Search results for: tomato yield prediction

Authors: Jayanta Pokharel, Gokarna Aryal, Netra Kanaal, Chris Tsokos

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Investment in stocks and shares aims to seek potential gains while weighing the risk of future needs, such as retirement, children's education etc. Analysis of the behavior of the stock market returns and making prediction is important for investors to mitigate risk on investment. Historically, the normal variance models have been used to describe the behavior of stock market returns. However, the returns of the financial assets are actually skewed with higher kurtosis, heavier tails, and a higher center than the normal distribution. The Laplace distribution and its family are natural candidates for modeling stock returns. The Variance-Gamma (VG) distribution is the most sought-after distributions for modeling asset returns and has been extensively discussed in financial literatures. In this paper, it explore the other Laplace family, such as Asymmetric Laplace, Skewed Laplace, Kumaraswamy Laplace (KS) together with Variance-Gamma to model the weekly returns of the S&P 500 Index and it's eleven business sector indices. The method of maximum likelihood is employed to estimate the parameters of the distributions and our empirical inquiry shows that the Kumaraswamy Laplace distribution performs much better for stock returns modeling among the choice of distributions used in this study and in practice, KS can be used as a strong alternative to VG distribution.

Keywords: stock returns, variance-gamma, kumaraswamy laplace, maximum likelihood

Procedia PDF Downloads 70

Authors: Amit Kumar, Amanpreet Chander, Ashish Sahani

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This paper presents our recent work on real-time human activity detection based on the media pipe pipeline and machine learning algorithms. The proposed system can detect human activities, including running, jumping, squatting, bending to the left or right, and standing still. This is a robust solution for developing a yoga, dance, metaverse, and fitness application that checks for the correction of the pose without having any additional monitor like a personal trainer. MediaPipe solution offers an open-source cross-platform which utilizes a two-step detector-tracker ML pipeline for live detection of key landmarks on our body which can be used for motion data collection. The prediction of real-time poses uses a variety of machine learning techniques and different types of analysis. Without primarily relying on powerful desktop environments for inference, our method achieves real-time performance on the majority of contemporary mobile phones, desktops/laptops, Python, or even the web. Experimental results show that our method outperforms the existing method in terms of accuracy and real-time capability, achieving an accuracy of 99.92% on testing datasets.

Keywords: human activity detection, media pipe, machine learning, metaverse applications

Procedia PDF Downloads 179

Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

Procedia PDF Downloads 175

Authors: Novutry Siregar, Afdal, Emilzon Taslim

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Hyaline Membrane Disease (HMD) is the main cause of respiratory failure in preterm neonates caused by surfactant deficiency. Nasal Continuous Positive Airway Pressure (NCPAP) is the therapy for HMD. The success of therapy is determined by gestational age, birth weight, HMD grade, time of NCAP administration, and time of breathing frequency recovery. The aim of this research is to identify the predictive factor of NCPAP therapy success in preterm neonates with HMD. This study used a cross-sectional design by using medical records of patients who were treated in the Perinatology of the Pediatric Department of Dr. M. Djamil Padang Central Hospital from January 2015 to December 2017. The samples were eighty-two neonates that were selected by using the total sampling technique. Data analysis was done by using the Chi-Square Test and the Multiple Logistic Regression Prediction Model. The results showed the success rate of NCPAP therapy reached 53.7%. Birth weight (p = 0.048, OR = 3.34 95% CI 1.01-11.07), HMD grade I (p = 0.018, OR = 4.95 CI 95% 1.31-18.68), HMD grade II (p = 0.044, OR = 5.52 95% CI 1.04-29.15), and time of breathing frequency recovery (p = 0,000, OR = 13.50 95% CI 3.58-50, 83) are the predictive factors of NCPAP therapy success in preterm neonates with HMD. The most significant predictive factor is the time of breathing frequency recovery.

Keywords: predictive factors, the success of therapy, NCPAP, preterm neonates, HMD

Procedia PDF Downloads 59

Authors: Hamidreza Saberkari, Mousa Shamsi, Hossein Ahmadi, Saeed Vaali, , MohammadHossein Sedaaghi

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In the recent years, using signal processing tools for accurate identification of the protein coding regions has become a challenge in bioinformatics. Most of the genomic signal processing methods is based on the period-3 characteristics of the nucleoids in DNA strands and consequently, spectral analysis is applied to the numerical sequences of DNA to find the location of periodical components. In this paper, a novel ensemble algorithm for gene selection in DNA sequences has been presented which is based on the combination of Goertzel algorithm and anti-notch filter (ANF). The proposed algorithm has many advantages when compared to other conventional methods. Firstly, it leads to identify the coding protein regions more accurate due to using the Goertzel algorithm which is tuned at the desired frequency. Secondly, faster detection time is achieved. The proposed algorithm is applied on several genes, including genes available in databases BG570 and HMR195 and their results are compared to other methods based on the nucleotide level evaluation criteria. Implementation results show the excellent performance of the proposed algorithm in identifying protein coding regions, specifically in identification of small-scale gene areas.

Keywords: protein coding regions, period-3, anti-notch filter, Goertzel algorithm

Procedia PDF Downloads 387

Authors: Nawel Boucherba, Azzedine Bettache, Abdelaziz Messis, Francis Duchiron, Said Benallaoua

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The impetus for research in the field of bioseparation has been sparked by the difficulty and complexity in the downstream processing of biological products. Indeed, 50% to 90% of the production cost for a typical biological product resides in the purification strategy. There is a need for efficient and economical large scale bioseparation techniques which will achieve high purity and high recovery while maintaining the biological activity of the molecule. One such purification technique which meets these criteria involves the partitioning of biomolecules between two immiscible phases in an aqueous system (ATPS). The Production of xylanases is carried out in 500ml of a liquid medium based on birchwood xylan. In each ATPS, PEG 1000 is added to a mixture consisting of dipotassium phosphate, sodium chloride and the culture medium inoculated with the strain Jonesia denitrificans, the mixture was adjusted to different pH. The concentration of PEG 1000 was varied: 8 to 16 % and the NaCl percentages are also varied from 2 to 4% while maintaining the other parameters constant. The results showed that the best ATPS for purification of xylanases is composed of PEG 1000 at 8.33%, 13.14 % of K2HPO4, 1.62% NaCl at pH 7. We obtained a yield of 96.62 %, a partition coefficient of 86.66 and a purification factor of 2.9. The zymogram showed that the activity is mainly detected in the top phase.

Keywords: Jonesia denitrificans BN13, xylanase, aqueous two phases system, zymogram

Procedia PDF Downloads 399

Authors: Yung-Jin Weng, Chia-Chi Chang, Chun-Yu Tsai

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This paper is focused on the research of imprinting and replica molding of quasi-grey scale soft mold curved surface microstructure mold. In this paper, a magnetic photocuring forming system is first developed and built independently, then the magnetic curved surface microstructure soft mode is created; moreover, the magnetic performance of the magnetic curved surface at different heights is tested and recorded, and through experimentation and simulation, the magnetic curved surface microstructure soft mold is used in the research of quasi-grey scale soft mold curved surface microstructure imprinting and replica molding. The experimental results show that, under different surface curvatures and voltage control conditions, different quasi-grey scale array microstructures take shape. In addition, this paper conducts research on the imprinting and replica molding of photoresist composite magnetic powder in order to discuss the forming performance of magnetic photoresist, and finally, the experimental result is compared with the simulation to obtain more accurate prediction and results. This research is predicted to provide microstructure component preparation technology with heterogeneity and controllability, and is a kind of valid shaping quasi-grey scale microstructure manufacturing technology method.

Keywords: soft mold, magnetic, microstructure, curved surface

Procedia PDF Downloads 326

Authors: Pompa Marcello, Mauro Capocelli, Vincenzo Piemonte

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This work focuses on a mathematical model able to describe the gastro-intestinal physiology and providing a rational tool for the design of an artificial gastro-intestinal system. This latter is mainly devoted to analyse the absorption and bioavailability of drugs and nutrients through in vitro tests in order to overcome (or, at least, to partially replace) in vivo trials. The provided model realizes a conjunction ring (with extended prediction capability) between in vivo tests and mechanical-laboratory models emulating the human body. On this basis, no empirical equations controlling the gastric emptying are implemented in this model as frequent in the cited literature and all the sub-unit and the related system of equations are physiologically based. More in detail, the model structure consists of six compartments (stomach, duodenum, jejunum, ileum, colon and blood) interconnected through pipes and valves. Paracetamol, Ketoprofen, Irbesartan and Ketoconazole are considered and analysed in this work as reference drugs. The mathematical model has been validated against in vivo literature data. Results obtained show a very good model reliability and highlight the possibility to realize tailored simulations for different couples patient-drug, including food adsorption dynamics.

Keywords: gastro-intestinal model, drugs bioavailability, paracetamol, ketoprofen

Procedia PDF Downloads 168

Authors: Zhenyu Yang, Qiunan Chen, Xiaocheng Huang

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Reliable prediction of tunnel collapse remains a prominent challenge in the field of civil engineering. In this study, leveraging the nonlinear Hoek-Brown failure criterion and the upper-bound theorem, an analytical solution for the collapse surface of shallowly buried circular tunnels was derived, taking into account the coupled effects of surface loads and pore water pressures. Initially, surface loads and pore water pressures were introduced as external force factors, equating the energy dissipation rate to the external force, yielding our objective function. Subsequently, the variational method was employed for optimization, and the outcomes were juxtaposed with previous research findings. Furthermore, we utilized the deduced equation set to systematically analyze the influence of various rock mass parameters on collapse shape and extent. To validate our analytical solutions, a comparison with prior studies was executed. The corroboration underscored the efficacy of our proposed methodology, offering invaluable insights for collapse risk assessment in practical engineering applications.

Keywords: tunnel roof stability, analytical solution, hoek–brown failure criterion, limit analysis

Procedia PDF Downloads 84

Authors: Ismael Zamora, Elisabeth Ortega, Tatiana Radchenko, Guillem Plasencia

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The structure elucidation based on Mass Spectra (MS) data of unknown substances is an unresolved problem that affects many different fields of application. The recent overview of software available for structure elucidation of small molecules has shown the demand for efficient computational tool that will be able to perform structure elucidation of unknown small molecules and peptides. We developed an algorithm for De-Novo fragment analysis based on MS data that proposes a set of scored and ranked structures that are compatible with the MS and MSMS spectra. Several different algorithms were developed depending on the initial set of fragments and the structure building processes. Also, in all cases, several scores for the final molecule ranking were computed. They were validated with small and middle databases (DB) with the eleven test set compounds. Similar results were obtained from any of the databases that contained the fragments of the expected compound. We presented an algorithm. Or De-Novo fragment analysis based on only mass spectrometry (MS) data only that proposed a set of scored/ranked structures that was validated on different types of databases and showed good results as proof of concept. Moreover, the solutions proposed by Mass Spectrometry were submitted to the prediction of NMR spectra in order to elucidate which of the proposed structures was compatible with the NMR spectra collected.

Keywords: De Novo, structure elucidation, mass spectrometry, NMR

Procedia PDF Downloads 295

Authors: C. G. Sawant, C. S. Patil

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The investigation was conducted during January 2016 on Farmer’s field at Nandur Madhyameshwar, Tq. Niphad, Dist. Nashik (Maharashtra: India) on bio-efficacy of newer insecticides against Plutella xylostella L. infesting cabbage. The cabbage crop (var. Saint) was raised according to package of practices except for plant protection measures. Six newer insecticides along with two conventional insecticides and one synthetic pyrethroid were applied twice at 30 and 55 days after transplanting. Insecticidal solutions were diluted in water (375-500 L ha-1) and applied using knapsack sprayer (16L) with hollow cone nozzle. Treatments included indoxacarb @ 40 g a.i.ha-1, spinosad @ 17.5 g a.i.ha-1, flubendiamide @18.24 g a.i. ha-1, diafenthiuron @ 300 g a. i. ha-1, emamectin benzoate @ 10 g a. i. ha-1, chlorantraniliprole @ 10 g a. i. ha-1, quinalphos @ 250 g a. i. ha-1, triazophos @ 500 g a. i. ha-1, bifenthrin @ 50 g a.i. ha-1 and untreated control. The larvae were counted on head and outside the head. Observations were recorded one day before spray (Precount) and 1,3,7,14 days after spray. Results revealed that all the insecticidal treatments were significantly superior over untreated control by recording lower larval count. Among the insecticidal treatments, significantly lowest number of larvae of diamondback moth was recorded in chlorantraniliprole @ 10 g a.i.ha-1 (1.00 larvae plant-1) followed by spinosad @ 17.5 g a.i. ha-1 (1.45 larvae plant-1 and flubendiamide 18.24 g a.i. ha-1(1.53 larvae plant-1). The efficacy of insecticides reflected on yield of marketable cabbage heads by recording 242.27 qt ha-1 (1:33.38) in the treatment of chlorantraniliprole @ 10 g a.i.ha-1. It was followed by spinosad @ 17.5 g a.i. ha-1 with 236.91 qt ha-1 (1:24.92) and flubendiamide 18.24 g a.i. ha-1 with 228.49 qt ha-1 (1:30.43).

Keywords: bio-efficacy, cabbage, chlorantraniliprole, Plutella xylostella L.

Procedia PDF Downloads 146

Authors: E. Ghasemi Ardi, K. J. Dong, A. B. Yu, R. Y. Yang

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In current work, a numerical model based on the discrete element method (DEM) was developed which provided information about particle dynamic and impact event condition inside a laboratory scale impact mill (Fritsch). It showed that each particle mostly experiences three impacts inside the mill. While the first impact frequently happens at front surface of the rotor’s rib, the frequent location of the second impact is side surfaces of the rotor’s rib. It was also showed that while the first impact happens at small impact angle mostly varying around 35º, the second impact happens at around 70º which is close to normal impact condition. Also analyzing impact energy revealed that varying mill speed from 6000 to 14000 rpm, the ratio of first impact’s average impact energy and minimum required energy to break particle (Wₘᵢₙ) increased from 0.30 to 0.85. Moreover, it was seen that second impact poses intense impact energy on particle which can be considered as the main cause of particle splitting. Finally, obtained information from DEM simulation along with obtained data from conducted experiments was implemented in semi-empirical equations in order to find selection and breakage functions. Then, using a back-calculation approach, those parameters were used to predict the PSDs of ground particles under different impact energies. Results were compared with experiment results and showed reasonable accuracy and prediction ability.

Keywords: single particle breakage, particle dynamic, population balance model, particle size distribution, discrete element method

Procedia PDF Downloads 291

Authors: Qudama Albu-Jasim, Majdi Kanaan

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A case study about the load rating and strengthening evaluation of the six-span of steel girders bridge in Colton city of State of California is investigated. To simulate the load rating strengthening assessment for the Colton Overhead bridge, a three-dimensional finite element model built in the CSiBridge program is simulated. Three-dimensional finite-element models of the bridge are established considering the nonlinear behavior of critical bridge components to determine the feasibility and strengthening capacity under load rating analysis. The bridge was evaluated according to Caltrans Bridge Load Rating Manual 1st edition for rating the superstructure using the Load and Resistance Factor Rating (LRFR) method. The analysis for the bridge was based on load rating to determine the largest loads that can be safely placed on existing I-girder steel members and permitted to pass over the bridge. Through extensive numerical simulations, the bridge is identified to be deficient in flexural and shear capacities, and therefore strengthening for reducing the risk is needed. An in-depth parametric study is considered to evaluate the sensitivity of the bridge’s load rating response to variations in its structural parameters. The parametric analysis has exhibited that uncertainties associated with the steel’s yield strength, the superstructure’s weight, and the diaphragm configurations should be considered during the fragility analysis of the bridge system.

Keywords: load rating, CSIBridge, strengthening, uncertainties, case study

Procedia PDF Downloads 211

Authors: Yousof Farrag, Sara Malmir, Rebeca Bouza, Maite Rico, Belén Montero, Luís Barral

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Biopolymers are being extensively studied in the last years as a replacement of the conventional petroleum derived polymers, especially in packaging industry. They are natural, biodegradable materials. However, the lack of good mechanical and barrier properties is a problem in the way of this replacement. One of the most abundant biopolymers in the nature is the starch, its renewable, biocompatible low cost polysaccharide, it can be obtained from wide variety of plants, it has been used in food, packaging and other industries. This work is focusing on the production a high yield of starch nanoparticles via nanoprecipitation, to be used as reinforcement filling of biopolymer packaging matrices made of different types of starch improving their mechanical and barrier properties. Wheat and corn starch solutions were prepared in different concentrations. Absolute ethanol, acetone and different concentrations of hydrochloric acid were added as antisolvents dropwise under different amplitudes of sonication and different speeds of stirring, the produced particles were analyzed with dynamic light scattering DLS and scanning electron microscope SEM getting the morphology and the size distribution to study the effect of those factors on the produced particles. DLS results show that we have nanoparticles using low concentration of corn starch (0.5%) using 0.1M HCl as antisolvent, [Z average: 209 nm, PDI: 0,49], in case of wheat starch, we could obtain nanoparticles [Z average: 159 nm, PDI: 0,45] using the same starch solution concentration together with absolute ethanol as antisolvent.

Keywords: biopolymers, nanoparticles, DLS, starch

Procedia PDF Downloads 327

Authors: Kehinde T. Kareem

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The need to increase the production of cucumber has led to the use of inorganic fertilizers. This chemical affects the ecological balance of nature by increasing the nitrogen and phosphorus contents of the soil. Surface runoffs into rivers and streams cause eutrophication which affects aquatic organisms as well as the consumers of aquatic animals. Therefore, this study was carried out in the screenhouse to investigate the use of a plant growth-promoting fungus; Trichoderma longibrachiatum for the growth promotion of conventional and in-vitro propagated Ashley and Marketmoor cucumber. Before planting of cucumber, spore suspension (108 cfu/ml) of Trichoderma longibrachiatum grown on Potato dextrose agar (PDA) was inoculated into the soil. Fruits were evaluated for the presence of Trichoderma longibrachiatum using a species-specific primer. Results revealed that the highest significant plant height produced by in-vitro propagated Ashley was 19 cm while the highest plant height of in-vitro propagated Marketmoor was 19.67 cm. The yield of the conventional propagated Ashley cucumber showed that the number of fruit/plant obtained from T. longibrachiatum-fertilized plants were significantly more than those of the control. The in-vitro Ashely had 7 fruits/plant while the control produced 4 fruits/plant. In-vitro Marketmoor had ten fruits/plant, and the control had a value of 4 fruits/plant. There were no traces of Trichoderma longibrachiatum genes in the harvested cucumber fruits. Therefore, the use of Trichoderma longibrachiatum as a plant growth-promoter is safe for human health as well as the environment.

Keywords: biofertilizer, cucumber, genes, growth-promoter, in-vitro, propagation

Procedia PDF Downloads 244

Authors: Yash Ambekar, Kapil Vhatkar, Prathamesh Swami, Kartikey Singh, Yashovardhan Kaware

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The rise of online courses and certifications has created new opportunities for individuals to enhance their skills. However, this digital transformation has also given rise to coun- terfeit certificates. To address this multifaceted issue, we present a comprehensive certificate management system founded on blockchain technology and strengthened by smart contracts. Our system comprises three pivotal components: certificate generation, authenticity verification, and a user-centric digital locker for certificate storage. Blockchain technology underpins the entire system, ensuring the immutability and integrity of each certificate. The inclusion of a cryptographic hash for each certificate is a fundamental aspect of our design. Any alteration in the certificate’s data will yield a distinct hash, a powerful indicator of potential tampering. Furthermore, our system includes a secure digital locker based on cloud storage that empowers users to efficiently manage and access all their certificates in one place. Moreover, our project is committed to providing features for certificate revocation and updating, thereby enhancing the system’s flexibility and security. Hence, the blockchain and smart contract-based certificate management system offers a robust and one-stop solution to the escalating problem of counterfeit certificates in the digital era.

Keywords: blockchain technology, smart contracts, counterfeit certificates, authenticity verification, cryptographic hash, digital locker

Procedia PDF Downloads 46

Authors: L. Adjlout, N.Benharrat, O. Ladjdel, F. Djemil, A. Adjlout, T. Yahiaoui

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The present investigation is an experimental and numerical studies of the turbulence level influence on the flow in a smooth staggered tube bundle. The experiments were carried out in a closed circuit wind tunnel of subsonic type (TE44). Three turbulence levels at the inlet namely 1%, 4.6% and 6.3% and two Reynolds numbers Re = 9300 and Re = 13950 were performed. The obtained results for the central tube show that there are two minimum values for the angles 70° and 280° corresponding to the separation points. The pressure coefficient distributions seem to have constant values between 120° and 240° resulting in Von Karman street configuration in the wake. These remarks were valid for the tests carried out. The numerical study was performed by the ANSYS FLUENT code which solves the averaged Navier-Stokes equations (RANS). Two turbulence models (k-ε RNG and k-ε realizable), two types of grids and two levels of turbulence at the entrance of 4.6% and 6.3% for Reynolds numbers of 9300 and 13950 were considered. The obtained results for the central tube were compared with the present experimental results. It is concluded that the K-ε realizable is more suitable for the pressure distribution prediction than the K-ε RNG model compared to the present experimental results for this studied case.

Keywords: tube bundle, staggered configuration, turbulence level, numerical, experimental

Procedia PDF Downloads 128

Authors: Wided Zerguine, Farid Habelhames

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The performance of photovoltaic devices with a light absorber consisting of a single-type conjugated polymer is poor, due to a low photo-generation yield of charge carriers, strong radiative recombination’s and low mobility of charge carriers. Recently, it has been shown that ultra-fast photoinduced charge transfer can also occur between a conjugated polymer and a metal oxide semiconductor such as SnO2, TiO2, ZnO, Nb2O5, etc. This has led to the fabrication of photovoltaic devices based on composites of oxide semiconductor nanoparticles embedded in a conjugated polymer matrix. In this work, Poly [2-methoxy-5-(20-ethylhexyloxy)-p-phenylenevinylene] (MEH-PPV), (6,6)-phenyl-C61-butyric acid methyl ester (PCBM) and titanium dioxide (TiO2) nanoparticles (n-type) were dissolved, mixed and deposited by physical methods (spin-coating) on indium tin-oxide (ITO) substrate. The incorporation of the titanium dioxide nanoparticles changed the morphology and increased the roughness of polymers film (MEH-PPV/PCBM), and the photocurrent density of the composite (MEH-PPV/PCBM +n-TiO2) was higher than that of single MEHPPV/ PCBM film. The study showed that the presence of n-TiO2 particles in the polymeric film improves the photoelectrochemical properties of MEH-PPV/PCBM composite.

Keywords: photocurrent density, organic nanostructures, hybrid coating, conducting polymer, titanium dioxide

Procedia PDF Downloads 328

Authors: Ali Reza Tahavvor, Saeed Hosseini, Nazli Jowkar, Afshin Karimzadeh Fard

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Experimental & numeral study of temperature distribution during milling process, is important in milling quality and tools life aspects. In the present study the milling cross-section temperature is determined by using Artificial Neural Networks (ANN) according to the temperature of certain points of the work piece and the points specifications and the milling rotational speed of the blade. In the present work, at first three-dimensional model of the work piece is provided and then by using the Computational Heat Transfer (CHT) simulations, temperature in different nods of the work piece are specified in steady-state conditions. Results obtained from CHT are used for training and testing the ANN approach. Using reverse engineering and setting the desired x, y, z and the milling rotational speed of the blade as input data to the network, the milling surface temperature determined by neural network is presented as output data. The desired points temperature for different milling blade rotational speed are obtained experimentally and by extrapolation method for the milling surface temperature is obtained and a comparison is performed among the soft programming ANN, CHT results and experimental data and it is observed that ANN soft programming code can be used more efficiently to determine the temperature in a milling process.

Keywords: artificial neural networks, milling process, rotational speed, temperature

Procedia PDF Downloads 405

Authors: Issam Aouari, Abdelmalek Abdelhamid

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For seismologists, the characterization of seismic demand should include the amplitude and duration of strong shaking in the system. The duration of ground shaking is one of the key parameters in earthquake resistant design of structures. This paper proposes a nonlinear statistical model to estimate earthquake ground motion duration in soft soils using multiple seismicity indicators. Three definitions of ground motion duration proposed by literature have been applied. With a comparative study, we select the most significant definition to use for predict the duration. A stochastic model is presented for the McCann and Shah Method using nonlinear regression analysis based on a data set for moment magnitude, source to site distance and site conditions. The data set applied is taken from PEER strong motion databank and contains shallow earthquakes from different regions in the world; America, Turkey, London, China, Italy, Chili, Mexico...etc. Main emphasis is placed on soft site condition. The predictive relationship has been developed based on 600 records and three input indicators. Results have been compared with others published models. It has been found that the proposed model can predict earthquake ground motion duration in soft soils for different regions and sites conditions.

Keywords: duration, earthquake, prediction, regression, soft soil

Procedia PDF Downloads 153

Authors: Raza Abdulla Saeed

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In this study, the three-dimensional cavitating turbulent flow in a complete Francis turbine is simulated using mixture model for cavity/liquid two-phase flows. Numerical analysis is carried out using ANSYS CFX software release 12, and standard k-ε turbulence model is adopted for this analysis. The computational fluid domain consist of spiral casing, stay vanes, guide vanes, runner and draft tube. The computational domain is discretized with a three-dimensional mesh system of unstructured tetrahedron mesh. The finite volume method (FVM) is used to solve the governing equations of the mixture model. Results of cavitation on the runner’s blades under three different boundary conditions are presented and discussed. From the numerical results it has been found that the numerical method was successfully applied to simulate the cavitating two-phase turbulent flow through a Francis turbine, and also cavitation is clearly predicted in the form of water vapor formation inside the turbine. By comparison the numerical prediction results with a real runner; it’s shown that the region of higher volume fraction obtained by simulation is consistent with the region of runner cavitation damage.

Keywords: computational fluid dynamics, hydraulic francis turbine, numerical simulation, two-phase mixture cavitation model

Procedia PDF Downloads 560

Authors: Linyue Jia, Wenbo Du, Zhaohui Wang, Ke Liu, Shubo Li

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Due to the great potential for weight reduction in aerospace and automotive industries, magnesium-rare earth (Mg-RE) based alloys with outstanding mechanical performance have been widely investigated for decades. However, magnesium alloys are still restricted in engineering applications because of their lower strength and ductility. Hence, there are large spaces and challenges in achieving high-performance Mg alloys. This work reports an Mg-Gd-Er-Zn-Zr alloy with ultrahigh strength and good ductility developed via hot extrusion, pre-deformation, and two-stage aging. The extruded alloy comprises fine dynamically recrystallized (DRXed) grains and coarse worked grains with a large aspect ratio. Pre-deformation has little effect on the microstructure and macro-texture and serves primarily to introduce a large number of dislocations, resulting in strain hardening and higher precipitation strengthening during subsequent aging due to more nucleation sites. As a result, the alloy exhibits a yield strength (YS) of 506 MPa, an ultimate tensile strength (UTS) of 549 MPa, and elongation (EL) of 8.2% at room temperature, showing superior strength-ductility balance than the other wrought Mg-RE alloys previously reported. The current study proposes a combination of pre-deformation and two-stage aging to further improve the mechanical properties of wrought Mg alloys for engineering applications.

Keywords: magnesium alloys, mechanical properties, microstructure, pre-deformation, two-stage aging

Procedia PDF Downloads 165

Authors: Lizhou Chen, Abdelhamid Belgaid, Assem Elsayed, Xiaoming Yang

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Compression index is essential in foundation settlement calculation. The traditional method for determining compression index is consolidation test which is expensive and time consuming. Many researchers have used regression methods to develop empirical equations for predicting compression index from soil properties. Based on a large number of compression index data collected from consolidation tests, the accuracy of some popularly empirical equations were assessed. It was found that primary compression index is significantly overestimated in some equations while it is underestimated in others. The sensitivity analyses of soil parameters including water content, liquid limit and void ratio were performed. The results indicate that the compression index obtained from void ratio is most accurate. The ANOVA (analysis of variance) demonstrates that the equations with multiple soil parameters cannot provide better predictions than the equations with single soil parameter. In other words, it is not necessary to develop the relationships between compression index and multiple soil parameters. Meanwhile, it was noted that secondary compression index is approximately 0.7-5.0% of primary compression index with an average of 2.0%. In the end, the proposed prediction equations using power regression technique were provided that can provide more accurate predictions than those from existing equations.

Keywords: compression index, clay, settlement, consolidation, secondary compression index, soil parameter

Procedia PDF Downloads 163

Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: activities of daily living, classification, internet of things, machine learning, prediction, smart home

Procedia PDF Downloads 357

Authors: Palash Dey, Sudip Talukdar

Abstract:

In this work, a cross-breed approach is presented for obtaining both the amount of the damage intensity and location of damage existing in thin-walled members. This cross-breed approach is developed based on response surface methodology (RSM) and genetic algorithm (GA). Theoretical finite element (FE) model of cracked angle section thin walled curved beam has been linked to the developed approach to carry out trial experiments to generate response surface functions (RSFs) of free, forced and heterogeneous dynamic response data. Subsequently, the error between the computed response surface functions and measured dynamic response data has been minimized using GA to find out the optimum damage parameters (amount of the damage intensity and location). A single crack of varying location and depth has been considered in this study. The presented approach has been found to reveal good accuracy in prediction of crack parameters and possess great potential in crack detection as it requires only the current response of a cracked beam.

Keywords: damage parameters, finite element, genetic algorithm, response surface methodology, thin walled curved beam

Procedia PDF Downloads 248

Authors: Despina Vamvuka, Despina Pentari

Abstract:

Forestry wastes are readily available in large quantities around the world. Based on European Green Deal for the deployment of renewable and decarbonized energy by 2050, as well as global energy crisis, energy recovery from such wastes reducing greenhouse gas emissions is very attractive. Gasification has superior environmental performance to combustion, producing a clean fuel gas utilized in internal combustion engines, gas turbines, solid oxide fuel cells, or for synthesis of liquid bio-fuels and value-added chemicals. In this work, pine needles, which are abundantly found in Mediterranean countries, were gasified by either steam or carbon dioxide via a two-step process to improve reactivity and eliminate tar, employing a fixed bed unit and a thermal analysis system. Solid, liquid and gaseous products from the whole process were characterized and their energy potential was determined. Thermal behaviour, reactivity, conversion and energy recovery were examined. The gasification process took place above 650°C. At 950°C conversion and energy recovery were 77% dry and 2 under a flow of steam and 85% dry and 2.9 under a flow of carbon dioxide, respectively. Organic matter was almost completely converted to syngas, the yield of which varied between 89% and 99%. The higher heating values of biochar, bio-oil and pyrolysis gas were 27.8 MJ/kg, 33.5 MJ/kg and 13.6 MJ/m3. Upon steam or carbon dioxide gasification, the higher heating value of syngas produced was 11.5 MJ/m3 and 12.7 MJ/m3, respectively.

Keywords: gasification, biomass, steam, carbon dioxide

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Authors: Divya Choudhary, Hariprasad P., S. N. Naik

Abstract:

This study examines a low-alcohol nutra-beverage made with shatavari, a plant commonly used in traditional medicine. During fermentation, the addition of a specific strain of yeast affected the beverage's properties, including its pH level, yeast count, ethanol content, and antioxidant, phenolic, and flavonoid levels. We also analyzed the beverage's storage and shelf life. Despite its bitter taste, the low alcohol content of the beverage made it enjoyable to drink and visually appealing. Our analysis showed that the optimal time for fermentation was between the 14th and 21st day when the beverage had ideal levels of sugar, organic acids, and vitamins. The final product contained fructose and citric acid but not succinic, pyruvic, lactic, or acetic acids. It also contained vitamins B2, B1, B12, and B9. During the shelf life analysis, we observed changes in the beverage's pH, TSS, and cfu levels, as well as its antioxidant activity. We also identified volatile (GC-MS) and non-volatile compounds (LC-MS/MS) in the fermented product, some of which were already present in the Shatavari root. The highest yield of product contained the maximum concentration of antioxidant compounds, which depended on both the pH and the microorganisms' physiological status. Overall, our study provides insight into the properties and potential health benefits of this Nutra-beverage.

Keywords: antioxidants, fermentation, volatile compounds, acetonin, 1-butanol, non-volatile compounds, Shatavarin V, IX, kaempferol

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Authors: Sadia Munir

Abstract:

Preeclampsia is the contributor to the worldwide maternal mortality of approximately 100,000 deaths a year. It complicates about 10% of all pregnancies and is the first cause of maternal admission to intensive care units. Predicting preeclampsia is a major challenge in obstetrics. More importantly, no major progress has been achieved in the treatment of preeclampsia. As placenta is the main cause of the disease, the only way to treat the disease is to extract placental and deliver the baby. In developed countries, the cost of an average case of preeclampsia is estimated at £9000. Interestingly, preeclampsia may have an impact on the health of mother or infant, beyond the pregnancy. We performed a systematic search of PubMed including the combination of terms such as preeclampsia, biomarkers, treatment, hypoxia, inflammation, oxidative stress, vascular endothelial growth factor A, activin A, inhibin A, placental growth factor, transforming growth factor β-1, Nodal, placenta, trophoblast cells, microRNAs. In this review, we have summarized current knowledge on the identification of potential biomarkers for the diagnosis of preeclampsia. Although these studies show promising data in early diagnosis of preeclampsia, the current value of these factors as biomarkers, for the precise prediction of preeclampsia, has its limitation. Therefore, future studies need to be done to support some of the very promising and interesting data to develop affordable and widely available tests for early detection and treatment of preeclampsia.

Keywords: activin, biomarkers, growth factors, miroRNA

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Authors: Ria M. Caramoan, Analiza P. Rollon, Karl N. Vergel

Abstract:

The Simple Interactive Models for Better Air Quality (SIM-air) is an integrated approach model that allows the available information to support the integrated urban air quality management. This study utilized the vehicular air pollution information system module of SIM-air for the assessment of vehicular emissions in Commonwealth Avenue, Quezon City, Philippines. The main objective of the study is to assess and predict the contribution of different types of vehicles to the vehicular emissions in terms of PM₁₀, SOₓ, and NOₓ at different policy and technology scenarios. For the base year 2017, the results show vehicular emissions of 735.46 tons of PM₁₀, 108.90 tons of SOₓ, and 2,101.11 tons of NOₓ. Motorcycle is the major source of particulates contributing about 52% of the PM₁₀ emissions. Meanwhile, Public Utility Jeepneys contribute 27% of SOₓ emissions and private cars using gasoline contribute 39% of NOₓ emissions. Ambient air quality monitoring was also conducted in the study area for the standard parameters of PM₁₀, S0₂, and NO₂. Results show an average of 88.11 µg/Ncm, 47.41 µg/Ncm and 22.54 µg/Ncm for PM₁₀, N0₂, and SO₂, respectively, all were within the DENR National Ambient Air Quality Guideline Values. Future emissions of PM₁₀, NOₓ, and SOₓ are estimated at different scenarios. Results show that in the year 2030, PM₁₀ emissions will be increased by 186.2%. NOₓ emissions and SOₓ emissions will also be increased by 38.9% and 5.5%, without the implementation of the scenarios.

Keywords: ambient air quality, emissions inventory, mobile air pollution, vehicular emissions

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Authors: Rawaz A. Ahmed, Katherine Huddersman

Abstract:

High-lipid Fats, Oils and Grease (FOGs) from wastewater are underutilized despite their potential for conversion into valuable fuels; this work describes a surface-functionalized fibrous Polyacrylonitrile (PAN) mesh as a novel heterogeneous acid catalyst for the conversion of free fatty acids (FFAs), via a catalytic esterification process into biodiesel. The esterification of stearic acid (SA) with methanol was studied over an acidified PAN solid acid catalyst. Disappearance of the carboxylic acid (C=O) peak of the stearic acid at 1696 cm-1 in the FT-IR spectrum with the associated appearance of the ester (C=O) peak at 1739 cm-1 confirmed the production of the methyl stearate. This was further supported by 1H NMR spectra with the appearance of the ester (-CH₂OCOR) at 3.60-3.70 ppm. Quantitate analysis by GC-FID showed the catalyst has excellent activity with >95 % yield of methyl stearate (MS) at 90 ◦C after 3 h and a molar ratio of methanol to SA of 35:1. To date, to our best knowledge, there is no research in the literature on the esterification reaction for biodiesel production using a modified PAN mesh as a catalyst. It is noteworthy that this acidified PAN mesh catalyst showed comparable activity to conventional Brönsted acids, namely H₂SO₄ and p-TSA, as well as exhibiting higher activity than various other heterogeneous catalysts such as zeolites, ion-exchange resins and acid clay.

Keywords: fats oil and greases (FOGs), free fatty acid, esterification reaction, methyl ester, PAN

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