Search results for: linear structural relations (LISREL)
7983 Estimation of Optimum Parameters of Non-Linear Muskingum Model of Routing Using Imperialist Competition Algorithm (ICA)
Authors: Davood Rajabi, Mojgan Yazdani
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Non-linear Muskingum model is an efficient method for flood routing, however, the efficiency of this method is influenced by three applied parameters. Therefore, efficiency assessment of Imperialist Competition Algorithm (ICA) to evaluate optimum parameters of non-linear Muskingum model was addressed through this study. In addition to ICA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were also used aiming at an available criterion to verdict ICA. In this regard, ICA was applied for Wilson flood routing; then, routing of two flood events of DoAab Samsami River was investigated. In case of Wilson flood that the target function was considered as the sum of squared deviation (SSQ) of observed and calculated discharges. Routing two other floods, in addition to SSQ, another target function was also considered as the sum of absolute deviations of observed and calculated discharge. For the first floodwater based on SSQ, GA indicated the best performance, however, ICA was on first place, based on SAD. For the second floodwater, based on both target functions, ICA indicated a better operation. According to the obtained results, it can be said that ICA could be used as an appropriate method to evaluate the parameters of Muskingum non-linear model.Keywords: Doab Samsami river, genetic algorithm, imperialist competition algorithm, meta-exploratory algorithms, particle swarm optimization, Wilson flood
Procedia PDF Downloads 5057982 Ontologies for Social Media Digital Evidence
Authors: Edlira Kalemi, Sule Yildirim-Yayilgan
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Online Social Networks (OSNs) are nowadays being used widely and intensively for crime investigation and prevention activities. As they provide a lot of information they are used by the law enforcement and intelligence. An extensive review on existing solutions and models for collecting intelligence from this source of information and making use of it for solving crimes has been presented in this article. The main focus is on smart solutions and models where ontologies have been used as the main approach for representing criminal domain knowledge. A framework for a prototype ontology named SC-Ont will be described. This defines terms of the criminal domain ontology and the relations between them. The terms and the relations are extracted during both this review and the discussions carried out with domain experts. The development of SC-Ont is still ongoing work, where in this paper, we report mainly on the motivation for using smart ontology models and the possible benefits of using them for solving crimes.Keywords: criminal digital evidence, social media, ontologies, reasoning
Procedia PDF Downloads 3907981 Liquid Chromatography Microfluidics for Detection and Quantification of Urine Albumin Using Linear Regression Method
Authors: Patricia B. Cruz, Catrina Jean G. Valenzuela, Analyn N. Yumang
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Nearly a hundred per million of the Filipino population is diagnosed with Chronic Kidney Disease (CKD). The early stage of CKD has no symptoms and can only be discovered once the patient undergoes urinalysis. Over the years, different methods were discovered and used for the quantification of the urinary albumin such as the immunochemical assays where most of these methods require large machinery that has a high cost in maintenance and resources, and a dipstick test which is yet to be proven and is still debated as a reliable method in detecting early stages of microalbuminuria. This research study involves the use of the liquid chromatography concept in microfluidic instruments with biosensor as a means of separation and detection respectively, and linear regression to quantify human urinary albumin. The researchers’ main objective was to create a miniature system that quantifies and detect patients’ urinary albumin while reducing the amount of volume used per five test samples. For this study, 30 urine samples of unknown albumin concentrations were tested using VITROS Analyzer and the microfluidic system for comparison. Based on the data shared by both methods, the actual vs. predicted regression were able to create a positive linear relationship with an R2 of 0.9995 and a linear equation of y = 1.09x + 0.07, indicating that the predicted values and actual values are approximately equal. Furthermore, the microfluidic instrument uses 75% less in total volume – sample and reagents combined, compared to the VITROS Analyzer per five test samples.Keywords: Chronic Kidney Disease, Linear Regression, Microfluidics, Urinary Albumin
Procedia PDF Downloads 1377980 Structural Elucidation of Intact Rough-Type Lipopolysaccharides using Field Asymmetric Ion Mobility Spectrometry and Kendrick Mass Defect Plots
Authors: Abanoub Mikhael, Darryl Hardie, Derek Smith, Helena Petrosova, Robert Ernst, David Goodlett
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Lipopolysaccharide (LPS) is a hallmark virulence factor of Gram-negative bacteria. It is a complex, structurally het- erogeneous mixture due to variations in number, type, and position of its simplest units: fatty acids and monosaccharides. Thus, LPS structural characterization by traditional mass spectrometry (MS) methods is challenging. Here, we describe the benefits of field asymmetric ion mobility spectrometry (FAIMS) for analysis of intact R-type lipopolysaccharide complex mixture (lipooligo- saccharide; LOS). Structural characterization was performed using Escherichia coli J5 (Rc mutant) LOS, a TLR4 agonist widely used in glycoconjugate vaccine research. FAIMS gas phase fractionation improved the (S/N) ratio and number of detected LOS species. Additionally, FAIMS allowed the separation of overlapping isobars facilitating their tandem MS characterization and un- equivocal structural assignments. In addition to FAIMS gas phase fractionation benefits, extra sorting of the structurally related LOS molecules was further accomplished using Kendrick mass defect (KMD) plots. Notably, a custom KMD base unit of [Na-H] created a highly organized KMD plot that allowed identification of interesting and novel structural differences across the different LOS ion families, i.e., ions with different acylation degrees, oligosaccharides composition, and chemical modifications. Defining the composition of a single LOS ion by tandem MS along with the organized KMD plot structural network was sufficient to deduce the composition of 181 LOS species out of 321 species present in the mixture. The combination of FAIMS and KMD plots allowed in-depth characterization of the complex LOS mixture and uncovered a wealth of novel information about its structural variations.Keywords: lipopolysaccharide, ion mobility MS, Kendrick mass defect, Tandem mass spectrometry
Procedia PDF Downloads 747979 Comparison of the Existing Damage Indices in Steel Moment-Resisting Frame Structures
Authors: Hamid Kazemi, Abbasali Sadeghi
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Assessment of seismic behavior of frame structures is just done for evaluating life and financial damages or lost. The new structural seismic behavior assessment methods have been proposed, so it is necessary to define a formulation as a damage index, which the damage amount has been quantified and qualified. In this paper, four new steel moment-resisting frames with intermediate ductility and different height (2, 5, 8, and 12-story) with regular geometry and simple rectangular plan were supposed and designed. The three existing groups’ damage indices were studied, each group consisting of local index (Drift, Maximum Roof Displacement, Banon Failure, Kinematic, Banon Normalized Cumulative Rotation, Cumulative Plastic Rotation and Ductility), global index (Roufaiel and Meyer, Papadopoulos, Sozen, Rosenblueth, Ductility and Base Shear), and story (Banon Failure and Inter-story Rotation). The necessary parameters for these damage indices have been calculated under the effect of far-fault ground motion records by Non-linear Dynamic Time History Analysis. Finally, prioritization of damage indices is defined based on more conservative values in terms of more damageability rate. The results show that the selected damage index has an important effect on estimation of the damage state. Also, failure, drift, and Rosenblueth damage indices are more conservative indices respectively for local, story and global damage indices.Keywords: damage index, far-fault ground motion records, non-linear time history analysis, SeismoStruct software, steel moment-resisting frame
Procedia PDF Downloads 2927978 Comparison of Different Machine Learning Algorithms for Solubility Prediction
Authors: Muhammet Baldan, Emel Timuçin
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Molecular solubility prediction plays a crucial role in various fields, such as drug discovery, environmental science, and material science. In this study, we compare the performance of five machine learning algorithms—linear regression, support vector machines (SVM), random forests, gradient boosting machines (GBM), and neural networks—for predicting molecular solubility using the AqSolDB dataset. The dataset consists of 9981 data points with their corresponding solubility values. MACCS keys (166 bits), RDKit properties (20 properties), and structural properties(3) features are extracted for every smile representation in the dataset. A total of 189 features were used for training and testing for every molecule. Each algorithm is trained on a subset of the dataset and evaluated using metrics accuracy scores. Additionally, computational time for training and testing is recorded to assess the efficiency of each algorithm. Our results demonstrate that random forest model outperformed other algorithms in terms of predictive accuracy, achieving an 0.93 accuracy score. Gradient boosting machines and neural networks also exhibit strong performance, closely followed by support vector machines. Linear regression, while simpler in nature, demonstrates competitive performance but with slightly higher errors compared to ensemble methods. Overall, this study provides valuable insights into the performance of machine learning algorithms for molecular solubility prediction, highlighting the importance of algorithm selection in achieving accurate and efficient predictions in practical applications.Keywords: random forest, machine learning, comparison, feature extraction
Procedia PDF Downloads 427977 Meteosat Second Generation Image Compression Based on the Radon Transform and Linear Predictive Coding: Comparison and Performance
Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane
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Image compression is used to reduce the number of bits required to represent an image. The Meteosat Second Generation satellite (MSG) allows the acquisition of 12 image files every 15 minutes. Which results a large databases sizes. The transform selected in the images compression should contribute to reduce the data representing the images. The Radon transform retrieves the Radon points that represent the sum of the pixels in a given angle for each direction. Linear predictive coding (LPC) with filtering provides a good decorrelation of Radon points using a Predictor constitute by the Symmetric Nearest Neighbor filter (SNN) coefficients, which result losses during decompression. Finally, Run Length Coding (RLC) gives us a high and fixed compression ratio regardless of the input image. In this paper, a novel image compression method based on the Radon transform and linear predictive coding (LPC) for MSG images is proposed. MSG image compression based on the Radon transform and the LPC provides a good compromise between compression and quality of reconstruction. A comparison of our method with other whose two based on DCT and one on DWT bi-orthogonal filtering is evaluated to show the power of the Radon transform in its resistibility against the quantization noise and to evaluate the performance of our method. Evaluation criteria like PSNR and the compression ratio allows showing the efficiency of our method of compression.Keywords: image compression, radon transform, linear predictive coding (LPC), run lengthcoding (RLC), meteosat second generation (MSG)
Procedia PDF Downloads 4227976 Fabrication of Nanoengineered Radiation Shielding Multifunctional Polymeric Sandwich Composites
Authors: Nasim Abuali Galehdari, Venkat Mani, Ajit D. Kelkar
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Space Radiation has become one of the major factors in successful long duration space exploration. Exposure to space radiation not only can affect the health of astronauts but also can disrupt or damage materials and electronics. Hazards to materials include degradation of properties, such as, modulus, strength, or glass transition temperature. Electronics may experience single event effects, gate rupture, burnout of field effect transistors and noise. Presently aluminum is the major component in most of the space structures due to its lightweight and good structural properties. However, aluminum is ineffective at blocking space radiation. Therefore, most of the past research involved studying at polymers which contain large amounts of hydrogen. Again, these materials are not structural materials and would require large amounts of material to achieve the structural properties needed. One of the materials to alleviate this problem is polymeric composite materials, which has good structural properties and use polymers that contained large amounts of hydrogen. This paper presents steps involved in fabrication of multi-functional hybrid sandwich panels that can provide beneficial radiation shielding as well as structural strength. Multifunctional hybrid sandwich panels were manufactured using vacuum assisted resin transfer molding process and were subjected to radiation treatment. Study indicates that various nanoparticles including Boron Nano powder, Boron Carbide and Gadolinium nanoparticles can be successfully used to block the space radiation without sacrificing the structural integrity.Keywords: multi-functional, polymer composites, radiation shielding, sandwich composites
Procedia PDF Downloads 2867975 Improving Fire Resistance of Wood and Wood-Based Composites and Fire Testing Systems
Authors: Nadir Ayrilmis
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Wood and wood-based panels are one of the oldest structural materials used in the construction industry due to their significant advantages such as good mechanical properties, low density, renewable material, low-cost, recycling, etc. However, they burn when exposed to a flame source or high temperatures. This is very important when the wood products are used as structural or hemi-structural materials in the construction industry, furniture industry, so on. For this reason, the fire resistance is demanded property for wood products. They can be impregnated with fire retardants to improve their fire resistance. The most used fire retardants, fire-retardant mechanism, and fire-testing systems, and national and international fire-durability classifications and standard requirements for fire-durability of wood and wood-based panels were given in this study.Keywords: fire resistance, wood-based panels, cone calorimeter, wood
Procedia PDF Downloads 1667974 Deep Learning-Based Automated Structure Deterioration Detection for Building Structures: A Technological Advancement for Ensuring Structural Integrity
Authors: Kavita Bodke
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Structural health monitoring (SHM) is experiencing growth, necessitating the development of distinct methodologies to address its expanding scope effectively. In this study, we developed automatic structure damage identification, which incorporates three unique types of a building’s structural integrity. The first pertains to the presence of fractures within the structure, the second relates to the issue of dampness within the structure, and the third involves corrosion inside the structure. This study employs image classification techniques to discern between intact and impaired structures within structural data. The aim of this research is to find automatic damage detection with the probability of each damage class being present in one image. Based on this probability, we know which class has a higher probability or is more affected than the other classes. Utilizing photographs captured by a mobile camera serves as the input for an image classification system. Image classification was employed in our study to perform multi-class and multi-label classification. The objective was to categorize structural data based on the presence of cracks, moisture, and corrosion. In the context of multi-class image classification, our study employed three distinct methodologies: Random Forest, Multilayer Perceptron, and CNN. For the task of multi-label image classification, the models employed were Rasnet, Xceptionet, and Inception.Keywords: SHM, CNN, deep learning, multi-class classification, multi-label classification
Procedia PDF Downloads 397973 Experimental and Numerical Analysis of Mustafa Paşa Mosque in Skopje
Authors: Ozden Saygili, Eser Cakti
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The masonry building stock in Istanbul and in other cities of Turkey are exposed to significant earthquake hazard. Determination of the safety of masonry structures against earthquakes is a complex challenge. This study deals with experimental tests and non-linear dynamic analysis of masonry structures modeled through discrete element method. The 1:10 scale model of Mustafa Paşa Mosque was constructed and the data were obtained from the sensors on it during its testing on the shake table. The results were used in the calibration/validation of the numerical model created on the basis of the 1:10 scale model built for shake table testing. 3D distinct element model was developed that represents the linear and nonlinear behavior of the shake table model as closely as possible during experimental tests. Results of numerical analyses with those from the experimental program were compared and discussed.Keywords: dynamic analysis, non-linear modeling, shake table tests, masonry
Procedia PDF Downloads 4277972 Generating a Functional Grammar for Architectural Design from Structural Hierarchy in Combination of Square and Equal Triangle
Authors: Sanaz Ahmadzadeh Siyahrood, Arghavan Ebrahimi, Mohammadjavad Mahdavinejad
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Islamic culture was accountable for a plethora of development in astronomy and science in the medieval term, and in geometry likewise. Geometric patterns are reputable in a considerable number of cultures, but in the Islamic culture the patterns have specific features that connect the Islamic faith to mathematics. In Islamic art, three fundamental shapes are generated from the circle shape: triangle, square and hexagon. Originating from their quiddity, each of these geometric shapes has its own specific structure. Even though the geometric patterns were generated from such simple forms as the circle and the square, they can be combined, duplicated, interlaced, and arranged in intricate combinations. So in order to explain geometrical interaction principles between square and equal triangle, in the first definition step, all types of their linear forces individually and in the second step, between them, would be illustrated. In this analysis, some angles will be created from intersection of their directions. All angles are categorized to some groups and the mathematical expressions among them are analyzed. Since the most geometric patterns in Islamic art and architecture are based on the repetition of a single motif, the evaluation results which are obtained from a small portion, is attributable to a large-scale domain while the development of infinitely repeating patterns can represent the unchanging laws. Geometric ornamentation in Islamic art offers the possibility of infinite growth and can accommodate the incorporation of other types of architectural layout as well, so the logic and mathematical relationships which have been obtained from this analysis are applicable in designing some architecture layers and developing the plan design.Keywords: angle, equal triangle, square, structural hierarchy
Procedia PDF Downloads 1967971 Gendered Perspectives on the Understanding of the Politics and the Social Life
Authors: Canan Cetin
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This essay analyses how gendered shaped views influence on our understanding of global politics. To do so, feminism used as a framework theory, thus masculinity is discussed in order to explain the male-dominated international relations (IR) discipline and the differences of reflections on our perspective considering the politics in a broader perspective. Particularly, it is highlighted that the social and cultural structures of societies have also an impact on our views about international relations and politics. From a different perspective, it is aimed that the sociological and cultural impression of the shifted gender perspectives on the political approach of different nations and societies will be examined by drawing on a range of sources. Instead of supporting one feminist theory, this essay engages with all traditions and enriches their arguments. Specifically, the main objective of the essay is hegemonic and plural masculinity on societies. The essay sets things up theoretically by looking at the nature of masculinity – the stage is set to show how this informs our understanding of IR.Keywords: feminism, politics, international affairs, social life
Procedia PDF Downloads 2067970 Preparation and Characterization of Nanometric Ni-Zn Ferrite via Different Methods
Authors: Ebtesam. E. Ateia, L. M. Salah, A. H. El-Bassuony
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The aim of the presented study was the possibility of developing a nanosized material with enhanced structural properties that was suitable for many applications. Nanostructure ferrite of composition Ni0.5 Zn0.5 Cr0.1 Fe1.9 O4 were prepared by sol–gel, co-precipitation, citrate-gel, flash and oxalate precursor methods. The Structural and micro structural analysis of the investigated samples were carried out. It was observed that the lattice parameter of cubic spinel was constant, and the positions of both tetrahedral and the octahedral bands had a fixed position. The values of the lattice parameter had a significant role in determining the stoichiometric cation distribution of the composition.The average crystalline sizes of the investigated samples were from 16.4 to 69 nm. Discussion was made on the basis of a comparison of average crystallite size of the investigated samples, indicating that the co-precipitation method was the the effective one in producing small crystallite sized samples.Keywords: chemical preparation, ferrite, grain size, nanocomposites, sol-gel
Procedia PDF Downloads 3417969 On Algebraic Structure of Improved Gauss-Seide Iteration
Authors: O. M. Bamigbola, A. A. Ibrahim
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Analysis of real life problems often results in linear systems of equations for which solutions are sought. The method to employ depends, to some extent, on the properties of the coefficient matrix. It is not always feasible to solve linear systems of equations by direct methods, as such the need to use an iterative method becomes imperative. Before an iterative method can be employed to solve a linear system of equations there must be a guaranty that the process of solution will converge. This guaranty, which must be determined a priori, involve the use of some criterion expressible in terms of the entries of the coefficient matrix. It is, therefore, logical that the convergence criterion should depend implicitly on the algebraic structure of such a method. However, in deference to this view is the practice of conducting convergence analysis for Gauss-Seidel iteration on a criterion formulated based on the algebraic structure of Jacobi iteration. To remedy this anomaly, the Gauss-Seidel iteration was studied for its algebraic structure and contrary to the usual assumption, it was discovered that some property of the iteration matrix of Gauss-Seidel method is only diagonally dominant in its first row while the other rows do not satisfy diagonal dominance. With the aid of this structure we herein fashion out an improved version of Gauss-Seidel iteration with the prospect of enhancing convergence and robustness of the method. A numerical section is included to demonstrate the validity of the theoretical results obtained for the improved Gauss-Seidel method.Keywords: linear algebraic system, Gauss-Seidel iteration, algebraic structure, convergence
Procedia PDF Downloads 4657968 Optimal Production Planning in Aromatic Coconuts Supply Chain Based on Mixed-Integer Linear Programming
Authors: Chaimongkol Limpianchob
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This work addresses the problem of production planning that arises in the production of aromatic coconuts from Samudsakhorn province in Thailand. The planning involves the forwarding of aromatic coconuts from the harvest areas to the factory, which is classified into two groups; self-owned areas and contracted areas, the decisions of aromatic coconuts flow in the plant, and addressing a question of which warehouse will be in use. The problem is formulated as a mixed-integer linear programming model within supply chain management framework. The objective function seeks to minimize the total cost including the harvesting, labor and inventory costs. Constraints on the system include the production activities in the company and demand requirements. Numerical results are presented to demonstrate the feasibility of coconuts supply chain model compared with base case.Keywords: aromatic coconut, supply chain management, production planning, mixed-integer linear programming
Procedia PDF Downloads 4607967 Structural Performance Evaluation of Segmented Wind Turbine Blade Through Finite Element Simulation
Authors: Chandrashekhar Bhat, Dilifa Jossley Noronha, Faber A. Saldana
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Transportation of long turbine blades from one place to another is a difficult process. Hence a feasibility study of modularization of wind turbine blade was taken from structural standpoint through finite element analysis. Initially, a non-segmented blade is modeled and its structural behavior is evaluated to serve as reference. The resonant, static bending and fatigue tests are simulated in accordance with IEC61400-23 standard for comparison purpose. The non-segmented test blade is separated at suitable location based on trade off studies and the segments are joined with an innovative double strap bonded joint configuration. The adhesive joint is modeled by adopting cohesive zone modeling approach in ANSYS. The developed blade model is analyzed for its structural response through simulation. Performances of both the blades are found to be similar, which indicates that, efficient segmentation of the long blade is possible which facilitates easy transportation of the blades and on site reassembling. The location selected for segmentation and adopted joint configuration has resulted in an efficient segmented blade model which proves the methodology adopted for segmentation was quite effective. The developed segmented blade appears to be the viable alternative considering its structural response specifically in fatigue within considered assumptions.Keywords: modularization, fatigue, cohesive zone modeling, wind turbine blade
Procedia PDF Downloads 4507966 Development and Validation of an Electronic Module in Linear Motion for First Year College Students of Iloilo City
Authors: Donna H. Gabor
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This study aimed to develop and validate an electronic module in physics for first-year college students of Iloilo and find out if there would be a significant difference in the performance of students before and after using the electronic module. The e-module was composed of one topic with two sub-lessons in linear motion (kinematics). The participants of the study were classified into three groups: the subject matter experts who are physics instructors who suggested the content, physical appearance, and limitations of the e-module; the IT experts who are active both in teaching and developing computer programs; and 28 students divided into two groups, 15 in the pilot group and 13 in the final test group. A researcher created 30 items checklist form (difficulty of a sample problem, comprehension, application, and definition of terms) was prepared and validated by the experts in subject matter for gathering data. To test the difference in student performance in physics, the researcher prepared an achievement test containing 25 items, multiple choices. The findings revealed that there was an increase in the performance of students in the pretest and post-test. T-test results revealed that there was a significant difference in the test scores of the students before and after using the module which can be used as a future reference for linear motion as an additional teaching tool in physics.Keywords: electronic module, kinematics, linear motion, physics
Procedia PDF Downloads 1357965 Effect of Whey Proteins and Caffeic Acid Interactions on Antioxidant Activity and Protein Structure
Authors: Tassia Batista Pessato, Francielli Pires Ribeiro Morais, Fernanda Guimaraes Drummond Silva, Flavia Maria Netto
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Proteins and phenolic compounds can interact mainly by hydrophobic interactions. Those interactions may lead to structural changes in both molecules, which in turn could affect positively or negatively their functional and nutritional properties. Here, the structural changes of whey proteins (WPI) due to interaction with caffeic acid (CA) were investigated by intrinsic and extrinsic fluorescence. The effects of protein-phenolic compounds interactions on the total phenolic content and antioxidant activity were also assessed. The WPI-CA complexes were obtained by mixture of WPI and CA stock solutions in deionized water. The complexation was carried out at room temperature during 60 min, using 0.1 M NaOH to adjust pH at 7.0. The WPI concentration was fixed at 5 mg/mL, whereas the CA concentration varied in order to obtain four different WPI:CA molar relations (1:1; 2:1; 5:1; 10:1). WPI and phenolic solutions were used as controls. Intrinsic fluorescence spectra of the complexes (mainly due to Trp fluorescence emission) were obtained at λex = 280 nm and the emission intensities were measured from 290 to 500 nm. Extrinsic fluorescence was obtained as the measure of protein surface hydrophobicity (S0) using ANS as a fluorescence probe. Total phenolic content was determined by Folin-Ciocalteau and the antioxidant activity by FRAP and ORAC methods. Increasing concentrations of CA resulted in decreasing of WPI intrinsic fluorescence. The emission band of WPI red shifted from 332 to 354 nm as the phenolic concentration increased, which is related to the exposure of Trp residue to the more hydrophilic environment and unfolding of protein structure. In general, the complexes presented lower S0 values than WPI, suggesting that CA hindered ANS binding to hydrophobic sites of WPI. The total phenolic content in the complexes was lower than the sum of two compounds isolated. WPI showed negligible AA measured by FRAP. However, as the relative concentration of CA increased in the complexes, the FRAP values enhanced, indicating that AA measure by this technique comes mainly from CA. In contrast, the WPI ORAC value (82.3 ± 1.5 µM TE/g) suggest that its AA is related to the capacity of H+ transfer. The complexes exhibited no important improvement of AA measured by ORAC in relation to the isolated components, suggesting complexation partially suppressed AA of the compounds. The results hereby presented indicate that interaction of WPI and CA occurred, and this interaction caused a structural change in the proteins. The complexation can either hide or expose antioxidant sites of both components. In conclusion, although the CA can undergo an AA suppression due to the interaction with proteins, the AA of WPI could be enhanced due to protein unfolding and exposure of antioxidant sites.Keywords: bioactive properties, milk proteins, phenolic acids, protein-phenolic compounds complexation
Procedia PDF Downloads 5507964 Fault-Tolerant Predictive Control for Polytopic LPV Systems Subject to Sensor Faults
Authors: Sofiane Bououden, Ilyes Boulkaibet
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In this paper, a robust fault-tolerant predictive control (FTPC) strategy is proposed for systems with linear parameter varying (LPV) models and input constraints subject to sensor faults. Generally, virtual observers are used for improving the observation precision and reduce the impacts of sensor faults and uncertainties in the system. However, this type of observer lacks certain system measurements which substantially reduce its accuracy. To deal with this issue, a real observer is then designed based on the virtual observer, and consequently a real observer-based robust predictive control is designed for polytopic LPV systems. Moreover, the proposed observer can entirely assure that all system states and sensor faults are estimated. As a result, and based on both observers, a robust fault-tolerant predictive control is then established via the Lyapunov method where sufficient conditions are proposed, for stability analysis and control purposes, in linear matrix inequalities (LMIs) form. Finally, simulation results are given to show the effectiveness of the proposed approach.Keywords: linear parameter varying systems, fault-tolerant predictive control, observer-based control, sensor faults, input constraints, linear matrix inequalities
Procedia PDF Downloads 2007963 Forecasting the Influences of Information and Communication Technology on the Structural Changes of Japanese Industrial Sectors: A Study Using Statistical Analysis
Authors: Ubaidillah Zuhdi, Shunsuke Mori, Kazuhisa Kamegai
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The purpose of this study is to forecast the influences of Information and Communication Technology (ICT) on the structural changes of Japanese economies based on Leontief Input-Output (IO) coefficients. This study establishes a statistical analysis to predict the future interrelationships among industries. We employ the Constrained Multivariate Regression (CMR) model to analyze the historical changes of input-output coefficients. Statistical significance of the model is then tested by Likelihood Ratio Test (LRT). In our model, ICT is represented by two explanatory variables, i.e. computers (including main parts and accessories) and telecommunications equipment. A previous study, which analyzed the influences of these variables on the structural changes of Japanese industrial sectors from 1985-2005, concluded that these variables had significant influences on the changes in the business circumstances of Japanese commerce, business services and office supplies, and personal services sectors. The projected future Japanese economic structure based on the above forecast generates the differentiated direct and indirect outcomes of ICT penetration.Keywords: forecast, ICT, industrial structural changes, statistical analysis
Procedia PDF Downloads 3757962 Three-Dimensional Numerical Investigation for Reinforced Concrete Slabs with Opening
Authors: Abdelrahman Elsehsah, Hany Madkour, Khalid Farah
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This article presents a 3-D modified non-linear elastic model in the strain space. The Helmholtz free energy function is introduced with the existence of a dissipation potential surface in the space of thermodynamic conjugate forces. The constitutive equation and the damage evolution were derived as well. The modified damage has been examined to model the nonlinear behavior of reinforced concrete (RC) slabs with an opening. A parametric study with RC was carried out to investigate the impact of different factors on the behavior of RC slabs. These factors are the opening area, the opening shape, the place of opening, and the thickness of the slabs. And the numerical results have been compared with the experimental data from literature. Finally, the model showed its ability to be applied to the structural analysis of RC slabs.Keywords: damage mechanics, 3-D numerical analysis, RC, slab with opening
Procedia PDF Downloads 1767961 Validation of Escherichia coli O157:H7 Inactivation on Apple-Carrot Juice Treated with Manothermosonication by Kinetic Models
Authors: Ozan Kahraman, Hao Feng
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Several models such as Weibull, Modified Gompertz, Biphasic linear, and Log-logistic models have been proposed in order to describe non-linear inactivation kinetics and used to fit non-linear inactivation data of several microorganisms for inactivation by heat, high pressure processing or pulsed electric field. First-order kinetic parameters (D-values and z-values) have often been used in order to identify microbial inactivation by non-thermal processing methods such as ultrasound. Most ultrasonic inactivation studies employed first-order kinetic parameters (D-values and z-values) in order to describe the reduction on microbial survival count. This study was conducted to analyze the E. coli O157:H7 inactivation data by using five microbial survival models (First-order, Weibull, Modified Gompertz, Biphasic linear and Log-logistic). First-order, Weibull, Modified Gompertz, Biphasic linear and Log-logistic kinetic models were used for fitting inactivation curves of Escherichia coli O157:H7. The residual sum of squares and the total sum of squares criteria were used to evaluate the models. The statistical indices of the kinetic models were used to fit inactivation data for E. coli O157:H7 by MTS at three temperatures (40, 50, and 60 0C) and three pressures (100, 200, and 300 kPa). Based on the statistical indices and visual observations, the Weibull and Biphasic models were best fitting of the data for MTS treatment as shown by high R2 values. The non-linear kinetic models, including the Modified Gompertz, First-order, and Log-logistic models did not provide any better fit to data from MTS compared the Weibull and Biphasic models. It was observed that the data found in this study did not follow the first-order kinetics. It is possibly because of the cells which are sensitive to ultrasound treatment were inactivated first, resulting in a fast inactivation period, while those resistant to ultrasound were killed slowly. The Weibull and biphasic models were found as more flexible in order to determine the survival curves of E. coli O157:H7 treated by MTS on apple-carrot juice.Keywords: Weibull, Biphasic, MTS, kinetic models, E.coli O157:H7
Procedia PDF Downloads 3667960 An Analytical Study on Rotational Capacity of Beam-Column Joints in Unit Modular Frames
Authors: Kyung-Suk Choi, Hyung-Joon Kim
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Modular structural systems are constructed using a method that they are assembled with prefabricated unit modular frames on-site. This provides a benefit that can significantly reduce building construction time. Their structural design is usually carried out under the assumption that the load-carrying mechanism is similar to that of a traditional steel moment-resisting system. However, both systems are different in terms of beam-column connection details which may strongly influence the lateral structural behavior. Specially, the presence of access holes in a beam-column joint of a unit modular frame could cause undesirable failure during strong earthquakes. Therefore, this study carried out finite element analyses (FEM) of unit modular frames to investigate the cyclic behavior of beam-column joints with the structural influence of access holes. Analysis results show that the unit modular frames present stable cyclic response with large deformation capacities, and their joints are classified into semi-rigid connections.Keywords: unit modular frame, steel moment connection, nonlinear analytical model, moment-rotation relation
Procedia PDF Downloads 6207959 Influence of Deficient Materials on the Reliability of Reinforced Concrete Members
Authors: Sami W. Tabsh
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The strength of reinforced concrete depends on the member dimensions and material properties. The properties of concrete and steel materials are not constant but random variables. The variability of concrete strength is due to batching errors, variations in mixing, cement quality uncertainties, differences in the degree of compaction and disparity in curing. Similarly, the variability of steel strength is attributed to the manufacturing process, rolling conditions, characteristics of base material, uncertainties in chemical composition, and the microstructure-property relationships. To account for such uncertainties, codes of practice for reinforced concrete design impose resistance factors to ensure structural reliability over the useful life of the structure. In this investigation, the effects of reductions in concrete and reinforcing steel strengths from the nominal values, beyond those accounted for in the structural design codes, on the structural reliability are assessed. The considered limit states are flexure, shear and axial compression based on the ACI 318-11 structural concrete building code. Structural safety is measured in terms of a reliability index. Probabilistic resistance and load models are compiled from the available literature. The study showed that there is a wide variation in the reliability index for reinforced concrete members designed for flexure, shear or axial compression, especially when the live-to-dead load ratio is low. Furthermore, variations in concrete strength have minor effect on the reliability of beams in flexure, moderate effect on the reliability of beams in shear, and sever effect on the reliability of columns in axial compression. On the other hand, changes in steel yield strength have great effect on the reliability of beams in flexure, moderate effect on the reliability of beams in shear, and mild effect on the reliability of columns in axial compression. Based on the outcome, it can be concluded that the reliability of beams is sensitive to changes in the yield strength of the steel reinforcement, whereas the reliability of columns is sensitive to variations in the concrete strength. Since the embedded target reliability in structural design codes results in lower structural safety in beams than in columns, large reductions in material strengths compromise the structural safety of beams much more than they affect columns.Keywords: code, flexure, limit states, random variables, reinforced concrete, reliability, reliability index, shear, structural safety
Procedia PDF Downloads 4307958 Material Characterization and Numerical Simulation of a Rubber Bumper
Authors: Tamás Mankovits, Dávid Huri, Imre Kállai, Imre Kocsis, Tamás Szabó
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Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. Rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. In this paper, a comprehensive investigation is introduced including laboratory measurements, mesh density analysis and complex finite element simulations to obtain the load-displacement curve of the chosen rubber bumper. Contact and friction effects are also taken into consideration. The aim of this research is to elaborate an FEM model which is accurate and competitive for a future shape optimization task.Keywords: rubber bumper, finite element analysis, compression test, Mooney-Rivlin material model
Procedia PDF Downloads 5097957 Steady State Creep Behavior of Functionally Graded Thick Cylinder
Authors: Tejeet Singh, Harmanjit Singh
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Creep behavior of thick-walled functionally graded cylinder consisting of AlSiC and subjected to internal pressure and high temperature has been analyzed. The functional relationship between strain rate with stress can be described by the well-known threshold stress based creep law with a stress exponent of five. The effect of imposing non-linear particle gradient on the distribution of creep stresses in the thick-walled functionally graded composite cylinder has been investigated. The study revealed that for the assumed non-linear particle distribution, the radial stress decreases throughout the cylinder, whereas the tangential, axial and effective stresses have averaging effect. The strain rates in the functionally graded composite cylinder could be reduced to significant extent by employing non-linear gradient in the distribution of reinforcement.Keywords: functionally graded material, pressure, steady state creep, thick-cylinder
Procedia PDF Downloads 4777956 Spatial Time Series Models for Rice and Cassava Yields Based on Bayesian Linear Mixed Models
Authors: Panudet Saengseedam, Nanthachai Kantanantha
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This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.Keywords: Bayesian method, linear mixed model, multivariate conditional autoregressive model, spatial time series
Procedia PDF Downloads 3977955 The Collapse of a Crane on Site: A Case Study
Authors: T. Teruzzi, S. Antonietti, C. Mosca, C. Paglia
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This paper discusses the causes of the structural failure in a tower crane. The structural collapse occurred at the upper joints of the extension element used to increase the height of the crane. The extension element consists of a steel lattice structure made with angular profiles and plates joined to the tower element by arc welding. Macroscopic inspection of the sections showed that the break was always observed on the angular profiles at the weld bead edge. The case study shows how, using mechanical characterization, chemical analysis of the steel and macroscopic and microscopic metallographic examinations, it was possible to obtain significant evidence that identified the mechanism causing the breakage. The analyses identified the causes of the structural failure as the use of materials that were not suitable for welding and poor performance in the welding joints.Keywords: failure, metals, weld, microstructure
Procedia PDF Downloads 1267954 An Inverse Optimal Control Approach for the Nonlinear System Design Using ANN
Authors: M. P. Nanda Kumar, K. Dheeraj
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The design of a feedback controller, so as to minimize a given performance criterion, for a general non-linear dynamical system is difficult; if not impossible. But for a large class of non-linear dynamical systems, the open loop control that minimizes a performance criterion can be obtained using calculus of variations and Pontryagin’s minimum principle. In this paper, the open loop optimal trajectories, that minimizes a given performance measure, is used to train the neural network whose inputs are state variables of non-linear dynamical systems and the open loop optimal control as the desired output. This trained neural network is used as the feedback controller. In other words, attempts are made here to solve the “inverse optimal control problem” by using the state and control trajectories that are optimal in an open loop sense.Keywords: inverse optimal control, radial basis function, neural network, controller design
Procedia PDF Downloads 554