Search results for: fixed weight beamforming
3308 Electrical and Magnetoelectric Properties of (y)Li0.5Ni0.7Zn0.05Fe2O4 + (1-y)Ba0.5Sr0.5TiO3 Magnetoelectric Composites
Authors: S. U. Durgadsimi, S. Chouguleb, S. Belladc
Abstract:
(y) Li0.5Ni0.7Zn0.05Fe2O4 + (1-y) Ba0.5Sr0.5TiO3 magnetoelectric composites with y = 0.1, 0.3 and 0.5 were prepared by a conventional standard double sintering ceramic technique. X-ray diffraction analysis confirmed the phase formation of ferrite, ferroelectric and their composites. logρdc Vs 1/T graphs reveal that the dc resistivity decreases with increasing temperature exhibiting semiconductor behavior. The plots of logσac Vs logω2 are almost linear indicating that the conductivity increases with increase in frequency i.e, conductivity in the composites is due to small polaron hopping. Dielectric constant (έ) and dielectric loss (tan δ) were studied as a function of frequency in the range 100Hz–1MHz which reveals the normal dielectric behavior except the composite with y=0.1 and as a function of temperature at four fixed frequencies (i.e. 100Hz, 1KHz, 10KHz, 100KHz). ME voltage coefficient decreases with increase in ferrite content and was observed to be maximum of about 7.495 mV/cmOe for (0.1) Li0.5Ni0.7Zn0.05Fe2O4 + (0.9) Ba0.5Sr0.5TiO3 composite.Keywords: XRD, dielectric constant, dielectric loss, DC and AC conductivity, ME voltage coefficient
Procedia PDF Downloads 3443307 Performance Evaluation of Grid Connected Photovoltaic System
Authors: Abdulkadir Magaji
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This study analyzes and compares the actual measured and simulated performance of a 3.2 kwP grid-connected photovoltaic system. The system is located at the Outdoor Facility of Government Day secondary School Katsina State, which lies approximately between coordinate of 12°15′N 7°30′E. The system consists of 14 Mono crystalline silicon modules connected in two strings of 7 series-connected modules, each facing north at a fixed tilt of 340. The data presented in this study were measured in the year 2015, where the system supplied a total of 4628 kWh to the local electric utility grid. The performance of the system was simulated using PVsyst software using measured and Meteonorm derived climate data sets (solar radiation, ambient temperature and wind speed). The comparison between measured and simulated energy yield are discussed. Although, both simulation results were similar, better comparison between measured and predicted monthly energy yield is observed with simulation performed using measured weather data at the site. The measured performance ratio in the present study shows 58.4% is higher than those reported elsewhere as compared in the study.Keywords: performance, evaluation, grid connection, photovoltaic system
Procedia PDF Downloads 1813306 Structural and Electrical Characterization of Polypyrrole and Cobalt Aluminum Oxide Nanocomposites
Authors: Sutar Rani Ananda, M. V. Murugendrappa
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To investigate electrical properties of conducting polypyrrole (PPy) and cobalt aluminum oxide (CAO) nanocomposites, impedance analyzer in frequency range of 100 Hz to 5 MHz is used. In this work, PPy/CAO nanocomposites were synthesized by chemical oxidation polymerization method in different weight percent of CAO in PPy. The dielectric properties and AC conductivity studies were carried out for different nanocomposites in temperature range of room temperature to 180 °C. With the increase in frequency, the dielectric constant for all the nanocomposites was observed to decrease. AC conductivity of PPy was improved by addition of CAO nanopowder.Keywords: polypyrrole, dielectric constant, dielectric loss, AC conductivity
Procedia PDF Downloads 2953305 Conflict and Hunger Revisit: Evidences from Global Surveys, 1989-2020
Authors: Manasse Elusma, Thung-Hong Lin, Chun-yin Lee
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The relationship between hunger and war or conflict remains to be discussed. Do wars or conflicts cause hunger and food scarcity, or is the reverse relationship is true? As the world becomes more peaceful and wealthier, some countries are still suffered from hunger and food shortage. So, eradicating hunger calls for a more comprehensive understanding of the relationship between conflict and hunger. Several studies are carried out to detect the importance of conflict or war on food security. Most of these studies, however, perform only descriptive analysis and largely use food security indicators instead of the global hunger index. Few studies have employed cross-country panel data to explicitly analyze the association between conflict and chronic hunger, including hidden hunger. Herein, this study addresses this issue and the knowledge gap. We combine global datasets to build a new panel dataset including 143 countries from 1989 to 2020. This study examines the effect of conflict on hunger with fixed effect models, and the results show that the increase of conflict frequency deteriorates hunger. Peacebuilding efforts and war prevention initiative are required to eradicate global hunger.Keywords: armed conflict, food scarcity, hidden hunger, hunger, malnutrition
Procedia PDF Downloads 1723304 Geo-Additive Modeling of Family Size in Nigeria
Authors: Oluwayemisi O. Alaba, John O. Olaomi
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The 2013 Nigerian Demographic Health Survey (NDHS) data was used to investigate the determinants of family size in Nigeria using the geo-additive model. The fixed effect of categorical covariates were modelled using the diffuse prior, P-spline with second-order random walk for the nonlinear effect of continuous variable, spatial effects followed Markov random field priors while the exchangeable normal priors were used for the random effects of the community and household. The Negative Binomial distribution was used to handle overdispersion of the dependent variable. Inference was fully Bayesian approach. Results showed a declining effect of secondary and higher education of mother, Yoruba tribe, Christianity, family planning, mother giving birth by caesarean section and having a partner who has secondary education on family size. Big family size is positively associated with age at first birth, number of daughters in a household, being gainfully employed, married and living with partner, community and household effects.Keywords: Bayesian analysis, family size, geo-additive model, negative binomial
Procedia PDF Downloads 5413303 Utilization of Municipal Solid Waste in Thermal Power Production: A Techno-Economic Study of Kasur City, Punjab, Pakistan
Authors: Hafiz Muhammad Umer Aslam, Mohammad Rafiq Khan
Abstract:
This techno-economic study reports the feasibility of generating thermoelectric power from municipal solid waste (MSW) of Kasur City by incineration process. The data was gathered from different establishments of Kasur, through appropriate permission from their heads, and processed to design different alternative projects for installation of a thermal power plant in the city of Kasur. A technique of discounted cash flow was used to evaluate alternative projects so that their Benefit to Cost Ratio, Net Present Value, Internal Rate of Return and Payback Period can be determined. The study revealed that Kasur City currently consumes 18MWh electricity and generates 179 tons/day MSW. The generated waste has the ability to produce 2.1MWh electricity at the cost of USD 0.0581/unit with an expenditure of USD 3,907,692 as initial fixed investment of forming about 1/7th of consumption of Kasur. The cost from this source, when compared to current rate of electricity in Pakistan (USD 0.1346), is roughly half.Keywords: Kasur City, resource recovery, thermoelectric power, waste management
Procedia PDF Downloads 1703302 Study on Robot Trajectory Planning by Robot End-Effector Using Dual Curvature Theory of the Ruled Surface
Authors: Y. S. Oh, P. Abhishesh, B. S. Ryuh
Abstract:
This paper presents the method of trajectory planning by the robot end-effector which accounts for more accurate and smooth differential geometry of the ruled surface generated by tool line fixed with end-effector based on the methods of curvature theory of ruled surface and the dual curvature theory, and focuses on the underlying relation to unite them for enhancing the efficiency for trajectory planning. Robot motion can be represented as motion properties of the ruled surface generated by trajectory of the Tool Center Point (TCP). The linear and angular properties of the six degree-of-freedom motion of end-effector are computed using the explicit formulas and functions from curvature theory and dual curvature theory. This paper explains the complete dualization of ruled surface and shows that the linear and angular motion applied using the method of dual curvature theory is more accurate and less complex.Keywords: dual curvature theory, robot end effector, ruled surface, TCP (Tool Center Point)
Procedia PDF Downloads 3653301 Deep Learning for SAR Images Restoration
Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli
Abstract:
In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network
Procedia PDF Downloads 693300 Investigation of Dynamic Characteristic of Planetary Gear Set Based On Three-Axes Torque Measurement
Authors: Masao Nakagawa, Toshiki Hirogaki, Eiichi Aoyama, Mohamed Ali Ben Abbes
Abstract:
A planetary gear set is widely used in hybrid vehicles as the power distribution system or in electric vehicles as the high reduction system, but due to its complexity with planet gears, its dynamic characteristic is not fully understood. There are many reports on two-axes driving or displacement of the planet gears under these conditions, but only few reports deal with three-axes driving. A three-axes driving condition is tested using three-axes torque measurement and focuses on the dynamic characteristic around the planet gears in this report. From experimental result, it was confirmed that the transition forces around the planet gears were balanced and the torques were also balanced around the instantaneous rotation center. The meshing frequency under these conditions was revealed to be the harmonics of two meshing frequencies; meshing frequency of the ring gear and that of the planet gears. The input power of the ring gear is distributed to the carrier and the sun gear in the dynamic sequential change of three fixed conditions; planet, star and solar modes.Keywords: dynamic characteristic, gear, planetary gear set, torque measuring
Procedia PDF Downloads 3813299 Medium-Scale Multi-Juice Extractor for Food Processing
Authors: Flordeliza L. Mercado, Teresito G. Aguinaldo, Helen F. Gavino, Victorino T. Taylan
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Most fruits and vegetables are available in large quantities during peak season which are oftentimes marketed at low price and left to rot or fed to farm animals. The lack of efficient storage facilities, and the additional cost and unavailability of small machinery for food processing, results to low price and wastage. Incidentally, processed fresh fruits and vegetables are gaining importance nowadays and health conscious people are also into ‘juicing’. One way to reduce wastage and ensure an all-season availability of crop juices at reasonable costs is to develop equipment for effective extraction of juice. The study was conducted to design, fabricate and evaluate a multi-juice extractor using locally available materials, making it relatively cheaper and affordable for medium-scale enterprises. The study was also conducted to formulate juice blends using extracted juices and calamansi juice at different blending percentage, and evaluate its chemical properties and sensory attributes. Furthermore, the chemical properties of extracted meals were evaluated for future applications. The multi-juice extractor has an overall dimension of 963mm x 300mm x 995mm, a gross weight of 82kg and 5 major components namely; feeding hopper, extracting chamber, juice and meal outlet, transmission assembly, and frame. The machine performance was evaluated based on juice recovery, extraction efficiency, extraction rate, extraction recovery, and extraction loss considering type of crop as apple and carrot with three replications each and was analyzed using T-test. The formulated juice blends were subjected to sensory evaluation and data gathered were analyzed using Analysis of Variance appropriate for Complete Randomized Design. Results showed that the machine’s juice recovery (73.39%), extraction rate (16.40li/hr), and extraction efficiency (88.11%) for apple were significantly higher than for carrot while extraction recovery (99.88%) was higher for apple than for carrot. Extraction loss (0.12%) was lower for apple than for carrot, but was not significantly affected by crop. Based on adding percentage mark-up on extraction cost (Php 2.75/kg), the breakeven weight and payback period for a 35% mark-up is 4,710.69kg and 1.22 years, respectively and for a 50% mark-up, the breakeven weight is 3,492.41kg and the payback period is 0.86 year (10.32 months). Results on the sensory evaluation of juice blends showed that the type of juice significantly influenced all the sensory parameters while the blending percentage including their respective interaction, had no significant effect on all sensory parameters, making the apple-calamansi juice blend more preferred than the carrot-calamansi juice blend in terms of all the sensory parameter. The machine’s performance is higher for apple than for carrot and the cost analysis on the use of the machine revealed that it is financially viable with a payback period of 1.22 years (35% mark-up) and 0.86 year (50% mark-up) for machine cost, generating an income of Php 23,961.60 and Php 34,444.80 per year using 35% and 50% mark-up, respectively. The juice blends were of good qualities based on the values obtained in the chemical analysis and the extracted meal could also be used to produce another product based on the values obtained from proximate analysis.Keywords: food processing, fruits and vegetables, juice extraction, multi-juice extractor
Procedia PDF Downloads 3243298 Alphabet Recognition Using Pixel Probability Distribution
Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay
Abstract:
Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix
Procedia PDF Downloads 3893297 MAOD Is Estimated by Sum of Contributions
Authors: David W. Hill, Linda W. Glass, Jakob L. Vingren
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Maximal accumulated oxygen deficit (MAOD), the gold standard measure of anaerobic capacity, is the difference between the oxygen cost of exhaustive severe intensity exercise and the accumulated oxygen consumption (O2; mL·kg–1). In theory, MAOD can be estimated as the sum of independent estimates of the phosphocreatine and glycolysis contributions, which we refer to as PCr+glycolysis. Purpose: The purpose was to test the hypothesis that PCr+glycolysis provides a valid measure of anaerobic capacity in cycling and running. Methods: The participants were 27 women (mean ± SD, age 22 ±1 y, height 165 ± 7 cm, weight 63.4 ± 9.7 kg) and 25 men (age 22 ± 1 y, height 179 ± 6 cm, weight 80.8 ± 14.8 kg). They performed two exhaustive cycling and running tests, at speeds and work rates that were tolerable for ~5 min. The rate of oxygen consumption (VO2; mL·kg–1·min–1) was measured in warmups, in the tests, and during 7 min of recovery. Fingerprick blood samples obtained after exercise were analysed to determine peak blood lactate concentration (PeakLac). The VO2 response in exercise was fitted to a model, with a fast ‘primary’ phase followed by a delayed ‘slow’ component, from which was calculated the accumulated O2 and the excess O2 attributable to the slow component. The VO2 response in recovery was fitted to a model with a fast phase and slow component, sharing a common time delay. Oxygen demand (in mL·kg–1·min–1) was determined by extrapolation from steady-state VO2 in warmups; the total oxygen cost (in mL·kg–1) was determined by multiplying this demand by time to exhaustion and adding the excess O2; then, MAOD was calculated as total oxygen cost minus accumulated O2. The phosphocreatine contribution (area under the fast phase of the post-exercise VO2) and the glycolytic contribution (converted from PeakLac) were summed to give PCr+glycolysis. There was not an interaction effect involving sex, so values for anaerobic capacity were examined using a two-way ANOVA, with repeated measures across method (PCr+glycolysis vs MAOD) and mode (cycling vs running). Results: There was a significant effect only for exercise mode. There was no difference between MAOD and PCr+glycolysis: values were 59 ± 6 mL·kg–1 and 61 ± 8 mL·kg–1 in cycling and 78 ± 7 mL·kg–1 and 75 ± 8 mL·kg–1 in running. Discussion: PCr+glycolysis is a valid measure of anaerobic capacity in cycling and running, and it is as valid for women as for men.Keywords: alactic, anaerobic, cycling, ergometer, glycolysis, lactic, lactate, oxygen deficit, phosphocreatine, running, treadmill
Procedia PDF Downloads 1363296 Anecic and Epigeic Earthworms as Potential Biocontrol Agents of Fusarium graminearum, Causal Agent of Fusarium Head Blight on Wheat
Authors: Gabriella Jorge, Carlos A. Pérez, Hanna Friberg, Sara Söderlund, Jan Lagerlöf
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Fusarium Head Blight (FHB) is one of the most important Fusarium-caused diseases, which affects cereals with serious detrimental effects on yield and grain quality worldwide. Earthworms have been suggested as an alternative to control this disease, which requires a combination of preventive methods to reduce level of damage, although it has been proven that their effect is species dependent. Our objective was to evaluate the effect of the earthworms Aporrectodea longa and Lumbricus rubellus, on the inoculum of Fusarium graminearum on wheat straw. To test this we kept earthworms in vessels with soil, and F. graminearum-inoculated straw covering the surface, under controlled conditions for 6 weeks. Two factors were evaluated with a complete factorial design: earthworms (three levels: without earthworms, A. longa, and L. rubellus), and straw (two levels: inoculated with the pathogen, and sterile). The presence of L. rubellus significantly (P<0.05) reduced the amount of inoculated straw at the soil surface 31% after 6 weeks, while the presence of A. longa, most found in quiescence, did not have any significant effect on the amount of straw when compared to the control. After incubation, F. graminearum was detected by qPCR, only in the surface straw in those treatments inoculated with the pathogen but without earthworms. None of the treatments showed presence of Fusarium in the buried straw, soil or earthworm casts. Both earthworm species decreased in body weight during incubation, most likely due to the decrease in soil water content during the experiment, from 25% to 20%, and/or inadequate food supply, since no other source of food was added. However, this reduction in weight occurred indistinctly of the presence or not of Fusarium (P<0.05). This indicates that both species, of different ecological groups, anecic and epigeic, can reduce F. graminearum inoculum present in wheat straw, while their growth is not negatively affected by this pathogen. These promising results place A. longa, and L. rubellus as potential biocontrol agents of this fungal plant pathogen responsible for Fusarium Head Blight disease in wheat, although further ongoing experiments are needed to confirm the repeatability of these results.Keywords: Aporrectodea longa, biological control, fungal plant pathogen, Lumbricus rubellus, qPCR, wheat straw
Procedia PDF Downloads 2733295 A New Study on Mathematical Modelling of COVID-19 with Caputo Fractional Derivative
Authors: Sadia Arshad
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The new coronavirus disease or COVID-19 still poses an alarming situation around the world. Modeling based on the derivative of fractional order is relatively important to capture real-world problems and to analyze the realistic situation of the proposed model. Weproposed a mathematical model for the investigation of COVID-19 dynamics in a generalized fractional framework. The new model is formulated in the Caputo sense and employs a nonlinear time-varying transmission rate. The existence and uniqueness solutions of the fractional order derivative have been studied using the fixed-point theory. The associated dynamical behaviors are discussed in terms of equilibrium, stability, and basic reproduction number. For the purpose of numerical implementation, an effcient approximation scheme is also employed to solve the fractional COVID-19 model. Numerical simulations are reported for various fractional orders, and simulation results are compared with a real case of COVID-19 pandemic. According to the comparative results with real data, we find the best value of fractional orderand justify the use of the fractional concept in the mathematical modelling, for the new fractional modelsimulates the reality more accurately than the other classical frameworks.Keywords: fractional calculus, modeling, stability, numerical solution
Procedia PDF Downloads 1113294 Robust State feedback Controller for an Active Suspension System
Authors: Hussein Altartouri
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The purpose of this paper is to present a modeling and control of the active suspension system using robust state feedback controller implemented for a half car model. This system represents a mechatronic system which contains all the essential components to be considered a complete mechatronic system. This system must adapt different conditions which are difficult to compromise, such as disturbances, slippage, and motion on rough road (that contains rocks, stones, and other miscellanies). Some current automobile suspension systems use passive components only by utilizing spring and damping coefficient with fixed rates. Vehicle suspensions systems are used to provide good road handling and improve passenger comfort. Passive suspensions only offer compromise between these two conflicting criteria. Active suspension poses the ability to reduce the traditional design as a compromise between handling and comfort by directly controlling the suspensions force actuators. In this study, the robust state feedback controller implemented to the active suspensions system for half car model.Keywords: half-car model, active suspension system, state feedback, road profile
Procedia PDF Downloads 3933293 Optimal Feature Extraction Dimension in Finger Vein Recognition Using Kernel Principal Component Analysis
Authors: Amir Hajian, Sepehr Damavandinejadmonfared
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In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)
Procedia PDF Downloads 3653292 Deep Learning Based Polarimetric SAR Images Restoration
Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli
Abstract:
In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry
Procedia PDF Downloads 903291 Plasma Gasification as a Sustainable Way for Energy Recovery from Scrap Tyre
Authors: Gloria James, S. K. Nema, T. S. Anantha Singh, P. Vadivel Murugan
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The usage of tyre has increased enormously in day to day life. The used tyre and rubber products pose major threat to the environment. Conventional thermal techniques such as low temperature pyrolysis and incineration produce high molecular organic compounds (condensed and collected as aromatic oil) and carbon soot particles. Plasma gasification technique can dispose tyre waste and generate combustible gases and avoid the formation of high molecular aromatic compounds. These gases generated in plasma gasification process can be used to generate electricity or as fuel wherever required. Although many experiments have been done on plasma pyrolysis of tyres, very little work has been done on plasma gasification of tyres. In this work plasma gasification of waste tyres have been conducted in a fixed bed reactor having graphite electrodes and direct current (DC) arc plasma system. The output of this work has been compared with the previous work done on plasma pyrolysis of tyres by different authors. The aim of this work is to compare different process based on gas generation, efficiency of the process and explore the most effective option for energy recovery from waste tyres.Keywords: plasma, gasification, syngas, tyre waste
Procedia PDF Downloads 1823290 Comparison of Meshing Stiffness of Altered Tooth Sum Spur Gear Tooth with Different Pressure Angles
Authors: H. K. Sachidananda, K. Raghunandana, B. Shivamurthy
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The estimation of gear tooth stiffness is important for finding the load distribution between the gear teeth when two consecutive sets of teeth are in contact. Based on dynamic model a C-program has been developed to compute mesh stiffness. By using this program position dependent mesh stiffness of spur gear tooth for various profile shifts have been computed for a fixed center distance and altering tooth-sum gearing (100 by ± 4%). It is found that the C-program using dynamic model is one of the rapid soft computing technique which helps in design of gears. The mesh tooth stiffness along the path of contact is studied for both 20° and 25° pressure angle gears at various profile shifts. Better tooth stiffness is noticed in case of negative alteration tooth-sum gears compared to standard and positive alteration tooth-sum gears. Also, in case of negative alteration tooth-sum gearing better mesh stiffness is noticed in 20° pressure angle when compared to 25°.Keywords: altered tooth-sum gearing, bending fatigue, mesh stiffness, spur gear
Procedia PDF Downloads 3253289 Effects of Dividend Policy on Firm Profitability and Growth in Light of Present Economic Conditions
Authors: Madani Chahinaz
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This study aims to shed light on the impact of dividend policy on corporate profitability and its relationship to growth, considering the economic developments taking place. The study was conducted on a sample of seven companies for the period from 2014 to 2020, based on a set of determinants to select variables affecting dividend distribution, where the descriptive analytical approach relied upon using graphical data models. The study concluded that companies that follow a well-studied dividend distribution policy enjoy higher profitability rates, which contributes to enhancing their growth in light of the economic developments taking place. There is also no statistically significant relationship between the variables of total asset growth and fixed asset growth and profitability. The study also concluded that there is statistical significance for the relationship between the sales volume growth variable, the self-financing ratio variable, and dividend distribution at a significance level of 0.05, as the random effects model was able to explain 68% of the changes in dividend distribution policy.Keywords: dividend distribution policy, profitability, growth, self-financing ratio
Procedia PDF Downloads 93288 Development of Column-Filters of Sulfur Limonene Polysulfide to Mercury Removal from Contaminated Effluents
Authors: Galo D. Soria, Jenny S. Casame, Eddy F. Pazmino
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In Ecuador, mining operations have significantly impacted water sources. Artisanal mining extensively relies in mercury amalgamation. Mercury is a neurotoxic substance even at low concentrations. The objective of this investigation is to exploit Hg-removal capacity of sulfur-limonene polysulfide (SLP), which is a low-cost polymer, in order to prepare granular media (sand) coated with SLP to be used in laboratory scale column-filtration systems. Preliminary results achieved 85% removal of Hg⁺⁺ from synthetic effluents using 20-cm length and 5-cm diameter columns at 119m/day average pore water velocity. During elution of the column, the SLP-coated sand indicated that Hg⁺⁺ is permanently fixed to the collector surface, in contrast, uncoated sand showed reversible retention in Hg⁺⁺ in the solid phase. Injection of 50 pore volumes decreased Hg⁺⁺ removal to 46%. Ongoing work has been focused in optimizing the synthesis of SLP and the polymer content in the porous media coating process to improve Hg⁺⁺ removal and extend the lifetime of the column-filter.Keywords: column-filter, mercury, mining, polysulfide, water treatment
Procedia PDF Downloads 1493287 Corporate Governance and Firms` Performance: Evidence from Quoted Firms on the Nigerian Stock Exchange
Authors: Ogunwole Cecilia Oluwakemi, Wahid Damilola Olanipekun, Omoyele Olufemi Samuel, Timothy Ayomitunde Aderemi
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The issues relating to corporate governance in both locally and internationally managed firms cannot be overemphasized because the lack of efficient corporate governance could orchestrate serious problems in any organization. Against this backdrop, this study examines the nexus between corporate governance and performance of firms from 2012 to 2020, using the case study of the Nigerian stock exchange. Consequently, data was collected from forty (40) listed firms on the Nigerian Stock Exchange. The study employed a fixed effect technique of estimation to address the objective of the study. It was discovered from the study that the influence of corporate governance components such as gender diversity, board independence and managerial ownership led to a significant positive impact on the performance of the firms under the investigation. In view of the above finding, this study makes the following recommendations for the policymakers in Nigeria that anytime the goal of the policymakers is the improvement of performance of the listed firms in the Nigerian stock exchange, board independence and a balance in the inclusion of male and female among the board of directors should be encouraged in these firms.Keywords: corporate, governance, firms, performance, Nigeria, stock, exchange
Procedia PDF Downloads 1763286 Development of Thermo-Regulating Fabric Using Microcapsules of Phase Change Material
Authors: D. Benmoussa, H. Hannache, O. Cherkaoui
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In textiles, the major interest in microencapsulation is currently in the application of durable fragrances, skin softeners, phase-change materials, antimicrobial agents and drug delivery systems onto textile materials. In our research “Polyethylene Glycol” was applied as phase change material and it was encapsulated in polymethacrylic acid (PMA) by radical polymerization in suspension of methacrylic acid in presence of N,N'-methylenebisacrylamide (MBAM) as crosslinking agent. Thereafter the obtained microcapsule was modified by amidation with ethylenediamine as a spacer molecule. At the end of this spacer trichlorotriazine reactive group was fixed. Microcapsules were grafted onto cotton textile substrate. The surface morphologies of the microencapsulated phase change materials (micro PCMs) were studied by scanning electron microscopy (SEM). Thermal properties, thermal reliabilities and thermal stabilities of the as-prepared micro PCMs were investigated by differential scanning calorimetry (DSC) and thermogravmetric analysis (TGA). The results obtained show the obtaining microcapsules with a mean diameter of 10 µm and the resistance of the microcapsules is demonstrated by thermal analysis.Keywords: energy storage, microencapsulation, phase-change materials, thermogravmetric analysis (TGA)
Procedia PDF Downloads 6753285 Flow Visualization around a Rotationally Oscillating Cylinder
Authors: Cemre Polat, Mustafa Soyler, Bulent Yaniktepe, Coskun Ozalp
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In this study, it was aimed to control the flow actively by giving an oscillating rotational motion to a vertically placed cylinder, and flow characteristics were determined. In the study, firstly, the flow structure around the flat cylinder was investigated with dye experiments, and then the cylinders with different oscillation angles (θ = 60°, θ = 120°, and θ = 180°) and different rotation speeds (15 rpm and 30 rpm) the flow structure around it was examined. Thus, the effectiveness of oscillation and rotation speed in flow control has been investigated. In the dye experiments, the dye/water mixture obtained by mixing Rhodamine 6G in powder form with water, which shines under laser light and allows detailed observation of the flow structure, was used. During the experiments, the dye was injected into the flow with the help of a thin needle at a distance that would not affect the flow from the front of the cylinder. In dye experiments, 100 frames per second were taken with a Canon brand EOS M50 (24MP) digital mirrorless camera at a resolution of 1280 * 720 pixels. Then, the images taken were analyzed, and the pictures representing the flow structure for each experiment were obtained. As a result of the study, it was observed that no separation points were formed at 180° swing angle at 15 rpm speed, 120° and 180° swing angle at 30 rpm, and the flow was controlled according to the fixed cylinder.Keywords: active flow control, cylinder, flow visualization rotationally oscillating
Procedia PDF Downloads 1753284 Achievable Average Secrecy Rates over Bank of Parallel Independent Fading Channels with Friendly Jamming
Authors: Munnujahan Ara
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In this paper, we investigate the effect of friendly jamming power allocation strategies on the achievable average secrecy rate over a bank of parallel fading wiretap channels. We investigate the achievable average secrecy rate in parallel fading wiretap channels subject to Rayleigh and Rician fading. The achievable average secrecy rate, due to the presence of a line-of-sight component in the jammer channel is also evaluated. Moreover, we study the detrimental effect of correlation across the parallel sub-channels, and evaluate the corresponding decrease in the achievable average secrecy rate for the various fading configurations. We also investigate the tradeoff between the transmission power and the jamming power for a fixed total power budget. Our results, which are applicable to current orthogonal frequency division multiplexing (OFDM) communications systems, shed further light on the achievable average secrecy rates over a bank of parallel fading channels in the presence of friendly jammers.Keywords: fading parallel channels, wire-tap channel, OFDM, secrecy capacity, power allocation
Procedia PDF Downloads 5123283 Evaluation of Commercial Back-analysis Package in Condition Assessment of Railways
Authors: Shadi Fathi, Moura Mehravar, Mujib Rahman
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Over the years,increased demands on railways, the emergence of high-speed trains and heavy axle loads, ageing, and deterioration of the existing tracks, is imposing costly maintenance actions on the railway sector. The need for developing a fast andcost-efficient non-destructive assessment method for the structural evaluation of railway tracksis therefore critically important. The layer modulus is the main parameter used in the structural design and evaluation of the railway track substructure (foundation). Among many recently developed NDTs, Falling Weight Deflectometer (FWD) test, widely used in pavement evaluation, has shown promising results for railway track substructure monitoring. The surface deflection data collected by FWD are used to estimate the modulus of substructure layers through the back-analysis technique. Although there are different commerciallyavailableback-analysis programs are used for pavement applications, there are onlya limited number of research-based techniques have been so far developed for railway track evaluation. In this paper, the suitability, accuracy, and reliability of the BAKFAAsoftware are investigated. The main rationale for selecting BAKFAA as it has a relatively straightforward user interfacethat is freely available and widely used in highway and airport pavement evaluation. As part of the study, a finite element (FE) model of a railway track section near Leominsterstation, Herefordshire, UK subjected to the FWD test, was developed and validated against available field data. Then, a virtual experimental database (including 218 sets of FWD testing data) was generated using theFE model and employed as the measured database for the BAKFAA software. This database was generated considering various layers’ moduli for each layer of track substructure over a predefined range. The BAKFAA predictions were compared against the cone penetration test (CPT) data (available from literature; conducted near to Leominster station same section as the FWD was performed). The results reveal that BAKFAA overestimatesthe layers’ moduli of each substructure layer. To adjust the BAKFA with the CPT data, this study introduces a correlation model to make the BAKFAA applicable in railway applications.Keywords: back-analysis, bakfaa, railway track substructure, falling weight deflectometer (FWD), cone penetration test (CPT)
Procedia PDF Downloads 1293282 High-Throughput, Purification-Free, Multiplexed Profiling of Circulating miRNA for Discovery, Validation, and Diagnostics
Authors: J. Hidalgo de Quintana, I. Stoner, M. Tackett, G. Doran, C. Rafferty, A. Windemuth, J. Tytell, D. Pregibon
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We have developed the Multiplexed Circulating microRNA assay that allows the detection of up to 68 microRNA targets per sample. The assay combines particlebased multiplexing, using patented Firefly hydrogel particles, with single step RT-PCR signal. Thus, the Circulating microRNA assay leverages PCR sensitivity while eliminating the need for separate reverse transcription reactions and mitigating amplification biases introduced by target-specific qPCR. Furthermore, the ability to multiplex targets in each well eliminates the need to split valuable samples into multiple reactions. Results from the Circulating microRNA assay are interpreted using Firefly Analysis Workbench, which allows visualization, normalization, and export of experimental data. To aid discovery and validation of biomarkers, we have generated fixed panels for Oncology, Cardiology, Neurology, Immunology, and Liver Toxicology. Here we present the data from several studies investigating circulating and tumor microRNA, showcasing the ability of the technology to sensitively and specifically detect microRNA biomarker signatures from fluid specimens.Keywords: biomarkers, biofluids, miRNA, photolithography, flowcytometry
Procedia PDF Downloads 3693281 Comparative Analysis of Effecting Factors on Fertility by Birth Order: A Hierarchical Approach
Authors: Ali Hesari, Arezoo Esmaeeli
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Regarding to dramatic changes of fertility and higher order births during recent decades in Iran, access to knowledge about affecting factors on different birth orders has crucial importance. In this study, According to hierarchical structure of many of social sciences data and the effect of variables of different levels of social phenomena that determine different birth orders in 365 days ending to 1390 census have been explored by multilevel approach. In this paper, 2% individual row data for 1390 census is analyzed by HLM software. Three different hierarchical linear regression models are estimated for data analysis of the first and second, third, fourth and more birth order. Research results displays different outcomes for three models. Individual level variables entered in equation are; region of residence (rural/urban), age, educational level and labor participation status and province level variable is GDP per capita. Results show that individual level variables have different effects in these three models and in second level we have different random and fixed effects in these models.Keywords: fertility, birth order, hierarchical approach, fixe effects, random effects
Procedia PDF Downloads 3393280 Topology Optimisation for Reduction in Material Use for Precast Concrete Elements: A Case Study of a 3D-Printed Staircase
Authors: Dengyu You, Alireza Kashani
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This study explores the potential of 3D concrete printing in manufacturing prefabricated staircases. The applications of 3D concrete printing in large-scale construction could enhance the industry’s implementation of the Industry 4.0 concept. In addition, the current global challenge is to achieve Net Zero Emissions by 2050. Innovation in the construction industry could potentially speed up achieving this target. The 3D printing technology offers a possible solution that reduces cement usage, minimises framework wastes, and is capable of manufacturing complex structures. The performance of the 3D concrete printed lightweight staircase needs to be evaluated. In this study, the staircase is designed using computer-aided technologies, fabricated by 3D concrete printing technologies, and tested with Australian Standard (AS 1657-2018 Fixed platforms, walkways, stairways, and ladders – design, construction, and installation) under a laboratory environment. The experiment results will be further compared with the FEM analysis. The results indicate that 3D concrete printing is capable of fast production, reducing material usage, and is highly automotive, which meets the industry’s future development goal.Keywords: concrete 3D printing, staircase, sustainability, automation
Procedia PDF Downloads 1053279 Evaluation of Genetic Potentials of Onion (Allium Cepa L.) Cultivars of North Western Nigeria
Authors: L. Abubakar, B. M. Sokoto, I. U. Mohammed, M. S. Na’allah, A. Mohammad, A. N. Garba, T. S. Bubuche
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Onion (Allium cepa var. cepa L.) is the most important species of the Allium group belonging to family Alliaceae and genus Allium. It can be regarded as the single important vegetable species in the world after tomatoes. Despite the similarities, which bring the species together, the genus is a strikingly diverse one, with more than five hundred species, which are perennial and mostly bulbous plants. Out of these, only seven species are in cultivation, and five are the most important species of the cultivated Allium. However, Allium cepa (onion) and Allium sativum (Garlic) are the two major cultivated species grown all over the world of which the onion crop is the most important. North Western Nigeria (Sokoto, Kebbi and Zamfara States) constitute the major onion producing zone in Nigeria, which is primarily during the dry season. However, onion production in the zone is seriously affected by two main factors i.e. diseases and storage losses, in addition to other constraints that limits the cultivation of the crop during the rainy season which include lack of prolonged rainy season to allow for proper maturation of the crop. The major onion disease in this zone is purple blotch caused by a fungus Alternaria porri and currently efforts are on to develop onion hybrids resistant to the disease. Genetic diversity plays an important role in plant breeding either to exploit heterosis or to generate productive recombinants. Assessment of a large number of genotypes for a genetic diversity is the first step in this direction. The objective of this research therefore is to evaluate the genetic potentials of the onion cultivars of North Western Nigeria, with a view of developing new cultivars that address the major production challenges to onion cultivation in North Western, Nigeria. Thirteen onion cultivars were collected during an expedition covering North western Nigeria and Southern part of Niger Republic during 2013, which are areas noted for onion production. The cultivars were evaluated at two locations; Sokoto, in Sokoto State and Jega in Kebbi State all in Nigeria during the 2013/14 onion season (dry season) under irrigation. The objective of the research was to determine the genetic potentials of onion cultivars of north western Nigeria as a basis for breeding purposes. Combined analysis of the results revealed highly significant variation between the cultivars across the locations with respect to plant height, number of leaves/plant, bolting %, bulb height, bulb weight, mean bulb yield and cured bulb weight, with significant variation in terms of bulb diameter. Tasa from Warra Local Government Area of Kebbi State (V4) recorded the greatest mean fresh bulb yield with Jar Albasa (V8) from Illela Local Government Area of Sokoto State recording the least. Similarly Marsa (V5) from Silame Local Government Area recorded the greatest mean cured bulb yield (marketable bulb)with Kiba (V11) from Goronyo Local Government of Sokoto State recording the least. Significant variation was recorded between the locations with respect to all characters, with Sokoto being better in terms of plant height, number of leaves/plant, bolting % and bulb diameter. Jega was better in terms of bulb height, bulb yield and cured bulb weight. Significant variation was therefore observed between the cultivars.Keywords: evaluation, genetic, onions, North Western Nigeria
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