Gas mixing enhanced by power modulations in atmospheric pressure microwave plasma jet

Microwave plasma jet operating in atmospheric pressure argon was power modulated by audio frequency sine envelope in the 10^2 W power range. Its effluent was imaged using interference filters and ICCD camera for several different phases of the modulating signal. The combination of this fast imaging with spatially resolved optical emission spectroscopy provides useful insights into the plasmachemical processes involved. Phase-resolved schlieren photography was performed to visualize the gas dynamics. The results show that for higher modulation frequencies the plasma chemistry is strongly influenced by formation of transient flow perturbation resembling a vortex during each period. The perturbation formation and speed are strongly influenced by the frequency and power variations while they depend only weakly on the working gas flow rate. From application point of view, the perturbation presence significantly broadened lateral distribution of active species, effectively increasing cross-sectional area suitable for applications

Trellis phase codes for power-bandwith efficient satellite communications

Support work on improved power and spectrum utilization on digital satellite channels was performed. Specific attention is given to the class of signalling schemes known as continuous phase modulation (CPM). The specific work described in this report addresses: analytical bounds on error probability for multi-h phase codes, power and bandwidth characterization of 4-ary multi-h codes, and initial results of channel simulation to assess the impact of band limiting filters and nonlinear amplifiers on CPM performance

Graphene films printable on flexible substrates for sensor applications

Fifteen-layered graphene films have been successfully deposited onto flexible substrates using a commercial ink consisting of graphene particles dispersed in an acrylic polymer binder. A value of 74.9 × 105cm−2 was obtained for the density of defects, primarily located at the flake edges, from the ratio of the D and G Raman peaks located at 1345cm1 and 1575cm1 respectively. 0.5μm thick drop-cast films on interdigitated silver electrodes exhibited Ohmic conduction with a small activation energy of 12meV over the temperature range from 260K to 330K . The photo-thermoelectric effect is believed to be responsible for photoconduction through graphene films under illumination intensity of 10mWm-2 at 270 nm, corresponding to the UV absorption peak. The photo-transient decay at the bias of 1V involves two relaxation processes when the illumination is switched off and values of 8.9 × 103 and 4.3 × 104 are found for the relaxation time constant using the Kohlrauch stretched exponential function analysis.Dr. Indrani Banerjee is grateful to Commonwealth Association, UK for funding the present research work under the fellowship placement scheme (Grant reference INCF-2014-66). The studentship of Ms Faris is partially sponsored by the Air Force Office of Scientific Research, Air Force Material Command, USAF, under Grant No. FA9550-15-1-0123. We are also thankful to Miss V. M. Torrejon of Brunel University for support in computer graphics

Abstract Hidden Markov Models: a monadic account of quantitative information flow

Hidden Markov Models, HMM's, are mathematical models of Markov processes with state that is hidden, but from which information can leak. They are typically represented as 3-way joint-probability distributions. We use HMM's as denotations of probabilistic hidden-state sequential programs: for that, we recast them as `abstract' HMM's, computations in the Giry monad $\mathbb{D}$, and we equip them with a partial order of increasing security. However to encode the monadic type with hiding over some state $\mathcal{X}$ we use $\mathbb{D}\mathcal{X}\to \mathbb{D}^2\mathcal{X}$ rather than the conventional $\mathcal{X}{\to}\mathbb{D}\mathcal{X}$ that suffices for Markov models whose state is not hidden. We illustrate the $\mathbb{D}\mathcal{X}\to \mathbb{D}^2\mathcal{X}$ construction with a small Haskell prototype. We then present uncertainty measures as a generalisation of the extant diversity of probabilistic entropies, with characteristic analytic properties for them, and show how the new entropies interact with the order of increasing security. Furthermore, we give a `backwards' uncertainty-transformer semantics for HMM's that is dual to the `forwards' abstract HMM's - it is an analogue of the duality between forwards, relational semantics and backwards, predicate-transformer semantics for imperative programs with demonic choice. Finally, we argue that, from this new denotational-semantic viewpoint, one can see that the Dalenius desideratum for statistical databases is actually an issue in compositionality. We propose a means for taking it into account

Soft-decision decoding of permutation codes in AWGN and fading channels

A Dissertation submitted in ful llment of the requirements for the degree of Master of Science in the School of Electrical and Information Engineering January, 2017Permutation codes provide the required redundancy for error correction in a noisy communication channel. Combined with MFSK modulation, the outcome produces an e cient system reliable in combating background and impulse noise in the com- munication channel. Part of this can be associated with how the redundancy scales up the amount of frequencies used in transmission. Permutation coding has also shown to be a good candidate for error correction in harsh channels such as the Powerline Communication channel. Extensive work has been done to construct permutation code books but existing decoding algorithms become impractical for large codebook sizes. This is because the algorithms need to compare the received codeword with all the codewords in the codebook used in encoding. This research therefore designs an e cient soft-decision decoder of Permutation codes. The decoder's decision mechanism does not require lookup comparison with all the codewords in the codebook. The code construction technique that derives the codebook is also irrelevant to the decoder. Results compare the decoding algorithm with Hard-decision plus Envelope Detec- tion in the Additive White Gaussian Noise (AWGN) and Rayleigh Fading Channels. The results show that with lesser iterations, improved error correction performance is achieved for high-rate codes. Lower rate codes require additional iterations for signi cant error correction performance. The decoder also requires much less comup- tational complexity compared with existing decoding algorithms.MT201

Spinal codes

Spinal codes are a new class of rateless codes that enable wireless networks to cope with time-varying channel conditions in a natural way, without requiring any explicit bit rate selection. The key idea in the code is the sequential application of a pseudo-random hash function to the message bits to produce a sequence of coded symbols for transmission. This encoding ensures that two input messages that differ in even one bit lead to very different coded sequences after the point at which they differ, providing good resilience to noise and bit errors. To decode spinal codes, this paper develops an approximate maximum-likelihood decoder, called the bubble decoder, which runs in time polynomial in the message size and achieves the Shannon capacity over both additive white Gaussian noise (AWGN) and binary symmetric channel (BSC) models. Experimental results obtained from a software implementation of a linear-time decoder show that spinal codes achieve higher throughput than fixed-rate LDPC codes, rateless Raptor codes, and the layered rateless coding approach of Strider, across a range of channel conditions and message sizes. An early hardware prototype that can decode at 10 Mbits/s in FPGA demonstrates that spinal codes are a practical construction.Massachusetts Institute of Technology (Irwin and Joan Jacobs Presidential Fellowship)Massachusetts Institute of Technology (Claude E. Shannon Assistantship)Intel Corporation (Intel Fellowship

A review of selected topics in physics based modeling for tunnel field-effect transistors

The research field on tunnel-FETs (TFETs) has been rapidly developing in the last ten years, driven by the quest for a new electronic switch operating at a supply voltage well below 1 V and thus delivering substantial improvements in the energy efficiency of integrated circuits. This paper reviews several aspects related to physics based modeling in TFETs, and shows how the description of these transistors implies a remarkable innovation and poses new challenges compared to conventional MOSFETs. A hierarchy of numerical models exist for TFETs covering a wide range of predictive capabilities and computational complexities. We start by reviewing seminal contributions on direct and indirect band-to-band tunneling (BTBT) modeling in semiconductors, from which most TCAD models have been actually derived. Then we move to the features and limitations of TCAD models themselves and to the discussion of what we define non-self-consistent quantum models, where BTBT is computed with rigorous quantum-mechanical models starting from frozen potential profiles and closed-boundary Schr\uf6dinger equation problems. We will then address models that solve the open-boundary Schr\uf6dinger equation problem, based either on the non-equilibrium Green's function NEGF or on the quantum-transmitting-boundary formalism, and show how the computational burden of these models may vary in a wide range depending on the Hamiltonian employed in the calculations. A specific section is devoted to TFETs based on 2D crystals and van der Waals hetero-structures. The main goal of this paper is to provide the reader with an introduction to the most important physics based models for TFETs, and with a possible guidance to the wide and rapidly developing literature in this exciting research field

Energy performances assessment of extruded and 3d printed polymers integrated into building envelopes for a south Italian case study

Plastic materials are increasingly becoming used in the building envelope, despite a lack of investigation on their effects. In this work, an extruded Acrylonitrile-Butadiene-Styrene panel has been tested as a second-skin layer in a ventilated facade system using a full-scale facility. The experimental results show that it is possible to achieve performances very similar to conventional materials. A numerical model has then been developed and used to investigate the performances of plastic and composite polymer panels as second-skin layers. The experimental data has been used to verify the behavior of the numerical model, from a thermal point of view, showing good reliability, with a root mean square error lower than 0.40◦C. This model has then been applied in different refurbishment cases upon varying: The polymer and the manufacturing technology (extruded or 3D-printed panels). Eight refurbishment case studies have been carried out on a typical office building located in Napoli (Italy), by means of a dynamic simulation software. The simulation results show that the proposed actions allow the reduction of the thermal and cooling energy demand (up to 6.9% and 3.1%, respectively), as well as the non-renewable primary energy consumption (up to 2.6%), in comparison to the reference case study

The SOFIA Massive (SOMA) Star Formation Survey. IV. Isolated Protostars

We present similar to 10-40 mu m SOFIA-FORCAST images of 11 isolated protostars as part of the SOFIA Massive (SOMA) Star Formation Survey, with this morphological classification based on 37 mu m imaging. We develop an automated method to define source aperture size using the gradient of its background-subtracted enclosed flux and apply this to build spectral energy distributions (SEDs). We fit the SEDs with radiative transfer models, developed within the framework of turbulent core accretion (TCA) theory, to estimate key protostellar properties. Here, we release the sedcreator python package that carries out these methods. The SEDs are generally well fitted by the TCA models, from which we infer initial core masses M ( c ) ranging from 20-430 M (circle dot), clump mass surface densities sigma(cl) similar to 0.3-1.7 g cm(-2), and current protostellar masses m (*) similar to 3-50 M (circle dot). From a uniform analysis of the 40 sources in the full SOMA survey to date, we find that massive protostars form across a wide range of clump mass surface density environments, placing constraints on theories that predict a minimum threshold sigma(cl) for massive star formation. However, the upper end of the m (*)-sigma(cl) distribution follows trends predicted by models of internal protostellar feedback that find greater star formation efficiency in higher sigma(cl) conditions. We also investigate protostellar far-IR variability by comparison with IRAS data, finding no significant variation over an similar to 40 yr baseline