Timing Is Everything: Temporal Reasoning and Temporal Data Maintenance in Medicine

This article proposes a crisp-based approach for representing and reasoning about concepts evolving in time and of their properties in terms of qualitative relations (e.g., “before”) in addition to quantitative ones, time intervals and points. It is not only suitable to handle precise time intervals and points, but also imprecise ones. It extends the 4D-fluents approach with crisp components to represent handed data. It also extends the Allen's interval algebra. This extension allows reasoning about imprecise time intervals. Compared to related work, it is based on crisp set theory. These relations preserve many properties of the original algebra. Their definitions are adapted to allow relating a time interval and a time point, and two time points. All relations can be used for temporal reasoning by means of transitivity tables. Finally, it proposes a crisp ontology that based on the extended Allen's algebra instantiates the 4D-fluents-based representation.

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Certain and Uncertain Temporal Data Representation and Reasoning in OWL 2

International Journal on Semantic Web and Information Systems ◽

10.4018/ijswis.2021070104 ◽

2021 ◽

Vol 17 (3) ◽

pp. 51-72

Author(s):

Nassira Achich ◽

Fatma Ghorbel ◽

Fayçal Hamdi ◽

Elisabeth Métais ◽

Faiez Gargouri

Keyword(s):

Uncertain Data ◽

Temporal Reasoning ◽

Data Representation ◽

Time Interval ◽

Temporal Data ◽

Time Intervals ◽

Time Points ◽

Interval Algebra ◽

Uncertain Time ◽

Time Point

Temporal data given by Alzheimer's patients are mostly uncertain. Many approaches have been proposed to handle certain temporal data and lack uncertain ones. This paper proposes an approach to represent and reason about quantitative time intervals and points and qualitative relations between them. It is suitable to handle certain and uncertain temporal data. It includes three parts. (1) The authors extend the 4D-fluents approach with certain components to represent certain and uncertain temporal data. (2) They extend the Allen's interval algebra to reason about certain and uncertain time intervals. They adapt these relations to relate a time interval and a time point, and two time points. All relations can be used for temporal reasoning by means of transitivity tables. (3) They propose a certain ontology based on the extensions. A prototype is implemented and integrated into an ontology-based memory prosthesis for Alzheimer's patients to handle uncertain data inputs. The evaluation proves the usefulness of the approach as all the inferences are well established and the precision results are promising.

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Dual systems for all: Higher-order, role-based relational reasoning as a uniquely derived feature of human cognition

Behavioral and Brain Sciences ◽

10.1017/s0140525x19000451 ◽

2019 ◽

Vol 42 ◽

Author(s):

Daniel J. Povinelli ◽

Gabrielle C. Glorioso ◽

Shannon L. Kuznar ◽

Mateja Pavlic

Keyword(s):

Temporal Reasoning ◽

Higher Order ◽

Important Case ◽

Human Cognition ◽

Relational Reasoning ◽

Dual Systems ◽

First Order ◽

Reasoning System ◽

Role Based

Abstract Hoerl and McCormack demonstrate that although animals possess a sophisticated temporal updating system, there is no evidence that they also possess a temporal reasoning system. This important case study is directly related to the broader claim that although animals are manifestly capable of first-order (perceptually-based) relational reasoning, they lack the capacity for higher-order, role-based relational reasoning. We argue this distinction applies to all domains of cognition.

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Statistical Analysis of Spatio-Temporal Data Based on Poisson Conditional Autoregressive Model

Informatica ◽

10.15388/informatica.2015.39 ◽

2015 ◽

Vol 26 (1) ◽

pp. 67-87

Author(s):

Yuriy Kharin ◽

Maryna Zhurak

Keyword(s):

Statistical Analysis ◽

Autoregressive Model ◽

Temporal Data ◽

Conditional Autoregressive Model ◽

Conditional Autoregressive ◽

Spatio Temporal

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Clustering Mutual Outline for Multi Assessment Temporal Data and cancer Data

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v6i1.7179 ◽

2018 ◽

Vol 6 (1) ◽

pp. 71-79

Author(s):

Sathishkumar. K ◽

◽

V. Thiagarasu ◽

E. Balamurugan ◽

David Otto Arthur ◽

...

Keyword(s):

Temporal Data ◽

Cancer Data

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Giscience in the Mountain Geography

Tribhuvan University Journal ◽

10.3126/tuj.v27i1-2.26390 ◽

2010 ◽

Vol 27 (1-2) ◽

pp. 81-90

Author(s):

Krishna Poudel

Keyword(s):

Spatial Data ◽

Environmental Data ◽

Temporal Data ◽

Observation Systems ◽

Research Findings ◽

Temporal And Spatial ◽

Temporal And Spatial Characteristics ◽

Mountain Geography ◽

Different Sources

Mountains have distinct geography and are dynamic in nature compared to the plains. 'Verticality' and 'variation' are two fundamental specificities of the mountain geography. They possess distinct temporal and spatial characteristics in a unique socio-cultural setting. There is an ever increasing need for spatial and temporal data for planning and management activities; and Geo Information (GI) Science (including Geographic Information and Earth Observation Systems). This is being recognized more and more as a common platform for integrating spatial data with social, economic and environmental data and information from different sources. This paper investigates the applicability and challenges of GISscience in the context of mountain geography with ample evidences and observations from the mountain specific publications, empirical research findings and reports. The contextual explanation of mountain geography, mountain specific problems, scientific concerns about the mountain geography, advances in GIScience, the role of GIScience for sustainable development, challenges on application of GIScience in the contexts of mountains are the points of discussion. Finally, conclusion has been made with some specific action oriented recommendations.

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