Search results for: deep seated gravitational slope deformation

Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 114

Authors: Negadi Kheira, Arab Ahmed, Kamal Elbokl Mohamed, Setti Fatima

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In order to evaluate influences of roots on soil shear strength, monotonic drained and undrained triaxial laboratory tests were carried out on reconstituted specimens at various confining pressure (σc’=50, 100, 200, 300, 400 kPa) and a constant relative density (Dr = 50%). Reinforcement of soil by fibrous roots is crucial for preventing soil erosion and degradation. Therefore, we investigated soil reinforcement by roots of acacia planted in the area of Chlef where shallow landslides and slope instability are frequent. These roots were distributed in soil in two forms: vertically and horizontally. The monotonic test results showed that roots have more impacts on the soil shear strength than the friction angle, and the presence of roots in soil substantially increased the soil shear strength. Also, the results showed that the contribution of roots on the shear strength mobilized increases with increase in the confining pressure.

Keywords: soil, monotonic, triaxial test, root fiber, undrained

Procedia PDF Downloads 415

Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

Procedia PDF Downloads 348

Authors: Izabela L. Ciesielska-Wrόbel

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This paper presents finite element models of the fingertip skin which have been created to simulate the contact of textile objects with the skin to gain a better understanding of the perception of textiles through the skin, so-called Hand of Textiles (HoT). Many objective and subjective techniques have been developed to analyze HoT, however none of them provide exact overall information concerning the sensation of textiles through the skin. As the human skin is a complex heterogeneous hyperelastic body composed of many particles, some simplifications had to be made at the stage of building the models. The same concerns models of woven structures, however their utilitarian value was maintained. The models reflect only friction between skin and woven textiles, deformation of the skin and fabrics when “touching” textiles and heat transfer from the surface of the skin into direction of textiles.

Keywords: fingertip skin models, finite element models, modelling of textiles, sensation of textiles through the skin

Procedia PDF Downloads 465

Authors: Entfellner Manuel, Wannenmacher Helmut, Reisenbauer Josef, Schubert Wulf

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When tunnelling in overstressed weak rocks ("squeezing ground"), two basic design approaches are available: the resistance principle, and the yielding principle. The resistance principle relies on rigid support systems to withstand the ground pressure. Alternatively, the yielding principle prioritizes controlled deformation, allowing the ground to deform without compromising tunnel integrity. This paper highlights the beneficial factors of the yielding principle for conventionally excavated tunnels in overstressed weak rocks. Especially the application of a ductile shotcrete lining with yielding elements is analysed in detail. Construction costs, safety, short- and long-term stabilities are discussed.

Keywords: squeezing ground, yielding principle, yielding element, conventional tunneling

Procedia PDF Downloads 71

Authors: F. Adjel, S. Almi, D. Barkat

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The synergistic solvent extraction of nickel ion from 0.33 mol dm^-3 Na2SO4 aqueous solutions with capric acid (HL) in the absence and presence of Tri-n-octylphosphine oxide (TOPO) in chloroform at 25°C, has been studied. The extracted species when the capric acid compound was used alone, is NiL2 and NiL2(HL). In the presence of TOPO, a remarkable enhancement on the extraction of nickel (II) with 0.02 mol dm^-3 capric acid was observed upon the addition of 0.00125 and 0.0025 mol dm^-3 TOPO in chloroform. From a synergistic extraction- equilibrium study, the synergistic enhancement was ascribed to the adduct formation NiL2(TOPO) and NiL2(HL)(TOPO). The TOPO-HL interaction strongly influences the synergistic extraction efficiency. The synergistic extraction stoichiometry of nickel (II) with capric acid and TOPO is studied with the methods of slope analysis. The equilibrium constants were determined.

Keywords: solvent extraction, nickel(II), capric acid, TOPO, synergism

Procedia PDF Downloads 598

Authors: Arina V. Tankanag, Gennady V. Krasnikov, Nikolai K. Chemeris

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The development of respiration-dependent oscillations in the peripheral blood flow may occur by at least two mechanisms. The first mechanism is related to the change of venous pressure due to mechanical activity of lungs. This phenomenon is known as ‘respiratory pump’ and is one of the mechanisms of venous return of blood from the peripheral vessels to the heart. The second mechanism is related to the vasomotor reflexes controlled by the respiratory modulation of the activity of centers of the vegetative nervous system. Early high phase synchronization of respiration-dependent blood flow oscillations of left and right forearm skin in healthy volunteers at rest was shown. The aim of the work was to study the effect of deep controlled breathing on the phase synchronization of skin blood flow oscillations. 29 normotensive non-smoking young women (18-25 years old) of the normal constitution without diagnosed pathologies of skin, cardiovascular and respiratory systems participated in the study. For each of the participants six recording sessions were carried out: first, at the spontaneous breathing rate; and the next five, in the regimes of controlled breathing with fixed breathing depth and different rates of enforced breathing regime. The following rates of controlled breathing regime were used: 0.25, 0.16, 0.10, 0.07 and 0.05 Hz. The breathing depth amounted to 40% of the maximal chest excursion. Blood perfusion was registered by laser flowmeter LAKK-02 (LAZMA, Russia) with two identical channels (wavelength 0.63 µm; emission power, 0.5 mW). The first probe was fastened to the palmar surface of the distal phalanx of left forefinger; the second probe was attached to the external surface of the left forearm near the wrist joint. These skin zones were chosen as zones with different dominant mechanisms of vascular tonus regulation. The degree of phase synchronization of the registered signals was estimated from the value of the wavelet phase coherence. The duration of all recording was 5 min. The sampling frequency of the signals was 16 Hz. The increasing of synchronization of the respiratory-dependent skin blood flow oscillations for all controlled breathing regimes was obtained. Since the formation of respiration-dependent oscillations in the peripheral blood flow is mainly caused by the respiratory modulation of system blood pressure, the observed effects are most likely dependent on the breathing depth. It should be noted that with spontaneous breathing depth does not exceed 15% of the maximal chest excursion, while in the present study the breathing depth was 40%. Therefore it has been suggested that the observed significant increase of the phase synchronization of blood flow oscillations in our conditions is primarily due to an increase of breathing depth. This is due to the enhancement of both potential mechanisms of respiratory oscillation generation: venous pressure and sympathetic modulation of vascular tone.

Keywords: deep controlled breathing, peripheral blood flow oscillations, phase synchronization, wavelet phase coherence

Procedia PDF Downloads 213

Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

Procedia PDF Downloads 90

Authors: Panagiotis Lemonakis, Nikolaos Moisiadis, Andromachi Gkoutzini, George Kaliabetsos, Nikos Eliou

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The proper surface water drainage not only affects vehicle movement dynamics but also increases the likelihood of an accident due to the fact that inadequate drainage is associated with potential hydroplaning and splash and spray driving conditions. Nine solutions have been proposed to address hydroplaning in sections with inadequate drainage, e.g., augmented superelevation and longitudinal rates, reduction of runoff length, and skew superelevation. The latter has been extensively implemented in highways recently, enhancing the safety level in the applied road segments in regards to the effective drainage of the rainwater. However, the concept of the skew superelevation has raised concerns regarding the driver’s comfort when traveling over skew superelevation sections, particularly at high speeds. These concerns alleviated through the concept of the round-up skew superelevation, which reduces both the lateral and the vertical acceleration imposed to the drivers and hence, improves comfort and traffic safety. Various research studies aimed at investigating driving comfort by evaluating the lateral and vertical accelerations sustained by the road users and vehicles. These studies focused on the influence of the skew superelevation to passenger cars, buses and trucks, and the drivers themselves, traveling at a certain range of speeds either below or above the design speed. The outcome of these investigations which based on the use of simulations, revealed that the imposed accelerations did not exceed the statutory thresholds even when the travelling speed was significantly greater than the design speed. Nevertheless, the effect of the skew superelevation to other vehicle types for instance, motorcycles, has not been investigated so far. The present research study aims to bridge this gap by investigating the impact of skew superelevation on the motorcycle rider’s comfort. Power two-wheeler riders are susceptible to any changes on the pavement surface and therefore a comparison between the traditional superelevation practice and the skew superelevation concept is of paramount importance. The methodology based on the utilization of sophisticated software in order to design the model of the road for several values of the longitudinal slope. Based on the values of the slopes and the use of a mathematical equation, the accelerations imposed on the wheel of the motorcycle were calculated. Due to the fact that the final aim of the study is the influence of the skew superelevation to the rider, it was deemed necessary to convey the calculated accelerations from the wheel to the rider. That was accomplished by implementing the quarter car suspension model adjusted to the features of two-wheeler vehicles. Finally, the accelerations derived from this process evaluated according to specific thresholds originated from the International Organization for Standardization, which correspond to certain levels of comfort. The most important conclusion drawn is that the comfort of the riders is not dependent on the form of road gradient to a great extent due to the fact that the vertical acceleration imposed to the riders took similar values regardless of the value of the longitudinal slope.

Keywords: acceleration, comfort, motorcycle, safety, skew superelevation

Procedia PDF Downloads 154

Authors: Majid Samiee Zenoozian

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The Persian Gulf is a bordering sea with an normal depth of 35 m and a supreme depth of 100 m near its narrow appearance. Its lengthen bathymetric axis divorces two main geological shires — the steady Arabian Foreland and the unbalanced Iranian Fold Belt — which are imitated in the conflicting shore and bathymetric morphologies of Arabia and Iran. The sediments were experimented with from 72 offshore positions through an oceanographic cruise in the winter of 2018. Throughout the observation era, several storms and river discharge actions happened, as well as the major flood on record since 1982. Suspended-sediment focus at all three sites varied in reaction to both wave resuspension and advection of river-derived sediments. We used hydrological models to evaluation and associate the wave height and inundation distance required to carriage the rocks inland. Our results establish that no known or possible storm happening on the Makran coast is accomplished of detaching and transporting the boulders. The fluid mud consequently is conveyed seaward due to gravitational forcing. The measured sediment focus and velocity profiles on the shelf provide a strong indication to provision this assumption. The sediment model is joined with a 3D hydrodynamic module in the Environmental Fluid Dynamics Code (EFDC) model that offers data on estuarine rotation and salinity transport under normal temperature conditions. 3-D sediment transport from model simulations specify dynamic sediment resuspension and transport near zones of highly industrious oyster beds.

Keywords: sediment transport, storm, coast, fluid dynamics

Procedia PDF Downloads 115

Authors: Ahmed Tamer AlMotasem, Jens Bergström, Anders Gåård, Pavel Krakhmalev, Thijs Jan Holleboom

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In sheet metal forming processes, accumulation and transfer of sheet material to tool surfaces, often referred to as galling, is the major cause of tool failure. Initiation of galling is assumed to occur due to local adhesive wear between two surfaces. Therefore, reducing adhesion between the tool and the work sheet has a great potential to improve the tool materials galling resistance. Experimental observations and theoretical studies show that the presence of primary micro-sized carbides and/or nitrides in alloyed steels may significantly improve galling resistance. Generally, decreased adhesion between the ceramic precipitates and the sheet material counter-surface are attributed as main reason to the latter observations. On the other hand, adhesion processes occur at an atomic scale and, hence, fundamental understanding of galling can be obtained via atomic scale simulations. In the present study, molecular dynamics simulations are used, with utilizing second nearest neighbor embedded atom method potential to investigate the influence of nano-sized cementite precipitates embedded in tool atoms. The main aim of the simulations is to gain new fundamental knowledge on galling initiation mechanisms. Two tool/work piece configurations, iron/iron and iron-cementite/iron, are studied under dry sliding conditions. We find that the average frictional force decreases whereas the normal force increases for the iron-cementite/iron system, in comparison to the iron/iron configuration. Moreover, the average friction coefficient between the tool/work-piece decreases by about 10 % for the iron-cementite/iron case. The increase of the normal force in the case of iron-cementite/iron system may be attributed to the high stiffness of cementite compared to bcc iron. In order to qualitatively explain the effect of cementite on adhesion, the adhesion force between self-mated iron/iron and cementite/iron surfaces has been determined and we found that iron/cementite surface exhibits lower adhesive force than that of iron-iron surface. The variation of adhesion force with temperature was investigated up to 600 K and we found that the adhesive force, generally, decreases with increasing temperature. Structural analyses show that plastic deformation is the main deformation mechanism of the work-piece, accompanied with dislocations generation.

Keywords: adhesion, cementite, galling, molecular dynamics

Procedia PDF Downloads 301

Authors: Brian E. Usibe

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This paper addresses the problem of a linear crack located in the middle of a homogeneous elastic media under normal tension-compression harmonic loading. The problem of deformation of the fractured media is solved using the direct finite element numerical procedure, including the analysis of the dynamic field variables of the problem. A finite element algorithm that satisfies the unilateral Signorini contact constraint is also presented for the solution of the contact interaction of the crack faces and how this accounts for the qualitative and quantitative changes in the solution when determining the dynamic fracture parameter.

Keywords: harmonic loading, linear crack, fracture parameter, wave number, FEA, contact interaction

Procedia PDF Downloads 42

Authors: Vyacheslav Furtak, Merja Roivainen, Olga Mirochnichenko, Majid Laassri, Bella Bidzhieva, Tatiana Zagorodnyaya, Vladimir Chizhikov, Konstantin Chumakov

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Molecular epidemiology and environmental surveillance are parts of a rational strategy to control infectious diseases. They have been widely used in the worldwide campaign to eradicate poliomyelitis, which otherwise would be complicated by the inability to rapidly respond to outbreaks and determine sources of the infection. The conventional scheme involves isolation of viruses from patients and the environment, followed by their identification by nucleotide sequences analysis to determine phylogenetic relationships. This is a tedious and time-consuming process that yields definitive results when it may be too late to implement countermeasures. Because of the difficulty of high-throughput full-genome sequencing, most such studies are conducted by sequencing only capsid genes or their parts. Therefore the important information about the contribution of other parts of the genome and inter- and intra-species recombination to viral evolution is not captured. Here we propose a new approach based on the rapid concentration of sewage samples with tangential flow filtration followed by deep sequencing and reconstruction of nucleotide sequences of viruses present in the samples. The entire nucleic acids content of each sample is sequenced, thus preserving in digital format the complete spectrum of viruses. A set of rapid algorithms was developed to separate deep sequence reads into discrete populations corresponding to each virus and assemble them into full-length consensus contigs, as well as to generate a complete profile of sequence heterogeneities in each of them. This provides an effective approach to study molecular epidemiology and evolution of natural viral populations.

Keywords: poliovirus, eradication, environmental surveillance, laboratory diagnosis

Procedia PDF Downloads 281

Authors: M. Y. Ismail, M. Inam, A. F. M. Zain, N. Misran

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Progressive phase distribution is an important consideration in reflect array antenna design which is required to form a planar wave in front of the reflect array aperture. This paper presents a detailed mathematical model in order to determine the required reflection phase values from individual element of a reflect array designed in Ku-band frequency range. The proposed technique of obtaining reflection phase can be applied for any geometrical design of elements and is independent of number of array elements. Moreover the model also deals with the solution of reflect array antenna design with both centre and off-set feed configurations. The theoretical modeling has also been implemented for reflect arrays constructed on 0.508 mm thickness of different dielectric substrates. The results show an increase in the slope of the phase curve from 4.61°/mm to 22.35°/mm by varying the material properties.

Keywords: mathematical modeling, progressive phase distribution, reflect array antenna, reflection phase

Procedia PDF Downloads 383

Authors: Ali Kadir, O. Anwar Beg

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Thermal barrier coatings are among the most popular methods for providing corrosion protection in high temperature applications including aircraft engine systems, external spacecraft structures, rocket chambers etc. Many different materials are available for such coatings, of which ceramics generally perform the best. Motivated by these applications, the current investigation presents detailed finite element simulations of coating stress analysis for a 3- dimensional, 3-layered model of a test sample representing a typical gas turbine component scenario. Structural steel is selected for the main inner layer, Titanium (Ti) alloy for the middle layer and Silicon Carbide (SiC) for the outermost layer. The model dimensions are 20 mm (width), 10 mm (height) and three 1mm deep layers. ANSYS software is employed to conduct three types of analysis- static structural, thermal stress analysis and also computational fluid dynamic erosion/corrosion analysis (via ANSYS FLUENT). The specified geometry which corresponds to corrosion test samples exactly is discretized using a body-sizing meshing approach, comprising mainly of tetrahedron cells. Refinements were concentrated at the connection points between the layers to shift the focus towards the static effects dissipated between them. A detailed grid independence study is conducted to confirm the accuracy of the selected mesh densities. To recreate gas turbine scenarios; in the stress analysis simulations, static loading and thermal environment conditions of up to 1000 N and 1000 degrees Kelvin are imposed. The default solver was used to set the controls for the simulation with the fixed support being set as one side of the model while subjecting the opposite side to a tabular force of 500 and 1000 Newtons. Equivalent elastic strain, total deformation, equivalent stress and strain energy were computed for all cases. Each analysis was duplicated twice to remove one of the layers each time, to allow testing of the static and thermal effects with each of the coatings. ANSYS FLUENT simulation was conducted to study the effect of corrosion on the model under similar thermal conditions. The momentum and energy equations were solved and the viscous heating option was applied to represent improved thermal physics of heat transfer between the layers of the structures. A Discrete Phase Model (DPM) in ANSYS FLUENT was employed which allows for the injection of continuous uniform air particles onto the model, thereby enabling an option for calculating the corrosion factor caused by hot air injection (particles prescribed 5 m/s velocity and 1273.15 K). Extensive visualization of results is provided. The simulations reveal interesting features associated with coating response to realistic gas turbine loading conditions including significantly different stress concentrations with different coatings.

Keywords: thermal coating, corrosion, ANSYS FEA, CFD

Procedia PDF Downloads 135

Authors: Renato Santos Paulinelli Raposo, Vinicius Resende Domingues, Manoel Porfirio Cordao Neto

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Rapid drawdown is one of the cases referred to ground stability study in dam projects. Due to the complexity generated by the combination of loads and the difficulty in determining the parameters, analyses of rapid drawdown are usually performed considering the immediate reduction of water level upstream. The proposal of a simulation, considering the gradual reduction in water level upstream, requires knowledge of parameters about consolidation and those related to unsaturated soil. In this context, the purpose of this study is to understand the methodology of collection and analysis of parameters to simulate a rapid drawdown in dams. Using a numerical tool, the study is complemented with a hypothetical case study that can assist the practical use of data compiled. The referenced dam presents homogeneous section composed of clay soil, a height of 70 meters, a width of 12 meters, and upstream slope with inclination 1V:3H.

Keywords: dam, GeoStudio, rapid drawdown, stability analysis

Procedia PDF Downloads 253

Authors: Chi Zhang, Jun Jiang

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Constitutive equations are very important in finite element (FE) modeling, and the accuracy of the material constants in the equations have significant effects on the accuracy of the FE models. A wide range of constitutive equations are available; however, fitting the material constants in the constitutive equations could be complex and time-consuming due to the strong non-linearity and relationship between the constants. This work will focus on the development of a set of unified MATLAB programs for fitting the material constants in the constitutive equations efficiently. Users will only need to supply experimental data in the required format and run the program without modifying functions or precisely guessing the initial values, or finding the parameters in previous works and will be able to fit the material constants efficiently.

Keywords: constitutive equations, FE modelling, MATLAB program, non-linear curve fitting

Procedia PDF Downloads 99

Authors: F. Ghazalnaz Sharifonnasabi, Iman Makhdoom

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Breast cancer is a serious health concern that affects many people around the world. According to a study published in the Breast journal, the global burden of breast cancer is expected to increase significantly over the next few decades. The number of deaths from breast cancer has been increasing over the years, but the age-standardized mortality rate has decreased in some countries. It’s important to be aware of the risk factors for breast cancer and to get regular check- ups to catch it early if it does occur. Machin learning techniques have been used to aid in the early detection and diagnosis of breast cancer. These techniques, that have been shown to be effective in predicting and diagnosing the disease, have become a research hotspot. In this study, we consider two deep learning approaches including: Multi-Layer Perceptron (MLP), and Convolutional Neural Network (CNN). We also considered the five-machine learning algorithm titled: Decision Tree (C4.5), Naïve Bayesian (NB), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) Algorithm and XGBoost (eXtreme Gradient Boosting) on the Breast Cancer Wisconsin Diagnostic dataset. We have carried out the process of evaluating and comparing classifiers involving selecting appropriate metrics to evaluate classifier performance and selecting an appropriate tool to quantify this performance. The main purpose of the study is predicting and diagnosis breast cancer, applying the mentioned algorithms and also discovering of the most effective with respect to confusion matrix, accuracy and precision. It is realized that CNN outperformed all other classifiers and achieved the highest accuracy (0.982456). The work is implemented in the Anaconda environment based on Python programing language.

Keywords: breast cancer, multi-layer perceptron, Naïve Bayesian, SVM, decision tree, convolutional neural network, XGBoost, KNN

Procedia PDF Downloads 75

Authors: Roman Kalvin, Anam Nadeem, Saba Arif

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Turbocharger is a device that is driven by the turbine and increases efficiency and power output of the engine by forcing external air into the combustion chamber. This study focused on the distribution of stress on the turbine blades and total deformation that may occur during its working along with turbocharger to carry out its static structural analysis of turbine blades. Structural steel was selected as the material for turbocharger. Assembly of turbocharger and turbine blades was designed on PRO ENGINEER. Furthermore, the structural analysis is performed by using ANSYS. This research concluded that by using structural steel, the efficiency of engine is improved and by increasing number of turbine blades, more waste heat from combustion chamber is emitted.

Keywords: turbocharger, turbine blades, structural steel, ANSYS

Procedia PDF Downloads 244

Authors: S. Olyaee, M. Seifouri, A. Nikoosohbat, M. Shams Esfand Abadi

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Photonic Crystal Fibers (PCFs) can be used in optical communications as transmission lines. For this reason, the PCFs with low confinement loss, low chromatic dispersion, and low nonlinear effects are highly suitable transmission media. In this paper, we introduce a new design of index-guiding photonic crystal fiber (IG-PCF) with ultra-low chromatic dispersion, low nonlinearity effects, and low confinement loss. Relatively low dispersion is achieved in the wavelength range of 1200 to 1600 nm using the proposed design. According to the new structure of IG-PCF presented in this study, the chromatic dispersion slope is -30(ps/km.nm) and the confinement loss reaches below 10-7 dB/km. While in the wavelength range mentioned above at the same time an effective area of more than 50.2μm2 is obtained.

Keywords: optical communication systems, index-guiding, dispersion, confinement loss, photonic crystal fiber

Procedia PDF Downloads 609

Authors: Fatna Benmessaoud, Mohammed Cheikh, Vencent Velay, Vanessa Vidal, Farhad Rezai-Aria, Christine Boher

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Ti-6Al-4V titanium alloy is one of the most widely used materials in aeronautical and aerospace industries. Because of its high specific strength, good fatigue, and corrosion resistance, this alloy is very suitable for moderate temperature applications. At room temperature, Ti-6Al-4V mechanical behavior is generally controlled by the behavior of alpha phase (beta phase percent is less than 8%). The plastic strain of this phase notably based on crystallographic slip can be hindered by various obstacles and mechanisms (crystal lattice friction, sessile dislocations, strengthening by solute atoms and grain boundaries…). The grains aspect of alpha phase (its morphology and texture) and the nature of its crystallographic lattice (which is hexagonal compact) give to plastic strain heterogeneous, discontinuous and anisotropic characteristics at the local scale. The aim of this work is to develop a multi-scale model for Ti-6Al-4V mechanical behavior using crystal plasticity approach; this multi-scale model is used then to investigate grains size, dispersion of grains size, crystallographic texture and slip systems activation effects on Ti-6Al-4V mechanical behavior under monotone quasi-static loading. Nine representative elementary volume (REV) are built for taking into account the physical elements (grains size, dispersion and crystallographic) mentioned above, then boundary conditions of tension test are applied. Finally, simulation of the mechanical behavior of Ti-6Al-4V and study of slip systems activation in alpha phase is reported. The results show that the macroscopic mechanical behavior of Ti-6Al-4V is strongly linked to the active slip systems family (prismatic, basal or pyramidal). The crystallographic texture determines which family of slip systems can be activated; therefore it gives to the plastic strain a heterogeneous character thus an anisotropic macroscopic mechanical behavior of Ti-6Al-4V alloy modeled. The grains size influences also on mechanical proprieties of Ti-6Al-4V, especially on the yield stress; by decreasing of the grain size, the yield strength increases. Finally, the grains' distribution which characterizes the morphology aspect (homogeneous or heterogeneous) gives to the deformation fields distribution enough heterogeneity because the crystallographic slip is easier in large grains compared to small grains, which generates a localization of plastic deformation in certain areas and a concentration of stresses in others.

Keywords: multi-scale modeling, Ti-6Al-4V alloy, crystal plasticity, grains size, crystallographic texture

Procedia PDF Downloads 157

Authors: S. Olyaee, M. Seifouri, A. Nikoosohbat, M. Shams Esfand Abadi

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Photonic Crystal Fibers (PCFs) can be used in optical communications as transmission lines. For this reason, the PCFs with low confinement loss, low chromatic dispersion, and low nonlinear effects are highly suitable transmission media. In this paper, we introduce a new design of index-guiding nanostructured photonic crystal fiber (IG-NPCF) with ultra-low chromatic dispersion, low nonlinearity effects, and low confinement loss. Relatively low dispersion is achieved in the wavelength range of 1200 to 1600nm using the proposed design. According to the new structure of nanostructured PCF presented in this study, the chromatic dispersion slope is -30(ps/km.nm) and the confinement loss reaches below 10-7 dB/km. While in the wavelength range mentioned above at the same time an effective area of more than 50.2μm2 is obtained.

Keywords: optical communication systems, nanostructured, index-guiding, dispersion, confinement loss, photonic crystal fiber

Procedia PDF Downloads 560

Authors: Dimitrios Triantakonstantis, Demetris Stathakis

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Urban areas have been expanded throughout the globe. Monitoring and modeling urban growth have become a necessity for a sustainable urban planning and decision making. Urban prediction models are important tools for analyzing the causes and consequences of urban land use dynamics. The objective of this research paper is to analyze and model the urban change, which has been occurred from 1990 to 2000 using CORINE land cover maps. The model was developed using drivers of urban changes (such as road distance, slope, etc.) under an Artificial Neural Network modeling approach. Validation was achieved using a prediction map for 2006 which was compared with a real map of Urban Atlas of 2006. The accuracy produced a Kappa index of agreement of 0,639 and a value of Cramer's V of 0,648. These encouraging results indicate the importance of the developed urban growth prediction model which using a set of available common biophysical drivers could serve as a management tool for the assessment of urban change.

Keywords: artificial neural networks, CORINE, urban atlas, urban growth prediction

Procedia PDF Downloads 529

Authors: Yujiang Wu

Abstract:

As electrical machine (e-machine) power density re-querulents become more stringent in vehicle electrification, mounting a temperature sensor for e-machine stator windings becomes increasingly difficult. This can lead to higher manufacturing costs, complicated harnesses, and reduced reliability. In this paper, we propose a deep-learning method for predicting electric machine winding temperature, which can either replace the sensor entirely or serve as a backup to the existing sensor. We compare the performance of our method, the stateful long short-term memory networks (LSTM) with truncated backpropagation through time (TBTT), with that of linear regression, as well as stateless LSTM with/without residual connection. Our results demonstrate the strength of combining stateful LSTM and TBTT in tackling nonlinear time series prediction problems with long sequence lengths. Additionally, in industrial applications, high-temperature region prediction accuracy is more important because winding temperature sensing is typically used for derating machine power when the temperature is high. To evaluate the performance of our algorithm, we developed a temperature-stratified MSE. We propose a simple but effective data preprocessing trick to improve the high-temperature region prediction accuracy. Our experimental results demonstrate the effectiveness of our proposed method in accurately predicting winding temperature, particularly in high-temperature regions, while also reducing manufacturing costs and improving reliability.

Keywords: deep learning, electrical machine, functional safety, long short-term memory networks (LSTM), thermal management, time series prediction

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Authors: Kwan U. Kim, Jin Sim, Ryong Jin Jang, Sung Duk Kim

Abstract:

108 years have passed since a great number of physicists explained astronomical and physical phenomena by solving geodesic equations in the Schwarzschild metric. However, when solving the geodesic equations in Schwarzschild metric, they did not correctly solve one branch of the component of space among spatial and temporal components of four-dimensional force and did not come up with physical laws correctly by means of physical analysis from the results obtained by solving the geodesic equations. In addition, they did not treat the astronomical and physical phenomena in a physical way based on the correct physical laws obtained from the solution of the geodesic equations in the Schwarzschild metric. Therefore, some former scholars mentioned that Einstein’s theoretical basis of a general theory of relativity was obscure and incorrect, but they did not give a correct physical solution to the problems. Furthermore, since the general theory of relativity has not given a quantitative solution to obscure and incorrect problems, the generalization of gravitational theory has not yet been successfully completed, although former scholars have thought of it and tried to do it. In order to solve the problems, it is necessary to explore the obscure and incorrect problems in a general theory of relativity based on the physical laws and to find out the methodology for solving the problems. Therefore, as the first step toward achieving this purpose, the right solution of the geodesic equation in the Schwarzschild metric has been presented. Next, the correct physical laws found by making a physical analysis of the results have been presented, the obscure and incorrect problems have been shown, and an analysis of them has been made based on the physical laws. In addition, the experimental verification of the physical laws found by us has been made.

Keywords: equivalence principle, general relativity, geometrodynamics, Schwarzschild, Poincaré

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Authors: Angelo Thurairajah

Abstract:

Sufficient ultimate deformation is necessary to demonstrate the member ductility, which is dependent on the section and the material ductility. The concrete cracking phase of softening prior to the plastic hinge formation is an essential feature as well. The nature of the overload behaviour is studied using the order of the ultimate deflection. The ultimate deflection is primarily dependent on the slenderness (span to depth ratio), the ductility of the reinforcing steel, the degree of moment redistribution, the type of loading, and the support conditions. The ultimate deflection and the degree of moment redistribution from the analytical study are in good agreement with the experimental results and the moment redistribution provisions of the Australian Standards AS3600 Concrete Structures Code.

Keywords: ductility, softening, ultimate deflection, overload behaviour, moment redistribution

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Authors: Souradip Paul, Arijit Paramanick, M. Suheshkumar Singh

Abstract:

Traumatic injury is the leading worldwide health problem. Annually, millions of surgical wounds are created for the sake of routine medical care. The healing of these unintended injuries is always monitored based on visual inspection. The maximal restoration of tissue functionality remains a significant concern of clinical care. Although minor injuries heal well with proper care and medical treatment, large injuries negatively influence various factors (vasculature insufficiency, tissue coagulation) and cause poor healing. Demographically, the number of people suffering from severe wounds and impaired healing conditions is burdensome for both human health and the economy. An incomplete understanding of the functional and molecular mechanism of tissue healing often leads to a lack of proper therapies and treatment. Hence, strong and promising medical guidance is necessary for monitoring the tissue regeneration processes. Photoacoustic imaging (PAI), is a non-invasive, hybrid imaging modality that can provide a suitable solution in this regard. Light combined with sound offers structural, functional and molecular information from the higher penetration depth. Therefore, molecular and structural mechanisms of tissue repair will be readily observable in PAI from the superficial layer and in the deep tissue region. Blood vessel formation and its growth is an essential tissue-repairing components. These vessels supply nutrition and oxygen to the cell in the wound region. Angiogenesis (formation of new capillaries from existing blood vessels) contributes to new blood vessel formation during tissue repair. The betterment of tissue healing directly depends on angiogenesis. Other optical microscopy techniques can visualize angiogenesis in micron-scale penetration depth but are unable to provide deep tissue information. PAI overcomes this barrier due to its unique capability. It is ideally suited for deep tissue imaging and provides the rich optical contrast generated by hemoglobin in blood vessels. Hence, an early angiogenesis detection method provided by PAI leads to monitoring the medical treatment of the wound. Along with functional property, mechanical property also plays a key role in tissue regeneration. The wound heals through a dynamic series of physiological events like coagulation, granulation tissue formation, and extracellular matrix (ECM) remodeling. Therefore tissue elasticity changes, can be identified using non-contact photoacoustic elastography (PAE). In a nutshell, angiogenesis and biomechanical properties are both critical parameters for tissue healing and these can be characterized in a single imaging modality (PAI).

Keywords: PAT, wound healing, tissue coagulation, angiogenesis

Procedia PDF Downloads 106

Authors: Apeng Dong, Shu Li, Wenguo Zhu, Ming Qi, Qiuyi Xu

Abstract:

The primary objective of this paper is to focus on the elasticity properties of three-dimensional full five directional (3Df5d) braided composite. A large body of research has been focused on the 3D four directional (4d) and 3D five directional (5d) structure but not much research on the 3Df5d material. Generally, the influence of the yarn shape on mechanical properties of braided materials tends to be ignored, which makes results too ideal. Besides, with the improvement of the computational ability, people are accustomed to using computers to predict the material parameters, which fails to give an explicit and concise result facilitating production and application. Based on the traditional mechanics, this paper firstly deduced the functional relation between elasticity properties and braiding parameters. In addition, considering the actual shape of yarns after consolidation, the longitudinal modulus is modified and defined practically. Firstly, the analytic model is established based on the certain assumptions for the sake of clarity, this paper assumes that: A: the cross section of axial yarns is square; B: The cross section of braiding yarns is hexagonal; C: the characters of braiding yarns and axial yarns are the same; D: The angle between the structure boundary and the projection of braiding yarns in transverse plane is 45°; E: The filling factor ε of composite yarns is π/4; F: The deformation of unit cell is under constant strain condition. Then, the functional relation between material constants and braiding parameters is systematically deduced aimed at the yarn deformation mode. Finally, considering the actual shape of axial yarns after consolidation, the concept of technology factor is proposed and the longitudinal modulus of the material is modified based on the energy theory. In this paper, the analytic solution of material parameters is given for the first time, which provides a good reference for further research and application for 3Df5d materials. Although the analysis model is established based on certain assumptions, the analysis method is also applicable for other braided structures. Meanwhile, it is crucial that the cross section shape and straightness of axial yarns play dominant roles in the longitudinal elastic property. So in the braiding and solidifying process, the stability of the axial yarns should be guaranteed to increase the technology factor to reduce the dispersion of material parameters. Overall, the elastic properties of this materials are closely related to the braiding parameters and can be strongly designable, and although the longitudinal modulus of the material is greatly influenced by the technology factors, it can be defined to certain extent.

Keywords: analytic solution, braided composites, elasticity properties, technology factor

Procedia PDF Downloads 237

Authors: Zeinab Sanaee, Hossein Jafaripour

Abstract:

Copper is an excellent conductive material that is widely used in the energy devices such as Lithium-ion batteries and supercapacitors as the current collector. On the other hand, copper oxide nanowires have been used in these applications as potential electrode material. In this paper, nanowires of Copper and Copper oxide have been synthesized through a simple and time and cost-effective approach. The thermally grown Copper oxide nanowires have been converted into Copper nanowires through annealing in the Hydrogen atmosphere in a DC-PECVD system. To have a proper Copper nanostructure formation, an Au nanolayer was coated on the surface of Copper oxide nanowires. The results show the successful achievement of Copper nanowires without deformation or cracking. These structures have a great potential for Lithium-ion batteries and supercapacitors.

Keywords: Copper, Copper oxide, nanowires, Hydrogen annealing, Lithium ion battery

Procedia PDF Downloads 87

Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, A. H. M. R. Imon

Abstract:

Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in two types of LFRM namely the full model of LFRM and in LFRM when the slope is estimated using a nonparametric method. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

Procedia PDF Downloads 455