Search results for: computational diagnostics

Authors: Waziri Victor Onomza, John K. Alhassan, Idris Ismaila, Noel Dogonyaro Moses

Abstract:

This paper describes the problem of building secure computational services for encrypted information in the Cloud Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy, confidentiality, availability of the users. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute theoretical presentations in high-level computational processes that are based on number theory and algebra that can easily be integrated and leveraged in the Cloud computing with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based cryptographic security algorithm.

Keywords: big data analytics, security, privacy, bootstrapping, homomorphic, homomorphic encryption scheme

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Authors: Jakub Zembrzuski, Bartosz Sobczyk, Mikołaj MIśkiewicz

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Besides designing new constructions, engineers all over the world must face another problem – maintenance, repairs, and assessment of the technical condition of existing bridges. To solve more complex issues, it is necessary to be familiar with the theory of finite element method and to have access to the software that provides sufficient tools which to enable create of sometimes significantly advanced numerical models. The paper includes a brief assessment of the technical condition, a description of the in situ non-destructive testing carried out and the FEM models created for global and local analysis. In situ testing was performed using strain gauges and displacement sensors. Numerical models were created using various software and numerical modeling techniques. Particularly noteworthy is the method of modeling riveted joints of the crossbeam of the viaduct. It is a simplified method that consists of the use of only basic numerical tools such as beam and shell finite elements, constraints, and simplified boundary conditions (fixed support and symmetry). The results of the numerical analyses were presented and discussed. It is clearly explained why the structure did not fail, despite the fact that the weld of the deck plate completely failed. A further research problem that was solved was to determine the cause of the rapid increase in values on the stress diagram in the cross-section of the transverse section. The problems were solved using the solely mentioned, simplified method of modeling riveted joints, which demonstrates that it is possible to solve such problems without access to sophisticated software that enables to performance of the advanced nonlinear analysis. Moreover, the obtained results are of great importance in the field of assessing the operation of bridge structures with an orthotropic plate.

Keywords: bridge, diagnostics, FEM simulations, failure, NDT, in situ testing

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Authors: Abhishek Mukherjee, Juan C. Cajas, Jenny Suckale, Guillaume Houzeaux, Oriol Lehmkuhl, Simone Marras

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The investigation of tsunami flow characteristics and the quantification of tsunami energy reduction through the coastal vegetation is important to understand the protective benefits of nature-based mitigation parks. In the present study, a three-dimensional non-hydrostatic incompressible Computational Fluid Dynamics model with a two-way coupling enabled fluid-structure interaction approach (FSI) is used. After validating the numerical model against experimental data, tsunami flow characteristics have been investigated by varying vegetation density, modulus of elasticity, the gap between stems, and arrangement or distribution of vegetation patches. Streamwise depth average velocity profiles, turbulent kinetic energy, energy flux reflection, and dissipation extracted by the numerical study will be presented in this study. These diagnostics are essential to assess the importance of different parameters to design the proper coastal defense systems. When a tsunami wave reaches the shore, it transforms into undular bores, which induce scour around offshore structures and sediment transport. The bed shear stress, instantaneous turbulent kinetic energy, and the vorticity near-bed will be presented to estimate the importance of vegetation to prevent tsunami-induced scour and sediment transport.

Keywords: coastal defense, energy flux, fluid-structure interaction, natural hazards, sediment transport, tsunami mitigation

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Authors: A. K. Visnuprasad, P. J. Jojo, Reshma Bhaskaran

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Computational fluid dynamics (CFD) is used to simulate the distribution of indoor radon concentration in a living room with elevated levels of radon concentration which varies from 22 Bqm-3 to 1533 Bqm-3 in 24 hours. Finite volume method (FVM) was used for the simulation. The simulation results were experimentally validated at 16 points in two horizontal planes (y=1.4m & y=2.0m) using pin-hole dosimeters and at 3 points using scintillation radon monitor (SRM). Passive measurement using pin-hole dosimeters were performed in all seasons. Another simulation was done to find a suitable position for a passive ventilation system for the effective mitigation of radon.

Keywords: indoor radon, computational fluid dynamics, radon flux, ventilation rate, pin-hole dosimeter

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Authors: Sarantos Psycharis

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Physical Computing, as an instructional model, is applied in the framework of the Engineering Pedagogy to teach “transversal/cross-cutting ideas” in a STEM content approach. Labview and Arduino were used in order to connect the physical world with real data in the framework of the so called Computational Experiment. Tertiary prospective engineering educators were engaged during their course and Computational Thinking (CT) concepts were registered before and after the intervention across didactic activities using validated questionnaires for the relationship between self-efficacy, computer programming, and CT concepts when STEM content epistemology is implemented in alignment with the Computational Pedagogy model. Results show a significant change in students’ responses for self-efficacy for CT before and after the instruction. Results also indicate a significant relation between the responses in the different CT concepts/practices. According to the findings, STEM content epistemology combined with Physical Computing should be a good candidate as a learning and teaching approach in university settings that enhances students’ engagement in CT concepts/practices.

Keywords: arduino, computational thinking, computer programming, Labview, self-efficacy, STEM

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Authors: Chahid K. Ghaddar

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The spreadsheet engine is exploited via a non-conventional mechanism to enable novel worksheet solver functions for computational calculus. The solver functions bypass inherent restrictions on built-in math and user defined functions by taking variable formulas as a new type of argument while retaining purity and recursion properties. The enabling mechanism permits integration of numerical algorithms into worksheet functions for solving virtually any computational problem that can be modelled by formulas and variables. Several examples are presented for computing integrals, derivatives, and systems of deferential-algebraic equations. Incorporation of the worksheet solver functions with the ubiquitous spreadsheet extend the utility of the latter as a powerful tool for computational mathematics.

Keywords: calculus, differential algebraic equations, solvers, spreadsheet

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Authors: David Nagy

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This paper exemplifies the influence of the purpose of an aircraft on the aerodynamic properties of its airfoil. In particular, the research takes into consideration two types of aircraft, namely cargo aircraft and military high-speed aircraft and compares their airfoil characteristics using their NACA airfoils as well as computational fluid dynamics. The results show that airfoils of aircraft designed for cargo have a heavier focus on maintaining a large lift force whereas speed-oriented airplanes focus on minimizing the drag force.

Keywords: aerodynamic simulation, aircraft, airfoil, computational fluid dynamics, lift to drag ratio, NACA 64-206, NACA 65-415

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Authors: Janneth González, George Barreto, Ludis Morales, Angélica Sabogal

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Sea anemone neurotoxins are peptides that interact with Na+ and K+ channels, resulting in specific alterations on their functions. Some of these neurotoxins (1ROO, 1BGK, 2K9E, 1BEI) are important for the treatment of nearly eighty autoimmune disorders due to their specificity for Kv1.3 channel. The aim of this study was to identify the common residues among these neurotoxins by computational methods, and establish whether there is a pattern useful for the future generation of a treatment for autoimmune diseases. Our results showed eight new key common residues between the studied neurotoxins interacting with a histidine ring and the selectivity filter of the receptor, thus showing a possible pattern of interaction. This knowledge may serve as an input for the design of more promising drugs for autoimmune treatments.

Keywords: neurotoxins, potassium channel, Kv1.3, computational methods, autoimmune diseases

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Authors: Victor Onomza Waziri, John K. Alhassan, Idris Ismaila, Noel Dogonyara

Abstract:

This paper describes the problem of building secure computational services for encrypted information in the Cloud. Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy or confidentiality, availability and integrity of the data and user’s security. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute a theoretical presentations in a high-level computational processes that are based on number theory that is derivable from abstract algebra which can easily be integrated and leveraged in the Cloud computing interface with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based on cryptographic security algorithm.

Keywords: big data analytics, security, privacy, bootstrapping, Fully Homomorphic Encryption Scheme

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Authors: Harsh Sadawarti, Kamal Malik

Abstract:

Humans are the unique and the most powerful creature on this planet just because of the high level of intelligence gifted by nature. Computational Intelligence is highly influenced by the term natural intelligence, neurosciences and mathematics. To deal with the in-depth study of computational intelligence and to utilize it in real-life applications, it is quite important to understand its simulation with the human brain. In this paper, the three important parts, Frontal Lobe, Occipital Lobe and Parietal Lobe of the human brain, are compared with the ANN(Artificial Neural Network), CNN(Convolutional Neural network), and RNN(Recurrent Neural Network), respectively. Intelligent computational systems are created by combining deductive reasoning, logical concepts and high-level algorithms with the simulation and study of the human brain. Human brain is a combination of Physiology, Psychology, emotions, calculations and many other parameters which are of utmost importance that determines the overall intelligence. To create intelligent algorithms, smart machines and to simulate the human brain in an effective manner, it is quite important to have an insight into the human brain and the basic concepts of biological neurosciences.

Keywords: computational intelligence, neurosciences, convolutional neural network, recurrent neural network, artificial neural network, frontal lobe, occipital lobe, parietal lobe

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Authors: Salah Al-Din I. Badran, Samad Ahmadi, Ismail Shahin

Abstract:

A blind source separation method is proposed; in this method we use a non-uniform filter bank and a novel normalisation. This method provides a reduced computational complexity and increased convergence speed comparing to the full-band algorithm. Recently, adaptive sub-band scheme has been recommended to solve two problems: reduction of computational complexity and increase the convergence speed of the adaptive algorithm for correlated input signals. In this work the reduction in computational complexity is achieved with the use of adaptive filters of orders less than the full-band adaptive filters, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each sub-band than the input signal at full bandwidth, and can promote better rates of convergence.

Keywords: blind source separation, computational complexity, subband, convergence speed, mixture

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Authors: Abdusalam Sharf

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In the oil and gas industries, one of the most important issues in drilling wells is understanding the behavior of a flow through an annulus gap in a vertical position, whose outer wall is stationary whilst the inner wall rotates. The main emphasis is placed on a comparison of experimental and computational investigations into the effects of the rotation speed of the inner pipe on the axial velocity profiles. The computational investigations were carried out by employing CFD software, and Gambit and Fluent. Three turbulence models were used: standard, RNG with enhanced wall treatment, and SST model. The profiles of the axial velocity had investigated at different rotation speeds of the inner pipe with three different volumetric flow rates. The comparison results showed that the calculations satisfactorily predict the qualitative features of the axial and swirl velocity profiles and the RNG model performs the best results.

Keywords: computational fluid dynamics (CFD), SST k−ω shear-stress transport (k−ω mode variant), RNG k–ε renormalisation group (k−ε mode variant), y+ dimensionless distance from wall

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Authors: Yosra Mefteh Rekik

Abstract:

A computational agent-based model of financial markets stresses interactions and dynamics among a very diverse set of traders. The growing body of research in this area relies heavily on computational tools which by-pass the restrictions of an analytical method. The main goal of this research is to understand how the stock market operates and behaves how to invest in the stock market and to study traders’ behavior within the context of the artificial stock markets populated by heterogeneous agents. All agents are characterized by adaptive learning behavior represented by the Artificial Neuron Networks. By using agent-based simulations on artificial market, we show that the existence of heterogeneous agents can explain the price dynamics in the financial market. We investigate the relation between market diversity and market efficiency. Our empirical findings demonstrate that greater market heterogeneity play key roles in market efficiency.

Keywords: agent-based modeling, artificial stock market, heterogeneous expectations, financial stylized facts, computational finance

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Authors: Jing Zhao, Yongqing Bai, Qiaofang Shi, Huaihao Zhang

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Advances in software technology enable computational chemistry to be commonly applied in various research fields, especially in pedagogy. Thus, in order to expand and improve experimental instructions of computational chemistry for undergraduates, we designed an introductory experiment—research on acrylamide molecular structure and physicochemical properties. Initially, students construct molecular models of acrylamide and polyacrylamide in Gaussian and Materials Studio software respectively. Then, the infrared spectral data, atomic charge and molecular orbitals of acrylamide as well as solvation effect of polyacrylamide are calculated to predict their physicochemical performance. At last, rheological experiments are used to validate these predictions. Through the combination of molecular simulation (performed on Gaussian, Materials Studio) with experimental verification (rheology experiment), learners have deeply comprehended the chemical nature of acrylamide and polyacrylamide, achieving good learning outcomes.

Keywords: upper-division undergraduate, computer-based learning, laboratory instruction, molecular modeling

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Authors: Salah Al-Din I. Badran, Samad Ahmadi, Ismail Shahin

Abstract:

A blind source separation method is proposed; in this method, we use a non-uniform filter bank and a novel normalisation. This method provides a reduced computational complexity and increased convergence speed comparing to the full-band algorithm. Recently, adaptive sub-band scheme has been recommended to solve two problems: reduction of computational complexity and increase the convergence speed of the adaptive algorithm for correlated input signals. In this work, the reduction in computational complexity is achieved with the use of adaptive filters of orders less than the full-band adaptive filters, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each subband than the input signal at full bandwidth, and can promote better rates of convergence.

Keywords: blind source separation, computational complexity, subband, convergence speed, mixture

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Authors: Keltoum Chahour, Mickael Binois

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Due to a lack of standardization during the invasive fractional flow reserve (FFR) procedure, the index is subject to many sources of uncertainties. In this paper, we investigate -through simulation- the effect of the (FFR) device position and configuration on the obtained value of the (FFR) fraction. For this purpose, we use computational fluid dynamics (CFD) in a 3D domain corresponding to a diseased arterial portion. The (FFR) pressure captor is introduced inside it with a given length and coefficient of bending to capture the (FFR) value. To get over the computational limitations, basically, the time of the simulation is about 2h 15min for one (FFR) value; we generate a Gaussian Process (GP) model for (FFR) prediction. The (GP) model indicates good accuracy and demonstrates the effective error in the measurement created by the random configuration of the pressure captor.

Keywords: fractional flow reserve, Gaussian processes, computational fluid dynamics, drift

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Authors: D. Šedivý, S. Fialová

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The main purpose of this study is to show differences between the numerical solution of the flow through the artificial heart valve using Newtonian or non-Newtonian fluid. The simulation was carried out by a commercial computational fluid dynamics (CFD) package based on finite-volume method. An aortic bileaflet heart valve (Sorin Bicarbon) was used as a pattern for model of real heart valve replacement. Computed tomography (CT) was used to gain the accurate parameters of the valve. Data from CT were transferred in the commercial 3D designer, where the model for CFD was made. Carreau rheology model was applied as non-Newtonian fluid. Physiological data of cardiac cycle were used as boundary conditions. Outputs were taken the leaflets excursion from opening to closure and the fluid dynamics through the valve. This study also includes experimental measurement of pressure fields in ambience of valve for verification numerical outputs. Results put in evidence a favorable comparison between the computational solutions of flow through the mechanical heart valve using Newtonian and non-Newtonian fluid.

Keywords: computational modeling, dynamic mesh, mechanical heart valve, non-Newtonian fluid

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Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra

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In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of Artificial Intelligence (AI), specifically Deep Learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our pioneering approach introduces a hybrid model, amalgamating the strengths of two renowned Convolutional Neural Networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging

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Authors: Gurubasavaraju T. M.

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The magnetorheological (MR) damper could provide variable damping force with respect to the different input magnetic field. The damping force could be estimated through computational analysis using finite element and computational fluid dynamics analysis. The double-ended damper operates without changing the total volume of fluid. In this paper, damping force of double ended damper under different magnetic field is computed. Initially, the magneto-statics analysis carried out to evaluate the magnetic flux density across the fluid flow gap. The respective change in the rheology of the MR fluid is computed by using the experimentally fitted polynomial equation of shear stress versus magnetic field plot of MR fluid. The obtained values are substituted in the Herschel Buckley model to express the non-Newtonian behavior of MR fluid. Later, using computational fluid dynamic (CFD) analysis damping characteristics in terms of force versus velocity and force versus displacement for the respective magnetic field is estimated. The purpose of the present approach is to characterize the preliminary designed MR damper before fabricating.

Keywords: MR fluid, double ended MR damper, CFD, FEA

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Authors: Nicole Ramlachan, Samuel Mark West

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Lung cancer is the leading cause of cancer-associated deaths in North America, with the vast majority being non-small cell lung cancer (NSCLC), with a five-year survival rate of only 24%. Non-invasive discovery of biomarkers associated with early-diagnosis of NSCLC can enable precision oncology efforts using liquid biopsy-based multiomics profiling of plasma. Although tissue biopsies are currently the gold standard for tumor profiling, this method presents many limitations since these are invasive, risky, and sometimes hard to obtain as well as only giving a limited tumor profile. Blood-based tests provides a less-invasive, more robust approach to interrogate both tumor- and non-tumor-derived signals. We intend to examine 30 stage III-IV NSCLC patients pre-surgery and collect plasma samples.Cell-free DNA (cfDNA) will be extracted from plasma, and next-generation sequencing (NGS) performed. Through the analysis of tumor-specific alterations, including single nucleotide variants (SNVs), insertions, deletions, copy number variations (CNVs), and methylation alterations, we intend to identify tumor-derived DNA—ctDNA among the total pool of cfDNA. This would generate data to be used as an accurate form of cancer genotyping for diagnostic purposes. Using liquid biopsies offer opportunities to improve the surveillance of cancer patients during treatment and would supplement current diagnosis and tumor profiling strategies previously not readily available in Trinidad and Tobago. It would be useful and advantageous to use this in diagnosis and tumour profiling as well as to monitor cancer patients, providing early information regarding disease evolution and treatment efficacy, and reorient treatment strategies in, timethereby improving clinical oncology outcomes.

Keywords: genomics, multiomics, clinical genetics, genotyping, oncology, diagnostics

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Authors: Asmaa M. Fahim

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In this investigation, the (E)-2-cyano-3-(dimethylamino)-N-(2,4-dioxo-1,2,3,4-tetrahydropyrimidin-5-yl)acrylam-ide (4) which used TAM as a template which interacts with Methacrylic Acid (MAA) monomer, in the presence of CH₃CN as progen. The TAM-MMA complex interactions are dependent on stable hydrogen bonding interaction between the carboxylic acid group of TAM(Template) and the hydroxyl group of MMA(methyl methacrylate) with minimal interference of porogen CH₃CN. The physical computational studies were used to optimize their structures and frequency calculations. The binding energies between TAM with different monomers showed the most stable molar ratio of 1:4, which was confirmed through experimental analysis. The optimized polymers were investigated in industrial applications.

Keywords: molecular imprinted polymer, computational studies, SEM, spectral analysis, industrial applications

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Authors: Vipan Kumar Sohpal, Rajesh K Sharma

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Diminishing of conventional fuels and hysterical vehicles emission leads to deterioration of the environment, which emphasize the research to work on biofuels. Biofuels from different sources attract the attention of research due to low emission and biodegradability. Emission of carbon monoxide, carbon dioxide and H-C reduced drastically using Biofuels (B-20) combustion. Contrary to the conventional fuel, engine emission results indicated that nitrous oxide emission is higher in Biofuels. So this paper examines and compares the nitrogen oxide emission of Jatropha Curcus (JCO) B-20% blends with the vegetable oil. In addition to that computational analysis of crude non edible oil performed to assess the impact of composition on emission quality. In conclusion, JCO have the potential feedstock for the biodiesel production after the genetic modification in the plant.

Keywords: jatropha curcus, computational analysis, emissions, NOx biofuels

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Authors: Hashem Al Argha

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Cerebral Aneurysms are the ballooning and defect that occurs in the arteries of the brain. This ballooning might enlarge in size due to mechanical forces and could lead to rupture and death. Computational Fluid Dynamics has been used in the recent years in creating a link between engineering sciences and medical sciences. In this paper, the effects of mechanical forces on cerebral aneurysms will be studied. Results of this study show that mechanical forces could lead to rupture of the aneurysm and could lead to death. High mechanical forces including stresses up to 1.7 MPa could pop aneurysms and lead to a brain hemorrhage.

Keywords: computational fluid dynamics, numerical, aneurysm, mechanical forces

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Authors: Dana Craciun, Daniela Dascalu, Adriana Isvoran

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Phthalates are a class of plastic additives that are used to enhance the physical properties of plastics and as solvents in paintings and some of them proved to be of particular concern for the human health. There are insufficient data concerning the health risks of phthalates and further research on evaluating their effects in humans is needed. As humans are not volunteers for such experiments, computational analysis may be used to predict the biological effects of phthalates in humans. Within this study we have used some computational approaches (SwissADME, admetSAR, FAFDrugs) for predicting the absorption, distribution, metabolization, excretion and toxicity (ADME-Tox) profiles and pharmacokinetics for the most common used phthalates. These computational tools are based on quantitative structure-activity relationship modeling approach. The predictions are further compared to the known effects of each considered phthalate in humans and correlations between computational results and experimental data are discussed. Our data revealed that phthalates are a class of compounds reflecting high toxicity both when ingested and when inhaled, but by inhalation their toxicity is even greater. The predicted harmful effects of phthalates are: toxicity and irritations of the respiratory and gastrointestinal tracts, dyspnea, skin and eye irritations and disruption of the functions of liver and of the reproductive system. Many of investigated phthalates are predicted to be able to inhibit some of the cytochromes involved in the metabolism of numerous drugs and consequently to affect the efficiency of administrated treatments for many diseases and to intensify the adverse drugs reactions. The obtained predictions are in good agreement with clinical data concerning the observed effects of some phthalates in cases of acute exposures. Our study emphasizes the possible health effects of numerous phthalates and underlines the applicability of computational methods for predicting the biological effects of xenobiotics.

Keywords: phthalates, ADME-Tox, pharmacokinetics, biological effects

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Authors: Ajay Wadhwa

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A Laboratory course on computational physics is different from the conventional lab course on other topics of physics like Mechanics, Heat, Optics, etc. because it involves active participation of the teacher as well as one-to-one interaction between teacher and the student. The course content requires the teacher to teach programming language as well as numerical methods along with their applications in physics. The task becomes more daunting when about 90% of the students in the class have no previous experience of any programming language. In the presented work, we have described a methodology for conducting the computational physics course by using the Google Drive and Dropitto.me cloud storage services. We have evaluated the performance in a class of sixty students by dividing them equally into four groups. One of the groups was made the peer group on whom the presented methodology was tested. The other groups were taught by using conventional method of classroom lectures. In order to assess our methodology, we analyzed the performance of students in four class tests. A study of certain statistical parameters like the mean, standard deviation, and Z-test hypothesis revealed that the cyber methodology based on cloud storage is more efficient than the conventional method of teaching.

Keywords: computational Physics, Z-test hypothesis, cloud storage, Google drive

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Authors: A. Hira Masood, B. Umer Hameed, C. Ezza Nasir

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Contemporary studies support the strong co-relation between psychology and design. This study elaborates how different psychological personality test can help a fashion designer to judge the needs of their clients with respect to have products which will satisfy the client's request concerning costumised clothing. This study will also help the designer to improve the lacking in the personality and will enable him to put his effort in required areas for grooming the customer, control and direct organization regarding quality maintenance. The use of psychology test to support the choice of certain design strategies that how the right clothing can make client a better intellectual with enhanced self-esteem and confidence. Different projective personality test are being used to suggest to evaluate personality traits. The Rorschach Inkblot Test is projective mental comprising of 10 ink-blots synonymous with the clinical brain research. Lüsher Color Diagnostics measures a person’s psycho physical state, his or her ability to withstand stress to perform and communicate. HTP is a projective responsibility test measuring self-perception, attitudes. The TAT test intend to evaluate a person’s patterns of thoughts, attitudes, observation, capacity and emotional response to this ambiguous test materials. No doubt designers are already crucially redesigning the individuals by their attires, but to expose the behavioral mechanism of the customer, designers should be able to recognize the hidden complexity behind his client by using the above mentioned methods. The study positively finds the design and psychology need to become substantially contacted in order to create a new regime of norms to groom a personality under the concentration and services of a fashion designer in terms of clothing, This interactive activity altimately upgrade design team to help customers to find the suited way to satisfy their needs and wishes, offer client relible relationship and quality management services, and to become more disereable.

Keywords: projective personality tests, customized clothing, Rorschach Inkblot test, TAT, HTP, Lüsher color diagnostics, quality management services

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Authors: Worrapol Koranuntachai, Tonkid Chantrasmi, Udomkiat Nontakaew

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Medical latex gloves are made from the latex compound in production lines. Latex dipping is considered one of the most important processes that directly affect the final product quality. In a continuous production line, a chain conveyor carries the formers through the process and partially submerges them into an open channel flow in a latex dipping tank. In general, the conveyor speed is determined by the desired production capacity, and the latex-dipping tank can then be designed accordingly. It is important to understand the flow behavior in the dipping tank in order to achieve high quality in the process. In this work, Computational Fluid Dynamics (CFD) was used to simulate the flow past an array of formers in a simplified latex dipping process. The computational results showed both the flow structure and the vortex generation between two formers. The maximum shear stress over the surface of the formers was used as the quality metric of the latex-dipping process when adjusting operation parameters.

Keywords: medical latex gloves, latex dipping, dipping tank, computational fluid dynamics

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Authors: Opeyemi Fadipe, Seong Lee, Guangming Chen, Steve Efe

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In comparison to conventional combustion technologies, fluidized bed combustion has several advantages, such as superior heat transfer characteristics due to homogeneous particle mixing, lower temperature needs, nearly isothermal process conditions, and the ability to operate continuously. Computational fluid dynamics (CFD) can help anticipate the intricate combustion process and the hydrodynamics of a fluidized bed thoroughly by using CFD techniques. Bubbling Fluidized bed was model using the Eulerian-Eulerian model, including the kinetic theory of the flow. The model was validated by comparing it with other simulation of the fluidized bed. The effects of operational gas velocity, volume fraction, and feed rate were also investigated numerically. A higher gas velocity and feed rate cause an increase in fluidization of the bed.

Keywords: fluidized bed, operational gas velocity, volume fraction, computational fluid dynamics

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Authors: Ibrahim Elnour Abdelrahman Eltayeb

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Computational modelling is a method used to investigate joint forces during a movement. It can get high accuracy in the joint forces via subject-specific models. However, the construction of subject-specific models remains time-consuming and expensive. The purpose of this paper was to identify what alterations we can make to generic computational models to get a better estimation of the joint forces. It appraised the impact of these alterations on the accuracy of the estimated joint forces. It found different strategies of alterations: joint model, muscle model, and an optimisation problem. All these alterations affected joint contact force accuracy, so showing the potential for improving the model predictions without involving costly and time-consuming medical images.

Keywords: joint force, joint model, optimisation problem, validation

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Authors: S. Kohestani, R. Amrollahi, P. Daryabor

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Microwave diagnostics such as reflectometry are receiving growing attention in magnetic confinement fusionresearch. In order to obtain the better understanding of plasma confinement physics, more detailed measurements on density profile and its fluctuations might be required. A 2D full-wave simulation of ordinary mode propagation has been written in an effort to model effects seen in reflectometry experiment. The code uses the finite-difference-time-domain method with a perfectly-matched-layer absorption boundary to solve Maxwell’s equations.The code has been used to simulate the reflectometer measurement in Alborz Tokamak.

Keywords: reflectometry, simulation, ordinary mode, tokamak

Procedia PDF Downloads 396