• Title/Summary/Keyword: Field-data

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Review on statistical methods for large spatial Gaussian data

  • Park, Jincheol
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.2
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    • pp.495-504
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    • 2015
  • The Gaussian geostatistical model has been widely used for modeling spatial data. However, this model suffers from a severe difficulty in computation because inference requires to invert a large covariance matrix in evaluating log-likelihood. In addressing this computational challenge, three strategies have been employed: likelihood approximation, lower dimensional space approximation, and Markov random field approximation. In this paper, we reviewed statistical approaches attacking the computational challenge. As an illustration, we also applied integrated nested Laplace approximation (INLA) technology, one of Markov approximation approach, to real data to provide an example of its use in practice dealing with large spatial data.

A Study on Warranty and Quality Assurance Model for Guided Missiles Based on Storage Reliability (저장신뢰도 기반의 유도탄 품질보증모델에 대한 연구)

  • Jung, Sanghoon;Lee, Sangbok
    • Journal of Applied Reliability
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    • v.17 no.2
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    • pp.83-91
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    • 2017
  • Purpose: The purpose of this study is to develop a quality assurance model and to determine appropriate warranty period for a guided missile using its field data. Methods: 10 years of actual firing data is collected from the defense industry company and military. Parametric maximum likelihood estimation for a reliability function is determined with the data. Results: The reliability function estimates average lifetime of the missile. That function shows a user requirement, 80% reliability (lifetime) is come up when 8 years have passed, which is longer than the estimates in the missile's development phase. Conclusion: Quality assurance warranty for a guided missile must be established with actual test data. It is necessary to update and modify the reliability prediction and the warranty period with actual field test data.

Pre-processing of load data of agricultural tractors during major field operations

  • Ryu, Myong-Jin;Kabir, Md. Shaha Nur;Choo, Youn-Kug;Chung, Sun-Ok;Kim, Yong-Joo;Ha, Jong-Kyou;Lee, Kyeong-Hwan
    • Korean Journal of Agricultural Science
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    • v.42 no.1
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    • pp.53-61
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    • 2015
  • Development of highly efficient and energy-saving tractors has been one of the issues in agricultural machinery. For design of such tractors, measurement and analysis of load on major power transmission parts of the tractors are the most important pre-requisite tasks. Objective of this study was to perform pre-processing procedures before effective analysis of load data of agricultural tractors (30, 75, and 82 kW) during major field operations such as plow tillage, rotary tillage, baling, bale wrapping, and to select the suitable pre-processing method for the analysis. A load measurement systems, equipped in the tractors, were consisted of strain-gauge, encoder, hydraulic pressure, and radar speed sensors to measure torque and rotational speed levels of transmission input shaft, PTO shaft, and driving axle shafts, pressure of the hydraulic inlet line, and travel speed, respectively. The entire sensor data were collected at a 200-Hz rate. Plow tillage, rotary tillage, baling, wrapping, and loader operations were selected as major field operations of agricultural tractors. Same or different farm works and driving levels were set differently for each of the load measuring experiment. Before load data analysis, pre-processing procedures such as outlier removal, low-pass filtering, and data division were performed. Data beyond the scope of the measuring range of the sensors and the operating range of the power transmission parts were removed. Considering engine and PTO rotational speeds, frequency components greater than 90, 60, and 60 Hz cut off frequencies were low-pass filtered for plow tillage, rotary tillage, and baler operations, respectively. Measured load data were divided into five parts: driving, working, implement up, implement down, and turning. Results of the study would provide useful information for load characteristics of tractors on major field operations.

Field measurement and numerical simulation of excavation damaged zone in a 2000 m-deep cavern

  • Zhang, Yuting;Ding, Xiuli;Huang, Shuling;Qin, Yang;Li, Peng;Li, Yujie
    • Geomechanics and Engineering
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    • v.16 no.4
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    • pp.399-413
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    • 2018
  • This paper addresses the issue of field measurement of excavation damage zone (EDZ) and its numerical simulation method considering both excavation unloading and blasting load effects. Firstly, a 2000 m-deep rock cavern in China is focused. A detailed analysis is conducted on the field measurement data regarding the mechanical response of rock masses subjected to excavation and blasting operation. The extent of EDZ is revealed 3.6 m-4.0 m, accounting for 28.6% of the cavern span, so it is significantly larger than rock caverns at conventional overburden depth. The rock mass mechanical response subjected to excavation and blasting is time-independent. Afterwards, based on findings of the field measurement data, a numerical evaluation method for EDZ determination considering both excavation unloading and blasting load effects is presented. The basic idea and general procedures are illustrated. It features a calibration operation of damage constant, which is defined in an elasto-plastic damage constitutive model, and a regression process of blasting load using field blasting vibration monitoring data. The numerical simulation results are basically consistent with the field measurement results. Further, some issues regarding the blasting loads, applicability of proposed numerical method, and some other factors are discussed. In conclusion, the field measurement data collected from the 2000 m-deep rock cavern and the corresponding findings will broaden the understanding of tunnel behavior subjected to excavation and blasting at great depth. Meanwhile, the presented numerical simulation method for EDZ determination considering both excavation unloading and blasting load effects can be used to evaluate rock caverns with similar characteristics.

Improving Field Crop Classification Accuracy Using GLCM and SVM with UAV-Acquired Images

  • Seung-Hwan Go;Jong-Hwa Park
    • Korean Journal of Remote Sensing
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    • v.40 no.1
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    • pp.93-101
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    • 2024
  • Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.

Paramedic student's awareness and performance of infection control on clinical field training (응급구조(학)과 학생들의 임상현장실습 시 감염관리에 대한 인지도와 수행도)

  • HuiJeong Kim;YuJin Lee;HyeonJin Choi;Seo Young Yim;Eun-Sook Choi
    • The Korean Journal of Emergency Medical Services
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    • v.28 no.1
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    • pp.47-62
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    • 2024
  • Purpose: This study aimed to provide basic data for infection control education plans based on infection control awareness and performance of paramedic students during clinical field training. Methods: Data were collected from paramedic students with experience in clinical field training. The data collection period was from May 4, 2023, to June 4, 2023, and 132 copies of the collected survey were analyzed using the SPSS27.0 program. Results: Infection control awareness and performance were 4.80±0.24 points and 4.49±0.55 points out of 5, respectively. The infection control awareness of the participants according to clinical field training-related characteristics differed significantly in university education before clinical field training (t=2.100, p=.038). In addition, there were significant differences in performance in the number of clinical field training sessions (F=9.149, p=.000), hospital education before clinical field training (t=5.365, p=.000), and hospital education during clinical field training (t=3.094, p=.002). Conclusion: Before clinical field training, schools should provide infection control education that combines theory and practice suitable for hospital practice so that students can complete the infection control education organized by the hospital. Furthermore, if a university develops infection control in the clinical field training guidelines, it will have a positive impact on students' infection control performance through prior education.

A Study on the Sharing of Research Data in Library and Information Science Field (문헌정보학 분야 연구데이터 공유에 관한 연구)

  • Cho, Jane
    • Journal of the Korean Society for information Management
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    • v.34 no.4
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    • pp.59-79
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    • 2017
  • This study analyzed the type, subject and open level of research data in the field of library and information science field shared by Figshare, and statistically analyzed the characteristics of data with relatively high recyclability. The results of the analysis showed that datasets and papers were most common data types, and open access and research data were the most common keywords of data, and that 70% of the data were published in a form that can not be processed mechanically such as pdf. As a result of analysis of the relationship between characteristics of research data and degree of sharing, open access areas such as APC (Article Processing Charge) were found to be most common in the subject. However in data type, gray literature such as paper found to be highly utilized rather than dataset.

Fatigue Reliability Evaluation of an In-service Steel Bridge Using Field Measurement Data (현장계측데이터를 활용한 공용 중 강교량의 피로 신뢰도평가)

  • Lee, Sang Hyeon;An, Lee-Sak;Park, Yeun Chul;Kim, Ho-Kyung
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.42 no.5
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    • pp.599-606
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    • 2022
  • Strain gauges and the bridge weigh-in-motion (BWIM) method are the representative field measurement methods used for fatigue evaluationsof a steel bridge-in-service. For a fatigue reliability evaluation to assess fatigue damage accumulation, the effective stress range and the number of stress cycles applied as the fatigue details can be estimated based on the AASHTO Manual for Bridge Evaluations with the field measurement data of the target bridge. However, the procedure for estimating the effective stress range and the stress cycles from field measurement data has not been explicitly presented. Furthermore, studies that quantitatively compare differences in fatigue evaluation results according to the field measurement data type or processing method used are still insufficient. Here, a fatigue reliability evaluation is conducted using strain and BWIM data that are measured simultaneously. A frame model and a shell-solid model were generated to examine the effect of the accuracy of the structural analysis model when using BWIM data. Also, two methods of handling BWIM data when estimating the effective stress range and average daily cycles are defined. As a result, differences in evaluation results according to the type of field measurement data used, the accuracy of the structural analysis model, and the data handling method could be quantitatively confirmed.

Development and Application of a GIS Interface for the Agricultural Nonpoint Source Pollution (AGNPS) Model(II) -Modification of AGNPS Model- (농업비점원오염모형을 위한 GIS 호환모형의 개발 빛 적용(II) -AGNPS모형의 수정-)

  • 김진택;박승우
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.39 no.2
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    • pp.53-61
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    • 1997
  • The interface system, GIS-AGNPS was to be validated with field data from six tested small watersheds ranging from 0.7 to 4.7$km^2$ in size which have steep topography and complex landuses. The model validation involved the calibration of input parameters and component modifications, in efforts to develop a model applicable to general uses for identifying and controlling nonpoint source pollution loads from agricultural watersheds. The simulated direct runoff from AGNPS was in good agreement with the field data for the averaged antecedent moisture conditions or AMC- II. The results differed, however, from the observed for AMC- I or III. A simple empirical relationship was proposed to estimate the curve number for AMC- I or m from AMC- II, which was found to result in simulated runoff close to the observed. The peak runoff relationship at AGNPS was also modified to reflect the watershed conditions and tested satisfactorily with the field data. The simulated sediment yields from the watersheds were fair as compared to the observed. Nutrient loads simulated from the model were different from the observed data. It appeared that the model was incapable of adequate depicting nutrient transport processes at paddy field and other landuses of the tested watersheds. Some modifications may be needed for the accurate representing the processes at paddy field.

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Deep Learning Based Semantic Similarity for Korean Legal Field (딥러닝을 이용한 법률 분야 한국어 의미 유사판단에 관한 연구)

  • Kim, Sung Won;Park, Gwang Ryeol
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.2
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    • pp.93-100
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    • 2022
  • Keyword-oriented search methods are mainly used as data search methods, but this is not suitable as a search method in the legal field where professional terms are widely used. In response, this paper proposes an effective data search method in the legal field. We describe embedding methods optimized for determining similarities between sentences in the field of natural language processing of legal domains. After embedding legal sentences based on keywords using TF-IDF or semantic embedding using Universal Sentence Encoder, we propose an optimal way to search for data by combining BERT models to check similarities between sentences in the legal field.