The convergence analysis and specification of the Population-Based Incremental Learning algorithm

In this paper, we investigate the global convergence properties in probability of the Population-Based Incremental Learning (PBIL) algorithm when the initial configuration p⁽⁰⁾ is fixed and the learning rate α is close to zero. The convergence in probability of PBIL is confirmed by the experimental results. This paper presents a meaningful discussion on how to establish a unified convergence theory of PBIL that is not affected by the population and the selected individuals.     

Barrier Lyapunov Functions for the control of output-constrained nonlinear systems

In this paper, we present control designs for single-input single-output (SISO) nonlinear systems in strict feedback form with an output constraint. To prevent constraint violation, we employ a Barrier Lyapunov Function, which grows to infinity when its arguments approach some limits. By ensuring boundedness of the Barrier Lyapunov Function in the closed loop, we ensure that those limits are not transgressed. Besides the nominal case where full knowledge of the plant is available, we also tackle scenarios wherein parametric uncertainties are present. Asymptotic tracking is achieved without violation of the constraint, and all closed loop signals remain bounded, under a mild condition on the initial output. Furthermore, we explore the use of an Asymmetric Barrier Lyapunov Function as a generalized approach that relaxes the requirements on the initial conditions. We also compare our control with one that is based on a Quadratic Lyapunov Function, and we show that our control requires less restrictive initial conditions. A numerical example is provided to illustrate the performance of the proposed control.     

ISICS2011, an updated version of ISICS: A program for calculation K-, L-, and M-shell cross sections from PWBA and ECPSSR theories using a personal computer

In this new version of ISICS, called ISICS2011, a few omissions and incorrect entries in the built-in file of electron binding energies have been corrected; operational situations leading to un-physical behavior have been identified and flagged.

New version program summary

Program title: ISICS2011Catalogue identifier: ADDS_v5_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADDS_v5_0.htmlProgram obtainable from: CPC Program Library, Queen?s University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 6011No. of bytes in distributed program, including test data, etc.: 130 587Distribution format: tar.gzProgramming language: CComputer: 80486 or higher-level PCsOperating system: WINDOWS XP and all earlier operating systemsClassification: 16.7Catalogue identifier of previous version: ADDS_v4_0Journal reference of previous version: Comput. Phys. Commun. 180 (2009) 1716.Does the new version supersede the previous version?: YesNature of problem: Ionization and X-ray production cross section calculations for ion–atom collisions.Solution method: Numerical integration of form factor using a logarithmic transform and Gaussian quadrature, plus exact integration limits.Reasons for new version: General need for higher precision in output format for projectile energies; some built-in binding energies needed correcting; some anomalous results occur due to faulty read-in data or calculated parameters becoming un-physical; erroneous calculations could result for the L and M shells when restricted K-shell options are inadvertently chosen; to achieve general compatibility with ISICSoo, a companion C++ version that is portable to Linux and MacOS platforms, has been submitted for publication in the CPC Program Library approximately at the same time as this present new standalone version of ISICS [1].Summary of revisions: The format field for projectile energies in the output has been expanded from two to four decimal places in order to distinguish between closely spaced energy values. There were a few entries in the executable binding energy file that needed correcting; K shell of Eu, M shells of Zn, M1 shell of Kr. The corrected values were also entered in the ENERGY.DAT file. In addition, an alternate data file of binding energies is included, called ENERGY_GW.DAT, which is more up-to-date [2]. Likewise, an alternate atomic parameters data file is now included, called FLOURE_JC.DAT, which is more up-to-date [3] fluorescence yields for the K and L shells and Coster–Kronig parameters for the L shell. Both data files can be read in using the -f usage option. To do this, the original energy file should be renamed and saved (e.g., ENERGY_BB.DAT) and the new file (ENERGY_GW.DAT ) should be duplicated as ENERGY.DAT to be read in using the -f option. Similarly for reading in an alternate FLOURE.DAT file. As with previous versions, the user can also simply input different values of any input quantity by invoking the “specify your own parameters” option from the main menu. You can also use this option to simply check the values of the built-in values of the parameters. If it still happens that a zero binding energy for a particular sub-shell is read in, the program will not completely abort, but will calculate results for the other sub-shells while setting the affected sub-shell output to zero. In calculating the Coulomb deflection factor, if the quantity inside the radical sign of the parameter zs becomes zero or negative, to prevent the program from aborting, the PWBA cross sections are still calculated while the ECPSSR cross sections are set to zero. This situation can happen for very low energy collisions, such as were noticed for helium ions on copper at energies of E?11.2 keV. It was observed during the engineering of ISICSoo [1] that erroneous calculations could result for the L- and M-shell cases when restricted K-shell R or HSR scaling options were inappropriately chosen. The program has now been fixed so that these inappropriate options are ignored for the L and M shells. In the previous versions, the usage for inputting a batch data file was incorrectly stated in the Users Manual as -Bxxx; the correct designation is -Fxxx, or alternatively, -Ixxx, as indicated on the usage screen in running the program.A revised Users Manual is also available.Restrictions: The consumed CPU time increases with the atomic shell (K, L, M), but execution is still very fast.Running time: This depends on which shell and the number of different energies to be used in the calculation. The running time is not significantly changed from the previous version.References:

• [1] 

  M. Batic, M.G. Pia, S. Cipolla, Comput. Phys. Commun. (2011), submitted for publication.

• [2] 

  http://www.jlab.org/~gwyn/ebindene.html.

• [3] 

  J. Campbell, At. Data Nucl. Data Tables 85 (2003) 291.

     

The minimum information about failures for solving non-local tasks in message-passing systems

We first define the basic notions of local and non-local tasks for distributed systems. Intuitively, a task is local if, in a system with no failures, each process can compute its output value locally by applying some local function on its own input value (so the output value of each process depends only on the process’ own input value, not on the input values of the other processes); a task is nonlocal otherwise. All the interesting distributed tasks, including all those that have been investigated in the literature (e.g., consensus, set agreement, renaming, atomic commit, etc.) are non-local. In this paper we consider non-local tasks and determine the minimum information about failures that is necessary to solve such tasks in message-passing distributed systems. As part of this work, we also introduces weak set agreement—a natural weakening of set agreement—and show that, in some precise sense, it is the weakest nonlocal task in message-passing systems.     

Failure detection and consensus in the crash-recovery model

Summary. We study the problems of failure detection and consensus in asynchronous systems in which processes may crash and recover, and links may lose messages. We first propose new failure detectors that are particularly suitable to the crash-recovery model. We next determine under what conditions stable storage is necessary to solve consensus in this model. Using the new failure detectors, we give two consensus algorithms that match these conditions: one requires stable storage and the other does not. Both algorithms tolerate link failures and are particularly efficient in the runs that are most likely in practice – those with no failures or failure detector mistakes. In such runs, consensus is achieved within time and with 4 n messages, where is the maximum message delay and n is the number of processes in the system. Received: May 1998 / Accepted: November 1999     

Symbolic computation with finite biquandles

A method of computing a basis for the second Yang–Baxter cohomology of a finite biquandle with coefficients in Q$\mathbb{Q}$ and _Zp${\mathbb{Z}}_p$ from a matrix presentation of the finite biquandle is described. We also describe a method for computing the Yang–Baxter cocycle invariants of an oriented knot or link represented as a signed Gauss code. We provide a URL for our Maple implementations of these algorithms.     

钓鱼冠军赛

钓鱼,是一项非常休闲的户外活动,大家对此一定不会陌生。笔者就是一个钓鱼迷,而且笔者相信绝大多数人也都有钓鱼的经历。但是你有没有试过在电脑中钓鱼呢？那些不曾钓过鱼的朋友也不用心急,先玩玩这个游戏体验一下钓鱼的感觉吧。     

Recovery and grade prediction of pilot plant flotation column concentrate by a hybrid neural genetic algorithm

Today flotation column has become an acceptable means of froth flotation for a fairly broad range of applications, in particular the cleaning of sulfides. Even after having been used for several years in mineral processing plants, the full potential of the flotation column process is still not fully exploited. There is no prediction of process performance for the complete use of available control capabilities. The on-line estimation of grade usually requires a significant amount of work in maintenance and calibration of on-stream analyzers, in order to maintain good accuracy and high availability. These difficulties and the high cost of investment and maintenance of these devices have encouraged the approach of prediction of metal grade and recovery. In this paper, a new approach has been proposed for metallurgical performance prediction in flotation columns using Artificial Neural Network (ANN). Despite of the wide range of applications and flexibility of NNs, there is still no general framework or procedure through which the appropriate network for a specific task can be designed. Design and structural optimization of NNs is still strongly dependent upon the designer’s experience. To mitigate this problem, a new method for the auto-design of NNs was used, based on Genetic Algorithm (GA). The new proposed method was evaluated by a case study in pilot plant flotation column at Sarcheshmeh copper plant. The chemical reagents dosage, froth height, air, wash water flow rates, gas holdup, Cu grade in the rougher feed, flotation column feed, column tail and final concentrate streams were used to the simulation by GANN. In this work, multi-layer NNs with Back Propagation (BP) algorithm with 8-17-10-2 and 8-13-6-2 arrangements have been applied to predict the Cu and Mo grades and recoveries, respectively. The correlation coefficient (R) values for the testing sets for Cu and Mo grades were 0.93, 0.94 and for their recoveries were 0.93, 0.92, respectively. The results discussed in this paper indicate that the proposed model can be used to predict the Cu and Mo grades and recoveries with a reasonable error.     

Achieving balance between proximity and diversity in multi-objective evolutionary algorithm

Currently, an alternative framework using the hypervolume indicator to guide the search for elite solutions of a multi-objective problem is studied in the evolutionary multi-objective optimization community very actively, comparing to the traditional Pareto dominance based approach. In this paper, we present a dynamic neighborhood multi-objective evolutionary algorithm based on hypervolume indicator (DNMOEA/HI), which benefits from both Pareto dominance and hypervolume indicator based frameworks. DNMOEA/HI is featured by the employment of hypervolume indicator as a truncation operator to prune the exceeded population, while a well-designed density estimator (i.e., tree neighborhood density) is combined with the Pareto strength value to perform fitness assignment. Moreover, a novel algorithm is proposed to directly evaluate the hypervolume contribution of a single individual. The performance of DNMOEA/HI is verified on a comprehensive benchmark suite, in comparison with six other multi-objective evolutionary algorithms. Experimental results demonstrate the efficiency of our proposed algorithm. Solutions obtained by DNMOEA/HI well approach the Pareto optimal front and are evenly distributed over the front, simultaneously.