967 resultados para man-machine interface


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The concept of domain integral used extensively for J integral has been applied in this work for the formulation of J(2) integral for linear elastic bimaterial body containing a crack at the interface and subjected to thermal loading. It is shown that, in the presence of thermal stresses, the J(k) domain integral over a closed path, which does not enclose singularities, is a function of temperature and body force. A method is proposed to compute the stress intensity factors for bimaterial interface crack subjected to thermal loading by combining this domain integral with the J(k) integral. The proposed method is validated by solving standard problems with known solutions.

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The well known features of crack face interpenetration/contact at the tip of an interface crack is re-examined using finite element analysis and assuming material nonlinear properties for the adherends. It was assumed in literature that the crack tips are fully open at all load levels in the presence of material nonlinearity of the adherends. Analysis for the case of remote tension shows that even in the presence of material nonlinearity, crack tip closes at small load levels and opens above a certain load level. Mixed-mode fracture parameters are evaluated for the situation when the crack tips are fully open. Due to the presence of nonlinearity, the mixed-mode fracture parameters are measured with the symmetric and anti-symmetric components of J-integral. The present analysis explains the sequence of events at the interface crack tip with progressively increasing remote tension load for the case of adherends with material nonlinear behaviour.

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Virtual Machine (VM) management is an obvious need in today's data centers for various management activities and is accomplished in two phases— finding an optimal VM placement plan and implementing that placement through live VM migrations. These phases result in two research problems— VM placement problem (VMPP) and VM migration scheduling problem (VMMSP). This research proposes and develops several evolutionary algorithms and heuristic algorithms to address the VMPP and VMMSP. Experimental results show the effectiveness and scalability of the proposed algorithms. Finally, a VM management framework has been proposed and developed to automate the VM management activity in cost-efficient way.

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Inventory management (IM) has a decisive role in the enhancement of manufacturing industry's competitiveness. Therefore, major manufacturing industries are following IM practices with the intention of improving their performance. However, the effort to introduce IM in SMEs is very limited due to lack of initiation, expertise, and financial constraints. This paper aims to provide a guideline for entrepreneurs in enhancing their IM performance, as it presents the results of a survey based study carried out for machine tool Small and Medium Enterprises (SMEs) in Bangalore. Having established the significance of inventory as an input, we probed the relationship between IM performance and economic performance of these SMEs. To the extent possible all the factors of production and performance indicators were deliberately considered in pure economic terms. All economic performance indicators adopted seem to have a positive and significant association with IM performance in SMEs. On the whole, we found that SMEs which are IM efficient are likely to perform better on the economic front also and experience higher returns to scale.

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Within the history of twentieth-century design, there are a number of well-known objects and stories that are invoked time and time again to capture a pivotal moment or summarize a much broader historical transition. For example, Marcel Breuer’s Model B3 chair is frequently used as a stand-in for the radical investigations of form and new industrial materials occurring at the Bauhaus in the mid-1920s. Similarly, Raymond Loewy’s streamlined pencil sharpener has become historical shorthand for the emergence of modern industrial design in the 1930s. And any discussion of the development of American postwar “organic design” seems incomplete without reference to Charles and Ray Eames’s molded plywood leg splint of 1942. Such objects and narratives are dear to historians of modern design. They are tangible, photogenic subjects that slot nicely into exhibitions, historical surveys, and coffee-table best sellers...

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The determination of the overconsolidation ratio (OCR) of clay deposits is an important task in geotechnical engineering practice. This paper examines the potential of a support vector machine (SVM) for predicting the OCR of clays from piezocone penetration test data. SVM is a statistical learning theory based on a structural risk minimization principle that minimizes both error and weight terms. The five input variables used for the SVM model for prediction of OCR are the corrected cone resistance (qt), vertical total stress (sigmav), hydrostatic pore pressure (u0), pore pressure at the cone tip (u1), and the pore pressure just above the cone base (u2). Sensitivity analysis has been performed to investigate the relative importance of each of the input parameters. From the sensitivity analysis, it is clear that qt=primary in situ data influenced by OCR followed by sigmav, u0, u2, and u1. Comparison between SVM and some of the traditional interpretation methods is also presented. The results of this study have shown that the SVM approach has the potential to be a practical tool for determination of OCR.

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In this paper we first present the 'wet N2O' furnace oxidation process to grow nitrided tunnel oxides in the thickness range 6 to 8 nm on silicon at a temperature of 800 degrees C. Electrical characteristics of MOS capacitors and MOSFETs fabricated using this oxide as gate oxide have been evaluated and the superior features of this oxide are ascertained The frequency response of the interface states, before and after subjecting the MOSFET gate oxide to constant current stress, is studied using a simple analytical model developed in this work.

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We investigate the events near the fusion interfaces of dissimilar welds using a phase-field model developed for single-phase solidification of binary alloys. The parameters used here correspond to the dissimilar welding of a Ni/Cu couple. The events at the Ni and the Cu interface are very different, which illustrate the importance of the phase diagram through the slope of the liquidus curves. In the Ni side, where the liquidus temperature decreases with increasing alloying, solutal melting of the base metal takes place; the resolidification, with continuously increasing solid composition, is very sluggish until the interface encounters a homogeneous melt composition. The growth difficulty of the base metal increases with increasing initial melt composition, which is equivalent to a steeper slope of the liquidus curve. In the Cu side, the initial conditions result in a deeply undercooled melt and contributions from both constrained and unconstrained modes of growth are observed. The simulations bring out the possibility of nucleation of a concentrated solid phase from the melt, and a secondary melting of the substrate due to the associated recalescence event. The results for the Ni and Cu interfaces can be used to understand more complex dissimilar weld interfaces involving multiphase solidification.

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The determination of settlement of shallow foundations on cohesionless soil is an important task in geotechnical engineering. Available methods for the determination of settlement are not reliable. In this study, the support vector machine (SVM), a novel type of learning algorithm based on statistical theory, has been used to predict the settlement of shallow foundations on cohesionless soil. SVM uses a regression technique by introducing an ε – insensitive loss function. A thorough sensitive analysis has been made to ascertain which parameters are having maximum influence on settlement. The study shows that SVM has the potential to be a useful and practical tool for prediction of settlement of shallow foundation on cohesionless soil.

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Domestic violence is currently undergoing a period of heightened visibility in Australia. This article uses social media to analyze public discussions about this violence with respect to a specific theoretical frame, which Adrian Howe has called the “Man” question: where and how are men visible or invisible in narratives about their violence against women? The article presents a qualitative study of the Twitter conversation surrounding a special episode of the Australian Broadcasting Corporation's television program Q&A, themed around family violence, which aired in February 2015. We found that the place of men in this conversation was contested. Some tweets privileged men's voices and concerns, as did the organization and production of the program. However, feminist voices were also highly visible via presenting facts, legitimating survivor voices, and recuperating anti-feminist memes to challenge hegemonic patriarchal discourses on men's violence against women. La violence conjugale connait actuellement une visibilité accrue en Australie. Les auteures du présent article utilisent les réseaux sociaux pour analyser les débats publics sur cette violence selon un cadre théorique précis, qu'Adrian Howe a appelé la question de « l'homme » : où et comment les hommes sont-ils visibles ou invisibles dans les récits de leur violence envers les femmes? L'article présente une étude qualitative d'une conversation sur Twitter au sujet d'un épisode axé sur la famille diffusé en février 2015 dans le cadre de l'émission Q & A, à la télévision nationale d'Australie. Nous avons remarqué que dans cette conversation la place des hommes était remise en question. Certains tweets privilégiaient les voix et les craintes des hommes, comme l'ont fait les organisateurs et les producteurs de l'émission. Cependant, il y avait une forte présence de voix féministes dans la présentation des faits, légitimant le point de vue des survivantes et relevant des éléments culturels antiféministes afin de défier les discours hégémoniques et patriarcaux sur la violence des hommes envers les femmes.

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Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.

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New metal-organic frameworks (MOFs) [Ni(C12N2H10)(H2O)][C6H3(COO)2(COOH)] (I), [Co2(H2O)6][C6H3(COO)3]2·(C4N2H12)(H2O)2 (II), [Ni2(H2O)6][C6H3(COO)3]2·(C4N2H12)(H2O)2 (III), [Ni(C13N2H14)(H2O)][C6H3(COO)2(COOH)] (IV), [Ni3(H2O)8][C6H3(COO)3] (V) and [Co(C4N2H4)(H2O)][C6H3(COO)3] (VI) {C6H3(COOH)3 = trimesic acid, C12N2H10 = 1,10-phenanthroline, C4N2H12 = piperazine dication, C13N2H14 = 1,3-bis(4-pyridyl)propane and C4N2H4 = pyrazine} have been synthesized by using an interface between two immiscible solvents, water and cyclohexanol. The compounds are constructed from the connectivity between the octahedral M2+ (M = Ni, Co) ions coordinated by oxygen atoms of carboxylate groups and water molecules and/or by nitrogen atoms of the ligand amines and the carboxylate units to form a variety of structures of different dimensionality. Strong hydrogen bonds of the type O-H···O are present in all the compounds, which give rise to supramolecularly organized higher-dimensional structures. In some cases ··· interactions are also observed. Magnetic studies indicate weak ferromagnetic interactions in I, IV and V and weak antiferromagnetic interactions in the other compounds (II, III and VI). All the compounds have been characterized by a variety of techniques.

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We report the results of an in situ small-angle x-ray scattering (SAXS) study of the aggregation of gold nanoparticles formed by an interfacial reaction at the toluene-water interface. The SAXS data provide a direct evidence for aggregate formation of nanoparticles having 1.3 nm gold core and an organic shell that gives a core-core separation of about 2.5 nm. Furthermore, the nanoparticles do not occupy all the cites of 13-member cluster. This occupancy decreases with reaction time and indicate reorganization of the clusters that generates planner disklike structures. A gradual increase in fractal dimension from 1.82 to 2.05 also indicate compactification of cluster aggregation with reaction time, the final exponent being close to 2 expected for disklike aggregates.

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This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.