We consider the problem of energy efficiency aware dynamic adaptation of data transmission rate and transmission power of the users in carrier sensing based Wireless Local Area Networks(WLANs)in the presence of path l...We consider the problem of energy efficiency aware dynamic adaptation of data transmission rate and transmission power of the users in carrier sensing based Wireless Local Area Networks(WLANs)in the presence of path loss,Rayleigh fading and log-normal shadowing.For a data packet transmission,we formulate an optimization problem,solve the problem,and propose a rate and transmission power adaptation scheme with a restriction methodology of data packet transmission for achieving the optimal energy efficiency.In the restriction methodology of data packet transmission,a user does not transmit a data packet if the instantaneous channel gain of the user is lower than a threshold.To evaluate the performance of the proposed scheme,we develop analytical models for computing the throughput and energy efficiency of WLANs under the proposed scheme considering a saturation traffic condition.We then validate the analytical models via simulation.We find that the proposed scheme provides better throughput and energy efficiency with acceptable throughput fairness if the restriction methodology of data packet transmission is included.By means of the analytical models and simulations,we demonstrate that the proposed scheme provides significantly higher throughput,energy efficiency and fairness index than a traditional non-adaptive scheme and an existing most relevant adaptive scheme.Throughput and energy efficiency gains obtained by the proposed scheme with respect to the existing adapting scheme are about 75%and 103%,respectively,for a fairness index of 0.8.We also study the effect of various system parameters on throughput and energy efficiency and provide various engineering insights.展开更多
Over the past decade,the significant growth of the convolutional neural network(CNN)based on deep learning(DL)approaches has greatly improved the machine learning(ML)algorithm’s performance on the semantic scene clas...Over the past decade,the significant growth of the convolutional neural network(CNN)based on deep learning(DL)approaches has greatly improved the machine learning(ML)algorithm’s performance on the semantic scene classification(SSC)of remote sensing images(RSI).However,the unbalanced attention to classification accuracy and efficiency has made the superiority of DL-based algorithms,e.g.,automation and simplicity,partially lost.Traditional ML strategies(e.g.,the handcrafted features or indicators)and accuracy-aimed strategies with a high trade-off(e.g.,the multi-stage CNNs and ensemble of multi-CNNs)are widely used without any training efficiency optimization involved,which may result in suboptimal performance.To address this problem,we propose a fast and simple training CNN framework(named FST-EfficientNet)for RSI-SSC based on an EfficientNetversion2 small(EfficientNetV2-S)CNN model.The whole algorithm flow is completely one-stage and end-to-end without any handcrafted features or discriminators introduced.In the implementation of training efficiency optimization,only several routine data augmentation tricks coupled with a fixed ratio of resolution or a gradually increasing resolution strategy are employed,so that the algorithm’s trade-off is very cheap.The performance evaluation shows that our FST-EfficientNet achieves new state-of-the-art(SOTA)records in the overall accuracy(OA)with about 0.8%to 2.7%ahead of all earlier methods on the Aerial Image Dataset(AID)and Northwestern Poly-technical University Remote Sensing Image Scene Classification 45 Dataset(NWPU-RESISC45D).Meanwhile,the results also demonstrate the importance and indispensability of training efficiency optimization strategies for RSI-SSC by DL.In fact,it is not necessary to gain better classification accuracy by completely relying on an excessive trade-off without efficiency.Ultimately,these findings are expected to contribute to the development of more efficient CNN-based approaches in RSI-SSC.展开更多
This paper investigates the effectiveness of conservation efforts in the Nyungwe Forest National Park (Nyungwe). The forest is one of the six key landscapes identified for conservation in the Albertine Rift because it...This paper investigates the effectiveness of conservation efforts in the Nyungwe Forest National Park (Nyungwe). The forest is one of the six key landscapes identified for conservation in the Albertine Rift because it hosts many threatened species. As such, a number of different stakeholders have been involved in its conservation since 1987;yet, studies that emphasize and evaluate the success of these conservation efforts are limited. We combined a rapid and relatively low cost remotely-sensed data and the Light Use Efficiency model to generate forest conservation indicators such as NDVI, forest canopy Net Primary Productivity and carbon sequestered from 1986 to 2010. The influence of topographic and climatic factors on these indicators was examined. The supervised classifier was used to catalogue the area into Forest, Wetland, and Bareland. The forest was the major category (above 90%) of Nyungwe relative to wetland and bareland. Based on degradation intensity, two distinctive periods were realised;the first period spans 8 years (1986-1994) whereas the second spans 16 years (1994-2010). The former degradation intensity period is 10 times higher than the latter period. Although the size of forest recovered up to 90%, the daily NPP and carbon sequestration capacity decreased by 37.1% (i.e. NPP 6.5 Mg tons in 1986 to 4.1 Mg tons in 2010). Areas of the forest that are physically constrained (high altitude) had a higher degradation. Guided by our indicators, there is an overall success in conservation efforts, but efforts were mostly concentrated in accessible areas. Therefore, conservation efforts that aim to respond to degradation of the inaccessible areas of the forest should be stressed in the management plan of the park.展开更多
In order to improve the energy efficiency(EE) in cognitive radio(CR), a joint optimal energy-efficient cooperative spectrum sensing(CSS) and transmission in multi-channel CR is proposed in this paper. EE is described ...In order to improve the energy efficiency(EE) in cognitive radio(CR), a joint optimal energy-efficient cooperative spectrum sensing(CSS) and transmission in multi-channel CR is proposed in this paper. EE is described as a tradeoff between the throughput and the entirely consumed power. A joint optimization problem is formulated to maximize EE by jointly optimizing local sensing time, number of cooperative sensing secondary users(SU), transmission bandwidth and power. A combined optimization algorithm of bi-level optimization, Polyblock optimization and Dinkelbach's optimization is proposed to solve the proposed non-convex optimization problem effectively. The simulation results show that, compared with throughput maximization model(TMM), the energy efficiency maximization model(EEMM) improves EE of the CR system and limits the excessive power consumption effectively.展开更多
Under the theory structure of compressive sensing （CS）, an underdetermined equation is deduced for describing the discrete solution of the electromagnetic integral equation of body of revolution （BOR）, which will ...Under the theory structure of compressive sensing （CS）, an underdetermined equation is deduced for describing the discrete solution of the electromagnetic integral equation of body of revolution （BOR）, which will result in a small-scale impedance matrix. In the new linear equation system, the small-scale impedance matrix can be regarded as the measurement matrix in CS, while the excited vector is the measurement of unknown currents. Instead of solving dense full rank matrix equations by the iterative method, with suitable sparse representation, for unknown currents on the surface of BOR, the entire current can be accurately obtained by reconstructed algorithms in CS for small-scale undetermined equations. Numerical results show that the proposed method can greatly improve the computgtional efficiency and can decrease memory consumed.展开更多
As a constraint for smart devices,energy consumption has attract people's attention for a long time period. How to get higher resource utilization with less energy consumption is a challenge for cognitive radio ne...As a constraint for smart devices,energy consumption has attract people's attention for a long time period. How to get higher resource utilization with less energy consumption is a challenge for cognitive radio networks. Secondary users have to participate in spectrum sensing at the cost of energy and access idle spectrum without interfering primary users. However,not all participating secondary users can access idle spectrum. How to ensure the participation users access spectrum efficiently with a larger probability is an urgent problem to be solved. We propose an Energy Efficiency-based Decision Making(EEDM) for cognitive radio networks,which fully considers residual energy and probability of obtaining spectrum resources. Simulation and analysis show that the proposed scheme can maximize proportion of allocated users under the premise of ensuring the accuracy of spectrum sensing,then balance users' energy consumption and access efficiency,so as to effectively improve the utilization of spectrum resources.展开更多
Measurements of column-averaged dry-air mole fractions of carbon dioxide and carbon monoxide,CO_(2)(XCO_(2))and CO(XCO),were performed throughout 2019 at an urban site in Beijing using a compact Fourier Transform Spec...Measurements of column-averaged dry-air mole fractions of carbon dioxide and carbon monoxide,CO_(2)(XCO_(2))and CO(XCO),were performed throughout 2019 at an urban site in Beijing using a compact Fourier Transform Spectrometer(FTS)EM27/SUN.This data set is used to assess the characteristics of combustion-related CO_(2)emissions of urban Beijing by analyzing the correlated daily anomalies of XCO and XCO_(2)(e.g.,ΔXCO andΔXCO_(2)).The EM27/SUN measurements were calibrated to a 125HR-FTS at the Xianghe station by an extra EM27/SUN instrument transferred between two sites.The ratio ofΔXCO overΔXCO_(2)(ΔXCO:ΔXCO_(2))is used to estimate the combustion efficiency in the Beijing region.A high correlation coefficient(0.86)betweenΔXCO andΔXCO_(2)is observed.The CO:CO_(2)emission ratio estimated from inventories is higher than the observedΔXCO:ΔXCO_(2)(10.46±0.11 ppb ppm^(−1))by 42.54%-101.15%,indicating an underestimation in combustion efficiency in the inventories.DailyΔXCO:ΔXCO_(2)are influenced by transportation governed by weather conditions,except for days in summer when the correlation is low due to the terrestrial biotic activity.By convolving the column footprint[ppm(μmol m-2 s-1)-1]generated by the Weather Research and Forecasting-X-Stochastic Time-Inverted Lagrangian Transport models(WRF-X-STILT)with two fossil-fuel emission inventories(the Multi-resolution Emission Inventory for China(MEIC)and the Peking University(PKU)inventory),the observed enhancements of CO_(2)and CO were used to evaluate the regional emissions.The CO_(2)emissions appear to be underestimated by 11%and 49%for the MEIC and PKU inventories,respectively,while CO emissions were overestimated by MEIC(30%)and PKU(35%)in the Beijing area.展开更多
Authors of the text present Polish context of teachers’ professional promotion and teachers’ competencies. The text also has its empirical dimension-a research about teachers’ sense of life quality has been done. T...Authors of the text present Polish context of teachers’ professional promotion and teachers’ competencies. The text also has its empirical dimension-a research about teachers’ sense of life quality has been done. There are teachers’ expressions, collected and quoted during qualitative research. Teachers’ thoughts are concerned about the sense of life quality in the context of working at lower secondary school.展开更多
Great changes have taken place in college English teaching in China in recent decades.Different teaching theories have been introduced into English teaching in many colleges and universities.However,college English,as...Great changes have taken place in college English teaching in China in recent decades.Different teaching theories have been introduced into English teaching in many colleges and universities.However,college English,as one of the required courses,is faced with a lot of complaints and criticism from the students and teachers as well as the society.The low efficiency in college English teaching is one of the problems,which attract the attention of all those concerned.It is of great significance to find out why students spend so much time,money and energy on English learning but are still at loss how to use English for communication.Surely,teaching and learning English is not an easy job.It involves a number of complicated interrelated factors.The article is meant to discuss the factors that are closely related to the low-efficiency in college English teaching in china,such as education notion,usage of textbooks,teacher quality as well as students motivations,aiming to make people have a clear idea of the problem so that some things can be done to improve the quality and efficiency of college English teaching in China.展开更多
In recent decades,several optimization algorithms have been developed for selecting the most energy efficient clusters in order to save power during trans-mission to a shorter distance while restricting the Primary Us...In recent decades,several optimization algorithms have been developed for selecting the most energy efficient clusters in order to save power during trans-mission to a shorter distance while restricting the Primary Users(PUs)interfer-ence.The Cognitive Radio(CR)system is based on the Adaptive Swarm Distributed Intelligent based Clustering algorithm(ASDIC)that shows better spectrum sensing among group of multiusers in terms of sensing error,power sav-ing,and convergence time.In this research paper,the proposed ASDIC algorithm develops better energy efficient distributed cluster based sensing with the optimal number of clusters on their connectivity.In this research,multiple random Sec-ondary Users(SUs),and PUs are considered for implementation.Hence,the pro-posed ASDIC algorithm improved the convergence speed by combining the multi-users clustered communication compared to the existing optimization algo-rithms.Experimental results showed that the proposed ASDIC algorithm reduced the node power of 9.646%compared to the existing algorithms.Similarly,ASDIC algorithm reduced 24.23%of SUs average node power compared to the existing algorithms.Probability of detection is higher by reducing the Signal-to-Noise Ratio(SNR)to 2 dB values.The proposed ASDIC delivers low false alarm rate compared to other existing optimization algorithms in the primary detection.Simulation results showed that the proposed ASDIC algorithm effectively solves the multimodal optimization problems and maximizes the performance of net-work capacity.展开更多
文摘We consider the problem of energy efficiency aware dynamic adaptation of data transmission rate and transmission power of the users in carrier sensing based Wireless Local Area Networks(WLANs)in the presence of path loss,Rayleigh fading and log-normal shadowing.For a data packet transmission,we formulate an optimization problem,solve the problem,and propose a rate and transmission power adaptation scheme with a restriction methodology of data packet transmission for achieving the optimal energy efficiency.In the restriction methodology of data packet transmission,a user does not transmit a data packet if the instantaneous channel gain of the user is lower than a threshold.To evaluate the performance of the proposed scheme,we develop analytical models for computing the throughput and energy efficiency of WLANs under the proposed scheme considering a saturation traffic condition.We then validate the analytical models via simulation.We find that the proposed scheme provides better throughput and energy efficiency with acceptable throughput fairness if the restriction methodology of data packet transmission is included.By means of the analytical models and simulations,we demonstrate that the proposed scheme provides significantly higher throughput,energy efficiency and fairness index than a traditional non-adaptive scheme and an existing most relevant adaptive scheme.Throughput and energy efficiency gains obtained by the proposed scheme with respect to the existing adapting scheme are about 75%and 103%,respectively,for a fairness index of 0.8.We also study the effect of various system parameters on throughput and energy efficiency and provide various engineering insights.
基金This research has been supported by Doctoral Research funding from Hunan University of Arts and Science,Grant Number E07016033.
文摘Over the past decade,the significant growth of the convolutional neural network(CNN)based on deep learning(DL)approaches has greatly improved the machine learning(ML)algorithm’s performance on the semantic scene classification(SSC)of remote sensing images(RSI).However,the unbalanced attention to classification accuracy and efficiency has made the superiority of DL-based algorithms,e.g.,automation and simplicity,partially lost.Traditional ML strategies(e.g.,the handcrafted features or indicators)and accuracy-aimed strategies with a high trade-off(e.g.,the multi-stage CNNs and ensemble of multi-CNNs)are widely used without any training efficiency optimization involved,which may result in suboptimal performance.To address this problem,we propose a fast and simple training CNN framework(named FST-EfficientNet)for RSI-SSC based on an EfficientNetversion2 small(EfficientNetV2-S)CNN model.The whole algorithm flow is completely one-stage and end-to-end without any handcrafted features or discriminators introduced.In the implementation of training efficiency optimization,only several routine data augmentation tricks coupled with a fixed ratio of resolution or a gradually increasing resolution strategy are employed,so that the algorithm’s trade-off is very cheap.The performance evaluation shows that our FST-EfficientNet achieves new state-of-the-art(SOTA)records in the overall accuracy(OA)with about 0.8%to 2.7%ahead of all earlier methods on the Aerial Image Dataset(AID)and Northwestern Poly-technical University Remote Sensing Image Scene Classification 45 Dataset(NWPU-RESISC45D).Meanwhile,the results also demonstrate the importance and indispensability of training efficiency optimization strategies for RSI-SSC by DL.In fact,it is not necessary to gain better classification accuracy by completely relying on an excessive trade-off without efficiency.Ultimately,these findings are expected to contribute to the development of more efficient CNN-based approaches in RSI-SSC.
文摘This paper investigates the effectiveness of conservation efforts in the Nyungwe Forest National Park (Nyungwe). The forest is one of the six key landscapes identified for conservation in the Albertine Rift because it hosts many threatened species. As such, a number of different stakeholders have been involved in its conservation since 1987;yet, studies that emphasize and evaluate the success of these conservation efforts are limited. We combined a rapid and relatively low cost remotely-sensed data and the Light Use Efficiency model to generate forest conservation indicators such as NDVI, forest canopy Net Primary Productivity and carbon sequestered from 1986 to 2010. The influence of topographic and climatic factors on these indicators was examined. The supervised classifier was used to catalogue the area into Forest, Wetland, and Bareland. The forest was the major category (above 90%) of Nyungwe relative to wetland and bareland. Based on degradation intensity, two distinctive periods were realised;the first period spans 8 years (1986-1994) whereas the second spans 16 years (1994-2010). The former degradation intensity period is 10 times higher than the latter period. Although the size of forest recovered up to 90%, the daily NPP and carbon sequestration capacity decreased by 37.1% (i.e. NPP 6.5 Mg tons in 1986 to 4.1 Mg tons in 2010). Areas of the forest that are physically constrained (high altitude) had a higher degradation. Guided by our indicators, there is an overall success in conservation efforts, but efforts were mostly concentrated in accessible areas. Therefore, conservation efforts that aim to respond to degradation of the inaccessible areas of the forest should be stressed in the management plan of the park.
基金supported by the National Natural Science Foundations of China under Grant Nos. 61301105, 61401288 and 61601221the Natural Science Foundations of Jiangsu Province under Grant No. BK20140828+1 种基金the China Postdoctoral Science Foundations under Grant Nos. 2015M581791 and 2015M580425the Fundamental Research Funds for the Central Universities under Grant No. DUT16RC(3)045
文摘In order to improve the energy efficiency(EE) in cognitive radio(CR), a joint optimal energy-efficient cooperative spectrum sensing(CSS) and transmission in multi-channel CR is proposed in this paper. EE is described as a tradeoff between the throughput and the entirely consumed power. A joint optimization problem is formulated to maximize EE by jointly optimizing local sensing time, number of cooperative sensing secondary users(SU), transmission bandwidth and power. A combined optimization algorithm of bi-level optimization, Polyblock optimization and Dinkelbach's optimization is proposed to solve the proposed non-convex optimization problem effectively. The simulation results show that, compared with throughput maximization model(TMM), the energy efficiency maximization model(EEMM) improves EE of the CR system and limits the excessive power consumption effectively.
基金Supported by the National Natural Science Foundation of China under Grant Nos 51477039 and 51207041the Program of Hefei Normal University under Grant Nos 2014136KJA04 and 2015TD01the Key Project of Provincial Natural Science Research of University of Anhui Province of China under Grant No KJ2015A174
文摘Under the theory structure of compressive sensing （CS）, an underdetermined equation is deduced for describing the discrete solution of the electromagnetic integral equation of body of revolution （BOR）, which will result in a small-scale impedance matrix. In the new linear equation system, the small-scale impedance matrix can be regarded as the measurement matrix in CS, while the excited vector is the measurement of unknown currents. Instead of solving dense full rank matrix equations by the iterative method, with suitable sparse representation, for unknown currents on the surface of BOR, the entire current can be accurately obtained by reconstructed algorithms in CS for small-scale undetermined equations. Numerical results show that the proposed method can greatly improve the computgtional efficiency and can decrease memory consumed.
基金supported by the National Natural Science Foundation of China (NO.61602358,No.61373170,NO.U1401251,No.U1536202)Fundamental Research Funds for the Central Universities(No.JB150114)the Natural Science Basic Research Plan in Shaanxi Province,China (No.2014JQ8308)
文摘As a constraint for smart devices,energy consumption has attract people's attention for a long time period. How to get higher resource utilization with less energy consumption is a challenge for cognitive radio networks. Secondary users have to participate in spectrum sensing at the cost of energy and access idle spectrum without interfering primary users. However,not all participating secondary users can access idle spectrum. How to ensure the participation users access spectrum efficiently with a larger probability is an urgent problem to be solved. We propose an Energy Efficiency-based Decision Making(EEDM) for cognitive radio networks,which fully considers residual energy and probability of obtaining spectrum resources. Simulation and analysis show that the proposed scheme can maximize proportion of allocated users under the premise of ensuring the accuracy of spectrum sensing,then balance users' energy consumption and access efficiency,so as to effectively improve the utilization of spectrum resources.
基金supported by grants from the National Key Research and Development Program of China(Grant No.2017YFB0504000)National Natural Science Foundation of China(Grant No.41875043)+2 种基金the Strategic Priority Research 275 Program of the Chinese Academy of Sciences(Grant No.XDA17010102)External Cooperation Program of the Chinese Academy of Science(Grant No.GJHZ1802)Youth Innovation Promotion Association,CAS.
文摘Measurements of column-averaged dry-air mole fractions of carbon dioxide and carbon monoxide,CO_(2)(XCO_(2))and CO(XCO),were performed throughout 2019 at an urban site in Beijing using a compact Fourier Transform Spectrometer(FTS)EM27/SUN.This data set is used to assess the characteristics of combustion-related CO_(2)emissions of urban Beijing by analyzing the correlated daily anomalies of XCO and XCO_(2)(e.g.,ΔXCO andΔXCO_(2)).The EM27/SUN measurements were calibrated to a 125HR-FTS at the Xianghe station by an extra EM27/SUN instrument transferred between two sites.The ratio ofΔXCO overΔXCO_(2)(ΔXCO:ΔXCO_(2))is used to estimate the combustion efficiency in the Beijing region.A high correlation coefficient(0.86)betweenΔXCO andΔXCO_(2)is observed.The CO:CO_(2)emission ratio estimated from inventories is higher than the observedΔXCO:ΔXCO_(2)(10.46±0.11 ppb ppm^(−1))by 42.54%-101.15%,indicating an underestimation in combustion efficiency in the inventories.DailyΔXCO:ΔXCO_(2)are influenced by transportation governed by weather conditions,except for days in summer when the correlation is low due to the terrestrial biotic activity.By convolving the column footprint[ppm(μmol m-2 s-1)-1]generated by the Weather Research and Forecasting-X-Stochastic Time-Inverted Lagrangian Transport models(WRF-X-STILT)with two fossil-fuel emission inventories(the Multi-resolution Emission Inventory for China(MEIC)and the Peking University(PKU)inventory),the observed enhancements of CO_(2)and CO were used to evaluate the regional emissions.The CO_(2)emissions appear to be underestimated by 11%and 49%for the MEIC and PKU inventories,respectively,while CO emissions were overestimated by MEIC(30%)and PKU(35%)in the Beijing area.
文摘Authors of the text present Polish context of teachers’ professional promotion and teachers’ competencies. The text also has its empirical dimension-a research about teachers’ sense of life quality has been done. There are teachers’ expressions, collected and quoted during qualitative research. Teachers’ thoughts are concerned about the sense of life quality in the context of working at lower secondary school.
文摘Great changes have taken place in college English teaching in China in recent decades.Different teaching theories have been introduced into English teaching in many colleges and universities.However,college English,as one of the required courses,is faced with a lot of complaints and criticism from the students and teachers as well as the society.The low efficiency in college English teaching is one of the problems,which attract the attention of all those concerned.It is of great significance to find out why students spend so much time,money and energy on English learning but are still at loss how to use English for communication.Surely,teaching and learning English is not an easy job.It involves a number of complicated interrelated factors.The article is meant to discuss the factors that are closely related to the low-efficiency in college English teaching in china,such as education notion,usage of textbooks,teacher quality as well as students motivations,aiming to make people have a clear idea of the problem so that some things can be done to improve the quality and efficiency of college English teaching in China.
文摘In recent decades,several optimization algorithms have been developed for selecting the most energy efficient clusters in order to save power during trans-mission to a shorter distance while restricting the Primary Users(PUs)interfer-ence.The Cognitive Radio(CR)system is based on the Adaptive Swarm Distributed Intelligent based Clustering algorithm(ASDIC)that shows better spectrum sensing among group of multiusers in terms of sensing error,power sav-ing,and convergence time.In this research paper,the proposed ASDIC algorithm develops better energy efficient distributed cluster based sensing with the optimal number of clusters on their connectivity.In this research,multiple random Sec-ondary Users(SUs),and PUs are considered for implementation.Hence,the pro-posed ASDIC algorithm improved the convergence speed by combining the multi-users clustered communication compared to the existing optimization algo-rithms.Experimental results showed that the proposed ASDIC algorithm reduced the node power of 9.646%compared to the existing algorithms.Similarly,ASDIC algorithm reduced 24.23%of SUs average node power compared to the existing algorithms.Probability of detection is higher by reducing the Signal-to-Noise Ratio(SNR)to 2 dB values.The proposed ASDIC delivers low false alarm rate compared to other existing optimization algorithms in the primary detection.Simulation results showed that the proposed ASDIC algorithm effectively solves the multimodal optimization problems and maximizes the performance of net-work capacity.
