322 research outputs found
A Near-Optimal Sensor Placement Algorithm to Achieve Complete Coverage/Discrimination in Sensor Networks
No full textIn this letter, we develop a robust and scalable
algorithm to cope with the sensor placement problem for target
location under constraints of the cost limitation and the complete
coverage. The problem is NP-complete for arbitrary sensor fields.
The grid-based placement scenario is adopted and the sensor
placement problem formulated as a combinatorial optimization
problem for minimizing the maximum distance error in a sensor
field under the constraints. The proposed algorithm is based
on the simulated annealing approach. The experimental results
reveal that, for small sensor fields, the algorithm can find the
optimal sensor placement under the minimum cost limitation.
Moreover, it can also find a placement with minimum distance
error for large sensor fields under the cost limitation
Multi-Rate Throughput Optimization with Fairness Constraints in Wireless Local Area Networks
No full textROTATIONAL ANALYSIS OF THE VIBRATIONAL GROUND STATE OF DIMETHYL ETHER,
No full textP. Groner, submitted. F. J. Lovas, H Lutz and H. Dreizler, J. Phys. Chem. Ref. Data (1979) 8, 1057-1107; J. R. During, Y.S. LI and P. Groner, J. Mol, Spectrose. (1976)62, 159--174 W. Neustock A. Guarnicri. J. Demaison and G. Wlodarczak, Z. Naturforsch, Part A (1990) 45m 702, 702--706.Author Institution: Department of Chemistry, University of Missouri; Department of Physics, Ohio State UniversityAn effective rotational was used to analyse the rotational transitions in the vibrational ground state of dimethyl ether. and mm- measurements from the literature were combined with new measurements between 100 and 550 GHz in a global fit of all four torsional substates. Frequencies between 8 and 550 GHz were fit for transitions involving energy levels with {J} up to 40 and up to 9. Only 22 spectroscopic parameters were necessary to fit 1499 frequencies to experimental precision (dimensionless standard deviation 0.67), The following parameters were determined in the least-squares fit: = 8.426(27) deg., parameters equivalent to the rotational, quartic and sextic distortion constants the internal energy tunneling parameters MHz and MHz and three tunneling constants related to the ``rotational” constants
Organic semiconductors in the limit of a few monolayers : molecular surface doping of pentacene thin film transistors
Full text linkThe FUP Credibility: a user satisfaction survey
Full text linkThis research deals with electronic publishing contemporary academic context. In particular the focus of the research is to verify the degree of credibility of Firenze University Press (FUP), academic electronic press project of the University of Florence, investigating its users’ perceptions and opinions. This survey was motivated by the need of FUP to develop a strategy focused to rationalise resources, responding to users requirements. Survey investigated mainly two categories of FUP user: professors as customers, authors (or potential authors) and students, as customers. Mixed method have adopted to draw the survey model, that combining qualitative and quantitative approaches, use both of them. Sample survey methodology have been used to obtain a picture of the general trend of faculty of the University of Florence, by selecting and measuring a sample from the whole population. Research have been directed to a sample of ‘electronically oriented’ users, those who have no prides towards Internet and email as information and communication tools and let personal email to be visible on the University website. On the basis of data and opinions gathered emerged:
1. high percent of user satisfaction;
2. promotional factors:
Primary
- high visibility
- copyright guarantee
Secondary
- speediness
- easiness
- extended access;
3. recommendations:
a) Activity of promotion and growth of visibility
b) Collaboration with commercial publishers, other University Presses
c) Production scheme
d) Editing
e) Access and sellin
Experimental condition selection in whole-genome functional classification
Full text linkMicroarray technologies enable the quantitative simultaneously monitoring of expression levels for thousands of genes under various experimental conditions. This is new technology has provided a new way of learning gene functional classes on a genome-wide. Previously, lots of unsupervised clustering methods and supervised classification have shown power in assigning functional annotations based on gene coexpression. However, due to the noisy and highly dimensional nature of microarray data and the inherent heterogeneity of gene functional classes, the whole-genome learning of gene functional classes from microarray data has remained a great challenge for scientists. Currently, most of the methods do not discriminate the different attribution of experimental conditions in the learning process, which impaired the ability of learning functional classes and prevented these methods from discovering the links between the experimental conditions and gene functional classes. In this study, we perform a selection of experiment conditions during the systematically learning of ∼100 functional classes categorized in MIPS's comprehensive yeast genome database. In particular, a hybridization of genetic algorithm and k-nearest neighbors classifier has been adopted here. Through a comparison of the results with other previous methods our studies indicate promising improvements in learning performance. Further, by identifying the critical experimental conditions, significant links between the experiments and the functional classes were uncovered
Instance-Based penalization techniques for classification
Full text linkSeveral instance-based large-margin classi¯ers have recentlybeen put forward in the literature: Support Hyperplanes, Nearest ConvexHull classifier, and Soft Nearest Neighbor. We examine those techniquesfrom a common fit-versus-complexity framework and study the links be-tween them. Finally, we compare the performance of these techniquesvis-a-vis each other and other standard classification methods.
Hundreds of variants clustered in genomic loci and biological pathways affect human height
Full text linkMost common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits(1), but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait(2,3). The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways
Testing the effectiveness of advertising strategies for established brands : an empirical investigation into and a technique for measuring the response of established brands' sales to changes in advertising weight and copy using continuous panel records
Full text linkManaging the advertising function for established brands
requires an understanding of the nature of the advertising-sales
relationship. Historically, both experimental and non-experimental
approaches have been used to investigate this relationship, but the
impressive amount of literature in this area seems to have identified
only a number of broad generalizations. In part, this is due to the
inadequacies of the different methodologies and data sources that have
been used, which make difficult a comparison of the reported studies
for the purpose of establishing guidelines for strategic advertising
management. Continuous panel-based experimental research seems to
offer greater potential for providing further insights into the nature
of the advertising-sales relationship.
The research first investigates the appropriateness and
sensitivity of a number of models in identifying and quantifying the
effect of changes in advertising strategy on sales, using The Test
Marketing Group's (TMG) consumer diary and scanner panel data. It is
shown that the ability to identify an advertising effect, referred to
as the system's sensitivity, is significantly influenced by a number
of factors, and that it can be predicted from the number of purchase
transactions of the test brand.
By using one specific model, thirty-five advertising strategy
tests are analyzed at the aggregate, panel level, in order to estimate
the probability of causing an advertising effect on all panelists, and
to identify factors that influence the effect. Application of this
methodology represents the first consistent analysis of a collection
of historical data with the objective of developing a knowledge base
regarding advertising strategy making and testing. It is found the
probability of causing an advertising effect does not differ between
copy and weight tests, but that a change in copy carries a significant
risk of causing a negative effect. Increases in weight are
particularly effective in causing a positive effect for small share
brands. among the tests that are analyzed there is a 37.1% probability
of observing an advertising effect at the panel level, which is lower
than the probability observed in the literature.
Subsequent analysis of the same tests examines the effect of a
change in advertising strategy at the disaggregate level, that is, on
certain segments of panelists. The results of this analysis show that
significant advertising effects are observed more often, thereby
increasing the probability of observing an advertising effect to 60%.
Thus, by applying one methodology consistently across a set of
panel-based advertising strategy tests, it is possible to identify a
number of empirical norms that can aid managers in determining
effective advertising strategies for their established brands. This so
far has been difficult to derive from reported advertising studies. It
is also suggested that further insights into the advertising-sales
relationship can be obtained by increasing TMG's ability to specify
advertising exposure. An experimental data collection system developed
and tested on the basis of this further research is presented and
evaluated
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