Search results for: residual life prediction
9387 A Risk Management Framework for Selling a Mega Power Plant Project in a New Market
Authors: Negar Ganjouhaghighi, Amirali Dolatshahi
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The origin of most risks of a mega project usually takes place in the phases before closing the contract. As a practical point of view, using project risk management techniques for preparing a proposal is not a total solution for managing the risks of a contract. The objective of this paper is to cover all those activities associated with risk management of a mega project sale’s processes; from entrance to a new market to awarding activities and the review of contract performance. In this study, the risk management happens in six consecutive steps that are divided into three distinct but interdependent phases upstream of the award of the contract: pre-tendering, tendering and closing. In the first step, by preparing standard market risk report, risks of the new market are identified. The next step is the bid or no bid decision making based on the previous gathered data. During the next three steps in tendering phase, project risk management techniques are applied for determining how much contingency reserve must be added or reduced to the estimated cost in order to put the residual risk to an acceptable level. Finally, the last step which happens in closing phase would be an overview of the project risks and final clarification of residual risks. The sales experience of more than 20,000 MW turn-key power plant projects alongside this framework, are used to develop a software that assists the sales team to have a better project risk management.Keywords: project marketing, risk management, tendering, project management, turn-key projects
Procedia PDF Downloads 3199386 The Application of Data Mining Technology in Building Energy Consumption Data Analysis
Authors: Liang Zhao, Jili Zhang, Chongquan Zhong
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Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given.Keywords: data mining, data analysis, prediction, optimization, building operational performance
Procedia PDF Downloads 8459385 Microstructure and Corrosion Properties of Pulsed Current Gas Metal Arc Welded Narrow Groove and Ultra-Narrow Groove of 304 LN Austenitic Stainless Steel
Authors: Nikki A. Barla, P. K. Ghosh, Sourav Das
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Two different groove sizes 13.6 mm (narrow groove) and 7.5 mm (ultra-narrow groove) of 304 LN austenitic stainless steel (ASS) plate was welded using pulse gas metal arc welding (P-GMAW). These grooves were welded using multi-pass single seam per layer (MSPPL) deposition technique with full assurance of groove wall fusion. During bead on plate deposition process, the thermal cycle was recorded using strain buster (temperature measuring device). Both the groove has heat affected Zone (HAZ) width of 1-2 mm. After welding, the microstructure studies was done which revealed that there was higher sensitization (Chromium carbide formation in grain boundary) in the HAZ of 13.6 mm groove weldment as compared to the HAZ of 7.5 mm weldment. Electrochemical potentiokinetic reactivation test (EPR) was done in 0.5 N H₂SO₄ + 1 M KSCN solution to study the degree of sensitization (DOS) and it was observed that 7.5 mm groove HAZ has lower DOS. Mass deposition in the 13.6 mm weld is higher than 7.5mm groove weld, which naturally induces higher residual stress in 13.6 mm weld. Comparison between microstructural studies and corrosion test summarized that the residual stress affects the sensitization property of welded ASS.Keywords: austenitic stainless steel (ASS), electrochemical potentiokinetic reactivation test (EPR), microstructure, pulse gas metal arc welding (P-GMAW), sensitization
Procedia PDF Downloads 1579384 An Implementation of Fuzzy Logic Technique for Prediction of the Power Transformer Faults
Authors: Omar M. Elmabrouk., Roaa Y. Taha., Najat M. Ebrahim, Sabbreen A. Mohammed
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Power transformers are the most crucial part of power electrical system, distribution and transmission grid. This part is maintained using predictive or condition-based maintenance approach. The diagnosis of power transformer condition is performed based on Dissolved Gas Analysis (DGA). There are five main methods utilized for analyzing these gases. These methods are International Electrotechnical Commission (IEC) gas ratio, Key Gas, Roger gas ratio, Doernenburg, and Duval Triangle. Moreover, due to the importance of the transformers, there is a need for an accurate technique to diagnose and hence predict the transformer condition. The main objective of this technique is to avoid the transformer faults and hence to maintain the power electrical system, distribution and transmission grid. In this paper, the DGA was utilized based on the data collected from the transformer records available in the General Electricity Company of Libya (GECOL) which is located in Benghazi-Libya. The Fuzzy Logic (FL) technique was implemented as a diagnostic approach based on IEC gas ratio method. The FL technique gave better results and approved to be used as an accurate prediction technique for power transformer faults. Also, this technique is approved to be a quite interesting for the readers and the concern researchers in the area of FL mathematics and power transformer.Keywords: dissolved gas-in-oil analysis, fuzzy logic, power transformer, prediction
Procedia PDF Downloads 1369383 Towards End-To-End Disease Prediction from Raw Metagenomic Data
Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker
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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine
Procedia PDF Downloads 1199382 Prediction of Marine Ecosystem Changes Based on the Integrated Analysis of Multivariate Data Sets
Authors: Prozorkevitch D., Mishurov A., Sokolov K., Karsakov L., Pestrikova L.
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The current body of knowledge about the marine environment and the dynamics of marine ecosystems includes a huge amount of heterogeneous data collected over decades. It generally includes a wide range of hydrological, biological and fishery data. Marine researchers collect these data and analyze how and why the ecosystem changes from past to present. Based on these historical records and linkages between the processes it is possible to predict future changes. Multivariate analysis of trends and their interconnection in the marine ecosystem may be used as an instrument for predicting further ecosystem evolution. A wide range of information about the components of the marine ecosystem for more than 50 years needs to be used to investigate how these arrays can help to predict the future.Keywords: barents sea ecosystem, abiotic, biotic, data sets, trends, prediction
Procedia PDF Downloads 1119381 Red-Tide Detection and Prediction Using MODIS Data in the Arabian Gulf of Qatar
Authors: Yasir E. Mohieldeen
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Qatar is one of the most water scarce countries in the World. In 2014, the average per capita rainfall was less than 29 m3/y/ca, while the global average is 6,000 m3/y/ca. However, the per capita water consumption in Qatar is among the highest in the World: more than 500 liters per person per day, whereas the global average is 160 liters per person per day. Since the early 2000s, Qatar has been relying heavily on desalinated water from the Arabian Gulf as the main source of fresh water. In 2009, about 99.9% of the total potable water produced was desalinated. Reliance on desalinated water makes Qatar very vulnerable to water related natural disasters, such as the red-tide phenomenon. Qatar’s strategic water reserve lasts for only 7 days. In case of red-tide outbreak, the country would not be able to desalinate water for days, let alone the months that this disaster would bring about (as it clogs the desalination equipment). The 2008-09 red-tide outbreak, for instance, lasted for more than eight months and forced the closure of desalination plants in the region for weeks. This study aims at identifying favorite conditions for red-tide outbreaks, using satellite data along with in-situ measurements. This identification would allow the prediction of these outbreaks and their hotspots. Prediction and monitoring of outbreaks are crucial to water security in the country, as different measures could be put in place in advance to prevent an outbreak and mitigate its impact if it happened. Red-tide outbreaks are detected using different algorithms for chlorophyll concentration in the Gulf waters. Vegetation indices, such as Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were used along with Surface Algae Bloom Index (SABI) to detect known outbreaks. MODIS (or Moderate Resolution Imaging Spectroradiometer) bands are used to calculate these indices. A red-tide outbreaks atlas in the Arabian Gulf is being produced. Prediction of red-tide outbreaks ahead of their occurrences would give critical information on possible water-shortage in the country. Detecting known outbreaks in the past few decades and related parameters (e.g. water salinity, water surface temperature, nutrition, sandstorms, … etc) enables the identification of favorite conditions of red-tide outbreak that are key to the prediction of these outbreaks.Keywords: Arabian Gulf, MODIS, red-tide detection, strategic water reserve, water desalination
Procedia PDF Downloads 1009380 Studies on the Applicability of Artificial Neural Network (ANN) in Prediction of Thermodynamic Behavior of Sodium Chloride Aqueous System Containing a Non-Electrolytes
Authors: Dariush Jafari, S. Mostafa Nowee
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In this study a ternary system containing sodium chloride as solute, water as primary solvent and ethanol as the antisolvent was considered to investigate the application of artificial neural network (ANN) in prediction of sodium solubility in the mixture of water as the solvent and ethanol as the antisolvent. The system was previously studied using by Extended UNIQUAC model by the authors of this study. The comparison between the results of the two models shows an excellent agreement between them (R2=0.99), and also approves the capability of ANN to predict the thermodynamic behavior of ternary electrolyte systems which are difficult to model.Keywords: thermodynamic modeling, ANN, solubility, ternary electrolyte system
Procedia PDF Downloads 3819379 Quality of Life of the Beneficiaries of the Government’s Bolsa Família Program: A Case Study in Mateiros/TO/Brazil
Authors: Mary L. G. S. Senna, Afonso R. Aquino, Veruska C. Dutra, Carlos H. C. Tolentino
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The quality of life index, despite elucidating many discussions, the conceptual subjectivity of the term does not show precision, and consequently, many researchers seek to develop methods aiming to measure this concept, bringing it to a more concrete approach. In this study, the quality of life index method was used to analyze the population of Mateiros, Tocantins, Brazil for quality of life. After data collection, it was compared the quality of life index between the population and the group of beneficiaries of the Brazilian government assistance program Bolsa Família (Family Allowance). Some of the people interviewed receive financial aid from the federal government program Bolsa Família (22%). Comparisons were made among the final score of the quality of life index of the Mateiros population and the following factors: Gender, age, education, those working or not with tourism and those who receive or do not receive the Bolsa Família. It was observed that only the factor, Bolsa Família (p-score 0.0138), shows an association with quality of life improvement, noticing that those who have financial aid had a higher quality of life improvement than the rest of the population. It was concluded that, government assistance has shown a decisive element on the enhancement of Mateiros population quality of life, indicating that similar actions should be maintained.Keywords: quality of life index, government aid to families, sustainable tourism, Bolsa Familia
Procedia PDF Downloads 2979378 Quality of Life of Mothers of Adolescents with Attention-Deficit/Hyperactivity Disorder Based on Lazarus-Folkman's Coping
Authors: Simin Hosseinian, Roghieh Nooripour
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Introduction: Attention-deficit/hyperactivity disorder (ADHD) is a major neuropsychiatric disorder diagnosis in children, adolescents. This study was aimed to investigate the quality of life of mothers of adolescents with ADHD based on Lazarus-Folkman's coping. Method: Due to this purpose, 120 mothers were selected with convenience sampling method that referred to counseling centers with their adolescents with ADHD for treatment of their adolescents and then they completed Iranian Quality of Life Questionnaire and The Ways of Coping Questionnaire (WCQ). Data were analyzed by the Pearson correlation and stepwise regression methods with SPSS-19. Results: The result showed that there was a positive significant relationship between quality of life and self-controlling and also a negative relationship between quality of life and accepting responsibility (p < 0.05). Conclusion: According to these findings, we can suggest suitable intervention for mothers who have adolescents with ADHD and enhance their quality of life.Keywords: ADHD, mother, adolescent, quality of life, Lazarus-Folkman
Procedia PDF Downloads 1689377 Strain Softening of Soil under Cyclic Loading
Authors: Kobid Panthi, Suttisak Soralump, Suriyon Prempramote
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In June 27, 2014 slope movement was observed in upstream side of Khlong Pa Bon Dam, Thailand. The slide did not have any major catastrophic impact on the dam structure but raised a very important question; why did the slide occur after 10 years of operation? Various site investigations (Bore Hole Test, SASW, Echo Sounding, and Geophysical Survey), laboratory analysis and numerical modelling using SIGMA/W and SLOPE/W were conducted to determine the cause of slope movement. It was observed that the dam had undergone the greatest differential drawdown in its operational history in the year 2014 and was termed as the major cause of movement. From the laboratory tests, it was found that the shear strength of clay had decreased with a period of time and was near its residual value. The cyclic movement of water, i.e., reservoir filling and emptying was coined out to be the major cause for the reduction of shear strength. The numerical analysis was carried out using a modified cam clay (MCC) model to determine the strain softening behavior of the clay. The strain accumulation was observed in the slope with each reservoir cycle triggering the slope failure in 2014. It can be inferred that if there was no major drawdown in 2014, the slope would not have failed but eventually would have failed after a long period of time. If there was no major drawdown in 2014, the slope would not have failed. However, even if there hadn’t been a drawdown, it would have failed eventually in the long run.Keywords: slope movement, strain softening, residual strength, modified cam clay
Procedia PDF Downloads 1239376 Novel GPU Approach in Predicting the Directional Trend of the S&P500
Authors: A. J. Regan, F. J. Lidgey, M. Betteridge, P. Georgiou, C. Toumazou, K. Hayatleh, J. R. Dibble
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Our goal is development of an algorithm capable of predicting the directional trend of the Standard and Poor’s 500 index (S&P 500). Extensive research has been published attempting to predict different financial markets using historical data testing on an in-sample and trend basis, with many authors employing excessively complex mathematical techniques. In reviewing and evaluating these in-sample methodologies, it became evident that this approach was unable to achieve sufficiently reliable prediction performance for commercial exploitation. For these reasons, we moved to an out-of-sample strategy based on linear regression analysis of an extensive set of financial data correlated with historical closing prices of the S&P 500. We are pleased to report a directional trend accuracy of greater than 55% for tomorrow (t+1) in predicting the S&P 500.Keywords: financial algorithm, GPU, S&P 500, stock market prediction
Procedia PDF Downloads 3449375 Numerical Investigation of the Boundary Conditions at Liquid-Liquid Interfaces in the Presence of Surfactants
Authors: Bamikole J. Adeyemi, Prashant Jadhawar, Lateef Akanji
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Liquid-liquid interfacial flow is an important process that has applications across many spheres. One such applications are residual oil mobilization, where crude oil and low salinity water are emulsified due to lowered interfacial tension under the condition of low shear rates. The amphiphilic components (asphaltenes and resins) in crude oil are considered to assemble at the interface between the two immiscible liquids. To justify emulsification, drag and snap-off suppression as the main effects of low salinity water, mobilization of residual oil is visualized as thickening and slip of the wetting phase at the brine/crude oil interface which results in the squeezing and drag of the non-wetting phase to the pressure sinks. Meanwhile, defining the boundary conditions for such a system can be very challenging since the interfacial dynamics do not only depend on interfacial tension but also the flow rate. Hence, understanding the flow boundary condition at the brine/crude oil interface is an important step towards defining the influence of low salinity water composition on residual oil mobilization. This work presents a numerical evaluation of three slip boundary conditions that may apply at liquid-liquid interfaces. A mathematical model was developed to describe the evolution of a viscoelastic interfacial thin liquid film. The base model is developed by the asymptotic expansion of the full Navier-Stokes equations for fluid motion due to gradients of surface tension. This model was upscaled to describe the dynamics of the film surface deformation. Subsequently, Jeffrey’s model was integrated into the formulations to account for viscoelastic stress within a long wave approximation of the Navier-Stokes equations. To study the fluid response to a prescribed disturbance, a linear stability analysis (LSA) was performed. The dispersion relation and the corresponding characteristic equation for the growth rate were obtained. Three slip (slip, 1; locking, -1; and no-slip, 0) boundary conditions were examined using the resulted characteristic equation. Also, the dynamics of the evolved interfacial thin liquid film were numerically evaluated by considering the influence of the boundary conditions. The linear stability analysis shows that the boundary conditions of such systems are greatly impacted by the presence of amphiphilic molecules when three different values of interfacial tension were tested. The results for slip and locking conditions are consistent with the fundamental solution representation of the diffusion equation where there is film decay. The interfacial films at both boundary conditions respond to exposure time in a similar manner with increasing growth rate which resulted in the formation of more droplets with time. Contrarily, no-slip boundary condition yielded an unbounded growth and it is not affected by interfacial tension.Keywords: boundary conditions, liquid-liquid interfaces, low salinity water, residual oil mobilization
Procedia PDF Downloads 1239374 Work Life Balance Strategies and Retention of Medical Professionals
Authors: Naseem M. Twaissi
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Medical professionals play an important role in society, and in general, they care more about their patients than about their personal well-being. They need to take a professional approach to maintain a work-life balance. Through a collection of primary data from 1020 medical professionals and the application of relevant statistical tools, this paper explores the pressures on medical professionals with reference to their work-life balance. This study highlights how hospital management, in addition to economic reasons, needs to identify variables to enhance the work-life balance of medical professionals so that quality healthcare facilities may be provided to the citizens of Jordan. Results indicate that formulation and implementation of policies for enhancing work-life balance together with career and retention plans for medical professionals would enhance the performance of hospitals and the quality of health care in Jordan, leading to greater societal well-being.Keywords: work life balance, job environment, job satisfaction, employee well-being, stress, hospital industry
Procedia PDF Downloads 1379373 Life Imprisonment: European Convention on Human Rights Standards and the New Serbian Criminal Code
Authors: Veljko Turanjanin
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In this article, an author deals with the issue of life imprisonment. Life imprisonment represents a new sentence in the Serbian legislature, in addition to the standard one, imprisonment. The author elaborated on judgments of the European Court of Human Rights (ECtHR), imposing the possibility of parole for the person sentenced to life imprisonment, emphasizing rehabilitation as the primary goal of penalties. According to the ECtHR, life imprisonment without parole is not permitted. The right to rehabilitation is very strictly set in the ECtHR jurisprudence. Life imprisonment represents a new sentence in the Serbian legislature, in addition to the standard one, imprisonment. The legislator provided the possibility of parole for most criminal offenses after 27 years in prison, while for some of them, a possibility of parole is explicitly prohibited. The author points out the shortcomings of the legal solution that exists in Serbia, which flagrantly threatens to violate the human rights of the offenders.Keywords: European Court of Human Rights, life imprisonment, parole, rehabilitation
Procedia PDF Downloads 1019372 A Social Care Intervention for Improving the Quality of Life of People Living with HIV/AIDS in Ghana
Authors: Tina Abrefa-Gyan
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Background: In Ghana and the rest of sub-Saharan Africa, HIV/AIDS is a public health threat and also causes medical crises for many who are infected with the virus. Objective: This study tested a social care intervention developed to help improve the quality of life of those living with HIV/AIDS in Ghana. Method: Adult respondents (N = 248) were assigned to receive the intervention or usual care for six weeks. Results: Results of the study revealed significant differences between the treatment and control groups in their reports of quality of life. Respondents reported better quality of life upon receiving the intervention. Implication: This study sheds light on the positive relationship between the intervention and quality of life among those living with HIV/AIDS in Ghana. Conclusion: The intervention is innovative and novel in the setting. It will, therefore, help to reduce the risks such as depression, low cognitive functioning, and low physical functioning associated with low quality of life among people living with HIV/AIDS in Ghana in specific, and in sub-Saharan Africa in general.Keywords: social care intervention, HIV/AIDS, Ghana, quality of life
Procedia PDF Downloads 4609371 Investigation of Fire Damaged Concrete Using Nonlinear Resonance Vibration Method
Authors: Kang-Gyu Park, Sun-Jong Park, Hong Jae Yim, Hyo-Gyung Kwak
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This paper attempts to evaluate the effect of fire damage on concrete by using nonlinear resonance vibration method, one of the nonlinear nondestructive method. Concrete exhibits not only nonlinear stress-strain relation but also hysteresis and discrete memory effect which are contained in consolidated materials. Hysteretic materials typically show the linear resonance frequency shift. Also, the shift of resonance frequency is changed according to the degree of micro damage. The degree of the shift can be obtained through nonlinear resonance vibration method. Five exposure scenarios were considered in order to make different internal micro damage. Also, the effect of post-fire-curing on fire-damaged concrete was taken into account to conform the change in internal damage. Hysteretic non linearity parameter was obtained by amplitude-dependent resonance frequency shift after specific curing periods. In addition, splitting tensile strength was measured on each sample to characterize the variation of residual strength. Then, a correlation between the hysteretic non linearity parameter and residual strength was proposed from each test result.Keywords: nonlinear resonance vibration method, non linearity parameter, splitting tensile strength, micro damage, post-fire-curing, fire damaged concrete
Procedia PDF Downloads 2649370 Natural Gas Production Forecasts Using Diffusion Models
Authors: Md. Abud Darda
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Different options for natural gas production in wide geographic areas may be described through diffusion of innovation models. This type of modeling approach provides an indirect estimate of an ultimately recoverable resource, URR, capture the quantitative effects of observed strategic interventions, and allow ex-ante assessments of future scenarios over time. In order to ensure a sustainable energy policy, it is important to forecast the availability of this natural resource. Considering a finite life cycle, in this paper we try to investigate the natural gas production of Myanmar and Algeria, two important natural gas provider in the world energy market. A number of homogeneous and heterogeneous diffusion models, with convenient extensions, have been used. Models validation has also been performed in terms of prediction capability.Keywords: diffusion models, energy forecast, natural gas, nonlinear production
Procedia PDF Downloads 2229369 Model Updating Based on Modal Parameters Using Hybrid Pattern Search Technique
Authors: N. Guo, C. Xu, Z. C. Yang
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In order to ensure the high reliability of an aircraft, the accurate structural dynamics analysis has become an indispensable part in the design of an aircraft structure. Therefore, the structural finite element model which can be used to accurately calculate the structural dynamics and their transfer relations is the prerequisite in structural dynamic design. A dynamic finite element model updating method is presented to correct the uncertain parameters of the finite element model of a structure using measured modal parameters. The coordinate modal assurance criterion is used to evaluate the correlation level at each coordinate over the experimental and the analytical mode shapes. Then, the weighted summation of the natural frequency residual and the coordinate modal assurance criterion residual is used as the objective function. Moreover, the hybrid pattern search (HPS) optimization technique, which synthesizes the advantages of pattern search (PS) optimization technique and genetic algorithm (GA), is introduced to solve the dynamic FE model updating problem. A numerical simulation and a model updating experiment for GARTEUR aircraft model are performed to validate the feasibility and effectiveness of the present dynamic model updating method, respectively. The updated results show that the proposed method can be successfully used to modify the incorrect parameters with good robustness.Keywords: model updating, modal parameter, coordinate modal assurance criterion, hybrid genetic/pattern search
Procedia PDF Downloads 1539368 Study of Slum Redevelopment Initiatives for Dharavi Slum, Mumbai and Its Effectiveness in Implementation in Other Cities
Authors: Anurag Jha
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Dharavi is the largest slum in Asia, for which many redevelopment projects have been put forth, to improve the housing conditions of the locals. And yet, these projects are met with much-unexpected resistance from the locals. The research analyses the why and the how of the resistances these projects face and analyses these programs and points out the flaws and benefits of such projects, by predicting its impact on the regulars of Dharavi. The research aims to analyze various aspects of Dharavi, which affect its socio-cultural backdrops, such as its history, and eventual growth into a mega slum. Through various surveys, the research aims to analyze the life of a slum dweller, the street life, and the effect of such settlement on the urban fabric. Various development projects such as Dharavi Museum Movement, are analyzed, and a feasibility and efficiency analysis of the proposals for redevelopment of Dharavi Slums has been theorized. Flaws and benefits of such projects, by predicting its impact on the regulars of Dharavi has been the major approach to the research. Also, prediction the implementation of these projects in another prominent slum area, Anand Nagar, Bhopal, with the use of generated hypothetical model has been done. The research provides a basic framework for a comparative analysis of various redevelopment projects and the effect of implementation of such projects on the general populace. Secondly, it proposes a hypothetical model for feasibility of such projects in certain slum areas.Keywords: Anand Nagar, Bhopal slums, Dharavi, slum redevelopment programmes
Procedia PDF Downloads 3269367 Design and Development of an Algorithm to Predict Fluctuations of Currency Rates
Authors: Nuwan Kuruwitaarachchi, M. K. M. Peiris, C. N. Madawala, K. M. A. R. Perera, V. U. N Perera
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Dealing with businesses with the foreign market always took a special place in a country’s economy. Political and social factors came into play making currency rate changes fluctuate rapidly. Currency rate prediction has become an important factor for larger international businesses since large amounts of money exchanged between countries. This research focuses on comparing the accuracy of mainly three models; Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Networks(ANN) and Support Vector Machines(SVM). series of data import, export, USD currency exchange rate respect to LKR has been selected for training using above mentioned algorithms. After training the data set and comparing each algorithm, it was able to see that prediction in SVM performed better than other models. It was improved more by combining SVM and SVR models together.Keywords: ARIMA, ANN, FFNN, RMSE, SVM, SVR
Procedia PDF Downloads 1989366 Impact of Welding Distortion on the Design of Fabricated T-Girders Using Finite Element Modeling
Authors: Ahmed Hammad, Yehia Abdel-Nasser, Mohamed Shamma
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The main configuration of ship construction consists of standard and fabricated stiffening members which are commonly used in shipbuilding such as fabricated T-sections. During the welding process, the non-uniform heating and rapid cooling lead to the inevitable presence of out-of-plane distortion and welding induced residual stresses. Because of these imperfections, the fabricated structural members may not attain their design load to be carried. The removal of these imperfections will require extra man-hours. In the present work, controlling these imperfections has been investigated at both design and fabrication stages. A typical fabricated T-girder is selected to investigate the problem of these imperfections using double-side welding. A numerical simulation based on finite element (FE) modeling has been used to investigate the effect of different parameters of the selected fabricated T-girder such as geometrical properties and welding sequences on the magnitude of welding imperfections. FE results were compared with the results of experimental model of a double-side fillet weld. The present work concludes that: Firstly, in the design stage, the optimum geometry of the fabricated T- girder is determined based on minimum steel weight and out- of- plane distortion. Secondly, in the fabrication stage, the best welding sequence is determined on the basis of minimum welding out- of- plane distortion.Keywords: fabricated T-girder, FEM, out-of-plane distortion, section modulus, welding residual stresses
Procedia PDF Downloads 1159365 Demographic Bomb or Bonus in All Provinces in 100 Years after Indonesian Independence
Authors: Fitri CaturLestari
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According to National Population and Family Planning Board (BKKBN), demographic bonus will occur in 2025-2035, when the number of people within the productive age bracket is higher than the number of elderly people and children. This time will be a gold moment for Indonesia to achieve maximum productivity and prosperity. But it will be a demographic bomb if it isn’t balanced by economic and social aspect considerations. Therefore it is important to make a prediction mapping of all provinces in Indonesia whether in demographic bomb or bonus condition after 100 years Indonesian independence. The purpose of this research were to make the demographic mapping based on the economic and social aspects of the provinces in Indonesia and categorizing them into demographic bomb and bonus condition. The research data are gained from Statistics Indonesia (BPS) as the secondary data. The multiregional component method, regression and quadrant analysis were used to predict the number of people, economic growth, Human Development Index (HDI), and gender equality in education and employment. There were different characteristic of provinces in Indonesia from economic aspect and social aspect. The west Indonesia was already better developed than the east one. The prediction result, many provinces in Indonesia will get demographic bonus but the others will get demographic bomb. It is important to prepare particular strategy to particular provinces with all of their characteristic based on the prediction result so the demographic bomb can be minimalized.Keywords: demography, economic growth, gender, HDI
Procedia PDF Downloads 3239364 Effect of Load Ratio on Probability Distribution of Fatigue Crack Propagation Life in Magnesium Alloys
Authors: Seon Soon Choi
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It is necessary to predict a fatigue crack propagation life for estimation of structural integrity. Because of an uncertainty and a randomness of a structural behavior, it is also required to analyze stochastic characteristics of the fatigue crack propagation life at a specified fatigue crack size. The essential purpose of this study is to present the good probability distribution fit for the fatigue crack propagation life at a specified fatigue crack size in magnesium alloys under various fatigue load ratio conditions. To investigate a stochastic crack growth behavior, fatigue crack propagation experiments are performed in laboratory air under several conditions of fatigue load ratio using AZ31. By Anderson-Darling test, a goodness-of-fit test for probability distribution of the fatigue crack propagation life is performed and the good probability distribution fit for the fatigue crack propagation life is presented. The effect of load ratio on variability of fatigue crack propagation life is also investigated.Keywords: fatigue crack propagation life, load ratio, magnesium alloys, probability distribution
Procedia PDF Downloads 6409363 Prediction of Bariatric Surgery Publications by Using Different Machine Learning Algorithms
Authors: Senol Dogan, Gunay Karli
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Identification of relevant publications based on a Medline query is time-consuming and error-prone. An all based process has the potential to solve this problem without any manual work. To the best of our knowledge, our study is the first to investigate the ability of machine learning to identify relevant articles accurately. 5 different machine learning algorithms were tested using 23 predictors based on several metadata fields attached to publications. We find that the Boosted model is the best-performing algorithm and its overall accuracy is 96%. In addition, specificity and sensitivity of the algorithm is 97 and 93%, respectively. As a result of the work, we understood that we can apply the same procedure to understand cancer gene expression big data.Keywords: prediction of publications, machine learning, algorithms, bariatric surgery, comparison of algorithms, boosted, tree, logistic regression, ANN model
Procedia PDF Downloads 2049362 Morality in Actual Behavior: The Moderation Effect of Identification with the Ingroup and Religion on Norm Compliance
Authors: Shauma L. Tamba
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This study examined whether morality is the most important aspect in actual behavior. The prediction was that people tend to behave in line with moral (as compared to competence) norms, especially when such norms are presented by their ingroup. The actual behavior that was tested was support for a military intervention without a mandate from the UN. In addition, this study also examined whether identification with the ingroup and religion moderated the effect of group and norm on support for the norm that was prescribed by their ingroup. The prediction was that those who identified themselves higher with the ingroup moral would show a higher support for the norm. Furthermore, the prediction was also that those who have religion would show a higher support for the norm in the ingroup moral rather than competence. In an online survey, participants were asked to read a scenario in which a military intervention without a mandate was framed as either the moral (but stupid) or smart (but immoral) thing to do by members of their own (ingroup) or another (outgroup) society. This study found that when people identified themselves with the smart (but immoral) norm, they showed a higher support for the norm. However, when people identified themselves with the moral (but stupid) norm, they tend to show a lesser support towards the norm. Most of the results in the study did not support the predictions. Possible explanations and implications are discussed.Keywords: morality, competence, ingroup identification, religion, group norm
Procedia PDF Downloads 4039361 Application of the Electrical Resistivity Tomography and Tunnel Seismic Prediction 303 Methods for Detection Fracture Zones Ahead of Tunnel: A Case Study
Authors: Nima Dastanboo, Xiao-Qing Li, Hamed Gharibdoost
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The purpose of this study is to investigate about the geological properties ahead of a tunnel face with using Electrical Resistivity Tomography ERT and Tunnel Seismic Prediction TSP303 methods. In deep tunnels with hydro-geological conditions, it is important to study the geological structures of the region before excavating tunnels. Otherwise, it would lead to unexpected accidents that impose serious damage to the project. For constructing Nosoud tunnel in west of Iran, the ERT and TSP303 methods are employed to predict the geological conditions dynamically during the excavation. In this paper, based on the engineering background of Nosoud tunnel, the important results of applying these methods are discussed. This work demonstrates seismic method and electrical tomography as two geophysical techniques that are able to detect a tunnel. The results of these two methods were being in agreement with each other but the results of TSP303 are more accurate and quality. In this case, the TSP 303 method was a useful tool for predicting unstable geological structures ahead of the tunnel face during excavation. Thus, using another geophysical method together with TSP303 could be helpful as a decision support in excavating, especially in complicated geological conditions.Keywords: tunnel seismic prediction (TSP303), electrical resistivity tomography (ERT), seismic wave, velocity analysis, low-velocity zones
Procedia PDF Downloads 1379360 Machine Learning Approach in Predicting Cracking Performance of Fiber Reinforced Asphalt Concrete Materials
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
Procedia PDF Downloads 1329359 Surface Roughness Analysis, Modelling and Prediction in Fused Deposition Modelling Additive Manufacturing Technology
Authors: Yusuf S. Dambatta, Ahmed A. D. Sarhan
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Fused deposition modelling (FDM) is one of the most prominent rapid prototyping (RP) technologies which is being used to efficiently fabricate CAD 3D geometric models. However, the process is coupled with many drawbacks, of which the surface quality of the manufactured RP parts is among. Hence, studies relating to improving the surface roughness have been a key issue in the field of RP research. In this work, a technique of modelling the surface roughness in FDM is presented. Using experimentally measured surface roughness response of the FDM parts, an ANFIS prediction model was developed to obtain the surface roughness in the FDM parts using the main critical process parameters that affects the surface quality. The ANFIS model was validated and compared with experimental test results.Keywords: surface roughness, fused deposition modelling (FDM), adaptive neuro fuzzy inference system (ANFIS), orientation
Procedia PDF Downloads 4489358 Impact of Design Choices on the Life Cycle Energy of Modern Buildings
Authors: Mahsa Karimpour, Martin Belusko, Ke Xing, Frank Bruno
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Traditionally the embodied energy of design choices which reduce operational energy were assumed to have a negligible impact on the life cycle energy of buildings. However with new buildings having considerably lower operational energy, the significance of embodied energy increases. A life cycle assessment of a population of house designs was conducted in a mild and mixed climate zone. It was determined not only that embodied energy dominates life cycle energy, but that the impact on embodied of design choices was of equal significance to the impact on operational energy.Keywords: building life cycle energy, embodied energy, energy design measures, low energy buildings
Procedia PDF Downloads 764