3D resistive RAM cell design for high-density storage class memory—a review

In this article, we comprehensively review recent progress in the ReRAM cell technology for 3D integration focusing on a material/device level. First we briefly mention pioneering work on high-density crossbar ReRAM arrays which paved the way to 3D integration. We discuss the two main proposed 3D integration schemes—3D horizontally stacked ReRAM vs 3D Vertical ReRAM and their respective advantages and disadvantages. We follow with the detailed memory cell design on important work in both areas, utilizing either filamentary or interface-limited switching mechanisms. We also discuss our own contributions on HfO₂-based filamentary 3D Vertical ReRAM as well as TaO_x/TiO₂ bilayer-based self-rectifying 3D Vertical ReRAM. Finally, we summarize the present status and provide an outlook for the nearterm future.     

Secure storage—Confidentiality and authentication

Secure disk storage is a rich and complex topic and its study is challenging in theory as well as in practice. In case of loss or theft of mobile devices (such as laptops and smartphones), the threat of data exposure is important and a natural security objective is to guarantee the confidentiality of the data-at-rest stored in such devices (e.g. on disks or solid-state drives). Classical approaches to encrypt data may have a severe impact on performance if the underlying architectural specificities are not considered. In particular, it is usually assumed that an encryption scheme suitable for the application of disk encryption must be length preserving. This so-called “full disk encryption” method provides confidentiality but does not provide cryptographic data integrity protection. It indeed rules out the use of authenticated encryption where an authentication tag is concatenated to the ciphertext. Moreover, authenticated encryption requires storing tags, and latency is added due to extra read/write accesses and tag computations. We present a comprehensive study of full disk encryption solutions and compare their features from a security perspective. We additionally present threat models for authenticated disk encryption and present a systematized analysis of the techniques usable in these settings (which has, up to now, received little attention from the research community). We finally review the current state-of-the-art of incremental cryptography and provide new insights for its use in secure disk storage contexts.     

Integrated statistical modeling method: part I—statistical simulations for symmetric distributions

Structural and Multidisciplinary Optimization - The use of parametric and nonparametric statistical modeling methods differs depending on data sufficiency. For sufficient data, the parametric...     

Atmospheric correction for inland waters—application to SeaWiFS

Inland waters are an increasingly valuable natural resource that has major impact and benefits for population and environment. The new generation of ocean colour sensors has better spatial resolution, and hence are suitable for monitoring water quality of lakes. As an alternative to standard algorithms developed for oceans, which often fail over inland waters, we propose here a scheme based on aerosol remote sensing over land. The ocean colour sensors have spectral bands that allow characterization of aerosols over dark land pixels (vegetation in the blue and in the red spectral bands). It is then possible to use a representative aerosol model (aerosol optical thickness and aerosol type) for atmospheric correction over inland waters after validating the spatial homogeneity of the aerosol model in the lake vicinity. The performance of this new algorithm is shown in Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) scenes of Lakes Balaton (Hungary) and Constance (Germany). We demonstrate the good spatial homogeneity of the aerosols and the meaningfulness of the water‐leaving reflectances derived over these two lakes.

We also addressed the particularity of Fresnel reflection computation. The direct to diffuse term of this Fresnel contribution is reduced because of the limited size of the lake. Based on the primary scattering approximation, we propose a simple formulation of this component. A specific Fresnel correction needs to be developed to fulfil the accuracy requirements.     

SIERRA—Simulation environment for memory redundancy algorithms

Extreme-scale computer systems take advantage of large arrays of general-purpose multicore processors coupled with specialized manycore accelerators. In order to support complex applications and correctly feed such processing elements, increasingly larger memory cores are integrated at different levels of the hierarchy. However, the adoption of increasingly aggressive manufacturing processes makes the memory sub-system particularly sensitive to faults. Error correcting codes (ECCs) allow the memory to recover from faults at run-time without interfering with the application execution. However, due to the loss of performance introduced every time an error must be corrected, the persistence of faults requires a more radical repair approach in which faulty cells are physically replaced by spare ones. Memory redundancy analysis (MRA) algorithms are used to drive the allocation process of spare resources. Many one-dimensional and two-dimensional MRAs have been proposed, but tools for evaluating their recovering capability are still not well established. This paper presents SIERRA, a simulation environment for precisely evaluating the repair efficiency of an MRA considering different fault signatures and faulty memory configurations. Our simulation engine provides a precise estimation of the MRA quality by analyzing the behavior of the MRA on several faulty memory configurations. To this end, different parameters such as the area of the memory blocks and the defect density are taken into account. The evaluation of the quality of an MRA takes into account its repairing capability, the power consumption derived from its execution, and the area overhead. Thanks to the use of a database for storing information, our tool is able to speed-up the simulation process by distributing it among several nodes. All these features make SIERRA essential in supporting the design of next-generation high-performance computers.     

Goal-oriented error estimation and h-adaptivity for Maxwell’s equations

Goal-oriented error estimates, based on dual solutions, are derived for the S-parameters of a waveguide cavity resonator and a computationally cheap method is proposed to compute these. Numerical results show that the error estimators are relatively accurate, usually well within a factor 2 from the exact errors. Adaptive mesh-refinement based on these estimates recovers optimal convergence rates for complete and incomplete, first and second order, curl-conforming finite elements of Nédélec type, despite singularities at reentrant corners. It is also shown numerically that the convergence rate is independent of the element-order when singularities are present and the mesh is refined uniformly.     

Should we routinely test for simultaneous location and scale changes?

It is argued that in many circumstances, there is no compelling reason to believe that measurements from several experimental groups have the same variability. If it is plausible that the variabilities may differ, a statistical test sensitive to changes of scale as well as to changes of location should be selected. Some references to such tests are given.     

Formulations and relaxations for a multi-echelon capacitated location–distribution problem

We consider a multi-echelon location–distribution problem arising from an actual application in fast delivery service. We present and compare two formulations for this problem: an arc-based model and a path-based model. We show that the linear programming (LP) relaxation of the path-based model provides a better bound than the LP relaxation of the arc-based model. We also compare the so-called binary relaxations of the models, which are obtained by relaxing the integrality constraints for the general integer variables, but not for the 0–1 variables. We show that the binary relaxations of the two models always provide the same bound, but that the path-based binary relaxation appears preferable from a computational point of view, since it can be reformulated as an equivalent simple plant location problem (SPLP), for which several efficient algorithms exist. We also show that the LP relaxation of this SPLP reformulation provides a better bound than the LP relaxation of the path-based model.     

Orthographic and morphological processing for English–Arabic statistical machine translation

Much of the work on statistical machine translation (SMT) from morphologically rich languages has shown that morphological tokenization and orthographic normalization help improve SMT quality because of the sparsity reduction they contribute. In this article, we study the effect of these processes on SMT when translating into a morphologically rich language, namely Arabic. We explore a space of tokenization schemes and normalization options. We also examine a set of six detokenization techniques and evaluate on detokenized and orthographically correct (enriched) output. Our results show that the best performing tokenization scheme is that of the Penn Arabic Treebank. Additionally, training on orthographically normalized (reduced) text then jointly enriching and detokenizing the output outperforms training on enriched text.     

Sensors and controllers location in distributed systems—A survey

A survey of the field of optimal sensors and/or controllers location for dynamical distributed parameter systems modelled by partial differential equations is presented. The recent contributions in this field are grouped according to the main goal for which the location problem is developed, namely: system identification, state estimation, and optimal control. In order to pose the sensors and controllers location problem, the semigroup approach for modelling distributed linear systems is briefly reviewed together with its equivalent (infinite dimensional) and approximate (finite dimensional) Fourier expansion representations. After presenting a concise general review of the several methods considered in the current literature, a classification of methods is also proposed. The main classifying factor concerns the use of N-modal approximation schemes, and the different stages of the optimization procedure in which they are required.     

Computer cryptographic techniques for processing and storage of confidential information†

This paper is concerned with basic techniques that are suitable for computational cryptography. The difficulties involved in constructing suitable crypto-programmes as well as the criteria for the choice of crypto-programmes are discussed. The relevant mathematical properties of transformations are worked out. On this basis, suitable transformation techniques such as arithmetical, logic, matrix, topological, functional and hierarchical schemes are described. Finally, a brief discussion is given on the system design for crypto -programming.     

Double encoding—a technique for reducing storage requirement of text

Many recent advances have been made in data storage and communications media. However, the explosive proliferation of information and the continuous growth of data applications are outgrowing any technological advances in storage devices and communications tools. Data compression offers an attractive approach to alleviate many of the problems associated with data proliferation. In this paper, we present a new double compression scheme for text, program source and documentation files. The first phase of compression is a dictionary-based method that also uses run-length encoding. The second phase of compression is based on utilizing the distributional and correlational properties of the output of the first phase. The technique achieves high degrees of compression and is further enhanced by the hardware assistance that VLSI technology will eventually offer to the realization of data compression techniques.     

A robust and convex metric for unconstrained optimization in statistical model calibration—probability residual (PR)

Structural and Multidisciplinary Optimization - Statistical model calibration is a practical tool for computational model development processes. However, in optimization-based model calibration,...     

A fourth-order B-spline collocation method and its error analysis for Bratu-type and Lane–Emden problems

Recently, Caglar et al. [B-spline method for solving Bratu's problem, Int. J. Comput. Math. 87(8) (2010), pp. 1885–1891] proposed a numerical technique based on cubic B-spline for solving a Bratu-type problem. This method provides a second-order convergent approximation to the solution of the problem. In this paper, we develop a high-order numerical method based on quartic B-spline collocation approach for the Bratu-type and Lane–Emden problems. The error analysis of the quartic B-spline interpolation is carried out. Some numerical examples are provided to demonstrate the efficiency and applicability of the method and to verify its rate of convergence. The numerical results are compared with exact solutions and a numerical method based on cubic B-spline approach. Comparison reveals that our method produces more accurate results than the method proposed by Caglar et al. [B-spline method for solving Bratu's problem, Int. J. Comput. Math. 87(8) (2010), pp. 1885–1891].     

A simple and effective evolutionary algorithm for the capacitated location–routing problem

This paper proposes a hybrid genetic algorithm (GA) to solve the capacitated location–routing problem. The proposed algorithm follows the standard GA framework using local search procedures in the mutation phase. Computational evaluation was carried out on three sets of benchmark instances from the literature. Results show that, although relatively simple, the proposed algorithm is effective, providing competitive results for benchmark instances within reasonable computing time.     

Design and experimental validation of a physics-based oxygen storage — thermal model for three way catalyst including aging

In this paper, a physics-based, oxygen storage-thermal model for a three way catalyst (TWC) is developed and experimentally validated. This model is then extended to account for aging impacts on the TWC. In order to identify the model parameters, a series of ad hoc experiments were designed to test the device over various engine operating conditions. Four TWCs of different ages were tested to investigate the effects of TWC aging on the oxygen storage dynamics. Results show that aging can be lumped within a single model parameter, referred to as oxygen storage capacity. Sensitivity analysis shows only negligible dependence of oxygen storage capacity on catalyst operating temperature. The comprehensive model is validated over real driving conditions for different catalyst ages. The developed model has the potential to enhance the design of optimization-control techniques for fuel consumption benefits and on-board diagnostics health measurement robustness.     

Goal-oriented error estimation and adaptivity for fluid–structure interaction using exact linearized adjoints

We develop duality-based a posteriori error estimates for functional outputs of solutions of steady fluid–structure-interaction problems. The crucial complication in obtaining these estimates pertains to the derivation of the coupled dual (exact linearized adjoint) problem owing to the free-boundary character of fluid–structure interaction. We present two approaches to derive the dual problem. In the domain-map linearization approach, the fluid subproblem is first transformed to a fixed reference domain, after which one essentially linearizes with respect to the domain transformation map. In the shape-linearization approach, fluid unknowns are fixed in the current configuration and a very weak formulation of the fluid subproblem is then linearized using shape-derivative techniques. We show that the dual problems correspond to coupled fluid–structure problems with nonstandard coupling conditions. Furthermore, we present numerical experiments that demonstrate the consistency of the dual-based error estimates and their usefulness in goal-oriented adaptive mesh-refinement.     

Dynamic–static unsupervised sequentiality,statistical subunits and lexicon for sign language recognition

We introduce a new computational phonetic modeling framework for sign language (SL) recognition. This is based on dynamic–static statistical subunits and provides sequentiality in an unsupervised manner, without prior linguistic information. Subunit “sequentiality” refers to the decomposition of signs into two types of parts, varying and non-varying, that are sequentially stacked across time. Our approach is inspired by the Movement–Hold SL linguistic model that refers to such sequences. First, we segment signs into intra-sign primitives, and classify each segment as dynamic or static, i.e., movements and non-movements. These segments are then clustered appropriately to construct a set of dynamic and static subunits. The dynamic/static discrimination allows us employing different visual features for clustering the dynamic or static segments. Sequences of the generated subunits are used as sign pronunciations in a data-driven lexicon. Based on this lexicon and the corresponding segmentation, each subunit is statistically represented and trained on multimodal sign data as a hidden Markov model. In the proposed approach, dynamic/static sequentiality is incorporated in an unsupervised manner. Further, handshape information is integrated in a parallel hidden Markov modeling scheme. The novel sign language modeling scheme is evaluated in recognition experiments on data from three corpora and two sign languages: Boston University American SL which is employed pre-segmented at the sign-level, Greek SL Lemmas, and American SL Large Vocabulary Dictionary, including both signer dependent and unseen signers' testing. Results show consistent improvements when compared with other approaches, demonstrating the importance of dynamic/static structure in sub-sign phonetic modeling.     

Forecasting daily total ozone concentration—a comparison between neurocomputing and statistical approaches

The present paper develops three predictive models for daily total ozone concentration over Arosa, Switzerland. The models are artificial neural network, multiple linear regression, and persistence forecast. Each model was judged for their predictive ability using analysis of variance, Pearson correlation study, and scatterplot analysis. Prediction errors were computed for each model. After painstaking analysis it was established that artificial neural network produces better forecasts than the statistical approaches like multiple linear regression and persistence forecast models.