865 resultados para stochastic and dynamic analysis


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Liposomes due to their biphasic characteristic and diversity in design, composition and construction, offer a dynamic and adaptable technology for enhancing drug solubility. Starting with equimolar egg-phosphatidylcholine (PC)/cholesterol liposomes, the influence of the liposomal composition and surface charge on the incorporation and retention of a model poorly water soluble drug, ibuprofen was investigated. Both the incorporation and the release of ibuprofen were influenced by the lipid composition of the multi-lamellar vesicles (MLV) with inclusion of the long alkyl chain lipid (dilignoceroyl phosphatidylcholine (C 24PC)) resulting in enhanced ibuprofen incorporation efficiency and retention. The cholesterol content of the liposome bilayer was also shown to influence ibuprofen incorporation with maximum ibuprofen incorporation efficiency achieved when 4 μmol of cholesterol was present in the MLV formulation. Addition of anionic lipid dicetylphosphate (DCP) reduced ibuprofen drug loading presumably due to electrostatic repulsive forces between the carboxyl group of ibuprofen and the anionic head-group of DCP. In contrast, the addition of 2 μmol of the cationic lipid stearylamine (SA) to the liposome formulation (PC:Chol - 16 μmol:4 μmol) increased ibuprofen incorporation efficiency by approximately 8%. However further increases of the SA content to 4 μmol and above reduced incorporation by almost 50% compared to liposome formulations excluding the cationic lipid. Environmental scanning electron microscopy (ESEM) was used to dynamically follow the changes in liposome morphology during dehydration to provide an alternative assay of liposome stability. ESEM analysis clearly demonstrated that ibuprofen incorporation improved the stability of PC:Chol liposomes as evidenced by an increased resistance to coalescence during dehydration. These finding suggest a positive interaction between amphiphilic ibuprofen molecules and the bilayer structure of the liposome. © 2004 Elsevier B.V. All rights reserved.

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Systemized analysis of trends towards integration and hybridization in contemporary expert systems is conducted, and a particular class of applied expert systems, integrated expert systems, is considered. For this purpose, terminology, classification, and models, proposed by the author, are employed. As examples of integrated expert systems, Russian systems designed in this field and available to the majority of specialists are analyzed.

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The impact of whole body vibrations (vibration stimulus mechanically transferred to the body) on muscular activity and neuromuscular response has been widely studied but without standard protocol and by using different kinds of exercises and parameters. In this study, we investigated how whole body vibration treatments affect electromyographic signal of rectus femoris during static and dynamic squat exercises. The aim was the identification of squat exercise characteristics useful to maximize neuromuscular activation and hence progress in training efficacy. Fourteen healthy volunteers performed both static and dynamic squat exercises without and with vibration treatments. Surface electromyographic signals of rectus femoris were recorded during the whole exercise and processed to reduce artifacts and to extract root mean square values. Paired t-test results demonstrated an increase of the root mean square values (p<0.05) in both static and dynamic squat exercises with vibrations respectively of 63% and 108%. For each exercise, subjects gave a rating of the perceived exertion according to the Borg's scale but there were no significant changes in the perceived exertion rate between exercises with and without vibration. Finally, results from analysis of electromyographic signals identified the static squat with WBV treatment as the exercise with higher neuromuscular system response. © 2012 IEEE.

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Electrically excited synchronous machines with brushes and slip rings are popular but hardly used in inflammable and explosive environments. This paper proposes a new brushless electrically excited synchronous motor with a hybrid rotor. It eliminates the use of brushes and slip rings so as to improve the reliability and cost-effectiveness of the traction drive. The proposed motor is characterized with two sets of stator windings with two different pole numbers to provide excitation and drive torque independently. This paper introduces the structure and operating principle of the machine, followed by the analysis of the air-gap magnetic field using the finite-element method. The influence of the excitation winding's pole number on the coupling capability is studied and the operating characteristics of the machine are simulated. These are further examined by the experimental tests on a 16 kW prototype motor. The machine is proved to have good static and dynamic performance, which meets the stringent requirements for traction applications.

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The advances in three related areas of state-space modeling, sequential Bayesian learning, and decision analysis are addressed, with the statistical challenges of scalability and associated dynamic sparsity. The key theme that ties the three areas is Bayesian model emulation: solving challenging analysis/computational problems using creative model emulators. This idea defines theoretical and applied advances in non-linear, non-Gaussian state-space modeling, dynamic sparsity, decision analysis and statistical computation, across linked contexts of multivariate time series and dynamic networks studies. Examples and applications in financial time series and portfolio analysis, macroeconomics and internet studies from computational advertising demonstrate the utility of the core methodological innovations.

Chapter 1 summarizes the three areas/problems and the key idea of emulating in those areas. Chapter 2 discusses the sequential analysis of latent threshold models with use of emulating models that allows for analytical filtering to enhance the efficiency of posterior sampling. Chapter 3 examines the emulator model in decision analysis, or the synthetic model, that is equivalent to the loss function in the original minimization problem, and shows its performance in the context of sequential portfolio optimization. Chapter 4 describes the method for modeling the steaming data of counts observed on a large network that relies on emulating the whole, dependent network model by independent, conjugate sub-models customized to each set of flow. Chapter 5 reviews those advances and makes the concluding remarks.

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The hydrologic system beneath the Antarctic Ice Sheet is thought to influence both the dynamics and distribution of fast flowing ice streams, which discharge most of the ice lost by the ice sheet. Despite considerable interest in understanding this subglacial network and its affect on ice flow, in situ observations from the ice sheet bed are exceedingly rare. Here we describe the first sediment cores recovered from an active subglacial lake. The lake, known as Subglacial Lake Whillans, is part of a broader, dynamic hydrologic network beneath the Whillans Ice Stream in West Antarctica. Even though "floods" pass through the lake, the lake floor shows no evidence of erosion or deposition by flowing water. By inference, these floods must have insufficient energy to erode or transport significant volumes of sediment coarser than silt. Consequently, water flow beneath the region is probably incapable of incising continuous channels into the bed and instead follows preexisting subglacial topography and surface slope. Sediment on the lake floor consists of till deposited during intermittent grounding of the ice stream following flood events. The fabrics within the till are weaker than those thought to develop in thick deforming beds suggesting subglacial sediment fluxes across the ice plain are currently low and unlikely to have a large stabilizing effect on the ice stream's grounding zone.

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As one of the most successfully commercialized distributed energy resources, the long-term effects of microturbines (MTs) on the distribution network has not been fully investigated due to the complex thermo-fluid-mechanical energy conversion processes. This is further complicated by the fact that the parameter and internal data of MTs are not always available to the electric utility, due to different ownerships and confidentiality concerns. To address this issue, a general modeling approach for MTs is proposed in this paper, which allows for the long-term simulation of the distribution network with multiple MTs. First, the feasibility of deriving a simplified MT model for long-term dynamic analysis of the distribution network is discussed, based on the physical understanding of dynamic processes that occurred within MTs. Then a three-stage identification method is developed in order to obtain a piecewise MT model and predict electro-mechanical system behaviors with saturation. Next, assisted with the electric power flow calculation tool, a fast simulation methodology is proposed to evaluate the long-term impact of multiple MTs on the distribution network. Finally, the model is verified by using Capstone C30 microturbine experiments, and further applied to the dynamic simulation of a modified IEEE 37-node test feeder with promising results.

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Android is becoming ubiquitous and currently has the largest share of the mobile OS market with billions of application downloads from the official app market. It has also become the platform most targeted by mobile malware that are becoming more sophisticated to evade state-of-the-art detection approaches. Many Android malware families employ obfuscation techniques in order to avoid detection and this may defeat static analysis based approaches. Dynamic analysis on the other hand may be used to overcome this limitation. Hence in this paper we propose DynaLog, a dynamic analysis based framework for characterizing Android applications. The framework provides the capability to analyse the behaviour of applications based on an extensive number of dynamic features. It provides an automated platform for mass analysis and characterization of apps that is useful for quickly identifying and isolating malicious applications. The DynaLog framework leverages existing open source tools to extract and log high level behaviours, API calls, and critical events that can be used to explore the characteristics of an application, thus providing an extensible dynamic analysis platform for detecting Android malware. DynaLog is evaluated using real malware samples and clean applications demonstrating its capabilities for effective analysis and detection of malicious applications.

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In this thesis, proactive marketing is suggested to be a broader concept than existing research assumes. Although the concept has been mentioned in the context of competitive advantage in previous research, it has not been comprehensively described. This thesis shows that proactive marketing is more than investing in marketing communications of a company. Proactive marketing is described as a three-phased process that contains different customer value identification, creation, and delivery activities. The purpose of proactive marketing is essentially to anticipate and pursue market opportunities that bring value to the company’s stakeholders. Ultimately, proactive marketing aims at acting first on the market, shaping the markets, and thus reaching competitive advantage. The proactive marketing process is supported by the structures of an organization. Suitable structures for proactive marketing are identified in the thesis based on existing research and through an empirical analysis. Moreover, proactive marketing is related to two management theories: the dynamic capabilities framework and the empowerment of employees. A dynamic environment requires companies that pursue proactive marketing to change continuously. Dynamic capabilities are considered as tools of the management, which enable companies to create suitable conditions for the constant change. Empowerment of employees is a management practice that creates proactive behaviors in individuals. The empirical analysis is conducted in an online company operating in the rapidly changing marketplace of the Internet. Through the empirical analysis, the thesis identifies in practice how proactiveness manifests in the marketing process of a company, how organizational structures facilitate proactive marketing, and how proactive marketing is managed. The theoretical contribution of this thesis consist of defining the proactive marketing concept comprehensively and providing further research suggestions related to proactive marketing.

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A simple but efficient voice activity detector based on the Hilbert transform and a dynamic threshold is presented to be used on the pre-processing of audio signals -- The algorithm to define the dynamic threshold is a modification of a convex combination found in literature -- This scheme allows the detection of prosodic and silence segments on a speech in presence of non-ideal conditions like a spectral overlapped noise -- The present work shows preliminary results over a database built with some political speech -- The tests were performed adding artificial noise to natural noises over the audio signals, and some algorithms are compared -- Results will be extrapolated to the field of adaptive filtering on monophonic signals and the analysis of speech pathologies on futures works

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With the increasing complexity of today's software, the software development process is becoming highly time and resource consuming. The increasing number of software configurations, input parameters, usage scenarios, supporting platforms, external dependencies, and versions plays an important role in expanding the costs of maintaining and repairing unforeseeable software faults. To repair software faults, developers spend considerable time in identifying the scenarios leading to those faults and root-causing the problems. While software debugging remains largely manual, it is not the case with software testing and verification. The goal of this research is to improve the software development process in general, and software debugging process in particular, by devising techniques and methods for automated software debugging, which leverage the advances in automatic test case generation and replay. In this research, novel algorithms are devised to discover faulty execution paths in programs by utilizing already existing software test cases, which can be either automatically or manually generated. The execution traces, or alternatively, the sequence covers of the failing test cases are extracted. Afterwards, commonalities between these test case sequence covers are extracted, processed, analyzed, and then presented to the developers in the form of subsequences that may be causing the fault. The hypothesis is that code sequences that are shared between a number of faulty test cases for the same reason resemble the faulty execution path, and hence, the search space for the faulty execution path can be narrowed down by using a large number of test cases. To achieve this goal, an efficient algorithm is implemented for finding common subsequences among a set of code sequence covers. Optimization techniques are devised to generate shorter and more logical sequence covers, and to select subsequences with high likelihood of containing the root cause among the set of all possible common subsequences. A hybrid static/dynamic analysis approach is designed to trace back the common subsequences from the end to the root cause. A debugging tool is created to enable developers to use the approach, and integrate it with an existing Integrated Development Environment. The tool is also integrated with the environment's program editors so that developers can benefit from both the tool suggestions, and their source code counterparts. Finally, a comparison between the developed approach and the state-of-the-art techniques shows that developers need only to inspect a small number of lines in order to find the root cause of the fault. Furthermore, experimental evaluation shows that the algorithm optimizations lead to better results in terms of both the algorithm running time and the output subsequence length.

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Cultivation of chilling-tolerant ornamental crops at lower temperature could reduce the energy demands of heated greenhouses. To provide a better understanding of how sub-optimal temperatures (12 degrees C vs. 16 degrees C) affect growth of the sensitive Petunia hybrida cultivar 'SweetSunshine Williams', the transcriptome, carbohydrate metabolism, and phytohormone homeostasis were monitored in aerial plant parts over 4 weeks by use of a microarray, enzymatic assays and GC-MS/MS. The data revealed three consecutive phases of chilling response. The first days were marked by a strong accumulation of sugars, particularly in source leaves, preferential up-regulation of genes in the same tissue and down-regulation of several genes in the shoot apex, especially those involved in the abiotic stress response. The midterm phase featured a partial normalization of carbohydrate levels and gene expression. After 3 weeks of chilling exposure, a new stabilized balance was established. Reduced hexose levels in the shoot apex, reduced ratios of sugar levels between the apex and source leaves and a higher apical sucrose/hexose ratio, associated with decreased activity and expression of cell wall invertase, indicate that prolonged chilling induced sugar accumulation in source leaves at the expense of reduced sugar transport to and reduced sucrose utilization in the shoot. This was associated with reduced levels of indole-3-acetic acid and abscisic acid in the apex and high numbers of differentially, particularly up-regulated genes, especially in the source leaves, including those regulating histones, ethylene action, transcription factors, and a jasmonate-ZIM-domain protein. Transcripts of one Jumonji C domain containing protein and one expansin accumulated in source leaves throughout the chilling period. The results reveal a dynamic and complex disturbance of plant function in response to mild chilling, opening new perspectives for the comparative analysis of differently tolerant cultivars.

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The aim of this thesis is to test the ability of some correlative models such as Alpert correlations on 1972 and re-examined on 2011, the investigation of Heskestad and Delichatsios in 1978, the correlations produced by Cooper in 1982, to define both dynamic and thermal characteristics of a fire induced ceiling-jet flow. The flow occurs when the fire plume impinges the ceiling and develops in the radial direction of the fire axis. Both temperature and velocity predictions are decisive for sprinklers positioning, fire alarms positions, detectors (heat, smoke) positions and activation times and back-layering predictions. These correlative models will be compared with a 3D numerical simulation software CFAST. For the results comparison of temperature and velocity near the ceiling. These results are also compared with a Computational Fluid Dynamics (CFD) analysis, using ANSYS FLUENT.

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Dynamic knee valgus is a multi-planar motion that has been associated with anterior cruciate ligament injuries and patellofemoral pain syndrome. Clinical assessment of dynamic knee valgus can be made by looking for the visual appearance of excessive medial knee displacement (MKD) in the double-leg squat (DLS). The purpose of this dissertation was to identify the movement patterns and neuromuscular strategies associated with MKD during the DLS. Twenty-four control subjects and eight individuals showing MKD during the DLS participated in the study. Significant differences were verified between subjects that demonstrated MKD and a control (CON) group for the eletromyographic amplitude of adductor magnus, biceps femoris, vastus lateralis and vastus medialis muscles (p < 0.05), during the descending phase of the DLS. During the ascending phase were found group differences for adductor magnus and rectus femoris muscles (p < 0.05). Results from kinematic analysis revealed higher minimum and maximum values of ankle abduction and knee internal rotation angles (p < 0.05) for the MKD group. Also, individuals showing excessive MKD had higher hip adduction/abduction excursion. Our results suggested that higher tibial internal rotation and knee internal rotation angles in the initial position of the DLS are associated with MKD. The neuromuscular strategies that contributed to MKD were higher adductor magnus activation, whereas biceps femoris, vastus lateralis and vastus medialis activated more to stabilize the knee in response to the internal rotation moment.

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This paper empirically investigates volatility transmission among stock and foreign exchange markets in seven major world economies during the period July 1988 to January 2015. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach) using a framework recently proposed by Diebold and Yilmaz (2014). Second, we make use of a dynamic analysis to evaluate the net directional connectedness for each market. To gain further insights, we examine the time-varying behaviour of net pair-wise directional connectedness during the financial turmoil periods experienced in the sample period Our results suggest that slightly more than half of the total variance of the forecast errors is explained by shocks across markets rather than by idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability.