Search results for: soil classification

Authors: Ismail Akkaya, Mucip Tapan, Ali Ozvan

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Some of the industrially prefabricated buildings located on clayey soils were damaged due to soil conditions. The reasons of these damages are generally due to different settlement capacity, the different plasticity of soils and the level of ground water. The aim of this study is to determine the source of these building damages by conducting in situ tests. Therefore, pressuremeter test, which is one of the borehole loading test conducted to determine the properties of soils under the foundations and Standart Penetration Test (SPT). The results of these two field tests were then used to accurately obtain the consistency and firmness of soils. Pressuremeter Deformation Module (EM) and Net Limiting Pressure (PL) of soils were calculated after the pressuremeter tests. These values were then compared with the SPT (N30) and SPT (N60) results. An empirical equation was developed to obtain EM and PL values of such soils from SPT test results. These values were then used to calculate soil bearing capacity as well as the soil settlement. Finally, the relationship between the foundation settlement and the damage of these buildings were checked. It was found that calculated settlement values were almost the same as measured settlement values.

Keywords: damaged building, pressuremeter, standard penetration test, low and high plasticity clay

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Authors: Ruchika Malhotra, Megha Khanna

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The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.

Keywords: change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics

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Authors: Jann-Eike Saathoff, Kirill Alexander Schmoor, Martin Achmus, Mauricio Terceros

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By using partial factors of safety, uncertainties due to the inherent variability of the soil properties and loads are taken into account in the geotechnical design process. According to the reliability index concept in Eurocode-0 in conjunction with Eurocode-7 a minimum safety level of β = 3.8 for reliability class RC2 shall be established. The reliability of the system depends heavily on the choice of the prespecified safety factor and the choice of the characteristic soil properties. The safety factors stated in the standards are mainly based on experience. However, no general accepted method for the calculation of a characteristic value within the current design practice exists. In this study, a laterally loaded monopile is investigated and the influence of the chosen quantile values of the deterministic system, calculated with p-y springs, will be presented. Monopiles are the most common foundation concepts for offshore wind energy converters. Based on the calculations for non-cohesive soils, a recommendation for an appropriate quantile value for the necessary safety level according to the standards for a deterministic design is given.

Keywords: asymptotic sampling, characteristic value, monopile foundation, probabilistic design, quantile values

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Authors: Levent Basayigit, Sinan Demir, Burhan Kara, Yusuf Ucar

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Cannabis is mostly used for drug production. In some countries, an excessive amount of illegal cannabis is cultivated and sold. Most of the illegal cannabis cultivation occurs on the lands far from settlements. In farmlands, it is cultivated with other crops. In this method, cannabis is surrounded by tall plants like corn and sunflower. It is also cultivated with tall crops as the mixed culture. The common method of the determination of the illegal cultivation areas is to investigate the information obtained from people. This method is not sufficient for the determination of illegal cultivation in remote areas. For this reason, more effective methods are needed for the determination of illegal cultivation. Remote Sensing is one of the most important technologies to monitor the plant growth on the land. The aim of this study is to monitor cannabis cultivation area using satellite imagery. The main purpose of this study was to develop an applicable method for monitoring the cannabis cultivation. For this purpose, cannabis was grown as single or surrounded by the corn and sunflower in plots. The morphological characteristics of cannabis were recorded two times per month during the vegetation period. The spectral signature library was created with the spectroradiometer. The parcels were monitored with high-resolution satellite imagery. With the processing of satellite imagery, the cultivation areas of cannabis were classified. To separate the Cannabis plots from the other plants, the multiresolution segmentation algorithm was found to be the most successful for classification. WorldView Improved Vegetative Index (WV-VI) classification was the most accurate method for monitoring the plant density. As a result, an object-based classification method and vegetation indices were sufficient for monitoring the cannabis cultivation in multi-temporal Earthwiev images.

Keywords: Cannabis, drug, remote sensing, object-based classification

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Authors: Lily Ingsrisawang, Tasanee Nacharoen

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Introduction: The problems of unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many research papers found that the performance of existing classifier tends to be biased towards the majority class. The k -nearest neighbors’ nonparametric discriminant analysis is one method that was proposed for classifying unbalanced classes with good performance. Hence, the methods of discriminant analysis are of interest to us in investigating misclassification error rates for class-imbalanced data of three diabetes risk groups. Objective: The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification application of class-imbalanced data of diabetes risk groups. Methods: Data from a healthy project for 599 staffs in a government hospital in Bangkok were obtained for the classification problem. The staffs were diagnosed into one of three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data along with the variables; diabetes risk group, age, gender, cholesterol, and BMI was analyzed and bootstrapped up to 50 and 100 samples, 599 observations per sample, for additional estimation of misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples show non-normality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. In finding the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions with three choices of (0.90:0.05:0.05), (0.80: 0.10: 0.10) or (0.70, 0.15, 0.15). Results: The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k = 3 or k = 4 and the prior probabilities of {non-risk:risk:diabetic} as {0.90:0.05:0.05} or {0.80:0.10:0.10} gave the smallest error rate of misclassification. Conclusion: The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: error rate, bootstrap, diabetes risk groups, k-nearest neighbors

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Authors: Danilo Habermann, Aleksander Medella, Carla Cremon, Yusef Caceres

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This paper aims to analyze the ability of 2d point clouds features to classify different models of helicopters using radars. This method does not need to estimate the blade length, the number of blades of helicopters, and the period of their micro-Doppler signatures. It is also not necessary to generate spectrograms (or any other image based on time and frequency domain). This work transforms a radar return signal into a 2D point cloud and extracts features of it. Three classifiers are used to distinguish 9 different helicopter models in order to analyze the performance of the features used in this work. The high accuracy obtained with each of the classifiers demonstrates that the 2D point clouds features are very useful for classifying helicopters from radar signal.

Keywords: helicopter classification, point clouds features, radar, supervised classifiers

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Authors: A. Şahin Zaimoglu

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A number of studies have been conducted recently to investigate the influence of randomly oriented fibers on some engineering properties of cohesive and cohesionless soils. However, few studies have been carried out on freezing-thawing behavior of fine-grained soils modified with discrete fiber inclusions and additive materials. This experimental study was performed to investigate the effect of randomly distributed polypropylene fibers (PP) and some additive materials [e.g.., borogypsum (BG), fly ash (FA) and cement (C)] on freezing-thawing durability (mass losses) of a fine-grained soil for 6,12 and 18 cycles. The Taguchi method was applied to the experiments and a standard L9 orthogonal array (OA) with four factors and three levels were chosen. A series of freezing-thawing tests were conducted on each specimen. 0-20 % BG, 0-20 % FA, 0-0.25 % PP and 0-3 % of C by total dry weight of mixture were used in the preparation of specimens. Experimental results showed that the most effective materials for the freezing-thawing durability (mass losses) of the samples were borogypsum and fly ash. The values of mass losses for 6, 12 and 18 cycles in optimum conditions were 16.1%, 5.1% and 3.6%, respectively.

Keywords: freezing-thawing, additive materials, reinforced soil, optimization

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Authors: Asnakew Mulualem Tegegne, Tarun Kumar Lohani, , Abunu Atlabachew Eshete

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Groundwater quality has become deteriorated due to natural and anthropogenic activities. Poor water quality has a potential risk to human health and the environment. Therefore, the study aimed to assess the potential risk of groundwater quality contamination levels and public health risks in the Gunabay watershed. For this task, seventy-eight groundwater samples were collected from thirty-nine locations in the dry and wet seasons during 2022. The ground water contamination index was applied to assess the overall quality of groundwater. Six major driving forces (temperature, population density, soil, land cover, recharge, and geology) and their quantitative impact of each factor on groundwater quality deterioration were demonstrated using Geodetector. The results showed that low groundwater quality was detected in urban and agricultural land. Especially nitrate contamination was highly linked to groundwater quality deterioration and public health risks, and a medium contamination level was observed in the area. This indicates that the inappropriate application of fertilizer on agricultural land and wastewater from urban areas has a great impact on shallow aquifers in the study area. Furthermore, the major influencing factors are ranked as soil type (0.33–0.31)>recharge (0.17–0.15)>temperature (0.13–0.08)>population density (0.1–0.08)>land cover types (0.07– 0.04)>lithology (0.05–0.04). The interaction detector revealed that the interaction between soil ∩ recharge, soil ∩ temperature, and soil ∩ land cover, temperature ∩ recharge is more influential to deteriorate groundwater quality in both seasons. Identification and quantification of the major influencing factors may provide new insight into groundwater resource management.

Keywords: groundwater contamination index, geographical detectors, public health · influencing factors, and water resources management

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Authors: Alefsi D. Sanchez-Reinoso, Leonardo Lombardini, Hermann Restrepo

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Colombian coffee is recognized worldwide for its mild flavor and aroma. Its cultivation generates a large amount of waste, such as fresh pulp, which leads to environmental, health, and economic problems. Obtaining biochar (BC) by pyrolysis of coffee pulp and its incorporation to the soil can be a complement to the crop mineral nutrition. The objective was to evaluate the effect of the application of BC obtained from coffee pulp on the physiology and agronomic performance of the Castillo variety coffee crop (Coffea arabica L.). The research was developed in field condition experiment, using a three-year-old commercial coffee crop, carried out in Tolima. Four doses of BC (0, 4, 8 and 16 t ha-1) and four levels of chemical fertilization (CF) (0%, 33%, 66% and 100% of the nutritional requirements) were evaluated. Three groups of variables were recorded during the experiment: i) physiological parameters such as Gas exchange, the maximum quantum yield of PSII (Fv/Fm), biomass, and water status were measured; ii) physical and chemical characteristics of the soil in a commercial coffee crop, and iii) physiochemical and sensorial parameters of roasted beans and coffee beverages. The results indicated that a positive effect was found in plants with 8 t ha-1 BC and fertilization levels of 66 and 100%. Also, a positive effect was observed in coffee trees treated with 8 t ha-1 BC and 100%. In addition, the application of 16 t ha-1 BC increased the soil pHand microbial respiration; reduced the apparent density and state of aggregation of the soil compared to 0 t ha-1 BC. Applications of 8 and 16 t ha-1 BC and 66%-100% chemical fertilization registered greater sensitivity to the aromatic compounds of roasted coffee beans in the electronic nose. Amendments of BC between 8 and 16 t ha-1 and CF between 66% and 100% increased the content of total soluble solids (TSS), reduced the pH, and increased the titratable acidity in beverages of roasted coffee beans. In conclusion, 8 t ha-1 BC of the coffee pulp can be an alternative to supplement the nutrition of coffee seedlings and trees. Applications between 8 and 16 t ha-1 BC support coffee soil management strategies and help the use of solid waste. BC as a complement to chemical fertilization showed a positive effect on the aromatic profile obtained for roasted coffee beans and cup quality attributes.

Keywords: crop yield, cup quality, mineral nutrition, pyrolysis, soil amendment

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Authors: Ameer A. Jebur, William Atherton, Rafid M. Alkhaddar, Edward Loffill

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Superstructures like offshore platforms, tall buildings, transition towers, skyscrapers and bridges are normally designed to resist compression, uplift and lateral forces from wind waves, negative skin friction, ship impact and other applied loads. Better understanding and the precise simulation of the response of batter piles under the action of independent uplift loads is a vital topic and an area of active research in the field of geotechnical engineering. This paper investigates the use of finite element code (FEC) to examine the behaviour of model batter piles penetrated in dense sand, subjected to pull-out pressure by means of numerical modelling. The concept of the Winkler Model (beam on elastic foundation) has been used in which the interaction between the pile embedded depth and adjacent soil in the bearing zone is simulated by nonlinear p-y curves. The analysis was conducted on different pile slenderness ratios (lc⁄d) ranging from 7.5, 15.22 and 30 respectively. In addition, the optimum batter angle for a model steel pile penetrated in dense sand has been chosen to be 20° as this is the best angle for this simulation as demonstrated by other researcher published in literature. In this numerical analysis, the soil response is idealized as elasto-plastic and the model piles are described as elastic materials for the purpose of simulation. The results revealed that the applied loads affect the pullout pile capacity as well as the lateral pile response for dense sand together with varying shear strength parameters linked to the pile critical depth. Furthermore, the pile pull-out capacity increases with increasing the pile aspect ratios.

Keywords: slenderness ratio, soil-pile interaction, winkler model (beam on elastic foundation), pull-out capacity

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Authors: Ghazal Banitahmasb, Nazanin Khakipour

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Potential contamination of rice by heavy metals such as Copper, Cobalt, Cadmium, Arsenic, Chromium, Mercury, Nickel, Lead and Magnesium in soil, water and pesticides affect the quality and nutritional properties of rice. The aim of this study was to evaluate the contamination of rice cultivated in the city of Savadkooh to Cadmium and its comparison with international standards. With the study on different areas of Savadkooh(a city in Mazanaran Province) 7 samples of rice with the soil in which they were grown was taken for sampling. According to the results of all rice grown in Savadkooh city there are some Cadmium but the amount measured is less than specified in the national standard, and is safe for consumers to use.

Keywords: cadmium, heavy metals, rice, Savadkooh

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Authors: Maria Manzoor, Iram Gul, Muhammad Arshad

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Bacterial strains were isolated from contaminated soil collected from Rawalpindi and Islamabad. The strains were investigated for lead resistance and their effect on Pb solubility and PGPR activity. Incubation experiments were carried for inoculated and unoculated soil containing different levels of Pb. Results revealed that few stains (BTM-4, BTM-11, BTM-14) were able to tolerate Pb up to 600 mg L-1, whereas five strains (BTM-3, BTM-6, BTM-10, BTM-21 and BTM-24) showed significant increase in solubility of Pb when compared to all other strains and control. The CaCl2 extractable Pb was increased by 13.6, 6.8, 4.4 and 2.4 folds compared to un-inoculated control soil at increased soil Pb concentration (500, 1000, 1500 and 200 mg kg-1, respectively). The selected bacterial strains (11) were further investigated for plant growth promotion activity through PGPR assays including. Germination and root elongation assays were also conducted under elevated metal concentration in controlled conditions to elucidate the effects of microbial strains upon plant growth and development. The results showed that all the strains tested in this study, produced significantly varying concentrations of IAA, siderophores and gibberellic acid along with ability to phosphorus solubilization index (PSI). The results of germination and root elongation assay further confirmed the beneficial role of the microbial strains in elevating metal stress through PGPR activity. Among all tested strains, BTM-10 significantly improved plant growth. 1.3 and 2.7 folds increase in root and shoot length was observed when compared to control. Which may be attributed to presence of important plant growth promoting enzymes (IAA 74.6 μg/ml; GA 19.23 μg/ml; Sidrophore units 49% and PSI 1.3 cm). The outcome of this study indicates that these Pb tolerant and solubilizing strains may have the potential for plant growth promotion under metal stress and can be used as mediator when coupled with heavy metal hyperaccumulator plants for phytoremediation of Pb contaminated soil.

Keywords: Pb resistant bacteria, Pb mobilizing bacteria, Phytoextraction of Pb, PGPR activity of bacteria

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Authors: Danielle Shackley, Yetunde Folajimi

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As more people turn to the internet seeking health-related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores to text, ranging from positive, neutral, and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing and tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial, and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced, and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process and substituting the Naive Bayes for a deep learning neural network model.

Keywords: sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model

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Authors: Bagher Bayat, Wouter Verhoef, Behnaz Arabi, Christiaan Van der Tol

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The aim of this study was to follow the canopy reflectance patterns in response to soil water deficit and to detect trends of changes in biophysical and biochemical parameters of grass (Poa pratensis species). We used visual interpretation, imaging spectroscopy and radiative transfer model inversion to monitor the gradual manifestation of water stress effects in a laboratory setting. Plots of 21 cm x 14.5 cm surface area with Poa pratensis plants that formed a closed canopy were subjected to water stress for 50 days. In a regular weekly schedule, canopy reflectance was measured. In addition, Leaf Area Index (LAI), Chlorophyll (a+b) content (Cab) and Leaf Water Content (Cw) were measured at regular time intervals. The 1-D bidirectional canopy reflectance model SAIL, coupled with the leaf optical properties model PROSPECT, was inverted using hyperspectral measurements by means of an iterative optimization method to retrieve vegetation biophysical and biochemical parameters. The relationships between retrieved LAI, Cab, Cw, and Cs (Senescent material) with soil moisture content were established in two separated groups; stress and non-stressed. To differentiate the water stress condition from the non-stressed condition, a threshold was defined that was based on the laboratory produced Soil Water Characteristic (SWC) curve. All parameters retrieved by model inversion using canopy spectral data showed good correlation with soil water content in the water stress condition. These parameters co-varied with soil moisture content under the stress condition (Chl: R2= 0.91, Cw: R2= 0.97, Cs: R2= 0.88 and LAI: R2=0.48) at the canopy level. To validate the results, the relationship between vegetation parameters that were measured in the laboratory and soil moisture content was established. The results were totally in agreement with the modeling outputs and confirmed the results produced by radiative transfer model inversion and spectroscopy. Since water stress changes all parts of the spectrum, we concluded that analysis of the reflectance spectrum in the VIS-NIR-MIR region is a promising tool for monitoring water stress impacts on vegetation.

Keywords: hyperspectral remote sensing, model inversion, vegetation responses, water stress

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Authors: Muhammad Asim Nazir

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The investigations reported in this manuscript were carried on the screening of one hundred and seventy-eight chickpea germplasm lines/cultivars against wilt disease, caused by Fusarium oxysporum f. sp. ciceris. The screening was conducted in vivo (field) conditions. The field screening was accompanied with the study of some epidemiological factors affecting the occurrence and severity of the disease. Among the epidemiological factors maximum temperature range (28-40°C), minimum temperature range (12-24°C), relative humidity (19-44%), soil temperature (26-41°C) and soil moisture range (19-34°C) was studied for affecting the disease incidence/severity. The results revealed that air temperature was positively correlated with diseases. Soil temperature data revealed that in all cultivars disease incidence was maximum as 39°C. Most of the plants show 40-50% disease incidence. Disease incidence decreased at 33.5°C. The result of correlation of relative humidity of air and wilt incidence revealed that all cultivars/lines were negatively correlated with relative humidity. With increasing relative humidity wilt incidence decreased and vice versa.

Keywords: chickpea, epidemiological, screening, disease

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Authors: Yanmei Xiong, Baowen Liao, Kun Xin, Zhongmao Jiang, Hao Guo, Yujun Chen, Mei Li

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Conversion of mangroves to aquaculture ponds represented as one major reason for mangrove loss in Asian countries in the 20th century. Recently the Chinese government has set a goal to increase 48,650 ha (more than the current mangrove area) of mangroves before the year of 2025 and “rehabilitation of aquaculture ponds to mangroves” projects are considered to be the major pathway to increase the mangrove area of China. It remains unclear whether natural colonization is feasible and what are the main influencing factors for mangrove restoration in these projects. In this study, a total of 17 rehabilitation sites in Dongzhai Bay, Hainan, China were surveyed for vegetation, soil and surface elevation five years after the rehabilitation project was initiated. Colonization of non-planted mangrove species was found at all sites and non-planted species dominated over planted species at 14 sites. Mangrove plants could only be found within the elevation range of -20 cm to 65 cm relative to the mean sea level. Soil carbon and nitrogen contents of the top 20 cm were generally low, ranging between 0.2%–1.4% and 0.03%–0.09%, respectively, and at each site, soil carbon and nitrogen were significantly lower at elevations with mangrove plants than lower elevations without mangrove plants. Seven sites located at the upper stream of river estuaries, where soil salinity was relatively lower, and nutrient was relatively higher, was dominated by non-planted Sonneratia caseolaris. Seven sites located at the down-stream of river estuaries or in the inner part of the bay, where soil salinity and nutrient were intermediate, were dominated by non-planted alien Sonneratia apetala. Another three sites located at the outer part of the bay, where soil salinity was higher and nutrient was lower, were dominated by planted species (Rhizophora stylosa, Kandelia obovata, Aegiceras corniculatum and Bruguiera sexangula) with non-planted S. apetala and Avicennia marina also found. The results suggest that natural colonization of mangroves is feasible in pond rehabilitation projects given the rehabilitation of tidal activities and appropriate elevations. Surface elevation is the major determinate for the success of mangrove rehabilitation, and soil salinity and nutrients are important in shaping vegetation structure. The colonization and dominance of alien species (Sonneratia apetala in this case) in some rehabilitation sites poses invasion risks and thus cautions should be taken when introducing alien mangrove species.

Keywords: coastal wetlands, ecological restoration, mangroves, natural colonization, shrimp pond rehabilitation, wetland restoration

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Authors: Nilufar Chowdhury, Fereydoun Najafian Jazi, Omid Ghasemi-Fare

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The thermal effect on soil properties induces significant variations in hydraulic conductivity, which is attributable to temperature-dependent transitions in soil properties. With the elevation of temperature, there can be a notable increase in intrinsic permeability due to the degeneration of bound water molecules into a free state facilitated by thermal energy input. Conversely, thermal consolidation may cause a reduction in intrinsic permeability as soil particles undergo densification. This thermal response of soil permeability exhibits pronounced heterogeneity across different soil types. Furthermore, this temperature-induced disruption of the bound water within clay matrices can enhance the mineral-to-mineral contact, initiating irreversible deformation within the clay structure. This indicates that when soil undergoes heating-cooling cycles, plastic strain can develop, which needs to be investigated for every soil type to understand the thermo-hydro mechanical behavior of clay properly. This research aims to study the effect of the heating-cooling cycle on the intrinsic permeability and time-dependent evaluation of thermal volume change of sodium Bentonite clay. A temperature-controlled triaxial permeameter cell is used in this study. The selected temperature is 20° C, 40° C, 40° C and 80° C. The hydraulic conductivity of Bentonite clay under 100 kPa confining stresses was measured. Hydraulic conductivity analysis was performed on a saturated sample for a void ratio e = 0.9, corresponding to a dry density of 1.2 Mg/m3. Different hydraulic gradients were applied between the top and bottom of the sample to obtain a measurable flow through the sample. The hydraulic gradient used for the experiment was 4000. The diameter and thickness of the sample are 101. 6 mm, and 25.4 mm, respectively. Both for heating and cooling, the hydraulic conductivity at each temperature is measured after the flow reaches the steady state condition to make sure the volume change due to thermal loading is stabilized. Thus, soil specimens were kept at a constant temperature during both the heating and cooling phases for at least 10-18 days to facilitate the equilibration of hydraulic transients. To assess the influence of temperature-induced volume changes of Bentonite clay, the evaluation of void ratio change during this time period has been monitored. It is observed that the intrinsic permeability increases by 30-40% during the heating cycle. The permeability during the cooling cycle is 10-12% lower compared to the permeability observed during the heating cycle at a particular temperature. This reduction in permeability implies a change in soil fabric due to the thermal effect. An initial increase followed by a rapid decrease in void ratio was observed, representing the occurrence of possible osmotic swelling phenomena followed by thermal consolidation. It has been observed that after a complete heating-cooling cycle, there is a significant change in the void ratio compared to the initial void ratio of the sample. The results obtained suggest that Bentonite clay’s microstructure can change subject to a complete heating-cooling process, which regulates macro behavior such as the permeability of Bentonite clay.

Keywords: bentonite, permeability, temperature, thermal volume change

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Authors: Elena Listo, Miguel Marchamalo

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This research studies the soil properties located in the watershed of Jabillo River in the Guanacaste province, Costa Rica. The soils are classified as Alfisols (T. Haplustalfs), in the flatter parts with grazing as Fluventic Haplustalfs or as a consequence of bad drainage as F. Epiaqualfs. The objective of this project is to define the status of the soil, to use remote sensing as a tool for analyzing the evolution of land use and determining the water balance of the watershed in order to improve the efficiency of the water collecting systems. Soil samples were analyzed from trial pits taken from secondary forests, degraded pastures, mature teak plantation, and regrowth -Tectona grandis L. F.- species developed favorably in the area. Furthermore, to complete the study, infiltration measurements were taken with an artificial rainfall simulator, as well as studies of soil compaction with a penetrometer, in points strategically selected from the different land uses. Regarding remote sensing, nearly 40 data samples were collected per plot of land. The source of radiation is reflected sunlight from the beam and the underside of leaves, bare soil, streams, roads and logs, and soil samples. Infiltration reached high levels. The majority of data came from the secondary forest and mature planting due to a high proportion of organic matter, relatively low bulk density, and high hydraulic conductivity. Teak regrowth had a low rate of infiltration because the studies made regarding the soil compaction showed a partial compaction over 50 cm. The secondary forest presented a compaction layer from 15 cm to 30 cm deep, and the degraded pasture, as a result of grazing, in the first 15 cm. In this area, the alfisols soils have high content of iron oxides, a fact that causes a higher reflectivity close to the infrared region of the electromagnetic spectrum (around 700mm), as a result of clay texture. Specifically in the teak plantation where the reflectivity reaches values of 90 %, this is due to the high content of clay in relation to others. In conclusion, the protective function of secondary forests is reaffirmed with regards to erosion and high rate of infiltration. In humid climates and permeable soils, the decrease of runoff is less, however, the percolation increases. The remote sensing indicates that being clay soils, they retain moisture in a better way and it means a low reflectivity despite being fine texture.

Keywords: alfisols, Costa Rica, infiltration, remote sensing

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Authors: G. Shahzadi, A. Soulaimani

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This research work aims to identify the physical parameters of the constitutive soil model in the design of a rockfill dam by inverse analysis. The best parameters of the constitutive soil model, are those that minimize the objective function, defined as the difference between the measured and numerical results. The Finite Element code (Plaxis) has been utilized for numerical simulation. Polynomial and neural network-based response surfaces have been generated to analyze the relationship between soil parameters and displacements. The performance of surrogate models has been analyzed and compared by evaluating the root mean square error. A comparative study has been done based on objective functions and optimization techniques. Objective functions are categorized by considering measured data with and without uncertainty in instruments, defined by the least square method, which estimates the norm between the predicted displacements and the measured values. Hydro Quebec provided data sets for the measured values of the Romaine-2 dam. Stochastic optimization, an approach that can overcome local minima, and solve non-convex and non-differentiable problems with ease, is used to obtain an optimum value. Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) are compared for the minimization problem, although all these techniques take time to converge to an optimum value; however, PSO provided the better convergence and best soil parameters. Overall, parameter identification analysis could be effectively used for the rockfill dam application and has the potential to become a valuable tool for geotechnical engineers for assessing dam performance and dam safety.

Keywords: Rockfill dam, parameter identification, stochastic analysis, regression, PLAXIS

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Authors: Javed Kamal

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A proposed field study of wheat-based cropping systems was conducted at Faisalabad (Post-Graduate Research Station). We used 7 treatments and Jantar as a green manuring crop to increase the fertility status of soil; after the vegetative phases of wheat, rice, sorghum, and mungbean, the agronomic parameters of these crops were recorded. Hopefully, all increased with jantar treatment when compared with controls. The benefit: cost ratio and physicochemical characteristics of the soil before and after the crop harvest were also calculated.

Keywords: benifit cost ratio, jantar, sunflower, rice, wheat

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Authors: Shivangi Somvanshi

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Poor crop productivity in salt-affected environment in the country is due to insufficient and untimely canal supply to agricultural land and inefficient field water management practices. This could further degrade due to inadequate maintenance of canal network, ongoing secondary soil salinization and waterlogging, worsening of groundwater quality. Large patches of low productivity in irrigation commands are occurring due to waterlogging and salt-affected soil, particularly in the scarcity rainfall year. Satellite remote sensing has been used for mapping of areas of low crop productivity, waterlogging and salt in irrigation commands. The spatial results obtained for these problems so far are less reliable for further use due to rapid change in soil quality parameters over the years. The existing spatial databases of canal network and flow data, groundwater quality and salt-affected soil were obtained from the central and state line departments/agencies and were integrated with GIS. Therefore, an integrated methodology based on remote sensing and GIS has been developed in ArcGIS environment on the basis of canal supply status, groundwater quality, salt-affected soils, and satellite-derived vegetation index (NDVI), salinity index (NDSI) and waterlogging index (NSWI). This methodology was tested for identification and delineation of area of low productivity in the Gautam Buddha Nagar district (Uttar Pradesh). It was found that the area affected by this problem lies mainly in Dankaur and Jewar blocks of the district. The problem area was verified with ground data and was found to be approximately 78% accurate. The methodology has potential to be used in other irrigation commands in the country to obtain reliable spatial data on low crop productivity.

Keywords: remote sensing, GIS, salt affected soil, crop productivity, Gautam Buddha Nagar

Procedia PDF Downloads 287

Authors: Yamma Rose, Kone Martine, Yonli Arsène, Wanko Ngnien Adrien

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Artisanal gold mining has seen a resurgence in recent years in Burkina Faso with its corollary of soil and water pollution. Indeed, in addition to visible impacts, it generates discharges rich in trace metal elements and acids. This pollution has significant environmental consequences, making these lands unusable while the population depends on the natural environment for its survival. The goal of this study is to assess the decontamination potential of Chrysopogon zizanioides on two artisanal gold processing sites in Burkina Faso. The cyanidation sites of Nebia (1Ha) and Nimbrogo (2Ha) located respectively in the Central West and Central South regions were selected. The soils were characterized to determine the initial pollution levels before the implementation of phytoremediation. After development of the site, parallel trenches equidistant 6 m apart, 30 cm deep, 40 cm wide and opposite to the water flow direction were dug and filled with earth amended with manure. The Chrysopogon zizanioides plants were transplanted 5 cm equidistant into the trenches. The mere fact that Chrysopogon zizanioides grew in the polluted soil is an indication that this plant tolerates and resists the toxicity of trace elements present on the site. The characterization shows sites very polluted with free cyanide 900 times higher than the national standard, the level of Hg in the soil is 5 times more than the limit value, iron and Zn are respectively 1000 times and 200 more than the tolerated environmental value. At time T1 (6 months) and T2 (12 months) of culture, Chrysopogon zizanioides showed less development on the Nimbrogo site than that of the Nebia site. Plant shoots and associated soil samples were collected and analyzed for total As, Hg, Fe and Zn concentration. The trace element content of the soil, the bioaccumulation factor and the hyper accumulation thresholds were also determined to assess the remediation potential. The concentration of As and Hg in the soil was below international risk thresholds, while that of Fe and Zn was well above these thresholds. The CN removal efficiency at the Nebia site is respectively 29.90% and 68.62% compared to 6.6% and 60.8% at Nimbrogo at time T1 and T2.

Keywords: chrysopogon zizanioides, in-situ phytoremediation, polluted soils, micropollutants

Procedia PDF Downloads 78

Authors: F. Ainlhout, S. Boutaleb, M. C. Diaz-Barradas, M. Zunzunegui

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Argania spinosa is an endemic tree of the southwest of Morocco, occupying 828,000 Ha, distributed mainly between Mediterranean vegetation and the desert. This tree can grow in extremely arid regions in Morocco, where annual rainfall ranges between 100-300 mm where no other tree species can live. It has been designated as a UNESCO Biosphere reserve since 1998. Argania tree is of great importance in human and animal feeding of rural population as well as for oil production, it is considered as a multi-usage tree. Admine forest located in the suburbs of Agadir city, 5 km inland, was selected to conduct this work. The aim of the study was to investigate the temporal variation in root-zone moisture dynamic in response to variation in climatic conditions and vegetation water uptake, using a geophysical technique called Electrical resistivity imaging (ERI). This technique discriminates resistive woody roots, dry and moisture soil. Time-dependent measurements (from April till July) of resistivity sections were performed along the surface transect (94 m Length) at 2 m fixed electrode spacing. Transect included eight Argan trees. The interactions between the tree and soil moisture were estimated by following the tree water status variations accompanying the soil moisture deficit. For that purpose we measured midday leaf water potential and relative water content during each sampling day, and for the eight trees. The first results showed that ERI can be used to accurately quantify the spatiotemporal distribution of root-zone moisture content and woody root. The section obtained shows three different layers: middle conductive one (moistured); a moderately resistive layer corresponding to relatively dry soil (calcareous formation with intercalation of marly strata) on top, this layer is interspersed by very resistant layer corresponding to woody roots. Below the conductive layer, we find the moderately resistive layer. We note that throughout the experiment, there was a continuous decrease in soil moisture at the different layers. With the ERI, we can clearly estimate the depth of the woody roots, which does not exceed 4 meters. In previous work on the same species, analyzing the δ18O in water of xylem and in the range of possible water sources, we argued that rain is the main water source in winter and spring, but not in summer, trees are not exploiting deep water from the aquifer as the popular assessment, instead of this they are using soil water at few meter depth. The results of the present work confirm the idea that the roots of Argania spinosa are not growing very deep.

Keywords: Argania spinosa, electrical resistivity imaging, root system, soil moisture

Procedia PDF Downloads 328

Authors: Sandy J. M. Balla, Jerry J. Walker, Isaac K. Kyere

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The heat transfer coefficient at the soil–air interface is important in calculating underground cable ampacity when convection occurs. Calculating the heat transfer coefficient accurately is complex because of the temperature variations at the earth's surface. This paper presents the effect of convection heat flow across the ground surface on the rating of three single-core, 132kV, XLPE cables buried underground. The Finite element method (FEM) is a numerical analysis technique used to determine the cable rating of buried cables under installation conditions that are difficult to support when using the analytical method. This study demonstrates the use of FEM to investigate the effect of convection on the rating ofburied cables in flat formation using QuickField finite element simulation software. As a result, developing a model to simulate this type of situation necessitates important considerations such as the following boundary conditions: burial depth, soil thermal resistivity, and soil temperature, which play an important role in the simulation's accuracy and reliability. The results show that when the ground surface is taken as a convection interface, the conductor temperature rises and may exceed the maximum permissible temperature when rated current flows. This is because the ground surface acts as a convection interface between the soil and the air (fluid). This result correlates and is compared with the rating obtained using the IEC60287 analytical method, which is based on the condition that the ground surface is an isotherm.

Keywords: finite element method, convection, buried cables, steady-state rating

Procedia PDF Downloads 131

Authors: T. Schmitt, J. Rosin, C. Butenweg

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Seismic design of buried pipeline systems for energy and water supply is not only important for plant and operational safety, but in particular for the maintenance of supply infrastructure after an earthquake. Past earthquakes have shown the vulnerability of pipeline systems. After the Kobe earthquake in Japan in 1995 for instance, in some regions the water supply was interrupted for almost two months. The present paper shows special issues of the seismic wave impacts on buried pipelines, describes calculation methods, proposes approaches and gives calculation examples. Buried pipelines are exposed to different effects of seismic impacts. This paper regards the effects of transient displacement differences and resulting tensions within the pipeline due to the wave propagation of the earthquake. Other effects are permanent displacements due to fault rupture displacements at the surface, soil liquefaction, landslides and seismic soil compaction. The presented model can also be used to calculate fault rupture induced displacements. Based on a three-dimensional Finite Element Model parameter studies are performed to show the influence of several parameters such as incoming wave angle, wave velocity, soil depth and selected displacement time histories. In the computer model, the interaction between the pipeline and the surrounding soil is modeled with non-linear soil springs. A propagating wave is simulated affecting the pipeline punctually independently in time and space. The resulting stresses mainly are caused by displacement differences of neighboring pipeline segments and by soil-structure interaction. The calculation examples focus on pipeline bends as the most critical parts. Special attention is given to the calculation of long-distance heat pipeline systems. Here, in regular distances expansion bends are arranged to ensure movements of the pipeline due to high temperature. Such expansion bends are usually designed with small bending radii, which in the event of an earthquake lead to high bending stresses at the cross-section of the pipeline. Therefore, Karman's elasticity factors, as well as the stress intensity factors for curved pipe sections, must be taken into account. The seismic verification of the pipeline for wave propagation in the soil can be achieved by observing normative strain criteria. Finally, an interpretation of the results and recommendations are given taking into account the most critical parameters.

Keywords: buried pipeline, earthquake, seismic impact, transient displacement

Procedia PDF Downloads 187

Authors: Rosa Figueroa, Christopher Flores

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Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

Procedia PDF Downloads 297

Authors: C. Mekala, Indumathi M. Nambi

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Nitrogen pollution in groundwater arising from wastewater and fertilizer application through vadose zone is a major problem and it causes a prime risk to groundwater based drinking water supplies. Nitrogenous compounds namely ammonium, nitrate and nitrite fate and transport in soil subsurface were studied experimentally. The major process like sorption, leaching, biotransformation involving microbial growth kinetics, and biological clogging due to biomass growth were assessed and modeled with advection-dispersion reaction equations for ammonium, nitrate and acetate in a saturated, heterogeneous soil medium. The transport process was coupled with freundlich sorption and monod inhibition kinetics for immobile bacteria and permeability reduction due to biomass growth will be verified and validated with the numerical model. This proposed mathematical model will be very helpful in the development of a management model for a sustainable and safe wastewater reuse strategies such as irrigation and groundwater recharge.

Keywords: nitrogen species transport, transformation, biological clogging, biokinetic parameters, contaminant transport model, saturated soil

Procedia PDF Downloads 400

Authors: Ghada S. Ellithy, John. W. Murphy, Maureen K. Corcoran

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Erosion rate of soils during a levee or dam overtopping event is a major component in risk assessment evaluation of breach time and downstream consequences. The mechanism and evolution of dam or levee breach caused by overtopping erosion is a complicated process and difficult to measure during overflow due to accessibility and quickly changing conditions. In this paper, the results of a flume erosion tests are presented and discussed. The tests are conducted on a coarse-grained material with a median grain size D50 of 5 mm in a 1-m (3-ft) wide flume under varying flow rates. Each test is performed by compacting the soil mix r to its near optimum moisture and dry density as determined from standard Proctor test in a box embedded in the flume floor. The box measures 0.45 m wide x 1.2 m long x 0.25 m deep. The material is tested several times at varying hydraulic loading to determine the erosion rate after equal time intervals. The water depth, velocity are measured at each hydraulic loading, and the acting bed shear is calculated. A shallow water lidar (SWL) system was utilized to record the progress of soil erodibility and water depth along the scanned profiles of the tested box. SWL is a non-contact system that transmits laser pulses from above the water and records the time-delay between top and bottom reflections. Results from the SWL scans are compared with before and after manual measurements to determine the erosion rate of the soil mix and other erosion parameters.

Keywords: coarse-grained materials, erosion rate, LIDAR system, soil erosion

Procedia PDF Downloads 112

Authors: Samuel Akinlabi Ola, Emeka Segun Nnochiri, Stephen Kayode Aderomose, Paul Ayesemhe Edoh

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Fadama soils of Northern Nigeria are generally a problem soil for highway and geotechnical engineers. There has been no consistent conclusion on the effect of the strain rate on the shear strength of soils, thus necessitating the need to clarify this issue with various types of soil. Consolidated undrained tests with pore pressure measurements were conducted at optimum moisture content and maximum dry density using standard proctor compaction. Back pressures were applied to saturate the soil. The shear strength parameters were determined. Analyzing the results and model studies using the Rate Process Theory, functional relationships between the deviator stress and strain rate were determined and expressed mathematically as deviator stress = β0+ β1 log(strain rate) at each cell pressure where β0 and β1 are constants. Also, functional relationships between the pore pressure coefficient Āf and the time to failure were determined and expressed mathematically as pore pressure coefficient, Āf = ψ0+ѱ1log (time to failure) where ψ0 and ѱ1 are constants. For cell pressure between 69 – 310 kN/m2 (10 - 45psi) the constants found for Fadama soil in this study are ψ0=0.17 and ѱ1=0.18. The study also shows the dependence of the angle of friction (ø’) on the rate of strain as it increases from 22o to 25o for an increase in the rate of strain from 0.08%/min to 1.0%/min. Conclusively, the study also shows that within the strain rate utilized in the research, the deviator strength increased with the strain rate while the excess pore water pressure decreased with an increase in the rate of strain.

Keywords: deviator stress, Fadama soils, pore pressure coefficient, rate process

Procedia PDF Downloads 76

Authors: H. Abas Nejad, A. R. Teymoori

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Facial expression recognition is one of the open problems in computer vision. Robust neutral face recognition in real time is a major challenge for various supervised learning based facial expression recognition methods. This is due to the fact that supervised methods cannot accommodate all appearance variability across the faces with respect to race, pose, lighting, facial biases, etc. in the limited amount of training data. Moreover, processing each and every frame to classify emotions is not required, as the user stays neutral for the majority of the time in usual applications like video chat or photo album/web browsing. Detecting neutral state at an early stage, thereby bypassing those frames from emotion classification would save the computational power. In this work, we propose a light-weight neutral vs. emotion classification engine, which acts as a preprocessor to the traditional supervised emotion classification approaches. It dynamically learns neutral appearance at Key Emotion (KE) points using a textural statistical model, constructed by a set of reference neutral frames for each user. The proposed method is made robust to various types of user head motions by accounting for affine distortions based on a textural statistical model. Robustness to dynamic shift of KE points is achieved by evaluating the similarities on a subset of neighborhood patches around each KE point using the prior information regarding the directionality of specific facial action units acting on the respective KE point. The proposed method, as a result, improves ER accuracy and simultaneously reduces the computational complexity of ER system, as validated on multiple databases.

Keywords: neutral vs. emotion classification, Constrained Local Model, procrustes analysis, Local Binary Pattern Histogram, statistical model

Procedia PDF Downloads 338