Beef Cattle Feeding

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Raising Beef Calves

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The Programmable City

AbstractThe worldwide proliferation of mobile connected devices has brought about a revolution in the way we live, and will inevitably guide the way in which we design the cities of the future. However, designing city-wide systems poses a new set of challenges in terms of scale, manageability and citizen involvement. Solving these challenges is crucial to making sure that the vision of a programmable Internet of Things (IoT) becomes reality. In this article we will analyse these issues and present a novel programming approach to designing scalable systems for the Internet of Things, with an emphasis on smart city applications, that addresses these issues

LIFE3: A predictive costing tool for digital collections

Predicting the costs of long-term digital preservation is a crucial yet complex task for even the largest repositories and institutions. For smaller projects and individual researchers faced with preservation requirements, the problem is even more overwhelming, as they lack the accumulated experience of the former. Yet being able to estimate future preservation costs is vital to answering a range of important questions for each. The LIFE (Life Cycle Information for E-Literature) project, which has just completed its third phase, helps institutions and researchers address these concerns, reducing the financial and preservation risks, and allowing decision makers to assess a range of options in order to achieve effective preservation while operating within financial restraints. The project is a collaboration between University College London (UCL), The British Library and the Humanities Advanced Technology and Information Institute (HATII) at the University of Glasgow. Funding has been supplied in the UK by the Joint Information Systems Committee (JISC) and the Research Information Network (RIN)

Digital curation and the cloud

Digital curation involves a wide range of activities, many of which could benefit from cloud deployment to a greater or lesser extent. These range from infrequent, resource-intensive tasks which benefit from the ability to rapidly provision resources to day-to-day collaborative activities which can be facilitated by networked cloud services. Associated benefits are offset by risks such as loss of data or service level, legal and governance incompatibilities and transfer bottlenecks. There is considerable variability across both risks and benefits according to the service and deployment models being adopted and the context in which activities are performed. Some risks, such as legal liabilities, are mitigated by the use of alternative, e.g., private cloud models, but this is typically at the expense of benefits such as resource elasticity and economies of scale. Infrastructure as a Service model may provide a basis on which more specialised software services may be provided. There is considerable work to be done in helping institutions understand the cloud and its associated costs, risks and benefits, and how these compare to their current working methods, in order that the most beneficial uses of cloud technologies may be identified. Specific proposals, echoing recent work coordinated by EPSRC and JISC are the development of advisory, costing and brokering services to facilitate appropriate cloud deployments, the exploration of opportunities for certifying or accrediting cloud preservation providers, and the targeted publicity of outputs from pilot studies to the full range of stakeholders within the curation lifecycle, including data creators and owners, repositories, institutional IT support professionals and senior manager

ESTIMATING DETERMINANTS OF STUDENT EVALUATION SCORES TO IMPROVE TEACHING

Student evaluations are used for both formative and summative assessment of teachers. This paper provides a method to make more effective use of these student evaluations by individual teachers. Data on three years of evaluations in two courses were used to develop regression models to explain overall effectiveness of teaching. The relative importance of explanatory variables changed with the course taught.Teaching/Communication/Extension/Profession,

Quantum Hall Effect on the Hyperbolic Plane

In this paper, we study both the continuous model and the discrete model of the Quantum Hall Effect (QHE) on the hyperbolic plane. The Hall conductivity is identified as a geometric invariant associated to an imprimitivity algebra of observables. We define a twisted analogue of the Kasparov map, which enables us to use the pairing between $K$-theory and cyclic cohomology theory, to identify this geometric invariant with a topological index, thereby proving the integrality of the Hall conductivity in this case.Comment: AMS-LaTeX, 28 page

Time delay and integration detectors using charge transfer devices

An imaging system comprises a multi-channel matrix array of CCD devices wherein a number of sensor cells (pixels) in each channel are subdivided and operated in discrete intercoupled groups of subarrays with a readout CCD shift register terminating each end of the channels. Clock voltages, applied to the subarrays, selectively cause charge signal flow in each subarray in either direction independent of the other subarrays. By selective application of four phase clock voltages, either one, two or all three of the sections subarray sections cause charge signal flow in one direction, while the remainder cause charge signal flow in the opposite direction. This creates a form of selective electronic exposure control which provides an effective variable time delay and integration of three, six or nine sensor cells or integration stages. The device is constructed on a semiconductor sustrate with a buried channel and is adapted for front surface imaging through transparent doped tin oxide gates

Distributed Optimization in Energy Harvesting Sensor Networks with Dynamic In-network Data Processing

Energy Harvesting Wireless Sensor Networks (EH- WSNs) have been attracting increasing interest in recent years. Most current EH-WSN approaches focus on sensing and net- working algorithm design, and therefore only consider the energy consumed by sensors and wireless transceivers for sensing and data transmissions respectively. In this paper, we incorporate CPU-intensive edge operations that constitute in-network data processing (e.g. data aggregation/fusion/compression) with sens- ing and networking; to jointly optimize their performance, while ensuring sustainable network operation (i.e. no sensor node runs out of energy). Based on realistic energy and network models, we formulate a stochastic optimization problem, and propose a lightweight on-line algorithm, namely Recycling Wasted Energy (RWE), to solve it. Through rigorous theoretical analysis, we prove that RWE achieves asymptotical optimality, bounded data queue size, and sustainable network operation. We implement RWE on a popular IoT operating system, Contiki OS, and eval- uate its performance using both real-world experiments based on the FIT IoT-LAB testbed, and extensive trace-driven simulations using Cooja. The evaluation results verify our theoretical analysis, and demonstrate that RWE can recycle more than 90% wasted energy caused by battery overflow, and achieve around 300% network utility gain in practical EH-WSNs