Iso-Quality of Service: Fairly Ranking Servers for Real-Time Data Analytics

We present a mathematically rigorous Quality-of-Service (QoS) metric which relates the achievable quality of service metric (QoS) for a real-time analytics service to the server energy cost of offering the service. Using a new iso-QoS evaluation methodology, we scale server resources to meet QoS targets and directly rank the servers in terms of their energy-efficiency and by extension cost of ownership. Our metric and method are platform-independent and enable fair comparison of datacenter compute servers with significant architectural diversity, including micro-servers. We deploy our metric and methodology to compare three servers running financial option pricing workloads on real-life market data. We find that server ranking is sensitive to data inputs and desired QoS level and that although scale-out micro-servers can be up to two times more energy-efficient than conventional heavyweight servers for the same target QoS, they are still six times less energy efficient than high-performance computational accelerators.

The use of YouTube Analytics of Video Lecture Capture as a Teaching and Learning Performance Enhancer

Do patterns in the YouTube viewing analytics of Lecture Capture videos point to areas of potential teaching and learning performance enhancement? The goal of this action based research project was to capture and quantitatively analyse the viewing behaviours and patterns of a series of video lecture captures across several computing modules in Queen’s University, Belfast, Northern Ireland. The research sought to establish if a quantitative analysis of viewing behaviours coupled with a qualitative evaluation of the material provided from the students could be correlated to provide generalised patterns that could then be used to understand the learning experience of students during face to face lectures and, thereby, present opportunities to reflectively enhance lecturer performance and the students’ overall learning experience and, ultimately, their level of academic attainment.

Improved lexicon-based sentiment analysis for social media analytics

Social media channels, such as Facebook or Twitter, allow for people to express their views and opinions about any public topics. Public sentiment related to future events, such as demonstrations or parades, indicate public attitude and therefore may be applied while trying to estimate the level of disruption and disorder during such events. Consequently, sentiment analysis of social media content may be of interest for different organisations, especially in security and law enforcement sectors. This paper presents a new lexicon-based sentiment analysis algorithm that has been designed with the main focus on real time Twitter content analysis. The algorithm consists of two key components, namely sentiment normalisation and evidence-based combination function, which have been used in order to estimate the intensity of the sentiment rather than positive/negative label and to support the mixed sentiment classification process. Finally, we illustrate a case study examining the relation between negative sentiment of twitter posts related to English Defence League and the level of disorder during the organisation’s related events.

Operator and Workflow Optimization for High-Performance Analytics

We make a case for studying the impact of intra-node parallelism on the performance of data analytics. We identify four performance optimizations that are enabled by an increasing number of processing cores on a chip. We discuss the performance impact of these opimizations on two analytics operators and we identify how these optimizations affect each another.

Teaching Programming - Understanding Lecture Capture YouTube Analytics

ABSTRACT
The proliferation in the use of video lecture capture in universities worldwide presents an opportunity to analyse video watching patterns in an attempt to quantify and qualify how students engage and learn with the videos. It also presents an opportunity to investigate if there are similar student learning patterns during the equivalent physical lecture. The goal of this action based research project was to capture and quantitatively analyse the viewing behaviours and patterns of a series of video lecture captures across several university Java programming modules. It sought to study if a quantitative analysis of viewing behaviours of Lecture Capture videos coupled with a qualitative evaluation from the students and lecturers could be correlated to provide generalised patterns that could then be used to understand the learning experience of students during videos and potentially face to face lectures and, thereby, present opportunities to reflectively enhance lecturer performance and the students’ overall learning experience. The report establishes a baseline understanding of the analytics of videos of several commonly used pedagogical teaching methods used in the delivery of programming courses. It reflects on possible concurrences within live lecture delivery with the potential to inform and improve lecturing performance.

NanoStreams: Codesigned Microservers for Edge Analytics in Real Time

NanoStreams explores the design, implementation,and system software stack of micro-servers aimed at processingdata in-situ and in real time. These micro-servers can serve theemerging Edge computing ecosystem, namely the provisioningof advanced computational, storage, and networking capabilitynear data sources to achieve both low latency event processingand high throughput analytical processing, before consideringoff-loading some of this processing to high-capacity datacentres.NanoStreams explores a scale-out micro-server architecture thatcan achieve equivalent QoS to that of conventional rack-mountedservers for high-capacity datacentres, but with dramaticallyreduced form factors and power consumption. To this end,NanoStreams introduces novel solutions in programmable & con-figurable hardware accelerators, as well as the system softwarestack used to access, share, and program those accelerators.Our NanoStreams micro-server prototype has demonstrated 5.5×higher energy-efficiency than a standard Xeon Server. Simulationsof the microserver’s memory system extended to leveragehybrid DDR/NVM main memory indicated 5× higher energyefficiencythan a conventional DDR-based system. 

Erstellung wiederverwendbarer RDF-Geodaten mit Google Refine

Das Forschungsinformationssystem VIVO bietet als Linked-Data-basiertes System die Möglichkeit, Daten aus anderen Quellen wiederzuverwenden. In der Praxis kann man dabei auf Konvertierungsprobleme stoßen. Oft liegen Daten nur in tabellarischem Format vor, z.B. als CSV-Datei. Zur Konvertierung dieser Daten existieren verschiedene Werkzeuge, viele dieser Werkzeuge erfordern jedoch entweder spezielle technische Umgebungen (oft Linux-Systeme) oder sie sind in der Bedienung sehr anspruchsvoll. Im Artikel wird ein Workflow für die Konvertierung von Daten aus GeoNames für VIVO mit Google Refine beschrieben.

O software Google Sketchup como instrumento no ensino da geometria descritiva

Relatório da Prática de Ensino Supervisionada, Ensino de Artes Visuais, Universidade de Lisboa, 2013

Prediction and Privacy in Healthcare Analytics

Thesis (Master's)--University of Washington, 2016-03

SecGOD - Google Docs: Now I Feel Safer!

This paper presents SecGOD. A tool that protects the privacy of documents created with online office suites. SecGOD is implemented as a Greasemonkey java-script making it deployable on all popular greesemonkey compatible browsers and utilizes symmetric key encryption. All operations run on the client side, with SecGOD operating invisibly as concerned by the cloud, with no changes needed to the code that is provided to the cloud server provider. Finally, the effectiveness of SecGOD is demonstrated by conducting extensive experiments measuring the processing time for the three versions of AES (128, 192, 256 bits).

Otimização do sítio web e google adwords

Relatório de estágio apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Empreendedorismo e Internacionalização, sob orientação de Doutora Ana Azevedo.

Innovations in technology: a friendly math project and the learning analytics “challenge”

Currently the world around us "reboots" every minute and “staying at the forefront” seems to be a very arduous task. The continuous and “speeded” progress of society requires, from all the actors, a dynamic and efficient attitude both in terms progress monitoring and moving adaptation. With regard to education, no matter how updated we are in relation to the contents, the didactic strategies and technological resources, we are inevitably compelled to adapt to new paradigms and rethink the traditional teaching methods. It is in this context that the contribution of e-learning platforms arises. Here teachers and students have at their disposal new ways to enhance the teaching and learning process, and these platforms are seen, at the present time, as significant virtual teaching and learning supporting environments. This paper presents a Project and attempts to illustrate the potential that new technologies present as a “backing” tool in different stages of teaching and learning at different levels and areas of knowledge, particularly in Mathematics. We intend to promote a constructive discussion moment, exposing our actual perception - that the use of the Learning Management System Moodle, by Higher Education teachers, as supplementary teaching-learning environment for virtual classroom sessions can contribute for greater efficiency and effectiveness of teaching practice and to improve student achievement. Regarding the Learning analytics experience we will present a few results obtained with some assessment Learning Analytics tools, where we profoundly felt that the assessment of students’ performance in online learning environments is a challenging and demanding task.