Search results for: classification of soils

Authors: Yunxiang Fang

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With the aging trend continuing to accelerate, open space is important for the daily life of the elderly, and its old-age friendliness is worthy of attention. Based on behavioral observation and literature research, this paper studies the behavior of the elderly in urban open space. Through the investigation, classification and quantitative analysis of the activity types, time characteristics and spatial behavior order of the elderly in Xicheng Square in Hangzhou, it summarizes the square space suitable for the psychological needs, physiology and activity needs of the elderly, combined with the basis of literature research. Finally, the suggestions for the improvement of the old-age friendship of Xicheng Square are put forward, from the aspects of microclimate, safety and accessibility, space richness and service facility quality.

Keywords: behavior characteristics, old-age friendliness, open space, square

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Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus

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Authors: Qassun S. Mohammed Shafiqu, Murtadha A. Abdulrasool

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The design of shallow foundations to withstand different dynamic loads has given considerable attention in recent years. Dynamic loads may be due to the earthquakes, pile driving, blasting, water waves, and machine vibrations. But, predicting the behavior of shallow foundations during earthquakes remains a difficult task for geotechnical engineers. A database for dynamic and static parameters for different soils in seismic active zones in Iraq is prepared which has been collected from geophysical and geotechnical investigation works. Then, analysis of a typical 3-D soil-raft foundation system under earthquake loading is carried out using the database. And a parametric study has been carried out taking into consideration the influence of some parameters on the dynamic behavior of the raft foundation, such as raft stiffness, damping ratio as well as the influence of the earthquake acceleration-time records. The results of the parametric study show that the settlement caused by the earthquake can be decreased by about 72% with increasing the thickness from 0.5 m to 1.5 m. But, it has been noticed that reduction in the maximum bending moment by about 82% was predicted by decreasing the raft thickness from 1.5 m to 0.5 m in all sites model. Also, it has been observed that the maximum lateral displacement, the maximum vertical settlement and the maximum bending moment for damping ratio 0% is about 14%, 20%, and 18% higher than that for damping ratio 7.5%, respectively for all sites model.

Keywords: shallow foundation, seismic behavior, raft thickness, damping ratio

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

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Soils of Greater Himalayas mostly pertain to Leh & Ladakh, Lahaul & Sppiti, & high reaches to Uttarakhand. The moisture regime is aridic. The arid zone starts from Baralacha pass in Lahaul and covers the entire Spiti valley in the district of Lahaul & Spiti, Himachal Pradesh of India. Here, the present study is an attempt to determine the suction value of soil collected from the arid zone of Spiti valley for different freezing-thawing cycles considering the climate ranges of Spiti valley. Suction is the basic and most important parameter which influences the behavior of unsaturated soil. It is essential to determine the suction value of unsaturated soil before other tests like shear test, and permeability. Basically, it is the negative pore water pressure in partially saturated soil measured in terms of the height of the water column. The filter paper method has been used for the study as an economical approach to evaluate suction. It is the only method from which both contact and non-contact suction can be deduced. In this study, soil specimens were subjected to 0, 1, 3, & 5 freezing-thawing (F-T) cycles for different degrees of saturation to have a wide range of suction, and soil freezing characteristic curves (SFCC) were formulated for all F-T cycles. The result data collected from the experiments have shown best-fitted values using Fredlund & Xing model for each SFCC.

Keywords: suction, arid region soil, soil freezing characteristic curve, freezing-thawing cycle

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Authors: Shrabani Ghosh

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Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

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Authors: Amanpreet Kaur

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Wavelet transform (WT) is a powerful statistical tool used in applied mathematics for signal and image processing. The different mother, wavelet basis function, has been compared to select the optimal wavelet function that represents the electromyogram signal characteristics of upper limb amputees. Four different EMG electrode has placed on different location of shoulder muscles. Twenty one wavelet functions from different wavelet families were investigated. These functions included Daubechies (db1-db10), Symlets (sym1-sym5), Coiflets (coif1-coif5) and Discrete Meyer. Using mean square error value, the significance of the mother wavelet functions has been determined for teres, pectorals, and infraspinatus around shoulder muscles. The results show that the best mother wavelet is the db3 from the Daubechies family for efficient classification of the signal.

Keywords: Daubechies, upper limb amputation, shoulder muscles, Symlets, Coiflets

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Authors: Kapil Pandey, Vishnu Goyal

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Spatial and temporal data analysis is very well known in the field of satellite image processing. When spatial data are correlated with time, series analysis it gives the significant results in change detection studies. In this paper the GIS and Remote sensing techniques has been used to find the change detection using time series satellite imagery of Uttarakhand state during the years of 1990-2010. Natural vegetation, urban area, forest cover etc. were chosen as main landuse classes to study. Landuse/ landcover classes within several years were prepared using satellite images. Maximum likelihood supervised classification technique was adopted in this work and finally landuse change index has been generated and graphical models were used to present the changes.

Keywords: GIS, landuse/landcover, spatial and temporal data, remote sensing

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Authors: Mahmoud M. S. Albattah

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Urbanization results in the expansion of administrative boundaries, mainly at the periphery, ultimately leading to changes in landcover. Agricultural land, naturally vegetated land, and other land types are converted into residential areas with a high density of constructs, such as transportation systems and housing. In urban regions of rapid growth and change, urban planners need regular information on up to date ground change. Amman (the capital of Jordan) is growing at unprecedented rates, creating extensive urban landscapes. Planners interact with these changes without having a global view of their impact. The use of aerial photographs and satellite images data combined with topographic information and field survey could provide effective information to develop urban change and growth inventory which could be explored towards producing a very important signature for the built-up area changes.

Keywords: highway design, satellite technologies, remote sensing, GIS, image segmentation, classification

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Authors: Piyush Samant, Ravinder Agarwal

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Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction

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Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation

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Authors: Zhao Haoyue

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Due to the combined effects of climate change, urban expansion, and population growth, various environmental issues, such as urban heat islands and pollution, arise. Therefore, reliable information on urban environmental climate is needed to address and mitigate the negative effects. The emergence of urban climate maps provides a practical basis for urban climate regulation and improvement. This article takes Shapingba District, Chongqing City, as an example to study the construction method of urban thermal environment climate maps based on GIS spatial analysis technology. The thermal load, ventilation potential analysis map, and thermal environment comprehensive analysis map were obtained. Based on the classification criteria obtained from the climate map, corresponding protection and planning mitigation measures have been proposed.

Keywords: urban climate, GIS, heat island analysis, urban thermal environment

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Authors: Soumia Merat, Lynda Djerbal, Ramdane Bahar, Mohammed Amin Benbouras

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Along with shear wave, many soil parameters are associated with the standard penetration test (SPT) as a dynamic in situ experiment. Both SPT-N data and geophysical data do not often exist in the same area. Statistical analysis of correlation between these parameters is an alternate method to estimate Vₛ conveniently and without additional investigations or data acquisition. Shear wave velocity is a basic engineering tool required to define dynamic properties of soils. In many instances, engineers opt for empirical correlations between shear wave velocity (Vₛ) and reliable static field test data like standard penetration test (SPT) N value, CPT (Cone Penetration Test) values, etc., to estimate shear wave velocity or dynamic soil parameters. The relation between Vs and SPT- N values of Algiers area is predicted using the collected data, and it is also compared with the previously suggested formulas of Vₛ determination by measuring Root Mean Square Error (RMSE) of each model. Algiers area is situated in high seismic zone (Zone III [RPA 2003: réglement parasismique algerien]), therefore the study is important for this region. The principal aim of this paper is to compare the field measurements of Down-hole test and the empirical models to show which one of these proposed formulas are applicable to predict and deduce shear wave velocity values.

Keywords: empirical models, RMSE, shear wave velocity, standard penetration test

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Authors: Loai Abdallah, Malik Yousef

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A domain space for the data should reflect the actual similarity between objects. Since objects belonging to the same cluster usually share some common traits even though their geometric distance might be relatively large. In general, the Euclidean distance of data points that represented by large number of features is not capturing the actual relation between those points. In this study, we propose a new method to construct a different space that is based on clustering to form a new distance metric. The new distance space is based on ensemble clustering (EC). The EC distance space is defined by tracking the membership of the points over multiple runs of clustering algorithm metric. Over this distance, we train the decision trees classifier (DT-EC). The results obtained by applying DT-EC on 10 datasets confirm our hypotheses that embedding the EC space as a distance metric would improve the performance.

Keywords: ensemble clustering, decision trees, classification, K nearest neighbors

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Authors: Shuai Zhao, Shalendra D. Sharma, Jin Xu

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This research uses advanced machine learning models to learn a number of hypotheses regarding political executives. Specifically, it analyses the impact these powerful leaders have on economic growth by using leaders’ data from the Archigos database from 1835 to the end of 2015. The data is processed by the AutoGluon, which was developed by Amazon. Automated Machine Learning (AutoML) and AutoGluon can automatically extract features from the data and then use multiple classifiers to train the data. Use a linear regression model and classification model to establish the relationship between leaders and economic growth (GDP per capita growth), and to clarify the relationship between their characteristics and economic growth from a machine learning perspective. Our work may show as a model or signal for collaboration between the fields of statistics and artificial intelligence (AI) that can light up the way for political researchers and economists.

Keywords: comparative politics, political executives, leaders’ characteristics, artificial intelligence

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Authors: Ilirian Laçi, Alketa Spahiu

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Modality of treatment in hepatocellular carcinoma (HCC) patients depends on the stage of the disease. The Barcelona Clinic Liver Cancer Classification (BCLC) is the preferred staging system. There are many patients initially present with intermediate-stage disease. For these patients, transarterial chemoembolization (TACE) is the treatment of choice. The differences in individual factors that are not captured by the BCLC framework, such as the tumor growth pattern, degree of hypervascularity, and vascular supply, complicate further evaluation of these patients. Because of these differences, not all patients benefit equally from TACE. Several tools have been devised to aid the decision-making process, which have shown promising initial results but have failed external evaluation and have not been translated to the clinic aspects. Criteria for treatment decisions in daily clinical practice are needed in all stages of the disease.

Keywords: hepatocellular carcinoma, transarterial chemoembolization, TACE, liver

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Authors: Rahul Patel, S. P. Dave, M. V Shah

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Ahmedabad is a rapidly growing city in western India that is experiencing significant urbanization and industrialization. With projections indicating that it will become a metropolitan city in the near future, various construction activities are taking place, making soil testing a crucial requirement before construction can commence. To achieve this, construction companies and contractors need to periodically conduct soil testing. This study focuses on the process of creating a spatial database that is digitally formatted and integrated with geotechnical data and a Geographic Information System (GIS). Building a comprehensive geotechnical Geo-database involves three essential steps. Firstly, borehole data is collected from reputable sources. Secondly, the accuracy and redundancy of the data are verified. Finally, the geotechnical information is standardized and organized for integration into the database. Once the Geo-database is complete, it is integrated with GIS. This integration allows users to visualize, analyze, and interpret geotechnical information spatially. Using a Topographic to Raster interpolation process in GIS, estimated values are assigned to all locations based on sampled geotechnical data values. The study area was contoured for SPT N-Values, Soil Classification, Φ-Values, and Bearing Capacity (T/m2). Various interpolation techniques were cross-validated to ensure information accuracy. The GIS map generated by this study enables the calculation of SPT N-Values, Φ-Values, and bearing capacities for different footing widths and various depths. This approach highlights the potential of GIS in providing an efficient solution to complex phenomena that would otherwise be tedious to achieve through other means. Not only does GIS offer greater accuracy, but it also generates valuable information that can be used as input for correlation analysis. Furthermore, this system serves as a decision support tool for geotechnical engineers. The information generated by this study can be utilized by engineers to make informed decisions during construction activities. For instance, they can use the data to optimize foundation designs and improve site selection. In conclusion, the rapid growth experienced by Ahmedabad requires extensive construction activities, necessitating soil testing. This study focused on the process of creating a comprehensive geotechnical database integrated with GIS. The database was developed by collecting borehole data from reputable sources, verifying its accuracy and redundancy, and organizing the information for integration. The GIS map generated by this study is an efficient solution that offers greater accuracy and generates valuable information that can be used as input for correlation analysis. It also serves as a decision support tool for geotechnical engineers, allowing them to make informed decisions during construction activities.

Keywords: arcGIS, borehole data, geographic information system (GIS), geo-database, interpolation, SPT N-value, soil classification, φ-value, bearing capacity

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Authors: Ephrem Getahun, Shengwen Qi, Songfeng Guo, Yu Zou, Melesse Alemayehu

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Residual shear characteristics of slide soil profile sections (SSPS) were examined using ring shear tests to know the relative residual shear behaviors among the sections of slide soil. The multistage-multiphase shearing techniques were employed to perform the experiment for each soil specimen continuously towards large displacements. The grain distribution analysis of SSPS samples was characterized by coarsening upward from bottom slip to the top sections; however, the slip surface was considered as a sheared zone that endorses their low shear resistance for failure. There is an average range of 1-2.5 mm axial displacement on each stage of loadings and phases of shearing that depicts the significant effect of dilation and compression of soil specimen. The middle section has the largest consolidation percentage (10-29%), and vertical displacement compared to other sections and showed high shear strengthening behavior having maximum shear stress of 189kPa at 240kPa loading compared to basal and top sections. It is found that the middle section of SSPS has relatively high shear resistance behavior for large displacement shearing. The residual shear assessment indicates that there is a significant influence of large displacement and rate on the friction coefficient behaviors; it resulted in shear weakening effect to attain their residual condition.

Keywords: comparison, displacements, residual shear stress, shear behavior, slide soils

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Authors: Alfonsina Buoniconto

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The aim of this study is to investigate the degree of cross-linguistic and intra-linguistic variation in the encoding of motion events (MEs) in English and Italian, these being typologically different languages both showing signs of disobedience to their respective types. As a matter of fact, the traditional typological classification of MEs encoding distributes languages into two macro-types, based on the preferred locus for the expression of Path, the main ME component (other components being Figure, Ground and Manner) characterized by conceptual and structural prominence. According to this model, Satellite-framed (SF) languages typically express Path information in verb-dependent items called satellites (e.g. preverbs and verb particles) with main verbs encoding Manner of motion; whereas Verb-framed languages (VF) tend to include Path information within the verbal locus, leaving Manner to adjuncts. Although this dichotomy is valid altogether, languages do not always behave according to their typical classification patterns. English, for example, is usually ascribed to the SF type due to the rich inventory of postverbal particles and phrasal verbs used to express spatial relations (i.e. the cat climbed down the tree); nevertheless, it is not uncommon to find constructions such as the fog descended slowly, which is typical of the VF type. Conversely, Italian is usually described as being VF (cf. Paolo uscì di corsa ‘Paolo went out running’), yet SF constructions like corse via in lacrime ‘She ran away in tears’ are also frequent. This paper will try to demonstrate that such a typological overlapping is due to the fact that the semantic units making up MEs are distributed within several loci of the sentence –not only verbs and satellites– thus determining a number of different constructions stemming from convergent factors. Indeed, the linguistic expression of motion events depends not only on the typological nature of languages in a traditional sense, but also on a series morphological, lexical, and syntactic resources, as well as on inferential, discursive, usage-related, and cultural factors that make semantic information more or less accessible, frequent, and easy to process. Hence, rather than describe English and Italian in dichotomic terms, this study focuses on the investigation of cross-linguistic and intra-linguistic variation in the use of all the strategies made available by each linguistic system to express motion. Evidence for these assumptions is provided by parallel corpora analysis. The sample texts are taken from two contemporary Italian novels and their respective English translations. The 400 motion occurrences selected (200 in English and 200 in Italian) were scanned according to the MODEG (an acronym for Motion Decoding Grid) methodology, which grants data comparability through the indexation and retrieval of combined morphosyntactic and semantic information at different levels of detail.

Keywords: construction typology, motion event encoding, parallel corpora, satellite-framed vs. verb-framed type

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Authors: Marina Yurievna Aleksandrova

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Research of the Holocaust retains value not only for history but also for sociology and psychology. One of the most important fields of study is how people were coping during and after this traumatic event. The aim of this paper is to identify the main contexts of the topic of love and to determine which contexts are more characteristic for different groups of victims of the Holocaust (gender, nationality, age). In this research, transcripts of interviews with Holocaust victims that were collected during 1946 for the "Voices of the Holocaust" project were used as data. Main contexts were analyzed with methods of network analysis and latent semantic analysis and classified by gender, age, and nationality with random forest. The results show that love is articulated and described significantly differently for male and female informants, nationality is shown results with lower values of quality metrics, as well as the age.

Keywords: Holocaust, latent semantic analysis, network analysis, text-mining, random forest

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Authors: Khandaker Fariha Ahmed, Md. Noman Munshi, Tarin Sultana, Md. Zoynul Abedin

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Suitability number (SN) is perhaps one of the most important parameters of coarse-grained soil in assessing its appropriateness to use as a backfill in retaining structures, sand compaction pile, Vibro compaction, and other similar foundation and ground improvement works. Though determined in an empirical manner, it is imperative to study SN to understand its relation with other aggregate properties like fineness modulus (FM), and strength and density properties of sandy soil. The present paper reports the findings of the study on the examination of the properties of sandy soil, as mentioned. Random numbers were generated to obtain the percent fineness on various sieve sizes, and fineness modulus and suitability numbers were predicted. Sand samples were collected from the field, and test samples were prepared to determine maximum density, minimum density and shear strength parameter φ against particular fineness modulus and corresponding suitability number Five samples of SN value of excellent (0-10) and three samples of SN value fair (20-30) were taken and relevant tests were done. The data obtained from the laboratory tests were statistically analyzed. Results show that with the increase of SN, the value of FM decreases. Within the SN value rated as excellent (0-10), there is a decreasing trend of φ for a higher value of SN. It is found that SN is dependent on various combinations of grain size properties like D10, D30, and D20, D50. Strong linear relationships were obtained between SN and FM (R²=.0.93) and between SN value and φ (R²=.94). Correlation equations are proposed to define relationships among SN, φ, and FM.

Keywords: density, fineness modulus, shear strength parameter, suitability number

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Authors: Omair Ghori, Anton Stadler, Stefan Wilk, Wolfgang Effelsberg

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Fire-related incidents account for extensive loss of life and material damage. Quick and reliable detection of occurring fires has high real world implications. Whereas a major research focus lies on the detection of outdoor fires, indoor camera-based fire detection is still an open issue. Cameras in combination with computer vision helps to detect flames and smoke more quickly than conventional fire detectors. In this work, we present a computer vision-based smoke detection algorithm based on contrast changes and a multi-step classification. This work accelerates computer vision-based fire detection considerably in comparison with classical indoor-fire detection.

Keywords: contrast analysis, early fire detection, video smoke detection, video surveillance

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Authors: Jayant Kumar, Aarcha Jayachandran Sasikala, Barry Adrian Shepherd

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Public Distribution System is a flagship welfare programme of the Government of India with both historical and political significance. Targeted at lower sections of society,it is one of the largest supply chain networks in the world. There has been several studies by academics and planning commission about the effectiveness of the system. Our study focuses on applying predictive analytics to aid the central body to keep track of the problem of breach of service level agreement between the two echelons of food supply chain. Each shop breach is leading to a potential additional inventory carrying cost. Thus, through this study, we aim to show that aided with such analytics, the network can be made more cost effective. The methods we illustrate in this study are applicable to other commercial supply chains as well.

Keywords: PDS, analytics, cost effectiveness, Karnataka, inventory cost, service level JEL classification: C53

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Authors: R. Ziaie Moayed, S. P. Emadoleslami Oskoei, S. D. Beladi Mousavi, A. Taleb Beydokhti

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There have been many reports of the destructive effects of cement on the environment in recent years. In the present research, it has been attempted to reduce the destructive effects of cement by replacing silica fume as adhesive materials instead of cement. The present study has attempted to improve the mechanical properties of cement slurry by using waste material from a glass production factory, located in Qazvin city of Iran, in which accumulation volume has become an environmental threat. The chemical analysis of the waste material indicates that this material contains about 94% of SiO₂ and AL₂O₃ and has a close structure to silica fume. Also, the particle grain size test was performed on the mentioned waste. Then, the unconfined compressive strength test of the slurry was performed by preparing a mixture of water and adhesives with different percentages of cement and silica fume. The water to an adhesive ratio of this mixture is 1:3, and the curing process last 28 days. It was found that the sample had an unconfined compressive strength of about 300 kg/cm² in a mixture with equal proportions of cement and silica fume. Besides, the sample had a brittle fracture in the slurry sample made of pure cement, however, the fracture in cement-silica fume slurry mixture is flexible and the structure of the specimen remains coherent after fracture. Therefore, considering the flexibility that is achieved by replacing this waste, it can be used to stabilize soils with cracking potential.

Keywords: cement replacement, cement slurry, environmental threat, natural pozzolan, silica fume, waste material

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Authors: Nebi Gedik

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One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).

Keywords: wave atom transform, statistical features, multi-resolution representation, mammogram

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Authors: Abdul Wakeel, Hafeez Ur Rehman, Muhammad Umair Mubarak

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Rice is the second most important staple food in Pakistan after wheat. It is not only a healthy food for the people of all age groups but also a source of foreign exchange for Pakistan. Instead of bright history for Basmati rice production, we are suffering from multiple problems reducing yield and quality as well. Rice lodging and water shortage for an-aerobic rice production system is among major glitches of it. Due to water shortage an-aerobic rice production system has to be supplemented or replaced by aerobic rice system. Aerobic rice system has been adopted for production of non-basmati rice in many parts of the world. Also for basmati rice, significant efforts have been made for aerobic rice production, however still has to be improved for effective recommendations. Among two major issues for aerobic rice, weed elimination has been solved to great extent by introducing suitable herbicides, however, low yield production due weak grains and panicle sterility is still elusive. It has been reported that potassium (K) has significant role to decrease panicle sterility in cereals. Potassium deficiency is obvious for rice under aerobic rice production system due to lack of K gradient coming with irrigation water and lowered indigenous K release from soils. Therefore it was hypothesized that K application under aerobic rice production system may improve the rice yield by decreasing panicle sterility. Results from pot and field experiments confirm that application of K fertilizer significantly increased the rice grain yield due to decreased panicle sterility and improving grain health. The quality of rice was also improved by K fertilization.

Keywords: DSR, Basmati rice, aerobic, potassium

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Authors: Preethi Grace Theva Neethi Dhas

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A healthy human gut microbiome has commensal and symbiotic functions in digestion and is a decisive factor for human health. The soil microbiome is a crucial component in the ecosystem of soils and their health and resilience. Changes in soil microbiome are linked to human health. Ever since the industrial era, the human and the soil microbiome have been going through drastic changes. The soil microbiome has changed due to industrialization and extensive agricultural practices, whereas humans have less contact with soil and increased intake of highly processed foods, leading to changes in the human gut microbiome. Regenerating the soil becomes crucial in maintaining a healthy ecosystem. The nutrients, once obtained from the soil, need to be given back to the soil. Soil degradation needs to be addressed in effective ways, like adding organic nutrients back to the soil. Manure from animals and humans needs to be returned to the soil, which can complete the nutrient cycle in the soil. On the other hand, fecal sludge management (FSM) is a growing concern in many parts of the developing world. Hence, it becomes crucial to treat and reuse fecal sludge in a safe manner, i.e., low in risk to human health. Co-composting fecal sludge with organic wastes is a practice that allows the safe management of fecal sludge and the safe application of nutrients to the soil. This paper will discuss the possible impact of co-composting fecal sludge with coconut choir waste on the soil, water, and ecosystem at large. Impact parameters like nitrogen, phosphorus, and fecal coliforms will be analyzed. The overall impact of fecal sludge application on the soil will be researched and presented in this study.

Keywords: fecal sludge management, nutrient cycle, soil health, composting

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Authors: Kavitha A.S., L.Govindaraju

Abstract:

Reinforced earth walls offer excellent solution to many problems associated with earth retaining structures especially under seismic conditions. Use of cohesive soils as backfill material reduces the cost of reinforced soil walls if proper drainage measures are taken. This paper presents a numerical study on the application of a new technique called sandwich technique in reinforced earth walls. In this technique, a thin layer of granular soil is placed above and below the reinforcement layer to initiate interface friction and the remaining portion of the backfill is filled up using the existing insitu cohesive soil. A 6 m high reinforced earth wall has been analysed as a two-dimensional plane strain finite element model. Three types of reinforcing elements such as geotextile, geogrid and metallic strips were used. The horizontal wall displacements and the tensile loads in the reinforcement were used as the criteria to evaluate the results at the end of construction and dynamic excitation phases. Also to verify the effectiveness of sandwich layer on the performance of the wall, the thickness of sand fill surrounding the reinforcement was varied. At the end of construction stage it is found that the wall with sandwich type backfill yielded lower displacements when compared to the wall with cohesive soil as backfill. Also with sandwich backfill, the reinforcement loads reduced substantially when compared to the wall with cohesive soil as backfill. Further, it is found that sandwich technique as backfill and geogrid as reinforcement is a good combination to reduce the deformations of geosynthetic reinforced walls during seismic loading.

Keywords: geogrid, geotextile, reinforced earth, sandwich technique

Procedia PDF Downloads 272

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

Abstract:

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

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

Procedia PDF Downloads 88

Authors: Hyun-Koo Kim, Yonghun Kim, Yong-Hoon Kim, Ju Hee Lee, Myungho Song

Abstract:

In this paper, we have described an efficient stereo matching method and pedestrian detection method using stereo types LWIR camera. We compared with three types stereo camera algorithm as block matching, ELAS, and SGM. For pedestrian detection using stereo LWIR camera, we used that SGM stereo matching method, free space detection method using u/v-disparity, and HOG feature based pedestrian detection. According to testing result, SGM method has better performance than block matching and ELAS algorithm. Combination of SGM, free space detection, and pedestrian detection using HOG features and SVM classification can detect pedestrian of 30m distance and has a distance error about 30 cm.

Keywords: advanced driver assistance system, pedestrian detection, stereo matching method, stereo long-wave IR camera

Procedia PDF Downloads 385

Authors: Alhusein Almahjoub, Dongyu Qiu

Abstract:

This paper deals with the random access procedure in next-generation networks and presents the solution to reduce total service time (TST) which is one of the most important performance metrics in current and future internet of things (IoT) based networks. The proposed solution focuses on the calculation of optimal transmission probability which maximizes the success probability and reduces TST. It uses the information of several idle preambles in every time slot, and based on it, it estimates the number of backlogged IoT devices using Naïve Bayes estimation which is a type of supervised learning in the machine learning domain. The estimation of backlogged devices is necessary since optimal transmission probability depends on it and the eNodeB does not have information about it. The simulations are carried out in MATLAB which verify that the proposed solution gives excellent performance.

Keywords: random access, LTE/LTE-A, 5G, machine learning, Naïve Bayes estimation

Procedia PDF Downloads 131