891 resultados para density based averaging


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Smart Card Automated Fare Collection (AFC) data has been extensively exploited to understand passenger behavior, passenger segment, trip purpose and improve transit planning through spatial travel pattern analysis. The literature has been evolving from simple to more sophisticated methods such as from aggregated to individual travel pattern analysis, and from stop-to-stop to flexible stop aggregation. However, the issue of high computing complexity has limited these methods in practical applications. This paper proposes a new algorithm named Weighted Stop Density Based Scanning Algorithm with Noise (WS-DBSCAN) based on the classical Density Based Scanning Algorithm with Noise (DBSCAN) algorithm to detect and update the daily changes in travel pattern. WS-DBSCAN converts the classical quadratic computation complexity DBSCAN to a problem of sub-quadratic complexity. The numerical experiment using the real AFC data in South East Queensland, Australia shows that the algorithm costs only 0.45% in computation time compared to the classical DBSCAN, but provides the same clustering results.

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Evaluation of intermolecular interactions in terms of both experimental and theoretical charge density analyses has produced a unified picture with which to classify strong and weak hydrogen bonds, along with van der Waals interactions, into three regions.

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N-gram analysis is an approach that investigates the structure of a program using bytes, characters or text strings. This research uses dynamic analysis to investigate malware detection using a classification approach based on N-gram analysis. The motivation for this research is to find a subset of Ngram features that makes a robust indicator of malware. The experiments within this paper represent programs as N-gram density histograms, gained through dynamic analysis. A Support Vector Machine (SVM) is used as the program classifier to determine the ability of N-grams to correctly determine the presence of malicious software. The preliminary findings show that an N-gram size N=3 and N=4 present the best avenues for further analysis.

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The X-ray structure and electron density distribution of ethane-1,2-diol (ethylene glycol), obtained at a resolution extending to 1.00 Å−1 in sin θ/λ (data completion = 100% at 100 K) by in situ cryocrystallization technique is reported. The diol is in the gauche (g′Gt) conformation with the crystal structure stabilised by a network of inter-molecular hydrogen bonds. In addition to the well-recognized O–H···O hydrogen bonds there is topological evidence for C–H···O inter-molecular interactions. There is no experimental electron density based topological evidence for the occurrence of an intra-molecular hydrogen bond. The O···H spacing is not, vert, similar0.45 Å greater than in the gas-phase with an O–H···O angle close to 90°, calling into question the general assumption that the gauche conformation of ethane-1,2-diol is stabilised by the intra-molecular oxygen–hydrogen interaction.

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Structural and charge density distribution studies have been carried out on a single crystal data of an ammonium borate, [C(10)H(26)N(4)][B(5)O(6)(OH)(4)](2), synthesized by solvothermal method. Further, the experimentally observed geometry is used for the theoretical charge density calculations using the B3LYP/6-31G** level of theory, and the results are compared with the experimental values. Topological analysis of charge density based on the Atoms in Molecules approach for B-O bonds exhibit mixed covalent/ionic character. Detailed analysis of the hydrogen bonds in the crystal structure in the ammonium borate provides insights into the understanding of the reaction pathways that net atomic charges and electrostatic potential isosurfaces also give additional such systems. could result in the formation of borate minerals. The input to evaluate chemical and physical properties in such systems.

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This tutorial review article is intended to provide a general guidance to a reader interested to learn about the methodologies to obtain accurate electron density mapping in molecules and crystalline solids, from theory or from experiment, and to carry out a sensible interpretation of the results, for chemical, biochemical or materials science applications. The review mainly focuses on X-ray diffraction techniques and refinement of experimental models, in particular multipolar models. Neutron diffraction, which was widely used in the past to fix accurate positions of atoms, is now used for more specific purposes. The review illustrates three principal analyses of the experimental or theoretical electron density, based on quantum chemical, semi-empirical or empirical interpretation schemes, such as the quantum theory of atoms in molecules, the semi-classical evaluation of interaction energies and the Hirshfeld analysis. In particular, it is shown that a simple topological analysis based on a partition of the electron density cannot alone reveal the whole nature of chemical bonding. More information based on the pair density is necessary. A connection between quantum mechanics and observable quantities is given in order to provide the physical grounds to explain the observations and to justify the interpretations.

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It is suggested here that the ultimate accuracy of DFT methods arises from the type of hybridization scheme followed. This idea can be cast into a mathematical formulation utilizing an integrand connecting the noninteracting and the interacting particle system. We consider two previously developed models for it, dubbed as HYB0 and QIDH, and assess a large number of exchange-correlation functionals against the AE6, G2/148, and S22 reference data sets. An interesting consequence of these hybridization schemes is that the error bars, including the standard deviation, are found to markedly decrease with respect to the density-based (nonhybrid) case. This improvement is substantially better than variations due to the underlying density functional used. We thus finally hypothesize about the universal character of the HYB0 and QIDH models.

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This paper presents a multiscale study using the coupled Meshless technique/Molecular Dynamics (M2) for exploring the deformation mechanism of mono-crystalline metal (focus on copper) under uniaxial tension. In M2, an advanced transition algorithm using transition particles is employed to ensure the compatibility of both displacements and their gradients, and an effective local quasi-continuum approach is also applied to obtain the equivalent continuum strain energy density based on the atomistic poentials and Cauchy-Born rule. The key parameters used in M2 are firstly investigated using a benchmark problem. Then M2 is applied to the multiscale simulation for a mono-crystalline copper bar. It has found that the mono-crystalline copper has very good elongation property, and the ultimate strength and Young's modulus are much higher than those obtained in macro-scale.

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Smart Card data from Automated Fare Collection system has been considered as a promising source of information for transit planning. However, literature has been limited to mining travel patterns from transit users and suggesting the potential of using this information. This paper proposes a method for mining spatial regular origins-destinations and temporal habitual travelling time from transit users. These travel regularity are discussed as being useful for transit planning. After reconstructing the travel itineraries, three levels of Density-Based Spatial Clustering of Application with Noise (DBSCAN) have been utilised to retrieve travel regularity of each of each frequent transit users. Analyses of passenger classifications and personal travel time variability estimation are performed as the examples of using travel regularity in transit planning. The methodology introduced in this paper is of interest for transit authorities in planning and managements

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Transit passenger market segmentation enables transit operators to target different classes of transit users to provide customized information and services. The Smart Card (SC) data, from Automated Fare Collection system, facilitates the understanding of multiday travel regularity of transit passengers, and can be used to segment them into identifiable classes of similar behaviors and needs. However, the use of SC data for market segmentation has attracted very limited attention in the literature. This paper proposes a novel methodology for mining spatial and temporal travel regularity from each individual passenger’s historical SC transactions and segments them into four segments of transit users. After reconstructing the travel itineraries from historical SC transactions, the paper adopts the Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm to mine travel regularity of each SC user. The travel regularity is then used to segment SC users by an a priori market segmentation approach. The methodology proposed in this paper assists transit operators to understand their passengers and provide them oriented information and services.

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Transit passenger market segmentation enables transit operators to target different classes of transit users for targeted surveys and various operational and strategic planning improvements. However, the existing market segmentation studies in the literature have been generally done using passenger surveys, which have various limitations. The smart card (SC) data from an automated fare collection system facilitate the understanding of the multiday travel pattern of transit passengers and can be used to segment them into identifiable types of similar behaviors and needs. This paper proposes a comprehensive methodology for passenger segmentation solely using SC data. After reconstructing the travel itineraries from SC transactions, this paper adopts the density-based spatial clustering of application with noise (DBSCAN) algorithm to mine the travel pattern of each SC user. An a priori market segmentation approach then segments transit passengers into four identifiable types. The methodology proposed in this paper assists transit operators to understand their passengers and provides them oriented information and services.

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Data on seasonal population abundance of Bemisia tabaci biotype B (silverleaf whitefly (SLW)) in Australian cotton fields collected over four consecutive growing seasons (2002/2003-2005/2006) were used to develop and validate a multiple-threshold-based management and sampling plan. Non-linear growth trajectories estimated from the field sampling data were used as benchmarks to classify adult SLW field populations into six density-based management zones with associated control recommendations in the context of peak flowering and open boll crop growth stages. Control options based on application of insect growth regulators (IGRs) are recommended for high-density populations (>2 adults/leaf) whereas conventional (non-IGR) products are recommended for the control of low to moderate population densities. A computerised re-sampling program was used to develop and test a binomial sampling plan. Binomial models with thresholds of T=1, 2 and 3 adults/leaf were tested using the field abundance data. A binomial plan based on a tally threshold of T=2 adults/leaf and a minimum sample of 20 leaves at nodes 3, 4 or 5 below the terminal is recommended as the most parsimonious and practical sampling protocol for Australian cotton fields. A decision support guide with management zone boundaries expressed as binomial counts and control options appropriate for various SLW density situations is presented. Appropriate use of chemical insecticides and tactics for successful field control of whiteflies are discussed.