Data analysis framework for visual interactive product design under the background of cloud social speech environment

2021 ◽  
Author(s):  
Xiao Ye ◽  
Xin Lv
Keyword(s):  
Data Analysis ◽  
Product Design ◽  
Analysis Framework ◽  
Interactive Product

scholarly journals Big data analysis for product design

2021 ◽  
Vol 1122 (1) ◽  
pp. 012064
Author(s):  
Juliza Hidayati ◽  
Shelvy Riry Gusrina ◽  
Nazaruddin Matondang
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Product Design ◽  
Big Data Analysis

scholarly journals A new data analysis framework for the search of continuous gravitational wave signals

2018 ◽  
Vol 36 (1) ◽  
pp. 015008 ◽  
Author(s):  
O J Piccinni ◽  
P Astone ◽  
S D’Antonio ◽  
S Frasca ◽  
G Intini ◽  
...  
Keyword(s):  
Data Analysis ◽  
Gravitational Wave ◽  
Analysis Framework

Interactive Product Design

2011 ◽  
pp. 45-84 ◽  
Author(s):  
Xavier Fischer ◽  
Georges Fadel ◽  
Yann Ledoux
Keyword(s):  
Product Design ◽  
Interactive Product

Interactive Product Design Selection With an Implicit Value Function

2002 ◽  
Author(s):  
K. Maddulapalli ◽  
S. Azarm ◽  
A. Boyars
Keyword(s):  
Product Design ◽  
Decision Maker ◽  
Trial Design ◽  
Value Function ◽  
Automated Method ◽  
Design Alternatives ◽  
Interactive Product ◽  
Electric Drill ◽  
Selection For ◽  
Design Selection

We present an automated method to aid a Decision Maker (DM) in selecting the ‘most preferred’ from a set of design alternatives. The method assumes that the DM’s preferences reflect an implicit value function that is quasi-concave. The method is iterative, using three approaches in sequence to eliminate lower-value alternatives at each trial design. The method is interactive, with the DM stating preferences in the form of attribute tradeoffs at each trial design. We present an approach for finding a new trial design at each iteration. We provide an example, the design selection for a cordless electric drill, to demonstrate the method.

scholarly journals Luiza: Analysis Framework for GLORIA

10.14311/1718 ◽  
2013 ◽  
Vol 53 (1) ◽  
Author(s):  
Aleksander Filip Żarnecki ◽  
Lech Wiktor Piotrowski ◽  
Lech Mankiewicz ◽  
Sebastian Małek
Keyword(s):  
Data Analysis ◽  
High Energy Physics ◽  
Linear Collider ◽  
International Linear Collider ◽  
High Energy ◽  
Distributed Data ◽  
Analysis Framework ◽  
Full Analysis ◽  
Distributed Data Analysis ◽  
Energy Physics

The Luiza analysis framework for GLORIA is based on the Marlin package, which was originally developed for data analysis in the new High Energy Physics (HEP) project, International Linear Collider (ILC). The HEP experiments have to deal with enormous amounts of data and distributed data analysis is therefore essential. The Marlin framework concept seems to be well suited for the needs of GLORIA. The idea (and large parts of the code) taken from Marlin is that every computing task is implemented as a processor (module) that analyzes the data stored in an internal data structure, and the additional output is also added to that collection. The advantage of this modular approach is that it keeps things as simple as possible. Each step of the full analysis chain, e.g. from raw images to light curves, can be processed step-by-step, and the output of each step is still self consistent and can be fed in to the next step without any manipulation.

The implementation of an automatic web-driven data analysis framework

2017 ◽  
Vol 2 (3/4) ◽  
pp. 150 ◽  
Author(s):  
Chun Hsiung Tseng ◽  
Yung Hui Chen ◽  
Yan Ru Jiang
Keyword(s):  
Data Analysis ◽  
Analysis Framework
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