A Predictive 6G Network with Environment Sensing Enhancement:From Radio Wave Propagation Perspective

In order to support the future digital society,sixth generation(6G)network faces the challenge to work efficiently and flexibly in a wider range of scenarios.The traditional way of system design is to sequentially get the electromagnetic wave propagation model of typical scenarios firstly and then do the network design by simulation offline,which obviously leads to a 6G network lacking of adaptation to dynamic environments.Recently,with the aid of sensing enhancement,more environment information can be obtained.Based on this,from radio wave propagation perspective,we propose a predictive 6G network with environment sensing enhancement,the electromagnetic wave propagation characteristics prediction enabled network(EWave Net),to further release the potential of 6G.To this end,a prediction plane is created to sense,predict and utilize the physical environment information in EWave Net to realize the electromagnetic wave propagation characteristics prediction timely.A two-level closed feedback workflow is also designed to enhance the sensing and prediction ability for EWave Net.Several promising application cases of EWave Net are analyzed and the open issues to achieve this goal are addressed finally.

Computer-Vision Based Object Detection and Recognition for Service Robot in Indoor Environment

The near future has been envisioned as a collaboration of humans with mobile robots to help in the day-to-day tasks.In this paper,we present a viable approach for a real-time computer vision based object detection and recognition for efficient indoor navigation of a mobile robot.The mobile robotic systems are utilized mainly for home assistance,emergency services and surveillance,in which critical action needs to be taken within a fraction of second or real-time.The object detection and recognition is enhanced with utilization of the proposed algorithm based on the modification of You Look Only Once(YOLO)algorithm,with lesser computational requirements and relatively smaller weight size of the network structure.The proposed computer-vision based algorithm has been compared with the other conventional object detection/recognition algorithms,in terms of mean Average Precision(mAP)score,mean inference time,weight size and false positive percentage.The presented framework also makes use of the result of efficient object detection/recognition,to aid the mobile robot navigate in an indoor environment with the utilization of the results produced by the proposed algorithm.The presented framework can be further utilized for a wide variety of applications involving indoor navigation robots for different services.

Femtosecond laser fabrication of nanograting-based distributed fiber sensors for extreme environmental applications

The femtosecond laser has emerged as a powerful tool for micro-and nanoscale device fabrication. Through nonlinear ionization processes, nanometer-sized material modifications can be inscribed in transparent materials for device fabrication. This paper describes femtosecond precision inscription of nanograting in silica fiber cores to form both distributed and point fiber sensors for sensing applications in extreme environmental conditions. Through the use of scanning electron microscope imaging and laser processing optimization,high-temperature stable, Type II femtosecond laser modifications were continuously inscribed,point by point, with only an insertion loss at 1 d B m~(-1) or 0.001 d B per point sensor device.High-temperature performance of fiber sensors was tested at 1000℃, which showed a temperature fluctuation of ±5.5℃ over 5 days. The low laser-induced insertion loss in optical fibers enabled the fabrication of a 1.4 m, radiation-resilient distributed fiber sensor. The in-pile testing of the distributed fiber sensor further showed that fiber sensors can execute stable and distributed temperature measurements in extreme radiation environments. Overall, this paper demonstrates that femtosecond-laser-fabricated fiber sensors are suitable measurement devices for applications in extreme environments.

Antenna design for a massive multiple input environmental sensor network

This article describes the design and simulation of a pair of antennas on a small PCB with minimal coupling for a massive multiple input sensor network. The two antennas are planar inverted-F antennas （PIFA） that are fed with microstrip feed lines. The critical design factors are minimizing mass while creating ISM band and GPS L1 band antennas and developing data transmission schemes for maximum usage of all communication channels. The designed board is a 60 mm diameter, 0.6 mm thick circular FR4 board that weighs approximately 5 g.

APPLICATIONS OF REMOTE SENSING IN ENVIRONMENTAL INVESTIGATION AND CHANGE ANALYSIS IN THE THREE GORGES AREA

1. INTRODUCTION The proposed Three Gorges Project, one of the biggest hydroelectric projects in the world, will dam the middle reaches of the Changjiang (Yangtze) River, the third longest river in the world, and form a large reservoir. Its impacts on environment have attracted wide attention. Entrusted by National Scientific-Technical Commission, the Chinese Academy of Sciences (CAS) was in charge of a research project on this issuse from 1984 to 1989. Tho use of remote sensing played an important role in the project considering the study area is mountainous and not convenientlv located, which makes it difficult to conduct the research onlv using conventional means.

REMOTE SENSING FOR ENVIRONMENTAL MONITORING IN GUANGZHOU

The comprehensive investigation of aerial remote sensing in Guangzhou was a systematic project to meet the needs of urban construction, planning and management, and environmental protection by the remote sensing technique. The project was consisted of five parts, i.e., urban geology, natural resources, urban developing state, urban environment and a series of remote sensing mapping. This paper shows the ways to monitor the environment of Guanzhou by the aerial remote sensing technique.

Creating Optimal Language Learning Environment

From the viewpoint of psycholinguistics, this paper concerns how to create an optimal language learning environment in language learning, to stimulate students enthusiasm to participate in classroom activities and to make language learning easier and more pleasant.

APPLICATION OF REMOTE SENSING IN THE ANALYSIS OF WATER ENVIRONMENT IN ZHUJIANG RIVER ESTUARY

1. PREFACE Lingdingyang is a trumpet estuary. It accepts the runoff of the Dongjiang River, the Beijiang River, the Zhengjiang River and the Liusihe River. It also accepts a part of the runoff of the Xijiang River. Its mean year runoff is 1.742×10" M^3. In resent ten years, industry and agriculture are developing rapidly in Guangzhou City, Dongguan City, Zhongshan City, Shunde County, Panyu County. Lingdingyang’s pollution is increesing. Water quality of lingdingyang is steadily deteriorated. In order to investigate the situation of water environment of Lingdingyang, we study its static environmental capacity of nitrogen and phosphorus. LANDSAT imageries are used in the study. The concentrations of nitrogen and phosphorous is detected by convention method.

Applications of Satellite Remote Sensing Technology in China's Environmental Monitoring

The environmental conditions in China are still very serious. In the years to come, the mission for environmental treatment and protection, supervision,

Visible Light Communication for Vehicular Applications: A Novel Architecture with Proof-of-Concept Prototype

When there is an increasing interest in visible light communication(VLC), outdoor vehicle VLC has emerged as a promising candidate technology for future intelligent transportation systems. However, in VLC based vehicular applications, several challenges impede successful commercial application of VLC based products. This article first provides a thorough overview of the existing challenges. To overcome these challenges, we propose a novel architecture with tracking and environment sensing ability for practical vehicular applications. Moreover, a proof-ofconcept prototype is implemented to validate the feasibility of the proposed system. Experimental and simulation results show that the proposed VLC system can provide reliable communications with a bit-error rate less than 10-4for vehicles under strong interference lights. Finally, based on the evaluations, we propose some key design issues for future studies in this research area.

Review of the field environmental sensing methods based on multi-sensor information fusion technology

Field environmental sensing can acquire real-time environmental information,which will be applied to field operation,through the fusion of multiple sensors.Multi-sensor fusion refers to the fusion of information obtained from multiple sensors using more advanced data processing methods.The main objective of applying this technology in field environment perception is to acquire real-time environmental information,making agricultural mechanical devices operate better in complex farmland environment with stronger sensing ability and operational accuracy.In this paper,the characteristics of sensors are studied to clarify the advantages and existing problems of each type of sensors and point out that multiple sensors can be introduced to compensate for the information loss.Secondly,the mainstream information fusion types at present are outlined.The characteristics,advantages and disadvantages of different fusion methods are analyzed.The important studies and applications related to multi-sensor information fusion technology published at home and abroad are listed.Eventually,the existing problems in the field environment sensing at present are summarized and the prospect for future of sensors precise sensing,multi-dimensional fusion strategies,discrepancies in sensor fusion and agricultural information processing are proposed in hope of providing reference for the deeper development of smart agriculture.

Projecting distributions of Argentine shortfin squid(Illex argentinus)in the Southwest Atlantic using a complex integrated model

We developed an approach that integrates generalized additive model（GAM） and neural network model（NNM）for projecting the distribution of Argentine shortfin squid（Illex argentinus）. The data for this paper was based on commercial fishery data and relevant remote sensing environmental data including sea surface temperature（SST）, sea surface height（SSH） and chlorophyll a（Chl a） from January to June during 2003 to 2011. The GAM was used to identify the significant oceanographic variables and establish their relationships with the fishery catch per unit effort（CPUE）. The NNM with the GAM identified significant variables as input vectors was used for predicting spatial distribution of CPUE. The GAM was found to explain 53.8% variances for CPUE. The spatial variables（longitude and latitude） and environmental variables（SST, SSH and Chl a） were significant. The CPUE had nonlinear relationship with SST and SSH but a linear relationship with Chl a. The NNM was found to be effective and robust in the projection with low mean square errors（MSE） and average relative variances（ARV）.The integrated approach can predict the spatial distribution and explain the migration pattern of Illex argentinus in the Southwest Atlantic Ocean.

A New model to forecast fishing ground of Scomber japonicus in the Yellow Sea and East China Sea

The pelagic species is closely related to the marine environmental factors, and establishment of forecasting model of fishing ground with high accuracy is an important content for pelagic fishery. The chub mackerel（Scomber japonicus） in the Yellow Sea and East China Sea is an important fishing target for Chinese lighting purse seine fishery. Based on the fishery data from China＇s mainland large-type lighting purse seine fishery for chub mackerel during the period of 2003 to 2010 and the environmental data including sea surface temperature（SST）, gradient of the sea surface temperature（GSST）, sea surface height（SSH） and geostrophic velocity（GV）, we attempt to establish one new forecasting model of fishing ground based on boosted regression trees. In this study, the fishing areas with fishing effort is considered as one fishing ground, and the areas with no fishing ground are randomly selected from a background field, in which the fishing areas have no records in the logbooks. The performance of the forecasting model of fishing ground is evaluated with the testing data from the actual fishing data in 2011. The results show that the forecasting model of fishing ground has a high prediction performance, and the area under receiver operating curve（AUC） attains 0.897. The predicted fishing grounds are coincided with the actual fishing locations in 2011, and the movement route is also the same as the shift of fishing vessels, which indicates that this forecasting model based on the boosted regression trees can be used to effectively forecast the fishing ground of chub mackerel in the Yellow Sea and East China Sea.

The spatial relationship between salt marsh vegetation patterns,soil elevation and tidal channels using remote sensing at Chongming Dongtan Nature Reserve, China

The analysis of vegetation-environment relationships has always been a study hotspot in ecology. A number of biotic, hydrologic and edaphic factors have great influence on the distribution of macrophytes within salt marsh.Since the exotic species Spartina alterniflora（S. alterniflora） was introduced in 1995, a rapid expansion has occurred at Chongming Dongtan Nature Reserve（CDNR） in the Changjiang（Yangtze） River Estuary, China.Several important vegetation-environment factors including soil elevation, tidal channels density（TCD）,vegetation classification and fractional vegetation cover（FVC） were extracted by remote sensing method combined with field measurement. To ignore the details in interaction between biological and physical process,the relationship between them was discussed at a large scale of the whole saltmarsh. The results showed that Scirpus mariqueter（S. mariqueter） can endure the greatest elevation variance with 0.33 m throughout the marsh in CDNR. But it is dominant in the area less than 2.5 m with the occurrence frequency reaching 98%. S. alterniflora has usually been found on the most elevated soils higher than 3.5 m but has a narrow spatial distribution. The rapid decrease of S. mariqueter can be explained by stronger competitive capacity of S. alterniflora on the high tidal flat. FVC increases with elevation which shows significant correlation with elevation（r=0.30, p〈0.001）. But the frequency distribution of FVC indicates that vegetation is not well developed on both elevated banks near tidal channels from the whole scale mainly due to tidal channel lateral swing and human activities. The significant negative correlation（r=–0.20, p〈0.001） was found between FVC and TCD, which shows vegetation is restricted to grow in higher TCD area corresponding to lower elevation mainly occupied by S. mariqueter communities. The maximum occurrence frequency of this species reaches to 97% at the salt marsh with TCD more than 8 m/m2.

A Review on Electrospinning as Versatile Supports for Diverse Nanofibers and Their Applications in Environmental Sensing

Rapid industrialization is accompanied by the deterioration of the natural environment.The deepening crisis associated with the ecological environment has garnered widespread attention toward strengthening environmental monitoring and protection.Environmental sensors are one of the key technologies for environmental monitoring,ultimately enabling environmental protection.In recent decades,micro/nanomaterials have been widely studied and applied in environmental sensing owing to their unique dimensional properties.Electrospinning has been developed and adopted as a facile,quick,and effective technology to produce continuous micro-and nanofiber materials.The technology has advanced rapidly and become one of the hotspots in the field of nanomaterials research.Environmental sensors made from electrospun nanofibers possess many advantages,such as having a porous structure and high specific surface area,which effectively improve their performance in environmental sensing.Furthermore,by introducing functional nanomaterials(carbon nanotubes,metal oxides,conjugated polymers,etc.)into electrospun fibers,synergistic effects between different materials can be utilized to improve the catalytic activity and sensitivity of the sensors.In this review,we aimed to outline the progress of research over the past decade on electrospinning nanofibers with different morphologies and functional characteristics in environmental sensors.

Tuning on passive interfacial cooling of covalent organic framework hydrogel for enhancing freshwater and electricity generation

Developing an efficient freshwater and electricity co-generation device(FECGD)can solve the shortage of freshwater and electricity.However,the poor salt resistance and refrigeration properties of the materials for FECGD put big challenges in the efficient and stable operation of these devices.To address these issues,we propose the covalent organic framework(COF)confined co-polymerization strategy to prepare COF-modified acrylamide cationic hydrogels(ACH-COF),where hydrogen bonding interlocking between negatively charged polymer chains and COF pores can form a salt resistant hydrogel for stabilizing tunable passive interfacial cooling(TPIC).The FECPDs based on the TPIC and salt resistance of ACH-COF display a maximum output power density of 2.28 W m-2,which is 4.3 times higher than that of a commercial thermoelec-tric generator under one solar radiation.The production rate of freshwater can reach 2.74 kg m-2 h-1.Our results suggest that the high efficiency and scala-bility of the FECGD can hold the promise of alleviating freshwater and power shortages.

(Super)paramagnetic nanoparticles as platform materials for environmental applications: From synthesis to demonstration

Over the past few decades,engineered,(super)paramagnetic nanoparticles have drawn extensive research attention for a broad range of applications based on their tunable size and shape,surface chemistries,and magnetic properties.This review summaries our recent work on the synthesis,surface modification,and environmental application of(super)paramagnetic nanoparticles.By utilizing high-temperature thermo-decomposition methods,first,we have broadly demonstrated the synthesis of highly monodispersed,(super)paramagnetic nanoparticles,via the pyrolysis of metal carboxylate salts in an organic phase.Highly uniform magnetic nanoparticles with various size,composition,and shape can be precisely tuned by controlled reaction parameters,such as the initial precursors,heating rate,final reaction temperature,reaction time,and the additives.These materials can be further rendered water stable via functionalization with surface mono/bi-layer coating structure using a series of tunable ionic/non-ionic surfactants.Finally,we have demonstrated platform potential of these materials for heavy metal ions sensing,sorption,and separation from the aqueous phase.

An Indoor Environment Sensing and Localization System via mmWave Phased Array

In this paper,an indoor layout sensing and localization system with testbed in the 60-GHz millimeter wave(mmWave)band,named mmReality,is elaborated.The mmReality system consists of one transmitter and one mobile receiver,both with a phased array and a single radio frequency(RF)chain.To reconstruct the room layout,the pilot signal is delivered from the transmitter to the receiver via different pairs of transmission and receiving beams,so that multipath signals in all directions can be captured.Then spatial smoothing and the two-dimensional multiple signal classification(MUSIC)algorithm are applied to detect the angle-of-departures(AoDs)and angle-of-arrivals(AoAs)of propagation paths.Moreover,the technique of multi-carrier ranging is adopted to measure the path lengths.Therefore,with the measurements of the receiver in different locations of the room,the receiver and virtual transmitters can be pinpointed to reconstruct the room layout.Experiments show that the reconstructed room layout can be utilized to localize a mobile device via the AoA spectrum.

Multimodal fiber antenna for proximity and stress sensing

Fiber sensors are commonly used to detect environmental,physiological,optical,chemical,and biological factors.Thermally drawn fibers offer numerous advantages over other commercial products,including enhanced sensitivity,accuracy,improved functionality,and ease of manufacturing.Multimaterial,multifunctional fibers encapsulate essential internal structures within a microscale fiber,unlike macroscale sensors requiring separate electronic components.The compact size of fiber sensors enables seamless integration into existing systems,providing the desired functionality.We present a multimodal fiber antenna monitoring,in real time,both the local deformation of the fiber and environmental changes caused by foreign objects in proximity to the fiber.Time domain reflectometry propagates an electromagnetic wave through the fiber,allowing precise determination of spatial changes along the fiber with exceptional resolution and sensitivity.Local changes in impedance reflect fiber deformation,whereas proximity is detected through alterations in the evanescent field surrounding the fiber.The fiber antenna operates as a waveguide to detect local deformation through the antisymmetric mode and environmental changes through the symmetric mode.This multifunctionality broadens its application areas from biomedical engineering to cyber-physical interfacing.In antisymmetric mode,the device can sense local changes in pressure,and,potentially,temperature,pH,and other physiological conditions.In symmetric mode,it can be used in touch screens,environmental detection for security,cyber-physical interfacing,and human-robot interactions.

三江源及其毗邻地区公里网格降水数据集(2009-2013)

三江源及其毗邻地区公里网格降水数据集(2009-2013)是对2009-2013年的TRMM3B43V7降水数据进行降尺度后生成的该区域降水数据及其相关对照或辅助数据。其中,降尺度后的TRMM数据是基于山地降水二次抛物型廓线(Quadratic Parabolic Profile,QPP)模型生成的。该方法包括两个步骤:(1)推算QPP模型参数。三江源及其毗邻地区的最大降水海拔和NDVI峰值海拔高度是对应的,因此,利用NDVI峰值所在空间位置来确定最大降水海拔,进而基于最大降水海拔推算该位置的降水量和降水抛物线方程的二次项系数。(2)模型参数空间外推。利用反距离权重(IDW)插值法对0.25°尺度参数进行空间外推,当从0.25°重采样到1 km分辨率时,则采用二次线性插值法获取各个像元降尺度模型的最终参数。结果表明,基于QPP模型降尺度后的TRMM3B43数据精度相对常用统计降尺度方法得到的结果精度更高,2009-2013年生长季(5-9月)逐月以及累积降水量降尺度结果用国家站观测数据计算的平均均方根误差(Root Mean Square Error,RMSE)为14、18、19、13、16和62 mm,平均绝对百分误差(Mean Absolute Percent Error,MAPE)为14%、12%、12%、12%、17%和11%。数据集采用WGS84坐标系,矢量数据采用.shp格式存储,栅格数据采用.grid或.tif格式存储。与数据集相关的科学发现论文已发表在《Remote Sensing of Environment》2018年第215卷。