Abstract
The crime is spread in every daily newspaper, and particularly on criminal investigation reports produced by several Police departments, creating an amount of data to be processed by Humans. Other research studies related to relation extraction (a branch of information retrieval) in Portuguese arisen along the years, but with few extracted relations and several computer methods approaches, that could be improved by recent features, to achieve better performance results. This paper aims to present the ongoing work related to SEM (Simple Event Model) ontology population with instances retrieved from crime-related documents, supported by an SVO (Subject, Verb, Object) algorithm using hand-crafted rules to extract events, achieving a performance measure of 0.86 (F-Measure). © Gonçalo Carnaz, Vitor Beires Nogueira, and Mário Antunes.

Abstract

Abstract
Bipolar Disorder (BD) is chronic and severe psychiatric illness presenting with mood alterations, including manic, hypomanic and depressive episodes. Due to the high clinical heterogeneity and lack of biological validation, both BD treatment and diagnostic are still problematic. Patients and clinicians would benefit from better clinical and biological characterization, ultimately opening a new possibility to distinct forms of treatment. In this context, we studied genome wide association (GWA) data from the Wellcome Trust Case Control Consortium (WTCCC). After an exploratory analysis, we found a higher prevalence of homozygous compared with heterozygous in different single nucleotide polymorphisms (SNPs) in genes previously associated with BD risk. Results from our association rules analysis indicate that there is a group of patients presenting with different groups of genotypes, including pairs or triples, while others present only one. We performed the same analysis with a control group from the same cohort (WTCCC) and found that although healthy subjects may present the same SNPs combinations, the risky alleles occur in a lower frequency. Moreover, no subject in the control group presented the same pairs or triples of genotypes found in the BD group, and if a pair or triple is found, the support and confidence are lower than in the BD group (< 50 %). © Springer Nature Switzerland AG 2020.

Abstract

Abstract
Given the centralized architecture of cloud computing, there is a genuine concern about its ability to adequately cope with the demands of connecting devices which are sharply increasing in number and capacity. This has led to the emergence of edge computing technologies, including but not limited to mobile edge-clouds. As a branch of Peer-to-Peer (P2P) networks, mobile edge-clouds inherits disturbing security concerns which have not been adequately addressed in previous methods. P2P security systems have featured many trust-based methods owing to their suitability and cost advantage, but these approaches still lack in a number of ways. They mostly focus on protecting client nodes from malicious service providers, but downplay the security of service provider nodes, thereby creating potential loopholes for bandwidth attack. Similarly, trust bootstrapping is often via default scores, or based on heuristics that does not reflect the identity of a newcomer. This work has patched these inherent loopholes and improved fairness among participating peers. The use cases of mobile edge-clouds have been particularly considered and a scalable reputation based security mechanism was derived to suit them. BitTorrent protocol was modified to form a suitable test bed, using Peersim simulator. The proposed method was compared to some related methods in the literature through detailed simulations. Results show that the new method can foster trust and significantly improve network security, in comparison to previous similar systems.

Abstract
Peer-to-Peer (P2P) overlay networks have gained popularity due to their robustness, cost advantage, network efficiency and openness. Unfortunately, the same properties that foster their success, also make them prone to several attacks. To mitigate these attacks, several scalable security mechanisms which are based on the concepts of trust and reputation have been proposed. These proposed methods tend to ignore some core practical requirements that are essential to make them more useful in the real world. Some of such requirements include efficient bootstrapping of each newcomer's reputation, and mitigating seeder(s) exploitation. Additionally, although interaction among participating peers is usually the bases for reputation, the importance given to the frequency of interaction between the peers is often minimized or ignored. This can result in situations where barely known peers end-up having similar trust scores to the well-known and consistently cooperative nodes. After a careful review of the literature, this work proposes a novel and scalable reputation based security mechanism that addresses the aforementioned problems. The new method offers more efficient reputation bootstrapping, mitigation of bandwidth attack and better management of interaction rate, which further leads to improved fairness. To evaluate its performance, the new reputation model has been implemented as an extension of the BitTorrent protocol. Its robustness was tested by exposing it to popular malicious behaviors in a series of extensive PeerSim simulations. Results show that the proposed method is very robust and can efficiently mitigate popular attacks on P2P overlay networks.