Customisable arithmetic hardware designs

Imperial Users onl

Applied AI/ML for automatic customisation of medical implants

Most knee replacement surgeries are performed using ‘off-the-shelf’ implants, supplied with a set number of standardised sizes. X-rays are taken during pre-operative assessment and used by clinicians to estimate the best options for patients. Manual templating and implant size selection have, however, been shown to be inaccurate, and frequently the generically shaped products do not adequately fit patients’ unique anatomies. Furthermore, off-the-shelf implants are typically made from solid metal and do not exhibit mechanical properties like the native bone. Consequently, the combination of these factors often leads to poor outcomes for patients. Various solutions have been outlined in the literature for customising the size, shape, and stiffness of implants for the specific needs of individuals. Such designs can be fabricated via additive manufacturing which enables bespoke and intricate geometries to be produced in biocompatible materials. Despite this, all customisation solutions identified required some level of manual input to segment image files, identify anatomical features, and/or drive design software. These tasks are time consuming, expensive, and require trained resource. Almost all currently available solutions also require CT imaging, which adds further expense, incurs high levels of potentially harmful radiation, and is not as commonly accessible as X-ray imaging. This thesis explores how various levels of knee replacement customisation can be completed automatically by applying artificial intelligence, machine learning and statistical methods. The principal output is a software application, believed to be the first true ‘mass-customisation’ solution. The software is compatible with both 2D X-ray and 3D CT data and enables fully automatic and accurate implant size prediction, shape customisation and stiffness matching. It is therefore seen to address the key limitations associated with current implant customisation solutions and will hopefully enable the benefits of customisation to be more widely accessible.Open Acces

The Metadata is the Message

The question "What is Web Science" is still frequently asked - even by authors of papers about Web Science. In this position paper we consider what part of the Web Science cycle makes this cycle emblematically "Web Science" rather than another form of either Law and Technology or Sociology and Technology or Computer Science and HCI. Based on our research developing and evaluating Semantic Web / Web 2.0 applications, and observations of current practice, we suggest that the particularity of Web Science is strongly correlated to a focus on human repurposing of particular Web technologies to support ever more rapid types of increased social contact. Based on this analysis, we ask how Web Science may help understand and shape this phenomenon, and what the implications may be for embracing this focus as a necessary criteria for assessing Web Science relevance of research work

Design and application of reconfigurable circuits and systems

Open Acces

Organizational Change in Digital Servitization

Master's thesis Industrial Economics and Technology Management IND590 - University of Agder 2018Recent changes in markets where customers are demanding more customisation, flexibility, freedom of choice, and instant response; manufacturers and other organizations seek to become more service-oriented and customer-centric for the purpose of recognising and realising product-service offerings, which will enable them to meet the needs of customers with greater capabilities. The process of becoming more service-oriented and customer-centric have been termed servitization, where recent advancements in digital technologies and the rise of Internet-of-Things have lead researchers to acknowledge the importance of embedding technology in product-service systems. This acknowledgement has brought the concept of digital servitization to life where more emphasis on digital technology is present. Digital servitization was first introduced in 2015 and has therefore just recently gained the attention of researchers; where the process of digital servitization, what digital technologies utilised in this regard, and how they are utilised, are yet to be explored. This study seeks to explore how organizations change when implementing a digital servitization strategy, and what digital technologies could be deployed to aid this process and enhance future product-service offerings. The following research is based on an abductive approach which implies that both deductive and inductive approaches are utilised, with more emphasis on the latter. It has been conducted with the qualitative method of multiple case-study where five manufacturers and two IT consultant agencies were interviewed. My findings indicate that these companies are increasing their focus on leveraging data. They seek to establish more sources for gathering data both internally and externally by emphasising a digital ecosystem; and engage in collaborative partnerships with other players in this ecosystem to accomplish greater capabilities in the leverage of data. A culture of sharing and receiving data will have to be mutual for all collaborators. Processes are to be as efficient as possible for allowing data to be transmitted and managed in real-time, where a strong digital infrastructure must be present for this to be possible. By establishing a single digital system, or platform which will consist of all the data, could allow for more complex digital services to be identified and developed; where digital technologies such as blockchains, digital twins, EHF, AI, IoT, AR, and VR are elements that could improve their capability in recognising and realising these services. The importance of a new way of thinking are highlighted due to opportunities in digital technologies being limited only by imagination. The findings in this study could help organizations to better implement a digital servitization strategy

CONSUMER ENGAGEMENT AND VALUE ENHANCEMENT THROUGH PRODUCT INDIVIDUALISATION

Product customisation has always been a regular practice as a form of self or group identification. Previous studies have demonstrated that when investing time and effort to customise a product, an emotional attachment to that product develops. Since the 1980s, new technologies in design, manufacturing and communications have facilitated customisation practices for mass manufacturers as well as for individual consumers. For example, computer algorithms can now automate customisation (i.e. individualise), meaning that the investment of time and effort can be significantly lower than in other customisation processes. Such novel automated practices have, however, not considered the effects on emotional attachment to products, which occurs when the consumer personally engages in the process. This research investigates individualisation as a form of customisation by looking at the relationship between an individualised product and the consumers’ attribution of value and emotional attachment to the end result. This was achieved through a mixed methods approach: following a literature review, in-depth interviews, observation and experiments were carried out. Four pilot studies were conducted, involving 42 respondents (designers, company directors, and consumers). The main study engaged a further 44 respondents, profiled as one of two types of consumers depending on their critical engagement with customisation processes, namely Active Consumers (AC) that Passive Consumers (PC). Data was collected through five Action Research cycles and incorporated key features of Design-Based Research. It was then processed, coded and analysed using thematic analysis. This study makes contributions to knowledge in the area of product customisation and individualisation, as well as in the research methods developed, applied and refined over the four pilot iterations and in the main study. Results suggest that despite limiting freedom of choice, individualisation is a valuable approach to product customisation, particularly for PCs willing to relinquish part of the decision making to an automated process, in order to obtain a customised and unique design. ACs, on the other hand, value their freedom to customise their own products and see individualisation as a limitation to the customisation experience and as a hindrance to developing emotional attachment to the product. These findings have the potential to inform entrepreneurs’ and designers’ decisions to better understand and exploit the benefits associated to individualisation processes. Offering specific consumer groups opportunities to engage with the individualisation process can trigger a strong emotional product attachment and potentially generate new business opportunities

Profile-directed specialisation of custom floating-point hardware

We present a methodology for generating floating-point arithmetic hardware designs which are, for suitable applications, much reduced in size, while still retaining performance and IEEE-754 compliance. Our system uses three key parts: a profiling tool, a set of customisable floating-point units and a selection of system integration methods. We use a profiling tool for floating-point behaviour to identify arithmetic operations where fundamental elements of IEEE-754 floating-point may be compromised, without generating erroneous results in the common case. In the uncommon case, we use simple detection logic to determine when operands lie outside the range of capabilities of the optimised hardware. Out-of-range operations are handled by a separate, fully capable, floatingpoint implementation, either on-chip or by returning calculations to a host processor. We present methods of system integration to achieve this errorcorrection. Thus the system suffers no compromise in IEEE-754 compliance, even when the synthesised hardware would generate erroneous results. In particular, we identify from input operands the shift amounts required for input operand alignment and post-operation normalisation. For operations where these are small, we synthesise hardware with reduced-size barrel-shifters. We also propose optimisations to take advantage of other profile-exposed behaviours, including removing the hardware required to swap operands in a floating-point adder or subtractor, and reducing the exponent range to fit observed values. We present profiling results for a range of applications, including a selection of computational science programs, Spec FP 95 benchmarks and the FFMPEG media processing tool, indicating which would be amenable to our method. Selected applications which demonstrate potential for optimisation are then taken through to a hardware implementation. We show up to a 45% decrease in hardware size for a floating-point datapath, with a correctable error-rate of less then 3%, even with non-profiled datasets

Integrated Project Support Study Group : findings

The challenges of the LHC project have lead CERN to produce a comprehensive set of project management tools covering engineering data management, project scheduling and costing, event management and document management. Each of these tools represents a significant and world-recognised advance in their respective domains. Reviewing the offering on the eve of LHC commissioning one can identify three major challenges: 1. How to integrate the tools to provide a uniform and integrated full-product lifecycle solution 2. How to evolve the functionality in certain areas to address weaknesses identified with our experience in constructing the LHC and integrate emerging industry best practices 3. How to coherently package the offering not just for future projects in CERN, but moreover in the context of providing a centre of excellence for worldwide collaboration in future HEP projects

Doctor of Philosophy

dissertationThe embedded system space is characterized by a rapid evolution in the complexity and functionality of applications. In addition, the short time-to-market nature of the business motivates the use of programmable devices capable of meeting the conflicting constraints of low-energy, high-performance, and short design times. The keys to achieving these conflicting constraints are specialization and maximally extracting available application parallelism. General purpose processors are flexible but are either too power hungry or lack the necessary performance. Application-specific integrated circuits (ASICS) efficiently meet the performance and power needs but are inflexible. Programmable domain-specific architectures (DSAs) are an attractive middle ground, but their design requires significant time, resources, and expertise in a variety of specialties, which range from application algorithms to architecture and ultimately, circuit design. This dissertation presents CoGenE, a design framework that automates the design of energy-performance-optimal DSAs for embedded systems. For a given application domain and a user-chosen initial architectural specification, CoGenE consists of a a Compiler to generate execution binary, a simulator Generator to collect performance/energy statistics, and an Explorer that modifies the current architecture to improve energy-performance-area characteristics. The above process repeats automatically until the user-specified constraints are achieved. This removes or alleviates the time needed to understand the application, manually design the DSA, and generate object code for the DSA. Thus, CoGenE is a new design methodology that represents a significant improvement in performance, energy dissipation, design time, and resources. This dissertation employs the face recognition domain to showcase a flexible architectural design methodology that creates "ASIC-like" DSAs. The DSAs are instruction set architecture (ISA)-independent and achieve good energy-performance characteristics by coscheduling the often conflicting constraints of data access, data movement, and computation through a flexible interconnect. This represents a significant increase in programming complexity and code generation time. To address this problem, the CoGenE compiler employs integer linear programming (ILP)-based 'interconnect-aware' scheduling techniques for automatic code generation. The CoGenE explorer employs an iterative technique to search the complete design space and select a set of energy-performance-optimal candidates. When compared to manual designs, results demonstrate that CoGenE produces superior designs for three application domains: face recognition, speech recognition and wireless telephony. While CoGenE is well suited to applications that exhibit a streaming behavior, multithreaded applications like ray tracing present a different but important challenge. To demonstrate its generality, CoGenE is evaluated in designing a novel multicore N-wide SIMD architecture, known as StreamRay, for the ray tracing domain. CoGenE is used to synthesize the SIMD execution cores, the compiler that generates the application binary, and the interconnection subsystem. Further, separating address and data computations in space reduces data movement and contention for resources, thereby significantly improving performance compared to existing ray tracing approaches

Plan a dashboard for energy measuring, improve overview of energy consumption, and increase energy recovery​

This thesis is written on behalf of a manufacturing company, focusing on energy consumption, recovery, and management. ​ The energy sector continuously changes through carbon emission targets and laws demanding action from companies in the transition to renewable energy resources. Therefore, companies target more innovative manufacturing solutions by measuring, controlling, and visualising energy consumption. Furthermore, the unstable and fluctuating energy situation, rising energy costs, and customers demanding sustainably produced products have enhanced the interest in energy questions at the company. Accordingly, the desire is to improve the overview of energy consumption, improve energy efficiency, and enable energy recovery through storage. Currently, energy measurements are limited to monthly reports based on historical data. This thesis attempts to overcome this by presenting a system providing all stakeholders access to real-time operational data. The energy management system with a dashboard visualising energy consumption and performance indicators could be used to plan production cycles, adjust product prices, and perform predictive maintenance more accurately. The method used in this thesis is qualitative research through interviews with stakeholders at the company. Based on the interview results, a dashboard design is developed through three different layouts, customised for all stakeholder groups. In addition, the proposed energy management system enables visualising collected real-time data in dashboards. The theoretical framework in this thesis is a literature review of scientific research in energy management, dashboard design, energy recovery, and storage. Previous research in energy management presents several implemented technologies improving efficiency, reliability, and stability in the energy supply. The thesis result includes an interview analysis, an energy management system, a dashboard design, and an energy storage system. The interview gives comprehensive knowledge to identify significant performance measures, experience, and interest from stakeholders in the field. The resulting energy management system is an IoT system with collecting assets, an edge platform, a database, and dashboard visualisation. The proposed energy storage system uses thermal energy storage technology with sand as a storage medium. This solution could be driven by renewable energy resources as primary energy resources and implemented to store recovered energy as secondary energy resources improving energy efficiency. In conclusion, this thesis proves that an energy management system with a dashboard visualising collected energy data could be implemented. Furthermore, this thesis concludes that involved stakeholders effectively provide knowledge and experience in the development process of customised dashboard designs