Study of techniques for the reduction of creep in plated wire memories Final report, 28 Jun. 1967 - 28 Aug. 1968

Magnetization reversal in thin films of plated wire memory element

Are HIV smartphone apps and online interventions fit for purpose?

Sexual health is an under-explored area of Human-Computer Interaction (HCI), particularly sexually transmitted infections such as HIV. Due to the stigma associated with these infections, people are often motivated to seek information online. With the rise of smartphone and web apps, there is enormous potential for technology to provide easily accessible information and resources. However, using online information raises important concerns about the trustworthiness of these resources and whether they are fit for purpose. We conducted a review of smartphone and web apps to investigate the landscape of currently available online apps and whether they meet the diverse needs of people seeking information on HIV online. Our functionality review revealed that existing technology interventions have a one-size-fits-all approach and do not support the breadth and complexity of HIV-related support needs. We argue that technology-based interventions need to signpost their offering and provide tailored support for different stages of HIV, including prevention, testing, diagnosis and management

The Paradox of Compacts: final report to the Home Office on monitoring the impact of Compacts

The Compact is an important building block in achieving a better relationship between Government and the voluntary and community sector. We are fully committed to partnership working with the sector and increasing their role in civil society and in the delivery of public s e rvices. The Compact helps us to work better together, so that we can better meet the needs of communities

Scholarly Communication Practices in Humanities and Social Sciences: A Study of Researchers’ Attitudes and Awareness of Open Access

This paper examines issues relating to the perceptions and adoption of open access (OA) and institutional repositories. Using a survey research design, we collected data from academics and other researchers in the humanities, arts and social sciences (HASS) at a university in Australia. We looked at factors influencing choice of publishers and journal outlets, as well as the use of social media and nontraditional channels for scholarly communication. We used an online questionnaire to collect data and used descriptive statistics to analyse the data. Our findings suggest that researchers are highly influenced by traditional measures of quality, such as journal impact factor, and are less concerned with making their work more findable and promoting it through social media. This highlights a disconnect between researchers’ desired outcomes and the efforts that they put in toward the same. Our findings also suggest that institutional policies have the potential to increase OA awareness and adoption. This study contributes to the growing literature on scholarly communication by offering evidence from the HASS field, where limited studies have been conducted. Based on the findings, we recommend that academic librarians engage with faculty through outreach and workshops to change perceptions of OA and the institutional repository

Emission-aware Energy Storage Scheduling for a Greener Grid

Reducing our reliance on carbon-intensive energy sources is vital for reducing the carbon footprint of the electric grid. Although the grid is seeing increasing deployments of clean, renewable sources of energy, a significant portion of the grid demand is still met using traditional carbon-intensive energy sources. In this paper, we study the problem of using energy storage deployed in the grid to reduce the grid's carbon emissions. While energy storage has previously been used for grid optimizations such as peak shaving and smoothing intermittent sources, our insight is to use distributed storage to enable utilities to reduce their reliance on their less efficient and most carbon-intensive power plants and thereby reduce their overall emission footprint. We formulate the problem of emission-aware scheduling of distributed energy storage as an optimization problem, and use a robust optimization approach that is well-suited for handling the uncertainty in load predictions, especially in the presence of intermittent renewables such as solar and wind. We evaluate our approach using a state of the art neural network load forecasting technique and real load traces from a distribution grid with 1,341 homes. Our results show a reduction of >0.5 million kg in annual carbon emissions -- equivalent to a drop of 23.3% in our electric grid emissions.Comment: 11 pages, 7 figure, This paper will appear in the Proceedings of the ACM International Conference on Future Energy Systems (e-Energy 20) June 2020, Australi

Comparing machine learning models to choose the variable ordering for cylindrical algebraic decomposition

There has been recent interest in the use of machine learning (ML) approaches within mathematical software to make choices that impact on the computing performance without affecting the mathematical correctness of the result. We address the problem of selecting the variable ordering for cylindrical algebraic decomposition (CAD), an important algorithm in Symbolic Computation. Prior work to apply ML on this problem implemented a Support Vector Machine (SVM) to select between three existing human-made heuristics, which did better than anyone heuristic alone. The present work extends to have ML select the variable ordering directly, and to try a wider variety of ML techniques. We experimented with the NLSAT dataset and the Regular Chains Library CAD function for Maple 2018. For each problem, the variable ordering leading to the shortest computing time was selected as the target class for ML. Features were generated from the polynomial input and used to train the following ML models: k-nearest neighbours (KNN) classifier, multi-layer perceptron (MLP), decision tree (DT) and SVM, as implemented in the Python scikit-learn package. We also compared these with the two leading human constructed heuristics for the problem: Brown's heuristic and sotd. On this dataset all of the ML approaches outperformed the human made heuristics, some by a large margin.Comment: Accepted into CICM 201

Abelian functions associated with a cyclic tetragonal curve of genus six

We develop the theory of Abelian functions defined using a tetragonal curve of genus six, discussing in detail the cyclic curve y^4 = x^5 + λ[4]x^4 + λ[3]x^3 + λ[2]x^2 + λ[1]x + λ[0]. We construct Abelian functions using the multivariate sigma-function associated with the curve, generalizing the theory of theWeierstrass℘-function. We demonstrate that such functions can give a solution to the KP-equation, outlining how a general class of solutions could be generated using a wider class of curves. We also present the associated partial differential equations satisfied by the functions, the solution of the Jacobi inversion problem, a power series expansion for σ(u) and a new addition formula