scholarly journals 4D Atlas: Statistical Analysis of the Spatiotemporal Variability in Longitudinal 3D Shape Data

2021 ◽  
Author(s):  
HAMID LAGA ◽  
Marcel Padilla ◽  
Ian H. Jermyn ◽  
Sebastian Kurtek ◽  
Mohammed Bennamoun ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Building Blocks ◽  
Shape Space ◽  
Spatiotemporal Variability ◽  
3D Shape ◽  
Execution Rates ◽  
And Performance ◽  
Body Shapes ◽  
Spatiotemporal Registration ◽  
Shape Data

We propose a novel framework to learn the spatiotemporal variability in longitudinal 3D shape data sets, which contain observations of subjects that evolve and deform over time. This problem is challenging since surfaces come with arbitrary parameterizations and thus, they need to be spatially registered onto each others. Also, different deforming subjects, hereinafter referred to as 4D surfaces, evolve at different speeds and thus, they need to be temporally aligned onto each others. We solve this spatiotemporal registration problem using a Riemannian approach. We treat a 3D surface as a point in a shape space equipped with an elastic Riemmanian metric that measures the amount of bending and stretching that the surfaces undergo. A 4D surface can then be seen as a trajectory in this space. With this formulation, the statistical analysis of 4D surfaces can be cast as the problem of analyzing trajectories, or 1D curves, embedded in a nonlinear Riemannian manifold. However, performing the spatiotemporal registration, and subsequently computing statistics, on such nonlinear spaces is not straightforward as they rely on complex nonlinear optimizations. Our core contribution is the mapping of the surfaces to the space of Square-Root Normal Fields (SRNF) where the L2 metric is equivalent to the partial elastic metric in the space of surfaces. Thus, by solving the spatial registration in the SRNF space, the problem of analyzing 4D surfaces becomes the problem of analyzing trajectories embedded in the SRNF space, which has a Euclidean structure. In this paper, we develop the building blocks that enable such analysis. These include: (1) the spatiotemporal registration of arbitrarily parameterized 4D surfaces even in the presence of large elastic deformations and large variations in their execution rates, (2) the computation of geodesics between 4D surfaces, (3) the computation of statistical summaries, such as means and modes of variation, of collections of 4D surfaces, and (4) the synthesis of random 4D surfaces. We demonstrate the utility and performance of the proposed framework using 4D facial surfaces and 4D human body shapes.

scholarly journals 4D Atlas: Statistical Analysis of the Spatiotemporal Variability in Longitudinal 3D Shape Data

2021 ◽  
Author(s):  
HAMID LAGA ◽  
Marcel Padilla ◽  
Ian H. Jermyn ◽  
Sebastian Kurtek ◽  
Mohammed Bennamoun ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Building Blocks ◽  
Shape Space ◽  
Spatiotemporal Variability ◽  
3D Shape ◽  
Execution Rates ◽  
And Performance ◽  
Body Shapes ◽  
Spatiotemporal Registration ◽  
Shape Data

We propose a novel framework to learn the spatiotemporal variability in longitudinal 3D shape data sets, which contain observations of subjects that evolve and deform over time. This problem is challenging since surfaces come with arbitrary parameterizations and thus, they need to be spatially registered onto each others. Also, different deforming subjects, hereinafter referred to as 4D surfaces, evolve at different speeds and thus, they need to be temporally aligned onto each others. We solve this spatiotemporal registration problem using a Riemannian approach. We treat a 3D surface as a point in a shape space equipped with an elastic Riemmanian metric that measures the amount of bending and stretching that the surfaces undergo. A 4D surface can then be seen as a trajectory in this space. With this formulation, the statistical analysis of 4D surfaces can be cast as the problem of analyzing trajectories, or 1D curves, embedded in a nonlinear Riemannian manifold. However, performing the spatiotemporal registration, and subsequently computing statistics, on such nonlinear spaces is not straightforward as they rely on complex nonlinear optimizations. Our core contribution is the mapping of the surfaces to the space of Square-Root Normal Fields (SRNF) where the L2 metric is equivalent to the partial elastic metric in the space of surfaces. Thus, by solving the spatial registration in the SRNF space, the problem of analyzing 4D surfaces becomes the problem of analyzing trajectories embedded in the SRNF space, which has a Euclidean structure. In this paper, we develop the building blocks that enable such analysis. These include: (1) the spatiotemporal registration of arbitrarily parameterized 4D surfaces even in the presence of large elastic deformations and large variations in their execution rates, (2) the computation of geodesics between 4D surfaces, (3) the computation of statistical summaries, such as means and modes of variation, of collections of 4D surfaces, and (4) the synthesis of random 4D surfaces. We demonstrate the utility and performance of the proposed framework using 4D facial surfaces and 4D human body shapes.

scholarly journals TESSA: design and implementation of a platform for situational sea awareness

2017 ◽  
Vol 17 (2) ◽  
pp. 185-196
Author(s):  
Mario Scalas ◽  
Palmalisa Marra ◽  
Luca Tedesco ◽  
Raffaele Quarta ◽  
Emanuele Cantoro ◽  
...  
Keyword(s):  
Situational Awareness ◽  
Building Blocks ◽  
Ministry Of Education ◽  
End User ◽  
Performance Requirements ◽  
Platform Architecture ◽  
Front End ◽  
Critical Issues ◽  
And Performance ◽  
Key Aspects

Abstract. This article describes the architecture of sea situational awareness (SSA) platform, a major asset within TESSA, an industrial research project funded by the Italian Ministry of Education and Research. The main aim of the platform is to collect, transform and provide forecast and observational data as information suitable for delivery across a variety of channels, like web and mobile; specifically, the ability to produce and provide forecast information suitable for creating SSA-enabled applications has been a critical driving factor when designing and evolving the whole architecture. Thus, starting from functional and performance requirements, the platform architecture is described in terms of its main building blocks and flows among them: front-end components that support end-user applications and map and data analysis components that allow for serving maps and querying data. Focus is directed to key aspects and decisions about the main issues faced, like interoperability, scalability, efficiency and adaptability, but it also considers insights about future works in this and similarly related subjects. Some analysis results are also provided in order to better characterize critical issues and related solutions.

High Yield Assembly of Compliant MEMS Snap Fasteners

2008 ◽  
Author(s):  
Rakesh Murthy ◽  
Aditya N. Das ◽  
Dan O. Popa
Keyword(s):  
Self Assembly ◽  
Building Blocks ◽  
Deformation Energy ◽  
High Yield ◽  
3 Dimensional ◽  
Lab Experiments ◽  
Trade Offs ◽  
Robotic Cells ◽  
And Performance ◽  
Important Design

Heterogeneous assembly at the microscale has recently emerged as a viable pathway to constructing 3-dimensional microrobots and other miniaturized devices. In contrast to self-assembly, this method is directed and deterministic, and is based on serial or parallel microassembly. Whereas at the meso and macro scales, automation is often undertaken after, and often benchmarked against manual assembly, we demonstrate that deterministic automation at the MEMS scale can be completed with higher yields through the use of engineered compliance and precision robotic cells. Snap fasteners have long been used as a way to exploit the inherent stability of local minima of the deformation energy caused by interference during part mating. In this paper we assume that the building blocks are 2 1/2 -dimensional, as is the case with lithographically microfabricated MEMS parts. The assembly of the snap fasteners is done using μ3, a multi-robot microassembly station with unique characteristics located at our ARRI’s Texas Microfactory lab. Experiments are performed to demonstrate that fast and reliable assemblies can be expected if the microparts and the robotic cell satisfy a so-called “High Yield Assembly Condition” (H.Y.A.C.). Important design trade-offs for assembly and performance of microsnap fasteners are discussed and experimentally evaluated.

scholarly journals ARTIKEL REKRUTMEN APARATUR DESA TERHADAP PENINGKATAN KINERJA PEMERINTAH DI DESA ANALUTUR, KECAMATAN BABAT TIMUR KABUPATEN MALUKU BARAT DAYA

2021 ◽  
Author(s):  
Yulius Luturmas
Keyword(s):  
Statistical Analysis ◽  
Confidence Level ◽  
Coefficient Of Determination ◽  
Government Performance ◽  
Structured Interviews ◽  
Literature Study ◽  
And Performance ◽  
Village Government ◽  
The Village ◽  
Recruitment Performance

ABSTRACTThe Village Government apparatus of Analutur, Southwest Maluku Regency is not excellent, and one of the influencing factors is that the Village Apparatus Recruitment is not carried out properly. By using associative research methods that link recruitment and performance. Data were collected by conducting structured interviews, observations, literature study, and distributing a list of questions to 50 respondents. then analyzed quantitatively (Product Moment Correlation Statistical Analysis). The results show that the correlation between apparatus recruitment and government performance in Analutur Village, Southwest Maluku Regency is 0.857. Based on the coefficient of determination, it is proven that recruitment contributes to performance by 62.2% and the remaining 37.8% is determined by other variables which are constant. Furthermore, a significant test was carried out using t-count at a confidence level of 0.05%. And the result is t-count of 8.888> t-table 1.68, which means that the hypothesis is accepted. Keywords: Apparatus Recruitment, Performance and Village Improvement

Drawing with Performance Prediction

1995 ◽  
Author(s):  
Peter Schwenn ◽  
George Hazen
Keyword(s):  
Design Optimization ◽  
Performance Prediction ◽  
Fold Increase ◽  
Building Blocks ◽  
Programming Environment ◽  
Immediate Feedback ◽  
Surface Stability ◽  
Performance Constraints ◽  
And Performance ◽  
The One

We describe some advances in Performance Prediction Programs - "PPP"1 for sailing yachts2 - primarily integrating PPP analysis into drawing and providing new sculpting operations in which fairness and desired hydrostatic and on her performance determining characteristics are maintained - the shape remains a boat or a ship of the desired kind during reshaping. Our building blocks for such an integration are: a thousand-fold increase in PPP speed3, new editing tools which maintain Boatness4 , and an accessible modularization of the engineering physics of the PPP within a new programming environment which allows immediate changes by designers. Specifically, these new functions are introduced at the boundary of Drawing and the PPP: - A live knotmeter is displayed with each design variant on the drawing boar, - alongside it's antagonist - Rating. - Continuously updated hydrotatics (including the speed determining factors LSM, wetted surface, stability, prismatics, .. ) are displayed with the knotometer, with the 'positive' factors (like length) graphically opposing the 'negative' (like wetted surface.) Dimensions for PPP use are calculated automatically from the shape at hand - in particular: appendage dimensions, hydrostatics, and so forth. - Bounding limits are set for a design optimization by drawing two or more outlier yacht forms. The space in between can be explored by hand or automatically. - Local optimums of Speed against rating are provided as a 'Snap' function. This is the one dimensional version of automatic exploration for optima. - Intermediate shapes are also controlled during design optimization to maintain realism and performance constraints on type, fairness, 'look', speed producing shape measures like prismatic and displacement etc., and even handicap. - Immediate feedback is available if one chooses to exploit the new programming environment to make aero hydro model changes or extensions to the internal PPP mechanisms while drawing and exploring.

Effect of forage maize harvested at different stages of maturity on feed intake and performance by growing beef cattle

1998 ◽  
Vol 1998 ◽  
pp. 148-148
Author(s):  
E.M. Browne ◽  
M.J. Bryant ◽  
D.E. Beever ◽  
C.L. Thorp
Keyword(s):  
Statistical Analysis ◽  
Beef Cattle ◽  
Dry Matter ◽  
Maize Silage ◽  
Initial Weight ◽  
Forage Maize ◽  
Maize Variety ◽  
Ad Libitum ◽  
Pre Treatment ◽  
And Performance

Dry matter (DM) concentration of maize silage is directly related to maturity of the crop at harvest and widely reported to be positively correlated with total forage DM intake. The objective of this experiment was to investigate these effects using a late maturing beef genotype and a contemporary forage maize variety.Forage maize (variety Hudson) was harvested at four different stages of maturity during September and October 1996. Each stage of maturity was ensiled in a separate clamp with no additive. Resultant silage corrected dry matter contents were 247 (L), 305 (M/L), 331(M/H) and 388 (H)g/kgFW, respectively. Each diet was formulated to be isonitrogenous with fishmeal fed twice daily on top of the silage. Silage was offered ad libitum to 32 growing Simmental X Friesian heifers (mean initial weight 217kg), housed in individual pens in an open-sided Dutch barn and bedded on wheat straw. Eight animals were allocated to each treatment, in a completely randomised design with pre-treatment intake (non-experimental maize silage) used as a covariate in the statistical analysis.

Identification of critical brand community variables and constructs using importance-performance analysis and neural networks

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Matti Haverila ◽  
Kai Christian Haverila ◽  
Caitlin McLaughlin
Keyword(s):  
Neural Networks ◽  
Statistical Analysis ◽  
Online Survey ◽  
Customer Engagement ◽  
Analysis Tool ◽  
Brand Community ◽  
Content Type ◽  
Target Construct ◽  
Statistical Analysis Tool ◽  
And Performance

Purpose This paper aims to use a unique statistical analysis tool to examine the importance and performance of critical brand community constructs and indicators to make concrete recommendations for brand community managers going forward. Design/methodology/approach An online survey was used to gather 501 responses from North American members of the Qualtrics panel. The data was analyzed with partial least squares (PLS) modeling software SmartPLS and neural networks available in statistical software JMP by SAS. Findings Using the brand community motives by Madupy and Cooley (2010), the results of this paper indicated that there was significant room for improvement in customer engagement. Based on further analysis, entertainment and identification with the brand community were the most important constructs in driving community engagement so that the identification construct received a “do better” ruling meaning that the improvement of the indentification construct score would enhance significantly the score of the target construct engagement score. Originality/value For brand community managers, it is important to know the true importance of the critical brand community constructs and indicators, along with an assessment of current performance. This helps to increase satisfaction and relationship quality among brand community members. The current study uses unique statistical analysis tools to make such concrete recommendations.

A Methodology for Evaluating Application Software

1986 ◽  
Vol 30 (1) ◽  
pp. 14-18 ◽  
Author(s):  
Andrew M. Cohill ◽  
David M. Gilfoil ◽  
John V. Pilitsis
Keyword(s):  
Statistical Analysis ◽  
Data Base ◽  
Software Package ◽  
Word Processing ◽  
The Other ◽  
Application Software ◽  
Raw Data ◽  
And Performance

A methodology for evaluating applications software is proposed, using five different categories of criteria. Three of the categories, functionality, usability, and performance, are tailored for each class of applications software. The other two categories, support and documentation, have generic criteria that can be applied to all types of application software. After a software package has been scored according to the criteria of a category, statistical analysis is used to convert the raw data to a numeric score that can be used to make between-product comparisons. The methodology has been successfully tested with UNIX-based* word processing and data base packages.

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