Search results for: uniform error
1229 Structural Evaluation of Airfield Pavement Using Finite Element Analysis Based Methodology
Authors: Richard Ji
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Nondestructive deflection testing has been accepted widely as a cost-effective tool for evaluating the structural condition of airfield pavements. Backcalculation of pavement layer moduli can be used to characterize the pavement existing condition in order to compute the load bearing capacity of pavement. This paper presents an improved best-fit backcalculation methodology based on deflection predictions obtained using finite element method (FEM). The best-fit approach is based on minimizing the squared error between falling weight deflectometer (FWD) measured deflections and FEM predicted deflections. Then, concrete elastic modulus and modulus of subgrade reaction were back-calculated using Heavy Weight Deflectometer (HWD) deflections collected at the National Airport Pavement Testing Facility (NAPTF) test site. It is an alternative and more versatile method in considering concrete slab geometry and HWD testing locations compared to methods currently available.Keywords: nondestructive testing, pavement moduli backcalculation, finite element method, concrete pavements
Procedia PDF Downloads 1661228 FPGA Implementation of Novel Triangular Systolic Array Based Architecture for Determining the Eigenvalues of Matrix
Authors: Soumitr Sanjay Dubey, Shubhajit Roy Chowdhury, Rahul Shrestha
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In this paper, we have presented a novel approach of calculating eigenvalues of any matrix for the first time on Field Programmable Gate Array (FPGA) using Triangular Systolic Arra (TSA) architecture. Conventionally, additional computation unit is required in the architecture which is compliant to the algorithm for determining the eigenvalues and this in return enhances the delay and power consumption. However, recently reported works are only dedicated for symmetric matrices or some specific case of matrix. This works presents an architecture to calculate eigenvalues of any matrix based on QR algorithm which is fully implementable on FPGA. For the implementation of QR algorithm we have used TSA architecture, which is further utilising CORDIC (CO-ordinate Rotation DIgital Computer) algorithm, to calculate various trigonometric and arithmetic functions involved in the procedure. The proposed architecture gives an error in the range of 10−4. Power consumption by the design is 0.598W. It can work at the frequency of 900 MHz.Keywords: coordinate rotation digital computer, three angle complex rotation, triangular systolic array, QR algorithm
Procedia PDF Downloads 4151227 Performance Investigation of Silica Gel Fluidized Bed
Authors: Sih-Li Chen, Chih-Hao Chen, Chi-Tong Chan
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Poor ventilation and high carbon dioxide (CO2) concentrations lead to the formation of sick buildings. This problem cannot simply be resolved by introducing fresh air from outdoor environments because this creates extra loads on indoor air-conditioning systems. Desiccants are widely used in air conditioning systems in tropical and subtropical regions with high humidity to reduce the latent heat load from fresh air. Desiccants are usually used as a packed-bed type, which is low cost, to combine with air-conditioning systems. Nevertheless, the pressure drop of a packed bed is too high, and the heat of adsorption caused by the adsorption process lets the temperature of the outlet air increase, bringing about an extra heat load, so the high pressure drop and the increased temperature of the outlet air are energy consumption sources needing to be resolved. For this reason, the gas-solid fluidised beds that have high heat and mass transfer rates, uniform properties and low pressure drops are very suitable for use in air-conditioning systems.This study experimentally investigates the performance of silica gel fluidized bed device which applying to an air conditioning system. In the experiments, commercial silica gel particles were filled in the two beds and to form a fixed packed bed and a fluidized bed. The results indicated that compared to the fixed packed bed device, the total adsorption and desorption by amounts of fluidized bed for 40 minutes increased 20.6% and 19.9% respectively when the bed height was 10 cm and superficial velocity was set to 2 m/s. In addition, under this condition, the pressure drop and outlet air temperature raise were reduced by 36.0% and 30.0%. Given the above results, application of the silica gel fluidized bed to air conditioning systems has great energy-saving potential.Keywords: fluidized bed, packed bed, silica gel, adsorption, desorption, pressure drop
Procedia PDF Downloads 5361226 Research on the Aeration Systems’ Efficiency of a Lab-Scale Wastewater Treatment Plant
Authors: Oliver Marunțălu, Elena Elisabeta Manea, Lăcrămioara Diana Robescu, Mihai Necșoiu, Gheorghe Lăzăroiu, Dana Andreya Bondrea
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In order to obtain efficient pollutants removal in small-scale wastewater treatment plants, uniform water flow has to be achieved. The experimental setup, designed for treating high-load wastewater (leachate), consists of two aerobic biological reactors and a lamellar settler. Both biological tanks were aerated by using three different types of aeration systems - perforated pipes, membrane air diffusers and tube ceramic diffusers. The possibility of homogenizing the water mass with each of the air diffusion systems was evaluated comparatively. The oxygen concentration was determined by optical sensors with data logging. The experimental data was analyzed comparatively for all three different air dispersion systems aiming to identify the oxygen concentration variation during different operational conditions. The Oxygenation Capacity was calculated for each of the three systems and used as performance and selection parameter. The global mass transfer coefficients were also evaluated as important tools in designing the aeration system. Even though using the tubular porous diffusers leads to higher oxygen concentration compared to the perforated pipe system (which provides medium-sized bubbles in the aqueous solution), it doesn’t achieve the threshold limit of 80% oxygen saturation in less than 30 minutes. The study has shown that the optimal solution for the studied configuration was the radial air diffusers which ensure an oxygen saturation of 80% in 20 minutes. An increment of the values was identified when the air flow was increased.Keywords: flow, aeration, bioreactor, oxygen concentration
Procedia PDF Downloads 3891225 PM₁₀ and PM2.5 Concentrations in Bangkok over Last 10 Years: Implications for Air Quality and Health
Authors: Tin Thongthammachart, Wanida Jinsart
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Atmospheric particulate matter particles with a diameter less than 10 microns (PM₁₀) and less than 2.5 microns (PM₂.₅) have adverse health effect. The impact from PM was studied from both health and regulatory perspective. Ambient PM data was collected over ten years in Bangkok and vicinity areas of Thailand from 2007 to 2017. Statistical models were used to forecast PM concentrations from 2018 to 2020. Monitoring monthly data averaged concentration of PM₁₀ and PM₂.₅ were used as input to forecast the monthly average concentration of PM. The forecasting results were validated by root means square error (RMSE). The predicted results were used to determine hazard risk for the carcinogenic disease. The health risk values were interpolated with GIS with ordinary kriging technique to create hazard maps in Bangkok and vicinity area. GIS-based maps illustrated the variability of PM distribution and high-risk locations. These evaluated results could support national policy for the sake of human health.Keywords: PM₁₀, PM₂.₅, statistical models, atmospheric particulate matter
Procedia PDF Downloads 1591224 Impulsive Synchronization of Periodically Forced Complex Duffing's Oscillators
Authors: Shaban Aly, Ali Al-Qahtani, Houari B. Khenous
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Synchronization is an important phenomenon commonly observed in nature. A system of periodically forced complex Duffings oscillators was introduced and shown to display chaotic behavior and possess strange attractors. Such complex oscillators appear in many problems of physics and engineering, as, for example, nonlinear optics, deep-water wave theory, plasma physics and bimolecular dynamics. In this paper, we study the remarkable phenomenon of chaotic synchronization on these oscillator systems, using impulsive synchronization techniques. We derive analytical expressions for impulsive control functions and show that the dynamics of error evolution is globally stable, by constructing appropriate Lyapunov functions. This means that, for a relatively large set initial conditions, the differences between the drive and response systems vanish exponentially and synchronization is achieved. Numerical results are obtained to test the validity of the analytical expressions and illustrate the efficiency of these techniques for inducing chaos synchronization in our nonlinear oscillators.Keywords: complex nonlinear oscillators, impulsive synchronization, chaotic systems, global exponential synchronization
Procedia PDF Downloads 4471223 Large Neural Networks Learning From Scratch With Very Few Data and Without Explicit Regularization
Authors: Christoph Linse, Thomas Martinetz
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Recent findings have shown that Neural Networks generalize also in over-parametrized regimes with zero training error. This is surprising, since it is completely against traditional machine learning wisdom. In our empirical study we fortify these findings in the domain of fine-grained image classification. We show that very large Convolutional Neural Networks with millions of weights do learn with only a handful of training samples and without image augmentation, explicit regularization or pretraining. We train the architectures ResNet018, ResNet101 and VGG19 on subsets of the difficult benchmark datasets Caltech101, CUB_200_2011, FGVCAircraft, Flowers102 and StanfordCars with 100 classes and more, perform a comprehensive comparative study and draw implications for the practical application of CNNs. Finally, we show that VGG19 with 140 million weights learns to distinguish airplanes and motorbikes with up to 95% accuracy using only 20 training samples per class.Keywords: convolutional neural networks, fine-grained image classification, generalization, image recognition, over-parameterized, small data sets
Procedia PDF Downloads 881222 BER of the Leaky Feeder under Rayleigh Fading Multichannel Reception with Imperfect Phase Estimation
Authors: Hasan Farahneh, Xavier Fernando
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Leaky Feeder (LF) has been a proven technology for many decades and its promises broadband wireless access in short range but being overlooked until now. The LF is a natural MIMO transceiver ideal for micro and pico cells. In this work, the LF is considered as a linear antenna array MultiInput-Single-Output (MISO) and derive the average bit error rate (BER) in Rayleigh fading channel considering ideal and independent paths (iid) which consider there is no correlation and mutual coupling between transmit antennas (slots) or receiver antenna considering QPSK modulation with imperfect phase estimation. We consider maximal ratio transmission (MRT) at the transmit end and maximal ratio combining (MRC) at the receiving end. Analytical expressions are derived for the BER with radiating cable transmitters. The effects of slot spacing and carrier frequency on the BER are also studied. Numerical evaluations show the radiating cable transmitter offer much lower BER than a single antenna transmitter with same SNR.Keywords: leaky feeder, BER, QPSK, rayleigh fading, channel gain, phase mismatch
Procedia PDF Downloads 3811221 A Pole Radius Varying Notch Filter with Transient Suppression for Electrocardiogram
Authors: Ramesh Rajagopalan, Adam Dahlstrom
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Noise removal techniques play a vital role in the performance of electrocardiographic (ECG) signal processing systems. ECG signals can be corrupted by various kinds of noise such as baseline wander noise, electromyographic interference, and power-line interference. One of the significant challenges in ECG signal processing is the degradation caused by additive 50 or 60 Hz power-line interference. This work investigates the removal of power line interference and suppression of transient response for filtering noise corrupted ECG signals. We demonstrate the effectiveness of Infinite Impulse Response (IIR) notch filter with time varying pole radius for improving the transient behavior. The temporary change in the pole radius of the filter diminishes the transient behavior. Simulation results show that the proposed IIR filter with time varying pole radius outperforms traditional IIR notch filters in terms of mean square error and transient suppression.Keywords: notch filter, ECG, transient, pole radius
Procedia PDF Downloads 3771220 Numerical Analysis for Soil Compaction and Plastic Points Extension in Pile Drivability
Authors: Omid Tavasoli, Mahmoud Ghazavi
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A numerical analysis of drivability of piles in different geometry is presented. In this paper, a three-dimensional finite difference analysis for plastic point extension and soil compaction in the effect of pile driving is analyzed. Four pile configurations such as cylindrical pile, fully tapered pile, T-C pile consists of a top tapered segment and a lower cylindrical segment and C-T pile has a top cylindrical part followed by a tapered part are investigated. All piles which driven up to a total penetration depth of 16 m have the same length with equivalent surface area and approximately with identical material volumes. An idealization for pile-soil system in pile driving is considered for this approach. A linear elastic material is assumed to model the vertical pile behaviors and the soil obeys the elasto-plastic constitutive low and its failure is controlled by the Mohr-Coulomb failure criterion. A slip which occurred at the pile-soil contact surfaces along the shaft and the toe in pile driving procedures is simulated with interface elements. All initial and boundary conditions are the same in all analyses. Quiet boundaries are used to prevent wave reflection in the lateral and vertical directions for the soil. The results obtained from numerical analyses were compared with available other numerical data and laboratory tests, indicating a satisfactory agreement. It will be shown that with increasing the angle of taper, the permanent piles toe settlement increase and therefore, the extension of plastic points increase. These are interesting phenomena in pile driving and are on the safe side for driven piles.Keywords: pile driving, finite difference method, non-uniform piles, pile geometry, pile set, plastic points, soil compaction
Procedia PDF Downloads 4841219 The Impact of Board of Directors on CEO Compensation: Evidence from the UK
Authors: Saleh Alagla, Murya Habbash
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The paper investigates whether the board of directors plays a monitoring role or not in CEO compensation for the UK firms during the eve of the recent financial crisis, 2004-2008. The use of heteroscedastic and autocorrelated error consistent estimation of the panel data shows, surprisingly, that four board characteristics variables are found to play a significant role in increasing the level of CEO compensation. This insightful result would suggest evidence of the managerial power theory in general and the cronyism hypothesis in particular. Moreover, the interesting evidence supporting managerial power perspective is that CEO-Chair duality reduces long-term compensation while increasing short-term compensation, thus suggesting that CEOs are risk averse who prefer short-term compensation to long-term compensation. Finally, consistent with the agency perspective board size is found to increase all compensation variables as expected.Keywords: corporate governance, CEO compensation, board of directors, internal governance mechanisms, agency theory, managerial power theory, cronyism hypothesis
Procedia PDF Downloads 8031218 Efficacy of Deep Learning for Below-Canopy Reconstruction of Satellite and Aerial Sensing Point Clouds through Fractal Tree Symmetry
Authors: Dhanuj M. Gandikota
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Sensor-derived three-dimensional (3D) point clouds of trees are invaluable in remote sensing analysis for the accurate measurement of key structural metrics, bio-inventory values, spatial planning/visualization, and ecological modeling. Machine learning (ML) holds the potential in addressing the restrictive tradeoffs in cost, spatial coverage, resolution, and information gain that exist in current point cloud sensing methods. Terrestrial laser scanning (TLS) remains the highest fidelity source of both canopy and below-canopy structural features, but usage is limited in both coverage and cost, requiring manual deployment to map out large, forested areas. While aerial laser scanning (ALS) remains a reliable avenue of LIDAR active remote sensing, ALS is also cost-restrictive in deployment methods. Space-borne photogrammetry from high-resolution satellite constellations is an avenue of passive remote sensing with promising viability in research for the accurate construction of vegetation 3-D point clouds. It provides both the lowest comparative cost and the largest spatial coverage across remote sensing methods. However, both space-borne photogrammetry and ALS demonstrate technical limitations in the capture of valuable below-canopy point cloud data. Looking to minimize these tradeoffs, we explored a class of powerful ML algorithms called Deep Learning (DL) that show promise in recent research on 3-D point cloud reconstruction and interpolation. Our research details the efficacy of applying these DL techniques to reconstruct accurate below-canopy point clouds from space-borne and aerial remote sensing through learned patterns of tree species fractal symmetry properties and the supplementation of locally sourced bio-inventory metrics. From our dataset, consisting of tree point clouds obtained from TLS, we deconstructed the point clouds of each tree into those that would be obtained through ALS and satellite photogrammetry of varying resolutions. We fed this ALS/satellite point cloud dataset, along with the simulated local bio-inventory metrics, into the DL point cloud reconstruction architectures to generate the full 3-D tree point clouds (the truth values are denoted by the full TLS tree point clouds containing the below-canopy information). Point cloud reconstruction accuracy was validated both through the measurement of error from the original TLS point clouds as well as the error of extraction of key structural metrics, such as crown base height, diameter above root crown, and leaf/wood volume. The results of this research additionally demonstrate the supplemental performance gain of using minimum locally sourced bio-inventory metric information as an input in ML systems to reach specified accuracy thresholds of tree point cloud reconstruction. This research provides insight into methods for the rapid, cost-effective, and accurate construction of below-canopy tree 3-D point clouds, as well as the supported potential of ML and DL to learn complex, unmodeled patterns of fractal tree growth symmetry.Keywords: deep learning, machine learning, satellite, photogrammetry, aerial laser scanning, terrestrial laser scanning, point cloud, fractal symmetry
Procedia PDF Downloads 1021217 Margin-Based Feed-Forward Neural Network Classifiers
Authors: Xiaohan Bookman, Xiaoyan Zhu
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Margin-Based Principle has been proposed for a long time, it has been proved that this principle could reduce the structural risk and improve the performance in both theoretical and practical aspects. Meanwhile, feed-forward neural network is a traditional classifier, which is very hot at present with a deeper architecture. However, the training algorithm of feed-forward neural network is developed and generated from Widrow-Hoff Principle that means to minimize the squared error. In this paper, we propose a new training algorithm for feed-forward neural networks based on Margin-Based Principle, which could effectively promote the accuracy and generalization ability of neural network classifiers with less labeled samples and flexible network. We have conducted experiments on four UCI open data sets and achieved good results as expected. In conclusion, our model could handle more sparse labeled and more high-dimension data set in a high accuracy while modification from old ANN method to our method is easy and almost free of work.Keywords: Max-Margin Principle, Feed-Forward Neural Network, classifier, structural risk
Procedia PDF Downloads 3411216 Comprehensive Framework for Pandemic-Resilient Cities to Avert Future Migrant Crisis: A Case of Mumbai
Authors: Vasudha Thapa, Kiran Chappa
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There is a pressing need to prepare cities in the developing countries of the global south such as India against the chaos created by COVID 19 pandemic and future disaster risks. This pandemic posed the nation with an unprecedented challenge of dealing with a wave of stranded migrant workers. These workers comprise the most vulnerable section of the society in case of any pandemic or disaster risks. The COVID 19 pandemic exposed the vulnerability of migrant workers in the urban form and the need for capacity-building strategies against future pandemics. This paper highlights the challenges of these migrant workers in the case of Mumbai city in lockdown, post lockdown, and the current uncertain scenarios. The paper deals with a thorough investigation of the existing and the recent policies and strategies taken by the Urban Local Bodies (ULBs), state, and central government to assist these migrants in the city during this mayhem of uncertainties. The paper looks further deep into the challenges and opportunities presented in the current scenario through the assessment of existing data and response to policy measures taken by the government organizations. The ULBs are at the forefront in the response to any disaster risk, hence the paper assesses the capacity gaps of the Urban local bodies in mitigating the risks posed by any pandemic-like situation. The study further recommends capacity-building strategies at various levels of governance and uniform policy measures to assist the migrant population of the city.Keywords: urban resilience, covid 19, migrant population, India, capacity building, governance
Procedia PDF Downloads 1871215 HPA Pre-Distorter Based on Neural Networks for 5G Satellite Communications
Authors: Abdelhamid Louliej, Younes Jabrane
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Satellites are becoming indispensable assets to fifth-generation (5G) new radio architecture, complementing wireless and terrestrial communication links. The combination of satellites and 5G architecture allows consumers to access all next-generation services anytime, anywhere, including scenarios, like traveling to remote areas (without coverage). Nevertheless, this solution faces several challenges, such as a significant propagation delay, Doppler frequency shift, and high Peak-to-Average Power Ratio (PAPR), causing signal distortion due to the non-linear saturation of the High-Power Amplifier (HPA). To compensate for HPA non-linearity in 5G satellite transmission, an efficient pre-distorter scheme using Neural Networks (NN) is proposed. To assess the proposed NN pre-distorter, two types of HPA were investigated: Travelling Wave Tube Amplifier (TWTA) and Solid-State Power Amplifier (SSPA). The results show that the NN pre-distorter design presents EVM improvement by 95.26%. NMSE and ACPR were reduced by -43,66 dB and 24.56 dBm, respectively. Moreover, the system suffers no degradation of the Bit Error Rate (BER) for TWTA and SSPA amplifiers.Keywords: satellites, 5G, neural networks, HPA, TWTA, SSPA, EVM, NMSE, ACPR
Procedia PDF Downloads 911214 Economic Loss due to Ganoderma Disease in Oil Palm
Authors: K. Assis, K. P. Chong, A. S. Idris, C. M. Ho
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Oil palm or Elaeis guineensis is considered as the golden crop in Malaysia. But oil palm industry in this country is now facing with the most devastating disease called as Ganoderma Basal Stem Rot disease. The objective of this paper is to analyze the economic loss due to this disease. There were three commercial oil palm sites selected for collecting the required data for economic analysis. Yield parameter used to measure the loss was the total weight of fresh fruit bunch in six months. The predictors include disease severity, change in disease severity, number of infected neighbor palms, age of palm, planting generation, topography, and first order interaction variables. The estimation model of yield loss was identified by using backward elimination based regression method. Diagnostic checking was conducted on the residual of the best yield loss model. The value of mean absolute percentage error (MAPE) was used to measure the forecast performance of the model. The best yield loss model was then used to estimate the economic loss by using the current monthly price of fresh fruit bunch at mill gate.Keywords: ganoderma, oil palm, regression model, yield loss, economic loss
Procedia PDF Downloads 3891213 Precoding-Assisted Frequency Division Multiple Access Transmission Scheme: A Cyclic Prefixes- Available Modulation-Based Filter Bank Multi-Carrier Technique
Authors: Ying Wang, Jianhong Xiang, Yu Zhong
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The offset Quadrature Amplitude Modulation-based Filter Bank Multi-Carrier (FBMC) system provides superior spectral properties over Orthogonal Frequency Division Multiplexing. However, seriously affected by imaginary interference, its performances are hampered in many areas. In this paper, we propose a Precoding-Assisted Frequency Division Multiple Access (PA-FDMA) modulation scheme. By spreading FBMC symbols into the frequency domain and transmitting them with a precoding matrix, the impact of imaginary interference can be eliminated. Specifically, we first generate the coding pre-solution matrix with a nonuniform Fast Fourier Transform and pick the best columns by introducing auxiliary factors. Secondly, according to the column indexes, we obtain the precoding matrix for one symbol and impose scaling factors to ensure that the power is approximately constant throughout the transmission time. Finally, we map the precoding matrix of one symbol to multiple symbols and transmit multiple data frames, thus achieving frequency-division multiple access. Additionally, observing the interference between adjacent frames, we mitigate them by adding frequency Cyclic Prefixes (CP) and evaluating them with a signal-to-interference ratio. Note that PA-FDMA can be considered a CP-available FBMC technique because the underlying strategy is FBMC. Simulation results show that the proposed scheme has better performance compared to Single Carrier Frequency Division Multiple Access (SC-FDMA), etc.Keywords: PA-FDMA, SC-FDMA, FBMC, non-uniform fast fourier transform
Procedia PDF Downloads 641212 The Theory of the Mystery: Unifying the Quantum and Cosmic Worlds
Authors: Md. Najiur Rahman
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This hypothesis reveals a profound and symmetrical connection that goes beyond the boundaries of quantum physics and cosmology, revolutionizing our understanding of the fundamental building blocks of the cosmos, given its name ‘The Theory of the Mystery’. This theory has an elegantly simple equation, “R = ∆r / √∆m” which establishes a beautiful and well-crafted relationship between the radius (R) of an elementary particle or galaxy, the relative change in radius (∆r), and the mass difference (∆m) between related entities. It is fascinating to note that this formula presents a super synchronization, one which involves the convergence of every basic particle and any single celestial entity into perfect alignment with its respective mass and radius. In addition, we have a Supporting equation that defines the mass-radius connection of an entity by the equation: R=√m/N, where N is an empirically established constant, determined to be approximately 42.86 kg/m, representing the proportionality between mass and radius. It provides precise predictions, collects empirical evidence, and explores the far-reaching consequences of theories such as General Relativity. This elegant symmetry reveals a fundamental principle that underpins the cosmos: each component, whether small or large, follows a precise mass-radius relationship to exert gravity by a universal law. This hypothesis represents a transformative process towards a unified theory of physics, and the pursuit of experimental verification will show that each particle and galaxy is bound by gravity and plays a unique but harmonious role in shaping the universe. It promises to reveal the great symphony of the mighty cosmos. The predictive power of our hypothesis invites the exploration of entities at the farthest reaches of the cosmos, providing a bridge between the known and the unknown.Keywords: unified theory, quantum gravity, mass-radius relationship, dark matter, uniform gravity
Procedia PDF Downloads 1051211 Modified Clusterwise Regression for Pavement Management
Authors: Mukesh Khadka, Alexander Paz, Hanns de la Fuente-Mella
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Typically, pavement performance models are developed in two steps: (i) pavement segments with similar characteristics are grouped together to form a cluster, and (ii) the corresponding performance models are developed using statistical techniques. A challenge is to select the characteristics that define clusters and the segments associated with them. If inappropriate characteristics are used, clusters may include homogeneous segments with different performance behavior or heterogeneous segments with similar performance behavior. Prediction accuracy of performance models can be improved by grouping the pavement segments into more uniform clusters by including both characteristics and a performance measure. This grouping is not always possible due to limited information. It is impractical to include all the potential significant factors because some of them are potentially unobserved or difficult to measure. Historical performance of pavement segments could be used as a proxy to incorporate the effect of the missing potential significant factors in clustering process. The current state-of-the-art proposes Clusterwise Linear Regression (CLR) to determine the pavement clusters and the associated performance models simultaneously. CLR incorporates the effect of significant factors as well as a performance measure. In this study, a mathematical program was formulated for CLR models including multiple explanatory variables. Pavement data collected recently over the entire state of Nevada were used. International Roughness Index (IRI) was used as a pavement performance measure because it serves as a unified standard that is widely accepted for evaluating pavement performance, especially in terms of riding quality. Results illustrate the advantage of the using CLR. Previous studies have used CLR along with experimental data. This study uses actual field data collected across a variety of environmental, traffic, design, and construction and maintenance conditions.Keywords: clusterwise regression, pavement management system, performance model, optimization
Procedia PDF Downloads 2511210 Experimental Approach for Determining Hemi-Anechoic Characteristics of Engineering Acoustical Test Chambers
Authors: Santiago Montoya-Ospina, Raúl E. Jiménez-Mejía, Rosa Elvira Correa Gutiérrez
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An experimental methodology is proposed for determining hemi-anechoic characteristics of an engineering acoustic room built at the facilities of Universidad Nacional de Colombia to evaluate the free-field conditions inside the chamber. Experimental results were compared with theoretical ones in both, the source and the sound propagation inside the chamber. Acoustic source was modeled by using monopole radiation pattern from punctual sources and the image method was considered for dealing with the reflective plane of the room, that means, the floor without insulation. Finite-difference time-domain (FDTD) method was implemented to calculate the sound pressure value at every spatial point of the chamber. Comparison between theoretical and experimental data yields to minimum error, giving satisfactory results for the hemi-anechoic characterization of the chamber.Keywords: acoustic impedance, finite-difference time-domain, hemi-anechoic characterization
Procedia PDF Downloads 1621209 The Effect of Addition of White Mulberry Fruit on the Sensory Quality of the New Developed Bioactive Bread
Authors: Kmiecik Dominik, Kobus-Cisowska Joanna, Gramza-Michalowska Anna, Marcinkowska Agata, Korczak Józef
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The relationship between the choice of a proper diet, a diet, lifestyle man and his health has been known for a long time. Because of the increase in public awareness of food ingredients and their influence on health status, measures have been taken towards the production of food, which is designed to not only eat, but also to protect against the incidence of lifestyle diseases. For this purpose, the bio active products with healthy properties was developed. Mulberry have a very high nutritional value, rich in chemical composition and many properties used in the prevention of lifestyle diseases. In addition to basic chemical components, nutrients, mulberry fruit contain compounds having a physiological effect. The aim of this study was to assess the effect of white mulberry fruit on the sensory quality of bread to be healthy diet of people suffering from anemia, diabetes, obesity and cardiovascular disease. Sensory analysis was carried out by the profile method. Intra-operative differentiators color, aroma, taste, texture, and overall assessment. Sensory analysis showed that all test trials were characterized by a uniform and concise consistency, similar in color from dark to light beige. The taste and smell of herbal characteristic was designed in an attempt to prevention of diabetes, while the other samples were characterized by a typical taste and smell of bread grain. There were no foreign taste and odor in the test bread. It was found that the addition of white mulberry fruit does not affect the sensory quality of the newly developed bioactive bread.Keywords: mulberry, bread, bioactive, sensory analysis
Procedia PDF Downloads 4621208 Ocular Biometry: Common Etiologies of Difference More Than 0.33mm between Axial Lengths of the 2 Eyes
Authors: Ghandehari Motlagh, Mohammad
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Purpose: We tried to find the most common etiologies for anisometropia in pre-op cataract cases: axial or refractive. Methods: In this cross-sectional study ,41 pre-op cataract eyes with more than 0.33 difference between axial lengths of 2 eyes were enrolled.Considered for each 1mm difference between axial lengths in long eyes( AXL more than 25):1.75-2.00 D of anisometropia, for normal eyes(AXL: 22- 25):2.50D and for short eyes (AXL less than 22):3.50-3.75 D as axial anisometropia. If there are more or lesser anisometropia, we recorded as refractive anisometropia. Results: Average of anisometropia :4.24 D, prevalence of PK or LK :1 (2.38%), kc:1(2.38%), glaucoma surgery: 1(2.38%), and pseudophakic status of the opposite eye 8(19.04%). Prevalence of axial anisometropia:21 (52.4%) and refractive anisometropia 20(47.6%).Then on basis of this study we can rely on the patient’s refraction exactly before phaco for evaluation of axial length differences between the 2 eyes, because most of the anisometropias are axial. Conclusion: In most cases, cataract does not induce significant change in refractive error (secondary myopia) and AXL difference between the 2 eyes are correlated with anisometropia.so it can be used for cataract patient’s ocular biometry evaluation. Pre-cataract refraction is a valuable variable should be measured and recorded in routin eye examination.Keywords: ocular axial length, anisometropia, cataract, ophthalmology and optometry
Procedia PDF Downloads 3811207 Prediction of Compressive Strength Using Artificial Neural Network
Authors: Vijay Pal Singh, Yogesh Chandra Kotiyal
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Structures are a combination of various load carrying members which transfer the loads to the foundation from the superstructure safely. At the design stage, the loading of the structure is defined and appropriate material choices are made based upon their properties, mainly related to strength. The strength of materials kept on reducing with time because of many factors like environmental exposure and deformation caused by unpredictable external loads. Hence, to predict the strength of materials used in structures, various techniques are used. Among these techniques, Non-Destructive Techniques (NDT) are the one that can be used to predict the strength without damaging the structure. In the present study, the compressive strength of concrete has been predicted using Artificial Neural Network (ANN). The predicted strength was compared with the experimentally obtained actual compressive strength of concrete and equations were developed for different models. A good co-relation has been obtained between the predicted strength by these models and experimental values. Further, the co-relation has been developed using two NDT techniques for prediction of strength by regression analysis. It was found that the percentage error has been reduced between the predicted strength by using combined techniques in place of single techniques.Keywords: rebound, ultra-sonic pulse, penetration, ANN, NDT, regression
Procedia PDF Downloads 4281206 Predicting Indonesia External Debt Crisis: An Artificial Neural Network Approach
Authors: Riznaldi Akbar
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In this study, we compared the performance of the Artificial Neural Network (ANN) model with back-propagation algorithm in correctly predicting in-sample and out-of-sample external debt crisis in Indonesia. We found that exchange rate, foreign reserves, and exports are the major determinants to experiencing external debt crisis. The ANN in-sample performance provides relatively superior results. The ANN model is able to classify correctly crisis of 89.12 per cent with reasonably low false alarms of 7.01 per cent. In out-of-sample, the prediction performance fairly deteriorates compared to their in-sample performances. It could be explained as the ANN model tends to over-fit the data in the in-sample, but it could not fit the out-of-sample very well. The 10-fold cross-validation has been used to improve the out-of-sample prediction accuracy. The results also offer policy implications. The out-of-sample performance could be very sensitive to the size of the samples, as it could yield a higher total misclassification error and lower prediction accuracy. The ANN model could be used to identify past crisis episodes with some accuracy, but predicting crisis outside the estimation sample is much more challenging because of the presence of uncertainty.Keywords: debt crisis, external debt, artificial neural network, ANN
Procedia PDF Downloads 4431205 Analysis and Prediction of Fine Particulate Matter in the Air Environment for 2007-2020 in Bangkok Thailand
Authors: Phawichsak Prapassornpitaya, Wanida Jinsart
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Daily monitoring PM₁₀ and PM₂.₅ data from 2007 to 2017 were analyzed to provide baseline data for prediction of the air pollution in Bangkok in the period of 2018 -2020. Two statistical models, Autoregressive Integrated Moving Average model (ARIMA) were used to evaluate the trends of pollutions. The prediction concentrations were tested by root means square error (RMSE) and index of agreement (IOA). This evaluation of the traffic PM₂.₅ and PM₁₀ were studied in association with the regulatory control and emission standard changes. The emission factors of particulate matter from diesel vehicles were decreased when applied higher number of euro standard. The trends of ambient air pollutions were expected to decrease. However, the Bangkok smog episode in February 2018 with temperature inversion caused high concentration of PM₂.₅ in the air environment of Bangkok. The impact of traffic pollutants was depended upon the emission sources, temperature variations, and metrological conditions.Keywords: fine particulate matter, ARIMA, RMSE, Bangkok
Procedia PDF Downloads 2781204 Characterization of Oxide Layer Developed during Tribo-Interaction of Zircaloys
Authors: Bharat Kumar, Deepak Kumar, Vijay Chaudhry
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Zirconium alloys are used as core components of nuclear reactors due to their high wear resistance, good corrosion properties, and good mechanical stability at high temperatures. The present work simulates the contact between the calandria tube and the liquid injection shutdown system (LISS) nozzle. The Calandria tube is the outer covering of the pressure tube. Water flows inside the pressure tube through fuel claddings which produces vibration in the pressure tube along with vibration in the calandria tube. Fretting wear takes place at the point of contact between the calandria tube and the LISS nozzle. Fretting tests were performed under different conditions, such as; varying fretting duration (i.e., 1 to 4 hours), varying frequency (i.e., 5 to 6.5 Hz), and varying amplitude (100 to 400 µm). The formation of the oxide layer was observed during the fretting wear test; as a result, the worn product. The worn surfaces were analyzed with scanning electron microscopy (SEM) to analyze the wear mechanism involved in the fretting test, and Energy dispersive x-ray spectroscopy (EDS) and Raman spectroscopy were used to confirm the presence of an oxide layer on the worn surface. The oxide layer becomes more uniform with fretting duration in case of water submerged condition as compared to dry contact condition. The oxide layer is deeply removed at high amplitude due to the change of wear mechanism from adhesion to abrasion, as confirmed by the presence of micro ploughing and micro cutting. Low amplitude fretting favors the formation of the tribo-oxide layer.Keywords: tribo-oxide layer, wear, mechanically mixed layer, zircaloy
Procedia PDF Downloads 851203 Hierarchical Piecewise Linear Representation of Time Series Data
Authors: Vineetha Bettaiah, Heggere S. Ranganath
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This paper presents a Hierarchical Piecewise Linear Approximation (HPLA) for the representation of time series data in which the time series is treated as a curve in the time-amplitude image space. The curve is partitioned into segments by choosing perceptually important points as break points. Each segment between adjacent break points is recursively partitioned into two segments at the best point or midpoint until the error between the approximating line and the original curve becomes less than a pre-specified threshold. The HPLA representation achieves dimensionality reduction while preserving prominent local features and general shape of time series. The representation permits course-fine processing at different levels of details, allows flexible definition of similarity based on mathematical measures or general time series shape, and supports time series data mining operations including query by content, clustering and classification based on whole or subsequence similarity.Keywords: data mining, dimensionality reduction, piecewise linear representation, time series representation
Procedia PDF Downloads 2751202 SVM-Based Modeling of Mass Transfer Potential of Multiple Plunging Jets
Authors: Surinder Deswal, Mahesh Pal
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The paper investigates the potential of support vector machines based regression approach to model the mass transfer capacity of multiple plunging jets, both vertical (θ = 90°) and inclined (θ = 60°). The data set used in this study consists of four input parameters with a total of eighty eight cases. For testing, tenfold cross validation was used. Correlation coefficient values of 0.971 and 0.981 (root mean square error values of 0.0025 and 0.0020) were achieved by using polynomial and radial basis kernel functions based support vector regression respectively. Results suggest an improved performance by radial basis function in comparison to polynomial kernel based support vector machines. The estimated overall mass transfer coefficient, by both the kernel functions, is in good agreement with actual experimental values (within a scatter of ±15 %); thereby suggesting the utility of support vector machines based regression approach.Keywords: mass transfer, multiple plunging jets, support vector machines, ecological sciences
Procedia PDF Downloads 4641201 Insights and Observation for Optimum Work Roll Cooling in Flat Hot Mills: A Case Study on Shape Defect Elimination
Authors: Uday S. Goel, G. Senthil Kumar, Biswajit Ghosh, V. V. Mahashabde, Dhirendra Kumar, H. Manjunath, Ritesh Kumar, Mahesh Bhagwat, Subodh Pandey
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Tata Steel Bhushan Steel Ltd.(TSBSL)’s Hot Mill at Angul , Orissa , India, was facing shape issues in Hot Rolled (HR) coils. This was resulting in a defect called as ‘Ridge’, which was appearing in subsequent cold rolling operations at various cold mills (CRM) and external customers. A collaborative project was undertaken to resolve this issue. One of the reasons identified was the strange drop in thermal crown after rolling of 20-25 coils in the finishing mill (FM ) schedule. On the shop floor, it was observed that work roll temperatures in the FM after rolling were very high and non uniform across the work roll barrel. Jammed work roll cooling nozzles, insufficient roll bite lubrication and inadequate roll cooling water quality were found to be the main reasons. Regular checking was initiated to check roll cooling nozzles health, and quick replacement done if found jammed was implemented. Improvements on roll lubrication, especially flow rates, was done. Usage of anti-peeling headers and inter stand descaling was enhanced. A subsequent project was also taken up for improving the quality of roll cooling water. Encouraging results were obtained from the project with a reduction in rejection due to ridge at CRM’s by almost 95% of the pre project start levels. Poor profile occurrence of HR coils at HSM was also reduced from a high of 32% in May’19 to <1% since Apr’20.Keywords: hot rolling flat, shape, ridge, work roll, roll cooling nozzle, lubrication
Procedia PDF Downloads 991200 Indigenous Patch Clamp Technique: Design of Highly Sensitive Amplifier Circuit for Measuring and Monitoring of Real Time Ultra Low Ionic Current through Cellular Gates
Authors: Moez ul Hassan, Bushra Noman, Sarmad Hameed, Shahab Mehmood, Asma Bashir
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The importance of Noble prize winning “Patch Clamp Technique” is well documented. However, Patch Clamp Technique is very expensive and hence hinders research in developing countries. In this paper, detection, processing and recording of ultra low current from induced cells by using transimpedence amplifier is described. The sensitivity of the proposed amplifier is in the range of femto amperes (fA). Capacitive-feedback is used with active load to obtain a 20MΩ transimpedance gain. The challenging task in designing includes achieving adequate performance in gain, noise immunity and stability. The circuit designed by the authors was able to measure current in the rangeof 300fA to 100pA. Adequate performance shown by the amplifier with different input current and outcome result was found to be within the acceptable error range. Results were recorded using LabVIEW 8.5®for further research.Keywords: drug discovery, ionic current, operational amplifier, patch clamp
Procedia PDF Downloads 519