This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractThere are around 285 million visually-impaired people worldwide, and around 370,000 people are registered as blind or partially sighted in the UK A . On-going advances in information technology (IT) are increasing the scope for IT-based mobile assistive technologies to facilitate the independence, safety, and improved quality of life of the visually impaired. Research is being directed at making mobile phones and other handheld devices accessible via our haptic (touch) and audio sensory channels. We review research and innovation within the field of mobile assistive technology for the visually impaired and, in so doing, highlight the need for successful collaboration between clinical expertise, computer science, and domain users to realize fully the potential benefits of such technologies. We initially reflect on research which has been conducted to make mobile phones more accessible to people with vision loss. We then discuss innovative assistive applications designed for the visually impaired that are either delivered via mainstream devices and can be used while in motion (e.g., mobile phones) or are embedded within an environment that may be in motion (e.g., public transport) or within which the user may be in motion (e.g., smart homes).

Abstract-Research into cyberbullying detection has increased in recent years, due in part to the proliferation of cyberbullying across social media and its detrimental effect on young people. A growing body of work is emerging on automated approaches to cyberbullying detection. These approaches utilise machine learning and natural language processing techniques to identify the characteristics of a cyberbullying exchange and automatically detect cyberbullying by matching textual data to the identified traits. In this paper, we present a systematic review of published research (as identified via Scopus, ACM and IEEE Xplore bibliographic databases) on cyberbullying detection approaches. On the basis of our extensive literature review, we categorise existing approaches into 4 main classes, namely supervised learning, lexicon-based, rule-based, and mixed-initiative approaches. Supervised learning-based approaches typically use classifiers such as SVM and Naïve Bayes to develop predictive models for cyberbullying detection. Lexicon-based systems utilise word lists and use the presence of words within the lists to detect cyberbullying. Rule-based approaches match text to predefined rules to identify bullying, and mixed-initiatives approaches combine human-based reasoning with one or more of the aforementioned approaches. We found lack of labelled datasets and non-holistic consideration of cyberbullying by researchers when developing detection systems are two key challenges facing cyberbullying detection research. This paper essentially maps out the state-of-the-art in cyberbullying detection research and serves as a resource for researchers to determine where to best direct their future research efforts in this field.

Mobile and wearable computers present input/output problems due to limited screen space and interaction techniques. When mobile, users typically focus their visual attention on navigating their environment -making visually demanding interface designs hard to operate. This paper presents two multimodal interaction techniques designed to overcome these problems and allow truly mobile, 'eyes-free' device use. The first is a 3D audio radial pie menu that uses head gestures for selecting items. An evaluation of a range of different audio designs showed that egocentric sounds reduced task completion time, perceived annoyance, and allowed users to walk closer to their preferred walking speed. The second is a sonically enhanced 2D gesture recognition system for use on a belt-mounted PDA. An evaluation of the system with and without audio feedback showed users' gestures were more accurate when dynamically guided by audio-feedback. These novel interaction techniques demonstrate effective alternatives to visual-centric interface designs on mobile devices.

Mobile and wearable computers present input/output problems due to limited screen space and interaction techniques. When mobile, users typically focus their visual attention on navigating their environment -making visually demanding interface designs hard to operate. This paper presents two multimodal interaction techniques designed to overcome these problems and allow truly mobile, 'eyes-free' device use. The first is a 3D audio radial pie menu that uses head gestures for selecting items. An evaluation of a range of different audio designs showed that egocentric sounds reduced task completion time, perceived annoyance, and allowed users to walk closer to their preferred walking speed. The second is a sonically enhanced 2D gesture recognition system for use on a belt-mounted PDA. An evaluation of the system with and without audio feedback showed users' gestures were more accurate when dynamically guided by audio-feedback. These novel interaction techniques demonstrate effective alternatives to visual-centric interface designs on mobile devices.

Trust is a critical component of successful e-Commerce. Given the impersonality, anonymity, and automation of transactions, online vendor trustworthiness cannot be assessed by means of body language and other environmental cues that consumers typically use when deciding to trust offline retailers. It is therefore essential that the design of e-Commerce websites compensate by incorporating circumstantial cues in the form of appropriate trust triggers. This paper presents and discusses the results of a study which took an initial look at whether consumers with different personality types (a) are generally more trusting and (b) rely on different trust cues during their assessment of first impression vendor trustworthiness in B2C e-Commerce.