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.     

Kalman filter for controlled hybrid systems

The linear partially observed discrete-continuous (hybrid) stochastic controllable system described by differential equations with measures is considered. The optimal filtering equations in the form of generalized Kalman filter are obtained in the case of non-anticipating control. This result could be a theoretical basis for the optimal control in stochastic hybrid systems with incomplete information.     

On quadratic two-parameter families of spheres and their envelopes

In the present paper we investigate rational two-parameter families of spheres and their envelope surfaces in Euclidean . The four dimensional cyclographic model of the set of spheres in is an appropriate framework to show that a quadratic triangular Bézier patch in corresponds to a two-parameter family of spheres with rational envelope surface. The construction shows also that the envelope has rational offsets. Further we outline how to generalize the construction to obtain a much larger class of surfaces with similar properties.     

The influence of microstructure on the fracture toughness of AISI M2 high‐speed steel

When modelling the fracture toughness of the investigated AISI M2 high‐speed steel, the stress‐modified critical strain criterion was used. The very important influence of microstructural parameters such as the volume fraction of undissolved eutectic carbides, their mean diameter, and the mean distance between the carbides, as well as the volume fraction of retained austenite in the matrix, was also taken into account. The influence of yield stress and fracture ductility was expressed in terms of the hardness of the steel. It was found that the plastic zone which develops, during fracture toughness measurements, ahead of the fatigue crack tip, was, as a rule, smaller than the prior austenite grain size, so that, in the case of the investigated high‐speed steel, the size of these grains did not have any influence on the measured fracture toughness value. However, importantly, the calculated fracture toughness values, which were derived using a newly developed semi‐empirical equation, agreed well with the experimental results obtained by the authors, as well as with results obtained by other authors.     

An auto-generated real-time iteration algorithm for nonlinear MPC in the microsecond range

In this paper, we present an automatic C-code generation strategy for real-time nonlinear model predictive control (NMPC), which is designed for applications with kilohertz sample rates. The corresponding code export module has been implemented within the software package ACADO Toolkit. It is capable of exporting fixed step-size integrators together with their sensitivities as well as a real-time Gauss–Newton method. Here, we employ the symbolic representation of optimal control problems in ACADO in order to auto-generate plain C-code which is optimized for final production. The exported code has been tested for model predictive control scenarios comprising constrained nonlinear dynamic systems with four states and a control horizon of ten samples. The numerical simulations show a promising performance of the exported code being able to provide feedback in much less than a millisecond.     

2D structured grid generation method producing a mesh with prescribed properties near boundary

A variational method of generating a structured mesh on a two-dimensional domain is considered. To this end, a quasiconformal mapping of the parametric domain with a given Cartesian mesh onto the underlying physical domain is used. The functions implementing the mapping are sought by solving the Dirichlet problem for the system of elliptic second-order partial differential equations. An additional control for the cell shape is executed by introducing a local mapping which induces a control metric. In some particular cases, instead of an additional local mapping, a global mapping of the parametric domain onto the intermediate domain is used, where the curvilinear mesh is produced, and next this domain is mapped onto the underlying physical domain. The control metric allows to obtain a mesh with required properties: grid line orthogonality and prescribed mesh point clustering near the domain boundary. Examples of mesh in the annulus and near airfoil are presented.     

Agents’ model of uncertainty

Multi-agent systems play an increasing role in sensor networks, software engineering, web design, e-commerce, robotics, and many others areas. Uncertainty is a fundamental property of these areas. Agent-based systems use probabilistic and other uncertainty models developed earlier without explicit consideration of agents. This paper explores the impact of agents on uncertainty models and theories. We compare two methods of introducing agents to uncertainty theories and propose a new theory called the agent-based uncertainty theory (AUT). We show advantages of AUT for advancing multi-agent systems and for solving an internal fundamental question of uncertainty theories, that is identifying coherent approaches to uncertainty. The advantages of AUT are that it provides a uniform agent-based representation and an operational empirical interpretation for several uncertainty theories such as rough set theory, fuzzy sets theory, evidence theory, and probability theory. We show also that the introduction of agents to intuitionist uncertainty formalisms can reduce their conceptual complexity. To build such uniformity the AUT exploits the fact that agents as independent entities can give conflicting evaluations of the same attribute. The AUT is based on complex aggregations of crisp (non-fuzzy) conflicting judgments of agents. The generality of AUT is derived from the logical classification of types (orders) of conflicts in the agent populations. At the first order of conflict, the two agent populations are disjoint and there is no interference of logic values assigned to any statement p and its negation by agents. The second order of conflict models superposition (interference) of logic values for overlapping agent populations where an agent assigns conflicting logic values (true, false) to the same attribute simultaneously.

Discovering common outcomes of agents’ communicative actions in various domains

We explore the common patterns of human behavior, expressed via communicative actions, and displayed in various domains of human activities associated with conflicts. We build the generic methodology based on machine learning and reasoning to predict specific communicative actions of human agents, given previous sequence of communicative actions of themselves and their opponents. This methodology is applied to textual as well as structured data on inter-human conflicts of diverse modalities. Scenarios are represented by directed graphs with labeled vertices (for communicative actions) and arcs (for temporal and causal relationships between subjects of these actions). Scenario representation and learning techniques are firstly developed in the domain of textual customer complaints, and then applied to such problems as predicting an outcome of international conflicts, assessment of an attitude of a security clearance candidate, mining emails for suspicious emotional profiles, and recognizing suspicious behavior of cell phone users. We present an evaluation of the proposed methodology in the domain of customer complaint and conduct some comparative evaluation in the other domains mentioned above. Successful use of the proposed methodology in rather distinct domains shows its adequacy for mining human attitude-related data in a wide range of applications.     

A network of ontology networks for building e-employment advanced systems

This paper presents the development of a network of ontology networks that enables data mediation between the Employment Services (ESs) participating in a semantic interoperability platform for the exchange of Curricula Vitae (CVs) and job offers in different languages. Such network is formed by (1) a set of local ontology networks that are language dependent, in which each network represents the local and particular view that each ES has of the employment market; and (2) a reference ontology network developed in English that represents a standardized and agreed upon terminology of the European employment market. In this network each local ontology network is aligned with the reference ontology network so that search queries, CVs, and job offers can be mediated through these alignments from any ES. The development of the ontologies has followed the methodological guidelines issued by the NeOn Methodology and is focused mainly on scenarios that involve reusing and re-engineering knowledge resources already agreed upon by employment experts and standardization bodies. This paper explains how these methodological guidelines have been applied for building e-employment ontologies. In addition, it shows that the approach to building ontologies by reusing and re-engineering agreed upon non-ontological resources speeds the ontology development, reduces development costs, and retrieves knowledge already agreed upon by a community of people in a more formal representation.