Test-time, Run-time, and Simulation-time Temporal Assertions in RSPCreation and Validation of Embedded Assertion Statecharts

Proceedings of the 16th International Workshop on Rapid System Prototyping (RSP’05)For cost-effective prototyping, system designers should have a clear understanding of the intended use of the prototype under development. This paper describes a classification of formal specification (temporal) assertions used during system prototyping. The classification introduces two new classes of assertions in addition to the well-known class of test-time assertions: (i) assertions used only during simulation, and (ii) deployable assertions integrated with run-time control flow. Separating the formal specification into three distinct classes allows system designers to de- velop more effective prototypes to evaluate the different system behaviors and constraints. A prototype of a naval torpedo system is used to illustrate the concept.The research reported in this article was funded in part by a grant from the U.S. Missile Defense Agency

Expert systems for real-time monitoring and fault diagnosis

Methods for building real-time onboard expert systems were investigated, and the use of expert systems technology was demonstrated in improving the performance of current real-time onboard monitoring and fault diagnosis applications. The potential applications of the proposed research include an expert system environment allowing the integration of expert systems into conventional time-critical application solutions, a grammar for describing the discrete event behavior of monitoring and fault diagnosis systems, and their applications to new real-time hardware fault diagnosis and monitoring systems for aircraft

Comparison and analysis of product stage and service life uncertainties in life cycle assessment of building elements

Life cycle assessment (LCA) has the potential to inform building decisions from the planning process to conceptual design. As such, there is intrinsic uncertainty that needs to be explored further to allow for proper decisions to be made. These uncertainties may be related to parameter definition, such as life cycle inventory or model as service life definition. This paper aims to analyze the influence of two recognized sources of uncertainties in LCA of buildings: product stage uncertainties and uncertainties from SL during the use stage. The Monte Carlo simulation method is applied to conduct uncertainty analysis of the LCA results of four building elements, namely, external cement plaster, external clay brick wall, external painting and internal painting. The functional unit is 1 m2 of each building element. Three different building reference study periods are considered: 50, 120 and 500 years. A global warming potential impact category is chosen since it is one of the most significant indicators for climate change mitigation strategies. Results indicate that SL uncertainties are greater than product stage uncertainties for the four building elements analyzed. Furthermore, based on the findings from this study, distribution choice influences the uncertainty analysis results in Monte Carlo simulation. Standardizing modeling of SL in the LCA of buildings could guide building LCA practitioners and researchers and lead to more comparable results

Interior-point methods for PDE-constrained optimization

In applied sciences PDEs model an extensive variety of phenomena. Typically the final goal of simulations is a system which is optimal in a certain sense. For instance optimal control problems identify a control to steer a system towards a desired state. Inverse problems seek PDE parameters which are most consistent with measurements. In these optimization problems PDEs appear as equality constraints. PDE-constrained optimization problems are large-scale and often nonconvex. Their numerical solution leads to large ill-conditioned linear systems. In many practical problems inequality constraints implement technical limitations or prior knowledge. In this thesis interior-point (IP) methods are considered to solve nonconvex large-scale PDE-constrained optimization problems with inequality constraints. To cope with enormous fill-in of direct linear solvers, inexact search directions are allowed in an inexact interior-point (IIP) method. This thesis builds upon the IIP method proposed in [Curtis, Schenk, Wächter, SIAM Journal on Scientific Computing, 2010]. SMART tests cope with the lack of inertia information to control Hessian modification and also specify termination tests for the iterative linear solver. The original IIP method needs to solve two sparse large-scale linear systems in each optimization step. This is improved to only a single linear system solution in most optimization steps. Within this improved IIP framework, two iterative linear solvers are evaluated: A general purpose algebraic multilevel incomplete L D L^T preconditioned SQMR method is applied to PDE-constrained optimization problems for optimal server room cooling in three space dimensions and to compute an ambient temperature for optimal cooling. The results show robustness and efficiency of the IIP method when compared with the exact IP method. These advantages are even more evident for a reduced-space preconditioned (RSP) GMRES solver which takes advantage of the linear system's structure. This RSP-IIP method is studied on the basis of distributed and boundary control problems originating from superconductivity and from two-dimensional and three-dimensional parameter estimation problems in groundwater modeling. The numerical results exhibit the improved efficiency especially for multiple PDE constraints. An inverse medium problem for the Helmholtz equation with pointwise box constraints is solved by IP methods. The ill-posedness of the problem is explored numerically and different regularization strategies are compared. The impact of box constraints and the importance of Hessian modification on the optimization algorithm is demonstrated. A real world seismic imaging problem is solved successfully by the RSP-IIP method

Model Checking and Co-simulation of a Dynamic Task Dispatcher Circuit using CADP

International audienceThe complexity of multiprocessor architectures for mobile multi-media applications renders their validation challenging. In addition, to provide the necessary flexibility, a part of the functionality is realized by software. Thus, a formal model has to take into account both hardware and software. In this paper we report on the use of LOTOS NT and CADP for the formal modeling and analysis of the DTD (Dynamic Task Dispatcher), a complex hardware block of an industrial hardware architecture developed by STMicroelectronics. Using LOTOS NT facilitated exploration of alternative design choices and increased the confidence in the DTD, by, on the one hand, automatic analysis of formal models easily understood by the architect of the DTD, and, on the other hand, co-simulation of the formal model with the implementation used for synthesis

Pattern-based security requirements specification using ontologies and boilerplates

The task of specifying and managing security requirements (SR) is a challenging one. Usually SR are often neglected or considered too late - leading to poor design, and cost overruns. Also, there is scarce expertise in managing SR, because most requirements engineering teams do not include security experts, which leads to prevalence of too vague or overly specific SR. In this work, we present an ontology-based approach that uses predefined pattern-based templates - requirements boilerplates - to aid requirements engineers in the formulation of SR. We realized the approach via a prototype tool that enables the formulation of SR from textual misuse case (TMUC) descriptions of security threat scenarios. The results from a preliminary evaluation suggest the viability of the proposed approach, in that the tool was judged as easy to use, supports reuse, and facilitates the formulation of good quality SR

Design and Verification Environment for High-Performance Video-Based Embedded Systems

In this dissertation, a method and a tool to enable design and verification of computation demanding embedded vision-based systems is presented. Starting with an executable specification in OpenCV, we provide subsequent refinements and verification down to a system-on-chip prototype into an FPGA-Based smart camera. At each level of abstraction, properties of image processing applications are used along with structure composition to provide a generic architecture that can be automatically verified and mapped to the lower abstraction level. The result is a framework that encapsulates the computer vision library OpenCV at the highest level, integrates Accelera\u27s System-C/TLM with UVM and QEMU-OS for virtual prototyping and verification and mapping to a lower level, the last of which is the FPGA. This will relieve hardware designers from time-consuming and error-prone manual implementations, thus allowing them to focus on other steps of the design process. We also propose a novel streaming interface, called Component Interconnect and Data Access (CIDA), for embedded video designs, along with a formal model and a component composition mechanism to cluster components in logical and operational groups that reduce resource usage and power consumption

Semantic Systems. The Power of AI and Knowledge Graphs

This open access book constitutes the refereed proceedings of the 15th International Conference on Semantic Systems, SEMANTiCS 2019, held in Karlsruhe, Germany, in September 2019. The 20 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 88 submissions. They cover topics such as: web semantics and linked (open) data; machine learning and deep learning techniques; semantic information management and knowledge integration; terminology, thesaurus and ontology management; data mining and knowledge discovery; semantics in blockchain and distributed ledger technologies