Abstract
The high-performance requirements needed to implement the most advanced functionalities of current and future Cyber-Physical Systems (CPSs) are challenging the development processes of CPSs. On one side, CPSs rely on model-driven engineering (MDE) to satisfy the non-functional constraints and to ensure a smooth and safe integration of new features. On the other side, the use of complex parallel and heterogeneous embedded processor architectures becomes mandatory to cope with the performance requirements. In this regard, parallel programming models, such as OpenMP or CUDA, are a fundamental brick to fully exploit the performance capabilities of these architectures. However, parallel programming models are not compatible with current MDE approaches, creating a gap between the MDE used to develop CPSs and the parallel programming models supported by novel and future embedded platforms. The AMPERE project will bridge this gap by implementing a novel software architecture for the development of advanced CPSs. To do so, the proposed software architecture will be capable of capturing the definition of the components and communications described in the MDE framework, together with the non-functional properties, and transform it into key parallel constructs present in current parallel models, which may require extensions. These features will allow for making an efficient use of underlying parallel and heterogeneous architectures, while ensuring compliance with non-functional requirements, including those on real-time performance of the system.

Abstract
Background: The short-term benefits of aerobic and resistance exercise in subjects affected by Peripheral Arterial Disease (PAD) are scarcely examined in interaction. This study aimed to identify the effects of combined aerobic and resistance exercise programs on walking performance compared with isolated aerobic exercise or with the usual care in patients with intermittent claudication. Methods: A systematic review was conducted following the PRISMA statement. A total of five electronic databases were searched (until October 2019) for randomized and non-randomized controlled trials. The focus comprised PAD patients with intermittent claudication who performed a combined aerobic and resistance exercise program that assessed the walking performance. Results: Seven studies include combined aerobic and resistance exercise vs. isolated aerobic or vs. usual care. The studies represented a sample size of 337 participants. The follow-up ranged from 4 to 12 weeks, 2 to 5 times-per-week. The risk of bias in the trials was a deemed moderate-to-high risk. After the interventions, the percent change in walking performance outcomes had a large variation. In the combined and isolated aerobic programs, the walking performance always improved, while in the usual care group oscillates between the deterioration and the improvement in all outcomes. Combined exercise and isolated aerobic exercise improved the claudication onset distance from 11 to 396%, and 30 to 422%, the absolute claudication distance from 81 to 197%, and 53 to 121%, and the maximal walking distance around 23 and 10%, respectively. Conclusions: Currently, there is insufficient evidence about the effects of combined aerobic and resistance exercise compared to isolated aerobic exercise or usual care on walking performance. However, despite the low quality of evidence, the combined aerobic and resistance exercise seems to be an effective strategy to improve walking performance in patients with intermittent claudication. These combined exercise modes or isolated aerobic exercise produce positive and significant results on walking performance. The usual care approach has a trend to deteriorate the walking performance. Thus, given the scarcity of data, new randomized controlled trial studies that include assessments of cardiovascular risk factors are urgently required to better determine the effect of this exercise combination.

Abstract
This work addresses a stochastic framework for optimal operation and long-term expansion planning of combined heat and power based microgrid as a part of an active distributing system. The microgrid utilizes renewable energy sources, electricity and heat generation units, energy storage systems, and demand response programs. The proposed model determines the optimal location and capacity of the electrical and thermal facilities, and it considers the impact of renewable energy sources and demand response on the expansion-planning problem. A stochastic mixed-integer linear programming formulation is utilized to minimize the investment and operation costs of system for five years. To evaluate the effectiveness of the proposed model, the algorithm is assessed for the 9-bus system and the 33-bus IEEE test systems. The results demonstrate that the utilization of the proposed algorithm reduces the operational cost and increases system revenues. © 2020 IEEE.

Abstract

Abstract
Fraud in telephony incurs huge revenue losses and causes a menace to both the service providers and legitimate users. This problem is growing alongside augmenting technologies. Yet, the works in this area are hindered by the availability of data and confidentiality of approaches. In this work, we deal with the problem of detecting different types of unsolicited users from spammers to fraudsters in a massive phone call network. Most of the malicious users in telecommunications have some of the characteristics in common. These characteristics can be defined by a set of features whose values are uncommon for normal users. We made use of graph-based metrics to detect profiles that are significantly far from the common user profiles in a real data log with millions of users. To achieve this, we looked for the high leverage points in the 99.99th percentile, which identified a substantial number of users as extreme anomalous points. Furthermore, clustering these points helped distinguish malicious users efficiently and minimized the problem space significantly. Convincingly, the learned profiles of these detected users coincided with fraudulent behaviors.

Abstract
<p>The UNEXUP project, funded under EIT Raw Materials, is a direct continuation of the Horizon 2020 UNEXMIN project. While in UNEXMIN efforts were made towards the design, development and testing of an innovative exploration technology for underground flooded mines, in UNEXUP the main goal is to push the UNEXMIN technology into the market, while further improving the system’s hardware, software and capabilities. In parallel, the aim is to make a strong business case for the improved UNEXUP technology, as a result of tests and data collection from previous testing. Improvements to the UX-1 research prototypes will raise technology readiness levels from TRL 6, as verified at the end of the UNEXMIN project, to TRL 7/8 by 2022. A "real service-to-real client" approach will be demonstrated, supporting mineral exploration and mine surveying efforts in Europe with unique data from flooded environments that cannot be obtained without high costs, or risks to human lives, in any other ways.</p><p>The specific purpose of UNEXUP is to commercially deploy a new raw materials exploration / mine mapping service based on a new class of mine explorer robots, for non-invasive resurveying of flooded mines. The inaccessibility of the environment makes autonomy a critical and primary objective of the project, which will present a substantial effort in resurveying mineral deposits in Europe where the major challenges are the geological uncertainty, and technological / economic feasibility of mine development. The robot’s ability to gather high-quality and high-resolution information from currently inaccessible mine sites will increase the knowledge of mineral deposits in Europe, whilst decreasing exploration costs – such as the number of deep exploration drillholes needed. This can potentially become a game changing technology in the mining panorama, where the struggle for resources is ever increasing.</p><p>On the technical side, a fourth robot, modular in nature, will be added to the current multi-robot platform, providing additional functionalities to the exploration system, including better range and depth performance. Hardware and software upgrades, as well as new capabilities delivered by the platform will greatly extend the usefulness of the platform in different environments and applications. Among these: rock sampling, better data acquisition and management, further downsizing, extended range, improved self-awareness and decision making, mature post-processing (such as the deployment of 3D virtual reality models), ability to rescue other robots, and interaction with the data will be targeted during the next years. Upgrading the overall technology with these tools, and possibly additional ones, will allow the system to operate with more reliability and security, with reduced costs.</p><p>These added functions arise from different stakeholders’ feedbacks from the UNEXMIN project. UNEXUP targets parties from the mining, robotics and mineral exploration sectors, as well as all other sectors that have any kind of underwater structure that needs to be surveyed – caves, underground reservoirs, water pipelines and fisheries are among them. For the purpose of exploitation of the technology, a joint company was founded, “UNEXMIN GeoRobotics Ltd”, which is part of the UNEXUP consortium, and is responsible for selling the service to the market.</p>