Abstract
Security is now becoming a well-established challenge for integrated circuits (ICs). Various types of IC attacks have been reported, including reverse engineering IPs, dumping on-chip data, and controlling/modifying IC operation. IEEE 1149.1, commonly known as Joint Test Action Group (JTAG), is a standard for providing test access to an IC. JTAG is primarily used for IC manufacturing test, but also for in-field debugging and failure analysis since it gives access to internal subsystems of the IC. Because the JTAG needs to be left intact and operational after fabrication, it inevitably provides a "backdoor" that can be exploited outside its intended use. This paper proposes machine learning-based approaches to detect illegitimate use of the JTAG. Specifically, JTAG operation is characterized using various features that are then classified as either legitimate or attack. Experiments using the OpenSPARC T2 platform demonstrate that the proposed approaches can classify legitimate JTAG operation and known attacks with significantly high accuracy. Experiments also demonstrate that unknown and disguised attacks can be detected with high accuracy as well (99% and 94%, respectively).

Abstract
Because of terminology mismatches, health consumers frequently face difficulties while searching the Web for health information. Difficulties arise in query formulation but also in understanding the retrieved documents. In this work we analyze how documents' readability affects users' comprehension and how both affect the retrieval performance, measured in different ways. In addition, we analyze how performance measures relate with each other. For this purpose we have conducted a laboratory user study with 40 participants. We found that readability is essential for a document to be at least partially relevant and that it becomes even more important if the document has medico-scientific terminology. Moreover, the relevance of a document to a specific user highly depends on its comprehension. In lay queries we found the medical accuracy of users' answers is related to the session's relevance assessments. This shows that users can, at least in part, relate their relevance assessments with the medical accuracy of the documents. On the other hand, this relationship does not exist with medico-scientific queries.

Abstract
This paper presents an overview on how the European Project Semester capstone programme offered by the Instituto Superior de Engenharia do Porto (EPS@ISEP) fosters learning by challenging engineering, business and product development undergraduates to address sustainability issues afflicting cities and communities nowadays. This will be done by analysing the reports and the learning journey of three multicultural and multidisciplinary EPS@ISEP teams during the design, development and test of a smart billboard, a self-oriented solar mirror and a level monitoring system for waste oil bins. These three projects were conducted within EPS@ISEP, a project-based learning framework dedicated to the development of key engineering skills, namely multidisciplinary teamwork, intercultural communication, ethical and sustainability-oriented problem-solving. The involved students contributed, not only, to make cities more inclusive, safe, resilient and sustainable, one of UNESCO's sustainable development goals, but learnt and practiced together sustainability-driven design, while searching for an innovative solution for a smart city problem. This conclusion is supported by the analysis of the content the three project reports.

Abstract
Even renewable energy sources provide several advantages, especially from an environmental point of view, where the world has faced great challenges in the last few decades; several negative issues also exist regarding the integration of renewable resources-based power production units in electric power systems. One of the main problems related to pivotal renewable energy resources such as solar, wind, etc., is their stochastic and uncontrollable nature in terms of power production. Therefore, this stochasticity in the supply side of the power system may pose many challenges for system operators. This issue is also problematic for smaller applications where the stochastic production by a main resource, such as a roof-top photovoltaic system, and load demand may not match perfectly at each time instant and therefore should be compensated by additional resources such as battery-based energy storage systems. Herein, the economic considerations to ensure minimum costs for such a hybrid system design are vital so as to increase the penetration of such systems. Therefore, the optimal sizing and planning of hybrid systems have recently gained increasing importance to enhance power system operation in the context of the smart grid paradigm. From a different perspective, harmonics are one of the most important power quality problems in system operations caused by widespread integration of power electronic loads with non-linear characteristics that should be considered. Thus, a new approach for grid-connected hybrid renewable energy system sizing is provided. In order to determine optimal capacities for photovoltaic (PV) and energy storage system (ESS) units for covering residential consumer demand, a mixed integer linear programming (MILP)-based formulation is presented. The main objective is minimizing total costs of the system consisting of investment, capital and maintenance cost functions. A daily power curve is created accurately with real measurements of non-linear loads considering harmonic contents of smart home appliances in Yildiz Technical University, Istanbul, Turkey. In addition, real radiation and temperature values are used in PV production as well as dynamic pricing schemes for realistic evaluations. Moreover, optimal sizing results are compared for both the harmonic-based power curve and rated power curve in terms of satisfying objective function.

Abstract
The importance of recycling is well known, either for environmental or economic reasons, it is impossible to escape it and the industry demands efficiency. Manual labour and traditional industrial sorting techniques are not capable of keeping up with the objectives demanded by the international community. Solutions based in computer vision techniques have the potential automate part of the waste handling tasks. In this paper, we propose a hierarchical deep learning approach for waste detection and classification in food trays. The proposed two-step approach retains the advantages of recent object detectors (as Faster R-CNN) and allows the classification task to be supported in higher resolution bounding boxes. Additionally, we also collect, annotate and make available to the scientific community a new dataset, named Labeled Waste in the Wild, for research and benchmark purposes. In the experimental comparison with standard deep learning approaches, the proposed hierarchical model shows better detection and classification performance. © 2019 IEEE.

Abstract
Purpose Considering the differences between rural and urban spaces, through the theoretical framework developed, the purpose of this paper is to uncover and rationalize the differences between rural and urban new ventures in terms of the environment surrounding the new venture, their general characteristics (e.g. sector, size) and export/economic performance. Design/methodology/approach The theoretical framework is empirically assessed resorting to exploratory statistical analysis based on data collected from a questionnaire survey responded by 408 new ventures headquartered in Portuguese business incubators and science parks. The data collected were treated with the Software Package for the Social Sciences. Findings The results evidence that rural and urban new ventures differ in terms of generic characteristics, namely sector, size and collaborators' human capital. Additionally, they differ concerning export and economic performance as well in relation to the perception of the municipality support. Originality/value The present study innovatively contributes to uncover the role of rural and urban context in entrepreneurship and adds to the scanty empirical literature in the area.