Human Body Specific Absorption Rate Reduction Employing a Compact Magneto-Dielectric AMC Structure for 5G Massive-MIMO Applications

A compact artificial magnetic conductor (AMC) structure for the application of specific absorption rate (SAR) reduction is presented in this paper. A magneto-dielectric (MD) structure as a host of AMC substrate is used to miniaturize the AMC size. The magneto-dielectric has been designed with a low-profile spiral loop in a way to have a high permittivity and permeability for the desired center frequency of 3.5 GHz. Simulation results confirm the zero-degree reflection phase of the proposed AMC unit cell. Moreover, a 70% reduction has been achieved in comparison to the conventional AMC. To validate the simulation results, a prototype of the board is fabricated and measured with a coplanar waveguide (CPW) antenna for the reflection coefficient. The measurement results display an excellent agreement with the simulation ones. A VOXEL model of a human body is utilized to determine the SAR value of the proposed structure. Considering the maximum SAR value for an average of 10 g human tissue, more than 70% SAR reduction is verified for the CPW antenna with the recommended MD-AMC structure compared to a conventional single CPW antenna.

The influence of layer and voxel geological modelling strategy on groundwater modelling results

Reliable groundwater model predictions are dependent on representative models of the geological environment, which can be modelled using several different techniques. In order to inform the choice of the geological modelling technique, the differences between a layer modelling approach and a voxel modelling approach were analyzed. The layer model consist of stratigraphically ordered surfaces, while the voxel model consist of a structured mesh of volumetric pixels. Groundwater models based on the two models were developed to investigate their impact on groundwater model predictions. The study was conducted in the relatively data-dense area Egebjerg, Denmark, where both a layer model and a voxel model has been developed based on the same data and geological conceptualization. The characteristics of the two methodologies for developing the geological models were shown to have a direct impact on the resulting models. The differences between the layer and the voxel models were however shown to be diverse and not related to larger conceptual elements with few exceptions. The analysis showed that the geological modelling approaches had an influence on preferred parameter values and thereby groundwater model predictions of hydraulic head, groundwater budget terms and particle tracking results. A significance test taking into account the predictive distributions showed that for many predictions the differences between the models were significant. The results suggest that the geological modelling strategy has an influence on groundwater model predictions even if based on the same geological conceptualization.

Integration of Remote Sensing Data into a Composite Voxel Model for Environmental Performance Analysis of Terraced Vineyards in Tuscany, Italy

Understanding socio-ecological systems and the discovery, recovery and adaptation of land knowledge are key challenges for sustainable land use. The analysis of sustainable agricultural systems and practices, for instance, requires interdisciplinary and transdisciplinary research and coordinated data acquisition, data integration and analysis. However, datasets, which are acquired using remote sensing, geospatial analysis and simulation techniques, are often limited by narrow disciplinary boundaries and therefore fall short in enabling a holistic approach across multiple domains and scales. In this work, we demonstrate a new workflow for interdisciplinary data acquisition and integration, focusing on terraced vineyards in Tuscany, Italy. We used multi-modal data acquisition and performed data integration via a voxelised point cloud that we term a composite voxel model. The latter facilitates a multi-domain and multi-scale data-integrated approach for advancing the discovery and recovery of land knowledge. This approach enables integration, correlation and analysis of data pertaining to different domains and scales in a single data structure.

Cutting State Estimation via Chatter Mark on End Milled Surface and Analysis of Its Formation Mechanism Using Voxel Model Simulation

When chatter vibrations occur during cutting, a characteristic pattern called chatter mark appears on the machined surface. In our previous studies, it was estimated that this chatter mark is formed by the tool (or workpiece) vibration in the normal direction with respect to the machined surface. We thus proposed a method to inversely analyze the chatter vibration information during cutting through the chatter mark using two-dimensional discrete Fourier transform. Previous studies confirmed that the analysis results of this method are in good agreement with those of the information obtained via conventional sensing. However, the correctness of the pattern formation mechanism is yet to be directly verified, as it is difficult to measure the cutting phenomenon directly. In this study, the chatter vibration during cutting was measured by the displacement of the tool-shank. Then, based on the results obtained in the static stiffness test, the movement of the tool edge was estimated. A cutting simulation using a voxel model was executed based on this tool-edge movement. When the simulation using the chatter vibration in the normal direction was performed, a chatter mark appeared on the simulated surface. It could thus be confirmed more directly that the analytical model is correct compared with the previous methods.

ESTIMATION OF OPTIMAL CROWN COVERAGE AND CANOPY SHAPE FOR SHADOW ESTIMATION ON TROPICAL MOIST BROADLEAF FOREST

Shadow fraction is essential for improving the estimation of gross primary production, but it is difficult to be observed by satellite due to the diurnal variations. Therefore, it is necessary to estimate the 3D model with physical parameters by simulating virtual forest reflectance. In this study, we aim to estimate the optimal combination of canopy shape and Crown Coverage (CC) through simulating virtual forests reflectance. First, satellite-derived Tree Height (TH) and CC for virtual forests were compared with the ones obtained by Canopy Hight Model (CHM). Second, virtual forests with different CC and canopy shapes were created, and the reflectance and shadow fraction were simulated. The canopy shape used were cylinder, ellipsoid, half-ellipsoid, and inverted half-ellipsoid. Finally, the simulated reflectance and shadow fraction were validated with Sentinel-2 reflectance and shadow fraction from voxel model. Our results show that the mean TH is 15 ± 2 m, and the CC was increased from 10% to 60% in 10% intervals. TH and CC obtained from the satellite had the Root Mean Square Error (RMSE) of 5m and 40%. Ellipsoid with 20% CC shows the lowest RMSE and the smallest discrepancy for shadow fractions at the same sun position. However, other combinations were more accurate in estimating mean daily shadow fraction. This would be caused by only one image adopted in validation, which could be improved by using multi-season images in the future.