Search results for: predicting models

Authors: Mohamed A. Shanan, Ashraf H. El-Zanaty, Kamal G. Metwally

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This paper presents the effect of concrete compressive strength and rectangularity ratio on strength and ductility of normal and high strength reinforced concrete columns confined with transverse steel under axial compressive loading. Nineteen normal strength concrete rectangular columns with different variables tested in this research were used to study the effect of concrete compressive strength and rectangularity ratio on strength and ductility of columns. The paper also presents a nonlinear finite element analysis for these specimens and another twenty high strength concrete square columns tested by other researchers using ANSYS 15 finite element software. The results indicate that the axial force – axial strain relationship obtained from the analytical model using ANSYS are in good agreement with the experimental data. The comparison shows that the ANSYS is capable of modeling and predicting the actual nonlinear behavior of confined normal and high-strength concrete columns under concentric loading. The maximum applied load and the maximum strain have also been confirmed to be satisfactory. Depending on this agreement between the experimental and analytical results, a parametric numerical study was conducted by ANSYS 15 to clarify and evaluate the effect of each variable on strength and ductility of the columns.

Keywords: ANSYS, concrete compressive strength effect, ductility, rectangularity ratio, strength

Procedia PDF Downloads 489

Authors: Hojjat Mohammadi, Randall Divito, Gary J. E. Kramer

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Tunnelling and pipe jacking in very soft soils (fat clays), even with an Earth Pressure Balance tunnel boring machine (EPBM), can cause large ground displacements. In this study, the short-term and long-term ground and tunnel response is predicted for twin, pipe-jacked EPBM 3 meter diameter tunnels with a narrow pillar width. Initial modelling indicated complete closure of the annulus gap at the tail shield onto the centrifugally cast, glass-fiber-reinforced, polymer mortar jacking pipe (FRP). Numerical modelling was employed to simulate the excavation and support installation sequence, examine the ground response during excavation, confirm the adequacy of the pillar width and check the structural adequacy of the installed pipe. In the numerical models, Mohr-Coulomb constitutive model with the effect of unloading was adopted for the fat clays, while for the bedrock layer, the generalized Hoek-Brown was employed. The numerical models considered explicit excavation sequences and different levels of ground convergence prior to support installation. The well-studied excavation sequences made the analysis possible for this study on a very soft clay, otherwise, obtaining the convergency in the numerical analysis would be impossible. The predicted results indicate that the ground displacements around the tunnel and its effect on the pipe would be acceptable despite predictions of large zones of plastic behaviour around the tunnels and within the entire pillar between them due to excavation-induced ground movements.

Keywords: finite element modeling (FEM), pipe-jacked tunneling, very soft clay, EPBM

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Authors: Solmaz Jahed Shiran, John Hearne, Tayebeh Saghapour

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Daily travel behavior is strongly influenced by the location of the places of residence, education, and employment. Hence a change in those locations due to a move or changes in an occupation leads to a change in travel behavior. Given the interventions of housing mobility and travel behaviors, the hypothesis is that a mobile housing market allows households to move as a result of any change in their life course, allowing them to be closer to central services, public transport facilities and workplace and hence reducing the time spent by individuals on daily travel. Conversely, household’s immobility may lead to longer commutes of residents, for example, after a change of a job or a need for new services such as schools for children who have reached their school age. This paper aims to investigate the association between residential mobility and travel behavior. The Victorian Integrated Survey of Travel and Activity (VISTA) data is used for the empirical analysis. Car ownership and journey to work time and distance of employed people are used as indicators of travel behavior. Change of usual residence within the last five years used to identify movers and non-movers. Statistical analysis, including regression models, is used to compare the travel behavior of movers and non-movers. The results show travel time, and the distance does not differ for movers and non-movers. However, this is not the case when taking into account the residence tenure-type. In addition, car ownership rate and number found to be significantly higher for non-movers. It is hoped that the results from this study will contribute to a better understanding of factors other than common socioeconomic and built environment features influencing travel behavior.

Keywords: journey to work, regression models, residential mobility, commute mode, car ownership

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Authors: Matthias Stange

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Architectural visualization has been practiced for as long as there have been buildings. Visualization (lat.: visibilis "visible") generally refers to bringing abstract data and relationships into a graphically, visually comprehensible form. Particularly, visualization refers to the process of translating relationships that are difficult to formulate linguistically or logically into visual media (e.g., drawings or models) to make them comprehensible. Building owners have always been interested in knowing how their building will look before it is built. In the empirical part of this study, the roots of architectural visualization are examined, starting from the ancient civilizations to the end of the Roman Empire. Extensive literature research on architectural theory and architectural history forms the basis for this analysis. The focus of the analysis is basic research from the emergence of the first two-dimensional drawings in the Neolithic period to the triggers of significant further developments of architectural representation, as well as their importance for subsequent methods and the transmission of knowledge over the following epochs. The analysis focuses on the development of analog methods of representation from the first Neolithic house floor plans to the Greek detailed stone models and paper drawings in the Roman Empire. In particular, the question of socio-cultural, socio-political, and economic changes as possible triggers for the development of representational media and methods will be analyzed. The study has shown that the development of visual building representation has been driven by scientific, technological, and social developments since the emergence of the first civilizations more than 6000 years ago first by the change in human’s subsistence strategy, from food appropriation by hunting and gathering to food production by agriculture and livestock, and the sedentary lifestyle required for this.

Keywords: ancient Greece, ancient orient, Roman Empire, architectural visualization

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Authors: Dicko Ali Hamadi, Tong-Yette Nicolas, Gilles Benjamin, Faure Francois, Palombi Olivier

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A novel hybrid model of the lumbar spine, allowing fast static and dynamic simulations of the disc pressure and the spine mobility, is introduced in this work. Our contribution is to combine rigid bodies, deformable finite elements, articular constraints, and springs into a unique model of the spine. Each vertebra is represented by a rigid body controlling a surface mesh to model contacts on the facet joints and the spinous process. The discs are modeled using a heterogeneous tetrahedral finite element model. The facet joints are represented as elastic joints with six degrees of freedom, while the ligaments are modeled using non-linear one-dimensional elastic elements. The challenge we tackle is to make these different models efficiently interact while respecting the principles of Anatomy and Mechanics. The mobility, the intradiscal pressure, the facet joint force and the instantaneous center of rotation of the lumbar spine are validated against the experimental and theoretical results of the literature on flexion, extension, lateral bending as well as axial rotation. Our hybrid model greatly simplifies the modeling task and dramatically accelerates the simulation of pressure within the discs, as well as the evaluation of the range of motion and the instantaneous centers of rotation, without penalizing precision. These results suggest that for some types of biomechanical simulations, simplified models allow far easier modeling and faster simulations compared to usual full-FEM approaches without any loss of accuracy.

Keywords: hybrid, modeling, fast simulation, lumbar spine

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Authors: Juan Sebastián Rivera Soriano, Rosa Urbano Gutiérrez

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The Shodan House and the Sarabhai House (Ahmedabad, India, 1954 and 1955, respectively) are considered some of the most important works of Le Corbusier produced in the last stage of his career. There are some academic publications that study the compositional and formal aspects of their architectural design, but there is no in-depth investigation into how the climatic conditions of this region were a determining factor in the design decisions implemented in these projects. This paper argues that Le Corbusier developed a specific architectural design strategy for these buildings based on scientific research on climate in the Indian context. This new language was informed by a pioneering study and interpretation of climatic data as a design methodology that would even involve the development of new design tools. This study investigated whether their use of climatic data meets values and levels of accuracy obtained with contemporary instruments and tools, such as Energy Plus weather data files and Climate Consultant. It also intended to find out if Le Corbusier's office’s intentions and decisions were indeed appropriate and efficient for those climate conditions by assessing these projects using BIM models and energy performance simulations from Design Builder. Accurate models were built using original historical data through archival research. The outcome is to provide a new understanding of the environment of these houses through the combination of modern building science and architectural history. The results confirm that in these houses, it was achieved a model of low energy consumption. This paper contributes new evidence not only on exemplary modern architecture concerned with environmental performance but also on how it developed progressive thinking in this direction.

Keywords: bioclimatic architecture, Le Corbusier, Shodan, Sarabhai Houses

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Authors: Tehreem Fatima, Enjun Xia

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The research investigates the relationship between total oil consumption and transport oil consumption, GDP, oil price, and oil reserve in order to forecast future oil demand in China. Annual time series data is used over the period of 1980 to 2015, and for this purpose, an oil demand function is estimated by applying structural time series model (STSM). The technique also uncovers the Underline energy demand trend (UEDT) for China oil demand and GDP, oil reserve, oil price and UEDT are considering important drivers of China oil demand. The long-run elasticity of total oil consumption with respect to GDP and price are (0.5, -0.04) respectively while GDP, oil reserve, and price remain (0.17; 0.23; -0.05) respectively. Moreover, the Estimated results of long-run elasticity of transport oil consumption with respect to GDP and price are (0.5, -0.00) respectively long-run estimates remain (0.28; 37.76;-37.8) for GDP, oil reserve, and price respectively. For both model estimated underline energy demand trend (UEDT) remains nonlinear and stochastic and with an increasing trend of (UEDT) and based on estimated equations, it is predicted that China total oil demand somewhere will be 9.9 thousand barrel per day by 2025 as compare to 9.4 thousand barrel per day in 2015, while transport oil demand predicting value is 9.0 thousand barrel per day by 2020 as compare to 8.8 thousand barrel per day in 2015.

Keywords: china, forecasting, oil, structural time series model (STSM), underline energy demand trend (UEDT)

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Authors: Mustafa Sertçelik, Turan Çalban, Hacali Necefoğlu, Sabri Çolak

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In this study, Chevreul’s salt solubility and its dissolution kinetics in ammonium chloride solutions were investigated. Chevreul’s salt that we used in the studies was obtained by using the optimum conditions (ammonium sulphide concentration; 0,4 M, copper sulphate concentration; 0,25 M, temperature; 60°C, stirring speed; 600 rev/min, pH; 4 and reaction time; 15 mins) determined by T. Çalban et al. Chevreul’s salt solubility in ammonium chloride solutions and the kinetics of dissolution were investigated. The selected parameters that affect solubility were reaction temperature, concentration of ammonium chloride, stirring speed, and solid/liquid ratio. Correlation of experimental results had been achieved using linear regression implemented in the statistical package program statistica. The effect of parameters on Chevreul’s salt solubility was examined and integrated rate expression of dissolution rate was found using kinetic models in solid-liquid heterogeneous reactions. The results revealed that the dissolution rate of Chevreul’s salt was decreasing while temperature, concentration of ammonium chloride and stirring speed were increasing. On the other hand, dissolution rate was found to be decreasing with the increase of solid/liquid ratio. Based on result of the applications of the obtained experimental results to the kinetic models, we can deduce that Chevreul’s salt dissolution rate is controlled by diffusion through the ash (or product layer). Activation energy of the reaction of dissolution was found as 74.83 kJ/mol. The integrated rate expression along with the effects of parameters on Chevreul's salt solubility was found to be as follows: 1-3(1-X)2/3+2(1-X)= [2,96.1013.(CA)3,08 .(S/L)-038.(W)1,23 e-9001,2/T].t

Keywords: Chevreul's salt, copper, ammonium chloride, ammonium sulphide, dissolution kinetics

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Authors: Steven D. P Moore

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A novel method referred to asKýklos(Ky) dimensional geometry is proposed as an entity specific core geometric dimensional measurement system. Ky geometric measures can constructscaled multi-dimensionalmodels using regular and irregular sets in IRn. This entity specific-derived geometric measurement system shares similar fractal methods in which a ‘fractal transformation operator’ is applied to a set S to produce a union of N copies. The Kýklos’ inputs use 1D geometry as a core measure. One-dimensional inputs include the radius interval of a circle/sphere or the semiminor/semimajor axes intervals of an ellipse or spheroid. These geometric inputs have finite values that can be measured by SI distance units. The outputs for each interval are divided and subdivided 1D subcomponents with a union equal to the interval geometry/length. Setting a limit of subdivision iterations creates a finite value for each 1Dsubcomponent. The uniqueness of this method is captured by allowing the simplest 1D inputs to define entity specific subclass geometric core measurements that can also be used to derive length measures. Current methodologies for celestial based measurement of time, as defined within SI units, fits within this methodology, thus combining spatial and temporal features into geometric core measures. The novel Ky method discussed here offers geometric measures to construct scaled multi-dimensional structures, even models. Ky classes proposed for consideration include celestial even subatomic. The application of this offers incredible possibilities, for example, geometric architecture that can represent scaled celestial models that incorporates planets (spheroids) and celestial motion (elliptical orbits).

Keywords: Kyklos, geometry, measurement, celestial, dimension

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Authors: Lule Basha, Eralda Gjika

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This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine-learning methods, such as random forest, are used to predict cereal yield responses to climacteric and other variables. Random Forest showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the Random Forest method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods.

Keywords: cereal yield, climate change, machine learning, multiple regression model, random forest

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Authors: J. Fox, J. Randhawa, M. Chan, L. Campbell, A. Weakely, D. J. Harvey, S. Tomaszewski Farias

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Early identification of individuals at risk for conversion to dementia provides an opportunity for preventative treatment. Many older adults (30-60%) report specific subjective cognitive decline (SCD); however, previous research is inconsistent in terms of what types of complaints predict future cognitive decline. The purpose of this study is to identify which specific complaints from the Everyday Cognition Scales (ECog) scales, a measure of self-reported concerns for everyday abilities across six cognitive domains, are associated with: 1) conversion from a clinical diagnosis of normal to either MCI or dementia (categorical variable) and 2) progressive cognitive decline in memory and executive function (continuous variables). 415 cognitively normal older adults were monitored annually for an average of 5 years. Cox proportional hazards models were used to assess associations between self-reported ECog items and progression to impairment (MCI or dementia). A total of 114 individuals progressed to impairment; the mean time to progression was 4.9 years (SD=3.4 years, range=0.8-13.8). Follow-up models were run controlling for depression. A subset of individuals (n=352) underwent repeat cognitive assessments for an average of 5.3 years. For those individuals, mixed effects models with random intercepts and slopes were used to assess associations between ECog items and change in neuropsychological measures of episodic memory or executive function. Prior to controlling for depression, subjective concerns on five of the eight Everyday Memory items, three of the nine Everyday Language items, one of the seven Everyday Visuospatial items, two of the five Everyday Planning items, and one of the six Everyday Organization items were associated with subsequent diagnostic conversion (HR=1.25 to 1.59, p=0.003 to 0.03). However, after controlling for depression, only two specific complaints of remembering appointments, meetings, and engagements and understanding spoken directions and instructions were associated with subsequent diagnostic conversion. Episodic memory in individuals reporting no concern on ECog items did not significantly change over time (p>0.4). More complaints on seven of the eight Everyday Memory items, three of the nine Everyday Language items, and three of the seven Everyday Visuospatial items were associated with a decline in episodic memory (Interaction estimate=-0.055 to 0.001, p=0.003 to 0.04). Executive function in those reporting no concern on ECog items declined slightly (p <0.001 to 0.06). More complaints on three of the eight Everyday Memory items and three of the nine Everyday Language items were associated with a decline in executive function (Interaction estimate=-0.021 to -0.012, p=0.002 to 0.04). These findings suggest that specific complaints across several cognitive domains are associated with diagnostic conversion. Specific complaints in the domains of Everyday Memory and Language are associated with a decline in both episodic memory and executive function. Increased monitoring and treatment of individuals with these specific SCD may be warranted.

Keywords: alzheimer’s disease, dementia, memory complaints, mild cognitive impairment, risk factors, subjective cognitive decline

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Authors: Rinku Varghese, S. Chandrakaran, K. Rangaswamy

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The standard one-dimensional consolidation test is used to find the consolidation behaviour of artificially consolidated organic soils. Incremental loading tests were conducted on the clay without and with organic matter. The study was conducted with soil having different organic content keeping all other parameters constant. The tests were conducted on clay and artificially prepared organic soil sample at different vertical pressure. The load increment ratio considered for the test is equal to one. Artificial organic soils are used for the test by adding starch to the clay. The percentage of organic content in starch is determined by adding 5% by weight starch into the clay (inorganic soil) sample and corresponding change in organic content of soil was determined. This was expressed as percentage by weight of starch, and it was found that about 95% organic content in the soil sample. Accordingly percentage of organic content fixed and added to the sample for testing to understand the consolidation behaviour clayey soils with organic content. A detailed study of the results obtained from IL test was investigated. The main items investigated were (i) coefficient of consolidation (cv), (ii) coefficient of volume compression (mv), (iii) coefficient of permeability (k). The consolidation parameter obtained from IL test was used for determining the creep strain and creep parameter and also predicting their variation with vertical stress and organic content.

Keywords: consolidation, secondary compression, creep, starch

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Authors: Alireza Nikbakht Shahbazi

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There are various factors that affect climate changes; drought is one of those factors. Investigation of efficient methods for estimating climate change impacts on drought should be assumed. The aim of this paper is to investigate climate change impacts on drought in Karoon3 watershed located south-western Iran in the future periods. The atmospheric general circulation models (GCM) data under Intergovernmental Panel on Climate Change (IPCC) scenarios should be used for this purpose. In this study, watershed drought under climate change impacts will be simulated in future periods (2011 to 2099). Standard precipitation index (SPI) as a drought index was selected and calculated using mean monthly precipitation data in Karoon3 watershed. SPI was calculated in 6, 12 and 24 months periods. Statistical analysis on daily precipitation and minimum and maximum daily temperature was performed. LRAS-WG5 was used to determine the feasibility of future period's meteorological data production. Model calibration and verification was performed for the base year (1980-2007). Meteorological data simulation for future periods under General Circulation Models and climate change IPCC scenarios was performed and then the drought status using SPI under climate change effects analyzed. Results showed that differences between monthly maximum and minimum temperature will decrease under climate change and spring precipitation shall increase while summer and autumn rainfall shall decrease. The precipitation occurs mainly between January and May in future periods and summer or autumn precipitation decline and lead up to short term drought in the study region. Normal and wet SPI category is more frequent in B1 and A2 emissions scenarios than A1B.

Keywords: climate change impact, drought severity, drought frequency, Karoon3 watershed

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Authors: M. Eskandarighadi, C. R. McGann

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It is observed from past experiences of earthquakes that local site conditions can significantly affect the strong ground motion characteristics experience at the site. One-dimensional seismic site response analysis is the most common approach for investigating site response. This approach assumes that soil is homogeneous and infinitely extended in the horizontal direction. Therefore, tying side boundaries together is one way to model this behavior, as the wave passage is assumed to be only vertical. However, 1D analysis cannot capture the 2D nature of wave propagation, soil heterogeneity, and 2D soil profile with features such as inclined layer boundaries. In contrast, 2D seismic site response modeling can consider all of the mentioned factors to better understand local site effects on strong ground motions. 2D wave propagation and considering that the soil profile on the two sides of the model may not be identical clarifies the importance of a boundary condition on each side that can minimize the unwanted reflections from the edges of the model and input appropriate loading conditions. Ideally, the model size should be sufficiently large to minimize the wave reflection, however, due to computational limitations, increasing the model size is impractical in some cases. Another approach is to employ free-field boundary conditions that take into account the free-field motion that would exist far from the model domain and apply this to the sides of the model. This research focuses on implementing free-field boundary conditions in OpenSees for 2D site response analysisComparisons are made between 1D models and 2D models with various boundary conditions, and details and limitations of the developed free-field boundary modeling approach are discussed.

Keywords: boundary condition, free-field, opensees, site response analysis, wave propagation

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Authors: Man-Yu Wong, Siyu Zhou, Zhiqiang Cao

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In quality of life, health service utilization is an important determinant of medical resource expenditures on Colorectal cancer (CRC) care, a better understanding of the increased utilization of health services is essential for optimizing the allocation of healthcare resources to services and thus for enhancing the service quality, especially for high expenditure on CRC care like Hong Kong region. In assessing the association between the health-related quality of life (HRQOL) and health service utilization in patients with colorectal neoplasm, count data models can be used, which account for over dispersion or extra zero counts. In our data, the HRQOL evaluation is a self-reported measure obtained from a questionnaire completed by the patients, misreports and variations in the data are inevitable. Besides, there are more zero counts from the observed number of clinical consultations (observed frequency of zero counts = 206) than those from a Poisson distribution with mean equal to 1.33 (expected frequency of zero counts = 156). This suggests that excess of zero counts may exist. Therefore, we study tests for detecting zero-inflation in models with measurement error in covariates. Method: Under classical measurement error model, the approximate likelihood function for zero-inflation Poisson regression model can be obtained, then Approximate Maximum Likelihood Estimation(AMLE) can be derived accordingly, which is consistent and asymptotically normally distributed. By calculating score function and Fisher information based on AMLE, a score test is proposed to detect zero-inflation effect in ZIP model with measurement error. The proposed test follows asymptotically standard normal distribution under H0, and it is consistent with the test proposed for zero-inflation effect when there is no measurement error. Results: Simulation results show that empirical power of our proposed test is the highest among existing tests for zero-inflation in ZIP model with measurement error. In real data analysis, with or without considering measurement error in covariates, existing tests, and our proposed test all imply H0 should be rejected with P-value less than 0.001, i.e., zero-inflation effect is very significant, ZIP model is superior to Poisson model for analyzing this data. However, if measurement error in covariates is not considered, only one covariate is significant; if measurement error in covariates is considered, only another covariate is significant. Moreover, the direction of coefficient estimations for these two covariates is different in ZIP regression model with or without considering measurement error. Conclusion: In our study, compared to Poisson model, ZIP model should be chosen when assessing the association between condition-specific HRQOL and health service utilization in patients with colorectal neoplasm. and models taking measurement error into account will result in statistically more reliable and precise information.

Keywords: count data, measurement error, score test, zero inflation

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Authors: Ma Lanting, S. Eguilior, A. Hurtado, Juan F. Llamas Borrajo

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Horizontal hydraulic fracturing is a technology to increase natural gas flow and improve productivity in the low permeability formation. During this drilling operation tons of flowback and produced water which contains many organic compounds return to the surface with a potential risk of influencing the surrounding environment and human health. A mathematical model is urgently needed to represent organic compounds in water transportation process behavior and the concentration change with time throughout the hydraulic fracturing operation life cycle. A comprehensive model combined Organic Matter Transport Dynamic Model with Two-Compartment First-order Model Constant (TFRC) Model has been established to quantify the organic compounds concentration. This algorithm model is composed of two transportation parts based on time factor. For the fast part, the curve fitting technique is applied using flowback water data from the Marcellus shale gas site fracturing and the coefficients of determination (R2) from all analyzed compounds demonstrate a high experimental feasibility of this numerical model. Furthermore, along a decade of drilling the concentration ratio curves have been estimated by the slow part of this model. The result shows that the larger value of Koc in chemicals, the later maximum concentration in water will reach, as well as all the maximum concentrations percentage would reach up to 90% of initial concentration from shale formation within a long sufficient period.

Keywords: model, shale gas, concentration, organic compounds

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Authors: Melody Yin

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Concussions impact a large amount of adolescents; they make up as much as half of the diagnosed concussions in America. This research proposes a hybrid machine learning model based on the combination of human/knowledge-based domains and computer-generated feature rankings to improve the accuracy of diagnosing sports related concussion (SRC). Using a data set of symptoms collected on the sideline post-SRC events, the symptom selection criteria method has been developed by using Google AutoML's important score function to identify the top 10 symptom features. In addition, symptom domains have been introduced as another parameter, categorizing the symptoms into physical, cognitive, sleep, and emotional domains. The hybrid machine learning model has been trained with a combination of the top 10 symptoms and 4 domains. From the results, the hybrid model was the best performer for symptom resolution time prediction in 2 and 4-week thresholds. This research is a proof of concept study in the use of domains along with machine learning in order to improve concussion prediction accuracy. It is also possible that the use of domains can make the model more efficient due to reduced training time. This research examines the use of a hybrid method in predicting sports-related concussion. This achievement is based on data preprocessing, using a hybrid method to select criteria to achieve high performance.

Keywords: hybrid model, machine learning, sports related concussion, symptom resolution time

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Authors: P. Hooshangitabrizi, I. Contreras, N. Bhuiyan

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This work presents an online scheduling problem which accommodates multiple requests of patients for chemotherapy treatments in a cancer center of a major metropolitan hospital in Canada. To solve the problem, an adaptive flexible approach is proposed which systematically combines two optimization models. The first model is intended to dynamically schedule arriving requests in the form of waiting lists whereas the second model is used to reschedule the already booked patients with the goal of finding better resource allocations when new information becomes available. Both models are created as mixed integer programming formulations. Various controllable and flexible parameters such as deviating the prescribed target dates by a pre-determined threshold, changing the start time of already booked appointments and the maximum number of appointments to move in the schedule are included in the proposed approach to have sufficient degrees of flexibility in handling arrival requests and unexpected changes. Several computational experiments are conducted to evaluate the performance of the proposed approach using historical data provided by the oncology clinic. Our approach achieves outstandingly better results as compared to those of the scheduling system being used in practice. Moreover, several analyses are conducted to evaluate the effect of considering different levels of flexibility on the obtained results and to assess the performance of the proposed approach in dealing with last-minute changes. We strongly believe that the proposed flexible adaptive approach is very well-suited for implementation at the clinic to provide better patient-care services and to utilize available resource more efficiently.

Keywords: chemotherapy scheduling, multi-appointment modeling, optimization of resources, satisfaction of patients, mixed integer programming

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Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

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Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/ unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages AIS messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring Automatic Identification System (AIS) messages. Our RRoT method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measure to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Fr´echet Distance (DFD), Dynamic Time Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an fmeasure of 99.08% using Dynamic Time Warping (DTW) similarity measure.

Keywords: spatial temporal data mining, trajectory mining, trajectory similarity, resource optimization

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Authors: Deyadeen Ali Alshibani

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In the literature, the multi-armed bandit problem as a statistical decision model of an agent trying to optimize his decisions while improving his information at the same time. There are several different algorithms models and their applications on this problem. In this paper, we evaluate the Regret-regression through comparing with Q-learning method. A simulation on determination of optimal treatment regime is presented in detail.

Keywords: optimal, bandit problem, optimization, dynamic programming

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Authors: Hu Zhenxing, Gao Jianxin

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Stereo-based digital image correlation (also referred to as three-dimensional (3D) digital image correlation (DIC)) is a technique for both 3D shape and surface deformation measurement of a component, which has found increasing applications in academia and industries. The accuracy of the reconstructed coordinate depends on many factors such as configuration of the setup, stereo-matching, distortion, etc. Most of these factors have been investigated in literature. For instance, the configuration of a binocular vision system determines the systematic errors. The stereo-matching errors depend on the speckle quality and the matching algorithm, which can only be controlled in a limited range. And the distortion is non-linear particularly in a complex imaging acquisition system. Thus, the distortion correction should be carefully considered. Moreover, the distortion function is difficult to formulate in a complex imaging acquisition system using conventional models in such cases where microscopes and other complex lenses are involved. The errors of the distortion correction will propagate to the reconstructed 3D coordinates. To address the problem, an accurate mapping method based on 2D B-spline functions is proposed in this study. The mapping functions are used to convert the distorted coordinates into an ideal plane without distortions. This approach is suitable for any image acquisition distortion models. It is used as a prior process to convert the distorted coordinate to an ideal position, which enables the camera to conform to the pin-hole model. A procedure of this approach is presented for stereo-based DIC. Using 3D speckle image generation, numerical simulations were carried out to compare the accuracy of both the conventional method and the proposed approach.

Keywords: distortion, stereo-based digital image correlation, b-spline, 3D, 2D

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Authors: Dongjoo Chin

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The purpose of this study was to investigate the effectiveness of an Early Intensive Behavioral Intervention (EIBI) program on infants with autism spectrum disorder (ASD) and to explore the factors predicting the effectiveness of the program, focusing on the infant's age, language ability, problem behaviors, and parental stress. 19 pairs of infants aged between 2 and 5 years who have had been diagnosed with ASD, and their parents participated in an EIBI program at a clinic providing evidence-based treatment based on applied behavior analysis. The measurement tools which were administered before and after the EIBI program and compared, included PEP-R, a curriculum evaluation, K-SIB-R, K-Vineland-II, K-CBCL, and PedsQL for the infants, and included PSI-SF and BDI-II for the parents. Statistical analysis was performed using a sample t-test and multiple regression analysis and the results were as follows. The EIBI program showed significant improvements in overall developmental age, curriculum assessment, and quality of life for infants. There was no difference in parenting stress or depression. Furthermore, measures for both children and parents at the start of the program predicted neither PEP-R nor the degree of improvement in curriculum evaluation measured six months later at the end of the program. Based on these results, the authors suggest future directions for developing an effective intensive early intervention (EIBI) program for infants with ASD in Korea, and discuss the implications and limitations of this study.

Keywords: applied behavior analysis, autism spectrum disorder, early intensive behavioral intervention, parental stress

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Authors: Mohammad Zamani, Ramin Mansouri

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Spillways are one of the most important hydraulic structures of dams that provide the stability of the dam and downstream areas at the time of flood. A circular vertical spillway with various inlet forms is very effective when there is not enough space for the other spillway. Hydraulic flow in a vertical circular spillway is divided into three groups: free, orifice, and under pressure (submerged). In this research, the hydraulic flow characteristics of a Circular Vertical Spillway are investigated with the CFD model. Two-dimensional unsteady RANS equations were solved numerically using Finite Volume Method. The PISO scheme was applied for the velocity-pressure coupling. The mostly used two-equation turbulence models, k-ε and k-ω, were chosen to model Reynolds shear stress term. The power law scheme was used for the discretization of momentum, k, ε, and ω equations. The VOF method (geometrically reconstruction algorithm) was adopted for interface simulation. In this study, three types of computational grids (coarse, intermediate, and fine) were used to discriminate the simulation environment. In order to simulate the flow, the k-ε (Standard, RNG, Realizable) and k-ω (standard and SST) models were used. Also, in order to find the best wall function, two types, standard wall, and non-equilibrium wall function, were investigated. The laminar model did not produce satisfactory flow depth and velocity along the Morning-Glory spillway. The results of the most commonly used two-equation turbulence models (k-ε and k-ω) were identical. Furthermore, the standard wall function produced better results compared to the non-equilibrium wall function. Thus, for other simulations, the standard k-ε with the standard wall function was preferred. The comparison criterion in this study is also the trajectory profile of jet water. The results show that the fine computational grid, the input speed condition for the flow input boundary, and the output pressure for the boundaries that are in contact with the air provide the best possible results. Also, the standard wall function is chosen for the effect of the wall function, and the turbulent model k-ε (Standard) has the most consistent results with experimental results. When the jet gets closer to the end of the basin, the computational results increase with the numerical results of their differences. The mesh with 10602 nodes, turbulent model k-ε standard and the standard wall function, provide the best results for modeling the flow in a vertical circular Spillway. There was a good agreement between numerical and experimental results in the upper and lower nappe profiles. In the study of water level over crest and discharge, in low water levels, the results of numerical modeling are good agreement with the experimental, but with the increasing water level, the difference between the numerical and experimental discharge is more. In the study of the flow coefficient, by decreasing in P/R ratio, the difference between the numerical and experimental result increases.

Keywords: circular vertical, spillway, numerical model, boundary conditions

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Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager

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This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.

Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties

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Authors: Anuruddha Jayasuriya, Thanakorn Pheeraphan

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In this paper, a review of different mathematical models which can be used as prediction tools to assess the time to crack reinforced concrete (RC) due to corrosion is investigated. This investigation leads to an experimental study to validate a selected prediction model. Most of these mathematical models depend upon the mechanical behaviors, chemical behaviors, electrochemical behaviors or geometric aspects of the RC members during a corrosion process. The experimental program is designed to verify the accuracy of a well-selected mathematical model from a rigorous literature study. Fundamentally, the experimental program exemplifies both one-dimensional chloride diffusion using RC squared slab elements of 500 mm by 500 mm and two-dimensional chloride diffusion using RC squared column elements of 225 mm by 225 mm by 500 mm. Each set consists of three water-to-cement ratios (w/c); 0.4, 0.5, 0.6 and two cover depths; 25 mm and 50 mm. 12 mm bars are used for column elements and 16 mm bars are used for slab elements. All the samples are subjected to accelerated chloride corrosion in a chloride bath of 5% (w/w) sodium chloride (NaCl) solution. Based on a pre-screening of different models, it is clear that the well-selected mathematical model had included mechanical properties, chemical and electrochemical properties, nature of corrosion whether it is accelerated or natural, and the amount of porous area that rust products can accommodate before exerting expansive pressure on the surrounding concrete. The experimental results have shown that the selected model for both one-dimensional and two-dimensional chloride diffusion had ±20% and ±10% respective accuracies compared to the experimental output. The half-cell potential readings are also used to see the corrosion probability, and experimental results have shown that the mass loss is proportional to the negative half-cell potential readings that are obtained. Additionally, a statistical analysis is carried out in order to determine the most influential factor that affects the time to corrode the reinforcement in the concrete due to chloride diffusion. The factors considered for this analysis are w/c, bar diameter, and cover depth. The analysis is accomplished by using Minitab statistical software, and it showed that cover depth is the significant effect on the time to crack the concrete from chloride induced corrosion than other factors considered. Thus, the time predictions can be illustrated through the selected mathematical model as it covers a wide range of factors affecting the corrosion process, and it can be used to predetermine the durability concern of RC structures that are vulnerable to chloride exposure. And eventually, it is further concluded that cover thickness plays a vital role in durability in terms of chloride diffusion.

Keywords: accelerated corrosion, chloride diffusion, corrosion cracks, passivation layer, reinforcement corrosion

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Authors: Segen Asayehegn

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Introduction: In Tigray, Ethiopia, next to cervical cancer, breast cancer is one of the most common cancer health problems for women. Objectives: This article is proposed to identify the prospective and potential risk factors affecting the time-to-first-recurrence of breast cancer patients in Tigray, Ethiopia. Methods: The data were taken from the patient’s medical record that registered from January 2010 to January 2020. The study considered a sample size of 1842 breast cancer patients. Powerful non-parametric and parametric shared frailty survival regression models (FSRM) were applied, and model comparisons were performed. Results: Out of 1842 breast cancer patients, about 1290 (70.02%) recovered/cured the disease. The median cure time from breast cancer is found at 12.8 months. The model comparison suggested that the lognormal parametric shared a frailty survival regression model predicted that treatment, stage of breast cancer, smoking habit, and marital status significantly affects the first recurrence of breast cancer. Conclusion: Factors like treatment, stages of cancer, and marital status were improved while smoking habits worsened the time to cure breast cancer. Recommendation: Thus, the authors recommend reducing breast cancer health problems, the regional health sector facilities need to be improved. More importantly, concerned bodies and medical doctors should emphasize the identified factors during treatment. Furthermore, general awareness programs should be given to the community on the identified factors.

Keywords: acceleration factor, breast cancer, Ethiopia, shared frailty survival models, Tigray

Procedia PDF Downloads 118

Authors: Tholokuhle T. Ntshakala, Seraphin D. Eyono Obono

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Nations are still finding it quite difficult to win mega sport competitions despite the major contribution of sport to society in terms of social and economic development, personal health, and in education. Even though the world of sports has been transformed into a huge global economy, it is important to note that the first step of sport is usually its introduction to children at school through physical education or PE. In other words, nations who do not win mega sport competitions also suffer from a weak and neglected PE system. This problem of the neglect of PE systems is the main motivation of this research aimed at examining the factors affecting the perceived awareness of physical education teachers on the ICT's that are adoptable for the teaching and learning of physical education. Two types of research objectives will materialize this aim: relevant theories will be identified in relation to the analysis of the perceived ICT awareness of PE teachers and subsequent models will be compiled and designed from existing literature; the empirical testing of such theories and models will also be achieved through the survey of PE teachers from the Camperdown magisterial district of the KwaZulu-Natal province of South Africa. The main hypothesis at the heart of this study is the relationship between the demographics of PE teachers, their behavior both as individuals and as social entities, and their perceived awareness of the ICTs that are adoptable for PE, as postulated by existing literature; except that this study categorizes human behavior under performance expectancy, computer attitude, and social influence. This hypothesis was partially confirmed by the survey conducted by this research in the sense that performance expectancy and teachers’ age, gender, computer usage, and class size were found to be the only factors affecting their awareness of ICT's for physical education.

Keywords: human behavior, ICT Awareness, physical education, teachers

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Authors: Amal Abo El-Maaty, Amira Mohamed, Nashwa Abu-Aita, Hisham Morgan

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For estimating markers of overweight or obesity of brood mares used for riding and training, 17 mares of different body conditions were subjected to blood sampling and ultrasound examination to measure rump fat thickness and monitor ovulation for six consecutive weeks. Also length (L), heart girth (G) and withers height (H) were measured to estimate body weight (BW), body fat %, body fat mass (BFM) and body mass index (BMI). Mares were classified into three groups according to both body condition score (BCS) and rump back fat (BF). Overweight mares (O) were having BCS > 7 and BF thickness >7mm, moderate body condition (M) mares were having BCS >3and ≤7and BF <3and <7mm, and emaciated mares (E) were having BCS ≤3 and BF ≤3mm. glucose, triglycerides, nitric oxide, ovarian, thyroid, insulin, insulin like growth factor-I (IGF-1), and leptin hormones were measured. Results revealed that BCS, G, L, L*G*H, BW, BF, fat %, BFM were significantly (P<0.0001) decreasing linearly from O to E. T4 concentrations of E were significantly high (P=0.04) compared to M and O but T3 concentrations tended to decrease in E (P>0.05). Insulin and IGF-1 concentrations tended to be high in O (P>0.05) and decrease with the decrease of body condition. M had (P=0.007) the highest leptin, but E mares had the lowest P4 concentrations (P=0.01). Concentrations of glucose and NO decreased with the decrease of BCS and BF but triglycerides of O were insignificantly high. In conclusion, exercise could prevent the development of metabolic syndrome in horses and back fat and morphometric measurements were the easiest and simple assessment of overweight and deviation to obesity.

Keywords: body condition score, insulin, leptin, mares, rump fat

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Authors: Sara Przetocka, Krzysztof Żak, Grzegorz Dubin, Tadeusz Holak

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Toll-like receptors (TLRs) play central role in the innate immune response and inflammation by recognizing pathogen-associated molecular patterns (PAMPs). A fundamental basis of TLR signalling is dependent upon the recruitment and association of adaptor molecules that contain the structurally conserved Toll/interleukin-1 receptor (TIR) domain. MyD88 (myeloid differentiation primary response gene 88) is the universal adaptor for TLRs and cooperates with Mal (MyD88 adapter-like protein, also known as TIRAP) in TLR4 response which is predominantly used in inflammation, host defence and carcinogenesis. Up to date two possible models of MyD88, Mal and TLR4 interactions have been proposed. The aim of our studies is to confirm or abolish presented models and accomplish the full structural characterisation of TIR domains interaction. Using molecular cloning methods we obtained several construct of MyD88 and Mal TIR domain with GST or 6xHis tag. Gel filtration method as well as pull-down analysis confirmed that recombinant TIR domains from MyD88 and Mal are binding in complexes. To examine whether obtained complexes are homo- or heterodimers we carried out cross-linking reaction of TIR domains with BS3 compound combined with mass spectrometry. To investigate which amino acid residues are involved in this interaction the NMR titration experiments were performed. 15N MyD88-TIR solution was complemented with non-labelled Mal-TIR. The results undoubtedly indicate that MyD88-TIR interact with Mal-TIR. Moreover 2D spectra demonstrated that simultaneously Mal-TIR self-dimerization occurs which is necessary to create proper scaffold for Mal-TIR and MyD88-TIR interaction. Final step of this study will be crystallization of MyD88 and Mal TIR domains complex. This crystal structure and characterisation of its interface will have an impact in understanding the TLR signalling pathway and possibly will be used in development of new anti-cancer treatment.

Keywords: cancer, MyD88, TIR domains, Toll-like receptors

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Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

Procedia PDF Downloads 240