Search results for: analytical validation

Authors: Tengqin Han

Abstract:

Delinquency has been a crucial factor in economics throughout the years. Commonly seen in credit card and mortgage, it played one of the crucial roles in causing the most recent financial crisis in 2008. In each case, a delinquency is a sign of the loaner being unable to pay off the debt, and thus may cause a lost of property in the end. Individually, one case of delinquency seems unimportant compared to the entire credit system. China, as an emerging economic entity, the national strength and economic strength has grown rapidly, and the gross domestic product (GDP) growth rate has remained as high as 8% in the past decades. However, potential risks exist behind the appearance of prosperity. Among the risks, the credit system is the most significant one. Due to long term and a large amount of balance of the mortgage, it is critical to monitor the risk during the performance period. In this project, about 300,000 mortgage account data are analyzed in order to develop a predictive model to predict the probability of delinquency. Through univariate analysis, the data is cleaned up, and through bivariate analysis, the variables with strong predictive power are detected. The project is divided into two parts. In the first part, the analysis data of 2005 are split into 2 parts, 60% for model development, and 40% for in-time model validation. The KS of model development is 31, and the KS for in-time validation is 31, indicating the model is stable. In addition, the model is further validation by out-of-time validation, which uses 40% of 2006 data, and KS is 33. This indicates the model is still stable and robust. In the second part, the model is improved by the addition of macroeconomic economic indexes, including GDP, consumer price index, unemployment rate, inflation rate, etc. The data of 2005 to 2010 is used for model development and validation. Compared with the base model (without microeconomic variables), KS is increased from 41 to 44, indicating that the macroeconomic variables can be used to improve the separation power of the model, and make the prediction more accurate.

Keywords: delinquency, mortgage, model development, model validation

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Authors: Wheyming Tina Song, Chi-Hao Hong, Peisyuan Lin

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An important performance measure for stochastic manufacturing networks is the system reliability, defined as the probability that the production output meets or exceeds a specified demand. The system parameters include the capacity of each workstation and numbers of the conforming parts produced in each workstation. We establish that eighteen archival publications, containing twenty-one examples, provide incorrect values of the system reliability. The author recently published the Song Rule, which provides the correct analytical system-reliability value; it is, however, computationally inefficient for large networks. In this paper, we use Monte Carlo simulation (implemented in C and Flexsim) to provide estimates for the above-mentioned twenty-one examples. The simulation estimates are consistent with the analytical solution for small networks but is computationally efficient for large networks. We argue here for three advantages of Monte Carlo simulation: (1) understanding stochastic systems, (2) validating analytical results, and (3) providing estimates even when analytical and numerical approaches are overly expensive in computation. Monte Carlo simulation could have detected the published analysis errors.

Keywords: Monte Carlo simulation, analytical results, leading digit rule, standard error

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Authors: Z. N. Haji, S. O. Oyadiji, H. Samami, O. Farrell

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The prediction of the vibration response of rubber products by analytical or numerical method depends mainly on the predefined intrinsic material properties such as Young’s modulus, damping factor and Poisson’s ratio. Such intrinsic properties are determined experimentally by subjecting a bonded rubber sample to compression tests. The compression tests on such a sample yield an apparent Young’s modulus which is greater in magnitude than the intrinsic Young’s modulus of the rubber. As a result, many analytical equations have been developed to determine Young’s modulus from an apparent Young’s modulus of bonded rubber materials. In this work, the applicability of some of these analytical equations is assessed via experimental testing. The assessment is based on testing of vulcanized nitrile butadiene rubber (NBR70) samples using tensile test and compression test methods. The analytical equations are used to determine the intrinsic Young’s modulus from the apparent modulus that is derived from the compression test data of the bonded rubber samples. Then, these Young’s moduli are compared with the actual Young’s modulus that is derived from the tensile test data. The results show significant discrepancy between the Young’s modulus derived using the analytical equations and the actual Young’s modulus.

Keywords: bonded rubber, quasi-static test, shape factor, apparent Young’s modulus

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Authors: Taghreed A. Ibrahim, Atef A. El-Hela, Hala M. El-Hefnawy

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The chromatographic profile of methanol extract of Hypericum sinaicum was determined using HPLC-DAD. Apigenin was used as an external standard in the development and validation of the HPLC method. The proposed method is simple, rapid and reliable and can be successfully applied for standardization of Hypericum sinaicum methanol extract.

Keywords: quality control, standardization, falvonoids, methanol extract

Procedia PDF Downloads 473

Authors: Pegah Eshraghi, Zahra Sadat Zomorodian, Mohammad Tahsildoost

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Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

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Authors: Ghazal Faraj, András Micsik

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Shapes Constraint Language (SHACL), a World Wide Web Consortium (W3C) language, provides well-defined shapes and RDF graphs, named "shape graphs". These shape graphs validate other resource description framework (RDF) graphs which are called "data graphs". The structural features of SHACL permit generating a variety of conditions to evaluate string matching patterns, value type, and other constraints. Moreover, the framework of SHACL supports high-level validation by expressing more complex conditions in languages such as SPARQL protocol and RDF Query Language (SPARQL). SHACL includes two parts: SHACL Core and SHACL-SPARQL. SHACL Core includes all shapes that cover the most frequent constraint components. While SHACL-SPARQL is an extension that allows SHACL to express more complex customized constraints. Validating the efficacy of dataset mapping is an essential component of reconciled data mechanisms, as the enhancement of different datasets linking is a sustainable process. The conventional validation methods are the semantic reasoner and SPARQL queries. The former checks formalization errors and data type inconsistency, while the latter validates the data contradiction. After executing SPARQL queries, the retrieved information needs to be checked manually by an expert. However, this methodology is time-consuming and inaccurate as it does not test the mapping model comprehensively. Therefore, there is a serious need to expose a new methodology that covers the entire validation aspects for linking and mapping diverse datasets. Our goal is to conduct a new approach to achieve optimal validation outcomes. The first step towards this goal is implementing SHACL to validate the mapping between the International Committee for Documentation (CIDOC) conceptual reference model (CRM) and one of its ontologies. To initiate this project successfully, a thorough understanding of both source and target ontologies was required. Subsequently, the proper environment to run SHACL and its shape graphs were determined. As a case study, we performed SHACL over a CIDOC-CRM dataset after running a Pellet reasoner via the Protégé program. The applied validation falls under multiple categories: a) data type validation which constrains whether the source data is mapped to the correct data type. For instance, checking whether a birthdate is assigned to xsd:datetime and linked to Person entity via crm:P82a_begin_of_the_begin property. b) Data integrity validation which detects inconsistent data. For instance, inspecting whether a person's birthdate occurred before any of the linked event creation dates. The expected results of our work are: 1) highlighting validation techniques and categories, 2) selecting the most suitable techniques for those various categories of validation tasks. The next plan is to establish a comprehensive validation model and generate SHACL shapes automatically.

Keywords: SHACL, CIDOC-CRM, SPARQL, validation of ontology mapping

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Authors: Wendy Flory, Kazi Czarnecki, Matthijs Mercy, Mark Joswiak, Mary Beth Seasholtz

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Polyurethane Materials are present in a wide range of industrial segments such as Furniture, Building and Construction, Composites, Automotive, Electronics, and more. Dow is one of the leaders for the manufacture of the two main raw materials, Isocyanates and Polyols used to produce polyurethane products. Dow is also a key player for the manufacture of Polyurethane Systems/Formulations designed for targeted applications. In 1990, the first analytical chemometric models were developed and deployed for use in the Dow QC labs of the polyols business for the quantification of OH, water, cloud point, and viscosity. Over the years many models have been added; there are now over 140 models for quantification and hundreds for product identification, too many to be reasonable for support. There are 29 global models alone for the quantification of OH across > 70 products at many sites. An attempt was made to consolidate these into a single model. While the consolidated model proved good statistics across the entire range of OH, several products had a bias by ASTM E1655 with individual product validation. This project summary will show the strategy for global model updates for OH, to reduce the number of models for quantification from over 140 to 5 or less using chemometric methods. In order to gain an understanding of the best product groupings, we identify clusters by reducing spectra to a few dimensions via Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP). Results from these cluster analyses and a separate validation set allowed dow to reduce the number of models for predicting OH from 29 to 3 without loss of accuracy.

Keywords: hydroxyl, global model, model maintenance, near infrared, polyol

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Authors: Rama Devi Kyatham, D. Ashok, K. S. K. Rao Patnaik, Raju Bathula

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We have shown the importance of pyrazoles as anti-microbial chemical entities. These compounds have generally been considered significant due to their wide range of pharmacological acivities and their discovery motivates new avenues of research.The proposed pyrazoles were synthesized and evaluated for their anti-microbial activities. The Synthesized compounds were analyzed by different spectroscopic methods.

Keywords: pyrazoles, validation, resistant microbial strains, anti-microbial activities

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Authors: Ahmed Aboforn

Abstract:

Butene-1 product is consider effectively raw material in Polyethylene production, however Oxygenates impurities existing will be effected ethylene/butene-1 copolymers synthesized through titanium-magnesium-supported Ziegler-Natta catalysts. Laterally, Petrochemical industries are challenge against poor quality of Butene-1 and other C4 mix – feedstock that reflected on business impact and production losing. In addition, propylene product suffering from contamination by oxygenates components and causing for lose production and plant upset of Polypropylene process plants. However, Multidimensional gas chromatography (MDGC) innovative analytical methodology is a chromatography technique used to separate complex samples, as mixing different functional group as Hydrocarbon and oxygenates compounds and have similar retention factors, by running the eluent through two or more columns instead of the customary single column. This analytical study striving to enhance the quality of Oxygenates analytical method, as monitoring the concentration of oxygenates with accurate and precise analytical method by utilizing multidimensional GC supported by Backflush technique and Flame Ionization Detector, which have high performance separation of hydrocarbon and Oxygenates; also improving the minimum detection limits (MDL) to detect the concentration <1.0 ppm. However different types of oxygenates as (Alcohols, Aldehyde, Ketones, Ester and Ether) may be determined in other Hydrocarbon streams asC3, C4-mix, until C12 mixture, supported by liquid injection auto-sampler.

Keywords: analytical chemistry, gas chromatography, petrochemicals, oxygenates

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Authors: Thassanant Unnanantn, Suttipong Boonphadung

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This research study aimed to survey and analyze the attitudes of pre-service teachers’ the analytical thinking development based on Miller’s Model. The informants of this study were 22 third year teacher students majoring in Thai. The course where the instruction was conducted was English for Academic Purposes in Thai Language 2. The instrument of this research was an open-ended questionnaire with two dimensions of questions: academic and satisfaction dimensions. The investigation revealed the positive attitudes. In the academic dimension, the majority of 12 (54.54%), the highest percentage, reflected that the method of teaching analytical thinking and language simultaneously was their new knowledge and the similar percentage also belonged to text cohesion in writing. For the satisfaction, the highest frequency count was from 17 of them (77.27%) and this majority favored the openness or friendliness of the teacher.

Keywords: analytical thinking development, Miller’s Model, attitudes, pre-service teachers

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Authors: Atieh Andakhshideh, S. Maleki, Sayed Sadegh Marashi

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In this paper, the interlaminar stresses of generally laminated piezoelectric plates are presented. The electromechanical coupling effect of the piezoelectric plate is considered and the governing equations and boundary conditions are derived using the principle of minimum total potential energy. The solution procedure is a three-dimensional multi-term extended Kantorovich method (3DMTEKM). The objective of this paper is to accurately study coupling influence on the edge effects of piezolaminated plates with finite dimensions, arbitrary lamination lay-ups and under uniform axial strain. These results can provide a benchmark for checking the accuracy of the other numerical method or two-dimensional laminate theories. To verify the accuracy of the 3DMTEKM, first examples are simplified to special cases such as cross-ply or symmetric laminations and are compared with other analytical solutions available in the literature. Excellent agreement is achieved in validation test and other numerical results are presented for general cases. Numerical examples indicate the singular behavior of interlaminar normal/shear stresses and electric field strength components near the edges of the piezolaminated plates. The coupling influence on the free edge effect with respect to lamination lay-ups of piezoelectric plate is studied in several examples.

Keywords: electromechanical coupling, generally laminated piezoelectric plates, Kantorovich method, edge effect, interlaminar stresses

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Authors: S. Saeed, T. Butt, M. Rehan, S. Khaliq

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Objective: To determine the frequency of pre-analytical errors in samples taken from patients for various lab tests at Fauji Foundation Hospital, Rawalpindi. Material and Methods: All the lab specimens for diagnostic purposes received at the lab from Fauji Foundation hospital, Rawalpindi indoor and outdoor patients were included. Total number of samples received in the lab is recorded in the computerized program made for the hospital. All the errors observed for pre-analytical process including patient identification, sampling techniques, test collection procedures, specimen transport/processing and storage were recorded in the log book kept for the purpose. Results: A total of 476616 specimens were received in the lab during the period of study including 237931 and 238685 from outdoor and indoor patients respectively. Forty-one percent of the samples (n=197976) revealed pre-analytical discrepancies. The discrepancies included Hemolyzed samples (34.8%), Clotted blood (27.8%), Incorrect samples (17.4%), Unlabeled samples (8.9%), Insufficient specimens (3.9%), Request forms without authorized signature (2.9%), Empty containers (3.9%) and tube breakage during centrifugation (0.8%). Most of these pre-analytical discrepancies were observed in samples received from the wards revealing that inappropriate sample collection by the medical staff of the ward, as most of the outdoor samples are collected by the lab staff who are properly trained for sample collection. Conclusion: It is mandatory to educate phlebotomists and paramedical staff particularly performing duties in the wards regarding timing and techniques of sampling/appropriate container to use/early delivery of the samples to the lab to reduce pre-analytical errors.

Keywords: pre analytical lab errors, tertiary care hospital, hemolyzed, paramedical staff

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Authors: Davood Yazdani Cherati, Hussein Hashemi Senejani

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In this paper, a convenient analytical solution for a system of coupled differential equations, derived from thermo-hydro-mechanical analysis of three-phase porous media such as unsaturated soils is developed. This kind of analysis can be used in various fields such as geothermal energy systems and seepage of leachate from buried municipal and domestic waste in geomaterials. Initially, a system of coupled differential equations, including energy, mass, and momentum conservation equations is considered, and an analytical method called AGM is employed to solve the problem. The method is straightforward and comprehensible and can be used to solve various nonlinear partial differential equations (PDEs). Results indicate the accuracy of the applied method for solving nonlinear partial differential equations.

Keywords: AGM, analytical solution, porous media, thermo-hydro-mechanical, unsaturated soils

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Authors: Stewart A. Keir, Faik A. Hamad

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This study aims to use both analytical and experimental methods of analysis to examine the accuracy of Computational Fluid Dynamics (CFD) models that can then be used for more complex analyses, accurately representing more elaborate flow phenomena such as internal shockwaves and boundary layers. The geometry used in the analytical study and CFD model is taken from the experimental rig. The analytical study is undertaken using isentropic and adiabatic relationships and the output of the analytical study, the 'shockwave location tool', is created. The results from the analytical study are then used to optimize the redesign an experimental rig for more favorable placement of pressure taps and gain a much better representation of the shockwaves occurring in the divergent section of the nozzle. The CFD model is then optimized through the selection of different parameters, e.g. turbulence models (Spalart-Almaras, Realizable k-epsilon & Standard k-omega) in order to develop an accurate, robust model. The results from the CFD model can then be directly compared to experimental and analytical results in order to gauge the accuracy of each method of analysis. The CFD model will be used to visualize the variation of various parameters such as velocity/Mach number, pressure and turbulence across the shock. The CFD results will be used to investigate the interaction between the shock wave and the boundary layer. The validated model can then be used to modify the nozzle designs which may offer better performance and ease of manufacture and may present feasible improvements to existing high-speed flow applications.

Keywords: CFD, nozzle, fluent, gas dynamics, shock-wave

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Authors: Syukri Himran, Rustan Taraka, Anto Duma

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The aim of the study is to improve the understanding of latent and sensible thermal energy storage within a paraffin wax media by an array of cylindrical tubes arranged both in in-line and staggered layouts. An analytical and experimental study was carried out in a horizontal shell-and-tube type system during the melting process. Pertamina paraffin-wax was used as a phase change material (PCM), where as the tubes are embedded in the PCM. From analytical study we can obtain the useful information in designing a thermal energy storage such as : the motion of interface, amount of material melted at any time in the process, and the heat storage characteristic during melting. The use of staggered tubes is proposed as superior to in-line layout for thermal storage. The experimental study was used to verify the validity of the analytical predictions. From the comparisons, the analytical and experimental data are in a good agreement.

Keywords: latent, sensible, paraffin-wax, thermal energy storage, conduction, natural convection

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Authors: Rajaian Hoonejani Mohammad, Eshraghi Pegah, Zomorodian Zahra Sadat, Tahsildoost Mohammad

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Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

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Authors: Leonardo C. Pacheco-Londoño, Nataly J Galan-Freyle, Lisandro Pacheco-Lugo, Antonio Acosta-Hoyos, Elkin Navarro, Gustavo Aroca-Martinez, Karin Rondón-Payares, Alberto C. Espinosa-Garavito, Samuel P. Hernández-Rivera

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At the Life Science Research Center at Simon Bolivar University, a primary focus is the diagnosis of various diseases, and the use of gold nanoparticles (Au-NPs) in diverse biomedical applications is continually expanding. In the present study, Au-NPs were employed as substrates for Surface-Enhanced Raman Spectroscopy (SERS) aimed at diagnosing kidney diseases arising from Lupus Nephritis (LN), preeclampsia (PC), and Hypertension (H). Discrimination models were developed for distinguishing patients with and without kidney diseases based on the SERS signals from urine samples by partial least squares-discriminant analysis (PLS-DA). A comparative study of the Raman signals across the three conditions was conducted, leading to the identification of potential metabolite signals. Model performance was assessed through cross-validation and external validation, determining parameters like sensitivity and specificity. Additionally, a secondary analysis was performed using machine learning (ML) models, wherein different ML algorithms were evaluated for their efficiency. Models’ validation was carried out using cross-validation and external validation, and other parameters were determined, such as sensitivity and specificity; the models showed average values of 0.9 for both parameters. Additionally, it is not possible to highlight this collaborative effort involved two university research centers and two healthcare institutions, ensuring ethical treatment and informed consent of patient samples.

Keywords: SERS, Raman, PLS-DA, kidney diseases

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Authors: Basant K. Jha, M. L. Kaurangini

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An approximate analytical solution is presented for convective flow in a horizontal channel filled with porous material. The Brinkman-Forchheimer extension of Darcy equation is utilized to model the fluid flow while the energy equation is utilized to model temperature distribution in the channel. The solutions were obtained utilizing the newly suggested technique and compared with those obtained from an implicit finite-difference solution.

Keywords: approximate analytical, convective flow, porous material, Brinkman-Forchiemer

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Authors: Mustafa Kaya

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In this study, the effect of pre-stressed strand diameters, providing the beam-to-column connections, was investigated from both experimental, and analytical aspects. In the experimental studies, the strength and stiffness, the capacities of the precast specimens were compared. The precast specimen with strands of 15.24 mm reached an equal strength of the reference specimen. Parallel results were obtained during the analytical studies from the aspects of strength, and behavior, but in terms of stiffness, it was seen that the initial stiffness of the analytical models was lower than that of the tested specimen.

Keywords: post-tensioned connections, beam to column connections, finite element method, strand diameter

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Authors: T. Zitoun, M. Bouhadef

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When a partially or completely immersed solid moves in a liquid such as water, it undergoes a force called hydrodynamic drag. Reducing this force has always been the objective of hydrodynamic engineers to make water slide better on submerged bodies. This paper deals with the examination of the different terms composing the analytical solution of the flow over an obstacle embedded at the bottom of a hydraulic channel. We have chosen to use a linear method to study a two-dimensional flow over an obstacle, in order to understand the evolution of the drag. We set the following assumptions: incompressible inviscid fluid, irrotational flow, low obstacle height compared to the water height. Those assumptions allow overcoming the difficulties associated with modelling these waves. We will mathematically formulate the equations that allow the determination of the stream function, and then the free surface equation. A similar method is used to determine the exact analytical solution for an obstacle in the shape of a sinusoidal arch.

Keywords: analytical solution, free-surface wave, hydraulic channel, inviscid fluid

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Authors: Nizar Tayem, AbuMuhammad Moinuddeen, Ahmed A. Hussain, Redha M. Radaydeh

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This research paper introduces an approach for estimating the direction of arrival (DOA) of multiple RF noncoherent sources in a uniform linear array (ULA). The proposed method utilizes a Capon-like estimation algorithm and incorporates LU decomposition to enhance the accuracy of DOA estimation while significantly reducing computational complexity compared to existing methods like the Capon method. Notably, the proposed method does not require prior knowledge of the number of sources. To validate its effectiveness, the proposed method undergoes validation through both software simulations and practical experimentation on a prototype testbed constructed using a software-defined radio (SDR) platform and GNU Radio software. The results obtained from MATLAB simulations and real-time experiments provide compelling evidence of the proposed method's efficacy.

Keywords: DOA estimation, real-time validation, software defined radio, computational complexity, Capon's method, GNU radio

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Authors: F. Z. Mahi, H. Marinchio, C. Palermo, L. Varani

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We propose an analytical approach for the admittance response calculation of the high mobility InGaAs channel transistors. The development of the small-signal admittance takes into account the longitudinal and transverse electric fields through a pseudo two-dimensional approximation of the Poisson equation. The total currents and the potentials matrix relation between the gate and the drain terminals determine the frequency-dependent small-signal admittance response. The analytical results show that the admittance spectrum exhibits a series of resonant peaks corresponding to the excitation of plasma waves. The appearance of the resonance is discussed and analyzed as functions of the channel length and the temperature. The model can be used, on one hand, to control the appearance of plasma resonances, and on the other hand, can give significant information about the admittance phase frequency dependence.

Keywords: small-signal admittance, Poisson equation, currents and potentials matrix, the drain and the gate terminals, analytical model

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Authors: Hasan Fatih Ertuğrul, Beytullah Okur, Huseyin Üvet, Kadir Erkan

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The objective of this paper is to analyze a 4-pole hybrid magnetic levitation system by using 3D finite element and analytical methods. The magnetostatic analysis of the system is carried out by using ANSYS MAXWELL-3D package. An analytical model is derived by magnetic equivalent circuit (MEC) method. The purpose of magnetostatic analysis is to determine the characteristics of attractive force and rotational torques by the change of air gap clearances, inclination angles and current excitations. The comparison between 3D finite element analysis and analytical results are presented at the rest of the paper.

Keywords: yoke hybrid electromagnet, 3D finite element analysis, magnetic levitation system, magnetostatic analysis

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Authors: Mohamad R. Moshtagh, Ahmad Bagheri

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Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

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Authors: A. E. Dumitriu

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The LHCb experiment is situated at one of the four points around CERN’s Large Hadron Collider, being a single-arm forward spectrometer covering 10 mrad to 300 (250) mrad in the bending (non-bending) plane, designed primarily to study particles containing b and c quarks. Each one of LHCb’s sub-detectors specializes in measuring a different characteristic of the particles produced by colliding protons, its significant detection characteristics including a high precision tracking system and 2 ring-imaging Cherenkov detectors for particle identification. The major two topics that I am currently concerned in are: the RIVET project (Robust Independent Validation of Experiment and Theory) which is an efficient and portable tool kit of C++ class library useful for validation and tuning of Monte Carlo (MC) event generator models by providing a large collection of standard experimental analyses useful for High Energy Physics MC generator development, validation, tuning and regression testing and V0 analysis for 2013 LHCb NoBias type data (trigger on bunch + bunch crossing) at √s=2.76 TeV.

Keywords: LHCb physics, RIVET plug-in, RIVET, CERN

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Authors: Jafar Razmi

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Integral abutment bridges are bridges that do not have joints. If these bridges are subject to large seasonal and daily temperature variations, the expansion and contraction of the bridge slab is transferred to the piles. Since the piles are deep into the soil, displacement induced by slab can cause bending and stresses in piles. These stresses cause fatigue and failure of piles. A complex mechanical interaction exists between the slab, pile, soil and abutment. This complex interaction needs to be understood in order to calculate the stresses in piles. This paper uses a mechanical approach in developing analytical equations for the complex structure to determine the stresses in piles. The solution to these analytical solutions is developed and compared with finite element analysis results and experimental data. Our comparison shows that using analytical approach can accurately predict the displacement in piles. This approach offers a simplified technique that can be utilized without the need for computationally extensive finite element model.

Keywords: integral abutment bridges, piles, thermo-mechanical stress, stress and strains

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Authors: Hossein Kabir, Amir Hossein Hassanpour Mati-Kolaie

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In the current study, the elastic field in an anisotropic elastic media is determined by implementing a general semi-analytical method. In this specific methodology, the displacement field is computed as a sum of finite functions with unknown coefficients. These aforementioned functions satisfy exactly both the homogeneous and inhomogeneous boundary conditions in the proposed media. It is worth mentioning that the unknown coefficients are determined by implementing the principle of minimum potential energy. The numerical integration is implemented by employing the Generalized Gaussian Quadrature solution. Furthermore, with the aid of the calculated unknown coefficients, the displacement field, as well as the other parameters of the elastic field, are obtainable as well. Finally, the comparison of the previous analytical method with the current semi-analytical method proposes the efficacy of the present methodology.

Keywords: anisotropic elastic media, semi-analytical method, elastic field, generalized gaussian quadrature solution

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Authors: Budiman Budiman

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This research aimed at describing and testing whether the students’ ability in writing analytical exposition text is increased by using comic strips at SMAN 12 Pekanbaru. The respondents of this study were the second-grade students, especially XI Science 3 academic year 2011-2012. The total number of students in this class was forty-two (42) students. The quantitative and qualitative data was collected by using writing test and observation sheets. The research finding reveals that there is a significant increase of students’ writing ability in writing analytical exposition text through comic strips. It can be proved by the average score of pre-test was 43.7 and the average score of post-test was 65.37. Besides, the students’ interest and motivation in learning are also improved. These can be seen from the increasing of students’ awareness and activeness in learning process based on observation sheets. The findings draw attention to the use of comic strips in teaching and learning is beneficial for better learning outcome.

Keywords: analytical exposition, comic strips, secondary school students, writing ability

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Authors: Waraporn Thaimit, Yuwadee Insamran, Natchanok Jansawang

Abstract:

Focusing on Analytical Thinking and Learning Achievement are the critical component of visual thinking that gives one the ability to solve problems quickly and effectively that allows to complex problems into components, and the result had been achieved or acquired form of the subject students of which resulted in changes within the individual as a result of activity in learning. The aims of this study are to administer on comparisons between students’ analytical thinking abilities and their learning achievements sample size consisted of 80 students who sat at the 12th grade level in 2 classes from Chaturaphak Phiman Ratchadaphisek School, the 40-student experimental group with the Problem-Based Learning (PBL) and 40-student controlling group with the Concept Mapping Instructional (CMI) methods were designed. Research instruments composed with the 5-lesson instructional plans to be assessed with the pretest and posttest techniques on each instructional method. Students’ responses of their analytical thinking abilities were assessed with the Analytical Thinking Tests and students’ learning achievements were tested of the Learning Achievement Tests. Statistically significant differences with the paired t-test and F-test (Two-way MANCOVA) between post- and pre-tests of the whole students in two chemistry classes were found. Associations between student learning outcomes in each instructional method and their analytical thinking abilities to their learning achievements also were found (ρ < .05). The use of two instructional methods for this study is revealed that the students perceive their abilities to be highly learning achievement in chemistry classes with the PBL group ought to higher than the CMI group. Suggestions that analytical thinking ability involves the process of gathering relevant information and identifying key issues related to the learning achievement information.

Keywords: comparisons, students learning achievements, analytical thinking abilities, the problem-based learning method, the concept mapping instructional method, gene and chromosome issue, chemistry classes

Procedia PDF Downloads 237

Authors: A. J. Francisco, K. C. Gallosa, R. J. Gasacao, J. R. Ros, B. J. Viado

Abstract:

The study focuses on the use of quality indicators (QI)s based on the standards made by the (IFCC), that could effectively identify and minimize errors occurring throughout the total testing process (TTP), in order to improve patient safety. The study was conducted through a survey questionnaire that was given to a random sample of 19 respondents (eight privately-owned and eleven government-owned hospitals), mainly CMTs, MTs, and Supervisors from UST-affiliated hospitals. The pre-analytical laboratory errors, which include misidentification errors, transcription errors, sample collection errors and sample handling and transportation errors, were considered as variables according to the IFCC WG-LEPS. Data gathered were analyzed using the Mann-Whitney U test, Percentile, Linear Regression, Percentage, and Frequency. The laboratory performance of both hospitals is High level. There is no significant difference between the laboratory performance between the two stated variables. Moreover, among the four QIs, sample handling and transportation errors contributed most to the difference between the two variables. Outcomes indicate satisfactory performance between both variables. However, in order to ensure high-quality and efficient laboratory operation, constant vigilance and improvements in pre-analytical QI are still needed. Expanding the coverage of the study, the inclusion of other phases, utilization of parametric tests are recommended.

Keywords: pre-analytical phase, quality indicators, laboratory performance, pre-analytical error

Procedia PDF Downloads 115