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Abstract stream information with ball array and binary code. Filtering machine algorithms. Sorting data. Vector technology background. Big data visualization. Information analytics concept.

Predictive analytics in the era of big data

Jacob Zahavi, from The Coller School of Management at Tel Aviv University, discusses the components of predictive analytics (PA) and the increasing complexity of PA problems in the world of Big Data.

A novel route to secure and low-power accelerators for edge computing

Dr. Fabio Pavanello, Researcher at CNRS/CROMA Laboratory, guides us through a novel route to secure and low-power accelerators for edge computing, or in other words, the NEUROPULS approach.
Figure 1: An optical image of a photonic circuit. (Inset) A Silicon Nitride waveguide monolithically coupled to the Silicon SPAD detector.

A portable quantum simulator on a silicon chip

Mher Ghulinyan, Senior researcher at the Fondazione Bruno Kessler’s Centre for Sensors and Devices, tells us about the EPIQUS project and the creation of a cost-effective, user-friendly, and high-performance quantum simulator based on full integration of silicon nitride photonics with silicon electronics.
processor chip, tech environment, blockchain concept

Algorithm “DPTM” for continuous authentication with behavioural biometrics

Takeshi Yamada, Professor from Daiichi Institute of Technology, describes the algorithm “DPTM” for continuous authentication with behavioural biometrics, beginning with the current device security outlook.

Do research software engineers have research methods?

Dr Joanna Leng, School of Computing, University of Leeds, Dr Phillip Brooker, School of Sociology, University of Liverpool and Emeritus Prof Wes Sharrock, School of Sociology, University of Manchester, all from the UK, ponder if Research Software Engineers have research methods, plus why today, we have increasingly more types of academic research institutions and organisations.
Figure 1: Stacked Codes (created with BioRender.com)

The role of stacked codes in the digital age

Chris Girard from Florida International University, sheds light on how, in the digital age, stacked genetic, computer, and quantum codes are being edited by university-trained experts.
Figure 1: Loosely based on the Abernathy-Utterback representation of the innovation pipeline of research software delivery models. Each curve is a model taken from experience and anecdotal evidence. Key: a,) The first stored memory computer is created b,) Grace Hopper and others develop programming languages and numerical methods c,) Teams of mathematicians develop research software, e.g., Dorothy Vaughan see Disney’s film Hidden Figures d,) Open source repository of numerical methods on punch cards collected from academic researchers by Rutherford Appleton Labs as a funding requirement e,) JISC funds research software development in faculty and IT services at universities where funding is along computing expertise, e.g., HPC, visualisation f,) eScience is funding initially to natural and then to social science for centralised teams funding is along research council remit g,) centralised generalised RSE teams are promoted over other models funded by Universities, RSE identified as technicians and more women join the profession h,) slow steady adoption of RSE in national research facilities.

Computing: Paradigm shifts, adoption, new digital professionals rising

Dr Joanna Leng, School of Computing, University of Leeds, UK and Dr Phillip Brooker, School of Sociology, University of Liverpool, Emeritus and Prof Wes Sharrock, School of Sociology, University of Manchester, focus on computing: paradigm shifts, charting the adoption and the rise of new digital professions.
Fig 1: The Abernathy-Utterback curve represents the innovation pipeline in this case as it transitions through the production of two consecutive stable products. It has three phases: 1) the Fluid Phase, where flexibility is needed because of uncertainty in the product idea, the technology and the market and in this case, the needs of the research community; 2) the Transitional Phase, when the technology, the application and the customer’s needs are better understood until a ‘dominant design’ emerges; 3,) the Specific Phase the ‘dominant design’ shifts from being different to having good performance

FFEA software: Repeated early innovation

Dr Joanna Leng, Senior Research Software Engineering Fellow at the University of Leeds, discusses software with repeated early innovation using the example of the FFEA software.

Computational biology is poised to advance precision medicine with machine learning

Today, scientists are attempting to model whole cells using computational biology, building virtual cells that capture the dynamics of living.
rock formations in Broome

Applications of discrete computation in paleoclimate systems

In this earth climate system focus, Michael R. Gipp, Acting President from Marine Mining Corp, details the applications of discrete computation in paleoclimate systems.

Supporting ICT employment opportunities for women in Egypt

Ragui Assaad and Irene Selwaness examine the increase of women in ICT jobs in Egypt, as well as gender disparities and the efforts to promote ICT employment growth.
Interior of big modern server room. 3d rendering illustration

The development of research software engineering as a profession

Dr Joanna Leng at the School of Computing explores Research Software Engineering (RSE) as an emerging profession, and how computing technology is core to many professions.
Abstract web background.

Discussing early innovation software by example of the PERPL software

Dr Joanna Leng, School of Computing, University of Leeds, UK, presents a project from the fellowship, on the PERPL (pattern extraction from relative positions of localisations) software which analyses super-resolution light microscopy (SRLM) data.

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