Cath Sleeman Discusses Explanatory and Exploratory Data Visualization, and Design Selection for the "Making Sense of Skills" Project

2021 ◽  
Keyword(s):  
Data Visualization ◽  
Making Sense ◽  
Exploratory Data ◽  
Selection For ◽  
Design Selection

Multimodal Coreference Resolution for Exploratory Data Visualization Dialogue: Context-Based Annotation and Gesture Identification

2017 ◽  
Author(s):  
Abhinav Kumar ◽  
Jillian Aurisano ◽  
Barbara Di Eugenio ◽  
Andrew Johnson ◽  
Abeer Alsaiari ◽  
...  
Keyword(s):  
Data Visualization ◽  
Coreference Resolution ◽  
Exploratory Data

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.

Design selection for strong orthogonal arrays

2019 ◽  
Vol 47 (2) ◽  
pp. 302-314
Author(s):  
Chenlu Shi ◽  
Boxin Tang
Keyword(s):  
Orthogonal Arrays ◽  
Selection For ◽  
Design Selection

Interactive Product Design Selection With an Implicit Value Function

2005 ◽  
Vol 127 (3) ◽  
pp. 367-377 ◽  
Author(s):  
K. Maddulapalli ◽  
S. Azarm ◽  
A. Boyars
Keyword(s):  
Trial Design ◽  
Value Function ◽  
Probability Distributions ◽  
Specific Design ◽  
Design Alternatives ◽  
Interactive Product ◽  
Electric Drill ◽  
Selection For ◽  
Design Selection ◽  
The Value Function

We present a new method to aid a decision maker (DM) in selecting the “most preferred” from a set of design alternatives. The method is deterministic and assumes that the DM’s preferences reflect an implicit value function that is quasi-concave. The method is interactive, with the DM stating preferences in the form of attribute tradeoffs at a series of trial designs, each a specific design under consideration. The method is iterative and uses the gradient of the value function obtained from the preferences of the DM to eliminate lower value designs 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. We provide results showing that (within the limit of our experimentation) our method needs only a few iterations to find the most preferred design alternative. Finally we extend our deterministic selection method to account for uncertainty in the attributes when the probability distributions governing the uncertainty are known.

MAKING SENSE OF THE WAYS WE MAKE SENSE OF THE PAST: THE PERIODO PROJECT

2016 ◽  
Vol 59 (2) ◽  
pp. 42-55 ◽  
Author(s):  
ADAM RABINOWITZ ◽  
RYAN SHAW ◽  
SARAH BUCHANAN ◽  
PATRICK GOLDEN ◽  
ERIC KANSA
Keyword(s):  
Data Visualization ◽  
Data Model ◽  
Linked Data ◽  
Digital Data ◽  
The Past ◽  
Making Sense ◽  
The Future ◽  
History Of ◽  
Future Direction

Abstract The PeriodO project seeks to fill a gap in the landscape of digital antiquity through the creation of a Linked Data gazetteer of period definitions that transparently record the spatial and temporal boundaries assigned to a given period by an authoritative source. Our presentation of the PeriodO gazetteer is prefaced by a history of the role of periodization in the study of the past, and an analysis of the difficulties created by the use of periods for both digital data visualization and integration. This is followed by an overview of the PeriodO data model, a description of the platform's architecture, and a discussion of the future direction of the project.

scholarly journals Pengelolaan Sarana Pembelajaran di Sekolah Dasar

2019 ◽  
Author(s):  
NOVA ATRIANI ◽  
hanif al kadri
Keyword(s):  
Learning Process ◽  
Teaching And Learning ◽  
Single Case ◽  
Facilities Planning ◽  
Key Informant ◽  
Data Validity ◽  
Analysis Design ◽  
Selection For ◽  
Design Selection ◽  
Main Components

The purpose of this article is research are to describe the characteristics of: 1) the learning facilities planning; 2) the utilities of learning facilities; and 3) the maintenance of learning facilities at Primary School to facilitate the teaching and learning process. The data collecting method was done using in-depth interviewing, observation, and document techniques. The data analysis was done using single case analysis design. The analysis design selection for qualitative research conveys three main components, namely data reduction, data display, and verification. The data validity is done using triangulation, key informant review and member-check techniques.The learning facilities controlling strategies were done by teacher that specifically assigned to manage the schools learning facilities; and 3) the learning facilities maintenance of multimedia laboratory was done cooperatively with the computer suplier by special contract system. It is done with the effectivity consideration so that the teacher may focus their attention in teaching and learning process and the facilities were ready to be used at any time.

Sign in / Sign up

Export Citation Format

Share Document