Engineering graphics’ knowledge: its persistence and application evaluation

2015 ◽  
Author(s):  
Zenonas Turskis ◽  
Birutė Juodagalvienė ◽  
Inga Garnytė Sapranavičienė
Keyword(s):  
Data Analysis ◽  
Civil Engineering ◽  
Real Data ◽  
Design Data ◽  
Data Set ◽  
Evaluation Data ◽  
Engineering Graphics ◽  
The Relationship ◽  
Constructional Design

The article deals with the knowledge of engineering graphics, obtained during studies and its application in architectural and constructional design. Data analysis was carried out and the relationship between the exams’ grades in lower and upper semesters was determined. The evaluations of the following subjects have been examined: General Engineering Graphics, Applied Engineering Graphics, Building Architecture and Structures 1, Building Architecture and Structures 2. The present paper describes the development of an approach that uses a real data set. The investigated data illustrates relevant concepts and methods in the application of introductory civil engineering. The creative use of students' scores evaluation data is recommended to facilitate the learning of civil engineering. The course has enrolments of approximately 250 students.

scholarly journals Spatial pattern and genetic diversity estimates are linked in stochastic models of population differentiation

2000 ◽  
Vol 23 (3) ◽  
pp. 541-544 ◽  
Author(s):  
José Alexandre Felizola Diniz-Filho ◽  
Mariana Pires de Campos Telles
Keyword(s):  
Genetic Diversity ◽  
Spatial Pattern ◽  
Stochastic Models ◽  
Population Differentiation ◽  
Real Data ◽  
Population Heterogeneity ◽  
Data Set ◽  
Mantel’S Test ◽  
The Relationship ◽  
Diversity Estimates

In the present study, we used both simulations and real data set analyses to show that, under stochastic processes of population differentiation, the concepts of spatial heterogeneity and spatial pattern overlap. In these processes, the proportion of variation among and within a population (measured by G ST and 1 - G ST, respectively) is correlated with the slope and intercept of a Mantel's test relating genetic and geographic distances. Beyond the conceptual interest, the inspection of the relationship between population heterogeneity and spatial pattern can be used to test departures from stochasticity in the study of population differentiation.

Common risk difference test and interval estimation of risk difference for stratified bilateral correlated data

2018 ◽  
Vol 28 (8) ◽  
pp. 2418-2438
Author(s):  
Xi Shen ◽  
Chang-Xing Ma ◽  
Kam C Yuen ◽  
Guo-Liang Tian
Keyword(s):  
Data Analysis ◽  
Confidence Interval ◽  
Score Test ◽  
Real Data ◽  
Risk Difference ◽  
Error Rates ◽  
Correlated Data ◽  
Test Statistic ◽  
Data Set ◽  
Intra Class Correlation

Bilateral correlated data are often encountered in medical researches such as ophthalmologic (or otolaryngologic) studies, in which each unit contributes information from paired organs to the data analysis, and the measurements from such paired organs are generally highly correlated. Various statistical methods have been developed to tackle intra-class correlation on bilateral correlated data analysis. In practice, it is very important to adjust the effect of confounder on statistical inferences, since either ignoring the intra-class correlation or confounding effect may lead to biased results. In this article, we propose three approaches for testing common risk difference for stratified bilateral correlated data under the assumption of equal correlation. Five confidence intervals of common difference of two proportions are derived. The performance of the proposed test methods and confidence interval estimations is evaluated by Monte Carlo simulations. The simulation results show that the score test statistic outperforms other statistics in the sense that the former has robust type [Formula: see text] error rates with high powers. The score confidence interval induced from the score test statistic performs satisfactorily in terms of coverage probabilities with reasonable interval widths. A real data set from an otolaryngologic study is used to illustrate the proposed methodologies.

Residual moveout in anisotropic angle-domain common-image gathers

Geophysics ◽  
2007 ◽  
Vol 72 (2) ◽  
pp. S93-S103 ◽  
Author(s):  
Biondo Biondi
Keyword(s):  
Real Data ◽  
Velocity Estimation ◽  
Aperture Angle ◽  
Data Set ◽  
3D Data ◽  
Wavefield Continuation ◽  
Transverse Isotropic ◽  
Phase Angles ◽  
The Relationship ◽  
General Method

I develop the fundamental concepts for quantitatively relating perturbations in anisotropic parameters to the corresponding reflector movements in angle-domain common-image gathers (ADCIGs) after anisotropic wavefield-continuation migration. The proposed theory potentially enables the application of residual moveout (RMO) analysis of ADCIGs to velocity estimation in realistic anisotropic conditions. I demonstrate that linearization of the relationship between anisotropic velocity parameters and reflector movements can be derived by assuming stationary raypaths. This assumption leads to a fairly simple analytical derivation. I then apply the general method to the particular case of RMO analysis of reflections from flat reflectors in a vertical transverse isotropic (VTI) medium. This analysis yields expressions to predict RMO curves in migrated ADCIGs. These RMO expressions are functions of both the phase aperture angle and the group aperture angle. Several numerical examples demonstrate the accuracy of the RMO curves predicted by my kinematic analysis. The synthetic examples also show that approximating the group angles with the phase angles in the application of the RMO expressions may lead to substantial errors for events reflected at wide aperture angles. The results obtained by migrating a 2D line extracted from a Gulf of Mexico 3D data set confirm the accuracy of the proposed method. The RMO curves predicted by the theory match the RMO function observed in the ADCIGs computed from the real data.

scholarly journals The AtGenExpress hormone and chemical treatment data set: experimental design, data evaluation, model data analysis and data access

2008 ◽  
Vol 55 (3) ◽  
pp. 526-542 ◽  
Author(s):  
Hideki Goda ◽  
Eriko Sasaki ◽  
Kenji Akiyama ◽  
Akiko Maruyama-Nakashita ◽  
Kazumi Nakabayashi ◽  
...  
Keyword(s):  
Data Analysis ◽  
Experimental Design ◽  
Chemical Treatment ◽  
Evaluation Model ◽  
Data Access ◽  
Data Evaluation ◽  
Model Data ◽  
Design Data ◽  
Data Set ◽  
Treatment Data

Identifying and Classifying Aberrant Response Patterns Through Functional Data Analysis

2020 ◽  
Vol 45 (6) ◽  
pp. 719-749
Author(s):  
Eduardo Doval ◽  
Pedro Delicado
Keyword(s):  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Simulated Data ◽  
Real Data ◽  
Response Patterns ◽  
Fit Indices ◽  
Person Fit ◽  
Data Set ◽  
Aberrant Response Patterns

We propose new methods for identifying and classifying aberrant response patterns (ARPs) by means of functional data analysis. These methods take the person response function (PRF) of an individual and compare it with the pattern that would correspond to a generic individual of the same ability according to the item-person response surface. ARPs correspond to atypical difference functions. The ARP classification is done with functional data clustering applied to the PRFs identified as ARP. We apply these methods to two sets of simulated data (the first is used to illustrate the ARP identification methods and the second demonstrates classification of the response patterns flagged as ARP) and a real data set (a Grade 12 science assessment test, SAT, with 32 items answered by 600 examinees). For comparative purposes, ARPs are also identified with three nonparametric person-fit indices (Ht, Modified Caution Index, and ZU3). Our results indicate that the ARP detection ability of one of our proposed methods is comparable to that of person-fit indices. Moreover, the proposed classification methods enable ARP associated with either spuriously low or spuriously high scores to be distinguished.

scholarly journals A theory for non-linear prediction approach in the presence of vague variables: with application to BMI monitoring

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
R. Pourmousa ◽  
M. Rezapour ◽  
M. Mashinchi
Keyword(s):  
Linear Prediction ◽  
Real Data ◽  
Continuous Data ◽  
Data Set ◽  
Truncated Data ◽  
Fault Inference ◽  
Prediction Approach ◽  
The Relationship ◽  
Threshold Point ◽  
Error Of Measurement

AbstractIn the statistical literature, truncated distributions can be used for modeling real data. Due to error of measurement in truncated continuous data, choosing a crisp trimmed point caucuses a fault inference, so using fuzzy sets to define a threshold pointmay leads us more efficient results with respect to crisp thresholds. Arellano-Valle et al. [2] defined a selection distribution for analysis of truncated data with crisp threshold. In this paper, we define fuzzy multivariate selection distribution that is an extension of the selection distributions using fuzzy threshold. A practical data set with a fuzzy threshold point is considered to investigate the relationship between high blood pressure and BMI.

scholarly journals Pengaruh Independence Commitment Terhadap Niat Melakukan Whistleblowing Dengan Group Cohesion Sebagai Variabel Moderasi: Sebuah Studi Eksperimen

2019 ◽  
Vol 1 (4) ◽  
pp. 1617-1632
Author(s):  
Yulina Eka Safitri ◽  
Sany Dwita
Keyword(s):  
Data Analysis ◽  
Hypothesis Test ◽  
Group Cohesion ◽  
Accounting Students ◽  
State University ◽  
Factorial Experimental Design ◽  
Design Data ◽  
Quasi Experimental ◽  
The Relationship ◽  
One Way Anova

This study aims to empirically examine the effect of independence commitment on the intention to do whistleblowing with group cohession as a moderating variable. This type of research is classified as quasi-experimental with 2 x 2 factorial experimental design. Data in this study were collected using a questionnaire on 80 accounting students of the Faculty of Economics, State University of Padang. Data analysis was performed using One way ANOVA and MRA. The results of this study conclude that independence commitment influences whistleblowing intentions, while group cohession does not moderate the relationship between independence commitment and whistleblowing. This is evidenced by the hypothesis test, where the H1 significance value is 0.001 <0.005 and the significance value at H2 is 0.184> 0.005.

scholarly journals The environmental theme in nurses’ qualification curriculum in a middle-sized brazilian city: convergences and divergences

2020 ◽  
Vol 9 (7) ◽  
pp. e94973819
Author(s):  
Camila Henriques Nunes ◽  
Mario Sergio Michaliszyn ◽  
Eduardo Shimoda
Keyword(s):  
Data Analysis ◽  
Nursing Students ◽  
Environmental Issues ◽  
Point Of View ◽  
Structured Interviews ◽  
Design Data ◽  
Documentary Analysis ◽  
Quantitative Data Analysis ◽  
The Relationship ◽  
The City

One of the goals of nursing is health promotion, and because of that, the study of the environment, standing for the relationship between the professional and society, must be fully incorporated into nurses’ qualifications. This study aimed to analyze the insertion of environmental issues into a nursing degree in a middle-sized Brazilian city from the point of view of the different actors involved: professors, students, and coordinators. The study had a mixed-methods design. Data collection was done through a documentary analysis of political teaching projects; questionnaires to nursing students; and semi-structured interviews with coordinators and professors of Higher Education Institutions of the city. The quantitative data analysis was done through statistical methods and the Scott‒Knott Test; the qualitative data analysis was done through the content analysis proposed by Bardin. The results demonstrate a lack of proper handling of environmental issues, with the work only involving the specific environmental subjects that are the most prominent. Although environmental issues are only inserted at random into the teaching, the students still understand the importance of environmental knowledge as it applies to the technical subjects of the nursing degree.

The AtGenExpress hormone- and chemical-treatment data set: Experimental design, data evaluation, model data analysis, and data access

2008 ◽  
Vol 0 (ja) ◽  
pp. 080414150319983 ◽  
Author(s):  
Hideki Goda ◽  
Eriko Sasaki ◽  
Kenji Akiyama ◽  
Akiko Maruyama-Nakashita ◽  
Kazumi Nakabayashi ◽  
...  
Keyword(s):  
Data Analysis ◽  
Experimental Design ◽  
Chemical Treatment ◽  
Evaluation Model ◽  
Data Access ◽  
Data Evaluation ◽  
Model Data ◽  
Design Data ◽  
Data Set ◽  
Treatment Data

scholarly journals A Panel Data Analysis of Relationship between Migration and Inequality

2016 ◽  
Vol 6 (1) ◽  
pp. 98-109
Author(s):  
Raju John
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Panel Data Analysis ◽  
The State ◽  
Current Status ◽  
Data Set ◽  
Different Types ◽  
Migrant Households ◽  
The Relationship

In this article, the relationship between migration and inequality in India is analyzed on the basis of an understanding of the role of migration in creating inequalities in the economy and society of the state of Kerala. The Centre for Development Studies (CDS), Thiruvanathapuram, Kerala, conducts periodic Kerala Migration Surveys (KMSs) to monitor the current status of emigration from and return emigration to the state of Kerala. This data set is used to discover the dynamics of migration–inequality relationship in the state. The results of the study suggest that migration causes inequalities in mobility between migrant and non-migrant households and between different types of migrant households.

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