scholarly journals Information Projection: Model and Applications

2011 ◽  
Vol 79 (3) ◽  
pp. 961-985 ◽  
Author(s):  
Kristóf Madarász
Keyword(s):  
Projection Model ◽  
Information Projection

Cognitive Components of Ingroup Projection

2014 ◽  
Vol 45 (1) ◽  
pp. 15-30 ◽  
Author(s):  
Maya Machunsky ◽  
Thorsten Meiser
Keyword(s):  
Mental Representation ◽  
Cognitive Representation ◽  
Social Categories ◽  
Projection Model ◽  
Minimal Group ◽  
Model Experiments ◽  
Superordinate Category ◽  
Cognitive Components ◽  
Per Se

This research investigated whether relative ingroup prototypicality (i.e., the tendency to perceive one’s own ingroup as more prototypical of a superordinate category than the outgroup) can result from a prototype-based versus exemplar-based mental representation of social categories, rather than from ingroup membership per se as previously suggested by the ingroup projection model. Experiments 1 and 2 showed that a prototype-based group was perceived as more prototypical of a superordinate category than an exemplar-based group supporting the hypothesis that an intergroup context is not necessary for biased prototypicality judgments. Experiment 3 introduced an intergroup context in a minimal-group-like paradigm. The findings demonstrated that both the kind of cognitive representation and motivational processes contribute to biased prototypicality judgments in intergroup settings.

A dual projection model of partisan attitude perceptions

2014 ◽  
Author(s):  
Jessica Keating ◽  
Leaf Van Boven ◽  
Charles Judd
Keyword(s):  
Projection Model ◽  
Dual Projection

Assessing the Calculation of Exchange Coupling Constants and Spin Crossover Gaps Using the Approximate Projection Model to Improve Density Function Calculations

2019 ◽  
Author(s):  
Xianghai Sheng ◽  
Lee Thompson ◽  
Hrant Hratchian
Keyword(s):  
Density Functional Theory ◽  
Exchange Coupling ◽  
Density Functional ◽  
Spin Crossover ◽  
Coupling Constants ◽  
Spin Projection ◽  
Coupling Constant ◽  
Projection Model ◽  
Functional Theory

This work evaluates the quality of exchange coupling constant and spin crossover gap calculations using density functional theory corrected by the Approximate Projection model. Results show that improvements using the Approximate Projection model range from modest to significant. This study demonstrates that, at least for the class of systems examined here, spin-projection generally improves the quality of density functional theory calculations of J-coupling constants and spin crossover gaps. Furthermore, it is shown that spin-projection can be important for both geometry optimization and energy evaluations. The Approximate Project model provides an affordable and practical approach for effectively correcting spin-contamination errors in molecular exchange coupling constant and spin crossover gap calculations.

scholarly journals Self-Localization of Mobile Robots Using a Single Catadioptric Camera with Line Feature Extraction

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4719
Author(s):  
Huei-Yung Lin ◽  
Yuan-Chi Chung ◽  
Ming-Liang Wang
Keyword(s):  
Mobile Robots ◽  
Ground Plane ◽  
Feature Correspondence ◽  
Projection Model ◽  
3D Space ◽  
Base Points ◽  
Real Scene ◽  
Correspondence Matching ◽  
Mobile Robot Localization ◽  
Catadioptric Camera

This paper presents a novel self-localization technique for mobile robots using a central catadioptric camera. A unified sphere model for the image projection is derived by the catadioptric camera calibration. The geometric property of the camera projection model is utilized to obtain the intersections of the vertical lines and ground plane in the scene. Different from the conventional stereo vision techniques, the feature points are projected onto a known planar surface, and the plane equation is used for depth computation. The 3D coordinates of the base points on the ground are calculated using the consecutive image frames. The derivation of motion trajectory is then carried out based on the computation of rotation and translation between the robot positions. We develop an algorithm for feature correspondence matching based on the invariability of the structure in the 3D space. The experimental results obtained using the real scene images have demonstrated the feasibility of the proposed method for mobile robot localization applications.

scholarly journals Computational Forecasting Methodology for Acute Respiratory Infectious Disease Dynamics

2020 ◽  
Vol 17 (12) ◽  
pp. 4540
Author(s):  
Daniel Alejandro Gónzalez-Bandala ◽  
Juan Carlos Cuevas-Tello ◽  
Daniel E. Noyola ◽  
Andreu Comas-García ◽  
Christian A García-Sepúlveda
Keyword(s):  
Infectious Disease ◽  
Percentage Error ◽  
Projection Model ◽  
Channel Calculation ◽  
Health Measures ◽  
Disease Behavior ◽  
Key Terms ◽  
Google Search ◽  
Infectious Disease Dynamics ◽  
Absolute Percent Error

The study of infectious disease behavior has been a scientific concern for many years as early identification of outbreaks provides great advantages including timely implementation of public health measures to limit the spread of an epidemic. We propose a methodology that merges the predictions of (i) a computational model with machine learning, (ii) a projection model, and (iii) a proposed smoothed endemic channel calculation. The predictions are made on weekly acute respiratory infection (ARI) data obtained from epidemiological reports in Mexico, along with the usage of key terms in the Google search engine. The results obtained with this methodology were compared with state-of-the-art techniques resulting in reduced root mean squared percentage error (RMPSE) and maximum absolute percent error (MAPE) metrics, achieving a MAPE of 21.7%. This methodology could be extended to detect and raise alerts on possible outbreaks on ARI as well as for other seasonal infectious diseases.

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