34 resultados para Peer-to-peer architecture (Computer networks)
Resumo:
The Mobile Network Optimization (MNO) technologies have advanced at a tremendous pace in recent years. And the Dynamic Network Optimization (DNO) concept emerged years ago, aimed to continuously optimize the network in response to variations in network traffic and conditions. Yet, DNO development is still at its infancy, mainly hindered by a significant bottleneck of the lengthy optimization runtime. This paper identifies parallelism in greedy MNO algorithms and presents an advanced distributed parallel solution. The solution is designed, implemented and applied to real-life projects whose results yield a significant, highly scalable and nearly linear speedup up to 6.9 and 14.5 on distributed 8-core and 16-core systems respectively. Meanwhile, optimization outputs exhibit self-consistency and high precision compared to their sequential counterpart. This is a milestone in realizing the DNO. Further, the techniques may be applied to similar greedy optimization algorithm based applications.
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The Bloom filter is a space efficient randomized data structure for representing a set and supporting membership queries. Bloom filters intrinsically allow false positives. However, the space savings they offer outweigh the disadvantage if the false positive rates are kept sufficiently low. Inspired by the recent application of the Bloom filter in a novel multicast forwarding fabric, this paper proposes a variant of the Bloom filter, the optihash. The optihash introduces an optimization for the false positive rate at the stage of Bloom filter formation using the same amount of space at the cost of slightly more processing than the classic Bloom filter. Often Bloom filters are used in situations where a fixed amount of space is a primary constraint. We present the optihash as a good alternative to Bloom filters since the amount of space is the same and the improvements in false positives can justify the additional processing. Specifically, we show via simulations and numerical analysis that using the optihash the false positives occurrences can be reduced and controlled at a cost of small additional processing. The simulations are carried out for in-packet forwarding. In this framework, the Bloom filter is used as a compact link/route identifier and it is placed in the packet header to encode the route. At each node, the Bloom filter is queried for membership in order to make forwarding decisions. A false positive in the forwarding decision is translated into packets forwarded along an unintended outgoing link. By using the optihash, false positives can be reduced. The optimization processing is carried out in an entity termed the Topology Manger which is part of the control plane of the multicast forwarding fabric. This processing is only carried out on a per-session basis, not for every packet. The aim of this paper is to present the optihash and evaluate its false positive performances via simulations in order to measure the influence of different parameters on the false positive rate. The false positive rate for the optihash is then compared with the false positive probability of the classic Bloom filter.
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The “butterfly effect” is a popularly known paradigm; commonly it is said that when a butterfly flaps its wings in Brazil, it may cause a tornado in Texas. This essentially describes how weather forecasts can be extremely senstive to small changes in the given atmospheric data, or initial conditions, used in computer model simulations. In 1961 Edward Lorenz found, when running a weather model, that small changes in the initial conditions given to the model can, over time, lead to entriely different forecasts (Lorenz, 1963). This discovery highlights one of the major challenges in modern weather forecasting; that is to provide the computer model with the most accurately specified initial conditions possible. A process known as data assimilation seeks to minimize the errors in the given initial conditions and was, in 1911, described by Bjerkness as “the ultimate problem in meteorology” (Bjerkness, 1911).
Resumo:
The European research project TIDE (Tidal Inlets Dynamics and Environment) is developing and validating coupled models describing the morphological, biological and ecological evolution of tidal environments. The interactions between the physical and biological processes occurring in these regions requires that the system be studied as a whole rather than as separate parts. Extensive use of remote sensing including LiDAR is being made to provide validation data for the modelling. This paper describes the different uses of LiDAR within the project and their relevance to the TIDE science objectives. LiDAR data have been acquired from three different environments, the Venice Lagoon in Italy, Morecambe Bay in England, and the Eden estuary in Scotland. LiDAR accuracy at each site has been evaluated using ground reference data acquired with differential GPS. A semi-automatic technique has been developed to extract tidal channel networks from LiDAR data either used alone or fused with aerial photography. While the resulting networks may require some correction, the procedure does allow network extraction over large areas using objective criteria and reduces fieldwork requirements. The networks extracted may subsequently be used in geomorphological analyses, for example to describe the drainage patterns induced by networks and to examine the rate of change of networks. Estimation of the heights of the low and sparse vegetation on marshes is being investigated by analysis of the statistical distribution of the measured LiDAR heights. Species having different mean heights may be separated using the first-order moments of the height distribution.
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Possible improvements to the conventional rules for using and writing the values of quantities in the International System of Units (SI) are discussed in the light of recent suggestions for improving the system with a view to making it more adaptable to use in computer codes.
Resumo:
1. Although the importance of plant community assemblages in structuring invertebrate assemblages is well known, the role that architectural complexity plays is less well understood. In particular, direct empirical data for a range of invertebrate taxa showing how functional groups respond to plant architecture is largely absent from the literature. 2. The significance of sward architectural complexity in determining the species richness of predatory and phytophagous functional groups of spiders, beetles, and true bugs, sampled from 135 field margin plots over 2 years was tested. The present study compares the relative importance of sward architectural complexity to that of plant community assemblage. 3. Sward architectural complexity was found to be a determinant of species richness for all phytophagous and predatory functional groups. When individual species responses were investigated, 62.5% of the spider and beetle species, and 50.0% of the true bugs responded to sward architectural complexity. 4. Interactions between sward architectural complexity and plant community assemblage indicate that the number of invertebrate species supported by the plant community alone could be increased by modification of sward architecture. Management practices could therefore play a key role in diversifying the architectural structure of existing floral assemblages for the benefit of invertebrate assemblages. 5. The contrasting effects of sward architecture on invertebrate functional groups characterised by either direct (phytophagous species) or indirect (predatory species) dependence on plant communities is discussed. It is suggested that for phytophagous taxa, plant community assemblage alone is likely to be insufficient to ensure successful species colonisation or persistence without appropriate development of sward architecture.
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Background: Medication errors are an important cause of morbidity and mortality in primary care. The aims of this study are to determine the effectiveness, cost effectiveness and acceptability of a pharmacist-led information-technology-based complex intervention compared with simple feedback in reducing proportions of patients at risk from potentially hazardous prescribing and medicines management in general (family) practice. Methods: Research subject group: "At-risk" patients registered with computerised general practices in two geographical regions in England. Design: Parallel group pragmatic cluster randomised trial. Interventions: Practices will be randomised to either: (i) Computer-generated feedback; or (ii) Pharmacist-led intervention comprising of computer-generated feedback, educational outreach and dedicated support. Primary outcome measures: The proportion of patients in each practice at six and 12 months post intervention: - with a computer-recorded history of peptic ulcer being prescribed non-selective non-steroidal anti-inflammatory drugs - with a computer-recorded diagnosis of asthma being prescribed beta-blockers - aged 75 years and older receiving long-term prescriptions for angiotensin converting enzyme inhibitors or loop diuretics without a recorded assessment of renal function and electrolytes in the preceding 15 months. Secondary outcome measures; These relate to a number of other examples of potentially hazardous prescribing and medicines management. Economic analysis: An economic evaluation will be done of the cost per error avoided, from the perspective of the UK National Health Service (NHS), comparing the pharmacist-led intervention with simple feedback. Qualitative analysis: A qualitative study will be conducted to explore the views and experiences of health care professionals and NHS managers concerning the interventions, and investigate possible reasons why the interventions prove effective, or conversely prove ineffective. Sample size: 34 practices in each of the two treatment arms would provide at least 80% power (two-tailed alpha of 0.05) to demonstrate a 50% reduction in error rates for each of the three primary outcome measures in the pharmacist-led intervention arm compared with a 11% reduction in the simple feedback arm. Discussion: At the time of submission of this article, 72 general practices have been recruited (36 in each arm of the trial) and the interventions have been delivered. Analysis has not yet been undertaken.
Resumo:
Nowadays the use of information and communication technology is becoming prevalent in many aspects of healthcare services from patient registration, to consultation, treatment and pathology tests request. Manual interface techniques have dominated data-capture activities in primary care and secondary care settings for decades. Despites the improvements made in IT, usability issues still remain over the use of I/O devices like the computer keyboard, touch-sensitive screens, light pen and barcodes. Furthermore, clinicians have to use several computer applications when providing healthcare services to patients. One of the problems faced by medical professionals is the lack of data integrity between the different software applications which in turn can hinder the provision of healthcare services tailored to the needs of the patients. The use of digital pen and paper technology integrated with legacy medical systems hold the promise of improving healthcare quality. This paper discusses the issue of data integrity in e-health systems and proposes the modelling of "Smart Forms" via semiotics to potentially improve integrity between legacy systems, making the work of medical professionals easier and improve the quality of care in primary care practices and hospitals.
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The perspex machine arose from the unification of projective geometry with the Turing machine. It uses a total arithmetic, called transreal arithmetic, that contains real arithmetic and allows division by zero. Transreal arithmetic is redefined here. The new arithmetic has both a positive and a negative infinity which lie at the extremes of the number line, and a number nullity that lies off the number line. We prove that nullity, 0/0, is a number. Hence a number may have one of four signs: negative, zero, positive, or nullity. It is, therefore, impossible to encode the sign of a number in one bit, as floating-, point arithmetic attempts to do, resulting in the difficulty of having both positive and negative zeros and NaNs. Transrational arithmetic is consistent with Cantor arithmetic. In an extension to real arithmetic, the product of zero, an infinity, or nullity with its reciprocal is nullity, not unity. This avoids the usual contradictions that follow from allowing division by zero. Transreal arithmetic has a fixed algebraic structure and does not admit options as IEEE, floating-point arithmetic does. Most significantly, nullity has a simple semantics that is related to zero. Zero means "no value" and nullity means "no information." We argue that nullity is as useful to a manufactured computer as zero is to a human computer. The perspex machine is intended to offer one solution to the mind-body problem by showing how the computable aspects of mind and. perhaps, the whole of mind relates to the geometrical aspects of body and, perhaps, the whole of body. We review some of Turing's writings and show that he held the view that his machine has spatial properties. In particular, that it has the property of being a 7D lattice of compact spaces. Thus, we read Turing as believing that his machine relates computation to geometrical bodies. We simplify the perspex machine by substituting an augmented Euclidean geometry for projective geometry. This leads to a general-linear perspex-machine which is very much easier to pro-ram than the original perspex-machine. We then show how to map the whole of perspex space into a unit cube. This allows us to construct a fractal of perspex machines with the cardinality of a real-numbered line or space. This fractal is the universal perspex machine. It can solve, in unit time, the halting problem for itself and for all perspex machines instantiated in real-numbered space, including all Turing machines. We cite an experiment that has been proposed to test the physical reality of the perspex machine's model of time, but we make no claim that the physical universe works this way or that it has the cardinality of the perspex machine. We leave it that the perspex machine provides an upper bound on the computational properties of physical things, including manufactured computers and biological organisms, that have a cardinality no greater than the real-number line.
Resumo:
The VERA (Virtual Environment for Research in Archaeology) project is based on a research excavation of part of the large Roman town at Silchester, which aims to trace the site's development from its origins before the Roman conquest to its abandonment in the fifth century A.D. [1]. The VERA project aims to investigate how archaeologists use Information Technology (IT) in the context of a field excavation, and also for post-excavation analysis. VERA is a two-year project funded by the JISC VRE 2 programme that involves researchers from the University of Reading, University College London, and York Archaeological Trust. The overall aim of the project is to assess and introduce new tools and technologies that can aid the archaeological processes of gathering, recording and later analysis of data on the finds and artefacts discovered. The researchers involved in the project have a mix of skills, ranging from those related to archaeology, and computer science, though to ones involving usability and user assessment. This paper reports on the status of the research and development work undertaken in the project so far; this includes addressing various programming hurdles, on-site experiments and experiences, and the outcomes of usability and assessment studies.
Resumo:
The use of n-tuple or weightless neural networks as pattern recognition devices has been well documented. They have a significant advantages over more common networks paradigms, such as the multilayer perceptron in that they can be easily implemented in digital hardware using standard random access memories. To date, n-tuple networks have predominantly been used as fast pattern classification devices. The paper describes how n-tuple techniques can be used in the hardware implementation of a general auto-associative network.
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In a world where data is captured on a large scale the major challenge for data mining algorithms is to be able to scale up to large datasets. There are two main approaches to inducing classification rules, one is the divide and conquer approach, also known as the top down induction of decision trees; the other approach is called the separate and conquer approach. A considerable amount of work has been done on scaling up the divide and conquer approach. However, very little work has been conducted on scaling up the separate and conquer approach.In this work we describe a parallel framework that allows the parallelisation of a certain family of separate and conquer algorithms, the Prism family. Parallelisation helps the Prism family of algorithms to harvest additional computer resources in a network of computers in order to make the induction of classification rules scale better on large datasets. Our framework also incorporates a pre-pruning facility for parallel Prism algorithms.
Resumo:
This research presents a novel multi-functional system for medical Imaging-enabled Assistive Diagnosis (IAD). Although the IAD demonstrator has focused on abdominal images and supports the clinical diagnosis of kidneys using CT/MRI imaging, it can be adapted to work on image delineation, annotation and 3D real-size volumetric modelling of other organ structures such as the brain, spine, etc. The IAD provides advanced real-time 3D visualisation and measurements with fully automated functionalities as developed in two stages. In the first stage, via the clinically driven user interface, specialist clinicians use CT/MRI imaging datasets to accurately delineate and annotate the kidneys and their possible abnormalities, thus creating “3D Golden Standard Models”. Based on these models, in the second stage, clinical support staff i.e. medical technicians interactively define model-based rules and parameters for the integrated “Automatic Recognition Framework” to achieve results which are closest to that of the clinicians. These specific rules and parameters are stored in “Templates” and can later be used by any clinician to automatically identify organ structures i.e. kidneys and their possible abnormalities. The system also supports the transmission of these “Templates” to another expert for a second opinion. A 3D model of the body, the organs and their possible pathology with real metrics is also integrated. The automatic functionality was tested on eleven MRI datasets (comprising of 286 images) and the 3D models were validated by comparing them with the metrics from the corresponding “3D Golden Standard Models”. The system provides metrics for the evaluation of the results, in terms of Accuracy, Precision, Sensitivity, Specificity and Dice Similarity Coefficient (DSC) so as to enable benchmarking of its performance. The first IAD prototype has produced promising results as its performance accuracy based on the most widely deployed evaluation metric, DSC, yields 97% for the recognition of kidneys and 96% for their abnormalities; whilst across all the above evaluation metrics its performance ranges between 96% and 100%. Further development of the IAD system is in progress to extend and evaluate its clinical diagnostic support capability through development and integration of additional algorithms to offer fully computer-aided identification of other organs and their abnormalities based on CT/MRI/Ultra-sound Imaging.
Resumo:
Safety is an element of extreme priority in mining operations, currently many traditional mining countries are investing in the implementation of wireless sensors capable of detecting risk factors; through early warning signs to prevent accidents and significant economic losses. The objective of this research is to contribute to the implementation of sensors for continuous monitoring inside underground mines providing technical parameters for the design of sensor networks applied in underground coal mines. The application of sensors capable of measuring in real time variables of interest, promises to be of great impact on safety for mining industry. The relationship between the geological conditions and mining method design, establish how to implement a system of continuous monitoring. In this paper, the main causes of accidents for underground coal mines are established based on existing worldwide reports. Variables (temperature, gas, structural faults, fires) that can be related to the most frequent causes of disaster and its relevant measuring range are then presented, also the advantages, management and mining operations are discussed, including the analyzed of applying these systems in terms of Benefit, Opportunity, Cost and Risk. The publication focuses on coal mining, based on the proportion of these events a year worldwide, where a significant number of workers are seriously injured or killed. Finally, a dynamic assessment of safety at underground mines it is proposed, this approach offers a contribution to design personalized monitoring networks, the experience developed in coal mines provides a tool that facilitates the application development of technology within underground coal mines.