• Title/Summary/Keyword: Big6 model

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A Study on the Development of a Fire Site Risk Prediction Model based on Initial Information using Big Data Analysis (빅데이터 분석을 활용한 초기 정보 기반 화재현장 위험도 예측 모델 개발 연구)

  • Kim, Do Hyoung;Jo, Byung wan
    • Journal of the Society of Disaster Information
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    • v.17 no.2
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    • pp.245-253
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    • 2021
  • Purpose: This study develops a risk prediction model that predicts the risk of a fire site by using initial information such as building information and reporter acquisition information, and supports effective mobilization of fire fighting resources and the establishment of damage minimization strategies for appropriate responses in the early stages of a disaster. Method: In order to identify the variables related to the fire damage scale on the fire statistics data, a correlation analysis between variables was performed using a machine learning algorithm to examine predictability, and a learning data set was constructed through preprocessing such as data standardization and discretization. Using this, we tested a plurality of machine learning algorithms, which are evaluated as having high prediction accuracy, and developed a risk prediction model applying the algorithm with the highest accuracy. Result: As a result of the machine learning algorithm performance test, the accuracy of the random forest algorithm was the highest, and it was confirmed that the accuracy of the intermediate value was relatively high for the risk class. Conclusion: The accuracy of the prediction model was limited due to the bias of the damage scale data in the fire statistics, and data refinement by matching data and supplementing the missing values was necessary to improve the predictive model performance.

Ligand Based HQSAR Analysis of CRTh2 Antagonists

  • Babu, Sathya;Madhavan, Thirumurthy
    • Journal of Integrative Natural Science
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    • v.8 no.1
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    • pp.1-12
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    • 2015
  • CRTh2 receptor is an important mediator of the inflammatory effects and act as beneficial target for the treatment of asthma, COPD, allergic rhinitis and atopic dermatitis. In the present work, Hologram QSAR studies were conducted on a series of 50 training set CRTh2 antagonists (2-(2-(benzylthio)-1H-benzo[d]imidazol-1-yl acetic acids). The best HQSAR model was obtained using atoms, bonds, connections and donor/acceptor as fragment distinction parameter using hologram length 257 and 6 components with fragment size of minimum 7 and maximum 10. Significant cross-validated correlation coefficient ($q^2=0.786$) and non cross-validated correlation coefficients ($r^2=0.954$) were obtained. The model was then used to evaluate the 15 external test compounds which are not included in the training set and the predicted values were in good agreement with the experimental results ($r^2_{pred}=0.739$). Contribution map show that presence of C ring and its substituents makes big contributions for activities. The HQSAR model and analysis from the contribution map could be useful for further design of novel structurally related CRTh2 antagonists.

Optimization Design on the Sealing Surface Profiles of Contacting Seal Units (접촉식 시일장치의 밀봉 접촉면 형상에 대한 최적화 설계연구)

  • Kim, Chung-Kyun
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.20 no.6
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    • pp.761-766
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    • 2011
  • In this study, the optimized design profiles between a seal ring and a seal seat of contacting seal units has been proposed based on the FEM computed results. The maximum temperatures, the thermal distortions in axial and radial directions, and maximum contact normal stresses between a seal ring and a seal seat have been analyzed for various contact sealing profiles. The FEM computed results present that the contact area between seal rings and seal seats is very important for a good tribological performance such as low friction heating, low wear, high contact normal stress in a primary sealing components. The seal surface model III in which has a small sealing contact area shows low dilatation of primary sealing components, and high contact stress between a seal ring and a seal seat. This model with small contact surface of a seal ring produces high friction heating and contact stress. But the model III produces very small deformations of contacting sealing surface because of high convection heat transfer by cooling water circulation around the seal ring surface. Thus, the analysis results recommend a short width of a primary sealing unit rather than a big width of contact surfaces of contacting seal units for reducing a leakage and axial deformation of primary seal components.

The Analysis of Priority Output Queuing Model by Short Bus Contention Method (Short Bus contention 방식의 Priority Output Queuing Model의 분석)

  • Jeong, Yong-Ju
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.2
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    • pp.459-466
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    • 1999
  • I broadband ISDN every packet will show different result if it would be processed according to its usage by the server. That is, normal data won't show big differences if they would be processed at normal speed. But it will improve the quality of service to process some kinds of data - for example real time video or voice type data or some data for a bid to by something through the internet - more fast than the normal type data. solution for this problem was suggested - priority packets. But the analyses of them are under way. Son in this paper a switching system for an output queuing model in a single server was assumed and some packets were given priorities and analysed. And correlation, simulating real life situation, was given too. These packets were analysed through three cases, first packets having no correlation, second packets having only correlation and finally packets having priority three cases, first packets having no correlation, second packets having only correlation and finally packets having priority and correlation. The result showed that correlation doesn't affect the mean delay time and the high priority packets have improved mean delay time regardless of the arrival rate. Those packets were assumed to be fixed-sized like ATM fixed-sized cell and the contention strategy was assumed to be short bus contention method for the output queue, and the mean delay length and the maximum 버퍼 length not to lose any packets were analysed.

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Causality between climatic and soil factors on Italian ryegrass yield in paddy field via climate and soil big data

  • Kim, Moonju;Peng, Jing-Lun;Sung, Kyungil
    • Journal of Animal Science and Technology
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    • v.61 no.6
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    • pp.324-332
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    • 2019
  • This study aimed to identify the causality between climatic and soil variables affecting the yield of Italian ryegrass (Lolium multiflorum Lam., IRG) in the paddy field by constructing the pathways via structure equation model. The IRG data (n = 133) was collected from the National Agricultural Cooperative Federation (1992-2013). The climatic variables were accumulated temperature, growing days and precipitation amount from the weather information system of Korea Meteorological Administration, and soil variables were effective soil depth, slope, gravel content and drainage class as soil physical properties from the soil information system of Rural Development Administration. In general, IRG cultivation by the rice-rotation system in paddy field is important and unique in East Asia because it contributes to the increase of income by cultivating IRG during agricultural off-season. As a result, the seasonal effects of accumulated temperature and growing days of autumn and next spring were evident, furthermore, autumnal temperature and spring precipitation indirectly influenced yield through spring temperature. The effect of autumnal temperature, spring temperature, spring precipitation and soil physics factors were 0.62, 0.36, 0.23, and 0.16 in order (p < 0.05). Even though the relationship between soil physical and precipitation was not significant, it does not mean there was no association. Because the soil physical variables were categorical, their effects were weakly reflected even with scale adjustment by jitter transformation. We expected that this study could contribute to increasing IRG yield by presenting the causality of climatic and soil factors and could be extended to various factors.

A Study on Exploring Digital Information Service Method through Analysis of PISA 2018 Reading Literacy Assessment Framework (PISA 2018 독서 리터러시 평가틀 분석을 통한 디지털 정보 서비스 방안 탐색)

  • Park, Juhyeon;Ranasinghe, W.M. Tharanga Dilruk
    • Journal of the Korean Society for Library and Information Science
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    • v.55 no.1
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    • pp.135-159
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    • 2021
  • The purpose of this study is to derive the implications needed to improve reading and information literacy and provide information services for students and citizens through changes in the concept of PISA 2018 Reading Literacy and its Assessment Framework analysis. The findings of the study are as follows. First, meaning of PISA Reading Literacy concept has changed along with the changes of the social and technological environments. Second, concept and assessment framework included the whole process of reading. Third, the Assessment Framework included a number of factors similar to the cognitive process of the information literacy model like Big6 Skills, but also there were differences. Fourth, the digital reading is reflected in the Assessment Framework. The PISA 2018 Reading Literacy Assessment Framework provides implications for the standards and methods required for librarians to develop reading and information literacy models and assessment frameworks to improve citizens' reading and information literacy, and to provide information services to them.

A Study on the Use of Stopword Corpus for Cleansing Unstructured Text Data (비정형 텍스트 데이터 정제를 위한 불용어 코퍼스의 활용에 관한 연구)

  • Lee, Won-Jo
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.6
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    • pp.891-897
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    • 2022
  • In big data analysis, raw text data mostly exists in various unstructured data forms, so it becomes a structured data form that can be analyzed only after undergoing heuristic pre-processing and computer post-processing cleansing. Therefore, in this study, unnecessary elements are purified through pre-processing of the collected raw data in order to apply the wordcloud of R program, which is one of the text data analysis techniques, and stopwords are removed in the post-processing process. Then, a case study of wordcloud analysis was conducted, which calculates the frequency of occurrence of words and expresses words with high frequency as key issues. In this study, to improve the problems of the "nested stopword source code" method, which is the existing stopword processing method, using the word cloud technique of R, we propose the use of "general stopword corpus" and "user-defined stopword corpus" and conduct case analysis. The advantages and disadvantages of the proposed "unstructured data cleansing process model" are comparatively verified and presented, and the practical application of word cloud visualization analysis using the "proposed external corpus cleansing technique" is presented.

A Study of Information Literacy Curriculum Using Topic Modeling (토픽모델링을 활용한 정보활용교육 연구주제 분석 및 교육내용 제안)

  • Jihye, Yun;Yoo Kyung, Jeong
    • Journal of the Korean Society for information Management
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    • v.39 no.4
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    • pp.1-21
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    • 2022
  • The aim of this study is to identify the research topics and suggest an information literacy curriculum by analyzing research articles on information literacy. For this purpose, we applied the topic modeling technique to 97 scientific articles and identified the core contents of information literacy education, such as media literacy, information literacy instruction, and the use of information resources. Based on the analysis results, we suggested an information literacy curriculum by considering the Big 6 model, information literacy standards of American Association of School Library, and Association of College and Research Libraries's information literacy competencies. This study is significant in that it considered 'use of information resources' and 'information ethics' to suggest information literacy education.

Enhanced ACGAN based on Progressive Step Training and Weight Transfer

  • Jinmo Byeon;Inshil Doh;Dana Yang
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.3
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    • pp.11-20
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    • 2024
  • Among the generative models in Artificial Intelligence (AI), especially Generative Adversarial Network (GAN) has been successful in various applications such as image processing, density estimation, and style transfer. While the GAN models including Conditional GAN (CGAN), CycleGAN, BigGAN, have been extended and improved, researchers face challenges in real-world applications in specific domains such as disaster simulation, healthcare, and urban planning due to data scarcity and unstable learning causing Image distortion. This paper proposes a new progressive learning methodology called Progressive Step Training (PST) based on the Auxiliary Classifier GAN (ACGAN) that discriminates class labels, leveraging the progressive learning approach of the Progressive Growing of GAN (PGGAN). The PST model achieves 70.82% faster stabilization, 51.3% lower standard deviation, stable convergence of loss values in the later high resolution stages, and a 94.6% faster loss reduction compared to conventional methods.

A Privacy Approach Model for Multi-Access to IoT Users based on Society 5.0 (소사이어티 5.0 기반 IoT 사용자에 대한 다중 접근방식의 프라이버시 접근 모델)

  • Jeong, Yoon-Su;Yon, Yong-Ho
    • Journal of Convergence for Information Technology
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    • v.10 no.4
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    • pp.18-24
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    • 2020
  • Recently, research on Society 5.0 has been actively carried out in Japan. The Society 5.0 is used in various areas using IoT sensors. This paper proposes a privacy approach model of multiple approaches to IoT users based on Society 5.0. The proposed model used multiple methods of synchronizing important information of IoT devices with one another in the virtual environment. The proposed model improved the efficiency of IoT information by accumulating the weight of IoT information on a probability-based basis. Further, it improves the accuracy of IoT information by segmenting it so that attribute information is linked to IoT information. As a result of the performance evaluation, the efficiency of IoT devices has improved by an average of 5.6 percent, depending on the number of IoT devices and the number of IoT hub devices. Accuracy has improved by an average of 15.9% depending on information collection and processing.