Using SimVenture in Fashion and Textiles

A case study from the Developing Enterprising Students project, a strategic teaching and learning project at the University of Huddersfield. The case study is based on an interview with Jo Conlon, Senior Lecturer in the Department of Design, School of Art, design and Architecture at the University of Huddersfield on 10 June 2014

Using SimVenture in Veterinary Practice

A case study from the Developing Enterprising Students project, a strategic teaching and learning project at the University of Huddersfield. The case study is based on an interview with Cathy Coates, Teaching Fellow at the University of Bristol on 25th June 2014

Using SimVenture in Information Systems

A case study from the Developing Enterprising Students project, a strategic teaching and learning project at the University of Huddersfield. The case study is based on an interview with Ms Jyoti Bhardwaj (17th June 2014) and a 2011 case study from the Learning, Teaching and Assessment Strategy and Resource Bank at Edinburgh Napier University written by Ms Jyoti Bhardwaj. Ms Jyoti Bhardwaj is a Lecturer and Teaching Fellow in the area of Information System at the School of Computing, Edinburgh Napier University and she has been using SimVenture since 2009/2010

Using SimVenture in Business Management

A case study from the Developing Enterprising Students project, a strategic teaching and learning project at the University of Huddersfield. This case study is based on a 2011 paper by Dina Williams, who was a Senior Lecturer in Entrepreneurship, Department of Strategy & Marketing at The Business School, University of Huddersfield. The paper ‘Impact of Business Simulation Games in Enterprise Education’ was presented at the 2010 University of Huddersfield Annual Learning and Teaching Conference

Using SimVenture in Computer Science & Information Systems Management

A case study from the Developing Enterprising Students project, a strategic teaching and learning project at the University of Huddersfield. The case study is based on an interview with Helen Southall, Senior Lecturer in the department of Computer Science and Information Systems on 22 July 2014

Quantum trajectories for time-dependent adiabatic master equations

We develop a quantum trajectories technique for the unraveling of the quantum adiabatic master equation in Lindblad form. By evolving a complex state vector of dimension $N$ instead of a complex density matrix of dimension $N^2$, simulations of larger system sizes become feasible. The cost of running many trajectories, which is required to recover the master equation evolution, can be minimized by running the trajectories in parallel, making this method suitable for high performance computing clusters. In general, the trajectories method can provide up to a factor $N$ advantage over directly solving the master equation. In special cases where only the expectation values of certain observables are desired, an advantage of up to a factor $N^2$ is possible. We test the method by demonstrating agreement with direct solution of the quantum adiabatic master equation for $8$-qubit quantum annealing examples. We also apply the quantum trajectories method to a $16$-qubit example originally introduced to demonstrate the role of tunneling in quantum annealing, which is significantly more time consuming to solve directly using the master equation. The quantum trajectories method provides insight into individual quantum jump trajectories and their statistics, thus shedding light on open system quantum adiabatic evolution beyond the master equation.Comment: 17 pages, 7 figure

Baseband Detection of Bistatic Electron Spin Signals in Magnetic Resonance Force Microscopy (MRFM)

In single spin Magnetic Resonance Force Microscopy (MRFM), the objective is to detect the presence of an electron (or nuclear) spin in a sample volume by measuring spin-induced attonewton forces using a micromachined cantilever. In the OSCAR method of single spin MRFM, the spins are manipulated by an external rf field to produce small periodic deviations in the resonant frequency of the cantilever. These deviations can be detected by frequency demodulation followed by conventional amplitude or energy detection. In this paper, we present an alternative to these detection methods, based on optimal detection theory and Gibbs sampling. On the basis of simulations, we show that our detector outperforms the conventional amplitude and energy detectors for realistic MRFM operating conditions. For example, to achieve a 10% false alarm rate and an 80% correct detection rate our detector has an 8 dB SNR advantage as compared with the conventional amplitude or energy detectors. Furthermore, at these detection rates it comes within 4 dB of the omniscient matched-filter lower bound.Comment: 8 pages, 9 figures, revision of paper contains correction to a typo on the first page (introduction section

An ontology for carcinoma classification for clinical bioinformatics

There are a number of existing classifications and staging schemes for carcinomas, one of the most frequently used being the TNM classification. Such classifications represent classes of entities which exist at various anatomical levels of granularity. We argue that in order to apply such representations to the Electronic Health Records one needs sound ontologies which take into consideration the diversity of the domains which are involved in clinical bioinformatics. Here we outline a formal theory for addressing these issues in a way that the ontologies can be used to support inferences relating to entities which exist at different anatomical levels of granularity. Our case study is the colon carcinoma, one of the most common carcinomas prevalent within the European population

An Open-Source 7-Axis, Robotic Platform to Enable Dexterous Procedures within CT Scanners

This paper describes the design, manufacture, and performance of a highly dexterous, low-profile, 7 Degree-of-Freedom (DOF) robotic arm for CT-guided percutaneous needle biopsy. Direct CT guidance allows physicians to localize tumours quickly; however, needle insertion is still performed by hand. This system is mounted to a fully active gantry superior to the patient's head and teleoperated by a radiologist. Unlike other similar robots, this robot's fully serial-link approach uses a unique combination of belt and cable drives for high-transparency and minimal-backlash, allowing for an expansive working area and numerous approach angles to targets all while maintaining a small in-bore cross-section of less than $16cm^2$. Simulations verified the system's expansive collision free work-space and ability to hit targets across the entire chest, as required for lung cancer biopsy. Targeting error is on average $<1mm$ on a teleoperated accuracy task, illustrating the system's sufficient accuracy to perform biopsy procedures. The system is designed for lung biopsies due to the large working volume that is required for reaching peripheral lung lesions, though, with its large working volume and small in-bore cross-sectional area, the robotic system is effectively a general-purpose CT-compatible manipulation device for percutaneous procedures. Finally, with the considerable development time undertaken in designing a precise and flexible-use system and with the desire to reduce the burden of other researchers in developing algorithms for image-guided surgery, this system provides open-access, and to the best of our knowledge, is the first open-hardware image-guided biopsy robot of its kind.Comment: 8 pages, 9 figures, final submission to IROS 201

Classification of Stellar Spectra with LLE

We investigate the use of dimensionality reduction techniques for the classification of stellar spectra selected from the SDSS. Using local linear embedding (LLE), a technique that preserves the local (and possibly non-linear) structure within high dimensional data sets, we show that the majority of stellar spectra can be represented as a one dimensional sequence within a three dimensional space. The position along this sequence is highly correlated with spectral temperature. Deviations from this "stellar locus" are indicative of spectra with strong emission lines (including misclassified galaxies) or broad absorption lines (e.g. Carbon stars). Based on this analysis, we propose a hierarchical classification scheme using LLE that progressively identifies and classifies stellar spectra in a manner that requires no feature extraction and that can reproduce the classic MK classifications to an accuracy of one type.Comment: 15 pages, 13 figures; accepted for publication in The Astronomical Journa