Studies in non-dispersice atomic fluorescence spectrometry

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Performance specifications for a meteorological satellite lidar Final report

Cirrus cloud cover observation capability and performance specifications for meteorological satellite lida

Aerothermodynamic radiation studies

We have built and made operational a 6 in. electric arc driven shock tube which alloys us to study the non-equilibrium radiation and kinetics of low pressure (0.1 to 1 torr) gases processed by 6 to 12 km/s shock waves. The diagnostic system allows simultaneous monitoring of shock radiation temporal histories by a bank of up to six radiometers, and spectral histories with two optical multi-channel analyzers. A data set of eight shots was assembled, comprising shocks in N2 and air at pressures between 0.1 and 1 torr and velocities of 6 to 12 km/s. Spectrally resolved data was taken in both the non-equilibrium and equilibrium shock regions on all shots. The present data appear to be the first spectrally resolved shock radiation measurements in N2 performed at 12 km/s. The data base was partially analyzed with salient features identified

Electrothermal atomisation into a low pressure microwave plasma for trace metal determinations

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Applications of a tunable dye laser for atomic fluoresence spectrometry

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Photoelectrochemical fabrication of spectroscopic diffraction gratings, phase 2

This program was directed toward the production of Echelle diffraction gratings by a light-driven, electrochemical etching technique (photoelectrochemical etching). Etching is carried out in single crystal materials, and the differential rate of etching of the different crystallographic planes used to define the groove profiles. Etching of V-groove profiles was first discovered by us during the first phase of this project, which was initially conceived as a general exploration of photoelectrochemical etching techniques for grating fabrication. This highly controllable V-groove etching process was considered to be of high significance for producing low pitch Echelles, and provided the basis for a more extensive Phase 2 investigation

Antennas and Propagation Aspects for Emerging Wireless Communication Technologies

The increasing demand for high data rate applications and the delivery of zero-latency multimedia content drives technological evolutions towards the design and implementation of next-generation broadband wireless networks. In this context, various novel technologies have been introduced, such as millimeter wave (mmWave) transmission, massive multiple input multiple output (MIMO) systems, and non-orthogonal multiple access (NOMA) schemes in order to support the vision of fifth generation (5G) wireless cellular networks. The introduction of these technologies, however, is inextricably connected with a holistic redesign of the current transceiver structures, as well as the network architecture reconfiguration. To this end, ultra-dense network deployment along with distributed massive MIMO technologies and intermediate relay nodes have been proposed, among others, in order to ensure an improved quality of services to all mobile users. In the same framework, the design and evaluation of novel antenna configurations able to support wideband applications is of utmost importance for 5G context support. Furthermore, in order to design reliable 5G systems, the channel characterization in these frequencies and in the complex propagation environments cannot be ignored because it plays a significant role. In this Special Issue, fourteen papers are published, covering various aspects of novel antenna designs for broadband applications, propagation models at mmWave bands, the deployment of NOMA techniques, radio network planning for 5G networks, and multi-beam antenna technologies for 5G wireless communications

Relating Multimodal Imagery Data in 3D

This research develops and improves the fundamental mathematical approaches and techniques required to relate imagery and imagery derived multimodal products in 3D. Image registration, in a 2D sense, will always be limited by the 3D effects of viewing geometry on the target. Therefore, effects such as occlusion, parallax, shadowing, and terrain/building elevation can often be mitigated with even a modest amounts of 3D target modeling. Additionally, the imaged scene may appear radically different based on the sensed modality of interest; this is evident from the differences in visible, infrared, polarimetric, and radar imagery of the same site. This thesis develops a `model-centric\u27 approach to relating multimodal imagery in a 3D environment. By correctly modeling a site of interest, both geometrically and physically, it is possible to remove/mitigate some of the most difficult challenges associated with multimodal image registration. In order to accomplish this feat, the mathematical framework necessary to relate imagery to geometric models is thoroughly examined. Since geometric models may need to be generated to apply this `model-centric\u27 approach, this research develops methods to derive 3D models from imagery and LIDAR data. Of critical note, is the implementation of complimentary techniques for relating multimodal imagery that utilize the geometric model in concert with physics based modeling to simulate scene appearance under diverse imaging scenarios. Finally, the often neglected final phase of mapping localized image registration results back to the world coordinate system model for final data archival are addressed. In short, once a target site is properly modeled, both geometrically and physically, it is possible to orient the 3D model to the same viewing perspective as a captured image to enable proper registration. If done accurately, the synthetic model\u27s physical appearance can simulate the imaged modality of interest while simultaneously removing the 3-D ambiguity between the model and the captured image. Once registered, the captured image can then be archived as a texture map on the geometric site model. In this way, the 3D information that was lost when the image was acquired can be regained and properly related with other datasets for data fusion and analysis