165 research outputs found
Frame delay and loss analysis for video transmission over time-correlated 802.11A/G channels
No full textThis paper presents simulation results for the transmission of unicast MAC frames over 802.11a/g. Fading channel models at various Doppler frequencies are developed to generate time- correlated SNR waveforms. These are then used together with a bit accurate MAC/PHY simulator to estimate the frame loss rate, the transmission delay, and the jitter for a steady flow of transmit frames. Time correlated channels are required to correctly simulate the bursty nature of packet loss in a wireless channel. The Doppler spread is shown to have a strong effect on the performance of the ARQ mechanism in the MAC layer. Delay is computed as the sum of the transmission delay and the accumulated queuing delay in the MAC buffer. Delay and frame loss are compared for time correlated and time uncorrelated fading channels. Compared to the slow fading case, in a fast fading channel fewer retransmissions are required and the end-to-end delay is significantly reduced. When channel conditions are poor the simulated delay and frame loss rate are seriously underestimated when time uncorrelated fading is assumed. To analyze the performance of video codecs, we show that a time correlated channel model must be combined with a dedicated 802.11a/g MAC/PHY simulation.This paper presents simulation results for the transmission of unicast MAC frames over 802.11a/g. Fading channel models at various Doppler frequencies are developed to generate time-correlated SNR waveforms. These are then used together with a bit accurate MAC/PHY simulator to estimate the frame loss rate, the transmission delay, and the jitter for a steady flow of transmit frames. Time correlated channels are required to correctly simulate the bursty nature of packet loss in a wireless channel. The Doppler spread is shown to have a strong effect on the performance of the ARQ mechanism in the MAC layer. Delay is computed as the sum of the transmission delay and the accumulated queuing delay in the MAC buffer. Delay and frame loss are compared for time correlated and time uncorrelated fading channels. Compared to the slow fading case, in a fast fading channel fewer retransmissions are required and the end-to-end delay is significantly reduced. When channel conditions are poor the simulated delay and frame loss rate are seriously underestimated when time uncorrelated fading is assumed. To analyze the performance of video codecs, we show that a time correlated channel model must be combined with a dedicated 802.11a/g MAC/PHY simulation
A geodesic framework for analyzing molecular similarities
No full textA fast self-organizing algorithm for extracting the minimum number of independent variables that can fully describe a set of observations was recently described (Agrafiotis, D. K.; Xu, H. Proc. Natl. Acad. Sci. U.S.A. 2002, 99, 15869-15872). The method, called stochastic proximity embedding (SPE), attempts to generate low-dimensional Euclidean maps that best preserve the similarities between a set of related objects. Unlike conventional multidimensional scaling (MDS) and nonlinear mapping (NLM), SPE preserves only local relationships and, by doing so, reveals the intrinsic dimensionality and metric structure of the data. Its success depends critically on the choice of the neighborhood radius, which should be consistent with the local curvature of the underlying manifold. Here, we describe a procedure for determining that radius by examining the tradeoff between the stress function and the number of connected components in the neighborhood graph and show that it can be used to produce meaningful maps in any embedding dimension. The power of the algorithm is illustrated in two major areas of computational drug design: conformational analysis and diversity profiling of large chemical libraries. I
Does Culture Matter? The Relevance of Culture in Politics and Governance in the Euro-Mediterranean Zone. ZEI Discussion Paper: 2002: C 111
No full text[Table of Contents]: Culture and Governance in the Mediterranean – A Rationale and Overview, by Indra de Soysa and Peter Zervakis; The Relevance of Culture in Democratic Governance – Lessons from the Western Hemisphere, by Lawrence E. Harrison; Culture in Politics and Governance – European Experiences, by Klaus von Beyme; Penser L’Espace Mediterranean, by Mohammed Arkoun; Muslim and Western Civilization – Is Co-Prosperity and Peace Possible?, by Erich Weede; Political Culture and Democracy in Turkey, by Ergun Özbudun; The Crisis of Political Culture in the Arab World – A Conflict of Paradigms, by Paul Salem; Euro-Mediterranean Formations – Cultural Imperatives of System Change, by Dimitris K. Xenakis and Dimitris Chryssochoou; Cross-cultural Currents in the Mediterranean – What Prospects, Stephan Calleya; Politics and Governance in the Mediterranean, by Franck Biancheri; The Mediterranean - New Directions of Research and Policy-Making, by Ludger Kühnha
Agrafiotis, “Nonlinear Mapping of Massive Data Sets by Fuzzy Clustering and Neural Networks
No full textABSTRACT: Producing good low-dimensional representations of high-dimensional data is a common and important task in many data mining applications. Two methods that have been particularly useful in this regard are multidimensional scaling and nonlinear mapping. These methods attempt to visualize a set of objects described by means of a dissimilarity or distance matrix on a low-dimensional display plane in a way that preserves the proximities of the objects to whatever extent is possible. Unfortunately, most known algorithms are of quadratic order, and their use has been limited to relatively small data sets. We recently demonstrated that nonlinear maps derived from a small random sample of a large data set exhibit the same structure and characteristics as that of the entire collection, and that this structure can be easily extracted by a neural network, making possible the scaling of data set orders of magnitude larger than those accessible with conventional methodologies. Here, we present a variant of this algorithm based on local learning. The method employs a fuzzy clustering methodology to partition the data space into a set of Voronoi polyhedra, and uses a separate neural network to perform the nonlinear mapping within each cell. We find that this local approach offers a number of advantages, and produces maps that are virtually indistinguishable from those derived with conventional algorithms. These advantages are discussed using examples from the fields of combinatorial chemistry and optical character recognition. c ○ 2001 John Wile
Correction to: A multilevel longitudinal study of obsessive compulsive symptoms in adolescence: male gender and emotional stability as protective factors
No full textAbstract The original version of this article unfortunately contained a mistake in the author name. The co-author’s name should be Dimitris Dikeos instead of Dimitris Dikaios
Conformational Analysis of Macrocycles: Finding What Common Search Methods Miss
No full textAs computational drug design becomes increasingly reliant on virtual screening and on high-throughput 3D modeling, the need for fast, robust, and reliable methods for sampling molecular conformations has become greater than ever. Furthermore, chemical novelty is at a premium, forcing medicinal chemists to explore more complex structural motifs and unusual topologies. This necessitates the use of conformational sampling techniques that work well in all cases. Here, we compare the performance of several popular conformational search algorithms on three broad classes of macrocyclic molecules. These methods include Catalyst, CAESAR, MacroModel, MOE, Omega, Rubicon and two newer self-organizing algorithms known as stochastic proximity embedding (SPE) and self-organizing superimposition (SOS) that have been developed at Johnson & Johnson. Our results show a compelling advantage for the three distance geometry methods (SOS, SPE, and Rubicon) followed to a lesser extent by MacroModel. The remaining techniques, particularly those based on systematic search, often failed to identify any of the lowest energy conformations and are unsuitable for this class of structures. Taken together with our previous study on drug-like molecules (Agrafiotis, D. K.; Gibbs, A.; Zhu, F.; Izrailev, S.; Martin, E. Conformational Sampling of Bioactive Molecules: A Comparative Study. J. Chem. Inf. Model., 2007, 47, 1067−1086), these results suggest that SPE and SOS are two of the most robust and universally applicable conformational search methods, with the latter being preferred because of its superior speed
Conformational Analysis of Macrocycles: Finding What Common Search Methods Miss
No full textAs computational drug design becomes increasingly reliant on virtual screening and on high-throughput 3D modeling, the need for fast, robust, and reliable methods for sampling molecular conformations has become greater than ever. Furthermore, chemical novelty is at a premium, forcing medicinal chemists to explore more complex structural motifs and unusual topologies. This necessitates the use of conformational sampling techniques that work well in all cases. Here, we compare the performance of several popular conformational search algorithms on three broad classes of macrocyclic molecules. These methods include Catalyst, CAESAR, MacroModel, MOE, Omega, Rubicon and two newer self-organizing algorithms known as stochastic proximity embedding (SPE) and self-organizing superimposition (SOS) that have been developed at Johnson & Johnson. Our results show a compelling advantage for the three distance geometry methods (SOS, SPE, and Rubicon) followed to a lesser extent by MacroModel. The remaining techniques, particularly those based on systematic search, often failed to identify any of the lowest energy conformations and are unsuitable for this class of structures. Taken together with our previous study on drug-like molecules (Agrafiotis, D. K.; Gibbs, A.; Zhu, F.; Izrailev, S.; Martin, E. Conformational Sampling of Bioactive Molecules: A Comparative Study. J. Chem. Inf. Model., 2007, 47, 1067−1086), these results suggest that SPE and SOS are two of the most robust and universally applicable conformational search methods, with the latter being preferred because of its superior speed
ChemInform Abstract: A Constant Time Algorithm for Estimating the Diversity of Large Chemical Libraries.
No full text
- …
