How did we come to this? Review of the funding crisis affecting further education college development in England

A review of progress on the Further Education building programme, identifying the main focus of the college developments in relation to regeneration and planning and the conditions that may have contributed to the funding crisis. A thorough literature review was undertaken, and a database compiled, containing information on college developments. Four themes were identified as most relevant to the Built Environment: funding of new college buildings; consolidation on one site and anchoring of regeneration projects; project procurement and delivery, and environmentally sustainable buildings. Four case study examples of colleges have been selected: Middlesbrough, Gateshead, Luton and Sussex Coast College Hastings, all examples of large college projects with a national spread

Emerging from the MIST: A Connector Tool for Supporting Programming by Non-programmers

Software development is an iterative process. As user re-quirements emerge software applications must be extended to support the new requirements. Typically, a programmer will add new code to an existing code base of an application to provide a new functionality. Previous research has shown that such extensions are easier when application logic is clearly separated from the user interface logic. Assuming that a programmer is already familiar with the existing code base, the task of writing the new code can be considered to be split into two sub-tasks: writing code for the application logic; that is, the actual functionality of the application; and writing code for the user interface that will expose the functionality to the end user. The goal of this research is to reduce the effort required to create a user interface once the application logic has been created, toward supporting scientists with minimal pro-gramming knowledge to be able to create and modify pro-grams. Using a Model View Controller based architecture, various model components which contain the application logic can be built and extended. The process of creating and extending the views (user interfaces) on these model components is simplified through the use of our Malleable Interactive Software Toolkit (MIST), a tool set an infrastructure intended to simplify the design and extension of dynamically reconfigurable interfaces. This paper focuses on one tool in the MIST suite, a connec-tor tool that enables the programmer to evolve the user interface as the application logic evolves by connecting related pieces of code together; either through simple drag-and-drop interactions or through the authoring of Python code. The connector tool exemplifies the types of tools in the MIST suite, which we expect will encourage collabora-tive development of applications by allowing users to inte-grate various components and minimizing the cost of de-veloping new user interfaces for the combined compo-nents

Scientists in the MIST: Simplifying Interface Design for End Users

We are building a Malleable Interactive Software Toolkit (MIST), a tool set and infrastructure to simplify the design and construction of dynamically-reconfigurable (malleable) interactive software. Malleable software offers the end-user powerful tools to reshape their interactive environment on the fly. We aim to make the construction of such software straightforward, and to make reconfiguration of the resulting systems approachable and manageable to an educated, but non-specialist, user. To do so, we draw on a diverse body of existing research on alternative approaches to user interface (UI) and interactive software construction, including declarative UI languages, constraint-based programming and UI management, reflection and data-driven programming, and visual programming techniques

On Instance Weighted Clustering Ensembles

© ESANN, 2023. This is the accepted manuscript version of an article which has been published in final form at: www.esann.org/proceedings/2023Ensemble clustering is a technique which combines multipleclustering results, and instance weighting is a technique which highlightsimportant instances in a dataset. Both techniques are known to enhanceclustering performance and robustness. In this research, ensembles andinstance weighting are integrated with the spectral clustering algorithm.We believe this is the first attempt at creating diversity in the generativemechanism using density based instance weighting for a spectral ensemble.The proposed approach is empirically validated using synthetic datasetscomparing against spectral and a spectral ensemble with random instanceweighting. Results show that using the instance weighted sub-samplingapproach as the generative mechanism for an ensemble of spectral cluster-ing leads to improved clustering performance on datasets with imbalancedclusters.Peer reviewe

Towards a Capability Maturity Framework: Adopting the universal elements of Digital Capability Maturity as an Organisational Strategy

As technology continues to evolve, there is a need for organisations to develop the ability to assess themselves and find ways to not only survive but also flourish in the dynamic economy. This paper reports part of the findings from a more extensive research work that aims to develop a Digital Capability Maturity (DCM) Framework for Higher Education Institutions (HEIs). Such a framework would allow organisations to leverage their capabilities for differential value. A systematic review was undertaken to uncover the key elements contributing to DCM, to stand as a baseline for the Maturity Framework. The objective of this paper is to report on the proposed standardisation for elements of DCM. A universal taxonomy is proposed suggesting these themes should be present in any organisational attempts to formalise digital initiatives. Furthermore, to maximise the impact of DCM on quality of output, the proposed framework must adopt the ecological systems perspective

Comparison of dimethyl sulfoxide treated highly conductive poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) electrodes for use in indium tin oxide-free organic electronic photovoltaic devices

Indium tin oxide (ITO)-free organic photovoltaic (OPV) devices were fabricated using highly conductive poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) as the transparent conductive electrode (TCE). The intrinsic conductivity of the PEDOT:PSS films was improved by two different dimethyl sulfoxide (DMSO) treatments – (i) DMSO was added directly to the PEDOT:PSS solution (PEDOT:PSSADD) and (ii) a pre-formed PEDOT:PSS film was immersed in DMSO (PEDOT:PSSIMM). X-ray photoelectron spectroscopy (XPS) and conductive atomic force microscopy (CAFM) studies showed a large amount of PSS was removed from the PEDOT:PSSIMM electrode surface. OPV devices based on a poly(3-hexylthiophene):[6,6]-phenyl-C61-butyric acid methyl ester (P3HT:PCBM) bulk hetrojunction showed that the PEDOT:PSSIMM electrode out-performed the PEDOT:PSSADD electrode, primarily due to an increase in short circuit current density from 6.62 mA cm−2 to 7.15 mA cm−2. The results highlight the importance of optimising the treatment of PEDOT:PSS electrodes and demonstrate their potential as an alternative TCE for rapid processing and low-cost OPV and other organic electronic devices

Revising Max-min for Scheduling in a Cloud Computing Context

Paper presented at the 2017 IEEE 26th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), Poznan, Poland, 21-23 June 2017. © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Adoption of Cloud Computing is on the rise[1] and many datacenter operators adhere to strict energy efficiency guidelines[2]. In this paper a novel approach to scheduling in a Cloud Computing context is proposed. The algorithm Maxmin Fast Track (MXFT) revises the Max-min algorithm to better support smaller tasks with stricter Service Level Agreements (SLAs), which makes it more relevant to Cloud Computing. MXFT is inspired by queuing in supermarkets, where there is a fast lane for customers with a smaller number of items. The algorithm outperforms Max-min in task execution times and outperforms Min-min in overall makespan. A by-product of investigating this algorithm was the development of simulator called “ScheduleSim”[3] which makes it simpler to prove a scheduling algorithm before committing to a specific scheduling problem in Cloud Computing and therefore might be a useful precursor to experiments using the established simulator CloudSim[4].Final Accepted Versio

A Bayesian semi-parametric model for thermal proteome profiling.

Funder: Wellcome TrustThe thermal stability of proteins can be altered when they interact with small molecules, other biomolecules or are subject to post-translation modifications. Thus monitoring the thermal stability of proteins under various cellular perturbations can provide insights into protein function, as well as potentially determine drug targets and off-targets. Thermal proteome profiling is a highly multiplexed mass-spectrommetry method for monitoring the melting behaviour of thousands of proteins in a single experiment. In essence, thermal proteome profiling assumes that proteins denature upon heating and hence become insoluble. Thus, by tracking the relative solubility of proteins at sequentially increasing temperatures, one can report on the thermal stability of a protein. Standard thermodynamics predicts a sigmoidal relationship between temperature and relative solubility and this is the basis of current robust statistical procedures. However, current methods do not model deviations from this behaviour and they do not quantify uncertainty in the melting profiles. To overcome these challenges, we propose the application of Bayesian functional data analysis tools which allow complex temperature-solubility behaviours. Our methods have improved sensitivity over the state-of-the art, identify new drug-protein associations and have less restrictive assumptions than current approaches. Our methods allows for comprehensive analysis of proteins that deviate from the predicted sigmoid behaviour and we uncover potentially biphasic phenomena with a series of published datasets