Search results for: smoothing spline method

Authors: Paolo Sassi, Jorge Freiria, Gabriel Usera

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In this work, a finite volume fluid flow solver is coupled with a discrete element method module for the simulation of the dynamics of free and elastic bodies in interaction with the fluid and between themselves. The open source fluid flow solver, caffa3d.MBRi, includes the capability to work with nested overlapping grids in order to easily refine the grid in the region where the bodies are moving. To do so, it is necessary to implement a recognition function able to identify the specific mesh block in which the device is moving in. The set of overlapping finer grids might be displaced along with the set of bodies being simulated. The interaction between the bodies and the fluid is computed through a two-way coupling. The velocity field of the fluid is first interpolated to determine the drag force on each object. After solving the objects displacements, subject to the elastic bonding among them, the force is applied back onto the fluid through a Gaussian smoothing considering the cells near the position of each object. The fishnet is represented as lumped masses connected by elastic lines. The internal forces are derived from the elasticity of these lines, and the external forces are due to drag, gravity, buoyancy and the load acting on each element of the system. When solving the ordinary differential equations system, that represents the motion of the elastic and flexible bodies, it was found that the Runge Kutta solver of fourth order is the best tool in terms of performance, but requires a finer grid than the fluid solver to make the system converge, which demands greater computing power. The coupled solver is demonstrated by simulating the interaction between the fluid, an elastic fishnet and a set of free bodies being captured by the net as they are dragged by the fluid. The deformation of the net, as well as the wake produced in the fluid stream are well captured by the method, without requiring the fluid solver mesh to adapt for the evolving geometry. Application of the same strategy to the simulation of elastic structures subject to the action of wind is also possible with the method presented, and one such application is currently under development.

Keywords: computational fluid dynamics, discrete element method, fishnets, nested overlapping grids

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Authors: Shan Jia, Jinbao Chen, Jinhua Zhou, Jiacheng Qian

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In response to the functional limitations of the fixed landers, those are to expand the detection range by the use of wheeled rovers with unavoidable path-repeatability in deep space exploration currently, a movable lander based on the leg-foot walking mechanism is presented. Firstly, a quadruped landing mechanism based on pushrod-damping is proposed. The configuration is of the bionic characteristics such as hip, knee and ankle joints, and the multi-function main/auxiliary buffers based on the crumple-energy absorption and screw-nut mechanism. Secondly, the workspace of the end of the leg-foot mechanism is solved by Monte Carlo method, and the key points on the desired trajectory of the end of the leg-foot mechanism are fitted by cubic spline curve. Finally, an optimal time-jerk trajectory based on weight coefficient is planned and analyzed by an adaptive genetic algorithm (AGA). The simulation results prove the rationality and stability of walking motion of the movable leg-foot lander in the star catalogue. In addition, this research can also provide a technical solution integrating of soft-landing, large-scale inspection and material transfer for future star catalogue exploration, and can even serve as the technical basis for developing the reusable landers.

Keywords: motion performance, trajectory planning, movable, leg-foot lander

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Authors: Chaluntorn Vichasilp, Sutee Wangtueai

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This study aims to develop a new method to detect active compounds in Thai herbs (1-deoxynojirimycin (DNJ) in mulberry leave, anthocyanin in Mao and curcumin in turmeric) using near infrared spectroscopy (NIRs). NIRs is non-destructive technique that rapid, non-chemical involved and low-cost determination. By NIRs and chemometrics technique, it was found that the DNJ prediction equation conducted with partial least square regression with cross-validation had low accuracy R2 (0.42) and SEP (31.87 mg/100g). On the other hand, the anthocyanin prediction equation showed moderate good results (R2 and SEP of 0.78 and 0.51 mg/g) with Multiplication scattering correction at wavelength of 2000-2200 nm. The high absorption could be observed at wavelength of 2047 nm and this model could be used as screening level. For curcumin prediction, the good result was obtained when applied original spectra with smoothing technique. The wavelength of 1400-2500 nm was created regression model with R2 (0.68) and SEP (0.17 mg/g). This model had high NIRs absorption at a wavelength of 1476, 1665, 1986 and 2395 nm, respectively. NIRs showed prospective technique for detection of some active compounds in Thai herbs.

Keywords: anthocyanin, curcumin, 1-deoxynojirimycin (DNJ), near infrared spectroscopy (NIRs)

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Authors: Mahdieh Farzin Asanjan, Erkan Unal Mumcuoglu

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Mitochondria are cytoplasmic organelles of the cell, which have a significant role in the variety of cellular metabolic functions. Mitochondria act as the power plants of the cell and are surrounded by two membranes. Significant morphological alterations are often due to changes in mitochondrial functions. A powerful technique in order to study the three-dimensional (3D) structure of mitochondria and its alterations in disease states is Electron microscope tomography. Detection of mitochondria in electron microscopy images due to the presence of various subcellular structures and imaging artifacts is a challenging problem. Another challenge is that each image typically contains more than one mitochondrion. Hand segmentation of mitochondria is tedious and time-consuming and also special knowledge about the mitochondria is needed. Fully automatic segmentation methods lead to over-segmentation and mitochondria are not segmented properly. Therefore, semi-automatic segmentation methods with minimum manual effort are required to edit the results of fully automatic segmentation methods. Here two editing tools were implemented by applying spline surface dragging and interactive live-wire segmentation tools. These editing tools were applied separately to the results of fully automatic segmentation. 3D extension of these tools was also studied and tested. Dice coefficients of 2D and 3D for surface dragging using splines were 0.93 and 0.92. This metric for 2D and 3D for live-wire method were 0.94 and 0.91 respectively. The root mean square symmetric surface distance values of 2D and 3D for surface dragging was measured as 0.69, 0.93. The same metrics for live-wire tool were 0.60 and 2.11. Comparing the results of these editing tools with the results of automatic segmentation method, it shows that these editing tools, led to better results and these results were more similar to ground truth image but the required time was higher than hand-segmentation time

Keywords: medical image segmentation, semi-automatic methods, transmission electron microscopy, surface dragging using splines, live-wire

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Authors: Jun Su Park, Byung Kwan Oh, Jin Woo Hwang, Yousok Kim, Hyo Seon Park

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For the structural safety, the maximum stress calculated from the stress distribution of a structure is widely used. The stress distribution can be estimated by deformed shape of the structure obtained from measurement. Although the estimation of stress is strongly affected by the location and number of sensing points, most studies have conducted the stress estimation without reasonable basis on sensing plan such as the location and number of sensors. In this paper, an optimal sensing technique for estimating the stress distribution is proposed. This technique proposes the optimal location and number of sensing points for a 2-D frame structure while minimizing the error of stress distribution between analytical model and estimation by cubic smoothing splines using genetic algorithm. To verify the proposed method, the optimal sensor measurement technique is applied to simulation tests on 2-D steel frame structure. The simulation tests are performed under various loading scenarios. Through those tests, the optimal sensing plan for the structure is suggested and verified.

Keywords: genetic algorithm, optimal sensing, optimizing sensor placements, steel frame structure

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Authors: Muhammad Jawwad, Riffat Iqbal

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The Socratic method, also known as the dialectical method and elenctic method, has significant relevance in the contemporary educational system. It can be incorporated into modern-day educational systems theoretically as well as practically. Being interactive and dialogue-based in nature, this teaching approach is followed by critical thinking and innovation. The pragmatic value of the Dialectical Method has been discussed in this article, and the limitations of the Socratic method have also been highlighted. The interactive Method of Socrates can be used in many subjects for students of different grades. The Limitations and delimitations of the Method have also been discussed for its proper implementation. This article has attempted to elaborate and analyze the teaching method of Socrates with all its pre-suppositions and Epistemological character.

Keywords: Socratic method, dialectical method, knowledge, teaching, virtue

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Authors: Salihah Alghamdi, Surajit Ray

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Space-time data can be observed over irregularly shaped manifolds, which might have complex boundaries or interior gaps. Most of the existing methods do not consider the shape of the data, and as a result, it is difficult to model irregularly shaped data accommodating the complex domain. We used a method that can deal with space-time data that are distributed over non-planner shaped regions. The method is based on partial differential equations and finite element analysis. The model can be estimated using a penalized least squares approach with a regularization term that controls the over-fitting. The model is regularized using two roughness penalties, which consider the spatial and temporal regularities separately. The integrated square of the second derivative of the basis function is used as temporal penalty. While the spatial penalty consists of the integrated square of Laplace operator, which is integrated exclusively over the domain of interest that is determined using finite element technique. In this paper, we applied a spatio-temporal regression model with partial differential equations regularization (ST-PDE) approach to analyze a remote sensing data measuring the greenness of vegetation, measure by an index called enhanced vegetation index (EVI). The EVI data consist of measurements that take values between -1 and 1 reflecting the level of greenness of some region over a period of time. We applied (ST-PDE) approach to irregular shaped region of the EVI data. The approach efficiently accommodates the irregular shaped regions taking into account the complex boundaries rather than smoothing across the boundaries. Furthermore, the approach succeeds in capturing the temporal variation in the data.

Keywords: irregularly shaped domain, partial differential equations, finite element analysis, complex boundray

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Authors: Ramin Vafadary, Maryam Khanbaghi

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Forecasting electricity load is important for various purposes like planning, operation, and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet, and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria, namely, the mean absolute error and root mean square error. The National Renewable Energy Laboratory (NREL) residential energy consumption data is used to train the models. The results of this study show that the SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts, we can improve the robustness of the models for 24 hours ahead of electricity load forecasting.

Keywords: bagging, Fbprophet, Holt-Winters, LSTM, load forecast, SARIMA, TensorFlow probability, time series

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Authors: Dongkyu Lee, Thanh Banh Thien, Soomi Shin

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In the present study, the isogeometric topology optimization is proposed for cracked structures through using Solid Isotropic Material with Penalization (SIMP) as a design model. Design density variables defined in the variable space are used to approximate the element analysis density by the bivariate B-spline basis functions. The mathematical formulation of topology optimization problem solving minimum structural compliance is an alternating active-phase algorithm with the Gauss-Seidel version as an optimization model of optimality criteria. Stiffness and adjoint sensitivity formulations linked to strain energy of cracked structure are proposed in terms of design density variables. Numerical examples demonstrate interactions of topology optimization to structures design with cracks.

Keywords: topology optimization, isogeometric, NURBS, design

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Authors: D. S. Naumann, B. J. Evans, O. Hassan

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This paper outlines the development of an automated aerodynamic optimisation algorithm using a novel method of parameterising a computational mesh by employing user–defined control nodes. The shape boundary movement is coupled to the movement of the novel concept of the control nodes via a quasi-1D-linear deformation. Additionally, a second order smoothing step has been integrated to act on the boundary during the mesh movement based on the change in its second derivative. This allows for both linear and non-linear shape transformations dependent on the preference of the user. The domain mesh movement is then coupled to the shape boundary movement via a Delaunay graph mapping. A Modified Cuckoo Search (MCS) algorithm is used for optimisation within the prescribed design space defined by the allowed range of control node displacement. A finite volume compressible NavierStokes solver is used for aerodynamic modelling to predict aerodynamic design fitness. The resulting coupled algorithm is applied to a range of test cases in two dimensions including the design of a subsonic, transonic and supersonic intake and the optimisation approach is compared with more conventional optimisation strategies. Ultimately, the algorithm is tested on a three dimensional wing optimisation case.

Keywords: mesh movement, aerodynamic shape optimization, cuckoo search, shape parameterisation

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Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

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Performance of different filtering approaches depends on modeling of dynamical system and algorithm structure. For modeling and smoothing the data the evaluation of posterior distribution in different filtering approach should be chosen carefully. In this paper different filtering approaches like filter KALMAN, EKF, UKF, EKS and smoother RTS is simulated in some trajectory tracking of path and accuracy and limitation of these approaches are explained. Then probability of model with different filters is compered and finally the effect of the noise variance to estimation is described with simulations results.

Keywords: Gaussian approximation, Kalman smoother, parameter estimation, noise variance

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Authors: Christobel Gondwe, Yongtao Lu, Claudia Mazzà, Xinshan Li

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Skeletal muscle plays an important role in the human body system and function by generating voluntary forces and facilitating body motion. However, The mechanical properties and behaviour of skeletal muscle are still not comprehensively known yet. As such, various robust engineering techniques have been applied to better elucidate the mechanical behaviour of skeletal muscle. It is considered that muscle mechanics are highly governed by the architecture of the fibre orientations. Therefore, the aim of this study was to investigate the effect of different fibre orientations on the mechanical behaviour of skeletal muscle.In this study, a continuum mechanics approach–finite element (FE) analysis was applied to the left bicep femoris long head to determine the contractile mechanism of the muscle using Hill’s three-element model. The geometry of the muscle was segmented from the magnetic resonance images. The muscle was modelled as a quasi-incompressible hyperelastic (Mooney-Rivlin) material. Two types of fibre orientations were implemented: one with the idealised fibre arrangement, i.e. parallel single-direction fibres going from the muscle origin to insertion sites, and the other with curved fibre arrangement which is aligned with the muscle shape.The second fibre arrangement was implemented through the finite element method; non-uniform rational B-spline (FEM-NURBs) technique by means of user material (UMAT) subroutines. The stress-strain behaviour of the muscle was investigated under idealised exercise conditions, and will be further analysed under physiological conditions. The results of the two different FE models have been outputted and qualitatively compared.

Keywords: FEM-NURBS, finite element analysis, Mooney-Rivlin hyperelastic, muscle architecture

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Authors: Adel S. Alanazi

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The transition of a student with a disability from school to work is the most crucial phase while moving from the stage of adolescence into early adulthood. In this process, young individuals face various difficulties and challenges in order to accomplish the next venture of life successfully. In this respect, this paper aims to examine the challenges encountered by the individuals with intellectual disabilities in transition to work in Saudi Arabia. For this purpose, this study has undertaken a qualitative research-based methodology; wherein interpretivist philosophy has been followed along with inductive approach and exploratory research design. The data for the research has been gathered with the help of semi-structured interviews, whose findings are analysed with the help of thematic analysis. Semi-structured interviews were conducted with parents of persons with intellectual disabilities, officials, supervisors and specialists of two vocational rehabilitation centres providing training to intellectually disabled students, in addition to that, directors of companies and websites in hiring those individuals. The total number of respondents for the interview was 15. The purposive sampling method was used to select the respondents for the interview. This sampling method is a non-probability sampling method which draws respondents from a known population and allows flexibility and suitability in selecting the participants for the study. The findings gathered from the interview revealed that the lack of awareness among their parents regarding the rights of their children who are intellectually disabled; the lack of adequate communication and coordination between various entities; concerns regarding their training and subsequent employment are the key difficulties experienced by the individuals with intellectual disabilities. Training in programmes such as bookbinding, carpentry, computing, agriculture, electricity and telephone exchange operations were involved as key training programmes. The findings of this study also revealed that information technology and media were playing a significant role in smoothing the transition to employment of individuals with intellectual disabilities. Furthermore, religious and cultural attitudes have been identified to be restricted for people with such disabilities in seeking advantages from job opportunities. On the basis of these findings, it can be implied that the information gathered through this study will serve to be highly beneficial for Saudi Arabian schools/ rehabilitation centres for individuals with intellectual disability to facilitate them in overcoming the problems they encounter during the transition to work.

Keywords: intellectual disability, transition services, rehabilitation centre, employment

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Authors: Emad E. Abdallah, Alaa E. Abdallah, Bajes Y. Alskarnah

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We introduce a robust three-dimensional watermarking algorithm for copyright protection and indexing. The basic idea behind our technique is to measure the interquartile range or the spread of the 3D model vertices. The algorithm starts by converting all the vertices to spherical coordinate followed by partitioning them into small groups. The proposed algorithm is slightly altering the interquartile range distribution of the small groups based on predefined watermark. The experimental results on several 3D meshes prove perceptual invisibility and the robustness of the proposed technique against the most common attacks including compression, noise, smoothing, scaling, rotation as well as combinations of these attacks.

Keywords: watermarking, three-dimensional models, perceptual invisibility, interquartile range, 3D attacks

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Authors: Xian Li, Qing-Guo Wang, Jiangshuai Huang, Jidong Liu, Ming Yu, Tan Kok Poh

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In power industry, accurate electricity demand forecasting for a certain leading time is important for system operation and control, etc. In this paper, we investigate the modeling and forecasting of Singapore’s electricity demand. Several standard models, such as HWT exponential smoothing model, the ARMA model and the ANNs model have been proposed based on historical demand data. We applied them to Singapore electricity market and proposed three refinements based on simulation to improve the modeling accuracy. Compared with existing models, our refined model can produce better forecasting accuracy. It is demonstrated in the simulation that by adding forecasting error into the forecasting equation, the modeling accuracy could be improved greatly.

Keywords: power industry, electricity demand, modeling, forecasting

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Authors: Mohammad Reza Akhavan Khaleghi

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This paper shows changes done to the Reduced Finite Element Method (RFEM) that its result will be the most powerful numerical method that has been proposed so far (some forms of this method are so powerful that they can approximate the most complex equations simply Laplace equation!). Finite Element Method (FEM) is a powerful numerical method that has been used successfully for the solution of the existing problems in various scientific and engineering fields such as its application in CFD. Many algorithms have been expressed based on FEM, but none have been used in popular CFD software. In this section, full monopoly is according to Finite Volume Method (FVM) due to better efficiency and adaptability with the physics of problems in comparison with FEM. It doesn't seem that FEM could compete with FVM unless it was fundamentally changed. This paper shows those changes and its result will be a powerful method that has much better performance in all subjects in comparison with FVM and another computational method. This method is not to compete with the finite volume method but to replace it.

Keywords: reduced finite element method, new computational package, new finite element formulation, new higher-order form, new isogeometric analysis

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Authors: O. Acan, Y. Keskin

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In this study, we will carry out a comparative study between the reduced differential transform method, the adomian decomposition method, the variational iteration method and the homotopy analysis method. These methods are used in many fields of engineering. This is been achieved by handling a kind of 2-Dimensional and forth-order partial differential equations called the Kuramoto–Sivashinsky equations. Three numerical examples have also been carried out to validate and demonstrate efficiency of the four methods. Furthermost, it is shown that the reduced differential transform method has advantage over other methods. This method is very effective and simple and could be applied for nonlinear problems which used in engineering.

Keywords: reduced differential transform method, adomian decomposition method, variational iteration method, homotopy analysis method

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Authors: Mohammed Farag, Mina Attari, S. Andrew Gadsden, Saeid R. Habibi

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Battery state of charge (SOC) estimation is an important parameter as it measures the total amount of electrical energy stored at a current time. The SOC percentage acts as a fuel gauge if it is compared with a conventional vehicle. Estimating the SOC is, therefore, essential for monitoring the amount of useful life remaining in the battery system. This paper looks at the implementation of three nonlinear estimation strategies for Li-Ion battery SOC estimation. One of the most common behavioral battery models is the one state hysteresis (OSH) model. The extended Kalman filter (EKF), the smooth variable structure filter (SVSF), and the time-varying smoothing boundary layer SVSF are applied on this model, and the results are compared.

Keywords: state of charge estimation, battery modeling, one-state hysteresis, filtering and estimation

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Authors: M. Benbouzid, Q. Bresson, A. Duclos, K. Longo, Q. Morel

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Currently, electricity suppliers must predict the consumption of their customers in order to deduce the power they need to produce. It is, then, important in a first step to optimize household consumption to obtain more constant curves by limiting peaks in energy consumption. Here centralized real time scheduling is proposed to manage the equipment's starting in parallel. The aim is not to exceed a certain limit while optimizing the power consumption across a habitat. The Raspberry Pi is used as a box; this scheduler interacts with the various sensors in 6LoWPAN. At the scale of a single dwelling, household consumption decreases, particularly at times corresponding to the peaks. However, it would be wiser to consider the use of a residential complex so that the result would be more significant. So, the ceiling would no longer be fixed. The scheduling would be done on two scales, firstly, per dwelling, and secondly, at the level of a residential complex.

Keywords: smart grid, energy box, scheduling, Gang Model, energy consumption, energy management system, wireless sensor network

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Authors: Edokpa Idemudia Waziri, Salisu S. Umar

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The Hotellng’s T^2 is a well-known statistic for detecting a shift in the mean vector of a multivariate normal distribution. Control charts based on T have been widely used in statistical process control for monitoring a multivariate process. Although it is a powerful tool, the T statistic is deficient when the shift to be detected in the mean vector of a multivariate process is small and consistent. The Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is one of the control statistics used to overcome the drawback of the Hotellng’s T statistic. In this paper, the probability distribution of the Average Run Length (ARL) of the MEWMA control chart when the quality characteristics exhibit substantial cross correlation and when the process is in-control and out-of-control was derived using the Markov Chain algorithm. The derivation of the probability functions and the moments of the run length distribution were also obtained and they were consistent with some existing results for the in-control and out-of-control situation. By simulation process, the procedure identified a class of ARL for the MEWMA control when the process is in-control and out-of-control. From our study, it was observed that the MEWMA scheme is quite adequate for detecting a small shift and a good way to improve the quality of goods and services in a multivariate situation. It was also observed that as the in-control average run length ARL0¬ or the number of variables (p) increases, the optimum value of the ARL0pt increases asymptotically and as the magnitude of the shift σ increases, the optimal ARLopt decreases. Finally, we use the example from the literature to illustrate our method and demonstrate its efficiency.

Keywords: average run length, markov chain, multivariate exponentially weighted moving average, optimal smoothing parameter

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Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

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Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: airborne laser scanning, digital terrain models, filtering, forested areas

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Authors: A. Bere, H. G. Sithuba, K. Kyei, C. Sigauke

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We employ a discrete logit survival model to investigate the risk factors for early alcohol intake among students at two tertiary institutions in Thohoyandou, South Africa. Data were collected from a sample of 744 students using a self-administered questionnaire. Significant covariates were arrived at through a regularization algorithm implemented using the glmmLasso package. The tuning parameter was determined using a five-fold cross-validation algorithm. The baseline hazard was modelled as a smooth function of time through the use of spline functions. The results show that the hazard of initial alcohol intake peaks at the age of about 16 years and that at any given time, being of a male gender, prior use of other drugs, having drinking peers, having experienced negative life events and physical abuse are associated with a higher risk of alcohol intake debut.

Keywords: cross-validation, discrete hazard model, LASSO, smooth baseline hazard

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Authors: Hyung Joo Lee, Jin Young Choi, Gun Soo Park, Kyo Sun Oh, Dong Jun Won

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The fluctuation of the output of the renewable generator caused by weather conditions must be mitigated because it imposes strain on the system and adversely affects power quality. In this paper, we focus on mitigating the output fluctuation of the photovoltaic (PV) using battery energy storage system (BESS). To satisfy tight conditions of system, proposed algorithm is developed. This algorithm focuses on adjusting the integrated output curve considering state of capacity (SOC) of the battery. In this paper, the simulation model is PSCAD / EMTDC software. SOC of the battery and the overall output curve are shown using the simulation results. We also considered losses and battery efficiency.

Keywords: photovoltaic generation, battery energy storage system, renewable integration, power smoothing

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Authors: Elvis Adam Alhassan, Kaiyu Tian, Akos Konadu, Ernest Zamanah, Michael Jackson Adjabui, Ibrahim Justice Musah, Esther Agyeiwaa Owusu, Emmanuel K. A. Agyeman

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In this paper, how to solve simultaneous equations using the Elvis improved method is shown. The Elvis improved method says; to make one variable in the first equation the subject; make the same variable in the second equation the subject; equate the results and simplify to obtain the value of the unknown variable; put the value of the variable found into one equation from the first or second steps and simplify for the remaining unknown variable. The difference between our Elvis improved method and the substitution method is that: with Elvis improved method, the same variable is made the subject in both equations, and the two resulting equations equated, unlike the substitution method where one variable is made the subject of only one equation and substituted into the other equation. After describing the Elvis improved method, findings from 100 secondary students and the views of 5 secondary tutors to demonstrate the effectiveness of the method are presented. The study's purpose is proved by hypothetical examples.

Keywords: simultaneous equations, substitution method, elimination method, graphical method, Elvis improved method

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Authors: Arezoo Hakimi, Afshin Farahbakhsh

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Herein, we comparison synthesized Fe3O4 using, hydrothermal method, Mechanochemical processes and solvent thermal method. The Hydrothermal Technique has been the most popular one, gathering interest from scientists and technologists of different disciplines, particularly in the last fifteen years. In the hydrothermal method Fe3O4 microspheres, in which many nearly monodisperse spherical particles with diameters of about 400nm, in the mechanochemical method regular morphology indicates that the particles are well crystallized and in the solvent thermal method Fe3O4 nanoparticles have good properties of uniform size and good dispersion.

Keywords: Fe3O4 nanoparticles, hydrothermal method, mechanochemical processes, solvent thermal method

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Authors: Ya-Mei Chang

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This research is intended to apply spatio-temporal point process methods to the dengue fever data in Tainan. The spatio-temporal intensity function of the dataset is assumed to be separable. The kernel estimation is a widely used approach to estimate intensity functions. The intensity function is very helpful to study the relation of the spatio-temporal point process and some covariates. The covariate effects might be nonlinear. An nonparametric smoothing estimator is used to detect the nonlinearity of the covariate effects. A fitted parametric model could describe the influence of the covariates to the dengue fever. The correlation between the data points is detected by the K-function. The result of this research could provide useful information to help the government or the stakeholders making decisions.

Keywords: dengue fever, spatial point process, kernel estimation, covariate effect

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Authors: Ross Guest, Bjarne Jensen

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This paper analyses a potentially new consumption dividend from lower fertility arising from imperfect labour substitution by age. A smaller proportion of young workers relative to older workers raises relative youth wages given imperfect labour substitution by age. Discounted lifetime labour income rises which provides a consumption dividend. Simulation results are reported for the four Scandinavian countries, adopting a simple overlapping generations model. Imperfect labour substitution is modelled using a CRESH functional form of an aggregate labour index. The magnitudes of this new consumption dividend from a Low fertility projection compared with a high fertility projection are found to be approximately 4 percent annually, on average over the Scandinavian countries in the very long run, but somewhat lower in the short term. There is some sensitivity to the interest rate and the degree of consumption smoothing.

Keywords: fertility, consumption, productivity, labour substitution

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Authors: Oluwayemisi O. Alaba, John O. Olaomi

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The 2013 Nigerian Demographic Health Survey (NDHS) data was used to investigate the determinants of family size in Nigeria using the geo-additive model. The fixed effect of categorical covariates were modelled using the diffuse prior, P-spline with second-order random walk for the nonlinear effect of continuous variable, spatial effects followed Markov random field priors while the exchangeable normal priors were used for the random effects of the community and household. The Negative Binomial distribution was used to handle overdispersion of the dependent variable. Inference was fully Bayesian approach. Results showed a declining effect of secondary and higher education of mother, Yoruba tribe, Christianity, family planning, mother giving birth by caesarean section and having a partner who has secondary education on family size. Big family size is positively associated with age at first birth, number of daughters in a household, being gainfully employed, married and living with partner, community and household effects.

Keywords: Bayesian analysis, family size, geo-additive model, negative binomial

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Authors: Bale Baidi Blaise, Gilles Marckmann, Liman Kaoye, Talaka Dya, Moustapha Bachirou, Gambo Betchewe, Tibi Beda

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This work highlights the capabilities of particles swarm optimization (PSO) method to identify parameters of hyperelastic models. The study compares this method with Genetic Algorithm (GA) method, Least Squares (LS) method, Pattern Search Algorithm (PSA) method, Beda-Chevalier (BC) method and the Levenberg-Marquardt (LM) method. Four classic hyperelastic models are used to test the different methods through parameters identification. Then, the study compares the ability of these models to reproduce experimental Treloar data in simple tension, biaxial tension and pure shear.

Keywords: particle swarm optimization, identification, hyperelastic, model

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Authors: Ehsan Mehryaar, Seyed Armin Motahari Tabari

Abstract:

Coarse-grained soils are known and commonly used in a wide range of geotechnical projects, including high earth dams or embankments for their high shear strength. The most important engineering property of these soils is friction angle which represents the interlocking between soil particles and can be applied widely in designing and constructing these earth structures. Friction angle and dilative behavior of coarse-grained soils can be estimated from empirical correlations with in-situ testing and physical properties of the soil or measured directly in the laboratory performing direct shear or triaxial tests. Unfortunately, large-scale testing is difficult, challenging, and expensive and is not possible in most soil mechanic laboratories. So, it is common to remove the large particles and do the tests, which cannot be counted as an exact estimation of the parameters and behavior of the original soil. This paper describes a new methodology to simulate particles grading distribution of a well-graded gravel sample to a smaller scale sample as it can be tested in an ordinary direct shear apparatus to estimate the stress-strain behavior, friction angle, and dilative behavior of the original coarse-grained soil considering its confining pressure, and relative density using a machine learning method. A total number of 72 direct shear tests are performed in 6 different sizes, 3 different confining pressures, and 4 different relative densities. Multivariate Adaptive Regression Spline (MARS) technique was used to develop an equation in order to predict shear strength and dilative behavior based on the size distribution of coarse-grained soil particles. Also, an uncertainty analysis was performed in order to examine the reliability of the proposed equation.

Keywords: MARS, coarse-grained soil, shear strength, uncertainty analysis

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