Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication toward 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space–air–ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains, including physical layer, network layer, and joint communication, computing, and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.

UAV Communications for 5G and Beyond: Recent Advances and Future Trends

Material issues in additive manufacturing: A review

Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight (LoS) connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication towards 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space-air-ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains including physical layer, network layer, and joint communication, computing and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.

There are 7 categories of additive manufacturing (AM) technologies, and a wide variety of materials can be used to build a CAD 3D object. The present article reviews the main AM processes for polymers for dental applications: stereolithography (SLA), digital light processing (DLP), material jetting (MJ), and material extrusion (ME). The manufacturing process, accuracy, and precision of these methods will be reviewed, as well as their prosthodontic applications.

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Additive Manufacturing Technologies Used for Processing Polymers: Current Status and Potential Application in Prosthetic Dentistry.

Synopsis: From the nostalgic remembrance of the first dynamic flight test this Survey Paper traces several milestones in the history of flight vehicle system identification. A comprehensive account of modern system identification techniques is provided. Several challenging examples bring out the fact that these techniques have reached a high level of maturity, making them a sophisticated and powerful tool not only for research purposes, but also to support the needs of the aircraft industry. This survey paper includes 183 references and provides a consolidated list of publications on the subject.

https://dlr.de/ft/en/portaldata/2/resources/dokumente/ft/jategaonkar/evol_sysid.pdf

Evolution of flight vehicle system identification

In the present work, a process based on the principle of polymer extrusion is developed: the extruder deposition process (EDP). This system uses a screw extruder to deposit the material on a computer-controlled positioning system to build components. Experiments (Box–Behnken technique is used for experimental design) are carried out to study the influence of three process variables: nozzle temperature, chamber temperature and road gap on bond strength (inter-road and interlayer) and surface finish. Surface roughness and ultimate tensile strength values are measured for test specimens. Analysis of variance (ANOVA) is used to determine the significance of process variables. It is concluded that the developed EDP eliminates many of the shortcomings of the systems developed based on the principles of extrusion and produces components having higher bond strength than that achieved in commercial fused deposition modelling (FDM) systems.

Fused deposition modelling using direct extrusion

Microsegregation gets eliminated significantly if subsequent hot working and/or annealing are done on cast products. Macrosegregation however persists, causing problems in quality, and hence, has to be attended to. Microsegregation is a consequence of rejection of solutes by the solid into the interdendritic liquid. Scheil’s equation is mostly employed. However, other equations have been proposed, which take into account diffusion in solid phase and/or incomplete mixing in liquid. Macrosegregation results from movements of microsegregated regions over macroscopic distances due to motion of liquid and free crystals. Motion of impure interdendritic liquid causes regions of positive macrosegregation, whereas purer solid crystals yield negative macrosegregation. Flow of interdendritic liquid is primarily natural convection due to thermal and solutal buoyancy, and partly forced convection due to suction by shrinkage cavity formation etc. The present paper briefly deals with fundamentals of the above and contains some recent studies as well. Experimental investigations in molten alloys do not allow visualization of the complex flow pattern as well as other phenomena, such as dendrite-tip detachment. Experiments with room temperature analogues, and mathematical modelling have supplemented these efforts. However, the complexity of the phenomena demands simplifying assumptions. The agreement with experimental data is mostly qualitative. The paper also briefly discusses centreline macrosegregation during continuous casting of steel, methods to avoid it, and the, importance of early columnar-to-equiaxed transition (CET) as well as the fundamentals of CET.

Segregation in cast products

A recently proposed method (christened ‘ ‘ the Delta method’ ’) of estimating aircraft parameters from e ight data using feed-forward neural networks is applied for the extraction of lateral ‐directional parameters from simulated as well as real-e ight data. The neural network is trained using aircraft motion and control variables as the network inputs and aerodynamic coefe cients as the network outputs; the trained network is used to predict aerodynamic coefe cients for a suitably modie ed input e le. An appropriate interpretation and manipulation of such input ‐output e les yields the estimates of the parameters. Flight data for lateral ‐directional dynamics are analyzed for various combinations and types of control inputs, and suitable control input forms are identie ed for better estimation via the proposed method. Robustness of the method with respect to measurement noise is demonstrated by its applicability to simulated e ight data with pseudomeasurement noise, and to real-e ight data.

Estimation of Aircraft Lateral-Directional Parameters Using Neural Networks

Two new techniques for estimating aircraft stability and control derivatives (parameters) from flight data using feed forward neural networks are proposed. Both techniques use motion variables and control inputs as the input file, while aerodynamic coefficients are presented as the output file for training a neural network. For the purpose of parameter estimation, the trained neural network is presented with a suitably modified input file, and the corresponding predicted output file of aerodynamic coefficients is obtained. Suitable interpretation and manipulation of such input-output files yields the estimated values of the parameters. The methods are validated first on the simulated flight data and then on real flight data obtained by digitising analogue data from a published report. Results are presented to show how the accuracy of the estimates is affected by the topology of the network, the number of iterations and the intensity of the measurement noise in simulated flight data. One of the significant features of the proposed methods is that they do not require guessing of a reasonable set of starting values of the parameters as a popular parameter estimator like the maximum likelihood method does.

Two new techniques for aircraft parameter estimation using neural networks

Coexistence of both magnetic ordering and ferroelectricity (with giant dielectric constant) have been observed for the first time in $\text{Co}{({\text{Fe}}_{1\ensuremath{-}x}{\text{Mo}}_{x})}_{2}{\text{O}}_{4}$. The magnetization of $\text{Co}{({\text{Fe}}_{1\ensuremath{-}x}{\text{Mo}}_{x})}_{2}{\text{O}}_{4}$ ($x$ ranges from 0 to 0.1) was found to increase with doping concentration of Mo. The magnetic properties indicate that Mo goes into the tetrahedral site. The giant dielectric constant may be attributed to the Maxwell-Wagner relaxation mechanism.

Ajoy Kanti Ghosh

Papers

Fused deposition modelling using direct extrusion

Segregation in cast products

Estimation of Aircraft Lateral-Directional Parameters Using Neural Networks

Two new techniques for aircraft parameter estimation using neural networks

Signature of ferroelectricity in magnetically ordered Mo-doped CoFe 2 O 4