Window materials for high power gyrotron

The room temperature application of sapphire as window material at higher frequencies is not feasible since its absorption coefficient increases almost linearly with increasing frequency in the millimeter wavelength region. At cryogenic temperature the absorption coefficient value decreases only by a few factors (factor of 2 to 3) in the 90 – 200 GHz region. The earlier reported temperature squared dependence (decrease) in the absorption coefficient or the loss tangent value is totally absent in our broad band continuous wave data we are reporting here (at 6.5 K, 35K, 77K and 300K) and one we reported at conferences earlier. Our results are verified by another technique. We utilize our precision millimeter wave dispersive Fourier transform spectroscopic techniques at room temperature and at cryogenic temperatures The extra high resistivity single crystal compensated silicon is no doubt the lowest loss material available at room temperature in the entire millimeter wavelength region At higher millimeter wave frequencies an extra high resistivity silicon window or an window made with extra high resistivity silicon coated with diamond film would certainly make a better candidate in the future. A single free standing synthetic diamond window seems to have higher absorption coefficient values at millimeter wavelength region at this time although it is claimed that it possesses good mechanical strength and higher thermal conductivity characteristics. It certainly does not rule out the use of diamond film on a single crystal high resistivity silicon to improve its mechanical strength and thermal conductivity     

MC-CDMA with exponential power profile in Nakagami fading channel

A refined study of multi-carrier code division multiple access transmission over a Nakagami fading channel is proposed. The channel power is modeled with an exponential power profile rather than the uniform profile prevalent in other papers. An expression for the bit error rate (BER) is then derived. Numerical results show that MC-CDMA performances depend on the power dispersion of interferers around the desired user power.     

The electrical properties of post-deposition annealed and as-deposited In-doped CdTe thin films

The electrical properties of CdTe thin film have been studied and discussed, including, the conduction mechanism, and the effect of temperature and indium doping on the current passing through the CdTe film and hence on the film conductivity. It is observed that the CdTe film is of the modified Poole–Frenkel conduction mechanism and the resistivity of the film can be lowered by more than one order of magnitude due to indium doping.     

Study of Lateral Spread of Ions Emitted from 2.3 kJ Plasma Focus with Hydrogen and Nitrogen Gases

The characteristics of ion beams of hydrogen and nitrogen with different filling pressures emitted from the plasma focus device of 2.3 kJ energy are investigated. CR-39 SSNTDs are employed for the registration of tracks of ions. The exposed detectors are etched in 6N NaOH solution at 70°C and then examined with an optical microscope. The ion flux is estimated to be of the order of 10^5–6 tracks/cm². The flux with the radial position does not exhibit any regular pattern of variation.     

An incentive scheduling mechanism for peer-to-peer video streaming

P2P video streaming networks are found as a scalable solution and an alternative for traditional client–server based video streaming over the Internet. One of the significant issues affecting the success of any P2P streaming network is cooperation between peers. Practical observations have proved the prevalence of free riders in P2P networks that degrade their performance. To solve this problem, using incentive mechanisms, which encourage peers to contribute more in the network, is necessary. In this paper, we designed and proposed a distributed and scalable incentive mechanism for mesh based P2P video streaming networks. In the proposed approach the contribution of the peers is measured and maintained in a distributed fashion. Furthermore, we proposed an incentive sending side scheduler in which peers are served based on their contribution in the network. Our simulation evaluations show the efficiency of the proposed approach in improving the overall perceived video quality by the non-free rider nodes and consequently in the whole network.     

File size models for shared content over the BitTorrent Peer-to-Peer network

Peer-to-Peer (P2P) traffic has increased rapidly over the past few years, with file sharing providing the main drive behind such traffic. In this work we perform a measurement study of the content shared over the popular BitTorrent P2P file sharing network. We mathematically model the file size distributions of shared files after categorizing them into Audio, Video, Archive and CD image classes. For each of these categories we look into the most popular shared file formats and investigate their file size statistics. This provides an important milestone to building a realistic simulation framework for P2P systems, and for future analytical modeling of P2P networks.     

On the application of Harris hawks optimization (HHO) algorithm to the design of microchannel heat sinks

Engineering with Computers - A novel Harris hawks optimization algorithm is applied to microchannel heat sinks for the minimization of entropy generation. In the formulation of the heat transfer...     

Automatic Channel Detection Using DNN on 2D Seismic Data

Geologists interpret seismic data to understand subsurface properties and subsequently to locate underground hydrocarbon resources. Channels are among the most important geological features interpreters analyze to locate petroleum reservoirs. However, manual channel picking is both time consuming and tedious. Moreover, similar to any other process dependent on human intervention, manual channel picking is error prone and inconsistent. To address these issues, automatic channel detection is both necessary and important for efficient and accurate seismic interpretation. Modern systems make use of real-time image processing techniques for different tasks. Automatic channel detection is a combination of different mathematical methods in digital image processing that can identify streaks within the images called channels that are important to the oil companies. In this paper, we propose an innovative automatic channel detection algorithm based on machine learning techniques. The new algorithm can identify channels in seismic data/images fully automatically and tremendously increases the efficiency and accuracy of the interpretation process. The algorithm uses deep neural network to train the classifier with both the channel and non-channel patches. We provide a field data example to demonstrate the performance of the new algorithm. The training phase gave a maximum accuracy of 84.6% for the classifier and it performed even better in the testing phase, giving a maximum accuracy of 90%.