• Title/Summary/Keyword: optimizing

Search Result 2,934, Processing Time 0.033 seconds

Mobbing Value Algorithm for Improvement Victims Management - based on Social Network in Military - (집단 따돌림 희생자 관리 개선을 위한 모빙 지수 알고리즘 - 소셜 네트워크 기반 군 조직을 중심으로 -)

  • Kim, Guk-Jin;Park, Gun-Woo;Lee, Sang-Hoon
    • Journal of the Korea Society of Computer and Information
    • /
    • v.14 no.11
    • /
    • pp.1-12
    • /
    • 2009
  • Mobbing is going the rounds through a society rapidly and Military is not exception. Because mobbing of military is expressed not only psychology exclusion that is mobbing pattern of adult society but also sometimes psychologic and physical mobbing, is possible to join serious military discipline like a suicide and outrageous behavior. Specially military try to protect occurrence of victims that is public service through various rules and management plan but victims is going on happen. It means importance of grasp not only current mobbing victims but also potential mobbing victims better than preparation of various rules and management plans. Therefore this paper extracts seven factors and fifty attributes that are related to this matter mobbing. Next, by using Gunwoo's Social Network Service that is made for oneself and expressing extracting factors as '1' if they are related me or not '0'. And apply similarity function(Dice's coefficient) to attributes summation included in factors to calculate similarity between the users. Third, calculate optimizing weight choosing factors included attributes by applying neural network algorithm of SPSS Clementine and propose Mobbing Value(MV) Algorithm through this total summation. Finally through this algorithm which will contribute to efficient personnel management, we can grasp mobbing victims and tentative mobbing victims.

Optimizing Graphene Growth on the Electrolytic Copper Foils by Controlling Surface Condition and Annealing Procedure (전해구리막의 표면 조건과 어닐링 과정을 통한 그래핀 성장 최적화)

  • Woo Jin Lee;Ha Eun Go;Tae Rim Koo;Jae Sung Lee;Joon Woo Lee;Soun Gi Hong;Sang-Ho Kim
    • Journal of the Korean institute of surface engineering
    • /
    • v.56 no.3
    • /
    • pp.192-200
    • /
    • 2023
  • Graphene, a two-dimensional material, has shown great potential in a variety of applications including microelectronics, optoelectronics, and graphene-based batteries due to its excellent electronic conductivity. However, the production of large-area, high-quality graphene remains a challenge. In this study, we investigated graphene growth on electrolytic copper foil using thermochemical vapor deposition (TCVD) to achieve a similar level of quality to the cold-rolled copper substrate at a lower cost. The combined effects of pre-annealing time, graphenized temperature, and partial pressure of hydrogen on graphene coverage and domain size were analyzed and correlated with the roughness and crystallographic texture of the copper substrate. Our results show that controlling the crystallographic texture of copper substrates through annealing is an effective way to improve graphene growth properties, which will potentially lead to more efficient and cost-effective graphene production. At a hydrogen partial pressure that is disadvantageous in graphene growth, electrolytic copper had an average size of 8.039 ㎛2, whereas rolled copper had a size of 19.092 ㎛2, which was a large difference of 42.1% compared to rolled copper. However, at the proper hydrogen partial pressure, electrolytic copper had an average size of 30.279 ㎛2 and rolled copper had a size of 32.378 ㎛2, showing a much smaller difference of 93.5% than before. This observation suggests this potentially leads the way for more efficient and cost-effective graphene production.

Development of surface functional coating thin film utilizing combined processes of plasma activation surface treatment and nanoclay dispersion: In applications for transparent water vapor and oxygen barrier packaging films (플라즈마 활성화 표면처리 공정과 나노클레이 분산 적층 코팅을 이용한 표면 기능성 코팅 박막 개발: 수분 및 산소 차단성이 우수한 투명 포장재)

  • Nam Il Kim;Geug Tae Kim
    • Journal of the Korean Crystal Growth and Crystal Technology
    • /
    • v.33 no.3
    • /
    • pp.97-103
    • /
    • 2023
  • Barrier films for transparent packaging materials with excellent moisture barrier properties are prepared, utilizing a nanoclay dispersion coating layer formed after a pretreatment process of plasma activation surface treatment process under vacuum at room temperature. Attention is paid on optimizing the coupling additive through the appropriate crosslinking process and optimal dispersion process of the coating process to enhance adhesion. Analysis of the functional coating thin film shows that the water vapor transmission rate is less than 10 g/m2/24 hrs (ASTM F-1249) and the oxygen transmission rate is less than 30 cc/m2/24 hrs (ASTM D3985). It is shown that water barrier properties of coating thin film prepared in this study are greater than conventional untreated films by 10 times or more. The thickness of the transparent gas barrier film is within 0.1 mm, and the transparent gas barrier complex is implemented in two layers. In the study of PET thin film interface characteristics, FT-IR experimental analysis shows the reaction activity was optimized at RDS 1.125 %.

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
    • /
    • v.29 no.3
    • /
    • pp.85-92
    • /
    • 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
    • /
    • v.9 no.3
    • /
    • pp.789-795
    • /
    • 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
    • /
    • v.38 no.3
    • /
    • pp.89-98
    • /
    • 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
    • /
    • v.36 no.6
    • /
    • pp.627-632
    • /
    • 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
    • /
    • v.28 no.10
    • /
    • pp.27-35
    • /
    • 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
    • /
    • v.8 no.4
    • /
    • pp.267-276
    • /
    • 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
    • /
    • v.66 no.6
    • /
    • pp.618-631
    • /
    • 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.