scholarly journals $$\mathcal {ALC({\mathbf {F}}})$$ : A New Description Logic for Spatial Reasoning in Images

2015 ◽  
pp. 370-384 ◽  
Author(s):  
Céline Hudelot ◽  
Jamal Atif ◽  
Isabelle Bloch
Keyword(s):  
Description Logic ◽  
Spatial Reasoning

Know When to Hold Em, Know When to Fold Em: WMC and Spatial Reasoning

2014 ◽  
Author(s):  
Allison J. Jaeger ◽  
Andrew F. Jarosz ◽  
Jennifer Wiley
Keyword(s):  
Spatial Reasoning

Spatial reasoning and learning in virtual reality

2001 ◽  
Author(s):  
John R. Rani ◽  
Thomas E. Dawson ◽  
Julia H. Chariker
Keyword(s):  
Virtual Reality ◽  
Spatial Reasoning

Deciding Query Entailment for Fuzzy Description Logic Knowledge Bases：The f-SH Family

2012 ◽  
Vol 35 (4) ◽  
pp. 767-785
Author(s):  
Jing-Wei CHENG ◽  
Zong-Min MA ◽  
Li YAN ◽  
Fu ZHANG
Keyword(s):  
Description Logic ◽  
Fuzzy Description

Semantics of OWL-S process model based on temporal description logic

2013 ◽  
Vol 33 (1) ◽  
pp. 266-269 ◽  
Author(s):  
Ming LI ◽  
Shiyi LIU ◽  
Fuzhong NIAN
Keyword(s):  
Process Model ◽  
Description Logic ◽  
Model Based

Evidence Accumulation for Spatial Reasoning.

1984 ◽  
Author(s):  
T. Matsuyama ◽  
V. S. S. Hwang ◽  
L. S. Davis
Keyword(s):  
Spatial Reasoning ◽  
Evidence Accumulation

Syndication on the Web Using a Description Logic Approach

2008 ◽  
Author(s):  
Christian Halaschek-Wiener ◽  
Vladimir Kolovski
Keyword(s):  
Description Logic ◽  
Logic Approach ◽  
The Web

scholarly journals Modeling Imprecise and Bipolar Algebraic and Topological Relations using Morphological Dilations

2021 ◽  
Vol 5 (1) ◽  
pp. 1-20
Author(s):  
Isabelle Bloch
Keyword(s):  
Information Processing ◽  
Fuzzy Sets ◽  
Mathematical Morphology ◽  
Complete Lattice ◽  
Spatial Reasoning ◽  
Topological Relations ◽  
Preference Modeling ◽  
Logical Sense ◽  
Bipolar Fuzzy Sets ◽  
Core Features

Abstract In many domains of information processing, such as knowledge representation, preference modeling, argumentation, multi-criteria decision analysis, spatial reasoning, both vagueness, or imprecision, and bipolarity, encompassing positive and negative parts of information, are core features of the information to be modeled and processed. This led to the development of the concept of bipolar fuzzy sets, and of associated models and tools, such as fusion and aggregation, similarity and distances, mathematical morphology. Here we propose to extend these tools by defining algebraic and topological relations between bipolar fuzzy sets, including intersection, inclusion, adjacency and RCC relations widely used in mereotopology, based on bipolar connectives (in a logical sense) and on mathematical morphology operators. These definitions are shown to have the desired properties and to be consistent with existing definitions on sets and fuzzy sets, while providing an additional bipolar feature. The proposed relations can be used for instance for preference modeling or spatial reasoning. They apply more generally to any type of functions taking values in a poset or a complete lattice, such as L-fuzzy sets.

scholarly journals Arithmetic Word Problems Revisited: Cognitive Processes and Academic Performance in Secondary School

2021 ◽  
Vol 11 (4) ◽  
pp. 155
Author(s):  
Gonzalo Duque de Blas ◽  
Isabel Gómez-Veiga ◽  
Juan A. García-Madruga
Keyword(s):  
Academic Performance ◽  
Word Problems ◽  
Spatial Reasoning ◽  
Deductive Reasoning ◽  
Executive Processes ◽  
Mathematical Operation ◽  
Visual Spatial ◽  
And Mathematics ◽  
The One ◽  
Memory Resources

Solving arithmetic word problems is a complex task that requires individuals to activate their working memory resources, as well as the correct performance of the underlying executive processes involved in order to inhibit semantic biases or superficial responses caused by the problem’s statement. This paper describes a study carried out with 135 students of Secondary Obligatory Education, each of whom solved 5 verbal arithmetic problems: 2 consistent problems, whose mathematical operation (add/subtract) and the verbal statement of the problem coincide, and 3 inconsistent problems, whose required operation is the inverse of the one suggested by the verbal term(s). Measures of reading comprehension, visual–spatial reasoning and deductive reasoning were also obtained. The results show the relationship between arithmetic problems and cognitive measures, as well as the ability of these problems to predict academic performance. Regression analyses confirmed that arithmetic word problems were the only measure with significant power of association with academic achievement in both History/Geography (β = 0.25) and Mathematics (β = 0.23).

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