Search results for: least square estimation (LSE)
2120 Estimation of Leachate Generation from Municipal Solid Waste Landfills in Selangor
Authors: Tengku Nilam Baizura, Noor Zalina Mahmood
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In Malaysia, landfilling is the most preferred method and most of it does not have the proper leachate treatment system which can cause environmental problems. Leachate is the major factor to river water pollution since most landfills are located near the river which is the main water resource for the country. The study aimed to estimate leachate production from landfills in Selangor. A simple mathematical modelling was used for the calculation of annual leachate volume. The estimate of identified landfill area (A) using Google Earth was multiplied by the annual rainfall (R). The product is expressed as volume (V). The data indicate that the leachate production is high even it is fully closed. It is important to design the efficient landfill and proper leachate treatment processes especially for the old/closed landfill. Extensive monitoring will be required to predict future impact.Keywords: landfill, leachate, municipal solid waste management, waste disposal
Procedia PDF Downloads 3702119 Amplified Ribosomal DNA Restriction Analysis Method to Assess Rumen Microbial Diversity of Ruminant
Authors: A. Natsir, M. Nadir, S. Syahrir, A. Mujnisa, N. Purnomo, A. R. Egan, B. J. Leury
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Rumen degradation characteristic of feedstuff is one of the prominent factors affecting microbial population in rumen of animal. High rumen degradation rate of faba bean protein may lead to inconstant rumen conditions that could have a prominent impact on rumen microbial diversity. Amplified Ribosomal DNA Restriction Analysis (ARDRA) is utilized to monitor diversity of rumen microbes on sheep fed low quality forage supplemented by faba beans. Four mature merino sheep with existing rumen cannula were used in this study according to 4 x 4 Latin square design. The results of study indicated that there were 37 different ARDRA types identified out of 136 clones examined. Among those clones, five main clone types existed across the treatments with different percentages. In conclusion, the ARDRA method is potential to be used as a routine tool to assess the temporary changes in the rumen community as a result of different feeding strategies.Keywords: ARDRA method, cattle, genomic diversity, rumen microbes
Procedia PDF Downloads 3612118 Longitudinal Static and Dynamic Stability of a Typical Reentry Body in Subsonic Conditions Using Computational Fluid Dynamics
Authors: M. Jathaveda, Joben Leons, G. Vidya
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Reentry from orbit is a critical phase in the entry trajectory. For a non-propulsive ballistic entry, static and dynamic stability play an important role in the trajectory, especially for the safe deployment of parachutes, typically at subsonic Mach numbers. Static stability of flight vehicles are being estimated through CFD techniques routinely. Advances in CFD software as well as computational facilities have enabled the estimation of the dynamic stability derivatives also through CFD techniques. Longitudinal static and dynamic stability of a typical reentry body for subsonic Mach number of 0.6 is predicted using commercial software CFD++ and presented here. Steady state simulations are carried out for α = 2° on an unstructured grid using SST k-ω model. Transient simulation using forced oscillation method is used to compute pitch damping derivatives.Keywords: stability, typical reentry body, subsonic, static and dynamic
Procedia PDF Downloads 1162117 Mechanical Behavior of CFTR Column Joint under Pull out Testing
Authors: Nasruddin Junus
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CFTR column is one of the improvements CFT columns by inserting reinforcing steel bars into infill concrete. The presence of inserting reinforcing steel bars is increasing the excellent structural performance of the CFT column, especially on the fire-resisting performance. Investigation on the mechanical behavior of CFTR column connection is summarized in the three parts; column to column joint, column to beam connection, and column base. Experiment that reported in this paper is concerned on the mechanical behavior of CFTR column joint under pull out testing, especially on its stress transfer mechanism. A number series of the pull out test on the CFT with inserting reinforcing steel bar are conducted. Ten test specimens are designed, constructed, and tested to examine experimentally the effect of the size of square steel tube, size of the bearing plate, length of embedment steel bars, kind of steel bars, and the numbers of rib plate.Keywords: CFTR column, pull out, stress, transfer mechanism
Procedia PDF Downloads 2902116 Monitoring of Belt-Drive Defects Using the Vibration Signals and Simulation Models
Authors: A. Nabhan, Mohamed R. El-Sharkawy, A. Rashed
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The main aim of this paper is to dedicate the belt drive system faults like cogs missing, misalignment and belt worm using vibration analysis technique. Experimentally, the belt drive test-rig is equipped to measure vibrations signals under different operating conditions. Finite element 3D model of belt drive system is created and vibration response analyzed using commercial finite element software ABAQUS/CAE. Root mean square (RMS) and Crest Factor will serve as indicators of average amplitude of envelope analysis signals. The vibration signals pattern obtained from the simulation model and experimental data have the same characteristics. It can be concluded that each case of the RMS is more effective in detecting the defect for acceleration response. While Crest Factor parameter has a response with the displacement and velocity of vibration signals. Also it can be noticed that the model has difficulty in completing the solution when the misalignment angle is higher than 1 degree.Keywords: simulation model, misalignment, cogs missing, vibration analysis
Procedia PDF Downloads 2842115 Prediction of the Transmittance of Various Bended Angles Lightpipe by Using Neural Network under Different Sky Clearness Condition
Authors: Li Zhang, Yuehong Su
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Lightpipe as a mature solar light tube technique has been employed worldwide. Accurately assessing the performance of lightpipe and evaluate daylighting available has been a challenging topic. Previous research had used regression model and computational simulation methods to estimate the performance of lightpipe. However, due to the nonlinear nature of solar light transferring in lightpipe, the methods mentioned above express inaccurate and time-costing issues. In the present study, a neural network model as an alternative method is investigated to predict the transmittance of lightpipe. Four types of commercial lightpipe with bended angle 0°, 30°, 45° and 60° are discussed under clear, intermediate and overcast sky conditions respectively. The neural network is generated in MATLAB by using the outcomes of an optical software Photopia simulations as targets for networks training and testing. The coefficient of determination (R²) for each model is higher than 0.98, and the mean square error (MSE) is less than 0.0019, which indicate the neural network strong predictive ability and the use of the neural network method could be an efficient technique for determining the performance of lightpipe.Keywords: neural network, bended lightpipe, transmittance, Photopia
Procedia PDF Downloads 1522114 Rheological Model for Describing Spunlace Nonwoven Behavior
Authors: Sana Ridene, Soumaya Sayeb, Houda Helali, Mohammed Ben Hassen
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Nonwoven structures have a range of applications which include Medical, filtration, geotextile and recently this unconventional fabric is finding a niche in fashion apparel. In this paper, a modified form of Vangheluwe rheological model is used to describe the mechanical behavior of nonwovens fabrics in uniaxial tension. This model is an association in parallel of three Maxwell elements characterized by damping coefficients η1, η2 and η3 and E1, E2, E3 elastic modulus and a nonlinear spring C. The model is verified experimentally with two types of nonwovens (50% viscose /50% Polyester) and (40% viscose/60% Polyester) and a range of three square weights values. Comparative analysis of the theoretical model and the experimental results of tensile test proofs a high correlation between them. The proposed model can fairly well replicate the behavior of nonwoven fabrics during relaxation and sample traction. This allowed us to predict the mechanical behavior in tension and relaxation of fabrics starting only from their technical parameters (composition and weight).Keywords: mechanical behavior, tensile strength, relaxation, rheological model
Procedia PDF Downloads 4092113 A Convolution Neural Network PM-10 Prediction System Based on a Dense Measurement Sensor Network in Poland
Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski
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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks
Procedia PDF Downloads 1492112 Optimization of the Transfer Molding Process by Implementation of Online Monitoring Techniques for Electronic Packages
Authors: Burcu Kaya, Jan-Martin Kaiser, Karl-Friedrich Becker, Tanja Braun, Klaus-Dieter Lang
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Quality of the molded packages is strongly influenced by the process parameters of the transfer molding. To achieve a better package quality and a stable transfer molding process, it is necessary to understand the influence of the process parameters on the package quality. This work aims to comprehend the relationship between the process parameters, and to identify the optimum process parameters for the transfer molding process in order to achieve less voids and wire sweep. To achieve this, a DoE is executed for process optimization and a regression analysis is carried out. A systematic approach is represented to generate models which enable an estimation of the number of voids and wire sweep. Validation experiments are conducted to verify the model and the results are presented.Keywords: dielectric analysis, electronic packages, epoxy molding compounds, transfer molding process
Procedia PDF Downloads 3822111 Application of Smplify-X Algorithm with Enhanced Gender Classifier in 3D Human Pose Estimation
Authors: Jiahe Liu, Hongyang Yu, Miao Luo, Feng Qian
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The widespread application of 3D human body reconstruction spans various fields. Smplify-X, an algorithm reliant on single-image input, employs three distinct body parameter templates, necessitating gender classification of individuals within the input image. Researchers employed a ResNet18 network to train a gender classifier within the Smplify-X framework, setting the threshold at 0.9, designating images falling below this threshold as having neutral gender. This model achieved 62.38% accurate predictions and 7.54% incorrect predictions. Our improvement involved refining the MobileNet network, resulting in a raised threshold of 0.97. Consequently, we attained 78.89% accurate predictions and a mere 0.2% incorrect predictions, markedly enhancing prediction precision and enabling more precise 3D human body reconstruction.Keywords: SMPLX, mobileNet, gender classification, 3D human reconstruction
Procedia PDF Downloads 1002110 A Survey on Frequency of Cryptosporidiosis and Giardiasis in Horses in Ahvaz South-West of Iran
Authors: Ali R. Ghadrdan-Mashhadi, Hosein Hamidi-Nejat, Parisa Alizadehnia
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Cryptosporidia and Giardia are protozoan parasites that have worldwide distribution and infect a variety of animals. Although, the infection to these parasites rarely caused to illness in horses, but some veterinarian recorded the clinical signs (such as diarrhea and malabsorbtion) especially in foals. In present study, the frequency of Cryptosporidiosis and Giardiasis in horses in Ahvaz investigated. The feces samples were taken from 100 horses that keep in seven horse breeding clubs, during spring and summer. The ages of horses were from 1 month to 27 years old. Fecal samples were stained by modified Ziehl-Neelsen and Tri-chrome methods. Results were analyzed with Chi-square Test and Fisher’s exact test. The results showed that the rate of infection to Cryptosporidium and Giardia were 18% and 40%, respectively. There weren't significant differences between infection to Cryptosporidium and Giardia with sex, age and fecal constancy. Although, the rate of infection to Cryptosporidium in studied horses is very similar to other studies but it seems, the rate of infection to Giardia is high in compare to other studies were done in the other countries.Keywords: Ahvaz, cryptosporidium, giardia, horse
Procedia PDF Downloads 3632109 Groundwater Seepage Estimation into Amirkabir Tunnel Using Analytical Methods and DEM and SGR Method
Authors: Hadi Farhadian, Homayoon Katibeh
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In this paper, groundwater seepage into Amirkabir tunnel has been estimated using analytical and numerical methods for 14 different sections of the tunnel. Site Groundwater Rating (SGR) method also has been performed for qualitative and quantitative classification of the tunnel sections. The obtained results of above-mentioned methods were compared together. The study shows reasonable accordance with results of the all methods unless for two sections of tunnel. In these two sections there are some significant discrepancies between numerical and analytical results mainly originated from model geometry and high overburden. SGR and the analytical and numerical calculations, confirm the high concentration of seepage inflow in fault zones. Maximum seepage flow into tunnel has been estimated 0.425 lit/sec/m using analytical method and 0.628 lit/sec/m using numerical method occurred in crashed zone. Based on SGR method, six sections of 14 sections in Amirkabir tunnel axis are found to be in "No Risk" class that is supported by the analytical and numerical seepage value of less than 0.04 lit/sec/m.Keywords: water Seepage, Amirkabir Tunnel, analytical method, DEM, SGR
Procedia PDF Downloads 4762108 A New Sign Subband Adaptive Filter Based on Dynamic Selection of Subbands
Authors: Mohammad Shams Esfand Abadi, Mehrdad Zalaghi, Reza ebrahimpour
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In this paper, we propose a sign adaptive filter algorithm with the ability of dynamic selection of subband filters which leads to low computational complexity compared with conventional sign subband adaptive filter (SSAF) algorithm. Dynamic selection criterion is based on largest reduction of the mean square deviation at each adaption. We demonstrate that this simple proposed algorithm has the same performance of the conventional SSAF and somewhat faster than it. In the presence of impulsive interferences robustness of the simple proposed algorithm as well as the conventional SSAF and outperform the conventional normalized subband adaptive filter (NSAF) algorithm. Therefore, it is preferred for environments under impulsive interferences. Simulation results are presented to verify these above considerations very well have been achieved.Keywords: acoustic echo cancellation (AEC), normalized subband adaptive filter (NSAF), dynamic selection subband adaptive filter (DS-NSAF), sign subband adaptive filter (SSAF), impulsive noise, robust filtering
Procedia PDF Downloads 5992107 Calculation of A Sustainable Quota Harvesting of Long-tailed Macaque (Macaca fascicularis Raffles) in Their Natural Habitats
Authors: Yanto Santosa, Dede Aulia Rahman, Cory Wulan, Abdul Haris Mustari
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The global demand for long-tailed macaques for medical experimentation has continued to increase. Fulfillment of Indonesian export demands has been mostly from natural habitats, based on a harvesting quota. This quota has been determined according to the total catch for a given year, and not based on consideration of any demographic parameters or physical environmental factors with regard to the animal; hence threatening the sustainability of the various populations. It is therefore necessary to formulate a method for calculating a sustainable harvesting quota, based on population parameters in natural habitats. Considering the possibility of variations in habitat characteristics and population parameters, a time series observation of demographic and physical/biotic parameters, in various habitats, was performed on 13 groups of long-tailed macaques, distributed throughout the West Java, Lampung and Yogyakarta areas of Indonesia. These provinces were selected for comparison of the influence of human/tourism activities. Data on population parameters that was collected included data on life expectancy according to age class, numbers of individuals by sex and age class, and ‘ratio of infants to reproductive females’. The estimation of population growth was based on a population dynamic growth model: the Leslie matrix. The harvesting quota was calculated as being the difference between the actual population size and the MVP (minimum viable population) for each sex and age class. Observation indicated that there were variations within group size (24 – 106 individuals), gender (sex) ratio (1:1 to 1:1.3), life expectancy value (0.30 to 0.93), and ‘ratio of infants to reproductive females’ (0.23 to 1.56). Results of subsequent calculations showed that sustainable harvesting quotas for each studied group of long-tailed macaques, ranged from 29 to 110 individuals. An estimation model of the MVP for each age class was formulated as Log Y = 0.315 + 0.884 Log Ni (number of individual on ith age class). This study also found that life expectancy for the juvenile age class was affected by the humidity under tree stands, and dietary plants’ density at sapling, pole and tree stages (equation: Y= 2.296 – 1.535 RH + 0.002 Kpcg – 0.002 Ktg – 0.001 Kphn, R2 = 89.6% with a significance value of 0.001). By contrast, for the sub-adult-adult age class, life expectancy was significantly affected by slope (equation: Y=0.377 = 0.012 Kml, R2 = 50.4%, with significance level of 0.007). The infant to reproductive female ratio was affected by humidity under tree stands, and dietary plant density at sapling and pole stages (equation: Y = -1.432 + 2.172 RH – 0.004 Kpcg + 0.003 Ktg, R2 = 82.0% with significance level of 0.001). This research confirmed the importance of population parameters in determining the minimum viable population, and that MVP varied according to habitat characteristics (especially food availability). It would be difficult therefore, to formulate a general mathematical equation model for determining a harvesting quota for the species as a whole.Keywords: harvesting, long-tailed macaque, population, quota
Procedia PDF Downloads 4242106 Water Leakage Detection System of Pipe Line using Radial Basis Function Neural Network
Authors: A. Ejah Umraeni Salam, M. Tola, M. Selintung, F. Maricar
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Clean water is an essential and fundamental human need. Therefore, its supply must be assured by maintaining the quality, quantity and water pressure. However the fact is, on its distribution system, leakage happens and becomes a common world issue. One of the technical causes of the leakage is a leaking pipe. The purpose of the research is how to use the Radial Basis Function Neural (RBFNN) model to detect the location and the magnitude of the pipeline leakage rapidly and efficiently. In this study the RBFNN are trained and tested on data from EPANET hydraulic modeling system. Method of Radial Basis Function Neural Network is proved capable to detect location and magnitude of pipeline leakage with of the accuracy of the prediction results based on the value of RMSE (Root Meant Square Error), comparison prediction and actual measurement approaches 0.000049 for the whole pipeline system.Keywords: radial basis function neural network, leakage pipeline, EPANET, RMSE
Procedia PDF Downloads 3582105 Optimism and Entrepreneurial Intentions: The Mediating Role of Emotional Intelligence
Authors: Neta Kela Madar, Tali Teeni-Harari, Tamar Icekson, Yaron Sela
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This paper proposes and empirically tests a theoretical model positing relationships between dispositional optimism, emotional intelligence, and entrepreneurial intention. To author's best knowledge, this study examined for the first time the role of dispositional optimism together with emotional intelligence as predictors of entrepreneurial intentions. The study findings suggest that optimism may increase entrepreneurial intentions indirectly by enhancing emotional intelligence/ model formulation is based on a random survey of students (N= 227). Model parameter estimation was supported by Structural Equation Modeling (SEM). Results indicate that students’ optimism and emotional intelligence are associated with increased levels of entrepreneurial intention. Additionally, the present study argues that emotional intelligence mediates the positive relationship between optimism and entrepreneurial intention. Theoretical and practical implications of this model are discussed.Keywords: entrepreneurial intentions, emotional intelligence, optimism, dispositional optimism
Procedia PDF Downloads 2272104 Wh-Movement in Second Language Acquisition: Evidence from Magnitude Estimation
Authors: Dong-Bo Hsu
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Universal Grammar (UG) claims that the constraints that are derived from this should operate in language users’ L2 grammars. This study investigated this hypothesis on knowledge of Subjacency and resumptive pronoun usage among Chinese learners of English. Chinese fulfills two requirements to examine the existence of UG, i.e., Subjacency does not operate in Chinese and resumptive pronouns in English are very different from those in Chinese and second L2 input undermines the knowledge of Subjacency. The results indicated that Chinese learners of English demonstrated a nearly identical pattern as English native speakers do but the resumptive pronoun in the embedding clauses. This may be explained in terms of the case that Chinese speakers’ usage of pronouns is not influenced by the number of embedding clauses. Chinese learners of English have full access to knowledge endowed by UG but their processing of English sentences may be different from native speakers as a general slow rate for processing in their L2 English.Keywords: universal grammar, Chinese, English, wh-questions, resumption
Procedia PDF Downloads 4692103 Batman Forever: The Economics of Overlapping Rights
Authors: Franziska Kaiser, Alexander Cuntz
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When copyrighted comic characters are also protected under trademark laws, intellectual property (IP) rights can overlap. Arguably, registering a trademark can increase transaction costs for cross-media uses of characters, or it can favor advertise across a number of sales channels. In an application to book, movie, and video game publishing industries, we thus ask how creative reuse is affected in situations of overlapping rights and whether ‘fuzzy boundaries’ of right frameworks are, in fact, enhancing or decreasing content sales. We use a major U.S. Supreme Court decision as a quasi-natural experiment to apply an IV estimation in our analysis. We find that overlapping rights frameworks negatively affect creative reuses. At large, when copyright-protected comic characters are additionally registered as U.S. trademarks, they are less often reprinted and enter fewer video game productions while generating less revenue from game sales.Keywords: copyright, fictional characters, trademark, reuse
Procedia PDF Downloads 2092102 Electrochemical Biosensor for Rutin Detection with Multiwall Carbon Nanotubes and Cerium Dioxide Nanoparticles
Authors: Stephen Rathinaraj Benjamin, Flavio Colmati Junior, Maria Izabel Florindo Guedes, Rosa Amalia Fireman Dutra
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A new enzymatic electrochemical biosensor based on multiwall carbon nanotubes and cerium oxide nanoparticles for the detection of rutin has been developed. The cerium oxide nanoparticles /HRP/ multiwall carbon nanotubes/ carbon paste electrode (HRP/ CeO2/MWCNTs/CPE) was prepared by ensuing addition of MWCNTs and HRP on the CPE, followed by the mixing with cerium oxide nanoparticles. Surface physical characteristics of the modified electrode and the electrochemical properties of the composite were investigated by scanning electron microscopy (SEM), transmission electron microscopy (TEM), cylic voltammetry (CV), differential pulse voltammetry (DPV) and square wave voltammetry (SWV). The HRP/ CeO2/MWCNTs/CPE showed good selectivity, stability and reproducibility, which was further applied to detect rutin tablet and capsule samples with satisfactory results.Keywords: cerium dioxide nanoparticles, horseradish peroxidase, multiwall carbon nanotubes, rutin
Procedia PDF Downloads 3932101 Numerical Simulation of Wishart Diffusion Processes
Authors: Raphael Naryongo, Philip Ngare, Anthony Waititu
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This paper deals with numerical simulation of Wishart processes for a single asset risky pricing model whose volatility is described by Wishart affine diffusion processes. The multi-factor specification of volatility will make the model more flexible enough to fit the stock market data for short or long maturities for better returns. The Wishart process is a stochastic process which is a positive semi-definite matrix-valued generalization of the square root process. The aim of the study is to model the log asset stock returns under the double Wishart stochastic volatility model. The solution of the log-asset return dynamics for Bi-Wishart processes will be obtained through Euler-Maruyama discretization schemes. The numerical results on the asset returns are compared to the existing models returns such as Heston stochastic volatility model and double Heston stochastic volatility modelKeywords: euler schemes, log-asset return, infinitesimal generator, wishart diffusion affine processes
Procedia PDF Downloads 3782100 Higher Education and Empowerment of Women: A Case Study
Authors: Anupam Deka
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Gender discrimination has been considered as a major obstacle in granting equal opportunity for woman in Higher education as education plays a pivotal role in a country’s socio-economic development. To examine the empowerment of women in the higher education field of Assam, a case study has been carried out. In the first stage, an overview of enrolment of students in different courses has been made by considering the whole state. In the second stage a study has been conducted regarding the enrolment of students in various degree and P-G courses for the period 2000-2007 under Gauhati University (which is one of the four universities of Assam) and the relevant data has been collected. It has been found that though the enrolment of students in the degree levels has been constantly increasing, but the enrolment of girls are not proportionately increasing, specially in commerce and law. On the other hand, in the post-graduate level, these proportions are higher in almost all the subjects (except some subjects like M. COM., L.L.M, M. C. A., Mathematics, etc.), indicating that more number of girls than boys are taking admission in the P-G courses.Keywords: field study, enrolment of girls in degree and P G levels, regression lines, Chi Square test, diagrams and statistical tables
Procedia PDF Downloads 2632099 Seawater Changes' Estimation at Tidal Flat in Korean Peninsula Using Drone Stereo Images
Authors: Hyoseong Lee, Duk-jin Kim, Jaehong Oh, Jungil Shin
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Tidal flat in Korean peninsula is one of the largest biodiversity tidal flats in the world. Therefore, digital elevation models (DEM) is continuously demanded to monitor of the tidal flat. In this study, DEM of tidal flat, according to different times, was produced by means of the Drone and commercial software in order to measure seawater change during high tide at water-channel in tidal flat. To correct the produced DEMs of the tidal flat where is inaccessible to collect control points, the DEM matching method was applied by using the reference DEM instead of the survey. After the ortho-image was made from the corrected DEM, the land cover classified image was produced. The changes of seawater amount according to the times were analyzed by using the classified images and DEMs. As a result, it was confirmed that the amount of water rapidly increased as the time passed during high tide.Keywords: tidal flat, drone, DEM, seawater change
Procedia PDF Downloads 2042098 Modelling the Indonesian Goverment Securities Yield Curve Using Nelson-Siegel-Svensson and Support Vector Regression
Authors: Jamilatuzzahro, Rezzy Eko Caraka
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The yield curve is the plot of the yield to maturity of zero-coupon bonds against maturity. In practice, the yield curve is not observed but must be extracted from observed bond prices for a set of (usually) incomplete maturities. There exist many methodologies and theory to analyze of yield curve. We use two methods (the Nelson-Siegel Method, the Svensson Method, and the SVR method) in order to construct and compare our zero-coupon yield curves. The objectives of this research were: (i) to study the adequacy of NSS model and SVR to Indonesian government bonds data, (ii) to choose the best optimization or estimation method for NSS model and SVR. To obtain that objective, this research was done by the following steps: data preparation, cleaning or filtering data, modeling, and model evaluation.Keywords: support vector regression, Nelson-Siegel-Svensson, yield curve, Indonesian government
Procedia PDF Downloads 2452097 The Brain’s Attenuation Coefficient as a Potential Estimator of Temperature Elevation during Intracranial High Intensity Focused Ultrasound Procedures
Authors: Daniel Dahis, Haim Azhari
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Noninvasive image-guided intracranial treatments using high intensity focused ultrasound (HIFU) are on the course of translation into clinical applications. They include, among others, tumor ablation, hyperthermia, and blood-brain-barrier (BBB) penetration. Since many of these procedures are associated with local temperature elevation, thermal monitoring is essential. MRI constitutes an imaging method with high spatial resolution and thermal mapping capacity. It is the currently leading modality for temperature guidance, commonly under the name MRgHIFU (magnetic-resonance guided HIFU). Nevertheless, MRI is a very expensive non-portable modality which jeopardizes its accessibility. Ultrasonic thermal monitoring, on the other hand, could provide a modular, cost-effective alternative with higher temporal resolution and accessibility. In order to assess the feasibility of ultrasonic brain thermal monitoring, this study investigated the usage of brain tissue attenuation coefficient (AC) temporal changes as potential estimators of thermal changes. Newton's law of cooling describes a temporal exponential decay behavior for the temperature of a heated object immersed in a relatively cold surrounding. Similarly, in the case of cerebral HIFU treatments, the temperature in the region of interest, i.e., focal zone, is suggested to follow the same law. Thus, it was hypothesized that the AC of the irradiated tissue may follow a temporal exponential behavior during cool down regime. Three ex-vivo bovine brain tissue specimens were inserted into plastic containers along with four thermocouple probes in each sample. The containers were placed inside a specially built ultrasonic tomograph and scanned at room temperature. The corresponding pixel-averaged AC was acquired for each specimen and used as a reference. Subsequently, the containers were placed in a beaker containing hot water and gradually heated to about 45ᵒC. They were then repeatedly rescanned during cool down using ultrasonic through-transmission raster trajectory until reaching about 30ᵒC. From the obtained images, the normalized AC and its temporal derivative as a function of temperature and time were registered. The results have demonstrated high correlation (R² > 0.92) between both the brain AC and its temporal derivative to temperature. This indicates the validity of the hypothesis and the possibility of obtaining brain tissue temperature estimation from the temporal AC thermal changes. It is important to note that each brain yielded different AC values and slopes. This implies that a calibration step is required for each specimen. Thus, for a practical acoustic monitoring of the brain, two steps are suggested. The first step consists of simply measuring the AC at normal body temperature. The second step entails measuring the AC after small temperature elevation. In face of the urging need for a more accessible thermal monitoring technique for brain treatments, the proposed methodology enables a cost-effective high temporal resolution acoustical temperature estimation during HIFU treatments.Keywords: attenuation coefficient, brain, HIFU, image-guidance, temperature
Procedia PDF Downloads 1612096 A Case Study of Assessing the Impact of Electronic Payment System on the Service Delivery of Banks in Nigeria
Authors: Idris Lawal
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Electronic payment system is simply a payment or monetary transaction made over the internet or a network of computers. This study was carried out in order to assess how electronic payment system has impacted on banks service delivery, to examine the efficiency of electronic payment system in Nigeria and to determine the level of customer's satisfaction as a direct result of the deployment of electronic payment systems. It is an empirical study conducted using structured questionnaire distributed to officials and customers of Access Bank plc. Chi-square(x2) was adopted for the purpose of data analysis. The result of the study showed that the development of electronic payment system offer great benefit to bank customers including improved services, reduced turn-around time, ease of banking transaction, significant cost saving etc. The study recommends that customer protection laws should be properly put in place to safeguard the interest of end users of e-payment instruments.Keywords: bank, electronic payment systems, service delivery, customer's satisfaction
Procedia PDF Downloads 3992095 Kinetic Modeling of Transesterification of Triacetin Using Synthesized Ion Exchange Resin (SIERs)
Authors: Hafizuddin W. Yussof, Syamsutajri S. Bahri, Adam P. Harvey
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Strong anion exchange resins with QN+OH-, have the potential to be developed and employed as heterogeneous catalyst for transesterification, as they are chemically stable to leaching of the functional group. Nine different SIERs (SIER1-9) with QN+OH- were prepared by suspension polymerization of vinylbenzyl chloride-divinylbenzene (VBC-DVB) copolymers in the presence of n-heptane (pore-forming agent). The amine group was successfully grafted into the polymeric resin beads through functionalization with trimethylamine. These SIERs are then used as a catalyst for the transesterification of triacetin with methanol. A set of differential equations that represents the Langmuir-Hinshelwood-Hougen-Watson (LHHW) and Eley-Rideal (ER) models for the transesterification reaction were developed. These kinetic models of LHHW and ER were fitted to the experimental data. Overall, the synthesized ion exchange resin-catalyzed reaction were well-described by the Eley-Rideal model compared to LHHW models, with sum of square error (SSE) of 0.742 and 0.996, respectively.Keywords: anion exchange resin, Eley-Rideal, Langmuir-Hinshelwood-Hougen-Watson, transesterification
Procedia PDF Downloads 3622094 Estimation of Soil Erosion and Sediment Yield for ONG River Using GIS
Authors: Sanjay Kumar Behera, Kanhu Charan Patra
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A GIS-based method has been applied for the determination of soil erosion and sediment yield in a small watershed in Ong River basin, Odisha, India. The method involves spatial disintegration of the catchment into homogenous grid cells to capture the catchment heterogeneity. The gross soil erosion in each cell was calculated using Universal Soil Loss Equation (USLE) by carefully determining its various parameters. The concept of sediment delivery ratio is used to route surface erosion from each of the discretized cells to the catchment outlet. The process of sediment delivery from grid cells to the catchment outlet is represented by the topographical characteristics of the cells. The effect of DEM resolution on sediment yield is analyzed using two different resolutions of DEM. The spatial discretization of the catchment and derivation of the physical parameters related to erosion in the cell are performed through GIS techniques.Keywords: DEM, GIS, sediment delivery ratio, sediment yield, soil erosion
Procedia PDF Downloads 4492093 Accounting and Auditing Standards Influence on Income Smoothing Perspective in Islamic Financial Institutions
Authors: Fatma Ezzahra Kateb, Neila Boulila Taktak, Mohamed Kabir Hassan
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We examine the impact of Islamic accounting and auditing standards issued by the Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) on the income smoothing perspective of Islamic financial institutions located in the Middle East and North Africa region between 2013 and 2018. Based on General Least square regression for panel data, we find a significant and positive relationship between intentional income smoothing and earning persistence and cash flow predictability in all models. However, we discovered that AAOIFI accounting standards (FAS) had a negative and significant effect on intentional income smoothing and earning persistence. As a result, the income smoothing efficiency is lower for IFIs that use FASs than IFIs that use IFRSs. Our findings emphasize the need for specific standards to enhance the relevance of financial reports disclosed by Islamic financial institutions.Keywords: AAOIFI, financial reporting quality, income smoothing perspective, MENA countries
Procedia PDF Downloads 942092 Application of Artificial Neural Network for Prediction of High Tensile Steel Strands in Post-Tensioned Slabs
Authors: Gaurav Sancheti
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This study presents an impacting approach of Artificial Neural Networks (ANNs) in determining the quantity of High Tensile Steel (HTS) strands required in post-tensioned (PT) slabs. Various PT slab configurations were generated by varying the span and depth of the slab. For each of these slab configurations, quantity of required HTS strands were recorded. ANNs with backpropagation algorithm and varying architectures were developed and their performance was evaluated in terms of Mean Square Error (MSE). The recorded data for the quantity of HTS strands was used as a feeder database for training the developed ANNs. The networks were validated using various validation techniques. The results show that the proposed ANNs have a great potential with good prediction and generalization capability.Keywords: artificial neural networks, back propagation, conceptual design, high tensile steel strands, post tensioned slabs, validation techniques
Procedia PDF Downloads 2212091 Speech Enhancement Using Kalman Filter in Communication
Authors: Eng. Alaa K. Satti Salih
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Revolutions Applications such as telecommunications, hands-free communications, recording, etc. which need at least one microphone, the signal is usually infected by noise and echo. The important application is the speech enhancement, which is done to remove suppressed noises and echoes taken by a microphone, beside preferred speech. Accordingly, the microphone signal has to be cleaned using digital signal processing DSP tools before it is played out, transmitted, or stored. Engineers have so far tried different approaches to improving the speech by get back the desired speech signal from the noisy observations. Especially Mobile communication, so in this paper will do reconstruction of the speech signal, observed in additive background noise, using the Kalman filter technique to estimate the parameters of the Autoregressive Process (AR) in the state space model and the output speech signal obtained by the MATLAB. The accurate estimation by Kalman filter on speech would enhance and reduce the noise then compare and discuss the results between actual values and estimated values which produce the reconstructed signals.Keywords: autoregressive process, Kalman filter, Matlab, noise speech
Procedia PDF Downloads 344