Search results for "Data type"
showing 10 items of 1183 documents
Using neural networks for (13)c NMR chemical shift prediction-comparison with traditional methods.
2002
Abstract Interpretation of 13 C chemical shifts is essential for structure elucidation of organic molecules by NMR. In this article, we present an improved neural network approach and compare its performance to that of commonly used approaches. Specifically, our recently proposed neural network ( J. Chem. Inf. Comput. Sci. 2000, 40, 1169–1176) is improved by introducing an extended hybrid numerical description of the carbon atom environment, resulting in a standard deviation (std. dev.) of 2.4 ppm for an independent test data set of ∼42,500 carbons. Thus, this neural network allows fast and accurate 13 C NMR chemical shift prediction without the necessity of access to molecule or fragment d…
Analyzing assessors and products in sorting tasks: DISTATIS, theory and applications
2007
Abstract In this paper we present a new method called distatis that can be applied to the analysis of sorting data. D istatis is a generalization of classical multidimensional scaling which allows one to analyze 3-ways distance tables. When used for analyzing sorting tasks, distatis takes into account individual sorting data. Specifically, when distatis is used to analyze the results of an experiment in which several assessors sort a set of products, we obtain two types of maps: One for the assessors and one for the products. In these maps, the proximity between two points reflects their similarity, and therefore these maps can be read using the same rules as standard metric multidimensiona…
DISTATIS: The Analysis of Multiple Distance Matrices
2006
In this paper we present a generalization of classical multidimensional scaling called DISTATIS which is a new method that can be used to compare algorithms when their outputs consist of distance matrices computed on the same set of objects. The method first evaluates the similarity between algorithms using a coefficient called the RV coefficient. From this analysis, a compromise matrix is computed which represents the best aggregate of the original matrices. In order to evaluate the differences between algorithms, the original distance matrices are then projected onto the compromise. We illustrate this method with a "toy example" in which four different "algorithms" (two computer programs …
Topology design to reduce energy consumption of distributed graph filtering in WSN
2017
The large number of nodes forming current sensor networks has made essential to introduce distributed mechanisms in many traditional applications. In the emerging field of graph signal processing, the distributed mechanism of information potentials constitutes a distributed graph filtering process that can be used to solve many different problems. An important limitation of this algorithm is that it is inherently iterative, which implies that the nodes incur in a repeated communication cost along the exchange periods of the filtering process. Since sensor nodes are battery powered and radio communications are one of the most energy demanding operations, in this work, we propose to redesign …
Comparison of stereo vision techniques for cloud-top height retrieval
2007
This paper presents an ongoing study for the estimation of the cloud-top height by using only geometrical methods. In agreement with some recent studies showing that it is possible to achieve reliable height estimations not only with the classical methods based on radiative transfer, this article includes a comparison of performances of a selected set of vision algorithms devoted to extract dense disparity maps or motion fields from Infra Red stereo image pairs. This collection includes both area-based techniques and an optical flow-based method and the comparison is accomplished by using a set of cloudy scenes selected from the Along-Track Scanning Radiometer (ATSR2) database. The first gr…
A rotating wheel system for the detection of spontaneously fissioning nuclides from heavy ion reactions
1981
Abstract A rotating wheel system for the detection of spontaneously fissioning reaction products from heavy ion reactions was developed. In this system products recoiling from a rotating target wheel are stopped in a catcher foil stack which can be rotated at various velocities up to 80 rotations per second. All products emitted within a wide emission cone are stopped in the catcher foils and are rotated into shielded positions with stationary fission-track detectors positioned on both sides of each rotating foil. This technique allows a sensitive detection of spontaneously fissioning nuclides over a broad range of half-lives from 1 ms to about 1 d. By post-bombardment exposure of the catch…
Virtual lock-and-key approach: The in silico revival of Fischer model by means of molecular descriptors
2010
Abstract In the last years the application of computational methodologies in the medicinal chemistry fields has found an amazing development. All the efforts were focused on the searching of new leads featuring a close affinity on a specific biological target. Thus, different molecular modeling approaches in simulation of molecular behavior for a specific biological target were employed. In spite of the increasing reliability of computational methodologies, not always the designed lead, once synthesized and screened, are suitable for the chosen biological target. To give another chance to these compounds, this work tries to resume the old concept of Fischer lock-and-key model. The same can …
Co-learning of recursive languages from positive data
1996
The present paper deals with the co-learnability of enumerable families L of uniformly recursive languages from positive data. This refers to the following scenario. A family L of target languages as well as hypothesis space for it are specified. The co-learner is fed eventually all positive examples of an unknown target language L chosen from L. The target language L is successfully co-learned iff the co-learner can definitely delete all but one possible hypotheses, and the remaining one has to correctly describe L.
Graph recursive least squares filter for topology inference in causal data processes
2017
In this paper, we introduce the concept of recursive least squares graph filters for online topology inference in data networks that are modelled as Causal Graph Processes (CGP). A Causal Graph Process (CGP) is an auto regressive process in the time series associated to different variables, and whose coefficients are the so-called graph filters, which are matrix polynomials with different orders of the graph adjacency matrix. Given the time series of data at different variables, the goal is to estimate these graph filters, hence the associated underlying adjacency matrix. Previously proposed algorithms have focused on a batch approach, assuming implicitly stationarity of the CGP. We propose…
Investigation of electrode material – redox couple systems for reverse electrodialysis processes. Part II: Experiments in a stack with 10–50 cell pai…
2013
Abstract The performances of reverse electrodialysis depend on several factors, including the nature of the electrode material and of the redox processes adopted to make possible the conversion between chemical potential and electric power. In this paper the possible utilization of various redox processes (reduction/oxidation of iron species, oxidation and reduction of water, oxidation of chlorine and reduction of water) was studied in a stack equipped with 10–50 cell pairs and by focused electrolyses in a three compartment cell. The effect of selected redox processes on power density output and eventual contamination of saline solutions flowing in the stack was evaluated in detail. The eff…