Search results for: wheat yield prediction

Authors: Amit Kumar Verma

Abstract:

The present study deals with fire prediction model in Terai Arc Landscape, one of the most dramatic ecosystems in Asia where large, wide-ranging species such as tiger, rhinos, and elephant will thrive while bringing economic benefits to the local people. Forest fires cause huge economic and ecological losses and release considerable quantities of carbon into the air and is an important factor inflating the global burden of carbon emissions. Forest fire is an important factor of behavioral cum ecological habit of tiger in wild. Post fire changes i.e. micro and macro habitat directly affect the tiger habitat or land. Vulnerability of fire depicts the changes in microhabitat (humus, soil profile, litter, vegetation, grassland ecosystem). Microorganism like spider, annelids, arthropods and other favorable microorganism directly affect by the forest fire and indirectly these entire microorganisms are responsible for the development of tiger (Panthera tigris) habitat. On the other hand, fire brings depletion in prey species and negative movement of tiger from wild to human- dominated areas, which may leads the conflict i.e. dangerous for both tiger & human beings. Early forest fire prediction through mapping the risk zones can help minimize the fire frequency and manage forest fires thereby minimizing losses. Satellite data plays a vital role in identifying and mapping forest fire and recording the frequency with which different vegetation types are affected. Thematic hazard maps have been generated by using IDW technique. A prediction model for fire occurrence is developed for TAL. The fire occurrence records were collected from state forest department from 2000 to 2014. Disciminant function models was used for developing a prediction model for forest fires in TAL, random points for non-occurrence of fire have been generated. Based on the attributes of points of occurrence and non-occurrence, the model developed predicts the fire occurrence. The map of predicted probabilities classified the study area into five classes very high (12.94%), high (23.63%), moderate (25.87%), low(27.46%) and no fire (10.1%) based upon the intensity of hazard. model is able to classify 78.73 percent of points correctly and hence can be used for the purpose with confidence. Overall, also the model works correctly with almost 69% of points. This study exemplifies the usefulness of prediction model of forest fire and offers a more effective way for management of forest fire. Overall, this study depicts the model for conservation of tiger’s natural habitat and forest conservation which is beneficial for the wild and human beings for future prospective.

Keywords: fire prediction model, forest fire hazard, GIS, landsat, MODIS, TAL

Procedia PDF Downloads 347

Authors: Mst. Tuhina-Khatun, Mohamed Hanafi Musa, Mohd Rafii Yosup, Wong Mui Yun, Md. Aktar-Uz-Zaman, Mahbod Sahebi

Abstract:

Rice is a staple crop of economic importance of most Asian people, and blast is the major constraints for its higher yield. Heritability of plants traits helps plant breeders to make an appropriate selection and to assess the magnitude of genetic improvement through hybridization. Diversity of crop plants is necessary to manage the continuing genetic erosion and address the issues of genetic conservation for successfully meet the future food requirements. Therefore, an experiment was conducted to estimate heritability and to determine the diversity of 27 blast resistant upland rice genotypes based on 18 quantitative traits using randomized complete block design. Heritability value was found to vary from 38 to 93%. The lowest heritability belonged to the character total number of tillers/plant (38%). In contrast, number of filled grains/panicle, and yield/plant (g) was recorded for their highest heritability value viz. 93 and 91% correspondingly. Cluster analysis based on 18 traits grouped 27 rice genotypes into six clusters. Cluster I was the biggest, which comprised 17 genotypes, accounted for about 62.96% of total population. The multivariate analysis suggested that the genotype ‘Chokoto 14’ could be hybridized with ‘IR 5533-55-1-11’ and ‘IR 5533-PP 854-1’ for broadening the gene pool of blast resistant upland rice germplasms for yield and other favorable characters.

Keywords: blast resistant, diversity analysis, heritability, upland rice

Procedia PDF Downloads 366

Authors: Abdullahi Jibrin, Aishetu Abdulkadir

Abstract:

The development of allometric models is crucial to accurate forest biomass/carbon stock assessment. The aim of this study was to develop a set of biomass prediction models that will enable the determination of total tree aboveground biomass for savannah woodland area in Niger State, Nigeria. Based on the data collected through biometric measurements of 1816 trees and destructive sampling of 36 trees, five species specific and one site specific models were developed. The sample size was distributed equally between the five most dominant species in the study site (Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa, Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the equations were developed for five individual species. Secondly these five species were mixed and were used to develop an allometric equation of mixed species. Overall, there was a strong positive relationship between total tree biomass and the stem diameter. The coefficient of determination (R2 values) ranging from 0.93 to 0.99 P < 0.001 were realised for the models; with considerable low standard error of the estimates (SEE) which confirms that the total tree above ground biomass has a significant relationship with the dbh. The F-test value for the biomass prediction models were also significant at p < 0.001 which indicates that the biomass prediction models are valid. This study recommends that for improved biomass estimates in the study site, the site specific biomass models should preferably be used instead of using generic models.

Keywords: allometriy, biomass, carbon stock , model, regression equation, woodland, inventory

Procedia PDF Downloads 441

Authors: Enikő Bene

Abstract:

Our sowing date experiment took place in the Demonstration Garden of Institution of Plant Sciences, Agricultural Center of University of Debrecen, in 2012-2014. The thesis contains data of test year 2014. Our purpose, besides several other examinations, was to observe how sowing date influences leaf area index and activity of photosynthesis of maize hybrids, and how those factors affect fruiting. In the experiment we monitored the change of the leaf area index and the photosynthesis of hybrids with four different growing seasons. The results obtained confirm that not only the environmental and agricultural factors in the growing season have effect on the yield, but also other factors like the leaf area index and the photosynthesis are determinative parameters, and all those factors together, modifying effects of each other, develop average yields

Keywords: sowing date, hybrid, leaf area index, photosynthetic capacity

Procedia PDF Downloads 324

Authors: Shu-Bo Yang, Wei Wu, Yuan-Heng Liu

Abstract:

This research aims to design a heat-exchanger type of methanol reformer coupled with a preheating design in gPROMS® environment. The endothermic methanol steam reforming reaction (MSR) and the exothermic preferential oxidation reaction (PROX) occur in the inner tube and the outer tube of the reformer, respectively. The effective heat transfer manner between the inner and outer tubes is investigated. It is verified that the countercurrent-flow type reformer provides the higher hydrogen yield than the cocurrent-flow type. Since the hot spot temperature appears in the outer tube, an improved scheme is proposed to suppress the hot spot temperature by splitting the excess air flowing into two sites. Finally, an optimization algorithm for maximizing the hydrogen yield is employed to determine optimal operating conditions.

Keywords: methanol reformer, methanol steam reforming, optimization, simulation

Procedia PDF Downloads 327

Authors: Mennatallah M. Hussein, Olivier de Weck

Abstract:

The advancement of space exploration demands a robust space launch services program capable of reliably propelling payloads into orbit. Despite rigorous testing and quality assurance, launch failures still occur, leading to significant financial losses and jeopardizing mission objectives. Traditional failure prediction methods often lack the sophistication to account for multi-mode failure scenarios, as well as the predictive capability in complex dynamic systems. Traditional approaches also rely on expert judgment, leading to variability in risk prioritization and mitigation strategies. Hence, there is a pressing need for robust approaches that enhance launch vehicle reliability from lift-off until it reaches its parking orbit through comprehensive simulation techniques. In this study, the developed model proposes a multi-mode launch vehicle simulation framework for predicting failure scenarios when incorporating new technologies, such as new propulsion systems or advanced staging separation mechanisms in the launch system. To this end, the model combined a 6-DOF system dynamics with comprehensive data analysis to simulate multiple failure modes impacting launch performance. The simulator utilizes high-fidelity physics-based simulations to capture the complex interactions between different subsystems and environmental conditions.

Keywords: launch vehicle, failure prediction, propulsion anomalies, rocket launch simulation, rocket dynamics

Procedia PDF Downloads 19

Authors: D. M. Reddy Prasad, Nur Sabrina Binti Rahmat, Huei Ruey Ong, Chin Kui Cheng, Maksudur Rahman Khan, D. Sathiyamoorthy

Abstract:

Carbon dioxide (CO₂) emission to the environment is inevitable which is responsible for global warming. Photocatalytic reduction of CO₂ to fuel, such as methanol, methane etc. is a promising way to reduce greenhouse gas CO₂ emission. In the present work, Bi₂S₃/CdS was synthesized as an effective visible light responsive photocatalyst for CO₂ reduction into methanol. The Bi₂S₃/CdS photocatalyst was prepared by hydrothermal reaction. The catalyst was characterized by X-ray diffraction (XRD) instrument. The photocatalytic activity of the catalyst has been investigated for methanol production as a function of time. Gas chromatograph flame ionization detector (GC-FID) was employed to analyze the product. The yield of methanol was found to increase with higher CdS concentration in Bi₂S₃/CdS and the maximum yield was obtained for 45 wt% of Bi₂S₃/CdS under visible light irradiation was 20 μmole/g. The result establishes that Bi₂S₃/CdS is favorable catalyst to reduce CO₂ to methanol.

Keywords: photocatalyst, CO2 reduction, methanol, visible light, XRD, GC-FID

Procedia PDF Downloads 494

Authors: Heri Hermansyah, Annisa Kurnia, A. Vania Anisya, Adi Surjosatyo, Yopi Sunarya, Rita Arbianti, Tania Surya Utami

Abstract:

Lipase is one of biocatalyst which is applied commercially for the process in industries, such as bioenergy, food, and pharmaceutical industry. Nowadays, biocatalysts are preferred in industries because they work in mild condition, high specificity, and reduce energy consumption (high pressure and temperature). But, the usage of lipase for industry scale is limited by economic reason due to the high price of lipase and difficulty of the separation system. Immobilization of lipase is one of the solutions to maintain the activity of lipase and reduce separation system in the process. Therefore, we conduct a study about lipase immobilization with the adsorption-cross linking method using glutaraldehyde because this method produces high enzyme loading and stability. Lipase is immobilized on different kind of resin with the various functional group. Highest enzyme loading (76.69%) was achieved by lipase immobilized on anion macroporous which have anion functional group (OH^‑). However, highest activity (24,69 U/g support) through olive oil emulsion method was achieved by lipase immobilized on anion macroporous-chitosan which have amino (NH₂) and anion (OH^-) functional group. In addition, it also success to produce biodiesel until reach yield 50,6% through interesterification reaction and after 4 cycles stable 63.9% relative with initial yield. While for Aspergillus, niger lipase immobilized on anion macroporous-kitosan have unit activity 22,84 U/g resin and yield biodiesel higher than commercial lipase (69,1%) and after 4 cycles stable reach 70.6% relative from initial yield. This shows that optimum functional group on support for immobilization with adsorption-cross linking is the support that contains amino (NH₂) and anion (OH^-) functional group because they can react with glutaraldehyde and binding with enzyme prevent desorption of lipase from support through binding lipase with a functional group on support.

Keywords: adsorption-cross linking, immobilization, lipase, resin

Procedia PDF Downloads 364

Authors: Rohini Hariharan, Yazhini R, Bhamidipati Naga Shrikarti

Abstract:

In the realm of cricket, particularly within the context of the Indian Premier League (IPL), the ability to predict team scores accurately holds significant importance for both cricket enthusiasts and stakeholders alike. This paper presents a comprehensive study on IPL score prediction utilizing various machine learning algorithms, including Support Vector Machines (SVM), XGBoost, Multiple Regression, Linear Regression, K-nearest neighbors (KNN), and Random Forest. Through meticulous data preprocessing, feature engineering, and model selection, we aimed to develop a robust predictive framework capable of forecasting team scores with high precision. Our experimentation involved the analysis of historical IPL match data encompassing diverse match and player statistics. Leveraging this data, we employed state-of-the-art machine learning techniques to train and evaluate the performance of each model. Notably, Multiple Regression emerged as the top-performing algorithm, achieving an impressive accuracy of 77.19% and a precision of 54.05% (within a threshold of +/- 10 runs). This research contributes to the advancement of sports analytics by demonstrating the efficacy of machine learning in predicting IPL team scores. The findings underscore the potential of advanced predictive modeling techniques to provide valuable insights for cricket enthusiasts, team management, and betting agencies. Additionally, this study serves as a benchmark for future research endeavors aimed at enhancing the accuracy and interpretability of IPL score prediction models.

Keywords: indian premier league (IPL), cricket, score prediction, machine learning, support vector machines (SVM), xgboost, multiple regression, linear regression, k-nearest neighbors (KNN), random forest, sports analytics

Procedia PDF Downloads 36

Authors: David Percy

Abstract:

Landslides are a geologic phenomenon that affects a large number of inhabited places and are constantly being monitored and studied for the prediction of future occurrences. Reconstructability analysis (RA) is a methodology for extracting informative models from large volumes of data that work exclusively with discrete data. While RA has been used in medical applications and social science extensively, we are introducing it to the spatial sciences through applications like landslide prediction. Since RA works exclusively with discrete data, such as soil classification or bedrock type, working with continuous data, such as porosity, requires that these data are binned for inclusion in the model. RA constructs models of the data which pick out the most informative elements, independent variables (IVs), from each layer that predict the dependent variable (DV), landslide occurrence. Each layer included in the model retains its classification data as a primary encoding of the data. Unlike other machine learning algorithms that force the data into one-hot encoding type of schemes, RA works directly with the data as it is encoded, with the exception of continuous data, which must be binned. The usual physical and derived layers are included in the model, and testing our results against other published methodologies, such as neural networks, yields accuracy that is similar but with the advantage of a completely transparent model. The results of an RA session with a data set are a report on every combination of variables and their probability of landslide events occurring. In this way, every combination of informative state combinations can be examined.

Keywords: reconstructability analysis, machine learning, landslides, raster analysis

Procedia PDF Downloads 55

Authors: Khalida Boutemak, Nasssima Benali, Nadji Moulai-Mostefa

Abstract:

Effect of enzyme on the yield and chemical composition of Artemisia campestris essential oil is reported in the present study. It was demonstrated that enzyme facilitated the extraction of essential oil with increase in oil yield and did not affect any noticeable change in flavour profile of the volatile oil. Essential oil was tested for antibacterial activity using Escherichia coli; which was extremely sensitive against control with the largest inhibition (29mm), whereas Staphylococcus aureus was the most sensitive against essential oil obtained from enzymatic pre-treatment with the largest inhibition zone (25mm). The antioxidant activity of the essential oil with hemicellulase pre-treatment (EO2) and control sample (EO1) was determined through reducing power. It was significantly lower than the standard drug (vitamin C) in this order: vitamin C˃EO2˃EO1.

Keywords: Artemisia campestris, enzyme pre-treatment, hemicellulase, antibacterial activity, antioxidant activity

Procedia PDF Downloads 324

Authors: Srinaath Anbu Durai, Wang Zhaoxia

Abstract:

Twitter sentiment has been used as a predictor to predict price values or trends in both the stock market and housing market. The pioneering works in this stream of research drew upon works in behavioural economics to show that sentiment or emotions impact economic decisions. Latest works in this stream focus on the algorithm used as opposed to the data used. A literature review of works in this stream through the lens of data used shows that there is a paucity of work that considers the impact of sentiments caused due to an external factor on either the stock or the housing market. This is despite an abundance of works in behavioural economics that show that sentiment or emotions caused due to an external factor impact economic decisions. To address this gap, this research studies the impact of Twitter sentiment pertaining to the Covid-19 pandemic on resale Housing Development Board (HDB) apartment prices in Singapore. It leverages SNSCRAPE to collect tweets pertaining to Covid-19 for sentiment analysis, lexicon based tools VADER and TextBlob are used for sentiment analysis, Granger Causality is used to examine the relationship between Covid-19 cases and the sentiment score, and neural networks are leveraged as prediction models. Twitter sentiment pertaining to Covid-19 as a predictor of HDB price in Singapore is studied in comparison with the traditional predictors of housing prices i.e., the structural and neighbourhood characteristics. The results indicate that using Twitter sentiment pertaining to Covid19 leads to better prediction than using only the traditional predictors and performs better as a predictor compared to two of the traditional predictors. Hence, Twitter sentiment pertaining to an external factor should be considered as important as traditional predictors. This paper demonstrates the real world economic applications of sentiment analysis of Twitter data.

Keywords: sentiment analysis, Covid-19, housing price prediction, tweets, social media, Singapore HDB, behavioral economics, neural networks

Procedia PDF Downloads 103

Authors: Alejandra Castillo-Arias, Carlos A. Fuenmayor, Carlos M. Zuluaga-Domínguez

Abstract:

The connection between health and nutrition has driven the food industry to explore healthier and more sustainable alternatives. Key strategies to enhance nutritional quality and extend shelf life include reducing saturated fats and incorporating natural ingredients. One area of focus is the use of modified starch in baked goods, which has attracted significant interest in food science and industry due to its functional benefits. Modified starches are commonly used for their gelling, thickening, and water-retention properties. Derived from sources like waxy corn, potatoes, tapioca, or rice, these polysaccharides improve thermal stability and resistance to dough. The use of modified starch enhances the texture and structure of baked goods, which is crucial for consumer acceptance. In this study, it was evaluated the effects of modified starch inclusion on dough used for puff pastry elaboration, measured with Mixolab analysis. This technique assesses flour quality by examining its behavior under varying conditions, providing a comprehensive profile of its baking properties. The analysis included measurements of water absorption capacity, dough development time, dough stability, softening, final consistency, and starch gelatinization. Each of these parameters offers insights into how the flour will perform during baking and the quality of the final product. The performance of wheat flour with varying levels of modified starch inclusion (10%, 20%, 30%, and 40%) was evaluated through Mixolab analysis, with a control sample consisting of 100% wheat flour. Water absorption, gluten content, and retrogradation indices were analyzed to understand how modified starch affects dough properties. The results showed that the inclusion of modified starch increased the absorption index, especially at levels above 30%, indicating a dough with better handling qualities and potentially improved texture in the final baked product. However, the reduction in wheat flour resulted in a lower kneading index, affecting dough strength. Conversely, incorporating more than 20% modified starch reduced the retrogradation index, indicating improved stability and resistance to crystallization after cooling. Additionally, the modified starch improved the gluten index, contributing to better dough elasticity and stability, providing good structural support and resistance to deformation during mixing and baking. As expected, the control sample exhibited a higher amylase index, due to the presence of enzymes in wheat flour. However, this is of low concern in puff pastry dough, as amylase activity is more relevant in fermented doughs, which is not the case here. Overall, the use of modified starch in puff pastry enhanced product quality by improving texture, structure, and shelf life, particularly when used at levels between 30% and 40%. This research underscores the potential of modified starches to address health concerns associated with traditional starches and to contribute to the development of higher-quality, consumer-friendly baked products. Furthermore, the findings suggest that modified starches could play a pivotal role in future innovations within the baking industry, particularly in products aiming to balance healthfulness with sensory appeal. By incorporating modified starch into their formulations, bakeries can meet the growing demand for healthier, more sustainable products while maintaining the indulgent qualities that consumers expect from baked goods.

Keywords: baking quality, dough properties, modified starch, puff pastry

Procedia PDF Downloads 11

Authors: A. Al-Rashidi, A. El-Hamalawi

Abstract:

In this paper, a performance study was conducted to investigate single and dual-axis PV systems to generate electricity in five different sites in Kuwait. Relevant data were obtained by using two sources for validation purposes. A commercial software, PVsyst, was used to analyse the data, such as metrological data and other input parameters, and compute the performance parameters such as capacity factor (CF) and final yield (YF). The results indicated that single and dual-axis PV systems would be very beneficial to electricity generation in Kuwait as an alternative source to conventional power plants, especially with the increased demand over time. The ranges were also found to be competitive in comparison to leading countries using similar systems. A significant increase in CF and YF values around 24% and 28.8% was achieved related to the use of single and dual systems, respectively.

Keywords: single-axis and dual-axis photovoltaic systems, capacity factor, final yield, Kuwait

Procedia PDF Downloads 290

Authors: Antoni Wibowo, Harry Pujianto, Dewi Retno Sari Saputro

Abstract:

The stock market can provide huge profits in a relatively short time in financial sector; however, it also has a high risk for investors and traders if they are not careful to look the factors that affect the stock market. Therefore, they should give attention to the dynamic fluctuations and movements of the stock market to optimize profits from their investment. In this paper, we present a nonlinear autoregressive exogenous model (NARX) to predict the movements of stock market; especially, the movements of the closing price index. As case study, we consider to predict the movement of the closing price in Indonesia composite index (IHSG) and choose the best structures of NARX for IHSG’s prediction.

Keywords: NARX (Nonlinear Autoregressive Exogenous Model), prediction, stock market, time series

Procedia PDF Downloads 237

Authors: S. V. Kuznetsov, M. N. Mayakova, V. Yu. Proydakova, V. V. Pavlov, A. S. Nizamutdinov, O. A. Morozov, V. V. Voronov, P. P. Fedorov

Abstract:

Increase in the share of electricity received by conversion of solar energy results in the reduction of the industrial impact on the environment from the use of the hydrocarbon energy sources. One way to increase said share is to improve the efficiency of solar energy conversion in silicon-based solar panels. Such efficiency increase can be achieved by transferring energy from sunlight-insensitive areas of work of silicon solar panels to the area of their photoresistivity. To achieve this goal, a transition to new luminescent materials with the high quantum yield of luminescence is necessary. Improvement in the quantum yield can be achieved by quantum cutting, which allows obtaining a quantum yield of down conversion of more than 150% due to the splitting of high-energy photons of the UV spectral range into lower-energy photons of the visible and near infrared spectral ranges. The goal of present work is to test approach of excitation through sensibilization of 4f-4f fluorescence of Yb3+ by various RE ions absorbing in UV and Vis spectral ranges. One of promising materials for quantum cutting luminophores are fluorides. In our investigation we have developed synthesis of nano- and submicron powders of calcium fluoride and strontium doped with rare-earth elements (Yb: Ce, Yb: Pr, Yb: Eu) of controlled dimensions and shape by co-precipitation from water solution technique. We have used Ca(NO3)2*4H2O, Sr(NO3)2, HF, NH4F as precursors. After initial solutions of nitrates were prepared they have been mixed with fluorine containing solution by dropwise manner. According to XRD data, the synthesis resulted in single phase samples with fluorite structure. By means of SEM measurements, we have confirmed spherical morphology and have determined sizes of particles (50-100 nm after synthesis and 150-300 nm after calcination). Temperature of calcination appeared to be 600°C. We have investigated the spectral-kinetic characteristics of above mentioned compounds. Here the diffuse reflection and laser induced fluorescence spectra of Yb3+ ions excited at around 4f-4f and 4f-5d transitions of Pr3+, Eu3+ and Ce3+ ions in the synthesized powders are reported. The investigation of down conversion luminescence capability of synthesized compounds included measurements of fluorescence decays and quantum yield of 2F5/2-2F7/2 fluorescence of Yb3+ ions as function of Yb3+ and sensitizer contents. An optimal chemical composition of CaF2-YbF3- LnF3 (Ln=Ce, Eu, Pr), SrF2-YbF3-LnF3 (Ln=Ce, Eu, Pr) micro- and nano- powders according to criteria of maximal IR fluorescence yield is proposed. We suppose that investigated materials are prospective in solar panels improvement applications. Work was supported by Russian Science Foundation grant #17-73- 20352.

Keywords: solar cell, fluorides, down-conversion luminescence, maximum quantum yield

Procedia PDF Downloads 268

Authors: Aboussalih Amira, Zarza Tahar, Fedaoui Kamel, Hammoudi Saleh

Abstract:

This work focuses on the simulation of the prediction of the behaviour of austenitic stainless steel (SS) 304L under complex loading in stress and imposed strain. The Chaboche model is a cable to describe the response of the material by the combination of two isotropic and nonlinear kinematic work hardening, the model is implemented in the ZébuLon computer code. First, we represent the evolution of the axial stress as a function of the plastic strain through hysteresis loops revealing a hardening behaviour caused by the increase in stress by stress in the direction of tension/compression. In a second step, the study of the ratcheting phenomenon takes a key place in this work by the appearance of the average stress. In addition to the solicitation of the material in the biaxial direction in traction / torsion.

Keywords: damage, 304L, Ratcheting, plastic strain

Procedia PDF Downloads 78

Authors: Jon Cobb, Nasir

Abstract:

Due to higher switching frequencies, the conducted Electromagnetic interference (EMI) noise is generated in a converter. It degrades the performance of a switching converter. Therefore, it is an essential requirement to mitigate EMI noise of high performance converter. Moreover, it includes two types of emission such as common mode (CM) and differential mode (DM) noise. CM noise is due to parasitic capacitance present in a converter and DM noise is caused by switching current. However, there is dire need to understand the main cause of EMI noise. Hence, we propose a novel method to predict conducted EMI noise of different converter topologies during early stage. This paper also presents the comparison of conducted electromagnetic interference (EMI) noise due to different SMPS topologies. We also make an attempt to develop an EMI noise model for a converter which allows detailed performance analysis. The proposed method is applied to different converter, as an example, and experimental results are verified the novel prediction technique.

Keywords: EMI, electromagnetic interference, SMPS, switch-mode power supply, common mode, CM, differential mode, DM, noise

Procedia PDF Downloads 1200

Authors: Oluseun S. Oyelakin, Olalekan W. Olaniyi

Abstract:

A field experiment was conducted at Ido town in Ido Local Government Area of Oyo state, Nigeria to determine the effects of intercropping maize (Zea mays L.) with Jack bean (Canavalia ensiformis L.) at different spacing and weeding regimes on crops productivity. The treatments were 2 x 2 x 3 factorial arrangement involving two spatial crop arrangements. Spacing of 75 cm x 50 cm and 90 cm x 42 cm (41.667 cm) with two plants per stand resulted in plant population of approximately 53,000 plants/hectare. Also, Randomized Complete Block Design (RCBD) with two cropping patterns (sole and intercrop), three weeding regimes (weedy check, weeds once, and weed twice) with three replicates was used. Data were analyzed with SAS (Statistical Analysis System) and statistical means separated using Least Significant Difference (LSD) (P ≤ 0.05). Intercropping and crop spacing did not have significant influence on the growth parameters and yield parameters. The maize grain yield of 1.11 t/ha obtained under sole maize was comparable to 1.05 t/ha from maize/jack beans. Weeding regime significantly influenced growth and yields of maize in intercropping with Jack beans. Weeding twice resulted in significantly higher growth than that of the other weeding regimes. Plant height at 6 Weeks After Sowing (WAS) under weeding twice regime (3 and 6 WAS) was 83.9 cm which was significantly different from 67.75 cm and 53.47 cm for weeding once (3 WAS) and no weeding regimes respectively. Moreover, maize grain yield of 1.3 t/ha obtained from plots weeded twice was comparable to that of 1.23 t/ha from single weeding and both were significantly higher than 0.71 t/ha maize grain yield obtained from the no weeding control. The dry matter production of Jack beans reduced at some growth stages due to intercropping of maize with Jack beans though with no significance effect on the other growth parameters of the crop. There was no effect on the growth parameters of Jack beans in maize/jack beans intercrop based on cropping spacing while comparable growth and dry matter production in Jack beans were produced in maize/Jack beans mixture with single weeding.

Keywords: crop spacing, intercropping, growth parameter, weeding regime, sole cropping, WAS, week after sowing

Procedia PDF Downloads 139

Authors: Shayla He

Abstract:

Background and Purpose: According to Chamie (2017), it’s estimated that no less than 150 million people, or about 2 percent of the world’s population, are homeless. The homeless population in the United States has grown rapidly in the past four decades. In New York City, the sheltered homeless population has increased from 12,830 in 1983 to 62,679 in 2020. Knowing the trend on the homeless population is crucial at helping the states and the cities make affordable housing plans, and other community service plans ahead of time to better prepare for the situation. This study utilized the data from New York City, examined the key factors associated with the homelessness, and developed systematic modeling to predict homeless populations of the future. Using the best model developed, named HP-RNN, an analysis on the homeless population change during the months of 2020 and 2021, which were impacted by the COVID-19 pandemic, was conducted. Moreover, HP-RNN was tested on the data from Seattle. Methods: The methodology involves four phases in developing robust prediction methods. Phase 1 gathered and analyzed raw data of homeless population and demographic conditions from five urban centers. Phase 2 identified the key factors that contribute to the rate of homelessness. In Phase 3, three models were built using Linear Regression, Random Forest, and Recurrent Neural Network (RNN), respectively, to predict the future trend of society's homeless population. Each model was trained and tuned based on the dataset from New York City for its accuracy measured by Mean Squared Error (MSE). In Phase 4, the final phase, the best model from Phase 3 was evaluated using the data from Seattle that was not part of the model training and tuning process in Phase 3. Results: Compared to the Linear Regression based model used by HUD et al (2019), HP-RNN significantly improved the prediction metrics of Coefficient of Determination (R2) from -11.73 to 0.88 and MSE by 99%. HP-RNN was then validated on the data from Seattle, WA, which showed a peak %error of 14.5% between the actual and the predicted count. Finally, the modeling results were collected to predict the trend during the COVID-19 pandemic. It shows a good correlation between the actual and the predicted homeless population, with the peak %error less than 8.6%. Conclusions and Implications: This work is the first work to apply RNN to model the time series of the homeless related data. The Model shows a close correlation between the actual and the predicted homeless population. There are two major implications of this result. First, the model can be used to predict the homeless population for the next several years, and the prediction can help the states and the cities plan ahead on affordable housing allocation and other community service to better prepare for the future. Moreover, this prediction can serve as a reference to policy makers and legislators as they seek to make changes that may impact the factors closely associated with the future homeless population trend.

Keywords: homeless, prediction, model, RNN

Procedia PDF Downloads 118

Authors: Sayed Mostafa, Siham Mostafa Mohamed Faheid, Ibrahim Rizk Sayed Ahmed, Yasser Fehry Mohamed Kishk, Gamal Hassan Ragab

Abstract:

Gluten-free foods are still the only treatment for gluten-allergic patients. Consequently, this study is concerned with improving the quality attributes of gluten-free bread using different concentrations (0, 20, 40, 60 and 80ppm) of all maltogenic α-amylase (MA) and xylanase (XY) compared with wheat flour Balady bread and untreated gluten-free Balady bread (GFBB). Pasting properties, falling number, water activity, alkaline water retention capacity (AWRC) and sensory properties (fresh bread, after 24h, after 48h and after 72h) of gluten-free bread were evaluated. Additionally, the effect of merging different concentrations of maltogenic α-amylase and xylanase on stalling behavior (AWRC) and sensory properties of gluten-free Balady bread was investigated. The addition of MA led to a gradually decreased peak viscosity, breakdown, setback and pasting temperature of GFBB with the increasing level of MA. Maltogenic α-amylase and xylanase addition led to a reduction in the FN values compared to the untreated gluten-free sample, noting that the MA-treated samples showed a significant decrease compared to the XY-treated and untreated samples. Wheat flour Balady bread significantly showed a higher value of AWRC compared to untreated gluten-free Balady bread at different storage periods (zero time, after 24h, after 48h and after 72h). MA-treated samples showed higher water binding capacity and water activity (aw)in comparison with XY-treated samples, with significance during all storage periods. Concerning the overall acceptability during the third day, the highest score (4.6) was observed by the GFBB sample containing 40ppm MA, followed by 4.3, which was investigated by the GFBB sample containing 80ppm XY with no significance between them and with significance compared to the other samples.

Keywords: celiac disease, gluten-free products, anti-stalling agents, maltogenic α-amylase, xylanase

Procedia PDF Downloads 74

Authors: Rosa Palmeri, Julieta I. Monteleone, Antonio C. Barbera, Carmelo Maucieri, Aldo Todaro, Virgilio Giannone, Giovanni Spagna

Abstract:

In recent years, considerable interest has been shown in the functional properties of foods, and a relevant role has been played by phenolic compounds, able to scavenge free radicals. A more sustainable agriculture has to emerge to guarantee food supply over the next years. Wheat, corn, and rice are the most common cereals cultivated, but also other cereal species, such as barley can be appreciated for their peculiarities. Barley (Hordeum vulgare L.) is a C3 winter cereal that shows high resistance at drought and salt stresses. There are growing interests in barley as ingredient for the production of functional foods due to its high content of phenolic compounds and Beta-glucans. In this respect, the possibility of separating specific functional fractions from food industry by-products looks very promising. Olive leaves represent a quantitatively significant by-product of olive grove farming, and are an interesting source of phenolic compounds. In particular, oleuropein, which provide important nutritional benefits, is the main phenolic compound in olive leaves and ranges from 17% to 23% depending upon the cultivar and growing season period. Together with oleuropein and its derivatives (e.g. dimethyloleuropein, oleuropein diglucoside), olive leaves further contain tyrosol, hydroxytyrosol, and a series of secondary metabolities structurally related to them: verbascoside, ligstroside, hydroxytyrosol glucoside, tyrosol glucoside, oleuroside, oleoside-11-methyl ester, and nuzhenide. Several flavonoids, flavonoid glycosides, and phenolic acids have also described in olive leaves. The aim of this work was the production of functional food with higher content of polyphenols and the evaluation of their shelf life. Organic durum wheat and barley grains contain higher levels of phenolic compounds were used for the production of crackers. Olive leaf extract (OLE) was obtained from cv. ‘Biancolilla’ by aqueous extraction method. Two baked goods trials were performed with both organic durum wheat and barley flours, adding olive leaf extract. Control crackers, made as comparison, were produced with the same formulation replacing OLE with water. Total phenolic compound, moisture content, activity water, and textural properties at different time of storage were determined to evaluate the shelf-life of the products. Our the preliminary results showed that the enriched crackers showed higher phenolic content and antioxidant activity than control. Alternative uses of olive leaf extracts for crackers production could represent a good candidate for the addition of functional ingredients because bakery items are daily consumed, and have long shelf-life.

Keywords: barley, functional foods, olive leaf, polyphenols, shelf life

Procedia PDF Downloads 297

Authors: A. Raceviciute-Stupeliene, V. Sasyte, V. Viliene, V. Slausgalvis, J. Al-Saifi, R. Gruzauskas

Abstract:

The objective of this study was to investigate the influence of special additives such as chelators, zinc sulphate and silicic acid on productivity parameters, carcass characteristics and meat quality of fattening pigs. The test started with 40 days old fattening pigs (mongrel (mother) and Yorkshire (father)) and lasted up to 156 days of age. During the fattening period, 32 pigs were divided into 2 groups (control and experimental) with 4 replicates (total of 8 pens).  The pigs were fed for 16 weeks’ ad libitum with a standard wheat-barley-soybean meal compound (Control group) supplemented with chelators, zinc sulphate and silicic acid (dosage 2 kg/t of feed, Experimental group). Meat traits in live pigs were measured by ultrasonic equipment Piglog 105. The results obtained throughout the experimental period suggest that supplementation of chelators, zinc sulphate and silicic acid tend to positively affect average daily gain and feed conversion ratio of pigs for fattening (p < 0.05). Pigs’ evaluation with Piglog 105 showed that thickness of fat in the first and second point was by 4% and 3% respectively higher in comparison to the control group (p < 0.05). Carcass weight, yield, and length, also thickness of fat showed no significant difference among the groups. The water holding capacity of meat in Experimental group was lower by 5.28%, and tenderness – lower by 12% compared with that of the pigs in the Control group (p < 0.05). Regarding pigs’ meat chemical composition of the experimental group, a statistically significant difference comparing with the data of the control group was not determined. Cholesterol concentration in muscles of pigs fed diets supplemented with chelators, zinc sulphate and silicic acid was lower by 7.93 mg/100 g of muscle in comparison to that of the control group. These results suggest that supplementation of chelators, zinc sulphate and silicic acid in the feed for fattening pigs had significant effect on pigs growing performance and meat quality.

Keywords: silicic acid, chelators, meat quality, pigs, zinc sulphate

Procedia PDF Downloads 176

Authors: M. Ben Slimene, M.-S. Ouali

Abstract:

Asset management of urban infrastructures faces a multitude of challenges that need to be overcome to obtain a reliable measurement of performances. Predicting the performance of slowly aging systems is one of those challenges, which helps the asset manager to investigate specific failure modes and to undertake the appropriate maintenance and rehabilitation interventions to avoid catastrophic failures as well as to optimize the maintenance costs. This article presents a methodology for modeling the deterioration of slowly degrading assets based on an operating history. It consists of extracting degradation profiles by grouping together assets that exhibit similar degradation sequences using an unsupervised classification technique derived from artificial intelligence. The obtained clusters are used to build the performance prediction models. This methodology is applied to a sample of a stormwater drainage culvert dataset.

Keywords: artificial Intelligence, clustering, culvert, regression model, slow degradation

Procedia PDF Downloads 101

Authors: Osama Moustafa Zayed

Abstract:

Aim of the work: To evaluate the effectiveness of venous glucose, levels of serum lactate and base deficit in polytraumatized patients as simple parameters to predict the mortality in these patients. Compared to the predictive value of Trauma and injury severity (TRISS) and Acute Physiology And Chronic Health Evaluation IV (APACHE IV). Introduction: Trauma is a serious global health problem, accounting for approximately one in 10 deaths worldwide. Trauma accounts for 5 million deaths per year. Prediction of mortality in trauma patients is an important part of trauma care. Several trauma scores have been devised to predict injury severity and risk of mortality. The trauma and injury severity score (TRISS) was most common used. Regardless of the accuracy of trauma scores, is based on an anatomical description of every injury and cannot be assigned to the patients until a full diagnostic procedure has been performed. So we hypothesized that alterations in admission glucose, lactate levels and base deficit would be an early and easy rapid predictor of mortality. Patient and Method: a comparative cross-sectional study. 282 Polytraumatized patients attended to the Emergency Department(ED) of the Suez Canal university Hospital constituted. The period from 1/1/2012 to 1/4/2013 was included. Results: We found that the best cut off value of TRISS probability of survival score for prediction of mortality among poly-traumatized patients is = 90, with 77% sensitivity and 89% specificity using area under the ROC curve (0.89) at (95%CI). APACHE IV demonstrated 67% sensitivity and 95% specificity at 95% CI at cut off point 99. The best cutoff value of Random Blood Sugar (RBS) for prediction of mortality was>140 mg/dl, with 89%, sensitivity, 49% specificity. The best cut off value of base deficit for prediction of mortality was less than -5.6 with 64% sensitivity, 93% specificity. The best cutoff point of lactate for prediction of mortality was > 2.6 mmol/L with 92%, sensitivity, 42% specificity. Conclusion: According to our results from all evaluated predictors of mortality (laboratory and scores) and mortality based on the estimated cutoff values using ROC curves analysis, the highest risk of mortality was found using a cutoff value of 90 in TRISS score while with laboratory parameters the highest risk of mortality was with serum lactate > 2.6 . Although that all of the three parameter are accurate in predicting mortality in poly-traumatized patients and near with each other, as in serum lactate the area under the curve 0.82, in BD 0.79 and 0.77 in RBS.

Keywords: APACHE IV, emergency department, polytraumatized patients, serum lactate

Procedia PDF Downloads 289

Authors: Ahmed I. Al-Amoud

Abstract:

A laboratory and field study were conducted on subsurface drip irrigation systems. In the first laboratory study, eight subsurface drip irrigation lines available locally, were selected and a number of experiments were made to evaluate line hydraulic characteristics to insure it's suitability for drip irrigation design requirements and high performance to select the best for field experiments. The second study involves field trials on mature date palm trees to study the effect of subsurface drip irrigation system on the yield and water consumption of date palms, and to compare that with the traditional surface drip irrigation system. Experiments were conducted in Alwatania Agricultural Project, on 50 mature palm trees (17 years old) of Helwa type with 10 meters spacing between rows and between trees. A high efficiency subsurface line (Techline) was used based on the results of the first study. Irrigation scheduling was made through a soil moisture sensing device to ensure enough soil water levels in the soil. Experiment layouts were installed during 2001 season, measurements continued till end of 2008 season. Results have indicated that there is an increase in the yield and a considerable saving in water compared to the conventional drip irrigation method. In addition there were high increases in water use efficiency using the subsurface system. The subsurface system proves to be durable and highly efficient for irrigating date palm trees.

Keywords: drip irrigation, subsurface drip irrigation, date palm trees, date palm water use, date palm yield

Procedia PDF Downloads 424

Authors: Gagan Brar, Munruchi Kaur

Abstract:

Macrocybe gigantea was collected from the wild, growing as pure white, fleshy, robust fruit bodies in caespitose clusters. Initially, the few ladies collecting these fruiting bodies for cooking revealed their edibility status, which was later confirmed through classical and molecular taxonomy. The culture of this potential wild edible taxa was raised with an aim of domesticating it. Various solid and liquid media were evaluated for their vegetative growth, in which Malt Extract Agar was found to be the best solid medium and Glucose Peptone medium as the best liquid medium. The effect of different temperatures as well as pH was also evaluated for the vegetative growth of M. gigantea, and it was found that it shows maximum vegetative growth at 30° and pH 5. For spawn preparation, various grains viz. Wheat grains, Jowar grains, Bajra grains and Maize grains were evaluated, and it was found that wheat grains boiled for 30 minutes gave the maximum mycelial growth. Mother spawn was thus prepared on wheat grains boiled for 30 minutes. For raising the fruiting bodies, different locally available agro-wastes were tried, and it was found that paddy straw gives the best growth. Both wilds as well as cultivated M. gigantea were compared through HPLC to evaluate the different nutritional and nutraceutical values. For the evaluation of different sugars in wild and cultivated M. gigantea, 15 sugars were taken for analysis. Among these Melezitose, Trehalose, Glucose, Xylose and Mannitol were found in the wild collection of M. gigantea; in the cultivated sample, Melezitose, Trehalose, Xylose and Dulcitol were detected. Among the 20 different amino acids, 18 amino acids were found, except Asparagine and Glutamine in both wild as well as cultivated samples. Among the 37 tested fatty acids, only 6 fatty acids, namely Palmitic acid, Stearic acid, Cis-9 Oleic acid, Linoleic acid, Gamma-Linolenic acid and Tricosanoic acid, were found in both wild and cultivated samples, although the concentration of these fatty acids was more in the cultivated sample. From the various vitamins tested, Vitamin C, D and E were present in both wild and cultivated samples. Both wild as well as cultivated samples were evaluated for the presence of phenols; for this purpose, eleven phenols were taken as standards in HPLC analysis, and it was found that Gallic acid, Resorcinol, Ferulic acid and Pyrogallol were present in the wild mushroom sample whereas in the cultivated sample Ferulic acid, Caffeic Acid, Vanillic acid and Vanillin are present. The flavonoid analysis revealed the presence of Rutin, Naringin and Quercetin in wild M. gigantea, while 5 Naringin, Catechol, Myrecetin, Gossypin and Quercetin were found in cultivated one. From the comparative chromatographic profiling of both wild as well as cultivated M. gigantea, it is concluded that no nutrient loss was found during its cultivation. An increase in percentage of secondary metabolites (i.e., phenols and flavonoids) was found in cultivated one as compared to wild M. gigantea. Thus, from future perspective cultivated species of M. gigantea can be recommended for the commercial purpose as a good food supplement.

Keywords: culture, edible, fruit bodies, wild

Procedia PDF Downloads 63

Authors: Caroline E. Mendes, Alberto C. Badino

Abstract:

Pneumatic reactors have been widely employed in various sectors of the chemical industry, especially where are required high heat and mass transfer rates. This study aimed to obtain correlations that allow the prediction of gas hold-up (Ԑ) and volumetric oxygen transfer coefficient (kLa), and compare these values, for three models of pneumatic reactors on two scales utilizing Newtonian fluids. Values of kLa were obtained using the dynamic pressure-step method, while  was used for a new proposed measure. Comparing the three models of reactors studied, it was observed that the mass transfer was superior to draft-tube airlift, reaching  of 0.173 and kLa of 0.00904s-1. All correlations showed good fit to the experimental data (R2≥94%), and comparisons with correlations from the literature demonstrate the need for further similar studies due to shortage of data available, mainly for airlift reactors and high viscosity fluids.

Keywords: bubble column, internal loop airlift, gas hold-up, kLa

Procedia PDF Downloads 269

Authors: Adesoji Tunbosun Jaiyeola, Josiah Adeyemo

Abstract:

Sediment yield can be considered to be the total sediment load that leaves a drainage basin. The knowledge of the quantity of sediments present in a river at a particular time can lead to better flood capacity in reservoirs and consequently help to control over-bane flooding. Furthermore, as sediment accumulates in the reservoir, it gradually loses its ability to store water for the purposes for which it was built. The development of hydrological models to forecast the quantity of sediment present in a reservoir helps planners and managers of water resources systems, to understand the system better in terms of its problems and alternative ways to address them. The application of artificial intelligence models and technique to such real-life situations have proven to be an effective approach of solving complex problems. This paper makes an extensive review of literature relevant to the theories and applications of evolutionary algorithms, and most especially genetic programming. The successful applications of genetic programming as a soft computing technique were reviewed in sediment modelling and other branches of knowledge. Some fundamental issues such as benchmark, generalization ability, bloat and over-fitting and other open issues relating to the working principles of GP, which needs to be addressed by the GP community were also highlighted. This review aim to give GP theoreticians, researchers and the general community of GP enough research direction, valuable guide and also keep all stakeholders abreast of the issues which need attention during the next decade for the advancement of GP.

Keywords: benchmark, bloat, generalization, genetic programming, over-fitting, sediment yield

Procedia PDF Downloads 440

Authors: V. P. Ramani, K. P. Patel, S. B. Patel

Abstract:

It is necessary to dispose of generated industrial wastes in the proper way to overcome the further pollution for a safe environment. Waste can be used in agriculture for good quality higher food production. In order to evaluate the effect and rate of processed industrial biomass on yield, contents, uptake and soil status in maize, a field experiment was conducted during 2009 - 2011 at Anand on loamy sand soil for two years. The treatments of different levels of NPK i.e. 100% RD, 75% RD and 50% RD were kept to study the possibility of reduction in fertilizer application with the use of processed biomass (BM) in different proportion with FYM. (Where, RD= Recommended dose, FYM= Farm Yard Manure, BM= Processed Biomass.) The significantly highest grain yield of maize was recorded under the treatment of 75% NPK + BM application @ 10t ha-1. The higher (10t ha-1) and lower (5t ha-1) application rate of BM with full dose of NPK was found beneficial being at par with the treatment 75% NPK along with BM application @ 10t ha-1. There is saving of 25% recommended dose of NPK when combined with BM application @ 10.0t ha-1 or 50% saving of organics when applied with full dose (100%) of NPK. The highest straw yield (7734 kg ha-1) of maize on pooled basis was observed under the treatment of recommended dose of NPK along with FYM application at 7.5t ha-1 coupled with BM application at 2.5t ha-1. It was also observed that highest straw yield was at par under all the treatments except control and application of 100% recommended dose of NPK coupled with BM application at 7.5t ha-1. The Fe content of maize straw were found altered significantly due to different treatments on pooled basis and it was noticed that biomass application at 7.5t ha-1 along with recommended dose of NPK showed significant enhancement in Fe content of straw over other treatments. Among heavy metals, Co, Pb and Cr contents of grain were found significantly altered due to application of different treatments variably during the pooled. While, Ni content of maize grain was not altered significantly due to application of different organics. However, at higher rate of BM application i.e. of 10t ha-1, there was slight increase in heavy metal content of grain/ straw as well as DTPA heavy metals in soil; although the increase was not alarming Thus, the overall results indicated that the application of BM at 5t ha-1 along with full dose of NPK is beneficial to get higher yield of maize without affecting soil / plant health adversely. It also indicated that the 5t BM ha-1 could be utilized in place of 10t FYM ha-1 where FYM availability is scarce. The 10t BM ha-1 helps to reduce a load of chemical fertilizer up to 25 percent in agriculture. The lower use of agro-chemicals always favors safe environment. However, the continuous use of biomass needs periodical monitoring to check any buildup of heavy metals in soil/ plant over the years.

Keywords: alternate use of industrial waste, heavy metals, maize, processed industrial biomass

Procedia PDF Downloads 315