It is understood that the sparse signal recovery with a standard compressive sensing（CS） strategy requires the measurement matrix known as a priori. The measurement matrix is, however, often perturbed in a practical...It is understood that the sparse signal recovery with a standard compressive sensing（CS） strategy requires the measurement matrix known as a priori. The measurement matrix is, however, often perturbed in a practical application.In order to handle such a case, an optimization problem by exploiting the sparsity characteristics of both the perturbations and signals is formulated. An algorithm named as the sparse perturbation signal recovery algorithm（SPSRA） is then proposed to solve the formulated optimization problem. The analytical results show that our SPSRA can simultaneously recover the signal and perturbation vectors by an alternative iteration way, while the convergence of the SPSRA is also analytically given and guaranteed. Moreover, the support patterns of the sparse signal and structured perturbation shown are the same and can be exploited to improve the estimation accuracy and reduce the computation complexity of the algorithm. The numerical simulation results verify the effectiveness of analytical ones.展开更多
Place attachment is an important motivation for people to spend more time outdoors and to protect landscapes.This study explores visitors' intention to conserve natural landscapes based on the relationship with th...Place attachment is an important motivation for people to spend more time outdoors and to protect landscapes.This study explores visitors' intention to conserve natural landscapes based on the relationship with their place attachment to National Park landscape. Structural equation modelling(SEM) was used to determine the relationship between landscape conservation and place attachment. A survey with a structured questionnaire was administered to visitors to the seven designated hiking courses of Harz National Park in Germany. The path coefficient of 0.77 revealed that place dependence positively and significantly affected place attachment, whereas place identity did not. Place attachment had a significant effect on both affective appraisals and visiting satisfaction. Higher place attachment led to higher emotional reaction to landscapes on site and higher satisfaction of visiting the park. Among the variables, visiting satisfaction, but not affective appraisals, played a statistically significant mediating role between place attachment and conservation intention. With a path coefficient of 0.86, conservation intention was highly affected by visiting satisfaction. These results suggest that the managers of National Parks should focus on increasing visiting satisfaction based on how visitors are emotionally bonded with their visiting places, in order to enhance the intentions to conserve the landscape of the visitors to National Parks.展开更多
An efficient and reliable automated model that can map physical Soil and Water Conservation（SWC） structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ...An efficient and reliable automated model that can map physical Soil and Water Conservation（SWC） structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and Arc GIS？ERDAS IMAGINE？and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures：（1） a high-pass spatial filter algorithm was applied to detect linear features,（2） morphological processing was used to remove unwanted linear features,（3） the raster format was vectorized,（4） the vectorized linear features were split per hectare（ha） and each line was then classified according to its compass directionand（5） the sum of all vector lengths per class of direction per ha was calculated. Finallythe direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Thereforethe model is useful for predicting and mapping physical SWC structures areas across diverse areas.展开更多
Compressed sensing （CS） enables people to acquire the compressed measurements directly and recover sparse or compressible signals faithfully even when the sampiing rate is much lower than the Nyquist rate. However, ...Compressed sensing （CS） enables people to acquire the compressed measurements directly and recover sparse or compressible signals faithfully even when the sampiing rate is much lower than the Nyquist rate. However, the pure random sensing matrices usually require huge memory for storage and high computational cost for signal reconstruction. Many structured sensing matrices have been proposed recently to simplify the sensing scheme and the hardware implementation in practice. Based on the restricted isometry property and coherence, couples of existing structured sensing matrices are reviewed in this paper, which have special structures, high recovery performance, and many advantages such as the simple construction, fast calculation and easy hardware implementation. The number of measurements and the universality of different structure matrices are compared.展开更多
In this work, ZnSn（OH）6with a cubic structure is successfully synthesized by one-step hydrothermal method without any catalyst. The response and recovery characteristics of gas sensing were investigated against vari...In this work, ZnSn（OH）6with a cubic structure is successfully synthesized by one-step hydrothermal method without any catalyst. The response and recovery characteristics of gas sensing were investigated against various gases via quartz crystal microbalance（QCM） at room temperature. The sensor exhibited high sensitivity and good selectivity toward CO gas. Moreover, a linear dependence of log^（àDelta F）about CO concentration was obtained. It is demonstrated that the QCM sensor coated cubic ZnSn（OH）6could be a suitable candidate for detecting CO.展开更多
Flower-like SnO2 nanopowders prepared by a hydrothermal method were surface modified with palla- dium via impregnation. The crystal structure, morphology, and surface chemistry states of the samples were characterized...Flower-like SnO2 nanopowders prepared by a hydrothermal method were surface modified with palla- dium via impregnation. The crystal structure, morphology, and surface chemistry states of the samples were characterized by means of X-ray diffraction （XRD）, scanning electron microscopy （SEM）, and X-ray photoelectron spectroscopy （XPS）, respectively. The gas sensing performances were also investigated. For a hydrothermal temperature of 220 ℃, flower-like SnO2 nanoparticles consist of nanorods with diameters of 40 nm and lengths of 100 nm. The XPS and XRD results reveal that palladium exists in the Pd0 chemical state but the crystal is too small to be detected. The 0.3 wt% Pd modified SnO2 sensor shows better sensi- tivity, up to 21, for 70 μL/L ethanol gas at an optimal working temperature of 250 ℃. The quick response time （3 s） and fast recovery time （-20 s） are the main characteristics of this sensor.展开更多
基金supported by the National Natural Science Foundation of China(61171127)
文摘It is understood that the sparse signal recovery with a standard compressive sensing（CS） strategy requires the measurement matrix known as a priori. The measurement matrix is, however, often perturbed in a practical application.In order to handle such a case, an optimization problem by exploiting the sparsity characteristics of both the perturbations and signals is formulated. An algorithm named as the sparse perturbation signal recovery algorithm（SPSRA） is then proposed to solve the formulated optimization problem. The analytical results show that our SPSRA can simultaneously recover the signal and perturbation vectors by an alternative iteration way, while the convergence of the SPSRA is also analytically given and guaranteed. Moreover, the support patterns of the sparse signal and structured perturbation shown are the same and can be exploited to improve the estimation accuracy and reduce the computation complexity of the algorithm. The numerical simulation results verify the effectiveness of analytical ones.
基金supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2015-013-20150012)
文摘Place attachment is an important motivation for people to spend more time outdoors and to protect landscapes.This study explores visitors' intention to conserve natural landscapes based on the relationship with their place attachment to National Park landscape. Structural equation modelling(SEM) was used to determine the relationship between landscape conservation and place attachment. A survey with a structured questionnaire was administered to visitors to the seven designated hiking courses of Harz National Park in Germany. The path coefficient of 0.77 revealed that place dependence positively and significantly affected place attachment, whereas place identity did not. Place attachment had a significant effect on both affective appraisals and visiting satisfaction. Higher place attachment led to higher emotional reaction to landscapes on site and higher satisfaction of visiting the park. Among the variables, visiting satisfaction, but not affective appraisals, played a statistically significant mediating role between place attachment and conservation intention. With a path coefficient of 0.86, conservation intention was highly affected by visiting satisfaction. These results suggest that the managers of National Parks should focus on increasing visiting satisfaction based on how visitors are emotionally bonded with their visiting places, in order to enhance the intentions to conserve the landscape of the visitors to National Parks.
基金covered by the Swiss National Centre of Competence in Research North-South (NCCR North-South) program
文摘An efficient and reliable automated model that can map physical Soil and Water Conservation（SWC） structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and Arc GIS？ERDAS IMAGINE？and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures：（1） a high-pass spatial filter algorithm was applied to detect linear features,（2） morphological processing was used to remove unwanted linear features,（3） the raster format was vectorized,（4） the vectorized linear features were split per hectare（ha） and each line was then classified according to its compass directionand（5） the sum of all vector lengths per class of direction per ha was calculated. Finallythe direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Thereforethe model is useful for predicting and mapping physical SWC structures areas across diverse areas.
文摘Compressed sensing （CS） enables people to acquire the compressed measurements directly and recover sparse or compressible signals faithfully even when the sampiing rate is much lower than the Nyquist rate. However, the pure random sensing matrices usually require huge memory for storage and high computational cost for signal reconstruction. Many structured sensing matrices have been proposed recently to simplify the sensing scheme and the hardware implementation in practice. Based on the restricted isometry property and coherence, couples of existing structured sensing matrices are reviewed in this paper, which have special structures, high recovery performance, and many advantages such as the simple construction, fast calculation and easy hardware implementation. The number of measurements and the universality of different structure matrices are compared.
基金financially supported by the Key Project of Sichuan provincial Education office(No.13ZA0183)Applied Basic Research Programs of Sichuan Provincial Science and Technology Office(No.2014JY0059)+1 种基金Foundation of Youth Science and Technology Innovation Team of Sichuan Province(No.2015TD0007)Program for New Century Excellent Talents in University of Ministof Education of China(No.NCET-13-0983)
文摘In this work, ZnSn（OH）6with a cubic structure is successfully synthesized by one-step hydrothermal method without any catalyst. The response and recovery characteristics of gas sensing were investigated against various gases via quartz crystal microbalance（QCM） at room temperature. The sensor exhibited high sensitivity and good selectivity toward CO gas. Moreover, a linear dependence of log^（àDelta F）about CO concentration was obtained. It is demonstrated that the QCM sensor coated cubic ZnSn（OH）6could be a suitable candidate for detecting CO.
基金the project sponsored by the NaturalScience Fund of Shandong Province(No.ZR2012EML07)
文摘Flower-like SnO2 nanopowders prepared by a hydrothermal method were surface modified with palla- dium via impregnation. The crystal structure, morphology, and surface chemistry states of the samples were characterized by means of X-ray diffraction （XRD）, scanning electron microscopy （SEM）, and X-ray photoelectron spectroscopy （XPS）, respectively. The gas sensing performances were also investigated. For a hydrothermal temperature of 220 ℃, flower-like SnO2 nanoparticles consist of nanorods with diameters of 40 nm and lengths of 100 nm. The XPS and XRD results reveal that palladium exists in the Pd0 chemical state but the crystal is too small to be detected. The 0.3 wt% Pd modified SnO2 sensor shows better sensi- tivity, up to 21, for 70 μL/L ethanol gas at an optimal working temperature of 250 ℃. The quick response time （3 s） and fast recovery time （-20 s） are the main characteristics of this sensor.
