Selected Computing Research Papers Volume 7 June 2018

Contents Critical Evaluation of Arabic Sentimental Analysis and Their Accuracy on Microblogs (Maha Al-Sakran) Evaluating Current Research on Psychometric Factors Affecting Teachers in ICT Integration (Daniel Otieno Aoko) A Critical Analysis of Current Measures for Preventing Use of Fraudulent Resources in Cloud Computing (Grant Bulman) An Analytical Assessment of Modern Human Robot Interaction Systems (Dominic Button) Critical Evaluation of Current Power Management Methods Used in Mobile Devices (One Lekula) A Critical Evaluation of Current Face Recognition Systems Research Aimed at Improving Accuracy for Class Attendance (Gladys B. Mogotsi) Usability of E-commerce Website Based on Perceived Homepage Visual Aesthetics (Mercy Ochiel) An Overview Investigation of Reducing the Impact of DDOS Attacks on Cloud Computing within Organisations (Jabed Rahman) Critical Analysis of Online Verification Techniques in Internet Banking Transactions (Fredrick Tshane

Text Similarity Between Concepts Extracted from Source Code and Documentation

Context: Constant evolution in software systems often results in its documentation losing sync with the content of the source code. The traceability research field has often helped in the past with the aim to recover links between code and documentation, when the two fell out of sync. Objective: The aim of this paper is to compare the concepts contained within the source code of a system with those extracted from its documentation, in order to detect how similar these two sets are. If vastly different, the difference between the two sets might indicate a considerable ageing of the documentation, and a need to update it. Methods: In this paper we reduce the source code of 50 software systems to a set of key terms, each containing the concepts of one of the systems sampled. At the same time, we reduce the documentation of each system to another set of key terms. We then use four different approaches for set comparison to detect how the sets are similar. Results: Using the well known Jaccard index as the benchmark for the comparisons, we have discovered that the cosine distance has excellent comparative powers, and depending on the pre-training of the machine learning model. In particular, the SpaCy and the FastText embeddings offer up to 80% and 90% similarity scores. Conclusion: For most of the sampled systems, the source code and the documentation tend to contain very similar concepts. Given the accuracy for one pre-trained model (e.g., FastText), it becomes also evident that a few systems show a measurable drift between the concepts contained in the documentation and in the source code.</p

Discourse in Action

From emails relating to adoption over the Internet to discussions in the airline cockpit, the spoken or written texts we produce can have significant social consequences. The area of Mediated Discourse Analysis considers texts in their social and cultural contexts to explore the actions individuals take with texts - and the consequences of those actions. Discourse in Action: brings together leading scholars from around the world in the area of Mediated Discourse Analysis reveals ways in which its theory and methodology can be used in research into contemporary social situations explores real situations and draws on real data in each chapter shows how analysis of texts in their social contexts broadens our understanding of the real world. Taken together, the chapters provide a comprehensive overview to the field and present a range of current studies that address some of the most important questions facing students and researchers in linguistics, education, communication studies and other fields

Retrieval-, Distributed-, and Interleaved Practice in the Classroom:A Systematic Review

Three of the most effective learning strategies identified are retrieval practice, distributed practice, and interleaved practice, also referred to as desirable difficulties. However, it is yet unknown to what extent these three practices foster learning in primary and secondary education classrooms (as opposed to the laboratory and/or tertiary education classrooms, where most research is conducted) and whether these strategies affect different students differently. To address these gaps, we conducted a systematic review. Initial and detailed screening of 869 documents found in a threefold search resulted in a pool of 29 journal articles published from 2006 through June 2020. Seventy-five effect sizes nested in 47 experiments nested in 29 documents were included in the review. Retrieval- and interleaved practice appeared to benefit students’ learning outcomes quite consistently; distributed practice less so. Furthermore, only cognitive Student*Task characteristics (i.e., features of the student’s cognition regarding the task, such as initial success) appeared to be significant moderators. We conclude that future research further conceptualising and operationalising initial effort is required, as is a differentiated approach to implementing desirable difficulties

Object narratives, imaginings and multilingual communities: young people’s digital stories in the making

This paper draws on research from a global 5-year project, Critical Connections: Multilingual Digital Storytelling (2012-2017), which links language and intercultural learning with literacy, active citizenship and the arts. A critical ethnographic approach was adopted in the research project and the multilingual digital stories were an integral part of the research process. With the project’s focus on multilingualism and creation of bilingual digital texts, young people had to imagine how to use language in new contexts, uncover narratives around objects, and negotiate interfaces between different cultural landscapes. The research findings revealed the complexity of multilingual digital storytelling and how young people (aged 6-18 years old) learnt to become meaning makers discovering their own voices in unfamiliar contexts. Through these digital stories the young people forged strong links with the past and created new multilingual communities

My Story. Digital Storytelling across Europe for Social Cohesion

‘My Story’ (Mysty) is a pan-European, Erasmus+ funded Digital Storytelling project focused on intercultural competency. It has eight partners (HE, secondary schools and NGOs) across four countries (Austria, Italy, Hungary and the UK) and involves the collection, editing and uploading of digital stories to a shared ‘toolbox’. These stories focus on ‘food’, ‘family’ and ‘festival’ and act as a platform for diversity awareness and digital upskilling. The project is driven by the principle that innovative teaching resources form part of broader pedagogic strategies that can actively help tackle issues of diversity common across the EU. The paper discusses the process the project went through, some of its challenges and its results and, on the basis of these, looks at the role digital storytelling as a way of expressing different ethical, cultural or personal issues

Conversations Across Generations: Tracing an Intellectual, Political, and Literary Genealogy From Women of Color Feminist Anthologies to Women of Color Feminist Tumblr

This dissertation examines the digital pedagogy and political genealogy of women of color feminist Tumblr, a networked community of antiracist users on the social media platform Tumblr. I show how these users’ free collection and distribution of social justice educational materials online constitutes a digital feminist of color pedagogy, one which challenges entrenched hierarchies of knowledge-production and circulation. Using textual and discursive analysis as well as social media-specific qualitative methods, I argue that women of color feminist Tumblr harnesses social media as an alternative feminist classroom space—one which challenges the presumed location of feminist and ethnic studies as they have come to be incorporated into the neoliberal multicultural university (Ferguson) and which reimagines their “theoretical subject” (Alarcón) as online users who lack institutional access to these fields’ emancipatory knowledge. Further, I show how the very ethics of this online feminist classroom space are derived from the longer history of women of color feminist praxis and the theorization of “women of color” as a cross-racial, coalitional feminist identity. Building upon the work of Norma Alarcón, Chela Sandoval, and Analouise Keating, who argue that Third World feminism’s “most potentially transformational theories” were largely “bypassed and ignored” (Keating) by mainstream feminist scholarship, my dissertation intervenes by analyzing Third World feminism’s “digital afterlife” (Adair and Nakamura) on social media. By centering questions of race, class, gender, and sexuality within the digital humanities, I join emergent critiques of the digital humanities (Bailey, Cong-Huyen, Lothian, and Phillips 2016) and show how ordinary users transform social media platforms into powerful tools of feminist (re)education.PHDEnglish Language & LiteratureUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163201/1/jalzate_1.pd

Audiovisual processing for sports-video summarisation technology

In this thesis a novel audiovisual feature-based scheme is proposed for the automatic summarization of sports-video content The scope of operability of the scheme is designed to encompass the wide variety o f sports genres that come under the description ‘field-sports’. Given the assumption that, in terms of conveying the narrative of a field-sports-video, score-update events constitute the most significant moments, it is proposed that their detection should thus yield a favourable summarisation solution. To this end, a generic methodology is proposed for the automatic identification of score-update events in field-sports-video content. The scheme is based on the development of robust extractors for a set of critical features, which are shown to reliably indicate their locations. The evidence gathered by the feature extractors is combined and analysed using a Support Vector Machine (SVM), which performs the event detection process. An SVM is chosen on the basis that its underlying technology represents an implementation of the latest generation of machine learning algorithms, based on the recent advances in statistical learning. Effectively, an SVM offers a solution to optimising the classification performance of a decision hypothesis, inferred from a given set of training data. Via a learning phase that utilizes a 90-hour field-sports-video trainmg-corpus, the SVM infers a score-update event model by observing patterns in the extracted feature evidence. Using a similar but distinct 90-hour evaluation corpus, the effectiveness of this model is then tested genencally across multiple genres of fieldsports- video including soccer, rugby, field hockey, hurling, and Gaelic football. The results suggest that in terms o f the summarization task, both high event retrieval and content rejection statistics are achievable