The sparse nature of location finding in the spatial domain makes it possible to exploit the Compressive Sensing (CS) theory for wireless location.CS-based location algorithm can largely reduce the number of online me...The sparse nature of location finding in the spatial domain makes it possible to exploit the Compressive Sensing (CS) theory for wireless location.CS-based location algorithm can largely reduce the number of online measurements while achieving a high level of localization accuracy,which makes the CS-based solution very attractive for indoor positioning.However,CS theory offers exact deterministic recovery of the sparse or compressible signals under two basic restriction conditions of sparsity and incoherence.In order to achieve a good recovery performance of sparse signals,CS-based solution needs to construct an efficient CS model.The model must satisfy the practical application requirements as well as following theoretical restrictions.In this paper,we propose two novel CS-based location solutions based on two different points of view:the CS-based algorithm with raising-dimension pre-processing and the CS-based algorithm with Minor Component Analysis (MCA).Analytical studies and simulations indicate that the proposed novel schemes achieve much higher localization accuracy.展开更多
The visual and aesthetic aspects of any object are defined by its color, texture, line, and form as well as compositional reference elements such as scale and spatial location in the three-dimensional context. Differe...The visual and aesthetic aspects of any object are defined by its color, texture, line, and form as well as compositional reference elements such as scale and spatial location in the three-dimensional context. Different methodologies have been developed to conduct visual assessments, based on analyses of the physical, aesthetic, and psychological attributes of the landscape. In this study, relationships between tourism buildings and the environment were analyzed across the perceived landscape and main shopping streets in terms of their color, texture, line and form, scale, and spatial location. Photographic-based questionnaires were administered in Kemer （near Antalya, Turkey） and Knokke （near Brugge, Belgium）. In each location, 30 photographs taken of the coast and principal shopping streets were shown to 100 respondents of different ages, educational backgrounds, and nationalities. Two questions were then asked regarding the visual relationships in the photographs. Six questions regarding socioeconomic characteristics of the respondents were also asked. In both locations, the respondents preferred natural landscapes with few structures, and tourist resorts characterized by small, low-rise, and traditional buildings. The results of this study may provide suggestions for building and landscape architects about how to successfully integrate tourism buildings into the landscape展开更多
基金supported by the National Natural Science Foundation of China under Grant No.61001119the Fund for Creative Research Groups of China under Grant No.61121001
文摘The sparse nature of location finding in the spatial domain makes it possible to exploit the Compressive Sensing (CS) theory for wireless location.CS-based location algorithm can largely reduce the number of online measurements while achieving a high level of localization accuracy,which makes the CS-based solution very attractive for indoor positioning.However,CS theory offers exact deterministic recovery of the sparse or compressible signals under two basic restriction conditions of sparsity and incoherence.In order to achieve a good recovery performance of sparse signals,CS-based solution needs to construct an efficient CS model.The model must satisfy the practical application requirements as well as following theoretical restrictions.In this paper,we propose two novel CS-based location solutions based on two different points of view:the CS-based algorithm with raising-dimension pre-processing and the CS-based algorithm with Minor Component Analysis (MCA).Analytical studies and simulations indicate that the proposed novel schemes achieve much higher localization accuracy.
文摘The visual and aesthetic aspects of any object are defined by its color, texture, line, and form as well as compositional reference elements such as scale and spatial location in the three-dimensional context. Different methodologies have been developed to conduct visual assessments, based on analyses of the physical, aesthetic, and psychological attributes of the landscape. In this study, relationships between tourism buildings and the environment were analyzed across the perceived landscape and main shopping streets in terms of their color, texture, line and form, scale, and spatial location. Photographic-based questionnaires were administered in Kemer （near Antalya, Turkey） and Knokke （near Brugge, Belgium）. In each location, 30 photographs taken of the coast and principal shopping streets were shown to 100 respondents of different ages, educational backgrounds, and nationalities. Two questions were then asked regarding the visual relationships in the photographs. Six questions regarding socioeconomic characteristics of the respondents were also asked. In both locations, the respondents preferred natural landscapes with few structures, and tourist resorts characterized by small, low-rise, and traditional buildings. The results of this study may provide suggestions for building and landscape architects about how to successfully integrate tourism buildings into the landscape
