• Journal of Information Processing Systems
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• 제8권2호
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• pp.241-262
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• 2012

An understanding of quality attributes is relevant for the software organization to deliver high software reliability. An empirical assessment of metrics to predict the quality attributes is essential in order to gain insight about the quality of software in the early phases of software development and to ensure corrective actions. In this paper, we predict a model to estimate fault proneness using Object Oriented CK metrics and QMOOD metrics. We apply one statistical method and six machine learning methods to predict the models. The proposed models are validated using dataset collected from Open Source software. The results are analyzed using Area Under the Curve (AUC) obtained from Receiver Operating Characteristics (ROC) analysis. The results show that the model predicted using the random forest and bagging methods outperformed all the other models. Hence, based on these results it is reasonable to claim that quality models have a significant relevance with Object Oriented metrics and that machine learning methods have a comparable performance with statistical methods.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2002년도 춘계 학술발표회 논문집
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• pp.1-5
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• 2002

We consider the problem of optimal bandwidth choice for nonparametric classification, based on kernel density estimators, where the problem of interest is distinguishing between two univariate distributions. When the densities intersect at a single point, optimal bandwidth choice depends on curvatures of the densities at that point. The problem of empirical bandwidth selection and classifying data in the tails of a distribution are also addressed.

• 한국연소학회:학술대회논문집
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• 한국연소학회 2012년도 제44회 KOSCO SYMPOSIUM 초록집
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• pp.107-109
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• 2012

A quasidimensional model is developed with the surrogate mechanism of isooctane and n-heptane to predict knock and emissions of a homogeneous GDI engine. It is composed of unburned and burned zone with the latter divided into multiple zones of equal mass to resolve temperature stratification. Validation is performed against measured pressure traces, NOx and CO emissions at different load and rpm conditions. Comparison is made between the empirical knock model and predictions by the chemistry model in this work.

• Communications for Statistical Applications and Methods
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• 제22권2호
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• pp.201-207
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• 2015

Support vector machine (SVM) is a well known kernel-trick supervised learning tool. This study proposes a working scheme for kernel-trick regression and classification (KtRC) as a SVM alternative. KtRC fits the model on a number of random subsamples and selects the best model. Empirical examples and a simulation study indicate that KtRC's performance is comparable to SVM.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1383-1385
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• 2003

Remote sensing has been widely used in the exploration of groundwater. In this paper, on the establishment of empirical function between ground water and soil moisture content 6S code is used to reduce uncertainties in the remote sensing of groundwater. Then ground water levels are calculated using 6S corrected and uncorrected ETM+ image along with isochronous meteorological information. Greater correspondence between field examined and satellite monitoring data is obtained from corrected image than from the uncorrected image.

• 한국자동차공학회논문집
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• 제8권4호
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• pp.42-50
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• 2000

Drop size distribution of an air-assisted fuel injector(AAFI) was investigated. Influence of parameters such as ambient air density supply pressure and air-liquid mass ratio(ALR) was examined through both measurement and analysis. The Sauter mean diameter$D_{32}$ varied from 9 to 25$\mu$m throughout all experimental conditions. An empirical correlation for droplet size was obtained. Analytical correlations for predicting $D_{32}$ with respect to operating conditions were also derived through energy consideration and introduction of a simplified model of the from the empirical fitting was adapted to the original equation the proposed correlation in this study matched more closely with measured results. The current correlation exhibited a favorable study matched more closely with measured results. The current correlation exhibited a favorable prediction for $D_{32}$ compared to that by the empirical correlation at selected experimental conditions so that it may be used to predict atomization performance of the AAFI at operating conditions which was not covered in the measurements. After validation the analytical equation was applied to survey the feasible operating conditions for gasoline direct injection application.

• Earthquakes and Structures
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• 제14권4호
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• pp.305-312
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• 2018

Significant research efforts were undertaken to evaluate seismic performance of vertically irregular buildings on flat ground. However, there is scarcity of study on seismic performance of buildings on hill slopes. The present study attempts to investigate seismic behaviour of reinforced concrete irregular stepback building frames with different configurations on sloping ground. Based on extensive regression study of free vibration results of four hundred seventeen frames with varying ground slope, number of story and span number, a modification is proposed to the code based empirical fundamental time period estimation formula. The modification to the fundamental time period estimation formula is a simplified function of ground slope and a newly introduced equivalent height parameter to reflect the effect of stiffness and mass irregularity. The derived empirical formula is successfully validated with various combinations of slope and framing configurations of buildings. The correlation between the predicted and the actual time period obtained from the free vibration analysis results are in good agreement. The various statistical parameters e.g., the root mean square error, coefficient of determination, standard average error generally used for validation of such regression equations also ensure the prediction capability of the proposed empirical relation with reasonable accuracy.

• Structural Monitoring and Maintenance
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• 제9권1호
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• pp.81-105
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• 2022

The use of concrete filled steel tube (CFST) column is widely accepted due to its property of high axial load carrying capacity, more ductility and more resistant to earthquake specially using in bridges and high-rise buildings. The initial imperfection (δ) that produces during casting or fixing causes the reduction in load carrying capacity, this is the reason, experimental capacity is always less then theoretical one. In this research, the effect of δ on load carrying capacity and behavior of concrete filled steel tube (CFST) column have been investigated by numerically simulation of large number of models with different δ and other geometric parameters that include length (L), width (B), steel tube thickness (t), f'_c and f_y. Finite element analysis software ANSYS v18 is used to develop model of SCFST column to evaluate strength capacity, buckling and failure pattern of member which is applied during experimental study under cyclic axial loading. After validation of results, 42 models with different parameters are evaluated to develop empirical equation predicting axial load carrying capacity for different value of δ. Results indicate that empirical equation shows the 0 to 9% error for finite element analysis Forty-two models in comparison with ANSYS results, respectively. Empirical equation can be used for predicting the axial capacity of early estimating the axial capacity of SCFT column including 𝛿.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제27권2호
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• pp.157-173
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• 2024

Researchers continue to emphasize the centrality of proof in the context of school mathematics and the importance of proof to student learning of mathematics is well articulated in nationwide curricula. However, researchers reported that students' performance in proving tasks is not promising and students are not likely to see the need to prove a proposition even if they learned mathematical proof previously. Research attributes this issue to students' tendencies to accept an empirical argument as proof for a mathematical proposition, thus not being able to recognize the limitation of an empirical argument as proof for a mathematical proposition. In Korea, there is little research that investigated high school students' views about the need for proof in mathematics and their understanding of the limitation of an empirical argument as proof for a mathematical generalization. Sixty-two 11^th graders were invited to participate in an online survey and the responses were recorded in writing and on either a four- or five-point Likert scale. The students were asked to express their agreement with the need of proof in school mathematics and to evaluate a set of mathematical arguments as to whether the given arguments were proofs. Results indicate that a slight majority of students were able to identify a proof amongst the given arguments with the vast majority of students acknowledging the need for proof in mathematics.

• Journal of Information Processing Systems
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• 제14권2호
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• pp.346-376
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• 2018

Digital forensics is a vital part of almost every criminal investigation given the amount of information available and the opportunities offered by electronic data to investigate and evidence a crime. However, in criminal justice proceedings, these electronic pieces of evidence are often considered with the utmost suspicion and uncertainty, although, on occasions are justifiable. Presently, the use of scientifically unproven forensic techniques are highly criticized in legal proceedings. Nevertheless, the exceedingly distinct and dynamic characteristics of electronic data, in addition to the current legislation and privacy laws remain as challenging aspects for systematically attesting evidence in a court of law. This article presents a comprehensive study to examine the issues that are considered essential to discuss and resolve, for the proper acceptance of evidence based on scientific grounds. Moreover, the article explains the state of forensics in emerging sub-fields of digital technology such as, cloud computing, social media, and the Internet of Things (IoT), and reviewing the challenges which may complicate the process of systematic validation of electronic evidence. The study further explores various solutions previously proposed, by researchers and academics, regarding their appropriateness based on their experimental evaluation. Additionally, this article suggests open research areas, highlighting many of the issues and problems associated with the empirical evaluation of these solutions for immediate attention by researchers and practitioners. Notably, academics must react to these challenges with appropriate emphasis on methodical verification. Therefore, for this purpose, the issues in the experiential validation of practices currently available are reviewed in this study. The review also discusses the struggle involved in demonstrating the reliability and validity of these approaches with contemporary evaluation methods. Furthermore, the development of best practices, reliable tools and the formulation of formal testing methods for digital forensic techniques are highlighted which could be extremely useful and of immense value to improve the trustworthiness of electronic evidence in legal proceedings.