Finite Element Analysis for Wave Propagation in Double Negative Metamaterials

In this paper, we develop both semi-discrete and fully-discrete mixed finite element methods for modeling wave propagation in three-dimensional double negative metamaterials. Here the model is formed as a time-dependent linear system involving four dependent vector variables: the electric and magnetic fields, and the induced electric and magnetic currents. Optimal error estimates for all four variables are proved for Nédélec tetrahedral elements. To our best knowledge, this is the first error analysis obtained for Maxwell’s equations when metamaterials are involved.      

A Legendre Pseudospectral Penalty Scheme for Solving Time-Domain Maxwell’s Equations

In this paper we present a Legendre pseudospectral algorithm based on a tensor product formulation for solving the time-domain Maxwell equations. Our approach starts by conducting an analysis for finding well-posed boundary operators for the Maxwell equations. We then discuss equivalent characteristic boundary conditions for common physical boundary constraints. These theoretical results are then employed to construct a pseudospectral penalty scheme which is asymptotically stable at the semidiscrete level. Numerical computations based on the proposed scheme are also provided for different cases where exact solutions exist. By measuring the differences between the computed and exact solutions, we observe the expected convergence patterns of the scheme. This work is supported by National Science Council grant No. NSC 95-2120-M-001-003.     

Non-Linear PML Equations for Time Dependent Electromagnetics in Three Dimensions

In this paper we present a new set of non-linear PML equations for the multi-dimensional Maxwell’s equation and show that they are strongly well posed and temporally stable. Numerical examples demonstrate the validity of the new method.     

Optimal design of periodic functionally graded composites with prescribed properties

The computational design of a composite where the properties of its constituents change gradually within a unit cell can be successfully achieved by means of a material design method that combines topology optimization with homogenization. This is an iterative numerical method, which leads to changes in the composite material unit cell until desired properties (or performance) are obtained. Such method has been applied to several types of materials in the last few years. In this work, the objective is to extend the material design method to obtain functionally graded material architectures, i.e. materials that are graded at the local level (e.g. microstructural level). Consistent with this goal, a continuum distribution of the design variable inside the finite element domain is considered to represent a fully continuous material variation during the design process. Thus the topology optimization naturally leads to a smoothly graded material system. To illustrate the theoretical and numerical approaches, numerical examples are provided. The homogenization method is verified by considering one-dimensional material gradation profiles for which analytical solutions for the effective elastic properties are available. The verification of the homogenization method is extended to two dimensions considering a trigonometric material gradation, and a material variation with discontinuous derivatives. These are also used as benchmark examples to verify the optimization method for functionally graded material cell design. Finally the influence of material gradation on extreme materials is investigated, which includes materials with near-zero shear modulus, and materials with negative Poisson’s ratio.     

On the Role of Hadamard Gates in Quantum Circuits

We study a reduced quantum circuit computation paradigm in which the only allowable gates either permute the computational basis states or else apply a “global Hadamard operation”, i.e. apply a Hadamard operation to every qubit simultaneously. In this model, we discuss complexity bounds (lower-bounding the number of global Hadamard operations) for common quantum algorithms: we illustrate upper bounds for Shor’s Algorithm, and prove lower bounds for Grover’s Algorithm. We also use our formalism to display a gate that is neither quantum-universal nor classically simulable, on the assumption that Integer Factoring is not in BPP.     

Error bounds for Newton refinement of solutions to algebraic riccati equations

Recent error bounds derived from the Schur method of solving algebraic Riccati equations (ARE) complement residual error bounds associated with Newton refinement of approximate solutions. These approaches to the problem of error estimation not only work well together but also represent the first computable error bounds for the solution of Riccati equations. In this paper the closed-loop Lyapunov operator is seen to be central to the question of whether Newton refinement will improve an approximate solution (region of convergence), as well as providing a means of bounding the actual error in terms of the residual error. In turn, both of these issues are related to the condition of the ARE and the damping of the associated closed-loop dynamical system. Numerical results are given for seven problems taken from the literature. This research was supported by the National Science Foundation (and AFOSR) under Grant No. ECS87-18897 and the National Science Foundation under Grant No. DMS88-00817.     

Groverian Entanglement Measure and Evolution of Entanglement in Search Algorithm for <Emphasis Type="Italic">n</Emphasis>(= 3, 5)-Qubit Systems with Real Coefficients

Evolution of entanglement with the processing of quantum algorithms affects the outcome of the algorithm. Particularly, the performance of Grover’s search algorithm gets worsened if the initial state of the algorithm is an entangled one. The success probability of search can be seen as an operational measure of entanglement. This paper demonstrates an entanglement measure based on the performance of Grover’s search algorithm for three and five qubit systems. We also show that although the overall pattern shows growth of entanglement, its rise to a maximum and then consequent decay, the presence of local fluctuation within each iterative step is likely.      

Stochastic processes in machine intelligence: Neural structures based on the model of the quantum harmonic oscillator

This paper studies neural structures with weights that follow the model of the quantum harmonic oscillator. The proposed neural networks have stochastic weights which are calculated from the solution of Schrödinger’s equation under the assumption of a parabolic (harmonic) potential. These weights correspond to diffusing particles, which interact with each other as the theory of Brownian motion (Wiener process) predicts. It is shown that conventional neural networks and learning algorithms based on error gradient can be conceived as a subset of the proposed quantum neural structures. The learning of the stochastic weights (convergence of the diffusing particles to an equilibrium) is analyzed. In the case of associative memories the proposed neural model results in an exponential increase of patterns storage capacity (number of attractors).     

The density of truth in monadic fragments of some intermediate logics

This paper is an attempt to count the proportion of tautologies of some intermediate logics among all formulas. Our interest concentrates especially on Medvedev’s logic and its fragment over language with one propositional variable.     

The emergence of cooperation in the random asynchronous prisoner’s dilemma

The iterated prisoners dilemma (IPD) is a simple model for the study of the emergence of cooperative behavior in populations of selfish individuals. In this work, we challenge the assumption that players move in synchrony, and develop a general Markovian model that allows the study of a wide spectrum of scenarios. Simulations show that the relative timing of player moves, and the reward for mutual cooperation, influences the strategy that eventually dominates the final population. For a synchronous environment, reciprocal behavior appears to be the key to the evolution of cooperation, while in an asynchronous environment, guarded generosity may be a route to the evolution of cooperation.     

Parameter’s setting of the ant colony algorithm applied in preventive maintenance optimization

Meta-heuristic applications have evolved a lot nowadays and have been used in many domains. However, their parameter setting stills, till now, a serious problem which influences their efficiency and their attitude. Under the title of preventive maintenance optimization, the Ant Colony (AC) is used as a search technique for the best intervention dates to preventively maintain a series-parallel system. The AC proves once again its efficiency (Samrout, M., Yalaoui, F., Chatelet, E., & Chebbo, N. (2005). Reliability Engineering & System Safety, 89, 346–354), but the parameter setting’s issue persists as a critical issue which needs more analysis. This paper offers a detailed study about the influence of the parameters on the AC operation. An experimental plan design is done. Obtained results are coherent with the convergence conditions of the ant colony algorithms. Based on those latter, improvements are done to the original ant colony algorithm and interesting results are obtained.     

The effects of viscosity in choice and refusal IPD environments

An objective of multi-agent systems is to build robust intelligent systems capable of existing in complex environments. These systems are often characterised as being uncertain and open to change which make such systems far more difficult to design and understand. Some of this uncertainty and change occurs in open agent environments where agents can freely enter and exit the system. In this paper we will examine this form of population change in a game theoretic setting. These simulations involve studying population change through a number of alternative viscosity models. The simulations will examine two possible trust models. All our simulations will use a simple choice and refusal game environment within which agents may freely choose with which of their peers to interact.     

Modeling the progression of Alzheimer’s disease for cognitive assistance in smart homes

Smart homes provide support to cognitively impaired people (such as those suffering from Alzheimer’s disease) so that they can remain at home in an autonomous and safe way. Models of this impaired population should benefit the cognitive assistance’s efficiency and responsiveness. This paper presents a way to model and simulate the progression of dementia of the Alzheimer’s type by evaluating performance in the execution of an activity of daily living (ADL). This model satisfies three objectives: first, it models an activity of daily living; second, it simulates the progression of the dementia and the errors potentially made by people suffering from it, and, finally, it simulates the support needed by the impaired person. To develop this model, we chose the ACT-R cognitive architecture, which uses symbolic and subsymbolic representations. The simulated results of 100 people suffering from Alzheimer’s disease closely resemble the results obtained by 106 people on an occupational assessment (the Kitchen Task Assessment).     

An instrument for the measurement of customer perceptions of quality management in the software industry: An empirical study in India

Most of the available literature on quality management is based on management’s perception; few studies examine critical issues of quality management from the customer’s perspective, especially in the software industry. In order to gain an insight into what customers expect from a product/service, an analysis of quality management from customer’s point of view is essential. Such an understanding would help the managers to adopt strategies that can enhance the satisfaction level of their customers. The present study highlights the critical factors of quality management in the software industry from the customer’s perspective. Six critical factors are identified: and an instrument, comprising these factors, is developed and validated so as to measure the customer’s perception of quality management in the software industry. George Issac is an Assistant Professor in Mar Athanasius College of Engineering, Kothamangalam, India. He holds a B.Sc (Engg.) degree in Mechanical Engineering from Kerala University, and M.Tech and Ph.D degrees in Management from IIT Madras. His research areas are TQM and Organizational Behavior. He has published articles in the area of quality management in journals such as Total Quality Management and Business Excellence, and Quality Management Journal of American Society for Quality. Chandrasekharan Rajendran is a Professor of Operations Management in the Indian Institute of Technology Madras. His research interests are in TQM, Scheduling and Simulation. He has published several articles in international journals. He has publications in the area of TQM in journals such as Total Quality Management, International Journal of Production Research, International Journal of Service Industry Management, International Journal of Bank Marketing, and Journal of Services Marketing. He serves as referee for many journals. He is a recipient of the Alexander von Humboldt Fellowship of Germany. R.N. Anantharaman is a Professor of Management in the Indian Institute of Technology, Madras. His research interests are in TQM, Organizational Behavior and Industrial Psychology. He has published several articles in international journals. He has published research articles in the area of TQM, HRM Practices, Change Management, etc., in Journals such as Total Quality Management, International Journal of Production Research, International Journal of Bank Marketing, International Journal of Service Industry Management, Journal of Services Marketing, International Journal of Human Resource Management, and Journal of Transnational Management Development.     

The internal consistency and precedence of key process areas in the capability maturity model for software

Evaluating the reliability of maturity level (ML) ratings is crucial for providing confidence in the results of software process assessments. This study investigates the dimensions underlying the maturity construct in the Capability Maturity Model (CMM) for Software (SW-CMM) and estimates the internal consistency of each dimension. The results suggest that SW-CMM maturity is a three-dimensional construct, with “Project Implementation” representing the ML 2 key process areas (KPAs), “Organization Implementation” representing the ML 3 KPAs, and “Quantitative Process Implementation” representing the KPAs at MLs 4 and 5. The internal consistency for each of the three dimensions as estimated by Cronbach’s alpha exceeds the recommended value of 0.9. Based on those results, this study builds and tests a theoretical model which posits that the achievement of lower ML KPAs sustains the implementation of higher ML KPAs. Results of path analysis using partial least squares (PLS) support the theoretical model and provide detailed understanding of the process improvement path. The analysis is based on 676 CMM-Based Appraisal for Internal Process Improvement (CBA IPI) assessments.

Direct methods of solving systems of linear algebraic ef ions with complex a-matrices

Algorithms of computer algebra are proposed for solving systems of linear algebraic equations with complex á- matrices. An analysis of roundoff errors for the computational schemes considered is given. Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 144–156, March–April, 2000.     

Formalization of algorithmic knowledge of object domains in terms of the algebra of algorithmics

Clones of algebras of n-relations are examined. These clones include algebras equipotent to Codd’s algebra. The results obtained earlier for semigroup (grammatical and algorithmic) clones are extended to clones of algebras of functional n-relations. One-dimensional and multidimensional computing structures and related object domains are outlined. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 6, pp. 3–17, November–December 2007.     

Learning to trust in the competence and commitment of agents

For agents to collaborate in open multi-agent systems, each agent must trust in the other agents’ ability to complete tasks and willingness to cooperate. Agents need to decide between cooperative and opportunistic behavior based on their assessment of another agents’ trustworthiness. In particular, an agent can have two beliefs about a potential partner that tend to indicate trustworthiness: that the partner is competent and that the partner expects to engage in future interactions. This paper explores an approach that models competence as an agent’s probability of successfully performing an action, and models belief in future interactions as a discount factor. We evaluate the underlying decision framework’s performance given accurate knowledge of the model’s parameters in an evolutionary game setting. We then introduce a game-theoretic framework in which an agent can learn a model of another agent online, using the Harsanyi transformation. The learning agents evaluate a set of competing hypotheses about another agent during the simulated play of an indefinitely repeated game. The Harsanyi strategy is shown to demonstrate robust and successful online play against a variety of static, classic, and learning strategies in a variable-payoff Iterated Prisoner’s Dilemma setting.