Speech enhancement with an adaptive Wiener filter

This paper proposes an adaptive Wiener filtering method for speech enhancement. This method depends on the adaptation of the filter transfer function from sample to sample based on the speech signal statistics; the local mean and the local variance. It is implemented in the time domain rather than in the frequency domain to accommodate for the time-varying nature of the speech signals. The proposed method is compared to the traditional frequency-domain Wiener filtering, spectral subtraction and wavelet denoising methods using different speech quality metrics. The simulation results reveal the superiority of the proposed Wiener filtering method in the case of Additive White Gaussian Noise (AWGN) as well as colored noise.     

On the Gröbner basis triangularization of constraint equations in natural coordinates

Efficient dynamic simulation code is essential in many situations (including hardware-in-the-loop and model-predictive control applications), and highly beneficial in others (such as design optimization, sensitivity analysis, parameter identification, and controller tuning tasks). When the number of modeling coordinates n exceeds the degrees-of-freedom of the system f, as is often the case when closed kinematic chains are present, the governing dynamic equations consist of n second-order ordinary differential equations (ODEs) coupled with m=n?f algebraic constraint equations. This set of n+m index-3 differential-algebraic equations can be difficult to solve in an efficient yet accurate manner. Embedding (or generalized coordinate partitioning) can be used to obtain f ODEs (one for each independent acceleration), which are generally more amenable to numerical integration; however, the dependent positions are typically computed from the independent positions at each time step. Newton–Raphson iteration is often used for solving the position-level kinematics, but only provides solutions to within a specified tolerance, and can require several iterations to converge. In this work, Gröbner bases are used to obtain recursively solvable symbolic solutions for the dependent positions, which can then be evaluated to within machine precision using a fixed number of arithmetic operations. Natural coordinates are particularly attractive in this context, since the resulting constraint equations are maximally quadratic polynomials and are, therefore, easily triangularized. The proposed approach is suitable for use in an automated formulation procedure and, as demonstrated by three examples, is capable of generating highly efficient simulation code with minimal additional effort required at the formulation stage.     

Online mining abnormal period patterns from multiple medical sensor data streams

With the advanced technology of medical devices and sensors, an abundance of medical data streams are available. However, data analysis techniques are very limited, especially for processing massive multiple physiological streams that may only be understood by medical experts. The state-of-the-art techniques only allow multiple medical devices to independently monitor different physiological parameters for the patient’s status, thus they signal too many false alarms, creating unnecessary noise, especially in the Intensive Care Unit (ICU). An effective solution which has been recently studied is to integrate information from multiple physiologic parameters to reduce alarms. But it is a challenge to detect abnormalities from high frequently changed physiological streams data, since abnormalities occur gradually due to the complex situation of patients. An analysis of ICU physiological data streams shows that many vital physiological parameters are changed periodically (such as heart rate, arterial pressure, and respiratory impedance) and thus abnormalities are generally abnormal period patterns. In this paper, we develop a Mining Abnormal Period Patterns from Multiple Physiological Streams (MAPPMPS) method to detect and rank abnormalities in medical sensor streams. The efficiency and effectiveness of the MAPPMPS method is demonstrated by a real-world massive database of multiple physiological streams sampled in ICU, comprising 250 patients’ streams (each stream involving over 1.3 million data points) with a total size of 28 GB data.     

Who and what links to the Internet Archive

The Internet Archive’s (IA) Wayback Machine is the largest and oldest public Web archive and has become a significant repository of our recent history and cultural heritage. Despite its importance, there has been little research about how it is discovered and used. Based on Web access logs, we analyze what users are looking for, why they come to IA, where they come from, and how pages link to IA. We find that users request English pages the most, followed by the European languages. Most human users come to Web archives because they do not find the requested pages on the live Web. About 65 % of the requested archived pages no longer exist on the live Web. We find that more than 82 % of human sessions connect to the Wayback Machine via referrals from other Web sites, while only 15 % of robots have referrers. Most of the links (86 %) from Websites are to individual archived pages at specific points in time, and of those 83 % no longer exist on the live Web. Finally, we find that users who come from search engines browse more pages than users who come from external Web sites.     

Authorized workflow schemas: deciding realizability through \mathsf{LTL }(\mathsf{F }) model checking

Many business processes are modeled as workflows, which often need to comply with business rules, legal requirements, and authorization policies. Workflow satisfiability is the problem of determining whether there exists a workflow instance that realizes the workflow specification while simultaneously complying with such constraints. This problem has already been studied by the computer security community, with the development of algorithms and the study of their worst-case complexity. These solutions are often tailored to a particular workflow model and are, therefore, of little or no use in analyzing different models; their worst-case complexities are likely to be an unreliable judge of their feasibility; and they lack support for other forms of analysis such as the determination of the smallest number of users required to satisfy a workflow specification. We propose model checking of an NP-complete fragment $\mathsf{LTL }(\mathsf{F })$ of propositional linear-time temporal logic as an alternative solution. We report encodings in LTL(F) that can compute a set of solutions (thus deciding satisfiability), compute minimal user bases and a safe bound on the resiliency of satisfiability under the removal of users. These theoretical contributions are validated through detailed experiments whose results attest to the viability of our proposed approach.     

Matching ratio between positive and negative electrodes for double-layer capacitors

For double-layer capacitors in alkaline electrolyte, the specific capacitance of the positive electrode is not equal to that of the negative one. Thus, capacitor performance cannot be optimal with a positive/negative electrode matching ratio of 1. In this study nanoporous glassy carbons (NPGCs) were employed as the electrodes of capacitors, and the influence of matching ratio between positive and negative electrode on capacitor performance was systematically investigated. In aqueous KOH, the specific capacitance of the positive electrode is lower than that of the negative electrode. The matching ratio at which a maximum capacitance is obtained is dependent on the values of the positive and negative electrode capacitance. At low current rate, the highest specific capacitance is achieved at a matching ratio slightly higher than 1. At high current rate, a capacitor has the highest specific capacitance with the lowest resistance at a matching ratio of 1.5. This indicates that an optimum matching relationship between positive and negative electrodes is attained.     

Compositional characterization of cottonseed soapstocks

Cottonseed soapstock samples, collected during the 1993–1994 crushing season from oilseed extraction mills throughout the United States Cotton Belt, were analyzed by chemical and chromatographic methods. Volatiles averaged 48.7±10.6% (mean±SD,n=39). On a dry basis, the samples averaged 33.3±7.3% fatty acids, 26.3±6.9% phospholipids, 8.4±6.4% triglycerides, and 7.5±3.0% gossypol. The analytical techniques accounted for 93.3±8.6% of the dry soapstock matter. The AOCS method for total fatty acids in soapstock yielded values in agreement with the chromatographic and phosphorus analyses. In contrast, the AOCS method for neutral oil in soapstock gave values that were significantly higher than those obtained by chromatography. The amount of nonlipid material in the samples correlated with the phosphorus content. Total gossypol and nitrogen levels were also related.     

An ensemble evolutionary constraint-based approach to understand the emergence of metabolic phenotypes

Constraint-based modeling is largely used in computational studies of metabolism. We propose here a novel approach that aims to identify ensembles of flux distributions that comply with one or more target phenotype(s). The methodology has been tested on a small-scale model of yeast energy metabolism. The target phenotypes describe the differential pattern of ethanol production and O₂ consumption observed in “Crabtree-positive” and “Crabtree-negative” yeasts in changing environment (i.e., when the upper limit of glucose uptake is varied). The ensembles were obtained either by selection among sampled flux distributions or by means of a search heuristic (genetic algorithm). The former approach provided indication about the probability to observe a given phenotype, but the resulting ensembles could not be unambiguously partitioned into “Crabtree-positive” and “Crabtree-negative” clusters. On the contrary well-separated clusters were obtained with the latter method. The cluster analysis further allowed identification of distinct groups within each target phenotype. The method may thus prove useful in characterizing the design principles underlying metabolic plasticity arising from evolving physio-pathological or developmental constraints.