• Title/Summary/Keyword: making techniques

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Estimation of Fuel Flow in Hall Thrusters Using Star-CCM and Optimization with Taguchi Method (Star-CCM을 통한 홀 추력기의 연료 유량 추정 및 다구찌 기법을 활용한 최적화 연구)

  • Jin-Young Park
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.17 no.5
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    • pp.313-322
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    • 2024
  • To ensure the stable flight of aerospace electric propulsion systems, it is necessary to measure the supplied flow rate and control it to an appropriate level. However, conventional flow sensors are costly and face limitations in space environments, making heat-based flow estimation a promising alternative. In this study, the Taguchi method, one of the experimental design techniques, was applied to perform thermal analysis simulations using Ansys under various variables and conditions. The Taguchi method was used to set heat supply and the positioning of inlet and outlet temperature sensors as key variables, and the optimal distance conditions were derived. Thermal analysis was conducted through Ansys to analyze the flow estimation results under each experimental condition. Therefore, this study demonstrates the practicality of the heat-based flow estimation method for fuel management systems in electric propulsion systems, presenting a new approach for the efficient and economical operation of electric propulsion. Additionally, this research contributes to the development of fuel management technologies that can be effectively utilized in the constrained environment of space.

Real-time simulation and control of indoor air exchange volume based on Digital Twin Platform

  • Chia-Ying Lin;I-Chen Wu
    • International conference on construction engineering and project management
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    • 2024.07a
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    • pp.637-644
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    • 2024
  • Building Information Modeling (BIM) technology has been widely adopted in the construction industry. However, a challenge encountered in the operational phase is that building object data cannot be updated in real time. The concept of Digital Twin is to digitally simulate objects, environments, and processes in the real world, employing real-time monitoring, simulation, and prediction to achieve dynamic integration between the virtual and the real. This research considers an example related to indoor air quality for realizing the concept of Digital Twin and solving the problem that the digital twin platform cannot be updated in real time. In indoor air quality monitoring, the ventilation rate and the presence of occupants significantly affects carbon dioxide concentration. This study uses the indoor carbon dioxide concentration recommended by the Taiwan Environmental Protection Agency as a reference standard for air quality measurement, providing a solution to the aforementioned challenges. The research develops a digital twin platform using Unity, which seamlessly integrates BIM and IoT technology to realize and synchronize virtual and real environments. Deep learning techniques are applied to process camera images and real-time monitoring data from IoT sensors. The camera images are utilized to detect the entry and exit of individuals indoors, while monitoring data to understand environmental conditions. These data serve as a basis for calculating carbon dioxide concentration and determining the optimal indoor air exchange volume. This platform not only simulates the air quality of the environment but also aids space managers in decision-making to optimize indoor environments. It enables real-time monitoring and contributes to energy conservation.

A Survey on the Latest Research Trends in Retrieval-Augmented Generation (검색 증강 생성(RAG) 기술의 최신 연구 동향에 대한 조사)

  • Eunbin Lee;Ho Bae
    • The Transactions of the Korea Information Processing Society
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    • v.13 no.9
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    • pp.429-436
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    • 2024
  • As Large Language Models (LLMs) continue to advance, effectively harnessing their potential has become increasingly important. LLMs, trained on vast datasets, are capable of generating text across a wide range of topics, making them useful in applications such as content creation, machine translation, and chatbots. However, they often face challenges in generalization due to gaps in specific or specialized knowledge, and updating these models with the latest information post-training remains a significant hurdle. To address these issues, Retrieval-Augmented Generation (RAG) models have been introduced. These models enhance response generation by retrieving information from continuously updated external databases, thereby reducing the hallucination phenomenon often seen in LLMs while improving efficiency and accuracy. This paper presents the foundational architecture of RAG, reviews recent research trends aimed at enhancing the retrieval capabilities of LLMs through RAG, and discusses evaluation techniques. Additionally, it explores performance optimization and real-world applications of RAG in various industries. Through this analysis, the paper aims to propose future research directions for the continued development of RAG models.

Maximizing the potential of male layer embryos for cultivated chicken meat cell sourcing

  • Sun A Ock;Yeongji Kim;Young-Im Kim;Poongyeon Lee;Bo Ram Lee;Min Gook Lee
    • Journal of Animal Reproduction and Biotechnology
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    • v.39 no.3
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    • pp.212-219
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    • 2024
  • Background: This study explores the potential of discarded male layer embryos as a sustainable and non-GMO cell source for cultivated chicken meat production. The research aims to identify efficient methods for isolating muscle progenitor cells (MPCs) with high proliferative potential by conducting transcriptome analysis on thigh muscle tissues from both male and female chick embryos. Methods: Transcriptome analysis was performed on the thigh muscle tissues of male and female chick embryos, aged 12-13 days, (n = 4 each), to investigate the gene expression profiles and identify strategies for efficiently isolating MPCs. This approach aims to pinpoint techniques that would allow for the selection of MPCs with optimal growth and proliferation capabilities. Results: Using heatmap, hierarchical clustering, and multidimensional scaling (MDS), we found no significant sex-based differences in gene expression, except for the overexpression of the female-specific gene LIPBLL. The expression of muscle stem cell factors, including PAX3, PAX7, and other myogenic regulatory genes, showed no significant variation. However, to recover MPC-rich cells isolated from male thigh muscle, we found that by the pre-plating 7 stage, myogenesis-related genes, MYHs and MUSTN1 were minimally expressed, while the cell cycle arrest gene CDKN1A sharply increased. Conclusions: Our findings suggest that simple cell isolation directly from tissue is a more scalable and efficient approach for cultivated meat production, compared to labor-intensive pre-plating methods, making it a viable solution for sustainable research and resource recycling.

Development of a Predictive Model forOccupational Disability Grades Using Workers'Compensation Insurance Data (산재보험 빅데이터를 활용한 장해등급 예측 모델 개발)

  • Choi, Keunho;Kim, Min Jeong;Lee, Jeonghwa
    • The Journal of Information Systems
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    • v.33 no.3
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    • pp.187-205
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    • 2024
  • Purpose A prediction model for occupational injuries can support more proactive, efficient, and effective policy-making. This study aims to develop a model that predicts the severity of occupational injuries, classified into 15 disability grades in South Korea, using machine learning techniques applied to COMWEL data. The primary goal is to improve prediction accuracy, offering an advanced tool for early intervention and evidence-based policy implementation. Design/methodology/approach The data analyzed in this study consists of 290,157 administrative records of occupational injury cases collected between 2018 and 2020 by the Korea Workers' Compensation & Welfare Service, based on the 'Workers' Compensation Insurance Application Form' submitted for occupational injury treatment. Four machine learning models - Decision Tree, DNN, XGBoost, and LightGBM - were developed and their performances compared to identify the optimal model. Additionally, the Permutation Feature Importance (PFI) method was used to assess the relative contribution of each variable to the model's performance, helping to identify key variables. Findings The DNN algorithm achieved the lowest Mean Absolute Error (MAE) of 0.7276. Key variables for predicting disability grades included the severity index, primary disease code, primary disease site, age at the time of the injury, and industry type. These findings highlight the importance of early policy intervention and emphasize the role of both medical and socioeconomic factors in model predictions. The academic and policy implications of these results were also discussed.

Stock-Index Invest Model Using News Big Data Opinion Mining (뉴스와 주가 : 빅데이터 감성분석을 통한 지능형 투자의사결정모형)

  • Kim, Yoo-Sin;Kim, Nam-Gyu;Jeong, Seung-Ryul
    • Journal of Intelligence and Information Systems
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    • v.18 no.2
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    • pp.143-156
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    • 2012
  • People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

Physicochemical Characteristics and Varietal Improvement Related to Palatability of Cooked Rice or Suitability to Food Processing in Rice (쌀 식미 및 가공적성에 관련된 이화학적 특성)

  • 최해춘
    • Proceedings of the Korean Journal of Food and Nutrition Conference
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    • 2001.12a
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    • pp.39-74
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    • 2001
  • The endeavors enhancing the grain quality of high-yielding japonica rice were steadily continued during 1980s∼1990s along with the self-sufficiency of rice production and the increasing demands of high-quality rices. During this time, considerably great, progress and success was obtained in development of high-quality japonica cultivars and qualify evaluation techniques including the elucidation of interrelationship between the physicochemical properties of rice grain and the physical or palatability components of cooked rice. In 1990s, some high-quality japonica rice caltivars and special rices adaptable for food processing such as large kernel, chalky endosperm aromatic and colored rices were developed and its objective preference and utility was also examined by a palatability meter, rapid-visco analyzer and texture analyzer. The water uptake rate and the maximum water absorption ratio showed significantly negative correlations with the K/Mg ratio and alkali digestion value(ADV) of milled rice. The rice materials showing the higher amount of hot water absorption exhibited the larger volume expansion of cooked rice. The harder rices with lower moisture content revealed the higher rate of water uptake at twenty minutes after soaking and the higher ratio of maximum water uptake under the room temperature condition. These water uptake characteristics were not associated with the protein and amylose contents of milled rice and the palatability of cooked rice. The water/rice ratio (in w/w basis) for optimum cooking was averaged to 1.52 in dry milled rices (12% wet basis) with varietal range from 1.45 to 1.61 and the expansion ratio of milled rice after proper boiling was average to 2.63(in v/v basis). The major physicochemical components of rice grain associated with the palatability of cooked rice were examined using japonica rice materials showing narrow varietal variation in grain size and shape, alkali digestibility, gel consistency, amylose and protein contents, but considerable difference in appearance and torture of cooked rice. The glossiness or gross palatability score of cooked rice were closely associated with the peak. hot paste and consistency viscosities of viscogram with year difference. The high-quality rice variety “Ilpumbyeo” showed less portion of amylose on the outer layer of milled rice grain and less and slower change in iodine blue value of extracted paste during twenty minutes of boiling. This highly palatable rice also exhibited very fine net structure in outer layer and fine-spongy and well-swollen shape of gelatinized starch granules in inner layer and core of cooked rice kernel compared with the poor palatable rice through image of scanning electronic mcroscope. Gross sensory score of cooked rice could be estimated by multiple linear regression formula, deduced from relationship between rice quality components mentioned above and eating quality of cooked rice, with high Probability of determination. The ${\alpha}$ -amylose-iodine method was adopted for checking the varietal difference in retrogradation of cooked rice. The rice cultivars revealing the relatively slow retrogradation in aged cooked rice were Ilpumbyeo, Chucheongbyeo, Sasanishiki, Jinbubyeo and Koshihikari. A Tongil-type rice, Taebaegbyeo, and a japonica cultivar, Seomjinbyeo, shelved the relatively fast deterioration of cooked rice. Generally, the better rice cultivars in eating quality of cooked rice showed less retrogiadation and much sponginess in cooled cooked rice. Also, the rice varieties exhibiting less retrogradation in cooled cooked rice revealed higher hot viscosity and lower cool viscosity of rice flour in amylogram. The sponginess of cooled cooked rice was closely associated with magnesium content and volume expansion of cooked rice. The hardness-changed ratio of cooked rice by cooling was negatively correlated with solids amount extracted during boiling and volume expansion of cooked rice. The major physicochemical properties of rice grain closely related to the palatability of cooked rice may be directly or indirectly associated with the retrogradation characteristics of cooked rice. The softer gel consistency and lower amylose content in milled rice revealed the higher ratio of popped rice and larger bulk density of popping. The stronger hardness of rice grain showed relatively higher ratio of popping and the more chalky or less translucent rice exhibited the lower ratio of intact popped brown rice. The potassium and magnesium contents of milled rice were negatively associated with gross score of noodle making mixed with wheat flour in half and the better rice for noodle making revealed relatively less amount of solid extraction during boiling. The more volume expansion of batters for making brown rice bread resulted the better loaf formation and more springiness in rice bread. The higher protein rices produced relatively the more moist white rice bread. The springiness of rice bread was also significantly correlated with high amylose content and hard gel consistency. The completely chalky and large gram rices showed better suitability for fermentation and brewing. Our breeding efforts on rice quality improvement for the future should focus on enhancement of palatability of cooked rice and marketing qualify as well as the diversification in morphological and physicochemical characteristics of rice grain for various value-added rice food processings.

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Matching Points Filtering Applied Panorama Image Processing Using SURF and RANSAC Algorithm (SURF와 RANSAC 알고리즘을 이용한 대응점 필터링 적용 파노라마 이미지 처리)

  • Kim, Jeongho;Kim, Daewon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.4
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    • pp.144-159
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    • 2014
  • Techniques for making a single panoramic image using multiple pictures are widely studied in many areas such as computer vision, computer graphics, etc. The panorama image can be applied to various fields like virtual reality, robot vision areas which require wide-angled shots as an useful way to overcome the limitations such as picture-angle, resolutions, and internal informations of an image taken from a single camera. It is so much meaningful in a point that a panoramic image usually provides better immersion feeling than a plain image. Although there are many ways to build a panoramic image, most of them are using the way of extracting feature points and matching points of each images for making a single panoramic image. In addition, those methods use the RANSAC(RANdom SAmple Consensus) algorithm with matching points and the Homography matrix to transform the image. The SURF(Speeded Up Robust Features) algorithm which is used in this paper to extract featuring points uses an image's black and white informations and local spatial informations. The SURF is widely being used since it is very much robust at detecting image's size, view-point changes, and additionally, faster than the SIFT(Scale Invariant Features Transform) algorithm. The SURF has a shortcoming of making an error which results in decreasing the RANSAC algorithm's performance speed when extracting image's feature points. As a result, this may increase the CPU usage occupation rate. The error of detecting matching points may role as a critical reason for disqualifying panoramic image's accuracy and lucidity. In this paper, in order to minimize errors of extracting matching points, we used $3{\times}3$ region's RGB pixel values around the matching points' coordinates to perform intermediate filtering process for removing wrong matching points. We have also presented analysis and evaluation results relating to enhanced working speed for producing a panorama image, CPU usage rate, extracted matching points' decreasing rate and accuracy.

The Making of Speaking Subject in Early Korean Protestantism: Focused on the Educational Spaces for Women (초기 한국 기독교의 교육공간과 말하는 주체의 탄생)

  • Lee, Sookjin
    • Journal of Christian Education in Korea
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    • v.62
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    • pp.227-255
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    • 2020
  • This paper aims to explore the nature of the making of speaking subject in early Korean Protestantism, focusing on the educational spaces for women. Traditional women could become a speaking subject through various educational programs provided by Protestantism in modern Korea. Especially three kinds of educational space played the crucial role of making women a speaking subject. The first was Bible class established for women in rural areas. Since most Korean women were unable to read and write, Protestant churches taught them Hangul[Korean alphabet] before teaching the Bible. Korean women studied the Bible in Bible class, Women's Bible School, and Women's High Bible School. Through this education, traditional women were liberated from the world of ignorance and obedience, and then become a speaking subject. The second was speeches and discussions that have emerged in institutional spaces such as mission schools for girls and women's organizations. Students at mission school were able to learn how to express their opinions by way of public speaking and discussion classes. Women were able to become speaking subjects in the process of learning such techniques of modern language. At that time, representative discussion spaces were Lee Mun-hoe, Joyce Chapter, and YWCA. The third was testimony and dialect. Unlike sermons and public prayers, which were only allowed to male elites, testimony and dialectics are a form of speech that transcends gender or status constraints. Especially in the space of the revival movement, women confirmed their dignity through active testimony, and their religious identity was strengthened in the process. Dialect also served as the language of liberation for women suffered and alienated from male-dominant culture. Dialect is a device that exercises the right to speak against transcendental authority. Furthermore, in Protestantism of early modern Korea, the speaking subject's act of speech was elevated beyond personal matters to social issues, women's issues, and ethnic issues.

A Study on The Iron Monument in The era of Joseon Dynasty (조선시대(朝鮮時代) 철비(鐵碑)의 조영(造營) 연구(硏究))

  • Hong, Dai Han
    • The Korean Journal of Archival Studies
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    • no.24
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    • pp.215-274
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    • 2010
  • Iron-making industries of the country, regardless of age has been the focus. This makes the iron production technology and production techniques that result in increased economic activity and because of the central charge. Therefore, the social development of ancient iron-making technology is based on phase-sensitive. Modern steel making up the monopoly of the country's target under the strict control of production, distribution was. It is essential to produce iron weapons was a threat is because you can keep the throne in the hands of the forces that can cause side effects when I went was to block. This study created a rail Cholbi(iron monument) and the regional distribution pattern of the production, construction background, looked on. Cholbi(iron monument) for the production and recording "the Annals of the Joseon Dynasty" often appear in history books and many academic interests, but was off target. Compared to a stone monument that was not generally as well as the Japanese colonial period and over the course of modernization destroyed, damaged a lot of cases the cause may be found in front. Cholbi(iron monument), except for the gravestones of the Joseon Dynasty monument erected in honor of virtue, as an example of content that dominated a packman business, founding of the school and confirmed that a few were built as a special purpose. Cholbi(iron monument) compared to the production technology or the cost of the monument's difficulty in financing follows. Therefore Cholbi(iron monument) the establishment of the Joseon Dynasty through the background of the economic situation and the local government can look. And iron technology began complaining about the object of history, economic conditions, with the change of season has been a change in people's consciousness tells you. Important data of ancient history as an epigraph that has been as important, the Middle Ages to modern times ranging from newly born to the time Cholbi(iron monument) in the development of the country's documentary subject to change should have been brought. Based on these discussions changes the identity of the hero monument and production inspector, review of production through the Joseon Dynasty period Cholbi (iron monument) contemplated the significance is reflected in production.