Search results for: corrosion prediction ductile fracture

Authors: Manit Pollar

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Identifying the dengue epidemic periods early would be helpful to take necessary actions to prevent the dengue outbreaks. Providing an accurate prediction on dengue epidemic seasons will allow sufficient time to take the necessary decisions and actions to safeguard the situation for local authorities. This study aimed to develop a forecasting model on number of dengue incidences in Nakhon Si Thammarat Province, Southern Thailand using time series analysis. We develop Seasonal Autoregressive Moving Average (SARIMA) models on the monthly data collected between 2003-2011 and validated the models using data collected between January-September 2012. The result of this study revealed that the SARIMA(1,1,0)(1,2,1)12 model closely described the trends and seasons of dengue incidence and confirmed the existence of dengue fever cases in Nakhon Si Thammarat for the years between 2003-2011. The study showed that the one-step approach for predicting dengue incidences provided significantly more accurate predictions than the twelve-step approach. The model, even if based purely on statistical data analysis, can provide a useful basis for allocation of resources for disease prevention.

Keywords: SARIMA, time series model, dengue cases, Thailand

Procedia PDF Downloads 347

Authors: Aml M. El-Sharkawy, Hossam M. Darwesh

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Abstract— Background/Aim: Hepatocellular carcinoma (HCC) is often diagnosed at advanced stage where effective therapies are lacking. Identification of new scoring system is needed to discriminate HCC patients from those with chronic liver disease. Based on the link between tumor associated trypsin inhibitor (TATI) and HCC progression, we aimed to develop a novel score based on combination of TATI and routine laboratory tests for early prediction of HCC. Methods: TATI was assayed for HCC group (123), liver cirrhosis group (210) and control group (50) by Enzyme Linked Immunosorbent Assay (ELISA). Data from all groups were retrospectively analyzed including α feto protein (AFP), international normalized ratio (INR), albumin and platelet count, transaminases, and age. Areas under ROC curve were used to develop the score. Results: A novel index named hepatocellular carcinoma-vascular endothelial growth factor score (HCC-TATI score) = 3.1 (numerical constant) + 0.09 ×AFP (U L-1) + 0.067 × TATI (ng ml-1) + 0.16 × INR – 1.17 × Albumin (g l-1) – 0.032 × Platelet count × 109 l-1 was developed. HCC-TATI score produce area under ROC curve of 0.98 for discriminating HCC patients from liver cirrhosis with sensitivity of 91% and specificity of 82% at cut-off 6.5 (ie less than 6.5 considered cirrhosis and greater than 4.4 considered HCC). Conclusion: Hepatocellular carcinoma-TATI score could replace AFP in HCC screening and follow up of cirrhotic patients.

Keywords: Hepatocellular carcinoma, cirrhosis, HCV, diagnosis, TATI

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Authors: Emilio A. Berny-Brandt, Sonia E. Ruiz

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Steel tubular towers serving as support structures for large wind turbines are subject to several hundred million stress cycles arising from the turbulent nature of the wind. This causes high-cycle fatigue which can govern tower design. The practice of maintaining the support structure after wind turbines reach its typical 20-year design life have become common, but without quantifying the changes in the reliability on the tower. There are several studies on this topic, but most of them are based on the S-N curve approach using the Miner’s rule damage summation method, the de-facto standard in the wind industry. However, the qualitative nature of Miner’s method makes desirable the use of fracture mechanics to measure the effects of fatigue in the capacity curve of the structure, which is important in order to evaluate the integrity and reliability of these towers. Temporal and spatially varying wind speed time histories are simulated based on power spectral density and coherence functions. Simulations are then applied to a SAP2000 finite element model and step-by-step analysis is used to obtain the stress time histories for a range of representative wind speeds expected during service conditions of the wind turbine. Rainflow method is then used to obtain cycle and stress range information of each of these time histories and a statistical analysis is performed to obtain the distribution parameters of each variable. Monte Carlo simulation is used here to evaluate crack growth over time in the tower base using the Paris-Erdogan equation. A nonlinear static pushover analysis to assess the capacity curve of the structure after a number of years is performed. The capacity curves are then used to evaluate the changes in reliability of a steel tower located in Oaxaca, Mexico, where wind energy facilities are expected to grow in the near future. Results show that fatigue on the tower base can have significant effects on the structural capacity of the wind turbine, especially after the 20-year design life when the crack growth curve starts behaving exponentially.

Keywords: crack growth, fatigue, Monte Carlo simulation, structural reliability, wind turbines

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Authors: Ruchika Malhotra, Megha Khanna

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The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.

Keywords: change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics

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Authors: Mustafa Bayram Gücen, Coşkun Yakar

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In this study, we have investigated the strict stability of fuzzy differential systems and we compare the classical notion of strict stability criteria of ordinary differential equations and the notion of strict stability of fuzzy differential systems. In addition that, we present definitions of stability and strict stability of fuzzy differential equations and also we have some theorems and comparison results. Strict Stability is a different stability definition and this stability type can give us an information about the rate of decay of the solutions. Lyapunov’s second method is a standard technique used in the study of the qualitative behavior of fuzzy differential systems along with a comparison result that allows the prediction of behavior of a fuzzy differential system when the behavior of the null solution of a fuzzy comparison system is known. This method is a usefull for investigating strict stability of fuzzy systems. First of all, we present definitions and necessary background material. Secondly, we discuss and compare the differences between the classical notion of stability and the recent notion of strict stability. And then, we have a comparison result in which the stability properties of the null solution of the comparison system imply the corresponding stability properties of the fuzzy differential system. Consequently, we give the strict stability results and a comparison theorem. We have used Lyapunov second method and we have proved a comparison result with scalar differential equations.

Keywords: fuzzy systems, fuzzy differential equations, fuzzy stability, strict stability

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Authors: P. Charvin, R. Bourrou, F. Lemont, C. Lafon, A. Russello

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For nuclear waste treatment and confinement, a specific IN-CAN melting module based on low-frequency induction heating have been designed. The frequency of 50Hz has been chosen to improve penetration length through metal. In this design, the liquid metal, strongly stirred by electromagnetic effects, presents shape of a dome caused by strong Laplace forces developing in the bulk of bath. Because of a lower density, the glass phase is located above the metal phase and is heated and stirred by metal through interface. Electric parameters (Intensity, frequency) give precious information about metal load and composition (resistivity of alloy) through impedance modification. Then, power supply can be adapted to energy transfer efficiency for suitable process supervision. Modeling of this system allows prediction of metal dome shape (in agreement with experimental measurement with a specific device), glass and metal velocity, heat and motion transfer through interface. MHD modeling is achieved with COMSOL and Fluent. First, a simplified model is used to obtain the shape of the metal dome. Then the shape is fixed to calculate the fluid flow and the thermal part.

Keywords: electromagnetic stirring, induction heating, interface modeling, metal load

Procedia PDF Downloads 252

Authors: Emmanuel Chinagorom Nwadike, Joseph Tagbo Nwabanne, Matthew Ndubuisi Abonyi, Onyemazu Andrew Azaka

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This research focused on the modeling of the convective drying of aerial yam using finite element methods. The thermo-gravimetric analyzer was used to determine the thermal stability of the sample. An aerial yam sample of size 30 x 20 x 4 mm was cut with a mold designed for the purpose and dried in a convective dryer set at 4m/s fan speed and temperatures of 68.58 and 60.56°C. The volume shrinkage of the resultant dried sample was determined by immersing the sample in a toluene solution. The finite element analysis was done with PDE tools in Matlab 2015. Seven kinetic models were employed to model the drying process. The result obtained revealed three regions in the thermogravimetric analysis (TGA) profile of aerial yam. The maximum thermal degradation rates of the sample occurred at 432.7°C. The effective thermal diffusivity of the sample increased as the temperature increased from 60.56°C to 68.58°C. The finite element prediction of moisture content of aerial yam at an air temperature of 68.58°C and 60.56°C shows R² of 0.9663 and 0.9155, respectively. There was a good agreement between the finite element predicted moisture content and the measured moisture content, which is indicative of a highly reliable finite element model developed. The result also shows that the best kinetic model for the aerial yam under the given drying conditions was the Logarithmic model with a correlation coefficient of 0.9991.

Keywords: aerial yam, finite element, convective, effective, diffusivity

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Authors: Abdullah Al Mamoon, Ataur Rahman

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Due to climate change, future rainfall will change at many locations on earth; however, the spatial and temporal patterns of this change are not easy to predict. One approach of predicting such future changes is to examine the trends in the historical rainfall data at a given region and use the identified trends to make future prediction. For this, a statistical trend test is commonly applied to the historical data. This paper examines the trends of daily extreme rainfall events from 30 rain gauges located in the State of Qatar. Rainfall data covering from 1962 to 2011 were used in the analysis. A combination of four non-parametric and parametric tests was applied to identify trends at 10%, 5%, and 1% significance levels. These tests are Mann-Kendall (MK), Spearman’s Rho (SR), Linear Regression (LR) and CUSUM tests. These tests showed both positive and negative trends throughout the country. Only eight stations showed positive (upward) trend, which were however not statistically significant. In contrast, significant negative (downward) trends were found at the 5% and 10% levels of significance in six stations. The MK, SR and LR tests exhibited very similar results. This finding has important implications in the derivation/upgrade of design rainfall for Qatar, which will affect design and operation of future urban drainage infrastructure in Qatar.

Keywords: trends, extreme rainfall, daily rainfall, Mann-Kendall test, climate change, Qatar

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Authors: L. Pu, C. Unluer

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MgO cements have the potential to sequester CO2 in construction products, and can be partial or complete replacement of PC in concrete. Construction block is a promising application for reactive MgO cements. Main advantages of blocks are: (i) suitability for sequestering CO2 due to their initially porous structure; (ii) lack of need for in-situ treatment as carbonation can take place during fabrication; and (iii) high potential for commercialization. Both strength gain and carbon sequestration of MgO cements depend on carbonation process. Fly ash and ground granulated blast-furnace slag (GGBS) are pozzolanic material and are proved to improve many of the performance characteristics of the concrete, such as strength, workability, permeability, durability and corrosion resistance. A very limited amount of work has been reported on the production of MgO blocks on a large scale so far. A much more extensive study, wherein blocks with different mix design is needed to verify the feasibility of commercial production. The changes in the performance of the samples were evaluated by compressive strength testing. The properties of the carbonation products were identified by X-ray diffraction (XRD) and scanning electron microscopy (SEM)/ field emission scanning electron microscopy (FESEM), and the degree of carbonation was obtained by thermogravimetric analysis (TGA), XRD and energy dispersive X-ray (EDX). The results of this study enabled the understanding the relationship between lab-scale samples and scale-up blocks based on their mechanical performance and microstructure. Results indicate that for both scaled-up and lab-scale samples, MgO samples always had the highest strength results, followed by MgO-fly ash samples and MgO-GGBS had relatively lowest strength. The lower strength of MgO with fly ash/GGBS samples at early stage is related to the relatively slow hydration process of pozzolanic materials. Lab-scale cubic samples were observed to have higher strength results than scaled-up samples. The large size of the scaled-up samples made it more difficult to let CO2 to reach inner part of the samples and less carbonation products formed. XRD, TGA and FESEM/EDX results indicate the existence of brucite and HMCs in MgO samples, M-S-H, hydrotalcite in the MgO-fly ash samples and C-S-H, hydrotalctie in the MgO-GGBS samples. Formation of hydration products (M-S-H, C-S-H, hydrotalcite) and carbonation products (hydromagnecite, dypingite) increased with curing duration, which is the reason of increasing strength. This study verifies the advantage of large-scale MgO blocks over common PC blocks and the feasibility of commercial production of MgO blocks.

Keywords: reactive MgO, fly ash, ground granulated blast-furnace slag, carbonation, CO₂

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Authors: John Davidson, Matteo Castelletti, Ismael Torres, Victor Terente, Jamie Irvine, Sylvie Raymackers

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The current industry approach to pile driving predictions consists of developing a model of the hammer-pile-soil system which simulates the relationship between soil resistance to driving (SRD) and blow counts (or pile penetration per blow). The SRD methods traditionally used are broadly based on static pile capacity calculations. The SRD is used in combination with the one-dimensional wave equation model to indicate the anticipated blowcounts with depth for specific hammer energy settings. This approach has predominantly been calibrated on relatively long slender piles used in the oil and gas industry but is now being extended to allow calculations to be undertaken for relatively short rigid large diameter monopile foundations. This paper evaluates the accuracy of current industry practice when applied to a site where large diameter monopiles were installed in predominantly stiff fissured clay. Actual geotechnical and pile installation data, including pile driving records and signal matching analysis (based upon pile driving monitoring techniques), were used for the assessment on the case study site.

Keywords: driven piles, fissured clay, London clay, monopiles, offshore foundations

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Authors: Klazina T. Havinga, Hilde R. H. de Geus

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Introduction: Pre-operative coagulation management of Apixaban prescribed patients, a new oral anticoagulant (a factor Xa inhibitor), is difficult, especially when chronic kidney disease (CKD) causes drug overdose. Apixaban is not dialyzable due to its high level of protein binding. An antidote, Andexanet α, is available but expensive and has an unfavorable short half-life. We report the successful extracorporeal removal of Apixaban prior to emergency surgery with the CytoSorb® Hemoadsorption device. Methods: A 89-year-old woman with CKD, with an Apixaban prescription for atrial fibrillation, was presented at the ER with traumatic rib fractures, a flail chest, and an unstable spinal fracture (T12) for which emergency surgery was indicated. However, due to very high Apixaban levels, this surgery had to be postponed. Based on the Apixaban-specific anti-factor Xa activity (AFXaA) measurements at admission and 10 hours later, complete clearance was expected after 48 hours. In order to enhance the Apixaban removal and reduce the time to operation, and therefore reduce pulmonary complications, CRRT with CytoSorb® cartridge was initiated. Apixaban-specific anti-factor Xa activity (AFXaA) was measured frequently as a substitute for Apixaban drug concentrations, pre- and post adsorber, in order to calculate the adsorber-related clearance. Results: The admission AFXaA concentration, as a substitute for Apixaban drug levels, was 218 ng/ml, which decreased to 157 ng/ml after ten hours. Due to sustained anticoagulation effects, surgery was again postponed. However, the AFXaA levels decreased quickly to sub-therapeutic levels after CRRT (Multifiltrate Pro, Fresenius Medical Care, Blood flow 200 ml/min, Dialysate Flow 4000 ml/h, Prescribed renal dose 51 ml-kg-h) with Cytosorb® connected in series into the circuit was initiated (within 5 hours). The adsorber-related (indirect) Apixaban clearance was calculated every half hour (Cl=Qe * (AFXaA pre- AFXaA post/ AFXaA pre) with Qe=plasma flow rate calculated with Ht=0.38 and system blood flow rate 200 ml-min): 100 ml/min, 72 ml/min and 57 ml/min. Although, as expected, the adsorber-related clearance decreased quickly due to saturation of the beads, still the reduction rate achieved resulted in a very rapid decrease in AFXaA levels. Surgery was ordered and possible within 5 hours after Cytosorb initiation. Conclusion: The CytoSorb® Hemoadsorption device enabled rapid correction of Apixaban associated anticoagulation.

Keywords: Apixaban, CytoSorb, emergency surgery, Hemoadsorption

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Authors: Irene Buj-Corral, Ali Bagheri, Alejandro Dominguez-Fernandez

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In recent years, use of ceramic prostheses as an implant in some parts of body has become common. In the present study, research has focused on replacement of the acetabulum bone, which is a part of the pelvis bone. Metallic prostheses have shown some problems such as release of metal ions into patient's blood. In addition, fracture of liners and squeezing between surface of femoral head and inner surface of acetabulum have been reported. Ceramic prostheses have the advantage of low debris and high strength, although they are more difficult to be manufactured than metallic ones. Specifically, new designs try to attempt an acetabulum in which the outer surface will be porous for proliferation of cells and fixation of the prostheses by means of osteointegration, while inner surface must be smooth enough to assure that the movement between femoral head and inner surface will be carried out with on feasibility. In the present study, 3D printing technologies are used for manufacturing ceramic prostheses. In Fused Deposition Modelling (FDM) process, 3D printed plastic prostheses are obtained by means of melting of a plastic filament and subsequent deposition on a glass surface. A similar process is applied to ceramics in which ceramic powders need to be mixed with a liquid polymer before depositing them. After 3D printing, parts are subjected to a sintering process in an oven so that they can achieve final strength. In the present paper, influence of printing parameters on surface roughness 3D printed ceramic parts are presented. Three parameter full factorial design of experiments was used. Selected variables were layer height, infill and nozzle diameter. Responses were average roughness Ra and mean roughness depth Rz. Regression analysis was applied to responses in order to obtain mathematical models for responses. Results showed that surface roughness depends mainly on layer height and nozzle diameter employed, while infill was found not to be significant. In order to get low surface roughness, low layer height and low infill should be selected. As a conclusion, layer height and infill are important parameters for obtaining good surface finish in ceramic 3D printed prostheses. However, use of too low infill could lead to prostheses with low mechanical strength. Such prostheses could not be able to bear the static and dynamic charges to which they are subjected once they are implanted in the body. This issue will be addressed in further research.

Keywords: ceramic, hip prostheses, surface roughness, 3D printing

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Authors: Zahra Hamedani

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Many wonderful technological developments in recent years has opened up the possibility of using intelligent buildings for a number of important applications, ranging from minimizing resource usage as well as increasing building efficiency to maximizing comfort, adaption to inhabitants and responsiveness to environmental changes. The concept of an intelligent building refers to the highly embedded, interactive environment within which by exploiting the use of artificial intelligence provides the ability to know its configuration, anticipate the optimum dynamic response to prevailing environmental stimuli, and actuate the appropriate physical reaction to provide comfort and efficiency. This paper contains a general identification of the intelligence paradigm and its impacts on the architecture arena, that with examining the performance of artificial intelligence, a mechanism to analyze and finally for decision-making to control the environment will be described. This mechanism would be a hierarchy of the rational agents which includes decision-making, information, communication and physical layers. This multi-agent system relies upon machine learning techniques for automated discovery, prediction and decision-making. Then, the application of this mechanism regarding adaptation and responsiveness of intelligent building will be provided in two scales of environmental and user. Finally, we review the identifications of sustainability and evaluate the potentials of intelligent building systems in the creation of sustainable architecture and environment.

Keywords: artificial intelligence, intelligent building, responsiveness, adaption, sustainability

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Authors: Jayanta Pokharel, Gokarna Aryal, Netra Kanaal, Chris Tsokos

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Investment in stocks and shares aims to seek potential gains while weighing the risk of future needs, such as retirement, children's education etc. Analysis of the behavior of the stock market returns and making prediction is important for investors to mitigate risk on investment. Historically, the normal variance models have been used to describe the behavior of stock market returns. However, the returns of the financial assets are actually skewed with higher kurtosis, heavier tails, and a higher center than the normal distribution. The Laplace distribution and its family are natural candidates for modeling stock returns. The Variance-Gamma (VG) distribution is the most sought-after distributions for modeling asset returns and has been extensively discussed in financial literatures. In this paper, it explore the other Laplace family, such as Asymmetric Laplace, Skewed Laplace, Kumaraswamy Laplace (KS) together with Variance-Gamma to model the weekly returns of the S&P 500 Index and it's eleven business sector indices. The method of maximum likelihood is employed to estimate the parameters of the distributions and our empirical inquiry shows that the Kumaraswamy Laplace distribution performs much better for stock returns modeling among the choice of distributions used in this study and in practice, KS can be used as a strong alternative to VG distribution.

Keywords: stock returns, variance-gamma, kumaraswamy laplace, maximum likelihood

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Authors: Amit Kumar, Amanpreet Chander, Ashish Sahani

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This paper presents our recent work on real-time human activity detection based on the media pipe pipeline and machine learning algorithms. The proposed system can detect human activities, including running, jumping, squatting, bending to the left or right, and standing still. This is a robust solution for developing a yoga, dance, metaverse, and fitness application that checks for the correction of the pose without having any additional monitor like a personal trainer. MediaPipe solution offers an open-source cross-platform which utilizes a two-step detector-tracker ML pipeline for live detection of key landmarks on our body which can be used for motion data collection. The prediction of real-time poses uses a variety of machine learning techniques and different types of analysis. Without primarily relying on powerful desktop environments for inference, our method achieves real-time performance on the majority of contemporary mobile phones, desktops/laptops, Python, or even the web. Experimental results show that our method outperforms the existing method in terms of accuracy and real-time capability, achieving an accuracy of 99.92% on testing datasets.

Keywords: human activity detection, media pipe, machine learning, metaverse applications

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

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Authors: Novutry Siregar, Afdal, Emilzon Taslim

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Hyaline Membrane Disease (HMD) is the main cause of respiratory failure in preterm neonates caused by surfactant deficiency. Nasal Continuous Positive Airway Pressure (NCPAP) is the therapy for HMD. The success of therapy is determined by gestational age, birth weight, HMD grade, time of NCAP administration, and time of breathing frequency recovery. The aim of this research is to identify the predictive factor of NCPAP therapy success in preterm neonates with HMD. This study used a cross-sectional design by using medical records of patients who were treated in the Perinatology of the Pediatric Department of Dr. M. Djamil Padang Central Hospital from January 2015 to December 2017. The samples were eighty-two neonates that were selected by using the total sampling technique. Data analysis was done by using the Chi-Square Test and the Multiple Logistic Regression Prediction Model. The results showed the success rate of NCPAP therapy reached 53.7%. Birth weight (p = 0.048, OR = 3.34 95% CI 1.01-11.07), HMD grade I (p = 0.018, OR = 4.95 CI 95% 1.31-18.68), HMD grade II (p = 0.044, OR = 5.52 95% CI 1.04-29.15), and time of breathing frequency recovery (p = 0,000, OR = 13.50 95% CI 3.58-50, 83) are the predictive factors of NCPAP therapy success in preterm neonates with HMD. The most significant predictive factor is the time of breathing frequency recovery.

Keywords: predictive factors, the success of therapy, NCPAP, preterm neonates, HMD

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Authors: Hamidreza Saberkari, Mousa Shamsi, Hossein Ahmadi, Saeed Vaali, , MohammadHossein Sedaaghi

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In the recent years, using signal processing tools for accurate identification of the protein coding regions has become a challenge in bioinformatics. Most of the genomic signal processing methods is based on the period-3 characteristics of the nucleoids in DNA strands and consequently, spectral analysis is applied to the numerical sequences of DNA to find the location of periodical components. In this paper, a novel ensemble algorithm for gene selection in DNA sequences has been presented which is based on the combination of Goertzel algorithm and anti-notch filter (ANF). The proposed algorithm has many advantages when compared to other conventional methods. Firstly, it leads to identify the coding protein regions more accurate due to using the Goertzel algorithm which is tuned at the desired frequency. Secondly, faster detection time is achieved. The proposed algorithm is applied on several genes, including genes available in databases BG570 and HMR195 and their results are compared to other methods based on the nucleotide level evaluation criteria. Implementation results show the excellent performance of the proposed algorithm in identifying protein coding regions, specifically in identification of small-scale gene areas.

Keywords: protein coding regions, period-3, anti-notch filter, Goertzel algorithm

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Authors: Yung-Jin Weng, Chia-Chi Chang, Chun-Yu Tsai

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This paper is focused on the research of imprinting and replica molding of quasi-grey scale soft mold curved surface microstructure mold. In this paper, a magnetic photocuring forming system is first developed and built independently, then the magnetic curved surface microstructure soft mode is created; moreover, the magnetic performance of the magnetic curved surface at different heights is tested and recorded, and through experimentation and simulation, the magnetic curved surface microstructure soft mold is used in the research of quasi-grey scale soft mold curved surface microstructure imprinting and replica molding. The experimental results show that, under different surface curvatures and voltage control conditions, different quasi-grey scale array microstructures take shape. In addition, this paper conducts research on the imprinting and replica molding of photoresist composite magnetic powder in order to discuss the forming performance of magnetic photoresist, and finally, the experimental result is compared with the simulation to obtain more accurate prediction and results. This research is predicted to provide microstructure component preparation technology with heterogeneity and controllability, and is a kind of valid shaping quasi-grey scale microstructure manufacturing technology method.

Keywords: soft mold, magnetic, microstructure, curved surface

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Authors: Pompa Marcello, Mauro Capocelli, Vincenzo Piemonte

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This work focuses on a mathematical model able to describe the gastro-intestinal physiology and providing a rational tool for the design of an artificial gastro-intestinal system. This latter is mainly devoted to analyse the absorption and bioavailability of drugs and nutrients through in vitro tests in order to overcome (or, at least, to partially replace) in vivo trials. The provided model realizes a conjunction ring (with extended prediction capability) between in vivo tests and mechanical-laboratory models emulating the human body. On this basis, no empirical equations controlling the gastric emptying are implemented in this model as frequent in the cited literature and all the sub-unit and the related system of equations are physiologically based. More in detail, the model structure consists of six compartments (stomach, duodenum, jejunum, ileum, colon and blood) interconnected through pipes and valves. Paracetamol, Ketoprofen, Irbesartan and Ketoconazole are considered and analysed in this work as reference drugs. The mathematical model has been validated against in vivo literature data. Results obtained show a very good model reliability and highlight the possibility to realize tailored simulations for different couples patient-drug, including food adsorption dynamics.

Keywords: gastro-intestinal model, drugs bioavailability, paracetamol, ketoprofen

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Authors: Zhenyu Yang, Qiunan Chen, Xiaocheng Huang

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Reliable prediction of tunnel collapse remains a prominent challenge in the field of civil engineering. In this study, leveraging the nonlinear Hoek-Brown failure criterion and the upper-bound theorem, an analytical solution for the collapse surface of shallowly buried circular tunnels was derived, taking into account the coupled effects of surface loads and pore water pressures. Initially, surface loads and pore water pressures were introduced as external force factors, equating the energy dissipation rate to the external force, yielding our objective function. Subsequently, the variational method was employed for optimization, and the outcomes were juxtaposed with previous research findings. Furthermore, we utilized the deduced equation set to systematically analyze the influence of various rock mass parameters on collapse shape and extent. To validate our analytical solutions, a comparison with prior studies was executed. The corroboration underscored the efficacy of our proposed methodology, offering invaluable insights for collapse risk assessment in practical engineering applications.

Keywords: tunnel roof stability, analytical solution, hoek–brown failure criterion, limit analysis

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Authors: Ismael Zamora, Elisabeth Ortega, Tatiana Radchenko, Guillem Plasencia

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The structure elucidation based on Mass Spectra (MS) data of unknown substances is an unresolved problem that affects many different fields of application. The recent overview of software available for structure elucidation of small molecules has shown the demand for efficient computational tool that will be able to perform structure elucidation of unknown small molecules and peptides. We developed an algorithm for De-Novo fragment analysis based on MS data that proposes a set of scored and ranked structures that are compatible with the MS and MSMS spectra. Several different algorithms were developed depending on the initial set of fragments and the structure building processes. Also, in all cases, several scores for the final molecule ranking were computed. They were validated with small and middle databases (DB) with the eleven test set compounds. Similar results were obtained from any of the databases that contained the fragments of the expected compound. We presented an algorithm. Or De-Novo fragment analysis based on only mass spectrometry (MS) data only that proposed a set of scored/ranked structures that was validated on different types of databases and showed good results as proof of concept. Moreover, the solutions proposed by Mass Spectrometry were submitted to the prediction of NMR spectra in order to elucidate which of the proposed structures was compatible with the NMR spectra collected.

Keywords: De Novo, structure elucidation, mass spectrometry, NMR

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Authors: Kirill M. Dubovikov, Ekaterina S. Marchenko, Gulsharat A. Baigonakova

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NiTi alloys are widely used as implants in medicine due to their unique properties such as superelasticity, shape memory effect and biocompatibility. However, despite these properties, one of the major problems is the release of nickel after prolonged use in the human body under dynamic stress. This occurs due to oxidation and cracking of NiTi implants, which provokes nickel segregation from the matrix to the surface and release into living tissues. As we know, nickel is a toxic element and can cause cancer, allergies, etc. One of the most popular ways to solve this problem is to create a corrosion resistant coating on NiTi. There are many coatings of this type, but not all of them have good biocompatibility, which is very important for medical implants. Coatings based on calcium phosphate phases have excellent biocompatibility because Ca and P are the main constituents of the mineral part of human bone. This fact suggests that a Ca-P coating on NiTi can enhance osteogenesis and accelerate the healing process. Therefore, the aim of this study is to investigate the structure of Ca-P coating on NiTi substrate. Plasma assisted radio frequency (RF) sputtering was used to obtain this film. This method was chosen because it allows the crystallinity and morphology of the Ca-P coating to be controlled by the sputtering parameters. It allows us to obtain three different NiTi samples with Ca-P coating. XRD, AFM, SEM and EDS were used to study the composition, structure and morphology of the coating phase. Scratch tests were carried out to evaluate the adhesion of the coating to the substrate. Wettability tests were used to investigate the hydrophilicity of the different coatings and to suggest which of them had better biocompatibility. XRD showed that the coatings of all samples were hydroxyapatite, but the matrix was represented by TiNi intermetallic compounds such as B2, Ti2Ni and Ni3Ti. The SEM shows that the densest and defect-free coating has only one sample after three hours of sputtering. Wettability tests show that the sample with the densest coating has the lowest contact angle of 40.2° and the largest free surface area of 57.17 mJ/m2, which is mostly disperse. A scratch test was carried out to investigate the adhesion of the coating to the surface and it was shown that all coatings were removed by a cohesive mechanism. However, at a load of 30N, the indenter reached the substrate in two out of three samples, except for the sample with the densest coating. It was concluded that the most promising sputtering mode was the third, which consisted of three hours of deposition. This mode produced a defect-free Ca-P coating with good wettability and adhesion.

Keywords: biocompatibility, calcium phosphate coating, NiTi alloy, radio frequency sputtering.

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Authors: Michel Soto Chalhoub

Abstract:

Building designers in the Mediterranean region and other parts of the world utilize natural stone panels on the exterior façades as skin cover. This type of finishing is not only intended for aesthetic reasons but also environmental. The stone, since the earliest ages of civilization, has been used in construction and to-date some of the most appealing buildings owe their beauty to stone finishing. The stone also provides warmth in winter and freshness in summer as it moderates heat transfer and absorbs radiation. However, as structural codes became increasingly stringent about the dynamic performance of buildings, it became essential to study the performance of stone panels under cyclic loading – a condition that arises under the building is subjected to wind or earthquakes. The present paper studies the performance of stone panels using mechanical connectors when subjected to load reversal. In this paper, we present a theoretical model that addresses modes of failure in the steel connectors, by yield, and modes of failure in the stone, by fracture. Then we provide an experimental set-up and test results for rectangular stone panels of varying thickness. When the building is subjected to an earthquake, its rectangular panels within the structural system are subjected to shear deformations, which in turn impart stress into the stone cover. Rectangular stone panels, which typically range from 40cmx80cm to 60cmx120cm, need to be designed to withstand transverse loading from the direct application of lateral loads, and to withstand simultaneously in-plane loading (membrane stress) caused by inter-story drift and overall building lateral deflection. Results show correlation between the theoretical model which we derive from solid mechanics fundamentals and the experimental results, and lead to practical design recommendations. We find that for panel thickness below a certain threshold, it is more advantageous to utilize structural adhesive materials to connect stone panels to the main structural system of the building. For larger panel thicknesses, it is recommended to utilize mechanical connectors with special detailing to ensure a minimum level of ductility and energy dissipation.

Keywords: solid mechanics, cyclic loading, mechanical connectors, natural stone, seismic, wind, building skin

Procedia PDF Downloads 250

Authors: E. Ghasemi Ardi, K. J. Dong, A. B. Yu, R. Y. Yang

Abstract:

In current work, a numerical model based on the discrete element method (DEM) was developed which provided information about particle dynamic and impact event condition inside a laboratory scale impact mill (Fritsch). It showed that each particle mostly experiences three impacts inside the mill. While the first impact frequently happens at front surface of the rotor’s rib, the frequent location of the second impact is side surfaces of the rotor’s rib. It was also showed that while the first impact happens at small impact angle mostly varying around 35º, the second impact happens at around 70º which is close to normal impact condition. Also analyzing impact energy revealed that varying mill speed from 6000 to 14000 rpm, the ratio of first impact’s average impact energy and minimum required energy to break particle (Wₘᵢₙ) increased from 0.30 to 0.85. Moreover, it was seen that second impact poses intense impact energy on particle which can be considered as the main cause of particle splitting. Finally, obtained information from DEM simulation along with obtained data from conducted experiments was implemented in semi-empirical equations in order to find selection and breakage functions. Then, using a back-calculation approach, those parameters were used to predict the PSDs of ground particles under different impact energies. Results were compared with experiment results and showed reasonable accuracy and prediction ability.

Keywords: single particle breakage, particle dynamic, population balance model, particle size distribution, discrete element method

Procedia PDF Downloads 280

Authors: L. Adjlout, N.Benharrat, O. Ladjdel, F. Djemil, A. Adjlout, T. Yahiaoui

Abstract:

The present investigation is an experimental and numerical studies of the turbulence level influence on the flow in a smooth staggered tube bundle. The experiments were carried out in a closed circuit wind tunnel of subsonic type (TE44). Three turbulence levels at the inlet namely 1%, 4.6% and 6.3% and two Reynolds numbers Re = 9300 and Re = 13950 were performed. The obtained results for the central tube show that there are two minimum values for the angles 70° and 280° corresponding to the separation points. The pressure coefficient distributions seem to have constant values between 120° and 240° resulting in Von Karman street configuration in the wake. These remarks were valid for the tests carried out. The numerical study was performed by the ANSYS FLUENT code which solves the averaged Navier-Stokes equations (RANS). Two turbulence models (k-ε RNG and k-ε realizable), two types of grids and two levels of turbulence at the entrance of 4.6% and 6.3% for Reynolds numbers of 9300 and 13950 were considered. The obtained results for the central tube were compared with the present experimental results. It is concluded that the K-ε realizable is more suitable for the pressure distribution prediction than the K-ε RNG model compared to the present experimental results for this studied case.

Keywords: tube bundle, staggered configuration, turbulence level, numerical, experimental

Procedia PDF Downloads 123

Authors: Nikoloz Jalabadze, Roin Chedia, Lili Nadaraia, Levan Khundadze

Abstract:

Nanocrystalline materials in powder condition can be manufactured by a number of different methods, however manufacture of composite materials product in the same nanocrystalline state is still a problem because the processes of compaction and synthesis of nanocrystalline powders go with intensive growth of particles – the process which promotes formation of pieces in an ordinary crystalline state instead of being crystallized in the desirable nanocrystalline state. To date spark plasma sintering (SPS) has been considered as the most promising and energy efficient method for producing dense bodies of composite materials. An advantage of the SPS method in comparison with other methods is mainly low temperature and short time of the sintering procedure. That finally gives an opportunity to obtain dense material with nanocrystalline structure. Graphene has recently garnered significant interest as a reinforcing phase in composite materials because of its excellent electrical, thermal and mechanical properties. Graphene nanoplatelets (GNPs) in particular have attracted much interest as reinforcements for ceramic matrix composites (mostly in Al2O3, Si3N4, TiO2, ZrB2 a. c.). SPS has been shown to fully densify a variety of ceramic systems effectively including Al2O3 and often with improvements in mechanical and functional behavior. Alumina consolidated by SPS has been shown to have superior hardness, fracture toughness, plasticity and optical translucency compared to conventionally processed alumina. Knowledge of how GNPs influence sintering behavior is important to effectively process and manufacture process. In this study, the effects of GNPs on the SPS processing of Al2O3 are investigated by systematically varying sintering temperature, holding time and pressure. Our experiments showed that SPS process is also appropriate for the synthesis of nanocrystalline powders of alumina-graphene composites. Depending on the size of the molds, it is possible to obtain different amount of nanopowders. Investigation of the structure, physical-chemical, mechanical and performance properties of the elaborated composite materials was performed. The results of this study provide a fundamental understanding of the effects of GNP on sintering behavior, thereby providing a foundation for future optimization of the processing of these promising nanocomposite systems.

Keywords: alumina oxide, ceramic matrix composites, graphene nanoplatelets, spark-plasma sintering

Procedia PDF Downloads 366

Authors: Ali Reza Tahavvor, Saeed Hosseini, Nazli Jowkar, Afshin Karimzadeh Fard

Abstract:

Experimental & numeral study of temperature distribution during milling process, is important in milling quality and tools life aspects. In the present study the milling cross-section temperature is determined by using Artificial Neural Networks (ANN) according to the temperature of certain points of the work piece and the points specifications and the milling rotational speed of the blade. In the present work, at first three-dimensional model of the work piece is provided and then by using the Computational Heat Transfer (CHT) simulations, temperature in different nods of the work piece are specified in steady-state conditions. Results obtained from CHT are used for training and testing the ANN approach. Using reverse engineering and setting the desired x, y, z and the milling rotational speed of the blade as input data to the network, the milling surface temperature determined by neural network is presented as output data. The desired points temperature for different milling blade rotational speed are obtained experimentally and by extrapolation method for the milling surface temperature is obtained and a comparison is performed among the soft programming ANN, CHT results and experimental data and it is observed that ANN soft programming code can be used more efficiently to determine the temperature in a milling process.

Keywords: artificial neural networks, milling process, rotational speed, temperature

Procedia PDF Downloads 389

Authors: B. S. Fatoyinbo, D. Stretch, O. T. Amoo, D. Allopi

Abstract:

This study extends the use of the Drainage Area Regionalization (DAR) method in generating synthetic data and calibrating PyTOPKAPI stream yield for an ungauged basin at a daily time scale. The generation of runoff in determining a river yield has been subjected to various topographic and spatial meteorological variables, which integers form the Catchment Characteristics Model (CCM). Many of the conventional CCM models adapted in Africa have been challenged with a paucity of adequate, relevance and accurate data to parameterize and validate the potential. The purpose of generating synthetic flow is to test a hydrological model, which will not suffer from the impact of very low flows or very high flows, thus allowing to check whether the model is structurally sound enough or not. The employed physically-based, watershed-scale hydrologic model (PyTOPKAPI) was parameterized with GIS-pre-processing parameters and remote sensing hydro-meteorological variables. The validation with mean annual runoff ratio proposes a decent graphical understanding between observed and the simulated discharge. The Nash-Sutcliffe efficiency and coefficient of determination (R²) values of 0.704 and 0.739 proves strong model efficiency. Given the current climate variability impact, water planner can now assert a tool for flow quantification and sustainable planning purposes.

Keywords: catchment characteristics model, GIS, synthetic data, ungauged basin

Procedia PDF Downloads 314

Authors: Issam Aouari, Abdelmalek Abdelhamid

Abstract:

For seismologists, the characterization of seismic demand should include the amplitude and duration of strong shaking in the system. The duration of ground shaking is one of the key parameters in earthquake resistant design of structures. This paper proposes a nonlinear statistical model to estimate earthquake ground motion duration in soft soils using multiple seismicity indicators. Three definitions of ground motion duration proposed by literature have been applied. With a comparative study, we select the most significant definition to use for predict the duration. A stochastic model is presented for the McCann and Shah Method using nonlinear regression analysis based on a data set for moment magnitude, source to site distance and site conditions. The data set applied is taken from PEER strong motion databank and contains shallow earthquakes from different regions in the world; America, Turkey, London, China, Italy, Chili, Mexico...etc. Main emphasis is placed on soft site condition. The predictive relationship has been developed based on 600 records and three input indicators. Results have been compared with others published models. It has been found that the proposed model can predict earthquake ground motion duration in soft soils for different regions and sites conditions.

Keywords: duration, earthquake, prediction, regression, soft soil

Procedia PDF Downloads 143