Search results for: soil classification

Authors: Valentina Rodas, Luis Almache

Abstract:

The interaction effects between the existing soil and the substructure of a 5-story building with an underground one were evaluated in such a way that the structural-geotechnical concepts were validated through the method of impedance factors with a program based on the method of the finite elements. The continuous wall-type foundation had a constant thickness and followed inclined and orthogonal directions, while the ground had homogeneous and medium-type characteristics. The soil considered was type C according to the Ecuadorian Construction Standard (NEC) and the corresponding foundation comprised a depth of 4.00 meters and a basement wall thickness of 40 centimeters. This project is part of a mid-rise building in the city of Azogues (Ecuador). The hypotheses raised responded to the objectives in such a way that the model implemented with springs had a variation with respect to the embedded base, obtaining conservative results.

Keywords: interaction, soil, substructure, springs, effects, modeling , embedment

Procedia PDF Downloads 230

Authors: Intissar Farid

Abstract:

Groundwater quality assessment is crucial for sustainable water use, especially in semi-arid regions like the Jeloula basin in Tunisia, where groundwater is essential for domestic and agricultural needs. The present research aims to characterize the suitability of groundwater for irrigational purposes by considering various parameters: total salt concentration as measured by Electrical Conductivity EC, relative proportions of Na⁺ as expressed by %Na and SAR, Kelly’s ratio, Permeability Index, Magnesium hazard and Residual Sodium chloride. Chemical data indicate that the percent sodium (%Na) in the study area ranged from 26.3 to 45.3%. According to the Wilcox diagram, the quality classification of irrigation water suggests that analyzed groundwaters are suitable for irrigation purposes. The SAR values vary between 2.1 and 5. Most of the groundwater samples plot in the Richards’C3S1 water class and indicate little danger from sodium content to soil and plant growth. The Kelly’s ratio of the analyzed samples ranged from 0.3 to 0.8. These values indicate that the waters are fit for agricultural purposes. Magnesium hazard (MH) values range from 27.5 to 52.6, with an average of 38.9 in the analyzed waters. Hence, the Mg²⁺ content of the groundwater from the shallow aquifer cannot cause any problem to the soil permeability. Permeability index (PI) values computed for the area ranged from 33.6 to 52.7%. The above result, therefore, suggests that most of the water samples fall within class I of the Doneen chart and can be categorized as good irrigation water. The groundwaters collected from the Jeloula shallow aquifer were found to be within the safe limits and thus suitable for irrigation purposes.

Keywords: Kelly's ratio, magnesium hazard, permeability index, residual sodium chloride

Procedia PDF Downloads 26

Authors: Ehsan Pegah, Huabei Liu

Abstract:

Determination of the internal friction angle (φ) in natural soil deposits is an important issue in geotechnical engineering. The main objective of this study was to examine the evaluation of this parameter in overconsolidated granular soil deposits by using the P-wave velocity and the anisotropic components of S-wave velocity (i.e., both the vertical component (SV) and the horizontal component (SH) of S-wave). To this end, seventeen pairs of P-wave and S-wave seismic refraction profiles were carried out at three different granular sites in Iran using non-invasive seismic wave methods. The acquired shot gathers were processed, from which the P-wave, SV-wave and SH-wave velocities were derived. The reference values of φ and overconsolidation ratio (OCR) in the soil deposits were measured through laboratory tests. By assuming cross-anisotropy of the soils, the P-wave and S-wave velocities were utilized to develop an equation for calculating the coefficient of lateral earth pressure at-rest (K₀) based on the theory of elasticity for a cross-anisotropic medium. In addition, to develop an equation for OCR estimation in granular geomaterials in terms of SH/SV velocity ratios, a general regression analysis was performed on the resulting information from this research incorporated with the respective data published in the literature. The calculated K₀ values coupled with the estimated OCR values were finally employed in the Mayne and Kulhawy formula to evaluate φ in granular soil deposits. The results showed that reliable values of φ could be estimated based on the seismic wave velocities. The findings of this study may be used as the appropriate approaches for economic and non-invasive determination of in-situ φ in granular soil deposits using the surface seismic surveys.

Keywords: angle of internal friction, overconsolidation ratio, granular soils, P-wave velocity, SV-wave velocity, SH-wave velocity

Procedia PDF Downloads 158

Authors: Majid Habib Khan, Jinwei Zhao, Xinhong Hei, Liu Jiedong, Rana Shahzad Noor, Muhammad Imran

Abstract:

Deep learning is increasingly employed in image classification, yet the scarcity and high cost of labeled data for training remain a challenge. Limited samples often lead to overfitting due to biased sample distribution. This paper introduces a dynamic distribution calibration method for few-shot learning. Initially, base and new class samples undergo normalization to mitigate disparate feature magnitudes. A pre-trained model then extracts feature vectors from both classes. The method dynamically selects distribution characteristics from base classes (both adjacent and remote) in the embedding space, using a threshold value approach for new class samples. Given the propensity of similar classes to share feature distributions like mean and variance, this research assumes a Gaussian distribution for feature vectors. Subsequently, distributional features of new class samples are calibrated using a corrected hyperparameter, derived from the distribution features of both adjacent and distant base classes. This calibration augments the new class sample set. The technique demonstrates significant improvements, with up to 4% accuracy gains in few-shot classification challenges, as evidenced by tests on miniImagenet and CUB datasets.

Keywords: deep learning, computer vision, image classification, few-shot learning, threshold

Procedia PDF Downloads 66

Authors: Mekamı Hayet, Bounoua Nacer, Benabderrahmane Sidahmed, Taleb Ahmed

Abstract:

Pose estimation is an important task in computer vision. Though the majority of the existing solutions provide good accuracy results, they are often overly complex and computationally expensive. In this perspective, we propose the use of dimensionality reduction techniques to address the problem of facial pose estimation. Firstly, a face image is converted into one-dimensional time series using Hilbert space filling curve, then the approach converts these time series data to a symbolic representation. Furthermore, a distance matrix is calculated between symbolic series of an input learning dataset of images, to generate classifiers of frontal vs. profile face pose. The proposed method is evaluated with three public datasets. Experimental results have shown that our approach is able to achieve a correct classification rate exceeding 97% with K-NN algorithm.

Keywords: machine learning, pattern recognition, facial pose classification, time series

Procedia PDF Downloads 350

Authors: Kenan Morani, Esra Kaya Ayana

Abstract:

This study aimed to develop a novel pipeline for COVID-19 detection using a large and rigorously annotated database of computed tomography (CT) images. The pipeline consists of UNet-based segmentation, lung extraction, and a classification part, with the addition of optional slice removal techniques following the segmentation part. In this work, a batch normalization was added to the original UNet model to produce lighter and better localization, which is then utilized to build a full pipeline for COVID-19 diagnosis. To evaluate the effectiveness of the proposed pipeline, various segmentation methods were compared in terms of their performance and complexity. The proposed segmentation method with batch normalization outperformed traditional methods and other alternatives, resulting in a higher dice score on a publicly available dataset. Moreover, at the slice level, the proposed pipeline demonstrated high validation accuracy, indicating the efficiency of predicting 2D slices. At the patient level, the full approach exhibited higher validation accuracy and macro F1 score compared to other alternatives, surpassing the baseline. The classification component of the proposed pipeline utilizes a convolutional neural network (CNN) to make final diagnosis decisions. The COV19-CT-DB dataset, which contains a large number of CT scans with various types of slices and rigorously annotated for COVID-19 detection, was utilized for classification. The proposed pipeline outperformed many other alternatives on the dataset.

Keywords: classification, computed tomography, lung extraction, macro F1 score, UNet segmentation

Procedia PDF Downloads 131

Authors: Guoliang Lu, Changhou Lu, Xueyong Li

Abstract:

In action recognition, previous studies have demonstrated the effectiveness of using multiple features to improve the recognition performance. We focus on two practical issues: i) most studies use a direct way of concatenating/accumulating multi features to evaluate the similarity between two actions. This way could be too strong since each kind of feature can include different dimensions, quantities, etc; ii) in many studies, the employed classification methods lack of a flexible and effective mechanism to add new feature(s) into classification. In this paper, we explore an unified scheme based on recently-proposed multi-dimensional dynamic time warping (MD-DTW). Experiments demonstrated the scheme's effectiveness of combining multi-feature and the flexibility of adding new feature(s) to increase the recognition performance. In addition, the explored scheme also provides us an open architecture for using new advanced classification methods in the future to enhance action recognition.

Keywords: action recognition, multi features, dynamic time warping, feature combination

Procedia PDF Downloads 437

Authors: Abbas S. Alwan, Waleed K. Hussan

Abstract:

In this paper, a general verification of possible heat treatment of steel has been done with the view of conditions of real abrasive wear of rotivater with soil texture. This technique is found promising to improve the quality of agriculture components working with the soil in dry condition. Abrasive wear resistance is very important in many applications and in most cases it is directly correlated with the hardness of materials surface. Responded of heat treatments were carried out in various media (Still air, Cottonseed oil, and Brine water 10 %) and follow by low-temperature tempering (250°C) was applied on steel type (AISI 1030). After heat treatment was applied wear with soil texture by using tillage process to determine the (actual wear rate) of the specimens depending on weight loss method. It was found; the wear resistance Increases with increase hardness with varying quenching media as follows; 30 HRC, 45 HRC, 52 HRC, and 60 HRC for nontreated (as received) cooling media as still air, cottonseed oil, and Brine water 10 %, respectively. Martensitic structure with retained austenite can be obtained depending on the quenching medium. Wear was presented on the worn surfaces of the steels which were used in this work.

Keywords: microstructures, hardness, abrasive wear, heat treatment, soil texture

Procedia PDF Downloads 388

Authors: Shirin Aghanajafizadeh

Abstract:

Nest site selection of Crested Lark was investigated in Boroyeh wildlife sanctuary of Harat during spring 2014. Habitat variables such as number of plant species, soil texture, distance to the nearest water resources, farms and roads were compared in the species presence plots with absence ones. Our analysis showed that the average number of Zygophyllum atriplicoidesand, Artemisia sieberi were higher while fine-textured soil percent cover (with very little and gravel) was lower in species presence plots than control plots. We resulted that the most affecting factor in the species nest site selection is the number of Z .atriplicoides and soil texture. Z. atriplicoides and A. sieberi can provide cover for nests and chickens against predators and environmental harsh events such as sunshine and wind. The stability of built nest forces the birds to select sites with not fine-textured soil. Some of the nests were detected in Alfalfa farms that can be related to its cover producing capability.

Keywords: habitat selection, Yazd Province, presence and absence plots, habitat variables

Procedia PDF Downloads 186

Authors: Miguel A. Orellana, Sonia E. Ruiz, Juan Bojórquez

Abstract:

Optimal load factors (dead, live and seismic) used for the design of buildings may be different, depending of the seismic ground motion characteristics to which they are subjected, which are closely related to the type of soil conditions where the structures are located. The influence of the type of soil on those load factors, is analyzed in the present study. A methodology that is useful for establishing optimal load factors that minimize the cost over the life cycle of the structure is employed; and as a restriction, it is established that the probability of structural failure must be less than or equal to a prescribed value. The life-cycle cost model used here includes different types of costs. The optimization methodology is applied to two groups of reinforced concrete buildings. One set (consisting on 4-, 7-, and 10-story buildings) is located on firm ground (with a dominant period Ts=0.5 s) and the other (consisting on 6-, 12-, and 16-story buildings) on soft soil (Ts=1.5 s) of Mexico City. Each group of buildings is designed using different combinations of load factors. The statistics of the maximums inter-story drifts (associated with the structural capacity) are found by means of incremental dynamic analyses. The buildings located on firm zone are analyzed under the action of 10 strong seismic records, and those on soft zone, under 13 strong ground motions. All the motions correspond to seismic subduction events with magnitudes M=6.9. Then, the structural damage and the expected total costs, corresponding to each group of buildings, are estimated. It is concluded that the optimal load factors combination is different for the design of buildings located on firm ground than that for buildings located on soft soil.

Keywords: life-cycle cost, optimal load factors, reinforced concrete buildings, total costs, type of soil

Procedia PDF Downloads 306

Authors: Arash Poordana, Reza Ziaie Moayed

Abstract:

Calcareous sands are found most commonly in areas adjacent to crude oil and gas, and particularly around water. These types of soil have high compressibility due to high inter-granular porosity, irregularity, fragility, and especially crushing. Also, based on experience, it has been shown that the behavior of these types of soil is not similar to silica sand in loading. Since the destructive effects of cement on the environment are obvious, other alternatives such as bentonite are popular to be used. Bentonite has always been used commercially in civil engineering projects and according to its low hydraulic conductivity, it is used for landfills, cut-off walls, and nuclear wastelands. In the present study, unconfined compression tests in five ageing periods (1, 3, 7, 14, and 28 days) after mixing different percentages of bentonite (5%, 7.5% and 10%) with Bushehr calcareous sand were performed. The relative density considered for the specimens is 50%. Optimum water content was then added to each specimen accordingly (19%, 18.5%, and 17.5%). The sample preparation method was wet tamping and the specimens were compacted in five layers. It can be concluded from the results that as the bentonite content increases, the unconfined compression strength of the soil increases. Based on the obtained results, 3-day and 7-day ageing periods showed 30% and 50% increase in the shear strength of soil, respectively.

Keywords: unconfined compression test, bentonite, Bushehr, calcareous sand

Procedia PDF Downloads 129

Authors: Joël Passicousset, David Gilbert, Chloé Chervier-Legourd, Emmanuel Caron-Garant, Didier Labarre

Abstract:

Living soil agriculture tries to reconciliate food production while improving soil health, soil biodiversity, soil fertility and more generally attenuating the inherent environmental drawbacks induced by modern agriculture. Using appropriate organic materials as soil amendments has a role to play in the aim of increasing the soil organic matter, improving soil fertility, sequestering carbon, and diminishing the dependence on both mineral fertilizer and pesticides. Insect farming consists in producing insects that can be used as a rich-in-protein and entomo-based food. Usually, detritivores are chosen, thus they can be fed with food wastes, which contributes to circular economy while producing low-carbon food. This process also produces frass, made of insect feces, exuvial material, and non-digested fibrous material, that have valuable fertilizer and biostimulation properties. But frass, used as a sole fertilizer on a crop may be not completely adequate for plants’ needs. This is why this project considers black soldier fly (termed BSF, one of the three main insect species grown commercially) frass as a complementary fertilizer, both in organic and in conventional contexts. Three kinds of experiments are made to understand the behaviour of fertilizer treatments based on frass incorporation. Lab-scale mineralization experiments suggest that BSF frass alone mineralizes more slowly than chicken manure alone (CM), but at a ratio of 90% CM-10% BSF frass, the mineralization rate of the mixture is higher than both frass and CM individually. For example, in the 7 days following the fertilization with same nitrogen amount introduced among treatments, around 80% of the nitrogen content supplied through 90% CM-10% BSF frass fertilization is present in the soil under mineral forms, compared to roughly 60% for commercial CM fertilization and 45% with BSF-frass. This suggests that BSF frass contains a more recalcitrant form of organic nitrogen than CM, but also that BSF frass has a highly active microbiota that can increase CM mineralization rate. Consequently, when progressive mineralization is needed, pure BSF-frass may be a consistent option from an agronomic aspect whereas, for specific crops that require spikes of readily available nitrogen sources (like cranberry), fast release 90CM-10BSF frass biofertilizer are more appropriate. Field experiments on cranberry suggests that, indeed, 90CM-10BSF frass is a potent candidate for organic cranberry production, as currently, organic growers rely solely on CM, whose mineralization kinetics are known to imperfectly match plant’s needs, which is known to be a major reason that sustains the current yield gap between conventional and organic cranberry sectors.

Keywords: soil mineralization, biofertilizer, BSF-frass, chicken manure, soil functions, nitrogen, soil microbiota

Procedia PDF Downloads 70

Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

Abstract:

Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: multiclass classification, convolution neural network, OpenCV

Procedia PDF Downloads 176

Authors: Ebtehal Aljedaani, Maha Aljohani

Abstract:

Privacy and security patterns are both important for developing software that protects users' data and privacy. Privacy patterns are designed to address common privacy problems, such as unauthorized data collection and disclosure. Security patterns are designed to protect software from attack and ensure reliability and trustworthiness. Using privacy and security patterns, software engineers can implement security and privacy by design principles, which means that security and privacy are considered throughout the software development process. These patterns are available to translate "security & privacy-by-design" into practical advice for software engineering. Previous research on privacy and security patterns has typically focused on one category of patterns at a time. This paper aims to bridge this gap by merging the two categories and identifying their similarities and differences. To do this, the authors conducted a systematic literature review of 25 research papers on privacy and security patterns. The papers were analysed based on the category of the pattern, the classification of the pattern, and the security requirements that the pattern addresses. This paper presents the results of a comprehensive review of privacy and security design patterns. The review is intended to help future IT designers understand the relationship between the two types of patterns and how to use them to design secure and privacy-preserving software. The paper provides a clear classification of privacy and security design patterns, along with examples of each type. The authors found that there is only one widely accepted classification of privacy design patterns, while there are several competing classifications of security design patterns. Three types of security design patterns were found to be the most commonly used.

Keywords: design patterns, security, privacy, classification of patterns, security patterns, privacy patterns

Procedia PDF Downloads 132

Authors: R. R. Ramsheeja, R. Sreeraj

Abstract:

For view the internal structures of the human body such as liver, brain, kidney etc have a wide range of different modalities for medical images are provided nowadays. Computer Tomography is one of the most significant medical image modalities. In this paper use CT liver images for study the use of automatic computer aided techniques to calculate the volume of the liver tumor. Segmentation method is used for the detection of tumor from the CT scan is proposed. Gaussian filter is used for denoising the liver image and Adaptive Thresholding algorithm is used for segmentation. Multiple Region Of Interest(ROI) based method that may help to characteristic the feature different. It provides a significant impact on classification performance. Due to the characteristic of liver tumor lesion, inherent difficulties appear selective. For a better performance, a novel proposed system is introduced. Multiple ROI based feature selection and classification are performed. In order to obtain of relevant features for Support Vector Machine(SVM) classifier is important for better generalization performance. The proposed system helps to improve the better classification performance, reason in which we can see a significant reduction of features is used. The diagnosis of liver cancer from the computer tomography images is very difficult in nature. Early detection of liver tumor is very helpful to save the human life.

Keywords: computed tomography (CT), multiple region of interest(ROI), feature values, segmentation, SVM classification

Procedia PDF Downloads 509

Authors: Mohamed ElMasry, Ahmad Ragheb, Tareq AbdelAziz, Mohamed Ghazy

Abstract:

Choosing the suitable infrastructure system is becoming more challenging with the increase in demand for heavier structures contemporarily. This is the case where piled raft foundations have been widely used around the world to support heavy structures without extensive settlement. In the latter system, piles are rigidly connected to the raft, and most of the load goes to the soil layer on which the piles are bearing. In spite of that, when soil profiles contain thicker soft clay layers near the surface, or at relatively shallow depths, it is unfavorable to use the rigid piled raft foundation system. Consequently, the disconnected piled raft system was introduced as an alternative approach for the rigidly connected system. In this system, piles are disconnected from the raft using a cushion of soil, mostly of a granular interlayer. The cushion is used to redistribute the stresses among the piles and the subsoil. Piles are also used to stiffen the subsoil, and by this way reduce the settlement without being rigidly connected to the raft. However, the seismic loading effect on such disconnected foundation systems remains a problem, since the soil profiles may include thick clay layers which raise risks of amplification of the dynamic earthquake loads. In this paper, the effects of seismic behavior on the connected and disconnected piled raft systems are studied through a numerical model using Midas GTS NX Software. The study concerns the soil-structure interaction and the expected behavior of the systems. Advantages and disadvantages of each foundation approach are studied, and a comparison between the results are presented to show the effects of using disconnected piled raft systems in highly seismic zones. This was done by showing the excitation amplification in each of the foundation systems.

Keywords: soil-structure interaction, disconnected piled-raft, risks, seismic zones

Procedia PDF Downloads 265

Authors: Hakima Althalb

Abstract:

Petroleum contamination of sandy soils is a severe environmental problem in Libya, but relatively little work has been carried out to optimize the bioremediation of such heavily contaminated soil, particularly at a pilot scale. The purpose of this research was to determine the potential for the microbial-based bioremediation of hydrocarbon-contaminated soil obtained from an oil refinery in Libya and to assess the potential of both ozonation and phytoremediation (both applied after initial bioremediation) to reduce residual hydrocarbon levels. Plots containing 500 kg soil (triplicates) (contaminated soil diluted with clean soil 50% volume) were set up, (designated as Land Treatment Units; LTUs) containing five different nutrient levels and mixtures (Urea + NPK (nitrogen; phosphor; potassium) mixtures) to obtain C:N:P ratios 100:10:1, and monitored for 90 days. Hydrocarbon levels, microbial numbers, and toxicity (EC50 using luminescent microbial based tests) were assessed. Hydrocarbon levels in non-diluted and diluted soil ranged from 20 733-22 366 mg/kg and from 16 000-17 000 mg/kg respectively. Although all the land treatment units revealed a significant hydrocarbon reduction over time, the highest reduction in hydrocarbon levels obtained was around 60%. For example, 63% hydrocarbon removal was observed using a mixture of urea and NPK with a C:N:P ratio of 100:10:1). Soil toxicity (as assessed using luminescence based toxicity assays) reduced in line with the reduction in total petroleum hydrocarbons observed. However, as relatively high residual TPH (total petroleum hydrocarbon) levels (ranging from 6033-14166mg/kg) were still present after initial bioremediation two ‘post-treatments’ (phytoremediation and ozonation) were attempted to remove residual hydrocarbons remaining. Five locally grown (agriculturally important) plant species were tested. The germination of all plants examined was strongly inhibited (80-100%) and seedlings failed to grow well in the contaminated soil, indicating that the previously bioremediated soils were still toxic to the plants. Subsequent ozonation followed by another bioremediation of soil was more successful than phytoremediation. But even the most promising successful treatment in this study (ozonation for 6 hours at 25ppm followed by bioremediation) still only removed approximately 31% of the residual hydrocarbons. Overall, this work showed that the bioremediation of such highly contaminated soils is difficult and that a combination of treatments would be required to achieve successful remediation. Even after initial dilution and bioremediation the soils remained toxic to plant growth and were therefore not suitable for phytoremediation.

Keywords: bioremediation, petroleum hydrocarbons, ozone, phytoremediation

Procedia PDF Downloads 183

Authors: Rosna Mat Taha, Sakinah Abdullah, Sadegh Mohajer, Asmah Awal

Abstract:

Lycium barbarum L. (Goji) belongs to Solanaceae family and native to some areas of China. Ethnobotanical studies have shown that this plant has been consumed by the Chinese since ancient times. It has been used as medicine in providing excellent effects on cardiovascular system and cholesterol level, besides contains high antioxidant and antidiabetic properties. In the present study, some tissue culture work has been carried out to induce callus, in vitro regeneration from various explants of Goji and also some acclimatization protocols were followed to transfer the regenerated plants to soil. The main aims being to establish high efficient regeneration system for mass production and commercialization for future uses, since the growth of this species is very limited in Malaysia. The optimum hormonal regime and the most suitable and responsive explants were identified. It was found that leaves and stems gave good responses. Murashige and Skoog’s (MS) medium supplemented with 2.0 mg/L NAA and 0.5 mg/L BAP was the best for callus induction and MS media fortified with 1.0 mg/L NAA and 1.0 mg/L BAP was optimum for in vitro regeneration. The survival rates of plantlets after acclimatization was 63±1.5 % on black soil and 50±1.3 % on mixed soil (combination of black and red soil at a ratio of 2 to 1), respectively.

Keywords: callus, acclimatization, in vitro culture, regeneration

Procedia PDF Downloads 446

Authors: Mayank Gupta, Siba Prasad Samal, Vasu Kakkirala

Abstract:

The internet world and its priorities have changed considerably in the last decade. Browsing on smart phones has increased manifold and is set to explode much more. Users spent considerable time browsing different websites, that gives a great deal of insight into user’s preferences. Instead of plain information classifying different aspects of browsing like Bookmarks, History, and Download Manager into useful categories would improve and enhance the user’s experience. Most of the classification solutions are server side that involves maintaining server and other heavy resources. It has security constraints and maybe misses on contextual data during classification. On device, classification solves many such problems, but the challenge is to achieve accuracy on classification with resource constraints. This on device classification can be much more useful in personalization, reducing dependency on cloud connectivity and better privacy/security. This approach provides more relevant results as compared to current standalone solutions because it uses content rendered by browser which is customized by the content provider based on user’s profile. This paper proposes a Naive Bayes based lightweight classification engine targeted for a resource constraint devices. Our solution integrates with Web Browser that in turn triggers classification algorithm. Whenever a user browses a webpage, this solution extracts DOM Tree data from the browser’s rendering engine. This DOM data is a dynamic, contextual and secure data that can’t be replicated. This proposal extracts different features of the webpage that runs on an algorithm to classify into multiple categories. Naive Bayes based engine is chosen in this solution for its inherent advantages in using limited resources compared to other classification algorithms like Support Vector Machine, Neural Networks, etc. Naive Bayes classification requires small memory footprint and less computation suitable for smartphone environment. This solution has a feature to partition the model into multiple chunks that in turn will facilitate less usage of memory instead of loading a complete model. Classification of the webpages done through integrated engine is faster, more relevant and energy efficient than other standalone on device solution. This classification engine has been tested on Samsung Z3 Tizen hardware. The Engine is integrated into Tizen Browser that uses Chromium Rendering Engine. For this solution, extensive dataset is sourced from dmoztools.net and cleaned. This cleaned dataset has 227.5K webpages which are divided into 8 generic categories ('education', 'games', 'health', 'entertainment', 'news', 'shopping', 'sports', 'travel'). Our browser integrated solution has resulted in 15% less memory usage (due to partition method) and 24% less power consumption in comparison with standalone solution. This solution considered 70% of the dataset for training the data model and the rest 30% dataset for testing. An average accuracy of ~96.3% is achieved across the above mentioned 8 categories. This engine can be further extended for suggesting Dynamic tags and using the classification for differential uses cases to enhance browsing experience.

Keywords: chromium, lightweight engine, mobile computing, Naive Bayes, Tizen, web browser, webpage classification

Procedia PDF Downloads 163

Authors: Sakshi Batra, Suresh Gupta, Pratik Pande, Navneet Kaur, Lovdeep Kaur

Abstract:

The objective of this study is removal of Methylene blue dye or reactive orange-16 from industrial waste water or from soil using bioremediation technique. As huge amount of dyes are releasing from textile industry in water and soil environment during dyeing process. In this study, we focused on removal of Methylene blue dye and Reactive orange dye from industrial soil at different initial concentration of dye. An experiment study was carried out at methylene blue dye or Reactive orange-16 dye at varying concentration of both the dye as 50 ppm, 100ppm, 200 ppm, 300 ppm and 400 ppm. Maximum removal is obtained at 16-20 hours Experiments are carried out for pH, Temperature and MSM composition. The final concentration has been observed by UV-VIS. The two species has been isolated from the Industrial effluent. Finally the product analysis has been done by GC-MS.

Keywords: bioremediation, cultural growth, dyes, environment

Procedia PDF Downloads 319

Authors: Doyin Afolabi, Phillip Adewole, Oladipupo Sennaike

Abstract:

Most well-known classifiers, including the decision tree algorithm, can make predictions on balanced datasets efficiently. However, the decision tree algorithm tends to be biased towards imbalanced datasets because of the skewness of the distribution of such datasets. To overcome this problem, this study proposes a weighted decision tree algorithm that aims to remove the bias toward the majority class and prevents the reduction of majority observations in imbalance datasets classification. The proposed weighted decision tree algorithm was tested on three imbalanced datasets- cancer dataset, german credit dataset, and banknote dataset. The specificity, sensitivity, and accuracy metrics were used to evaluate the performance of the proposed decision tree algorithm on the datasets. The evaluation results show that for some of the weights of our proposed decision tree, the specificity, sensitivity, and accuracy metrics gave better results compared to that of the ID3 decision tree and decision tree induced with minority entropy for all three datasets.

Keywords: data mining, decision tree, classification, imbalance dataset

Procedia PDF Downloads 137

Authors: Eiman Kattan

Abstract:

This study aims to evaluate the impact of classifying labelled remote sensing images conventional neural network (CNN) architecture, i.e., AlexNet on different land cover scenarios based on two remotely sensed datasets from different point of views such as the computational time and performance. Thus, a set of experiments were conducted to specify the effectiveness of the selected convolutional neural network using two implementing approaches, named fully trained and fine-tuned. For validation purposes, two remote sensing datasets, AID, and RSSCN7 which are publicly available and have different land covers features were used in the experiments. These datasets have a wide diversity of input data, number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in training, validation, and testing. As a result, the fully trained approach has achieved a trivial result for both of the two data sets, AID and RSSCN7 by 73.346% and 71.857% within 24 min, 1 sec and 8 min, 3 sec respectively. However, dramatic improvement of the classification performance using the fine-tuning approach has been recorded by 92.5% and 91% respectively within 24min, 44 secs and 8 min 41 sec respectively. The represented conclusion opens the opportunities for a better classification performance in various applications such as agriculture and crops remote sensing.

Keywords: conventional neural network, remote sensing, land cover, land use

Procedia PDF Downloads 370

Authors: Arian Hosseini, Mahmudul Hasan

Abstract:

To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

Procedia PDF Downloads 55

Authors: J. Dharmaraj, C. Gunasekaran

Abstract:

Invertebrates are the reliable ecological indicators of disturbance of the forest ecosystems and they respond to environment changes more quickly than other fauna. Among these the terrestrial invertebrates are vital to functioning ecosystems, contributing to processes such as decomposition, nutrient cycling and soil fertility. The natural ecosystems of the forests have been subject to various types of disturbances, which lead to decline of flora and fauna. The comparative diversity of micro-arthropods in natural forest, wattle plantation and eucalyptus plantations were studied in Nilgiris. The study area was divided in to five major sites (Emerald (Site-I), Thalaikundha (Site-II), Kodapmund (Site-III), Aravankad (Site-IV), Kattabettu (Site-V). The research was conducted during period from March 2014 to August 2014. The leaf and soil samples were collected and isolated by using Berlese funnel extraction methods. Specimens were isolated and identified according to their morphology (Balogh 1972). In the present study results clearly showed the variation in soil pH, NPK (Major Nutrients) and organic carbon among the study sites. The chemical components of the leaf litters of the plantation decreased the diversity of micro-arthropods and decomposition rate leads to low amount of carbon and other nutrients present in the soil. Moreover eucalyptus and wattle plantations decreases the availability of the ground water source to other plantations and micro-arthropods and hences affects the soil fertility. Hence, the present study suggests to minimize the growth of wattle and eucalyptus tree plantations in the natural areas which may help to reduce the decline of forests.

Keywords: micro-arthropods, assemblage, berlese funnel, morphology, NPK, nilgiris

Procedia PDF Downloads 308

Authors: Ale M. O., Manuwa S. I., Olukunle O. J., Ewetumo T.

Abstract:

Five varying speeds of 1.5, 1.8, 2.1, 2.3, and 2.6 km/h were used at a constant soil depth of 100 mm to determine the effects of forward speed on the draught requirement of a semi-automatic cassava planter under the pneumatic wheel and rigid wheel usage on a well prepared sandy clay loam soil. The soil draught was electronically measured using an on-the-go soil draught measuring instrumentation system developed for the purpose of this research. The results showed an exponential relationship between forward speed and draught, in which draught ranging between 24.91 and 744.44N increased with an increase in forward speed in the rigid wheel experiment. This is contrary to the polynomial relationship observed in the pneumatic wheel experiment in which the draught varied between 96.09 and 343.53 N. It was observed in the experiments that the optimum speed of 1.5 km/h had the least values of draught in both the pneumatic wheel and rigid wheel experiments, with higher values in the pneumatic experiment. It was generally noted that the rigid wheel planter with less value of draught requires less energy required for operation. It is therefore concluded that operating the semi-automatic cassava planter with rigid wheels will be more economical for cassava farmers than operating the planter with pneumatic wheels.

Keywords: Cassava planter, planting, forward speed, draught, wheel type

Procedia PDF Downloads 96

Authors: Reza Ziaie Moayed, Saeideh Mohammadi

Abstract:

Soft soil is used in many of civil engineering projects like coastal, marine and road projects. Because of low shear strength and stiffness of soft soils, large settlement and low bearing capacity will occur under superstructure loads. This will make the civil engineering activities more difficult and costlier. In the case of soft soils, improvement is a suitable method to increase the shear strength and stiffness for engineering purposes. In recent years, the artificial cementation of soil by cement and lime has been extensively used for soft soil improvement. Cement stabilization is a well-established technique for improving soft soils. Artificial cementation increases the shear strength and hardness of the natural soils. On the other hand, in soft soils, the use of piles to transfer loads to the depths of ground is usual. By using cement treated soil around the piles, high bearing capacity and low settlement in piles can be achieved. In the present study, lateral bearing capacity of short piles in cemented soils is investigated by numerical approach. For this purpose, three dimensional (3D) finite difference software, FLAC 3D is used. Cement treated soil has a strain hardening-softening behavior, because of breaking of bonds between cement agent and soil particle. To simulate such behavior, strain hardening-softening soil constitutive model is used for cement treated soft soil. Additionally, conventional elastic-plastic Mohr Coulomb constitutive model and linear elastic model are used for stress-strain behavior of natural soils and pile. To determine the parameters of constitutive models and also for verification of numerical model, the results of available triaxial laboratory tests on and insitu loading of piles in cement treated soft soil are used. Different parameters are considered in parametric study to determine the effective parameters on the bearing of the piles on cemented treated soils. In the present paper, the effect of various length and height of the artificial cemented area, different diameter and length of the pile and the properties of the materials are studied. Also, the effect of choosing a constitutive model for cemented treated soils in the bearing capacity of the pile is investigated.

Keywords: bearing capacity, cement-treated soils, FLAC 3D, pile

Procedia PDF Downloads 126

Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

Abstract:

Harbor protection systems are so important. The need for automatic protection systems has increased over the last years. Diver detection active sonar has great significance. It used to detect underwater threats such as divers and autonomous underwater vehicle. To automatically detect such threats the sonar image is processed by algorithms. These algorithms used to detect, track and classify of underwater objects. In this work, divers tracking and classification algorithm is improved be proposing a robust wake detection method. To detect objects the sonar images is normalized then segmented based on fixed threshold. Next, the centroids of the segments are found and clustered based on distance metric. Then to track the objects linear Kalman filter is applied. To reduce effect of noise and creation of false tracks, the Kalman tracker is fine tuned. The tuning is done based on our active sonar specifications. After the tracks are initialed and updated they are subjected to a filtering stage to eliminate the noisy and unstable tracks. Also to eliminate object with a speed out of the diver speed range such as buoys and fast boats. Afterwards the result tracks are subjected to a classification stage to deiced the type of the object been tracked. Here the classification stage is to deice wither if the tracked object is an open circuit diver or a close circuit diver. At the classification stage, a small area around the object is extracted and a novel wake detection method is applied. The morphological features of the object with his wake is extracted. We used support vector machine to find the best classifier. The sonar training images and the test images are collected by ARMELSAN Defense Technologies Company using the portable diver detection sonar ARAS-2023. After applying the algorithm to the test sonar data, we get fine and stable tracks of the divers. The total classification accuracy achieved with the diver type is 97%.

Keywords: harbor protection, diver detection, active sonar, wake detection, diver classification

Procedia PDF Downloads 238

Authors: Salima Smiti, Ines Gasmi, Makram Soui

Abstract:

Credit risk is the most important issue for financial institutions. Its assessment becomes an important task used to predict defaulter customers and classify customers as good or bad payers. To this objective, numerous techniques have been applied for credit risk assessment. However, to our knowledge, several evaluation techniques are black-box models such as neural networks, SVM, etc. They generate applicants’ classes without any explanation. In this paper, we propose to assess credit risk using rules classification method. Our output is a set of rules which describe and explain the decision. To this end, we will compare seven classification algorithms (JRip, Decision Table, OneR, ZeroR, Fuzzy Rule, PART and Genetic programming (GP)) where the goal is to find the best rules satisfying many criteria: accuracy, sensitivity, and specificity. The obtained results confirm the efficiency of the GP algorithm for German and Australian datasets compared to other rule-based techniques to predict the credit risk.

Keywords: credit risk assessment, classification algorithms, data mining, rule extraction

Procedia PDF Downloads 181

Authors: Masoud Mahdavi

Abstract:

Today, developed and industrial cities have all kinds of sewage and water transfer canals, subway tunnels, infrastructure facilities, etc., which have caused underground cavities to be created under the buildings. The presence of these cavities causes behavioral changes in the structural behavior that must be fully evaluated. In the present study, using Abaqus finite element software, the effect of cavities with 0.5 and 1.5 meters in diameter at a depth of 2.5 meters from the earth's surface (with a circular cross-section) on the performance of the foundation and the ground (soil) has been evaluated. For this purpose, the Kobe earthquake was applied to the models for 10 seconds. Also, pore water pressure and weight were considered on the models to get complete results. The results showed that by creating and increasing the diameter of circular cavities in the soil, three indicators; 1) von Mises stress, 2) displacement and 3) plastic strain have had oscillating, ascending and ascending processes, respectively, which shows the relationship between increasing the diameter index of underground cavities and structural indicators of structure-foundation-soil.

Keywords: underground excavations, foundation, structural substrates, Abaqus software, Kobe earthquake, time history analysis

Procedia PDF Downloads 121

Authors: A. Rosazlin Abdullah, I. Che Fauziah, K. Wan Rasidah, A. B. Rosenani

Abstract:

The paper industry performs an essential role in the global economy of the world. A study was conducted on the paper mill sludge that is applied on the Khaya senegalensis for 1 year planning period at University Agriculture Park, Puchong, Selangor, Malaysia to determine the growth of Khaya senegalensis, soil properties, nutrients concentrations and effects on the status of heavy metals. Paper Mill Sludge (PMS) and composted Recycled Paper Mill Sludge (RPMS) were used with different rates of nitrogen (0, 150, 300 and 600 kg ha-1) at the ratio of 1:1 (Recycled Paper Mill Sludge (RPMS) : Empty Fruit Brunch (EFB). The growth parameters were measured twice a month for 1 year. Plant nutrients and heavy metal uptake were determined. The paper mill sludge has the potential to be a supplementary N fertilizer as well as a soil amendment. The application of RPMS with N, significantly contributed to the improvement in plant growth parameters such as plant height (4.24 m), basal diameter (10.30 cm), total plant biomass and improved soil physical and chemical properties. The pH, EC, available P and total C in soil were varied among the treatments during the planting period. The treatments with raw and RPM compost had higher pH values than those applied with inorganic fertilizer and control. Nevertheless, there was no salinity problem recorded during the planting period and available P in soil treated with raw and RPMS compost was higher than the control plots that reflects the mineralization of organic P from the decomposition of pulp sludge. The weight of the free and occluded light fractions of carbon concentration was significantly higher in the soils treated with raw and RPMS compost. The application of raw and composted RPMS gave significantly higher concentration of the heavy metals, but the total concentrations of heavy metals in the soils were below the critical values. Hence, the paper mill sludge can be successfully used as soil amendment in acidic soil without any serious threat. The use of paper mill sludge for the soil fertility, shows improvement in land application signifies a unique opportunity to recycle sludge back to the land to alleviate the potential waste management problem.

Keywords: growth, heavy metals, nutrients uptake, production, waste management

Procedia PDF Downloads 368