Division of Electrical, Communications & Cyber Systems

Experiments at the ionospheric heating facility of the High Frequency Active Auroral Research Program (HAARP) are performed employing dual HF beams amplitude modulated at ELF/VLF with a phase offset between the two modulation waveforms. The amplitude of the observed ELF/VLF waves is strongly dependent on the imposed ELF/VLF phase offset, the modulation waveform, and the orientation of the HF beams. Data from two ground stations are interpreted using simulations of modulated heating power envelopes as well as a comprehensive model of ionospheric ELF/VLF generation. It is found that two colocated vertical beams HF beams excite a single ionospheric ELF/VLF source, but independent ELF/VLF sources can be induced in the ionospheric region above the heater if the HF beams are offset from zenith to intersect at their 3 dB points. Furthermore, the use of two vertical HF beams with ELF phase offset is found to be a potential diagnostic method for the ionospheric D region.

Cyber-physical systems mix digital and analog devices, interfaces, networks, pc systems, and also the like with the natural and unreal physical world. Cyber-physical systems that combine discrete and continuous dynamics are everywhere including automatic or semi-automatic controllers in modern cars, trains, airplanes, ground robots, robotic household appliances, or surgical robots. Cyber–physical systems (CPSs) are considered to be the next generation systems in which computing, communication, and control technologies are firmly integrated. Research on CPSs is fundamentally important for engineered systems in many important application domains such as transportation, energy, medical systems and major investments are being made worldwide to develop the technology. In this paper we are going to discuss about the features of developing cyber physical systems, Design challenges and the application of CPS in automotive domain. Most of the innovation in automotive domain is in electronics and software. All new features in modern cars—like advanced driver assistance systems—are based on electronics and software rather than on mechanical engineering innovations. A modern high-end car has over 100 million lines of code and it is widely believed that this number will continue to grow in the near future. Such code implements different control applications spanning across various functionalities—from safety-critical functions, to driver-assistance and comfort-related ones.

This paper presents a detailed model of devices utilizing many nanotubes and the coupling between them based on the electromagnetic model of a device using one nanotube. Empirical equations are proposed to link the device conductance with the number of nanotubes per device. Then, a circuit model is developed to predict the effect of the number of nanotubes per device on the overall conductance, capacitance, and the frequency response of the device. A prototype structure is fabricated. Its performance is tested and compared with the proposed model, and it shows promising agreements. The model is flexible and can be integrated with quantum transport models.

The 59 articles in this special issue focus on nanosensors for defense and security.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.

These datasets are produced from the Forest Inventory and Analysis database and interpolated values produced by the `forestTIME` R package. For a more detailed description of the methods used, see the documentation for the `forestTIME` package.