Adaptive generic product structure modelling for design reuse in engineer-to-order products

In product lifecycle management, the efficiency of information reuse relies on the definition and management of equivalence information between various product data and structure representations. Equivalence information ensures the consistency and traceability of product information throughout the product lifecycle. The sales-delivery process of engineer-to-order (ETO) products presents a great potential for design reuse, i.e. the reuse of previously validated design solutions in the design of new product variants according to customer-specific requirements. A product family data model that focuses on the interdependencies of viewpoints on information will therefore improve the setup of design reuse mechanisms such as modularity. This paper describes the Adaptive Generic Product Structure (AGPS), a dynamic structure-based product family modelling approach that enables the systematic aggregation of product variants and their distinctive components. The purpose of the approach is to capitalize on the expanding component variety developed within previous product variants as early as the sales lead phase of the sales-delivery process, in order to reduce customer-driven design costs and shorten lead-times. An illustrative example based on the aerospace industry is presented.     

Competitive ratio of List Scheduling on uniform machines and randomized heuristics

We study online scheduling on m uniform machines, where m−1 of them have a reference speed 1 and the last one a speed s with 0≤s≤1. The competitive ratio of the well-known List Scheduling (LS) algorithm is determined. For some values of s and m=3, LS is proven to be the best deterministic algorithm. We describe a randomized heuristic for m machines. Finally, for the case m=3, we develop and analyze the competitive ratio of a randomized algorithm which outperforms LS for any s.     

Hierarchical control system design using approximate simulation

In this paper, we present a new approach for hierarchical control based on the recent notions of approximate simulation and simulation functions, a quantitative version of the simulation relations. Given a complex system that needs to be controlled and a simpler abstraction, we show how the knowledge of a simulation function allows us to synthesize hierarchical control laws by first controlling the abstraction and then lifting the abstract control law to the complex system using an interface. For the class of linear control systems, we give an effective characterization of the simulation functions and of the associated interfaces. This characterization allows us to use algorithmic procedures for their computation. We show how to choose an abstraction for a linear control system such that our hierarchical control approach can be used. Finally, we show the effectiveness of our approach on an example.     

Vision-based control of near-obstacle flight

This paper presents a novel control strategy, which we call optiPilot, for autonomous flight in the vicinity of obstacles. Most existing autopilots rely on a complete 6-degree-of-freedom state estimation using a GPS and an Inertial Measurement Unit (IMU) and are unable to detect and avoid obstacles. This is a limitation for missions such as surveillance and environment monitoring that may require near-obstacle flight in urban areas or mountainous environments. OptiPilot instead uses optic flow to estimate proximity of obstacles and avoid them. Our approach takes advantage of the fact that, for most platforms in translational flight (as opposed to near-hover flight), the translatory motion is essentially aligned with the aircraft main axis. This property allows us to directly interpret optic flow measurements as proximity indications. We take inspiration from neural and behavioural strategies of flying insects to propose a simple mapping of optic flow measurements into control signals that requires only a lightweight and power-efficient sensor suite and minimal processing power.     

EGALITARIAN NEGOTIATIONS IN AGENT SOCIETIES

Achieving fairness among the members of a society is an important issue in many resource allocation problems. The increasing focus of the computer sciences community is motivated by a large panel of applications where other welfare notions do not suit. Centralized approaches are usually used, but they suffer from important drawbacks. Because relationships among society members are not considered, the provided resource allocation may not be achievable in practice. This study seeks to provide an evenly distributed approach based on a multiagent system, which overcomes the main drawbacks of centralized approaches. We provide an adaptive, anytime, and scalable algorithm to hold efficient egalitarian negotiations. Negotiation processes lead to socially efficient allocations as an emergent phenomenon. We also evaluate the “price of the social graph” toward the negotiation efficiency, and we provide the agent behavior to implement in order to achieve fair allocations.     

Analytic preconditioners for the electric field integral equation

Since the advent of the fast multipole method, large‐scale electromagnetic scattering problems based on the electric field integral equation (EFIE) formulation are generally solved by a Krylov iterative solver. A well‐known fact is that the dense complex non‐hermitian linear system associated to the EFIE becomes ill‐conditioned especially in the high‐frequency regime. As a consequence, this slows down the convergence rate of Krylov subspace iterative solvers. In this work, a new analytic preconditioner based on the combination of a finite element method with a local absorbing boundary condition is proposed to improve the convergence of the iterative solver for an open boundary. Some numerical tests precise the behaviour of the new preconditioner. Moreover, comparisons are performed with the analytic preconditioner based on the Calderòn's relations for integral equations for several kinds of scatterers. Copyright © 2004 John Wiley & Sons, Ltd.     

Reversible,Fast, and Wide‐Range Oxygen Sensor Based on Nanostructured Organometal Halide Perovskite

Nanostructured materials characterized by high surface–volume ratio hold the promise to constitute the active materials for next‐generation sensors. Solution‐processed hybrid organohalide perovskites, which have been extensively used in the last few years for optoelectronic applications, are characterized by a self‐assembled nanostructured morphology, which makes them an ideal candidate for gas sensing. Hitherto, detailed studies of the dependence of their electrical characteristics on the environmental atmosphere have not been performed, and even the effect of a ubiquitous gas such as O₂ has been widely overlooked. Here, the electrical response of organohalide perovskites to oxygen is studied. Surprisingly, a colossal increase (3000‐fold) in the resistance of perovskite‐based lateral devices is found when measured in a full oxygen atmosphere, which is ascribed to a trap healing mechanism originating from an O₂‐mediated iodine vacancies filling. A variation as small as 70 ppm in the oxygen concentration can be detected. The effect is fast (<400 ms) and fully reversible, making organohalide perovskites ideal active materials for oxygen sensing. The effect of oxygen on the electrical characteristics of organohalide perovskites must be taken into deep consideration for the design and optimization of any other perovskite‐based (opto‐) electronic device working in ambient conditions.     

International patent families: from application strategies to statistical indicators

This paper provides an in-depth analysis of the characteristics of international patent families, including their domestic component. We exploit a relatively under-studied feature of patent families, namely the number of patents covering the same invention within a given jurisdiction. Using this information, we highlight common patterns in the structure of international patent families, which reflect both the patenting strategies of innovators and the peculiarities of the different patent systems. While the literature has extensively used family size, i.e. the number of countries in which a given invention is protected, as a measure of patent value, our results suggest that the number of patent filings in the priority country within a patent family as well as the timespan between the first and last filings within a family are other insightful indicators of the value of patented innovations.     

Templated Solid‐State Dewetting of Thin Silicon Films

Thin film dewetting can be efficiently exploited for the implementation of functionalized surfaces over very large scales. Although the formation of sub‐micrometer sized crystals via solid‐state dewetting represents a viable method for the fabrication of quantum dots and optical meta‐surfaces, there are several limitations related to the intrinsic features of dewetting in a crystalline medium. Disordered spatial organization, size, and shape fluctuations are relevant issues not properly addressed so far. This study reports on the deterministic nucleation and precise positioning of Si‐ and SiGe‐based nanocrystals by templated solid‐state dewetting of thin silicon films. The dewetting dynamics is guided by pattern size and shape taking full control over number, size, shape, and relative position of the particles (islands dimensions and relative distances are in the hundreds nm range and fluctuate ≈11% for the volumes and ≈5% for the positioning).