Search results for: unified soil classification system.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21066

Search results for: unified soil classification system.

20886 A Summary-Based Text Classification Model for Graph Attention Networks

Authors: Shuo Liu

Abstract:

In Chinese text classification tasks, redundant words and phrases can interfere with the formation of extracted and analyzed text information, leading to a decrease in the accuracy of the classification model. To reduce irrelevant elements, extract and utilize text content information more efficiently and improve the accuracy of text classification models. In this paper, the text in the corpus is first extracted using the TextRank algorithm for abstraction, the words in the abstract are used as nodes to construct a text graph, and then the graph attention network (GAT) is used to complete the task of classifying the text. Testing on a Chinese dataset from the network, the classification accuracy was improved over the direct method of generating graph structures using text.

Keywords: Chinese natural language processing, text classification, abstract extraction, graph attention network

Procedia PDF Downloads 65
20885 Analysis of Different Classification Techniques Using WEKA for Diabetic Disease

Authors: Usama Ahmed

Abstract:

Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model.

Keywords: data mining, classification, diabetes, WEKA

Procedia PDF Downloads 121
20884 Studying the Impact of Soil Characteristics in Displacement of Retaining Walls Using Finite Element

Authors: Mojtaba Ahmadabadi, Akbar Masoudi, Morteza Rezai

Abstract:

In this paper, using the finite element method, the effect of soil and wall characteristics was investigated. Thirty and two different models were studied by different parameters. These studies could calculate displacement at any height of the wall for frictional-cohesive soils. The main purpose of this research is to determine the most effective soil characteristics in reducing the wall displacement. Comparing different models showed that the overall increase in internal friction angle, angle of friction between soil and wall and modulus of elasticity reduce the replacement of the wall. In addition, increase in special weight of soil will increase the wall displacement. Based on results, it can be said that all wall displacements were overturning and in the backfill, soil was bulging. Results show that the highest impact is seen in reducing wall displacement, internal friction angle, and the angle friction between soil and wall. One of the advantages of this study is taking into account all the parameters of the soil and walls replacement distribution in wall and backfill soil. In this paper, using the finite element method and considering all parameters of the soil, we investigated the impact of soil parameter in wall displacement. The aim of this study is to provide the best conditions in reducing the wall displacement and displacement wall and soil distribution.

Keywords: retaining wall, fem, soil and wall interaction, angle of internal friction of the soil, wall displacement

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20883 Contribution to the Study of the Rill Density Effects on Soil Erosion: Laboratory Experiments

Authors: L. Mouzai, M. Bouhadef

Abstract:

Rills begin to be generated once overland flow shear capacity overcomes the soil surface resistance. This resistance depends on soil texture, the arrangement of soil particles and on chemical and physical properties. The rill density could affect soil erosion, especially when the distance between the rills (interrill) contributes to the variation of the rill characteristics, and consequently on sediment concentration. To investigate this point, agricultural sandy soil, a soil tray of 0.2x1x3m³ and a piece of hardwood rectangular in shape to build up rills were the base of this work. The results have shown that small lines have been developed between the rills and the flow acceleration increased in comparison to the flow on the flat surface (interrill). Sediment concentration increased with increasing rill number (density).

Keywords: artificial rainfall, experiments, rills, soil erosion, transport capacity

Procedia PDF Downloads 131
20882 Arabic Text Classification: Review Study

Authors: M. Hijazi, A. Zeki, A. Ismail

Abstract:

An enormous amount of valuable human knowledge is preserved in documents. The rapid growth in the number of machine-readable documents for public or private access requires the use of automatic text classification. Text classification can be defined as assigning or structuring documents into a defined set of classes known in advance. Arabic text classification methods have emerged as a natural result of the existence of a massive amount of varied textual information written in the Arabic language on the web. This paper presents a review on the published researches of Arabic Text Classification using classical data representation, Bag of words (BoW), and using conceptual data representation based on semantic resources such as Arabic WordNet and Wikipedia.

Keywords: Arabic text classification, Arabic WordNet, bag of words, conceptual representation, semantic relations

Procedia PDF Downloads 398
20881 Comparison of Mean Monthly Soil Temperature at (5 and 30 cm) Depths at Compton Experimental Site, West Midlands (UK), between 1976-2008

Authors: Aminu Mansur

Abstract:

A comparison of soil temperature at (5 and 30 cm) depths at a research site over the period (1976-2008) was analyzed. Based on the statistical analysis of the database of (12,045) days of individual soil temperature measurements in sandy-loam of the (salwick series) soils, the mean soil temperature revealed a statistically significant increase of about -1.1 to 10.9°C at 5 cm depth in 1976 compared to 2008. Similarly, soil temperature at 30 cm depth increased by -0.1 to 2.1°C in 2008 compared to 1976. Although, rapid increase in soil temperature at all depths was observed during that period, but a thorough assessment of these conditions suggested that the soil temperature at 5 cm depth are progressively increasing over time. A typical example of those increases in soil temperature was provided for agriculture where Miscanthus (elephant) plant that grows within the study area is adversely affected by the mean soil temperature increase. The study concluded that these observations contribute to the growing mass of evidence of global warming and knowledge on secular trends. Therefore, there was statistically significant increase in soil temperature at Compton Experimental Site between 1976-2008.

Keywords: soil temperature, warming trend, environment science, climate and atmospheric sciences

Procedia PDF Downloads 273
20880 Image Classification with Localization Using Convolutional Neural Networks

Authors: Bhuyain Mobarok Hossain

Abstract:

Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

Procedia PDF Downloads 267
20879 Compression Strength of Treated Fine-Grained Soils with Epoxy or Cement

Authors: M. Mlhem

Abstract:

Geotechnical engineers face many problematic soils upon construction and they have the choice for replacing these soils with more appropriate soils or attempting to improve the engineering properties of the soil through a suitable soil stabilization technique. Mostly, improving soils is environmental, easier and more economical than other solutions. Stabilization soils technique is applied by introducing a cementing agent or by injecting a substance to fill the pore volume. Chemical stabilizers are divided into two groups: traditional agents such as cement or lime and non-traditional agents such as polymers. This paper studies the effect of epoxy additives on the compression strength of four types of soil and then compares with the effect of cement on the compression strength for the same soils. Overall, the epoxy additives are more effective in increasing the strength for different types of soils regardless its classification. On the other hand, there was no clear relation between studied parameters liquid limit, passing No.200, unit weight and between the strength of samples for different types of soils.

Keywords: additives, clay, compression strength, epoxy, stabilization

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20878 Automatic Classification for the Degree of Disc Narrowing from X-Ray Images Using CNN

Authors: Kwangmin Joo

Abstract:

Automatic detection of lumbar vertebrae and classification method is proposed for evaluating the degree of disc narrowing. Prior to classification, deep learning based segmentation is applied to detect individual lumbar vertebra. M-net is applied to segment five lumbar vertebrae and fine-tuning segmentation is employed to improve the accuracy of segmentation. Using the features extracted from previous step, clustering technique, k-means clustering, is applied to estimate the degree of disc space narrowing under four grade scoring system. As preliminary study, techniques proposed in this research could help building an automatic scoring system to diagnose the severity of disc narrowing from X-ray images.

Keywords: Disc space narrowing, Degenerative disc disorders, Deep learning based segmentation, Clustering technique

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20877 Use of Gaussian-Euclidean Hybrid Function Based Artificial Immune System for Breast Cancer Diagnosis

Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

Abstract:

Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: artificial immune system, breast cancer diagnosis, Euclidean function, Gaussian function

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20876 Microbiological Analysis of Soil from Onu-Ebonyi Contaminated with Inorganic Fertilizer

Authors: M. N. Alo, U. C. C. Egbule, J. O. Orji, C. J. Aneke

Abstract:

Microbiological analysis of soil from Onu-Ebonyi Izzi local government area of Ebonyi State, Nigeria contaminated with inorganic fertilizer was carried out with a view to determine the effect of the fertilizer on the microbial flora of the soil. soil samples were analyzed for microbial burden. the result showed that the following organisms were isolated with their frequency of their occurrence as follows:pseudomonas species (33.3%) and aspergillus species (54.4%) had the highest frequncy of occurence in the whole sample of batches, while streptococcus species had 6.0% and Geotrichum species (5.3%) had the least and other predominant microorganism isolated: bacillus species,staphylococcus species and vibrio species, Escherichia species, rhzizopus species, mucor species and fusaruim species. From the result, it could be concluded that the soil was contaminated and this could affect adversely the fertility of the soil .

Keywords: soil, bacteria, fungi, inorganic fertilizer, Onu- Ebonyi

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20875 Prediction of Permeability of Frozen Unsaturated Soil Using Van Genuchten Model and Fredlund-Xing Model in Soil Vision

Authors: Bhavita S. Dave, Jaimin Vaidya, Chandresh H. Solanki, Atul K.

Abstract:

To measure the permeability of a soil specimen, one of the basic assumptions of Darcy's law is that the soil sample should be saturated. Unlike saturated soils, the permeability of unsaturated soils cannot be found using conventional methods as it does not follow Darcy's law. Many empirical models, such as the Van Genuchten Model and Fredlund-Xing Model were suggested to predict permeability value for unsaturated soil. Such models use data from the soil-freezing characteristic curve to find fitting parameters for frozen unsaturated soils. In this study, soil specimens were subjected to 0, 1, 3, and 5 freezing-thawing (F-T) cycles for different degrees of saturation to have a wide range of suction, and its soil freezing characteristic curves were formulated for all F-T cycles. Changes in fitting parameters and relative permeability with subsequent F-T cycles are presented in this paper for both models.

Keywords: frozen unsaturated soil, Fredlund Xing model, soil-freezing characteristic curve, Van Genuchten model

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20874 Intelligent Irrigation Control System Using Wireless Sensors and Android Application

Authors: Rajeshwari Madli, Santhosh Hebbar, Vishwanath Heddoori, G. V. Prasad

Abstract:

Agriculture is the major occupation in India and forms the backbone of Indian economy in which irrigation plays a crucial role for increasing the quality and quantity of crop yield. In spite of many revolutionary advancements in agriculture, there has not been a dramatic increase in agricultural performance. Lack of irrigation infrastructure and agricultural knowledge are the critical factors influencing agricultural performance. However, by using advanced agricultural equipment, the effect of these factors can be curtailed.  The presented system aims at increasing the yield of crops by using an intelligent irrigation controller that makes use of wireless sensors. Sensors are used to monitor primary parameters such as soil moisture, soil pH, temperature and humidity. Irrigation decisions are taken based on the sensed data and the type of crop being grown. The system provides a mobile application in which farmers can remotely monitor and control the irrigation system. Also, the water pump is protected against damages due to voltage variations and dry running.

Keywords: android application, Bluetooth, wireless sensors, irrigation, temperature, soil pH

Procedia PDF Downloads 353
20873 Soil Penetration Resistance and Water Content Spatial Distribution Following Different Tillage and Crop Rotation in a Chinese Mollisol

Authors: Xuewen Chen, Aizhen Liang, Xiaoping Zhang

Abstract:

To better understand the spatial variability of soil penetration resistance (SPR) and soil water content (SWC) induced by different tillage and crop rotation in a Mollisol of Northeast China, the soil was sampled from the tillage experiment which was established in Dehui County, Jilin Province, Northeast China, in 2001. Effect of no-tillage (NT), moldboard plow (MP) and ridge tillage (RT) under corn-soybean rotation (C-S) and continuous corn (C-C) system on SPR and SWC were compared with horizontal and vertical variations. The results showed that SPR and SWC spatially varied across the ridge. SPR in the rows was higher than inter-rows, especially in topsoil (2.5-15 cm) of NT and RT plots. SPR of MP changed in the trend with the curve-shaped ridge. In contrast to MP, NT, and RT resulted in average increment of 166.3% and 152.3% at a depth of 2.5-17.5 cm in the row positions, respectively. The mean SPR in topsoil in the rows means soil compaction is not the main factor limiting plant growth and crop yield. SPR in the row of RT soil was lower than NT at a depth of 2.5-12.5 cm. The SWC in NT and RT soil was highest in the inter-rows and least in the rows or shoulders, respectively. However, the lateral variation trend of MP was opposite to NT. From the profile view of SWC, MP was greater than NT and RT in 0-20 cm of the rows. SWC in RT soil was higher than NT in the row of 0-20 cm. Crop rotation did not have a marked impact on SPR and SWC. In addition to the tillage practices, the factor which affects SPR greatly was depth but not position. These two factors have significant effects on SWC. These results indicated that the adoption of RT was a more suitable conservation tillage practices than NT in the black soil of Northeast China.

Keywords: row, soil penetration resistance, spatial variability, tillage practice

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20872 Vehicle Type Classification with Geometric and Appearance Attributes

Authors: Ghada S. Moussa

Abstract:

With the increase in population along with economic prosperity, an enormous increase in the number and types of vehicles on the roads occurred. This fact brings a growing need for efficiently yet effectively classifying vehicles into their corresponding categories, which play a crucial role in many areas of infrastructure planning and traffic management. This paper presents two vehicle-type classification approaches; 1) geometric-based and 2) appearance-based. The two classification approaches are used for two tasks: multi-class and intra-class vehicle classifications. For the evaluation purpose of the proposed classification approaches’ performance and the identification of the most effective yet efficient one, 10-fold cross-validation technique is used with a large dataset. The proposed approaches are distinguishable from previous research on vehicle classification in which: i) they consider both geometric and appearance attributes of vehicles, and ii) they perform remarkably well in both multi-class and intra-class vehicle classification. Experimental results exhibit promising potentials implementations of the proposed vehicle classification approaches into real-world applications.

Keywords: appearance attributes, geometric attributes, support vector machine, vehicle classification

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20871 Mite Soil as Biological Indicators the Quality of the Soil in the Forested Area of the Coast of Algeria

Authors: Soumeya Fekkoun, Djelloul Ghezali, Doumandji Salaheddine

Abstract:

The majority of the mite soil contributes to decompose the organic matter in the soil, the richness or poverty is a way of knowing the quality of the soil, in this regard we studied the ecological side of the soil mite in a forest park «coast of Algeria». 6 by taking soil samples every month for the year 2010/2011 .The samples are collected and extracted using the technique of Berlese Tullgren. It was obtained 604 individuals. These riches can indicate the fertility of soil and knead the high proportion of organic material in it. The largest number observed in the spring, followed by the separation of the 252 individuals fall 222 individuals and then the summer with 106 individuals and winter 80 individuals. Among the 18 families obtained. Scheloribatidae is the most dominant with 30.6% followed by Ceratozetidae with 16%, then Euphthiracaridae 14%. The families remain involved with low percentages. the diversity index Schanonweaver varied between 2.3 bits in the summer and 3.83 bits in the spring. As the results of the analysis statistic confirm the existence of a clear difference between the four seasons and the richness of soil mite and diversity.

Keywords: soil mite, forest, coast of Algeria, diversity

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20870 Heterogeneity of Soil Moisture and Its Impacts on the Mountainous Watershed Hydrology in Northwest China

Authors: Chansheng He, Zhongfu Wang, Xiao Bai, Jie Tian, Xin Jin

Abstract:

Heterogeneity of soil hydraulic properties directly affects hydrological processes at different scales. Understanding heterogeneity of soil hydraulic properties such as soil moisture is therefore essential for modeling watershed ecohydrological processes, particularly in hard to access, topographically complex mountainous watersheds. This study maps spatial variations of soil moisture by in situ observation network that consists of sampling points, zones, and tributaries, and monitors corresponding hydrological variables of air and soil temperatures, evapotranspiration, infiltration, and runoff in the Upper Reach of the Heihe River Watershed, a second largest inland river (terminal lake) with a drainage area of over 128,000 km² in Northwest China. Subsequently, the study uses a hydrological model, SWAT (Soil and Water Assessment Tool) to simulate the effects of heterogeneity of soil moisture on watershed hydrological processes. The spatial clustering method, Full-Order-CLK was employed to derive five soil heterogeneous zones (Configuration 97, 80, 65, 40, and 20) for soil input to SWAT. Results show the simulations by the SWAT model with the spatially clustered soil hydraulic information from the field sampling data had much better representation of the soil heterogeneity and more accurate performance than the model using the average soil property values for each soil type derived from the coarse soil datasets. Thus, incorporating detailed field sampling soil heterogeneity data greatly improves performance in hydrologic modeling.

Keywords: heterogeneity, soil moisture, SWAT, up-scaling

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20869 Impact of Fly Ash on Soil Quality in Semi-Arid Region

Authors: Anjuri Srivastava, Akhouri Nishant Bhanu

Abstract:

Soil is a natural material with a distinctive form. It is regarded to be a natural source of nutrients and minerals for plants. It meets many of our needs through the crops, trees, and inhabited places that have grown on or underneath it. Productive and rich soil plays a crucial role in both its wealth and well-being. If any external substance changes the soil's composition, it directly impacts the plant that was grown in that soil. If the soil is deficient in one or more essential components, fly ash can be utilized as fertilizer by incorporating it into the soil. This can also increase the porosity of the soil. Fly ash has a sufficient concentration of essential components to promote the growth of plants. The high concentration of elements in fly ash, including C, Na, K, Fe, and Zn, increases crop yields. Hazardous compounds harm plant life as soon as they get into the soil. The US Environmental Protection Agency and other regulatory agencies have found it as non-hazardous. By employing fly ash as a potential fertilizer supplement for degraded soils, the problem of disposing of solid waste can be partially handled. Fly ash's rapid growth can slow down mineralization because it contains a higher proportion of harmful heavy metals. The chemical characteristics, inclusion ratio, and composting process of fly ash have a significant impact on the fly ash compost’s potential to improve soil nutrition. Research institutions and regulatory agencies have been thoroughly investigating fly ash for a long time. Guard cells on plant leaves that accumulate fly ash trigger the regulatory system. Fly ash increases both chemical and physical damage at certain humidity levels. The lengthy sowing period is caused by the high levels of fly ash in the soil, which also slows down seedling germination and growth. For the sake of human health, it is crucial to consider the bioaccumulation of dangerous heavy metals and their necessary concentrations in plant tissues and soil.

Keywords: soil, fly ash, plant, fertilizer, composts

Procedia PDF Downloads 61
20868 Soil-Structure Interaction Models for the Reinforced Foundation System – A State-of-the-Art Review

Authors: Ashwini V. Chavan, Sukhanand S. Bhosale

Abstract:

Challenges of weak soil subgrade are often resolved either by stabilization or reinforcing it. However, it is also practiced to reinforce the granular fill to improve the load-settlement behavior of over weak soil strata. The inclusion of reinforcement in the engineered granular fill provided a new impetus for the development of enhanced Soil-Structure Interaction (SSI) models, also known as mechanical foundation models or lumped parameter models. Several researchers have been working in this direction to understand the mechanism of granular fill-reinforcement interaction and the response of weak soil under the application of load. These models have been developed by extending available SSI models such as the Winkler Model, Pasternak Model, Hetenyi Model, Kerr Model etc., and are helpful to visualize the load-settlement behavior of a physical system through 1-D and 2-D analysis considering beam and plate resting on the foundation respectively. Based on the literature survey, these models are categorized as ‘Reinforced Pasternak Model,’ ‘Double Beam Model,’ ‘Reinforced Timoshenko Beam Model,’ and ‘Reinforced Kerr Model.’ The present work reviews the past 30+ years of research in the field of SSI models for reinforced foundation systems, presenting the conceptual development of these models systematically and discussing their limitations. Special efforts are taken to tabulate the parameters and their significance in the load-settlement analysis, which may be helpful in future studies for the comparison and enhancement of results and findings of physical models.

Keywords: geosynthetics, mathematical modeling, reinforced foundation, soil-structure interaction, ground improvement, soft soil

Procedia PDF Downloads 96
20867 Effects of Soil Erosion on Vegetation Development

Authors: Josephine Wanja Nyatia

Abstract:

The relationship between vegetation and soil erosion deserves attention due to its scientific importance and practical applications. A great deal of information is available about the mechanisms and benefits of vegetation in the control of soil erosion, but the effects of soil erosion on vegetation development and succession is poorly documented. Research shows that soil erosion is the most important driving force for the degradation of upland and mountain ecosystems. Soil erosion interferes with the process of plant community development and vegetation succession, commencing with seed formation and impacting throughout the whole growth phase and affecting seed availability, dispersal, germination and establishment, plant community structure and spatial distribution. There have been almost no studies on the effects of soil erosion on seed development and availability, of surface flows on seed movement and redistribution, and their influences on soil seed bank and on vegetation establishment and distribution. However, these effects may be the main cause of low vegetation cover in regions of high soil erosion activity, and these issues need to be investigated. Moreover, soil erosion is not only a negative influence on vegetation succession and restoration but also a driving force of plant adaptation and evolution. Consequently, we need to study the effects of soil erosion on ecological processes and on development and regulation of vegetation succession from the points of view of pedology and vegetation, plant and seed ecology, and to establish an integrated theory and technology for deriving practical solutions to soil erosion problems

Keywords: soil erosion, vegetation, development, seed availability

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20866 Soil Properties and Yam Performance as Influenced by Poultry Manure and Tillage on an Alfisol in Southwestern Nigeria

Authors: E. O. Adeleye

Abstract:

Field experiments were conducted to investigate the effect of soil tillage techniques and poultry manure application on the soil properties and yam (Dioscorea rotundata) performance in Ondo, southwestern Nigeria for two farming seasons. Five soil tillage techniques, namely ploughing (P), ploughing plus harrowing (PH), manual ridging (MR), manual heaping (MH) and zero-tillage (ZT) each combined with and without poultry manure at the rate of 10 tha-1 were investigated. Data were obtained on soil properties, nutrient uptake, growth and yield of yam. Soil moisture content, bulk density, total porosity and post harvest soil chemical characteristics were significantly (p>0.05) influenced by soil tillage-manure treatments. Addition of poultry manure to the tillage techniques in the study increased soil total porosity, soil moisture content and reduced soil bulk density. Poultry manure improved soil organic matter, total nitrogen, available phosphorous, exchangeable Ca, k, leaf nutrients content of yam, yam growth and tuber yield relative to tillage techniques plots without poultry manure application. It is concluded that the possible deleterious effect of tillage on soil properties, growth and yield of yam on an alfisol in southwestern Nigeria can be reduced by combining tillage with poultry manure.

Keywords: poultry manure, tillage, soil chemical properties, yield

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20865 Correction Factors for Soil-Structure Interaction Predicted by Simplified Models: Axisymmetric 3D Model versus Fully 3D Model

Authors: Fu Jia

Abstract:

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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20864 Effect of Humic Acids on Agricultural Soil Structure and Stability and Its Implication on Soil Quality

Authors: Omkar Gaonkar, Indumathi Nambi, Suresh G. Kumar

Abstract:

The functional and morphological aspects of soil structure determine the soil quality. The dispersion of colloidal soil particles, especially the clay fraction and rupture of soil aggregates, both of which play an important role in soil structure development, lead to degradation of soil quality. The main objective of this work was to determine the effect of the behaviour of soil colloids on the agricultural soil structure and quality. The effect of commercial humic acid and soil natural organic matter on the electrical and structural properties of the soil colloids was also studied. Agricultural soil, belonging to the sandy loam texture class from northern part of India was considered in this study. In order to understand the changes in the soil quality in the presence and absence of humic acids, the soil fabric and structure was analyzed by X-ray diffraction (XRD), Fourier Transform Infrared (FTIR) Spectroscopy and Scanning Electron Microscopy (SEM). Electrical properties of natural soil colloids in aqueous suspensions were assessed by zeta potential measurements at varying pH values with and without the presence of humic acids. The influence of natural organic matter was analyzed by oxidizing the natural soil organic matter with hydrogen peroxide. The zeta potential of the soil colloids was found to be negative in the pH range studied. The results indicated that hydrogen peroxide treatment leads to deflocculation of colloidal soil particles. In addition, the humic acids undergoes effective adsorption onto the soil surface imparting more negative zeta potential to the colloidal soil particles. The soil hydrophilicity decreased in the presence of humic acids which was confirmed by surface free energy determination. Thus, it can be concluded that the presence of humic acids altered the soil fabric and structure, thereby affecting the soil quality. This study assumes significance in understanding soil aggregation and the interactions at soil solid-liquid interface.

Keywords: humic acids, natural organic matter, zeta potential, soil quality

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20863 Effect of the Soil-Foundation Interface Condition in the Determination of the Resistance Domain of Rigid Shallow Foundations

Authors: Nivine Abbas, Sergio Lagomarsino, Serena Cattari

Abstract:

The resistance domain of a generally loaded rigid shallow foundation is normally represented as an interaction diagram limited by a failure surface in the three dimensional (3D) load space (N, V, M), where N is the vertical centric load component, V is the horizontal load component and M is the bending moment component. Usually, this resistance domain is constructed neglecting the foundation sliding mechanism that take place at the level of soil-foundation interface once the applied horizontal load exceeds the interface frictional resistance of the foundation. This issue is translated in the literature by the fact that the failure limit in the (2D) load space (N, V) is constructed as a parabola having an initial slope, at the center of the coordinate system, that depends, in some works, only of the soil friction angle, and in other works, has an empirical value. However, considering a given geometry of the foundation lying on a given soil type, the initial slope of the failure limit must change, for instance, when varying the roughness of the foundation surface at its interface with the soil. The present study discusses the effect of the soil-foundation interface condition on the construction of the resistance domain, and proposes a correction to be applied to the failure limit in order to overcome this effect.

Keywords: soil-foundation interface, sliding mechanism, soil shearing, resistance domain, rigid shallow foundation

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20862 Detection and Classification of Mammogram Images Using Principle Component Analysis and Lazy Classifiers

Authors: Rajkumar Kolangarakandy

Abstract:

Feature extraction and selection is the primary part of any mammogram classification algorithms. The choice of feature, attribute or measurements have an important influence in any classification system. Discrete Wavelet Transformation (DWT) coefficients are one of the prominent features for representing images in frequency domain. The features obtained after the decomposition of the mammogram images using wavelet transformations have higher dimension. Even though the features are higher in dimension, they were highly correlated and redundant in nature. The dimensionality reduction techniques play an important role in selecting the optimum number of features from the higher dimension data, which are highly correlated. PCA is a mathematical tool that reduces the dimensionality of the data while retaining most of the variation in the dataset. In this paper, a multilevel classification of mammogram images using reduced discrete wavelet transformation coefficients and lazy classifiers is proposed. The classification is accomplished in two different levels. In the first level, mammogram ROIs extracted from the dataset is classified as normal and abnormal types. In the second level, all the abnormal mammogram ROIs is classified into benign and malignant too. A further classification is also accomplished based on the variation in structure and intensity distribution of the images in the dataset. The Lazy classifiers called Kstar, IBL and LWL are used for classification. The classification results obtained with the reduced feature set is highly promising and the result is also compared with the performance obtained without dimension reduction.

Keywords: PCA, wavelet transformation, lazy classifiers, Kstar, IBL, LWL

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20861 Using Electro-Biogrouting to Stabilize of Soft Soil

Authors: Hamed A. Keykha, Hadi Miri

Abstract:

This paper describes a new method of soil stabilisation, electro-biogrouting (EBM), for improvement of soft soil with low hydraulic conductivity. This method uses an applied voltage gradient across the soil to induce the ions and bacteria cells through the soil matrix, resulting in CaCO3 precipitation and an increase of the soil shear strength in the process. The EBM were used effectively with two injection methods; bacteria injection and products of bacteria injection. The bacteria cells, calcium ions and urea were moved across the soil by electromigration and electro osmotic flow respectively. The products of bacteria (CO3-2) were moved by electromigration. The results showed that the undrained shear strength of the soil increased from 6 to 65 and 70 kPa for first and second injection method respectively. The injection of carbonate solution and calcium could be effectively flowed in the clay soil compare to injection of bacteria cells. The detection of CaCO3 percentage and its corresponding water content across the specimen showed that the increase of undrained shear strength relates to the deposit of calcite crystals between soil particles.

Keywords: Sporosarcina pasteurii, electrophoresis, electromigration, electroosmosis, biocement

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20860 Automatic Classification of Lung Diseases from CT Images

Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

Abstract:

Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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20859 Investigating the Impacts of Climate Change on Soil Erosion: A Case Study of Kasilian Watershed, Northern Iran

Authors: Mohammad Zare, Mahbubeh Sheikh

Abstract:

Many of the impact of climate change will material through change in soil erosion which were rarely addressed in Iran. This paper presents an investigation of the impacts of climate change soil erosin for the Kasilian basin. LARS-WG5 was used to downscale the IPCM4 and GFCM21 predictions of the A2 scenarios for the projected periods of 1985-2030 and 2080-2099. This analysis was carried out by means of the dataset the International Centre for Theoretical Physics (ICTP) of Trieste. Soil loss modeling using Revised Universal Soil Loss Equation (RUSLE). Results indicate that soil erosion increase or decrease, depending on which climate scenarios are considered. The potential for climate change to increase soil loss rate, soil erosion in future periods was established, whereas considerable decreases in erosion are projected when land use is increased from baseline periods.

Keywords: Kasilian watershed, climatic change, soil erosion, LARS-WG5 Model, RUSLE

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20858 Assessment of Soil Quality Indicators in Rice Soils Under Rainfed Ecosystem

Authors: R. Kaleeswari

Abstract:

An investigation was carried out to assess the soil biological quality parameters in rice soils under rainfed and to compare soil quality indexing methods viz., Principal component analysis, Minimum data set and Indicator scoring method and to develop soil quality indices for formulating soil and crop management strategies.Soil samples were collected and analyzed for soil biological properties by adopting standard procedure. Biological indicators were determined for soil quality assessment, viz., microbial biomass carbon and nitrogen (MBC and MBN), potentially mineralizable nitrogen (PMN) and soil respiration and dehydrogenease activity. Among the methods of rice cultivation, Organic nutrition, Integrated Nutrient Management (INM) and System of Rice Intensification (SRI ), rice cultivation registered higher values of MBC, MBN and PMN. Mechanical and conventional rice cultivation registered lower values of biological quality indicators. Organic nutrient management and INM enhanced the soil respiration rate. SRI and aerobic rice cultivation methods increased the rate of soil respiration, while conventional and mechanical rice farming lowered the soil respiration rate. Dehydrogenase activity (DHA) was registered to be higher in soils under organic nutrition and Integrated Nutrient Management INM. System of Rice Intensification SRI and aerobic rice cultivation enhanced the DHA; while conventional and mechanical rice cultivation methods reduced DHA. The microbial biomass carbon (MBC) of the rice soils varied from 65 to 244 mg kg-1. Among the nutrient management practices, INM registered the highest available microbial biomass carbon of 285 mg kg-1.Potentially mineralizable N content of the rice soils varied from 20.3 to 56.8 mg kg-1. Aerobic rice farming registered the highest potentially mineralizable N of 78.9 mg kg-1..The soil respiration rate of the rice soils varied from 60 to 125 µgCO2 g-1. Nutrient management practices ofINM practice registered the highest. soil respiration rate of 129 µgCO2 g-1.The dehydrogenase activity of the rice soils varied from 38.3 to 135.3µgTPFg-1 day-1. SRI method of rice cultivation registered the highest dehydrogenase activity of 160.2 µgTPFg-1 day-1. Soil variables from each PC were considered for minimum soil data set (MDS). Principal component analysis (PCA) was used to select the representative soil quality indicators. In intensive rice cultivating regions, soil quality indicators were selected based on factor loading value and contribution percentage value using principal component analysis (PCA).Variables having significant difference within production systems were used for the preparation of minimum data set (MDS).

Keywords: soil quality, rice, biological properties, PCA analysis

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20857 Performance Analysis of Traffic Classification with Machine Learning

Authors: Htay Htay Yi, Zin May Aye

Abstract:

Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: false negative rate, intrusion detection system, machine learning methods, performance

Procedia PDF Downloads 96