Abstract
This work focuses on the issues encountered when using current evaluation tools to assess the accessibility and usability of web and mobile applications. Therefore, we present a case study, where we tested three accessibility assessment tools against the official website of Portuguese Institute for Employment and Vocational (IEFP), used by millions of users nationwide. Indeed, we found that individual tools still provide limited coverage of success criteria and, thus, user verification is consistently needed. In this regard, we also aim at proposing a new tool called IncWeb, that can automatically alter any web or mobile application into a usable and fully accessible one, in a way that is transparent to the user and adapted to his type of disability. As such, this work emphasizes the importance of having appropriate tools to facilitate the lives of people with disabilities and/or special needs, presenting not only the problems of other assessment tools, but also proposing a new paradigm-changing solution to overcome those known challenges. © 2022 Elsevier B.V.. All rights reserved.

Abstract
Assistive environments is a well established research area, particularly, the Ambient Assisted Living (AAL) paradigm, which relies in data and artificial intelligence to infer the user's actions and status, thus enabling assistive actions. In a very distinct environment - the manufacturing industry, we propose a twin concept - the Ambient Assisted Working (AAW), to provide assistance to the workers on the factory floor, using solutions with design principles similar to AAL systems. The Industry 4.0 (I4.0) Technical Assistance design principle, introduces the assistance concept in I4.0 solutions and the AAW builds on top of that design principle.

Abstract

Abstract
The advance of technology in the automotive industry brought several new functionalities providing more efficiency and safety. This, however, has one important concern: the development has become more complex. AMALTHEA is a framework for automotive system design and development in a model-based development fashion. It includes several features, including testing, software design, simulation and traceability. This paper presents ongoing work to integrate GPU tracing in the AMALTHEA standard format for tracing execution events, thus enabling platform heterogeneity to be supported in the tracing model. © 2022, Ada-Europe. All rights reserved.

Abstract
The automotive software industry is gradually introducing new functionalities and technologies that increase the efficiency, safety, and comfort of vehicles. These functionalities are quickly accepted by consumers; however, the consequences of this evolution are twofold. First, developing correct systems that integrate more applications and hardware is becoming more complex. To cope with this, new standards (such as Adaptive AUTOSAR) and frameworks (such as AMALTHEA) are being proposed, to assist the development of flexible systems based on high-performance electronic control units (ECU). Second, the increase of functionality is supported by a dramatic increase of electronic parts on automotive systems. Consequently, the impact of software on the electrical power and energy non-functional requirements of automotive systems has come under focus. In this paper we propose an automatic and self-contained approach that supplements a model of an automotive system described on the AMALTHEA platform with energy-related annotations. From the analysis of simulation (or execution) traces of the modelled software, we estimate the power consumption for each software component, on a target hardware platform. This method enables energy analysis during the entire development life-cycle; furthermore, it contributes for the development of energy management strategies for dynamic and self-adaptive systems.

Abstract
Parallel programming models (e.g., OpenMP) are more and more used to improve the performance of real-time applications in modern processors. Nevertheless, these processors have complex architectures, being very difficult to understand their timing behavior. The main challenge with most of existing works is that they apply static timing analysis for simpler models or measurement-based analysis using traditional platforms (e.g., single core) or considering only sequential algorithms. How to provide an efficient configuration for the allocation of the parallel program in the computing units of the processor is still an open challenge. This paper studies the problem of performing timing analysis on complex multi-core platforms, pointing out a methodology to understand the applications' timing behavior, and guide the configuration of the platform. As an example, the paper uses an OpenMP-based program of the Heat benchmark on a NVIDIA Jetson AGX Xavier. The main objectives are to analyze the execution time of OpenMP tasks, specify the best configuration of OpenMP directives, identify critical tasks, and discuss the predictability of the system/application. A Linux perf based measurement tool, which has been extended by our team, is applied to measure each task across multiple executions in terms of total CPU cycles, the number of cache accesses, and the number of cache misses at different cache levels, including L1, L2 and L3. The evaluation process is performed using the measurement of the performance metrics by our tool to study the predictability of the system/application.