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Numerous studies from the past five decades have shown that selective retrieval of some studied items can impair recall of other items. This chapter reviews more recent work, in which it is demonstrated that selective memory retrieval has two faces and that it can both impair and improve recall of other items. In this recent work, participants' access to study context during selective retrieval was experimentally manipulated and it was examined whether such manipulation influences the effects of selective retrieval. Access to study context was manipulated using listwise directed forgetting, context-dependent forgetting and time-dependent forgetting. The results consistently showed that selective retrieval impairs recall of other memories if access to study context during retrieval is largely maintained, but that selective retrieval can improve recall if study context access is impaired. The findings are explained by a two-factor account, which claims that, in general, selective retrieval does not only trigger inhibition and blocking but also triggers context reactivation processes. The proposal is that primarily inhibition and blocking operate when study context access during selective retrieval is largely maintained, whereas primarily context reactivation processes operate when study context access is impaired. Current findings on the two faces of selective retrieval are well consistent with this theoretical view.
The open and cooperative nature of Cyber-Physical Systems (CPS) poses new challenges in assuring dependability. The DEIS project (Dependability Engineering Innovation for automotive CPS. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 732242, see http://www.deis-project.eu) addresses these challenges by developing technologies that form a science of dependable system integration. In the core of these technologies lies the concept of a Digital Dependability Identity (DDI) of a component or system. DDIs are modular, composable, and executable in the field facilitating (a) efficient synthesis of component and system dependability information over the supply chain and (b) effective evaluation of this information in-the-field for safe and secure composition of highly distributed and autonomous CPS. The paper outlines the DDI concept and opportunities for application in four industrial use cases.
Comprehensive guide to the process and test methods used for electronic device failure analysis. Contains dozens of articles—contributed by industry experts—covering a wide range of topics involving the failure analysis of microelectronics. It places the most important and up-to-date information on this subject at your fingertips.
Topic coverage includes:
Failure Analysis Process Flow
Failure Verification
Failure Modes and Failure Classification
Special Devices (MEMS, Optoelectronics, Passives)
Fault Localization Techniques: Package Level (NDT)
Die Level (Depackaging, Photon Emission, Microthermography, Laser-Based Methods, Particle Beam Methods)
Deprocessing & Imaging Techniques: Deprocessing
General Imaging Techniques
Local Deprocessing & Imaging
Circuit Edit and Design Modification
Material Analysis Techniques
Reference Information: Important Topics for Semiconductor Devices
Failure Analysis Techniques Roadmap
Failure Analysis Operations and Management
Appendices: Failure Analysis Terms, Definitions, and Acronyms
Industry Standards
Abstraction is the most basic principle of software engineering. Abstractions are provided by models. Modeling and model transformation constitute the core of model-driven development. Models can be refined and finally be transformed into a technical implementation, i.e., a software system.
The aim of this book is to give an overview of the state of the art in model-driven software development. Achievements are considered from a conceptual point of view in the first part, while the second part describes technical advances and infrastructures. Finally, the third part summarizes experiences gained in actual projects employing model-driven development.
Beydeda, Book and Gruhn put together the results from leading researchers in this area, both from industry and academia. The result is a collection of papers which gives both researchers and graduate students a comprehensive overview of current research issues and industrial forefront practice, as promoted by OMG’s MDA initiative.