A wireless sensor network (WSN) is spatially distributing independent sensors to monitor physical and environmental characteristics such as temperature, sound, pressure and also provides different applications such as...A wireless sensor network (WSN) is spatially distributing independent sensors to monitor physical and environmental characteristics such as temperature, sound, pressure and also provides different applications such as battlefield inspection and biological detection. The Constrained Motion and Sensor (CMS) Model represents the features and explain k-step reach ability testing to describe the states. The description and calculation based on CMS model does not solve the problem in mobile robots. The ADD framework based on monitoring radio measurements creates a threshold. But the methods are not effective in dynamic coverage of complex environment. In this paper, a Localized Coverage based on Shape and Area Detection (LCSAD) Framework is developed to increase the dynamic coverage using mobile robots. To facilitate the measurement in mobile robots, two algorithms are designed to identify the coverage area, (i.e.,) the area of a coverage hole or not. The two algorithms are Localized Geometric Voronoi Hexagon (LGVH) and Acquaintance Area Hexagon (AAH). LGVH senses all the shapes and it is simple to show all the boundary area nodes. AAH based algorithm simply takes directional information by locating the area of local and global convex points of coverage area. Both these algorithms are applied to WSN of random topologies. The simulation result shows that the proposed LCSAD framework attains minimal energy utilization, lesser waiting time, and also achieves higher scalability, throughput, delivery rate and 8% maximal coverage connectivity in sensor network compared to state-of-art works.展开更多
Joint probability function of local surfaces-particle and phase velocities is derived for a stationary Gaussianwave field with narrow-band spectrum. From the function a model of whitecap coverage is further derived by...Joint probability function of local surfaces-particle and phase velocities is derived for a stationary Gaussianwave field with narrow-band spectrum. From the function a model of whitecap coverage is further derived by using thekinematic condition (including the effect of drift current) for wave breaking. The drift current velocity in the model isthen replaced by the friction velocity through an existing empirical formula. A coefficient in the model for relating temporal and spatial scales of wave breaking is determined by using an existing empirical formula of oceanic whitecap coverage and the well-known Pierson-Moskowitz spectrum. The main features of the model agree well with our generalknowledge and observational evidence on wave breaking in deep waters.展开更多
Remote sensing techniques have the potential to provide information on agricultural crops quantitatively , instantaneously and above all nondestructively over large areas . Crop simulation models describe the relation...Remote sensing techniques have the potential to provide information on agricultural crops quantitatively , instantaneously and above all nondestructively over large areas . Crop simulation models describe the relationship between physiological processes in plants and environmental growing conditions. The integration between remote sensing data and crop growth simulation model is an important trend for yield estimation and prediction, since remote sensing can provide information on the actual status of the agricultural crop. In this study, a new model(Rice-SRS) was developed based mainly on ORYZA1 model and modified to accept remote sensing data as input from different sources. The model can accept three kinds of NDVI data: NOAA AVHRR(LAC)-NDVI,NOAA AVHRR(GAC)-NDVI and radiometric measurements-NDVI. The integration between NOAA AVHRR (LAC) data and simulation model as applied to Rice-SRS resulted in accurate estimates for rice yield in the Shaoxing area, reduced the estimating error to 1.027%,0.794% and (-0.787%) for early, single, and late season respectively. Utilizing NDVI data derived from NOAA AVHRR (GAC) as input in Rice-SRS can yield good estimation for rice yield with the average error (-7.43%). Testing the new model for radiometric measurements showed that the average estimation error for 10 varieties under early rice conditions was less than 1%.展开更多
Silver-copper electrocatalysts have demonstrated effectively catalytic performance in electroreduction CO_(2) toward CH_(4),yet a revealing insight into the reaction pathway and mechanism has remained elusive.Herein,w...Silver-copper electrocatalysts have demonstrated effectively catalytic performance in electroreduction CO_(2) toward CH_(4),yet a revealing insight into the reaction pathway and mechanism has remained elusive.Herein,we construct chemically bonded Ag-Cu_(2)O boundaries,in which the complete reduction of Cu_(2)O to Cu has been strongly impeded owing to the presence of surface Ag shell.The interfacial confinement effect helps to maintain Cu^(+)sites at the Ag-Cu_(2)O boundaries.Using in situ/operando spectroscopy and theoretical simulations,it is revealed that CO_(2) is enriched at the Ag-Cu_(2)O boundaries due to the enhanced physisorption and chemisorption to CO_(2),activating CO_(2) to form the stable intermediate^(*)CO.The boundaries between Ag shell and the Cu_(2)O mediate local^(*)CO coverage and promote^(*)CHO intermediate formation,consequently facilitating CO_(2)-to-CH_(4) conversion.This work not only reveals the structure-activity relationships but also offers insights into the reaction mechanism on Ag-Cu catalysts for efficient electrocatalytic CO_(2) reduction.展开更多
文摘A wireless sensor network (WSN) is spatially distributing independent sensors to monitor physical and environmental characteristics such as temperature, sound, pressure and also provides different applications such as battlefield inspection and biological detection. The Constrained Motion and Sensor (CMS) Model represents the features and explain k-step reach ability testing to describe the states. The description and calculation based on CMS model does not solve the problem in mobile robots. The ADD framework based on monitoring radio measurements creates a threshold. But the methods are not effective in dynamic coverage of complex environment. In this paper, a Localized Coverage based on Shape and Area Detection (LCSAD) Framework is developed to increase the dynamic coverage using mobile robots. To facilitate the measurement in mobile robots, two algorithms are designed to identify the coverage area, (i.e.,) the area of a coverage hole or not. The two algorithms are Localized Geometric Voronoi Hexagon (LGVH) and Acquaintance Area Hexagon (AAH). LGVH senses all the shapes and it is simple to show all the boundary area nodes. AAH based algorithm simply takes directional information by locating the area of local and global convex points of coverage area. Both these algorithms are applied to WSN of random topologies. The simulation result shows that the proposed LCSAD framework attains minimal energy utilization, lesser waiting time, and also achieves higher scalability, throughput, delivery rate and 8% maximal coverage connectivity in sensor network compared to state-of-art works.
文摘Joint probability function of local surfaces-particle and phase velocities is derived for a stationary Gaussianwave field with narrow-band spectrum. From the function a model of whitecap coverage is further derived by using thekinematic condition (including the effect of drift current) for wave breaking. The drift current velocity in the model isthen replaced by the friction velocity through an existing empirical formula. A coefficient in the model for relating temporal and spatial scales of wave breaking is determined by using an existing empirical formula of oceanic whitecap coverage and the well-known Pierson-Moskowitz spectrum. The main features of the model agree well with our generalknowledge and observational evidence on wave breaking in deep waters.
文摘Remote sensing techniques have the potential to provide information on agricultural crops quantitatively , instantaneously and above all nondestructively over large areas . Crop simulation models describe the relationship between physiological processes in plants and environmental growing conditions. The integration between remote sensing data and crop growth simulation model is an important trend for yield estimation and prediction, since remote sensing can provide information on the actual status of the agricultural crop. In this study, a new model(Rice-SRS) was developed based mainly on ORYZA1 model and modified to accept remote sensing data as input from different sources. The model can accept three kinds of NDVI data: NOAA AVHRR(LAC)-NDVI,NOAA AVHRR(GAC)-NDVI and radiometric measurements-NDVI. The integration between NOAA AVHRR (LAC) data and simulation model as applied to Rice-SRS resulted in accurate estimates for rice yield in the Shaoxing area, reduced the estimating error to 1.027%,0.794% and (-0.787%) for early, single, and late season respectively. Utilizing NDVI data derived from NOAA AVHRR (GAC) as input in Rice-SRS can yield good estimation for rice yield with the average error (-7.43%). Testing the new model for radiometric measurements showed that the average estimation error for 10 varieties under early rice conditions was less than 1%.
基金financially supported by the National Natural Science Foundation of China (21968020)the Natural Science Foundation of Inner Mongolia (2022MS02011 and 2023MS02014)+1 种基金the Science and Technology Projects of China Northern Rare Earth (BFXT-2022-D-0023)the Open Research Subject of Zhejiang Key Laboratory of Petrochemical Environmental Pollution Control (2021Z01)。
文摘Silver-copper electrocatalysts have demonstrated effectively catalytic performance in electroreduction CO_(2) toward CH_(4),yet a revealing insight into the reaction pathway and mechanism has remained elusive.Herein,we construct chemically bonded Ag-Cu_(2)O boundaries,in which the complete reduction of Cu_(2)O to Cu has been strongly impeded owing to the presence of surface Ag shell.The interfacial confinement effect helps to maintain Cu^(+)sites at the Ag-Cu_(2)O boundaries.Using in situ/operando spectroscopy and theoretical simulations,it is revealed that CO_(2) is enriched at the Ag-Cu_(2)O boundaries due to the enhanced physisorption and chemisorption to CO_(2),activating CO_(2) to form the stable intermediate^(*)CO.The boundaries between Ag shell and the Cu_(2)O mediate local^(*)CO coverage and promote^(*)CHO intermediate formation,consequently facilitating CO_(2)-to-CH_(4) conversion.This work not only reveals the structure-activity relationships but also offers insights into the reaction mechanism on Ag-Cu catalysts for efficient electrocatalytic CO_(2) reduction.
