Grid Services for 3D Data Analysis in Virtual Laboratories

2009 ◽  
pp. 481-498 ◽  
Author(s):  
A. Clematis ◽  
A. Corana ◽  
D. D’Agostino ◽  
V. Gianuzzi ◽  
A. Merlo
Keyword(s):  
Data Analysis ◽  
Grid Services ◽  
3D Data ◽  
Virtual Laboratories

Exploratory Data Analysis

2018 ◽  
pp. 112-136
Keyword(s):  
Data Analysis ◽  
Probability Space ◽  
Exploratory Data Analysis ◽  
Spatial Location ◽  
K Index ◽  
3D Data ◽  
Gaussian Density ◽  
Exploratory Data ◽  
Nearest Neighborhood ◽  
Quadrat Analysis

Exploratory data analysis (EDA) tries to summarize datasets main characteristics such as nearest neighborhood indexes, standard deviation, scatterplots or quadrat analysis. This EDA chapter is divided into several sections to cover myGeoffice© options not forgetting the graphical mode when facing outputs: file data input (after all, any analysis demands data); Descriptive study of the variable (mean, kurtosis, distribution plot, etc.); 2D-3D data posting (spatial location of the data samples); Cutoff layout map (a spatial colorful plot according to the data samples values that are higher and lower against any particular threshold); G and Kipley's K Index (to disclose clustered, uniform and random space sampling); Kernel Gaussian density (a non-parametric way to estimate the probability space density function of a variable); T-Student and F-tests (a parametric approach to check statistical differences between two sub-regions), including a brief section regarding the two-way ANOVA technique; Quadrat analysis (comparison of the statistically expected and actual counts of objects within spatial sampling areas to test randomness and clustering); XX profile scatterplot (silhouette view of the data along XX axis); and YY profile scatterplot (silhouette view of the data along YY axis).

Assisting Pottery Restoration Procedures with Digital Technologies

2019 ◽  
Vol 3 (1) ◽  
pp. 20-32 ◽  
Author(s):  
Ioannis Kalasarinis ◽  
Anestis Koutsoudis
Keyword(s):  
Data Analysis ◽  
Open Source Software ◽  
Shape Matching ◽  
Low Cost ◽  
Digital Technologies ◽  
Hellenistic Period ◽  
Ancient Greek ◽  
3D Data ◽  
Wide Range ◽  
3D Digitisation

The fragmentary nature of pottery is considered a common place. Conservators are requested to apply a proper restoration solution by taking under consideration a wide range of morphological features and physicochemical properties that derive from the artefact itself. In this work, the authors discuss on a low-cost pottery-oriented restoration pipeline that is based on the exploitation of technologies such as 3D digitisation, data analysis, processing and printing. The pipeline uses low-cost commercial and open source software tools and on the authors' previously published 3D pose normalisation algorithm that was initially designed for 3D vessel shape matching. The authors objectively evaluate the pipeline by applying it on two ancient Greek vessels of the Hellenistic period. The authors describe in detail the involved procedures such as the photogrammetric 3D digitisation, the 3D data analysis and processing, the 3D printing procedures and the synthetic shreds post processing. They quantify the pipeline's applicability and efficiency in terms of cost, knowledge overhead and other aspects related to restoration tasks.

Preface on Numerical Computation in 2D & 3D Data Analysis

2017 ◽  
Author(s):  
Ryszard Kozera ◽  
Władysław Homenda ◽  
Agnieszka Szczęsna ◽  
Artur Wiliński
Keyword(s):  
Data Analysis ◽  
Numerical Computation ◽  
3D Data

Workshop on Numerical Computation in 2D & 3D Data Analysis, WNCDA 2017 Symposium 18, ICNAAM 2017

2018 ◽  
Author(s):  
Ryszard Kozera ◽  
Agnieszka Szczęsna ◽  
Artur Wiliński
Keyword(s):  
Data Analysis ◽  
Numerical Computation ◽  
3D Data

scholarly journals THE USE OF VIRTUAL LABORATORY TO IMPROVE STUDENTS' CONCEPTUAL UNDERSTANDING IN ACID BASE TITRATION SUBJECT

2019 ◽  
Vol 3 (1) ◽  
pp. 43
Author(s):  
Erni Erni
Keyword(s):  
Data Analysis ◽  
Conceptual Understanding ◽  
T Test ◽  
Virtual Laboratory ◽  
Acid Base ◽  
Virtual Laboratories ◽  
Analysis Technique ◽  
Acid Base Titration ◽  
Final Data ◽  
The Mean

The research has been conducted to figure out the use of virtual laboratories on students' conceptual understanding of acid-base titration subject at SMAN 1 Tambusai. The study was an experimental research with one group pretest-posttest design. The sample consisted of one class, XI IPA2, a class that was treated with a virtual laboratory. The data analysis technique used was the t-test. Based on the results of the final data processing using the t-test, it was obtained that sig 5 ≤ 0.05; where 0,000 ≤ 0.05; so it was concluded that there were significant differences between the mean scores of the pretest and posttest. This shows that there is an increase by the use of virtual laboratories towards the students' conceptual understanding

MACSPIN: 3D DATA ANALYSIS SOFTWARE

Terra Nova ◽  
1992 ◽  
Vol 4 (6) ◽  
pp. 701-704
Author(s):  
Paul Browning
Keyword(s):  
Data Analysis ◽  
Analysis Software ◽  
3D Data ◽  
Data Analysis Software

scholarly journals Towards an Understanding of Augmented Reality Extensions for Existing 3D Data Analysis Tools

2020 ◽  
Author(s):  
Xiyao Wang ◽  
Lonni Besançon ◽  
David Rousseau ◽  
Mickael Sereno ◽  
Mehdi Ammi ◽  
...  
Keyword(s):  
Data Analysis ◽  
Augmented Reality ◽  
Analysis Tools ◽  
3D Data

scholarly journals Student Science Process Skills through the Application of Computer Based Scaffolding assisted by PhET Simulation

At-Taqaddum ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 21-38
Author(s):  
Affa Ardhi Saputri
Keyword(s):  
Online Learning ◽  
Data Analysis ◽  
Sampling Technique ◽  
Data Interpretation ◽  
Process Skills ◽  
Science Process Skills ◽  
Offline Learning ◽  
Virtual Laboratories ◽  
Basic Physics ◽  
Computer Based

Basic physics practicum learning through virtual laboratories is less than optimal in developing students' science process skills. This study reveals the results of improving students' science process skills based on the application of computer scaffolding assisted by PhET simulation. This study uses a quantitative approach with a sample of 14 students through purposive sampling technique. The research stages consist of introduction, implementation, and evaluation. Collecting data through interviews, tests, and observations. Data analysis using the N-gain test. The results showed an increase in students' science process skills on several indicators with various categories. The indicator is observing 0.49 (medium category), formulating hypotheses 0.34 (medium category), carrying out experiments 0.39 (medium category), data interpretation and analysis 0.42 (medium category), communicating 0.33 (medium category), and concluded 0.29 (low category). Computer-based scaffolding with PhET simulation is an online learning solution that can also be collaborated with offline learning to improve students' science process skills.

scholarly journals Discrete Distortion for 3D Data Analysis

2012 ◽  
pp. 3-25
Author(s):  
Leila De Floriani ◽  
Federico Iuricich ◽  
Paola Magillo ◽  
Mohammed Mostefa Mesmoudi ◽  
Kenneth Weiss
Keyword(s):  
Data Analysis ◽  
3D Data

scholarly journals Development of a Sizing System and a Draping Pattern for Hip Protector based on 3D Data Analysis of Korean Older Women

2016 ◽  
Vol 18 (1) ◽  
pp. 120-129 ◽  
Author(s):  
Eun-Jin Jeon ◽  
Sei-Kwon Park ◽  
Hee-Cheon You ◽  
Hee-Eun Kim
Keyword(s):  
Data Analysis ◽  
Older Women ◽  
Hip Protector ◽  
3D Data ◽  
Sizing System
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