Search results for: dimensional model

Authors: Abdelrahman Elsehsah, Hany Madkour, Khalid Farah

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This article presents a 3-D modified non-linear elastic model in the strain space. The Helmholtz free energy function is introduced with the existence of a dissipation potential surface in the space of thermodynamic conjugate forces. The constitutive equation and the damage evolution were derived as well. The modified damage has been examined to model the nonlinear behavior of reinforced concrete (RC) slabs with an opening. A parametric study with RC was carried out to investigate the impact of different factors on the behavior of RC slabs. These factors are the opening area, the opening shape, the place of opening, and the thickness of the slabs. And the numerical results have been compared with the experimental data from literature. Finally, the model showed its ability to be applied to the structural analysis of RC slabs.

Keywords: damage mechanics, 3-D numerical analysis, RC, slab with opening

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Authors: Isobel M. Thompson, Dorian Audot, Dominic Hudson, Martin Warner, Joseph Banks

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Underwater fly kick is an essential skill in swimming, which can have a considerable impact upon overall race performance in competition, especially in sprint events. Reduced wave drags acting upon the body under the surface means that the underwater fly kick will potentially be the fastest the swimmer is travelling throughout the race. It is therefore critical to understand fly kicking techniques and determining biomechanical factors involved in the performance. Most previous studies assessing fly kick kinematics have focused on two-dimensional analysis; therefore, the three-dimensional elements of the underwater fly kick techniques are not well understood. Those studies that have investigated fly kicking techniques using three-dimensional methodologies have not reported full three-dimensional kinematics for the techniques observed, choosing to focus on one or two joints. There has not been a direct comparison completed on the results obtained using two-dimensional and three-dimensional analysis, and how these different approaches might affect the interpretation of subsequent results. The aim of this research is to quantify the differences in kinematics observed in underwater fly kicks obtained from both two and three-dimensional analyses of the same test conditions. In order to achieve this, a six-camera underwater Qualisys system was used to develop an experimental methodology suitable for assessing the kinematics of swimmer’s starts and turns. The cameras, capturing at a frequency of 100Hz, were arranged along the side of the pool spaced equally up to 20m creating a capture volume of 7m x 2m x 1.5m. Within the measurement volume, error levels were estimated at 0.8%. Prior to pool trials, participants completed a landside calibration in order to define joint center locations, as certain markers became occluded once the swimmer assumed the underwater fly kick position in the pool. Thirty-four reflective markers were placed on key anatomical landmarks, 9 of which were then removed for the pool-based trials. The fly-kick swimming conditions included in the analysis are as follows: maximum effort prone, 100m pace prone, 200m pace prone, 400m pace prone, and maximum pace supine. All trials were completed from a push start to 15m to ensure consistent kick cycles were captured. Both two-dimensional and three-dimensional kinematics are calculated from joint locations, and the results are compared. Key variables reported include kick frequency and kick amplitude, as well as full angular kinematics of the lower body. Key differences in these variables obtained from two-dimensional and three-dimensional analysis are identified. Internal rotation (up to 15º) and external rotation (up to -28º) were observed using three-dimensional methods. Abduction (5º) and adduction (15º) were also reported. These motions are not observed in the two-dimensional analysis. Results also give an indication of different techniques adopted by swimmers at various paces and orientations. The results of this research provide evidence of the strengths of both two dimensional and three dimensional motion capture methods in underwater fly kick, highlighting limitations which could affect the interpretation of results from both methods.

Keywords: swimming, underwater fly kick, performance, motion capture

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Authors: Kazuki Kamada, Haruka Yamashita

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In Japan, taxi is one of the popular transportations and taxi industry is one of the big businesses. However, in recent years, there has been a difficult problem of reducing the number of taxi drivers. In the taxi business, mainly three passenger catching methods are applied. One style is "cruising" that drivers catches passengers while driving on a road. Second is "waiting" that waits passengers near by the places with many requirements for taxies such as entrances of hospitals, train stations. The third one is "dispatching" that is allocated based on the contact from the taxi company. Above all, the cruising taxi drivers need the experience and intuition for finding passengers, and it is difficult to decide "the destination for cruising". The strong recommendation system for the cruising taxies supports the new drivers to find passengers, and it can be the solution for the decreasing the number of drivers in the taxi industry. In this research, we propose a method of recommending a destination for cruising taxi drivers. On the other hand, as a machine learning technique, the embedding models that embed the high dimensional data to a low dimensional space is widely used for the data analysis, in order to represent the relationship of the meaning between the data clearly. Taxi drivers have their favorite courses based on their experiences, and the courses are different for each driver. We assume that the course of cruising taxies has meaning such as the course for finding business man passengers (go around the business area of the city of go to main stations) and course for finding traveler passengers (go around the sightseeing places or big hotels), and extract the meaning of their destinations. We analyze the cruising history data of taxis based on the embedding model and propose the recommendation system for passengers. Finally, we demonstrate the recommendation of destinations for cruising taxi drivers based on the real-world data analysis using proposing method.

Keywords: taxi industry, decision making, recommendation system, embedding model

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Authors: Yongxu Fu, Shaolong Wan

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We study the band degeneracy, defectiveness, as well as exceptional points of non-Hermitian systems and materials analytically. We elaborate on the energy bands, the band degeneracy, and the defectiveness of eigenstates under open boundary conditions based on developing a general theory of one-dimensional (1D) non-Hermitian systems. We research the presence of the exceptional points in a generalized non-Hermitian Su-Schrieffer-Heeger model under open boundary conditions. Beyond our general theory, there exist infernal points in 1D non-Hermitian systems, where the energy spectra under open boundary conditions converge on some discrete energy values. We study two 1D non-Hermitian models with the existence of infernal points. We generalize the infernal points to the infernal knots in four-dimensional non-Hermitian systems.

Keywords: non-hermitian, degeneracy, defectiveness, exceptional points, infernal points

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Authors: Nicolò Vaiana, Filip C. Filippou, Giorgio Serino

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The solution of the nonlinear dynamic equilibrium equations of base-isolated structures adopting a conventional monolithic solution approach, i.e. an implicit single-step time integration method employed with an iteration procedure, and the use of existing nonlinear analytical models, such as differential equation models, to simulate the dynamic behavior of seismic isolators can require a significant computational effort. In order to reduce numerical computations, a partitioned solution method and a one dimensional nonlinear analytical model are presented in this paper. A partitioned solution approach can be easily applied to base-isolated structures in which the base isolation system is much more flexible than the superstructure. Thus, in this work, the explicit conditionally stable central difference method is used to evaluate the base isolation system nonlinear response and the implicit unconditionally stable Newmark’s constant average acceleration method is adopted to predict the superstructure linear response with the benefit in avoiding iterations in each time step of a nonlinear dynamic analysis. The proposed mathematical model is able to simulate the dynamic behavior of seismic isolators without requiring the solution of a nonlinear differential equation, as in the case of widely used differential equation model. The proposed mixed explicit-implicit time integration method and nonlinear exponential model are adopted to analyze a three dimensional seismically isolated structure with a lead rubber bearing system subjected to earthquake excitation. The numerical results show the good accuracy and the significant computational efficiency of the proposed solution approach and analytical model compared to the conventional solution method and mathematical model adopted in this work. Furthermore, the low stiffness value of the base isolation system with lead rubber bearings allows to have a critical time step considerably larger than the imposed ground acceleration time step, thus avoiding stability problems in the proposed mixed method.

Keywords: base-isolated structures, earthquake engineering, mixed time integration, nonlinear exponential model

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Authors: Nicholas D. Assimakis

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In linear estimation, the traditional Kalman filter uses the Kalman filter gain in order to produce estimation and prediction of the n-dimensional state vector using the m-dimensional measurement vector. The computation of the Kalman filter gain requires the inversion of an m x m matrix in every iteration. In this paper, a variation of the Kalman filter eliminating the Kalman filter gain is proposed. In the time varying case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix and the inversion of an m x m matrix in every iteration. In the time invariant case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix in every iteration. The proposed Kalman filter gain elimination algorithm may be faster than the conventional Kalman filter, depending on the model dimensions.

Keywords: discrete time, estimation, Kalman filter, Kalman filter gain

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Authors: Bharat Singh Om Prakash Vyas

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Now a day’s applications deal with High Dimensional Data have tremendously used in the popular areas. To tackle with such kind of data various approached has been developed by researchers in the last few decades. To tackle with such kind of data various approached has been developed by researchers in the last few decades. One of the problems with the NMF approaches, its randomized valued could not provide absolute optimization in limited iteration, but having local optimization. Due to this, we have proposed a new approach that considers the initial values of the decomposition to tackle the issues of computationally expensive. We have devised an algorithm for initializing the values of the decomposed matrix based on the PSO (Particle Swarm Optimization). Through the experimental result, we will show the proposed method converse very fast in comparison to other row rank approximation like simple NMF multiplicative, and ACLS techniques.

Keywords: ALS, NMF, high dimensional data, RMSE

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Authors: Tarek M. Alguhane, Ayman H. Khalil, Nour M. Fayed, Ayman M. Ismail

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An existing RC building in Madinah is seismically evaluated with and without infill wall. Four model systems have been considered i. e. model I (no infill), model IIA (strut infill-update from field test), model IIB (strut infill- ASCE/SEI 41) and model IIC (strut infill-Soft storey-ASCE/SEI 41). Three dimensional pushover analyses have been carried out using SAP 2000 software incorporating inelastic material behavior for concrete, steel and infill walls. Infill wall has been modeled as equivalent strut according to suggested equation matching field test measurements and to the ASCE/SEI 41 equation. The effect of building modeling on the performance point as well as capacity and demand spectra due to EQ design spectrum function in Madinah area has been investigated. The response modification factor (R) for the 5 story RC building is evaluated from capacity and demand spectra (ATC-40) for the studied models. The results are summarized and discussed.

Keywords: infill wall, pushover analysis, response modification factor, seismic assessment

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Authors: Mohammad Ahmad, Dayalan Kasilingam

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In this paper, a spectral domain implementation of the fast multipole method is presented. It is shown that the aggregation, translation, and disaggregation stages of the fast multipole method (FMM) can be performed using the spectral domain (SD) analysis. The spectral domain fast multipole method (SD-FMM) has the advantage of eliminating the near field/far field classification used in conventional FMM formulation. The study focuses on the application of SD-FMM to one-dimensional (1D) and two-dimensional (2D) electric field integral equation (EFIE). The case of perfectly conducting strip, circular and square cylinders are numerically analyzed and compared with the results from the standard method of moments (MoM).

Keywords: electric field integral equation, fast multipole method, method of moments, wave scattering, spectral domain

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Authors: Mahzabin Afroz, Indubhushan Patnaikuni, Srikanth Venkatesan

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It is well-known that fly ash can be used in high volume as a partial replacement of cement to get beneficial effects on concrete. High volume fly ash (HVFA) concrete is currently emerging as a popular option to strengthen by fiber. Although studies have supported the use of fibers with fly ash, a unified model along with the incorporation into finite element software package to estimate the maximum flexural loads need to be developed. In this study, nonlinear finite element analysis of steel fiber reinforced high strength HVFA concrete beam under static loadings was conducted to investigate their failure modes in terms of ultimate load. First of all, the experimental investigation of mechanical properties of high strength HVFA concrete was done and validates with developed numerical model with the appropriate modeling of element size and mesh by ANSYS 16.2. To model the fiber within the concrete, three-dimensional random fiber distribution was simulated by spherical coordinate system. Three types of high strength HVFA concrete beams were analyzed reinforced with 0.5, 1 and 1.5% volume fractions of steel fibers with specific mechanical and physical properties. The result reveals that the use of nonlinear finite element analysis technique and three-dimensional random fiber orientation exhibited fairly good agreement with the experimental results of flexural strength, load deflection and crack propagation mechanism. By utilizing this improved model, it is possible to determine the flexural behavior of different types and proportions of steel fiber reinforced HVFA concrete beam under static load. So, this paper has the originality to predict the flexural properties of steel fiber reinforced high strength HVFA concrete by numerical simulations.

Keywords: finite element analysis, high volume fly ash, steel fibers, spherical coordinate system

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Authors: S. Zhuiykov, Z. Wei

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Conformal defect-free two-dimensional (2D) WO₃ and TiO₂ semiconductors have been developed by the atomic layer deposition (ALD) technique on wafer scale with unique approach to the thickness control with precision of ± 10% from the monolayer of nanomaterial (less than 1.0 nm thick) to the nano-layered 2D structures with thickness of ~3.0-7.0 nm. Developed 2D nanostructures exhibited unique, distinguishable properties at nanoscale compare to their thicker counterparts. Specifically, 2D TiO₂-Au bilayer demonstrated improved photocatalytic degradation of palmitic acid under UV and visible light illumination. Improved functional capabilities of 2D semiconductors would be advantageous to various environmental, nano-energy and bio-sensing applications. The ALD-enabled approach is proven to be versatile, scalable and applicable to the broader range of 2D semiconductors.

Keywords: two-dimensional (2D) semiconductors, ALD, WO₃, TiO₂, wafer scale

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Authors: Scott M. Black, Craig Maclean, Pauline Hall Barrientos, Konstantinos Ritos, Asimina Kazakidi

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Aortic aneurysms and dissections are leading causes of death in cardiovascular disease. Both inevitably lead to hemodynamic instability without surgical intervention in the form of vascular stent-graft deployment. An accurate description of the aortic geometry and blood flow in patient-specific cases is vital for treatment planning and long-term success of such grafts, as they must generate physiological branch perfusion and in-stent hemodynamics. The aim of this study was to create patient-specific computational fluid dynamics (CFD) models through a multi-modality, multi-dimensional approach with boundary condition optimization to predict branch flow rates and in-stent hemodynamics in custom stent-graft configurations. Three-dimensional (3D) thoracoabdominal aortae were reconstructed from four-dimensional flow-magnetic resonance imaging (4D Flow-MRI) and computed tomography (CT) medical images. The former employed a novel approach to generate and enhance vessel lumen contrast via through-plane velocity at discrete, user defined cardiac time steps post-hoc. To produce patient-specific boundary conditions (BCs), the aortic geometry was reduced to a one-dimensional (1D) model. Thereafter, a zero-dimensional (0D) 3-Element Windkessel model (3EWM) was coupled to each terminal branch to represent the distal vasculature. In this coupled 0D-1D model, the 3EWM parameters were optimized to yield branch flow waveforms which are representative of the 4D Flow-MRI-derived in-vivo data. Thereafter, a 0D-3D CFD model was created, utilizing the optimized 3EWM BCs and a 4D Flow-MRI-obtained inlet velocity profile. A sensitivity analysis on the effects of stent-graft configuration and BC parameters was then undertaken using multiple stent-graft configurations and a range of distal vasculature conditions. 4D Flow-MRI granted unparalleled visualization of blood flow throughout the cardiac cycle in both the pre- and postsurgical states. Segmentation and reconstruction of healthy and stented regions from retrospective 4D Flow-MRI images also generated 3D models with geometries which were successfully validated against their CT-derived counterparts. 0D-1D coupling efficiently captured branch flow and pressure waveforms, while 0D-3D models also enabled 3D flow visualization and quantification of clinically relevant hemodynamic parameters for in-stent thrombosis and graft limb occlusion. It was apparent that changes in 3EWM BC parameters had a pronounced effect on perfusion distribution and near-wall hemodynamics. Results show that the 3EWM parameters could be iteratively changed to simulate a range of graft limb diameters and distal vasculature conditions for a given stent-graft to determine the optimal configuration prior to surgery. To conclude, this study outlined a methodology to aid in the prediction post-surgical branch perfusion and in-stent hemodynamics in patient specific cases for the implementation of custom stent-grafts.

Keywords: 4D flow-MRI, computational fluid dynamics, vascular stent-grafts, windkessel

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Authors: Petter Eklund, Jonathan Sjölund, Sandra Eriksson, Mats Leijon

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The spoke type rotor can be used to obtain magnetic flux concentration in permanent magnet machines. This allows the air gap magnetic flux density to exceed the remanent flux density of the permanent magnets but gives problems with leakage fluxes in the magnetic circuit. The end leakage flux of one spoke type permanent magnet rotor design is studied through measurements and finite element simulations. The measurements are performed in the end regions of a 12 kW prototype generator for a vertical axis wind turbine. The simulations are made using three dimensional finite elements to calculate the magnetic field distribution in the end regions of the machine. Also two dimensional finite element simulations are performed and the impact of the two dimensional approximation is studied. It is found that the magnetic leakage flux in the end regions of the machine is equal to about 20% of the flux in the permanent magnets. The overestimation of the performance by the two dimensional approximation is quantified and a curve-fitted expression for its behavior is suggested.

Keywords: end effects, end leakage flux, permanent magnet machine, spoke type rotor

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Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang

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Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.

Keywords: t-SNE, UMAP, fashion MNIST, neural networks

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Authors: Lyka Selene Magnayi, Marcos Vinas, Roseanne Ramos

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As the real estate industry continually grows in the Philippines, Geographic Information Systems (GIS) provide advantages in generating spatial databases for efficient delivery of information and services. The real estate sector is not only providing qualitative data about real estate properties but also utilizes various spatial aspects of these properties for different applications such as hazard mapping and assessment. In this study, a three-dimensional (3D) model and a spatial database of real estate properties in Fort Bonifacio, Taguig City are developed using GIS and SketchUp. Spatial datasets include political boundaries, buildings, road network, digital terrain model (DTM) derived from Interferometric Synthetic Aperture Radar (IFSAR) image, Google Earth satellite imageries, and hazard maps. Multiple model layers were created based on property listings by a partner real estate company, including existing and future property buildings. Actual building dimensions, building facade, and building floorplans are incorporated in these 3D models for geovisualization. Hazard model layers are determined through spatial overlays, and different scenarios of hazards are also presented in the models. Animated maps and walkthrough videos were created for company presentation and evaluation. Model evaluation is conducted through client surveys requiring scores in terms of the appropriateness, information content, and design of the 3D models. Survey results show very satisfactory ratings, with the highest average evaluation score equivalent to 9.21 out of 10. The output maps and videos obtained passing rates based on the criteria and standards set by the intended users of the partner real estate company. The methodologies presented in this study were found useful and have remarkable advantages in the real estate industry. This work may be extended to automated mapping and creation of online spatial databases for better storage, access of real property listings and interactive platform using web-based GIS.

Keywords: geovisualization, geographic information systems, GIS, real estate, spatial database, three-dimensional model

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Authors: Abdullah Eqal Al Mazrooei

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In this work, a new nonlinear model will be introduced. The model is in the state-space form. The nonlinearity of this model is in the state equation where the state vector is multiplied by its self. This technique makes our model generalizes many famous models as Lotka-Volterra model and Lorenz model which have many applications in the real life. We will apply our new model to estimate the wind speed by using a new nonlinear estimator which suitable to work with our model.

Keywords: nonlinear systems, state-space model, Kronecker product, nonlinear estimator

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Authors: Y. Galerkin, K. Soldatova, A. Drozdov

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The 6th version of Universal modeling method for centrifugal compressor stage calculation is described. Identification of the new mathematical model was made. As a result of identification the uniform set of empirical coefficients is received. The efficiency definition error is 0,86 % at a design point. The efficiency definition error at five flow rate points (except a point of the maximum flow rate) is 1,22 %. Several variants of the stage with 3D impellers designed by 6th version program and quasi three-dimensional calculation programs were compared by their gas dynamic performances CFD (NUMECA FINE TURBO). Performance comparison demonstrated general principles of design validity and leads to some design recommendations.

Keywords: compressor design, loss model, performance prediction, test data, model stages, flow rate coefficient, work coefficient

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Authors: O. D. Arbeláez-Echeverri, E. Restrepo-Parra, J. C. Riano-Rojas

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A two dimensional geometric model of Bit Patterned Media is proposed, the model is based on the crystal structure of the materials commonly used to produce the nano islands in bit patterned materials and the possible defects that may arise from the interaction between the nano islands and the matrix material. The dynamic magnetic properties of the material are then computed using time aware integration methods for the multi spin Hamiltonian. The Hamiltonian takes into account both the spatial and topological disorder of the sample as well as the high perpendicular anisotropy that is pursued when building bit patterned media. The main finding of the research was the possibility of replicating the results of previous experiments on similar materials and the ability of computing the switching field distribution given the geometry of the material and the parameters required by the model.

Keywords: nanostructures, Monte Carlo, pattern media, magnetic properties

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

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Authors: Ligia Florio, João Mauricio Castaldelli-Maia

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Background: Food addiction (FA) emerged in the 1990s as a possible contributor to the increasing prevalence of obesity and overweight, in conjunction with changing food environments and mental health conditions. However, FA is not yet listed as one of the disorders in the DSM-5 and/or the ICD-11. Although there are controversies and debates in the literature about the classification and construct of FA, the most common approach to access it is the use of a research tool - the Yale Food Addiction Scale (YFAS) - which approximates the concept of FA to the concept diagnosis of dependence on psychoactive substances. There is a need to explore the dimensional phenotypes accessed by YFAS in different population groups for a better understanding and scientific support of FA diagnoses. Methods: The primary objective of this project was to investigate the construct validity of the FA concept by mYFAS 2.0 in individuals who underwent bariatric surgery (n = 100) at the Hospital Estadual Mário Covas since 2011. Statistical analyzes were conducted using the STATA software. In this sense, structural or factor validity was the type of construct validity investigated using exploratory factor analysis (EFA) and item response theory (IRT) techniques. Results: EFA showed that the one-dimensional model was the most parsimonious. The IRT showed that all criteria contributed to the latent structure, presenting discrimination values greater than 0.5, with most presenting values greater than 2. Conclusion: This study reinforces a FA dimension in patients who underwent bariatric surgery. Within this dimension, we identified the most severe and discriminating criteria for the diagnosis of FA.

Keywords: obesity, food addiction, bariatric surgery, regain

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Authors: Narendra Nath Patra

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Several recent studies reinforce the existence of a thick molecular disc in galaxies along with the dynamically cold thin disc. Assuming a two-component molecular disc, we model the disc of NGC 6946 as a four-component system consists of stars, HI, thin disc molecular gas, and thick disc molecular gas in vertical hydrostatic equilibrium. Following, we set up the joint Poisson-Boltzmann equation of hydrostatic equilibrium and solve it numerically to obtain a three-dimensional density distribution of different baryonic components. Using the density solutions and the observed rotation curve, we further build a three-dimensional dynamical model of the molecular disc and consecutively produce simulated CO spectral cube and spectral width profile. We find that the simulated spectral width profiles distinguishably differs for different assumed thick disc molecular gas fraction. Several CO spectral width profiles are then produced for different assumed thick disc molecular gas fractions and compared with the observed one to obtain the best fit thick disc molecular gas fraction profile. We find that the thick disc molecular gas fraction in NGC 6946 largely remains constant across its molecular disc with a mean value of 0.70 +/- 0.09. We also estimate the amount of extra-planar molecular gas in NGC 6946. We find 60% of the total molecular gas is extra-planar at the central region, whereas this fraction reduces to ~ 35% at the edge of the molecular disc. With our method, for the first time, we estimate the thick disc molecular gas fraction as a function of radius in an external galaxy with sub-kpc resolution.

Keywords: galaxies: kinematics and dynamic, galaxies: spiral, galaxies: structure , ISM: molecules, molecular data

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Authors: Weiliang Wen, Xinyu Guo, Ying Zhang, Jianjun Du, Boxiang Xiao

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Reconstructing and analyzing three-dimensional (3D) models from situ measured data is important for a number of researches and applications in plant science, including plant phenotyping, functional-structural plant modeling (FSPM), plant germplasm resources protection, agricultural technology popularization. It has many scales like cell, tissue, organ, plant and canopy from micro to macroscopic. The techniques currently used for data capture, feature analysis, and 3D reconstruction are quite different of different scales. In this context, morphological data acquisition, 3D analysis and modeling of plants on different scales are introduced systematically. The commonly used data capture equipment for these multiscale is introduced. Then hot issues and difficulties of different scales are described respectively. Some examples are also given, such as Micron-scale phenotyping quantification and 3D microstructure reconstruction of vascular bundles within maize stalks based on micro-CT scanning, 3D reconstruction of leaf surfaces and feature extraction from point cloud acquired by using 3D handheld scanner, plant modeling by combining parameter driven 3D organ templates. Several application examples by using the 3D models and analysis results of plants are also introduced. A 3D maize canopy was constructed, and light distribution was simulated within the canopy, which was used for the designation of ideal plant type. A grape tree model was constructed from 3D digital and point cloud data, which was used for the production of science content of 11th international conference on grapevine breeding and genetics. By using the tissue models of plants, a Google glass was used to look around visually inside the plant to understand the internal structure of plants. With the development of information technology, 3D data acquisition, and data processing techniques will play a greater role in plant science.

Keywords: plant, three dimensional modeling, multi-scale, plant phenotyping, three dimensional data acquisition

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Authors: Alok S Chauhan, Sridhar S., Pradyumna R.

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In the process of precision investment casting of turbine hollow blade/vane components, a part of the dimensional deviations observed in the castings can be attributed to the wax pattern. In the process of injection moulding of wax to produce patterns, heated wax shrinks in size during cooling in the die, leading to a reduction in the dimensions of the pattern. Also, flow and thermal induced residual stresses result in shrinkage & warpage of the component after removal from the die, further adding to the deviations. Injection moulding parameters such as wax temperature, flow rate, packing pressure, etc. affect the flow and thermal behavior of the component and hence are directly responsible for the dimensional deviations. There is a need to precisely determine and control these deviations in order to achieve stringent dimensional accuracies imposed on these castings by aerospace standards. Simulation based approaches provide a platform to predict these dimensional deviations without resorting to elaborate experimentation. In the present paper, Moldex3D simulation package has been utilized to analyze the effect of variations in injection temperature, packing pressure and cooling time on the shrinkage behavior of a stepped pattern. Two types of waxes with different rheological properties have been included in the study to gauge the effect of change in wax on the dimensional deviations. A full factorial design of experiments has been configured with these parameters and results of analysis of variance have been presented.

Keywords: wax patterns, investment casting, pattern die/mould, wax injection, Moldex3D simulation

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Authors: Heval Serhat Uluk, Sam M. Dakka, Kuldeep Singh, Richard Jefferson-Loveday

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This paper will focus on the suitability of a trapped vortex combustor as a candidate for gas turbine combustor objectives to minimize pressure drop across the combustor and investigate aerodynamic performance. Non-reacting simulation of axisymmetric cavity trapped vortex combustors were simulated to investigate the pressure drop for various cavity aspect ratios of 0.3, 0.6, and 1 and for air mass flow rates of 14 m/s, 28 m/s, and 42 m/s. A numerical study of an axisymmetric trapped vortex combustor was carried out by using two-dimensional and three-dimensional computational domains. A comparison study was conducted between Reynolds Averaged Navier Stokes (RANS) k-ε Realizable with enhanced wall treatment and RANS k-ω Shear Stress Transport (SST) models to find the most suitable turbulence model. It was found that the k-ω SST model gives relatively close results to experimental outcomes. The numerical results were validated and showed good agreement with the experimental data. Pressure drop rises with increasing air mass flow rate, and the lowest pressure drop was observed at 0.6 cavity aspect ratio for all air mass flow rates tested, which agrees with the experimental outcome. A mixing enhancement study showed that 30-degree angle air injectors provide improved fuel-air mixing.

Keywords: aerodynamic, computational fluid dynamics, propulsion, trapped vortex combustor

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Authors: M. Shaban, A. Alibeigloo

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This paper studies free vibration behavior of single-walled carbon nanotubes (SWCNTs) embedded on elastic medium based on three-dimensional theory of elasticity. To accounting the size effect of carbon nanotubes, nonlocal theory is adopted to shell model. The nonlocal parameter is incorporated into all constitutive equations in three dimensions. The surrounding medium is modeled as two-parameter elastic foundation. By using Fourier series expansion in axial and circumferential direction, the set of coupled governing equations are reduced to the ordinary differential equations in thickness direction. Then, the state-space method as an efficient and accurate method is used to solve the resulting equations analytically. Comprehensive parametric studies are carried out to show the influences of the nonlocal parameter, radial and shear elastic stiffness, thickness-to-radius ratio and radius-to-length ratio.

Keywords: carbon nanotubes, embedded, nonlocal, free vibration

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Authors: I. Hosni, L. Bennaceur Farah, N. Saber, R Bennaceur

Abstract:

Soil moisture content is a key variable in many environmental sciences. Even though it represents a small proportion of the liquid freshwater on Earth, it modulates interactions between the land surface and the atmosphere, thereby influencing climate and weather. Accurate modeling of the above processes depends on the ability to provide a proper spatial characterization of soil moisture. The measurement of soil moisture content allows assessment of soil water resources in the field of hydrology and agronomy. The second parameter in interaction with the radar signal is the geometric structure of the soil. Most traditional electromagnetic models consider natural surfaces as single scale zero mean stationary Gaussian random processes. Roughness behavior is characterized by statistical parameters like the Root Mean Square (RMS) height and the correlation length. Then, the main problem is that the agreement between experimental measurements and theoretical values is usually poor due to the large variability of the correlation function, and as a consequence, backscattering models have often failed to predict correctly backscattering. In this study, surfaces are considered as band-limited fractal random processes corresponding to a superposition of a finite number of one-dimensional Gaussian process each one having a spatial scale. Multiscale roughness is characterized by two parameters, the first one is proportional to the RMS height, and the other one is related to the fractal dimension. Soil moisture is related to the complex dielectric constant. This multiscale description has been adapted to two-dimensional profiles using the bi-dimensional wavelet transform and the Mallat algorithm to describe more correctly natural surfaces. We characterize the soil surfaces and sub-surfaces by a three layers geo-electrical model. The upper layer is described by its dielectric constant, thickness, a multiscale bi-dimensional surface roughness model by using the wavelet transform and the Mallat algorithm, and volume scattering parameters. The lower layer is divided into three fictive layers separated by an assumed plane interface. These three layers were modeled by an effective medium characterized by an apparent effective dielectric constant taking into account the presence of air pockets in the soil. We have adopted the 2D multiscale three layers small perturbations model including, firstly air pockets in the soil sub-structure, and then a vegetable canopy in the soil surface structure, that is to simulate the radar backscattering. A sensitivity analysis of backscattering coefficient dependence on multiscale roughness and new soil moisture has been performed. Later, we proposed to change the dielectric constant of the multilayer medium because it takes into account the different moisture values of each layer in the soil. A sensitivity analysis of the backscattering coefficient, including the air pockets in the volume structure with respect to the multiscale roughness parameters and the apparent dielectric constant, was carried out. Finally, we proposed to study the behavior of the backscattering coefficient of the radar on a soil having a vegetable layer in its surface structure.

Keywords: multiscale, bidimensional, wavelets, backscattering, multilayer, SPM, air pockets

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Authors: Yibin Qiu, Yubo Ouyang, Shihan Li, Guorui Zhang, Qi Li, Weirong Chen

Abstract:

This paper aims at exploring the impacts of high dimensional dependencies of wind speed among wind farms on probabilistic optimal power flow. To obtain the reactive power optimization faster and more accurately, a mixture vine Copula structure model combining the K-means clustering, C vine copula and D vine copula is proposed in this paper, through which a more accurate correlation model can be obtained. Moreover, a Modified Backtracking Search Algorithm (MBSA), the three-point estimate method is applied to probabilistic optimal power flow. The validity of the mixture vine copula structure model and the MBSA are respectively tested in IEEE30 node system with measured data of 3 adjacent wind farms in a certain area, and the results indicate effectiveness of these methods.

Keywords: mixture vine copula structure model, three-point estimate method, the probability integral transform, modified backtracking search algorithm, reactive power optimization

Procedia PDF Downloads 229

Authors: Reut Lanyado, David Mendlovic

Abstract:

Most biological methods for authentication require special equipment and, some of them are easy to fake. We proposed a method for authentication based on hand movement while typing a sentence with a regular camera. This technique uses the full video of the hand, which is harder to fake. In the first phase, we tracked the hand joints in each frame. Next, we represented a single frame for each individual using our Pose Agnostic Rotation and Movement (PARM) dimensional space. Then, we indicated a full video of hand movement in a fixed low dimensional space using this method: Fixed Dimension Video by Interpolation Statistics (FDVIS). Finally, we identified each individual in the FDVIS representation using unsupervised clustering and supervised methods. Accuracy exceeds 96% for 80 individuals by using supervised KNN.

Keywords: authentication, feature extraction, hand recognition, security, signal processing

Procedia PDF Downloads 88

Authors: Yarra Sulina, Nunna Tagore Sai Priya, Ankhi Banerjee

Abstract:

With the rapid growth in tourist arrivals, there has been a huge demand for the growth of infrastructure in the destinations. With the increasing preference of tourists to stay near attractions, there has been a considerable change in the land use around tourist sites. However, with the inclusion of certain regulations and guidelines provided by the authorities based on the nature of tourism activity and geographical constraints, the pattern of growth of built form is different for various tourist sites. Therefore, this study explores the patterns of growth of built-up for a decade from 2009 to 2019 through two-dimensional and three-dimensional analysis. Land use maps are created through supervised classification of satellite images obtained from LANDSAT 4-5 and LANDSAT 8 for 2009 and 2019, respectively. The overall expansion of the built-up area in the region is analyzed in relation to the distance from the city's geographical center and the tourism-related growth regions are identified which are influenced by the proximity of tourist attractions. The primary tourist sites of various destinations with different geographical characteristics and tourism activities, that have undergone a significant increase in built-up area and are occupied with tourism-related infrastructure are selected for further study. Proximity analysis of the tourism-related growth sites is carried out to delineate the influence zone of the tourist site in a destination. Further, a temporal analysis of volumetric growth of built form is carried out to understand the morphology of the tourist precincts over time. The Digital Surface Model (DSM) and Digital Terrain Model (DTM) are used to extract the building footprints along with building height. Factors such as building height, and building density are evaluated to understand the patterns of three-dimensional growth of the built area in the region. The study also explores the underlying reasons for such changes in built form around various tourist sites and predicts the impact of such growth patterns in the region. The building height and building density around tourist site creates a huge impact on the appeal of the destination. The surroundings that are incompatible with the theme of the tourist site have a negative impact on the attractiveness of the destination that leads to negative feedback by the tourists, which is not a sustainable form of development. Therefore, proper spatial measures are necessary in terms of area and volume of the built environment for a healthy and sustainable environment around the tourist sites in the destination.

Keywords: sustainable tourism, growth patterns, land-use changes, 3-dimensional analysis of built-up area

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Authors: Sofia M. Karadimitriou, Kostas Triantafyllopoulos, Timothy Heaton

Abstract:

Reduced dimension Dynamic Spatio-Temporal Models (DSTMs) jointly describe the spatial and temporal evolution of a function observed subject to noise. A basic state space model is adopted for the discrete temporal variation, while a continuous autoregressive structure describes the continuous spatial evolution. Application of such a DSTM relies upon the pre-selection of a suitable reduced set of basic functions and this can present a challenge in practice. In this talk, we propose an online estimation method for high dimensional spatio-temporal data based upon DSTM and we attempt to resolve this issue by allowing the basis to adapt to the observed data. Specifically, we present a wavelet decomposition in order to obtain a parsimonious approximation of the spatial continuous process. This parsimony can be achieved by placing a Laplace prior distribution on the wavelet coefficients. The aim of using the Laplace prior, is to filter wavelet coefficients with low contribution, and thus achieve the dimension reduction with significant computation savings. We then propose a Hierarchical Bayesian State Space model, for the estimation of which we offer an appropriate particle filter algorithm. The proposed methodology is illustrated using real environmental data.

Keywords: multidimensional Laplace prior, particle filtering, spatio-temporal modelling, wavelets

Procedia PDF Downloads 400