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Becker, Brett A.
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Becker, Brett A.
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Becker, Brett A.
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Now showing 1 - 10 of 25
- PublicationCurrent Challenges and Future Research Areas for Digital Forensic Investigation(2016-05-24)
; ; ; Given the ever-increasing prevalence of technology in modern life, there is a corresponding increase in the likelihood of digital devices being pertinent to a criminal investigation or civil litigation. As a direct consequence, the number of investigations requiring digital forensic expertise is resulting in huge digital evidence backlogs being encountered by law enforcement agencies throughout the world. It can be anticipated that the number of cases requiring digital forensic analysis will greatly increase in the future. It is also likely that each case will require the analysis of an increasing number of devices including computers, smartphones, tablets, cloud-based services, Internet of Things devices, wearables, etc. The variety of new digital evidence sources poses new and challenging problems for the digital investigator from an identification, acquisition, storage and analysis perspective. This paper explores the current challenges contributing to the backlog in digital forensics from a technical standpoint and outlines a number of future research topics that could greatly contribute to a more efficient digital forensic process.547 - PublicationAn Evaluation of Google Plus Communities as an Active Learning Journal Alternative to Improve Learning EfficacyLearning journals are a very beneficial learning tool for students across a range of disciplines. The requirement of frequent entries to a journal encourages students to start achieving the learning objectives from the first week of a module. The completed journal serves as a useful revision resource for students preparing for a final exam or even long after the module’s completion. The downside to learning journals is that they are passive and the class as a whole does not benefit from the variety of opinions, articles and personal experiences logged in their classmates' journals. If the journal is only handed in at the end a semester, there is no room for feedback for the students on their entries until after the module has completed. In this paper, guidelines for the deployment of an active learning journal alternative, using Google Plus Communities, are presented. A literature review is also included for alternative case studies in using learning journals, weblogs, and wikis for recording and encouraging student learning throughout a module.
131 - PublicationHigh-Level Data Partitioning for Parallel Computing on Heterogeneous Hierarchical HPC PlatformsThe current state and foreseeable future of high performance scientific computing (HPC) can be described in three words: heterogeneous, parallel and distributed. These three simple words have a great impact on the architecture and design of HPC platforms and the creation and execution of efficient algorithms and programs designed to run on them. As a result of the inherent heterogeneity, parallelism and distribution which promises to continue to pervade scientific computing in the coming years, the issue of data distribution and therefore data partitioning is unavoidable. This data distribution and partitioning is due to the inherent parallelism of almost all scientific computing platforms. Cluster computing has become all but ubiquitous with the development of clusters of clusters and grids becoming increasingly popular. Even at a lower level, high performance symmetric multiprocessor (SMP) machines, General Purpose Graphical Processing Unit (GPGPU) computing, and multiprocessor parallel machines play an important role. At a very low level, multicore technology is now widespread, increasing in heterogeneity, and promises to be omnipresent in the near future. The prospect of prevalent manycore architectures will inevitably bring yet more heterogeneity. Scientific computing is undergoing a paradigm shift like none before. Only a decade ago most high performance scientific architectures were homogeneous in design and heterogeneity was seen as a difficult and somewhat limiting feature of some architectures. However this past decade has seen the rapid development of architectures designed not only to exploit heterogeneity but architectures designed to be heterogeneous. Grid and massively distributed computing has led the way on this front. The current shift is moving from this to architectures that are not heterogeneous by definition, but heterogeneous by necessity. Cloud and exascale computing architectures and platforms are not designed to be heterogeneous as much as they are heterogeneous by definition. Indeed such architectures cannot be homogeneous on any large (and useful) scale. In fact more and more researchers see heterogeneity as the natural state of computing. Further to hardware advances, scientific problems have become so large that the use of more than one of any of the above platforms in parallel has become necessary, if not unavoidable. Problems such as climatology and projects including the Large Hadron Collider necessitate the use of extreme-scale parallel platforms, often encompassing more than one geographically central supercomputer or cluster. Even at the core level large amounts of information must be shared efficiently. One of the greatest difficulties in solving problems on such architectures is the distribution of data between the different components in a way that optimizes runtime. There have been numerous algorithms developed to do so over the years. Most seek to optimize runtime by reducing the total volume of communication between processing entities. Much research has been conducted to do so between distinct processors or nodes, less so between distributed clusters. This report presents new data partitioning algorithms for matrix and linear algebra operations. These algorithms would in fact work with little or no modification for any application with similar communication patterns. In practice these partitionings distribute data between a small number of computing entities, each of which can have great computational power themselves, and an even greater aggregate power. These partitionings may also be deployed in a hierarchical manner, which allows the flexibility to be employed in a great range of problem domains and computational platforms. These partitionings, in hybrid form, working together with more traditional partitionings, minimize the total volume of communication between entities in a manner proven to be optimal. This is done regardless of the power ratio that exists between the entities, thus minimizing execution time. There is also no restriction on the algorithms or methods employed on the clusters themselves locally, thus maximizing flexibility. Finally, most heterogeneous algorithms and partitionings are designed by modifying existing homogeneous ones. With this in mind the ultimate contribution of this report is to demonstrate that non-traditional and perhaps unintuitive algorithms and partitionings designed with heterogeneity in mind from the start can result in better, and in many cases optimal, algorithms and partitionings for heterogeneous platforms. The importance of this given the current outlook for, and trends in, the future of high performance scientific computing is obvious.
29 - PublicationMindfulness and contemplative practices: The voice of the studentThere is a large spectrum of Mindfulness and Contemplative Practices (MCPs) which are gaining traction in the classroom. Many of these are aimed at reducing stress, reflecting on different points of view, expressing empathy, appreciating diversity and reducing absenteeism to name a few. Some of these practices hold promise to possibly improve attention, concentration and memory capabilities. However, there is no agreed consensus for what students want from MCPs (if anything), if they enjoy them, and if they want to engage in them. Further, it is likely that given the personal nature of MCPs, any findings are likely to be discipline and environment specific, if not specific to the cohort, or even the individual, warranting each educator to determine where their unique students stand. This paper draws motivation from previous empirical research, and the desire of the authors to capture the students? voice on what they want, and what they think works. The environment is a BSc in IT programme in Dublin, Ireland. Students were invited to participate in a mindfulness and contemplative practice workshop in which a number of MCPs were explored with faculty guidance. The MCPs were tailored using results of a preworkshop questionnaire completed by students, with inspiration drawn from the Tree of Contemplative Practices (The Center for Contemplative Mind in Society, 2015). During the workshop various practical sessions were led and results were captured through a postworkshop questionnaire. Results show a significant interest in MPCs, a range of motivations for engaging in them, and diverse practice interests. Overall, a high level of student engagement is a substantial outcome. This paper looks to inform educators seeking to introduce simple contemplative pedagogy practices in the classroom, hopefully making their first attempts more fruitful by allowing them to take into account their students? perceptions and desires. This can be determined by running their own workshop with their own students, or by using the results from ours, and making adjustments as required.
245 - PublicationProgSnap2: A Flexible Format for Programming Process Data(2019-03-04)
; ; ; ; In this paper, we introduce ProgSnap2, a standardized format for logging programming process data. The goal of this common format is to encourage collaboration among researchers by helping them to share data, analysis code, and data-driven tools to support students. We first highlight possible use cases for ProgSnap2 and give a high-level overview of the format. We then share two case studies of our experience using the format and outline goals for the future of ProgSnap2, including a call for collaboration with interested researchers.336 - PublicationReflective Learning Journals in Computer Science: The Student ExperienceThis paper is centred on undergraduate students enrolled on a BSc in IT programme in Dublin, Ireland, with a view to enhancing student engagement in learning through reflexivity. Reflective learning places the emphasis on the self as the source of learning and is inherently an individual and interactive process. Boud et al. (1985) state that reflection is an important human activity in which people recapture their experience, think about it, mull it over and evaluate it. It is this working with experience that is important in learning. The authors developed and evaluated a reflective learning journal tool that was used to capture the reflective learning processes within students studying computer programming, a subject known to present significant learning barriers for 1st year BSc computing students. In addition, existing student study habit behaviours were investigated to determine which approaches, materials and sources they had a preference for, to further shape the delivery of module content in the future.
223 - PublicationCategorizing Compiler Error Messages with Principal Component Analysis(2016-05-29)
; Being a competent programmer is critical for students in all computing disciplines and software engineering in particular. Novice programming students face a number of challenges and these have been shown to contribute to worrying dropout rates for students majoring in computing, and the growing number of non-majors who are learning to program. Methods of identifying and helping at-risk programming students have been researched for decades. Much of this research focuses on categorizing the errors that novice programmers make, in order to help understand why these errors are made, with the goal of helping them overcome these errors quickly, or avoid them altogether. This paper presents the first known work on categorizing compiler errors using Principal Component Analysis. In this, we find a new way of discovering categories of related errors from data produced by the students in the course of their programming activity. This method may be used to identify where these students are struggling and provide direction in efforts to help them.285 - PublicationIntroducing Contemplative Pedagogy to the Classroom: Implementation, Experience and Effects on Concentration(2014-12-05)
; ; While there is no single theory or praxis of contemplative pedagogy (Coburn, 2011), there is a wide spectrum of Mindfulness Meditation Practices (MMPs) being used in the classroom at a growing number of institutions. Many of these are aimed outcomes such as reducing stress, reflection (including self-reflection), expressing empathy, appreciating diversity and reducing absenteeism. Some of these practices also hold promise to possibly improve cognition, concentration and memory capabilities. This paper explores the experience of implementing a one-pointedness MMP in the classroom at an Irish higher education institution. The focus is on simplicity of implementation, minimal disruption, student engagement with the practice and any positive effects this may bring to the concentration/attention abilities of students. Specifically, a one-pointedness meditation is practiced by students at the outset of each lecture in a specified module. At the end of the lecture period, students are given a form of Wilkins¿ counting test, a measure of sustained focused concentration. Results are then compared to the performance of the same cohort in another module with no one-pointedness exercise, serving as control. Results show a small and borderline statistically-significant increase in the concentration abilities of students in the module that includes the one-pointedness meditation. Students also participated in a questionnaire and a discussion group, reflecting on their experience with the practice, and their opinions on introducing MMPs into their learning. Overall the student experience was much more positive than the authors had envisioned, even hoped for. At a minimum the results of this paper can inform educators looking to introduce simple contemplative pedagogy practices in the classroom, hopefully making their first attempts more fruitful.54 - PublicationInvestigating the Impact of the COVID-19 Pandemic on Computing Students' Sense of BelongingSense of belonging, or belongingness, describes how accepted one feels in their academic community and is an important factor in creating inclusive learning environments. Belongingness is influenced by many factors including: students' backgrounds and experiences; other people; environments (physical and virtual); academic discipline; external factors such as local, regional, and global issues; and time. 2020 has been dominated by several major events including the COVID-19 pandemic which dramatically impacted education. The Black Lives Matter movement has further raised global awareness of equality, diversity and inclusion not just in society, but in educational contexts. Climate change concerns, and politically-charged news are also increasingly affecting our students. We have been monitoring our undergraduate computing students' sense of belonging for over three years, providing us with a unique opportunity to gauge recent changes during the pandemic. Our results surprised us. We found statistically significant reductions in the belongingness of students identifying as men as well as those not identifying as being part of a minority. However, investigating intersectionality of self-identified gender and minority status revealed more complicated and nuanced trends, illustrating important shifts in the belongingness of our students that we are only beginning to understand.
227Scopus© Citations 15 - PublicationImproving Borderline Adulthood Facial Age Estimation through Ensemble Learning(ACM, 2019-08-26)
; ; ; ; ; ; Achieving high performance for facial age estimation with subjects in the borderline between adulthood and non-adulthood has always been a challenge. Several studies have used different approaches from the age of a baby to an elder adult and different datasets have been employed to measure the mean absolute error (MAE) ranging between 1.47 to 8 years. The weakness of the algorithms specifically in the borderline has been a motivation for this paper. In our approach, we have developed an ensemble technique that improves the accuracy of underage estimation in conjunction with our deep learning model (DS13K) that has been fine-tuned on the Deep Expectation (DEX) model. We have achieved an accuracy of 68% for the age group 16 to 17 years old, which is 4 times better than the DEX accuracy for such age range. We also present an evaluation of existing cloud-based and offline facial age prediction services, such as Amazon Rekognition, Microsoft Azure Cognitive Services, How-Old.net and DEX.218Scopus© Citations 10