Perceptually enhanced blind single-channel music source separation by Non-negative Matrix Factorization

We propose a new approach that improves perceptual quality of the separated sources in blind single-channel musical source separation. It uses the advantages of subspace learning based on Non-negative Matrix Factorization (NMF) in which the bases represent the notes. The cost function is formulated in the form of weighted β-divergence by adopting the PEAQ auditory model defined in ITU-R BS.1387 into the source separation. The proposed perceptually weighted factorization scheme is integrated into the Non-negative Matrix Factor 2-D Deconvolution (NMF2D) and Clustered Non-negative Matrix Factorization (CNMF) to overcome the source clustering problem encountered in under-determined source separation. It is shown that the introduced perceptually weighted NMF schemes, named as PW-NMF2D and PW-CNMF, efficiently learn the bases that enable us to apply a simple resynthesis of the musical sources based on the temporal model stored in the encoding matrix. Source separation performance has been reported on musical mixtures where 1–2 dB improvement is achieved in terms of SDR, SIR and SAR compared to the state-of-the-art methods. Performance has also been evaluated by perceptual measures resulting an improvement of 2–5 in OPS, TPS, IPS and APS values.     

Fuzzy FMEA application to improve purchasing process in a public hospital

Failure mode and effects analysis (FMEA) is one of the well-known techniques of quality management that is used for continuous improvements in product or process designs. While applying this technique, determining the risk priority numbers, which indicate the levels of risks associated with potential problems, is of prime importance for the success of application. These numbers are generally attained from past experience and engineering judgments, and this way of risk assessment sometimes leads to inaccuracies and inconsistencies during priority numbering. Fuzzy logic approach is preferable in order to remove these deficiencies in assigning the risk priority numbers. In this study, a fuzzy-based FMEA is to be applied first time to improve the purchasing process of a public hospital. Results indicate that the application of fuzzy FMEA method can solve the problems that have arisen from conventional FMEA, and can efficiently discover the potential failure modes and effects. It can also provide the stability of process assurance.     

Integrating job parallelism in real-time scheduling theory

We investigate the global scheduling of sporadic, implicit deadline, real-time task systems on multiprocessor platforms. We provide a task model which integrates job parallelism. We prove that the time-complexity of the feasibility problem of these systems is linear relatively to the number of (sporadic) tasks for a fixed number of processors. We propose a scheduling algorithm theoretically optimal (i.e., preemptions and migrations neglected). Moreover, we provide an exact feasibility utilization bound. Lastly, we propose a technique to limit the number of migrations and preemptions.     

ECM: An evidential version of the fuzzy c-means algorithm

A new clustering method for object data, called ECM (evidential c-means) is introduced, in the theoretical framework of belief functions. It is based on the concept of credal partition, extending those of hard, fuzzy, and possibilistic ones. To derive such a structure, a suitable objective function is minimized using an FCM-like algorithm. A validity index allowing the determination of the proper number of clusters is also proposed. Experiments with synthetic and real data sets show that the proposed algorithm can be considered as a promising tool in the field of exploratory statistics.     

A component‐based framework for radio‐astronomical imaging software systems

This paper describes a component‐based framework for radio‐astronomical imaging software systems. We consider optimal re‐use strategies for packages of disparate architectures brought together within a modern component framework. In this practical case study, the legacy codes include both procedural and object‐oriented architectures. We consider also the special requirements on scientific component middleware, with a specific focus on high‐performance computing. We present an example application in this component architecture and outline future development planned for this project. Copyright © 2007 John Wiley & Sons, Ltd.     

Data Compression for Proof Replay

We describe a compressing translation from SAT solver generated propositional resolution refutation proofs to classical natural deduction proofs. The resulting proof can usually be checked quicker than one that simply simulates the original resolution proof. We use this result in interactive theorem provers, to speed up reconstruction of SAT solver generated proofs. The translation is fast and scales up to large proofs with millions of inferences.     

Fair referee assignments for professional football leagues

Assignment of referees to football games is an important problem faced in professional football leagues. Despite its importance, the problem has received limited academic attention. This paper presents a model and analysis of the problem for fair referee assignments, and develops a constructive heuristic and a local search procedure for its solution. Results from an extensive computational study show that the methods are effective in solving the problem in a second of computation time and yielding an excellent solution quality.