no.3
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    • pp.89-98
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    • 2023
  • Currently, no guidelines exist regarding the maximum residues of pesticides in edible oil which is a processed food commonly consumed in Korea. This lack of guidelines hinders the evaluation of the safety of edible oil in terms of pesticide contamination. In this study, an analysis method based on heat distillation and GC-MS/MS was established by optimizing the extraction and purification procedure for 68 pesticides. Important variables in the thermal distillation procedure included heating temperature and time, and we found the nitrogen flow rate as a mobile phase and the type of dissolving solvent were not considerably affected. The determination coefficient (R2) of the residual pesticide was 0.99 or higher, and the quantitative limit (LOQ) was 0.01-0.02 mg/L. The average recovery rate (n=5) was 66.1-120.0% and the relative standard deviation was lower than ±10% when 68 pesticides were spiked at concentrations of 0.01-0.02, 0.1, and 0.5 mg/L. In addition, the within-laboratory precision was less than ±11%, meeting the Korea Food and Drug Safety Evaluation Institute's Guidelines on Standard Procedures for Preparing Food Testing Methods (2016). Therefore, the test method developed in this study can be used as a test method for managing the safety of the residual pesticide concentration in edible oil.

Investigation of Microstructure and Ionic Conductivity of Li1.5Al0.5Ti1.5(PO4)3 Ceramic Solid Electrolytes by B2O3 Incorporation (Li1.5Al0.5Ti1.5(PO4)3 세라믹 고체전해질의 B2O3 첨가에 따른 미세구조 및 이온전도도에 대한 연구)

  • Min-Jae Kwon;Hyeon Il Han;Seulgi Shin;Sang-Mo Koo;Weon Ho Shin
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.36 no.6
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    • pp.627-632
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    • 2023
  • Lithium-ion batteries are widely used in various applications, including electric vehicles and portable electronics, due to their high energy density and long cycle life. The performance of lithium-ion batteries can be improved by using solid electrolytes, in terms of higher safety, stability, and energy density. Li1.5Al0.5Ti1.5(PO4)3 (LATP) is a promising solid electrolyte for all-solid-state lithium batteries due to its high ionic conductivity and excellent stability. However, the ionic conductivity of LATP needs to be improved for commercializing all-solid-state lithium battery systems. In this study, we investigate the microstructures and ionic conductivities of LATP by incorporating B2O3 glass ceramics. The smaller grain size and narrow size distribution were obtained after the introduction of B2O3 in LATP, which is attributed to the B2O3 glass on grain boundaries of LATP. Moreover, higher ionic conductivity can be obtained after B2O3 incorporation, where the optimal composition is 0.1 wt% B2O3 incorporated LATP and the ionic conductivity reaches 8.8×10-5 S/cm, more than 3 times higher value than pristine LATP. More research could be followed for having higher ionic conductivity and density by optimizing the processing conditions. This facile approach for establishing higher ionic conductivity in LATP solid electrolytes could accelerate the commercialization of all-solid-state lithium batteries.

Establishment of a deep learning-based defect classification system for optimizing textile manufacturing equipment

  • YuLim Kim;Jaeil Kim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.10
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    • pp.27-35
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    • 2023
  • In this paper, we propose a process of increasing productivity by applying a deep learning-based defect detection and classification system to the prepreg fiber manufacturing process, which is in high demand in the field of producing composite materials. In order to apply it to toe prepreg manufacturing equipment that requires a solution due to the occurrence of a large amount of defects in various conditions, the optimal environment was first established by selecting cameras and lights necessary for defect detection and classification model production. In addition, data necessary for the production of multiple classification models were collected and labeled according to normal and defective conditions. The multi-classification model is made based on CNN and applies pre-learning models such as VGGNet, MobileNet, ResNet, etc. to compare performance and identify improvement directions with accuracy and loss graphs. Data augmentation and dropout techniques were applied to identify and improve overfitting problems as major problems. In order to evaluate the performance of the model, a performance evaluation was conducted using the confusion matrix as a performance indicator, and the performance of more than 99% was confirmed. In addition, it checks the classification results for images acquired in real time by applying them to the actual process to check whether the discrimination values are accurately derived.

A Study on the Economic Efficiency of Tourism Industry in China's Bohai Rim Region Using DEA Model (DEA 모델을 이용한 중국 환 발해만 지역 관광산업의 경제효율성에 관한 연구)

  • Li Ting;Jae Yeon Sim
    • Industry Promotion Research
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    • v.8 no.4
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    • pp.267-276
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    • 2023
  • Based on the tourism input-output data of five provinces and cities in China's Bohai Rim region from 2015~2021, this study analyzes the efficiency of regional tourism using DEA-BCC and DEA-Malmquist index, as well as its contribution to regional economic efficiency, and identifies factors influencing the comprehensive efficiency. The research results indicate that the comprehensive efficiency of the tourism industry in the China Bohai Sea region has reached an optimal level of 88.9%, but there is still room for improvement, with overall fluctuations. The overall productivity of the tourism industry exhibits a "U"-shaped fluctuating pattern, with growth mainly driven by technological advancements. Due to the impact of the COVID-19 pandemic, the region experienced a nearly 50% decrease in total factor productivity in 2019~2020. However, in 2021, with the implementation of various government stimulus policies, the tourism efficiency rapidly recovered to 80% of pre-pandemic levels. In terms of the impact of the tourism industry on the regional economy in the China Bohai Sea region, Hebei Province stands out as a significant contributor. Based on the aforementioned research findings, the following recommendations are proposed in three aspects: optimizing the supply structure, increasing innovation investment, and strengthening internal collaboration. These recommendations provide valuable insights for enhancing regional tourism efficiency and promoting regional synergy.

The Unique Relationship between Neuro-Critical Care and Critical Illness-Related Corticosteroid Insufficiency : Implications for Neurosurgeons in Neuro-Critical Care

  • Yoon Hee Choo;Moinay Kim;Jae Hyun Kim;Hanwool Jeon;Hee-Won Jung;Eun Jin Ha;Jiwoong Oh;Youngbo Shim;Seung Bin Kim;Han-Gil Jung;So Hee Park;Jung Ook Kim;Junhyung Kim;Hyeseon Kim;Seungjoo Lee
    • Journal of Korean Neurosurgical Society
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    • v.66 no.6
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    • pp.618-631
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    • 2023
  • The brain houses vital hormonal regulatory structures such as the hypothalamus and pituitary gland, which may confer unique susceptibilities to critical illness-related corticosteroid insufficiency (CIRCI) in patients with neurological disorders. In addition, the frequent use of steroids for therapeutic purposes in various neurological conditions may lead to the development of steroid insufficiency. This abstract aims to highlight the significance of understanding these relationships in the context of patient care and management for physicians. Neurological disorders may predispose patients to CIRCI due to the role of the brain in hormonal regulation. Early recognition of CIRCI in the context of neurological diseases is essential to ensure prompt and appropriate intervention. Moreover, the frequent use of steroids for treating neurological conditions can contribute to the development of steroid insufficiency, further complicating the clinical picture. Physicians must be aware of these unique interactions and be prepared to evaluate and manage patients with CIRCI and steroid insufficiency in the context of neurological disorders. This includes timely diagnosis, appropriate steroid administration, and careful monitoring for potential adverse effects. A comprehensive understanding of the interplay between neurological disease, CIRCI, and steroid insufficiency is critical for optimizing patient care and outcomes in this complex patient population.

Research and improvement of image analysis and bar code and QR recognition technology for the development of visually impaired applications (시각장애인 애플리케이션 개발을 위한 이미지 분석과 바코드, QR 인식 기술의 연구 및 개선)

  • MinSeok Cho;MinKi Yoon;MinSu Seo;YoungHoon Hwang;Hyun Woo;WonWhoi Huh
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.6
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    • pp.861-866
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    • 2023
  • Individuals with visual impairments face difficulties in accessing accurate information about medical services and medications, making it challenging for them to ensure proper medication intake. While there are healthcare laws addressing this issue, there is a lack of standardized solutions, and not all over-the-counter medications are covered. Therefore, we have undertaken the design of a mobile application that utilizes image recognition technology, barcode scanning, and QR code recognition to provide guidance on how to take over-the-counter medications, filling the existing gaps in the knowledge of visually impaired individuals. Currently available applications for individuals with visual impairments allow them to access information about medications. However, they still require the user to remember which specific medication they are taking, posing a significant challenge. In this research, we are optimizing the camera capture environment, user interface (UI), and user experience (UX) screens for image recognition, ensuring greater accessibility and convenience for visually impaired individuals. By implementing the findings from our research into the application, we aim to assist visually impaired individuals in acquiring the correct methods for taking over-the-counter medications.

Determination of Domoic Acid in Seafood Matrices using HPLC-UV with Solid Phase Extraction Cleanup (고체상 추출 전처리 및 HPLC-UV를 이용한 수산물 중 domoic acid의 분석)

  • Si Eun Kim;Sang Yoo Lee;Ji Eun Park;Hyunjin Jung;Hyang Sook Chun
    • Journal of Food Hygiene and Safety
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    • v.38 no.5
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    • pp.297-304
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    • 2023
  • Domoic acid (DA), a neurotoxin produced naturally by diatoms, is responsible for incidents of amnesic shellfish poisoning. In this study, a modified analytical method was established to determine domoic acid in seafood using solid phase extraction cleanup and optimizing the amount of sample and extraction solvent to reduce interference effects. The modified method using high-performance liquid chromatography with ultraviolet detection was validated using three seafood matrices (mussel, red snow crab, and anchovy) at three concentrations (1, 2, and 4 mg/kg) and compared to the Food Code method. Compared to the Food Code method, the modified method showed better performance in terms of linearity (R2>0.999), detection limit (0.02-0.03 mg/kg), quantification limit (0.05-0.09 mg/kg), intra-/inter-day accuracy (86.2-100.4%), and intra-/inter-day precision (0.2-4.0%). Furthermore, the method was successfully applied for the analysis of 87 seafood samples marketed in Korea, and DA was detected at a low concentration of 140 ㎍/kg in one anchovy sample. These results suggest that the modified method can be used for routine determination of DA in seafood.

Improving Biomass Productivity of Freshwater microalga, Parachlorella sp. by Controlling Gas Supply Rate and Light Intensity in a Bubble Column Photobioreactor (가스공급속도 및 광도조절을 이용한 담수미세조류 Parachlorella sp.의 바이오매스 생산성 향상)

  • Z-Hun Kim;Kyung Jun Yim;Seong-Joo Hong;Huisoo Jang;Hyun-Jin Jang;Suk Min Yun;Seung Hwan Lee;Choul-Gyun Lee;Chang Soo Lee
    • Journal of Marine Bioscience and Biotechnology
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    • v.15 no.2
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    • pp.41-48
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    • 2023
  • The objective of the present study was to improve the biomass productivity of newly isolated freshwater green microalga Parachlorella sp. This was accomplished by culture conditions optimization, including CO2 concentration, superficial gas velocity, and light intensity, in 0.5 L bubble column photobioreactors. The supplied CO2 concentration and gas velocity varied from 0.032% (air) to 10% and 0.02 m/s - 0.11 m/s, respectively, to evaluate their effects on growth kinetics. Next, to maximize the production rate of Parachlorella sp., a lumostatic operation based on a specific light uptake rate (qe) was applied. From these results, the optimal CO2 concentration in the supplied gas and the gas velocity were determined to be 5% and 0.064 m/s, respectively. For the lumostatic operation at 10.2 µmol/g/s, biomass productivity and photon yield showed significant increases of 83% and 66%, respectively, relative to cultures under constant light intensity. These results indicate that the biomass productivity of Parachlorella sp. can be improved by optimizing gas properties and light control as cell concentrations vary over time.