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Finding Errors of Hybrid Systems by Optimising an Abstraction-Based Quality Estimate [chapter]

Stefan Ratschan, Jan-Georg Smaus
2009 Lecture Notes in Computer Science  
We present an algorithm for falsifying safety properties of hybrid systems, i.e., for finding a trajectory to an unsafe state.  ...  The approach is to approximate how close a point is to being an initial point of an error trajectory using a real-valued quality function, and then to use numerical optimisation to search for an optimum  ...  Then we use numerical optimisation techniques to search for an optimum of this quality estimate.  ... 
doi:10.1007/978-3-642-02949-3_12 fatcat:dorxbcuzlbg63ln7qb4np3ylsm

Soft computing-based colour quantisation

Gerald Schaefer
2014 EURASIP Journal on Image and Video Processing  
Those selected colours form a colour palette, while the resulting image quality is directly determined by the choice of colours in the palette.  ...  Finally, it is demonstrated how optimisation-based colour quantisation can be employed in conjunction with a more appropriate measure for image quality.  ...  The solid line represents the average quantisation error over time (iterations) while the dashed line represents the best solution of each iteration. 255 2 MSE(O, Q) , (13) Hybrid optimisation-based  ... 
doi:10.1186/1687-5281-2014-8 fatcat:2pyewn4ybngrhhdkjubzsx2noe

A survey of AI in operations management from 2005 to 2009

Khairy A.H. Kobbacy, Sunil Vadera, Khairy A.H. Kobbacy
2011 Journal of Manufacturing Technology Management  
Research on utilising neural networks, case based reasoning, fuzzy logic, knowledge based systems, data mining, and hybrid AI in the four application areas are identified.  ...  Findings: The survey categorises over 1400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future  ...  They compare the hybrid system with a pure GA based approach and conclude that their hybrid system produces better results.  ... 
doi:10.1108/17410381111149602 fatcat:htpu2mf4q5gu5aamziz46pzf7m

Cross-layer signalling and middleware: A survey for inelastic soft real-time applications in MANETs

Sarogini Grace Pease, Lin Guan, Iain Phillips, Alan Grigg
2011 Journal of Network and Computer Applications  
These streams are characterised by critical timing and throughput requirements and low packet loss tolerance levels.  ...  Many Cross Layer approaches exist either for provision of QoS to soft real-time streams in static wireless networks or to improve the performance of real and non-real-time transmissions in MANETs.  ...  Acknowledgment This work is sponsored by the Engineering and Physical Science Research Council (EPSRC) and BAE Systems, UK.  ... 
doi:10.1016/j.jnca.2011.07.005 fatcat:pwk3w6q72vf6zj2kzbczhdrxxm

Guiding Complex Design Optimisation Using Bayesian Networks [chapter]

John Leaney, Artem Parakhine
2010 Bayesian Network  
The process of design optimisation is a special form of design synthesis characterised by a high level of specificity with respect to its goals.  ...  prevalent approaches to architectural system design can be separated into two groups based on their main artefacts: quality-driven and model-driven (Parakhine, 2009, p. 22).  ...  The ultimate aim of the process is to find a solution that represents an optimal compromise on competing system qualities.  ... 
doi:10.5772/10074 fatcat:3w2qwhdsefdqdeojah5fnapmee

D2.1 Requirements, KPIs, evaluation plan and architecture - First version

Luciano Baresi
2020 Zenodo  
Both UML use cases and architecture will be treated as living artifacts and will be evolved and updated on the basis of the new findings that will arise through the project.  ...  In particular, D6.1, among the other data, provides a list of the used technologies with the corresponding references, the time plan for the development of the SODALITE platform, as well as the implementation  ...  Acknowledgement The work described in this document has been conducted within the Research & Innovation action SODALITE (project no. 825480), started in February 2019, and co-funded by the European Commis  ... 
doi:10.5281/zenodo.4280682 fatcat:ajp6mvopmfhdlgr2gj7g4cep4e

Additive Manufacturing, Cloud-Based 3D Printing and Associated Services—Overview

Felix Baumann, Dieter Roller
2017 Journal of Manufacturing and Materials Processing  
With this review we provide an overview over CM, AM and relevant domains as well as present the historical development of scientific research in these fields, starting from 2002.  ...  In order to be of use in these scenarios the AM resources must adhere to a strict principle of transparency and service composition in adherence to the Cloud Computing (CC) paradigm.  ...  Conflicts of Interest: The authors declare no conflict of interest. Disclaimer: This work is not funded by any third party.  ... 
doi:10.3390/jmmp1020015 fatcat:36ygp5r6xjebbha6p75vyqvxue

Multi-objective design optimisation of standalone hybrid wind-PV-diesel systems under uncertainties

Alireza Maheri
2014 Renewable Energy  
Abstract Optimal design of a standalone wind-PV-diesel hybrid system is a multi-objective optimisation problem with conflicting objectives of cost and reliability.  ...  Citation: Maheri, Alireza (2014) Multi-objective design optimisation of standalone hybrid wind-PV-diesel systems under uncertainties. Renewable Energy, 66. pp. 650-661.  ...  The solution space for hybrid systems is clustered with multiple local optima. This can impact the search performance of an ordinary GA.  ... 
doi:10.1016/j.renene.2014.01.009 fatcat:fqs5mu44t5giphwtntt4ojd2ua

Machine learning for biochemical engineering: A review

Max Mowbray, Thomas Savage, Chufan Wu, Ziqi Song, Bovinille Anye Cho, Ehecatl A. Del Rio-Chanona, Dongda Zhang
2021 Biochemical engineering journal  
Finally, core challenges into the application of machine learning in biochemical engineering are thoroughly discussed, and further insight into adoption of innovative hybrid modelling and transfer learning  ...  A B S T R A C T The field of machine learning is comprised of techniques, which have proven powerful approaches to knowledge discovery and construction of 'digital twins' in the highly dimensional, nonlinear  ...  In the offline learning stage, the authors abstract optimal control inputs to the system based on an assumed model of the system.  ... 
doi:10.1016/j.bej.2021.108054 fatcat:jvbkblcoevghxm4swnormswt64

Fixed-point refinement of digital signal processing systems [chapter]

Daniel Ménard, Gabriel Caffarena, Juan Antonio Lopez, David Novo, Olivier Sentieys
2019 Digitally Enhanced Mixed Signal Systems  
Fixed-point arithmetic provides low-cost operators at the expense of an unavoidable error between the ideal precision values and the finite precision ones.  ...  For the digital signal processing (DSP) part of mixed-signal systems, fixed-point arithmetic is favoured due to its high efficiency in terms of implementation cost, namely energy consumption, area, and  ...  The error estimation is based on analytical techniques, using the Signal-to-Quantisation-Noise Ratio (SQNR) to steer the optimisation (see Section 6.2.2).  ... 
doi:10.1049/pbcs040e_ch8 fatcat:32bburhxjreypjca3zuc4bodb4

CodeSLAM - Learning a Compact, Optimisable Representation for Dense Visual SLAM [article]

Michael Bloesch, Jan Czarnowski, Ronald Clark, Stefan Leutenegger, Andrew J. Davison
2019 arXiv   pre-print
Our approach is suitable for use in a keyframe-based monocular dense SLAM system: While each keyframe with a code can produce a depth map, the code can be optimised efficiently jointly with pose variables  ...  The representation of geometry in real-time 3D perception systems continues to be a critical research issue.  ...  Acknowledgements Research presented in this paper has been supported by Dyson Technology Ltd.  ... 
arXiv:1804.00874v2 fatcat:amays4eaijdm3ibmjgsm45yl3m

WCET and Mixed-Criticality: What does Confidence in WCET Estimations Depend Upon?

Sebastian Altmeyer, Björn Lisper, Claire Maiza, Jan Reineke, Christine Rochange, Marc Herbstritt
2015 Worst-Case Execution Time Analysis  
In this paper, we refine this view by exploring sources of doubt in the correctness of both static and measurement-based WCET analysis.  ...  One aspect of correctness is timing. Confidence in worst-case execution time (WCET) estimates depends on the process by which they have been obtained.  ...  Discussion and Open questions We have discussed possible sources of errors in different WCET analysis methods: static, measurement-based, and hybrid methods, and how the potential for such errors will  ... 
doi:10.4230/oasics.wcet.2015.65 dblp:conf/wcet/AltmeyerLMRR15 fatcat:cj4y66ubdrfdzkcmy3livaae7a

CodeSLAM - Learning a Compact, Optimisable Representation for Dense Visual SLAM

Michael Bloesch, Jan Czarnowski, Ronald Clark, Stefan Leutenegger, Andrew J. Davison
2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition  
Our approach is suitable for use in a keyframe-based monocular dense SLAM system: While each keyframe with a code can produce a depth map, the code can be optimised efficiently jointly with pose variables  ...  The representation of geometry in real-time 3D perception systems continues to be a critical research issue.  ...  Acknowledgements Research presented in this paper has been supported by Dyson Technology Ltd.  ... 
doi:10.1109/cvpr.2018.00271 dblp:conf/cvpr/BloeschCCLD18 fatcat:bnftzklvqfb2ffdoxkiu4pmfm4

A computational study of turbulent flow separation for a circular cylinder using skin friction boundary conditions [chapter]

Johan Hoffman, Niclas Jansson
2011 ERCOFTAC Series  
In moment-closure approximations, the BE is projected onto a polynomial space, in the velocity dependence, and the system is closed by providing an approximation to the one-particle marginal based on the  ...  This is scheduled in an overall adaptive scheme, trying to realize step by step verification and validation of this coupled process. Abstract.  ...  ACKNOWLEDGEMENTS The editors and conference organizers acknowledge the support by the following organizations, which made possible the publication of this book of Abstracts, the (online or CD) publication  ... 
doi:10.1007/978-94-007-0231-8_5 fatcat:f6ll6iawcbeo7pbj4rb7t4o2tq

A Population-Based Incremental Learning Method for Constrained Portfolio Optimisation

Yan Jin, Rong Qu, Jason Atkin
2014 2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing  
This paper investigates a hybrid algorithm which utilizes exact and heuristic methods to optimise asset selection and capital allocation in portfolio optimisation.  ...  It is based on the standard Markowitz model with additional practical constraints such as cardinality on the number of assets and quantity of the allocated capital.  ...  Abstract-This paper investigates a hybrid algorithm which utilizes exact and heuristic methods to optimise asset selection and capital allocation in portfolio optimisation.  ... 
doi:10.1109/synasc.2014.36 dblp:conf/synasc/JinQA14 fatcat:x2g7mwgvhzhexbq3qgvmxadx7y
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