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Wireless Personal Communications - In recent years, the emergence of Internet of things and cyber-physical system provide a proactive and efficacious solution to enable remote monitoring, machine... 相似文献
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Lima A.M.N. Deep G.S. Neto J.S.R. Freire R.C.S. Lobo P.C. 《IEEE transactions on instrumentation and measurement》1994,43(2):133-138
An identification procedure to estimate the parameters of a thermoresistive solar radiation sensor is presented. The proposed technique employs only electrical excitation for the sensor. The estimation algorithm is recursive and is applied to the sensor model derived from the thermodynamic equilibrium differential equations. The simulation and the experimental results demonstrate the validity of the proposed approach 相似文献
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The promising potential of cloud computing and its convergence with technologies such as mobile computing, wireless networks, sensor technologies allows for creation and delivery of newer type of cloud services. In this paper, we advocate the use of cloud computing for the creation and management of cloud based health care services. As a representative case study, we design a Cloud Based Intelligent Health Care Service (CBIHCS) that performs real time monitoring of user health data for diagnosis of chronic illness such as diabetes. Advance body sensor components are utilized to gather user specific health data and store in cloud based storage repositories for subsequent analysis and classification. In addition, infrastructure level mechanisms are proposed to provide dynamic resource elasticity for CBIHCS. Experimental results demonstrate that classification accuracy of 92.59% is achieved with our prototype system and the predicted patterns of CPU usage offer better opportunities for adaptive resource elasticity. 相似文献
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M.?Todd?GardnerEmail author Rebecca?May Cory?Beard Deep?Medhi 《Journal of Network and Systems Management》2016,24(3):711-745
Various natural and man-made disasters as well as major political events (like riots) have increased the importance of understanding geographic failures and how correlated failures impact networks. Since mission critical networks are overlaid as virtual networks over a physical network infrastructure forming multilayer networks, there is an increasing need for methods to analyze multilayer networks for geographic vulnerabilities. In this paper, we present a novel impact-based resilience metric. Our new metric uses ideas borrowed from performability to combine network impact with state probability to calculate a new metric called Network Impact Resilience. The idea is that the highest impact to the mission of a network should drive its resilience metric. Furthermore, we present a state space analysis method that analyzes multilayer networks for geographic vulnerabilities. To demonstrate the methods, the inability to provision a given number of upper layer services is used as the criteria for network failure. Mapping techniques for multilayer network states are presented. Simplifying geographic state mapping techniques to reduce enumeration costs are also presented and tested. Finally, these techniques are tested on networks of varying sizes. 相似文献
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Sangram Ganguly Arindam Samanta Mitchell A. Schull Nikolay V. Shabanov Cristina Milesi Ramakrishna R. Nemani Yuri Knyazikhin Ranga B. Myneni 《Remote sensing of environment》2008,112(12):4318-4332
The evaluation of a new global monthly leaf area index (LAI) data set for the period July 1981 to December 2006 derived from AVHRR Normalized Difference Vegetation Index (NDVI) data is described. The physically based algorithm is detailed in the first of the two part series. Here, the implementation, production and evaluation of the data set are described. The data set is evaluated both by direct comparisons to ground data and indirectly through inter-comparisons with similar data sets. This indirect validation showed satisfactory agreement with existing LAI products, importantly MODIS, at a range of spatial scales, and significant correlations with key climate variables in areas where temperature and precipitation limit plant growth. The data set successfully reproduced well-documented spatio-temporal trends and inter-annual variations in vegetation activity in the northern latitudes and semi-arid tropics. Comparison with plot scale field measurements over homogeneous vegetation patches indicated a 7% underestimation when all major vegetation types are taken into account. The error in mean values obtained from distributions of AVHRR LAI and high-resolution field LAI maps for different biomes is within 0.5 LAI for six out of the ten selected sites. These validation exercises though limited by the amount of field data, and thus less than comprehensive, indicated satisfactory agreement between the LAI product and field measurements. Overall, the inter-comparison with short-term LAI data sets, evaluation of long term trends with known variations in climate variables, and validation with field measurements together build confidence in the utility of this new 26 year LAI record for long term vegetation monitoring and modeling studies. 相似文献
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This paper presents a system for monitoring and prognostics of machine conditions using soft computing (SC) techniques. The machine condition is assessed through a suitable ‘monitoring index’ extracted from the vibration signals. The progression of the monitoring index is predicted using an SC technique, namely adaptive neuro-fuzzy inference system (ANFIS). Comparison with a machine learning method, namely support vector regression (SVR), is also presented. The proposed prediction procedures have been evaluated through benchmark data sets. The prognostic effectiveness of the techniques has been illustrated through previously published data on several types of faults in machines. The performance of SVR was found to be better than ANFIS for the data sets used. The results are helpful in understanding the relationship of machine conditions, the corresponding indicating features, the level of damage/degradation and their progression. 相似文献
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Choudhury Alokeparna Samanta Sourav Pratihar Sanjoy Bandyopadhyay Oishila 《Applied Intelligence》2022,52(7):7339-7372
Applied Intelligence - Microscopic Image segmentation has a crucial role in detecting and diagnosing numerous critical diseases like Alzheimer’s disease, Kidney disease, Cancer, many... 相似文献
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