On the use of Locality for Improving SVM-Based Spam Filtering

Recent growths in the use of email for communication and the corresponding growths in the volume of email received have made automatic processing of emails desirable. In tandem is the prevailing problem of Advance Fee fraud E-mails that pervades inboxes globally. These genres of e-mails solicit for financial transactions and funds transfers from unsuspecting users. Most modern mail-reading software packages provide some forms of programmable automatic filtering, typically in the form of sets of rules that file or otherwise dispose mails based on keywords detected in the headers or message body. Unfortunately programming these filters is an arcane and sometimes inefficient process. An adaptive mail system which can learn its users’ mail sorting preferences would therefore be more desirable. Premised on the work of Blanzieri & Bryl (2007), we proposes a framework dedicated to the phenomenon of locality in email data analysis of advance fee fraud e-mails which engages Support Vector Machines (SVM) classifier for building local decision rules into the classification process of the spam filter design for this genre of e-mails

Towards the Development of a Time-Out Multiple C-R CAPTCHA Framework Using Integrated Mathematical Modeling

The internet has suffered from large forms of insecurity ranging from scamming, hacking and theft of information. Lately the use of CAPTCHAs has become a common security tool for authentication and authorization. However CAPTCHAS has suffered from certain vulnerabilities in the context of the simplicity offered by the challenge-response scenario and its timing which leaves room for improvement. This paper proposes a Time-Out Multiple Challenge-Response (C-R) CAPTCHA Framework that Utilizes Mathematical Modelling as a basis for overcoming some of the challenges faced by current CAPTCHA Systems. Our approach ensures security during the authorization and authentication process

A maximum entropy classification scheme for phishing detection using parsimonious features

Over the years, electronic mail (e-mail) has been the target of several malicious attacks. Phishing is one of the most recognizable forms of manipulation aimed at e-mail users and usually, employs social engineering to trick innocent users into supplying sensitive information into an imposter website. Attacks from phishing emails can result in the exposure of confidential information, financial loss, data misuse, and others. This paper presents the implementation of a maximum entropy (ME) classification method for an efficient approach to the identification of phishing emails. Our result showed that maximum entropy with parsimonious feature space gives a better classification precision than both the Naïve Bayes and support vector machine (SVM)

Facial expressions depicting compassionate and critical emotions: the development and validation of a new emotional face stimulus set

Attachment with altruistic others requires the ability to appropriately process affiliative and kind facial cues. Yet there is no stimulus set available to investigate such processes. Here, we developed a stimulus set depicting compassionate and critical facial expressions, and validated its effectiveness using well-established visual-probe methodology. In Study 1, 62 participants rated photographs of actors displaying compassionate/kind and critical faces on strength of emotion type. This produced a new stimulus set based on N = 31 actors, whose facial expressions were reliably distinguished as compassionate, critical and neutral. In Study 2, 70 participants completed a visual-probe task measuring attentional orientation to critical and compassionate/kind faces. This revealed that participants lower in self-criticism demonstrated enhanced attention to compassionate/kind faces whereas those higher in self-criticism showed no bias. To sum, the new stimulus set produced interpretable findings using visual-probe methodology and is the first to include higher order, complex positive affect displays

The factor structure of the Forms of Self-Criticising/Attacking & Self-Reassuring Scale in thirteen distinct populations

There is considerable evidence that self-criticism plays a major role in the vulnerability to and recovery from psychopathology. Methods to measure this process, and its change over time, are therefore important for research in psychopathology and well-being. This study examined the factor structure of a widely used measure, the Forms of Self-Criticising/Attacking & Self-Reassuring Scale in thirteen nonclinical samples (N = 7510) from twelve different countries: Australia (N = 319), Canada (N = 383), Switzerland (N = 230), Israel (N = 476), Italy (N = 389), Japan (N = 264), the Netherlands (N = 360), Portugal (N = 764), Slovakia (N = 1326), Taiwan (N = 417), the United Kingdom 1 (N = 1570), the United Kingdom 2 (N = 883), and USA (N = 331). This study used more advanced analyses than prior reports: a bifactor item-response theory model, a two-tier item-response theory model, and a non-parametric item-response theory (Mokken) scale analysis. Although the original three-factor solution for the FSCRS (distinguishing between Inadequate-Self, Hated-Self, and Reassured-Self) had an acceptable fit, two-tier models, with two general factors (Self-criticism and Self-reassurance) demonstrated the best fit across all samples. This study provides preliminary evidence suggesting that this two-factor structure can be used in a range of nonclinical contexts across countries and cultures. Inadequate-Self and Hated-Self might not by distinct factors in nonclinical samples. Future work may benefit from distinguishing between self-correction versus shame-based self-criticism.Peer reviewe

The domain of organizational cognitive neuroscience:theoretical and empirical challenges

In this editorial, the authors respond to the 2011 article in the Journal of Management by Becker, Cropanzano, and Sanfey, titled “Organizational Neuroscience: Taking Organizational Theory Inside the Neural Black Box.” More specifically, the authors build on the ideas of Becker et al. first to clarify and extend their work and then to explore the critical philosophical issues involved in drawing inferences from neuroscientific research. They argue that these problems are yet to be solved and that organizational researchers who wish to incorporate neuroscientific advances into their work need to engage with them

The development of compassionate engagement and action scales for self and others

Background Studies of the value of compassion on physical and mental health and social relationships have proliferated in the last 25 years. Although, there are several conceptualisations and measures of compassion, this study develops three new measures of compassion competencies derived from an evolutionary, motivational approach. The scales assess 1. the compassion we experience for others, 2. the compassion we experience from others, and 3. self-compassion based on a standard definition of compassion as a ‘sensitivity to suffering in self and others with a commitment to try to alleviate and prevent it’. We explored these in relationship to other compassion scales, self-criticism, depression, anxiety, stress and well-being. Methods Participants from three different countries (UK, Portugal and USA) completed a range of scales including compassion for others, self-compassion, self-criticism, shame, depression, anxiety and stress with the newly developed ‘The Compassionate Engagement and Actions’ scale. Results All three scales have good validity. Interestingly, we found that the three orientations of compassion are only moderately correlated to one another (r < .5). We also found that some elements of self-compassion (e.g., being sensitive to, and moved by one’s suffering) have a complex relationship with other attributes of compassion (e.g., empathy), and with depression, anxiety and stress. A path-analysis showed that self-compassion is a significant mediator of the association between self-reassurance and well-being, while self-criticism has a direct effect on depressive symptoms, not mediated by self-compassion. Discussion Compassion evolved from caring motivation and in humans is associated with a range of different socially intelligent competencies. Understanding how these competencies can be inhibited and facilitated is an important research endeavour. These new scales were designed to assess these competencies. Conclusions This is the first study to measure the three orientations of compassion derived from an evolutionary model of caring motivation with specified competencies. Our three new measures of compassion further indicate important complex relationships between different potentiation’s of compassion, well-being, and vulnerability to psychopathologies.N/

Deep Brain Stimulation of Nucleus Accumbens Region in Alcoholism Affects Reward Processing

The influence of bilateral deep brain stimulation (DBS) of the nucleus nucleus (NAcc) on the processing of reward in a gambling paradigm was investigated using H2[15O]-PET (positron emission tomography) in a 38-year-old man treated for severe alcohol addiction. Behavioral data analysis revealed a less risky, more careful choice behavior under active DBS compared to DBS switched off. PET showed win- and loss-related activations in the paracingulate cortex, temporal poles, precuneus and hippocampus under active DBS, brain areas that have been implicated in action monitoring and behavioral control. Except for the temporal pole these activations were not seen when DBS was deactivated. These findings suggest that DBS of the NAcc may act partially by improving behavioral control