227 resultados para Degree of automation


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Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

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Acyl carrier protein (ACIP) plays a central role in many metabolic processes inside the cell, and almost 4% of the total enzymes inside the cell require it as a cofactor. Here, we report self-acylation properties in ACPs from Plasmodium falciparum and Brassica napus that are essential components of type II fatty acid biosynthesis (FAS II), disproving the existing notion that this phenomenon is restricted only to ACPs involved in polyketide biosynthesis. We also provide strong evidence to suggest that catalytic self-acylation is intrinsic to the individual ACP. Mutational analysis of these ACPs revealed the key residue(s) involved in this phenomenon. We also demonstrate that these FAS 11 ACPs exhibit a high degree of selectivity for self-acylation employing only dicarboxylic acids as substrates. A plausible mechanism for the self-acylation reaction is also proposed.

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Formation of high value procurement networks involves a bottom-up assembly of complex production, assembly, and exchange relationships through supplier selection and contracting decisions, where suppliers are intelligent and rational agents who act strategically. In this paper we address the problem of forming procurement networks for items with value adding stages that are linearly arranged We model the problem of Procurement Network Formation (PNF) for multiple units of a single item as a cooperative game where agents cooperate to form a surplus maximizing procurement network and then share the surplus in a stable and fair manner We first investigate the stability of such networks by examining the conditions under which the core of the game is non-empty. We then present a protocol, based on the extensive form game realization of the core, for forming such networks so that the resulting network is stable. We also mention a key result when the Shapley value is applied as a solution concept.

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The enzyme UDP-galactose-4-epimerase (GAL10) catalyzes a key step in galactose metabolism converting UDP-galactose to UDPglucose which then can get metabolized through glycolysis and TCA cycle thus allowing the cell to use galactose as a carbon and energy source. As in many fungi, a functional homolog of GAL10 exists in Candida albicans. The domainal organization of the homologs from Saccharomyces cerevisiae and C albicans show high degree of homology having both mutarotase and an epimerase domain. The former is responsible for the conversion of beta-D-galactose to alpha-D-galactose and the hitter for epimerization of UDP-galactose to UDP-glucose. Absence of C albicans GAL10 (CaGAL10) affects cell-wall organization, oxidative stress response, biofilm formation and filamentation. Cagal10 mutant cells tend to flocculate extensively as compared to the wild-type cells. The excessive filamentation in this mutant is reflected in its irregular and wrinkled colony morphology. Cagal10 strain is more susceptible to oxidative stress when tested in presence of H2O2. While the S. cerevsiae GAL10 (ScGAL10), essential for survival in the presence of galactose, has not been reported to have defects in the absence of galactose, the C albicans homolog shows these phenotypes during growth in the absence of galactose. Thus a functional CaGal10 is required not only for galactose metabolism but also for normal hyphal morphogenesis, colony morphology, maintenance of cell-wall integrity and for resistance to oxidative stress even in the absence of galactose. (c) 2006 Elsevier Inc. All rights reserved.

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Surface models of biomolecules have become crucially important for the study and understanding of interaction between biomolecules and their environment. We argue for the need for a detailed understanding of biomolecular surfaces by describing several applications in computational and structural biology. We review methods used to model, represent, characterize, and visualize biomolecular surfaces focusing on the role that geometry and topology play in identifying features on the surface. These methods enable the development of efficient computational and visualization tools for studying the function of biomolecules.

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PURPOSE. To understand the molecular features underlying autosomal dominant congenital cataracts caused by the deletion mutations W156X in human gamma D-crystallin and W157X in human gamma C-crystallin. METHODS. Normal and mutant cDNAs (with the enhanced green fluorescent protein [EGFP] tag in the front) were cloned into the pEGFP-C1 vector, transfected into various cell lines, and observed under a confocal microscope for EGFP fluorescence. Normal and W156X gamma D cDNAs were also cloned into the pET21a(+) vector, and the recombinant proteins were overexpressed in the BL-21(DE3) pLysS strain of Escherichia coli, purified, and isolated. The conformational features, structural stability, and solubility in aqueous solution of the mutant protein were compared with those of the wild type using spectroscopic methods. Comparative molecular modeling was performed to provide additional structural information. RESULTS. Transfection of the EGFP-tagged mutant cDNAs into several cell lines led to the visualization of aggregates, whereas that of wild-type cDNAs did not. Turning to the properties of the expressed proteins, the mutant molecules show remarkable reduction in solubility. They also seem to have a greater degree of surface hydrophobicity than the wild-type molecules, most likely accounting for self-aggregation. Molecular modeling studies support these features. CONCLUSIONS. The deletion of C-terminal 18 residues of human gamma C-and gamma D-crystallins exposes the side chains of several hydrophobic residues in the sequence to the solvent, causing the molecule to self-aggregate. This feature appears to be reflected in situ on the introduction of the mutants in human lens epithelial cells.

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The ignition behaviour of boron powder, prepared through electrowinning process, was studied by using thermogravimetry coupled with simultaneous differential thermal analysis (TG-SDTA). The dependence of the inception of the ignition reaction on the partial pressure of oxygen, particle size of the boron powder and heating rate was investigated. It was observed that all these factors affect the ignition temperature. Boron powder with a mean particle size of about 10 mu m was found to be susceptible to ignition in oxygen even at 783K. In general, the susceptibility to ignition was found to vary inversely with the degree of crystallinity. Presence of carbon was found to retard the oxidation of boron and raise the ignition temperature. These results are useful in safe handling and storage of finely divided boron powder and in the subsequent production of boron carbide from it. (C) 2009 Elsevier B.V. All rights reserved.

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The Ball-Larus path-profiling algorithm is an efficient technique to collect acyclic path frequencies of a program. However, longer paths -those extending across loop iterations - describe the runtime behaviour of programs better. We generalize the Ball-Larus profiling algorithm for profiling k-iteration paths - paths that can span up to to k iterations of a loop. We show that it is possible to number suchk-iteration paths perfectly, thus allowing for an efficient profiling algorithm for such longer paths. We also describe a scheme for mixed-mode profiling: profiling different parts of a procedure with different path lengths. Experimental results show that k-iteration profiling is realistic.

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The StreamIt programming model has been proposed to exploit parallelism in streaming applications on general purpose multi-core architectures. This model allows programmers to specify the structure of a program as a set of filters that act upon data, and a set of communication channels between them. The StreamIt graphs describe task, data and pipeline parallelism which can be exploited on modern Graphics Processing Units (GPUs), as they support abundant parallelism in hardware. In this paper, we describe the challenges in mapping StreamIt to GPUs and propose an efficient technique to software pipeline the execution of stream programs on GPUs. We formulate this problem - both scheduling and assignment of filters to processors - as an efficient Integer Linear Program (ILP), which is then solved using ILP solvers. We also describe a novel buffer layout technique for GPUs which facilitates exploiting the high memory bandwidth available in GPUs. The proposed scheduling utilizes both the scalar units in GPU, to exploit data parallelism, and multiprocessors, to exploit task and pipelin parallelism. Further it takes into consideration the synchronization and bandwidth limitations of GPUs, and yields speedups between 1.87X and 36.83X over a single threaded CPU.

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Apart from their intrinsic physical interest, spin-polarized many-body effects are expected to be important to the working of spintronic devices. A vast literature exists on the effects of a spin-unpolarized electron-hole plasma on the optical properties of a semiconductor. Here, we include the spin degree of freedom to model optical absorption of circularly polarized light by spin-polarized bulk GaAs. Our model is easy to implement and does not require elaborate numerics, since it is based on the closed-form analytical pair-equation formula that is valid in 3d. The efficacy of our approach is demonstrated by a comparison with recent experimental data.

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Modern database systems incorporate a query optimizer to identify the most efficient "query execution plan" for executing the declarative SQL queries submitted by users. A dynamic-programming-based approach is used to exhaustively enumerate the combinatorially large search space of plan alternatives and, using a cost model, to identify the optimal choice. While dynamic programming (DP) works very well for moderately complex queries with up to around a dozen base relations, it usually fails to scale beyond this stage due to its inherent exponential space and time complexity. Therefore, DP becomes practically infeasible for complex queries with a large number of base relations, such as those found in current decision-support and enterprise management applications. To address the above problem, a variety of approaches have been proposed in the literature. Some completely jettison the DP approach and resort to alternative techniques such as randomized algorithms, whereas others have retained DP by using heuristics to prune the search space to computationally manageable levels. In the latter class, a well-known strategy is "iterative dynamic programming" (IDP) wherein DP is employed bottom-up until it hits its feasibility limit, and then iteratively restarted with a significantly reduced subset of the execution plans currently under consideration. The experimental evaluation of IDP indicated that by appropriate choice of algorithmic parameters, it was possible to almost always obtain "good" (within a factor of twice of the optimal) plans, and in the few remaining cases, mostly "acceptable" (within an order of magnitude of the optimal) plans, and rarely, a "bad" plan. While IDP is certainly an innovative and powerful approach, we have found that there are a variety of common query frameworks wherein it can fail to consistently produce good plans, let alone the optimal choice. This is especially so when star or clique components are present, increasing the complexity of th- e join graphs. Worse, this shortcoming is exacerbated when the number of relations participating in the query is scaled upwards.

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Recommender systems aggregate individual user ratings into predictions of products or services that might interest visitors. The quality of this aggregation process crucially affects the user experience and hence the effectiveness of recommenders in e-commerce. We present a characterization of nearest-neighbor collaborative filtering that allows us to disaggregate global recommender performance measures into contributions made by each individual rating. In particular, we formulate three roles-scouts, promoters, and connectors-that capture how users receive recommendations, how items get recommended, and how ratings of these two types are themselves connected, respectively. These roles find direct uses in improving recommendations for users, in better targeting of items and, most importantly, in helping monitor the health of the system as a whole. For instance, they can be used to track the evolution of neighborhoods, to identify rating subspaces that do not contribute ( or contribute negatively) to system performance, to enumerate users who are in danger of leaving, and to assess the susceptibility of the system to attacks such as shilling. We argue that the three rating roles presented here provide broad primitives to manage a recommender system and its community.

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Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

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Apart from their intrinsic physical interest, spin-polarized many-body effects are expected to be important to the working of spintronic devices. A vast literature exists on the effects of a spin-unpolarized electron-hole plasma on the optical properties of a semiconductor. Here, we include the spin degree of freedom to model optical absorption of circularly polarized light by spin-polarized bulk GaAs. Our model is easy to implement and does not require elaborate numerics, since it is based on the closed-form analytical pair-equation formula that is valid in 3d. The efficacy of our approach is demonstrated by a comparison with recent experimental data.

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We have characterized the phase behavior of mixtures of the cationic surfactant cetyltrimethylammonium bromide (CTAB) and the organic salt 3-sodium-2-hydroxy naphthoate (SHN) over a wide range of surfactant concentrations using polarizing optical microscopy and X-ray diffraction. A variety of liquid crystalline phases, such as hexagonal, lamellar with and without curvature defects, and nematic, are observed in these mixtures. At high temperatures the curvature defects in the lamellar phase are annealed gradually on decreasing the water content. However, at lower temperatures these two lamellar structures are separated by an intermediate phase, where the bilayer defects appear to order into a lattice. The ternary phase diagram shows a high degree of symmetry about the line corresponding to equimolar CTAB/SHN composition, as in the case of mixtures of cationic and anionic surfactants.