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This 2028 Special Issue presents recent developments and achievements in the field of Mechanism and Machine Science coming from the Italian community with international collaborations and ranging from theoretical contributions to experimental and practical applications. It contains selected contributions that were accepted for presentation at the Second International Conference of IFToMM Italy, IFIT2018, that has been held in Cassino on 29 and 30 November 2018. This IFIT conference is the second event of a series that was established in 2016 by IFToMM Italy in Vicenza. IFIT was established to bring together researchers, industry professionals and students, from the Italian and the international community in an intimate, collegial and stimulating environment.

biomechanical engineering --- wearable robotics --- hand exoskeleton --- mechanism design and optimization --- kinematic analysis --- mechatronics --- Handwheelchair.q --- Disabled sport --- Manual wheelchair --- water wheel --- grain water mill --- wooden teeth gear --- history of mechanism and machine science --- micro-hydro --- renewable energy --- magneto-rheological elastomers --- smart materials --- semi-active isolator --- iron powder --- wearable device --- blood ultrafiltration --- mechatronic device --- renal replacement --- bevel gears --- gear design --- Tredgold --- numerical simulations --- shape memory alloy --- SMA wires --- flexible actuator --- modular actuator --- mathematical model --- experimental test --- tilting pad journal bearing --- nonlinear behavior --- experimental characterization --- stiffness modelling --- performance indices --- condition number --- volumetric isotropy index --- parallel manipulator --- two-stage planetary gearbox --- varying load --- dynamic torque --- efficiency --- rotating machinery --- Intelligent tire --- flex sensor --- PVDF sensor --- energy saving --- vehicle dynamics --- smart systems --- vibroprotection --- seismic --- rolling bearer --- vibration --- non-linear vibrations --- cumulative curves --- singular point --- n/a

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This computationally oriented book describes and explains the mathematical relationships among matrices, moments, orthogonal polynomials, quadrature rules, and the Lanczos and conjugate gradient algorithms. The book bridges different mathematical areas to obtain algorithms to estimate bilinear forms involving two vectors and a function of the matrix. The first part of the book provides the necessary mathematical background and explains the theory. The second part describes the applications and gives numerical examples of the algorithms and techniques developed in the first part. Applications addressed in the book include computing elements of functions of matrices; obtaining estimates of the error norm in iterative methods for solving linear systems and computing parameters in least squares and total least squares; and solving ill-posed problems using Tikhonov regularization. This book will interest researchers in numerical linear algebra and matrix computations, as well as scientists and engineers working on problems involving computation of bilinear forms.

Matrices. --- Numerical analysis. --- Mathematical analysis --- Algebra, Matrix --- Cracovians (Mathematics) --- Matrix algebra --- Matrixes (Algebra) --- Algebra, Abstract --- Algebra, Universal --- Matrices --- Numerical analysis --- Algorithm. --- Analysis of algorithms. --- Analytic function. --- Asymptotic analysis. --- Basis (linear algebra). --- Basis function. --- Biconjugate gradient method. --- Bidiagonal matrix. --- Bilinear form. --- Calculation. --- Characteristic polynomial. --- Chebyshev polynomials. --- Coefficient. --- Complex number. --- Computation. --- Condition number. --- Conjugate gradient method. --- Conjugate transpose. --- Cross-validation (statistics). --- Curve fitting. --- Degeneracy (mathematics). --- Determinant. --- Diagonal matrix. --- Dimension (vector space). --- Eigenvalues and eigenvectors. --- Equation. --- Estimation. --- Estimator. --- Exponential function. --- Factorization. --- Function (mathematics). --- Function of a real variable. --- Functional analysis. --- Gaussian quadrature. --- Hankel matrix. --- Hermite interpolation. --- Hessenberg matrix. --- Hilbert matrix. --- Holomorphic function. --- Identity matrix. --- Interlacing (bitmaps). --- Inverse iteration. --- Inverse problem. --- Invertible matrix. --- Iteration. --- Iterative method. --- Jacobi matrix. --- Krylov subspace. --- Laguerre polynomials. --- Lanczos algorithm. --- Linear differential equation. --- Linear regression. --- Linear subspace. --- Logarithm. --- Machine epsilon. --- Matrix function. --- Matrix polynomial. --- Maxima and minima. --- Mean value theorem. --- Meromorphic function. --- Moment (mathematics). --- Moment matrix. --- Moment problem. --- Monic polynomial. --- Monomial. --- Monotonic function. --- Newton's method. --- Numerical integration. --- Numerical linear algebra. --- Orthogonal basis. --- Orthogonal matrix. --- Orthogonal polynomials. --- Orthogonal transformation. --- Orthogonality. --- Orthogonalization. --- Orthonormal basis. --- Partial fraction decomposition. --- Polynomial. --- Preconditioner. --- QR algorithm. --- QR decomposition. --- Quadratic form. --- Rate of convergence. --- Recurrence relation. --- Regularization (mathematics). --- Rotation matrix. --- Singular value. --- Square (algebra). --- Summation. --- Symmetric matrix. --- Theorem. --- Tikhonov regularization. --- Trace (linear algebra). --- Triangular matrix. --- Tridiagonal matrix. --- Upper and lower bounds. --- Variable (mathematics). --- Vector space. --- Weight function.

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Many industries, such as transportation and manufacturing, use control systems to insure that parameters such as temperature or altitude behave in a desirable way over time. For example, pilots need assurance that the plane they are flying will maintain a particular heading. An integral part of control systems is a mechanism for failure detection to insure safety and reliability. This book offers an alternative failure detection approach that addresses two of the fundamental problems in the safe and efficient operation of modern control systems: failure detection--deciding when a failure has occurred--and model identification--deciding which kind of failure has occurred. Much of the work in both categories has been based on statistical methods and under the assumption that a given system was monitored passively. Campbell and Nikoukhah's book proposes an "active" multimodel approach. It calls for applying an auxiliary signal that will affect the output so that it can be used to easily determine if there has been a failure and what type of failure it is. This auxiliary signal must be kept small, and often brief in duration, in order not to interfere with system performance and to ensure timely detection of the failure. The approach is robust and uses tools from robust control theory. Unlike some approaches, it is applicable to complex systems. The authors present the theory in a rigorous and intuitive manner and provide practical algorithms for implementation of the procedures.

System failures (Engineering) --- Fault location (Engineering) --- Signal processing. --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Location of system faults --- System fault location (Engineering) --- Dynamic testing --- Failure of engineering systems --- Reliability (Engineering) --- Systems engineering --- A priori estimate. --- AIXI. --- Abuse of notation. --- Accuracy and precision. --- Additive white Gaussian noise. --- Algorithm. --- Approximation. --- Asymptotic analysis. --- Bisection method. --- Boundary value problem. --- Calculation. --- Catastrophic failure. --- Combination. --- Computation. --- Condition number. --- Continuous function. --- Control theory. --- Control variable. --- Decision theory. --- Derivative. --- Detection. --- Deterministic system. --- Diagram (category theory). --- Differential equation. --- Discrete time and continuous time. --- Discretization. --- Dynamic programming. --- Engineering design process. --- Engineering. --- Equation. --- Error message. --- Estimation theory. --- Estimation. --- Finite difference. --- Gain scheduling. --- Inequality (mathematics). --- Initial condition. --- Integrator. --- Invertible matrix. --- Laplace transform. --- Least squares. --- Likelihood function. --- Likelihood-ratio test. --- Limit point. --- Linear programming. --- Linearization. --- Mathematical optimization. --- Mathematical problem. --- Maxima and minima. --- Measurement. --- Method of lines. --- Monotonic function. --- Noise power. --- Nonlinear control. --- Nonlinear programming. --- Norm (mathematics). --- Numerical analysis. --- Numerical control. --- Numerical integration. --- Observational error. --- Open problem. --- Optimal control. --- Optimization problem. --- Parameter. --- Partial differential equation. --- Piecewise. --- Pointwise. --- Prediction. --- Probability. --- Random variable. --- Realizability. --- Remedial action. --- Requirement. --- Rewriting. --- Riccati equation. --- Runge–Kutta methods. --- Sampled data systems. --- Sampling (signal processing). --- Scientific notation. --- Scilab. --- Shift operator. --- Signal (electrical engineering). --- Sine wave. --- Solver. --- Special case. --- Stochastic Modeling. --- Stochastic calculus. --- Stochastic interpretation. --- Stochastic process. --- Stochastic. --- Theorem. --- Time complexity. --- Time-invariant system. --- Trade-off. --- Transfer function. --- Transient response. --- Uncertainty. --- Utilization. --- Variable (mathematics). --- Variance.