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In a series of papers (2011-2013) N. Ma and P. Ishwar considered a range of distributed source coding problems that arise in the context of interactive computation of functions, characterizing the region of achievable communication rates. We consider the problems of interactive computation of functions by two terminals and interactive computation in a collocated network, showing that the rate regions for both these problems can be achieved using several rounds of polar-coded transmissions. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates the response of composite sandwich beams with honeycomb core subjected to low-velocity impact by using a finite-element model implemented in Abaqus/Explicit code. The face-sheets behaviour was modelled through a VUMAT subroutine, in which a failure model based on Hou failure criteria was implemented. The aluminium honeycomb core behaviour was defined as an elastic–plastic material. A series of low-velocity impact tests were carried out to validate the numerical model. Good agreement, in terms of contact-force histories, energy histories, absorbed energy, and failure of the sandwich beam was observed between the experimental data and the numerical results. The contribution of both the face-sheets and the core to the energy absorption process was analysed separately. It was found that the core controlled the energy absorption of the sandwich beams at the lowest impact velocities studied; however, at higher impact velocities the face-sheets were more involved. [Copyright &y& Elsevier]

Abstract: This paper provides FORTRAN subroutines for the calculation of the partially-Correlated quadratic-Speed-Dependent Hard-Collision (pCqSDHC) profile and of its two limits: the quadratic-Speed-Dependent Voigt (qSDV) and the quadratic-Speed-Dependent Hard-Collision (qSDHC) profiles. Numerical tests successfully confirm the analytically derived fact that all these profiles can be expressed as combinations of complex Voigt probability functions. Based on a slightly improved version of the CPF subroutine [Humlicek. J Quant Spectrosc Radiat Transfer 1979;21:309] for the calculation of the complex probability function, we show that the pCqSDHC, qSDHC and qSDV profiles can be quickly calculated with an accuracy better than 10−4. [Copyright &y& Elsevier]

Highlights: [•] A new approach for the formation of type-2 membership functions is introduced. [•] The footprint of uncertainty is formed by using rectangular type-2 fuzzy granules. [•] This new approach provides more degrees of freedom and design flexibility in type-2 fuzzy logic systems. [•] Mathematical expressions and derivative computations of granular type-2 membership functions are very simple. [•] Type-2 fuzzy logic systems using granular type-2 membership functions have more potential to model and handle uncertainties. [ABSTRACT FROM AUTHOR]

Abstract: This numerical investigation of an advanced Gurson–Tvergaard–Needleman (GTN) model is an extension of the original work of Ben Bettaiebet al. (2011 [18]). The model has been implemented as a user-defined material model subroutine (VUMAT) in the Abaqus/explicit FE code. The current damage model extends the previous version by integrating the three damage mechanisms: nucleation, growth and coalescence of voids. Physically based void nucleation and growth laws are considered, including an effect of the kinematic hardening. These new contributions are based and validated on experimental results provided by high-resolution X-ray absorption tomography measurements. The current damage model is applied to predict the damage evolution and the stress state in a tensile notched specimen experiment. [Copyright &y& Elsevier]

Abstract: A potential-based cohesive zone model, so called the PPR model, is implemented in a commercial software, e.g. ABAQUS, as a user-defined element (UEL) subroutine. The intrinsic cohesive zone modeling approach is employed because it can be formulated within the standard finite element framework. The implementation procedure for a two-dimensional linear cohesive element and the algorithm for the PPR potential-based model are presented in-detail. The source code of the UEL subroutine is provided in for educational purposes. Three computational examples are investigated to verify the PPR model and its implementation. The computational results of the model agree well with the analytical solutions. [Copyright &y& Elsevier]

Abstract: In this work, artificial neural networks (ANNs) are proposed to predict the dorsal pressure over the foot surface exerted by the shoe upper while walking. A model that is based on the multilayer perceptron (MLP) is used since it can provide a single equation to model the exerted pressure for all the materials used as shoe uppers. Five different models are produced, one model for each one of the four subjects under study and an overall model for the four subjects. The inputs to the neural model include the characteristics of the material and the positions during a whole step of 14 pressure sensors placed on the foot surface. The goal is to find models with good generalization capabilities, (i.e., models that work appropriately not only for the cases used to train the model but also for new cases) in order to have a useful predictor in routine practice. New cases may involve either new materials for the same subject or even new subjects and new materials. To accomplish this goal, two thirds of the patterns are trained to obtain the model (training data set) and the remaining third is kept for validation purposes. The achieved accuracy was very satisfactory since correlation coefficients between the predicted output and the actual pressure in the validation data were higher than 0.95 for those models developed for individual subjects. For the much more challenging problem of an overall prediction for all the subjects, the correlation coefficient was close to 0.9 in the validation data set (i.e., with data not previously seen by the model). [Copyright &y& Elsevier]

In this article we describe an object perception system for autonomous robots performing everyday manipulation tasks in kitchen environments. The perception system gains its strengths by exploiting that the robots are to perform the same kinds of tasks with the same objects over and over again. It does so by learning the object representations necessary for the recognition and reconstruction in the context of pick-and-place tasks. The system employs a library of specialized perception routines that solve different, well-defined perceptual sub-tasks and can be combined into composite perceptual activities including the construction of an object model database, multimodal object classification, and object model reconstruction for grasping. We evaluate the effectiveness of our methods, and give examples of application scenarios using our personal robotic assistants acting in a human living environment. [ABSTRACT FROM PUBLISHER]

In this work, we study the computational perspective of network coding, focusing on two issues. First, we address the computational complexity of finding a network code for acyclic multicast networks. Second, we address the issue of reducing the amount of computation performed by network nodes. In particular, we consider the problem of finding a network code with the minimum possible number of encoding nodes, i.e., nodes that generate new packets by performing algebraic operations on packets received over incoming links. We present a deterministic algorithm that finds a feasible network code for a multicast network over an underlying graph G(V, E) in time O(∣E∣kh + ∣V∣k²h² + h4k³(k + h)), where k is the number of destinations and h is the number of packets. Our algorithm improves the best known running time for network code construction. In addition, our algorithm guarantees that the number of encoding nodes in the obtained network code is upper-bounded by O(h³k²). Next, we address the problem of finding integral and fractional network codes with the minimum number of encoding nodes. We prove that in the majority of settings this problem is NP-hard. However, we show that if h, = O(1), k = O(1), and the underlying communication graph is acyclic, then there exists an algorithm that solves this problem in polynomial time. [ABSTRACT FROM AUTHOR]

A high-performance architecture of elliptic curve scalar multiplication based on the Montgomery ladder method over finite field CF(2m) is proposed. A pseudopipelined word-serial finite field multiplier, with word size w, suitable for the scalar multiplication is also developed, Implemented in hardware, this system performs a scalar multiplication in approximately 6[m/w](m - 1) clock cycles, and the gate delay in the critical path is equal to TAND + log2(w/k)]TXOR, where TAND and TXOR are delays due to two-input AND and XOR gates, respectively, and 1 ≤ k ⪡ w is used to shorten the critical path. [ABSTRACT FROM AUTHOR]

The problem of computing functions of values at the nodes in a network in a fully distributed manner, where nodes do not have unique identities and make decisions based only on local information, has applications in sensor, peer-to-peer, and ad hoc networks. The task of computing separable functions, which can be written as linear combinations of functions of individual variables, is studied in this context. Known iterative algorithms for averaging can be used to compute the normalized values of such functions, but these algorithms do not extend, in general, to the computation of the actual values of separable functions. The main contribution of this paper is the design of a distributed randomized algorithm for computing separable functions. The running time of the algorithm is shown to depend on the running time of a minimum computation algorithm used as a subroutine. Using a randomized gossip mechanism for minimum computation as the sub-routine yields a complete fully distributed algorithm for computing separable functions. For a class of graphs with small spectral gap, such as grid graphs, the time used by the algorithm to compute averages is of a smaller order than the time required by a known iterative averaging scheme. [ABSTRACT FROM AUTHOR]

A number of authors have looked at the problem of deriving a checking experiment from a nondeterministic finite state machine that models the required behaviour of a system. We show that these methods can be extended if it is known that the implementation is equivalent to some (unknown) deterministic finite state machine. When testing a deterministic implementation, the test output provides information about the implementation under test and can thus guide future testing. The use of an adaptive test process is thus proposed. [ABSTRACT FROM AUTHOR]

SUMMARY The subroutine system FIT is a new algorithm for the fitting of statistical models to data. Its purpose is to make available a wide range of model-fitting procedures in a single system. At the same time, the algorithm is a case study for the design of statistical computing systems; a number of relevant questions (and possibly a few answers) have arisen during the design of the system. [ABSTRACT FROM AUTHOR]

Abstract: Coastal and regional ocean forecasts can be currently performed on a daily basis due to the advances in numerical techniques and in computational resources. Maintenance of routine forecasts is a demanding task from the point of view of software engineering since it involves a number of new additional tasks difficult to code efficiently in the compiled languages in which ocean models are written. In this contribution, we present a set of free, open-source, portable and fast modules named OOFɛ – Operational Ocean Forecast Python Engine that provide a way to cope with the demanding requirements of routine execution of a regional ocean model written in a compiled language (namely the Regional Ocean Modelling System, ROMS, developed in Fortran) and that make the forecast process possible and fully automatic and robust. [Copyright &y& Elsevier]

Focuses on several improvements to the estimation of partial derivatives in Algorithm 761. Calculation of the probability and final weights in subroutine SDPD3P; Computation of a determinant in subroutine SDLEQN; Calculation of the condition number of a matrix in subroutine SDLEQN.