• Nuclear Engineering and Technology
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• 제49권7호
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• pp.1483-1488
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• 2017

In order to predict and control the environmental and health impacts of ionizing radiation in environmental sources such as groundwater, it is necessary to identify the radionuclides present. Beta-emitting radionuclides are frequently identified by measuring their characteristic energy spectra. The present work shows that self-attenuation effects from volume sources result in a geometry-dependent shift in the characteristic spectra, which needs to be taken into account in order to correctly identify the radionuclides present. These effects are shown to be compounded due to the subsequent shift in the photon spectra produced by the detector, in this case an inorganic solid scintillator ($CaF_2:Eu$) monitored using a silicon photomultiplier. Using tritiated water as an environmentally relevant, and notoriously difficult to monitor case study, analytical predictions for the shift in the energy spectra as a function of depth of source have been derived. These predictions have been validated using Geant4 simulations and experimental results measured using bespoke instrumentation.

• 한국대기환경학회지
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• 제3권1호
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• pp.34-40
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• 1987

The Texas Climatological Model (TCM) Predicts long-term pollutant concentrations for a rectilinear array or receptors defined by the user. This paper describes the TCM and compares predictions from TCM with predictions from the Climatological Dispersion Model (CDMQC). A number of model runs have been made with the TCM and CDMQC using the same source inventories and sets of climatology. The concentrations predicted by these two models are compared and the result of several types of statistical analyses are reported. In most cases, the TCM predicts concentrations that are equivalent to those predicted by the CDMQC. However, in certain cases, the CDMQC tends to predict concentrations that are unrealistically high. In the computer time, the TCM requires about one-eights of the computer time used by the CDMQC.

• 지식경영연구
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• 제21권2호
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• pp.177-196
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• 2020

Since the adoption of K-IFRS(Korean International Financial Reporting Standards), the amount of financial footnotes has been increased. However, due to the stereotypical phrase and the lack of conciseness, deriving the core information from footnotes is not really easy yet. To propose a solution for this problem, this study tried financial footnote analysis for financial ratio predictions based on text-mining techniques. Using the financial statements data from 2013 to 2018, we tried to predict the earning per share (EPS) of the following quarter. We found that measured prediction errors were significantly reduced when text-mined footnotes data were jointly used. We believe this result came from the fact that discretionary financial figures, which were hardly predicted with quantitative financial data, were more correlated with footnotes texts.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2008년도 정기총회 및 학술발표대회
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• pp.183-186
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• 2008

All measures to cope with flooding rely on flood predictions to some extent, and the effectiveness of these measures is dependent on the quality of flood predictions. It is important to track properly the movements of the river-bankline in numerical modeling because the location of it varies continuously in the flood inundation. In this study, the wet and dry treatment is used to describe the moving river-bankline accurately (Cho, 1996). An oscillatory flow motion in a parabolic basin is used to validate the performance of the developed model based on quadtree grids. As a result of a simulation, a reasonable agreement is observed with analytical and Cho's results.

• 한국정밀공학회지
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• 제16권9호
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• pp.135-142
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• 1999

A constitutive model was proposed to study the effects of fiber waviness on the elastic properties of unidirectional composite materials. The predictions showed that the degree of fiber waviness significantly affected the elastic properties of composite materials. A special fabrication technique was developed for thic composite materials with various fiber waviness ratios. Tensile, compressive and flexural tests were conducted to obtain the elastic properties of composite materials with fiber waviness experimentally. The experimental result were in good agreement with the predictions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권6호
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• pp.1449-1461
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• 2024

As technology advances, processor speeds are increasing at a rapid pace and digital systems require a significant amount of data bandwidth. As a result, careful consideration of signal integrity is required to ensure reliable and high-speed data processing. Crosstalk has become a vital area of research in signal integrity for electronic packages, mainly because of the high level of integration. Analytic formulas were analyzed in this study to identify the features that can predict crosstalk in multi-conductor transmission lines. Through the analysis, five variables were found and obtained a dataset consisting of 302,500, data points. The study evaluated the performance of various regression models for optimization via automatic machine learning by comparing the machine learning predictions with the analytic solution. Extra tree regression consistently outperformed other algorithms, with coefficients of determination exceeding 0.9 and root mean square logarithmic errors below 0.35. The study also notes that different algorithms produced varied predictions for the two metrics.

• Parasites, Hosts and Diseases
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• 제47권3호
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• pp.235-241
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• 2009

The aim of this study was to estimate the benefit from repeated examinations in the diagnosis of enterobiasis in nursery school groups, and to test the effectiveness of individual-based risk predictions using different methods. A total of 604 children were examined using double, and 96 using triple, anal swab examinations. The questionnaires for parents, structured observations, and interviews with supervisors were used to identify factors of possible infection risk. In order to model the risk of enterobiasis at individual level, a similarity-based machine learning and prediction software Constud was compared with data mining methods in the Statistica 8 Data Miner software package. Prevalence according to a single examination was 22.5%; the increase as a result of double examinations was 8.2%. Single swabs resulted in an estimated prevalence of 20.1% among children examined 3 times; double swabs increased this by 10.1%, and triple swabs by 7.3%. Random forest classification, boosting classification trees, and Constud correctly predicted about 2/3 of the results of the second examination. Constud estimated a mean prevalence of 31.5% in groups. Constud was able to yield the highest overall fit of individual-based predictions while boosting classification tree and random forest models were more effective in recognizing Enterobius positive persons. As a rule, the actual prevalence of enterobiasis is higher than indicated by a single examination. We suggest using either the values of the mean increase in prevalence after double examinations compared to single examinations or group estimations deduced from individual-level modelled risk predictions.

• 지적과 국토정보
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• 제46권2호
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• pp.43-55
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• 2016

본 연구는 사례 기반 학습(instance-based learning)의 논리를 활용하여 지가를 추정하였다. 다양한 사례 기반 학습 기법 중 k-최근린법을 이용하였으며, k-최근린법 적용시 유사성을 측정하는 거리척도는 유클리디안 거리를 비롯해 문헌에 비교적 자주 등장하는 10개의 거리척도를 사용하였다. 본 연구에서는 k-최근린법에 의한 10 종류의 예측값 중 가장 우수한 성능을 보이는 1개의 예측값을 최종 가격으로 선택하는 대신, 이들 예측값들을 병합하는 앙상블(ensemble) 기법의 논리를 적용하여 최종 예측값을 결정하였다. 앙상블 기법 중 일종의 잔차 적합 모형인 경사 부스팅 앨고리듬을 적용하여 최종 가격을 정하였다. 본 연구에서는 이러한 사례 기반 학습과 앙상블 기법의 이점을 실증적으로 제시하기 위해 전라남도 해남군 소재 농지를 사례로 하여 가격을 추정하였으며, k-최근린법에 의한 10 종류의 예측값보다 앙상블 기법에 의한 가격이 보다 정확한 것을 확인할 수 있었다.

• 천문학회지
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• 제40권4호
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• pp.99-106
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• 2007

Statistical analyses were performed to investigate the relative success and accuracy of daily maximum X-ray flux (MXF) predictions, using both multilinear regression and autoregressive time-series prediction methods. As input data for this work, we used 14 solar activity parameters recorded over the prior 2 year period (1989-1990) during the solar maximum of cycle 22. We applied the multilinear regression method to the following three groups: all 14 variables (G1), the 2 so-called 'cause' variables (sunspot complexity and sunspot group area) showing the highest correlations with MXF (G2), and the 2 'effect' variables (previous day MXF and the number of flares stronger than C4 class) showing the highest correlations with MXF (G3). For the advanced three days forecast, we applied the autoregressive timeseries method to the MXF data (GT). We compared the statistical results of these groups for 1991 data, using several statistical measures obtained from a $2{\times}2$ contingency table for forecasted versus observed events. As a result, we found that the statistical results of G1 and G3 are nearly the same each other and the 'effect' variables (G3) are more reliable predictors than the 'cause' variables. It is also found that while the statistical results of GT are a little worse than those of G1 for relatively weak flares, they are comparable to each other for strong flares. In general, all statistical measures show good predictions from all groups, provided that the flares are weaker than about M5 class; stronger flares rapidly become difficult to predict well, which is probably due to statistical inaccuracies arising from their rarity. Our statistical results of all flares except for the X-class flares were confirmed by Yates' $X^2$ statistical significance tests, at the 99% confidence level. Based on our model testing, we recommend a practical strategy for solar X-ray flare predictions.

• Steel and Composite Structures
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• 제42권1호
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• pp.91-106
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• 2022

Concrete-filled square stainless steel tubes (CFSSST), which possess relatively large flexural stiffness, high corrosion resistance and require simple joint configurations and low maintenance cost, have a great potential in constructional applications. Despite that the use of stainless steel may result in high initial cost compared to their conventional carbon steel counterparts, the whole-life cost of CFSSST is however considered to be lower, which offers a competitive choice in engineering practice. In this paper, a comprehensive experimental and numerical program on 24 CFSSST stub column specimens, including 3 austenitic and 3 duplex stainless steel square hollow section (SHS) stub columns and 9 austenitic and 9 duplex CFSSST stub columns, has been carried out. Finite element (FE) models were developed to be used in parametric analysis to investigate the influence of the tube thickness and concrete strength on the ultimate capacities more accurately. Comparisons of the experimental and numerical results with the predictions made by design guides ACI 318, ANSI/AISC 360, Eurocode 4 and GB 50936 have been performed. It was found that these design methods generally give conservative predictions to the ultimate capacities of CFSSST stub columns. Improved calculation methods, developed based on the Continuous Strength Method, have been proposed to provide more accurate estimations of the ultimate resistances of CFSSST stub columns. The suitability of these proposals has been validated by comparison with the test results, where a good agreement between the predictions and the test results have been achieved.