Pictorial representations of fuzzy connectives, Part II: Cases of compensatory operators and self-dual operators

1989 ◽  
Vol 32 (1) ◽  
pp. 45-79 ◽  
Author(s):  
Masaharu Mizumoto
Author(s):  
C. T. Nightingale ◽  
S. E. Summers ◽  
T. P. Turnbull

The ease of operation of the scanning electron microscope has insured its wide application in medicine and industry. The micrographs are pictorial representations of surface topography obtained directly from the specimen. The need to replicate is eliminated. The great depth of field and the high resolving power provide far more information than light microscopy.


2019 ◽  
Vol 26 (1) ◽  
pp. 219-244
Author(s):  
Erica Torrens

Abstract This paper provides an overview of the state of Mexican genetics and biomedical knowledge during the second half of the twentieth century, as well as its impact on the visual representation of human groups and racial hierarchies, based on social studies of scientific imaging and visualization (SIV) and theoretical concepts and methods. It also addresses the genealogy and shifts of the concept of race and racialization of Mexican bodies, concluding with the novel visual culture that resulted from genetic knowledge merged with the racist phenomenon in the second half of the twentieth century in Mexico.


2015 ◽  
Vol 262 ◽  
pp. 78-101 ◽  
Author(s):  
Libor Běhounek ◽  
Ulrich Bodenhofer ◽  
Petr Cintula ◽  
Susanne Saminger-Platz ◽  
Peter Sarkoci

Author(s):  
Florian Jentsch

Conveying safety information to aircraft passengers is an important task for the designers of aircraft passenger safety information cards. Since the information must be understood by all passengers, regardless of native language or nationality, many designers use pictorial representations that are considered “culture free.” The current study investigated the comprehension of 13 pictograms from a sample of actual safety cards among participants from four language groups in Europe and the U.S. One-hundred-and-fifty students whose native languages were English (British and U.S.), French, or German, respectively, interpreted 13 pictograms. From their responses, three main conclusions can be drawn: 1. Conveying aviation safety information by pictorial means appears to be largely effective, as indicated by general comprehension levels above 85%. 2. While passengers may get the “essence” of a particular pictogram, it is often difficult for them to recognize specific details. 3. There are relatively small differences in the comprehension levels between participants from different language groups, pointing towards the “universality” of pictograms in conveying safety information. Future research needs to focus on identifying exactly which features of pictograms are most effective in conveying safety information, without introducing cultural or language biases.


IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 68403-68414 ◽  
Author(s):  
Gleb Beliakov ◽  
Gita Das ◽  
Huy Quan Vu ◽  
Tim Wilkin ◽  
Yong Xiang

Perception ◽  
10.1068/p2976 ◽  
2000 ◽  
Vol 29 (6) ◽  
pp. 635-648 ◽  
Author(s):  
James E Cutting

For more than 30 years James Gibson studied pictures and he studied motion, particularly the relationship between movement through an environment and its visual consequences. For the latter, he also struggled with how best to present his ideas to students and fellow researchers, and employed various representations and formats. This article explores the relationships between the concepts of the fidelity of pictures (an idea he first promoted and later eschewed) and evocativeness as applied to his images. Gibson ended his struggle with an image of a bird flying over a plane surrounded by a spherical representation of a vector field, an image high in evocativeness but less than completely faithful to optical flow.


2018 ◽  
Vol 7 (3.1) ◽  
pp. 13
Author(s):  
Raveendra K ◽  
R Vinoth Kanna

Automatic logo based document image retrieval process is an essential and mostly used method in the feature extraction applications. In this paper the architecture of Convolutional Neural Network (CNN) was elaborately explained with pictorial representations in order to understand the complex Convolutional Neural Networks process in a simplified way. The main objective of this paper is to effectively utilize the CNN in the process of automatic logo based document image retrieval methods.  


Sign in / Sign up

Export Citation Format

Share Document