Search results for: dynamic algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7068

Search results for: dynamic algorithm

4998 Drug Delivery to Solid Tumor: Effect of Dynamic Capillary Network Induced by Tumor

Authors: Mostafa Sefidgar, Kaamran Raahemifar, Hossein Bazmara, Madjid Soltani

Abstract:

The computational methods provide condition for investigation related to the process of drug delivery, such as convection and diffusion of drug in extracellular matrices, and drug extravasation from microvascular. The information of this process clarifies the mechanisms of drug delivery from the injection site to absorption by a solid tumor. In this study, an advanced numerical method is used to solve fluid flow and solute transport equations simultaneously to show how capillary network structure induced by tumor affects drug delivery. The effect of heterogeneous capillary network induced by tumor on interstitial fluid flow and drug delivery is investigated by this multi scale method. The sprouting angiogenesis model is used for generating capillary network induced by tumor. Fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network and fluid flow in normal and tumor tissues. The Starling’s law is used for closing this system of equations and coupling the intravascular and extravascular flows. Finally, convection-diffusion-reaction equation is used to simulate drug delivery. The dynamic approach which changes the capillary network structure based on signals sent by hemodynamic and metabolic stimuli is used in this study for more realistic assumption. The study indicates that drug delivery to solid tumors depends on the tumor induced capillary network structure. The dynamic approach generates the irregular capillary network around the tumor and predicts a higher interstitial pressure in the tumor region. This elevated interstitial pressure with irregular capillary network leads to a heterogeneous distribution of drug in the tumor region similar to in vivo observations. The investigation indicates that the drug transport properties have a significant role against the physiological barrier of drug delivery to a solid tumor.

Keywords: solid tumor, physiological barriers to drug delivery, angiogenesis, microvascular network, solute transport

Procedia PDF Downloads 295
4997 The Investigation of Oil Price Shocks by Using a Dynamic Stochastic General Equilibrium: The Case of Iran

Authors: Bahram Fathi, Karim Alizadeh, Azam Mohammadbagheri

Abstract:

The aim of this paper is to investigate the role of oil price shocks in explaining business cycles in Iran using a dynamic stochastic general equilibrium approach. This model incorporates both productivity and oil revenue shocks. The results indicate that productivity shocks are relatively more important to business cycles than oil shocks. The model with two shocks produces different values for volatility, but these values have the same ranking as that of the actual data for most variables. In addition, the actual data are close to the ratio of standard deviations to the output obtained from the model with two shocks. The results indicate that productivity shocks are relatively more important to business cycles than the oil shocks. The model with only a productivity shock produces the most similar figures in term of volatility magnitude to that of the actual data. Next, we use the Impulse Response Functions (IRF) to evaluate the capability of the model. The IRF shows no effect of an oil shock on the capital stocks and on labor hours, which is a feature of the model. When the log-linearized system of equations is solved numerically, investment and labor hours were not found to be functions of the oil shock. This research recommends using different techniques to compare the model’s robustness. One method by which to do this is to have all decision variables as a function of the oil shock by inducing the stationary to the model differently. Another method is to impose a bond adjustment cost. This study intends to fill that gap. To achieve this objective, we derive a DSGE model that allows for the world oil price and productivity shocks. Second, we calibrate the model to the Iran economy. Next, we compare the moments from the theoretical model with both single and multiple shocks with that obtained from the actual data to see the extent to which business cycles in Iran can be explained by total oil revenue shock. Then, we use an impulse response function to evaluate the role of world oil price shocks. Finally, I present implications of the findings and interpretations in accordance with economic theory.

Keywords: oil price, shocks, dynamic stochastic general equilibrium, Iran

Procedia PDF Downloads 417
4996 Home Range and Spatial Interaction Modelling of Black Bears

Authors: Fekadu L. Bayisa, Elvan Ceyhan, Todd D. Steury

Abstract:

Interaction between individuals within the same species is an important component of population dynamics. An interaction can be either static (based on spatial overlap) or dynamic (based on movement interactions). Using GPS collar data, we can quantify both static and dynamic interactions between black bears. The goal of this work is to determine the level of black bear interactions using the 95% and 50% home ranges, as well as to model black bear spatial interactions, which could be attraction, avoidance/repulsion, or a lack of interaction at all, to gain new insights and improve our understanding of ecological processes. Recent methodological developments in home range estimation, inhomogeneous multitype/cross-type summary statistics, and envelope testing methods are explored to study the nature of black bear interactions. Our findings, in general, indicate that the black bears of one type in our data set tend to cluster around another type.

Keywords: autocorrelated kernel density estimator, cross-type summary function, inhomogeneous multitype Poisson process, kernel density estimator, minimum convex polygon, pointwise and global envelope tests

Procedia PDF Downloads 66
4995 Dynamic Effects of Charitable Giving in a Ramsey Model

Authors: Riham Barbar

Abstract:

This paper studies the dynamic effects of charitable giving in a Ramsey model à la Becker and Foias (1994), such that heterogeneity is reduced to two types of agents: rich and poor. It is assumed that rich show a great concern for poor and enjoy giving. The introduction of charitable giving in this paper is inspired from the notion of Zakat (borrowed from the Islamic Economics) and is defined according to the warm-glow of Andreoni (1990). In this framework, we prove the existence of a steady state where only the patient agent holds capital. Furthermore, we show that local indetermincay appears. While moderate values of charitable-giving elasticity makes the appearance of endogenous fluctuations due to self-fulfilling expectations more likely, high values of this elasticity stabilizes endogenous fluctuations, by narrowing down the range of parameter values compatible with local indeterminacy and may rule out expectations-driven fluctuations if it exceeds certain threshold. Finally, cycles of period two emerge. However, charitable-giving makes it less likely for these cycles to emerge.

Keywords: charitable giving, warm-glow, bifurcations, heterogeneous agents, indeterminacy, self-fulfilling expectations, endogenous fluctuations

Procedia PDF Downloads 302
4994 Experimental Analysis of Control in Electric Vehicle Charging Station Based Grid Tied Photovoltaic-Battery System

Authors: A. Hassoune, M. Khafallah, A. Mesbahi, T. Bouragba

Abstract:

This work presents an improved strategy of control for charging a lithium-ion battery in an electric vehicle charging station using two charger topologies i.e. single ended primary inductor converter (SEPIC) and forward converter. In terms of rapidity and accuracy, the power system consists of a topology/control diagram that would overcome the performance constraints, for instance the power instability, the battery overloading and how the energy conversion blocks would react efficiently to any kind of perturbations. Simulation results show the effectiveness of the proposed topologies operated with a power management algorithm based on voltage/peak current mode controls. In order to provide credible findings, a low power prototype is developed to test the control strategy via experimental evaluations of the converter topology and its controls.

Keywords: battery storage buffer, charging station, electric vehicle, experimental analysis, management algorithm, switches control

Procedia PDF Downloads 154
4993 A Context Aware Mobile Learning System with a Cognitive Recommendation Engine

Authors: Jalal Maqbool, Gyu Myoung Lee

Abstract:

Using smart devices for context aware mobile learning is becoming increasingly popular. This has led to mobile learning technology becoming an indispensable part of today’s learning environment and platforms. However, some fundamental issues remain - namely, mobile learning still lacks the ability to truly understand human reaction and user behaviour. This is due to the fact that current mobile learning systems are passive and not aware of learners’ changing contextual situations. They rely on static information about mobile learners. In addition, current mobile learning platforms lack the capability to incorporate dynamic contextual situations into learners’ preferences. Thus, this thesis aims to address these issues highlighted by designing a context aware framework which is able to sense learner’s contextual situations, handle data dynamically, and which can use contextual information to suggest bespoke learning content according to a learner’s preferences. This is to be underpinned by a robust recommendation system, which has the capability to perform these functions, thus providing learners with a truly context-aware mobile learning experience, delivering learning contents using smart devices and adapting to learning preferences as and when it is required. In addition, part of designing an algorithm for the recommendation engine has to be based on learner and application needs, personal characteristics and circumstances, as well as being able to comprehend human cognitive processes which would enable the technology to interact effectively and deliver mobile learning content which is relevant, according to the learner’s contextual situations. The concept of this proposed project is to provide a new method of smart learning, based on a capable recommendation engine for providing an intuitive mobile learning model based on learner actions.

Keywords: aware, context, learning, mobile

Procedia PDF Downloads 234
4992 Routing Protocol in Ship Dynamic Positioning Based on WSN Clustering Data Fusion System

Authors: Zhou Mo, Dennis Chow

Abstract:

In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing protocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turn out to reduce the energy consumption of nodes and increase the efficiency of data delivery.

Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols

Procedia PDF Downloads 508
4991 Finding Related Scientific Documents Using Formal Concept Analysis

Authors: Nadeem Akhtar, Hira Javed

Abstract:

An important aspect of research is literature survey. Availability of a large amount of literature across different domains triggers the need for optimized systems which provide relevant literature to researchers. We propose a search system based on keywords for text documents. This experimental approach provides a hierarchical structure to the document corpus. The documents are labelled with keywords using KEA (Keyword Extraction Algorithm) and are automatically organized in a lattice structure using Formal Concept Analysis (FCA). This groups the semantically related documents together. The hierarchical structure, based on keywords gives out only those documents which precisely contain them. This approach open doors for multi-domain research. The documents across multiple domains which are indexed by similar keywords are grouped together. A hierarchical relationship between keywords is obtained. To signify the effectiveness of the approach, we have carried out the experiment and evaluation on Semeval-2010 Dataset. Results depict that the presented method is considerably successful in indexing of scientific papers.

Keywords: formal concept analysis, keyword extraction algorithm, scientific documents, lattice

Procedia PDF Downloads 314
4990 Design and Development of Fleet Management System for Multi-Agent Autonomous Surface Vessel

Authors: Zulkifli Zainal Abidin, Ahmad Shahril Mohd Ghani

Abstract:

Agent-based systems technology has been addressed as a new paradigm for conceptualizing, designing, and implementing software systems. Agents are sophisticated systems that act autonomously across open and distributed environments in solving problems. Nevertheless, it is impractical to rely on a single agent to do all computing processes in solving complex problems. An increasing number of applications lately require multiple agents to work together. A multi-agent system (MAS) is a loosely coupled network of agents that interact to solve problems that are beyond the individual capacities or knowledge of each problem solver. However, the network of MAS still requires a main system to govern or oversees the operation of the agents in order to achieve a unified goal. We had developed a fleet management system (FMS) in order to manage the fleet of agents, plan route for the agents, perform real-time data processing and analysis, and issue sets of general and specific instructions to the agents. This FMS should be able to perform real-time data processing, communicate with the autonomous surface vehicle (ASV) agents and generate bathymetric map according to the data received from each ASV unit. The first algorithm is developed to communicate with the ASV via radio communication using standard National Marine Electronics Association (NMEA) protocol sentences. Next, the second algorithm will take care of the path planning, formation and pattern generation is tested using various sample data. Lastly, the bathymetry map generation algorithm will make use of data collected by the agents to create bathymetry map in real-time. The outcome of this research is expected can be applied on various other multi-agent systems.

Keywords: autonomous surface vehicle, fleet management system, multi agent system, bathymetry

Procedia PDF Downloads 258
4989 Estimation of the Temperatures in an Asynchronous Machine Using Extended Kalman Filter

Authors: Yi Huang, Clemens Guehmann

Abstract:

In order to monitor the thermal behavior of an asynchronous machine with squirrel cage rotor, a 9th-order extended Kalman filter (EKF) algorithm is implemented to estimate the temperatures of the stator windings, the rotor cage and the stator core. The state-space equations of EKF are established based on the electrical, mechanical and the simplified thermal models of an asynchronous machine. The asynchronous machine with simplified thermal model in Dymola is compiled as DymolaBlock, a physical model in MATLAB/Simulink. The coolant air temperature, three-phase voltages and currents are exported from the physical model and are processed by EKF estimator as inputs. Compared to the temperatures exported from the physical model of the machine, three parts of temperatures can be estimated quite accurately by the EKF estimator. The online EKF estimator is independent from the machine control algorithm and can work under any speed and load condition if the stator current is nonzero current system.

Keywords: asynchronous machine, extended Kalman filter, resistance, simulation, temperature estimation, thermal model

Procedia PDF Downloads 272
4988 Long-Term Follow-Up of Dynamic Balance, Pain and Functional Performance in Cruciate Retaining, Posterior Stabilized Total Knee Arthroplasty

Authors: Ahmed R. Z. Baghdadi,  Mona H. Gamal Eldein

Abstract:

Background: With the perceived pain and poor function experienced following knee arthroplasty, patients usually feel unsatisfied. Yet, a controversy still persists on the appropriate operative technique that doesn’t affect proprioception much. Purpose: This study compared the effects of Cruciate Retaining (CR) and Posterior Stabilized (PS) total knee arthroplasty (TKA on dynamic balance, pain and functional performance following rehabilitation. Methods: Thirty patients with CRTKA (group I), thirty with PSTKA (group II) and fifteen indicated for arthroplasty but weren’t operated on yet (group III) participated in the study. The mean age was 54.53±3.44, 55.13±3.48 and 55.33±2.32 years and BMI 35.7±3.03, 35.7±1.99 and 35.73±1.03 kg/m2 for group I, II, and III respectively. The Berg Balance Scale (BBS), WOMAC pain subscale and Timed-Up-and-Go (TUG) and Stair-Climbing (SC) tests were used for assessment. Assessments were conducted four weeks pre- and post-operatively, three, six and twelve months post-operatively with the control group being assessed at the same time intervals. The post-operative rehabilitation involved hospitalization (1st week), home-based (2nd-4th weeks), and outpatient clinic (5th-12th weeks) programs, follow-up to all groups for twelve months. Results: The Mixed design MANOVA revealed that group I had significantly lower pain scores and SC time compared with group II three, six and twelve months post-operatively. Moreover, the BBS scores increased significantly and the pain scores and TUG and SC time decreased significantly six months post-operatively compared with four weeks pre- and post-operatively and three months post-operatively in group I and II with the opposite being true four weeks post-operatively. But no significant differences in BBS scores, pain scores and TUG and SC time between six and twelve months post-operatively in group I and II. Interpretation/Conclusion: CRTKA is preferable to PSTKA, possibly due to the preserved human proprioceptors in the un-excised PCL.

Keywords: dynamic balance, functional performance, knee arthroplasty, long-term

Procedia PDF Downloads 396
4987 Peril´s Environment of Energetic Infrastructure Complex System, Modelling by the Crisis Situation Algorithms

Authors: Jiří F. Urbánek, Alena Oulehlová, Hana Malachová, Jiří J. Urbánek Jr.

Abstract:

Crisis situations investigation and modelling are introduced and made within the complex system of energetic critical infrastructure, operating on peril´s environments. Every crisis situations and perils has an origin in the emergency/ crisis event occurrence and they need critical/ crisis interfaces assessment. Here, the emergency events can be expected - then crisis scenarios can be pre-prepared by pertinent organizational crisis management authorities towards their coping; or it may be unexpected - without pre-prepared scenario of event. But the both need operational coping by means of crisis management as well. The operation, forms, characteristics, behaviour and utilization of crisis management have various qualities, depending on real critical infrastructure organization perils, and prevention training processes. An aim is always - better security and continuity of the organization, which successful obtainment needs to find and investigate critical/ crisis zones and functions in critical infrastructure organization models, operating in pertinent perils environment. Our DYVELOP (Dynamic Vector Logistics of Processes) method is disposables for it. Here, it is necessary to derive and create identification algorithm of critical/ crisis interfaces. The locations of critical/ crisis interfaces are the flags of crisis situation in organization of critical infrastructure models. Then, the model of crisis situation will be displayed at real organization of Czech energetic crisis infrastructure subject in real peril environment. These efficient measures are necessary for the infrastructure protection. They will be derived for peril mitigation, crisis situation coping and for environmentally friendly organization survival, continuity and its sustainable development advanced possibilities.

Keywords: algorithms, energetic infrastructure complex system, modelling, peril´s environment

Procedia PDF Downloads 388
4986 Phantom and Clinical Evaluation of Block Sequential Regularized Expectation Maximization Reconstruction Algorithm in Ga-PSMA PET/CT Studies Using Various Relative Difference Penalties and Acquisition Durations

Authors: Fatemeh Sadeghi, Peyman Sheikhzadeh

Abstract:

Introduction: Block Sequential Regularized Expectation Maximization (BSREM) reconstruction algorithm was recently developed to suppress excessive noise by applying a relative difference penalty. The aim of this study was to investigate the effect of various strengths of noise penalization factor in the BSREM algorithm under different acquisition duration and lesion sizes in order to determine an optimum penalty factor by considering both quantitative and qualitative image evaluation parameters in clinical uses. Materials and Methods: The NEMA IQ phantom and 15 clinical whole-body patients with prostate cancer were evaluated. Phantom and patients were injected withGallium-68 Prostate-Specific Membrane Antigen(68 Ga-PSMA)and scanned on a non-time-of-flight Discovery IQ Positron Emission Tomography/Computed Tomography(PET/CT) scanner with BGO crystals. The data were reconstructed using BSREM with a β-value of 100-500 at an interval of 100. These reconstructions were compared to OSEM as a widely used reconstruction algorithm. Following the standard NEMA measurement procedure, background variability (BV), recovery coefficient (RC), contrast recovery (CR) and residual lung error (LE) from phantom data and signal-to-noise ratio (SNR), signal-to-background ratio (SBR) and tumor SUV from clinical data were measured. Qualitative features of clinical images visually were ranked by one nuclear medicine expert. Results: The β-value acts as a noise suppression factor, so BSREM showed a decreasing image noise with an increasing β-value. BSREM, with a β-value of 400 at a decreased acquisition duration (2 min/ bp), made an approximately equal noise level with OSEM at an increased acquisition duration (5 min/ bp). For the β-value of 400 at 2 min/bp duration, SNR increased by 43.7%, and LE decreased by 62%, compared with OSEM at a 5 min/bp duration. In both phantom and clinical data, an increase in the β-value is translated into a decrease in SUV. The lowest level of SUV and noise were reached with the highest β-value (β=500), resulting in the highest SNR and lowest SBR due to the greater noise reduction than SUV reduction at the highest β-value. In compression of BSREM with different β-values, the relative difference in the quantitative parameters was generally larger for smaller lesions. As the β-value decreased from 500 to 100, the increase in CR was 160.2% for the smallest sphere (10mm) and 12.6% for the largest sphere (37mm), and the trend was similar for SNR (-58.4% and -20.5%, respectively). BSREM visually was ranked more than OSEM in all Qualitative features. Conclusions: The BSREM algorithm using more iteration numbers leads to more quantitative accuracy without excessive noise, which translates into higher overall image quality and lesion detectability. This improvement can be used to shorter acquisition time.

Keywords: BSREM reconstruction, PET/CT imaging, noise penalization, quantification accuracy

Procedia PDF Downloads 80
4985 Dynamic Balance and Functional Performance in Total Hip Arthroplasty

Authors: Mahmoud Ghazy, Ahmed R. Z. Baghdadi

Abstract:

Background: With the perceived pain and poor function experienced following total hip Arthroplasty (THA), patients usually feel un-satisfied. Methods: Thirty patients with THA (group I) and thirty indicated for arthroplasty but weren’t operated on yet (group II) participated in the study. The mean age was 54.53±3.44 and 55.33±2.32 years and BMI 35.7±3.03 and 35.73±1.03 kg/m2 for group I and III respectively. The Berg Balance Scale (BBS), Timed Up-and-Go (TUG) and Stair-Climbing (SC) tests were used for assessment. Assessments were conducted four weeks pre- and post-operatively and three months post-operatively with the control group being assessed at the same time intervals. The post-operative rehabilitation involved hospitalization (1st week), home-based (2nd-4th weeks), and outpatient clinic (5th-12th weeks) programs. Results: group I had significantly lower TUG and SC time compared with group II four weeks and three months post-operatively. Moreover, the BBS scores increased significantly and the pain scores and TUG and SC time decreased significantly four weeks and three months post-operatively compared with four weeks pre- operatively in group. But no significant differences in BBS scores four weeks and three months post-operatively in group I compared with group II. Interpretation/Conclusion : Patients with THA still have defects in proprioception, so they needs more concentration on proprioception training.

Keywords: dynamic balance, functional performance, hip arthroplasty, total

Procedia PDF Downloads 358
4984 Building Scalable and Accurate Hybrid Kernel Mapping Recommender

Authors: Hina Iqbal, Mustansar Ali Ghazanfar, Sandor Szedmak

Abstract:

Recommender systems uses artificial intelligence practices for filtering obscure information and can predict if a user likes a specified item. Kernel mapping Recommender systems have been proposed which are accurate and state-of-the-art algorithms and resolve recommender system’s design objectives such as; long tail, cold-start, and sparsity. The aim of research is to propose hybrid framework that can efficiently integrate different versions— namely item-based and user-based KMR— of KMR algorithm. We have proposed various heuristic algorithms that integrate different versions of KMR (into a unified framework) resulting in improved accuracy and elimination of problems associated with conventional recommender system. We have tested our system on publically available movies dataset and benchmark with KMR. The results (in terms of accuracy, precision, recall, F1 measure and ROC metrics) reveal that the proposed algorithm is quite accurate especially under cold-start and sparse scenarios.

Keywords: Kernel Mapping Recommender Systems, hybrid recommender systems, cold start, sparsity, long tail

Procedia PDF Downloads 322
4983 Quantification and Evaluation of Tumors Heterogeneity Utilizing Multimodality Imaging

Authors: Ramin Ghasemi Shayan, Morteza Janebifam

Abstract:

Tumors are regularly inhomogeneous. Provincial varieties in death, metabolic action, multiplication and body part are watched. There’s expanding proof that strong tumors may contain subpopulations of cells with various genotypes and phenotypes. These unmistakable populaces of malignancy cells can connect during a serious way and may contrast in affectability to medications. Most tumors show organic heterogeneity1–3 remembering heterogeneity for genomic subtypes, varieties inside the statement of development variables and genius, and hostile to angiogenic factors4–9 and varieties inside the tumoural microenvironment. These can present as contrasts between tumors in a few people. for instance, O6-methylguanine-DNA methyltransferase, a DNA fix compound, is hushed by methylation of the quality advertiser in half of glioblastoma (GBM), adding to chemosensitivity, and improved endurance. From the outset, there includes been specific enthusiasm inside the usage of dissemination weighted imaging (DWI) and dynamic complexity upgraded MRI (DCE-MRI). DWI sharpens MRI to water dispersion inside the extravascular extracellular space (EES) and is wiped out with the size and setup of the cell populace. Additionally, DCE-MRI utilizes dynamic obtaining of pictures during and after the infusion of intravenous complexity operator. Signal changes are additionally changed to outright grouping of differentiation permitting examination utilizing pharmacokinetic models. PET scan modality gives one of a kind natural particularity, permitting dynamic or static imaging of organic atoms marked with positron emanating isotopes (for example, 15O, 18F, 11C). The strategy is explained to a colossal radiation portion, which points of confinement rehashed estimations, particularly when utilized together with PC tomography (CT). At long last, it's of incredible enthusiasm to quantify territorial hemoglobin state, which could be joined with DCE-CT vascular physiology estimation to create significant experiences for understanding tumor hypoxia.

Keywords: heterogeneity, computerized tomography scan, magnetic resonance imaging, PET

Procedia PDF Downloads 133
4982 Frequency Response of Complex Systems with Localized Nonlinearities

Authors: E. Menga, S. Hernandez

Abstract:

Finite Element Models (FEMs) are widely used in order to study and predict the dynamic properties of structures and usually, the prediction can be obtained with much more accuracy in the case of a single component than in the case of assemblies. Especially for structural dynamics studies, in the low and middle frequency range, most complex FEMs can be seen as assemblies made by linear components joined together at interfaces. From a modelling and computational point of view, these types of joints can be seen as localized sources of stiffness and damping and can be modelled as lumped spring/damper elements, most of time, characterized by nonlinear constitutive laws. On the other side, most of FE programs are able to run nonlinear analysis in time-domain. They treat the whole structure as nonlinear, even if there is one nonlinear degree of freedom (DOF) out of thousands of linear ones, making the analysis unnecessarily expensive from a computational point of view. In this work, a methodology in order to obtain the nonlinear frequency response of structures, whose nonlinearities can be considered as localized sources, is presented. The work extends the well-known Structural Dynamic Modification Method (SDMM) to a nonlinear set of modifications, and allows getting the Nonlinear Frequency Response Functions (NLFRFs), through an ‘updating’ process of the Linear Frequency Response Functions (LFRFs). A brief summary of the analytical concepts is given, starting from the linear formulation and understanding what the implications of the nonlinear one, are. The response of the system is formulated in both: time and frequency domain. First the Modal Database is extracted and the linear response is calculated. Secondly the nonlinear response is obtained thru the NL SDMM, by updating the underlying linear behavior of the system. The methodology, implemented in MATLAB, has been successfully applied to estimate the nonlinear frequency response of two systems. The first one is a two DOFs spring-mass-damper system, and the second example takes into account a full aircraft FE Model. In spite of the different levels of complexity, both examples show the reliability and effectiveness of the method. The results highlight a feasible and robust procedure, which allows a quick estimation of the effect of localized nonlinearities on the dynamic behavior. The method is particularly powerful when most of the FE Model can be considered as acting linearly and the nonlinear behavior is restricted to few degrees of freedom. The procedure is very attractive from a computational point of view because the FEM needs to be run just once, which allows faster nonlinear sensitivity analysis and easier implementation of optimization procedures for the calibration of nonlinear models.

Keywords: frequency response, nonlinear dynamics, structural dynamic modification, softening effect, rubber

Procedia PDF Downloads 256
4981 Numerical Investigation of Dynamic Stall over a Wind Turbine Pitching Airfoil by Using OpenFOAM

Authors: Mahbod Seyednia, Shidvash Vakilipour, Mehran Masdari

Abstract:

Computations for two-dimensional flow past a stationary and harmonically pitching wind turbine airfoil at a moderate value of Reynolds number (400000) are carried out by progressively increasing the angle of attack for stationary airfoil and at fixed pitching frequencies for rotary one. The incompressible Navier-Stokes equations in conjunction with Unsteady Reynolds Average Navier-Stokes (URANS) equations for turbulence modeling are solved by OpenFOAM package to investigate the aerodynamic phenomena occurred at stationary and pitching conditions on a NACA 6-series wind turbine airfoil. The aim of this study is to enhance the accuracy of numerical simulation in predicting the aerodynamic behavior of an oscillating airfoil in OpenFOAM. Hence, for turbulence modelling, k-ω-SST with low-Reynolds correction is employed to capture the unsteady phenomena occurred in stationary and oscillating motion of the airfoil. Using aerodynamic and pressure coefficients along with flow patterns, the unsteady aerodynamics at pre-, near-, and post-static stall regions are analyzed in harmonically pitching airfoil, and the results are validated with the corresponding experimental data possessed by the authors. The results indicate that implementing the mentioned turbulence model leads to accurate prediction of the angle of static stall for stationary airfoil and flow separation, dynamic stall phenomenon, and reattachment of the flow on the surface of airfoil for pitching one. Due to the geometry of the studied 6-series airfoil, the vortex on the upper surface of the airfoil during upstrokes is formed at the trailing edge. Therefore, the pattern flow obtained by our numerical simulations represents the formation and change of the trailing-edge vortex at near- and post-stall regions where this process determines the dynamic stall phenomenon.

Keywords: CFD, moderate Reynolds number, OpenFOAM, pitching oscillation, unsteady aerodynamics, wind turbine

Procedia PDF Downloads 188
4980 Integration of Climatic Factors in the Meta-Population Modelling of the Dynamic of Malaria Transmission, Case of Douala and Yaoundé, Two Cities of Cameroon

Authors: Justin-Herve Noubissi, Jean Claude Kamgang, Eric Ramat, Januarius Asongu, Christophe Cambier

Abstract:

The goal of our study is to analyse the impact of climatic factors in malaria transmission taking into account migration between Douala and Yaoundé, two cities of Cameroon country. We show how variations of climatic factors such as temperature and relative humidity affect the malaria spread. We propose a meta-population model of the dynamic transmission of malaria that evolves in space and time and that takes into account temperature and relative humidity and the migration between Douala and Yaoundé. We also integrate the variation of environmental factors as events also called mathematical impulsion that can disrupt the model evolution at any time. Our modelling has been done using the Discrete EVents System Specification (DEVS) formalism. Our implementation has been done on Virtual Laboratory Environment (VLE) that uses DEVS formalism and abstract simulators for coupling models by integrating the concept of DEVS.

Keywords: compartmental models, DEVS, discrete events, meta-population model, VLE

Procedia PDF Downloads 543
4979 A Review on Applications of Evolutionary Algorithms to Reservoir Operation for Hydropower Production

Authors: Nkechi Neboh, Josiah Adeyemo, Abimbola Enitan, Oludayo Olugbara

Abstract:

Evolutionary algorithms are techniques extensively used in the planning and management of water resources and systems. It is useful in finding optimal solutions to water resources problems considering the complexities involved in the analysis. River basin management is an essential area that involves the management of upstream, river inflow and outflow including downstream aspects of a reservoir. Water as a scarce resource is needed by human and the environment for survival and its management involve a lot of complexities. Management of this scarce resource is necessary for proper distribution to competing users in a river basin. This presents a lot of complexities involving many constraints and conflicting objectives. Evolutionary algorithms are very useful in solving this kind of complex problems with ease. Evolutionary algorithms are easy to use, fast and robust with many other advantages. Many applications of evolutionary algorithms, which are population based search algorithm, are discussed. Different methodologies involved in the modeling and simulation of water management problems in river basins are explained. It was found from this work that different evolutionary algorithms are suitable for different problems. Therefore, appropriate algorithms are suggested for different methodologies and applications based on results of previous studies reviewed. It is concluded that evolutionary algorithms, with wide applications in water resources management, are viable and easy algorithms for most of the applications. The results suggested that evolutionary algorithms, applied in the right application areas, can suggest superior solutions for river basin management especially in reservoir operations, irrigation planning and management, stream flow forecasting and real-time applications. The future directions in this work are suggested. This study will assist decision makers and stakeholders on the best evolutionary algorithm to use in varied optimization issues in water resources management.

Keywords: evolutionary algorithm, multi-objective, reservoir operation, river basin management

Procedia PDF Downloads 473
4978 Research on Routing Protocol in Ship Dynamic Positioning Based on WSN Clustering Data Fusion System

Authors: Zhou Mo, Dennis Chow

Abstract:

In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing pro-tocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turns out to reduce the energy consumption of nodes and increase the efficiency of data delivery.

Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols

Procedia PDF Downloads 433
4977 Automatic Classification of Periodic Heart Sounds Using Convolutional Neural Network

Authors: Jia Xin Low, Keng Wah Choo

Abstract:

This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.

Keywords: convolutional neural network, discrete wavelet transform, deep learning, heart sound classification

Procedia PDF Downloads 332
4976 A Novel Combined Finger Counting and Finite State Machine Technique for ASL Translation Using Kinect

Authors: Rania Ahmed Kadry Abdel Gawad Birry, Mohamed El-Habrouk

Abstract:

This paper presents a brief survey of the techniques used for sign language recognition along with the types of sensors used to perform the task. It presents a modified method for identification of an isolated sign language gesture using Microsoft Kinect with the OpenNI framework. It presents the way of extracting robust features from the depth image provided by Microsoft Kinect and the OpenNI interface and to use them in creating a robust and accurate gesture recognition system, for the purpose of ASL translation. The Prime Sense’s Natural Interaction Technology for End-user - NITE™ - was also used in the C++ implementation of the system. The algorithm presents a simple finger counting algorithm for static signs as well as directional Finite State Machine (FSM) description of the hand motion in order to help in translating a sign language gesture. This includes both letters and numbers performed by a user, which in-turn may be used as an input for voice pronunciation systems.

Keywords: American sign language, finger counting, hand tracking, Microsoft Kinect

Procedia PDF Downloads 279
4975 Theory of Constraints: Approach for Performance Enhancement and Boosting Overhaul Activities

Authors: Sunil Dutta

Abstract:

Synchronization is defined as ‘the sequencing and re-sequencing of all relative and absolute activities in time and space and continuous alignment of those actions with purposeful objective in a complex and dynamic atmosphere. In a complex and dynamic production / maintenance setup, no single group can work in isolation for long. In addition, many activities in projects take place simultaneously at the same time. Work of every section / group is interwoven with work of others. The various activities / interactions which take place in production / overhaul workshops are interlinked because of physical requirements (information, material, workforces, equipment, and space) and dependencies. The activity sequencing is determined by physical dependencies of various department / sections / units (e.g., inventory availability must be ensured before stripping and disassembling of equipment), whereas resource dependencies do not. Theory of constraint facilitates identification, analyses and exploitation of the constraint in methodical manner. These constraints (equipment, manpower, policies etc.) prevent the department / sections / units from getting optimum exploitation of available resources. The significance of theory of constraints for achieving synchronization at overhaul workshop is illustrated in this paper.

Keywords: synchronization, overhaul, throughput, obsolescence, uncertainty

Procedia PDF Downloads 334
4974 Dynamic Analysis of Commodity Price Fluctuation and Fiscal Management in Sub-Saharan Africa

Authors: Abidemi C. Adegboye, Nosakhare Ikponmwosa, Rogers A. Akinsokeji

Abstract:

For many resource-rich developing countries, fiscal policy has become a key tool used for short-run fiscal management since it is considered as playing a critical role in injecting part of resource rents into the economies. However, given its instability, reliance on revenue from commodity exports renders fiscal management, budgetary planning and the efficient use of public resources difficult. In this study, the linkage between commodity prices and fiscal operations among a sample of commodity-exporting countries in sub-Saharan Africa (SSA) is investigated. The main question is whether commodity price fluctuations affects the effectiveness of fiscal policy as a macroeconomic stabilization tool in these countries. Fiscal management effectiveness is considered as the ability of fiscal policy to react countercyclically to output gaps in the economy. Fiscal policy is measured as the ratio of fiscal deficit to GDP and the ratio of government spending to GDP, output gap is measured as a Hodrick-Prescott filter of output growth for each country, while commodity prices are associated with each country based on its main export commodity. Given the dynamic nature of fiscal policy effects on the economy overtime, a dynamic framework is devised for the empirical analysis. The panel cointegration and error correction methodology is used to explain the relationships. In particular, the study employs the panel ECM technique to trace short-term effects of commodity prices on fiscal management and also uses the fully modified OLS (FMOLS) technique to determine the long run relationships. These procedures provide sufficient estimation of the dynamic effects of commodity prices on fiscal policy. Data used cover the period 1992 to 2016 for 11 SSA countries. The study finds that the elasticity of the fiscal policy measures with respect to the output gap is significant and positive, suggesting that fiscal policy is actually procyclical among the countries in the sample. This implies that fiscal management for these countries follows the trend of economic performance. Moreover, it is found that fiscal policy has not performed well in delivering macroeconomic stabilization for these countries. The difficulty in applying fiscal stabilization measures is attributable to the unstable revenue inflows due to the highly volatile nature of commodity prices in the international market. For commodity-exporting countries in SSA to improve fiscal management, therefore, fiscal planning should be largely decoupled from commodity revenues, domestic revenue bases must be improved, and longer period perspectives in fiscal policy management are the critical suggestions in this study.

Keywords: commodity prices, ECM, fiscal policy, fiscal procyclicality, fully modified OLS, sub-saharan africa

Procedia PDF Downloads 147
4973 Assessment of Drug Delivery Systems from Molecular Dynamic Perspective

Authors: M. Rahimnejad, B. Vahidi, B. Ebrahimi Hoseinzadeh, F. Yazdian, P. Motamed Fath, R. Jamjah

Abstract:

In this study, we developed and simulated nano-drug delivery systems efficacy in compare to free drug prescription. Computational models can be utilized to accelerate experimental steps and control the experiments high cost. Molecular dynamics simulation (MDS), in particular NAMD was utilized to better understand the anti-cancer drug interaction with cell membrane model. Paclitaxel (PTX) and dipalmitoylphosphatidylcholine (DPPC) were selected for the drug molecule and as a natural phospholipid nanocarrier, respectively. This work focused on two important interaction parameters between molecules in terms of center of mass (COM) and van der Waals interaction energy. Furthermore, we compared the simulation results of the PTX interaction with the cell membrane and the interaction of DPPC as a nanocarrier loaded by the drug with the cell membrane. The molecular dynamic analysis resulted in low energy between the nanocarrier and the cell membrane as well as significant decrease of COM amount in the nanocarrier and the cell membrane system during the interaction. Thus, the drug vehicle showed notably better interaction with the cell membrane in compared to free drug interaction with the cell membrane.

Keywords: anti-cancer drug, center of mass, interaction energy, molecular dynamics simulation, nanocarrier

Procedia PDF Downloads 322
4972 Registration of Multi-Temporal Unmanned Aerial Vehicle Images for Facility Monitoring

Authors: Dongyeob Han, Jungwon Huh, Quang Huy Tran, Choonghyun Kang

Abstract:

Unmanned Aerial Vehicles (UAVs) have been used for surveillance, monitoring, inspection, and mapping. In this paper, we present a systematic approach for automatic registration of UAV images for monitoring facilities such as building, green house, and civil structures. The two-step process is applied; 1) an image matching technique based on SURF (Speeded up Robust Feature) and RANSAC (Random Sample Consensus), 2) bundle adjustment of multi-temporal images. Image matching to find corresponding points is one of the most important steps for the precise registration of multi-temporal images. We used the SURF algorithm to find a quick and effective matching points. RANSAC algorithm was used in the process of finding matching points between images and in the bundle adjustment process. Experimental results from UAV images showed that our approach has a good accuracy to be applied to the change detection of facility.

Keywords: building, image matching, temperature, unmanned aerial vehicle

Procedia PDF Downloads 278
4971 Effect of Nano-Alumina on the Mechanical Properties of Cold Recycled Asphalt

Authors: Shahab Hasani Nasab, Aran Aeini, Navid Kermanshahi

Abstract:

In order to reduce road building costs and reduce environmental damage, recycled materials can be used instead of mineral materials in the production of asphalt mixtures. Today, in most parts of the world, cold recycled asphalt with bitumen emulsion, has acceptable results. However, Cold Recycled Asphalt have some deficiency such as stripping, thermal cracking, and rutting. This requires the addition of additives to reduce this deficiency of recycled pavement with emulsified asphalt. In this research, nano-alumina and emulsified asphalt were used to modify the properties of recycled asphalt mixtures according to the technical specifications and the operation of cold recycling. Marshall test methods, dynamic creep test, and resiliency modulus test has been used to obtain the nano-alumina’s effects on asphalt mixture properties. The results show that the addition of nano-alumina would reduce the Marshall stability in samples but increases the rutting resistance. The resiliency modulus increases significantly with this additive.

Keywords: cold asphalt, cold recycling, nano-alumina, dynamic creep, bitumen emulsion

Procedia PDF Downloads 147
4970 Predicting Emerging Agricultural Investment Opportunities: The Potential of Structural Evolution Index

Authors: Kwaku Damoah

Abstract:

The agricultural sector is characterized by continuous transformation, driven by factors such as demographic shifts, evolving consumer preferences, climate change, and migration trends. This dynamic environment presents complex challenges for key stakeholders including farmers, governments, and investors, who must navigate these changes to achieve optimal investment returns. To effectively predict market trends and uncover promising investment opportunities, a systematic, data-driven approach is essential. This paper introduces the Structural Evolution Index (SEI), a machine learning-based methodology. SEI is specifically designed to analyse long-term trends and forecast the potential of emerging agricultural products for investment. Versatile in application, it evaluates various agricultural metrics such as production, yield, trade, land use, and consumption, providing a comprehensive view of the evolution within agricultural markets. By harnessing data from the UN Food and Agricultural Organisation (FAOSTAT), this study demonstrates the SEI's capabilities through Comparative Exploratory Analysis and evaluation of international trade in agricultural products, focusing on Malaysia and Singapore. The SEI methodology reveals intricate patterns and transitions within the agricultural sector, enabling stakeholders to strategically identify and capitalize on emerging markets. This predictive framework is a powerful tool for decision-makers, offering crucial insights that help anticipate market shifts and align investments with anticipated returns.

Keywords: agricultural investment, algorithm, comparative exploratory analytics, machine learning, market trends, predictive analytics, structural evolution index

Procedia PDF Downloads 47
4969 Physical and Mechanical Characterization of Limestone in the Quarry of Meftah (Algeria)

Authors: Khaled Benyounes

Abstract:

Determination of the rock mechanical properties such as unconfined compressive strength UCS, Young’s modulus E, and tensile strength by the Brazilian test Rtb is considered to be the most important component in drilling and mining engineering project. Research related to establishing correlation between strength and physical parameters of rocks has always been of interest to mining and reservoir engineering. For this, many rock blocks of limestone were collected from the quarry located in Meftah (Algeria), the cores were crafted in the laboratory using a core drill. This work examines the relationships between mechanical properties and some physical properties of limestone. Many empirical equations are established between UCS and physical properties of limestone (such as dry bulk density, velocity of P-waves, dynamic Young’s modulus, alteration index, and total porosity). Other correlations, UCS - tensile strength, dynamic Young’s modulus - static Young’s modulus have been find. Based on the Mohr-Coulomb failure criterion, we were able to establish mathematical relationships that will allow estimating the cohesion and internal friction angle from UCS and indirect tensile strength. Results from this study can be useful for mining industry for resolve range of geomechanical problems such as slope stability.

Keywords: limestone, mechanical strength, Young’s modulus, porosity

Procedia PDF Downloads 624