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Twitter and the jus ad bellum: threats of force and other implications
Get PDFA recent report noted that ninety-seven per cent of UN member states currently have an official Twitter presence. The report also highlighted the proliferation of Twitter accounts of Heads of State, including those that blur the ‘state’ and ‘personal’ divide. For example, the number of followers of the handle @realDonaldTrump has more than doubled in size since the US President took office in January 2017, while the number of people following the French President’s Twitter account, @EmmanuelMacron, has tripled since his election in May 2017.
This editorial provides some initial thoughts on the implications of this increased use of Twitter by states (and, in particular, Heads of State) for the jus ad bellum. Its main focus, in section 1, which takes up the bulk of the editorial, is on the question of whether a tweet by a Head of State could constitute a violation of the prohibition of the threat of force in Article 2(4) of the United Nations (UN) Charter. In addition, though, section 2 briefly considers other possible ad bellum implications of the rise of Twitter as a means of state-level communication
TPICDS: A Two-Phase Parallel Approach for Incremental Clustering of Data Streams
Get PDFParallel and distributed solutions are essential for clustering data streams due to the large volumes of data. This paper first examines a direct adaptation of a recently developed prototype-based algorithm into three existing parallel frameworks. Based on the evaluation of performance, the paper then presents a customised pipeline framework that combines incremental and twophase
learning into a balanced approach that dynamically allocates the available processing resources. This new framework is evaluated on a collection of synthetic datasets. The experimental results reveal that the framework not only produces correct final clusters on the one hand, but also significantly improves the clustering efficienc
Greece Unscathed by Jihadism
Get PDFThis thesis examines why Greece has, at least so far, remained unscathed by the threat of Jihadist terrorism. It attempts to explore why the level of Jihadist threat in Greece remains low in comparison to that in other European countries such as the UK, by looking to foreign policy, counter-terrorism policy and wider political, social and geographical characteristics. In doing so, it first explores the concept of Jihadism, adopting a new framework for the analysis of this phenomenon and, by extension, a new means of evaluating the threat it poses to Greek national security. The UK is used as a comparison largely because of its struggle with Jihadist terrorism, and this comparison is useful in shedding light on the twin issues of home-grown terrorism and radicalisation among sizeable Muslim communities across Europe. These two issues were further used as analytical instruments to examine the level of the Jihadist threat to Greek national security.
Although this work relies on a substantial literature review in setting out the scope and scale of the problem of Jihadist terrorism, it also produces primary data, contributing to existing awareness of the issue in both scholarly literature and in the wider political arena. Elite interviews, carried out with distinguished Greek experts and security officials, as well as leading figures from the Muslim community, were utilised for the purposes of gathering primary data for this investigation. These interviews were conducted across two separate time periods, in order to improve validity and reliability, as well as to provide the researcher with the chance to observe any changes in attitude toward the topic. Content analysis, a useful, tried-and-tested mode of qualitative data analysis, was then used to interpret this data, revealing that Greece is currently experiencing low levels of threat from Jihadist terrorism. The data collected and analysed here also suggests that this is attributable to Greek’s continued attempts to maintain excellent political, economic and cultural relations with the Muslim world; the lack of negative history with the Muslim community that the UK holds due to recent involvement in wars in the Middle East; the successful integration of the Greek Muslim population made up mainly of first-generation immigrants looking to earn a living peacefully; and the usefulness of Greece as a transit country for terrorist organisations. Based on the primary research conducted within this research, as well as the literature consulted in the preparation of the literature review, this thesis suggests that to ensure continued peace, security and positive relations with the Muslim community, it would be beneficial to adopt elements of the UK’s policies on counter-radicalisation and counter-terrorism
'Merlin's Debt in Keats's "The Eve of St. Agnes', Lines 170-71
Get PDFThis article looks in detail what has long been regarded as a crux of meaning in Keats's 'The Eve of St. Agnes': the last two lines of stanza 19, i.e. lines 170-71: 'Never on such a night have lovers met, / Since Merlin paid his Demon all the monstrous debt'. Early commentators, including Leigh Hunt, admitted to finding the basic meaning of the comparison here baffling, and modern commentators often note the lines as 'puzzling', uncertain, or ambiguous. The article proposes a clear reading of the lines, and begins to trace some of its implications in terms of how we read the poem as a whole
Android Pattern Unlock Authentication - effectiveness of local and global dynamic features
Get PDFThis study conducts a holistic analysis of the performances of biometric features incorporated into Pattern Unlock authentication. The objective is to enhance the strength of the authentication by adding an implicit layer. Earlier studies have incorporated either global or local dynamic features for verification; however, as found in this paper, different features have variable discriminating power, especially at different extraction levels. The discriminating potential of global, local and their combination are evaluated. Results showed that locally extracted features have higher discriminating power than global features and combining both features gives the best verification performance. Further, a novel feature was proposed and evaluated, which was found to have a varied impact (both positive and negative) on the system performance. From our findings, it is essential to evaluate features (independently and collectively), extracted at different levels (global and local) and different combination for some might impede on the verification performance of the system
Evaluation of machine learning methods with Fourier Transform features for classifying ovarian tumors based on ultrasound images
Get PDFIntroduction: Ovarian tumors are the most common diagnostic challenge for gynecologists and ultrasound examination has become the main technique for assessment of ovarian pathology and for preoperative distinction between malignant and benign ovarian tumors. However, ultrasonography is highly examiner-dependent and there may be an important variability between two different specialists when examining the same case. The objective of this work is the evaluation of different well-known Machine Learning (ML) systems to perform the automatic categorization of ovarian tumors from ultrasound images. Methods: We have used a real patient database whose input features have been extracted from 348 images, from the IOTA tumor images database, holding together with the class labels of the images. For each patient case and ultrasound image, its input features have been previously extracted using Fourier descriptors computed on the Region Of Interest (ROI). Then, four ML techniques are considered for performing the classification stage: K-Nearest Neighbors (KNN), Linear Discriminant (LD), Support Vector Machine (SVM) and Extreme Learning Machine (ELM). Results: According to our obtained results, the KNN classifier provides inaccurate predictions (less than 60% of accuracy) independently of the size of the local approximation, whereas the classifiers based on LD, SVM and ELM are robust in this biomedical classification (more than 85% of accuracy). Conclusions: ML methods can be efficiently used for developing the classification stage in computer-aided diagnosis systems of ovarian tumor from ultrasound images. These approaches are able to provide automatic classification with a high rate of accuracy. Future work should aim at enhancing the classifier design using ensemble techniques. Another ongoing work is to exploit different kind of features extracted from ultrasound images
Perceptions of UK Community Pharmacists on Current Consultation Skills and Motivational Interviewing as a Consultation Approach: A Qualitative Study
Get PDFCommunity pharmacists' roles in the UK are evolving; pharmacists currently deliver a wider range of clinical services with more patient-focused care. The objectives of this study were (i) to investigate UK community pharmacists' views on their current communication skills in pharmacist-patient facing consultations, and (ii) to explore the perceptions of UK community pharmacists towards the application of motivational interviewing (MI) in a pharmacy consultation. In-depth qualitative face-to-face, semi-structured interviews with ten practicing community pharmacists were carried out, ranging from 30-60 minutes in length. The interviews were audio recorded, transcribed verbatim and thematic analysis was employed. Four themes emerged from the data: (1) the fight for time; (2) wrestling with consultation styles; (3) a personal communication evolution; and (4) unfamiliar but engaging motivational interviewing. These themes demonstrated the juxtaposition between the desire for patient-centred care and the pressures of managing broader dispensing work. Participants were critical of academic and continuous professional learning (CPD) training in communication skills and there was a strong recognition of the potential role of MI in promoting patient autonomy and outcomes. Participants recognized a few elements of MI techniques in their current consultations, but welcomed further training on behavioral change for effective consultations, expressing a desire for practical MI-specific training. Face-to-face CPD of consultation skills is needed to avoid the feeling of isolation among UK practicing pharmacists and rigidity in consultation delivery. Support for community pharmacists from other pharmacy staff could relieve current pressures and allow pharmacists time to develop and acquire effective skills for patient facing roles. Behavioural change consultation skills training for pharmacists could be an effective strategy to address these current challenges
OC04.04 : A machine-learning algorithm to distinguish benign and malignant adnexal tumours from ultrasound images
Get PDFThe accurate preoperative diagnosis of adnexal tumours as benign or malignant is pivotal to optimise patient management. We developed a Machine Learning (ML) Algorithm to characterise adnexal tumours as benign or malignant from ultrasound images
Rights and Reparations: An Assessment of the UNDRIP's Contribution to American Indian Land Claims
No full textTowards Scene Understanding Implementing the Stixel World
Get PDFIn this paper, we present our work towards scene
understanding based on modeling the scene prior to understanding its content. We describe the environment representation model used, the Stixel World, and its benefits for compact scene representation. We show our preliminary results of its application in a diverse environment and the limitations reached in our experiments using imaging systems. We argue that this method has been developed in an ideal scenario and does not generalise well to uncommon changes in the environment. We also found that this method is sensitive to the quality of the stereo rectification and the calibration of the optics, among other parameters, which makes it time-consuming and delicate to prepare in real-time applications.
We think that pixel-wise semantic segmentation techniques can address some of the shortcomings of the concept presented in a theoretical discussion