958 resultados para Radial basis function network


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The energy demand for operating Information and Communication Technology (ICT) systems has been growing, implying in high operational costs and consequent increase of carbon emissions. Both in datacenters and telecom infrastructures, the networks represent a significant amount of energy spending. Given that, there is an increased demand for energy eficiency solutions, and several capabilities to save energy have been proposed. However, it is very dificult to orchestrate such energy eficiency capabilities, i.e., coordinate or combine them in the same network, ensuring a conflict-free operation and choosing the best one for a given scenario, ensuring that a capability not suited to the current bandwidth utilization will not be applied and lead to congestion or packet loss. Also, there is no way in the literature to do this taking business directives into account. In this regard, a method able to orchestrate diferent energy eficiency capabilities is proposed considering the possible combinations and conflicts among them, as well as the best option for a given bandwidth utilization and network characteristics. In the proposed method, the business policies specified in a high-level interface are refined down to the network level in order to bring highlevel directives into the operation, and a Utility Function is used to combine energy eficiency and performance requirements. A Decision Tree able to determine what to do in each scenario is deployed in a Software Defined Network environment. The proposed method was validated with diferent experiments, testing the Utility Function, checking the extra savings when combining several capabilities, the decision tree interpolation and dynamicity aspects. The orchestration proved to be valid to solve the problem of finding the best combination for a given scenario, achieving additional savings due to the combination, besides ensuring a conflict-free operation.

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Author: Kerry W. Holton Title: SCHLEIERMACHER’S DOCTRINE OF BIBLICAL AUTHORITY: AN ALTERNATIVE TO CONTENT-BASED/SUPERNATURALIST AND FUNCTION- BASED/RATIONALIST MODELS Advisor: Theodore M. Vial, Jr. Degree Date: August 2015 This dissertation examines Friedrich Schleiermacher’s understanding of biblical authority and argues that, as an alternative to strictly supernaturalistic and rationalistic models, his understanding allows the New Testament to speak authoritatively in Christian religion in an age of critical, historical awareness. After classifying Schleiermacher’s position in a typology of the doctrine of biblical authority, this dissertation explores his conception of divine revelation and inspiration vis-à-vis scripture. It demonstrates that although he did not believe there is warrant for the claim of a direct connection between divine revelation and scripture, or that scripture is the foundation of faith, he nonetheless asserted that the New Testament is authoritative. He asserted the normative authority of the New Testament on the basis that it is the first presentation of Christian faith. This dissertation examines Schleiermacher’s “canon within the canon,” as well as his denial that the Old Testament shares the same normative worth and inspiration of the New. Although this dissertation finds difficulty with some of Schleiermacher’s views regarding the Old Testament, it names two significant strengths of what is identified as his evangelical, content-based, and rationalist approach to biblical authority. First, it recognizes and values the co-presence and co-activity of the supernatural and the natural !ii in the production of the New Testament canon. This allows both scripture and the church to share religious authority. Second, it allows Christian faith and the historical-method to coexist, as it does not require people to contradict what they know to be the case about science, history, and philosophy. Thus, this dissertation asserts that Schleiermacher’s understanding of biblical authority is a robust one, since, for him, the authority of scripture does not lie in some property of the texts themselves that historians or unbelievers can take away.

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Comunicación presentada en el 2nd International Workshop on Pattern Recognition in Information Systems, Alicante, April, 2002.

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Sustainable Development (SD) is one of the most widely used terms during the last years. It is a multidisciplinary concept, which applies mostly to life sciences but is not limited to them. Even though the short survey conducted by the authors revealed that there are only a few cases of Higher Educational Institutes (HEIs) around Europe that provide programs dedicated to SD, it is obvious that there is a constant raise in the need for implementing courses related to SD in existing programs. This paper discusses the case study of I.S.L.E., an Erasmus Academic Network, which aims to use the existing knowledge and tools in the context of teaching sustainable development topics in Universities and HEIs around Europe as a basis, and elaborate further by introducing an innovative approach towards the improvement of teaching SD in HEIs, based on the current needs as they are identified by the actions of the Network.

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his paper discusses a process to graphically view and analyze information obtained from a network of urban streets, using an algorithm that establishes a ranking of importance of the nodes of the network itself. The basis of this process is to quantify the network information obtained by assigning numerical values to each node, representing numerically the information. These values are used to construct a data matrix that allows us to apply a classification algorithm of nodes in a network in order of importance. From this numerical ranking of the nodes, the process finish with the graphical visualization of the network. An example is shown to illustrate the whole process.

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In this paper the model of an Innovative Monitoring Network involving properly connected nodes to develop an Information and Communication Technology (ICT) solution for preventive maintenance of historical centres from early warnings is proposed. It is well known that the protection of historical centres generally goes from a large-scale monitoring to a local one and it could be supported by a unique ICT solution. More in detail, the models of a virtually organized monitoring system could enable the implementation of automated analyses by presenting various alert levels. An adequate ICT solution tool would allow to define a monitoring network for a shared processing of data and results. Thus, a possible retrofit solution could be planned for pilot cases shared among the nodes of the network on the basis of a suitable procedure utilizing a retrofit catalogue. The final objective would consist in providing a model of an innovative tool to identify hazards, damages and possible retrofit solutions for historical centres, assuring an easy early warning support for stakeholders. The action could proactively target the needs and requirements of users, such as decision makers responsible for damage mitigation and safeguarding of cultural heritage assets.

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Urban researchers and planners are often interested in understanding how economic activities are distributed in urban regions, what forces influence their special pattern and how urban structure and functions are mutually dependent. In this paper, we want to show how an algorithm for ranking the nodes in a network can be used to understand and visualize certain commercial activities of a city. The first part of the method consists of collecting real information about different types of commercial activities at each location in the urban network of the city of Murcia, Spain. Four clearly differentiated commercial activities are studied, such as restaurants and bars, shops, banks and supermarkets or department stores, but obviously we can study other. The information collected is then quantified by means of a data matrix, which is used as the basis for the implementation of a PageRank algorithm which produces a ranking of all the nodes in the network, according to their significance within it. Finally, we visualize the resulting classification using a colour scale that helps us to represent the business network.

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We have studied the radial dependence of the energy deposition of the secondary electron generated by swift proton beams incident with energies T = 50 keV–5 MeV on poly(methylmethacrylate) (PMMA). Two different approaches have been used to model the electronic excitation spectrum of PMMA through its energy loss function (ELF), namely the extended-Drude ELF and the Mermin ELF. The singly differential cross section and the total cross section for ionization, as well as the average energy of the generated secondary electrons, show sizeable differences at T ⩽ 0.1 MeV when evaluated with these two ELF models. In order to know the radial distribution around the proton track of the energy deposited by the cascade of secondary electrons, a simulation has been performed that follows the motion of the electrons through the target taking into account both the inelastic interactions (via electronic ionizations and excitations as well as electron-phonon and electron trapping by polaron creation) and the elastic interactions. The radial distribution of the energy deposited by the secondary electrons around the proton track shows notable differences between the simulations performed with the extended-Drude ELF or the Mermin ELF, being the former more spread out (and, therefore, less peaked) than the latter. The highest intensity and sharpness of the deposited energy distributions takes place for proton beams incident with T ~ 0.1–1 MeV. We have also studied the influence in the radial distribution of deposited energy of using a full energy distribution of secondary electrons generated by proton impact or using a single value (namely, the average value of the distribution); our results show that differences between both simulations become important for proton energies larger than ~0.1 MeV. The results presented in this work have potential applications in materials science, as well as hadron therapy (due to the use of PMMA as a tissue phantom) in order to properly consider the generation of electrons by proton beams and their subsequent transport and energy deposition through the target in nanometric scales.

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Multinational companies' (MNCs) corporate social responsibility (CSR) programs frequently comprise a portfolio of disconnected country-level programs or, alternatively, consist of blanket corporate policies that apply in the same way across the geographies where the company operates. Yet, the international nonmarket environment in which CSR programs operate is neither a completely fragmented nor a perfectly homogeneous one. Building on the concept of stakeholder-issue-networks, we develop a model that explicitly takes into consideration the role of geography in the characterization of a firm's nonmarket environment. This allows us to develop a taxonomy of nonmarket environments on the basis of their geographic spread and their degree of cross-border connectedness. We then explore the strategic and organizational implications that different ideal types of (cross-border) nonmarket environments have for the development of international CSR policies.

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Hox genes encode transcription factors that regulate morphogenesis in all animals with bilateral symmetry. Although Hox genes have been extensively studied, their molecular function is not clear in vertebrates, and only a limited number of genes regulated by Hox transcription factors have been identified. Hoxa2 is required for correct development of the second branchial arch, its major domain of expression. We now show that Meox1 is genetically downstream from Hoxa2 and is a direct target. Meox1 expression is downregulated in the second arch of Hoxa2 mouse mutant embryos. In chromatin immunoprecipitation (ChIP), Hoxa2 binds to the Meox1 proximal promoter. Two highly conserved binding sites contained in this sequence are required for Hoxa2-dependent activation of the Meox1 promoter. Remarkably, in the absence of Meox1 and its close homolog Meox2, the second branchial arch develops abnormally and two of the three skeletal elements patterned by Hoxa2 are malformed. Finally, we show that Meox1 can specifically bind the DNA sequences recognized by Hoxa2 on its functional target genes. These results provide new insight into the Hoxa2 regulatory network that controls branchial arch identity.

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Eleven commercial nuclear reactors used to generate electricity are currently operating at six sites in Illinois; no other state has as many nuclear reactors. In addition, there are two major research facilities in Illinois operated by the US Department of Energy (Argonne National Laboratory and FermiLab), uranium processing facilities at Metropolis and in nearby Paducah, Kentucky, several manufacturers of radiopharmaceuticals and other radioactive materials, thousands of radiation-producing machines used in medicine and industry, and a network of major arterial highways and rail lines over which radioactive material shipments move on a regular basis. Protecting the health and safety of Illinois citizens and the environment from the potentially harmful effects of ionizing radiation is a key function of IEMA'S Division of Nuclear Safety (DNS). That role is fulfilled through programs that monitor nuclear facilities around the clock, ensure the proper operation of radiation-producing equipment and the use of radioactive materials, and measure radioactivity in the environment to ensure no threats to public health exist.

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Background. Australian Aborigines living in remote areas have exceedingly high rates of renal failure together with increased cardiovascular morbidity and mortality. To examine the basis of this association, we studied markers of renal function and cardiovascular (CV) risk in a coastal Aboriginal community in a remote area of the Northern Territory of Australia. End-stage renal disease (ESRD) incidence rates in that community are 15 times the national non-Aboriginal rate and CV mortality rates in the region are increased 5-fold. Methods. A cross-sectional community survey was conducted. Markers of early renal disease examined included urine albumin/creatinine ratio (ACR), serum creatinine concentration and calculated glomerular filtration rate (GFR). CV risk markers included blood pressure as well as measures of glycaemia, diabetes and serum lipids. Results. The study group included 237 people, 58% of the adult population of the community. The crude prevalence of microalbuminuria (urine ACR: 3.4-33.9 g/mol, 30-299 mg/g) was 31% and of overt albuminuria (urine ACR: greater than or equal to34 g/mol, greater than or equal to300 mg/g), 13%. The prevalence of overt albuminuria increased with age, but the prevalence of microalbuminuria was greatest in the 45-54 year age group. Microalbuminuria was associated with increasing body mass index, whereas overt albuminuria was associated with increasing glycated haemoglobin (HbA1c) and systolic blood pressure and a history of diabetes. The prevalence of elevated serum creatinine concentration (greater than or equal to120 mumol/l) was 10%. GFR (calculated using the MDRD equation) was <60 ml/min/1.73m(2) in 12% and 60-79 ml/min/1.73 m(2) in a further 36% of the study population. Although many people with albuminuria had well preserved GFRs, mean GFR was lower in people with higher levels of albuminuria. Conclusions. The high prevalence of markers of renal disease in this community was consistent with their high rates of ESRD. The distribution of microalbuminuria suggested a 'cohort effect', representing a group who will progress to overt albuminuria. The powerful association of renal disease markers with CV risk factors confirms a strong link between renal and CV disease in the early, asymptomatic stages of each. Thus, pathologic albuminuria, in part, might be a manifestation of the metabolic/haemodynamic syndrome and both conditions might arise out of a common menu of risk factors. Hence, a single agenda of primary and secondary intervention may benefit both.

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A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further. Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage). Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag. Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.