Search results for: strength prediction

Authors: Jisong Zhang, Yinghua Zhao

Abstract:

The present study investigated the mechanical properties and microstructure of Ultra-High Performance Concrete (UHPC) containing supplementary cementitious materials (SCMs), such as fly ash (FA) and silica fume (SF), and to verify the synergistic effect in the ternary system. On the basis of 30% fly ash replacement, the incorporation of either 10% SF or 20% SF show a better performance compared to the reference sample. The efficiency factor (k-value) was calculated as a synergistic effect to predict the compressive strength of UHPC with these SCMs. The SEM of micrographs and pore volume from BJH method indicate a high correlation with compressive strength. Further, an artificial neural networks model was constructed for prediction of the compressive strength of UHPC containing these SCMs.

Keywords: artificial neural network, fly ash, mechanical properties, ultra-high performance concrete

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Authors: Jeonghwan Jeon

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With the advent of IPTV in the fierce competition with existing broadcasting system, it is emerged as an important issue to predict how much the adoption of IPTV service will be. This paper aims to suggest a prediction model for adopting IPTV using classification and Ranking Belief Simplex (CaRBS). A simplex plot method of representing data allows a clear visual representation to the degree of interaction of the support from the variables to the prediction of the objects. CaRBS is applied to the survey data on the IPTV adoption.

Keywords: prediction, adoption, IPTV, CaRBS

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Authors: Behzad Behnia, Noah LaRussa-Trott

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In recent years, fibers have been successfully used as an additive to reinforce asphalt concrete materials and to enhance the sustainability and resiliency of transportation infrastructure. Roads covered with fiber-reinforced asphalt concrete (FRAC) require less frequent maintenance and tend to have a longer lifespan. The present work investigates the application of sasobit-coated aramid fibers in asphalt pavements and employs machine learning to develop prediction models to evaluate the cracking performance of FRAC materials. For the experimental part of the study, the effects of several important parameters such as fiber content, fiber length, and testing temperature on fracture characteristics of FRAC mixtures were thoroughly investigated. Two mechanical performance tests, i.e., the disk-shaped compact tension [DC(T)] and indirect tensile [ID(T)] strength tests, as well as the non-destructive acoustic emission test, were utilized to experimentally measure the cracking behavior of the FRAC material in both macro and micro level, respectively. The experimental results were used to train the supervised machine learning approach in order to establish prediction models for fracture performance of the FRAC mixtures in the field. Experimental results demonstrated that adding fibers improved the overall fracture performance of asphalt concrete materials by increasing their fracture energy, tensile strength and lowering their 'embrittlement temperature'. FRAC mixtures containing long-size fibers exhibited better cracking performance than regular-size fiber mixtures. The developed prediction models of this study could be easily employed by pavement engineers in the assessment of the FRAC pavements.

Keywords: fiber reinforced asphalt concrete, machine learning, cracking performance tests, prediction model

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Authors: Ali Sagiroglu, Sema Noyan Alacali, Guray Arslan

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This paper presents a study on the influence of the safety factor in the concrete contribution to shear strength of high-strength concrete (HSC) beams according to TS500. In TS500, the contribution of concrete to shear strength is obtained by reducing diagonal cracking strength with a safety factor of 0.8. It was investigated that the coefficient of 0.8 considered in determining the contribution of concrete to the shear strength corresponds to which value of failure probability. Also, the changes in the reduction factor depending on different coefficients of variation of concrete were examined.

Keywords: reinforced concrete, beam, shear strength, failure probability, safety factor

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Authors: Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi

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For machine learning based epileptic seizure prediction, it is important for the model to be implemented in small implantable or wearable devices that can be used to monitor epilepsy patients; however, current state-of-the-art methods are complex and computationally intensive. We use Shapley Additive Explanation (SHAP) to find relevant intracranial electroencephalogram (iEEG) features and improve the computational efficiency of a state-of-the-art seizure prediction method based on the extra trees classifier while maintaining prediction performance. Results for a small contest dataset and a much larger dataset with continuous recordings of up to 3 years per patient from 15 patients yield better than chance prediction performance (p < 0.004). Moreover, while the performance of the SHAP-based model is comparable to that of the benchmark, the overall training and prediction time of the model has been reduced by a factor of 1.83. It can also be noted that the feature called zero crossing value is the best EEG feature for seizure prediction. These results suggest state-of-the-art seizure prediction performance can be achieved using efficient methods based on optimal feature selection.

Keywords: machine learning, seizure prediction, extra tree classifier, SHAP, epilepsy

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Authors: A. Daftari, W. Kudla

Abstract:

Liquefaction is a phenomenon in which the strength and stiffness of a soil is reduced by earthquake shaking or other rapid cyclic loading. Liquefaction and related phenomena have been responsible for huge amounts of damage in historical earthquakes around the world. Modelling of soil behaviour is the main step in soil liquefaction prediction process. Nowadays, several constitutive models for sand have been presented. Nevertheless, only some of them can satisfy this mechanism. One of the most useful models in this term is UBCSAND model. In this research, the capability of this model is considered by using PLAXIS software. The real data of superstition hills earthquake 1987 in the Imperial Valley was used. The results of the simulation have shown resembling trend of the UBC3D-PLM model.

Keywords: liquefaction, plaxis, pore-water pressure, UBC3D-PLM

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Authors: Anindya Ghosh

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Structural parameters, yarn to yarn friction, strength of ring, rotor, air-jet and open-end friction spun yarns and the strength of fabrics made from these yarns are measured. The ratio of fabric strip strength per yarn and corresponding single yarn strength is considered as a measure of quantifying the fabric assistance. Mechanism of yarn failure inside the fabric is different as that of single yarn and the former exhibit more fibre rupture. Fabrics made from weaker yarns have higher ratio of strip strength to single yarn strength than that made from stronger yarns due to larger increase in the percentage of rupture fibres in the former. The fabric assistance also depends to some extent on the degree of gripping of the yarns that is influenced by the yarn to yarn friction, extent of yarn flattening and yarn diameter.

Keywords: fabric assistance, fabric strength, yarn diameter, yarn friction, yarn strength

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Authors: Nimesh D. Chaudhari

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The purpose of this study was to find out the interrelationship of BMI with strength, i.e. endurance strength of abdominal muscles and explosive strength of leg muscles, speed and flexibility which are respectively assessed by sit up, standing broad jump, 50 yard dash and sit and reach tests. 48 boys, aged 7 to 13 years as group A and 40 boys, aged 17 to 28 years asgroup B were selected as the subjects for the study. Product moment correlation coefficient test (r at 0.05 level of significance) was applied to test hypothesis. The findings of the study shows that there is significant relationship of BMI with endurance strength of abdominal muscles, explosive strength of leg muscles, and flexibility whereas a negative significant relationship was found between BMI and speed in group A, i.e. aged from 7 to 13 years. However, there was no significant relationship of BMI with endurance strength of abdominal muscles, explosive strength of leg muscles, speed and flexibility in higher age group.

Keywords: body mass index, strength of abdominal muscles, explosive strength of leg muscles, flexibility of lower back and hamstring muscles

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Authors: John-Nelson Ekumah, Selorm Yao-Say Solomon Adade, Mingming Zhong, Yufan Sun, Qiufang Liang, Muhammad Safiullah Virk, Xorlali Nunekpeku, Nana Adwoa Nkuma Johnson, Bridget Ama Kwadzokpui, Xiaofeng Ren

Abstract:

Enhancing starch gel strength and stability is crucial. However, traditional gel property assessment methods are destructive, time-consuming, and resource-intensive. Thus, understanding ethanol treatment effects on kudzu starch gel strength and developing a rapid, nondestructive gel strength assessment method is essential for optimizing the treatment process and ensuring product quality consistency. This study investigated the effects of different ethanol concentrations on the microstructure of kudzu starch gels using a comprehensive microstructural analysis. We also developed a nondestructive method for predicting gel strength and classifying treatment levels using near-infrared (NIR) spectroscopy, and advanced data analytics. Scanning electron microscopy revealed progressive network densification and pore collapse with increasing ethanol concentration, correlating with enhanced mechanical properties. NIR spectroscopy, combined with various variable selection methods (CARS, GA, and UVE) and modeling algorithms (PLS, SVM, and ELM), was employed to develop predictive models for gel strength. The UVE-SVM model demonstrated exceptional performance, with the highest R² values (Rc = 0.9786, Rp = 0.9688) and lowest error rates (RMSEC = 6.1340, RMSEP = 6.0283). Pattern recognition algorithms (PCA, LDA, and KNN) successfully classified gels based on ethanol treatment levels, achieving near-perfect accuracy. This integrated approach provided a multiscale perspective on ethanol-induced starch gel modification, from molecular interactions to macroscopic properties. Our findings demonstrate the potential of NIR spectroscopy, coupled with advanced data analysis, as a powerful tool for rapid, nondestructive quality assessment in starch gel production. This study contributes significantly to the understanding of starch modification processes and opens new avenues for research and industrial applications in food science, pharmaceuticals, and biomaterials.

Keywords: kudzu starch gel, near-infrared spectroscopy, gel strength prediction, support vector machine, pattern recognition algorithms, ethanol treatment

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Authors: Nor Zila Abd Hamid, Mohd Salmi M. Noorani

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This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series.

Keywords: chaotic approach, phase space, Cao method, local linear approximation method

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Authors: J. Y. Lee, H. S. Lim, S. H. Yoon

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This paper presents an analysis of the diagonal crack widths of RC members with various types of materials by simulating a compatibility-aided truss model. The analytical results indicated that the diagonal crack width was influenced by not only the shear reinforcement ratio but also the yield strength of shear reinforcement and the compressive strength of concrete. The yield strength of shear reinforcement and the compressive strength of concrete decreased the diagonal shear crack width of RC members for the same shear force because of the change of shear failure modes. However, regarding the maximum shear crack width at shear failure, the shear crack width of the beam with high strength materials was greater than that of the beam with normal strength materials.

Keywords: diagonal crack width, high strength stirrups, high strength concrete, RC members, shear behavior

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Authors: J. P. Gorninski, J. M. L. Reis

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This present work was aimed to develop polymeric mortars having as binder two polyester resins namely isophtalic and orthophtalic polyester. The inorganic phase was composed by medium-size river sand and fly ash fíller, a by-product of the burning of coal in power plants. The compositions in this study are high performance mortars and were assessed by mechanical properties, through compressive strength and flexural strength, by durability strength when exposed to the cyclical variation of temperature from -400C to +300C and by the chemical aggression test. The composites displayed good performance when exposed to cyclical temperature variations and chemical solutions. The mechanical strength values reached the 100 MPa, the flexural strength yielded values of about twenty percent of mechanical strength.

Keywords: polymer mortar, mechanical strength, cyclical temperatures, chemical strength, sustainability

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Authors: I Lamri, L Arabet, M. Hidjeb

Abstract:

The direct shear test was used to determine the shear strength parameters C and Ø of a series of samples with different cement content. Samples stabilized with a certain percentage of cement showed a substantial gain in compressive strength and a significant increase in shear strength parameters. C and Ø. The laboratory equipment used in UCS tests consisted of a conventional 102mm diameter sample triaxial loading machine. Beyond 4% cement content a very important increase in shear strength was observed. It can be deduced from a comparative study of shear strength of soil samples with 4%, 7%, and 10% cement with sample containing 2 %, that the sample with a 4% cement content showed 90% increase in shear strength while those with 7% and 10% showed an increase of around 13 and 21 fold.

Keywords: cement, compression strength, shear stress, cohesion, angle of internal friction

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Authors: Hy Dang, Bo Mei

Abstract:

The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: classification, machine learning, time representation, stock prediction

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Authors: A. J. Shah, Neeraj Kumar Sahu

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Reactive powder concrete (RPC) is high performance and high strength concrete which composes of very fine powdered materials like cement, sand, silica fume and quartz powder. It also constitutes steel fibre (optional) and super-plasticizer. The present study investigates the performance of reactive powder concrete with fly ash as a replacement of cement under hot water and normal water curing conditions. The replacement of cement with fly ash is done at 10%, 20%, 30% and 40%. To compare the results of cement replaced RPC and traditional RPC, the performance of various mixes is evaluated by compressive strength, flexural strength, split tensile strength and durability. The results show that with increasing percentage of fly ash, improvement in durability is observed and a slight decrease in compressive strength and flexural strength is also observed. It is observed that specimen under hot water curing showed 15 to 20 % more strength than specimens under normal water curing.

Keywords: high strength concrete, the flexural strength of RPC, compressive strength of RPC, durability

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Authors: Supriya H. S., Chandrakala B. M.

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Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.

Keywords: MLHN, network traffic prediction

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Authors: Shree Laxmi Prashant, Subhash C. Yaragal, K. S. Babu Narayan

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Concrete is found to undergo degradation when subjected to elevated temperatures and loose substantial amount of its strength. The loss of strength in concrete is mainly attributed to decomposition of C-S-H and release of physically and chemically bound water, which begins when the exposure temperature exceeds 100°C. When such a concrete comes in contact with moisture, the cement paste is found rehydrate and considerable amount of strength lost is found to recover. This paper presents results of an experimental program carried out to investigate the effect of recuring on strength gain of OPC concrete specimens subjected to elevated temperatures from 200°C to 800°C, which were subjected to retention time of two hours and four hours at the designated temperature. Strength recoveries for concrete subjected to 7 designated elevated temperatures are compared. It is found that the efficacy of recuring as a measure of strength recovery reduces with increase in exposure temperature.

Keywords: elevated temperature, recuring, strength recovery, compressive strength

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Authors: Bao Thach Nguyen, Abbas Mohajerani

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The California bearing ratio (CBR) has been acknowledged as an important parameter to characterize the bearing capacity of earth structures, such as earth dams, road embankments, airport runways, bridge abutments, and pavements. Technically, the CBR test can be carried out in the laboratory or in the field. The CBR test is time-consuming and is infrequently performed due to the equipment needed and the fact that the field moisture content keeps changing over time. Over the years, many correlations have been developed for the prediction of CBR by various researchers, including the dynamic cone penetrometer, undrained shear strength, and Clegg impact hammer. This paper reports and discusses some of the results from a study on the prediction of CBR. In the current study, the CBR test was performed in the laboratory on some fine-grained subgrade soils collected from various locations in Victoria. Based on the test results, a satisfactory empirical correlation was found between the CBR and the physical properties of the experimental soils.

Keywords: California bearing ratio, fine-grained soils, soil physical properties, pavement, soil test

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Authors: Kebaili Bachir

Abstract:

The reuse of concrete waste as a secondary aggregate could be an efficient solution for sustainable development and long-term environmental protection. The variable nature of waste concrete, with various compressive strengths, can have a negative effect on the final compressive strength of recycled concrete. Accordingly, an experimental test programme was developed to evaluate the effect of parent concrete qualities on the performance of recycled concrete. Three grades with different compressive strengths 10MPa, 20MPa, and 30MPa were considered in the study; moreover, an unknown compressive strength was introduced as well. The trial mixes used 40% secondary aggregates (both course and fine) and 60% of natural aggregates. The compressive strength of the test concrete decrease between 15 and 25% compared to normal concrete with no secondary aggregates. This work proves that the strength properties of the parent concrete have a limited effect on the compressive strength of recycled concrete. Low compressive strength parent concrete when crushed generate a high percentage of recycled coarse aggregates with the less attached mortar and give the same compressive strength as an excellent parent concrete. However, the decrease in compressive strength can be mitigated by increasing the cement content 4% by weight of recycled aggregates used.

Keywords: compressive, concrete, quality, recycled, strength

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Authors: D. K. Soni

Abstract:

A study of engineering properties of stones, i.e. compressive strength, tensile strength, modulus of elasticity, density, hardness were carried out to explore the possibility of optimum utilization of stone. The laboratory test results on equally dimensioned discs of the stone show a considerable variation in computed split tensile strength with varied rates of deformation. Hence, the effect of strain rate on the tensile strength of a sand stone and lime stone under wet and dry conditions has been studied experimentally using the split tensile strength test technique. It has been observed that the tensile strength of these stone is very much dependent on the rate of deformation particularly in a dry state. On saturation the value of split tensile strength reduced considerably depending upon the structure of rock and amount of water absorption.

Keywords: sedimentary rocks, split tensile test, deformation rate, saturation rate, sand stone, lime stone

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Authors: M. S. Meon, M. N. Rao, K-U. Schröder

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Mechanical fasteners especially bolting is commonly used in joining carbon-fiber reinforced polymer (CFRP) composite structures due to their good joinability and easy for maintenance characteristics. Since this approach involves with notching, a proper progressive damage model (PDM) need to be implemented and verified to capture existence of damages in the structure. A three dimensional (3D) failure criteria of Puck is established to predict the ultimate bearing failure of such joint. The failure criteria incorporated with degradation scheme are coded based on user subroutine executed in Abaqus. Single lap joint (SLJ) of composite bolted joint is used as target configuration. The results revealed that the PDM adopted here could sufficiently predict the behaviour of composite bolted joint up to ultimate bearing failure. In addition, mesh refinement near holes increased the accuracy of predicted strength as well as computational effort.

Keywords: bearing strength, bolted joint, degradation scheme, progressive damage model

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Authors: Alaa I. Arafa, Hemdan O. A. Said. Marwa A. M. Ali

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This paper investigates and evaluates experimentally the structural behavior of high strength concrete (HSC) beams under fire and compares it with that of Normal strength concrete (NSC) beams. The main investigated parameters are: concrete compressive strength (300 or 600 kg/cm²); the concrete cover thickness (3 or 5 cm); the degree of temperature (room temperature or 600 ^oC); the type of cooling (air or water); and the fire exposure time (3 or 5 hours). Test results showed that the concrete compressive strength decreases significantly as the exposure time to fire increases.

Keywords: experimental, fire, high strength concrete beams, monotonic loading

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Authors: K. M. Aldossari, W. A. Elsaigh, M. J. Shannag

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An experimental study was conducted to investigate the effect of hooked-end steel fibers on the flexural behavior of normal and high strength concrete matrices. The fiber content appropriate for the concrete matrices investigated was also determined based on flexural tests on standard prisms. Parameters investigated include: Matrix compressive strength ranging from 45 MPa to 70 MPa, corresponding to normal and high strength concrete matrices respectively; Fiber volume fraction including 0, 0.5%, 0.76%, and 1%, equivalent to 0, 40, 60, and 80 kg/m3 of hooked-end steel fibers respectively. Test results indicated that flexural strength and toughness of normal and high strength concrete matrices were significantly improved with the increase in the fiber content added; Whereas a slight improvement in compressive strength was observed for the same matrices. Furthermore, the test results indicated that the effect of increasing the fiber content was more pronounced on increasing the flexural strength of high strength concrete than that of normal concrete.

Keywords: concrete, flexural strength, toughness, steel fibers

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Authors: Asra Yousuf, Ajaykumar Tannirkulum

Abstract:

Inferring rural-urban migration trends can help design effective policies that promote better urban planning and rural development. In this paper, we describe how machine learning algorithms can be applied to predict internal migration decisions of people. We consider data collected from household surveys in Tamil Nadu to train our model. To measure the performance of the model, we use data on past migration from National Sample Survey Organisation of India. The factors for training the model include socioeconomic characteristic of each individual like age, gender, place of residence, outstanding loans, strength of the household, etc. and his past migration history. We perform a comparative analysis of the performance of a number of machine learning algorithm to determine their prediction accuracy. Our results show that machine learning algorithms provide a stronger prediction accuracy as compared to statistical models. Our goal through this research is to propose the use of data science techniques in understanding human decisions and behaviour in developing countries.

Keywords: development, migration, internal migration, machine learning, prediction

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Authors: Mohammad Zavid Parvez, Manoranjan Paul

Abstract:

A seizure prediction method is proposed by extracting global features using phase correlation between adjacent epochs for detecting relative changes and local features using fluctuation/deviation within an epoch for determining fine changes of different EEG signals. A classifier and a regularization technique are applied for the reduction of false alarms and improvement of the overall prediction accuracy. The experiments show that the proposed method outperforms the state-of-the-art methods and provides high prediction accuracy (i.e., 97.70%) with low false alarm using EEG signals in different brain locations from a benchmark data set.

Keywords: Epilepsy, seizure, phase correlation, fluctuation, deviation.

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Authors: S. Ritddech, P. Aroonjarattham, K. Aroonjarattham

Abstract:

The pullout strength had an effect on the stability of plate screw fixation when inserted in the cervical spine. Nine different titanium alloy bone screws were used to test the pullout strength through finite element analysis. The result showed that the Moss Miami I can bear the highest pullout force at 1,075 N, which causes the maximum von Mises stress at 858.87 MPa, a value over the yield strength of titanium. The bone screw should have large outer diameter, core diameter and proximal root radius to increase the pullout strength.

Keywords: pullout strength, screw parameter, cervical spine, finite element analysis

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Authors: H. B. Mahmud, Syamsul Bahri, Y. W. Yee, Y. T. Yeap

Abstract:

This paper reports the strength and durability properties of high strength high performance concrete incorporating rice husk ash (RHA) having high silica, low carbon content and appropriate fineness. In this study concrete containing 10%, 15% and 20% RHA as cement replacement and water to binder ratio of 0.25 were investigated. The results show that increasing amount of RHA increases the dosage of superplasticizer to maintain similar workability. Partial replacement of cement with RHA did not increase the early age compressive strength of concrete. However, concrete containing RHA showed higher compressive strength at later ages. The results showed that compressive strength of concrete in the 90-115 MPa range can be obtained at 28 curing days and the durability properties of RHA concrete performed better than that of control concrete. The water absorption of concrete incorporating 15% RHA exhibited the lowest value. The porosity of concrete is consistent with water absorption whereby higher replacement of RHA decreased the porosity of concrete. There is a positive correlation between reducing porosity and increasing compressive strength of high strength high performance concrete. The results also indicate that up to 20% of RHA incorporation could be advantageously blended with cement without adversely affecting the strength and durability properties of concrete.

Keywords: compressive strength, durability, high performance concrete, rice husk ash

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Authors: Jeena R. S., Sukesh Kumar A.

Abstract:

Stroke is one of the major reasons of adult disability and morbidity in many of the developing countries like India. Early diagnosis of stroke is essential for timely prevention and cure. Various conventional statistical methods and computational intelligent models have been developed for predicting the risk and outcome of stroke. This research work focuses on a multilevel approach for predicting the occurrence of stroke based on various risk factors and invasive techniques like retinal imaging. This risk prediction model can aid in clinical decision making and help patients to have an improved and reliable risk prediction.

Keywords: prediction, retinal imaging, risk factors, stroke

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Authors: Jongho Park, Taekyun Kim, Jungbhin You, Sungnam Hong, Sun-Kyu Park

Abstract:

The deterioration of the reinforced concrete is continuously accelerated due to aging of the reinforced concrete, enlargement of the structure, increase if the self-weight due to the manhattanization and cracking due to external force. Also, due to the abnormal climate phenomenon, cracking of reinforced concrete structures is accelerated. Therefore, research on the Textile Reinforced Concrete (TRC) which replaced reinforcement with textile is under study. However, in previous studies, adhesion performance to single yarn was examined without parameters, which does not reflect the effect of fiber twisting and concrete strength. In the present paper, the effect of concrete strength and embedded length on 2400tex (gram per 1000 meters) and 640tex textile were investigated. The result confirm that the increasing compressive strength of the concrete did not affect the pullout strength. However, as the embedded length increased, the pullout strength tended to increase gradually, especially at 2400tex with more twists.

Keywords: textile, TRC, pullout, strength, embedded length, concrete

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Authors: Butchi Kameswara Rao Chittem, Rooban Kumar

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Cement concrete is a complex mixture of different materials. Concrete is believed to have a good fire resistance. Behaviour of concrete depends on its mix proportions and its constituent materials when it is subjected to elevated temperatures. Loss in compressive strength, loss in weight or mass, change in colour and spall of concrete are reported in literature as effects of elevated temperature on concrete. In this paper results are reported on the behaviour of normal strength concrete and high strength concrete subjected to temperatures 200°C, 400°C, 600°C, and 800°C and different cooling regimes viz. air cooling, water quenching. Rebound hammer test was also conducted to study the changes in surface hardness of concrete specimens subjected to elevated temperatures.

Keywords: normal strength concrete, high-strength concrete, temperature, NDT

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