Search results for: gel strength prediction
5133 Investigation of the Addition of Macro and Micro Polypropylene Fibers on Mechanical Properties of Concrete Pavement
Authors: Seyed Javad Vaziri Kang Olyaei, Asma Sadat Dabiri, Hassan Fazaeli, Amir Ali Amini
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Cracks in concrete pavements are places for the entrance of water and corrosive substances to the pavement, which can reduce the durability of concrete in the long term as well as the serviceability of road. The use of fibers in concrete pavement is one of the effective methods to control and mitigate cracking. This study investigates the effect of the addition of micro and macro polypropylene fibers in different types and volumes and also in combination with the mechanical properties of concrete used in concrete pavements, including compressive strength, splitting tensile strength, modulus of rupture, and average residual strength. The fibers included micro-polypropylene, macro-polypropylene, and hybrid micro and micro polypropylene in different percentages. The results showed that macro polypropylene has the most significant effect on improving the mechanical properties of concrete. Also, the hybrid micro and macro polypropylene fibers increase the mechanical properties of concrete more. It was observed that according to the results of the average residual strength, macro polypropylene fibers alone and together with micro polypropylene fibers could have excellent performance in controlling the sudden formation of cracks and their growth after the formation of cracking which is an essential property in concrete pavements.Keywords: concrete pavement, mechanical properties, macro polypropylene fibers, micro polypropylene fibers
Procedia PDF Downloads 1565132 The Ratio of Second-to-Fourth Digit Length (2D:4D) and the Physical Ability in Men and Women
Authors: Marek Kociuba, Jarosław Kurek
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Introduction: The digit length ratio (2D:4D) is generally higher in women compared to men. Lower 2D:4D is linked with greater physical ability, strength, and better sporting performance. Second-to-fourth digit lengths ratio (2D:4D) is an indicator of PT exposure. Lower 2D:4D indicates higher PT exposure and vice versa. Methods: The objectives of this paper were to investigate the relationship of 2D:4D with physical fitness in men and women. The study compared 137 female and 174 male students from Wrocław. Besides calculating 2D:4D for each hand, height and weight were also recorded. Assessment of physical fitness and endurance were performed through Eurofit tests. Handgrip strength was measured by a standardized isometric dynamometer. Results: Male participants had significantly lower 2D:4D than females on each hand. A weak relationship between 2D:4D and the results of strength tests was found.Keywords: 2D:4D, physical fitness, prenatal testosterone, sexual dimorphism
Procedia PDF Downloads 1265131 The Effects of Electrical Muscle Stimulation (EMS) towards Male Skeletal Muscle Mass
Authors: Mohd Faridz Ahmad, Amirul Hakim Hasbullah
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Electrical Muscle Stimulation (EMS) has been introduced to the world in the 19th and 20th centuries and has globally gained increasing attention on its usefulness. EMS is known as the application of electrical current transcutaneous to muscles through electrodes to induce involuntary contractions that can lead to the increment of muscle mass and strength. This study can be used as an alternative to help people especially those living a sedentary lifestyle to improve their muscle activity without having to go through a heavy workout session. Therefore, this study intended to investigate the effectiveness of EMS training in 5 weeks interventions towards male body composition. It was a quasi-experimental design, held at the Impulse Studio Bangsar, which examined the effects of EMS training towards skeletal muscle mass among the subjects. Fifteen subjects (n = 15) were selected to assist in this study. The demographic data showed that, the average age of the subjects was 43.07 years old ± 9.90, height (173.4 cm ± 9.09) and weight was (85.79 kg ± 18.07). Results showed that there was a significant difference on the skeletal muscle mass (p = 0.01 < 0.05), upper body (p = 0.01 < 0.05) and lower body (p = 0.00 < 0.05). Therefore, the null hypothesis has been rejected in this study. As a conclusion, the application of EMS towards body composition can increase the muscle size and strength. This method has been proven to be able to improve athlete strength and thus, may be implemented in the sports science area of knowledge.Keywords: body composition, EMS, skeletal muscle mass, strength
Procedia PDF Downloads 4895130 Impacts of Low-Density Polyethylene (Plastic Shopping Bags) on Structural Strength and Permeability of Hot-Mix-Asphalt Pavements
Authors: Chayanon Boonyuid
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This paper experiments the effects of low-density polyethylene (LDPE) on the structural strength and permeability of hot-mix-asphalt (HMA) pavements. Different proportions of bitumen (4%, 4.5%, 5%, 5.5% and 6% of total aggregates) and plastic (5%, 10% and 15% of bitumen) contents in HMA mixtures were investigated to estimate the optimum mixture of bitumen and plastic in HMA pavement with long-term performance. Marshall Tests and Falling Head Tests were performed to experiment the structure strength and permeability of HMA mixtures with different percentages of plastic materials and bitumen. The laboratory results show that the optimum binder content was 5.5% by weight of aggregates with higher contents of plastic materials, increase structural stability, reduce permanent deformation, increase ductility, and improve fatigue life of HMA pavements. The use of recycled plastic shopping bags can reduce the use of bitumen content by 0.5% - 1% in HMA mixtures resulting in cheaper material costs with better long-term performance. The plastic materials increase the impermeability of HMA pavements. This study has two-fold contributions: optimum contents of both bitumen and plastic materials in HMA mixtures and the impacts of plastic materials on the permeability of HMA pavements.Keywords: plastic bags, bitumen, structural strength, permeability
Procedia PDF Downloads 1495129 Analytical Model for Vacuum Cathode Arcs in an Oblique Magnetic Field
Authors: P. W. Chen, C. T. Chang, Y. Peng, J. Y. Wu, D. J. Jan, Md. Manirul Ali
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In the last decade, the nature of cathode spot splitting and the current per spot depended on an oblique magnetic field was investigated. This model for cathode current splitting is developed that we have investigated with relationship the magnetic pressures produced by kinetic pressure, self-magnetic pressure, and changed with an external magnetic field. We propose a theoretical model that has been established to an external magnetic field with components normal and tangential to the cathode surface influenced on magnetic pressure strength. We mainly focus on developed to understand the current per spot influenced with the tangential magnetic field strength and normal magnetic field strength.Keywords: cathode spot, vacuum arc discharge, oblique magnetic field, tangential magnetic field
Procedia PDF Downloads 3245128 Enhancing a Recidivism Prediction Tool with Machine Learning: Effectiveness and Algorithmic Fairness
Authors: Marzieh Karimihaghighi, Carlos Castillo
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This work studies how Machine Learning (ML) may be used to increase the effectiveness of a criminal recidivism risk assessment tool, RisCanvi. The two key dimensions of this analysis are predictive accuracy and algorithmic fairness. ML-based prediction models obtained in this study are more accurate at predicting criminal recidivism than the manually-created formula used in RisCanvi, achieving an AUC of 0.76 and 0.73 in predicting violent and general recidivism respectively. However, the improvements are small, and it is noticed that algorithmic discrimination can easily be introduced between groups such as national vs foreigner, or young vs old. It is described how effectiveness and algorithmic fairness objectives can be balanced, applying a method in which a single error disparity in terms of generalized false positive rate is minimized, while calibration is maintained across groups. Obtained results show that this bias mitigation procedure can substantially reduce generalized false positive rate disparities across multiple groups. Based on these results, it is proposed that ML-based criminal recidivism risk prediction should not be introduced without applying algorithmic bias mitigation procedures.Keywords: algorithmic fairness, criminal risk assessment, equalized odds, recidivism
Procedia PDF Downloads 1525127 Assessment of Some Local Clay Minerals Used for the Production of Floor Tiles: Panacea for Economic Growth
Authors: Ekenyem Stan Chinweike
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The suitability of some clay deposits in south eastern Nigeria (Unwana, Ekebedi and Nsu) as materials for the production of floor tiles was investigated. The clay samples were analyzed using wet classical method to determine their chemical composition. Floor tile test specimens were produced using standard method. The test specimens were tested for physical properties such as compressive strength and porosity at 1050◦c and 1150◦c temperature levels. The chemical analysis showed the following results: Unwana (5102 52.24%, AL2o3, 27.20%, Fe2o3 7%, T102 (1.52%), Ekebedi (S102 (58.53%), Al2o3 28.42%, Fe2o3 7%, Ti o2 (1.12%),NSU SIo2 (58.16%), Al2O3 (28.42%), Fe2O3 1.89%, T102 (0.82%) The compressive strength of Unwana, Ekebedi and Nsu clays at 1050◦c are respectively: 15MPa, 13.75MPa and 13.5MPa. At 1150◦c, the values are 16.2MPa and 16.0MPa for Ekebedi and Nsu clays respectively. The porosity of Unwana, Ekebedi and Nsu clays at 1050◦c are respectively31.57%, 23.15% and 24.21%. At 1150◦c, the values are 23.65% and 24.75% for Ekebedi and Nsu respectively. The three clays can be used for production of tiles but Ekebedi has the highest compressive strength which makes it the most suitable clay for the production of floor tiles when compared with floor tiles of the same nominal size stipulated by ASTM standard.Keywords: feldspar, quartz, porosity, compressive strength, clay minerals
Procedia PDF Downloads 3825126 Prediction of Saturated Hydraulic Conductivity Dynamics in an Iowan Agriculture Watershed
Authors: Mohamed Elhakeem, A. N. Thanos Papanicolaou, Christopher Wilson, Yi-Jia Chang
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In this study, a physically-based, modelling framework was developed to predict saturated hydraulic conductivity (KSAT) dynamics in the Clear Creek Watershed (CCW), Iowa. The modelling framework integrated selected pedotransfer functions and watershed models with geospatial tools. A number of pedotransfer functions and agricultural watershed models were examined to select the appropriate models that represent the study site conditions. Models selection was based on statistical measures of the models’ errors compared to the KSAT field measurements conducted in the CCW under different soil, climate and land use conditions. The study has shown that the predictions of the combined pedotransfer function of Rosetta and the Water Erosion Prediction Project (WEPP) provided the best agreement to the measured KSAT values in the CCW compared to the other tested models. Therefore, Rosetta and WEPP were integrated with the Geographic Information System (GIS) tools for visualization of the data in forms of geospatial maps and prediction of KSAT variability in CCW due to the seasonal changes in climate and land use activities.Keywords: saturated hydraulic conductivity, pedotransfer functions, watershed models, geospatial tools
Procedia PDF Downloads 2605125 Artificial Neural Network and Statistical Method
Authors: Tomas Berhanu Bekele
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Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea of avoiding traffic instabilities and homogenizing traffic flow in such a way that the risk of accidents is minimized and traffic flow is maximized. Lately, Intelligent Transport Systems (ITS) has become an important area of research to solve such road traffic-related issues for making smart decisions. It links people, roads and vehicles together using communication technologies to increase safety and mobility. Moreover, accurate prediction of road traffic is important to manage traffic congestion. The aim of this study is to develop an ANN model for the prediction of traffic flow and to compare the ANN model with the linear regression model of traffic flow predictions. Data extraction was carried out in intervals of 15 minutes from the video player. Video of mixed traffic flow was taken and then counted during office work in order to determine the traffic volume. Vehicles were classified into six categories, namely Car, Motorcycle, Minibus, mid-bus, Bus, and Truck vehicles. The average time taken by each vehicle type to travel the trap length was measured by time displayed on a video screen.Keywords: intelligent transport system (ITS), traffic flow prediction, artificial neural network (ANN), linear regression
Procedia PDF Downloads 675124 Top-K Shortest Distance as a Similarity Measure
Authors: Andrey Lebedev, Ilya Dmitrenok, JooYoung Lee, Leonard Johard
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Top-k shortest path routing problem is an extension of finding the shortest path in a given network. Shortest path is one of the most essential measures as it reveals the relations between two nodes in a network. However, in many real world networks, whose diameters are small, top-k shortest path is more interesting as it contains more information about the network topology. Many variations to compute top-k shortest paths have been studied. In this paper, we apply an efficient top-k shortest distance routing algorithm to the link prediction problem and test its efficacy. We compare the results with other base line and state-of-the-art methods as well as with the shortest path. Then, we also propose a top-k distance based graph matching algorithm.Keywords: graph matching, link prediction, shortest path, similarity
Procedia PDF Downloads 3585123 Fracture Properties Investigation of Artocarpus odoratissimus Composite with Polypropylene (PP)
Authors: M. Kamal M. Shah, Al Fareez Bin Aslie, O. Irma Wani, J. Sahari
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Wood plastic composites (WPC) were made using matrix of polypropylene (PP) thermoplastic resin with wood fiber from Artocarpus Odoratissimus as filler. The purpose of this project is to investigate the fracture properties of Artocarpus odoratissimus composite with PP. The WPC were manufactured by hot-press technique with varying formulations which are 10:0 (100% pure PP), 50:50 (40 g of wood fiber and 40 g of PP) and 60:40 (48 g of wood fiber and 32 g of PP). The mechanical properties were investigated. Tensile and flexural were carried out according to ASTM D 638 and ASTM D 790. The results were analysed to calculate the tensile strength. Tensile strength at break is ranged from 13.2 N/mm2 to 21.7 N/mm2 while, the flexural strength obtained is varying from 14.7 N/mm2 to 31.1 N/mm2. The results of the experiment showed that tensile and flexural properties of the composite were increased with the adding of wood fiber material. Finally, the Scanning Electron Microscope (SEM), have been done to study the fracture behavior of the WPC specimens.Keywords: Artocarpus odoratissimus, polypropylene thermoplastic, wood fiber, WPC
Procedia PDF Downloads 4005122 Characteristics of Cement Pastes Incorporating Different Amounts of Waste Cellular Concrete Powder
Authors: Mohammed Abed, Rita Nemes
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In this study different amounts of waste cellular concrete powder (WCCP) as replacement of cement have been investigated as an attempt to produce green binder, which is useful for sustainable construction applications. From zero to up to 60% of WCCP by mass replacement amounts of cement has been conducted. Consistency, compressive strength, bending strength and the activity index of WCCP through seven to ninety days old specimens have been examined, where the optimum WCCP replacement was up to 30%, depending on which the activity index still increased to the end of test period (90 days) and this could be an evidence for its continuity to increase for longer age. Also up to 30% of WCCP increased the bending strength to be higher than the control one. The main point in the present study that there is a possibility of replacing cement by 30% of WCCP, however, it is preferable to be less than this amount.Keywords: cellular concrete powder, waste cellular concrete powder (WCCP), supplementary cementatious material, SCM, activity index, mechanical properties
Procedia PDF Downloads 2195121 High Strength Steel Thin-Walled Cold-Formed Profiles Manufactured for Automated Rack Supported Warehouses
Authors: A. Natali, F. V. Lippi, F. Morelli, W. Salvatore, J. H. M. De Paula Filho, P. Pol
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Automated Rack Supported Warehouses (ARSWs) are storage buildings whose load-bearing structure is made of the same steel racks where goods are stocked. These racks are made of cold formed elements, and the main supporting structure is repeated several times along the length of the building, resulting in a huge quantity of steel. The possibility of using high strength steel to manufacture the traditional cold-formed profiles used for ARSWs is numerically investigated, with the aim of reducing the necessary steel quantity but guaranteeing optimal structural performance levels.Keywords: steel racks, automated rack supported warehouse, thin-walled cold-formed elements, high strength steel, structural optimization
Procedia PDF Downloads 1575120 Effect of Fiber Inclusion on the Geotechnical Parameters of Clayey Soil Subjected to Freeze-Thaw Cycles
Authors: Arun Prasad, P. B. Ramudu, Deep Shikha, Deep Jyoti Singh
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A number of studies have been conducted recently to investigate the influence of randomly oriented fibers on some engineering properties of cohesive soils.Freezing and thawing of soil affects the strength, durability and permeability of soil adversely. Experiments were carried out in order to investigate the effect of inclusion of randomly distributed polypropylene fibers on the strength, hydraulic conductivity and durability of local soil (CL) subjected to freeze–thaw cycles. For evaluating the change in strength of soil, a series of unconfined compression tests as well as tri-axial tests were carried out on reinforced and unreinforced soil samples. All the samples were subjected to seven cycles of freezing and thawing. Freezing was carried out at a temperature of - 15 to -18 °C; and thawing was carried out by keeping the samples at room temperature. The reinforcement of soil samples was done by mixing with polypropylene fibers, 12 mm long and with an aspect ratio of 240. The content of fibers was varied from 0.25 to 1% by dry weight of soil. The maximum strength of soil was found in samples having a fiber content of 0.75% for all the samples that were prepared at optimum moisture content (OMC), and if the OMC was increased (+2% OMC) or decreased (-2% OMC), the maximum strength observed at 0.5% fiber inclusion. The effect of fiber inclusion and freeze–thaw on the hydraulic conductivity was studied increased from around 25 times to 300 times that of the unreinforced soil, without subjected to any freeze-thaw cycles. For studying the increased durability of soil, mass loss after each freeze-thaw cycle was calculated and it was found that samples reinforced with polypropylene fibers show 50-60% less loss in weight than that of the unreinforced soil.Keywords: fiber reinforcement, freezingand thawing, hydraulic conductivity, unconfined compressive strength
Procedia PDF Downloads 4005119 Effect of vr Based Wii Fit Training on Muscle Strength, Sensory Integration Ability and Walking Abilities in Patients with Parkinson's Disease: A Randomized Control Trial
Authors: Ying-Yi Laio, Yea-Ru Yang, Yih-Ru Wu, Ray-Yau Wang
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Background: Virtual reality (VR) systems are proved to increase motor performance in stroke and elderly. However, the effects have not been established in patients with Parkinson’s disease (PD). Purpose: To examine the effects of VR based training in improving muscle strength, sensory integration ability and walking abilities in patients with PD by a randomized controlled trial. Method: Thirty six participants with diagnosis of PD were randomly assigned to one of the three groups (n=12 for each group). Participants received VR-based Wii Fit exercise (VRWii group) or traditional exercise (TE group) for 45 minutes, followed by treadmill training for another 15 minutes for 12 sessions in 6 weeks. Participants in the control group received no structured exercise program but fall-prevention education. Outcomes included lower extremity muscle strength, sensory integration ability, walking velocity, stride length, and functional gait assessment (FGA). All outcomes were assessed at baseline, after training and at 1-month follow-up. Results: Both VRWii and TE groups showed more improvement in level walking velocity, stride length, FGA, muscle strength and vestibular system integration than control group after training and at 1-month follow-up. The VRWii training, but not the TE training, resulted in more improvement in visual system integration than the control. Conclusions: VRWii training is as beneficial as traditional exercise in improving walking abilities, sensory integration ability and muscle strength in patients with PD, and such improvements persisted at least for 1 month. The VRWii training is then suggested to be implemented in patients with PD.Keywords: virtual reality, walking, sensory integration, muscle strength, Parkinson’s disease
Procedia PDF Downloads 3295118 Digital Structural Monitoring Tools @ADaPT for Cracks Initiation and Growth due to Mechanical Damage Mechanism
Authors: Faizul Azly Abd Dzubir, Muhammad F. Othman
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Conventional structural health monitoring approach for mechanical equipment uses inspection data from Non-Destructive Testing (NDT) during plant shut down window and fitness for service evaluation to estimate the integrity of the equipment that is prone to crack damage. Yet, this forecast is fraught with uncertainty because it is often based on assumptions of future operational parameters, and the prediction is not continuous or online. Advanced Diagnostic and Prognostic Technology (ADaPT) uses Acoustic Emission (AE) technology and a stochastic prognostic model to provide real-time monitoring and prediction of mechanical defects or cracks. The forecast can help the plant authority handle their cracked equipment before it ruptures, causing an unscheduled shutdown of the facility. The ADaPT employs process historical data trending, finite element analysis, fitness for service, and probabilistic statistical analysis to develop a prediction model for crack initiation and growth due to mechanical damage. The prediction model is combined with live equipment operating data for real-time prediction of the remaining life span owing to fracture. ADaPT was devised at a hot combined feed exchanger (HCFE) that had suffered creep crack damage. The ADaPT tool predicts the initiation of a crack at the top weldment area by April 2019. During the shutdown window in April 2019, a crack was discovered and repaired. Furthermore, ADaPT successfully advised the plant owner to run at full capacity and improve output by up to 7% by April 2019. ADaPT was also used on a coke drum that had extensive fatigue cracking. The initial cracks are declared safe with ADaPT, with remaining crack lifetimes extended another five (5) months, just in time for another planned facility downtime to execute repair. The prediction model, when combined with plant information data, allows plant operators to continuously monitor crack propagation caused by mechanical damage for improved maintenance planning and to avoid costly shutdowns to repair immediately.Keywords: mechanical damage, cracks, continuous monitoring tool, remaining life, acoustic emission, prognostic model
Procedia PDF Downloads 765117 Churn Prediction for Savings Bank Customers: A Machine Learning Approach
Authors: Prashant Verma
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Commercial banks are facing immense pressure, including financial disintermediation, interest rate volatility and digital ways of finance. Retaining an existing customer is 5 to 25 less expensive than acquiring a new one. This paper explores customer churn prediction, based on various statistical & machine learning models and uses under-sampling, to improve the predictive power of these models. The results show that out of the various machine learning models, Random Forest which predicts the churn with 78% accuracy, has been found to be the most powerful model for the scenario. Customer vintage, customer’s age, average balance, occupation code, population code, average withdrawal amount, and an average number of transactions were found to be the variables with high predictive power for the churn prediction model. The model can be deployed by the commercial banks in order to avoid the customer churn so that they may retain the funds, which are kept by savings bank (SB) customers. The article suggests a customized campaign to be initiated by commercial banks to avoid SB customer churn. Hence, by giving better customer satisfaction and experience, the commercial banks can limit the customer churn and maintain their deposits.Keywords: savings bank, customer churn, customer retention, random forests, machine learning, under-sampling
Procedia PDF Downloads 1435116 Municipal Solid Waste Management and Analysis of Waste Generation: A Case Study of Bangkok, Thailand
Authors: Pitchayanin Sukholthaman
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Gradually accumulated, the enormous amount of waste has caused tremendous adverse impacts to the world. Bangkok, Thailand, is chosen as an urban city of a developing country having coped with serious MSW problems due to the vast amount of waste generated, ineffective and improper waste management problems. Waste generation is the most important factor for successful planning of MSW management system. Thus, the prediction of MSW is a very important role to understand MSW distribution and characteristic; to be used for strategic planning issues. This study aims to find influencing variables that affect the amount of Bangkok MSW generation quantity.Keywords: MSW generation, MSW quantity prediction, MSW management, multiple regression, Bangkok
Procedia PDF Downloads 4215115 Development of a Predictive Model to Prevent Financial Crisis
Authors: Tengqin Han
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Delinquency has been a crucial factor in economics throughout the years. Commonly seen in credit card and mortgage, it played one of the crucial roles in causing the most recent financial crisis in 2008. In each case, a delinquency is a sign of the loaner being unable to pay off the debt, and thus may cause a lost of property in the end. Individually, one case of delinquency seems unimportant compared to the entire credit system. China, as an emerging economic entity, the national strength and economic strength has grown rapidly, and the gross domestic product (GDP) growth rate has remained as high as 8% in the past decades. However, potential risks exist behind the appearance of prosperity. Among the risks, the credit system is the most significant one. Due to long term and a large amount of balance of the mortgage, it is critical to monitor the risk during the performance period. In this project, about 300,000 mortgage account data are analyzed in order to develop a predictive model to predict the probability of delinquency. Through univariate analysis, the data is cleaned up, and through bivariate analysis, the variables with strong predictive power are detected. The project is divided into two parts. In the first part, the analysis data of 2005 are split into 2 parts, 60% for model development, and 40% for in-time model validation. The KS of model development is 31, and the KS for in-time validation is 31, indicating the model is stable. In addition, the model is further validation by out-of-time validation, which uses 40% of 2006 data, and KS is 33. This indicates the model is still stable and robust. In the second part, the model is improved by the addition of macroeconomic economic indexes, including GDP, consumer price index, unemployment rate, inflation rate, etc. The data of 2005 to 2010 is used for model development and validation. Compared with the base model (without microeconomic variables), KS is increased from 41 to 44, indicating that the macroeconomic variables can be used to improve the separation power of the model, and make the prediction more accurate.Keywords: delinquency, mortgage, model development, model validation
Procedia PDF Downloads 2285114 Principles for the Realistic Determination of the in-situ Concrete Compressive Strength under Consideration of Rearrangement Effects
Authors: Rabea Sefrin, Christian Glock, Juergen Schnell
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The preservation of existing structures is of great economic interest because it contributes to higher sustainability and resource conservation. In the case of existing buildings, in addition to repair and maintenance, modernization or reconstruction works often take place in the course of adjustments or changes in use. Since the structural framework and the associated load level are usually changed in the course of the structural measures, the stability of the structure must be verified in accordance with the currently valid regulations. The concrete compressive strength of the existing structures concrete and the derived mechanical parameters are of central importance for the recalculation and verification. However, the compressive strength of the existing concrete is usually set comparatively low and thus underestimated. The reasons for this are too small numbers, and large scatter of material properties of the drill cores, which are used for the experimental determination of the design value of the compressive strength. Within a structural component, the load is usually transferred over the area with higher stiffness and consequently with higher compressive strength. Therefore, existing strength variations within a component only play a subordinate role due to rearrangement effects. This paper deals with the experimental and numerical determination of such rearrangement effects in order to calculate the concrete compressive strength of existing structures more realistic and economical. The influence of individual parameters such as the specimen geometry (prism or cylinder) or the coefficient of variation of the concrete compressive strength is analyzed in experimental small-part tests. The coefficients of variation commonly used in practice are adjusted by dividing the test specimens into several layers consisting of different concretes, which are monolithically connected to each other. From each combination, a sufficient number of the test specimen is produced and tested to enable evaluation on a statistical basis. Based on the experimental tests, FE simulations are carried out to validate the test results. In the frame of a subsequent parameter study, a large number of combinations is considered, which had not been investigated in the experimental tests yet. Thus, the influence of individual parameters on the size and characteristic of the rearrangement effect is determined and described more detailed. Based on the parameter study and the experimental results, a calculation model for a more realistic determination of the in situ concrete compressive strength is developed and presented. By considering rearrangement effects in concrete during recalculation, a higher number of existing structures can be maintained without structural measures. The preservation of existing structures is not only decisive from an economic, sustainable, and resource-saving point of view but also represents an added value for cultural and social aspects.Keywords: existing structures, in-situ concrete compressive strength, rearrangement effects, recalculation
Procedia PDF Downloads 1185113 Artificial Intelligence Based Predictive Models for Short Term Global Horizontal Irradiation Prediction
Authors: Kudzanayi Chiteka, Wellington Makondo
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The whole world is on the drive to go green owing to the negative effects of burning fossil fuels. Therefore, there is immediate need to identify and utilise alternative renewable energy sources. Among these energy sources solar energy is one of the most dominant in Zimbabwe. Solar power plants used to generate electricity are entirely dependent on solar radiation. For planning purposes, solar radiation values should be known in advance to make necessary arrangements to minimise the negative effects of the absence of solar radiation due to cloud cover and other naturally occurring phenomena. This research focused on the prediction of Global Horizontal Irradiation values for the sixth day given values for the past five days. Artificial intelligence techniques were used in this research. Three models were developed based on Support Vector Machines, Radial Basis Function, and Feed Forward Back-Propagation Artificial neural network. Results revealed that Support Vector Machines gives the best results compared to the other two with a mean absolute percentage error (MAPE) of 2%, Mean Absolute Error (MAE) of 0.05kWh/m²/day root mean square (RMS) error of 0.15kWh/m²/day and a coefficient of determination of 0.990. The other predictive models had prediction accuracies of MAPEs of 4.5% and 6% respectively for Radial Basis Function and Feed Forward Back-propagation Artificial neural network. These two models also had coefficients of determination of 0.975 and 0.970 respectively. It was found that prediction of GHI values for the future days is possible using artificial intelligence-based predictive models.Keywords: solar energy, global horizontal irradiation, artificial intelligence, predictive models
Procedia PDF Downloads 2745112 Estimation of Rock Strength from Diamond Drilling
Authors: Hing Hao Chan, Thomas Richard, Masood Mostofi
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The mining industry relies on an estimate of rock strength at several stages of a mine life cycle: mining (excavating, blasting, tunnelling) and processing (crushing and grinding), both very energy-intensive activities. An effective comminution design that can yield significant dividends often requires a reliable estimate of the material rock strength. Common laboratory tests such as rod, ball mill, and uniaxial compressive strength share common shortcomings such as time, sample preparation, bias in plug selection cost, repeatability, and sample amount to ensure reliable estimates. In this paper, the authors present a methodology to derive an estimate of the rock strength from drilling data recorded while coring with a diamond core head. The work presented in this paper builds on a phenomenological model of the bit-rock interface proposed by Franca et al. (2015) and is inspired by the now well-established use of the scratch test with PDC (Polycrystalline Diamond Compact) cutter to derive the rock uniaxial compressive strength. The first part of the paper introduces the phenomenological model of the bit-rock interface for a diamond core head that relates the forces acting on the drill bit (torque, axial thrust) to the bit kinematic variables (rate of penetration and angular velocity) and introduces the intrinsic specific energy or the energy required to drill a unit volume of rock for an ideally sharp drilling tool (meaning ideally sharp diamonds and no contact between the bit matrix and rock debris) that is found well correlated to the rock uniaxial compressive strength for PDC and roller cone bits. The second part describes the laboratory drill rig, the experimental procedure that is tailored to minimize the effect of diamond polishing over the duration of the experiments, and the step-by-step methodology to derive the intrinsic specific energy from the recorded data. The third section presents the results and shows that the intrinsic specific energy correlates well to the uniaxial compressive strength for the 11 tested rock materials (7 sedimentary and 4 igneous rocks). The last section discusses best drilling practices and a method to estimate the rock strength from field drilling data considering the compliance of the drill string and frictional losses along the borehole. The approach is illustrated with a case study from drilling data recorded while drilling an exploration well in Australia.Keywords: bit-rock interaction, drilling experiment, impregnated diamond drilling, uniaxial compressive strength
Procedia PDF Downloads 1375111 Review of Friction Stir Welding of Dissimilar 5000 and 6000 Series Aluminum Alloy Plates
Authors: K. Subbaiah
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Friction stir welding is a solid state welding process. Friction stir welding process eliminates the defects found in fusion welding processes. It is environmentally friend process. 5000 and 6000 series aluminum alloys are widely used in the transportation industries. The Al-Mg-Mn (5000) and Al-Mg-Si (6000) alloys are preferably offer best combination of use in Marine construction. The medium strength and high corrosion resistant 5000 series alloys are the aluminum alloys, which are found maximum utility in the world. In this review, the tool pin profile, process parameters such as hardness, yield strength and tensile strength, and microstructural evolution of friction stir welding of Al-Mg alloys 5000 Series and 6000 series have been discussed.Keywords: 5000 series and 6000 series Al alloys, friction stir welding, tool pin profile, microstructure and properties
Procedia PDF Downloads 4665110 Prediction of B-Cell Epitope for 24 Mite Allergens: An in Silico Approach towards Epitope-Based Immune Therapeutics
Authors: Narjes Ebrahimi, Soheila Alyasin, Navid Nezafat, Hossein Esmailzadeh, Younes Ghasemi, Seyed Hesamodin Nabavizadeh
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Immunotherapy with allergy vaccines is of great importance in allergen-specific immunotherapy. In recent years, B-cell epitope-based vaccines have attracted considerable attention and the prediction of epitopes is crucial to design these types of allergy vaccines. B-cell epitopes might be linear or conformational. The prerequisite for the identification of conformational epitopes is the information about allergens' tertiary structures. Bioinformatics approaches have paved the way towards the design of epitope-based allergy vaccines through the prediction of tertiary structures and epitopes. Mite allergens are one of the major allergy contributors. Several mite allergens can elicit allergic reactions; however, their structures and epitopes are not well established. So, B-cell epitopes of various groups of mite allergens (24 allergens in 6 allergen groups) were predicted in the present work. Tertiary structures of 17 allergens with unknown structure were predicted and refined with RaptorX and GalaxyRefine servers, respectively. The predicted structures were further evaluated by Rampage, ProSA-web, ERRAT and Verify 3D servers. Linear and conformational B-cell epitopes were identified with Ellipro, Bcepred, and DiscoTope 2 servers. To improve the accuracy level, consensus epitopes were selected. Fifty-four conformational and 133 linear consensus epitopes were predicted. Furthermore, overlapping epitopes in each allergen group were defined, following the sequence alignment of the allergens in each group. The predicted epitopes were also compared with the experimentally identified epitopes. The presented results provide valuable information for further studies about allergy vaccine design.Keywords: B-cell epitope, Immunotherapy, In silico prediction, Mite allergens, Tertiary structure
Procedia PDF Downloads 1605109 Correlation and Prediction of Biodiesel Density
Authors: Nieves M. C. Talavera-Prieto, Abel G. M. Ferreira, António T. G. Portugal, Rui J. Moreira, Jaime B. Santos
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The knowledge of biodiesel density over large ranges of temperature and pressure is important for predicting the behavior of fuel injection and combustion systems in diesel engines, and for the optimization of such systems. In this study, cottonseed oil was transesterified into biodiesel and its density was measured at temperatures between 288 K and 358 K and pressures between 0.1 MPa and 30 MPa, with expanded uncertainty estimated as ±1.6 kg.m^-3. Experimental pressure-volume-temperature (pVT) cottonseed data was used along with literature data relative to other 18 biodiesels, in order to build a database used to test the correlation of density with temperarure and pressure using the Goharshadi–Morsali–Abbaspour equation of state (GMA EoS). To our knowledge, this is the first that density measurements are presented for cottonseed biodiesel under such high pressures, and the GMA EoS used to model biodiesel density. The new tested EoS allowed correlations within 0.2 kg•m-3 corresponding to average relative deviations within 0.02%. The built database was used to develop and test a new full predictive model derived from the observed linear relation between density and degree of unsaturation (DU), which depended from biodiesel FAMEs profile. The average density deviation of this method was only about 3 kg.m-3 within the temperature and pressure limits of application. These results represent appreciable improvements in the context of density prediction at high pressure when compared with other equations of state.Keywords: biodiesel density, correlation, equation of state, prediction
Procedia PDF Downloads 6155108 On the Creep of Concrete Structures
Authors: A. Brahma
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Analysis of deferred deformations of concrete under sustained load shows that the creep has a leading role on deferred deformations of concrete structures. Knowledge of the creep characteristics of concrete is a Necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable deformation in pre-stressed concrete or reinforced and the appropriate steps can be taken in design to accommodate this movement. In this study, we propose a prediction model that involves the acting principal parameters on the deferred behaviour of concrete structures. For the estimation of the model parameters Levenberg-Marquardt method has proven very satisfactory. A confrontation between the experimental results and the predictions of models designed shows that it is well suited to describe the evolution of the creep of concrete structures.Keywords: concrete structure, creep, modelling, prediction
Procedia PDF Downloads 2915107 Determination of the Shear Strength of Wastes Using Back-Analyses from Observed Failures
Authors: Sadek Salah
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The determination of the strength characteristics of waste materials is essential when evaluating the stability of waste fills during initial placement and at the time of closure and rehabilitation of the landfill. Significant efforts, mostly experimental, have been deployed to date in attempts to quantify the mechanical properties of municipal wastes various stages of decomposition. Even though the studies and work done so far have helped in setting baseline parameters and characteristics for waste materials, inherent concerns remain as to the scalability of the findings between the laboratory and the field along with questions as to the suitability of the actual test conditions. These concerns are compounded by the complexity of the problem itself with significant variability in composition, placement conditions, and levels of decay of the various constituents of the waste fills. A complimentary, if not necessarily an alternative approach is to rely on field observations of behavior and instability of such materials. This paper describes an effort at obtaining relevant shear strength parameters from back-analyses of failures which have been observed at a major un-engineered waste fill along the Mediterranean shoreline. Results from the limit-equilibrium failure back-analyses are presented and compared to results from laboratory-scale testing on comparable waste materials.Keywords: solid waste, shear strength, landfills, slope stability
Procedia PDF Downloads 2425106 Directional Solidification of Al–Cu–Mg Eutectic Alloy
Authors: Yusuf Kaygısız, Necmetti̇n Maraşlı
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Aluminum alloys are produced and used at various areas of industry and especially in the aerospace industry. The advantages of these alloys over traditional iron-based alloys are lightweight, corrosion resistance, and very good thermal and electrical conductivity. The aim of this work is to experimentally investigate the effect of growth rates on the eutectic spacings (λ), microhardness, tensile strength and electrical resistivity in Al–30wt.%Cu–6wt.%Mg eutectic alloy. Al–Cu–Mg eutectic alloy was directionally solidified at a constant temperature gradient (G=8.55 K/mm) with different growth rates, 9.43 to 173.3 µm/s by using a Bridgman-type furnace. The dependency of microstructure, microhardness, tensile strength and electrical resistivity for directionally solidified the Al-Cu-Mg eutectic alloy were investigated. Eutectic microstructure is consisting of regular Al2CuMg lamellar and Al2Cu rod phases with in the α (Al) solid solution matrix. The lamellar eutectic spacings were measured from transverse sections of the samples. It was found that the value of microstructures decrease with the increase the value the growth rates. The microhardness, tensile strength and electrical resistivity of the alloy also were measured from sample and relationships between them were experimentally analyzed by using regression analysis. According to present results, values tensile strength and electrical resistivity increase with increasing growth rates.Keywords: directional solidification, aluminum alloys, microstructure, electrical properties, hardness test
Procedia PDF Downloads 2945105 Teaching Children With Differential Learning Needs By Understanding Their Talents And Interests
Authors: Eunice Tan
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The purpose of this presentation is to look at an alternative to the approach and methodologies of working with special needs. The strength-based approach to education embodies a paradigm shift. It is a strategy to move away from a deficit-based methodology which inadvertently may lead to an extensive list of things that the child cannot do or is unable to do. Today, many parents of individuals with special needs are focused on the child’s deficits rather than on his or her strengths. Even when parents Recognise and identify their child’s strengths to be valuable and wish to develop their abilities, they face the challenge that there are insufficient programs committed to supporting the development and improvement of such abilities. What is a strength-based approach in education? A strength-based approach in education focuses on students' positive qualities and contributions to class instead of the skills and abilities they may not have. Many schools are focused on the child’s special educational needs rather than the whole child. Parents interviewed have said that they have to engage external tutors to help hone in on their child’s interests and strengths.Keywords: differential learning needs, special needs, instructional style, talents
Procedia PDF Downloads 1965104 Improved 3D Structure Prediction of Beta-Barrel Membrane Proteins by Using Evolutionary Coupling Constraints, Reduced State Space and an Empirical Potential Function
Authors: Wei Tian, Jie Liang, Hammad Naveed
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Beta-barrel membrane proteins are found in the outer membrane of gram-negative bacteria, mitochondria, and chloroplasts. They carry out diverse biological functions, including pore formation, membrane anchoring, enzyme activity, and bacterial virulence. In addition, beta-barrel membrane proteins increasingly serve as scaffolds for bacterial surface display and nanopore-based DNA sequencing. Due to difficulties in experimental structure determination, they are sparsely represented in the protein structure databank and computational methods can help to understand their biophysical principles. We have developed a novel computational method to predict the 3D structure of beta-barrel membrane proteins using evolutionary coupling (EC) constraints and a reduced state space. Combined with an empirical potential function, we can successfully predict strand register at > 80% accuracy for a set of 49 non-homologous proteins with known structures. This is a significant improvement from previous results using EC alone (44%) and using empirical potential function alone (73%). Our method is general and can be applied to genome-wide structural prediction.Keywords: beta-barrel membrane proteins, structure prediction, evolutionary constraints, reduced state space
Procedia PDF Downloads 618