Extreme learning machines for virtual metrology and etch rate prediction

Virtual metrology (VM) aims to predict metrology values using sensor data from production equipment and physical metrology values of preceding samples. VM is a promising technology for the semiconductor manufacturing industry as it can reduce the frequency of in-line metrology operations and provide supportive information for other operations such as fault detection, predictive maintenance and run-to-run control. Methods with minimal user intervention are required to perform VM in a real-time industrial process. In this paper we propose extreme learning machines (ELM) as a competitive alternative to popular methods like lasso and ridge regression for developing VM models. In addition, we propose a new way to choose the hidden layer weights of ELMs that leads to an improvement in its prediction performance.

Holding Shareholders to Account: British Banking Stability and Contingent Capital

This chapter seeks to explain the relative stability of the British banking system in terms of its capital structure. From 1826 joint-stock banking was allowed, but shareholder liability was jointly and severally unlimited. Limited liability banks were allowed from 1857–8, but these banks issued partly paid shares with an obligation on shareholders to subscribe for uncalled capital. Contingent capital meant that shareholders and managers would suffer losses in the event of failure and this discouraged risk shifting at the expense of note-holders and depositors. Although individual banks collapsed, the failure rate of banks (in terms of number or capital) did not reach a critical level—10 per cent—beyond which the payments system might have been threatened. This chapter argues that agency problems and systemic risk rose after the abolition of contingent share capital in 1958 and the deregulation of the banking sector in the 1970s.

Understanding perception and action in sport:How can virtual reality technology help?

Although technology can facilitate improvements in performance by allowing us to understand, monitor and evaluate performance, improvements must ultimately come from within the athlete. The first part of this article will focus on understanding how perception and action relate to performance from two different theoretical viewpoints. The first will be predominantly a cognitive or indirect approach that suggests that expertise and decision-making processes are mediated by athletes accruing large knowledge bases that are built up through practice and experience. The second, and alternative approach, will advocate a more 'direct' solution, where the athlete learns to 'tune' into the relevant information that is embedded in their relationship with the surrounding environment and unfolding action. The second part of the article will attempt to show how emerging virtual reality technology is revealing new evidence that helps us understand elite performance. Possibilities of how new types of training could be developed from this technology will also be discussed. © 2014 Crown Copyright.

Turing’s Menagerie: Talking Lions, Virtual Bats, Electric Sheep and Analogical Peacocks: Common Ground and Common Interest are Necessary Components of Engagement

This theoretical paper attempts to define some of the key components and challenges required to create embodied conversational agents that can be genuinely interesting conversational partners. Wittgenstein’s argument concerning talking lions emphasizes the importance of having a shared common ground as a basis for conversational interactions. Virtual bats suggests that–for some people at least–it is important that there be a feeling of authenticity concerning a subjectively experiencing entity that can convey what it is like to be that entity. Electric sheep reminds us of the importance of empathy in human conversational interaction and that we should provide a full communicative repertoire of both verbal and non-verbal components if we are to create genuinely engaging interactions. Also we may be making the task more difficult rather than easy if we leave out non-verbal aspects of communication. Finally, analogical peacocks highlights the importance of between minds alignment and establishes a longer term goal of being interesting, creative, and humorous if an embodied conversational is to be truly an engaging conversational partner. Some potential directions and solutions to addressing these issues are suggested.

Generating analysis topology using virtual topology operators

Virtual topology operations have been utilized to generate an analysis topology definition suitable for downstream mesh generation. Detailed descriptions are provided for virtual topology merge and split operations for all topological entities, where virtual decompositions are robustly linked to the underlying geometry. Current virtual topology technology is extended to allow the virtual partitioning of volume cells. A valid description of the topology, including relative orientations, is maintained which enables downstream interrogations to be performed on the analysis topology description, such as determining if a specific meshing strategy can be applied to the virtual volume cells. As the virtual representation is a true non-manifold description of the sub-divided domain the interfaces between cells are recorded automatically. Therefore, the advantages of non-manifold modelling are exploited within the manifold modelling environment of a major commercial CAD system without any adaptation of the underlying CAD model. A hierarchical virtual structure is maintained where virtual entities are merged or partitioned. This has a major benefit over existing solutions as the virtual dependencies here are stored in an open and accessible manner, providing the analyst with the freedom to create, modify and edit the analysis topology in any preferred sequence.

Container-based Cloud Virtual Machine Benchmarking

With the availability of a wide range of cloud Virtual Machines (VMs) it is difficult to determine which VMs can maximise the performance of an application. Benchmarking is commonly used to this end for capturing the performance of VMs. Most cloud benchmarking techniques are typically heavyweight - time consuming processes which have to benchmark the entire VM in order to obtain accurate benchmark data. Such benchmarks cannot be used in real-time on the cloud and incur extra costs even before an application is deployed.

In this paper, we present lightweight cloud benchmarking techniques that execute quickly and can be used in near real-time on the cloud. The exploration of lightweight benchmarking techniques are facilitated by the development of DocLite - Docker Container-based Lightweight Benchmarking. DocLite is built on the Docker container technology which allows a user-defined portion (such as memory size and the number of CPU cores) of the VM to be benchmarked. DocLite operates in two modes, in the first mode, containers are used to benchmark a small portion of the VM to generate performance ranks. In the second mode, historic benchmark data is used along with the first mode as a hybrid to generate VM ranks. The generated ranks are evaluated against three scientific high-performance computing applications. The proposed techniques are up to 91 times faster than a heavyweight technique which benchmarks the entire VM. It is observed that the first mode can generate ranks with over 90% and 86% accuracy for sequential and parallel execution of an application. The hybrid mode improves the correlation slightly but the first mode is sufficient for benchmarking cloud VMs.

Following instructions in a virtual school: Does working memory play a role?

Accumulating evidence that working memory supports the ability to follow instructions has so far been restricted to experimental paradigms that have greatly simplified the practical demands of performing actions to instructions in everyday tasks. The aim of the present study was to investigate whether working memory is involved in maintaining information over the longer periods of time that are more typical of everyday situations that require performing instructions to command. Forty-two children 7–11 years of age completed assessments of working memory, a real-world following-instructions task employing 3-D objects, and two new computerized instruction-following tasks involving navigation around a virtual school to complete a sequence of practical spoken commands. One task involved performing actions in a single classroom, and the other, performing actions in multiple locations in a virtual school building. Verbal working memory was closely linked with all three following-instructions paradigms, but with greater association to the virtual than to the real-world tasks. These results indicate that verbal working memory plays a key role in following instructions over extended periods of activity.

The virtual atomic and molecular data centre (VAMDC) consortium

The Virtual Atomic and Molecular Data Centre (VAMDC) Consortium is a worldwide consortium which federates atomic and molecular databases through an e-science infrastructure and an organisation to support this activity. About 90% of the inter-connected databases handle data that are used for the interpretation of astronomical spectra and for modelling in many fields of astrophysics. Recently the VAMDC Consortium has connected databases from the radiation damage and the plasma communities, as well as promoting the publication of data from Indian institutes. This paper describes how the VAMDC Consortium is organised for the optimal distribution of atomic and molecular data for scientific research. It is noted that the VAMDC Consortium strongly advocates that authors of research papers using data cite the original experimental and theoretical papers as well as the relevant databases.