Search results for: skewed generalized error distribution

Authors: Heng Han, Zhilei Liang, Xiangong Zhou

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In this paper, the finite element method is used to study the temperature field of the main cable of the suspension bridge, and the calculation method of the average temperature of the cross-section of the main cable suitable for the construction control of the cable system is proposed; By comparing and analyzing the temperature field of the main cable with five diameters, a reasonable diameter limit for calculating the average temperature of the cross section of the main cable by finite element method is proposed. The results show that the maximum error of this method is less than 1℃, which meets the requirements of construction control accuracy; For the main cable with a diameter greater than 400mm, the surface temperature measuring points combined with the finite element method shall be used to calculate the average cross-section temperature.

Keywords: suspension bridge, main cable, temperature field, finite element

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Authors: Shahin A. Abdel-Naby, Asad T. Hassan

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Astrophysical plasma environments can be classified into collisionally ionized (CP) and photoionizedplasmas (PP). In the PP, ionization is caused by an external radiation field, while it is caused by electron collision in the CP. Accurate and reliable laboratory astrophysical data for electron-ion recombination is needed for plasma modeling for low and high-temperatures. Dielectronic recombination (DR) is the dominant recombination process for the CP for most of the ions. When a free electron is captured by an ion with simultaneous excitation of its core, a doubly-exited intermediate state may be formed. The doubly excited state relaxes either by electron emission (autoionization) or by radiative decay (photon emission). DR process takes place when the relaxation occurs to a bound state by a photon emission. DR calculations at low-temperatures are problematic and challenging since small uncertaintiesin the low-energy DR resonance positions can produce huge uncertainties in DR rate coefficients.DR rate coefficients for N²⁺ and O³⁺ ions are calculated using state-of-the-art multi-configurationBreit-Pauli atomic structure AUTOSTRUCTURE collisional package within the generalized collisional-radiative framework. Level-resolved calculations for RR and DR rate coefficients from the ground and metastable initial states are produced in an intermediate coupling scheme associated withn = 0 and n = 1 core-excitations. DR cross sections for these ions are convoluted with the experimental electron-cooler temperatures to produce DR rate coefficients. Good agreements are foundbetween these rate coefficients and theexperimental measurements performed at CRYRING heavy-ionstorage ring for both ions.

Keywords: atomic data, atomic process, electron-ion collision, plasmas

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Authors: M. I. Youssef, A. E. Emam, M. Abd Elghany

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The performance of wireless communication systems is affected mainly by the environment of its associated channel, which is characterized by dynamic and unpredictable behavior. In this paper, different statistical earth-satellite channel models are studied with emphasize on two main models, first is the Rice-Log normal model, due to its representation for the environment including shadowing and multi-path components that affect the propagated signal along its path, and a three-state model that take into account different fading conditions (clear area, moderate shadow and heavy shadowing). The provided models are based on AWGN, Rician, Rayleigh, and log-normal distributions were their Probability Density Functions (PDFs) are presented. The transmission system Bit Error Rate (BER), Peak-Average-Power Ratio (PAPR), and the channel capacity vs. fading models are measured and analyzed. These simulations are implemented using MATLAB tool, and the results had shown the performance of transmission system over different channel models.

Keywords: fading channels, MIMO communication, RNS scheme, statistical modeling

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Authors: Ravi Kumar, Santhosh Kumar Dubba

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This paper presents an experimental study of a diabatic flow of R-600a through a concentric configured capillary tube suction line heat exchanger. The details of experimental facility for testing the diabatic capillary tube with different inlet sub-cooling degree and pressure are discussed. The effect of coil diameter, capillary length, capillary tube diameter, sub-cooling degree and inlet pressure on mass flow rate are presented. The degree of sub-cooling at the inlet of capillary tube is varied from 3-20°C. The refrigerant mass flow rate is scattered up with rising of pressure. A semi-empirical correlation to predict the mass flow rate of R-600a flowing through a diabatic capillary tube is proposed for sub-cooled inlet conditions. The proposed correlation predicts measured data with an error band of ±20 percent.

Keywords: diabatic, capillary tube, concentric, R-600a

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Authors: James Purnama, Riri Fitri Sari

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We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods.

Keywords: gaze estimation, gaze tracking, eye tracking, kinect, regression model, orange python

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Authors: Apolinar Picado, Ronald Solís, Rafael Gamero

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The thin-layer drying characteristics of instant coffee solution were investigated in a laboratory tunnel dryer. Drying experiments were carried out at three temperatures (80, 100 and 120 °C) and an air velocity of 1.2 m/s. Drying experimental data obtained are fitted to six (6) thin-layer drying models using the non-linear least squares regression analysis. The acceptability of the thin-layer drying model has been based on a value of the correlation coefficient that should be close to one, and low values for root mean square error (RMSE) and chi-square (x²). According to this evaluation, the most suitable model for describing drying process of thin-layer instant coffee solution is the Page model. Further, the effective moisture diffusivity and the activation energy were computed employing the drying experimental data. The effective moisture diffusivity values varied from 1.6133 × 10⁻⁹ to 1.6224 × 10⁻⁹ m²/s over the temperature range studied and the activation energy was estimated to be 162.62 J/mol.

Keywords: activation energy, diffusivity, instant coffee, thin-layer models

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Authors: Fernando P. Silva, Valter J. S. Leite, Erivelton G. Nepomuceno

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In this paper, a nonlinear controller design for an omnidirectional mobile is presented. The robot controller consists of an inner-loop controller and an outer-loop controller, the first is designed using state feedback (robust allocation) and the second controller is designed based on Robust Multi Inversion (RMI) approach. The objective of RMI controller is rendering the robust inversion of the dynamic, when the model is affected by uncertainties. A model nonlinear MIMO of an omni-directional robot (small-league of Robocup) is used to simulate the RMI approach. The parameters of linear and nonlinear model are varied to cause modelling uncertainties among the model and the real model (real system) generating an error in inner-loop controller signal that must be compensated by RMI controller. The simulation test results show that the RMI is capable of compensating the uncertainties and keep the system stable and controlled under uncertainties.

Keywords: robust multi inversion, omni-directional robot, robocup, nonlinear control

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Authors: Huseyn Nuraddin Qurbanov

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The reliable food supply of the population of the republic is one of the main directions of the state's economic policy. Grain growing, which is the basis of agriculture, is important in this area. In the cultivation of cereals on the slopes, the application of equal amounts of mineral fertilizers the under the soil before sowing is a very important technological process. The low level of technical equipment in this area prevents producers from providing the country with the necessary quality cereals. Experience in the operation of modern technical means has shown that, at present, there is a need to provide an equal amount of fertilizer on the slopes to under the soil, fully meeting the agro-technical requirements. No fundamental changes have been made to the industrial machines that fertilize the under the soil, and unequal application of fertilizers under the soil on the slopes has been applied. This technological process leads to the destruction of new seedlings and reduced productivity due to intolerance to frost during the winter for the plant planted in the fall. In special climatic conditions, there is an optimal fertilization rate for each agricultural product. The application of fertilizers to the soil is one of the conditions that increase their efficiency in the field. As can be seen, the development of a new technical proposal for fertilizing and plowing the slopes in equal amounts on the slopes, improving the technological and design parameters, and taking into account the physical and mechanical properties of fertilizers is very important. Taking into account the above-mentioned issues, a combined plough was developed in our laboratory. Combined plough carries out pre-sowing technological operation in the cultivation of cereals, providing a smooth equal amount of mineral fertilizers under the soil on the slopes. Mathematical models of a smooth spreader that evenly distributes fertilizers in the field have been developed. Thus, diagrams and graphs obtained without distribution on the 8 partitions of the smooth spreader are constructed under the inclined angles of the slopes. Percentage and productivity of equal distribution in the field were noted by practical and theoretical analysis.

Keywords: combined plough, mineral fertilizer, equal sowing, fertilizer norm, grain-crops, sowing fertilizer

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Authors: Li Zhang, Yuehong Su

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Lightpipe as a mature solar light tube technique has been employed worldwide. Accurately assessing the performance of lightpipe and evaluate daylighting available has been a challenging topic. Previous research had used regression model and computational simulation methods to estimate the performance of lightpipe. However, due to the nonlinear nature of solar light transferring in lightpipe, the methods mentioned above express inaccurate and time-costing issues. In the present study, a neural network model as an alternative method is investigated to predict the transmittance of lightpipe. Four types of commercial lightpipe with bended angle 0°, 30°, 45° and 60° are discussed under clear, intermediate and overcast sky conditions respectively. The neural network is generated in MATLAB by using the outcomes of an optical software Photopia simulations as targets for networks training and testing. The coefficient of determination (R²) for each model is higher than 0.98, and the mean square error (MSE) is less than 0.0019, which indicate the neural network strong predictive ability and the use of the neural network method could be an efficient technique for determining the performance of lightpipe.

Keywords: neural network, bended lightpipe, transmittance, Photopia

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Authors: Wayan Widhiada, Cok Indra Partha, Gusti Ngurah Nitya Santhiarsa

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The purpose of this paper is to investigate the sophistication of the use of Proportional Integral and Derivative Control to control the kinematic motion of the mobile robot manipulator. Simulation and experimental methods will be used to investigate the sophistication of PID control to control the mobile robot arm in the collection and placement of several kinds of objects quickly, accurately and correctly. Mathematical modeling will be done by utilizing the integration of Solidworks and MATLAB / Simmechanics software. This method works by converting the physical model file into the xml file. This method is easy, fast and accurate done in modeling and design robotics. The automatic control design of this robot manipulator will be validated in simulations and experimental in control labs as evidence that the mobile robot manipulator gripper control design can achieve the best performance such as the error signal is lower than 5%, small overshoot and get steady signal response as quickly.

Keywords: control analysis, kinematics motion, mobile robot manipulator, performance

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Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

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Authors: Haniye Dehestani, Yadollah Ordokhani

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In this work, we present an efficient approach for solving variable-order time-fractional partial differential equations, which are based on Legendre and Laguerre polynomials. First, we introduced the pseudo-operational matrices of integer and variable fractional order of integration by use of some properties of Riemann-Liouville fractional integral. Then, applied together with collocation method and Legendre-Laguerre functions for solving variable-order time-fractional partial differential equations. Also, an estimation of the error is presented. At last, we investigate numerical examples which arise in physics to demonstrate the accuracy of the present method. In comparison results obtained by the present method with the exact solution and the other methods reveals that the method is very effective.

Keywords: collocation method, fractional partial differential equations, legendre-laguerre functions, pseudo-operational matrix of integration

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Authors: Belkacem Laimouche

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With the field of artificial intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, interlaboratory comparison, data analysis, data reliability, measurement of bias impact on predictions, improvement of model accuracy and reliability

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Authors: Yassine Sadji

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Some architectural conditions required some shapes often lead to an irregular distribution of masses, rigidities, and resistances. The main object of the present study consists in estimating the influence of the irregularity both in plan and in elevation which presenting some structures on the dynamic characteristics and his influence on the behavior of this structures. To do this, it is necessary to make apply both dynamic methods proposed by the RPA99 (spectral modal method and method of analysis by accélérogramme) on certain similar prototypes and to analyze the parameters measuring the answer of these structures and to proceed to a comparison of the results.

Keywords: irregularity, seismic, response, structure, ductility

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Authors: Osarobo Omorogieva Ighodaro, Josephus Otejere

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This paper contains the modelling and simulation of GT13E2 combined cycle gas turbine with the aid of the software EBSILON PROFESSIONAL. The design mode was modeled using guaranteed performance data from the power plant, in the off design, temperature variation of ambient air and fogging (spray water at inlet to compressor) was simulated. The fogging was simulated under two different modes; constant fuel consumption and constant turbine exhaust temperature .The model results were validated using actual operating data by applying error percentage analysis. The validation results obtained ranged from -0.0038% to 0% in design condition while the results varied from -0.9202% to 10.24% The model shows that fogging decreases compressor inlet temperature which in turn decreases the power required to drive the compressor hence improving the simple cycle efficiency and hence increasing power generated.

Keywords: inlet fogging, off design, combined cycle, modelling

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Authors: H. Barati, M. Wu, A. Kharicha, A. Ludwig

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A transient model for nozzle clogging has been developed and successfully validated against a laboratory experiment. Key steps of clogging are considered: transport of particles by turbulent flow towards the nozzle wall; interactions between fluid flow and nozzle wall, and the adhesion of the particle on the wall; the growth of the clog layer and its interaction with the flow. The current paper is to investigate the mesh (size and type) sensitivity of the model in both two and three dimensions. It is found that the algorithm for clog growth alone excluding the flow effect is insensitive to the mesh type and size, but the calculation including flow becomes sensitive to the mesh quality. The use of 2D meshes leads to overestimation of the clog growth because the 3D nature of flow in the boundary layer cannot be properly solved by 2D calculation. 3D simulation with tetrahedron mesh can also lead to an error estimation of the clog growth. A mesh-independent result can be achieved with hexahedral mesh, or at least with triangular prism (inflation layer) for near-wall regions.

Keywords: clogging, continuous casting, inclusion, simulation, submerged entry nozzle

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Authors: Shubham Jaiswal

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During modeling of transport phenomena in porous media, many nonlinear partial differential equations (NPDEs) encountered which greatly described the convection, diffusion and reaction process. To solve such types of nonlinear problems, a reliable and efficient technique is needed. In this article, the numerical solution of NPDEs encountered in porous media is derived. Here Jacobi collocation method is used to solve the considered problems which convert the NPDEs in systems of nonlinear algebraic equations that can be solved using Newton-Raphson method. The numerical results of some illustrative examples are reported to show the efficiency and high accuracy of the proposed approach. The comparison of the numerical results with the existing analytical results already reported in the literature and the error analysis for each example exhibited through graphs and tables confirms the exponential convergence rate of the proposed method.

Keywords: nonlinear porous media equation, shifted Jacobi polynomials, operational matrix, spectral collocation method

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Authors: Saba Rahman, Arvind K. Jain, S. D. Bharti, T. K. Datta

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Chimneys are generally tall and slender structures with circular cross-sections, due to which they are highly prone to wind forces. Wind exerts pressure on the wall of the chimneys, which produces unwanted forces. Vortex-induced oscillation is one of such excitations which can lead to the failure of the chimneys. Therefore, vortex-induced oscillation of chimneys is of great concern to researchers and practitioners since many failures of chimneys due to vortex shedding have occurred in the past. As a consequence, extensive research has taken place on the subject over decades. Many laboratory experiments have been performed to verify the theoretical models proposed to predict vortex-induced forces, including aero-elastic effects. Comparatively, very few proto-type measurement data have been recorded to verify the proposed theoretical models. Because of this reason, the theoretical models developed with the help of experimental laboratory data are utilized for analyzing the chimneys for vortex-induced forces. This calls for reliability analysis of the predictions of the responses of the chimneys produced due to vortex shedding phenomena. Although several works of literature exist on the vortex-induced oscillation of chimneys, including code provisions, the reliability analysis of chimneys against failure caused due to vortex shedding is scanty. In the present study, the reliability analysis of chimneys against vortex shedding failure is presented, assuming the uncertainty in vortex shedding phenomena to be significantly more than other uncertainties, and hence, the latter is ignored. The vortex shedding is modeled as a stationary random process and is represented by a power spectral density function (PSDF). It is assumed that the vortex shedding forces are perfectly correlated and act over the top one-third height of the chimney. The PSDF of the tip displacement of the chimney is obtained by performing a frequency domain spectral analysis using a matrix approach. For this purpose, both chimney and random wind forces are discretized over a number of points along with the height of the chimney. The method of analysis duly accounts for the aero-elastic effects. The double barrier threshold crossing level, as proposed by Vanmarcke, is used for determining the probability of crossing different threshold levels of the tip displacement of the chimney. Assuming the annual distribution of the mean wind velocity to be a Gumbel type-I distribution, the fragility curve denoting the variation of the annual probability of threshold crossing against different threshold levels of the tip displacement of the chimney is determined. The reliability estimate is derived from the fragility curve. A 210m tall concrete chimney with a base diameter of 35m, top diameter as 21m, and thickness as 0.3m has been taken as an illustrative example. The terrain condition is assumed to be that corresponding to the city center. The expression for the PSDF of the vortex shedding force is taken to be used by Vickery and Basu. The results of the study show that the threshold crossing reliability of the tip displacement of the chimney is significantly influenced by the assumed structural damping and the Gumbel distribution parameters. Further, the aero-elastic effect influences the reliability estimate to a great extent for small structural damping.

Keywords: chimney, fragility curve, reliability analysis, vortex-induced vibration

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Authors: Marco Avila Lopez, Hasnae Ait-Douchi, Silvia De Los Santos, Badr Eddine Lebrouhi, Pamela Ramírez Vidal

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In the context of the energy transition, fuel cell technology has emerged as a solution for harnessing hydrogen energy and mitigating greenhouse gas emissions. An in-depth study was conducted on a PEMFC-type fuel cell, with an initiation of an analysis of its operational principles and constituent components. Subsequently, the modelling of the fuel cell was undertaken using the Python programming language, encompassing both steady-state and transient regimes. In the case of the steady-state regime, the physical and electrochemical phenomena occurring within the fuel cell were modelled, with the assumption of uniform temperature throughout all cell compartments. Parametric identification was carried out, resulting in a remarkable mean error of only 1.62% when the model results were compared to experimental data documented in the literature. The dynamic model that was developed enabled the scrutiny of the fuel cell's response in terms of temperature and voltage under varying current conditions.

Keywords: fuel cell, modelling, dynamic, thermal model, PEMFC

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Authors: N. Ploysook, R. Rugsaj, C. Suvanjumrat

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The characteristic requirement for producing rectangular shape bottles was a uniform thickness of the plastic bottle wall. Die shaping was a good technique which controlled the wall thickness of bottles. An advance technology which was the finite element method (FEM) for blowing parison to be a rectangular shape bottle was conducted to reduce waste plastic from a trial and error method of a die shaping and parison control method. The artificial intelligent (AI) comprised of artificial neural network and genetic algorithm was selected to optimize the die gap shape from the FEM results. The application of AI technique could optimize the suitable die gap shape for the parison blow molding which did not depend on the parison control method to produce rectangular bottles with the uniform wall. Particularly, this application can be used with cheap blow molding machines without a parison controller therefore it will reduce cost of production in the bottle blow molding process.

Keywords: AI, bottle, die shaping, FEM

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Authors: Rana I. Abdulghani, Amera I. Melhum

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With the abnormal growth of the usage of computers over networks and under the consideration or agreement of most of the computer security experts who said that the goal of building a secure system is never achieved effectively, all these points led to the design of the intrusion detection systems(IDS). This research adopts a comparison between two techniques for network intrusion detection, The first one used the (Particles Swarm Optimization) that fall within the field (Swarm Intelligence). In this Act, the algorithm Enhanced for the purpose of obtaining the minimum error rate by amending the cluster centers when better fitness function is found through the training stages. Results show that this modification gives more efficient exploration of the original algorithm. The second algorithm used a (Back propagation NN) algorithm. Finally a comparison between the results of two methods used were based on (NSL_KDD) data sets for the construction and evaluation of intrusion detection systems. This research is only interested in clustering the two categories (Normal and Abnormal) for the given connection records. Practices experiments result in intrude detection rate (99.183818%) for EPSO and intrude detection rate (69.446416%) for BP neural network.

Keywords: IDS, SI, BP, NSL_KDD, PSO

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Authors: R. Khenata, T. Djied, R. Ahmed, H. Baltache, S. Bin-Omran, A. Bouhemadou

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We predict structural, phase transition as well as opto-electronic properties of the filled-tetrahedral (Nowotny-Juza) NaZnAs compound in this study. Calculations are carried out by employing the full potential (FP) linearized augmented plane wave (LAPW) plus local orbitals (lo) scheme developed within the structure of density functional theory (DFT). Exchange-correlation energy/potential (EXC/VXC) functional is treated using Perdew-Burke and Ernzerhof (PBE) parameterization for generalized gradient approximation (GGA). In addition to Trans-Blaha (TB) modified Becke-Johnson (mBJ) potential is incorporated to get better precision for optoelectronic properties. Geometry optimization is carried out to obtain the reliable results of the total energy as well as other structural parameters for each phase of NaZnAs compound. Order of the structural transitions as a function of pressure is found as: Cu2Sb type → β → α phase in our study. Our calculated electronic energy band structures for all structural phases at the level of PBE-GGA as well as mBJ potential point out; NaZnAs compound is a direct (Γ–Γ) band gap semiconductor material. However, as compared to PBE-GGA, mBJ potential approximation reproduces higher values of fundamental band gap. Regarding the optical properties, calculations of real and imaginary parts of the dielectric function, refractive index, reflectivity coefficient, absorption coefficient and energy loss-function spectra are performed over a photon energy ranging from 0.0 to 30.0 eV by polarizing incident radiation in parallel to both [100] and [001] crystalline directions.

Keywords: NaZnAs, FP-LAPW+lo, structural properties, phase transition, electronic band-structure, optical properties

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Authors: Annie Gedion, Johan Severinus Tati, Jacinta Caroline Peter

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Syntax error analysis studies have a significant role in English language teaching especially in the second language. This study investigates the syntax errors in written composition by 50 multilingual ESL learners in Politeknik Kota Kinabalu Sabah, Malaysia. The subjects speak their own dialect, Malay as their second language and English as their third or foreign language. Data were collected from the written discourse in the form of descriptive essays. The subjects were asked to write in the classroom within 45 minutes. 15 categories of errors were classified into a set of syntactic categories and were analysed based on the five steps of the syntactic analysis procedure. The findings of the study showed that the mother tongue interference, as well as lack of vocabulary and grammar knowledge, were the major sources of syntax errors in the learners’ written composition. Learners should be exposed to the differentiation of Malay and English grammar to avoid interference and effective learning of second language writing.

Keywords: errors analysis, syntactic analysis, English as a second language, ESL writing

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Authors: Sabrina Azzi, Michal Iglewski, Véronique Nabelsi

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Diagnosis error problem is frequent and one of the most important safety problems today. One of the main objectives of our work is to propose an ontological representation that takes into account the diagnostic criteria in order to improve the diagnostic. We choose pneumonia disease since it is one of the frequent diseases affected by diagnosis errors and have harmful effects on patients. To achieve our aim, we use a semi-automated method to integrate diverse knowledge sources that include publically available pneumonia disease guidelines from international repositories, biomedical ontologies and electronic health records. We follow the principles of the Open Biomedical Ontologies (OBO) Foundry. The resulting ontology covers symptoms and signs, all the types of pneumonia, antecedents, pathogens, and diagnostic testing. The first evaluation results show that most of the terms are covered by the ontology. This work is still in progress and represents a first and major step toward a development of a diagnosis decision support system for pneumonia.

Keywords: Clinical decision support system, Diagnostic errors, Ontology, Pneumonia

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Authors: Moses Aron, Elias Mwakilama, Jimmy Namangale

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Spending more time on long queues for a basic service remains a common challenge to most developing countries, including Malawi. For health sector in particular, Out-Patient Department (OPD) experiences long queues. This puts the lives of patients at risk. However, using queuing analysis to under the nature of the problems and efficiency of service systems, such problems can be abated. Based on a kind of service, literature proposes different possible queuing models. However, unlike using generalized assumed models proposed by literature, use of real time case study data can help in deeper understanding the particular problem model and how such a model can vary from one day to the other and also from each case to another. As such, this study uses data obtained from one urban HC for BP, Pediatric and General OPD cases to investigate an average queuing time for patients within the system. It seeks to highlight the proper queuing model by investigating the kind of distributions functions over patient’s arrival time, inter-arrival time, waiting time and service time. Comparable with the standard set values by WHO, the study found that patients at this HC spend more waiting times than service times. On model investigation, different days presented different models ranging from an assumed M/M/1, M/M/2 to M/Er/2. As such, through sensitivity analysis, in general, a commonly assumed M/M/1 model failed to fit the data but rather an M/Er/2 demonstrated to fit well. An M/Er/3 model seemed to be good in terms of measuring resource utilization, proposing a need to increase medical personnel at this HC. However, an M/Er/4 showed to cause more idleness of human resources.

Keywords: health care, out-patient department, queuing model, sensitivity analysis

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Authors: Justin Reverdi, Sixin Zhang, Serge Gratton, Said Aoues, Thomas Pellegrini

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In Vapor Cycle Systems, the flow sensor plays a key role in different monitoring and control purposes. However, physical sensors can be expensive, inaccurate, heavy, cumbersome, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor based on other standard sensors is a good alternative. In this paper, a data-driven model using a Convolutional Neural Network is proposed to estimate the flow of the compressor. To fit the model to our dataset, we tested different loss functions. We show in our application that a Dynamic Time Warping based loss function called DILATE leads to better dynamical performance than the vanilla mean squared error (MSE) loss function. DILATE allows choosing a trade-off between static and dynamic performance.

Keywords: deep learning, dynamic time warping, vapor cycle system, virtual sensor

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Authors: Umit Duru

Abstract:

The Soil and Water Assessment Tool (SWAT) was tested for prediction of water balance and sediment yield in the Ankara gauged basin, Turkey. The overall objective of this study was to evaluate the performance and applicability of the SWAT in this region of Turkey. Thirteen years of monthly stream flow, and suspended sediment, data were used for calibration and validation. This research assessed model performance based on differences between observed and predicted suspended sediment yield during calibration (1987-1996) and validation (1982-1984) periods. Statistical comparisons of suspended sediment produced values for NSE (Nash Sutcliffe efficiency), RE (relative error), and R² (coefficient of determination), of 0.81, -1.55, and 0.93, respectively, during the calibration period, and NSE, RE (%), and R² of 0.77, -2.61, and 0.87, respectively, during the validation period. Based on the analyses, SWAT satisfactorily simulated observed hydrology and sediment yields and can be used as a tool in decision making for water resources planning and management in the basin.

Keywords: calibration, GIS, sediment yield, SWAT, validation

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Authors: Shaikah Alsubayae, Gianluigi Casse, Carlos Chavez, Jon Taylor, Alan Taylor, Mohammad Alsulimane

Abstract:

Achieving precise radiotherapy through carbon therapy necessitates the accurate monitoring of radiation dose distribution within the patient's body. This process is pivotal for targeted tumor treatment, minimizing harm to healthy tissues, and enhancing overall treatment effectiveness while reducing the risk of side effects. In our investigation, we adopted a methodological approach to monitor secondary proton doses in carbon therapy using Monte Carlo (MC) simulations. Initially, Geant4 simulations were employed to extract the initial positions of secondary particles generated during interactions between carbon ions and water, including protons, gamma rays, alpha particles, neutrons, and tritons. Subsequently, we explored the relationship between the carbon ion beam and these secondary particles. Interaction vertex imaging (IVI) proves valuable for monitoring dose distribution during carbon therapy, providing information about secondary particle locations and abundances, particularly protons. The IVI method relies on charged particles produced during ion fragmentation to gather range information by reconstructing particle trajectories back to their point of origin, known as the vertex. In the context of carbon ion therapy, our simulation results indicated a strong correlation between some secondary particles and the range of carbon ions. However, challenges arose due to the unique elongated geometry of the target, hindering the straightforward transmission of forward-generated protons. Consequently, the limited protons that did emerge predominantly originated from points close to the target entrance. Fragment (protons) trajectories were approximated as straight lines, and a beam back-projection algorithm, utilizing interaction positions recorded in Si detectors, was developed to reconstruct vertices. The analysis revealed a correlation between the reconstructed and actual positions.

Keywords: radiotherapy, carbon therapy, monitor secondary proton doses, interaction vertex imaging

Procedia PDF Downloads 78

Authors: The Danh Phan

Abstract:

House price forecasting is a main topic in the real estate market research. Effective house price prediction models could not only allow home buyers and real estate agents to make better data-driven decisions but may also be beneficial for the property policymaking process. This study investigates the housing market by using machine learning techniques to analyze real historical house sale transactions in Australia. It seeks useful models which could be deployed as an application for house buyers and sellers. Data analytics show a high discrepancy between the house price in the most expensive suburbs and the most affordable suburbs in the city of Melbourne. In addition, experiments demonstrate that the combination of Stepwise and Support Vector Machine (SVM), based on the Mean Squared Error (MSE) measurement, consistently outperforms other models in terms of prediction accuracy.

Keywords: house price prediction, regression trees, neural network, support vector machine, stepwise

Procedia PDF Downloads 231

Authors: Mahmoudi Noureddine

Abstract:

In this study the use of two variable refined plate theories of laminated composite plates to static response of laminated plates. The plate theory accounts for parabolic distribution of the transverse shear strains, and satisfies the zero traction boundary conditions on the surfaces of the plate without using shear correction factor. The validity of the present theory is demonstrated by comparison with solutions available in the literature and finite element method. The result is presented for the static response of simply supported rectangular plates under uniform sinusoidal mechanical loadings.

Keywords: bending, composite, laminate, plates, fem

Procedia PDF Downloads 406