Fuzzy Approach to Rank Global Climate Models

Eleven coupled model intercomparison project 3 based global climate models are evaluated for the case study of Upper Malaprabha catchment, India for precipitation rate. Correlation coefficient, normalised root mean square deviation, and skill score are considered as performance indicators for evaluation in fuzzy environment and assumed to have equal impact on the global climate models. Fuzzy technique for order preference by similarity to an ideal solution is used to rank global climate models. Top three positions are occupied by MIROC3, GFDL2.1 and GISS with relative closeness of 0.7867, 0.7070, and 0.7068. IPSL-CM4, NCAR-PCMI occupied the tenth and eleventh positions with relative closeness of 0.4959 and 0.4562.

Biochemical and Behavioral Evaluation of Human MAPT Mutations in Transgenic Drosophila melanogaster

Mutations in the human microtubule-associated protein tau (hMAPT) gene including R406W and V337M result in autosomal dominant neurodegenerative disorder. These mutations lead to hyperphosphorylation and aggregation of Tau protein which is a known genetic factor underlying development of Alzheimer's disease (AD). In the present study, transgenic Drosophila models of AD expressing wild-type and mutant forms of hMAPT exhibit a progressive neurodegeneration which was manifested in the form of early death and impairment of cognitive ability. Moreover, they were also found to have significantly decreased activity of neurotransmitter enzymes accompanied by decreased cellular endogenous antioxidant profile. The extent of neurodegeneration, memory impairment, and biochemical profiles was different in the tau transgenic strains which indicate multiple molecular and cellular responses underlie each particular form of hMAPT.

Evaluation of the Interfacial Adhesion between Brittle Coating and Ductile Substrate by Cross-Secitional Indention

The cross-sectional indentation method is extended to evaluate the interfacial adhesion between brittle coating and ductile substrate. The experimental results on electroplated chromium coating/steel substrate show that the interfacial separation occurs due to the edge chipping of brittle coating. The corresponding models are established to elucidate interfacial separation processes. This work further highlights the advantages and potential of this novel indentation method.

Evaluation of the Interfacial Adhesion between Brittle Coating and Ductile Substrate by Cross-Secitional Indention

The cross-sectional indentation method is extended to evaluate the interfacial adhesion between brittle coating and ductile substrate. The experimental results on electroplated chromium coating/steel substrate show that the interfacial separation occurs due to the edge chipping of brittle coating. The corresponding models are established to elucidate interfacial separation processes. This work further highlights the advantages and potential of this novel indentation method

Use of generalised additive models to categorise continuous variables in clinical prediction

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Analytical efficiency evaluation of a network mobility management protocol for Intelligent Transportation Systems

One of the major concerns in an Intelligent Transportation System (ITS) scenario, such as that which may be found on a long-distance train service, is the provision of efficient communication services, satisfying users' expectations, and fulfilling even highly demanding application requirements, such as safety-oriented services. In an ITS scenario, it is common to have a significant amount of onboard devices that comprise a cluster of nodes (a mobile network) that demand connectivity to the outside networks. This demand has to be satisfied without service disruption. Consequently, the mobility of the mobile network has to be managed. Due to the nature of mobile networks, efficient and lightweight protocols are desired in the ITS context to ensure adequate service performance. However, the security is also a key factor in this scenario. Since the management of the mobility is essential for providing communications, the protocol for managing this mobility has to be protected. Furthermore, there are safety-oriented services in this scenario, so user application data should also be protected. Nevertheless, providing security is expensive in terms of efficiency. Based on this considerations, we have developed a solution for managing the network mobility for ITS scenarios: the NeMHIP protocol. This approach provides a secure management of network mobility in an efficient manner. In this article, we present this protocol and the strategy developed to maintain its security and efficiency in satisfactory levels. We also present the developed analytical models to analyze quantitatively the efficiency of the protocol. More specifically, we have developed models for assessing it in terms of signaling cost, which demonstrates that NeMHIP generates up to 73.47% less signaling compared to other relevant approaches. Therefore, the results obtained demonstrate that NeMHIP is the most efficient and secure solution for providing communications in mobile network scenarios such as in an ITS context.

Advancements in jet turbulence and noise modeling: accurate one-way solutions and empirical evaluation of the nonlinear forcing of wavepackets

Jet noise reduction is an important goal within both commercial and military aviation. Although large-scale numerical simulations are now able to simultaneously compute turbulent jets and their radiated sound, lost-cost, physically-motivated models are needed to guide noise-reduction efforts. A particularly promising modeling approach centers around certain large-scale coherent structures, called wavepackets, that are observed in jets and their radiated sound. The typical approach to modeling wavepackets is to approximate them as linear modal solutions of the Euler or Navier-Stokes equations linearized about the long-time mean of the turbulent flow field. The near-field wavepackets obtained from these models show compelling agreement with those educed from experimental and simulation data for both subsonic and supersonic jets, but the acoustic radiation is severely under-predicted in the subsonic case. This thesis contributes to two aspects of these models. First, two new solution methods are developed that can be used to efficiently compute wavepackets and their acoustic radiation, reducing the computational cost of the model by more than an order of magnitude. The new techniques are spatial integration methods and constitute a well-posed, convergent alternative to the frequently used parabolized stability equations. Using concepts related to well-posed boundary conditions, the methods are formulated for general hyperbolic equations and thus have potential applications in many fields of physics and engineering. Second, the nonlinear and stochastic forcing of wavepackets is investigated with the goal of identifying and characterizing the missing dynamics responsible for the under-prediction of acoustic radiation by linear wavepacket models for subsonic jets. Specifically, we use ensembles of large-eddy-simulation flow and force data along with two data decomposition techniques to educe the actual nonlinear forcing experienced by wavepackets in a Mach 0.9 turbulent jet. Modes with high energy are extracted using proper orthogonal decomposition, while high gain modes are identified using a novel technique called empirical resolvent-mode decomposition. In contrast to the flow and acoustic fields, the forcing field is characterized by a lack of energetic coherent structures. Furthermore, the structures that do exist are largely uncorrelated with the acoustic field. Instead, the forces that most efficiently excite an acoustic response appear to take the form of random turbulent fluctuations, implying that direct feedback from nonlinear interactions amongst wavepackets is not an essential noise source mechanism. This suggests that the essential ingredients of sound generation in high Reynolds number jets are contained within the linearized Navier-Stokes operator rather than in the nonlinear forcing terms, a conclusion that has important implications for jet noise modeling.

The application of methods of ecosystem analysis to the evaluation of water quality

Guided by experience and the theoretical development of hydrobiology, it can be considered that the main aim of water quality control should be the establishment of the rates of the self-purification process of water bodies which are capable of maintaining communities in a state of dynamic balance without changing the integrity of the ecosystem. Hence, general approaches in the elaboration of methods for hydrobiological control are based on the following principles: a. the balance of matter and energy in water bodies; b. the integrity of the ecosystem structure and of its separate components at all levels. Ecosystem analysis makes possible a revelation of the whole totality of factors which determine the anthropogenic evolution of a water body. This is necessary for the study of long-term changes in water bodies. The principles of ecosystem analysis of water bodies, together with the creation of their mathematical models, are important because, in future, with the transition of water demanding production into closed cycles of water supply, changes in water bodies will arise in the main through the influence of 'diffuse' pollution (from the atmosphere, with utilisation in transport etc.).

Design, construction and evaluation of systems to predict risk in obstetrics.

We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy.

An evaluation of back-calculation methodology using simulated otolith data

I simulated somatic growth and accompanying otolith growth using an individual-based bioenergetics model in order to examine the performance of several back-calculation methods. Four shapes of otolith radius-total length relations (OR-TL) were simulated. Ten different back-calculation equations, two different regression models of radius length, and two schemes of annulus selection were examined for a total of 20 different methods to estimate size at age from simulated data sets of length and annulus measurements. The accuracy of each of the twenty methods was evaluated by comparing the back-calculated length-at-age and the true length-at-age. The best back-calculation technique was directly related to how well the OR-TL model fitted. When the OR-TL was sigmoid shaped and all annuli were used, employing a least squares linear regression coupled with a log-transformed Lee back-calculation equation (y-intercept corrected) resulted in the least error; when only the last annulus was used, employing a direct proportionality back-calculation equation resulted in the least error. When the OR-TL was linear, employing a functional regression coupled with the Lee back-calculation equation resulted in the least error when all annuli were used, and also when only the last annulus was used. If the OR-TL was exponentially shaped, direct substitution into the fitted quadratic equation resulted in the least error when all annuli were used, and when only the last annulus was used. Finally, an asymptotically shaped OR-TL was best modeled by the individually corrected Weibull cumulative distribution function when all annuli were used, and when only the last annulus was used.

Refractive index evaluation of multi-walled carbon nanotube arrays

Transmission terahertz time-domain spectroscopy (THz-TDS) measurements of carbon nanotube arrays are presented. A relatively thin film with vertically aligned multi-walled carbon nanotubes has been prepared and measured using THz-TDS. Experimental results were obtained from 80GHz to 2.5THz, and the sample has been characterized by extracting the relative permittivity of the carbon nanotubes. A combination of the Maxwell-Garnett and Drude models within the frequency range provide a good fit to the measured permittivity.

Ecological models and GIS maps of macroalgae, as bioindicator for ecological status of Hormozgan rocky shores

In this study a total of 75 species were identified, from which 17 species, 9 genes and 6 families; belonged to Green Algae, 18 species, 7 genes and 4 families; belonged to Brown Algae, and 40 species, 18 genes and 11 families; belonged to Red Algae. From total times spent for sampling, it was determined that at lengeh harbor with 6 species, had the lowest diversity of green algae. The species diversity of brown algae at Michael location with 10 species each; had the highest, and Tahooneh location with 5 species; had the lowest species diversity. Species diversity of red algae at Michael location with 28 species; had the highest, and Sayeh Khosh location with 13 species; had the lowest diversity. From all locations where sampling took place, the highest species diversity regarding Time and Space for all three groups of algae; were associated to Late February (20th. Feb. ), and late March(20th. March). Coverage data of macroalgae and Ecological Evaluation Index indicate a high level of eutrophication for the Saieh khosh, and Bostaneh, They are classified as zones with a bad and poor ecological status. It has been proved that concentrations of biogenic elements and phytoplankton blooming are higher in these zones. The best values of the estimated metrics at Tahooneh and Michaeil could be explained with the good ecological conditions in that zone and the absence of pollution sources close to that transect . The values of abundance of macroalgae and Ecological Evaluation Index indicate a moderate ecological conditions for the Koohin, Lengeh and Chirooieh.

An investigation of customer delight during product evaluation: Implications for the development of desirable products

This paper reports findings from three research methods used to study customer delight during product evaluation. The results are framed in terms of existing models, high-lighting inadequacies in the assumptions these models make. Implications for product development are proposed in the form of practical strategies for understanding and delighting customers. © IMechE 2007.

Phrase-based statistical language generation using graphical models and active learning

Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of generated utterances, or (b) using statistics to inform the generation decision process. Both approaches rely on the existence of a handcrafted generator, which limits their scalability to new domains. This paper presents BAGEL, a statistical language generator which uses dynamic Bayesian networks to learn from semantically-aligned data produced by 42 untrained annotators. A human evaluation shows that BAGEL can generate natural and informative utterances from unseen inputs in the information presentation domain. Additionally, generation performance on sparse datasets is improved significantly by using certainty-based active learning, yielding ratings close to the human gold standard with a fraction of the data. © 2010 Association for Computational Linguistics.

A global model for effective use and evaluation of e-learning in health.

Healthcare systems worldwide face a wide range of challenges, including demographic change, rising drug and medical technology costs, and persistent and widening health inequalities both within and between countries. Simultaneously, issues such as professional silos, static medical curricula, and perceptions of "information overload" have made it difficult for medical training and continued professional development (CPD) to adapt to the changing needs of healthcare professionals in increasingly patient-centered, collaborative, and/or remote delivery contexts. In response to these challenges, increasing numbers of medical education and CPD programs have adopted e-learning approaches, which have been shown to provide flexible, low-cost, user-centered, and easily updated learning. The effectiveness of e-learning varies from context to context, however, and has also been shown to make considerable demands on users' motivation and "digital literacy" and on providing institutions. Consequently, there is a need to evaluate the effectiveness of e-learning in healthcare as part of ongoing quality improvement efforts. This article outlines the key issues for developing successful models for analyzing e-health learning.