An efficient ant colony system based on receding horizon control for the aircraft arrival sequencing and scheduling problem

The aircraft arrival sequencing and scheduling (ASS) problem is a salient problem in air traffic control (ATC), which proves to be nondeterministic polynomial (NP) hard. This paper formulates the ASS problem in the form of a permutation problem and proposes a new solution framework that makes the first attempt at using an ant colony system (ACS) algorithm based on the receding horizon control (RHC) to solve it. The resultant RHC-improved ACS algorithm for the ASS problem (termed the RHC-ACS-ASS algorithm) is robust, effective, and efficient, not only due to that the ACS algorithm has a strong global search ability and has been proven to be suitable for these kinds of NP-hard problems but also due to that the RHC technique can divide the problem with receding time windows to reduce the computational burden and enhance the solution's quality. The RHC-ACS-ASS algorithm is extensively tested on the cases from the literatures and the cases randomly generated. Comprehensive investigations are also made for the evaluation of the influences of ACS and RHC parameters on the performance of the algorithm. Moreover, the proposed algorithm is further enhanced by using a two-opt exchange heuristic local search. Experimental results verify that the proposed RHC-ACS-ASS algorithm generally outperforms ordinary ACS without using the RHC technique and genetic algorithms (GAs) in solving the ASS problems and offers high robustness, effectiveness, and efficienc

Metastable behavior of vortex matter in the electronic transport processes of homogenous superconductors

We study numerically the effect of vortex pinning on the hysteresis voltage-temperature (V-T) loop of vortex matter. It is found that different types of the V-T loops result from different densities of vortex pinning center. An anticlockwise V-T loop is observed for the vortex system with dense pinning centers, whereas a clockwise V-T loop is brought about for vortices with dilute pinning centers. It is shown that the size of the V-T loop becomes smaller for lower experimental speed, higher magnetic field, or weak pinning strength. Our numerical observation is in good agreement with experiments

GPU Implementation of DPSO-RE Algorithm for Parameters Identification of Surface PMSM Considering VSI Nonlinearity

In this paper, an accurate parameter estimation model of surface permanent magnet synchronous machines (SPMSMs) is established by taking into account voltage-source-inverter (VSI) nonlinearity. A fast dynamic particle swarm optimization (DPSO) algorithm combined with a receptor editing (RE) strategy is proposed to explore the optimal values of parameter estimations. This combination provides an accelerated implementation on graphics processing unit (GPU), and the proposed method is, therefore, referred to as G-DPSORE. In G-DPSO-RE, a dynamic labor division strategy is incorporated into the swarms according to the designed evolutionary factor during the evolution process. Two novel modifications of the movement equation are designed to update the velocity of particles. Moreover, a chaotic-logistic-based immune RE operator is developed to facilitate the global best individual (gBest particle) to explore a potentially better region. Furthermore, a GPU parallel acceleration technique is utilized to speed up parameter estimation procedure. It has been demonstrated that the proposed method is effective for simultaneous estimation of the PMSM parameters and the disturbance voltage (Vdead) due to VSI nonlinearity from experimental data for currents and rotor speed measured with inexpensive equipment. The influence of the VSI nonlinearity on the accuracy of parameter estimation is analyzed

Cystic meningioangiomatosis with enhancing mural nodule on MRI and no calcification on CT

The neuroradiological features of meningioangiomatosis (MA) are non-specific. We report a young man with sporadic MA. The plain computerized tomography (CT) demonstrated a deep located right cystic lesion without calcification. On magnetic resonance imaging, the cystic mass lesion was confirmed with a mural nodule with significant enhancement on contrast-enhanced images

Parameter estimation for VSI-Fed PMSM based on a dynamic PSO with learning strategies

© 1986-2012 IEEE.A dynamic particle swarm optimization with learning strategy (DPSO-LS) is proposed for key parameter estimation for permanent magnet synchronous machines (PMSMs), where the voltage-source inverter (VSI) nonlinearities are taken into account in the parameter estimation model and can be estimated simultaneously with other machine parameters. In the DPSO-LS algorithm, a novel movement modification equation with variable exploration vector is designed to effectively update particles, enabling swarms to cover large areas of search space with large probability and thus the global search ability is enhanced. Moreover, a Gaussian-distribution-based dynamic opposition-based learning strategy is developed to help the pBest jump out local optima. The proposed DPSO-LS can significantly enhance the estimator model accuracy and dynamic performance. Finally, the proposed algorithm is applied to multiple parameter estimation including the VSI nonlinearities of a PMSM. The performance of DPSO-LS is compared with several existing PSO algorithms, and the comparison results show that the proposed parameters estimation method has better performance in tracking the variation of machine parameters effectively and estimating the VSI nonlinearities under different operation conditions

PSO-based Parameter Estimation of Nonlinear Kinetic Models for β-Mannanase Fermentation

Particle swarm optimization (PSO), as a novel evolutionary algorithm involved in social interaction for global space search, was firstly used in kinetic parameter estimation. Based on three developed nonlinear kinetic equations for bacterial cell growth, total sugar utilization and β-mannanase production by Bacillus licheniformis under the support of a batch fermentation process, various PSO algorithms as well as gene algorithms (GA) were developed to estimate kinetic parameters. The performance comparison among these algorithms indicates the improved PSO (Trelea 1) is most suitable for kinetic parameter estimation of β-mannanase fermentation. In order to find the physical-chemical-meanings of kinetic parameters from many optimized results, multiobjective optimization with a normalized weight method was adopted. The 9 desired parameters in equations were obtained by the Trelea 1 type PSO with two batches fermentation data, and the results predicted by the models were also in good agreement with the experimental observations

Application of the fruit fly optimization algorithm to an optimized neural network model in radar target recognition

With the development of computer technology, there are more and more algorithms and models for data processing and analysis, which brings a new direction to radar target recognition. This study mainly analyzed the recognition of high resolution range profile (HRRP) in radar target recognition and applied the generalized regression neural network (GRNN) model for HRRP recognition. In order to improve the performance of HRRP, the fruit fly optimization algorithm (FOA) algorithm was improved to optimize the parameters of the GRNN model. Simulation experiments were carried out on three types of aircraft. The improved FOA-GRNN (IFOA-GRNN) model was compared with the radial basis function (RBF) and GRNN models. The results showed that the IFOA-GRNN model had a better convergence accuracy, the highest average recognition rate (96.4 %), the shortest average calculation time (275 s), and a good recognition rate under noise in-terference. The experimental results show that the IFOA-GRNN model has a good performance in radar target recognition and can be further promoted and applied in practice

Nuclear halo and its scaling laws

We have proposed a procedure to extract the probability for valence particle being out of the binding potential from the measured nuclear asymptotic normalization coefficients. With this procedure, available data regarding the nuclear halo candidates are systematically analyzed and a number of halo nuclei are confirmed. Based on these results we have got a much relaxed condition for nuclear halo occurrence. Furthermore, we have presented the scaling laws for the dimensionless quantity $/R^{2}$ of nuclear halo in terms of the analytical expressions of the expectation value for the operator $r^{2}$ in a finite square-well potential.Comment: 14 pages, 3 figure

Multi-neutron transfer coupling in sub-barrier 32S+90,96Zr fusion reactions

The role of neutron transfers is investigated in the fusion process below the Coulomb barrier by analyzing 32S+90Zr and 32S+96Zr as benchmark reactions. A full coupled-channel calculation of the fusion excitation functions has been performed for both systems by using multi-neutron transfer coupling for the more neutron-rich reaction. The enhancement of fusion cross sections for 32S+96Zr is well reproduced at sub-barrier energies by NTFus code calculations including the coupling of the neutron-transfer channels following the Zagrebaev semiclassical model. We found similar effects for 40Ca+90Zr and 40Ca+96Zr fusion excitation functions.Comment: Minor corrections, 11 pages, 4 figures, Fusion11 Conference, Saint Malo, France, 2-6 mai 201

Reoperation rates following intramedullary nailing versus external fixation of Gustilo Type 3A open tibia shaft fractures

Background: Open tibia fractures are among the most difficult to manage due to the lack of soft tissue coverage and poor blood supply. This is especially true in developing settings primarily due to a lack of resources. Both locked Intramedullary Nailing (IM) and External Fixation (EF) are two possible modalities for surgical treatment of open tibia fractures. However, it is unknown at this time which one is most suitable in low resource regions especially with regards to the risk of serious complications requiring reoperation. This study was conducted to identify which method is safest and minimizes this risk in patients with open tibia fractures.Methodology: A prospective cohort study of Gustilo 3A open tibia shaft factures treated either by intramedullary nailing or external fixation was conducted from March 2013 to February 2014 at Muhimbili Orthopaedic Institute (Dar es Salaam, Tanzania). Follow-up was conducted at 2, 6 10, 14, and 18 weeks postoperatively. The primary outcome assessed was all-cause reoperation.Results: Fifty patients were enrolled and completed follow-up at all-time points; twenty-six were treated with IM nail and twenty-four were treated by EF. There were 9 (37.5%) EF patients who required reoperation compared to 1(3.8%) IM nail patient (p=0.004). Reasons for reoperation among EF patients were infection (2 patients), malalignment (3 patients), and delayed union (4 patients). The one IM nail patient presented with signs of infection and wound dehiscence at 14 weeks postoperatively. No patients presented with hardware failure or malrotation.Conclusion: Treatment of Gustilo Type 3A open tibia shaft fractures with interlocking intramedullary nailing results in lower reoperation rate in the early stages of treatment compared to uniplanar external fixation.Keywords: Orthopaedic surgery, Tanzania, Intramedullary nail, External fixation, Open tibia fractur