933 resultados para Set of Weak Stationary Dynamic Actions
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Structural monitoring and dynamic identification of the manmade and natural hazard objects is under consideration. Math model of testing object by set of weak stationary dynamic actions is offered. The response of structures to the set of signals is under processing for getting important information about object condition in high frequency band. Making decision procedure into active monitoring system is discussed as well. As an example the monitoring outcome of pillar-type monument is given.
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Active monitoring and problem of non-stable of sound signal parameters in the regime of piling up response signal of environment is under consideration. Math model of testing object by set of weak stationary dynamic actions is offered. The response of structures to the set of signals is under processing for getting important information about object condition in high frequency band. Making decision procedure by using researcher’s heuristic and aprioristic knowledge is discussed as well. As an example the result of numerical solution is given.
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Due to the growing complexity and adaptability requirements of real-time systems, which often exhibit unrestricted Quality of Service (QoS) inter-dependencies among supported services and user-imposed quality constraints, it is increasingly difficult to optimise the level of service of a dynamic task set within an useful and bounded time. This is even more difficult when intending to benefit from the full potential of an open distributed cooperating environment, where service characteristics are not known beforehand and tasks may be inter-dependent. This paper focuses on optimising a dynamic local set of inter-dependent tasks that can be executed at varying levels of QoS to achieve an efficient resource usage that is constantly adapted to the specific constraints of devices and users, nature of executing tasks and dynamically changing system conditions. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves as the algorithms are given more time to run, with a minimum overhead when compared against their traditional versions.
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This thesis deals with the so-called Basis Set Superposition Error (BSSE) from both a methodological and a practical point of view. The purpose of the present thesis is twofold: (a) to contribute step ahead in the correct characterization of weakly bound complexes and, (b) to shed light the understanding of the actual implications of the basis set extension effects in the ab intio calculations and contribute to the BSSE debate. The existing BSSE-correction procedures are deeply analyzed, compared, validated and, if necessary, improved. A new interpretation of the counterpoise (CP) method is used in order to define counterpoise-corrected descriptions of the molecular complexes. This novel point of view allows for a study of the BSSE-effects not only in the interaction energy but also on the potential energy surface and, in general, in any property derived from the molecular energy and its derivatives A program has been developed for the calculation of CP-corrected geometry optimizations and vibrational frequencies, also using several counterpoise schemes for the case of molecular clusters. The method has also been implemented in Gaussian98 revA10 package. The Chemical Hamiltonian Approach (CHA) methodology has been also implemented at the RHF and UHF levels of theory for an arbitrary number interacting systems using an algorithm based on block-diagonal matrices. Along with the methodological development, the effects of the BSSE on the properties of molecular complexes have been discussed in detail. The CP and CHA methodologies are used for the determination of BSSE-corrected molecular complexes properties related to the Potential Energy Surfaces and molecular wavefunction, respectively. First, the behaviour of both BSSE-correction schemes are systematically compared at different levels of theory and basis sets for a number of hydrogen-bonded complexes. The Complete Basis Set (CBS) limit of both uncorrected and CP-corrected molecular properties like stabilization energies and intermolecular distances has also been determined, showing the capital importance of the BSSE correction. Several controversial topics of the BSSE correction are addressed as well. The application of the counterpoise method is applied to internal rotational barriers. The importance of the nuclear relaxation term is also pointed out. The viability of the CP method for dealing with charged complexes and the BSSE effects on the double-well PES blue-shifted hydrogen bonds is also studied in detail. In the case of the molecular clusters the effect of high-order BSSE effects introduced with the hierarchical counterpoise scheme is also determined. The effect of the BSSE on the electron density-related properties is also addressed. The first-order electron density obtained with the CHA/F and CHA/DFT methodologies was used to assess, both graphically and numerically, the redistribution of the charge density upon BSSE-correction. Several tools like the Atoms in Molecules topologycal analysis, density difference maps, Quantum Molecular Similarity, and Chemical Energy Component Analysis were used to deeply analyze, for the first time, the BSSE effects on the electron density of several hydrogen bonded complexes of increasing size. The indirect effect of the BSSE on intermolecular perturbation theory results is also pointed out It is shown that for a BSSE-free SAPT study of hydrogen fluoride clusters, the use of a counterpoise-corrected PES is essential in order to determine the proper molecular geometry to perform the SAPT analysis.
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Mode of access: Internet.
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Histamine is an important biogenic amine, which acts with a group of four G-protein coupled receptors (GPCRs), namely H(1) to H(4) (H(1)R - H(4)R) receptors. The actions of histamine at H(4)R are related to immunological and inflammatory processes, particularly in pathophysiology of asthma, and H(4)R ligands having antagonistic properties could be helpful as antiinflammatory agents. In this work, molecular modeling and QSAR studies of a set of 30 compounds, indole and benzimidazole derivatives, as H(4)R antagonists were performed. The QSAR models were built and optimized using a genetic algorithm function and partial least squares regression (WOLF 5.5 program). The best QSAR model constructed with training set (N = 25) presented the following statistical measures: r (2) = 0.76, q (2) = 0.62, LOF = 0.15, and LSE = 0.07, and was validated using the LNO and y-randomization techniques. Four of five compounds of test set were well predicted by the selected QSAR model, which presented an external prediction power of 80%. These findings can be quite useful to aid the designing of new anti-H(4) compounds with improved biological response.
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This study examines the impact of globalization on cross-country inequality and poverty using a panel data set for 65 developing counties, over the period 1970-2008. With separate modelling for poverty and inequality, explicit control for financial intermediation, and comparative analysis for developing countries, the study attempts to provide a deeper understanding of cross country variations in income inequality and poverty. The major findings of the study are five fold. First, a non-monotonic relationship between income distribution and the level of economic development holds in all samples of countries. Second, both openness to trade and FDI do not have a favourable effect on income distribution in developing countries. Third, high financial liberalization exerts a negative and significant influence on income distribution in developing countries. Fourth, inflation seems to distort income distribution in all sets of countries. Finally, the government emerges as a major player in impacting income distribution in developing countries.
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Tämän hetken trendit kuten globalisoituminen, ympäristömme turbulenttisuus, elintason nousu, turvallisuuden tarpeen kasvu ja teknologian kehitysnopeus korostavatmuutosten ennakoinnin tarpeellisuutta. Pysyäkseen kilpailukykyisenä yritysten tulee kerätä, analysoida ja hyödyntää liiketoimintatietoa, jokatukee niiden toimintaa viranomaisten, kilpailijoiden ja asiakkaiden toimenpiteiden ennakoinnissa. Innovoinnin ja uusien konseptien kehittäminen, kilpailijoiden toiminnan arviointi, asiakkaiden tarpeet muun muassa vaativatennakoivaa arviointia. Heikot signaalit ovat keskeisessä osassa organisaatioiden valmistautumisessa tulevaisuuden tapahtumiin. Opinnäytetyön tarkoitus on luoda ja kehittää heikkojen signaalien ymmärrystä ja hallintaa sekäkehittää konseptuaalinen ja käytännöllinen lähestymistapa ennakoivan toiminnan edistämiselle. Heikkojen signaalien tyyppien luokittelu perustuu ominaisuuksiin ajan, voimakkuuden ja liiketoimintaan integroinnin suhteen. Erityyppiset heikot signaalit piirteineen luovat reunaehdot laatutekijöiden keräämiselle ja siitä edelleen laatujärjestelmän ja matemaattiseen malliin perustuvan työvälineen kehittämiselle. Heikkojen signaalien laatutekijät on kerätty yhteen kaikista heikkojen signaalien konseptin alueista. Analysoidut ja kohdistetut laatumuuttujat antavat mahdollisuuden kehittää esianalyysiä ja ICT - työvälineitä perustuen matemaattisen mallin käyttöön. Opinnäytetyön tavoitteiden saavuttamiseksi tehtiin ensin Business Intelligence -kirjallisuustutkimus. Hiekkojen signaalien prosessi ja systeemi perustuvat koottuun Business Intelligence - systeemiin. Keskeisinä kehitysalueina tarkasteltiin liiketoiminnan integraatiota ja systemaattisen menetelmän kehitysaluetta. Heikkojen signaalien menetelmien ja määritelmien kerääminen sekä integrointi määriteltyyn prosessiin luovat uuden konseptin perustan, johon tyypitys ja laatutekijät kytkeytyvät. Käytännöllisen toiminnan tarkastelun ja käyttöönoton mahdollistamiseksi toteutettiin Business Intelligence markkinatutkimus (n=156) sekä yhteenveto muihin saatavilla oleviin markkinatutkimuksiin. Syvähaastatteluilla (n=21) varmennettiin laadullisen tarkastelun oikeellisuus. Lisäksi analysoitiin neljä käytännön projektia, joiden yhteenvedot kytkettiin uuden konseptin kehittämiseen. Prosessi voidaan jakaa kahteen luokkaan: yritysten markkinasignaalit vuoden ennakoinnilla ja julkisen sektorin verkostoprojektit kehittäen ennakoinnin struktuurin luonnin 7-15 vuoden ennakoivalle toiminnalle. Tutkimus rajattiin koskemaan pääasiassa ulkoisen tiedon aluetta. IT työvälineet ja lopullisen laatusysteemin kehittäminen jätettiin tutkimuksen ulkopuolelle. Opinnäytetyön tavoitteena ollut heikkojen signaalien konseptin kehittäminen toteutti sille asetetut odotusarvot. Heikkojen signaalien systemaattista tarkastelua ja kehittämistyötä on mahdollista edistää Business Intelligence - systematiikan hyödyntämisellä. Business Intelligence - systematiikkaa käytetään isojen yritysten liiketoiminnan suunnittelun tukena.Organisaatioiden toiminnassa ei ole kuitenkaan yleisesti hyödynnetty laadulliseen analyysiin tukeutuvaa ennakoinnin weak signals - toimintaa. Ulkoisenja sisäisen tiedon integroinnin ja systematiikan hyödyt PK -yritysten tukena vaativat merkittävää panostusta julkishallinnon rahoituksen ja kehitystoiminnan tukimuotoina. Ennakointi onkin tuottanut lukuisia julkishallinnon raportteja, mutta ei käytännön toteutuksia. Toisaalta analysoitujen case-tapausten tuloksena voidaan nähdä, ettei organisaatioissa välttämättä tarvita omaa projektipäällikköä liiketoiminnan tuen kehittämiseksi. Business vastuun ottamiseksi ja asiaan sitoutumiseen on kuitenkin löydyttävä oikea henkilö
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We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. The performance of each expert may change over time in a manner unknown to the learner. We formulate a class of universal learning algorithms for this problem by expressing them as simple Bayesian algorithms operating on models analogous to Hidden Markov Models (HMMs). We derive a new performance bound for such algorithms which is considerably simpler than existing bounds. The bound provides the basis for learning the rate at which the identity of the optimal expert switches over time. We find an analytic expression for the a priori resolution at which we need to learn the rate parameter. We extend our scalar switching-rate result to models of the switching-rate that are governed by a matrix of parameters, i.e. arbitrary homogeneous HMMs. We apply and examine our algorithm in the context of the problem of energy management in wireless networks. We analyze the new results in the framework of Information Theory.
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We analyze the dynamics of a reaction-diffusion equation with homogeneous Neumann boundary conditions in a dumbbell domain. We provide an appropriate functional setting to treat this problem and, as a first step, we show in this paper the continuity of the set of equilibria and of its linear unstable manifolds. (c) 2006 Elsevier B.V. All rights reserved.
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Matrix metalloproteinases (MMPs) constitute a family of zinc-dependent proteases involved in the extracellular matrix degradation. MMP-2 and MMP9 are overexpressed in several human cancer types, including melanoma, thus the development of new compounds to inhibit MMPs' activity is desirable. Molecular dynamic simulation and molecular properties calculations were performed on a set of novel beta-N-biaryl ether sulfonamide-based hydroxamates, reported as MMP-2 and MMP-9 inhibitors, for providing data to develop an exploratory analysis. Thermodynamic, electronic, and steric descriptors have significantly discriminated highly active from moderately and less active inhibitors of MMP-2 whereas apparent partition coefficient at pH 1.5 was also significant for the MMP-9 data set. Compound 47 was considered an outlier in all analysis, indicating the presence of a bulky substituent group in R3 is crucial to this set of inhibitors for the establishment of molecular interactions with the S1 subsite of both enzymes, but there is a limit. (C) 2012 Wiley Periodicals, Inc.
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The African great lakes are of utmost importance for the local economy (fishing), as well as being essential to the survival of the local people. During the past decades, these lakes experienced fast changes in ecosystem structure and functioning, and their future evolution is a major concern. In this study, for the first time a set of one-dimensional lake models are evaluated for Lake Kivu (2.28°S; 28.98°E), East Africa. The unique limnology of this meromictic lake, with the importance of salinity and subsurface springs in a tropical high-altitude climate, presents a worthy challenge to the seven models involved in the Lake Model Intercomparison Project (LakeMIP). Meteorological observations from two automatic weather stations are used to drive the models, whereas a unique dataset, containing over 150 temperature profiles recorded since 2002, is used to assess the model’s performance. Simulations are performed over the freshwater layer only (60 m) and over the average lake depth (240 m), since salinity increases with depth below 60 m in Lake Kivu and some lake models do not account for the influence of salinity upon lake stratification. All models are able to reproduce the mixing seasonality in Lake Kivu, as well as the magnitude and seasonal cycle of the lake enthalpy change. Differences between the models can be ascribed to variations in the treatment of the radiative forcing and the computation of the turbulent heat fluxes. Fluctuations in wind velocity and solar radiation explain inter-annual variability of observed water column temperatures. The good agreement between the deep simulations and the observed meromictic stratification also shows that a subset of models is able to account for the salinity- and geothermal-induced effects upon deep-water stratification. Finally, based on the strengths and weaknesses discerned in this study, an informed choice of a one-dimensional lake model for a given research purpose becomes possible.