3D Surface Modeling From Point Clouds

The goal of this thesis is to implement software for creating 3D models from point clouds. Point clouds are acquired with stereo cameras, monocular systems or laser scanners. The created 3D models are triangular models or NURBS (Non-Uniform Rational B-Splines) models. Triangular models are constructed from selected areas from the point clouds and resulted triangular models are translated into a set of quads. The quads are further translated into an estimated grid structure and used for NURBS surface approximation. Finally, we have a set of NURBS surfaces which represent the whole model. The problem wasn’t so easy to solve. The selected triangular surface reconstruction algorithm did not deal well with noise in point clouds. To handle this problem, a clustering method is introduced for simplificating the model and removing noise. As we had better results with the smaller point clouds produced by clustering, we used points in clusters to better estimate the grids for NURBS models. The overall results were good when the point cloud did not have much noise. The point clouds with small amount of error had good results as the triangular model was solid. NURBS surface reconstruction performed well on solid models.

Bag-of-Features Approach to Unsupervised Visual Object Categorisation

The large and growing number of digital images is making manual image search laborious. Only a fraction of the images contain metadata that can be used to search for a particular type of image. Thus, the main research question of this thesis is whether it is possible to learn visual object categories directly from images. Computers process images as long lists of pixels that do not have a clear connection to high-level semantics which could be used in the image search. There are various methods introduced in the literature to extract low-level image features and also approaches to connect these low-level features with high-level semantics. One of these approaches is called Bag-of-Features which is studied in the thesis. In the Bag-of-Features approach, the images are described using a visual codebook. The codebook is built from the descriptions of the image patches using clustering. The images are described by matching descriptions of image patches with the visual codebook and computing the number of matches for each code. In this thesis, unsupervised visual object categorisation using the Bag-of-Features approach is studied. The goal is to find groups of similar images, e.g., images that contain an object from the same category. The standard Bag-of-Features approach is improved by using spatial information and visual saliency. It was found that the performance of the visual object categorisation can be improved by using spatial information of local features to verify the matches. However, this process is computationally heavy, and thus, the number of images must be limited in the spatial matching, for example, by using the Bag-of-Features method as in this study. Different approaches for saliency detection are studied and a new method based on the Hessian-Affine local feature detector is proposed. The new method achieves comparable results with current state-of-the-art. The visual object categorisation performance was improved by using foreground segmentation based on saliency information, especially when the background could be considered as clutter.

Neural correlates of language learning in adults

The human language-learning ability persists throughout life, indicating considerable flexibility at the cognitive and neural level. This ability spans from expanding the vocabulary in the mother tongue to acquisition of a new language with its lexicon and grammar. The present thesis consists of five studies that tap both of these aspects of adult language learning by using magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) during language processing and language learning tasks. The thesis shows that learning novel phonological word forms, either in the native tongue or when exposed to a foreign phonology, activates the brain in similar ways. The results also show that novel native words readily become integrated in the mental lexicon. Several studies in the thesis highlight the left temporal cortex as an important brain region in learning and accessing phonological forms. Incidental learning of foreign phonological word forms was reflected in functionally distinct temporal lobe areas that, respectively, reflected short-term memory processes and more stable learning that persisted to the next day. In a study where explicitly trained items were tracked for ten months, it was found that enhanced naming-related temporal and frontal activation one week after learning was predictive of good long-term memory. The results suggest that memory maintenance is an active process that depends on mechanisms of reconsolidation, and that these process vary considerably between individuals. The thesis put special emphasis on studying language learning in the context of language production. The neural foundation of language production has been studied considerably less than that of perceptive language, especially on the sentence level. A well-known paradigm in language production studies is picture naming, also used as a clinical tool in neuropsychology. This thesis shows that accessing the meaning and phonological form of a depicted object are subserved by different neural implementations. Moreover, a comparison between action and object naming from identical images indicated that the grammatical class of the retrieved word (verb, noun) is less important than the visual content of the image. In the present thesis, the picture naming was further modified into a novel paradigm in order to probe sentence-level speech production in a newly learned miniature language. Neural activity related to grammatical processing did not differ between the novel language and the mother tongue, but stronger neural activation for the novel language was observed during the planning of the upcoming output, likely related to more demanding lexical retrieval and short-term memory. In sum, the thesis aimed at examining language learning by combining different linguistic domains, such as phonology, semantics, and grammar, in a dynamic description of language processing in the human brain.

Software Development Process Modeling. Developers Perspective to Contemporary Modeling Techniques

Formal software development processes and well-defined development methodologies are nowadays seen as the definite way to produce high-quality software within time-limits and budgets. The variety of such high-level methodologies is huge ranging from rigorous process frameworks like CMMI and RUP to more lightweight agile methodologies. The need for managing this variety and the fact that practically every software development organization has its own unique set of development processes and methods have created a profession of software process engineers. Different kinds of informal and formal software process modeling languages are essential tools for process engineers. These are used to define processes in a way which allows easy management of processes, for example process dissemination, process tailoring and process enactment. The process modeling languages are usually used as a tool for process engineering where the main focus is on the processes themselves. This dissertation has a different emphasis. The dissertation analyses modern software development process modeling from the software developers’ point of view. The goal of the dissertation is to investigate whether the software process modeling and the software process models aid software developers in their day-to-day work and what are the main mechanisms for this. The focus of the work is on the Software Process Engineering Metamodel (SPEM) framework which is currently one of the most influential process modeling notations in software engineering. The research theme is elaborated through six scientific articles which represent the dissertation research done with process modeling during an approximately five year period. The research follows the classical engineering research discipline where the current situation is analyzed, a potentially better solution is developed and finally its implications are analyzed. The research applies a variety of different research techniques ranging from literature surveys to qualitative studies done amongst software practitioners. The key finding of the dissertation is that software process modeling notations and techniques are usually developed in process engineering terms. As a consequence the connection between the process models and actual development work is loose. In addition, the modeling standards like SPEM are partially incomplete when it comes to pragmatic process modeling needs, like light-weight modeling and combining pre-defined process components. This leads to a situation, where the full potential of process modeling techniques for aiding the daily development activities can not be achieved. Despite these difficulties the dissertation shows that it is possible to use modeling standards like SPEM to aid software developers in their work. The dissertation presents a light-weight modeling technique, which software development teams can use to quickly analyze their work practices in a more objective manner. The dissertation also shows how process modeling can be used to more easily compare different software development situations and to analyze their differences in a systematic way. Models also help to share this knowledge with others. A qualitative study done amongst Finnish software practitioners verifies the conclusions of other studies in the dissertation. Although processes and development methodologies are seen as an essential part of software development, the process modeling techniques are rarely used during the daily development work. However, the potential of these techniques intrigues the practitioners. As a conclusion the dissertation shows that process modeling techniques, most commonly used as tools for process engineers, can also be used as tools for organizing the daily software development work. This work presents theoretical solutions for bringing the process modeling closer to the ground-level software development activities. These theories are proven feasible by presenting several case studies where the modeling techniques are used e.g. to find differences in the work methods of the members of a software team and to share the process knowledge to a wider audience.

Sulpun kuvantaminen painelajittelussa

Painelajittelussa sellusta poistetaan epäpuhtauksia. Painelajittimien suunnittelussa on tärkeää ymmärtää lajittimessa tapahtuvia ilmiöitä. Työn tavoitteena oli kehittää kuvaamiseen perustuva mittausjärjestelmä kuitujen liikkeiden mittaamista varten. Mittauksen kohteena ovat sellusulpun kuitujen ja epäpuhtauksien nopeudet. Kuvaamisessa käytetyllä kaksoisvalotuksella pystytään mittaamaan kuitujen ja roskien nopeuksia. Nopeuksien mittaamiseen kuvista kehitettiin järjestelmä ja tutkittiin mahdollisuutta automatisoida mittaaminen. Yksittäisten kuitujen havaitsemiseen sellumassasta käytettiin optisella kirkasteella kirkastettuja kuituja ja UV-valoa. Kuituja värjättiin myös mustiksi ja kuvattiin näkyvällä valolla. Kaksoisvalotukseen käytettiin kahta stroboskooppia. Prosessin kuvaamisessa käytettiin ulkoisella herätteellä ohjattavaa kameraa. Kuvan tuomiseen kameralle ja kohteen valaistukseen käytettiin boroskooppia. Saatujen kuvien käsittelyä ja nopeuksien mittausta varten tehtiin tietokoneohjelma. Käytetyn boroskoopin valovoima ei ollut riittävä kuvausten suorittamiseen, mutta muilta osin laitteisto havaittiin toimivaksi. Kuitujen ja roskien nopeuksia pystyttiin laskemaan ohjelmalla kuvista, joita otettiin ilman boroskooppia. Mittaustiedon hankinnan automatisointi näyttää mahdolliselta tekemällä muutoksia kuvauslaitteistoon.

Towards desired crystalline product properties: In-situ monitoring of batch crystallization

The objective of industrial crystallization is to obtain a crystalline product which has the desired crystal size distribution, mean crystal size, crystal shape, purity, polymorphic and pseudopolymorphic form. Effective control of the product quality requires an understanding of the thermodynamics of the crystallizing system and the effects of operation parameters on the crystalline product properties. Therefore, obtaining reliable in-line information about crystal properties and supersaturation, which is the driving force of crystallization, would be very advantageous. Advanced techniques, such asRaman spectroscopy, attenuated total reflection Fourier transform infrared (ATR FTIR) spectroscopy, and in-line imaging techniques, offer great potential for obtaining reliable information during crystallization, and thus giving a better understanding of the fundamental mechanisms (nucleation and crystal growth) involved. In the present work, the relative stability of anhydrate and dihydrate carbamazepine in mixed solvents containing water and ethanol were investigated. The kinetics of the solvent mediated phase transformation of the anhydrate to hydrate in the mixed solvents was studied using an in-line Raman immersion probe. The effects of the operation parameters in terms of solvent composition, temperature and the use of certain additives on the phase transformation kineticswere explored. Comparison of the off-line measured solute concentration and the solid-phase composition measured by in-line Raman spectroscopy allowedthe identification of the fundamental processes during the phase transformation. The effects of thermodynamic and kinetic factors on the anhydrate/hydrate phase of carbamazepine crystals during cooling crystallization were also investigated. The effect of certain additives on the batch cooling crystallization of potassium dihydrogen phosphate (KDP) wasinvestigated. The crystal growth rate of a certain crystal face was determined from images taken with an in-line video microscope. An in-line image processing method was developed to characterize the size and shape of thecrystals. An ATR FTIR and a laser reflection particle size analyzer were used to study the effects of cooling modes and seeding parameters onthe final crystal size distribution of an organic compound C15. Based on the obtained results, an operation condition was proposed which gives improved product property in terms of increased mean crystal size and narrowersize distribution.

Wood species identification by visual characterization of fibers

Kandidaatintyö tehtiin osana PulpVision-tutkimusprojektia, jonka tarkoituksena on kehittää kuvapohjaisia laskenta- ja luokittelumetodeja sellun laaduntarkkailuun paperin valmistuksessa. Tämän tutkimusprojektin osana on aiemmin kehitetty metodi, jolla etsittiin kaarevia rakenteita kuvista, ja tätä metodia hyödynnettiin kuitujen etsintään kuvista. Tätä metodia käytettiin lähtökohtana kandidaatintyölle. Työn tarkoituksena oli tutkia, voidaanko erilaisista kuitukuvista laskettujen piirteiden avulla tunnistaa kuvassa olevien kuitujen laji. Näissä kuitukuvissa oli kuituja neljästä eri puulajista ja yhdestä kasvista. Nämä lajit olivat akasia, koivu, mänty, eukalyptus ja vehnä. Jokaisesta lajista valittiin 100 kuitukuvaa ja nämä kuvat jaettiin kahteen ryhmään, joista ensimmäistä käytettiin opetusryhmänä ja toista testausryhmänä. Opetusryhmän avulla jokaiselle kuitulajille laskettiin näitä kuvaavia piirteitä, joiden avulla pyrittiin tunnistamaan testausryhmän kuvissa olevat kuitulajit. Nämä kuvat oli tuottanut CEMIS-Oulu (Center for Measurement and Information Systems), joka on mittaustekniikkaan keskittynyt yksikkö Oulun yliopistossa. Yksittäiselle opetusryhmän kuitukuvalle laskettiin keskiarvot ja keskihajonnat kolmesta eri piirteestä, jotka olivat pituus, leveys ja kaarevuus. Lisäksi laskettiin, kuinka monta kuitua kuvasta löydettiin. Näiden piirteiden eri yhdistelmien avulla testattiin tunnistamisen tarkkuutta käyttämällä k:n lähimmän naapurin menetelmää ja Naiivi Bayes -luokitinta testausryhmän kuville. Testeistä saatiin lupaavia tuloksia muun muassa pituuden ja leveyden keskiarvoja käytettäessä saavutettiin jopa noin 98 %:n tarkkuus molemmilla algoritmeilla. Tunnistuksessa kuitujen keskimäärinen pituus vaikutti olevan kuitukuvia parhaiten kuvaava piirre. Käytettyjen algoritmien välillä ei ollut suurta vaihtelua tarkkuudessa. Testeissä saatujen tulosten perusteella voidaan todeta, että kuitukuvien tunnistaminen on mahdollista. Testien perusteella kuitukuvista tarvitsee laskea vain kaksi piirrettä, joilla kuidut voidaan tunnistaa tarkasti. Käytetyt lajittelualgoritmit olivat hyvin yksinkertaisia, mutta ne toimivat testeissä hyvin.

Selecting Wavelet Filter for Compression of Spectra from Multispectral Images

The problem of selecting anappropriate wavelet filter is always present in signal compression based on thewavelet transform. In this report, we propose a method to select a wavelet filter from a predefined set of filters for the compression of spectra from a multispectral image. The wavelet filter selection is based on the Learning Vector Quantization (LVQ). In the training phase for the test images, the best wavelet filter for each spectrum has been found by a careful compression-decompression evaluation. Certain spectral features are used in characterizing the pixel spectra. The LVQ is used to form the best wavelet filter class for different types of spectra from multispectral images. When a new image is to be compressed, a set of spectra from that image is selected, the spectra are classified by the trained LVQand the filter associated to the largest class is selected for the compression of every spectrum from the multispectral image. The results show, that almost inevery case our method finds the most suitable wavelet filter from the pre-defined set for the compression.

Computing the persistent homology of range images with alpha shapes

Laser scanning is becoming an increasingly popular method for measuring 3D objects in industrial design. Laser scanners produce a cloud of 3D points. For CAD software to be able to use such data, however, this point cloud needs to be turned into a vector format. A popular way to do this is to triangulate the assumed surface of the point cloud using alpha shapes. Alpha shapes start from the convex hull of the point cloud and gradually refine it towards the true surface of the object. Often it is nontrivial to decide when to stop this refinement. One criterion for this is to do so when the homology of the object stops changing. This is known as the persistent homology of the object. The goal of this thesis is to develop a way to compute the homology of a given point cloud when processed with alpha shapes, and to infer from it when the persistent homology has been achieved. Practically, the computation of such a characteristic of the target might be applied to power line tower span analysis.

Modeling reaction kinetics and mass transfer in ozonation in water solutions

This dissertation is based on four articles dealing with modeling of ozonation. The literature part of this considers some models for hydrodynamics in bubble column simulation. A literature review of methods for obtaining mass transfer coefficients is presented. The methods presented to obtain mass transfer are general models and can be applied to any gas-liquid system. Ozonation reaction models and methods for obtaining stoichiometric coefficients and reaction rate coefficients for ozonation reactions are discussed in the final section of the literature part. In the first article, ozone gas-liquid mass transfer into water in a bubble column was investigated for different pH values. A more general method for estimation of mass transfer and Henry’s coefficient was developed from the Beltrán method. The ozone volumetric mass transfer coefficient and the Henry’s coefficient were determined simultaneously by parameter estimation using a nonlinear optimization method. A minor dependence of the Henry’s law constant on pH was detected at the pH range 4 - 9. In the second article, a new method using the axial dispersion model for estimation of ozone self-decomposition kinetics in a semi-batch bubble column reactor was developed. The reaction rate coefficients for literature equations of ozone decomposition and the gas phase dispersion coefficient were estimated and compared with the literature data. The reaction order in the pH range 7-10 with respect to ozone 1.12 and 0.51 the hydroxyl ion were obtained, which is in good agreement with literature. The model parameters were determined by parameter estimation using a nonlinear optimization method. Sensitivity analysis was conducted using object function method to obtain information about the reliability and identifiability of the estimated parameters. In the third article, the reaction rate coefficients and the stoichiometric coefficients in the reaction of ozone with the model component p-nitrophenol were estimated at low pH of water using nonlinear optimization. A novel method for estimation of multireaction model parameters in ozonation was developed. In this method the concentration of unknown intermediate compounds is presented as a residual COD (chemical oxygen demand) calculated from the measured COD and the theoretical COD for the known species. The decomposition rate of p-nitrophenol on the pathway producing hydroquinone was found to be about two times faster than the p-nitrophenol decomposition rate on the pathway producing 4- nitrocatechol. In the fourth article, the reaction kinetics of p-nitrophenol ozonation was studied in a bubble column at pH 2. Using the new reaction kinetic model presented in the previous article, the reaction kinetic parameters, rate coefficients, and stoichiometric coefficients as well as the mass transfer coefficient were estimated with nonlinear estimation. The decomposition rate of pnitrophenol was found to be equal both on the pathway producing hydroquinone and on the path way producing 4-nitrocathecol. Comparison of the rate coefficients with the case at initial pH 5 indicates that the p-nitrophenol degradation producing 4- nitrocathecol is more selective towards molecular ozone than the reaction producing hydroquinone. The identifiability and reliability of the estimated parameters were analyzed with the Marcov chain Monte Carlo (MCMC) method. @All rights reserved. No part of the publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of the author.

Unsupervised visual object categorization

The number of digital images has been increasing exponentially in the last few years. People have problems managing their image collections and finding a specific image. An automatic image categorization system could help them to manage images and find specific images. In this thesis, an unsupervised visual object categorization system was implemented to categorize a set of unknown images. The system is unsupervised, and hence, it does not need known images to train the system which needs to be manually obtained. Therefore, the number of possible categories and images can be huge. The system implemented in the thesis extracts local features from the images. These local features are used to build a codebook. The local features and the codebook are then used to generate a feature vector for an image. Images are categorized based on the feature vectors. The system is able to categorize any given set of images based on the visual appearance of the images. Images that have similar image regions are grouped together in the same category. Thus, for example, images which contain cars are assigned to the same cluster. The unsupervised visual object categorization system can be used in many situations, e.g., in an Internet search engine. The system can categorize images for a user, and the user can then easily find a specific type of image.

Comparison of Local Feature Detectors and Descriptors for Visual Object Categorization

Local features are used in many computer vision tasks including visual object categorization, content-based image retrieval and object recognition to mention a few. Local features are points, blobs or regions in images that are extracted using a local feature detector. To make use of extracted local features the localized interest points are described using a local feature descriptor. A descriptor histogram vector is a compact representation of an image and can be used for searching and matching images in databases. In this thesis the performance of local feature detectors and descriptors is evaluated for object class detection task. Features are extracted from image samples belonging to several object classes. Matching features are then searched using random image pairs of a same class. The goal of this thesis is to find out what are the best detector and descriptor methods for such task in terms of detector repeatability and descriptor matching rate.

Modeling of electrolyte sorption – from phase equilibria to dynamic separation systems

In this thesis, general approach is devised to model electrolyte sorption from aqueous solutions on solid materials. Electrolyte sorption is often considered as unwanted phenomenon in ion exchange and its potential as an independent separation method has not been fully explored. The solid sorbents studied here are porous and non-porous organic or inorganic materials with or without specific functional groups attached on the solid matrix. Accordingly, the sorption mechanisms include physical adsorption, chemisorption on the functional groups and partition restricted by electrostatic or steric factors. The model is tested in four Cases Studies dealing with chelating adsorption of transition metal mixtures, physical adsorption of metal and metalloid complexes from chloride solutions, size exclusion of electrolytes in nano-porous materials and electrolyte exclusion of electrolyte/non-electrolyte mixtures. The model parameters are estimated using experimental data from equilibrium and batch kinetic measurements, and they are used to simulate actual single-column fixed-bed separations. Phase equilibrium between the solution and solid phases is described using thermodynamic Gibbs-Donnan model and various adsorption models depending on the properties of the sorbent. The 3-dimensional thermodynamic approach is used for volume sorption in gel-type ion exchangers and in nano-porous adsorbents, and satisfactory correlation is obtained provided that both mixing and exclusion effects are adequately taken into account. 2-Dimensional surface adsorption models are successfully applied to physical adsorption of complex species and to chelating adsorption of transition metal salts. In the latter case, comparison is also made with complex formation models. Results of the mass transport studies show that uptake rates even in a competitive high-affinity system can be described by constant diffusion coefficients, when the adsorbent structure and the phase equilibrium conditions are adequately included in the model. Furthermore, a simplified solution based on the linear driving force approximation and the shrinking-core model is developed for very non-linear adsorption systems. In each Case Study, the actual separation is carried out batch-wise in fixed-beds and the experimental data are simulated/correlated using the parameters derived from equilibrium and kinetic data. Good agreement between the calculated and experimental break-through curves is usually obtained indicating that the proposed approach is useful in systems, which at first sight are very different. For example, the important improvement in copper separation from concentrated zinc sulfate solution at elevated temperatures can be correctly predicted by the model. In some cases, however, re-adjustment of model parameters is needed due to e.g. high solution viscosity.

Application of Computational Fluid Dynamics in Modeling Blood Flow in Human Thoracic Aorta

The aim of this study was to simulate blood flow in thoracic human aorta and understand the role of flow dynamics in the initialization and localization of atherosclerotic plaque in human thoracic aorta. The blood flow dynamics in idealized and realistic models of human thoracic aorta were numerically simulated in three idealized and two realistic thoracic aorta models. The idealized models of thoracic aorta were reconstructed with measurements available from literature, and the realistic models of thoracic aorta were constructed by image processing Computed Tomographic (CT) images. The CT images were made available by South Karelia Central Hospital in Lappeenranta. The reconstruction of thoracic aorta consisted of operations, such as contrast adjustment, image segmentations, and 3D surface rendering. Additional design operations were performed to make the aorta model compatible for the numerical method based computer code. The image processing and design operations were performed with specialized medical image processing software. Pulsatile pressure and velocity boundary conditions were deployed as inlet boundary conditions. The blood flow was assumed homogeneous and incompressible. The blood was assumed to be a Newtonian fluid. The simulations with idealized models of thoracic aorta were carried out with Finite Element Method based computer code, while the simulations with realistic models of thoracic aorta were carried out with Finite Volume Method based computer code. Simulations were carried out for four cardiac cycles. The distribution of flow, pressure and Wall Shear Stress (WSS) observed during the fourth cardiac cycle were extensively analyzed. The aim of carrying out the simulations with idealized model was to get an estimate of flow dynamics in a realistic aorta model. The motive behind the choice of three aorta models with distinct features was to understand the dependence of flow dynamics on aorta anatomy. Highly disturbed and nonuniform distribution of velocity and WSS was observed in aortic arch, near brachiocephalic, left common artery, and left subclavian artery. On the other hand, the WSS profiles at the roots of branches show significant differences with geometry variation of aorta and branches. The comparison of instantaneous WSS profiles revealed that the model with straight branching arteries had relatively lower WSS compared to that in the aorta model with curved branches. In addition to this, significant differences were observed in the spatial and temporal profiles of WSS, flow, and pressure. The study with idealized model was extended to study blood flow in thoracic aorta under the effects of hypertension and hypotension. One of the idealized aorta models was modified along with the boundary conditions to mimic the thoracic aorta under the effects of hypertension and hypotension. The results of simulations with realistic models extracted from CT scans demonstrated more realistic flow dynamics than that in the idealized models. During systole, the velocity in ascending aorta was skewed towards the outer wall of aortic arch. The flow develops secondary flow patterns as it moves downstream towards aortic arch. Unlike idealized models, the distribution of flow was nonplanar and heavily guided by the artery anatomy. Flow cavitation was observed in the aorta model which was imaged giving longer branches. This could not be properly observed in the model with imaging containing a shorter length for aortic branches. The flow circulation was also observed in the inner wall of the aortic arch. However, during the diastole, the flow profiles were almost flat and regular due the acceleration of flow at the inlet. The flow profiles were weakly turbulent during the flow reversal. The complex flow patterns caused a non-uniform distribution of WSS. High WSS was distributed at the junction of branches and aortic arch. Low WSS was distributed at the proximal part of the junction, while intermedium WSS was distributed in the distal part of the junction. The pulsatile nature of the inflow caused oscillating WSS at the branch entry region and inner curvature of aortic arch. Based on the WSS distribution in the realistic model, one of the aorta models was altered to induce artificial atherosclerotic plaque at the branch entry region and inner curvature of aortic arch. Atherosclerotic plaque causing 50% blockage of lumen was introduced in brachiocephalic artery, common carotid artery, left subclavian artery, and aortic arch. The aim of this part of the study was first to study the effect of stenosis on flow and WSS distribution, understand the effect of shape of atherosclerotic plaque on flow and WSS distribution, and finally to investigate the effect of lumen blockage severity on flow and WSS distributions. The results revealed that the distribution of WSS is significantly affected by plaque with mere 50% stenosis. The asymmetric shape of stenosis causes higher WSS in branching arteries than in the cases with symmetric plaque. The flow dynamics within thoracic aorta models has been extensively studied and reported here. The effects of pressure and arterial anatomy on the flow dynamic were investigated. The distribution of complex flow and WSS is correlated with the localization of atherosclerosis. With the available results we can conclude that the thoracic aorta, with complex anatomy is the most vulnerable artery for the localization and development of atherosclerosis. The flow dynamics and arterial anatomy play a role in the localization of atherosclerosis. The patient specific image based models can be used to diagnose the locations in the aorta vulnerable to the development of arterial diseases such as atherosclerosis.