Search results for "Statistical"
showing 10 items of 4960 documents
STATISTICS OF DATA RELATED TO AMAZING SUBSTANCES ANALYZED AT THE “LABORATORY OF CHEMICAL INVESTIGATIONS” OF THE PALERMO SCIENTIFIC POLICE
2019
The substances analyzed mainly at the “Chemical Investigation Laboratory” of the Regional Cabinet of Palermo, in the period from 2013 to 2018, are heroin and cocaine. For analytical techniques, mass spectrometry techniques associated with gas chromatography were used. Statistical analysis revealed a general increase in both the distribution and the average percentage of active ingredient in heroin, a substance currently available on the illicit market at a lower price than in the past, often cut with substances of synthetic derivation.Comparison of heroin seizure data in western Sicily and throughout the national territory shows a growth trend; in particular, in 2017 there is an average per…
On the geometry of the characteristic class of a star product on a symplectic manifold
2001
The characteristic class of a star product on a symplectic manifold appears as the class of a deformation of a given symplectic connection, as described by Fedosov. In contrast, one usually thinks of the characteristic class of a star product as the class of a deformation of the Poisson structure (as in Kontsevich's work). In this paper, we present, in the symplectic framework, a natural procedure for constructing a star product by directly quantizing a deformation of the symplectic structure. Basically, in Fedosov's recursive formula for the star product with zero characteristic class, we replace the symplectic structure by one of its formal deformations in the parameter $\hbar$. We then s…
Finite-size scaling analysis of the ?4 field theory on the square lattice
1986
Monte-Carlo calculations are performed for the model Hamiltonian ℋ = ∑i[(r/2)Φ 2(i)+(u/4)/gF4(i)]+∑ (C/2)[Φ (i)−Φ(j)]2 for various values of the parametersr, u, C in the crossover region from the Ising limit (r→-∞,u+∞) to the displacive limit (r=0). The variableφ(i) is a scalar continuous spin variable which can lie in the range-∞<φ(i)<+∞, for each lattice site (i).φ(i) is a priori selected proportional to the single-site probability in our Monte Carlo algorithm. The critical line is obtained in very good agreement with other previous approaches. A decrease of apparent critical exponents, deduced from a finite-size scaling analysis, is attributed to a crossover toward mean-field values at t…
Atypical transistor-based chaotic oscillators: Design, realization, and diversity
2017
In this paper, we show that novel autonomous chaotic oscillators based on one or two bipolar junction transistors and a limited number of passive components can be obtained via random search with suitable heuristics. Chaos is a pervasive occurrence in these circuits, particularly after manual adjustment of a variable resistor placed in series with the supply voltage source. Following this approach, 49 unique circuits generating chaotic signals when physically realized were designed, representing the largest collection of circuits of this kind to date. These circuits are atypical as they do not trivially map onto known topologies or variations thereof. They feature diverse spectra and predom…
Using Chemical Structural Indicators for Periodic Classification of Local Anaesthetics
2011
Algorithms for classification and taxonomy based on criteria as information entropy and its production are proposed. Some local anaesthetics, currently in use, are classified using five characteristic chemical properties of different portions of their molecules. Many classification algorithms are based on information entropy. When applying the procedures to sets of moderate size, an excessive number of results appear compatible with data and the number suffers a combinatorial explosion. However, after the equipartition conjecture one has a selection criterion between different variants resulting from classification between hierarchical trees. Information entropy and principal component anal…
Optimal band selection for future satellite sensor dedicated to soil science
2009
Hyperspectral imaging systems could be used for identifying the different soil types from the satellites. However, detecting the reflectance of the soils in all the wavelengths involves the use of a large number of sensors with high accuracy and also creates a problem in transmitting the data to earth stations for processing. The current sensors can reach a bandwidth of 20 nm and hence, the reflectance obtained using the sensors are the integration of reflectance obtained in each of the wavelength present in the spectral band. Moreover, not all spectral bands contribute equally to classification and hence, identifying the bands necessary to have a good classification is necessary to reduce …
Effects of morphometric descriptor changes on statistical classification and morphospaces
2004
Ten morphometric descriptors (five pairs of form and shape parameters) are used to describe the complex morphology of the first lower molar of two morphologically similar species, Microtus arvalis and M. agrestis. These descriptors are derived either from linear measurements or from outline analysis. The effects of these different descriptors on classical analysis as used in biology or palaeobiology are explored. First, the reliability of results in statistical classification is assessed. All of the descriptors discriminate well between the two species. The initial morphometric scheme (linear or outline) does not induce marked differences in statistical classification and the major discrepa…
Parasite infracommunities as predictors of harvest location of bogue (Boops boops L.): a pilot study using statistical classifiers
2005
The accuracy of classifying bogue (Boops boops) according to the fishery from which it was harvested was evaluated by applying several statistical classification techniques to fish parasite abundances. Bogue captured in 2001 in two fisheries off the Atlantic coast of Spain were compared with one off the Spanish Mediterranean coast. One hundred bogue were classified to each harvest location (fishery) using different numbers of parasite species chosen as predictors by a best subset method. Two parametric methods of classification (linear and quadratic discriminant analysis) were compared with two non-parametric approaches (k-nearest neighbour classification and feed-forward neural network) an…