Search results for: accurate shape of cardiac actionpotential.
805 Biosynthesis of Titanium Dioxide Nanoparticles and Their Antibacterial Property
Authors: Prachi Singh
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This paper presents a low-cost, eco-friendly and reproducible microbe mediated biosynthesis of TiO2 nanoparticles. TiO2 nanoparticles synthesized using the bacterium, Bacillus subtilis, from titanium as a precursor, were confirmed by TEM analysis. The morphological characteristics state spherical shape, with the size of individual or aggregate nanoparticles, around 30-40 nm. Microbial resistance represents a challenge for the scientific community to develop new bioactive compounds. Here, the antibacterial effect of TiO2 nanoparticles on Escherichia coli was investigated, which was confirmed by CFU (Colony-forming unit). Further, growth curve study of E. coli Hb101 in the presence and absence of TiO2 nanoparticles was done. Optical density decrease was observed with the increase in the concentration of TiO2. It could be attributed to the inactivation of cellular enzymes and DNA by binding to electron-donating groups such as carboxylates, amides, indoles, hydroxyls, thiols, etc. which cause little pores in bacterial cell walls, leading to increased permeability and cell death. This justifies that TiO2 nanoparticles have efficient antibacterial effect and have potential to be used as an antibacterial agent for different purposes.
Keywords: Antibacterial effect, CFU, Escherichia coli Hb101, growth curve, TEM, TiO2 nanoparticle, toxicity, UV-Vis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2277804 Comparative Study of Fault Identification and Classification on EHV Lines Using Discrete Wavelet Transform and Fourier Transform Based ANN
Authors: K.Gayathri, N. Kumarappan
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An appropriate method for fault identification and classification on extra high voltage transmission line using discrete wavelet transform is proposed in this paper. The sharp variations of the generated short circuit transient signals which are recorded at the sending end of the transmission line are adopted to identify the fault. The threshold values involve fault classification and these are done on the basis of the multiresolution analysis. A comparative study of the performance is also presented for Discrete Fourier Transform (DFT) based Artificial Neural Network (ANN) and Discrete Wavelet Transform (DWT). The results prove that the proposed method is an effective and efficient one in obtaining the accurate result within short duration of time by using Daubechies 4 and 9. Simulation of the power system is done using MATLAB.
Keywords: EHV transmission line, Fault identification and classification, Discrete wavelet transform, Multiresolution analysis, Artificial neural network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2458803 Semi Empirical Equations for Peak Shear Strength of Rectangular Reinforced Concrete Walls
Authors: Ali Kezmane, Said Boukais, Mohand Hamizi
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This paper presents an analytical study on the behavior of reinforced concrete walls with rectangular cross section. Several experiments on such walls have been selected to be studied. Database from various experiments were collected and nominal shear wall strengths have been calculated using formulas, such as those of the ACI (American), NZS (New Zealand), Mexican (NTCC), and Wood and Barda equations. Subsequently, nominal shear wall strengths from the formulas were compared with the ultimate shear wall strengths from the database. These formulas vary substantially in functional form and do not account for all variables that affect the response of walls. There is substantial scatter in the predicted values of ultimate shear strength. Two new semi empirical equations are developed using data from tests of 57 walls for transitions walls and 27 for slender walls with the objective of improving the prediction of peak strength of walls with the most possible accurate.Keywords: Shear strength, reinforced concrete walls, rectangular walls, shear walls, models.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1454802 Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries
Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammadhossein Sedaaghi
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Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy CMeans (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic CMeans (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.
Keywords: Facial image, segmentation, PCM, FCM, skin error, facial surgery.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1990801 Bayesian Online Learning of Corresponding Points of Objects with Sequential Monte Carlo
Authors: Miika Toivanen, Jouko Lampinen
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This paper presents an online method that learns the corresponding points of an object from un-annotated grayscale images containing instances of the object. In the first image being processed, an ensemble of node points is automatically selected which is matched in the subsequent images. A Bayesian posterior distribution for the locations of the nodes in the images is formed. The likelihood is formed from Gabor responses and the prior assumes the mean shape of the node ensemble to be similar in a translation and scale free space. An association model is applied for separating the object nodes and background nodes. The posterior distribution is sampled with Sequential Monte Carlo method. The matched object nodes are inferred to be the corresponding points of the object instances. The results show that our system matches the object nodes as accurately as other methods that train the model with annotated training images.Keywords: Bayesian modeling, Gabor filters, Online learning, Sequential Monte Carlo.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1582800 The Use Support Vector Machine and Back Propagation Neural Network for Prediction of Daily Tidal Levels along the Jeddah Coast, Saudi Arabia
Authors: E. A. Mlybari, M. S. Elbisy, A. H. Alshahri, O. M. Albarakati
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Sea level rise threatens to increase the impact of future storms and hurricanes on coastal communities. Accurate sea level change prediction and supplement is an important task in determining constructions and human activities in coastal and oceanic areas. In this study, support vector machines (SVM) is proposed to predict daily tidal levels along the Jeddah Coast, Saudi Arabia. The optimal parameter values of kernel function are determined using a genetic algorithm. The SVM results are compared with the field data and with back propagation (BP). Among the models, the SVM is superior to BPNN and has better generalization performance.
Keywords: Tides, Prediction, Support Vector Machines, Genetic Algorithm, Back-Propagation Neural Network, Risk, Hazards.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2386799 Determining the Best Fitting Distributions for Minimum Flows of Streams in Gediz Basin
Authors: Naci Büyükkaracığan
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Today, the need for water sources is swiftly increasing due to population growth. At the same time, it is known that some regions will face with shortage of water and drought because of the global warming and climate change. In this context, evaluation and analysis of hydrological data such as the observed trends, drought and flood prediction of short term flow has great deal of importance. The most accurate selection probability distribution is important to describe the low flow statistics for the studies related to drought analysis. As in many basins In Turkey, Gediz River basin will be affected enough by the drought and will decrease the amount of used water. The aim of this study is to derive appropriate probability distributions for frequency analysis of annual minimum flows at 6 gauging stations of the Gediz Basin. After applying 10 different probability distributions, six different parameter estimation methods and 3 fitness test, the Pearson 3 distribution and general extreme values distributions were found to give optimal results.
Keywords: Gediz Basin, goodness-of-fit tests, Minimum flows, probability distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2506798 Accurate Fault Classification and Section Identification Scheme in TCSC Compensated Transmission Line using SVM
Authors: Pushkar Tripathi, Abhishek Sharma, G. N. Pillai, Indira Gupta
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This paper presents a new approach for the protection of Thyristor-Controlled Series Compensator (TCSC) line using Support Vector Machine (SVM). One SVM is trained for fault classification and another for section identification. This method use three phase current measurement that results in better speed and accuracy than other SVM based methods which used single phase current measurement. This makes it suitable for real-time protection. The method was tested on 10,000 data instances with a very wide variation in system conditions such as compensation level, source impedance, location of fault, fault inception angle, load angle at source bus and fault resistance. The proposed method requires only local current measurement.Keywords: Fault Classification, Section Identification, Feature Selection, Support Vector Machine (SVM), Thyristor-Controlled Series Compensator (TCSC)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2526797 CFD Simulation of Condensing Vapor Bubble using VOF Model
Authors: Seong-Su Jeon, Seong-Jin Kim, Goon-Cherl Park
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In this study, direct numerical simulation for the bubble condensation in the subcooled boiling flow was performed. The main goal was to develop the CFD modeling for the bubble condensation and to evaluate the accuracy of the VOF model with the developed CFD modeling. CFD modeling for the bubble condensation was developed by modeling the source terms in the governing equations of VOF model using UDF. In the modeling, the amount of condensation was determined using the interfacial heat transfer coefficient obtained from the bubble velocity, liquid temperature and bubble diameter every time step. To evaluate the VOF model using the CFD modeling for the bubble condensation, CFD simulation results were compared with SNU experimental results such as bubble volume and shape, interfacial area, bubble diameter and bubble velocity. Simulation results predicted well the behavior of the actual condensing bubble. Therefore, it can be concluded that the VOF model using the CFD modeling for the bubble condensation will be a useful computational fluid dynamics tool for analyzing the behavior of the condensing bubble in a wide range of the subcooled boiling flow.
Keywords: Bubble condensation, CFD modeling, Subcooled boiling flow, VOF model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6748796 Krylov Model Order Reduction of a Thermal Subsea Model
Authors: J. Šindler, A. Suleng, T. Jelstad Olsen, P. Bárta
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A subsea hydrocarbon production system can undergo planned and unplanned shutdowns during the life of the field. The thermal FEA is used to simulate the cool down to verify the insulation design of the subsea equipment, but it is also used to derive an acceptable insulation design for the cold spots. The driving factors of subsea analyses require fast responding and accurate models of the equipment cool down. This paper presents cool down analysis carried out by a Krylov subspace reduction method, and compares this approach to the commonly used FEA solvers. The model considered represents a typical component of a subsea production system, a closed valve on a dead leg. The results from the Krylov reduction method exhibits the least error and requires the shortest computational time to reach the solution. These findings make the Krylov model order reduction method very suitable for the above mentioned subsea applications.
Keywords: Model order reduction, Krylov subspace, subsea production system, finite element.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2321795 Statistical Modeling of Mobile Fading Channels Based on Triply Stochastic Filtered Marked Poisson Point Processes
Authors: Jihad S. Daba, J. P. Dubois
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Understanding the statistics of non-isotropic scattering multipath channels that fade randomly with respect to time, frequency, and space in a mobile environment is very crucial for the accurate detection of received signals in wireless and cellular communication systems. In this paper, we derive stochastic models for the probability density function (PDF) of the shift in the carrier frequency caused by the Doppler Effect on the received illuminating signal in the presence of a dominant line of sight. Our derivation is based on a generalized Clarke’s and a two-wave partially developed scattering models, where the statistical distribution of the frequency shift is shown to be consistent with the power spectral density of the Doppler shifted signal.
Keywords: Doppler shift, filtered Poisson process, generalized Clark’s model, non-isotropic scattering, partially developed scattering, Rician distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 833794 Determination of Chemical Oxygen Demand in Spent Caustic by Potentiometric Determination
Authors: Hamed Harrafi, Masoumeh Khedri, Karim Karaminejad
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Measurement of the COD of a spent caustic solution involves firstly digestion of a test sample with dichromate solution and secondly measurement of dichromate remained by titration by ferrous ammonium sulfate [FAS] to an end point. In this paper we study by a potentiometric end point with Ag/AgCl reference electrode and gold rode electrode. The potentiometric end point is sharp and easily identified especially for the samples with high turbidity and color that other methods such as colorimetric in this type of sample do not result in high precision. Because interim of titration responds quickly to potential changes within the [Cr+6/Cr+3& Fe+2/Fe+3] solution producing stable readings that is lead to accurate COD measurement. Finally results are compared with data determined using colorimetric method for standard samples. It is shown that the potentiometric end point titration with gold rode electrode can be used with equal or better facility
Keywords: chemical oxygen demand, spent caustic and potentiometric determination
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4577793 An Agent-based Model for Analyzing Interaction of Two Stable Social Networks
Authors: Masatora Daito, Hisashi Kojima
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In this research, the authors analyze network stability using agent-based simulation. Firstly, the authors focus on analyzing large networks (eight agents) by connecting different two stable small social networks (A small stable network is consisted on four agents.). Secondly, the authors analyze the network (eight agents) shape which is added one agent to a stable network (seven agents). Thirdly, the authors analyze interpersonal comparison of utility. The “star-network "was not found on the result of interaction among stable two small networks. On the other hand, “decentralized network" was formed from several combination. In case of added one agent to a stable network (seven agents), if the value of “c"(maintenance cost of per a link) was larger, the number of patterns of stable network was also larger. In this case, the authors identified the characteristics of a large stable network. The authors discovered the cases of decreasing personal utility under condition increasing total utility.Keywords: Social Network, Symmetric Situation, Network Stability, Agent-Based Modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1533792 Seismic Response of Braced Steel Frames with Shape Memory Alloy and Mega Bracing Systems
Authors: Mohamed Omar
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Steel bracing members are widely used in steel structures to reduce lateral displacement and dissipate energy during earthquake motions. Concentric steel bracing provide an excellent approach for strengthening and stiffening steel buildings. Using these braces the designer can hardly adjust the stiffness together with ductility as needed because of buckling of braces in compression. In this study the use of SMA bracing and steel bracing (Mega) utilized in steel frames are investigated. The effectiveness of these two systems in rehabilitating a mid-rise eight-storey steel frames were examined using time-history nonlinear analysis utilizing seismostruct software. Results show that both systems improve the strength and stiffness of the original structure but due to excellent behavior of SMA in nonlinear phase and under compressive forces this system shows much better performance than the rehabilitation system of Mega bracing.
Keywords: Finite element analysis, seismic response, shapes memory alloy, steel frame, mega bracing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4206791 Differential Protection for Power Transformer Using Wavelet Transform and PNN
Authors: S. Sendilkumar, B. L. Mathur, Joseph Henry
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A new approach for protection of power transformer is presented using a time-frequency transform known as Wavelet transform. Different operating conditions such as inrush, Normal, load, External fault and internal fault current are sampled and processed to obtain wavelet coefficients. Different Operating conditions provide variation in wavelet coefficients. Features like energy and Standard deviation are calculated using Parsevals theorem. These features are used as inputs to PNN (Probabilistic neural network) for fault classification. The proposed algorithm provides more accurate results even in the presence of noise inputs and accurately identifies inrush and fault currents. Overall classification accuracy of the proposed method is found to be 96.45%. Simulation of the fault (with and without noise) was done using MATLAB AND SIMULINK software taking 2 cycles of data window (40 m sec) containing 800 samples. The algorithm was evaluated by using 10 % Gaussian white noise.Keywords: Power Transformer, differential Protection, internalfault, inrush current, Wavelet Energy, Db9.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3131790 On The Comparison of Fuzzy Logic and State Space Averaging based Sliding Control Methods Applied onan Arc Welding Machine
Authors: İres İskender, Ahmet Karaarslan
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In this study, the performance of a high-frequency arc welding machine including a two-switch inverter is analyzed. The control of the system is achieved using two different control techniques i- fuzzy logic control (FLC) ii- state space averaging based sliding control. Fuzzy logic control does not need accurate mathematical model of a plant and can be used in nonlinear applications. The second method needs the mathematical model of the system. In this method the state space equations of the system are derived for two different “on" and “off" states of the switches. The derived state equations are combined with the sliding control rule considering the duty-cycle of the converter. The performance of the system is analyzed by simulating the system using SIMULINK tool box of MATLAB. The simulation results show that fuzzy logic controller is more robust and less sensitive to parameter variations.Keywords: Fuzzy logic, arc welding, sliding state space control, PWM, current control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2052789 Knowledge Based Wear Particle Analysis
Authors: Mohammad S. Laghari, Qurban A. Memon, Gulzar A. Khuwaja
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The paper describes a knowledge based system for analysis of microscopic wear particles. Wear particles contained in lubricating oil carry important information concerning machine condition, in particular the state of wear. Experts (Tribologists) in the field extract this information to monitor the operation of the machine and ensure safety, efficiency, quality, productivity, and economy of operation. This procedure is not always objective and it can also be expensive. The aim is to classify these particles according to their morphological attributes of size, shape, edge detail, thickness ratio, color, and texture, and by using this classification thereby predict wear failure modes in engines and other machinery. The attribute knowledge links human expertise to the devised Knowledge Based Wear Particle Analysis System (KBWPAS). The system provides an automated and systematic approach to wear particle identification which is linked directly to wear processes and modes that occur in machinery. This brings consistency in wear judgment prediction which leads to standardization and also less dependence on Tribologists.Keywords: Computer vision, knowledge based systems, morphology, wear particles.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1744788 Numerical Simulation of the Bond Behavior between Concrete and Steel Reinforcing Bars in Specialty Concrete
Authors: Camille A. Issa, Omar Masri
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In this study, the commercial finite element software ABAQUS was used to develop a three-dimensional nonlinear finite element model capable of simulating the pull-out test of reinforcing bars from underwater concrete. The results of thirty-two pull-out tests that have different parameters were implemented in the software to study the effect of the concrete cover, the bar size, the use of stirrups, and the compressive strength of concrete. The interaction properties used in the model provided accurate results in comparison with the experimental bond-slip results, thus the model has successfully simulated the pull-out test. The results of the finite element model are used to better understand and visualize the distribution of stresses in each component of the model, and to study the effect of the various parameters used in this study including the role of the stirrups in preventing the stress from reaching to the sides of the specimens.Keywords: Bond strength, nonlinear finite element analysis, pull-out test, underwater concrete.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4615787 Millimeter Wave I/Q Generation with the Inductive Resonator Matched Poly-Phase Filter
Authors: Ki-Jin Kim, Sanghoon Park, K. H. Ahn
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A way of generating millimeter wave I/Q signal using inductive resonator matched poly-phase filter is suggested. Normally the poly-phase filter generates quite accurate I/Q phase and magnitude but the loss of the filter is considerable due to series connection of passive RC components. This loss term directly increases system noise figure when the poly-phase filter is used in RF Front-end. The proposed matching method eliminates above mentioned loss and in addition provides gain on the passive filter. The working algorithm is illustrated by mathematical analysis. The generated I/Q signal is used in implementing millimeter wave phase shifter for the 60 GHz communication system to verify its effectiveness. The circuit is fabricated in 90 nm TSMC RF CMOS process under 1.2 V supply voltage. The measurement results showed that the suggested method improved gain by 6.5 dB and noise by 2.3 dB. The summary of the proposed I/Q generation is compared with previous works.
Keywords: Millimeter Wave Circuits, Local Distribution, I/Q Generator.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2010786 Wireless Based System for Continuous Electrocardiography Monitoring during Surgery
Authors: K. Bensafia, A. Mansour, G. Le Maillot, B. Clement, O. Reynet, P. Ariès, S. Haddab
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This paper presents a system designed for wireless acquisition, the recording of electrocardiogram (ECG) signals and the monitoring of the heart’s health during surgery. This wireless recording system allows us to visualize and monitor the state of the heart’s health during a surgery, even if the patient is moved from the operating theater to post anesthesia care unit. The acquired signal is transmitted via a Bluetooth unit to a PC where the data are displayed, stored and processed. To test the reliability of our system, a comparison between ECG signals processed by a conventional ECG monitoring system (Datex-Ohmeda) and by our wireless system is made. The comparison is based on the shape of the ECG signal, the duration of the QRS complex, the P and T waves, as well as the position of the ST segments with respect to the isoelectric line. The proposed system is presented and discussed. The results have confirmed that the use of Bluetooth during surgery does not affect the devices used and vice versa. Pre- and post-processing steps are briefly discussed. Experimental results are also provided.
Keywords: Electrocardiography, monitoring, surgery, wireless system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1048785 Development of a GPS Buoy for Ocean Surface Monitoring: Initial Results
Authors: Anuar Mohd Salleh, Mohd Effendi Daud
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This study presents a kinematic positioning approach that uses a global positioning system (GPS) buoy for precise ocean surface monitoring. The GPS buoy data from the two experiments are processed using an accurate, medium-range differential kinematic technique. In each case, the data from a nearby coastal site are collected at a high rate (1 Hz) for more than 24 hours, and measurements are conducted in neighboring tidal stations to verify the estimated sea surface heights. The GPS buoy kinematic coordinates are estimated using epoch-wise pre-elimination and a backward substitution algorithm. Test results show that centimeterlevel accuracy can be successfully achieved in determining sea surface height using the proposed technique. The centimeter-level agreement between the two methods also suggests the possibility of using this inexpensive and more flexible GPS buoy equipment to enhance (or even replace) current tidal gauge stations.
Keywords: Global positioning system, kinematic GPS, sea surface height, GPS buoy, tide gauge.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1419784 High Gain Circularly Polarized Wire Antenna for DSRC Applications
Authors: Mohammad J. Almalkawi
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In this communication, a low-cost circularly polarized wire antenna exhibiting improved gain performance for Dedicated Short Range Communications (DSRC), vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications is presented. The proposed antenna comprises a Y-shaped quarterwavelength monopole antenna surrounded by two iterations of eight conductive arched walls acting as parasitic elements to enhance the overall antenna gain and to shape the radiation pattern in the H-plane. A hemispherical radome shell is added to protect the antenna structure and its effect on the antenna performance is discussed. The designed antenna demonstrates antenna gain of 8.2 dB with omnidirectional far-field radiation pattern in the H-plane. The gain of the proposed antenna is also compared with the characteristic of the stand-alone Y-shaped monopole to highlight the advantages of the proposed approach.Keywords: Circularly polarized, dedicated short-range communication, omnidirectional pattern, vehicle-to-infrastructure (V2I), vehicle-to-vehicle (V2V), Y-shaped wire monopole antenna.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2849783 Road Accidents Bigdata Mining and Visualization Using Support Vector Machines
Authors: Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma
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Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new framework model which can be trained and adapt itself to new data and make accurate predictions. This work also throws some light on use of SVM’s methodology for text classifiers from the obtained traffic data. Finally, it emphasizes the uniqueness and adaptability of SVMs methodology appropriate for this kind of research work.Keywords: Road accident, machine learning, support vector machines.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1129782 Investigation of a Transition from Steady Convection to Chaos in Porous Media Using Piecewise Variational Iteration Method
Authors: Mohamed M. Mousa, Aidarkhan Kaltayev Shahwar F. Ragab
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In this paper, a new dependable algorithm based on an adaptation of the standard variational iteration method (VIM) is used for analyzing the transition from steady convection to chaos for lowto-intermediate Rayleigh numbers convection in porous media. The solution trajectories show the transition from steady convection to chaos that occurs at a slightly subcritical value of Rayleigh number, the critical value being associated with the loss of linear stability of the steady convection solution. The VIM is treated as an algorithm in a sequence of intervals for finding accurate approximate solutions to the considered model and other dynamical systems. We shall call this technique as the piecewise VIM. Numerical comparisons between the piecewise VIM and the classical fourth-order Runge–Kutta (RK4) numerical solutions reveal that the proposed technique is a promising tool for the nonlinear chaotic and nonchaotic systems.
Keywords: Variational iteration method, free convection, Chaos, Lorenz equations.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1536781 Using Machine Learning Techniques for Autism Spectrum Disorder Analysis and Detection in Children
Authors: Norah Alshahrani, Abdulaziz Almaleh
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Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD: Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by SVM, achieving 0.98% in the toddler dataset and 0.99% in the children dataset.
Keywords: Autism Spectrum Disorder, ASD, Machine Learning, ML, Feature Selection, Support Vector Machine, SVM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 599780 Joint Adaptive Block Matching Search (JABMS) Algorithm
Authors: V.K.Ananthashayana, Pushpa.M.K
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In this paper a new Joint Adaptive Block Matching Search (JABMS) algorithm is proposed to generate motion vector and search a best match macro block by classifying the motion vector movement based on prediction error. Diamond Search (DS) algorithm generates high estimation accuracy when motion vector is small and Adaptive Rood Pattern Search (ARPS) algorithm can handle large motion vector but is not very accurate. The proposed JABMS algorithm which is capable of considering both small and large motions gives improved estimation accuracy and the computational cost is reduced by 15.2 times compared with Exhaustive Search (ES) algorithm and is 1.3 times less compared with Diamond search algorithm.Keywords: Adaptive rood pattern search, Block matching, Diamond search, Joint Adaptive search, Motion estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1694779 The Effect of the Tool Geometry and Cutting Conditions on the Tool Deflection and Cutting Forces
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In this paper by measuring the cutting forces the effect of the tool shape and qualifications (sharp and worn cutting tools of both vee and knife edge profile) and cutting conditions (depth of cut and cutting speed) in the turning operation on the tool deflection and cutting force is investigated. The workpiece material was mild steel and the cutting tool was made of high speed steel. Cutting forces were measured by a dynamometer (type P.E.I. serial No 154). The dynamometer essentially consisted of a cantilever structure which held the cutting tool. Deflection of the cantilever was measured by an L.V.D.T (Mercer 122) deflection indicator. No cutting fluid was used during the turning operations. A modern CNC lathe machine (Okuma LH35-N) was used for the tests. It was noted that worn vee profile tools tended to produce a greater increase in the vertical force component than the axial component, whereas knife tools tended to show a more pronounced increase in the axial component.Keywords: Cutting force, Tool deflection, Turning, Cuttingconditions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3352778 Verification and Application of Finite Element Model Developed for Flood Routing in Rivers
Authors: A. L. Qureshi, A. A. Mahessar, A. Baloch
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Flood wave propagation in river channel flow can be enunciated by nonlinear equations of motion for unsteady flow. It is difficult to find analytical solution of these non-linear equations. Hence, in this paper verification of the finite element model has been carried out against available numerical predictions and field data. The results of the model indicate a good matching with both Preissmann scheme and HEC-RAS model for a river reach of 29km at both sites (15km from upstream and at downstream end) for discharge hydrographs. It also has an agreeable comparison with the Preissemann scheme for the flow depth (stage) hydrographs. The proposed model has also been applying to forecast daily discharges at 400km downstream in the Indus River from Sukkur barrage of Sindh, Pakistan, which demonstrates accurate model predictions with observed the daily discharges. Hence, this model may be utilized for flood warnings in advance.
Keywords: Finite Element Method, Flood Forecasting, HEC-RAS, Indus river.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2685777 Modified Hybrid Genetic Algorithm-Based Artificial Neural Network Application on Wall Shear Stress Prediction
Authors: Zohreh Sheikh Khozani, Wan Hanna Melini Wan Mohtar, Mojtaba Porhemmat
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Prediction of wall shear stress in a rectangular channel, with non-homogeneous roughness distribution, was studied. Estimation of shear stress is an important subject in hydraulic engineering, since it affects the flow structure directly. In this study, the Genetic Algorithm Artificial (GAA) neural network is introduced as a hybrid methodology of the Artificial Neural Network (ANN) and modified Genetic Algorithm (GA) combination. This GAA method was employed to predict the wall shear stress. Various input combinations and transfer functions were considered to find the most appropriate GAA model. The results show that the proposed GAA method could predict the wall shear stress of open channels with high accuracy, by Root Mean Square Error (RMSE) of 0.064 in the test dataset. Thus, using GAA provides an accurate and practical simple-to-use equation.
Keywords: Artificial neural network, genetic algorithm, genetic programming, rectangular channel, shear stress.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 672776 Design of a CMOS Highly Linear Front-end IC with Auto Gain Controller for a Magnetic Field Transceiver
Authors: Yeon-kug Moon, Kang-Yoon Lee, Yun-Jae Won, Seung-Ok Lim
Abstract:
This paper describes a low-voltage and low-power channel selection analog front end with continuous-time low pass filters and highly linear programmable gain amplifier (PGA). The filters were realized as balanced Gm-C biquadratic filters to achieve a low current consumption. High linearity and a constant wide bandwidth are achieved by using a new transconductance (Gm) cell. The PGA has a voltage gain varying from 0 to 65dB, while maintaining a constant bandwidth. A filter tuning circuit that requires an accurate time base but no external components is presented. With a 1-Vrms differential input and output, the filter achieves -85dB THD and a 78dB signal-to-noise ratio. Both the filter and PGA were implemented in a 0.18um 1P6M n-well CMOS process. They consume 3.2mW from a 1.8V power supply and occupy an area of 0.19mm2.Keywords: component ; Channel selection filters, DC offset, programmable gain amplifier, tuning circuit
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