Abstract
Both logic programming in general and Prolog in particular have a long and fascinating history, intermingled with that of many disciplines they inherited from or catalyzed. A large body of research has been gathered over the last 50 years, supported by many Prolog implementations. Many implementations are still actively developed, while new ones keep appearing. Often, the features added by different systems were motivated by the interdisciplinary needs of programmers and implementors, yielding systems that, while sharing the classic core language, in particular, the main aspects of the ISO-Prolog standard, also depart from each other in other aspects. This obviously poses challenges for code portability. The field has also inspired many related, but quite different languages that have created their own communities. This article aims at integrating and applying the main lessons learned in the process of evolution of Prolog. It is structured into three major parts. First, we overview the evolution of Prolog systems and the community approximately up to the ISO standard, considering both the main historic developments and the motivations behind several Prolog implementations, as well as other logic programming languages influenced by Prolog. Then, we discuss the Prolog implementations that are most active after the appearance of the standard: their visions, goals, commonalities, and incompatibilities. Finally, we perform a SWOT analysis in order to better identify the potential of Prolog and propose future directions along with which Prolog might continue to add useful features, interfaces, libraries, and tools, while at the same time improving compatibility between implementations.

Abstract
We propose an approach to summarize large semantics graphs using namespaces. Semantic graphs based on the Resource Description Framework (RDF) use namespaces on their serializations. Although these namespaces are not part of RDF semantics, they have intrinsic meaning. Based on this insight, we use namespaces to create summary graphs of reduced size, more amenable to be visualized. In the summarization, object literals are also reduced to their data type and the blank nodes to a group of their own. The visualization created for the summary graph aims to give insight of the original large graph. This paper describes the proposed approach and reports on the results obtained with representative large semantic graphs. © Ana Rita Santos Lopes da Costa, André Santos, and José Paulo Leal.

Abstract
Memristor crossbar arrays can compose the efficient hardware for artificial intelligent applications. However, the requirements for a linear and symmetric synaptic weight update and low cycle-to-cycle (C2C) and device-to-device variability as well as the sneak-path current issue have been delaying its further development. This study reports on a thin-film amorphous oxide-based 4x4 1-transistor 1-memristor (1T1M) crossbar. The a-IGZO crossbar is built on a flexible polyimide substrate, enabling IoT and wearable applications. In the novel framework, the thin-film transistor and memristor are fabricated at the same level, with the same processing steps and sharing the same materials for all layers. The 1T1M cells show linear and symmetrical plasticity characteristic with low C2C variability. The memristor performs like an analog dot product engine and vector-matrix multiplications in the 4x4 crossbars is demonstrated experimentally, in which the sneak-path current issue is successfully suppressed, resulting in a proof-of-concept for a cost-effective, flexible artificial neural networks hardware.

Abstract
Due to the value and diversity of data that organizations use and produce in their activity, it is extremely important to protect this asset. Security flaws can arise due to several factors and whenever it is difficult to access the desired information because of technological barriers. In this case, attacks are redirected to the exploitation of human beings vulnerabilities through various techniques. The objective of this work focuses on literature review, studying the underlying theme of Social Engineering, as it uses human trust, convincing someone of something fake, using various interactions and different vectors to gain access to private information. Design Science Research will support the research work due to the possibility of construction, evaluation, and subsequent validation of the artefact. The contribution of a framework proposal for preventing social engineering attacks in organizations and providing the best recommendations, guiding, and supporting the stakeholders in the selection and definition of controls that guarantee the security of organizational information and avoid possible attacks by Social Engineering. It is expected that the practical effects of the future work will result in a reduction in the number of attacks using Social Engineering, greater individual and collective preparation to deal with this problem and, over time, the incentive to the continued expansion of the adoption of these artefacts at the organizational level.

Abstract
The worldwide Web has dramatically evolved in recent years. Web pages are dynamic, expressed by programs written in common programming languages given rise to sophisticated Web applications. Thus, Web browsers are almost operating systems, having to interpret/compile such programs and execute them. Although JavaScript is widely used to express dynamic Web pages, it has several shortcomings and performance inefficiencies. To overcome such limitations, major IT powerhouses are developing a new portable and size/load efficient language: WebAssembly. In this paper, we conduct the first systematic study on the energy and run-time performance of WebAssembly and JavaScript on the Web. We used micro-benchmarks and also real applications in order to have more realistic results. Preliminary results show that WebAssembly, while still in its infancy, is starting to already outperform JavaScript, with much more room to grow. A statistical analysis indicates that WebAssembly produces significant performance differences compared to JavaScript. However, these differences differ between micro-benchmarks and real-world benchmarks. Our results also show that WebAssembly improved energy efficiency by 30%, on average, and showed how different WebAssembly behaviour is among three popular Web Browsers: Google Chrome, Microsoft Edge, and Mozilla Firefox. Our findings indicate that WebAssembly is faster than JavaScript and even more energy-efficient. Additionally, our benchmarking framework is also available to allow further research and replication.

Abstract
Tampered multimedia content is increasingly being used in a broad range of cybercrime activities. The spread of fake news, misinformation, digital kidnapping, and ransomware-related crimes are among the most recurrent crimes in which manipulated digital photos are being used as an attacking vector. One of the linchpins of accurately detecting manipulated multimedia content is the use of machine learning and deep learning algorithms. This work proposed a dataset of photos and videos suitable for digital forensics, which has been used to benchmark Support Vector Machines (SVM) and Convolution Neural Networks algorithms (CNN). An SVM-based module for the Autopsy digital forensics open-source application has also been developed. This was evaluated as a very capable and useful forensic tool, winning second place on the OSDFCon international Autopsy modules competition.