A Double Joint Bayesian Approach for J-Vector Based Text-dependent Speaker Verification

J-vector has been proved to be very effective in text-dependent speaker verification with short-duration speech. However, the current state-of-the-art back-end classifiers, e.g. joint Bayesian model, cannot make full use of such deep features. In this paper, we generalize the standard joint Bayesian approach to model the multi-faceted information in the j-vector explicitly and jointly. In our generalization, the j-vector was modeled as a result derived by a generative Double Joint Bayesian (DoJoBa) model, which contains several kinds of latent variables. With DoJoBa, we are able to explicitly build a model that can combine multiple heterogeneous information from the j-vectors. In verification step, we calculated the likelihood to describe whether the two j-vectors having consistent labels or not. On the public RSR2015 data corpus, the experimental results showed that our approach can achieve 0.02\% EER and 0.02\% EER for impostor wrong and impostor correct cases respectively

Computer Simulation of Bioprocess

Bioprocess optimization is important in order to make the bioproduction process more efficient and economic. The conventional optimization methods are costly and less efficient. On the other hand, modeling and computer simulation can reveal the mechanisms behind the phenomenon to some extent, to assist the deep analysis and efficient optimization of bioprocesses. In this chapter, modeling and computer simulation of microbial growth and metabolism kinetics, bioreactor dynamics, bioreactor feedback control will be made to show the application methods and the usefulness of modeling and computer simulation methods in optimization of the bioprocess technology

Patterns and driving forces of dimensionality-dependent charge density waves in 2H-type transition metal dichalcogenides

Two-dimensional (2D) materials have become a fertile playground for the exploration and manipulation of novel collective electronic states. Recent experiments have unveiled a variety of robust 2D orders in highly-crystalline materials ranging from magnetism to ferroelectricity and from superconductivity to charge density wave (CDW) instability. The latter, in particular, appears in diverse patterns even within the same family of materials with isoelectronic species. Furthermore, how they evolve with dimensionality has so far remained elusive. Here we propose a general framework that provides a unfied picture of CDW ordering in the 2H polytype of four isoelectronic transition metal dichalcogenides 2H-MX$_2$ (M=Nb, Ta and X=S, Se). We first show experimentally that whilst NbSe$_2$ exhibits a strongly enhanced CDW order in the 2D limit, the opposite trend exists for TaSe$_2$ and TaS$_2$, with CDW being entirely absent in NbS$_2$ from its bulk to the monolayer. Such distinct behaviours are then demonstrated to be the result of a subtle, yet profound, competition between three factors: ionic charge transfer, electron-phonon coupling, and the spreading extension of the electronic wave functions. Despite its simplicity, our approach can, in essence, be applied to other quasi-2D materials to account for their CDW response at different thicknesses, thereby shedding new light on this intriguing quantum phenomenon and its underlying mechanisms

Measurement method of torsional vibration signal to extract gear meshing characteristics

A technique in measuring torsional vibration signal based on an optical encoder and a discrete wavelet transform is proposed for the extraction of gear meshing characteristics. The method measures the rotation angles of the input and output shafts of a gear pair by using two optical encoders and obtains the time interval sequences of the two shafts. By spline interpolation, the time interval sequences based on uniform angle sampling can be converted into angle interval sequences on the basis of uniform time sampling. The curve of the relative displacement of the gear pair on the meshing line (initial torsional vibration signal) can then be obtained by comparing the rotation angles of the input and output shafts at the interpolated time series. The initial torsional vibration signal is often disturbed by noise. Therefore, a discrete wavelet transform is used to decompose the signal at certain scales; the torsional vibration signal of the gear can then be obtained after filtering. The proposed method was verified by simulation and experimentation, and the results showed that the method could successfully obtain the torsional vibration signal of the gear at a high frequency. The waveforms of the torsional vibration could reflect the meshing characteristics of the teeth. These findings could provide a basis for fault diagnosis of gears

Analysis of batch and repeated fedbatch productions of Candida utilis cell mass using mathematical modeling method

Background: Candida utilis is widely used in bioindustry, and its cell mass needs to be produced in a cost effective way. Process optimization based on the experimental results is the major way to reduce the production cost. However, this process is expensive, time consuming and labor intensive. Mathematical modeling is a useful tool for process analysis and optimization. Furthermore, sufficient information can be obtained with fewer experiments by using the mathematical modeling, and some results can be predicted even without doing experiments. Results: In the present study, we performed the mathematical modeling and simulation for the cell mass production of Candida utilis based on limited batch and repeated fedbatch experiments. The model parameters were optimized using genetic algorithm (GA), and the processes were analyzed. Conclusions: Taken together, this newly developed method is efficient, labor saving and cost effective

Direct fabrication of high-performance high speed steel products enhanced by LaB6

A direct fabrication technology (DFT) without smelting has been developed for fabricating sophisticated high speed steel products with low pollution, near-net shaping and short process. The steel consisting of (wt.%): 6.4W, 5.0Mo, 4.2Cr, 3.1V, 8.5Co and 1.28C, was fabricated as exemplary material. The activated and reactive sintering of green compacts under vacuum with low activation energy, redox reaction enhanced diffusion and the construction of concentration gradient of alloying elements around pores, promotes the nearly full densification (>\ua099.40%). Also, the DFT steels show high purity and superior mechanical properties. Minor strengthening agent LaB (0.1\ua0wt.%), which is easily to be accurately introduced in DFT, obviously increases the hot hardness, temper resistance, bend strength and toughness of DFT M3:2. The strengthening effect of boron atoms and La-rich complexes are proposed to directly result in the high hot hardness and temper resistance of LaB containing steel