1,182 research outputs found

    Trading reliability targets within a supply chain using Shapley's value

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    The development of complex systems involves a multi-tier supply chain, with each organisation allocated a reliability target for their sub-system or component part apportioned from system requirements. Agreements about targets are made early in the system lifecycle when considerable uncertainty exists about the design detail and potential failure modes. Hence resources required to achieve reliability are unpredictable. Some types of contracts provide incentives for organisations to negotiate targets so that system reliability requirements are met, but at minimum cost to the supply chain. This paper proposes a mechanism for deriving a fair price for trading reliability targets between suppliers using information gained about potential failure modes through development and the costs of activities required to generate such information. The approach is based upon Shapley's value and is illustrated through examples for a particular reliability growth model, and associated empirical cost model, developed for problems motivated by the aerospace industry. The paper aims to demonstrate the feasibility of the method and discuss how it could be extended to other reliability allocation models

    On the Evolution of Boomerang Uniformity in Cryptographic S-boxes

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    S-boxes are an important primitive that help cryptographic algorithms to be resilient against various attacks. The resilience against specific attacks can be connected with a certain property of an S-box, and the better the property value, the more secure the algorithm. One example of such a property is called boomerang uniformity, which helps to be resilient against boomerang attacks. How to construct S-boxes with good boomerang uniformity is not always clear. There are algebraic techniques that can result in good boomerang uniformity, but the results are still rare. In this work, we explore the evolution of S-boxes with good values of boomerang uniformity. We consider three different encodings and five S-box sizes. For sizes 4×44\times 4 and 5×55\times 5, we manage to obtain optimal solutions. For 6×66\times 6, we obtain optimal boomerang uniformity for the non-APN function. For larger sizes, the results indicate the problem to be very difficult (even more difficult than evolving differential uniformity, which can be considered a well-researched problem).Comment: 15 pages, 3 figures, 4 table

    A GPU-based multi-criteria optimization algorithm for HDR brachytherapy

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    Currently in HDR brachytherapy planning, a manual fine-tuning of an objective function is necessary to obtain case-specific valid plans. This study intends to facilitate this process by proposing a patient-specific inverse planning algorithm for HDR prostate brachytherapy: GPU-based multi-criteria optimization (gMCO). Two GPU-based optimization engines including simulated annealing (gSA) and a quasi-Newton optimizer (gL-BFGS) were implemented to compute multiple plans in parallel. After evaluating the equivalence and the computation performance of these two optimization engines, one preferred optimization engine was selected for the gMCO algorithm. Five hundred sixty-two previously treated prostate HDR cases were divided into validation set (100) and test set (462). In the validation set, the number of Pareto optimal plans to achieve the best plan quality was determined for the gMCO algorithm. In the test set, gMCO plans were compared with the physician-approved clinical plans. Over 462 cases, the number of clinically valid plans was 428 (92.6%) for clinical plans and 461 (99.8%) for gMCO plans. The number of valid plans with target V100 coverage greater than 95% was 288 (62.3%) for clinical plans and 414 (89.6%) for gMCO plans. The mean planning time was 9.4 s for the gMCO algorithm to generate 1000 Pareto optimal plans. In conclusion, gL-BFGS is able to compute thousands of SA equivalent treatment plans within a short time frame. Powered by gL-BFGS, an ultra-fast and robust multi-criteria optimization algorithm was implemented for HDR prostate brachytherapy. A large-scale comparison against physician approved clinical plans showed that treatment plan quality could be improved and planning time could be significantly reduced with the proposed gMCO algorithm.Comment: 18 pages, 7 figure

    Design Optimization of Folding Solar Powered Autonomous Underwater Vehicles Using Origami Structure

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    Origami, as an application for morphing structure engineering, which has been studied for a long time, has recently made remarkable progress in terms of technology. The most distinctive feature of this technology is the presence of two types, flat mode and folded mode. The origami algorithm enables the conversion of these two modes based on the mathematical formulations. Completion of this algorithm now means that origami is part of the design process and can be applied to applications. This thesis demonstrates a design process for origami-inspired morphing structures that transform between a flat configuration and a folded convex shape. There are many obstacles in the development of the design process. In particular, consideration should be given to the surface difference of the flat configuration and the folded convex mode. In this thesis, I introduce the design process which takes into consideration the origami structure design deeply. To demonstrate this process, I have selected an application which is emerging and interesting, that is, unmanned vehicles. Especially, the design of Autonomous Underwater Vehicles (AUVs) is a difficult challenge since it requires the consideration of various aspects such as mission range, controllability, energy source, and carrying capacity. The Predictive Parameterized Pareto Genetic Algorithm (P3GA) is selected as the optimization method to determine a parameterized Pareto frontier of design options with desired characteristics for a variety of missions for the AUV

    Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design – FMCAD 2021

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    The Conference on Formal Methods in Computer-Aided Design (FMCAD) is an annual conference on the theory and applications of formal methods in hardware and system verification. FMCAD provides a leading forum to researchers in academia and industry for presenting and discussing groundbreaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system design including verification, specification, synthesis, and testing

    Limited Information Shared Control and its Applications to Large Vehicle Manipulators

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    Diese Dissertation beschäftigt sich mit der kooperativen Regelung einer mobilen Arbeitsmaschine, welche aus einem Nutzfahrzeug und einem oder mehreren hydraulischen Manipulatoren besteht. Solche Maschinen werden für Aufgaben in der Straßenunterhaltungsaufgaben eingesetzt. Die Arbeitsumgebung des Manipulators ist unstrukturiert, was die Bestimmung einer Referenztrajektorie erschwert oder unmöglich macht. Deshalb wird in dieser Arbeit ein Ansatz vorgeschlagen, welcher nur das Fahrzeug automatisiert, während der menschliche Bediener ein Teil des Systems bleibt und den Manipulator steuert. Eine solche Teilautomatisierung des Gesamtsystems führt zu einer speziellen Klasse von Mensch-Maschine-Interaktionen, welche in der Literatur noch nicht untersucht wurde: Eine kooperative Regelung zwischen zwei Teilsystemen, bei der die Automatisierung keine Informationen von dem vom Menschen gesteuerten Teilsystem hat. Deswegen wird in dieser Arbeit ein systematischer Ansatz der kooperativen Regelung mit begrenzter Information vorgestellt, der den menschlichen Bediener unterstützen kann, ohne die Referenzen oder die Systemzustände des Manipulators zu messen. Außerdem wird ein systematisches Entwurfskonzept für die kooperative Regelung mit begrenzter Information vorgestellt. Für diese Entwurfsmethode werden zwei neue Unterklassen der sogenannten Potenzialspiele eingeführt, die eine systematische Berechnung der Parameter der entwickelten kooperativen Regelung ohne manuelle Abstimmung ermöglichen. Schließlich wird das entwickelte Konzept der kooperativen Regelung am Beispiel einer großen mobilen Arbeitsmaschine angewandt, um seine Vorteile zu ermitteln und zu bewerten. Nach der Analyse in Simulationen wird die praktische Anwendbarkeit der Methode in drei Experimenten mit menschlichen Probanden an einem Simulator untersucht. Die Ergebnisse zeigen die Überlegenheit des entwickelten kooperativen Regelungskonzepts gegenüber der manuellen Steuerung und der nicht-kooperativen Steuerung hinsichtlich sowohl der objektiven Performanz als auch der subjektiven Bewertung der Probanden. Somit zeigt diese Dissertation, dass die kooperative Regelung mobiler Arbeitsmaschinen mit den entwickelten theoretischen Konzepten sowohl hilfreich als auch praktisch anwendbar ist
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