Joint Beamforming Design for RIS-enabled Integrated Positioning and Communication in Millimeter Wave Systems

Integrated positioning and communication (IPAC) system and reconfigurable intelligent surface (RIS) are both considered to be key technologies for future wireless networks. Therefore, in this paper, we propose a RIS-enabled IPAC scheme with the millimeter wave system. First, we derive the explicit expressions of the time-of-arrival (ToA)-based Cram\'er-Rao bound (CRB) and positioning error bound (PEB) for the RIS-aided system as the positioning metrics. Then, we formulate the IPAC system by jointly optimizing active beamforming in the base station (BS) and passive beamforming in the RIS to minimize the transmit power, while satisfying the communication data rate and PEB constraints. Finally, we propose an efficient two-stage algorithm to solve the optimization problem based on a series of methods such as the exhaustive search and semidefinite relaxation (SDR). Simulation results show that by changing various critical system parameters, the proposed RIS-enabled IPAC system can cater to both reliable data rates and high-precision positioning in different transmission environments

Robust Power Allocation for UAV-aided ISAC Systems with Uncertain Location Sensing Errors

Unmanned aerial vehicle (UAV) holds immense potential in integrated sensing and communication (ISAC) systems for the Internet of Things (IoT). In this paper, we propose a UAV-aided ISAC framework and investigate three robust power allocation schemes. First, we derive an explicit expression of the Cram\'er-Rao bound (CRB) based on time-of-arrival (ToA) estimation, which serves as the performance metric for location sensing. Then, we analyze the impact of the location sensing error (LSE) on communications, revealing the inherent coupling relationship between communication and sensing. Moreover, we formulate three robust communication and sensing power allocation problems by respectively characterizing the LSE as an ellipsoidal distributed model, a Gaussian distributed model, and an arbitrary distributed model. Notably, the optimization problems seek to minimize the CRB, subject to data rate and total power constraints. However, these problems are non-convex and intractable. To address the challenges related to the three aforementioned LSE models, we respectively propose to use the ${\cal{S}}$-Procedure and alternating optimization (${\cal{S}}$-AO) method, Bernstein-type inequality and successive convex approximation (BI-SCA) method, and conditional value-at-risk (CVaR) and AO (CVaR-AO) method to solve these problems. Finally, simulation results demonstrate the robustness of our proposed UAV-aided ISAC system against the LSE by comparing with the non-robust design, and evaluate the trade-off between communication and sensing in the ISAC system

Solution Path Algorithm for Twin Multi-class Support Vector Machine

The twin support vector machine and its extensions have made great achievements in dealing with binary classification problems, however, which is faced with some difficulties such as model selection and solving multi-classification problems quickly. This paper is devoted to the fast regularization parameter tuning algorithm for the twin multi-class support vector machine. A new sample dataset division method is adopted and the Lagrangian multipliers are proved to be piecewise linear with respect to the regularization parameters by combining the linear equations and block matrix theory. Eight kinds of events are defined to seek for the starting event and then the solution path algorithm is designed, which greatly reduces the computational cost. In addition, only few points are combined to complete the initialization and Lagrangian multipliers are proved to be 1 as the regularization parameter tends to infinity. Simulation results based on UCI datasets show that the proposed method can achieve good classification performance with reducing the computational cost of grid search method from exponential level to the constant level

The Sentinel-2 MSI Can Increase the Temporal Resolution of 30m Satellite-Derived LAI Estimates

The successful launch of the European Space Agency (ESA) Sentinel-2A (S2-A) on 23 June 2015 with its MultiSpectral Instrument (MSI) provides an important means to augment Earth-observation capabilities following the legacy of Landsat. After the three-month satellite commissioning campaign, the MSI onboard S-2A is performing very well (ESA, 2015). By 3 December 2015, the sensor data records have achieved provisional maturity status and have been accessed in level-1C Top-Of-Atmosphere (TOA) reflectance by the remote sensing community worldwide. Near-nadir observations by the MSI onboard S-2A and the Operational Land Imager (OLI) onboard Landsat 8 were collected during Simultaneous Nadir Overpasses as well as nearly coincident overpasses. This paper presents a processing chain using harmonized S-2A MSI and Landsat 8 OLI sensors to obtain increased temporal resolution in Leaf Area Index (LAI) estimates using the red-edge band B8A of MSI to replace the NIR band B08. Results demonstrate that LAI estimates from the MSI and OLI are comparable, and, given sufficient preprocessing for atmospheric correction and geometric rectification, can be used interchangeably to improve the frequency with which low LAI canopies can be monitored

Spatial and temporal distribution characteristics and prediction analysis of nitrogen and phosphorus surface source pollution in Shandong Province under the climate and land use changes

The aim of this study was to explore the characteristics of non-point source pollution of nitrogen (N) and phosphorus (P) under the background of climate and land use in Shandong Province. First, using the InVEST NDR module in the model, N and P non-point source pollution in 2010 and 2020 in Shandong Province were simulated; then, based on precipitation data under three different global climate models (MRI-ESM-0, GFDL-ESM4, and Ec-Earth3) and two Shared Socioeconomic Pathways (SSP245 and SSP585), land use data under two Shared Socioeconomic Pathways (SSP245 and SSP585) were used to simulate and predict the non-point source pollution of N and P in Shandong Province in 2030. The results showed the following: (1) On the time scale, the output load and total output of N and P decreased during 2010–2020, while the output load and total output of N and P increased during 2020–2030. (2) On the spatial scale, the spatial distribution of N and P output loads in 2010, 2020, and 2030 is roughly the same, being “low in the northwest and high in the southeast”. (3) Different climate scenarios have a great influence on N and P output load and total output, and the N and P pollution in the SSP585 scenario is more serious. The total output of N and P did not change much in different climate models, while the spatial distribution of the output load of N and P varied significantly, indicating that different climate models had a greater impact on the spatial distribution of the output load of N and P. (4) The overall cold hot spot pattern of nitrogen and phosphorus pollution in Shandong Province is stable, basically showing a “band + cluster + scatter” distribution pattern; the hot spot area in the central and southern region of Shandong Province changes little regardless of the model, the northwest is basically a cold spot area, and the nitrogen and phosphorus hot spot area under the SSP245 scenario in Ec-Earth3 model had the least amount of change. According to research results, combined with the actual situation of Shandong Province, it is hoped that it can provide theoretical basis for the prevention and control of non-point source pollution in Shandong Province in the future

A General Method to Normalize Landsat Reflectance Data to Nadir BRDF Adjusted Reflectance

The Landsat satellites have been providing spectacular imagery of the Earth\u27s surface for over 40 years. However, they acquire images at view angles ±7.5° from nadir that cause small directional effects in the surface reflectance. There are also variations with solar zenith angle over the year that can cause apparent change in reflectance even if the surface properties remain constant. When Landsat data from adjoining paths, or from long time series are used, a model of the surface anisotropy is required to adjust all Landsat observations to a uniform nadir view (primarily for visual consistency, vegetation monitoring, or detection of subtle surface changes). Here a generalized approach is developed to provide consistent view angle corrections across the Landsat archive. While this approach is not applicable for generation of Landsat surface albedo, which requires a full characterization of the surface bidirectional reflectance distribution function (BRDF), or for correction to a constant solar illumination angle across a wide range of sun angles, it provides Landsat nadir BRDF-adjusted reflectance (NBAR) for a range of terrestrial monitoring applications. The Landsat NBAR is derived as the product of the observed Landsat reflectance and the ratio of the reflectances modeled using MODIS BRDF spectral model parameters for the observed Landsat and for a nadir view and fixed solar zenith geometry. In this study, a total of 567 conterminous United States (CONUS) January and July 2010 Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper (ETM+) images that have swath edge overlapping paths sensed in alternating backscatter and forward scattering orientations were used. The average difference between Landsat 5 TM and Landsat 7 ETM+ surface reflectance in the forward and backward scatter directions at the overlapping Landsat scan edges was quantified. The CONUS July view zenith BRDF effects were about 0.02 in the Landsat visible bands, and about 0.03, 0.05 and 0.06, in the 2.1 μm, 1.6 μm and nearinfrared bands respectively. Comparisons of Landsat 5 TM and Landsat 7 ETM+ NBAR derived using MODIS BRDF spectral model parameters defined with respect to different spatial and temporal scales, and defined with respect to different land cover types, were undertaken. The results suggest that, because the BRDF shapes of different terrestrial surfaces are sufficiently similar over the narrow 15° Landsat field of view, a fixed set of MODIS BRDF spectral model parameters may be adequate for Landsat NBAR derivation with little sensitivity to the land cover type, condition, or surface disturbance. A fixed set of BRDF spectral model parameters, derived from a global year of highest quality snow-free MODIS BRDF product values, are provided so users may implement the described Landsat NBAR generation method

Uncertain Multiplicative Language Decision Method Based on Group Compromise Framework for Evaluation of Mobile Medical APPs in China

The mobile medical application (M-medical APP) can optimize medical service process and reduce health management costs for users, which has become an important complementary form of traditional medical services. To assist users including patients choose the ideal M-medical APP, we proposed a novel multiple attribute group decision making algorithm based on group compromise framework, which need not determine the weight of decision-maker. The algorithm utilized an uncertain multiplicative linguistic variable to measure the individual original preference to express the real evaluation information as much as possible. The attribute weight was calculated by maximizing the differences among alternatives. It determined the individual alternatives ranking according to the net flow of each alternative. By solved the 0–1 optimal model with the objective of minimizing the differences between individual ranking, the ultimate group compromise ranking was obtained. Then we took 10 well-known M-medical APPs in Chinese as an example, we summarized service categories provided for users and constructed the assessment system consisting of 8 indexes considering the service quality users are concerned with. Finally, the effectiveness and superiority of the proposed method and the consistency of ranking results were verified, through comparing the group ranking results of 3 similar algorithms. The experiments show that group compromise ranking is sensitive to attribute weight

The Major Factors Causing the Microspore Abortion of Genic Male Sterile Mutant NWMS1 in Wheat (Triticum aestivum L.)

Male sterility is a valuable trait for genetic research and production application of wheat (Triticum aestivum L.). NWMS1, a novel typical genic male sterility mutant, was obtained from Shengnong 1, mutagenized with ethyl methane sulfonate (EMS). Microstructure and ultrastructure observations of the anthers and microspores indicated that the pollen abortion of NWMS1 started at the early uninucleate microspore stage. Pollen grain collapse, plasmolysis, and absent starch grains were the three typical characteristics of the abnormal microspores. The anther transcriptomes of NWMS1 and its wild type Shengnong 1 were compared at the early anther development stage, pollen mother cell meiotic stage, and binucleate microspore stage. Several biological pathways clearly involved in abnormal anther development were identified, including protein processing in endoplasmic reticulum, starch and sucrose metabolism, lipid metabolism, and plant hormone signal transduction. There were 20 key genes involved in the abnormal anther development, screened out by weighted gene co-expression network analysis (WGCNA), including SKP1B, BIP5, KCS11, ADH3, BGLU6, and TIFY10B. The results indicated that the defect in starch and sucrose metabolism was the most important factor causing male sterility in NWMS1. Based on the experimental data, a primary molecular regulation model of abnormal anther and pollen developments in mutant NWMS1 was established. These results laid a solid foundation for further research on the molecular mechanism of wheat male sterility

Hierarchical Coordinated Control Method of In-Wheel Motor Drive Electric Vehicle Based on Energy Optimization

In order to improve the endurance mileage and stability of an electric vehicle at the same time, a hierarchical coordinated control method of an in-wheel motor drive electric vehicle based on energy optimization is presented in this paper. The driving architecture of an in-wheel motor drive electric vehicle is developed, and a corresponding simulation model is established in CarSim software; then, the bicycle model of an electric vehicle is derived from vehicle dynamic equations. The energy-saving feasibility of an in-wheel motor drive electric vehicle is analyzed by a motor efficiency map, and on the basis of this, the hierarchical coordinated control method is proposed to achieve the simultaneous energy optimization control and stability control of the electric vehicle. The results show that the energy consumption is decreased by 32.41%, 45.92%, and 4.07% in different simulation manoeuver cases, and the vehicle stability can be ensured by the proposed control method