Search results for: hybrid meshless method
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 20225

Search results for: hybrid meshless method

17675 Study of Electron Cyclotron Resonance Acceleration by Cylindrical TE₀₁₁ Mode

Authors: Oswaldo Otero, Eduardo A. Orozco, Ana M. Herrera

Abstract:

In this work, we present results from analytical and numerical studies of the electron acceleration by a TE₀₁₁ cylindrical microwave mode in a static homogeneous magnetic field under electron cyclotron resonance (ECR) condition. The stability of the orbits is analyzed using the particle orbit theory. In order to get a better understanding of the interaction wave-particle, we decompose the azimuthally electric field component as the superposition of right and left-hand circular polarization standing waves. The trajectory, energy and phase-shift of the electron are found through a numerical solution of the relativistic Newton-Lorentz equation in a finite difference method by the Boris method. It is shown that an electron longitudinally injected with an energy of 7 keV in a radial position r=Rc/2, being Rc the cavity radius, is accelerated up to energy of 90 keV by an electric field strength of 14 kV/cm and frequency of 2.45 GHz. This energy can be used to produce X-ray for medical imaging. These results can be used as a starting point for study the acceleration of electrons in a magnetic field changing slowly in time (GYRAC), which has some important applications as the electron cyclotron resonance ion proton accelerator (ECR-IPAC) for cancer therapy and to control plasma bunches with relativistic electrons.

Keywords: Boris method, electron cyclotron resonance, finite difference method, particle orbit theory, X-ray

Procedia PDF Downloads 159
17674 The Analysis of Own Signals of PM Electrical Machines – Example of Eccentricity

Authors: Marcin Baranski

Abstract:

This article presents a vibration diagnostic method designed for permanent magnets (PM) traction motors. Those machines are commonly used in traction drives of electrical vehicles. Specific structural properties of machines excited by permanent magnets are used in this method - electromotive force (EMF) generated due to vibrations. This work presents: field-circuit model, results of static tests, results of calculations and simulations.

Keywords: electrical vehicle, permanent magnet, traction drive, vibrations, electrical machine, eccentricity

Procedia PDF Downloads 630
17673 Integrating Artificial Neural Network and Taguchi Method on Constructing the Real Estate Appraisal Model

Authors: Mu-Yen Chen, Min-Hsuan Fan, Chia-Chen Chen, Siang-Yu Jhong

Abstract:

In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Keywords: artificial neural network, Taguchi method, real estate valuation model, investors

Procedia PDF Downloads 491
17672 Efficient Principal Components Estimation of Large Factor Models

Authors: Rachida Ouysse

Abstract:

This paper proposes a constrained principal components (CnPC) estimator for efficient estimation of large-dimensional factor models when errors are cross sectionally correlated and the number of cross-sections (N) may be larger than the number of observations (T). Although principal components (PC) method is consistent for any path of the panel dimensions, it is inefficient as the errors are treated to be homoskedastic and uncorrelated. The new CnPC exploits the assumption of bounded cross-sectional dependence, which defines Chamberlain and Rothschild’s (1983) approximate factor structure, as an explicit constraint and solves a constrained PC problem. The CnPC method is computationally equivalent to the PC method applied to a regularized form of the data covariance matrix. Unlike maximum likelihood type methods, the CnPC method does not require inverting a large covariance matrix and thus is valid for panels with N ≥ T. The paper derives a convergence rate and an asymptotic normality result for the CnPC estimators of the common factors. We provide feasible estimators and show in a simulation study that they are more accurate than the PC estimator, especially for panels with N larger than T, and the generalized PC type estimators, especially for panels with N almost as large as T.

Keywords: high dimensionality, unknown factors, principal components, cross-sectional correlation, shrinkage regression, regularization, pseudo-out-of-sample forecasting

Procedia PDF Downloads 151
17671 Recirculated Sedimentation Method to Control Contamination for Algal Biomass Production

Authors: Ismail S. Bostanci, Ebru Akkaya

Abstract:

Microalgae-derived biodiesel, fertilizer or industrial chemicals' production with wastewater has great potential. Especially water from a municipal wastewater treatment plant is a very important nutrient source for biofuel production. Microalgae biomass production in open ponds system is lower cost culture systems. There are many hurdles for commercial algal biomass production in large scale. One of the important technical bottlenecks for microalgae production in open system is culture contamination. The algae culture contaminants can generally be described as invading organisms which could cause pond crash. These invading organisms can be competitors, parasites, and predators. Contamination is unavoidable in open systems. Potential contaminant organisms are already inoculated if wastewater is utilized for algal biomass cultivation. Especially, it is important to control contaminants to retain in acceptable level in order to reach true potential of algal biofuel production. There are several contamination management methods in algae industry, ranging from mechanical, chemical, biological and growth condition change applications. However, none of them are accepted as a suitable contamination control method. This experiment describes an innovative contamination control method, 'Recirculated Sedimentation Method', to manage contamination to avoid pond cash. The method can be used for the production of algal biofuel, fertilizer etc. and algal wastewater treatment. To evaluate the performance of the method on algal culture, an experiment was conducted for 90 days at a lab-scale raceway (60 L) reactor with the use of non-sterilized and non-filtered wastewater (secondary effluent and centrate of anaerobic digestion). The application of the method provided the following; removing contaminants (predators and diatoms) and other debris from reactor without discharging the culture (with microscopic evidence), increasing raceway tank’s suspended solids holding capacity (770 mg L-1), increasing ammonium removal rate (29.83 mg L-1 d-1), decreasing algal and microbial biofilm formation on inner walls of reactor, washing out generated nitrifier from reactor to prevent ammonium consumption.

Keywords: contamination control, microalgae culture contamination, pond crash, predator control

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17670 Efficient Numerical Simulation for LDC

Authors: Badr Alkahtani

Abstract:

In this poster, numerical solutions of two-dimensional and three-dimensional lid driven cavity are presented by solving the steady Navier-Stokes equations at high Reynolds numbers where it becomes difficult. Lid driven cavity is where the a fluid contained in a cube and the upper wall is moving. In two dimensions, we use the streamfunction-vorticity formulation to solve the problem in a square domain. A numerical method is employed to discretize the problem in the x and y directions with a spectral collocation method. The problem is coded in the MATLAB programming environment. Solutions at high Reynolds numbers are obtained up to Re=20000 on a fine grid of 131 * 131. Also in this presentation, the numerical solutions for the three-dimensional lid-driven cavity problem are obtained by solving the velocity-vorticity formulation of the Navier-Stokes equations (which is the first time that this has been simulated with special boundary conditions) for various Reynolds numbers. A spectral collocation method is employed to discretize the y and z directions and a finite difference method is used to discretize the x direction. Numerical solutions are obtained for Reynolds number up to 200. , The work prepared here is to show the efficiency of methods used to simulate the physical problem where accurate simulations of lid driven cavity are obtained at high Reynolds number as mentioned above. The result for the two dimensional problem is far from the previous researcher result.

Keywords: lid driven cavity, navier-stokes, simulation, Reynolds number

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17669 Development of Lipid Architectonics for Improving Efficacy and Ameliorating the Oral Bioavailability of Elvitegravir

Authors: Bushra Nabi, Saleha Rehman, Sanjula Baboota, Javed Ali

Abstract:

Aim: The objective of research undertaken is analytical method validation (HPLC method) of an anti-HIV drug Elvitegravir (EVG). Additionally carrying out the forced degradation studies of the drug under different stress conditions to determine its stability. It is envisaged in order to determine the suitable technique for drug estimation, which would be employed in further research. Furthermore, comparative pharmacokinetic profile of the drug from lipid architectonics and drug suspension would be obtained post oral administration. Method: Lipid Architectonics (LA) of EVR was formulated using probe sonication technique and optimized using QbD (Box-Behnken design). For the estimation of drug during further analysis HPLC method has been validation on the parameters (Linearity, Precision, Accuracy, Robustness) and Limit of Detection (LOD) and Limit of Quantification (LOQ) has been determined. Furthermore, HPLC quantification of forced degradation studies was carried out under different stress conditions (acid induced, base induced, oxidative, photolytic and thermal). For pharmacokinetic (PK) study, Albino Wistar rats were used weighing between 200-250g. Different formulations were given per oral route, and blood was collected at designated time intervals. A plasma concentration profile over time was plotted from which the following parameters were determined:

Keywords: AIDS, Elvitegravir, HPLC, nanostructured lipid carriers, pharmacokinetics

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17668 Self-Calibration of Fish-Eye Camera for Advanced Driver Assistance Systems

Authors: Atef Alaaeddine Sarraj, Brendan Jackman, Frank Walsh

Abstract:

Tomorrow’s car will be more automated and increasingly connected. Innovative and intuitive interfaces are essential to accompany this functional enrichment. For that, today the automotive companies are competing to offer an advanced driver assistance system (ADAS) which will be able to provide enhanced navigation, collision avoidance, intersection support and lane keeping. These vision-based functions require an accurately calibrated camera. To achieve such differentiation in ADAS requires sophisticated sensors and efficient algorithms. This paper explores the different calibration methods applicable to vehicle-mounted fish-eye cameras with arbitrary fields of view and defines the first steps towards a self-calibration method that adequately addresses ADAS requirements. In particular, we present a self-calibration method after comparing different camera calibration algorithms in the context of ADAS requirements. Our method gathers data from unknown scenes while the car is moving, estimates the camera intrinsic and extrinsic parameters and corrects the wide-angle distortion. Our solution enables continuous and real-time detection of objects, pedestrians, road markings and other cars. In contrast, other camera calibration algorithms for ADAS need pre-calibration, while the presented method calibrates the camera without prior knowledge of the scene and in real-time.

Keywords: advanced driver assistance system (ADAS), fish-eye, real-time, self-calibration

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17667 Coupling Heat Transfer by Natural Convection and Thermal Radiation in a Storage Tank of LNG

Authors: R. Hariti, M. Saighi, H. Saidani-Scott

Abstract:

A numerical simulation of natural convection double diffusion, coupled with thermal radiation in unsteady laminar regime in a storage tank is carried out. The storage tank contains a liquefied natural gas (LNG) in its gaseous phase. Fluent, a commercial CFD package, based on the numerical finite volume method, is used to simulate the flow. The radiative transfer equation is solved using the discrete coordinate method. This numerical simulation is used to determine the temperature profiles, stream function, velocity vectors and variation of the heat flux density for unsteady laminar natural convection. Furthermore, the influence of thermal radiation on the heat transfer has been investigated and the results obtained were compared to those found in the literature. Good agreement between the results obtained by the numerical method and those taken on site for the temperature values.

Keywords: tank, storage, liquefied natural gas, natural convection, thermal radiation, numerical simulation

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17666 A Simple Finite Element Method for Glioma Tumor Growth Model with Density Dependent Diffusion

Authors: Shangerganesh Lingeshwaran

Abstract:

In this presentation, we have performed numerical simulations for a reaction-diffusion equation with various nonlinear density-dependent diffusion operators and proliferation functions. The mathematical model represented by parabolic partial differential equation is considered to study the invasion of gliomas (the most common type of brain tumors) and to describe the growth of cancer cells and response to their treatment. The unknown quantity of the given reaction-diffusion equation is the density of cancer cells and the mathematical model based on the proliferation and migration of glioma cells. A standard Galerkin finite element method is used to perform the numerical simulations of the given model. Finally, important observations on the each of nonlinear diffusion functions and proliferation functions are presented with the help of computational results.

Keywords: glioma invasion, nonlinear diffusion, reaction-diffusion, finite eleament method

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17665 Assessing Remote and Hybrid Education Amidst the COVID-19 Pandemic: Insights and Innovations from Secondary School Educators

Authors: Azzeddine Atibi, Khadija El Kababi, Salim Ahmed, Mohamed Radid

Abstract:

The principal objective of this study is to undertake a comprehensive comparative analysis of distance learning and blended learning modalities, with a particular emphasis on evaluating their effectiveness during the confinement period mandated by the COVID-19 pandemic. This investigation is rooted in the firsthand experiences of educators at the high school and secondary levels within both private and public educational institutions. To acquire the requisite data, we meticulously designed and distributed a survey to these educators, soliciting detailed narratives of their professional experiences throughout this challenging period. The survey aims to elucidate the specific difficulties encountered by teachers, as well as to highlight the innovative pedagogical strategies they devised in response to these challenges. By synthesizing the insights garnered from this survey, our goal is to foster an exchange of experiences among educators and to generate informed recommendations that will inform future educational reforms. Ultimately, this study aspires to contribute to the ongoing discourse on optimizing educational practices in the face of unprecedented disruptions.

Keywords: distance learning, blended learning, covid 19, secondary/ high school, teachingperformance, evaluation

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17664 Simulation of Growth and Yield of Rice Under Irrigation and Nitrogen Management Using ORYZA2000

Authors: Mojtaba Esmaeilzad Limoudehi

Abstract:

To evaluate the model ORYZA2000, under the management of irrigation and nitrogen fertilization experiment, a split plot with a randomized complete block design with three replications on hybrid cultivars (spring) in the 1388-1387 crop year was conducted at the Rice Research Institute. Permanent flood irrigation as the main plot in the fourth level, around 5 days, from 11 days to 8 days away, and the four levels of nitrogen fertilizer as the subplots 0, 90, 120, and 150 kg N Ha were considered. Simulated and measured values of leaf area index, grain yield, and biological parameters using the regression coefficient, t-test, the root mean square error (RMSE), and normalized root mean square error (RMSEn) were performed. Results, the normalized root mean square error of 10% in grain yield, the biological yield of 9%, and 23% of maximum LAI was determined. The simulation results show that grain yield and biological ORYZA2000 model accuracy are good but do not simulate maximum LAI well. The results show that the model can support ORYZA2000 test results and can be used under conditions of nitrogen fertilizer and irrigation management.

Keywords: evaluation, rice, nitrogen fertilizer, model ORYZA2000

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17663 Intelligent Fault Diagnosis for the Connection Elements of Modular Offshore Platforms

Authors: Jixiang Lei, Alexander Fuchs, Franz Pernkopf, Katrin Ellermann

Abstract:

Within the Space@Sea project, funded by the Horizon 2020 program, an island consisting of multiple platforms was designed. The platforms are connected by ropes and fenders. The connection is critical with respect to the safety of the whole system. Therefore, fault detection systems are investigated, which could detect early warning signs for a possible failure in the connection elements. Previously, a model-based method called Extended Kalman Filter was developed to detect the reduction of rope stiffness. This method detected several types of faults reliably, but some types of faults were much more difficult to detect. Furthermore, the model-based method is sensitive to environmental noise. When the wave height is low, a long time is needed to detect a fault and the accuracy is not always satisfactory. In this sense, it is necessary to develop a more accurate and robust technique that can detect all rope faults under a wide range of operational conditions. Inspired by this work on the Space at Sea design, we introduce a fault diagnosis method based on deep neural networks. Our method cannot only detect rope degradation by using the acceleration data from each platform but also estimate the contributions of the specific acceleration sensors using methods from explainable AI. In order to adapt to different operational conditions, the domain adaptation technique DANN is applied. The proposed model can accurately estimate rope degradation under a wide range of environmental conditions and help users understand the relationship between the output and the contributions of each acceleration sensor.

Keywords: fault diagnosis, deep learning, domain adaptation, explainable AI

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17662 A Modified QuEChERS Method Using Activated Carbon Fibers as r-DSPE Sorbent for Sample Cleanup: Application to Pesticides Residues Analysis in Food Commodities Using GC-MS/MS

Authors: Anshuman Srivastava, Shiv Singh, Sheelendra Pratap Singh

Abstract:

A simple, sensitive and effective gas chromatography tandem mass spectrometry (GC-MS/MS) method was developed for simultaneous analysis of multi pesticide residues (organophosphate, organochlorines, synthetic pyrethroids and herbicides) in food commodities using phenolic resin based activated carbon fibers (ACFs) as reversed-dispersive solid phase extraction (r-DSPE) sorbent in modified QuEChERS (Quick Easy Cheap Effective Rugged Safe) method. The acetonitrile-based QuEChERS technique was used for the extraction of the analytes from food matrices followed by sample cleanup with ACFs instead of traditionally used primary secondary amine (PSA). Different physico-chemical characterization techniques such as Fourier transform infrared spectroscopy, scanning electron microscopy, X-ray diffraction and Brunauer-Emmet-Teller surface area analysis were employed to investigate the engineering and structural properties of ACFs. The recovery of pesticides and herbicides was tested at concentration levels of 0.02 and 0.2 mg/kg in different commodities such as cauliflower, cucumber, banana, apple, wheat and black gram. The recoveries of all twenty-six pesticides and herbicides were found in acceptable limit (70-120%) according to SANCO guideline with relative standard deviation value < 15%. The limit of detection and limit of quantification of the method was in the range of 0.38-3.69 ng/mL and 1.26 -12.19 ng/mL, respectively. In traditional QuEChERS method, PSA used as r-DSPE sorbent plays a vital role in sample clean-up process and demonstrates good recoveries for multiclass pesticides. This study reports that ACFs are better in terms of removal of co-extractives in comparison of PSA without compromising the recoveries of multi pesticides from food matrices. Further, ACF replaces the need of charcoal in addition to the PSA from traditional QuEChERS method which is used to remove pigments. The developed method will be cost effective because the ACFs are significantly cheaper than the PSA. So the proposed modified QuEChERS method is more robust, effective and has better sample cleanup efficiency for multiclass multi pesticide residues analysis in different food matrices such as vegetables, grains and fruits.

Keywords: QuEChERS, activated carbon fibers, primary secondary amine, pesticides, sample preparation, carbon nanomaterials

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17661 Numerical Simulations on Feasibility of Stochastic Model Predictive Control for Linear Discrete-Time Systems with Random Dither Quantization

Authors: Taiki Baba, Tomoaki Hashimoto

Abstract:

The random dither quantization method enables us to achieve much better performance than the simple uniform quantization method for the design of quantized control systems. Motivated by this fact, the stochastic model predictive control method in which a performance index is minimized subject to probabilistic constraints imposed on the state variables of systems has been proposed for linear feedback control systems with random dither quantization. In other words, a method for solving optimal control problems subject to probabilistic state constraints for linear discrete-time control systems with random dither quantization has been already established. To our best knowledge, however, the feasibility of such a kind of optimal control problems has not yet been studied. Our objective in this paper is to investigate the feasibility of stochastic model predictive control problems for linear discrete-time control systems with random dither quantization. To this end, we provide the results of numerical simulations that verify the feasibility of stochastic model predictive control problems for linear discrete-time control systems with random dither quantization.

Keywords: model predictive control, stochastic systems, probabilistic constraints, random dither quantization

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17660 The Estimation Method of Stress Distribution for Beam Structures Using the Terrestrial Laser Scanning

Authors: Sang Wook Park, Jun Su Park, Byung Kwan Oh, Yousok Kim, Hyo Seon Park

Abstract:

This study suggests the estimation method of stress distribution for the beam structures based on TLS (Terrestrial Laser Scanning). The main components of method are the creation of the lattices of raw data from TLS to satisfy the suitable condition and application of CSSI (Cubic Smoothing Spline Interpolation) for estimating stress distribution. Estimation of stress distribution for the structural member or the whole structure is one of the important factors for safety evaluation of the structure. Existing sensors which include ESG (Electric strain gauge) and LVDT (Linear Variable Differential Transformer) can be categorized as contact type sensor which should be installed on the structural members and also there are various limitations such as the need of separate space where the network cables are installed and the difficulty of access for sensor installation in real buildings. To overcome these problems inherent in the contact type sensors, TLS system of LiDAR (light detection and ranging), which can measure the displacement of a target in a long range without the influence of surrounding environment and also get the whole shape of the structure, has been applied to the field of structural health monitoring. The important characteristic of TLS measuring is a formation of point clouds which has many points including the local coordinate. Point clouds is not linear distribution but dispersed shape. Thus, to analyze point clouds, the interpolation is needed vitally. Through formation of averaged lattices and CSSI for the raw data, the method which can estimate the displacement of simple beam was developed. Also, the developed method can be extended to calculate the strain and finally applicable to estimate a stress distribution of a structural member. To verify the validity of the method, the loading test on a simple beam was conducted and TLS measured it. Through a comparison of the estimated stress and reference stress, the validity of the method is confirmed.

Keywords: structural healthcare monitoring, terrestrial laser scanning, estimation of stress distribution, coordinate transformation, cubic smoothing spline interpolation

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17659 Shield Tunnel Excavation Simulation of a Case Study Using a So-Called 'Stress Relaxation' Method

Authors: Shengwei Zhu, Alireza Afshani, Hirokazu Akagi

Abstract:

Ground surface settlement induced by shield tunneling is addressing increasing attention as shield tunneling becomes a popular construction technique for tunnels in urban areas. This paper discusses a 2D longitudinal FEM simulation of a tunneling case study in Japan (Tokyo Metro Yurakucho Line). Tunneling-induced field data was already collected and is used here for comparison and evaluating purposes. In this model, earth pressure, face pressure, backfilling grouting, elastic tunnel lining, and Mohr-Coulomb failure criterion for soil elements are considered. A method called ‘stress relaxation’ is also exploited to simulate the gradual tunneling excavation. Ground surface settlements obtained from numerical results using the introduced method are then compared with the measurement data.

Keywords: 2D longitudinal FEM model, tunneling case study, stress relaxation, shield tunneling excavation

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17658 Design of an Energy Efficient Electric Auto Rickshaw

Authors: Muhammad Asghar, Aamer Iqbal Bhatti, Qadeer Ahmed, Tahir Izhar

Abstract:

Three wheeler auto Rickshaw, often termed as ‘auto rickshaw’ is very common in Pakistan and is considered as the most affordable means of transportation to the local people. Problems caused by the gasoline engine on the environment and people, the researchers and the automotive industry have turned to the hybrid electric vehicles and electrical powered vehicle. The research in this paper explains the design of energy efficient Electric auto Rickshaw. An electric auto rickshaw is being developed at Center for Energy Research and Development, (Lahore), which is running on the roads of Lahore city. Energy storage capacity of batteries is at least 25 times heavier than fossil fuel and having volume 10 times in comparison to fuel, resulting an increase of the Rickshaw weight. A set of specifications is derived according to the mobility requirements of the electric auto rickshaw. The design choices considering the power-train and component selection are explained in detail. It was concluded that electric auto rickshaw has many advantages and benefits over the conventional auto rickshaw. It is cleaner and much more energy efficient but limited to the distance it can travel before recharging of battery. In addition, a brief future view of the battery technology is given.

Keywords: conventional auto rickshaw, energy efficiency, electric auto rickshaw, internal combustion engine, environment

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17657 A Guide for Using Viscoelasticity in ANSYS

Authors: A. Fettahoglu

Abstract:

Theory of viscoelasticity is used by many researchers to represent the behavior of many materials such as pavements on roads or bridges. Several researches used analytical methods and rheology to predict the material behaviors of simple models. Today, more complex engineering structures are analyzed using Finite Element Method, in which material behavior is embedded by means of three dimensional viscoelastic material laws. As a result, structures of unordinary geometry and domain can be analyzed by means of Finite Element Method and three dimensional viscoelastic equations. In the scope of this study, rheological models embedded in ANSYS, namely, generalized Maxwell model and Prony series, which are two methods used by ANSYS to represent viscoelastic material behavior, are presented explicitly. Afterwards, a guide is illustrated to ease using of viscoelasticity tool in ANSYS.

Keywords: ANSYS, generalized Maxwell model, finite element method, Prony series, viscoelasticity, viscoelastic material curve fitting

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17656 Method for Tuning Level Control Loops Based on Internal Model Control and Closed Loop Step Test Data

Authors: Arnaud Nougues

Abstract:

This paper describes a two-stage methodology derived from internal model control (IMC) for tuning a proportional-integral-derivative (PID) controller for levels or other integrating processes in an industrial environment. Focus is the ease of use and implementation speed which are critical for an industrial application. Tuning can be done with minimum effort and without the need for time-consuming open-loop step tests on the plant. The first stage of the method applies to levels only: the vessel residence time is calculated from equipment dimensions and used to derive a set of preliminary proportional-integral (PI) settings with IMC. The second stage, re-tuning in closed-loop, applies to levels as well as other integrating processes: a tuning correction mechanism has been developed based on a series of closed-loop simulations with model errors. The tuning correction is done from a simple closed-loop step test and the application of a generic correlation between observed overshoot and integral time correction. A spin-off of the method is that an estimate of the vessel residence time (levels) or open-loop process gain (other integrating process) is obtained from the closed-loop data.

Keywords: closed-loop model identification, IMC-PID tuning method, integrating process control, on-line PID tuning adaptation

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17655 A Survey of Recognizing of Daily Living Activities in Multi-User Smart Home Environments

Authors: Kulsoom S. Bughio, Naeem K. Janjua, Gordana Dermody, Leslie F. Sikos, Shamsul Islam

Abstract:

The advancement in information and communication technologies (ICT) and wireless sensor networks have played a pivotal role in the design and development of real-time healthcare solutions, mainly targeting the elderly living in health-assistive smart homes. Such smart homes are equipped with sensor technologies to detect and record activities of daily living (ADL). This survey reviews and evaluates existing approaches and techniques based on real-time sensor-based modeling and reasoning in single-user and multi-user environments. It classifies the approaches into three main categories: learning-based, knowledge-based, and hybrid, and evaluates how they handle temporal relations, granularity, and uncertainty. The survey also highlights open challenges across various disciplines (including computer and information sciences and health sciences) to encourage interdisciplinary research for the detection and recognition of ADLs and discusses future directions.

Keywords: daily living activities, smart homes, single-user environment, multi-user environment

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17654 A Preparatory Method for Building Construction Implemented in a Case Study in Brazil

Authors: Aline Valverde Arroteia, Tatiana Gondim do Amaral, Silvio Burrattino Melhado

Abstract:

During the last twenty years, the construction field in Brazil has evolved significantly in response to its market growing and competitiveness. However, this evolving path has faced many obstacles such as cultural barriers and the lack of efforts to achieve quality at the construction site. At the same time, the greatest amount of information generated on the designing or construction phases is lost due to the lack of an effective coordination of these activities. Face this problem, the aim of this research was to implement a French method named PEO which means preparation for building construction (in Portuguese) seeking to understand the design management process and its interface with the building construction phase. The research method applied was qualitative, and it was carried out through two case studies in the city of Goiania, in Goias, Brazil. The research was divided into two stages called pilot study at Company A and implementation of PEO at Company B. After the implementation; the results demonstrated the PEO method's effectiveness and feasibility while a booster on the quality improvement of design management. The analysis showed that the method has a purpose to improve the design and allow the reduction of failures, errors and rework commonly found in the production of buildings. Therefore, it can be concluded that the PEO is feasible to be applied to real estate and building companies. But, companies need to believe in the contribution they can make to the discovery of design failures in conjunction with other stakeholders forming a construction team. The result of PEO can be maximized when adopting the principles of simultaneous engineering and insertion of new computer technologies, which use a three-dimensional model of the building with BIM process.

Keywords: communication, design and construction interface management, preparation for building construction (PEO), proactive coordination (CPA)

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17653 The Hyperbolic Smoothing Approach for Automatic Calibration of Rainfall-Runoff Models

Authors: Adilson Elias Xavier, Otto Corrêa Rotunno Filho, Paulo Canedo De Magalhães

Abstract:

This paper addresses the issue of automatic parameter estimation in conceptual rainfall-runoff (CRR) models. Due to threshold structures commonly occurring in CRR models, the associated mathematical optimization problems have the significant characteristic of being strongly non-differentiable. In order to face this enormous task, the resolution method proposed adopts a smoothing strategy using a special C∞ differentiable class function. The final estimation solution is obtained by solving a sequence of differentiable subproblems which gradually approach the original conceptual problem. The use of this technique, called Hyperbolic Smoothing Method (HSM), makes possible the application of the most powerful minimization algorithms, and also allows for the main difficulties presented by the original CRR problem to be overcome. A set of computational experiments is presented for the purpose of illustrating both the reliability and the efficiency of the proposed approach.

Keywords: rainfall-runoff models, automatic calibration, hyperbolic smoothing method

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17652 Performance Comparison of Non-Binary RA and QC-LDPC Codes

Authors: Ni Wenli, He Jing

Abstract:

Repeat–Accumulate (RA) codes are subclass of LDPC codes with fast encoder structures. In this paper, we consider a nonbinary extension of binary LDPC codes over GF(q) and construct a non-binary RA code and a non-binary QC-LDPC code over GF(2^4), we construct non-binary RA codes with linear encoding method and non-binary QC-LDPC codes with algebraic constructions method. And the BER performance of RA and QC-LDPC codes over GF(q) are compared with BP decoding and by simulation over the Additive White Gaussian Noise (AWGN) channels.

Keywords: non-binary RA codes, QC-LDPC codes, performance comparison, BP algorithm

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17651 Determination of Vitamin C (Ascorbic Acid) in Orange Juices Product

Authors: Wanida Wonsawat

Abstract:

This research describes a voltammetric approach to determine amounts of vitamin C (Ascorbic acid) in orange juice sample, using three screen printed electrode. The anodic currents of vitamin C were proportional to vitamin C concentration in the range of 0 – 10.0 mM with the limit of detection of 1.36 mM. The method was successfully employed with 2 µL of the working solution dropped on the electrode surface. The proposed method was applied for the analysis of vitamin C in packed orange juice without sample purification or complexion of sample preparation step.

Keywords: ascorbic acid, vitamin C, juice, voltammetry

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17650 Deep Learning Approaches for Accurate Detection of Epileptic Seizures from Electroencephalogram Data

Authors: Ramzi Rihane, Yassine Benayed

Abstract:

Epilepsy is a chronic neurological disorder characterized by recurrent, unprovoked seizures resulting from abnormal electrical activity in the brain. Timely and accurate detection of these seizures is essential for improving patient care. In this study, we leverage the UK Bonn University open-source EEG dataset and employ advanced deep-learning techniques to automate the detection of epileptic seizures. By extracting key features from both time and frequency domains, as well as Spectrogram features, we enhance the performance of various deep learning models. Our investigation includes architectures such as Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), 1D Convolutional Neural Networks (1D-CNN), and hybrid CNN-LSTM and CNN-BiLSTM models. The models achieved impressive accuracies: LSTM (98.52%), Bi-LSTM (98.61%), CNN-LSTM (98.91%), CNN-BiLSTM (98.83%), and CNN (98.73%). Additionally, we utilized a data augmentation technique called SMOTE, which yielded the following results: CNN (97.36%), LSTM (97.01%), Bi-LSTM (97.23%), CNN-LSTM (97.45%), and CNN-BiLSTM (97.34%). These findings demonstrate the effectiveness of deep learning in capturing complex patterns in EEG signals, providing a reliable and scalable solution for real-time seizure detection in clinical environments.

Keywords: electroencephalogram, epileptic seizure, deep learning, LSTM, CNN, BI-LSTM, seizure detection

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17649 Controller Design Using GA for SMC Systems

Authors: Susy Thomas, Sajju Thomas, Varghese Vaidyan

Abstract:

This paper considers SMCs using linear feedback with switched gains and proposes a method which can minimize the pole perturbation. The method is able to enhance the robustness property of the controller. A pre-assigned neighborhood of the ‘nominal’ positions is assigned and the system poles are not allowed to stray out of these bounds even when parameters variations/uncertainties act upon the system. A quasi SMM is maintained within the assigned boundaries of the sliding surface.

Keywords: parameter variations, pole perturbation, sliding mode control, switching surface, robust switching vector

Procedia PDF Downloads 366
17648 Application of a Hybrid QFD-FEA Methodology for Nigerian Garment Designs

Authors: Adepeju A. Opaleye, Adekunle Kolawole, Muyiwa A. Opaleye

Abstract:

Consumers’ perceived quality of imported product has been an impediment to business in the Nigeria garment industry. To improve patronage of made- in-Nigeria designs, the first step is to understand what the consumer expects, then proffer ways to meet this expectation through product redesign or improvement of the garment production process. The purpose of this study is to investigate drivers of consumers’ value for typical Nigerian garment design (NGD). An integrated quality function deployment (QFD) and functional, expressive and aesthetic (FEA) Consumer Needs methodology helps to minimize incorrect understanding of potential consumer’s requirements in mass customized garments. Six themes emerged as drivers of consumer’s satisfaction: (1) Style variety (2) Dimensions (3) Finishing (4) Fabric quality (5) Garment Durability and (6) Aesthetics. Existing designs found to lead foreign designs in terms of its acceptance for informal events, style variety and fit. The latter may be linked to its mode of acquisition. A conceptual model of NGD acceptance in the context of consumer’s inherent characteristics, social and the business environment is proposed.

Keywords: Perceived quality, Garment design, Quality function deployment, FEA Model , Mass customisation

Procedia PDF Downloads 138
17647 Generalization of Tau Approximant and Error Estimate of Integral Form of Tau Methods for Some Class of Ordinary Differential Equations

Authors: A. I. Ma’ali, R. B. Adeniyi, A. Y. Badeggi, U. Mohammed

Abstract:

An error estimation of the integrated formulation of the Lanczos tau method for some class of ordinary differential equations was reported. This paper is concern with the generalization of tau approximants and their corresponding error estimates for some class of ordinary differential equations (ODEs) characterized by m + s =3 (i.e for m =1, s=2; m=2, s=1; and m=3, s=0) where m and s are the order of differential equations and number of overdetermination, respectively. The general result obtained were validated with some numerical examples.

Keywords: approximant, error estimate, tau method, overdetermination

Procedia PDF Downloads 609
17646 Decision-Making Tool for Planning the Construction of Infrastructure Projects

Authors: Rolla Monib, Chris I. Goodier, Alistair Gibbs

Abstract:

The aim of this paper is to investigate the key drivers in planning the construction phase for infrastructure projects to reduce project delays. To achieve this aim, the research conducted three case studies using semi-structured and unstructured interviews (n=36). The results conclude that a lack of modularisation awareness is among the key factors attributed to project delays. The current emotive and ill-informed approach to decision-making, coupled with the lack of knowledge regarding appropriate construction method selection, prevents the potential benefits of modularisation being fully realised. To assist with decision-making for the best construction method, the research presents project management tools to help decision makers to choose the most appropriate construction approach through optimising the use of modularisation in EC. A decision-making checklist and diagram are presented in this paper. These checklist tools and diagrams assist the project team in determining the best construction method, taking into consideration the module type.

Keywords: infrastructure, modularization, decision support, decision-making

Procedia PDF Downloads 63