An exploration of integrated data on the social dynamics of suicide among women

The gender based nature of suicide related behaviour is largely accepted.However, studies which report exclusively on female fatal suicides are rare.Here we demonstrate how female fatal suicide has effectively been ‘othered’ and appears ‘incidental’ in studies which compare female behaviour with that of their male counterparts. We highlight how recent studies of suicide have tended to be dominated by male only approaches,which increasingly link issues of masculinity with male death by suicide.Drawing on data collected from the GP and Coroner’s office, we then apply the Sociological Autopsy approach to a cohort of 78 deaths recorded as suicides in the UK between 2007 and 2009. By focusing on females in isolation from males, we demonstrate that as in male suicide only studies,it is similarly possible to draw out issues associated with the feminine identity which can be linked to death by suicide. We identify that bereavement, sexual violence and motherhood could all be linked to the lives and help-seeking of the females who died. In closing, we suggest are orientation towards sociological analytic approaches of female suicide may help to produce further reductions in the rate of female death by suicide.

Linguistics and Information Theory: Analytic advantages

The analytic advantages of central concepts from linguistics and information theory, and the analogies demonstrated between them, for understanding patterns of retrieval from full-text indexes to documents are developed. The interaction between the syntagm and the paradigm in computational operations on written language in indexing, searching, and retrieval is used to account for transformations of the signified or meaning between documents and their representation and between queries and documents retrieved. Characteristics of the message, and messages for selection for written language, are brought to explain the relative frequency of occurrence of words and multiple word sequences in documents. The examples given in the companion article are revisited and a fuller example introduced. The signified of the sequence stood for, the term classically used in the definitions of the sign, as something standing for something else, can itself change rapidly according to its syntagm. A greater than ordinary discourse understanding of patterns in retrieval is obtained.

Humour: Stylistic Approaches

An important focus in contemporary stylistics has been on the connections between style and verbal humor, and this article charts the ways in which stylisticians have used a variety of linguistic models to analyze humorous discourse. The idea of stylistic incongruity is identified as being especially important in triggering the humor reflex. The principle of incongruity applies to any level of language or discourse, as is illustrated here by examples of puns and related forms of humor as well as by incongruities that are more to do with mismatches between text and discourse context. The principle of incongruity is also aligned with the concept of irony, through which a number of points are made about the stylistic analysis of both parody and satire.

Analysis of Bayesian classification-based approaches for Android malware detection

Mobile malware has been growing in scale and complexity spurred by the unabated uptake of smartphones worldwide. Android is fast becoming the most popular mobile platform resulting in sharp increase in malware targeting the platform. Additionally, Android malware is evolving rapidly to evade detection by traditional signature-based scanning. Despite current detection measures in place, timely discovery of new malware is still a critical issue. This calls for novel approaches to mitigate the growing threat of zero-day Android malware. Hence, the authors develop and analyse proactive machine-learning approaches based on Bayesian classification aimed at uncovering unknown Android malware via static analysis. The study, which is based on a large malware sample set of majority of the existing families, demonstrates detection capabilities with high accuracy. Empirical results and comparative analysis are presented offering useful insight towards development of effective static-analytic Bayesian classification-based solutions for detecting unknown Android malware.