852 resultados para Semiconductor Services, Ubiquitous Sensor Network
Resumo:
We carried out a retrospective review of the videoconference activity records in a university-run hospital telemedicine studio. Usage records describing videoconferencing activity in the telemedicine studio were compared with the billing records provided by the telecommunications company. During a seven-month period there were 211 entries in the studio log: 108 calls made from the studio and 103 calls made from a far-end location. We found that 103 calls from a total of 195 calls reported by the telecommunications company were recorded in the usage log. The remaining 92 calls were not recorded, probably for one of several reasons, including: failed calls-a large number of unrecorded calls (57%) lasted for less than 2 min (median 1.6 min); origin of videoconference calls-calls may have been recorded incorrectly in the usage diary (i.e. as being initiated from the far end, when actually initiated from the studio); and human error. Our study showed that manual recording of videoconference activity may not accurately reflect the actual activity taking place. Those responsible for recording and analysing videoconference activity, particularly in large telemedicine networks, should do so with care.
Resumo:
In this paper, a novel approach is developed to evaluate the overall performance of a local area network as well as to monitor some possible intrusion detections. The data is obtained via system utility 'ping' and huge data is analyzed via statistical methods. Finally, an overall performance index is defined and simulation experiments in three months proved the effectiveness of the proposed performance index. A software package is developed based on these ideas.
Resumo:
Rural and remote community pharmacies service large areas of rural Queensland, and because of the distances involved often do not meet the patients for whom they provide medication. Telepharmacy would improve the quality of pharmaceutical services provided in rural and remote areas, by allowing community pharmacists to have realtime contact with dispensing doctors, aboriginal health workers and patients via a video-phone. We used commercial (analogue) videophones to connect community pharmacists to dispensing doctors, patients in depot pharmacies (i.e. those with no pharmacist) and aboriginal health workers. However, various problems occurred and only 10 video-phone interactions were recorded during the six-month project. In all of the recorded interactions, the video-phone was actually used as a conventional telephone because a video-connection could not be established at the time of the call. (This may have been due to telephone network problems in the rural areas.) Despite these problems, all project participants showed great enthusiasm for the potential benefits of such a service.
Resumo:
Internet of Things (IoT) can be defined as a “network of networks” composed by billions of uniquely identified physical Smart Objects (SO), organized in an Internet-like structure. Smart Objects can be items equipped with sensors, consumer devices (e.g., smartphones, tablets, or wearable devices), and enterprise assets that are connected both to the Internet and to each others. The birth of the IoT, with its communications paradigms, can be considered as an enabling factor for the creation of the so-called Smart Cities. A Smart City uses Information and Communication Technologies (ICT) to enhance quality, performance and interactivity of urban services, ranging from traffic management and pollution monitoring to government services and energy management. This thesis is focused on multi-hop data dissemination within IoT and Smart Cities scenarios. The proposed multi-hop techniques, mostly based on probabilistic forwarding, have been used for different purposes: from the improvement of the performance of unicast protocols for Wireless Sensor Networks (WSNs) to the efficient data dissemination within Vehicular Ad-hoc NETworks (VANETs).
Resumo:
Current methods for retrieving near surface winds from scatterometer observations over the ocean surface require a foward sensor model which maps the wind vector to the measured backscatter. This paper develops a hybrid neural network forward model, which retains the physical understanding embodied in ¸mod, but incorporates greater flexibility, allowing a better fit to the observations. By introducing a separate model for the mid-beam and using a common model for the fore- and aft-beams, we show a significant improvement in local wind vector retrieval. The hybrid model also fits the scatterometer observations more closely. The model is trained in a Bayesian framework, accounting for the noise on the wind vector inputs. We show that adding more high wind speed observations in the training set improves wind vector retrieval at high wind speeds without compromising performance at medium or low wind speeds.
Resumo:
The provision of advisory support to small firms is almost ubiquitous in OECD countries, although it is organised in different ways and is justified on slightly different grounds. In England publicly supported advisory services are provided through the Business Link (BL) network. Here, we consider two questions: what sort of companies receive advisory support from BL; and, what types of firms benefit most from that support? Our analysis is based on a telephone survey of 2000 firms, around half of which had received intensive assistance from BL between April and October 2003. Probit analysis suggests that the probability of receiving assistance was greater among younger businesses, those with larger numbers of directors in the firm, and those with more gender diversity among the firm's leadership team. Our business-growth models suggest that BL intensive assistance was having a positive effect on employment growth in 2003. BL had a positive but insignificant impact on sales growth over the period. Employment growth effects tend to be larger where firms have a management and organisational structure, which is more conducive to absorbing and making use of external advice. The analysis suggests that BL might increase its impact through targeting these larger, more export-orientated, businesses. Employment growth effects differ little, however, depending on either the ethnic or the gender diversity of the leadership team.
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A city's branding is investigated using generic product and services branding models. Two generic branding models and tourism segmentation models guide an investigation into city branding 'as it should be' and 'as it is' using Birmingham, England as a case study. The unique characteristics of city brands are identified and Keller's Brand Report Card provides a theoretical framework for building a picture of the brand-building activity taking place in the city. Four themes emerge and are discussed: 1) the impact of a network on brand models developed for organisations; 2) segmentation of brand elements; 3) corporate branding; and 4) the political dimension. A conclusion is that city branding would be more effective if the systems and structures of generic branding models were adopted.
Resumo:
In England, publicly supported advice to small firms is organized primarily through the Business Link (BL) network. Using the programme theory underlying this business support, we develop four propositions and test these empirically using data from a new survey of over 3000 English SMEs. We find strong support for the value to BL operators of a high profile to boost take-up. We find support for the BL’s market segmentation that targets intensive assistance to younger firms and those with limited liability. Allowing for sample selection, we find no significant effects on growth from ‘other’ assistance but find a significant employment boost from intensive assistance. This partially supports the programme theory assertion that BL improves business growth and strongly supports the proposition that there are differential outcomes from intensive and other assistance. This suggests an improvement in the BL network, compared with earlier studies, notably Roper et al. (2001), Roper and Hart (2005).
Resumo:
This thesis presents a novel high-performance approach to time-division-multiplexing (TDM) fibre Bragg grating (FBG) optical sensors, known as the resonant cavity architecture. A background theory of FBG optical sensing includes several techniques for multiplexing sensors. The limitations of current wavelength-division-multiplexing (WDM) schemes are contrasted against the technological and commercial advantage of TDM. The author’s hypothesis that ‘it should be possible to achieve TDM FBG sensor interrogation using an electrically switched semiconductor optical amplifier (SOA)’ is then explained. Research and development of a commercially viable optical sensor interrogator based on the resonant cavity architecture forms the remainder of this thesis. A fully programmable SOA drive system allows interrogation of sensor arrays 10km long with a spatial resolution of 8cm and a variable gain system provides dynamic compensation for fluctuating system losses. Ratiometric filter- and diffractive-element spectrometer-based wavelength measurement systems are developed and analysed for different commercial applications. The ratiometric design provides a low-cost solution that has picometre resolution and low noise using 4% reflective sensors, but is less tolerant to variation in system loss. The spectrometer design is more expensive, but delivers exceptional performance with picometre resolution, low noise and tolerance to 13dB system loss variation. Finally, this thesis details the interrogator’s peripheral components, its compliance for operation in harsh industrial environments and several examples of commercial applications where it has been deployed. Applications include laboratory instruments, temperature monitoring systems for oil production, dynamic control for wind-energy and battery powered, self-contained sub-sea strain monitoring.
Resumo:
Satellite-borne scatterometers are used to measure backscattered micro-wave radiation from the ocean surface. This data may be used to infer surface wind vectors where no direct measurements exist. Inherent in this data are outliers owing to aberrations on the water surface and measurement errors within the equipment. We present two techniques for identifying outliers using neural networks; the outliers may then be removed to improve models derived from the data. Firstly the generative topographic mapping (GTM) is used to create a probability density model; data with low probability under the model may be classed as outliers. In the second part of the paper, a sensor model with input-dependent noise is used and outliers are identified based on their probability under this model. GTM was successfully modified to incorporate prior knowledge of the shape of the observation manifold; however, GTM could not learn the double skinned nature of the observation manifold. To learn this double skinned manifold necessitated the use of a sensor model which imposes strong constraints on the mapping. The results using GTM with a fixed noise level suggested the noise level may vary as a function of wind speed. This was confirmed by experiments using a sensor model with input-dependent noise, where the variation in noise is most sensitive to the wind speed input. Both models successfully identified gross outliers with the largest differences between models occurring at low wind speeds. © 2003 Elsevier Science Ltd. All rights reserved.