Search results for: linear spectral unmixing
3624 Geometrically Non-Linear Axisymmetric Free Vibration Analysis of Functionally Graded Annular Plates
Authors: Boutahar Lhoucine, El Bikri Khalid, Benamar Rhali
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In this paper, the non-linear free axisymmetric vibration of a thin annular plate made of functionally graded material (FGM) has been studied by using the energy method and a multimode approach. FGM properties vary continuously as well as non-homogeneity through the thickness direction of the plate. The theoretical model is based on the classical plate theory and the Von Kármán geometrical non-linearity assumptions. An approximation has been adopted in the present work consisting of neglecting the in-plane deformation in the formulation. Hamilton’s principle is used to derive the governing equation of motion. The problem is solved by a numerical iterative procedure in order to obtain more accurate results for vibration amplitudes up to 1.5 times the plate thickness. The numerical results are given for the first axisymmetric non-linear mode shape for a wide range of vibration amplitudes and they are presented either in tabular form or in graphical form to show the effect that the vibration amplitude and the variation in material properties have significant effects on the frequencies and the bending stresses in large amplitude vibration of the functionally graded annular plate.Keywords: non-linear vibrations, annular plates, large amplitudes, functionally graded material
Procedia PDF Downloads 3573623 Linear Prediction System in Measuring Glucose Level in Blood
Authors: Intan Maisarah Abd Rahim, Herlina Abdul Rahim, Rashidah Ghazali
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Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.Keywords: diabetes, glucose level, linear, near-infrared, non-invasive, prediction system
Procedia PDF Downloads 1533622 Generalized Additive Model for Estimating Propensity Score
Authors: Tahmidul Islam
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Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching
Procedia PDF Downloads 3623621 A Filtering Algorithm for a Nonlinear State-Space Model
Authors: Abdullah Eqal Al Mazrooei
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Kalman filter is a famous algorithm that utilizes to estimate the state in the linear systems. It has numerous applications in technology and science. Since of the most of applications in real life can be described by nonlinear systems. So, Kalman filter does not work with the nonlinear systems because it is suitable to linear systems only. In this work, a nonlinear filtering algorithm is presented which is suitable to use with the special kinds of nonlinear systems. This filter generalizes the Kalman filter. This means that this filter also can be used for the linear systems. Our algorithm depends on a special linearization of the second degree. We introduced the nonlinear algorithm with a bilinear state-space model. A simulation example is presented to illustrate the efficiency of the algorithm.Keywords: Kalman filter, filtering algorithm, nonlinear systems, state-space model
Procedia PDF Downloads 3683620 Analysis of Detection Concealed Objects Based on Multispectral and Hyperspectral Signatures
Authors: M. Kastek, M. Kowalski, M. Szustakowski, H. Polakowski, T. Sosnowski
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Development of highly efficient security systems is one of the most urgent topics for science and engineering. There are many kinds of threats and many methods of prevention. It is very important to detect a threat as early as possible in order to neutralize it. One of the very challenging problems is detection of dangerous objects hidden under human’s clothing. This problem is particularly important for safety of airport passengers. In order to develop methods and algorithms to detect hidden objects it is necessary to determine the thermal signatures of such objects of interest. The laboratory measurements were conducted to determine the thermal signatures of dangerous tools hidden under various clothes in different ambient conditions. Cameras used for measurements were working in spectral range 0.6-12.5 μm An infrared imaging Fourier transform spectroradiometer was also used, working in spectral range 7.7-11.7 μm. Analysis of registered thermograms and hyperspectral datacubes has yielded the thermal signatures for two types of guns, two types of knives and home-made explosive bombs. The determined thermal signatures will be used in the development of method and algorithms of image analysis implemented in proposed monitoring systems.Keywords: hyperspectral detection, nultispectral detection, image processing, monitoring systems
Procedia PDF Downloads 3413619 Evaluation of Features Extraction Algorithms for a Real-Time Isolated Word Recognition System
Authors: Tomyslav Sledevič, Artūras Serackis, Gintautas Tamulevičius, Dalius Navakauskas
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This paper presents a comparative evaluation of features extraction algorithm for a real-time isolated word recognition system based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were implemented in hardware/software design. The proposed system was investigated in the speaker-dependent mode for 100 different Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signals to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients give best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose, the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfies the real-time requirements and is suitable for applications in embedded systems.Keywords: isolated word recognition, features extraction, MFCC, LFCC, LPCC, LPC, FPGA, DTW
Procedia PDF Downloads 4863618 Development and Validation of First Derivative Method and Artificial Neural Network for Simultaneous Spectrophotometric Determination of Two Closely Related Antioxidant Nutraceuticals in Their Binary Mixture”
Authors: Mohamed Korany, Azza Gazy, Essam Khamis, Marwa Adel, Miranda Fawzy
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Background: Two new, simple and specific methods; First, a Zero-crossing first-derivative technique and second, a chemometric-assisted spectrophotometric artificial neural network (ANN) were developed and validated in accordance with ICH guidelines. Both methods were used for the simultaneous estimation of the two closely related antioxidant nutraceuticals ; Coenzyme Q10 (Q) ; also known as Ubidecarenone or Ubiquinone-10, and Vitamin E (E); alpha-tocopherol acetate, in their pharmaceutical binary mixture. Results: For first method: By applying the first derivative, both Q and E were alternatively determined; each at the zero-crossing of the other. The D1 amplitudes of Q and E, at 285 nm and 235 nm respectively, were recorded and correlated to their concentrations. The calibration curve is linear over the concentration range of 10-60 and 5.6-70 μg mL-1 for Q and E, respectively. For second method: ANN (as a multivariate calibration method) was developed and applied for the simultaneous determination of both analytes. A training set (or a concentration set) of 90 different synthetic mixtures containing Q and E, in wide concentration ranges between 0-100 µg/mL and 0-556 µg/mL respectively, were prepared in ethanol. The absorption spectra of the training sets were recorded in the spectral region of 230–300 nm. A Gradient Descend Back Propagation ANN chemometric calibration was computed by relating the concentration sets (x-block) to their corresponding absorption data (y-block). Another set of 45 synthetic mixtures of the two drugs, in defined range, was used to validate the proposed network. Neither chemical separation, preparation stage nor mathematical graphical treatment were required. Conclusions: The proposed methods were successfully applied for the assay of Q and E in laboratory prepared mixtures and combined pharmaceutical tablet with excellent recoveries. The ANN method was superior over the derivative technique as the former determined both drugs in the non-linear experimental conditions. It also offers rapidity, high accuracy, effort and money saving. Moreover, no need for an analyst for its application. Although the ANN technique needed a large training set, it is the method of choice in the routine analysis of Q and E tablet. No interference was observed from common pharmaceutical additives. The results of the two methods were compared togetherKeywords: coenzyme Q10, vitamin E, chemometry, quantitative analysis, first derivative spectrophotometry, artificial neural network
Procedia PDF Downloads 4393617 Computational Simulations on Stability of Model Predictive Control for Linear Discrete-Time Stochastic Systems
Authors: Tomoaki Hashimoto
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Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the validity of the obtained stability condition.Keywords: computational simulations, optimal control, predictive control, stochastic systems, discrete-time systems
Procedia PDF Downloads 4253616 Theoretical Approach to Kinetic of Heat Transfer under Irradiation
Authors: Pavlo Selyshchev
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A theoretical approach to describe kinetic of heat transfer between an irradiated sample and environment is developed via formalism of the Complex systems and kinetic equations. The irradiated material is a metastable system with non-linear feedbacks, which can give rise to different regimes of buildup and annealing of radiation-induced defects, heating and heat transfer with environment. Irradiation with energetic particles heats the sample and produces defects of the crystal lattice of the sample. The crystal with defects accumulates extra (non-thermal) energy, which is transformed into heat during the defect annealing. Any increase of temperature leads to acceleration of defect annealing, to additional transformation of non-thermal energy into heat and to further growth of the temperature. Thus a non-linear feedback is formed. It is shown that at certain conditions of irradiation this non-linear feedback leads to self-oscillations of the defect density, the temperature of the irradiated sample and the heat transfer between the sample and environment. Simulation and analysis of these phenomena is performed. The frequency of the self-oscillations is obtained. It is determined that the period of the self-oscillations is varied from minutes to several hours depending on conditions of irradiation and properties of the sample. Obtaining results are compared with experimental ones.Keywords: irradiation, heat transfer, non-linear feed-back, self-oscillations
Procedia PDF Downloads 2223615 Stochastic Model Predictive Control for Linear Discrete-Time Systems with Random Dither Quantization
Authors: Tomoaki Hashimoto
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Recently, feedback control systems using random dither quantizers have been proposed for linear discrete-time systems. However, the constraints imposed on state and control variables have not yet been taken into account for the design of feedback control systems with random dither quantization. Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial and terminal time. An important advantage of model predictive control is its ability to handle constraints imposed on state and control variables. Based on the model predictive control approach, the objective of this paper is to present a control method that satisfies probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization. In other words, this paper provides a method for solving the optimal control problems subject to probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization.Keywords: optimal control, stochastic systems, random dither, quantization
Procedia PDF Downloads 4353614 Constant Order Predictor Corrector Method for the Solution of Modeled Problems of First Order IVPs of ODEs
Authors: A. A. James, A. O. Adesanya, M. R. Odekunle, D. G. Yakubu
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This paper examines the development of one step, five hybrid point method for the solution of first order initial value problems. We adopted the method of collocation and interpolation of power series approximate solution to generate a continuous linear multistep method. The continuous linear multistep method was evaluated at selected grid points to give the discrete linear multistep method. The method was implemented using a constant order predictor of order seven over an overlapping interval. The basic properties of the derived corrector was investigated and found to be zero stable, consistent and convergent. The region of absolute stability was also investigated. The method was tested on some numerical experiments and found to compete favorably with the existing methods.Keywords: interpolation, approximate solution, collocation, differential system, half step, converges, block method, efficiency
Procedia PDF Downloads 3283613 Interaction with Earth’s Surface in Remote Sensing
Authors: Spoorthi Sripad
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Remote sensing is a powerful tool for acquiring information about the Earth's surface without direct contact, relying on the interaction of electromagnetic radiation with various materials and features. This paper explores the fundamental principle of "Interaction with Earth's Surface" in remote sensing, shedding light on the intricate processes that occur when electromagnetic waves encounter different surfaces. The absorption, reflection, and transmission of radiation generate distinct spectral signatures, allowing for the identification and classification of surface materials. The paper delves into the significance of the visible, infrared, and thermal infrared regions of the electromagnetic spectrum, highlighting how their unique interactions contribute to a wealth of applications, from land cover classification to environmental monitoring. The discussion encompasses the types of sensors and platforms used to capture these interactions, including multispectral and hyperspectral imaging systems. By examining real-world applications, such as land cover classification and environmental monitoring, the paper underscores the critical role of understanding the interaction with the Earth's surface for accurate and meaningful interpretation of remote sensing data.Keywords: remote sensing, earth's surface interaction, electromagnetic radiation, spectral signatures, land cover classification, archeology and cultural heritage preservation
Procedia PDF Downloads 483612 Decentralized Control of Interconnected Systems with Non-Linear Unknown Interconnections
Authors: Haci Mehmet Guzey, Levent Acar
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In this paper, a novel decentralized controller is developed for linear systems with nonlinear unknown interconnections. A model linear decoupled system is assigned for each system. By using the difference actual and model state dynamics, the problem is formulated as inverse problem. Then, the interconnected dynamics are approximated by using Galerkin’s expansion method for inverse problems. Two different sets of orthogonal basis functions are utilized to approximate the interconnected dynamics. Approximated interconnections are utilized in the controller to cancel the interconnections and decouple the systems. Subsequently, the interconnected systems behave as a collection of decoupled systems.Keywords: decentralized control, inverse problems, large scale systems, nonlinear interconnections, basis functions, system identification
Procedia PDF Downloads 5283611 Analysis of Risk Factors Affecting the Motor Insurance Pricing with Generalized Linear Models
Authors: Puttharapong Sakulwaropas, Uraiwan Jaroengeratikun
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Casualty insurance business, the optimal premium pricing and adequate cost for an insurance company are important in risk management. Normally, the insurance pure premium can be determined by multiplying the claim frequency with the claim cost. The aim of this research was to study in the application of generalized linear models to select the risk factor for model of claim frequency and claim cost for estimating a pure premium. In this study, the data set was the claim of comprehensive motor insurance, which was provided by one of the insurance company in Thailand. The results of this study found that the risk factors significantly related to pure premium at the 0.05 level consisted of no claim bonus (NCB) and used of the car (Car code).Keywords: generalized linear models, risk factor, pure premium, regression model
Procedia PDF Downloads 4603610 Spatio-Temporal Analysis of Land Use Land Cover Change Using Remote Sensing and Multispectral Satellite Imagery of Islamabad Pakistan
Authors: Basit Aftab, Feng Zhongke
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The land use/land cover change (LULCC) is a significant indicator sensitive to an area's environmental changes. As a rapidly developing capital city near the Himalayas Mountains, the city area of Islamabad, Pakistan, has expanded dramatically over the past 20 years. In order to precisely measure the impact of urbanization on the forest and agricultural lands, the Spatio-temporal analysis of LULCC was utilized, which helped us to know the impacts of urbanization, especially on ecosystem processes, biological cycles, and biodiversity. The Islamabad region's Multispectral Satellite Images (MSI) for 2000, 2010, and 2020 were employed as the remote sensing data source. Local documents of city planning, forest inventory and archives in the agriculture management departments were included to verify the image-derived result. The results showed that from 2000 to 2020, the built-up area increased to 48.3% (505.02 Km2). Meanwhile, the forest, agricultural, and barre land decreased to 28.9% (305.64 Km2), 10.04% (104.87 Km2), and 11.61% (121.30 Km2). The overall percentage change in land area between 2000 – 2020 was recorded maximum for the built-up (227.04%). Results revealed that the increase in the built-up area decreased forestland, barren, and agricultural lands (-0.36, -1.00 & -0.34). The association of built-up with respective years was positively linear (R2 = 0.96), whereas forestland, agricultural, and barren lands association with years were recorded as negatively linear (R2 = -0.29, R2 = -0.02, and R2 = -0.96). Large-scale deforestation leads to multiple negative impacts on the local environment, e.g., water degradation and climate change. It would finally affect the environment of the greater Himalayan region in some way. We further analyzed the driving forces of urbanization. It was determined by economic expansion, climate change, and population growth. We hope our study could be utilized to develop efforts to mitigate the consequences of deforestation and agricultural land damage, reducing greenhouse gas emissions while preserving the area's biodiversity.Keywords: urbanization, Himalaya mountains, landuse landcover change (LULCC), remote sensing., multi-spectral satellite imagery
Procedia PDF Downloads 243609 A Statistical Approach to Predict and Classify the Commercial Hatchability of Chickens Using Extrinsic Parameters of Breeders and Eggs
Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa
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Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.Keywords: classification models, egg weight, fertilised eggs, multiple linear regression
Procedia PDF Downloads 823608 A Study on the Coefficient of Transforming Relative Lateral Displacement under Linear Analysis of Structure to Its Real Relative Lateral Displacement
Authors: Abtin Farokhipanah
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In recent years, analysis of structures is based on ductility design in contradictory to strength design in surveying earthquake effects on structures. ASCE07-10 code offers to intensify relative drifts calculated from a linear analysis with Cd which is called (Deflection Amplification Factor) to obtain the real relative drifts which can be calculated using nonlinear analysis. This lateral drift should be limited to the code boundaries. Calculation of this amplification factor for different structures, comparing with ASCE07-10 code and offering the best coefficient are the purposes of this research. Following our target, short and tall building steel structures with various earthquake resistant systems in linear and nonlinear analysis should be surveyed, so these questions will be answered: 1. Does the Response Modification Coefficient (R) have a meaningful relation to Deflection Amplification Factor? 2. Does structure height, seismic zone, response spectrum and similar parameters have an effect on the conversion coefficient of linear analysis to real drift of structure? The procedure has used to conduct this research includes: (a) Study on earthquake resistant systems, (b) Selection of systems and modeling, (c) Analyzing modeled systems using linear and nonlinear methods, (d) Calculating conversion coefficient for each system and (e) Comparing conversion coefficients with the code offered ones and concluding results.Keywords: ASCE07-10 code, deflection amplification factor, earthquake engineering, lateral displacement of structures, response modification coefficient
Procedia PDF Downloads 3493607 Geothermal Energy Evaluation of Lower Benue Trough Using Spectral Analysis of Aeromagnetic Data
Authors: Stella C. Okenu, Stephen O. Adikwu, Martins E. Okoro
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The geothermal energy resource potential of the Lower Benue Trough (LBT) in Nigeria was evaluated in this study using spectral analysis of high-resolution aeromagnetic (HRAM) data. The reduced to the equator aeromagnetic data was divided into sixteen (16) overlapping blocks, and each of the blocks was analyzed to obtain the radial averaged power spectrum which enabled the computation of the top and centroid depths to magnetic sources. The values were then used to assess the Curie Point Depth (CPD), geothermal gradients, and heat flow variations in the study area. Results showed that CPD varies from 7.03 to 18.23 km, with an average of 12.26 km; geothermal gradient values vary between 31.82 and 82.50°C/km, with an average of 51.21°C/km, while heat flow variations range from 79.54 to 206.26 mW/m², with an average of 128.02 mW/m². Shallow CPD zones that run from the eastern through the western and southwestern parts of the study area correspond to zones of high geothermal gradient values and high subsurface heat flow distributions. These areas signify zones associated with anomalous subsurface thermal conditions and are therefore recommended for detailed geothermal energy exploration studies.Keywords: geothermal energy, curie-point depth, geothermal gradient, heat flow, aeromagnetic data, LBT
Procedia PDF Downloads 693606 An Improved Data Aided Channel Estimation Technique Using Genetic Algorithm for Massive Multi-Input Multiple-Output
Authors: M. Kislu Noman, Syed Mohammed Shamsul Islam, Shahriar Hassan, Raihana Pervin
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With the increasing rate of wireless devices and high bandwidth operations, wireless networking and communications are becoming over crowded. To cope with such crowdy and messy situation, massive MIMO is designed to work with hundreds of low costs serving antennas at a time as well as improve the spectral efficiency at the same time. TDD has been used for gaining beamforming which is a major part of massive MIMO, to gain its best improvement to transmit and receive pilot sequences. All the benefits are only possible if the channel state information or channel estimation is gained properly. The common methods to estimate channel matrix used so far is LS, MMSE and a linear version of MMSE also proposed in many research works. We have optimized these methods using genetic algorithm to minimize the mean squared error and finding the best channel matrix from existing algorithms with less computational complexity. Our simulation result has shown that the use of GA worked beautifully on existing algorithms in a Rayleigh slow fading channel and existence of Additive White Gaussian Noise. We found that the GA optimized LS is better than existing algorithms as GA provides optimal result in some few iterations in terms of MSE with respect to SNR and computational complexity.Keywords: channel estimation, LMMSE, LS, MIMO, MMSE
Procedia PDF Downloads 1873605 A Mixed Integer Linear Programming Model for Flexible Job Shop Scheduling Problem
Authors: Mohsen Ziaee
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In this paper, a mixed integer linear programming (MILP) model is presented to solve the flexible job shop scheduling problem (FJSP). This problem is one of the hardest combinatorial problems. The objective considered is the minimization of the makespan. The computational results of the proposed MILP model were compared with those of the best known mathematical model in the literature in terms of the computational time. The results show that our model has better performance with respect to all the considered performance measures including relative percentage deviation (RPD) value, number of constraints, and total number of variables. By this improved mathematical model, larger FJS problems can be optimally solved in reasonable time, and therefore, the model would be a better tool for the performance evaluation of the approximation algorithms developed for the problem.Keywords: scheduling, flexible job shop, makespan, mixed integer linear programming
Procedia PDF Downloads 1763604 Design and Simulation of a Double-Stator Linear Induction Machine with Short Squirrel-Cage Mover
Authors: David Rafetseder, Walter Bauer, Florian Poltschak, Wolfgang Amrhein
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A flat double-stator linear induction machine (DSLIM) with a short squirrel-cage mover is designed for high thrust force at moderate speed < 5m/s. The performance and motor parameters are determined on the basis of a 2D time-transient simulation with the finite element (FE) software Maxwell 2015. Design guidelines and transformation rules for space vector theory of the LIM are presented. Resulting thrust calculated by flux and current vectors is compared with the FE results showing good coherence and reduced noise. The parameters of the equivalent circuit model are obtained.Keywords: equivalent circuit model, finite element model, linear induction motor, space vector theory
Procedia PDF Downloads 5593603 Geoinformation Technology of Agricultural Monitoring Using Multi-Temporal Satellite Imagery
Authors: Olena Kavats, Dmitry Khramov, Kateryna Sergieieva, Vladimir Vasyliev, Iurii Kavats
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Geoinformation technologies of space agromonitoring are a means of operative decision making support in the tasks of managing the agricultural sector of the economy. Existing technologies use satellite images in the optical range of electromagnetic spectrum. Time series of optical images often contain gaps due to the presence of clouds and haze. A geoinformation technology is created. It allows to fill gaps in time series of optical images (Sentinel-2, Landsat-8, PROBA-V, MODIS) with radar survey data (Sentinel-1) and use information about agrometeorological conditions of the growing season for individual monitoring years. The technology allows to perform crop classification and mapping for spring-summer (winter and spring crops) and autumn-winter (winter crops) periods of vegetation, monitoring the dynamics of crop state seasonal changes, crop yield forecasting. Crop classification is based on supervised classification algorithms, takes into account the peculiarities of crop growth at different vegetation stages (dates of sowing, emergence, active vegetation, and harvesting) and agriculture land state characteristics (row spacing, seedling density, etc.). A catalog of samples of the main agricultural crops (Ukraine) is created and crop spectral signatures are calculated with the preliminary removal of row spacing, cloud cover, and cloud shadows in order to construct time series of crop growth characteristics. The obtained data is used in grain crop growth tracking and in timely detection of growth trends deviations from reference samples of a given crop for a selected date. Statistical models of crop yield forecast are created in the forms of linear and nonlinear interconnections between crop yield indicators and crop state characteristics (temperature, precipitation, vegetation indices, etc.). Predicted values of grain crop yield are evaluated with an accuracy up to 95%. The developed technology was used for agricultural areas monitoring in a number of Great Britain and Ukraine regions using EOS Crop Monitoring Platform (https://crop-monitoring.eos.com). The obtained results allow to conclude that joint use of Sentinel-1 and Sentinel-2 images improve separation of winter crops (rapeseed, wheat, barley) in the early stages of vegetation (October-December). It allows to separate successfully the soybean, corn, and sunflower sowing areas that are quite similar in their spectral characteristics.Keywords: geoinformation technology, crop classification, crop yield prediction, agricultural monitoring, EOS Crop Monitoring Platform
Procedia PDF Downloads 4443602 Achieving 13th Sustainable Development Goal: Urbanization and ICT Empowerment in Pursuit of Carbon Neutrality - Beyond Linear Thinking
Authors: Salim Khan
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The attainment of the carbon neutrality objective and Sustainable Development Goal 13 (SDG-13) target, which pertains to climate actions, received widespread attention in developing and emerging nations. Given the increasing pace of urbanization, technological advancements, and rapid growth, it is imperative to examine the linear and nonlinear effects of urbanization and economic growth and the linear impact of information and communication technology (ICT) on carbon emissions (CO2e). This study employs the Dynamic System GMM (DSGMM) and Panel Quantile Regression (PQR) methodologies to investigate the causal relationship between urbanization, ICT, economic growth, and their interplay on CO2e in 39 BRI countries from 2001 to 2020. The study's findings indicate that the impact of urbanization on CO2e exhibits linear and nonlinear patterns. The specific nonlinear impact of urbanization leads to a decrease in CO2e, hence facilitating the achievement of carbon neutrality and contributing to SDG-13. The study highlights the importance of ICT in achieving SDG-13 by reducing CO2e, emphasizing the need for informatization. Simultaneously, the findings support the Environmental Kuznets Curve (EKC) hypothesis and support the pollution haven theory. Finally, based on empirical findings, significant policy implications are suggested for achieving SGD 13 and carbon neutrality.Keywords: urbanization, ICT, CO2 emission, EKC, pollution haven, BRI
Procedia PDF Downloads 173601 Control of a Stewart Platform for Minimizing Impact Energy in Simulating Spacecraft Docking Operations
Authors: Leonardo Herrera, Shield B. Lin, Stephen J. Montgomery-Smith, Ziraguen O. Williams
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Three control algorithms: Proportional-Integral-Derivative, Linear-Quadratic-Gaussian, and Linear-Quadratic-Gaussian with the shift, were applied to the computer simulation of a one-directional dynamic model of a Stewart Platform. The goal was to compare the dynamic system responses under the three control algorithms and to minimize the impact energy when simulating spacecraft docking operations. Equations were derived for the control algorithms and the input and output of the feedback control system. Using MATLAB, Simulink diagrams were created to represent the three control schemes. A switch selector was used for the convenience of changing among different controllers. The simulation demonstrated the controller using the algorithm of Linear-Quadratic-Gaussian with the shift resulting in the lowest impact energy.Keywords: controller, Stewart platform, docking operation, spacecraft
Procedia PDF Downloads 403600 Electrochemical Study of Interaction of Thiol Containing Proteins with As (III)
Authors: Sunil Mittal, Sukhpreet Singh, Hardeep Kaur
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The affinity of thiol group with heavy metals is a well-established phenomenon. The present investigation has been focused on electrochemical response of cysteine and thioredoxin against arsenite (As III) on indium tin oxide (ITO) electrodes. It was observed that both the compounds produce distinct response in free and immobilised form at the electrode. The SEM, FTIR, and impedance studies of the modified electrode were conducted for characterization. Various parameters were optimized to achieve As (III) effect on the reduction potential of the compounds. Cyclic voltammetry and linear sweep voltammetry were employed as the analysis techniques. The optimum response was observed at neutral pH in both the cases, at optimum concentration of 2 mM and 4.27 µM for cysteine and thioredoxin respectively. It was observed that presence of As (III) increases the reduction current of both the moieties. The linear range of detection for As (III) with cysteine was from 1 to 10 mg L⁻¹ with detection limit of 0.8 mg L⁻¹. The thioredoxin was found more sensitive to As (III) and displayed a linear range from 0.1 to 1 mg L⁻¹ with detection limit of 10 µg L⁻¹.Keywords: arsenite, cyclic voltammetry, cysteine, thioredoxin
Procedia PDF Downloads 2063599 Development of High-Efficiency Down-Conversion Fluoride Phosphors to Increase the Efficiency of Solar Panels
Authors: S. V. Kuznetsov, M. N. Mayakova, V. Yu. Proydakova, V. V. Pavlov, A. S. Nizamutdinov, O. A. Morozov, V. V. Voronov, P. P. Fedorov
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Increase in the share of electricity received by conversion of solar energy results in the reduction of the industrial impact on the environment from the use of the hydrocarbon energy sources. One way to increase said share is to improve the efficiency of solar energy conversion in silicon-based solar panels. Such efficiency increase can be achieved by transferring energy from sunlight-insensitive areas of work of silicon solar panels to the area of their photoresistivity. To achieve this goal, a transition to new luminescent materials with the high quantum yield of luminescence is necessary. Improvement in the quantum yield can be achieved by quantum cutting, which allows obtaining a quantum yield of down conversion of more than 150% due to the splitting of high-energy photons of the UV spectral range into lower-energy photons of the visible and near infrared spectral ranges. The goal of present work is to test approach of excitation through sensibilization of 4f-4f fluorescence of Yb3+ by various RE ions absorbing in UV and Vis spectral ranges. One of promising materials for quantum cutting luminophores are fluorides. In our investigation we have developed synthesis of nano- and submicron powders of calcium fluoride and strontium doped with rare-earth elements (Yb: Ce, Yb: Pr, Yb: Eu) of controlled dimensions and shape by co-precipitation from water solution technique. We have used Ca(NO3)2*4H2O, Sr(NO3)2, HF, NH4F as precursors. After initial solutions of nitrates were prepared they have been mixed with fluorine containing solution by dropwise manner. According to XRD data, the synthesis resulted in single phase samples with fluorite structure. By means of SEM measurements, we have confirmed spherical morphology and have determined sizes of particles (50-100 nm after synthesis and 150-300 nm after calcination). Temperature of calcination appeared to be 600°C. We have investigated the spectral-kinetic characteristics of above mentioned compounds. Here the diffuse reflection and laser induced fluorescence spectra of Yb3+ ions excited at around 4f-4f and 4f-5d transitions of Pr3+, Eu3+ and Ce3+ ions in the synthesized powders are reported. The investigation of down conversion luminescence capability of synthesized compounds included measurements of fluorescence decays and quantum yield of 2F5/2-2F7/2 fluorescence of Yb3+ ions as function of Yb3+ and sensitizer contents. An optimal chemical composition of CaF2-YbF3- LnF3 (Ln=Ce, Eu, Pr), SrF2-YbF3-LnF3 (Ln=Ce, Eu, Pr) micro- and nano- powders according to criteria of maximal IR fluorescence yield is proposed. We suppose that investigated materials are prospective in solar panels improvement applications. Work was supported by Russian Science Foundation grant #17-73- 20352.Keywords: solar cell, fluorides, down-conversion luminescence, maximum quantum yield
Procedia PDF Downloads 2673598 Mapping Stress in Submerged Aquatic Vegetation Using Multispectral Imagery and Structure from Motion Photogrammetry
Authors: Amritha Nair, Fleur Visser, Ian Maddock, Jonas Schoelynck
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Inland waters such as streams sustain a rich variety of species and are essentially hotspots for biodiversity. Submerged aquatic vegetation, also known as SAV, forms an important part of ecologically healthy river systems. Direct and indirect human influences, such as climate change are putting stress on aquatic plant communities, ranging from the invasion of non-native species and grazing, to changes in the river flow conditions and temperature. There is a need to monitor SAV, because they are in a state of deterioration and their disappearance will greatly impact river ecosystems. Like terrestrial plants, SAV can show visible signs of stress. However, the techniques used to map terrestrial vegetation from its spectral reflectance, are not easily transferable to a submerged environment. Optical remote sensing techniques are employed to detect the stress from remotely sensed images through multispectral imagery and Structure from Motion photogrammetry. The effect of the overlying water column in the form of refraction, attenuation of visible and near infrared bands in water, as well as highly moving targets, are NIR) key challenges that arise when remotely mapping SAV. This study looks into the possibility of mapping the changes in spectral signatures from SAV and their response to certain stresses.Keywords: submerged aquatic vegetation, structure from motion, photogrammetry, multispectral, spectroscopy
Procedia PDF Downloads 853597 Timetabling Communities’ Demands for an Effective Examination Timetabling Using Integer Linear Programming
Authors: N. F. Jamaluddin, N. A. H. Aizam
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This paper explains the educational timetabling problem, a type of scheduling problem that is considered as one of the most challenging problem in optimization and operational research. The university examination timetabling problem (UETP), which involves assigning a set number of exams into a set number of timeslots whilst fulfilling all required conditions, has been widely investigated. The limitation of available timeslots and resources with the increasing number of examinations are the main reasons in the difficulty of solving this problem. Dynamical change in the examination scheduling system adds up the complication particularly in coping up with the demand and new requirements by the communities. Our objective is to investigate these demands and requirements with subjects taken from Universiti Malaysia Terengganu (UMT), through questionnaires. Integer linear programming model which reflects the preferences obtained to produce an effective examination timetabling was formed.Keywords: demands, educational timetabling, integer linear programming, scheduling, university examination timetabling problem (UETP)
Procedia PDF Downloads 3343596 The Linear Combination of Kernels in the Estimation of the Cumulative Distribution Functions
Authors: Abdel-Razzaq Mugdadi, Ruqayyah Sani
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The Kernel Distribution Function Estimator (KDFE) method is the most popular method for nonparametric estimation of the cumulative distribution function. The kernel and the bandwidth are the most important components of this estimator. In this investigation, we replace the kernel in the KDFE with a linear combination of kernels to obtain a new estimator based on the linear combination of kernels, the mean integrated squared error (MISE), asymptotic mean integrated squared error (AMISE) and the asymptotically optimal bandwidth for the new estimator are derived. We propose a new data-based method to select the bandwidth for the new estimator. The new technique is based on the Plug-in technique in density estimation. We evaluate the new estimator and the new technique using simulations and real-life data.Keywords: estimation, bandwidth, mean square error, cumulative distribution function
Procedia PDF Downloads 5693595 The Prediction of Evolutionary Process of Coloured Vision in Mammals: A System Biology Approach
Authors: Shivani Sharma, Prashant Saxena, Inamul Hasan Madar
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Since the time of Darwin, it has been considered that genetic change is the direct indicator of variation in phenotype. But a few studies in system biology in the past years have proposed that epigenetic developmental processes also affect the phenotype thus shifting the focus from a linear genotype-phenotype map to a non-linear G-P map. In this paper, we attempt at explaining the evolution of colour vision in mammals by taking LWS/ Long-wave sensitive gene under consideration.Keywords: evolution, phenotypes, epigenetics, LWS gene, G-P map
Procedia PDF Downloads 513