Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first prop...Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first proposed in this paper.Here,a novel four-dimensional fractional-order memristive cellular neural network(FO-MCNN)model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its performance.Then,its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation platforms.Subsequently,it is used toward secure communication application scenarios.Taking it as the pseudo-random number generator(PRNG),a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing(ASR-CS)model.Eventually,the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance.展开更多
The escalating deployment of distributed power sources and random loads in DC distribution networks hasamplified the potential consequences of faults if left uncontrolled. To expedite the process of achieving an optim...The escalating deployment of distributed power sources and random loads in DC distribution networks hasamplified the potential consequences of faults if left uncontrolled. To expedite the process of achieving an optimalconfiguration of measurement points, this paper presents an optimal configuration scheme for fault locationmeasurement points in DC distribution networks based on an improved particle swarm optimization algorithm.Initially, a measurement point distribution optimization model is formulated, leveraging compressive sensing.The model aims to achieve the minimum number of measurement points while attaining the best compressivesensing reconstruction effect. It incorporates constraints from the compressive sensing algorithm and networkwide viewability. Subsequently, the traditional particle swarm algorithm is enhanced by utilizing the Haltonsequence for population initialization, generating uniformly distributed individuals. This enhancement reducesindividual search blindness and overlap probability, thereby promoting population diversity. Furthermore, anadaptive t-distribution perturbation strategy is introduced during the particle update process to enhance the globalsearch capability and search speed. The established model for the optimal configuration of measurement points issolved, and the results demonstrate the efficacy and practicality of the proposed method. The optimal configurationreduces the number of measurement points, enhances localization accuracy, and improves the convergence speedof the algorithm. These findings validate the effectiveness and utility of the proposed approach.展开更多
As one of the most promising platforms for wireless communication,radiofrequency(RF)electronics have been widely advocated for the development of sensing systems.In particular,monolayer and few-layer two-dimensional(2...As one of the most promising platforms for wireless communication,radiofrequency(RF)electronics have been widely advocated for the development of sensing systems.In particular,monolayer and few-layer two-dimensional(2D)materials exhibiting extraordinary electrical properties not only can be integrated to improve the performance of RF circuits,but also to display exceptional sensing capabilities.This review provides an in-depth perspective of current trends and challenges in the application of 2D materials for RF biochemical sensing,including:(i)theoretical bases to achieve different sensing schemes;(ii)unique properties of 2D materials for reasoning their applications in RF sensing;(iii)developments in 2D RF sensors to facilitate the practice of biochemical sensors with ever-demanding sensitivities,as well as their potential uses in meeting the requirements and challenges of biochemical sensors in the Internet-of-Things era.展开更多
Abuja is witnessing an upsurge of victims from Road Traffic Crash (RTC) which is mostly due to the attendant rapid increase in the volume of vehicles, traffic jams, bad driving, over speeding, insufficient road signs ...Abuja is witnessing an upsurge of victims from Road Traffic Crash (RTC) which is mostly due to the attendant rapid increase in the volume of vehicles, traffic jams, bad driving, over speeding, insufficient road signs and bad conditions of vehicles that ply the roads. The problem is compounded by a lack of early emergency response. Geographic Information System (GIS) based travel time model was applied in the street network analysis to identify RTC black spots that are outside the close reach of Federal Road Safety Commission (FRSC) rescue points/health facilities in Federal Capital City (FCC). Five minutes, Ten minutes and Fifteen minutes travel times were used as the impedance factor. Remote Sensing and GIS techniques were used to carry out network analysis. This was achieved by conducting the closest facility operation in the ArcGIS network analyst extension using the time of travel from each FRSC zebra point location to the RTC black spot zones/health facility. The results were presented on road network maps and bar graphs. The areas where quick response and medical facilities are insufficient were identified. It was concluded that the available health centres can sufficiently service RTC black spots in FCC, but the FRSC zebra points are insufficient which renders rescue operations inefficient and thereby exposes RTC victims to more danger. In order to ensure that there is sufficient coverage for response times, it was suggested that additional zebra points be created.展开更多
Intensive aeolian processes occur due to the scarcity of rainfall and lack of vegetation cover in arid regions. The study of recent surface sediments in arid areas is important for environmental assessments, evaluatio...Intensive aeolian processes occur due to the scarcity of rainfall and lack of vegetation cover in arid regions. The study of recent surface sediments in arid areas is important for environmental assessments, evaluation of natural resources, and land use planning. In this study, two areas were chosen as they show changes in lithology, environment and landforms. The two study areas are Al-Rawdatain in the northern part, and Al-Managish in the southern part of Kuwait. The current study aims to define the sedimentomorphic zones in these areas, with an emphasis on Quaternary geomorphological evolution by providing an integrated approach based on satellite images, topographic maps, field measurements, and laboratory analysis. Remote sensing data were spatially analyzed to classify and detect the temporal changes in the surface sediments and geomorphology based on the field measurements (n = 42) as ground truthing points for supervising the classification. Samples from both areas were collected and subjected to grain size (dry mechanical sieving) and X-Ray Diffraction (XRD) analysis. The resulting data were statistically analyzed for grain size distributions and mineralogy based on the US standard set of sieves. The study found that the Aeolian sand sheet deposits are the most frequent recent surface deposits in Kuwait and cover most of the other sediments. The direction of movement of the sand sheets is from NW towards SE. The mineralogical composition of the aeolian recent surface sediments revealed that they are mostly derived from the Dibdibba Formation and Tigris-Euphrates fluvial terrace deposits. Quartz is the most frequent component of the studied surface sediments in the study areas (66%). The calcite mineral is also found in subordinate amounts in the study areas (10%).展开更多
With the continuous improvement of the performance and the increasing variety of optical mapping and remote sensing satellites,they have become an important support for obtaining global accurate surveying and mapping ...With the continuous improvement of the performance and the increasing variety of optical mapping and remote sensing satellites,they have become an important support for obtaining global accurate surveying and mapping remote sensing information.At present,optical mapping and remote sensing satellites already have sub-meter spatial resolution capabilities,but there is a serious lag problem in mapping and remote sensing information services.It is urgent to develop intelligent mapping and remote sensing satellites to promote the transformation and upgrading to real-time intelligent services.Firstly,based on the three imaging systems of the optical mapping and remote sensing satellites and their realization methods and application characteristics,this paper analyzes the applicable system of the intelligent mapping and remote sensing satellites.Further,according to the application requirements of real-time,intelligence,and popularization,puts forward the design concept of integrated intelligent remote sensing satellite integrating communication,navigation,and remote sensing and focuses on the service mode and integrated function composition of intelligent remote sensing satellite.Then expounds on the performance and characteristics of the Luojia-301 satellite,a new generation of intelligent surveying and mapping remote sensing scientific test satellite.And finally summarizes and prospects the development and mission of intelligent mapping remote sensing satellites.Luojia-301 satellite integrates remote sensing and communication functions.It explores an efficient and intelligent service mode of mapping and remote sensing information from data acquisition to the application terminal and provides a real service verification platform for on-orbit processing and real-time transmission of remote sensing data based on space-ground internet,which is of great significance to the construction of China’s spatial information network.展开更多
Single atom catalysts(SACs)have garnered significant attention in the field of catalysis over the past decade due to their exceptional atom utilization efficiency and distinct physical and chemical properties.For the ...Single atom catalysts(SACs)have garnered significant attention in the field of catalysis over the past decade due to their exceptional atom utilization efficiency and distinct physical and chemical properties.For the semiconductor-based electrical gas sensor,the core is the catalysis process of target gas molecules on the sensitive materials.In this context,the SACs offer great potential for highly sensitive and selective gas sensing,however,only some of the bubbles come to the surface.To facilitate practical applications,we present a comprehensive review of the preparation strategies for SACs,with a focus on overcoming the challenges of aggregation and low loading.Extensive research efforts have been devoted to investigating the gas sensing mechanism,exploring sensitive materials,optimizing device structures,and refining signal post-processing techniques.Finally,the challenges and future perspectives on the SACs based gas sensing are presented.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
Conventional blood sampling for glucose detection is prone to cause pain and fails to continuously record glucose fluctuations in vivo.Continuous glucose monitoring based on implantable electrodes could induce pain an...Conventional blood sampling for glucose detection is prone to cause pain and fails to continuously record glucose fluctuations in vivo.Continuous glucose monitoring based on implantable electrodes could induce pain and potential tissue inflammation,and the presence of reactive oxygen species(ROS)due to inflammationmay affect glucose detection.Microneedle technology is less invasive,yet microneedle adhesion with skin tissue is limited.In this work,we developed a microarrow sensor array(MASA),which provided enhanced skin surface adhesion and enabled simultaneous detection of glucose and H_(2)O_(2)(representative of ROS)in interstitial fluid in vivo.The microarrows fabricated via laser micromachining were modified with functional coating and integrated into a patch of a three-dimensional(3D)microneedle array.Due to the arrow tip mechanically interlocking with the tissue,the microarrow array could better adhere to the skin surface after penetration into skin.The MASA was demonstrated to provide continuous in vivo monitoring of glucose and H_(2)O_(2) concentrations,with the detection of H_(2)O_(2) providing a valuable reference for assessing the inflammation state.Finally,the MASA was integrated into a monitoring system using custom circuitry.This work provides a promising tool for the stable and reliable monitoring of blood glucose in diabetic patients.展开更多
In this paper, we carry out QoE (Quality of Experience) assessment to investigate influences of olfactory and auditory senses on fairness for a networked virtual 3D object identification game with haptics. In the game...In this paper, we carry out QoE (Quality of Experience) assessment to investigate influences of olfactory and auditory senses on fairness for a networked virtual 3D object identification game with haptics. In the game, two players try to identify objects which are placed in a shared 3D virtual space. In the assessment, we carry out the game in four cases. Smells and sounds are presented in the first case, only sounds are done in the second case, and only smells are done in the third case. In the last case, we present neither smell nor sound. As a result, we demonstrate that the fairness deteriorates more largely as the difference in conditions between two users becomes larger.展开更多
Cereal is an essential source of calories and protein for the global population.Accurately predicting cereal quality before harvest is highly desirable in order to optimise management for farmers,grading harvest and c...Cereal is an essential source of calories and protein for the global population.Accurately predicting cereal quality before harvest is highly desirable in order to optimise management for farmers,grading harvest and categorised storage for enterprises,future trading prices,and policy planning.The use of remote sensing data with extensive spatial coverage demonstrates some potential in predicting crop quality traits.Many studies have also proposed models and methods for predicting such traits based on multiplatform remote sensing data.In this paper,the key quality traits that are of interest to producers and consumers are introduced.The literature related to grain quality prediction was analyzed in detail,and a review was conducted on remote sensing platforms,commonly used methods,potential gaps,and future trends in crop quality prediction.This review recommends new research directions that go beyond the traditional methods and discusses grain quality retrieval and the associated challenges from the perspective of remote sensing data.展开更多
Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into...Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into photosynthesis. It is very sensible for factors affecting on vegetation variability such as climate, soils, plant characteristics and human activities. So, it can be used as an indicator of actual and potential trend of vegetation. In this study we used the actual NPP which was derived from MODIS to assess the response of NPP to climate variables in Gadarif State, from 2000 to 2010. The correlations between NPP and climate variables (temperature and precipitation) are calculated using Pearson’s Correlation Coefficient and ordinary least squares regression. The main results show the following 1) the correlation Coefficient between NPP and mean annual temperature is Somewhat negative for Feshaga, Rahd, Gadarif and Galabat areas and weakly negative in Faw area;2) the correlation Coefficient between NPP and annual total precipitation is weakly negative in Faw, Rahd and Galabat areas and somewhat negative in Galabat and Rahd areas. This study demonstrated that the correlation analysis between NPP and climate variables (precipitation and temperature) gives reliably result of NPP responses to climate variables that is clearly in a very large scale of study area.展开更多
An innovative complex lidar system deployed on an airborne rotorcraft platform for remote sensing of atmospheric pollution is proposed and demonstrated.The system incorporates integrated-path differential absorption l...An innovative complex lidar system deployed on an airborne rotorcraft platform for remote sensing of atmospheric pollution is proposed and demonstrated.The system incorporates integrated-path differential absorption lidar(DIAL) and coherent-doppler lidar(CDL) techniques using a dual tunable TEA CO_(2)laser in the 9—11 μm band and a 1.55 μm fiber laser.By combining the principles of differential absorption detection and pulsed coherent detection,the system enables agile and remote sensing of atmospheric pollution.Extensive static tests validate the system’s real-time detection capabilities,including the measurement of concentration-path-length product(CL),front distance,and path wind speed of air pollution plumes over long distances exceeding 4 km.Flight experiments is conducted with the helicopter.Scanning of the pollutant concentration and the wind field is carried out in an approximately 1 km slant range over scanning angle ranges from 45°to 65°,with a radial resolution of 30 m and10 s.The test results demonstrate the system’s ability to spatially map atmospheric pollution plumes and predict their motion and dispersion patterns,thereby ensuring the protection of public safety.展开更多
Beam management,including initial access(IA)and beam tracking,is essential to the millimeter-wave Unmanned Aerial Vehicle(UAV)network.However,the conventional communicationonly and feedback-based schemes suffer a high...Beam management,including initial access(IA)and beam tracking,is essential to the millimeter-wave Unmanned Aerial Vehicle(UAV)network.However,the conventional communicationonly and feedback-based schemes suffer a high delay and low accuracy of beam alignment,since they only enable the receiver to passively“hear”the information of the transmitter from the radio domain.This paper presents a novel sensing-assisted beam management approach,the first solution that fully utilizes the information from the visual domain to improve communication performance.We employ both integrated sensing and communication and computer vision techniques and design an extended Kalman filtering method for beam tracking and prediction.Besides,we also propose a novel dual identity association solution to distinguish multiple UAVs in dynamic environments.Real-world experiments and numerical results show that the proposed solution outperforms the conventional methods in IA delay,association accuracy,tracking error,and communication performance.展开更多
Landslide disasters comprise the majority of geological incidents on slopes,posing severe threats to the safety of human lives and property while exerting a significant impact on the geological environment.The rapid i...Landslide disasters comprise the majority of geological incidents on slopes,posing severe threats to the safety of human lives and property while exerting a significant impact on the geological environment.The rapid identification of landslides is important for disaster prevention and control;however,currently,landslide identification relies mainly on the manual interpretation of remote sensing images.Manual interpretation and feature recognition methods are time-consuming,labor-intensive,and challenging when confronted with complex scenarios.Consequently,automatic landslide recognition has emerged as a pivotal avenue for future development.In this study,a dataset comprising 2000 landslide images was constructed using open-source remote sensing images and datasets.The YOLOv7 model was enhanced using data augmentation algorithms and attention mechanisms.Three optimization models were formulated to realize automatic landslide recognition.The findings demonstrate the commendable performance of the optimized model in automatic landslide recognition,achieving a peak accuracy of 95.92%.Subsequently,the optimized model was applied to regional landslide identification,co-seismic landslide identification,and landslide recognition at various scales,all of which showed robust recognition capabilities.Nevertheless,the model exhibits limitations in detecting small targets,indicating areas for refining the deep-learning algorithms.The results of this research offer valuable technical support for the swift identification,prevention,and mitigation of landslide disasters.展开更多
Himalayan glaciers are shrinking rapidly,especially after 2000.Glacier shrinkage,however,shows a differential pattern in space and time,emphasizing the need to monitor and assess glacier changes at a larger scale.In t...Himalayan glaciers are shrinking rapidly,especially after 2000.Glacier shrinkage,however,shows a differential pattern in space and time,emphasizing the need to monitor and assess glacier changes at a larger scale.In this study,changes of 48 glaciers situated around the twin peaks of the Nun and Kun mountains in the northwestern Himalaya,hereafter referred to as Nun-Kun Group of Glaciers(NKGG),were investigated using Landsat satellite data during 2000-2020.Changes in glacier area,snout position,Equilibrium Line Altitude(ELA),surface thickness and glacier velocity were assessed using remote sensing data supplemented by field observations.The study revealed that the NKGG glaciers have experienced a recession of 4.5%±3.4%and their snouts have retreated at the rate of 6.4±1.6 m·a^(-1).Additionally,there was a 41%increase observed in the debris cover area during the observation period.Using the geodetic approach,an average glacier elevation change of-1.4±0.4 m·a^(-1)was observed between 2000 and 2012.The observed mass loss of the NKGG has resulted in the deceleration of glacier velocity from 27.0±3.7 m·a^(-1)in 2000 to 21.2±2.2 m·a^(-1)in 2020.The ELA has shifted upwards by 83.0±22 m during the period.Glacier morphological and topographic factors showed a strong influence on glacier recession.Furthermore,a higher recession of 12.9%±3.2%was observed in small glaciers,compared to 2.7%±3.1%in larger glaciers.The debris-covered glaciers showed lower shrinkage(2.8%±1.1%)compared to the clean glaciers(9.3%±5%).The glacier depletion recorded in the NKGG during the last two decades,if continued,would severely diminish glacial volume and capacity to store water,thus jeopardizing the sustainability of water resources in the basin.展开更多
In this paper,we formulate the precoding problem of integrated sensing and communication(ISAC)waveform as a non-convex quadratically constrained quadratic programming(QCQP),in which the weighted sum of communication m...In this paper,we formulate the precoding problem of integrated sensing and communication(ISAC)waveform as a non-convex quadratically constrained quadratic programming(QCQP),in which the weighted sum of communication multi-user interference(MUI)and the gap between dual-use waveform and ideal radar waveform is minimized with peak-toaverage power ratio(PAPR)constraints.We propose an efficient algorithm based on alternating direction method of multipliers(ADMM),which is able to decouple multiple variables and provide a closed-form solution for each subproblem.In addition,to improve the sensing performance in both spatial and temporal domains,we propose a new criteria to design the ideal radar waveform,in which the beam pattern is made similar to the ideal one and the integrated sidelobe level of the ambiguity function in each target direction is minimized in the region of interest.The limited memory Broyden-Fletcher-Goldfarb-Shanno(LBFGS)algorithm is applied to the design of the ideal radar waveform which works as a reference in the design of the dual-function waveform.Numerical results indicate that the designed dual-function waveform is capable of offering good communication quality of service(QoS)and sensing performance.展开更多
文摘Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first proposed in this paper.Here,a novel four-dimensional fractional-order memristive cellular neural network(FO-MCNN)model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its performance.Then,its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation platforms.Subsequently,it is used toward secure communication application scenarios.Taking it as the pseudo-random number generator(PRNG),a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing(ASR-CS)model.Eventually,the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance.
基金the National Natural Science Foundation of China(52177074).
文摘The escalating deployment of distributed power sources and random loads in DC distribution networks hasamplified the potential consequences of faults if left uncontrolled. To expedite the process of achieving an optimalconfiguration of measurement points, this paper presents an optimal configuration scheme for fault locationmeasurement points in DC distribution networks based on an improved particle swarm optimization algorithm.Initially, a measurement point distribution optimization model is formulated, leveraging compressive sensing.The model aims to achieve the minimum number of measurement points while attaining the best compressivesensing reconstruction effect. It incorporates constraints from the compressive sensing algorithm and networkwide viewability. Subsequently, the traditional particle swarm algorithm is enhanced by utilizing the Haltonsequence for population initialization, generating uniformly distributed individuals. This enhancement reducesindividual search blindness and overlap probability, thereby promoting population diversity. Furthermore, anadaptive t-distribution perturbation strategy is introduced during the particle update process to enhance the globalsearch capability and search speed. The established model for the optimal configuration of measurement points issolved, and the results demonstrate the efficacy and practicality of the proposed method. The optimal configurationreduces the number of measurement points, enhances localization accuracy, and improves the convergence speedof the algorithm. These findings validate the effectiveness and utility of the proposed approach.
基金the National Natural Science Foundation of China(Nos.52073160,62004114 and 62174098)the National Key Research and Development Program of China(Nos.2020YFF01014706 and 2020YFB2008704)+2 种基金Beijing Municipal Science and Technology Commission(Z211100002421012 and Z221100005822011)Tsinghua University Initiative Scientific Research Center(2022Z02ORD008 and 2022Z11QYJ022)TsinghuaFoshan Innovation Special Fund(2021THFS0215)。
文摘As one of the most promising platforms for wireless communication,radiofrequency(RF)electronics have been widely advocated for the development of sensing systems.In particular,monolayer and few-layer two-dimensional(2D)materials exhibiting extraordinary electrical properties not only can be integrated to improve the performance of RF circuits,but also to display exceptional sensing capabilities.This review provides an in-depth perspective of current trends and challenges in the application of 2D materials for RF biochemical sensing,including:(i)theoretical bases to achieve different sensing schemes;(ii)unique properties of 2D materials for reasoning their applications in RF sensing;(iii)developments in 2D RF sensors to facilitate the practice of biochemical sensors with ever-demanding sensitivities,as well as their potential uses in meeting the requirements and challenges of biochemical sensors in the Internet-of-Things era.
文摘Abuja is witnessing an upsurge of victims from Road Traffic Crash (RTC) which is mostly due to the attendant rapid increase in the volume of vehicles, traffic jams, bad driving, over speeding, insufficient road signs and bad conditions of vehicles that ply the roads. The problem is compounded by a lack of early emergency response. Geographic Information System (GIS) based travel time model was applied in the street network analysis to identify RTC black spots that are outside the close reach of Federal Road Safety Commission (FRSC) rescue points/health facilities in Federal Capital City (FCC). Five minutes, Ten minutes and Fifteen minutes travel times were used as the impedance factor. Remote Sensing and GIS techniques were used to carry out network analysis. This was achieved by conducting the closest facility operation in the ArcGIS network analyst extension using the time of travel from each FRSC zebra point location to the RTC black spot zones/health facility. The results were presented on road network maps and bar graphs. The areas where quick response and medical facilities are insufficient were identified. It was concluded that the available health centres can sufficiently service RTC black spots in FCC, but the FRSC zebra points are insufficient which renders rescue operations inefficient and thereby exposes RTC victims to more danger. In order to ensure that there is sufficient coverage for response times, it was suggested that additional zebra points be created.
文摘Intensive aeolian processes occur due to the scarcity of rainfall and lack of vegetation cover in arid regions. The study of recent surface sediments in arid areas is important for environmental assessments, evaluation of natural resources, and land use planning. In this study, two areas were chosen as they show changes in lithology, environment and landforms. The two study areas are Al-Rawdatain in the northern part, and Al-Managish in the southern part of Kuwait. The current study aims to define the sedimentomorphic zones in these areas, with an emphasis on Quaternary geomorphological evolution by providing an integrated approach based on satellite images, topographic maps, field measurements, and laboratory analysis. Remote sensing data were spatially analyzed to classify and detect the temporal changes in the surface sediments and geomorphology based on the field measurements (n = 42) as ground truthing points for supervising the classification. Samples from both areas were collected and subjected to grain size (dry mechanical sieving) and X-Ray Diffraction (XRD) analysis. The resulting data were statistically analyzed for grain size distributions and mineralogy based on the US standard set of sieves. The study found that the Aeolian sand sheet deposits are the most frequent recent surface deposits in Kuwait and cover most of the other sediments. The direction of movement of the sand sheets is from NW towards SE. The mineralogical composition of the aeolian recent surface sediments revealed that they are mostly derived from the Dibdibba Formation and Tigris-Euphrates fluvial terrace deposits. Quartz is the most frequent component of the studied surface sediments in the study areas (66%). The calcite mineral is also found in subordinate amounts in the study areas (10%).
基金National Natural Science Foundation of China(Nos.91738302,91838303)。
文摘With the continuous improvement of the performance and the increasing variety of optical mapping and remote sensing satellites,they have become an important support for obtaining global accurate surveying and mapping remote sensing information.At present,optical mapping and remote sensing satellites already have sub-meter spatial resolution capabilities,but there is a serious lag problem in mapping and remote sensing information services.It is urgent to develop intelligent mapping and remote sensing satellites to promote the transformation and upgrading to real-time intelligent services.Firstly,based on the three imaging systems of the optical mapping and remote sensing satellites and their realization methods and application characteristics,this paper analyzes the applicable system of the intelligent mapping and remote sensing satellites.Further,according to the application requirements of real-time,intelligence,and popularization,puts forward the design concept of integrated intelligent remote sensing satellite integrating communication,navigation,and remote sensing and focuses on the service mode and integrated function composition of intelligent remote sensing satellite.Then expounds on the performance and characteristics of the Luojia-301 satellite,a new generation of intelligent surveying and mapping remote sensing scientific test satellite.And finally summarizes and prospects the development and mission of intelligent mapping remote sensing satellites.Luojia-301 satellite integrates remote sensing and communication functions.It explores an efficient and intelligent service mode of mapping and remote sensing information from data acquisition to the application terminal and provides a real service verification platform for on-orbit processing and real-time transmission of remote sensing data based on space-ground internet,which is of great significance to the construction of China’s spatial information network.
基金supported by the National Key Research and Development Program of China(2022YFB3204700)the National Natural Science Foundation of China(52122513)+2 种基金the Natural Science Foundation of Heilongjiang Province(YQ2021E022)the Natural Science Foundation of Chongqing(2023NSCQ-MSX2286)the Fundamental Research Funds for the Central Universities(HIT.BRET.2021010)。
文摘Single atom catalysts(SACs)have garnered significant attention in the field of catalysis over the past decade due to their exceptional atom utilization efficiency and distinct physical and chemical properties.For the semiconductor-based electrical gas sensor,the core is the catalysis process of target gas molecules on the sensitive materials.In this context,the SACs offer great potential for highly sensitive and selective gas sensing,however,only some of the bubbles come to the surface.To facilitate practical applications,we present a comprehensive review of the preparation strategies for SACs,with a focus on overcoming the challenges of aggregation and low loading.Extensive research efforts have been devoted to investigating the gas sensing mechanism,exploring sensitive materials,optimizing device structures,and refining signal post-processing techniques.Finally,the challenges and future perspectives on the SACs based gas sensing are presented.
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.
基金This work was financially supported by the National Key R&D Program of China(Nos.2021YFF1200700 and 2021YFA0911100)the National Natural Science Foundation of China(Nos.32171399,32171456,and T2225010)+6 种基金the Guangdong Basic and Applied Basic Research Foundation(No.2021A1515012261)the Science and Technology Program of Guangzhou,China(No.202103000076)the Fundamental Research Funds for the Central Universities,Sun Yat-Sen University(No.22dfx02),and Pazhou Lab,Guangzhou(No.PZL2021KF0003)FML would like to thank the National Natural Science Foundation of China(Nos.32171335 and 31900954)JL would like to thank the National Natural Science Foundation of China(No.62105380)the China Postdoctoral Science Foundation(No.2021M693686)QQOY would like to thank the China Postdoctoral Science Foundation(No.2022M713645).
文摘Conventional blood sampling for glucose detection is prone to cause pain and fails to continuously record glucose fluctuations in vivo.Continuous glucose monitoring based on implantable electrodes could induce pain and potential tissue inflammation,and the presence of reactive oxygen species(ROS)due to inflammationmay affect glucose detection.Microneedle technology is less invasive,yet microneedle adhesion with skin tissue is limited.In this work,we developed a microarrow sensor array(MASA),which provided enhanced skin surface adhesion and enabled simultaneous detection of glucose and H_(2)O_(2)(representative of ROS)in interstitial fluid in vivo.The microarrows fabricated via laser micromachining were modified with functional coating and integrated into a patch of a three-dimensional(3D)microneedle array.Due to the arrow tip mechanically interlocking with the tissue,the microarrow array could better adhere to the skin surface after penetration into skin.The MASA was demonstrated to provide continuous in vivo monitoring of glucose and H_(2)O_(2) concentrations,with the detection of H_(2)O_(2) providing a valuable reference for assessing the inflammation state.Finally,the MASA was integrated into a monitoring system using custom circuitry.This work provides a promising tool for the stable and reliable monitoring of blood glucose in diabetic patients.
文摘In this paper, we carry out QoE (Quality of Experience) assessment to investigate influences of olfactory and auditory senses on fairness for a networked virtual 3D object identification game with haptics. In the game, two players try to identify objects which are placed in a shared 3D virtual space. In the assessment, we carry out the game in four cases. Smells and sounds are presented in the first case, only sounds are done in the second case, and only smells are done in the third case. In the last case, we present neither smell nor sound. As a result, we demonstrate that the fairness deteriorates more largely as the difference in conditions between two users becomes larger.
基金This study was supported by the National Natural Science Foundation of China(42271396)the Natural Science Foundation of Shandong Province(ZR2022MD017)+1 种基金the Key R&D Project of Hebei Province(22326406D)The European Space Agency(ESA)and Ministry of Science and Technology of China(MOST)Dragon(57457).
文摘Cereal is an essential source of calories and protein for the global population.Accurately predicting cereal quality before harvest is highly desirable in order to optimise management for farmers,grading harvest and categorised storage for enterprises,future trading prices,and policy planning.The use of remote sensing data with extensive spatial coverage demonstrates some potential in predicting crop quality traits.Many studies have also proposed models and methods for predicting such traits based on multiplatform remote sensing data.In this paper,the key quality traits that are of interest to producers and consumers are introduced.The literature related to grain quality prediction was analyzed in detail,and a review was conducted on remote sensing platforms,commonly used methods,potential gaps,and future trends in crop quality prediction.This review recommends new research directions that go beyond the traditional methods and discusses grain quality retrieval and the associated challenges from the perspective of remote sensing data.
文摘Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into photosynthesis. It is very sensible for factors affecting on vegetation variability such as climate, soils, plant characteristics and human activities. So, it can be used as an indicator of actual and potential trend of vegetation. In this study we used the actual NPP which was derived from MODIS to assess the response of NPP to climate variables in Gadarif State, from 2000 to 2010. The correlations between NPP and climate variables (temperature and precipitation) are calculated using Pearson’s Correlation Coefficient and ordinary least squares regression. The main results show the following 1) the correlation Coefficient between NPP and mean annual temperature is Somewhat negative for Feshaga, Rahd, Gadarif and Galabat areas and weakly negative in Faw area;2) the correlation Coefficient between NPP and annual total precipitation is weakly negative in Faw, Rahd and Galabat areas and somewhat negative in Galabat and Rahd areas. This study demonstrated that the correlation analysis between NPP and climate variables (precipitation and temperature) gives reliably result of NPP responses to climate variables that is clearly in a very large scale of study area.
文摘An innovative complex lidar system deployed on an airborne rotorcraft platform for remote sensing of atmospheric pollution is proposed and demonstrated.The system incorporates integrated-path differential absorption lidar(DIAL) and coherent-doppler lidar(CDL) techniques using a dual tunable TEA CO_(2)laser in the 9—11 μm band and a 1.55 μm fiber laser.By combining the principles of differential absorption detection and pulsed coherent detection,the system enables agile and remote sensing of atmospheric pollution.Extensive static tests validate the system’s real-time detection capabilities,including the measurement of concentration-path-length product(CL),front distance,and path wind speed of air pollution plumes over long distances exceeding 4 km.Flight experiments is conducted with the helicopter.Scanning of the pollutant concentration and the wind field is carried out in an approximately 1 km slant range over scanning angle ranges from 45°to 65°,with a radial resolution of 30 m and10 s.The test results demonstrate the system’s ability to spatially map atmospheric pollution plumes and predict their motion and dispersion patterns,thereby ensuring the protection of public safety.
基金supported by the Major Research Projects of the National Natural Science Foundation of China(92267202)the National Key Research and Development Project(2020YFA0711303)the BUPT Excellent Ph.D.Students Foundation(CX2022208).
文摘Beam management,including initial access(IA)and beam tracking,is essential to the millimeter-wave Unmanned Aerial Vehicle(UAV)network.However,the conventional communicationonly and feedback-based schemes suffer a high delay and low accuracy of beam alignment,since they only enable the receiver to passively“hear”the information of the transmitter from the radio domain.This paper presents a novel sensing-assisted beam management approach,the first solution that fully utilizes the information from the visual domain to improve communication performance.We employ both integrated sensing and communication and computer vision techniques and design an extended Kalman filtering method for beam tracking and prediction.Besides,we also propose a novel dual identity association solution to distinguish multiple UAVs in dynamic environments.Real-world experiments and numerical results show that the proposed solution outperforms the conventional methods in IA delay,association accuracy,tracking error,and communication performance.
基金The authors sincerely appreciate the valuable comments from the anonymous reviewers.The team of Jishunping from Wuhan University is acknowledged for supplying open-source remote sensing data.This research was supported by the Second Tibetan Plateau Scientific Expedition and Research Program(Grant No.2019QZKK0904)the National Natural Science Foundation of China(Grant No.U22A20597).
文摘Landslide disasters comprise the majority of geological incidents on slopes,posing severe threats to the safety of human lives and property while exerting a significant impact on the geological environment.The rapid identification of landslides is important for disaster prevention and control;however,currently,landslide identification relies mainly on the manual interpretation of remote sensing images.Manual interpretation and feature recognition methods are time-consuming,labor-intensive,and challenging when confronted with complex scenarios.Consequently,automatic landslide recognition has emerged as a pivotal avenue for future development.In this study,a dataset comprising 2000 landslide images was constructed using open-source remote sensing images and datasets.The YOLOv7 model was enhanced using data augmentation algorithms and attention mechanisms.Three optimization models were formulated to realize automatic landslide recognition.The findings demonstrate the commendable performance of the optimized model in automatic landslide recognition,achieving a peak accuracy of 95.92%.Subsequently,the optimized model was applied to regional landslide identification,co-seismic landslide identification,and landslide recognition at various scales,all of which showed robust recognition capabilities.Nevertheless,the model exhibits limitations in detecting small targets,indicating areas for refining the deep-learning algorithms.The results of this research offer valuable technical support for the swift identification,prevention,and mitigation of landslide disasters.
基金as part of the Department of Science and Technology (DST), Government of India sponsored research projects titled “Centre of Excellence for Glaciological Research in Western Himalaya”the financial assistance received from the Department under the projects to conduct the research。
文摘Himalayan glaciers are shrinking rapidly,especially after 2000.Glacier shrinkage,however,shows a differential pattern in space and time,emphasizing the need to monitor and assess glacier changes at a larger scale.In this study,changes of 48 glaciers situated around the twin peaks of the Nun and Kun mountains in the northwestern Himalaya,hereafter referred to as Nun-Kun Group of Glaciers(NKGG),were investigated using Landsat satellite data during 2000-2020.Changes in glacier area,snout position,Equilibrium Line Altitude(ELA),surface thickness and glacier velocity were assessed using remote sensing data supplemented by field observations.The study revealed that the NKGG glaciers have experienced a recession of 4.5%±3.4%and their snouts have retreated at the rate of 6.4±1.6 m·a^(-1).Additionally,there was a 41%increase observed in the debris cover area during the observation period.Using the geodetic approach,an average glacier elevation change of-1.4±0.4 m·a^(-1)was observed between 2000 and 2012.The observed mass loss of the NKGG has resulted in the deceleration of glacier velocity from 27.0±3.7 m·a^(-1)in 2000 to 21.2±2.2 m·a^(-1)in 2020.The ELA has shifted upwards by 83.0±22 m during the period.Glacier morphological and topographic factors showed a strong influence on glacier recession.Furthermore,a higher recession of 12.9%±3.2%was observed in small glaciers,compared to 2.7%±3.1%in larger glaciers.The debris-covered glaciers showed lower shrinkage(2.8%±1.1%)compared to the clean glaciers(9.3%±5%).The glacier depletion recorded in the NKGG during the last two decades,if continued,would severely diminish glacial volume and capacity to store water,thus jeopardizing the sustainability of water resources in the basin.
基金supported in part by the National Natural Science Foundation of China under Grant 62271142in part by the Key Research and Development Program of Jiangsu Province BE2023021+2 种基金in part by the Jiangsu Key Research and Development Program Project under Grant BE2023011-2in part by the Young Scholar Funding of Southeast Universityin part by the Fundamental Research Funds for the Central Universities 2242022k60001。
文摘In this paper,we formulate the precoding problem of integrated sensing and communication(ISAC)waveform as a non-convex quadratically constrained quadratic programming(QCQP),in which the weighted sum of communication multi-user interference(MUI)and the gap between dual-use waveform and ideal radar waveform is minimized with peak-toaverage power ratio(PAPR)constraints.We propose an efficient algorithm based on alternating direction method of multipliers(ADMM),which is able to decouple multiple variables and provide a closed-form solution for each subproblem.In addition,to improve the sensing performance in both spatial and temporal domains,we propose a new criteria to design the ideal radar waveform,in which the beam pattern is made similar to the ideal one and the integrated sidelobe level of the ambiguity function in each target direction is minimized in the region of interest.The limited memory Broyden-Fletcher-Goldfarb-Shanno(LBFGS)algorithm is applied to the design of the ideal radar waveform which works as a reference in the design of the dual-function waveform.Numerical results indicate that the designed dual-function waveform is capable of offering good communication quality of service(QoS)and sensing performance.