Dual Sequence Simulated Annealing with Round-Robin Approach for University Course Timetabling

The university course timetabling problem involves assigning a given number of events into a limited number of timeslots and rooms under a given set of constraints; the objective is to satisfy the hard constraints (essential requirements) and minimize the violation of soft constraints (desirable requirements). In this study we employed a Dual-sequence Simulated Annealing (DSA) algorithm as an improvement algorithm. The Round Robin (RR) algorithm is used to control the selection of neighbourhood structures within DSA. The performance of our approach is tested over eleven benchmark datasets. Experimental results show that our approach is able to generate competitive results when compared with other state-of-the-art techniques.

Revisioning assessment through a children’s rights approach: implications for policy, process and practice

The linkage between the impact of assessment and compliance with children’s rights is a connection, which although seemingly obvious, is nonetheless rarely made, particularly by governments, which, as signatories to the relevant human rights treaties, have the primary responsibility for ensuring that educational practice is compatible with international children’s rights standards. While some jurisdictions are explicit about an adherence to children’s rights frameworks in general policy documentation, such a commitment rarely features when the focus is on assessment and testing. Thus, in spite of significant public and academic attention given to the consequences of assessment for children and governments committed to working within children’s rights standards, the two are rarely considered together. This paper examines the implications for the policy, process and practice of assessment in light of international human rights standards. Three key children’s rights principles and standards are used as a critical lens to examine assessment policy and practice: (1) best interests; (2) non-discrimination; and (3) participation. The paper seeks new insights into the complexities of assessment practice from the critical perspective of children’s rights and argues that such standards not only provide a convenient benchmark for developing, implementing and evaluating assessment practices, but also acknowledge the significance of assessment in the delivery of children’s rights to, in and through education more generally.

Design of quantum-dot cellular automata circuits using cut-set retiming

As a potential alternative to CMOS technology, QCA provides an interesting paradigm in both communication and computation. However, QCAs unique four-phase clocking scheme and timing constraints present serious timing issues for interconnection and feedback. In this work, a cut-set retiming design procedure is proposed to resolve these QCA timing issues. The proposed design procedure can accommodate QCAs unique characteristics by performing delay-transfer and time-scaling to reallocate the existing delays so as to achieve efficient clocking zone assignment. Cut-set retiming makes it possible to effectively design relatively complex QCA circuits that include feedback. It utilizes the similar characteristics of synchronization, deep pipelines and local interconnections common to both QCA and systolic architectures. As a case study, a systolic Montgomery modular multiplier is designed to illustrate the procedure. Furthermore, a nonsystolic architecture, an S27 benchmark circuit, is designed and compared with previous designs. The comparison shows that the cut-set retiming method achieves a more efficient design, with a reduction of 22%, 44%, and 46% in terms of cell count, area, and latency, respectively.

A hybrid metaheuristic approach to the university course timetabling problem

This paper describes the development of a novel metaheuristic that combines an electromagnetic-like mechanism (EM) and the great deluge algorithm (GD) for the University course timetabling problem. This well-known timetabling problem assigns lectures to specific numbers of timeslots and rooms maximizing the overall quality of the timetable while taking various constraints into account. EM is a population-based stochastic global optimization algorithm that is based on the theory of physics, simulating attraction and repulsion of sample points in moving toward optimality. GD is a local search procedure that allows worse solutions to be accepted based on some given upper boundary or ‘level’. In this paper, the dynamic force calculated from the attraction-repulsion mechanism is used as a decreasing rate to update the ‘level’ within the search process. The proposed method has been applied to a range of benchmark university course timetabling test problems from the literature. Moreover, the viability of the method has been tested by comparing its results with other reported results from the literature, demonstrating that the method is able to produce improved solutions to those currently published. We believe this is due to the combination of both approaches and the ability of the resultant algorithm to converge all solutions at every search process.

Target Structure Induced Suppression of the Ionization Cross Section for Very Low Energy Antiproton-Hydrogen Collisions

Low energy antiprotons have been used previously to give benchmark data for theories of atomic collisions. Here we present measurements of the cross section for single, nondissociative ionization of molecular hydrogen for impact of antiprotons with kinetic energies in the range 2-11 keV, i.e., in the velocity interval of 0.3-0.65 a.u. We find a cross section which is proportional to the projectile velocity, which is quite unlike the behavior of corresponding atomic cross sections, and which has never previously been observed experimentally.

Model Selection in SVMs Using Differential Evolution

To improve the performance of classification using Support Vector Machines (SVMs) while reducing the model selection time, this paper introduces Differential Evolution, a heuristic method for model selection in two-class SVMs with a RBF kernel. The model selection method and related tuning algorithm are both presented. Experimental results from application to a selection of benchmark datasets for SVMs show that this method can produce an optimized classification in less time and with higher accuracy than a classical grid search. Comparison with a Particle Swarm Optimization (PSO) based alternative is also included.

Hybrid methods for witnessing entanglement in a microscopic-macroscopic system

We propose a hybrid approach to the experimental assessment of the genuine quantum features of a general system consisting of microscopic and macroscopic parts. We infer entanglement by combining dichotomic measurements on a bidimensional system and phase-space inference through the Wigner distribution associated with the macroscopic component of the state. As a benchmark, we investigate the feasibility of our proposal in a bipartite-entangled state composed of a single-photon and a multiphoton field. Our analysis shows that, under ideal conditions, maximal violation of a Clauser-Horne-Shimony-Holt-based inequality is achievable regardless of the number of photons in the macroscopic part of the state. The difficulty in observing entanglement when losses and detection inefficiency are included can be overcome by using a hybrid entanglement witness that allows efficient correction for losses in the few-photon regime.

Dynamic evolution of the genetic search region through fuzzy coding

A technique for automatic exploration of the genetic search region through fuzzy coding (Sharma and Irwin, 2003) has been proposed. Fuzzy coding (FC) provides the value of a variable on the basis of the optimum number of selected fuzzy sets and their effectiveness in terms of degree-of-membership. It is an indirect encoding method and has been shown to perform better than other conventional binary, Gray and floating-point encoding methods. However, the static range of the membership functions is a major problem in fuzzy coding, resulting in longer times to arrive at an optimum solution in large or complicated search spaces. This paper proposes a new algorithm, called fuzzy coding with a dynamic range (FCDR), which dynamically allocates the range of the variables to evolve an effective search region, thereby achieving faster convergence. Results are presented for two benchmark optimisation problems, and also for a case study involving neural identification of a highly non-linear pH neutralisation process from experimental data. It is shown that dynamic exploration of the genetic search region is effective for parameter optimisation in problems where the search space is complicated.

Fast ion acceleration from thin foils irradiated by ultra-high intensity, ultra-high contrast laser pulses

Ion acceleration resulting from the interaction of ultra-high intensity (2 x 10(20) W/cm(2)) and ultra-high contrast (similar to 10(10)) laser pulses with 0.05-10 mu m thick Al foils at normal (0 degrees) and 35 degrees laser incidence is investigated. When decreasing the target thickness from 10 mu m down to 0.05 mu m, the accelerated ions become less divergent and the ion flux increases, particularly at normal (0 degrees) laser incidence on the target. A laser energy conversion into protons of,similar to 6.5% is estimated at 35 degrees laser incidence. Experimental results are in reasonable agreement with theoretical estimates and can be a benchmark for further theoretical and computational work. (C) 2011 American Institute of Physics. [doi:10.1063/1.3643133]

A New Model for Automated Examination Timetabling

Automated examination timetabling has been addressed by a wide variety of methodologies and techniques over the last ten years or so. Many of the methods in this broad range of approaches have been evaluated on a collection of benchmark instances provided at the University of Toronto in 1996. Whilst the existence of these datasets has provided an invaluable resource for research into examination timetabling, the instances have significant limitations in terms of their relevance to real-world examination timetabling in modern universities. This paper presents a detailed model which draws upon experiences of implementing examination timetabling systems in universities in Europe, Australasia and America. This model represents the problem that was presented in the 2nd International Timetabling Competition (ITC2007). In presenting this detailed new model, this paper describes the examination timetabling track introduced as part of the competition. In addition to the model, the datasets used in the competition are also based on current real-world instances introduced by EventMAP Limited. It is hoped that the interest generated as part of the competition will lead to the development, investigation and application of a host of novel and exciting techniques to address this important real-world search domain. Moreover, the motivating goal of this paper is to close the currently existing gap between theory and practice in examination timetabling by presenting the research community with a rigorous model which represents the complexity of the real-world situation. In this paper we describe the model and its motivations, followed by a full formal definition.

Mixed radix Reed-Muller expansions

The choice of radix is crucial for multi-valued logic synthesis. Practical examples, however, reveal that it is not always possible to find the optimal radix when taking into consideration actual physical parameters of multi-valued operations. In other words, each radix has its advantages and disadvantages. Our proposal is to synthesise logic in different radices, so it may benefit from their combination. The theory presented in this paper is based on Reed-Muller expansions over Galois field arithmetic. The work aims to firstly estimate the potential of the new approach and to secondly analyse its impact on circuit parameters down to the level of physical gates. The presented theory has been applied to real-life examples focusing on cryptographic circuits where Galois Fields find frequent application. The benchmark results show the approach creates a new dimension for the trade-off between circuit parameters and provides information on how the implemented functions are related to different radices.

Characterisation of the photocatalyst Pilkington Activ (TM): a reference film photocatalyst?

Pilkington Glass Activ(TM) represents a possible suitable successor to P25 TiO2, especially as a benchmark photocatalyst film for comparing other photocatalyst or PSH self-cleaning films. Activ(TM) is a glass product with a clear, colourless, effectively invisible, photocatalytic coating of titania that also exhibits PSH. Although not as active as a film of P25 TiO2, Activ(TM) vastly superior mechanical stability, very reproducible activity and widespread commercial availability makes it highly attractive as a reference photocatalytic film. The photocatalytic and photo-induced superhydrophilitic (PSH) properties of Activ(TM) are studied in some detail and the results reported. Thus, the kinetics of stearic acid destruction (a 104 electron process) are zero order over the stearic acid range 4-129 monolayers and exhibit formal quantum efficiencies (FQE) of 0.7 X 10(-5) and 10.2 x 10(-5) molecules per photon when irradiated with light of 365 +/- 20 and 254 nm, respectively; the latter appears also to be the quantum yield for Activ(TM) at 254 nm. The kinetics of stearic acid destruction exhibit Langmuir-Hinshelwood-like saturation type kinetics as a function of oxygen partial pressure, with no destruction occurring in the absence of oxygen and the rate of destruction appearing the same in air and oxygen atmospheres. Further kinetic work revealed a Langmuir adsorption type constant for oxygen of 0.45 +/- 0.16 kPa(-1) and an activation energy of 19 +/- 1 Kj mol(-1). A study of the PSH properties of Activ(TM) reveals a high water contact angle (67) before ultra-bandgap irradiation reduced to 0degrees after prolonged irradiation. The kinetics of PSH are similar to those reported by others for sol-gel films using a low level of UV light. The kinetics of contact angle recovery in the dark appear monophasic and different to the biphasic kinetics reported recently by others for sol-gel films [J. Phys. Chem. B 107 (2003) 1028]. Overall, Activ(TM) appears a very suitable reference material for semiconductor film photocatalysis. (C) 2003 Elsevier Science B.V All rights reserved.

The Paralax Infrastructure: Automatic Parallelization With a Helping Hand

Speeding up sequential programs on multicores is a challenging problem that is in urgent need of a solution. Automatic parallelization of irregular pointer-intensive codes, exempli?ed by the SPECint codes, is a very hard problem. This paper shows that, with a helping hand, such auto-parallelization is possible and fruitful. This paper makes the following contributions: (i) A compiler framework for extracting pipeline-like parallelism from outer program loops is presented. (ii) Using a light-weight programming model based on annotations, the programmer helps the compiler to ?nd thread-level parallelism. Each of the annotations speci?es only a small piece of semantic information that compiler analysis misses, e.g. stating that a variable is dead at a certain program point. The annotations are designed such that correctness is easily veri?ed. Furthermore, we present a tool for suggesting annotations to the programmer. (iii) The methodology is applied to autoparallelize several SPECint benchmarks. For the benchmark with most parallelism (hmmer), we obtain a scalable 7-fold speedup on an AMD quad-core dual processor. The annotations constitute a parallel programming model that relies extensively on a sequential program representation. Hereby, the complexity of debugging is not increased and it does not obscure the source code. These properties could prove valuable to increase the ef?ciency of parallel programming.

Improved conjugate gradient implementation for least squares support vector machines

As a promising method for pattern recognition and function estimation, least squares support vector machines (LS-SVM) express the training in terms of solving a linear system instead of a quadratic programming problem as for conventional support vector machines (SVM). In this paper, by using the information provided by the equality constraint, we transform the minimization problem with a single equality constraint in LS-SVM into an unconstrained minimization problem, then propose reduced formulations for LS-SVM. By introducing this transformation, the times of using conjugate gradient (CG) method, which is a greatly time-consuming step in obtaining the numerical solution, are reduced to one instead of two as proposed by Suykens et al. (1999). The comparison on computational speed of our method with the CG method proposed by Suykens et al. and the first order and second order SMO methods on several benchmark data sets shows a reduction of training time by up to 44%. (C) 2011 Elsevier B.V. All rights reserved.

A sequential algorithm for sparse support vector classifiers

Support vector machines (SVMs), though accurate, are not preferred in applications requiring high classification speed or when deployed in systems of limited computational resources, due to the large number of support vectors involved in the model. To overcome this problem we have devised a primal SVM method with the following properties: (1) it solves for the SVM representation without the need to invoke the representer theorem, (2) forward and backward selections are combined to approach the final globally optimal solution, and (3) a criterion is introduced for identification of support vectors leading to a much reduced support vector set. In addition to introducing this method the paper analyzes the complexity of the algorithm and presents test results on three public benchmark problems and a human activity recognition application. These applications demonstrate the effectiveness and efficiency of the proposed algorithm.


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