Search results for: soil texture prediction

Authors: Kudzanayi Chiteka, Wellington Makondo

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The whole world is on the drive to go green owing to the negative effects of burning fossil fuels. Therefore, there is immediate need to identify and utilise alternative renewable energy sources. Among these energy sources solar energy is one of the most dominant in Zimbabwe. Solar power plants used to generate electricity are entirely dependent on solar radiation. For planning purposes, solar radiation values should be known in advance to make necessary arrangements to minimise the negative effects of the absence of solar radiation due to cloud cover and other naturally occurring phenomena. This research focused on the prediction of Global Horizontal Irradiation values for the sixth day given values for the past five days. Artificial intelligence techniques were used in this research. Three models were developed based on Support Vector Machines, Radial Basis Function, and Feed Forward Back-Propagation Artificial neural network. Results revealed that Support Vector Machines gives the best results compared to the other two with a mean absolute percentage error (MAPE) of 2%, Mean Absolute Error (MAE) of 0.05kWh/m²/day root mean square (RMS) error of 0.15kWh/m²/day and a coefficient of determination of 0.990. The other predictive models had prediction accuracies of MAPEs of 4.5% and 6% respectively for Radial Basis Function and Feed Forward Back-propagation Artificial neural network. These two models also had coefficients of determination of 0.975 and 0.970 respectively. It was found that prediction of GHI values for the future days is possible using artificial intelligence-based predictive models.

Keywords: solar energy, global horizontal irradiation, artificial intelligence, predictive models

Procedia PDF Downloads 262

Authors: Abel Mahowe

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Furrow erosion is the major problem menacing sustainability of irrigation in Malawi and polluting water bodies resulting in death of many aquatic animals. Many rivers in Malawi are drying due to some poor practices that are being practiced around these water bodies, furrow erosion is one of the cause of sedimentation in these rivers although it has gradual effect on deteriorating of these rivers hence neglected, but has got long term disastrous effect on water bodies. Many aquatic animals also suffer when these sediments are taken into these water bodies. An assessment of effect of manure treatment on furrow erosion was carried out in Sagawika irrigation scheme located in Kasungu District north part of Malawi. The soil on the field was clay loam and had just been tilled. The average furrow slope of 0.2% and was divided into two blocks, A and B. Each block had 20V-shaped furrow having a length of 10 m. Three different manure were used to construct these furrows by mixing it with soil which was moderately moist and 5 furrows from each block were constructed without manure. In each block 5furrow were made using a specific type of manure, and one set of five furrows in each block was made without manure treatment. The types of manure that were used were goat manure, pig manure, and manure from crop residuals. The manure application late was 5 kg/m. The furrow was constructed at a spacing of 0.6 m. Tomato was planted in the two blocks at spacing of 0.15 m between rows and 0.15 m between planting stations. Irrigation water was led from feeder canal into the irrigation furrows using siphons. The siphons discharge into each furrow was set at 1.86 L/S. The ¾ rule was used to determine the cut-off time for the irrigation cycles in order to reduce the run-off at the tail end. During each irrigation cycle, samples of the runoff water were collected at one-minute intervals and analyzed for total sediment concentration for use in estimating the total soil sediment loss. The results of the study have shown that a significant amount of soil is lost in soils without many organic matters, there was a low level of erosion in furrows that were constructed using manure treatment within the blocks. In addition, the results have shown that manure also differs in their ability to control erosion since pig manure proved to have greater abilities in binding the soil together than other manure since they were reduction in the amount of sediments at the tail end of furrows constructed by this type of manure. The results prove that manure contains organic matters which helps soil particles to bind together hence resisting the erosive force of water. The use of manure when constructing furrows in soil with less organic matter can highly reduce erosion hence reducing also pollution of water bodies and improve the conditions of aquatic animals.

Keywords: aquatic, erosion, furrow, soil

Procedia PDF Downloads 275

Authors: Amal Hentati, Mbarka Selmi, Tarek Kormi, Julien Baroth, Barthelemy Harthong

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The impact of uncertainties on the performance assessment of shallow foundations is often significant. The need of the geotechnical engineers to a more objective and rigorous description of soil variations permitting to quantify these uncertainties and to incorporate them into calculation methods led to the development of reliability approaches. In this context, a mechanical-reliability coupling was developed in this paper, using a program coded in Matlab and the finite element software Abaqus, for the bearing capacity assessment of shallow foundations. The reliability analysis, based on the finite element method, assumed both soil cohesion and friction angle as uncertain parameters characterized by normal or lognormal probability distributions. The inherent spatial variability of both soil properties was, then, taken into account using 1D stationary random fields. The application of the proposed methodology to a shallow foundation subjected to a centered vertical loading permitted to highlight the proposed process interest. Findings proved the insufficiency of the conventional approach to predict the foundation failure and a high sensitivity of the ultimate loads to the soil properties uncertainties, mainly those related to the friction angle, was noted. Moreover, an asymmetry of both displacement and velocity fields was obtained.

Keywords: mechanical-reliability coupling, finite element method, shallow foundation, random fields, spatial variability

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Authors: Siti Khadijah Che Osmi, Syed Mohd Ahmad

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This paper presents a methodology to develop fragility curves for shallow tunnels so as to describe a relationship between seismic hazard and tunnel vulnerability. Emphasis is given to the influence of surrounding soil material properties because the dynamic behaviour of the tunnel mostly depends on it. Four ground properties of soils ranging from stiff to soft soils are selected. A 3D nonlinear time history analysis is used to evaluate the seismic response of the tunnel when subjected to five real earthquake ground intensities. The derived curves show the future probabilistic performance of the tunnels based on the predicted level of damage states corresponding to the peak ground acceleration. A comparison of the obtained results with the previous literature is provided to validate the reliability of the proposed fragility curves. Results show the significant role of soil properties and input motions in evaluating the seismic performance and response of shallow tunnels.

Keywords: fragility analysis, seismic performance, tunnel lining, vulnerability

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Authors: Kshanaprava Dhalsamant, Punyadarshini P. Tripathy, Shanker L. Shrivastava

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With present high global population, the need for rising food usage by minimizing food wastage and investment is highly necessary to achieve food security. The purpose of this study is to enlighten the effect of pre-drying treatment on rehydration, color, texture, nanohardness, microstructure and surface morphology of solar dried potato samples dried in the mixed-mode solar dryer. Locally bought potatoes were cleaned and cut into cylindrical pieces and pretreated with sodium metabisulfite (0.5%) for 10 min before placing them in natural convection solar dryer designed and developed in Indian Institute of Technology Kharagpur, India. Advanced quality characteristics were studied using Atomic Force Microscope (AFM), Scanning Electron Microscopy (SEM) and nanoindentation method, along with color, texture and water activity. The rehydration indices of solar dried potatoes were significantly biased by pretreatment followed by rehydration temperature. A lower redness index (a*) with a higher value of yellowness index (b*), chroma (C*) and hue angle (h*) were obtained for pretreated samples. Also, the average nanohardness (H) of untreated samples exhibited substantial lower value (18.46%) compared to pretreated samples. Additionally, a creep displacement of 43.27 nm during 20 s dwell time under constant load of 200

Keywords: pretreatment, nanohardness, microstructure, surface morphology

Procedia PDF Downloads 156

Authors: Narjes Ebrahimi, Soheila Alyasin, Navid Nezafat, Hossein Esmailzadeh, Younes Ghasemi, Seyed Hesamodin Nabavizadeh

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Immunotherapy with allergy vaccines is of great importance in allergen-specific immunotherapy. In recent years, B-cell epitope-based vaccines have attracted considerable attention and the prediction of epitopes is crucial to design these types of allergy vaccines. B-cell epitopes might be linear or conformational. The prerequisite for the identification of conformational epitopes is the information about allergens' tertiary structures. Bioinformatics approaches have paved the way towards the design of epitope-based allergy vaccines through the prediction of tertiary structures and epitopes. Mite allergens are one of the major allergy contributors. Several mite allergens can elicit allergic reactions; however, their structures and epitopes are not well established. So, B-cell epitopes of various groups of mite allergens (24 allergens in 6 allergen groups) were predicted in the present work. Tertiary structures of 17 allergens with unknown structure were predicted and refined with RaptorX and GalaxyRefine servers, respectively. The predicted structures were further evaluated by Rampage, ProSA-web, ERRAT and Verify 3D servers. Linear and conformational B-cell epitopes were identified with Ellipro, Bcepred, and DiscoTope 2 servers. To improve the accuracy level, consensus epitopes were selected. Fifty-four conformational and 133 linear consensus epitopes were predicted. Furthermore, overlapping epitopes in each allergen group were defined, following the sequence alignment of the allergens in each group. The predicted epitopes were also compared with the experimentally identified epitopes. The presented results provide valuable information for further studies about allergy vaccine design.

Keywords: B-cell epitope, Immunotherapy, In silico prediction, Mite allergens, Tertiary structure

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Authors: Nieves M. C. Talavera-Prieto, Abel G. M. Ferreira, António T. G. Portugal, Rui J. Moreira, Jaime B. Santos

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The knowledge of biodiesel density over large ranges of temperature and pressure is important for predicting the behavior of fuel injection and combustion systems in diesel engines, and for the optimization of such systems. In this study, cottonseed oil was transesterified into biodiesel and its density was measured at temperatures between 288 K and 358 K and pressures between 0.1 MPa and 30 MPa, with expanded uncertainty estimated as ±1.6 kg.m^-3. Experimental pressure-volume-temperature (pVT) cottonseed data was used along with literature data relative to other 18 biodiesels, in order to build a database used to test the correlation of density with temperarure and pressure using the Goharshadi–Morsali–Abbaspour equation of state (GMA EoS). To our knowledge, this is the first that density measurements are presented for cottonseed biodiesel under such high pressures, and the GMA EoS used to model biodiesel density. The new tested EoS allowed correlations within 0.2 kg•m-3 corresponding to average relative deviations within 0.02%. The built database was used to develop and test a new full predictive model derived from the observed linear relation between density and degree of unsaturation (DU), which depended from biodiesel FAMEs profile. The average density deviation of this method was only about 3 kg.m-3 within the temperature and pressure limits of application. These results represent appreciable improvements in the context of density prediction at high pressure when compared with other equations of state.

Keywords: biodiesel density, correlation, equation of state, prediction

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Authors: A. Brahma

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Analysis of deferred deformations of concrete under sustained load shows that the creep has a leading role on deferred deformations of concrete structures. Knowledge of the creep characteristics of concrete is a Necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable deformation in pre-stressed concrete or reinforced and the appropriate steps can be taken in design to accommodate this movement. In this study, we propose a prediction model that involves the acting principal parameters on the deferred behaviour of concrete structures. For the estimation of the model parameters Levenberg-Marquardt method has proven very satisfactory. A confrontation between the experimental results and the predictions of models designed shows that it is well suited to describe the evolution of the creep of concrete structures.

Keywords: concrete structure, creep, modelling, prediction

Procedia PDF Downloads 282

Authors: Mir Md. Abdus Salam, Muhammad Mohsin, Pertti Pulkkinen, Paavo Pelkonen, Ari Pappinen

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Soil and water pollution caused by extensive mining practices can adversely affect environmental components, such as humans, animals, and plants. Despite a generally positive contribution to society, mining practices have become a serious threat to biological systems. As metals do not degrade completely, they require immobilization, toxicity reduction, or removal. A greenhouse experiment was conducted to evaluate the effects of lime and N100 (11-amino-1-hydroxyundecylidene) chelate amendment on the growth and phytoextraction potential of the willow variety Klara (S. viminalis × S. schwerinii × S. dasyclados) grown in soils heavily contaminated with copper (Cu). The plants were irrigated with tap or processed water (mine wastewater). The sequential extraction technique and inductively coupled plasma-mass spectrometry (ICP-MS) tool were used to determine the extractable metals and evaluate the fraction of metals in the soil that could be potentially available for plant uptake. The results suggest that the combined effects of the contaminated soil and processed water inhibited growth parameter values. In contrast, the accumulation of Cu in the plant tissues was increased compared to the control. When the soil was supplemented with lime and N100; growth parameter and resistance capacity were significantly higher compared to unamended soil treatments, especially in the contaminated soil treatments. The combined lime- and N100-amended soil treatment produced higher growth rate of biomass, resistance capacity and phytoextraction efficiency levels relative to either the lime-amended or the N100-amended soil treatments. This study provides practical evidence of the efficient chelate-assisted phytoextraction capability of Klara and highlights its potential as a viable and inexpensive novel approach for in-situ remediation of Cu-contaminated soils and mine wastewaters. Abandoned agricultural, industrial and mining sites can also be utilized by a Salix afforestation program without conflict with the production of food crops. This kind of program may create opportunities for bioenergy production and economic development, but contamination levels should be examined before bioenergy products are used.

Keywords: copper, Klara, lime, N100, phytoextraction

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Authors: Ayodele A. Otaiku

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Purpose: Nigeria has become the largest importer of rice in Africa and second in the world, 2015. Investigate interactions of organic rice farming on soil quality and health from bio-waste converted to biofertilizer and its environmental impact on rice crop. Methodology: Bio-wastes, poultry waste, organic agriculture wastes, wood ash mixed with microbial inoculant organisms called OBD-Plus microbes (broad spectrum) composted in anaerobic digester to OBD-biofertilizer (2010 - 2012) uses microbes to build humus and other stable carbons. Two field experiments were carried out at Badeggi, Niger state in 2011 and 2012 to evaluate the response of lowland rice production using biofertilizer. The experimental field was laid out in a strip-plot design with five treatments and three replications and at twenty-one day old seedlings of FARO 44 and FARO 52 rice varieties were transplanted. Plots without fertiliser application served as control. Findings: The highest rice grain yield increase of 4.4 t/ha over the control in 2012 against the Nigeria average of lowland rice grain yields of 1.5 t/ha. The utilization of OBD-Biofertilizer can decrease the use of chemical nitrogen fertilizer, prevent the depletion of soil organic matter and reduce environmental pollution. Increasing the floodwater productivity and optimizing the recycling of nutrients cum grazer populations and disease by biocontrols microbes present in the OBD-Biofertilizer. Organic matter in the soil improves by 58% and C/N 15 (2011) and 13.35 (2012). Implications: OBD- Biofertilizer produce plant growth hormones such as indole acetic acid (IAA), glomalin related soil protein and extracellular enzymes as phosphatases that promote soil health and quality. Conclusion: Microorganisms can enhance nutrients use efficiency by increasing root surface area e.g., mycorrhizal, fungi, promoting other beneficial symbioses of the host plant and microbial interactions resulting to increase in soil organic matter. By 2030, climate change is projected to depress cereal production in Africa by 2 to 3 percent. Improved seeds and increased fertilizer use should more than compensate, but this factor will still weigh heavily on efforts to make progress.

Keywords: OBD-plus microbial consortia, OBD-biofertilizer, rice production, soil quality, sustainable agriculture

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Authors: Wei Tian, Jie Liang, Hammad Naveed

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Beta-barrel membrane proteins are found in the outer membrane of gram-negative bacteria, mitochondria, and chloroplasts. They carry out diverse biological functions, including pore formation, membrane anchoring, enzyme activity, and bacterial virulence. In addition, beta-barrel membrane proteins increasingly serve as scaffolds for bacterial surface display and nanopore-based DNA sequencing. Due to difficulties in experimental structure determination, they are sparsely represented in the protein structure databank and computational methods can help to understand their biophysical principles. We have developed a novel computational method to predict the 3D structure of beta-barrel membrane proteins using evolutionary coupling (EC) constraints and a reduced state space. Combined with an empirical potential function, we can successfully predict strand register at > 80% accuracy for a set of 49 non-homologous proteins with known structures. This is a significant improvement from previous results using EC alone (44%) and using empirical potential function alone (73%). Our method is general and can be applied to genome-wide structural prediction.

Keywords: beta-barrel membrane proteins, structure prediction, evolutionary constraints, reduced state space

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Authors: Tauha Hussain Ali, Shabir Hussain Khahro, Nafees Ahmed Memon

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Accurate prediction of project time for planning and bid preparation stage should contain realistic dates. Constructors use their experience to estimate the project duration for the new projects, which is based on intuitions. It has been a constant concern to both researchers and constructors to analyze the accurate prediction of project duration for bid preparation stage. In Pakistan, such study for time cost relationship has been lacked to predict duration performance for the construction projects. This study is an attempt to explore the time cost relationship that would conclude with a mathematical model to predict the time for the drainage rehabilitation projects in the province of Sindh, Pakistan. The data has been collected from National Engineering Services (NESPAK), Pakistan and regression analysis has been carried out for the analysis of results. Significant relationship has been found between time and cost of the construction projects in Sindh and the generated mathematical model can be used by the constructors to predict the project duration for the upcoming projects of same nature. This study also provides the professionals with a requisite knowledge to make decisions regarding project duration, which is significantly important to win the projects at the bid stage.

Keywords: BTC Model, project time, relationship of time cost, regression

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Authors: S. N. Moghaddas Tafreshi, S. M. Amin Ghotbi

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This paper presents a numerical study for investigating the effectiveness of geocell reinforcement in reducing pressure and settlement over EPS geofoam blocks in road embankments. A 3-D FEM model of soil and geofoam was created in ABAQUS, and geocell was also modeled realistically using membrane elements. The accuracy of the model was tested by comparing its results with previous works. Sensitivity analyses showed that reinforcing the soil cover with geocell has a significant influence on the reduction of imposed stresses over geofoam and consequently decreasing its deformation.

Keywords: EPS geofoam, geocell, reinforcement, road embankments, lightweight fill

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Authors: Gul Muhammad, Amanullah Marri, Asif Abbas

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Thermal treatment changes the physical and mechanical properties of clayey soils. Thermally treated soils have been used since ancient times for making trails for access and bricks for residence. In this study, it has been focused to observe and analyze the effect of baking (burning) temperature on the mechanical properties of clayey soils usually used for the construction of adobe houses in the rural areas of many of the developing countries. In the first stage of experimental work, a series of tests on clayey soil moulds (100 mm height and 50 mm diameter in size) added different percentages of lime and wheat straw (typically 2%, 4%, 6%, 8%, and 10%) were conducted. In the second stage; samples were made of clayey soils and were subjected to six level of temperatures i.e., 25, 100, 200, 300, 400, and 500⁰C. In the third stage, the moulds of clayey soil were submerged in water prior to testing in order to investigate the flood resilience of the moulds prepared with and without the addition of lime and wheat straw. The experimental results suggest that samples with 6% of lime content and on 2% of wheat straw contents have shown the maximum value of compressive strength. The effect of baking temperature on the clayey soils has shown that maximum UCS is obtained at 200⁰C. The results also suggest reinforcement with 2% wheat straw, give 70.8% increase in the compressive strength compared to soil only, whereas the flooding resilience can be better resist by adding 6% lime and 2% wheat straw.

Keywords: baked temperature, submersion, lime, uniaxial, wheat straw

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Authors: Ahmed Hosny Abdel-Rahman, Mohamed Abdel-Moneim

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Reinforced earth structures are generally subjected to cyclic loading generated from earthquakes. This paper presents a summary of the results and analyses of a testing program carried out in a large-scale multi-function geosynthetic testing apparatus that accommodates soil samples up to 1.0 m3. This apparatus performs different shear and pullout tests under both static and cyclic loading. The testing program was carried out to investigate the controlling factors affecting soil/geogrid interaction under cyclic loading. The extensibility of the geogrids, the applied normal stresses, the characteristics of the cyclic loading (frequency, and amplitude), and initial static load within the geogrid sheet were considered in the testing program. Based on the findings of the testing program, the effect of these parameters on the pullout resistance of geogrids, as well as the displacement mobility under cyclic loading were evaluated. Conclusions and recommendations for the design of reinforced earth walls under cyclic loading are presented.

Keywords: geogrid, soil, interface, cyclic loading, pullout, large scale testing

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Authors: Fu Jia

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The effects of soil-structure interaction (SSI) are often studied using axial-symmetric three-dimensional (3D) models to avoid the high computational cost of the more realistic, fully 3D models, which require 2-3 orders of magnitude more computer time and storage. This paper analyzes the error and presents correction factors for system frequency, system damping, and peak amplitude of structural response computed by axisymmetric models, embedded in uniform or layered half-space. The results are compared with those for fully 3D rectangular foundations of different aspect ratios. Correction factors are presented for a range of the model parameters, such as fixed-base frequency, structure mass, height and length-to-width ratio, foundation embedment, soil-layer stiffness and thickness. It is shown that the errors are larger for stiffer, taller and heavier structures, deeper foundations and deeper soil layer. For example, for a stiff structure like Millikan Library (NS response; length-to-width ratio 1), the error is 6.5% in system frequency, 49% in system damping and 180% in peak amplitude. Analysis of a case study shows that the NEHRP-2015 provisions for reduction of base shear force due to SSI effects may be unsafe for some structures and need revision. The presented correction factor diagrams can be used in practical design and other applications.

Keywords: 3D soil-structure interaction, correction factors for axisymmetric models, length-to-width ratio, NEHRP-2015 provisions for reduction of base shear force, rectangular embedded foundations, SSI system frequency, SSI system damping

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Authors: Marjan Golmaryami, Marzieh Behzadi

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Recent developments in stock exchange highlight the need for an efficient and accurate method that helps stockholders make better decision. Since stock markets have lots of fluctuations during the time and different effective parameters, it is difficult to make good decisions. The purpose of this study is to employ artificial neural network (ANN) which can deal with time series data and nonlinear relation among variables to forecast next day stock price. Unlike other evolutionary algorithms which were utilized in stock exchange prediction, we trained our proposed neural network with metaheuristic bat algorithm, with fast and powerful convergence and applied it in stock price prediction for the first time. In order to prove the performance of the proposed method, this research selected a 7 year dataset from Parsian Bank stocks and after imposing data preprocessing, used 3 types of ANN (back propagation-ANN, particle swarm optimization-ANN and bat-ANN) to predict the closed price of stocks. Afterwards, this study engaged MATLAB to simulate 3 types of ANN, with the scoring target of mean absolute percentage error (MAPE). The results may be adapted to other companies stocks too.

Keywords: artificial neural network (ANN), bat algorithm, particle swarm optimization algorithm (PSO), stock exchange

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Authors: Rosdyana Mangir Irawan Kusuma, Wei-Chun Kao, Ho-Thi Trang, Yu-Yen Ou, Kai-Lung Hua

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Stock market prediction is still a challenging problem because there are many factors that affect the stock market price such as company news and performance, industry performance, investor sentiment, social media sentiment, and economic factors. This work explores the predictability in the stock market using deep convolutional network and candlestick charts. The outcome is utilized to design a decision support framework that can be used by traders to provide suggested indications of future stock price direction. We perform this work using various types of neural networks like convolutional neural network, residual network and visual geometry group network. From stock market historical data, we converted it to candlestick charts. Finally, these candlestick charts will be feed as input for training a convolutional neural network model. This convolutional neural network model will help us to analyze the patterns inside the candlestick chart and predict the future movements of the stock market. The effectiveness of our method is evaluated in stock market prediction with promising results; 92.2% and 92.1 % accuracy for Taiwan and Indonesian stock market dataset respectively.

Keywords: candlestick chart, deep learning, neural network, stock market prediction

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Authors: Nurdan Olguncelik Kaplan, Aysen Akay

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Nowadays soil pollution has become a global problem. External added polluters to the soil are destroying and changing the structure of the soil and the problems are becoming more complex and in this sense the correction of these problems is going to be harder and more costly. Cadmium has got a fast mobility in the soil and plant system because of that cadmium can interfere very easily to the human and animal food chain and in the same time this can be very dangerous. The cadmium which is absorbed and stored by the plants is causing to many metabolic changes of the plants like; protein synthesis, nitrogen and carbohydrate metabolism, enzyme (nitrate reductase) activation, photo and chlorophyll synthesis. The biological function of cadmium is not known over the plants and it is not a necessary element. The plant is generally taking in small amounts the cadmium and this element is competing with the zinc. Cadmium is causing root damages. Buckwheat (Fagopyrum esculentum) is an important nutraceutical because of its high content of flavonoids, minerals and vitamins, and their nutritionally balanced amino-acid composition. Buckwheat has relatively high biomass productivity, is adapted to many areas of the world, and can flourish in sterile fields; therefore buckwheat plants are widely used for the phytoremediation process.The aim of this study were to evaluate the phytoremediation capacity of the high-yielding plant Buckwheat (Fagopyrum esculentum) in soils contaminated with Cd and Zn. The soils were applied to differrent doses cd(0-12.5-25-50-100 mg Cd kg−1 soil in the form of 3CdSO4.8H2O ) and Zn (0-10-30 mg Zn kg−1 soil in the form of ZnSO4.7H2O) and incubated about 60 days. Later buckwheat seeds were sown and grown for three mounth under greenhouse conditions. The test plants were irrigated by using pure water after the planting process. Buckwheat seeds (Gunes and Aktas species) were taken from Bahri Dagdas International Agricultural Research. After harvest, Cd and Zn concentrations of plant biomass and grain, yield and translocation factors (TFs) for Cd and Cd were determined. Cadmium accumulation in biomass and grain significantly increased in dose-dependent manner. Long term field trials are required to further investigate the potential of buckwheat to reclaimed the soil. But this could be undertaken in conjunction with actual remediation schemes. However, the differences in element accumulation among the genotypes were affected more by the properties of genotypes than by the soil properties. Gunes genotype accumulated higher lead than Aktas genotypes.

Keywords: buckwheat, cadmium, phytoremediation, zinc

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Authors: Seyed Abolhasan Naeini, Javad Shamsi Soosahab

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The use of geosynthetic reinforcement within the footing soils is a very effective and useful method to avoid the construction of costly deep foundations. This study investigated the use of geosynthetics for soil improvement based on numerical modeling using FELA software. Pressure settlement behavior and bearing capacity ratio of foundation on geogrid reinforced sand is investigated and the effect of different parameters like as number of geogrid layers and vertical distance between elements in three different relative density soil is studied. The effects of geometrical parameters of reinforcement layers were studied for determining the optimal values to reach to maximum bearing capacity. The results indicated that the optimum range of the distance ratio between the reinforcement layers was achieved at 0.5 to 0.6 and after number of geogrid layers of 4, no significant effect on increasing the bearing capacity of footing on reinforced sandy with geogrid

Keywords: geogrid, reinforced sand, FELA software, distance ratio, number of geogrid layers

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Authors: Abadi Berhane, Walelign Worku, Berhanu Abrha, Gebre Hadgu

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Sesame is an important oilseed crop in Ethiopia, which is the second most exported agricultural commodity next to coffee. However, there is poor soil fertility management and a research-led farming system for the crop. The AquaCrop model was applied as a decision-support tool, which performs a semi-quantitative approach to simulate the yield of crops under different soil fertility levels. The objective of this experiment was to calibrate and validate the AquaCrop model for simulating the growth and yield of sesame under different nitrogen fertilizer levels and to test the performance of the model as a decision-support tool for improved sesame cultivation in the study area. The experiment was laid out as a randomized complete block design (RCBD) in a factorial arrangement in the 2016, 2017, and 2018 main cropping seasons. In this experiment, four nitrogen fertilizer rates, 0, 23, 46, and 69 Kg/ha nitrogen, and three improved varieties (Setit-1, Setit-2, and Humera-1). In the meantime, growth, yield, and yield components of sesame were collected from each treatment. Coefficient of determination (R2), Root mean square error (RMSE), Normalized root mean square error (N-RMSE), Model efficiency (E), and Degree of agreement (D) were used to test the performance of the model. The results indicated that the AquaCrop model successfully simulated soil water content with R2 varying from 0.92 to 0.98, RMSE 6.5 to 13.9 mm, E 0.78 to 0.94, and D 0.95 to 0.99, and the corresponding values for AB also varied from 0.92 to 0.98, 0.33 to 0.54 tons/ha, 0.74 to 0.93, and 0.9 to 0.98, respectively. The results on the canopy cover of sesame also showed that the model acceptably simulated canopy cover with R2 varying from 0.95 to 0.99 and a RMSE of 5.3 to 8.6%. The AquaCrop model was appropriately calibrated to simulate soil water content, canopy cover, aboveground biomass, and sesame yield; the results indicated that the model adequately simulated the growth and yield of sesame under the different nitrogen fertilizer levels. The AquaCrop model might be an important tool for improved soil fertility management and yield enhancement strategies of sesame. Hence, the model might be applied as a decision-support tool in soil fertility management in sesame production.

Keywords: aquacrop model, normalized water productivity, nitrogen fertilizer, canopy cover, sesame

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Authors: Pramod Kumar Sharma, Pratibha Kumari, Udai Pratap Singh, Sustainability

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In the Indo-Gangetic Plains of South-East Asia, the rice-wheat cropping system (RWCS) is dominant with conventional tillage (CT) without residue management, which shows depletion of soil fertility and non-sustainable crop productivity. Hence, this investigation was planned to identify suitable natural resource management practices involving different tillage and crop establishment (TCE) methods along with crop residue and their effects, on the sustainability of dominant cropping systems through enhancing soil fertility and productivity. This study was conducted for two consecutive years 2018-19 and 2019-20 on a long-term field experiment that was started in the year 2015-16 taking six different combinations of TCE methods viz. CT, partial conservation agriculture (PCA) i.e. anchored residue of rice and full conservation agriculture (FCA)] i.e. anchored residue of rice and wheat under RWCS in terms of crop productivity, sustainability of soil health, and crop nutrition by the crops. Results showed that zero tillage direct-seeded rice (ZTDSR) - zero tillage wheat (ZTW) [FCA + green gram residue retention (RR)] recorded the highest yield attributes and yield during both the crops. Compared to conventional tillage rice (CTR)-conventional tillage wheat (CTW) [residue removal (R 0 )], the soil quality parameters were improved significantly with ZTDSR-ZTW (FCA+RR). Overall, ZTDSR-ZTW (FCA+RR) had higher nutrient uptake by the crops than CT-based treatment CTR-CTW (R 0 ) and CTR-CTW (RI).These results showed that there is significant profitability of yield and resource utilization by the adoption of FCA it may be a better alternative to the dominant tillage system i.e. CT in RWSC.

Keywords: tillage and crop establishment, soil fertility, rice-wheat cropping system, sustainability

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Authors: Ekrem Canli, Thomas Glade

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The precise prediction of rainfall in space and time is a key element to most landslide early warning systems. Unfortunately, the spatial variability of rainfall in many early warning applications is often disregarded. A common simplification is to use uniformly distributed rainfall to characterize aerial rainfall intensity. With spatially differentiated rainfall information, real-time comparison with rainfall thresholds or the implementation in process-based approaches might form the basis for improved landslide warnings. This study suggests an automated workflow from the hourly, web-based collection of rain gauge data to the generation of spatially differentiated rainfall predictions based on kriging. Because the application of kriging is usually a labor intensive task, a simplified and consequently automated variogram modeling procedure was applied to up-to-date rainfall data. The entire workflow was carried out purely with open source technology. Validation results, albeit promising, pointed out the challenges that are involved in pure distance based, automated geostatistical interpolation techniques for ever-changing environmental phenomena over short temporal and spatial extent.

Keywords: kriging, landslide early warning system, spatial rainfall prediction, variogram modelling, web scraping

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Authors: Umit Duru

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The Soil and Water Assessment Tool (SWAT) was tested for prediction of water balance and sediment yield in the Ankara gauged basin, Turkey. The overall objective of this study was to evaluate the performance and applicability of the SWAT in this region of Turkey. Thirteen years of monthly stream flow, and suspended sediment, data were used for calibration and validation. This research assessed model performance based on differences between observed and predicted suspended sediment yield during calibration (1987-1996) and validation (1982-1984) periods. Statistical comparisons of suspended sediment produced values for NSE (Nash Sutcliffe efficiency), RE (relative error), and R² (coefficient of determination), of 0.81, -1.55, and 0.93, respectively, during the calibration period, and NSE, RE (%), and R² of 0.77, -2.61, and 0.87, respectively, during the validation period. Based on the analyses, SWAT satisfactorily simulated observed hydrology and sediment yields and can be used as a tool in decision making for water resources planning and management in the basin.

Keywords: calibration, GIS, sediment yield, SWAT, validation

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Authors: Melik Kara, Gulsah Tulger Kara

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The soil is a crucial component of the ecosystem, and in industrial and urban areas it receives large amounts of trace elements from several sources. Therefore, accumulated pollutants in surface soils can be transported to different environmental components, such as deep soil, water, plants, and dust particles. While elemental contamination of soils is caused mainly by atmospheric deposition, soil also affects the air quality since enriched trace elemental contents in atmospheric particulate matter originate from resuspension of polluted soils. The objectives of this study were to determine the total and leachate concentrations of trace elements in soils of city area in Izmir and characterize their spatial distribution and to identify the possible sources of trace elements in surface soils. The surface soil samples were collected from 20 sites. They were analyzed for total element concentrations and leachate concentrations. Analyses of trace elements (Ag, Al, As, B, Ba, Be, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Er, Eu, Fe, Ga, Gd, Hf, Ho, K, La, Li, Lu, Mg, Mn, Mo, Na, Nd, Ni, P, Pb, Pr, Rb, Sb, Sc, Se, Si, Sm, Sn, Sr, Tb, Th, Ti, Tl, Tm, U, V, W, Y, Yb, Zn and Zr) were carried out using ICP-MS (Inductively Coupled Plasma-Mass Spectrometer). The elemental concentrations were calculated along with overall median, kurtosis, and skewness statistics. Elemental composition indicated that the soil samples were dominated by crustal elements such as Si, Al, Fe, Ca, K, Mg and the sea salt element, Na which is typical for Aegean region. These elements were followed by Ti, P, Mn, Ba and Sr. On the other hand, Zn, Cr, V, Pb, Cu, and Ni (which are anthropogenic based elements) were measured as 61.6, 39.4, 37.9, 26.9, 22.4, and 19.4 mg/kg dw, respectively. The leachate element concentrations were showed similar sorting although their concentrations were much lower than total concentrations. In the study area, the spatial distribution patterns of elemental concentrations varied among sampling sites. The highest concentrations were measured in the vicinity of industrial areas and main roads. To determine the relationships among elements and to identify the possible sources, PCA (Principal Component Analysis) was applied to the data. The analysis resulted in six factors. The first factor exhibited high loadings of Co, K, Mn, Rb, V, Al, Fe, Ni, Ga, Se, and Cr. This factor could be interpreted as residential heating because of Co, K, Rb, and Se. The second factor associated positively with V, Al, Fe, Na, Ba, Ga, Sr, Ti, Se, and Si. Therefore, this factor presents mixed city dust. The third factor showed high loadings with Fe, Ni, Sb, As, Cr. This factor could be associated with industrial facilities. The fourth factor associated with Cu, Mo, Zn, Sn which are the marker elements of traffic. The fifth factor presents crustal dust, due to its high correlation with Si, Ca, and Mg. The last factor is loaded with Pb and Cd emitted from industrial activities.

Keywords: trace elements, surface soil, source apportionment, Izmir

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Authors: Nzereogu Stella Kosi, Igwe Ogbonnaya, Emeh Chukwuebuka Odinaka

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A comparative analysis of the expansion rate and soil erodibility of some gullies in Nnewi and Nnobi both of Nanka Formation were studied. The study involved an integration of field observations, geotechnical analysis, slope stability analysis, multivariate statistical analysis, gully expansion rate analysis, and determination of the soil erodibility factor (K) from Revised Universal Soil Loss Equation (RUSLE). Fifteen representative gullies were studied extensively, and results reveal that the geotechnical properties of the soil, topography, vegetation cover, rainfall intensity, and the anthropogenic activities in the study area were major factors propagating and influencing the erodibility of the soils. The specific gravity of the soils ranged from 2.45-2.66 and 2.54-2.78 for Nnewi and Nnobi, respectively. Grain size distribution analysis revealed that the soils are composed of gravel (5.77-17.67%), sand (79.90-91.01%), and fines (2.36-4.05%) for Nnewi and gravel (7.01-13.65%), sand (82.47-88.67%), and fines (3.78-5.02%) for Nnobi. The soils are moderately permeable with values ranging from 2.92 x 10-5 - 6.80 x 10-4 m/sec and 2.35 x 10-6 - 3.84 x 10⁻⁴m/sec for Nnewi and Nnobi respectively. All have low cohesion values ranging from 1–5kPa and 2-5kPa and internal friction angle ranging from 29-38° and 30-34° for Nnewi and Nnobi, respectively, which suggests that the soils have low shear strength and are susceptible to shear failure. Furthermore, the compaction test revealed that the soils were loose and easily erodible with values of maximum dry density (MDD) and optimum moisture content (OMC) ranging from 1.82-2.11g/cm³ and 8.20-17.81% for Nnewi and 1.98-2.13g/cm³ and 6.00-17.80% respectively. The plasticity index (PI) of the fines showed that they are nonplastic to low plastic soils and highly liquefiable with values ranging from 0-10% and 0-9% for Nnewi and Nnobi, respectively. Multivariate statistical analyses were used to establish relationship among the determined parameters. Slope stability analysis gave factor of safety (FoS) values in the range of 0.50-0.76 and 0.82-0.95 for saturated condition and 0.73-0.98 and 0.87-1.04 for unsaturated condition for both Nnewi and Nnobi, respectively indicating that the slopes are generally unstable to critically stable. The erosion expansion rate analysis for a fifteen-year period (2005-2020) revealed an average longitudinal expansion rate of 36.05m/yr, 10.76m/yr, and 183m/yr for Nnewi, Nnobi, and Nanka type gullies, respectively. The soil erodibility factor (K) are 8.57x10⁻² and 1.62x10-4 for Nnewi and Nnobi, respectively, indicating that the soils in Nnewi have higher erodibility potentials than those of Nnobi. From the study, both the Nnewi and Nnobi areas are highly prone to erosion. However, based on the relatively lower fine content of the soil, relatively lower topography, steeper slope angle, and sparsely vegetated terrain in Nnewi, soil erodibility and gully intensity are more profound in Nnewi than Nnobi.

Keywords: soil erodibility, gully expansion, nnewi-nnobi, slope stability, factor of safety

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Authors: Zhaopeng Zhu, Xianzhi Song, Gensheng Li, Shuo Zhu, Shiming Duan, Xuezhe Yao

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Accurate calculation of wellbore pressure is of great significance to prevent wellbore risk during drilling. The traditional mechanism model needs a lot of iterative solving procedures in the calculation process, which reduces the calculation efficiency and is difficult to meet the demand of dynamic control of wellbore pressure. In recent years, many scholars have introduced artificial intelligence algorithms into wellbore pressure calculation, which significantly improves the calculation efficiency and accuracy of wellbore pressure. However, due to the ‘black box’ property of intelligent algorithm, the existing intelligent calculation model of wellbore pressure is difficult to play a role outside the scope of training data and overreacts to data noise, often resulting in abnormal calculation results. In this study, the multi-phase flow mechanism is embedded into the objective function of the neural network model as a constraint condition, and an intelligent prediction model of wellbore pressure under the constraint condition is established based on more than 400,000 sets of pressure measurement while drilling (MPD) data. The constraint of the multi-phase flow mechanism makes the prediction results of the neural network model more consistent with the distribution law of wellbore pressure, which overcomes the black-box attribute of the neural network model to some extent. The main performance is that the accuracy of the independent test data set is further improved, and the abnormal calculation values basically disappear. This method is a prediction method driven by MPD data and multi-phase flow mechanism, and it is the main way to predict wellbore pressure accurately and efficiently in the future.

Keywords: multiphase flow mechanism, pressure while drilling data, wellbore pressure, mechanism constraints, combined drive

Procedia PDF Downloads 163

Authors: Noé D. Lazos-Gallardo, Sonia E. Ruiz, Federico Valenzuela-Beltran

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A simplified mathematical expression to estimate ductility reduction factors of the displacement spectra corresponding to the soft soil zone of Mexico City is proposed. The aim is to allow a better characterization of the displacement spectra and provide a simple expression to be used in displacement based design (DBD). Emphasis is on the Mexico City Building Code. The study is based on the analysis of single degree of freedom (SDOF) systems with elasto-plastic hysteretic behavior. Several seismic ground motions corresponding to subduction events with magnitudes equal to or greater than 6 and recorded in different stations of Mexico City are used. The proposed expression involves the ratio of elastic and inelastic pseudo-aceleration spectra, and depends on factors such the ductility demand and the vibration period of the structural system. The resulting ductility reduction factors obtained in this study are compared with others existing in the literature, and their advantages and disadvantages are discussed.

Keywords: displacement based design, displacements spectrum, ductility reduction factors, soft soil

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Authors: Adekunle Taiwo Adenike, I. K. Ogundoyin

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Lassa fever is a neglected tropical virus that has become a significant public health issue in Nigeria, with the country having the greatest burden in Africa. This paper presents a Geo-Computational Model for Analysis and Prediction of Lassa Fever Dynamics and Outbreaks in Nigeria. The model investigates the dynamics of the virus with respect to environmental factors and human populations. It confirms the role of the rodent host in virus transmission and identifies how climate and human population are affected. The proposed methodology is carried out on a Linux operating system using the OSGeoLive virtual machine for geographical computing, which serves as a base for spatial ecology computing. The model design uses Unified Modeling Language (UML), and the performance evaluation uses machine learning algorithms such as random forest, fuzzy logic, and neural networks. The study aims to contribute to the control of Lassa fever, which is achievable through the combined efforts of public health professionals and geocomputational and machine learning tools. The research findings will potentially be more readily accepted and utilized by decision-makers for the attainment of Lassa fever elimination.

Keywords: geo-computational model, lassa fever dynamics, lassa fever, outbreak prediction, nigeria

Procedia PDF Downloads 79

Authors: Bencheikh Messaouda, Aidoud Assia, Salima Boukour, Benamara Fatima Zohra, Boukhatem Ghania, Zegueur Chaouki Salah Eddine

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The utilization of waste materials in civil engineering has gained widespread attention in recent years due to their adverse effects on the environment. One such waste material is coffee grounds, a black residue generated daily across the country after coffee brewing. Instead of disposing of it, there is a growing interest in repurposing it for various agricultural and industrial applications. Utilizing coffee grounds in geotechnical engineering, such as in road embankments, presents an opportunity for its valorization. The study aims to contribute to the valorization of coffee grounds by enhancing the physical and mechanical properties of clayey soils through their incorporation at varying weight percentages (3%, 6%, 9%, 12%) as partial replacements in these soils. This not only addresses the issue of coffee ground waste but also makes a tangible contribution to sustainable development. The findings demonstrate that incorporating coffee grounds generally has positive effects on the physical and mechanical properties of clayey soil. However, the extent of these effects depends on factors such as the quantity of coffee grounds added, the particle size of the grounds, and the characteristics of the soil. Additionally, coffee grounds can improve the compression and tensile strength of clayey soil, resulting in increased stability and reduced susceptibility to deformation under external forces.

Keywords: clay soil, coffee grounds, optimizing, improvement, valorization, waste

Procedia PDF Downloads 30