Designers and manufacturers’ perspectives on inclusive/universal design

Inclusive design in the U.K. and its U.S. counterpart, universal design, present opportunities and challenges to industry. In order to encourage manufacturers and design companies to adopt more inclusive design practices, the research has been carried out to gain an understanding of why and how companies adopt inclusive design practices, what are the barriers when implementing them and what are the key strategies for facilitating inclusive/universal design in an industrial context. Based on interviews with a number of U.K. design consultancies and an investigation among manufacturers in the U.S., a comparison between U.K. consultant designers and U.S. consumer product manufacturers’ perspectives on inclusive/universal design was made. It was found that designers are reluctant to sacrifice the aesthetics of the brand to design for inclusion, but nevertheless would like to have practical tools to help them develop more inclusive solutions. For manufacturers, the key motivation for such practices is that of government regulation and legislation requiring the accessibility of products and services

When Universal Access does not go to plan: Lessons to be learned

While the theory of designing for Universal Access is increasingly understood, there remain persistent issues over realising products and systems that meet the goal of being accessible and usable by the broadest possible set of users. Clearly products or service that are designed without even considering the needs of the wider user base are implicitly going to struggle to be universally accessible. However, even products that have been designed knowing that they are to be used by broad user bases frequently still struggle to achieve the ambition of being universally accessible. This paper examines a number of such products that did not achieve, at least initially, the desired level of universal accessibility. Principal recommendations from each case study are presented to provide a guide to common issues to be avoided

The role of simulation in designing for universal access

It is known that the adoption of user-centred design processes can lead to more universally accessible products and services. However, the most frequently cited approach to user-centred design, i.e. participatory design, can be both problematic and expensive to implement., particularly over the difficulty of finding and recruiting suitable participants. Simulation aids offer a potentially cost-effective replacement or complement to participatory design. This paper examines a number of the issues associated with the use of simulation aids when designing for Universal Access. It concludes that simulation aids can play an effective role, but need to be used with due consideration over what insights they provide

Assessing the number of users who are excluded by domestic heating controls

This is the pre-print version of the Article. This Article is also referred to as: "Assessing the 'Design Exclusion' of Heating Controls at a Low-Cost, Low-Carbon Housing Development". - Copyright @ 2011 Taylor & FrancisSpace heating accounts for almost 60% of the energy delivered to housing which in turn accounts for nearly 27% of the total UK's carbon emissions. This study was conducted to investigate the influence of heating control design on the degree of ‘user exclusion’. This was calculated using the Design Exclusion Calculator, developed by the Engineering Design Centre at the University of Cambridge. To elucidate the capability requirements of the system, a detailed hierarchical task analysis was produced, due to the complexity of the overall task. The Exclusion Calculation found that the current design placed excessive demands upon the capabilities of at least 9.5% of the UK population over 16 years old, particularly in terms of ‘vision’, ‘thinking’ and ‘dexterity’ requirements. This increased to 20.7% for users over 60 years old. The method does not account for the level of numeracy and literacy and so the true exclusion may be higher. Usability testing was conducted to help validate the results which indicated that 66% of users at a low-carbon housing development could not programme their controls as desired. Therefore, more detailed analysis of the cognitive demands placed upon the users is required to understand where problems within the programming process occur. Further research focusing on this cognitive interaction will work towards a solution that may allow users to behave easily in a more sustainable manner

On the breaking of collinear factorization in QCD

We investigate the breakdown of collinear factorization for non-inclusive observables in hadron-hadron collisions. For pure QCD processes, factorization is violated at the three-loop level and it has a structure identical to that encountered previously in the case of super-leading logarithms. In particular, it is driven by the non-commutation of Coulomb/Glauber gluon exchanges with other soft exchanges. Beyond QCD, factorization may be violated at the two-loop level provided that the hard subprocess contains matrix element contributions with phase differences between different colour topologies.Comment: Version 2: minor improvements for journal publicatio

Using Deep Neural Networks to Classify Symbolic Road Markings for Autonomous Vehicles

To make autonomous cars as safe as feasible for all road users, it is essential to interpret as many sources of trustworthy information as possible. There has been substantial research into interpreting objects such as traffic lights and pedestrian information, however, less attention has been paid to the Symbolic Road Markings (SRMs). SRMs are essential information that needs to be interpreted by autonomous vehicles, hence, this case study presents a comprehensive model primarily focused on classifying painted symbolic road markings by using a region of interest (ROI) detector and a deep convolutional neural network (DCNN). This two-stage model has been trained and tested using an extensive public dataset. The two-stage model investigated in this research includes SRM classification by using Hough lines where features were extracted and the CNN model was trained and tested. An ROI detector is presented that crops and segments the road lane to eliminate non-essential features of the image. The investigated model is robust, achieving up to 92.96 percent accuracy with 26.07 and 40.1 frames per second (FPS) using ROI scaled and raw images, respectively

Jet vetoing and Herwig++

We investigate the simulation of events with gaps between jets with a veto on additional radiation in the gap in Herwig++. We discover that the currently-used random treatment of radiation in the parton shower is generating some unphysical behaviour for wide-angle gluon emission in QCD 2 to 2 scatterings. We explore this behaviour quantitatively by making the same assumptions as the parton shower in the analytical calculation. We then modify the parton shower algorithm in order to correct the simulation of QCD radiation.Comment: 18 pages, 11 figure

Computer Vision-Based Kidney’s (HK-2) Damaged Cells Classification with Reconfigurable Hardware Accelerator (FPGA)

In medical and health sciences, the detection of cell injury plays an important role in diagnosis, personal treatment and disease prevention. Despite recent advancements in tools and methods for image classification, it is challenging to classify cell images with higher precision and accuracy. Cell classification based on computer vision offers significant benefits in biomedicine and healthcare. There have been studies reported where cell classification techniques have been complemented by Artificial Intelligence-based classifiers such as Convolutional Neural Networks. These classifiers suffer from the drawback of the scale of computational resources required for training and hence do not offer real-time classification capabilities for an embedded system platform. Field Programmable Gate Arrays (FPGAs) offer the flexibility of hardware reconfiguration and have emerged as a viable platform for algorithm acceleration. Given that the logic resources and on-chip memory available on a single device are still limited, hardware/software co-design is proposed where image pre-processing and network training were performed in software, and trained architectures were mapped onto an FPGA device (Nexys4DDR) for real-time cell classification. This paper demonstrates that the embedded hardware-based cell classifier performs with almost 100% accuracy in detecting different types of damaged kidney cells