Search results for: computational neural networks

Authors: Temidayo Otunniyi

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This paper presents a low computational channelization algorithm for the multi-standards platform using poly phase implementation of a critically sampled hybrid Trigonometry generalized Discrete Fourier Transform, (HGDFT). An HGDFT channelization algorithm exploits the orthogonality of two trigonometry Fourier functions, together with the properties of Quadrature Mirror Filter Bank (QMFB) and Exponential Modulated filter Bank (EMFB), respectively. HGDFT shows improvement in its implementation in terms of high reconfigurability, lower filter length, parallelism, and medium computational activities. Type 1 and type 111 poly phase structures are derived for real-valued HGDFT modulation. The design specifications are decimated critically and over-sampled for both single and multi standards receiver platforms. Evaluating the performance of oversampled single standard receiver channels, the HGDFT algorithm achieved 40% complexity reduction, compared to 34% and 38% reduction in the Discrete Fourier Transform (DFT) and tree quadrature mirror filter (TQMF) algorithm. The parallel generalized discrete Fourier transform (PGDFT) and recombined generalized discrete Fourier transform (RGDFT) had 41% complexity reduction and HGDFT had a 46% reduction in oversampling multi-standards mode. While in the critically sampled multi-standard receiver channels, HGDFT had complexity reduction of 70% while both PGDFT and RGDFT had a 34% reduction.

Keywords: software defined radio, channelization, critical sample rate, over-sample rate

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Authors: Mai Abdul Latif, Yuntian Feng

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Applied Element Method (AEM) is a method that was developed to aid in the analysis of the collapse of structures. Current available methods cannot deal with structural collapse accurately; however, AEM can simulate the behavior of a structure from an initial state of no loading until collapse of the structure. The elements in AEM are connected with sets of normal and shear springs along the edges of the elements, that represent the stresses and strains of the element in that region. The elements are rigid, and the material properties are introduced through the spring stiffness. Nonlinear dynamic analysis has been widely modelled using the finite element method for analysis of progressive collapse of structures; however, difficulties in the analysis were found at the presence of excessively deformed elements with cracking or crushing, as well as having a high computational cost, and difficulties on choosing the appropriate material models for analysis. The Applied Element method is developed and coded to significantly improve the accuracy and also reduce the computational costs of the method. The scheme works for both linear elastic, and nonlinear cases, including elasto-plastic materials. This paper will focus on elastic and elasto-plastic material behaviour, where the number of springs required for an accurate analysis is tested. A steel cantilever beam is used as the structural element for the analysis. The first modification of the method is based on the Gaussian Quadrature to distribute the springs. Usually, the springs are equally distributed along the face of the element, but it was found that using Gaussian springs, only up to 2 springs were required for perfectly elastic cases, while with equal springs at least 5 springs were required. The method runs on a Newton-Raphson iteration scheme, and quadratic convergence was obtained. The second modification is based on adapting the number of springs required depending on the elasticity of the material. After the first Newton Raphson iteration, Von Mises stress conditions were used to calculate the stresses in the springs, and the springs are classified as elastic or plastic. Then transition springs, springs located exactly between the elastic and plastic region, are interpolated between regions to strictly identify the elastic and plastic regions in the cross section. Since a rectangular cross-section was analyzed, there were two plastic regions (top and bottom), and one elastic region (middle). The results of the present study show that elasto-plastic cases require only 2 springs for the elastic region, and 2 springs for the plastic region. This showed to improve the computational cost, reducing the minimum number of springs in elasto-plastic cases to only 6 springs. All the work is done using MATLAB and the results will be compared to models of structural elements using the finite element method in ANSYS.

Keywords: applied element method, elasto-plastic, Gaussian springs, nonlinear

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Authors: Aymen Laadhari

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The cardiovascular system is centered on the heart and is characterized by a very complex structure with different physical scales in space (e.g. micrometers for erythrocytes and centimeters for organs) and time (e.g. milliseconds for human brain activity and several years for development of some pathologies). The development and numerical implementation of mathematical models of the cardiovascular system is a tremendously challenging topic at the theoretical and computational levels, inducing consequently a growing interest over the past decade. The accurate computational investigations in both healthy and pathological cases of processes related to the functioning of the human cardiovascular system can be of great potential in tackling several problems of clinical relevance and in improving the diagnosis of specific diseases. In this talk, we focus on the specific task of simulating three particular phenomena related to the cardiovascular system on the macroscopic, mesoscopic and microscopic scales, respectively. Namely, we develop numerical methodologies tailored for the simulation of (i) the haemodynamics (i.e., fluid mechanics of blood) in the aorta and sinus of Valsalva interacting with highly deformable thin leaflets, (ii) the hyperelastic anisotropic behaviour of cardiomyocytes and the influence of calcium concentrations on the contraction of single cells, and (iii) the dynamics of red blood cells in microvasculature. For each problem, we present an appropriate fully Eulerian finite element methodology. We report several numerical examples to address in detail the relevance of the mathematical models in terms of physiological meaning and to illustrate the accuracy and efficiency of the numerical methods.

Keywords: finite element method, cardiovascular system, Eulerian framework, haemodynamics, heart valve, cardiomyocyte, red blood cell

Procedia PDF Downloads 251

Authors: Jonghyuk Yoon, Hyoungwoon Song, Youngbae Kim, Eunju Kim

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Recently, with the rapid growth of semiconductor industry, lots of interests have been focused on after treatment system that remove the polluted gas produced from semiconductor manufacturing process, and a wet scrubber is the one of the widely used system. When it comes to mechanism of removing the gas, the polluted gas is removed firstly by chemical reaction in a reactor part. After that, the polluted gas stream is brought into contact with the scrubbing liquid, by spraying it with the liquid. Effective design of the reactor part inside the wet scrubber is highly important since removal performance of the polluted gas in the reactor plays an important role in overall performance and stability. In the present study, a CFD (Computational Fluid Dynamics) analysis was performed to figure out the thermal and flow characteristics inside unit a reactor of wet scrubber. In order to verify the numerical result, temperature distribution of the numerical result at various monitoring points was compared to the experimental result. The average error rates (12~15%) between them was shown and the numerical result of temperature distribution was in good agreement with the experimental data. By using validated numerical method, the effect of the reactor geometry on heat transfer rate was also taken into consideration. Uniformity of temperature distribution was improved about 15%. Overall, the result of present study could be useful information to identify the fluid behavior and thermal performance for various scrubber systems. This project is supported by the ‘R&D Center for the reduction of Non-CO₂ Greenhouse gases (RE201706054)’ funded by the Korea Ministry of Environment (MOE) as the Global Top Environment R&D Program.

Keywords: semiconductor, polluted gas, CFD (Computational Fluid Dynamics), wet scrubber, reactor

Procedia PDF Downloads 142

Authors: Michael Williams

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The ability to control a flowing well is of the utmost important. During the kill phase, heavy weight kill mud is circulated around the well. While increasing bottom hole pressure near wellbore formation, the damage is increased. The addition of high density spherical objects has the potential to minimise this near wellbore damage, increase bottom hole pressure and reduce operational time to kill the well. This operational time saving is seen in the rapid deployment of high density spherical objects instead of building high density drilling fluid. The research aims to model the well kill process using a Computational Fluid Dynamics software. A model has been created as a proof of concept to analyse the flow of micron sized spherical objects in the drilling fluid. Initial results show that this new methodology of spherical objects in drilling fluid agrees with traditional stream lines seen in non-particle flow. Additional models have been created to demonstrate that areas of higher flow rate around the bit can lead to increased probability of wash out of formations but do not affect the flow of micron sized spherical objects. Interestingly, areas that experience dimensional changes such as tool joints and various BHA components do not appear at this initial stage to experience increased velocity or create areas of turbulent flow, which could lead to further borehole stability. In conclusion, the initial models of this novel well control methodology have not demonstrated any adverse flow patterns, which would conclude that this model may be viable under field conditions.

Keywords: well control, fluid mechanics, safety, environment

Procedia PDF Downloads 171

Authors: E. G. Karvelas, C. Liosis, A. Theodorakakos, T. E. Karakasidis

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Magnetic navigation of the drug inside the human vessels is a very important concept since the drug is delivered to the desired area. Consequently, the quantity of the drug required to reach therapeutic levels is being reduced while the drug concentration at targeted sites is increased. Magnetic navigation of drug agents can be achieved with the use of magnetic nanoparticles where anti-tumor agents are loaded on the surface of the nanoparticles. The magnetic field that is required to navigate the particles inside the human arteries is produced by a magnetic resonance imaging (MRI) device. The main factors which influence the efficiency of the usage of magnetic nanoparticles for biomedical applications in magnetic driving are the size and the magnetization of the biocompatible nanoparticles. In this study, a computational platform for the simulation of the optimal gradient magnetic fields for the navigation of magnetic nanoparticles inside a carotid artery is presented. For the propulsion model of the particles, seven major forces are considered, i.e., the magnetic force from MRIs main magnet static field as well as the magnetic field gradient force from the special propulsion gradient coils. The static field is responsible for the aggregation of nanoparticles, while the magnetic gradient contributes to the navigation of the agglomerates that are formed. Moreover, the contact forces among the aggregated nanoparticles and the wall and the Stokes drag force for each particle are considered, while only spherical particles are used in this study. In addition, gravitational forces due to gravity and the force due to buoyancy are included. Finally, Van der Walls force and Brownian motion are taken into account in the simulation. The OpenFoam platform is used for the calculation of the flow field and the uncoupled equations of particles' motion. To verify the optimal gradient magnetic fields, a covariance matrix adaptation evolution strategy (CMAES) is used in order to navigate the particles into the desired area. A desired trajectory is inserted into the computational geometry, which the particles are going to be navigated in. Initially, the CMAES optimization strategy provides the OpenFOAM program with random values of the gradient magnetic field. At the end of each simulation, the computational platform evaluates the distance between the particles and the desired trajectory. The present model can simulate the motion of particles when they are navigated by the magnetic field that is produced by the MRI device. Under the influence of fluid flow, the model investigates the effect of different gradient magnetic fields in order to minimize the distance of particles from the desired trajectory. In addition, the platform can navigate the particles into the desired trajectory with an efficiency between 80-90%. On the other hand, a small number of particles are stuck to the walls and remains there for the rest of the simulation.

Keywords: artery, drug, nanoparticles, navigation

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Authors: Raghava Dhanya, Shashank S.

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This paper delves into the intersection of chess and computer science, specifically focusing on the efficient representation of chess game states. We propose two methods: the Static Method and the Dynamic Method, each offering unique advantages in terms of space efficiency and computational complexity. The Static Method aims to represent the game state using a fixedlength encoding, allocating 192 bits to capture the positions of all pieces on the board. This method introduces a protocol for ordering and encoding piece positions, ensuring efficient storage and retrieval. However, it faces challenges in representing pieces no longer in play. In contrast, the Dynamic Method adapts to the evolving game state by dynamically adjusting the encoding length based on the number of pieces in play. By incorporating Alive Bits for each piece kind, this method achieves greater flexibility and space efficiency. Additionally, it includes provisions for encoding additional game state information such as castling rights and en passant squares. Our findings demonstrate that the Dynamic Method offers superior space efficiency compared to traditional Forsyth-Edwards Notation (FEN), particularly as the game progresses and pieces are captured. However, it comes with increased complexity in encoding and decoding processes. In conclusion, this study provides insights into optimizing the representation of chess game states, offering potential applications in chess engines, game databases, and artificial intelligence research. The proposed methods offer a balance between space efficiency and computational overhead, paving the way for further advancements in the field.

Keywords: chess, optimisation, encoding, bit manipulation

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Authors: Olaide O. Wahab, Lukman O. Olasunkanmi, Krishna K. Govender, Penny P. Govender

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The economic and environmental challenges associated with azo disperse dyes applications are due to poor aqueous solubility and low degradation tendency which stems from low chemical reactivity. Poor aqueous solubility property of this group of dyes necessitates the use of dispersing agents which increase operational costs and also release toxic chemical components into the environment, while their low degradation tendency is due to the high stability of the azo functional group (-N=N-) in their chemical structures. To address these problems, this study investigated theoretically the effects of some polar substituents on the aqueous solubility and reactivity properties of disperse yellow (DY) 119 dye with a view to theoretically develop new azo disperse dyes with improved solubility in water and higher degradation tendency in the environment using DMol³ computational code. All calculations were carried out using the Becke and Perdew version of Volsko-Wilk-Nusair (VWN-BP) level of density functional theory in conjunction with double numerical basis set containing polarization function (DNP). The aqueous solubility determination was achieved with conductor-like screening model for realistic solvation (COSMO-RS) in conjunction with known empirical solubility model, while the reactivity was predicted using frontier molecular orbital calculations. Most of the new derivatives studied showed evidence of higher aqueous solubility and degradation tendency compared to the parent dye. We conclude that these derivatives are promising alternative dyes for more economic and environmental benign dyeing practice and therefore recommend them for synthesis.

Keywords: aqueous solubility, azo disperse dye, degradation, disperse yellow 119, DMol³, reactivity

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Authors: Kubra Sultan Yuzuncuyil, Aytekin İsman, Berkay Bulus

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With the developments of information and communication technologies, the forms of molding public opinion have changed. In the presence of Internet, the notion of activism has been endowed with digital codes. Activists have engaged the use of Internet into their campaigns and the process of creating collective identity. Activist movements have been incorporating the relevance of new communication technologies for their goals and opposition. Creating and managing activism through Internet is called Online Activism. In this main, Slow Food Movement which was emerged within the philosophy of defending regional, fair and sustainable food has been engaging Internet into their activist campaign. This movement supports the idea that a new food system which allows strong connections between plate and planet is possible. In order to make their voices heard, it has utilized social networks and develop particular skills in the framework online activism. This study analyzes online activist skills of Slow Food Movement (SFM) develop and attempts to measure its effectiveness. To achieve this aim, it adopts the model proposed by Sivitandies and Shah and conduct both qualitiative and quantiative content analysis on social network use of Slow Food Movement. In this regard, the sample is chosen as the official profile and analyzed between in a three month period respectively March-May 2017. It was found that SFM develops particular techniques that appeal to the model of Sivitandies and Shah. The prominent skill in this regard was found as hyperlink abbreviation and use of multimedia elements. On the other hand, there are inadequacies in hashtag and interactivity use. The importance of this study is that it highlights and discusses how online activism can be engaged into a social movement. It also reveals current online activism skills of SFM and their effectiveness. Furthermore, it makes suggestions to enhance the related abilities and strengthen its voice on social networks.

Keywords: slow food movement, Twitter, internet, online activism

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Authors: Takeshi Takemoto, Naoya Suzuki, Naohisa Takagaki, Satoru Komori, Masako Terui, George Truscott

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Drag coefficient is an important parameter in order to correctly estimate the air-sea momentum flux. However, The parameterization of the drag coefficient hasn’t been established due to the variation in the field data. Instead, a number of drag coefficient model formulae have been proposed, even though almost all these models haven’t discussed the extreme wind speed range. With regards to such models, it is unclear how the drag coefficient changes in the extreme wind speed range as the wind speed increased. In this study, we investigated the effect of the drag coefficient models concerning the air-sea momentum flux in the extreme wind range on a global scale, comparing two different drag coefficient models. Interestingly, one model didn’t discuss the extreme wind speed range while the other model considered it. We found that the difference of the models in the annual global air-sea momentum flux was small because the occurrence frequency of strong wind was approximately 1% with a wind speed of 20m/s or more. However, we also discovered that the difference of the models was shown in the middle latitude where the annual mean air-sea momentum flux was large and the occurrence frequency of strong wind was high. In addition, the estimated data showed that the difference of the models in the drag coefficient was large in the extreme wind speed range and that the largest difference became 23% with a wind speed of 35m/s or more. These results clearly show that the difference of the two models concerning the drag coefficient has a significant impact on the estimation of a regional air-sea momentum flux in an extreme wind speed range such as that seen in a tropical cyclone environment. Furthermore, we estimated each air-sea momentum flux using several kinds of drag coefficient models. We will also provide data from an observation tower and result from CFD (Computational Fluid Dynamics) concerning the influence of wind flow at and around the place.

Keywords: air-sea interaction, drag coefficient, air-sea momentum flux, CFD (Computational Fluid Dynamics)

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Authors: Tanit Daniel Jodar Vecina, Adriane Prisco Petry

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The shape of the wind velocity profile changes according to local features of terrain shape and roughness, which are parameters responsible for defining the Atmospheric Boundary Layer (ABL) profile. Air flow characteristics over and around landforms, such as hills, are of considerable importance for applications related to Wind Farm and Turbine Engineering. The air flow is accelerated on top of hills, which can represent a decisive factor for Wind Turbine placement choices. The present work focuses on the study of ABL behavior as a function of slope and surface roughness of hill-shaped landforms, using the Computational Fluid Dynamics (CFD) to build wind velocity and turbulent intensity profiles. Reynolds-Averaged Navier-Stokes (RANS) equations are closed using the SST k-ω turbulence model; numerical results are compared to experimental data measured in wind tunnel over scale models of the hills under consideration. Eight hill models with slopes varying from 25° to 68° were tested for two types of terrain categories in 2D and 3D, and two analytical codes are used to represent the inlet velocity profiles. Numerical results for the velocity profiles show differences under 4% when compared to their respective experimental data. Turbulent intensity profiles show maximum differences around 7% when compared to experimental data; this can be explained by not being possible to insert inlet turbulent intensity profiles in the simulations. Alternatively, constant values based on the averages of the turbulent intensity at the wind tunnel inlet were used.

Keywords: Atmospheric Boundary Layer, Computational Fluid Dynamic (CFD), Numerical Modeling, Wind Tunnel

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Authors: Mengnan Sun

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It is unclear about the association between air pollution and Tourette Syndrome (TS), although people have suspected that air pollution might trigger TS. TS is a type of neural system disease usually found among children. The number of TS patients has significantly increased in recent decades, suggesting an importance and urgency to examine the possible triggers or conditions that are associated with TS. In this study, the correlation between air pollution and three allergic diseases---asthma, allergic conjunctivitis (AC), and allergic rhinitis (AR)---is examined. Then, a correlation between these allergic diseases and TS is proved. In this way, this study establishes a positive correlation between air pollution and TS. Measures the public can take to help TS patients are also analyzed at the end of this article. The article hopes to raise people’s awareness to reduce air pollution for the good of TS patients or people with other disorders that are associated with air pollution.

Keywords: air pollution, allergic diseases, climate change, Tourette Syndrome

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Authors: Akim Borbuev, Francisco de León

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Economic and population growth in densely-populated urban areas introduce major challenges to distribution system operators, planers, and designers. To supply added loads, utilities are frequently forced to invest in new distribution feeders. However, this is becoming increasingly more challenging due to space limitations and rising installation costs in urban settings. This paper proposes the conversion of critical alternating current (ac) distribution feeders into direct current (dc) feeders to increase the power transfer capacity by a factor as high as four. Current trends suggest that the return of dc transmission, distribution, and utilization are inevitable. Since a total system-level transformation to dc operation is not possible in a short period of time due to the needed huge investments and utility unreadiness, this paper recommends that feeders that are expected to exceed their limits in near future are converted to dc. The increase in power transfer capacity is achieved through several key differences between ac and dc power transmission systems. First, it is shown that underground cables can be operated at higher dc voltage than the ac voltage for the same dielectric stress in the insulation. Second, cable sheath losses, due to induced voltages yielding circulation currents, that can be as high as phase conductor losses under ac operation, are not present under dc. Finally, skin and proximity effects in conductors and sheaths do not exist in dc cables. The paper demonstrates that in addition to the increased power transfer capacity utilities substituting ac feeders by dc feeders could benefit from significant lower costs and reduced losses. Installing dc feeders is less expensive than installing new ac feeders even when new trenches are not needed. Case studies using the IEEE 342-Node Low Voltage Networked Test System quantify the technical and economic benefits of dc feeders.

Keywords: DC power systems, distribution feeders, distribution networks, power transfer capacity

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Authors: Laxmi R. Kasaraneni

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The Internet connects all the networks, including the nation’s critical infrastructure that are used extensively by not only a nation’s government and military to protect sensitive information and execute missions, but also the primary infrastructure that provides services that enable modern conveniences such as education, potable water, electricity, natural gas, and financial transactions. It has become the central nervous system for the government, the citizens, and the industries. When it is attacked, the effects can ripple far and wide impacts not only to citizens’ well-being but nation’s economy, civil infrastructure, and national security. As such, these critical services may be targeted by malicious hackers during cyber warfare, it is imperative to not only protect them and mitigate any immediate or potential threats, but to also understand the current or potential impacts beyond the IT networks or the organization. The Nation’s IT infrastructure which is now vital for communication, commerce, and control of our physical infrastructure, is highly vulnerable to attack. While existing technologies can address some vulnerabilities, fundamentally new architectures and technologies are needed to address the larger structural insecurities of an infrastructure developed in a more trusting time when mass cyber attacks were not foreseen. This research is intended to improve the core functions of the Internet and critical-sector information systems by providing a clear path to create a safe, secure, and resilient cyber environment that help stakeholders at all levels of government, and the private sector work together to develop the cybersecurity capabilities that are key to our economy, national security, and public health and safety. This research paper also emphasizes the present and future cyber security threats, the capabilities and goals of cyber attackers, a strategic concept and steps to implement cybersecurity for maximum effectiveness, enabling technologies, some strategic assumptions and critical challenges, and the future of cyberspace.

Keywords: critical challenges, critical infrastructure, cyber security, enabling technologies, national security

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Authors: Muhsin Kizhisseri, Jorg Schluter, Saleh Gharie

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Atherosclerosis is the main reason of stroke, which is one of the deadliest diseases in the world. The carotid artery in the brain is the prominent location for atherosclerotic progression, which hinders the blood flow into the brain. The inclusion of computational fluid dynamics (CFD) into the diagnosis cycle to understand the hemodynamics of the patient-specific carotid artery can give insights into stroke prediction. Realistic outlet boundary conditions are an inevitable part of the numerical simulations, which is one of the major factors in determining the accuracy of the CFD results. The Windkessel model-based outlet boundary conditions can give more realistic characteristics of the distal vascular branches of the carotid artery, such as the resistance to the blood flow and compliance of the distal arterial walls. This study aims to find the most influential distal branches of the carotid artery by using the Windkessel model parameters in the outlet boundary conditions. The parametric study approach to Windkessel model parameters can include the geometrical features of the distal branches, such as radius and length. The incorporation of the variations of the geometrical features of the major distal branches such as the middle cerebral artery, anterior cerebral artery, and ophthalmic artery through the Windkessel model can aid in identifying the most influential distal branch in the carotid artery. The results from this study can help physicians and stroke neurologists to have a more detailed and accurate judgment of the patient's condition.

Keywords: stroke, carotid artery, computational fluid dynamics, patient-specific, Windkessel model, distal vascular branches

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Authors: Tai Yuan Yu, Pei-Jen Wang

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A simulation scheme of rotational motions for predictions of bump-type gas foil bearings operating at steady-state is proposed; and, the scheme is based on multi-physics coupling computer aided engineering packages modularized with computational fluid dynamic model and structure elasticity model to numerically solve the dynamic equation of motions of a hydrodynamic loaded shaft supported by an elastic bump foil. The bump foil is assumed to be modelled as infinite number of Hookean springs mounted on stiff wall. Hence, the top foil stiffness is constant on the periphery of the bearing housing. The hydrodynamic pressure generated by the air film lubrication transfers to the top foil and induces elastic deformation needed to be solved by a finite element method program, whereas the pressure profile applied on the top foil must be solved by a finite element method program based on Reynolds Equation in lubrication theory. As a result, the equation of motions for the bearing shaft are iteratively solved via coupling of the two finite element method programs simultaneously. In conclusion, the two-dimensional center trajectory of the shaft plus the deformation map on top foil at constant rotational speed are calculated for comparisons with the experimental results.

Keywords: computational fluid dynamics, fluid structure interaction multi-physics simulations, gas foil bearing, load capacity

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Authors: Caroline Rocco, Feyza Karasu, Céline Croutxé-Barghorn, Xavier Allonas, Maxime Lecompère, Gérard Riess, Yujing Zhang, Catarina Esteves, Leendert van der Ven, Rolf van Benthem Gijsbertus de With

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Acrylates are widely used in UV-curing technology. Their high reactivity can, however, limit their conversion due to early vitrification. In addition, the free radical photopolymerization is known to be sensitive to oxygen inhibition leading to tacky surfaces. Although epoxides can lead to full polymerization, they are sensitive to humidity and exhibit low polymerization rate. To overcome the intrinsic limitations of both classes of monomers, Interpenetrating Polymer Networks (IPNs) can be synthesized. They consist of at least two cross linked polymers which are permanently entangled. They can be achieved under thermal and/or light induced polymerization in one or two steps approach. IPNs can display homogeneous to heterogeneous morphologies with various degrees of phase separation strongly linked to the monomer miscibility and also synthesis parameters. In this presentation, we synthesize UV-cured methacrylate - epoxide based IPNs with different chemical compositions in order to get a better understanding of their formation and phase separation. Miscibility before and during the photopolymerization, reaction kinetics, as well as mechanical properties and morphology have been investigated. The key parameters controlling the morphology and the phase separation, namely monomer miscibility and synthesis parameters have been identified. By monitoring the stiffness changes on the film surface, atomic force acoustic microscopy (AFAM) gave, in conjunction with polymerization kinetic profiles and thermomechanical properties, explanations and corroborated the miscibility predictions. When varying the methacrylate / epoxide ratio, it was possible to move from a miscible and highly-interpenetrated IPN to a totally immiscible and phase-separated one.

Keywords: investigation of properties and morphology, kinetics, phase separation, UV-cured IPNs

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Authors: D. Hilton

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An analysis of the Australian Diabetes Screening Study estimated undiagnosed diabetes mellitus [DM] prevalence in a high risk general practice based cohort. DM prevalence varied from 9.4% to 18.1% depending upon the diagnostic criteria utilised with age being a highly significant risk factor. Utilising the gold standard oral glucose tolerance test, the prevalence of DM was 22-23% in those aged >= 70 years and <15% in those aged 40-59 years. Opportunistic screening in Australian general practice potentially can identify many persons with undiagnosed type 2 DM. An Australian Bureau of Statistics document published three years ago, reported the highest rate of DM in men aged 65-74 years [19%] whereas the rate for women was highest in those over 75 years [13%]. If you consider that the Australian Bureau of Statistics report in 2007 found that 13% of the population was over 65 years of age and that this will increase to 23-25% by 2056 with a further projected increase to 25-28% by 2101, obviously this information has to be factored into the equation when age related diabetes prevalence predictions are calculated. This 10-15% proportional increase of elderly persons within the population demographics has dramatic implications for the estimated number of elderly persons with DM in these age groupings. Computational methodology showing the age related demographic changes reported in these official statistical documents will be done showing estimates for 2056 and 2101 for different age groups. This has relevance for future diabetes prevalence rates and shows that along with many countries worldwide Australia is facing an increasing pandemic. In contrast Japan is expected to have a decrease in the next twenty years in the number of persons with diabetes.

Keywords: epidemiological methods, aging, prevalence, diabetes mellitus

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Authors: Fathi Abid, Bilel Kaffel

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The olive tree, the olive harvest during winter season and the production of olive oil better known by professionals under the name of the crushing operation have interested institutional traders such as olive-oil offices and private companies such as food industry refining and extracting pomace olive oil as well as export-import public and private companies specializing in olive oil. The major problem facing producers of olive oil each winter campaign, contrary to what is expected, it is not whether the harvest will be good or not but whether the sale price will allow them to cover production costs and achieve a reasonable margin of profit or not. These questions are entirely legitimate if we judge by the importance of the issue and the heavy complexity of the uncertainty and competition made tougher by a high level of indebtedness and the experience and expertise of speculators and producers whose objectives are sometimes conflicting. The aim of this paper is to study the formation mechanism of olive oil prices in order to learn about speculators’ behavior and expectations in the market, how they contribute by their industry knowledge and their financial alliances and the size the financial challenge that may be involved for them to build private information hoses globally to take advantage. The methodology used in this paper is based on two stages, in the first stage we study econometrically the formation mechanisms of olive oil price in order to understand the market participant behavior by implementing ARMA, SARMA, GARCH and stochastic diffusion processes models, the second stage is devoted to prediction purposes, we use a combined wavelet- ANN approach. Our main findings indicate that olive oil market participants interact with each other in a way that they promote stylized facts formation. The unstable participant’s behaviors create the volatility clustering, non-linearity dependent and cyclicity phenomena. By imitating each other in some periods of the campaign, different participants contribute to the fat tails observed in the olive oil price distribution. The best prediction model for the olive oil price is based on a back propagation artificial neural network approach with input information based on wavelet decomposition and recent past history.

Keywords: olive oil price, stylized facts, ARMA model, SARMA model, GARCH model, combined wavelet-artificial neural network, continuous-time stochastic volatility mode

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Authors: Abdul Haq

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The goal of this research is to better understand how wind loads affect bridges and develop strategies for designing bridges that are more stable and resistant to wind. The effect of wind on bridges is essential to their safety and functionality, especially in areas that are prone to high wind speeds or violent wind conditions. The study looks at the aerodynamic forces and vibrations caused by wind and how they affect bridge construction. Part of the research method involves first understanding the underlying ideas influencing wind flow near bridges. Computational fluid dynamics (CFD) simulations are used to model and forecast the aerodynamic behaviour of bridges under different wind conditions. These models incorporate several factors, such as wind directionality, wind speed, turbulence intensity, and the influence of nearby structures or topography. The results provide significant new insights into the loads and pressures that wind places on different bridge elements, such as decks, pylons, and connections. Following the determination of the wind loads, the structural response of bridges is assessed. By simulating their dynamic behavior under wind-induced forces, Finite Element Analysis (FEA) is used to model the bridge's component parts. This work contributes to the understanding of which areas are at risk of experiencing excessive stresses, vibrations, or oscillations due to wind excitations. Because the bridge has inherent modes and frequencies, the study considers both static and dynamic responses. Various strategies are examined to maximize the design of bridges to withstand wind. It is possible to alter the bridge's geometry, add aerodynamic components, add dampers or tuned mass dampers to lessen vibrations, and boost structural rigidity. Through an analysis of several design modifications and their effectiveness, the study aims to offer guidelines and recommendations for wind-resistant bridge design. In addition to the numerical simulations and analyses, there are experimental studies. In order to assess the computational models and validate the practicality of proposed design strategies, scaled bridge models are tested in a wind tunnel. These investigations help to improve numerical models and prediction precision by providing valuable information on wind-induced forces, pressures, and flow patterns. Using a combination of numerical models, actual testing, and long-term performance evaluation, the project aims to offer practical insights and recommendations for building wind-resistant bridges that are secure, long-lasting, and comfortable for users.

Keywords: wind effects, aerodynamic forces, computational fluid dynamics, finite element analysis

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Authors: Adandé Belarmain Fandohan

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Climate change has become a major concern globally, particularly in rural communities that have to find rapid coping solutions. Several vulnerability assessment approaches have been developed in the last decades. This comes along with a higher risk for different methods to result in different conclusions, thereby making comparisons difficult and decision-making non-consistent across areas. The effect of methods and computational approaches on estimates of people’s vulnerability was assessed using data collected from the Gambia. Twenty-four indicators reflecting vulnerability components: (exposure, sensitivity, and adaptive capacity) were selected for this purpose. Data were collected through household surveys and key informant interviews. One hundred and fifteen respondents were surveyed across six communities and two administrative districts. Results were compared over three computational approaches: the maximum value transformation normalization, the z-score transformation normalization, and simple averaging. Regardless of the approaches used, communities that have high exposure to climate change and extreme events were the most vulnerable. Furthermore, the vulnerability was strongly related to the socio-economic characteristics of farmers. The survey evidenced variability in vulnerability among communities and administrative districts. Comparing output across approaches, overall, people in the study area were found to be highly vulnerable using the simple average and maximum value transformation, whereas they were only moderately vulnerable using the z-score transformation approach. It is suggested that assessment approach-induced discrepancies be accounted for in international debates to harmonize/standardize assessment approaches to the end of making outputs comparable across regions. This will also likely increase the relevance of decision-making for adaptation policies.

Keywords: maximum value transformation, simple averaging, vulnerability assessment, West Africa, z-score transformation

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Authors: Muneeb Ullah, Daishihan, Xiadong Young

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Deep learning plays a crucial role in identifying COVID-19 and preventing its spread. To improve the accuracy of COVID-19 diagnoses, it is important to have access to a sufficient number of training images of CXRs (chest X-rays) depicting the disease. However, there is currently a shortage of such images. To address this issue, this paper introduces COVID-19 GAN, a model that uses generative adversarial networks (GANs) to generate realistic CXR images of COVID-19, which can be used to train identification models. Initially, a generator model is created that uses digressive channels to generate images of CXR scans for COVID-19. To differentiate between real and fake disease images, an efficient discriminator is developed by combining the dense connectivity strategy and instance normalization. This approach makes use of their feature extraction capabilities on CXR hazy areas. Lastly, the deep regret gradient penalty technique is utilized to ensure stable training of the model. With the use of 4,062 grape leaf disease images, the Leaf GAN model successfully produces 8,124 COVID-19 CXR images. The COVID-19 GAN model produces COVID-19 CXR images that outperform DCGAN and WGAN in terms of the Fréchet inception distance. Experimental findings suggest that the COVID-19 GAN-generated CXR images possess noticeable haziness, offering a promising approach to address the limited training data available for COVID-19 model training. When the dataset was expanded, CNN-based classification models outperformed other models, yielding higher accuracy rates than those of the initial dataset and other augmentation techniques. Among these models, ImagNet exhibited the best recognition accuracy of 99.70% on the testing set. These findings suggest that the proposed augmentation method is a solution to address overfitting issues in disease identification and can enhance identification accuracy effectively.

Keywords: classification, deep learning, medical images, CXR, GAN.

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Authors: Hongbo Zhang, Xinlu Tang, Jiangwei Li, Chi Yan

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Home zone parking pilot (HPP) is a fast-growing segment in low-speed autonomous driving applications. It requires the car automatically cruise around a parking lot and park itself in a range of up to 100 meters inside a recurrent home/office parking lot, which requires precise parking lot mapping and localization solution. Although Lidar is ideal for SLAM, the car OEMs favor a low-cost fish-eye camera based visual SLAM approach. Recent approaches have employed segmentation models to extract semantic features and improve mapping accuracy, but these AI models are memory unfriendly and computationally expensive, making deploying on embedded ADAS systems difficult. To address this issue, we proposed a new method that utilizes object detection models to extract robust and accurate parking lot features. The proposed method could reduce computational costs while maintaining high accuracy. Once combined with vehicles’ wheel-pulse information, the system could construct maps and locate the vehicle in real-time. This article will discuss in detail (1) the fish-eye based Around View Monitoring (AVM) with transparent chassis images as the inputs, (2) an Object Detection (OD) based feature point extraction algorithm to generate point cloud, (3) a low computational parking lot mapping algorithm and (4) the real-time localization algorithm. At last, we will demonstrate the experiment results with an embedded ADAS system installed on a real car in the underground parking lot.

Keywords: ADAS, home zone parking pilot, object detection, visual SLAM

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Authors: Roderick Melnik, Sanjay Prabhakar

Abstract:

The relaxed state of graphene nanostructures due to externally applied tensile stress along both the armchair and zigzag directions are analyzed in detail. The results, obtained with the Finite Element Method (FEM), demonstrate that the amplitude of ripple waves in such nanostructures increases with temperature. Details of the multi-scale multi-physics computational procedure developed for this analysis are also provided.

Keywords: nanostructures, modeling, coupled processes, computer-aided design, nanotechnological applications

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Authors: Seppo Sirkemaa

Abstract:

Information systems infrastructure is the basis of business systems and processes in the company. It should be a reliable platform for business processes and activities but also have the flexibility to change business needs. The development of an infrastructure that is robust, reliable, and flexible is a challenge. Understanding technological capabilities and business needs is a key element in the development of successful information systems infrastructure.

Keywords: development, information technology, networks, technology

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Authors: Hadas Sopher, Davide Schaumann, Yehuda E. Kalay

Abstract:

This paper addresses the shortcomings of architectural computation tools in representing human behavior in built environments, prior to construction and occupancy of those environments. Evaluating whether a design fits the needs of its future users is currently done solely post construction, or is based on the knowledge and intuition of the designer. This issue is of high importance when designing complex buildings such as hospitals, where the quality of treatment as well as patient and staff satisfaction are of major concern. Existing computational pre-occupancy human behavior evaluation methods are geared mainly to test ergonomic issues, such as wheelchair accessibility, emergency egress, etc. As such, they rely on Agent Based Modeling (ABM) techniques, which emphasize the individual user. Yet we know that most human activities are social, and involve a number of actors working together, which ABM methods cannot handle. Therefore, we present an event-based model that manages the interaction between multiple Actors, Spaces, and Activities, to describe dynamically how people use spaces. This approach requires expanding the computational representation of Actors beyond their physical description, to include psychological, social, cultural, and other parameters. The model presented in this paper includes cognitive abilities and rules that describe the response of actors to their physical and social surroundings, based on the actors’ internal status. The model has been applied in a simulation of hospital wards, and showed adaptability to a wide variety of situated behaviors and interactions.

Keywords: agent based modeling, architectural design evaluation, event modeling, human behavior simulation, spatial cognition

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Authors: R. Whalley

Abstract:

The heat transfer modelling for a diffusion process will be considered. Difficulties in computing the time-distance dynamics of the representation will be addressed. Incomplete and irrational Laplace function will be identified as the computational issue. Alternative approaches to the response evaluation process will be provided. An illustration application problem will be presented. Graphical results confirming the theoretical procedures employed will be provided.

Keywords: heat, transfer, diffusion, modelling, computation

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Authors: Xiaohua Zhu, Lingling Ma, Yongguang Zhao

Abstract:

Leaf Area Index (LAI) is a key structural characteristic of crops and plays a significant role in precision agricultural management and farmland ecosystem modeling. However, LAI retrieved from different resolution data contain a scaling bias due to the spatial heterogeneity and model non-linearity, that is, there is scale effect during multi-scale LAI estimate. In this article, a typical farmland in semi-arid regions of Chinese Inner Mongolia is taken as the study area, based on the combination of PROSPECT model and SAIL model, a multiple dimensional Look-Up-Table (LUT) is generated for multiple crops LAI estimation from unmanned aerial vehicle (UAV) hyperspectral data. Based on Taylor expansion method and computational geometry model, a scale transfer model considering both difference between inter- and intra-class is constructed for scale effect analysis of LAI inversion over inhomogeneous surface. The results indicate that, (1) the LUT method based on classification and parameter sensitive analysis is useful for LAI retrieval of corn, potato, sunflower and melon on the typical farmland, with correlation coefficient R2 of 0.82 and root mean square error RMSE of 0.43m2/m-2. (2) The scale effect of LAI is becoming obvious with the decrease of image resolution, and maximum scale bias is more than 45%. (3) The scale effect of inter-classes is higher than that of intra-class, which can be corrected efficiently by the scale transfer model established based Taylor expansion and Computational geometry. After corrected, the maximum scale bias can be reduced to 1.2%.

Keywords: leaf area index (LAI), scale effect, UAV-based hyperspectral data, look-up-table (LUT), remote sensing

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Authors: Houman Tamaddon, Mehrdad Behnia, Masud Behnia

Abstract:

An accurate study of blood flow is associated with an accurate vascular pattern and geometrical properties of the organ of interest. Due to the complexity of vascular networks and poor accessibility in vivo, it is challenging to reconstruct the entire vasculature of any organ experimentally. The objective of this study is to introduce an innovative approach for the reconstruction of a full vascular tree from available morphometric data. Our method consists of implementing morphometric data on those parts of the vascular tree that are smaller than the resolution of medical imaging methods. This technique reconstructs the entire arterial tree down to the capillaries. Vessels greater than 2 mm are obtained from direct volume and surface analysis using contrast enhanced computed tomography (CT). Vessels smaller than 2mm are reconstructed from available morphometric and distensibility data and rearranged by applying Murray’s Laws. Implementation of morphometric data to reconstruct the branching pattern and applying Murray’s Laws to every vessel bifurcation simultaneously, lead to an accurate vascular tree reconstruction. The reconstruction algorithm generates full arterial tree topography down to the first capillary bifurcation. Geometry of each order of the vascular tree is generated separately to minimize the construction and simulation time. The node-to-node connectivity along with the diameter and length of every vessel segment is established and order numbers, according to the diameter-defined Strahler system, are assigned. During the simulation, we used the averaged flow rate for each order to predict the pressure drop and once the pressure drop is predicted, the flow rate is corrected to match the computed pressure drop for each vessel. The final results for 3 cardiac cycles is presented and compared to the clinical data.

Keywords: blood flow, morphometric data, vascular tree, Strahler ordering system

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Authors: Mohammad Zamani, Ramin Mansouri

Abstract:

Spillways are one of the most important hydraulic structures of dams that provide the stability of the dam and downstream areas at the time of flood. A circular vertical spillway with various inlet forms is very effective when there is not enough space for the other spillway. Hydraulic flow in a vertical circular spillway is divided into three groups: free, orifice, and under pressure (submerged). In this research, the hydraulic flow characteristics of a Circular Vertical Spillway are investigated with the CFD model. Two-dimensional unsteady RANS equations were solved numerically using Finite Volume Method. The PISO scheme was applied for the velocity-pressure coupling. The mostly used two-equation turbulence models, k-ε and k-ω, were chosen to model Reynolds shear stress term. The power law scheme was used for the discretization of momentum, k, ε, and ω equations. The VOF method (geometrically reconstruction algorithm) was adopted for interface simulation. In this study, three types of computational grids (coarse, intermediate, and fine) were used to discriminate the simulation environment. In order to simulate the flow, the k-ε (Standard, RNG, Realizable) and k-ω (standard and SST) models were used. Also, in order to find the best wall function, two types, standard wall, and non-equilibrium wall function, were investigated. The laminar model did not produce satisfactory flow depth and velocity along the Morning-Glory spillway. The results of the most commonly used two-equation turbulence models (k-ε and k-ω) were identical. Furthermore, the standard wall function produced better results compared to the non-equilibrium wall function. Thus, for other simulations, the standard k-ε with the standard wall function was preferred. The comparison criterion in this study is also the trajectory profile of jet water. The results show that the fine computational grid, the input speed condition for the flow input boundary, and the output pressure for the boundaries that are in contact with the air provide the best possible results. Also, the standard wall function is chosen for the effect of the wall function, and the turbulent model k-ε (Standard) has the most consistent results with experimental results. When the jet gets closer to the end of the basin, the computational results increase with the numerical results of their differences. The mesh with 10602 nodes, turbulent model k-ε standard and the standard wall function, provide the best results for modeling the flow in a vertical circular Spillway. There was a good agreement between numerical and experimental results in the upper and lower nappe profiles. In the study of water level over crest and discharge, in low water levels, the results of numerical modeling are good agreement with the experimental, but with the increasing water level, the difference between the numerical and experimental discharge is more. In the study of the flow coefficient, by decreasing in P/R ratio, the difference between the numerical and experimental result increases.

Keywords: circular vertical, spillway, numerical model, boundary conditions

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