The menstrual cycle has been a topic of interest in relation to behavior and cognition for many years, with historical beliefs associating it with cognitive impairment. However, recent research has challenged these be...The menstrual cycle has been a topic of interest in relation to behavior and cognition for many years, with historical beliefs associating it with cognitive impairment. However, recent research has challenged these beliefs and suggested potential positive effects of the menstrual cycle on cognitive performance. Despite these emerging findings, there is still a lack of consensus regarding the impact of the menstrual cycle on cognition, particularly in domains such as spatial reasoning, visual memory, and numerical memory. Hence, this study aimed to explore the relationship between the menstrual cycle and cognitive performance in these specific domains. Previous studies have reported mixed findings, with some suggesting no significant association and others indicating potential differences across the menstrual cycle. To contribute to this body of knowledge, we explored the research question of whether the menstrual cycles have a significant effect on cognition, particularly in the domains of spatial reasoning, visual and numerical memory in a regionally diverse sample of menstruating females. A total of 30 menstruating females from mixed geographical backgrounds participated in the study, and a repeated measures design was used to assess their cognitive performance in two phases of the menstrual cycle: follicular and luteal. The results of the study revealed that while spatial reasoning was not significantly related to the menstrual cycle (p = 0.256), both visual and numerical memory had significant positive associations (p < 0.001) with the luteal phase. However, since the effect sizes were very small, the importance of this relationship might be commonly overestimated. Future studies could thus entail designs with larger sample sizes, including neuro-biological measures of menstrual stages, and consequently inform competent interventions and support systems.展开更多
Human beings use hierarchies to simplify their conceptual models of reality and to perform reasoning more efficiently. Hierarchical structures are conceptually imposed on space and allow performance of complex tasks i...Human beings use hierarchies to simplify their conceptual models of reality and to perform reasoning more efficiently. Hierarchical structures are conceptually imposed on space and allow performance of complex tasks in very large contexts easily. Hierarchical spatial reasoning is an important method for solving spatial problems. This paper briefly discusses the definition and frame of hierarchical spatial reasoning and its application to way-finding of road networks.展开更多
Qualitative spatial reasoning on topological relations can extract hidden spatial knowledge from qualitatively described topological information,which is of significant importance for decisionmaking and query optimiza...Qualitative spatial reasoning on topological relations can extract hidden spatial knowledge from qualitatively described topological information,which is of significant importance for decisionmaking and query optimization in spatial analysis.Qualitative reasoning on spatial topological information based on semantic knowledge and reasoning rules is an efficient means of reducing both the known relations and the corresponding rules,which can result in enhanced reasoning performance.This paper proposes a qualitative reasoning method for spatial topological relations based on the semantic description of reasoning rules and constraint set.Combined with knowledge from the Semantic Web,the proposed method can easily extract potential spatial results consistent with both unique and non-unique rules.The Constraint-Satisfactionbased approach,describing constraint set with semantic expressions,is then used together with an improved path consistency algorithm to verify the consistency of the unique-rules-based and non-unique-rules-based reasoning results.The verification can eliminate certain reasoning results to ensure the reliability of the final results.Thus,the task of qualitative spatial reasoning on topological relations is completed.展开更多
Direction relation is an important spatial relation. Descriptions and representations for direction relations have different levels of detail because of the varying dimensions of spatial objects and different scales o...Direction relation is an important spatial relation. Descriptions and representations for direction relations have different levels of detail because of the varying dimensions of spatial objects and different scales of the embedding spaces. Based on a direction- relation matrix, the hierarchical frame of spatial direction relations which partitions direction relations orderly and thoroughly is built. Interior direction relations are used to perfect the representation of direction relations and the binary-encoding idea is creatively applied to construct an interior detailed matrix describing multiple interior direction relations by a uniform matrix. The model integrates topological information into the description model for direction relations, which will lay the foundations of spatial compositive reasoning.展开更多
文摘The menstrual cycle has been a topic of interest in relation to behavior and cognition for many years, with historical beliefs associating it with cognitive impairment. However, recent research has challenged these beliefs and suggested potential positive effects of the menstrual cycle on cognitive performance. Despite these emerging findings, there is still a lack of consensus regarding the impact of the menstrual cycle on cognition, particularly in domains such as spatial reasoning, visual memory, and numerical memory. Hence, this study aimed to explore the relationship between the menstrual cycle and cognitive performance in these specific domains. Previous studies have reported mixed findings, with some suggesting no significant association and others indicating potential differences across the menstrual cycle. To contribute to this body of knowledge, we explored the research question of whether the menstrual cycles have a significant effect on cognition, particularly in the domains of spatial reasoning, visual and numerical memory in a regionally diverse sample of menstruating females. A total of 30 menstruating females from mixed geographical backgrounds participated in the study, and a repeated measures design was used to assess their cognitive performance in two phases of the menstrual cycle: follicular and luteal. The results of the study revealed that while spatial reasoning was not significantly related to the menstrual cycle (p = 0.256), both visual and numerical memory had significant positive associations (p < 0.001) with the luteal phase. However, since the effect sizes were very small, the importance of this relationship might be commonly overestimated. Future studies could thus entail designs with larger sample sizes, including neuro-biological measures of menstrual stages, and consequently inform competent interventions and support systems.
基金Supported by the National 863 Program of China (No.2006AA12 z202)
文摘Human beings use hierarchies to simplify their conceptual models of reality and to perform reasoning more efficiently. Hierarchical structures are conceptually imposed on space and allow performance of complex tasks in very large contexts easily. Hierarchical spatial reasoning is an important method for solving spatial problems. This paper briefly discusses the definition and frame of hierarchical spatial reasoning and its application to way-finding of road networks.
基金This work is funded by the National Natural Science Foundation of China[grant number 41271399]the China Special Fund for Surveying,Mapping and Geo-information Research in the Public Interest[grant number 201512015]the National Key Research Program of China[grant number 2016YFB0501400].
文摘Qualitative spatial reasoning on topological relations can extract hidden spatial knowledge from qualitatively described topological information,which is of significant importance for decisionmaking and query optimization in spatial analysis.Qualitative reasoning on spatial topological information based on semantic knowledge and reasoning rules is an efficient means of reducing both the known relations and the corresponding rules,which can result in enhanced reasoning performance.This paper proposes a qualitative reasoning method for spatial topological relations based on the semantic description of reasoning rules and constraint set.Combined with knowledge from the Semantic Web,the proposed method can easily extract potential spatial results consistent with both unique and non-unique rules.The Constraint-Satisfactionbased approach,describing constraint set with semantic expressions,is then used together with an improved path consistency algorithm to verify the consistency of the unique-rules-based and non-unique-rules-based reasoning results.The verification can eliminate certain reasoning results to ensure the reliability of the final results.Thus,the task of qualitative spatial reasoning on topological relations is completed.
文摘Direction relation is an important spatial relation. Descriptions and representations for direction relations have different levels of detail because of the varying dimensions of spatial objects and different scales of the embedding spaces. Based on a direction- relation matrix, the hierarchical frame of spatial direction relations which partitions direction relations orderly and thoroughly is built. Interior direction relations are used to perfect the representation of direction relations and the binary-encoding idea is creatively applied to construct an interior detailed matrix describing multiple interior direction relations by a uniform matrix. The model integrates topological information into the description model for direction relations, which will lay the foundations of spatial compositive reasoning.
