Simplified supervised i-vector modeling with application to robust and efficient language identification and speaker verification

This paper presents a simplified and supervised i-vector modeling approach with applications to robust and efficient language identification and speaker verification. First, by concatenating the label vector and the linear regression matrix at the end of the mean supervector and the i-vector factor loading matrix, respectively, the traditional i-vectors are extended to label-regularized supervised i-vectors. These supervised i-vectors are optimized to not only reconstruct the mean supervectors well but also minimize the mean square error between the original and the reconstructed label vectors to make the supervised i-vectors become more discriminative in terms of the label information. Second, factor analysis (FA) is performed on the pre-normalized centered GMM first order statistics supervector to ensure each gaussian component's statistics sub-vector is treated equally in the FA, which reduces the computational cost by a factor of 25 in the simplified i-vector framework. Third, since the entire matrix inversion term in the simplified i-vector extraction only depends on one single variable (total frame number), we make a global table of the resulting matrices against the frame numbers’ log values. Using this lookup table, each utterance's simplified i-vector extraction is further sped up by a factor of 4 and suffers only a small quantization error. Finally, the simplified version of the supervised i-vector modeling is proposed to enhance both the robustness and efficiency. The proposed methods are evaluated on the DARPA RATS dev2 task, the NIST LRE 2007 general task and the NIST SRE 2010 female condition 5 task for noisy channel language identification, clean channel language identification and clean channel speaker verification, respectively. For language identification on the DARPA RATS, the simplified supervised i-vector modeling achieved 2%, 16%, and 7% relative equal error rate (EER) reduction on three different feature sets and sped up by a factor of more than 100 against the baseline i-vector method for the 120 s task. Similar results were observed on the NIST LRE 2007 30 s task with 7% relative average cost reduction. Results also show that the use of Gammatone frequency cepstral coefficients, Mel-frequency cepstral coefficients and spectro-temporal Gabor features in conjunction with shifted-delta-cepstral features improves the overall language identification performance significantly. For speaker verification, the proposed supervised i-vector approach outperforms the i-vector baseline by relatively 12% and 7% in terms of EER and norm old minDCF values, respectively.     

Robust numerical approach to steady-state calibration of mean-value models

A numerically robust approach to steady-state calibration of nonlinear dynamic models is presented. The approach is based on explicit formulation of the constraints on validity of internal model signals by set of inequalities. The constrained optimization with feasible iterates guarantees that the model will never be evaluated with invalid internal signals. This overcomes numerical difficulties often encountered when dealing with highly nonlinear models. Because the approach uses a large number of slack variables, distributed least squares algorithm is proposed. The robustness of this approach is demonstrated on a steady-state calibration of turbocharged diesel engine model starting from grossly inaccurate initial estimates.     

防爆电梯防爆安全危险辨识及对策分析

依据防爆电梯检验标准和现场检验案例，统计归纳了工业领域在用防爆电梯防爆安全存在的问题和隐患，并分析了防爆电梯安全隐患的特点及成因。在此基础上从防爆电梯的防爆等级选型、安装与监督检验、在用防爆电梯维护与保养等环节提出了相应的安全技术与管理措施。     

Model predictive control suitable for closed-loop re-identification

The main problem of a closed-loop re-identification procedure is that, in general, the dynamic control and identification objectives are conflicting. In fact, to perform a suitable identification, a persistent excitation of the system is needed, while the control objective is to stabilize the system at a given equilibrium point. However, a generalization of the concept of stability, from punctual stability to (invariant) set stability, allows for a flexibility that can be used to avoid the conflict between these objectives. Taking into account that an invariant target set includes not only a stationary component, but also a transient one, the system could be excited without deteriorating the stability of the closed-loop. In this work, a MPC controller is proposed that ensures the stability of invariant sets at the same time that a signal suitable for closed-loop re-identification is generated. Several simulation results show the propose controller formulation properties.     

Benchmark problems for nonlinear system identification and control using Soft Computing methods: Need and overview

Using benchmark problems to demonstrate and compare novel methods to the work of others could be more widely adopted by the Soft Computing community. This article contains a collection of several benchmark problems in nonlinear control and system identification, which are presented in a standardized format. Each problem is augmented by examples where it has been adopted for comparison. The selected examples range from component to plant level problems and originate mainly from the areas of mechatronics/drives and process systems. The authors hope that this overview contributes to a better adoption of benchmarking in method development, test and demonstration.     

Mathematical modelling and parameter identification of a stainless steel annealing furnace

A new, comprehensive mathematical model of continuous annealing furnaces is developed, under consideration of both the radiative and convective heat transfer of the furnace components. Based on measured normal operating data from an industrial stainless steel plant, parameter identification is basically carried out using a nonlinear least-squares optimization algorithm for the whole annealing furnace, to estimate optimal values of uncertain parameters, such as emissivities. Due to the complexity of the model, a sequential approach for parameter identification is proposed and implemented, i.e. the parameter set is divided into different subsets, and the parameter estimation is carried out sequentially in several steps and iterations. The performance of the model with the estimated parameters is then evaluated on a different test data set. It is shown that the obtained model can predict temperature evolutions along the furnace in good agreement to measured data, under both steady-state and transient conditions. The presented model is suitable for controller design and process optimization.     

基于软件身份标签的安全性研究

当前,由于软件发行商通常不为应用程序和可执行文件（程序文件,共享库,脚本等）提供用以验证其可靠性的关键信息,所以计算机管理员想要自动辨别这些文件是否被第三方修改过变得十分困难.通过与民航飞行的安全性要求进行类比,分析了软件身份标签如何从身份鉴别、应用关联、防止篡改和未知威胁这四方面改善软件的安全性.     

Italian market fish species identification and commercial frauds revealing by DNA sequencing

To guarantee consumers about the security of what they eat is the main goal of all the institutions working to assure food safety. In seafood field it appears of prime importance to be able to identify fish species throughout the production cycle also when the product has been already processed (breaded fish, fillets etc). In this context the latest system proposed for species identification is the so called “DNA-Barcoding”, made by carrying out the DNA sequencing of a standard barcode region. In the present study we carried out bi-directional sequence analysis of mitochondrial cytochrome b gene (Cytb) and cytochrome oxidase subunit I gene (COI). The main goal of the research was to unambiguously classify the most common fishes traded in Italy, being able to ascertain possible labeling frauds made substituting value species with less precious ones. With both genes we could correctly identify almost all the samples in study: respectively 58/58 with COI and 56/58 with Cytb. This study confirms mitochondrial genes Cytb and COI as good candidates for fish species identification by DNA sequencing. This method appears particularly suitable especially when morphological characterization is difficult, (for very close species), or impossible (for transformed foodstuffs) to carry out. What's more we could efficiently identify many fishes belonging to the Mediterranean fauna, which, to our knowledge, underwent for the first time this kind of analysis. Further development will concern the extension of the analysis to a largest number of local species.     

Parameter identification of proton exchange membrane fuel cell via Levenberg-Marquardt backpropagation algorithm

It is essential to develop an accurate model of proton exchange membrane fuel cell (PEMFC) for a reliable operation and analysis, in which unknown parameters usually need to be determined. The inherent nonlinear, strong coupling, and diversification of PEMFC model seriously hinder traditional methods to identify the parameters. For the sake of overcoming these thorny obstacles, Levenberg-Marquardt backpropagation (LMBP) algorithm based on artificial neural networks (ANNs) is proposed for PEMFC parameter identification. Furthermore, the performance of LMBP is thoroughly evaluated and compared with four typical meta-heuristic algorithms under three cases. Simulation results indicate that LMBP performs a higher accuracy and faster speed for parameter identification. In particular, accuracy and convergence speed can achieve as much as 99.8% and 95.9% growth via LMBP, respectively.     

Stability and antioxidant activity of anthocyanins from purple sweet potato (Ipomoea batatas L. cultivar Eshu No. 8) subjected to simulated in vitro gastrointestinal digestion

The study was aimed to investigate the stability and antioxidant activities of anthocyanins obtained from purple sweet potato via an in vitro digestion system. Three fractions of anthocyanin-rich extracts were obtained via ODS packing column. Anthocyanins and copigment (primary phenolic acids) of fraction 2 were investigated during simulated an in vitro gastrointestinal digestion. Anthocyanins and copigment were recognised by UPLC-LTQ-MS/MS. Besides, anthocyanins were found effectively stable under the acidic gastric digestion conditions. However, the anthocyanins recovery was greatly decreased at around 10% after intestinal digestion. An association between the type, number of acylated group and stability to intestinal digestion was found. Di-acylated anthocyanins possessed higher stability compared with mono-acylated anthocyanins and the stability of acylated group in digestion process followed the order of p-hydroxybenzoyl > feruloyl > caffeoyl. However, there was no much difference in copigment content which was found during digestion process. Moreover, the radical scavenging ability and xanthine oxidase (XO) inhibition showed that the digestion products possessed good biological activities mainly due to its anthocyanin composition.