Control sets on grammars

Given a setC of strings of rewriting rules of a phrase structure grammarG, we consider the setL _c (G) of those words generated by leftmost derivations inG whose corresponding string of rewriting rules is an element ofC. The paper concerns the nature of the setL _c (G) whenC andG are assumed to have special form. For example, forG an arbitrary phrase structure grammar,L _c (G) is an abstract family of languages ifC is an abstract family of languages, andL _c (G) is bounded ifC is bounded.Research sponsored in part by the Air Force Cambridge Research Laboratories, Office of Aerospace Research, USAF, under Contract F1962867C0008, and by the Air Force Office of Scientific Research, Office of Aerospace Research, USAF, under AFOSR Grant No. AF-AFOSR-1203-67.     

Defocus electron microscopy of multiphase polymers: use and misuse

Application of defocus microscopy to the imaging of multiphase polymers is investigated. Theoretical image contrast of ideally phase separated, model objects is predicted by application of the transfer theory of imaging. The calculations are in good agreement with observed images of a polypropylene film. Easy recognition of the cross-hatched structure of polypropylene, however, necessitates the use of very high defocus values. Application of this defocus technique to more complex systems causes problems. Defocused images of a polyurethane film are found to be indistinguishable from those of a carbon film or an amorphous polystyrene film, i.e. the image is dominated by the spatially filtered noise structure. It is suggested that previous electron-micrographs of domain structures of polyurethanes have been misinterpreted.     

Variable Partitioning and Scheduling for MPSoC with Virtually Shared Scratch Pad Memory

One of the most critical components that determine the success of an MPSoC based architecture is its on-chip memory. Scratch Pad Memory (SPM) is increasingly being applied to substitute cache as the on-chip memory of embedded MPSoCs due to its superior chip area, power consumption and timing predictability. SPM can be organized as a Virtually Shared SPM (VS-SPM) architecture that takes advantage of both shared and private SPM. However, making effective use of the VS-SPM architecture strongly depends on two inter-dependent problems: variable partitioning and task scheduling. In this paper, we decouple these two problems and solve them in phase-ordered manner. We propose two variable partitioning heuristics based on an initial schedule: High Access Frequency First (HAFF) variable partitioning and Global View Prediction (GVP) variable partitioning. Then, we present a loop pipeline scheduling algorithm known as Rotation Scheduling with Variable Partitioning (RSVP) to improve overall throughput. Our experimental results obtained on MiBench show that the average performance improvements over IDAS (Integrated Data Assignment with Scheduling) are 23.74% for HAFF and 31.91% for GVP on four-core MPSoC. The average schedule length generated by RSVP is 25.96% shorter than that of list scheduling with optimal variable partition.     

Magnetic Flux Leakage Signal Inversion Based on Improved Efficient Population Utilization Strategy for Particle Swarm Optimization

In this paper, an improved efficient population utilization strategy for particle swarm optimization (IEPUS-PSO) for high dimension problem is proposed to estimate defect profile from magnetic flux leakage (MFL) signals. In the IEPUS-PSO, a mutation probability is proposed to distinguish local version and global version in particle change model and a self-adapted mutation operator, which is used to update the particles’ positions randomly, is introduced into EPUS-PSO. The IEPUS-PSO- based inversing technique is used to estimate the defect profiles. The estimated defect profiles of simulation signals demonstrate that the inversing technique based on the IEPUS-PSO outperforms the one based on EPUS-PSO. The results estimated from real MFL signals by the IEPUS-PSO-based inversing technique indicate that the algorithm is capable of decreasing the computation time. The results show that the IEPUS-PSO-based inversing technique could improve the reconstruction precision by two orders of magnitude for the MFL simulation signals, and for the real MFL signals, the computation time is reduced by about 30% nearly under the same reconstruction precision.     

Hybrid particle swarm optimization for parameter estimation of Muskingum model

The Muskingum model is the most widely used and efficient method for flood routing in hydrologic engineering; however, the applications of this model still suffer from a lack of an efficient method for parameter estimation. Thus, in this paper, we present a hybrid particle swarm optimization (HPSO) to estimate the Muskingum model parameters by employing PSO hybridized with Nelder–Mead simplex method. The HPSO algorithm does not require initial values for each parameter, which helps to avoid the subjective estimation usually found in traditional estimation methods and to decrease the computation for global optimum search of the parameter values. We have carried out a set of simulation experiments to test the proposed model when applied to a Muskingum model, and we compared the results with eight superior methods. The results show that our scheme can improve the search accuracy and the convergence speed of Muskingum model for flood routing; that is, it has higher precision and faster convergence compared with other techniques.