A Lite Distributed Semantic Communication System for Internet of Things

The rapid development of deep learning (DL) and widespread applications of Internet-of-Things (IoT) have made the devices smarter than before, and enabled them to perform more intelligent tasks. However, it is challenging for any IoT device to train and run DL models independently due to its limited computing capability. In this paper, we consider an IoT network where the cloud/edge platform performs the DL based semantic communication (DeepSC) model training and updating while IoT devices perform data collection and transmission based on the trained model. To make it affordable for IoT devices, we propose a lite distributed semantic communication system based on DL, named L-DeepSC, for text transmission with low complexity, where the data transmission from the IoT devices to the cloud/edge works at the semantic level to improve transmission efficiency. Particularly, by pruning the model redundancy and lowering the weight resolution, the L-DeepSC becomes affordable for IoT devices and the bandwidth required for model weight transmission between IoT devices and the cloud/edge is reduced significantly. Through analyzing the effects of fading channels in forward-propagation and back-propagation during the training of L-DeepSC, we develop a channel state information (CSI) aided training processing to decrease the effects of fading channels on transmission. Meanwhile, we tailor the semantic constellation to make it implementable on capacity-limited IoT devices. Simulation demonstrates that the proposed L-DeepSC achieves competitive performance compared with traditional methods, especially in the low signal-to-noise (SNR) region. In particular, while it can reach as large as 40x compression ratio without performance degradation.Comment: Accpeted by JSA

Experimental investigation of piloted flameholders

Four configurations of piloted flameholders were tested. The range of flame stabilization, flame propagation, pressure oscillation during ignition, and pressure drop of the configurations were determined. Some tests showed a very strong effect of inlet flow velocity profile and flameholder geometry on flame stabilization. These tests led to the following conclusions. (1) The use of a piloted flameholder in the turbofan augmentor may minimize the peak pressure rise during ignition. At the present experimental conditions, delta P/P asterisk over 2 is less than 10 percent; therefore, the use of a piloted flameholder is a good method to realize soft ignition. (2) The geometry of the piloted flameholder and the amount of fuel injected into the flameholder have a strong effect on the pressure oscillation during ignition of the fuel-air mixture in the secondary zone. (3) Compared with the V-gutter flameholder with holes in its wall, the V-gutter flameholder without holes not only has advantages such as simple structure and good rigidity but offers a wide combustion stability limit and a high capability of igniting the fuel-air mixture of the secondary zone

Generalized Haldane Equation and Fluctuation Theorem in the Steady State Cycle Kinetics of Single Enzymes

Enyzme kinetics are cyclic. We study a Markov renewal process model of single-enzyme turnover in nonequilibrium steady-state (NESS) with sustained concentrations for substrates and products. We show that the forward and backward cycle times have idential non-exponential distributions: \QQ_+(t)=\QQ_-(t). This equation generalizes the Haldane relation in reversible enzyme kinetics. In terms of the probabilities for the forward ($p_+$) and backward ($p_-$) cycles, $k_BT\ln(p_+/p_-)$ is shown to be the chemical driving force of the NESS, $\Delta\mu$. More interestingly, the moment generating function of the stochastic number of substrate cycle $\nu(t)$, follows the fluctuation theorem in the form of Kurchan-Lebowitz-Spohn-type symmetry. When $\lambda$ = $\Delta\mu/k_BT$, we obtain the Jarzynski-Hatano-Sasa-type equality: $\equiv$ 1 for all $t$, where $\nu\Delta\mu$ is the fluctuating chemical work done for sustaining the NESS. This theory suggests possible methods to experimentally determine the nonequilibrium driving force {\it in situ} from turnover data via single-molecule enzymology.Comment: 4 pages, 3 figure

A model for luminescence of localized state ensemble

A distribution function for localized carriers, $f(E,T)=\frac{1}{e^{(E-E_a)/k_BT}+\tau_{tr}/\tau_r}$, is proposed by solving a rate equation, in which, electrical carriers' generation, thermal escape, recapture and radiative recombination are taken into account. Based on this distribution function, a model is developed for luminescence from localized state ensemble with a Gaussian-type density of states. The model reproduces quantitatively all the anomalous temperature behaviors of localized state luminescence. It reduces to the well-known band-tail and luminescence quenching models under certain approximations.Comment: 14 pages, 4 figure