Search results for: excitation propagation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1148

Search results for: excitation propagation

308 Electric Arc Furnaces as a Source of Voltage Fluctuations in the Power System

Authors: Zbigniew Olczykowski

Abstract:

The paper presents the impact of work on the electric arc furnace power grid. The arc furnace operating will be modeled at different power conditions of steelworks. The paper will describe how to determine the increase in voltage fluctuations caused by working in parallel arc furnaces. The analysis of indicators characterizing the quality of electricity recorded during several cycles of measurement made at the same time at three points grid, with different power and different short-circuit rated voltage, will be carried out. The measurements analysis presented in this paper were conducted in the mains of one of the Polish steel. The indicators characterizing the quality of electricity was recorded during several cycles of measurement while making measurements at three points of different power network short-circuit power and various voltage ratings. Measurements of power quality indices included the one-week measurement cycles in accordance with the EN-50160. Data analysis will include the results obtained during the simultaneous measurement of three-point grid. This will determine the actual propagation of interference generated by the device. Based on the model studies and measurements of quality indices of electricity we will establish the effect of a specific arc on the mains. The short-circuit power network’s minimum value will also be estimated, this is necessary to limit the voltage fluctuations generated by arc furnaces.

Keywords: arc furnaces, long-term flicker, measurement and modeling of power quality, voltage fluctuations

Procedia PDF Downloads 257
307 A New Correlation Between SPT-N and SSPT-N values for Various Soil Types in Peninsular Malaysia

Authors: Abdull Halim

Abstract:

The Standard Penetration Test (SPT-N) is the most common in situ test for soil investigations. The Shearing Seismic Standard Penetration Test (SSPT-N), on the other hand, is a new method using shearing wave with propagation exponent equation between the shearing wave, Vs., and hardness, N values without any need for borehole data. Due to the fast and accurate results that can be obtained, the SSPT has found many applications such as in the field rectification buried pipe line, the acid tank settlement and foundation design analyses, and the quality control assessment. Many geotechnical regimes and properties have attempted to correlate both the SSPT and the SPT-N values. Various foundation design methods have been developed based on the outcomes of these tests. Hence, it is pertinent to correlate these tests so that either one of the test can be used in the absence of the other, especially for preliminary evaluation and design purposes. The primary purpose of this study was to investigate the relationship between the SSPT-N and SPT-N values for different types of cohesive soil in Peninsular Malaysia. Data were collected from four different sites, and the correlations were established between the hardness N values, principal stress-strain Mohr circle curve, cohesion, friction angle and vertical effective stress. A positive exponent relationship was found between the shearing wave, sVs., and the hardness N values of the soil. In general, the SSPT-N value was slightly lower than the SPT-N value due to the upper limit boundary of the soil layer.

Keywords: InsituSoil determination; shearing wave; hardness; correlation, SSPT-N, SPT-N

Procedia PDF Downloads 160
306 Numerical Modelling of Dust Propagation in the Atmosphere of Tbilisi City in Case of Western Background Light Air

Authors: N. Gigauri, V. Kukhalashvili, A. Surmava, L. Intskirveli, L. Gverdtsiteli

Abstract:

Tbilisi, a large city of the South Caucasus, is a junction point connecting Asia and Europe, Russia and republics of the Asia Minor. Over the last years, its atmosphere has been experienced an increasing anthropogenic load. Numerical modeling method is used for study of Tbilisi atmospheric air pollution. By means of 3D non-linear non-steady numerical model a peculiarity of city atmosphere pollution is investigated during background western light air. Dust concentration spatial and time changes are determined. There are identified the zones of high, average and less pollution, dust accumulation areas, transfer directions etc. By numerical modeling, there is shown that the process of air pollution by the dust proceeds in four stages, and they depend on the intensity of motor traffic, the micro-relief of the city, and the location of city mains. In the interval of time 06:00-09:00 the intensive growth, 09:00-15:00 a constancy or weak decrease, 18:00-21:00 an increase, and from 21:00 to 06:00 a reduction of the dust concentrations take place. The highly polluted areas are located in the vicinity of the city center and at some peripherical territories of the city, where the maximum dust concentration at 9PM is equal to 2 maximum allowable concentrations. The similar investigations conducted in case of various meteorological situations will enable us to compile the map of background urban pollution and to elaborate practical measures for ambient air protection.

Keywords: air pollution, dust, numerical modeling, urban

Procedia PDF Downloads 162
305 Estimating Anthropometric Dimensions for Saudi Males Using Artificial Neural Networks

Authors: Waleed Basuliman

Abstract:

Anthropometric dimensions are considered one of the important factors when designing human-machine systems. In this study, the estimation of anthropometric dimensions has been improved by using Artificial Neural Network (ANN) model that is able to predict the anthropometric measurements of Saudi males in Riyadh City. A total of 1427 Saudi males aged 6 to 60 years participated in measuring 20 anthropometric dimensions. These anthropometric measurements are considered important for designing the work and life applications in Saudi Arabia. The data were collected during eight months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining 15 dimensions were set to be the measured variables (Model’s outcomes). The hidden layers varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was able to estimate the body dimensions of Saudi male population in Riyadh City. The network's mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found to be 0.0348 and 3.225, respectively. These results were found less, and then better, than the errors found in the literature. Finally, the accuracy of the developed neural network was evaluated by comparing the predicted outcomes with regression model. The ANN model showed higher coefficient of determination (R2) between the predicted and actual dimensions than the regression model.

Keywords: artificial neural network, anthropometric measurements, back-propagation

Procedia PDF Downloads 465
304 Studying the Dynamical Response of Nano-Microelectromechanical Devices for Nanomechanical Testing of Nanostructures

Authors: Mohammad Reza Zamani Kouhpanji

Abstract:

Characterizing the fatigue and fracture properties of nanostructures is one of the most challenging tasks in nanoscience and nanotechnology due to lack of a MEMS/NEMS device for generating uniform cyclic loadings at high frequencies. Here, the dynamic response of a recently proposed MEMS/NEMS device under different inputs signals is completely investigated. This MEMS/NEMS device is designed and modeled based on the electromagnetic force induced between paired parallel wires carrying electrical currents, known as Ampere’s Force Law (AFL). Since this MEMS/NEMS device only uses two paired wires for actuation part and sensing part, it represents highly sensitive and linear response for nanostructures with any stiffness and shapes (single or arrays of nanowires, nanotubes, nanosheets or nanowalls). In addition to studying the maximum gains at different resonance frequencies of the MEMS/NEMS device, its dynamical responses are investigated for different inputs and nanostructure properties to demonstrate the capability, usability, and reliability of the device for wide range of nanostructures. This MEMS/NEMS device can be readily integrated into SEM/TEM instruments to provide real time study of the fatigue and fracture properties of nanostructures as well as their softening or hardening behaviors, and initiation and/or propagation of nanocracks in them.

Keywords: MEMS/NEMS devices, paired wire actuators and sensors, dynamical response, fatigue and fracture characterization, Ampere’s force law

Procedia PDF Downloads 375
303 Prediction of the Lateral Bearing Capacity of Short Piles in Clayey Soils Using Imperialist Competitive Algorithm-Based Artificial Neural Networks

Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

Abstract:

Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: artificial neural network, clayey soil, imperialist competition algorithm, lateral bearing capacity, short pile

Procedia PDF Downloads 121
302 Polarization Effects in Cosmic-Ray Acceleration by Cyclotron Auto-Resonance

Authors: Yousef I. Salamin

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Theoretical investigations, analytical as well as numerical, have shown that electrons can be accelerated to GeV energies by the process of cyclotron auto-resonance acceleration (CARA). In CARA, the particle would be injected along the lines of a uniform magnetic field aligned parallel to the direction of propagation of a plane-wave radiation field. Unfortunately, an accelerator based on CARA would be prohibitively too long and too expensive to build and maintain. However, the process stands a better chance of success near the polar cap of a compact object (such as a neutron star, a black hole or a magnetar) or in an environment created in the wake of a binary neutron-star or blackhole merger. Dynamics of the nuclides ₁H¹, ₂He⁴, ₂₆Fe⁵⁶, and ₂₈Ni⁶², in such astrophysical conditions, have been investigated by single-particle calculations and many-particle simulations. The investigations show that these nuclides can reach ZeV energies (1 ZeV = 10²¹ eV) due to interaction with super-intense radiation of wavelengths = 1 and 10 m and = 50 pm and magnetic fields of strengths at the mega- and giga-tesla levels. Examples employing radiation intensities in the range 10³²-10⁴² W/m² have been used. Employing a two-parameter model for representing the radiation field, CARA is analytically generalized to include any state of polarization, and the basic working equations are derived rigorously and in closed analytic form.

Keywords: compact objects, cosmic-ray acceleration, cyclotron auto-resonance, polarization effects, zevatron

Procedia PDF Downloads 95
301 Neuron Efficiency in Fluid Dynamics and Prediction of Groundwater Reservoirs'' Properties Using Pattern Recognition

Authors: J. K. Adedeji, S. T. Ijatuyi

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The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p1), fractured layer (p2), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable gr (gravitational resistance) can be deduced from the elevation and apparent resistivity pa. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

Procedia PDF Downloads 190
300 The Investigation of Fiber Reinforcement Self-Compacting Concrete and Fiber Reinforcement Concrete

Authors: Orod Zarrin, Mohesn Ramezan Shirazi, Hassan Moniri

Abstract:

The use of pile foundations technique is developed to support structures and buildings on soft soil. The most important dynamic load that can affect the pile structure is earthquake vibrations. From the 1960s the comprehensive investigation of pile foundations during earthquake excitation indicate that, piles are subject to damage by affecting the superstructure integrity and serviceability. The main part of these research has been focused on the behavior of liquefiable soil and lateral spreading load on piles. During an earthquake, two types of stresses can damage the pile head, inertial load that is caused by superstructure and deformation which caused by the surrounding soil. Soil deformation and inertial load are associated with the acceleration developed in an earthquake. The acceleration amplitude at the ground surface depends on the magnitude of earthquakes, soil properties and seismic source distance. According to the investigation, the damage is between the liquefiable and non-liquefiable layers and also soft and stiff layers. This damage crushes the pile head by increasing the inertial load which is applied by the superstructure. On the other hand, the cracks on the piles due to the surrounding soil are directly related to the soil profile and causes cracks from small to large. And researchers have been listed the large cracks reason such as liquefaction, lateral spreading and inertial load. In the field of designing, elastic response of piles are always a challenge for designer in liquefaction soil, by allowing deflection at top of piles. Moreover, absence of plastic hinges in piles should be insured, because the damage in the piles is not observed directly. In this study, the performance and behavior of pile foundations during liquefaction and lateral spreading are investigated. And emphasize on the soil behavior in the liquefiable and non-liquefiable layers by different aspect of piles damage such as ranking, location and degree of damage are going to discuss.

Keywords: self-compacting concrete, fiber, tensile strength, post-cracking, direct and inverse technique

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299 Effects of Positron Concentration and Temperature on Ion-Acoustic Solitons in Magnetized Electron-Positron-Ion Plasma

Authors: S. K. Jain, M. K. Mishra

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Oblique propagation of ion-acoustic solitons in magnetized electron-positron-ion (EPI) plasma with warm adiabatic ions and isothermal electrons has been studied. Korteweg-de Vries (KdV) equation using reductive perturbation method has been derived for the system, which admits an obliquely propagating soliton solution. It is found that for the selected set of parameter values, the system supports only compressive solitons. Investigations reveal that an increase in positron concentration diminishes the amplitude as well as the width of the soliton. It is also found that the temperature ratio of electron to positron (γ) affects the amplitude of the solitary wave. An external magnetic field do not affect the amplitude of ion-acoustic solitons, but obliqueness angle (θ), the angle between wave vector and magnetic field affects the amplitude. The amplitude of the ion-acoustic solitons increases with increase in angle of obliqueness. Magnetization and obliqueness drastically affect the width of the soliton. An increase in ionic temperature decreases the amplitude and width. For the fixed set of parameters, profiles have been drawn to study the combined effect with variation of two parameters on the characteristics of the ion-acoustic solitons (i.e., amplitude and width). The result may be applicable to plasma in the laboratory as well as in the magnetospheric region of the earth.

Keywords: ion-acoustic solitons, Korteweg-de Vries (KdV) equation, magnetized electron-positron-ion (EPI) plasma, reductive perturbation method

Procedia PDF Downloads 263
298 Preparation of Metal Containing Epoxy Polymer and Investigation of Their Properties as Fluorescent Probe

Authors: Ertuğ Yıldırım, Dile Kara, Salih Zeki Yıldız

Abstract:

Metal containing polymers (MCPs) are macro molecules usually containing metal-ligand coordination units and are a multidisciplinary research field mainly based at the interface between coordination chemistry and polymer science. The progress of this area has also been reinforced by the growth of several other closely related disciplines including macro molecular engineering, crystal engineering, organic synthesis, supra molecular chemistry and colloidal and material science. Schiff base ligands are very effective in constructing supra molecular architectures such as coordination polymers, double helical and triple helical complexes. In addition, Schiff base derivatives incorporating a fluorescent moiety are appealing tools for optical sensing of metal ions. MCPs are well-known systems in which the combinations of local parameters are possible by means of fluoro metric techniques. Generally, without incorporation of the fluorescent groups with polymers is unspecific, and it is not useful to analyze their fluorescent properties. Therefore, it is necessary to prepare a new type epoxy polymers with fluorescent groups in terms of metal sensing prop and the other photo chemical applications. In the present study metal containing polymers were prepared via poly functional monomeric Schiff base metal chelate complexes in the presence of dis functional monomers such as diglycidyl ether Bisphenol A (DGEBA). The synthesized complexes and polymers were characterized by FTIR, UV-VIS and mass spectroscopies. The preparations of epoxy polymers have been carried out at 185 °C. The prepared composites having sharp and narrow excitation/emission properties are expected to be applicable in various systems such as heat-resistant polymers and photo voltaic devices. The prepared composite is also ideal for various applications, easily prepared, safe, and maintain good fluorescence properties.

Keywords: Schiff base ligands, crystal engineering, fluorescence properties, Metal Containing Polymers (MCPs)

Procedia PDF Downloads 324
297 Real-Time Hybrid Simulation for a Tuned Liquid Column Damper Implementation

Authors: Carlos Riascos, Peter Thomson

Abstract:

Real-time hybrid simulation (RTHS) is a modern cyber-physical technique used for the experimental evaluation of complex systems, that treats the system components with predictable behavior as a numerical substructure and the components that are difficult to model as an experimental substructure. Therefore it is an attractive method for evaluation of the response of civil structures under earthquake, wind and anthropic loads. Another practical application of RTHS is the evaluation of control systems, as these devices are often nonlinear and their characterization is an important step in the design of controllers with the desired performance. In this paper, the response of three-story shear frame controlled by a tuned liquid column damper (TLCD) and subject to base excitation is considered. Both passive and semi-active control strategies were implemented and are compared. While the passive TLCD achieved a reduction of 50% in the acceleration response of the main structure in comparison with the structure without control, the semi-active TLCD achieved a reduction of 70%, and was robust to variations in the dynamic properties of the main structure. In addition, a RTHS was implemented with the main structure modeled as a linear, time-invariant (LTI) system through a state space representation and the TLCD, with both control strategies, was evaluated on a shake table that reproduced the displacement of the virtual structure. Current assessment measures for RTHS were used to quantify the performance with parameters such as generalized amplitude, equivalent time delay between the target and measured displacement of the shake table, and energy error using the measured force, and prove that the RTHS described in this paper is an accurate method for the experimental evaluation of structural control systems.

Keywords: structural control, hybrid simulation, tuned liquid column damper, semi-active sontrol strategy

Procedia PDF Downloads 276
296 Detection of Defects in CFRP by Ultrasonic IR Thermographic Method

Authors: W. Swiderski

Abstract:

In the paper introduced the diagnostic technique making possible the research of internal structures in composite materials reinforced fibres using in different applications. The main reason of damages in structures of these materials is the changing distribution of load in constructions in the lifetime. Appearing defect is largely complicated because of the appearance of disturbing of continuity of reinforced fibres, binder cracks and loss of fibres adhesiveness from binders. Defect in composite materials is usually more complicated than in metals. At present, infrared thermography is the most effective method in non-destructive testing composite. One of IR thermography methods used in non-destructive evaluation is vibrothermography. The vibrothermography is not a new non-destructive method, but the new solution in this test is use ultrasonic waves to thermal stimulation of materials. In this paper, both modelling and experimental results which illustrate the advantages and limitations of ultrasonic IR thermography in inspecting composite materials will be presented. The ThermoSon computer program for computing 3D dynamic temperature distribuions in anisotropic layered solids with subsurface defects subject to ulrasonic stimulation was used to optimise heating parameters in the detection of subsurface defects in composite materials. The program allows for the analysis of transient heat conduction and ultrasonic wave propagation phenomena in solids. The experiments at MIAT were fulfilled by means of FLIR SC 7600 IR camera. Ultrasonic stimulation was performed with the frequency from 15 kHz to 30 kHz with maximum power up to 2 kW.

Keywords: composite material, ultrasonic, infrared thermography, non-destructive testing

Procedia PDF Downloads 273
295 Prediction of Seismic Damage Using Scalar Intensity Measures Based on Integration of Spectral Values

Authors: Konstantinos G. Kostinakis, Asimina M. Athanatopoulou

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A key issue in seismic risk analysis within the context of Performance-Based Earthquake Engineering is the evaluation of the expected seismic damage of structures under a specific earthquake ground motion. The assessment of the seismic performance strongly depends on the choice of the seismic Intensity Measure (IM), which quantifies the characteristics of a ground motion that are important to the nonlinear structural response. Several conventional IMs of ground motion have been used to estimate their damage potential to structures. Yet, none of them has been proved to be able to predict adequately the seismic damage. Therefore, alternative, scalar intensity measures, which take into account not only ground motion characteristics but also structural information have been proposed. Some of these IMs are based on integration of spectral values over a range of periods, in an attempt to account for the information that the shape of the acceleration, velocity or displacement spectrum provides. The adequacy of a number of these IMs in predicting the structural damage of 3D R/C buildings is investigated in the present paper. The investigated IMs, some of which are structure specific and some are nonstructure-specific, are defined via integration of spectral values. To achieve this purpose three symmetric in plan R/C buildings are studied. The buildings are subjected to 59 bidirectional earthquake ground motions. The two horizontal accelerograms of each ground motion are applied along the structural axes. The response is determined by nonlinear time history analysis. The structural damage is expressed in terms of the maximum interstory drift as well as the overall structural damage index. The values of the aforementioned seismic damage measures are correlated with seven scalar ground motion IMs. The comparative assessment of the results revealed that the structure-specific IMs present higher correlation with the seismic damage of the three buildings. However, the adequacy of the IMs for estimation of the structural damage depends on the response parameter adopted. Furthermore, it was confirmed that the widely used spectral acceleration at the fundamental period of the structure is a good indicator of the expected earthquake damage level.

Keywords: damage measures, bidirectional excitation, spectral based IMs, R/C buildings

Procedia PDF Downloads 301
294 Dynamic Behavior of Brain Tissue under Transient Loading

Authors: Y. J. Zhou, G. Lu

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In this paper, an analytical study is made for the dynamic behavior of human brain tissue under transient loading. In this analytical model the Mooney-Rivlin constitutive law is coupled with visco-elastic constitutive equations to take into account both the nonlinear and time-dependent mechanical behavior of brain tissue. Five ordinary differential equations representing the relationships of five main parameters (radial stress, circumferential stress, radial strain, circumferential strain, and particle velocity) are obtained by using the characteristic method to transform five partial differential equations (two continuity equations, one motion equation, and two constitutive equations). Analytical expressions of the attenuation properties for spherical wave in brain tissue are analytically derived. Numerical results are obtained based on the five ordinary differential equations. The mechanical responses (particle velocity and stress) of brain are compared at different radii including 5, 6, 10, 15 and 25 mm under four different input conditions. The results illustrate that loading curves types of the particle velocity significantly influences the stress in brain tissue. The understanding of the influence by the input loading cures can be used to reduce the potentially injury to brain under head impact by designing protective structures to control the loading curves types.

Keywords: analytical method, mechanical responses, spherical wave propagation, traumatic brain injury

Procedia PDF Downloads 245
293 Experimental and Numerical Studies on Earthquake Shear Rupture Generation

Authors: Louis N. Y. Wong

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En-echelon fractures are commonly found in rocks, which appear as a special set of regularly oriented and spaced fractures. By using both experimental and numerical approaches, this study investigates the interaction among them, and how this interaction finally contributes to the development of a shear rupture (fault), especially in brittle natural rocks. Firstly, uniaxial compression tests are conducted on marble specimens containing en-echelon flaws. The latter is cut by using the water abrasive jet into the rock specimens. The fracturing processes of these specimens leading to the formation of a fault are observed in detail by the use of a high speed camera. The influences of the flaw geometry on the production of tensile cracks and shear cracks, which in turn dictate the coalescence patterns of the entire set of en-echelon flaws are comprehensively studied. Secondly, a numerical study based on a recently developed contact model, flat-joint contact model using the discrete element method (DEM) is carried out to model the present laboratory experiments. The numerical results provide a quantitative assessment of the interaction of en-echelon flaws. Particularly, the evolution of the stress field, as well as the characteristics of new crack initiation, propagation and coalescence associated with the generation of an eventual shear rupture are studied in detail. The numerical results are found to agree well with the experimental results obtained in both microscopic and macroscopic observations.

Keywords: discrete element method, en-echelon flaws, fault, marble

Procedia PDF Downloads 238
292 Identifying Autism Spectrum Disorder Using Optimization-Based Clustering

Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: autism spectrum disorder, clustering, optimization, unsupervised machine learning

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291 Patented Free-Space Optical System for Auto Aligned Optical Beam Allowing to Compensate Mechanical Misalignments

Authors: Aurelien Boutin

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In optical systems such as Variable Optical Delay Lines, where a collimated beam has to go back and forth, corner cubes are used in order to keep the reflected beam parallel to the incoming beam. However, the reflected beam can be laterally shifted, which will lead to losses. In this paper, we report on a patented optical design that allows keeping the reflected beam with the exact same position and direction whatever the displacement of the corner cube leading to zero losses. After explaining how the optical design works and theoretically allows to compensate for any defects in the translation of the corner cube, we will present the results of experimental comparisons between a standard layout (i.e., only corner cubes) and our optical layout. To compare both optical layouts, we used a fiber-to-fiber coupling setup. It consists of a couple of lights from one fiber to the other, thanks to two lenses. The ensemble [fiber+lense] is fixed and called a collimator so that the light is coupled from one collimator to another. Each collimator was precisely made in order to have a precise working distance. In the experiment, we measured and compared the Insertion Losses (IL) variations between both collimators with the distance between them (i.e., natural Gaussian beam coupling losses) and between both collimators in the different optical layouts tested, with the same optical length propagation. We will show that the IL variations of our setup are less than 0.05dB with respect to the IL variations of collimators alone.

Keywords: free-space optics, variable optical delay lines, optical cavity, auto-alignment

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290 A Multi-Scale Approach for the Analysis of Fiber-Reinforced Composites

Authors: Azeez Shaik, Amit Salvi, B. P. Gautham

Abstract:

Fiber reinforced polymer resin composite materials are finding wide variety of applications in automotive and aerospace industry because of their high specific stiffness and specific strengths when compared to metals. New class of 2D and 3D textile and woven fabric composites offer excellent fracture toughens as they bridge the cracks formed during fracture. Due to complexity of their fiber architectures and its resulting composite microstructures, optimized design and analysis of these structures is very complicated. A traditional homogenization approach is typically used to analyze structures made up of these materials. This approach usually fails to predict damage initiation as well as damage propagation and ultimate failure of structure made up of woven and textile composites. This study demonstrates a methodology to analyze woven and textile composites by using the multi-level multi-scale modelling approach. In this approach, a geometric repetitive unit cell (RUC) is developed with all its constituents to develop a representative volume element (RVE) with all its constituents and their interaction modeled correctly. The structure is modeled based on the RUC/RVE and analyzed at different length scales with desired levels of fidelity incorporating the damage and failure. The results are passed across (up and down) the scales qualitatively as well as quantitatively from the perspective of material, configuration and architecture.

Keywords: cohesive zone, multi-scale modeling, rate dependency, RUC, woven textiles

Procedia PDF Downloads 344
289 Improvement in Acoustic Performance at Low Frequency via Application of Acoustic Resistance of Vented Hole in In-Ear Earphones

Authors: Tzu-Hsuan Lei, Shu-Chien Wu, Kuang-Che Lo, Shu-Chi Liu, Yu-Cheng Liu

Abstract:

The focus of this study was on the effects of air propagation associated with vented holes on acoustic resistance properties. A cylindrical hole with diameter and depth of 0.7 mm and 1.0 mm, respectively, was the research target. By constructing a finite element analytical model of its sound field properties, the acoustic-specific airflow resistance relationships were obtained for the differences in sound pressure and flow velocity at the two ends of this vented hole. In addition, the acoustic properties of this vented hole were included in the in-ear earphone simulation model to complete the sound pressure curve simulation analysis of the in-ear earphone system with a vented hole of corresponding size. Then, the simulation results were compared with actual measurements obtained from the standard system. Based on the results, when the in-ear earphone vented hole simulation model considered the simulated specific airflow resistance values of this cylindrical hole, the overall simulated sound pressure performance was highly consistent with that of measured values. The difference in the first peak values of sound pressure at mid-to-low frequencies was reduced from 5.64% when the simulation model did not consider the specific airflow resistance of the cylindrical hole to 1.18%, and the accuracy of the overall simulation was around 70%. This indicates the importance of the acoustic resistance properties of vented holes. Moreover, as specific airflow resistance values were able to be further quantified, the accuracy of the entire in-ear earphone simulation was ultimately and effectively elevated.

Keywords: specific airflow resistance, vented holes, in-ear earphone, finite element method

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288 Somatic Embryogenesis of Lachenalia viridiflora, a Critically Endangered Ornamental Geophyte with High Floricultural Potential

Authors: Vijay Kumar, Mack Moyo, Johannes Van Staden

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Lachenalia viridiflora is a critically endangered bulbous plant with high potential on the international floriculture market. In the present study, an efficient protocol for in vitro plantlet regeneration through somatic embryogenesis was developed. Embryogenic callus was established on Murashige and Skoog (MS) basal medium supplemented with various concentrations and combinations of picloram and thidiazuron (TDZ). A high number of SEs (28.5 ± 1.49) with at different developmental stages of somatic embryos (SEs: globular embryos, torpedo and cotyledon embryo with bipolar characteristics) was obtained on Murashige and Skoog (MS) (Murashige and Skoog 1962) medium with 2.5 μM picloram, and 1.0 μM TDZ. Histological and scanning electron microscopic (SEM) analysis confirmed the presence of somatic embryos. Mature somatic embryos germinated and developed into plantlets after 6 weeks on half/full strength MS medium. High plant regeneration frequency (91.11 %) was achieved on full-strength MS medium supplemented with 5 μM phloroglucinol (PG). Well-developed healthy plantlets were successfully acclimatized in the greenhouse with a survival rate of 80%. The result of this study is beneficial in the mass propagation of high-quality Lachenalia viridiflora clonal plants for the commercial horticultural market and also provides a platform for future genetic transformation studies on the plant.

Keywords: horticultural plant, Lachenalia viridiflora, phloroglucinol, somatic embryogenesis, thidiazuron

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287 Rapid Formation of Ortho-Boronoimines and Derivatives for Reversible and Dynamic Bioconjugation Under Physiological Conditions

Authors: Nicholas C. Rose, Christopher D. Spicer

Abstract:

The regeneration of damaged or diseased tissues would provide an invaluable therapeutic tool in biological research and medicine. Cells must be provided with a number of different biochemical signals in order to form mature tissue through complex signaling networks that are difficult to recreate in synthetic materials. The ability to attach and detach bioactive proteins from material in an iterative and dynamic manner would therefore present a powerful way to mimic natural biochemical signaling cascades for tissue growth. We propose to reversibly attach these bioactive proteins using ortho-boronoimine (oBI) linkages and related derivatives formed by the reaction of an ortho-boronobenzaldehyde with a nucleophilic amine derivative. To enable the use of oBIs for biomaterial modification, we have studied binding and cleavage processes with precise detail in the context of small molecule models. A panel of oBI complexes has been synthesized and screened using a novel Förster resonance energy transfer (FRET) assay, using a cyanine dye FRET pair (Cy3 and Cy5), to identify the most reactive boron-aldehyde/amine nucleophile pairs. Upon conjugation of the dyes, FRET occurs under Cy3 excitation and the resultant ratio of Cy3:Cy5 emission directly correlates to conversion. Reaction kinetics and equilibria can be accurately quantified for reactive pairs, with dissociation constants of oBI derivatives in water (KD) found to span 9-orders of magnitude (10⁻²-10⁻¹¹ M). These studies have provided us with a better understanding of oBI linkages that we hope to exploit to reversibly attach bioconjugates to materials. The long-term aim of the project is to develop a modular biomaterial platform that can be used to help combat chronic diseases such as osteoarthritis, heart disease, and chronic wounds by providing cells with potent biological stimuli for tissue engineering.

Keywords: dynamic, bioconjugation, bornoimine, rapid, physiological

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286 Investigating Climate Change Trend Based on Data Simulation and IPCC Scenario during 2010-2030 AD: Case Study of Fars Province

Authors: Leila Rashidian, Abbas Ebrahimi

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The development of industrial activities, increase in fossil fuel consumption, vehicles, destruction of forests and grasslands, changes in land use, and population growth have caused to increase the amount of greenhouse gases especially CO2 in the atmosphere in recent decades. This has led to global warming and climate change. In the present paper, we have investigated the trend of climate change according to the data simulation during the time interval of 2010-2030 in the Fars province. In this research, the daily climatic parameters such as maximum and minimum temperature, precipitation and number of sunny hours during the 1977-2008 time interval for synoptic stations of Shiraz and Abadeh and during 1995-2008 for Lar stations and also the output of HADCM3 model in 2010-2030 time interval have been used based on the A2 propagation scenario. The results of the model show that the average temperature will increase by about 1 degree centigrade and the amount of precipitation will increase by 23.9% compared to the observational data. In conclusion, according to the temperature increase in this province, the amount of precipitation in the form of snow will be reduced and precipitations often will occur in the form of rain. This 1-degree centigrade increase during the season will reduce production by 6 to 10% because of shortening the growing period of wheat.

Keywords: climate change, Lars WG, HADCM3, Gillan province, climatic parameters, A2 scenario

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285 A Highly Efficient Broadcast Algorithm for Computer Networks

Authors: Ganesh Nandakumaran, Mehmet Karaata

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A wave is a distributed execution, often made up of a broadcast phase followed by a feedback phase, requiring the participation of all the system processes before a particular event called decision is taken. Wave algorithms with one initiator such as the 1-wave algorithm have been shown to be very efficient for broadcasting messages in tree networks. Extensions of this algorithm broadcasting a sequence of waves using a single initiator have been implemented in algorithms such as the m-wave algorithm. However as the network size increases, having a single initiator adversely affects the message delivery times to nodes further away from the initiator. As a remedy, broadcast waves can be allowed to be initiated by multiple initiator nodes distributed across the network to reduce the completion time of broadcasts. These waves initiated by one or more initiator processes form a collection of waves covering the entire network. Solutions to global-snapshots, distributed broadcast and various synchronization problems can be solved efficiently using waves with multiple concurrent initiators. In this paper, we propose the first stabilizing multi-wave sequence algorithm implementing waves started by multiple initiator processes such that every process in the network receives at least one sequence of broadcasts. Due to being stabilizing, the proposed algorithm can withstand transient faults and do not require initialization. We view a fault as a transient fault if it perturbs the configuration of the system but not its program.

Keywords: distributed computing, multi-node broadcast, propagation of information with feedback and cleaning (PFC), stabilization, wave algorithms

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284 The Influence of Colloidal Metal Nanoparticles on Growth and Proliferation of in Vitro Cultures of Potato

Authors: Przewodowski Włodzimierz, Przewodowska Agnieszka, Sekrecka Danuta, Michałowska Dorota

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Colloidal metal nanoparticles are widely applied in various areas and have great potential in different biotechnological applications. Their particular properties associated with both the antiseptic, antioxidant and anti aging properties as well as ability to penetrate most of the biological barriers, synergy in the absorption of nutrients and nontoxic to plants. The properties make them potentially useful in the fast and safe production of healthy, certified starting material in the production of plants exposed to many pathogenic microorganisms causing serious diseases, significantly affecting yield and causing the economic losses. In this case it is crucial to provide appropriate conditions for the production, storage and distribution of the plant material. Therefore, the aim of the proposed research was to develop and identify the influence of four colloidal metal nanoparticles on growth and proliferation of in vitro cultures of potato (Solanum tuberosum) - one of the most economically important strategic crops in the world. The research on different varieties of potato was performed by placing the explants of the in vitro cultures on sterile Murashige and Skoog (MS) type medium. The influence of the nanocolloids was evaluated using the MS medium impregnated with the examinated nanoparticles. The vigour of growth and the rate of proliferation was examinated for 6-8 weeks with both night/day-length and temperature over the ranges 8/16 h and 20–22 °C respectively. The results of our preliminary work confirmed high usefulness of the nanocolloids in the safe production of the examinated in vitro cultures.

Keywords: colloidal metal nanoparticles, in vitro cultures, potato, propagation

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283 An Engineered Epidemic: Big Pharma's Role in the Opioid Crisis

Authors: Donna L. Roberts

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2019 marked 23 years since Purdue Pharma launched its flagship drug, OxyContin, that unleashed an unprecedented epidemic touching both celebrities and common citizens, metropolitan, suburbia and rural areas and all levels of socioeconomic status. From rural Appalachia to East LA individuals, families and communities have been devastated by a trajectory of addiction that often began with the legitimate prescription of a pain killer for anything from a tooth extraction to a sports injury to recovery from surgery or chronic arthritis. Far from being a serendipitous progression of events, the proliferation of this new breed of 'miracle drug' was instead a carefully crafted marketing program aimed at both the medical community and common citizens. This research represents and in-depth investigation of the evolution of the marketing, distribution and promotion of prescription opioids by pharmaceutical companies and its relationship to the propagation of the opioid crisis. Specifically, key components of Purdue Pharma’s aggressive marketing campaign, including its bonus system and sales incentives, were analyzed in the context of the sociopolitical environment that essential created the proverbial 'perfect storm' for the changing manner in which pain is treated in the U.S. The analyses of these series of events clearly indicate their role in first, the increase in prescription of opioids for non-terminal pain relief and subsequently, the incidence of related addiction, overdose, and death. Through this examination of the conditions that facilitated and maintained this drug crisis, perhaps we can begin to chart a course toward its resolution.

Keywords: addiction, opioid, opioid crisis, Purdue Pharma

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282 Measurement Technologies for Advanced Characterization of Magnetic Materials Used in Electric Drives and Automotive Applications

Authors: Lukasz Mierczak, Patrick Denke, Piotr Klimczyk, Stefan Siebert

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Due to the high complexity of the magnetization in electrical machines and influence of the manufacturing processes on the magnetic properties of their components, the assessment and prediction of hysteresis and eddy current losses has remained a challenge. In the design process of electric motors and generators, the power losses of stators and rotors are calculated based on the material supplier’s data from standard magnetic measurements. This type of data does not include the additional loss from non-sinusoidal multi-harmonic motor excitation nor the detrimental effects of residual stress remaining in the motor laminations after manufacturing processes, such as punching, housing shrink fitting and winding. Moreover, in production, considerable attention is given to the measurements of mechanical dimensions of stator and rotor cores, whereas verification of their magnetic properties is typically neglected, which can lead to inconsistent efficiency of assembled motors. Therefore, to enable a comprehensive characterization of motor materials and components, Brockhaus Measurements developed a range of in-line and offline measurement technologies for testing their magnetic properties under actual motor operating conditions. Multiple sets of experimental data were obtained to evaluate the influence of various factors, such as elevated temperature, applied and residual stress, and arbitrary magnetization on the magnetic properties of different grades of non-oriented steel. Measured power loss for tested samples and stator cores varied significantly, by more than 100%, comparing to standard measurement conditions. Quantitative effects of each of the applied measurement were analyzed. This research and applied Brockhaus measurement methodologies emphasized the requirement for advanced characterization of magnetic materials used in electric drives and automotive applications.

Keywords: magnetic materials, measurement technologies, permanent magnets, stator and rotor cores

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281 Fracture Control of the Soda-Lime Glass in Laser Thermal Cleavage

Authors: Jehnming Lin

Abstract:

The effects of the contact ball-lens on the soda lime glass in laser thermal cleavage with a cw Nd-YAG laser were investigated in this study. A contact ball-lens was adopted to generate a bending force on the crack formation of the soda-lime glass in the laser cutting process. The Nd-YAG laser beam (wavelength of 1064 nm) was focused through the ball-lens and transmitted to the soda-lime glass, which was coated with a carbon film on the surface with a bending force from a ball-lens to generate a tensile stress state on the surface cracking. The fracture was controlled by the contact ball-lens and a straight cutting was tested to demonstrate the feasibility. Experimental observations on the crack propagation from the leading edge, main section and trailing edge of the glass sheet were compared with various mechanical and thermal loadings. Further analyses on the stress under various laser powers and contact ball loadings were made to characterize the innovative technology. The results show that the distributions of the side crack at the leading and trailing edges are mainly dependent on the boundary condition, contact force, cutting speed and laser power. With the increase of the mechanical and thermal loadings, the region of the side cracks might be dramatically reduced with proper selection of the geometrical constraints. Therefore, the application of the contact ball-lens is a possible way to control the fracture in laser cleavage with improved cutting qualities.

Keywords: laser cleavage, stress analysis, crack visualization, laser

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280 Health Trajectory Clustering Using Deep Belief Networks

Authors: Farshid Hajati, Federico Girosi, Shima Ghassempour

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We present a Deep Belief Network (DBN) method for clustering health trajectories. Deep Belief Network (DBN) is a deep architecture that consists of a stack of Restricted Boltzmann Machines (RBM). In a deep architecture, each layer learns more complex features than the past layers. The proposed method depends on DBN in clustering without using back propagation learning algorithm. The proposed DBN has a better a performance compared to the deep neural network due the initialization of the connecting weights. We use Contrastive Divergence (CD) method for training the RBMs which increases the performance of the network. The performance of the proposed method is evaluated extensively on the Health and Retirement Study (HRS) database. The University of Michigan Health and Retirement Study (HRS) is a nationally representative longitudinal study that has surveyed more than 27,000 elderly and near-elderly Americans since its inception in 1992. Participants are interviewed every two years and they collect data on physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The dataset is publicly available and we use the RAND HRS version L, which is easy to use and cleaned up version of the data. The size of sample data set is 268 and the length of the trajectories is equal to 10. The trajectories do not stop when the patient dies and represent 10 different interviews of live patients. Compared to the state-of-the-art benchmarks, the experimental results show the effectiveness and superiority of the proposed method in clustering health trajectories.

Keywords: health trajectory, clustering, deep learning, DBN

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279 Bridge Health Monitoring: A Review

Authors: Mohammad Bakhshandeh

Abstract:

Structural Health Monitoring (SHM) is a crucial and necessary practice that plays a vital role in ensuring the safety and integrity of critical structures, and in particular, bridges. The continuous monitoring of bridges for signs of damage or degradation through Bridge Health Monitoring (BHM) enables early detection of potential problems, allowing for prompt corrective action to be taken before significant damage occurs. Although all monitoring techniques aim to provide accurate and decisive information regarding the remaining useful life, safety, integrity, and serviceability of bridges, understanding the development and propagation of damage is vital for maintaining uninterrupted bridge operation. Over the years, extensive research has been conducted on BHM methods, and experts in the field have increasingly adopted new methodologies. In this article, we provide a comprehensive exploration of the various BHM approaches, including sensor-based, non-destructive testing (NDT), model-based, and artificial intelligence (AI)-based methods. We also discuss the challenges associated with BHM, including sensor placement and data acquisition, data analysis and interpretation, cost and complexity, and environmental effects, through an extensive review of relevant literature and research studies. Additionally, we examine potential solutions to these challenges and propose future research ideas to address critical gaps in BHM.

Keywords: structural health monitoring (SHM), bridge health monitoring (BHM), sensor-based methods, machine-learning algorithms, and model-based techniques, sensor placement, data acquisition, data analysis

Procedia PDF Downloads 68