Search results for: Approximate Bayesian computation(ABC)

Authors: Bin Su

Abstract:

This study focuses on the impact of school building design factors on winter extra energy consumption which mainly includes space heating, water heating and other appliances related to winter indoor thermal conditions. A number of Auckland schools were randomly selected for the study which introduces a method of using real monthly energy consumption data for a year to calculate winter extra energy data of school buildings. The study seeks to identify the relationships between winter extra energy data related to school building design data related to the main architectural features, building envelope and elements of the sample schools. The relationships can be used to estimate the approximate saving in winter extra energy consumption which would result from a changed design datum for future school development, and identify any major energy-efficient design problems. The relationships are also valuable for developing passive design guides for school energy efficiency.

Keywords: building energy efficiency, building thermal design, building thermal performance, school building design

Procedia PDF Downloads 439

Authors: Xia Huo

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The composition and metabolites of the gut microbiota can be altered by environmental pollutants. However, the effect of co-exposure to multiple pollutants on the human gut microbiota has not been sufficiently studied. In this study, gut microorganisms and their metabolites were compared between 33 children from Guiyu and 34 children from Haojiang. The exposure level was assessed by estimating the daily intake (EDI) of polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs), 6PPD-quinone (6PPDQ), and metal(loid)s in dust. Significant correlations were found between the EDIs of 6PPDQ, BDE28, PCB52, Ni, Cu, and both the alpha diversity index and specific metabolites in single-element models. The study found that the Bayesian kernel machine regression (BKMR) model showed a negative correlation between the EDIs of five pollutants (6PPDQ, BDE28, PCB52, Ni, and Cu) and the Chao 1 index, particularly beyond the 55th percentile. Furthermore, the EDIs of these five pollutants were positively correlated with the levels of the metabolite 2,4-diaminobutyric acid while negatively correlated with the levels of d-erythro-sphingosine and d-threitol. Our research suggests that exposure to 6PPDQ, BDE28, PCB52, Ni, and Cu in kindergarten dust is associated with alterations in the gut microbiota and its metabolites. These alterations may be associated with neurodevelopmental abnormalities in children.

Keywords: gut microbiota, 6PPDQ, PBDEs, PCBs, metal(loid)s, BKMR

Procedia PDF Downloads 51

Authors: Mishari AlNaim

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A field experiment was conducted for two seasons of 2011 and 2012 in The Agricultural Experiment Research Station in King Faisal University at Al-Hasa region, Saudi Arabia to estimate evapotranspiration (ETC) of Eggplant crop using Drainage Lysimeter with surface area of 2 x 2 m and depth of 1.5 m. The irrigation was applied daily. The amount of drainage was measured before each irrigation event. The results showed that there was almost no difference in the seasonal evapotranspiration of eggplant crop in the two seasons. The average evapotranspiration values for eggplant crop for the summer and winter seasons were 823.4 mm and 479.7 mm respectively. The highest and the lowest weekly measured values of (ETC) of eggplant crop during the two summer seasons were 8.6 mm/day and 3.9 mm/day respectively, while the highest and lowest weekly measured values of (ETC) of eggplant crop during the two winter seasons were 3.9 mm/day and 2.0 mm/day respectively. The measured values of ETc, in conjunction with the results of Penmen-Monteith equation for reference Evapotranspiration (ETR), were used to determine the crop coefficient (KC ini, KC mid and KC end) for eggplant crop. The average values were 0.50, 84 and 0.60 for KC ini, KC mid and KC end in Al-Hasa region, respectively. These estimated values for KC were used to approximate (ETc) for eggplant crop. High positive correlation coefficient (0.959) was detected between the approximated and measured values of eggplant crop evapotranspiration.

Keywords: evapotranspiration, eggpant, ETC, Al-Hasa

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Authors: Yuanhao Gao, Ping Lin, Kees Weijer

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An optimal control system model is proposed for the cell flow in the process of chick embryo gastrulation in this paper. The target is to determine the cellular interaction forces which are hard to measure. This paper will take an approach to investigate the forces with the idea of the inverse problem. By choosing the forces as the control variable and regarding the cell flow as Stokes fluid, an objective functional will be established to match the numerical result of cell velocity with the experimental data. So that the forces could be determined by minimizing the objective functional. The Lagrange multiplier method is utilized to derive the state and adjoint equations consisting the optimal control system, which specifies the first-order necessary conditions. Finite element method is used to discretize and approximate equations. A conjugate gradient algorithm is given for solving the minimum solution of the system and determine the forces.

Keywords: optimal control model, Stokes equation, conjugate gradient method, finite element method, chick embryo gastrulation

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Authors: Sarah Beaver, Renee Bryce

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Audiograms detect hearing impairment, but missing values pose problems. This work explores imputations in an attempt to improve accuracy. This work implements Linear Regression, Lasso, Linear Support Vector Regression, Bayesian Ridge, K Nearest Neighbors (KNN), and Random Forest machine learning techniques to impute audiogram frequencies ranging from 125Hz to 8000Hz. The data contains patients who had or were candidates for cochlear implants. Accuracy is compared across two different Nested Cross-Validation k values. Over 4000 audiograms were used from 800 unique patients. Additionally, training on data combines and compares left and right ear audiograms versus single ear side audiograms. The accuracy achieved using Root Mean Square Error (RMSE) values for the best models for Random Forest ranges from 4.74 to 6.37. The R\textsuperscript{2} values for the best models for Random Forest ranges from .91 to .96. The accuracy achieved using RMSE values for the best models for KNN ranges from 5.00 to 7.72. The R\textsuperscript{2} values for the best models for KNN ranges from .89 to .95. The best imputation models received R\textsuperscript{2} between .89 to .96 and RMSE values less than 8dB. We also show that the accuracy of classification predictive models performed better with our best imputation models versus constant imputations by a two percent increase.

Keywords: machine learning, audiograms, data imputations, single imputations

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Authors: Hung-Jiun Chi, Cheng-En Tsai, Jia-Ying Tu

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Semi-active control of Magnetorheological (MR) dampers for vibration reduction of structural systems has received considerable attention in civil and earthquake engineering, because the effective stiffness and damping properties of MR fluid can change in a very short time in reaction to external loading, requiring only a low level of power. However, the inherent nonlinear dynamics of hysteresis raise challenges in the modeling and control processes. In order to control the MR damper, an innovative Duffing-like equation is proposed to approximate the hysteresis dynamics in a deterministic and systematic manner than previously has been possible. Then, the model-reference adaptive control technique based on the Duffing-like model and the Lyapunov method is discussed. Parameter identification work with experimental data is presented to show the effectiveness of the Duffing-like model. In addition, simulation results show that the resulting adaptive gains enable the MR damper force to track the desired response of the reference model satisfactorily, verifying the effectiveness of the proposed modeling and control techniques.

Keywords: magnetorheological damper, duffing equation, model-reference adaptive control, Lyapunov function, hysteresis

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Authors: Ambuj Kumar Gautam, V. Vasu

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This paper introduces a head movement based Human Machine Interface (HMI) that uses the right and left movements of head to control a robot motion. Here we present an approach for making an effective technique for real-time face orientation information system, to control a robot which can be efficiently used for Electrical Powered Wheelchair (EPW). Basically this project aims at application related to HMI. The system (machine) identifies the orientation of the face movement with respect to the pixel values of image in a certain areas. Initially we take an image and divide that whole image into three parts on the basis of its number of columns. On the basis of orientation of face, maximum pixel value of approximate same range of (R, G, and B value of a pixel) lie in one of divided parts of image. This information we transfer to the microcontroller through serial communication port and control the motion of robot like forward motion, left and right turn and stop in real time by using head movements.

Keywords: electrical powered wheelchair (EPW), human machine interface (HMI), robotics, microcontroller

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Authors: Hamdy Elgohary, Majid Assas

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Estimation of lateral displacement and interstory drifts represent a major step in multistory frames design. In the preliminary design stage, it is essential to perform a fast check for the expected values of lateral deformations. This step will help to ensure the compliance of the expected values with the design code requirements. Also, in some cases during or after the detailed design stage, it may be required to carry fast check of lateral deformations by design reviewer. In the present paper, a parametric study is carried out on the factors affecting in the lateral displacements of multistory frame buildings. Based on the results of the parametric study, simplified empirical equations are recommended for the direct determination of the lateral deflection of multistory frames. The results obtained using the recommended equations have been compared with the results obtained by finite element analysis. The comparison shows that the proposed equations lead to good approximation for the estimation of lateral deflection of multistory RC frame buildings.

Keywords: lateral deflection, interstory drift, approximate analysis, multistory frames

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Authors: Jugal Bhandari, K. Hari Priya

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The ECG signal provides important clinical information which could be used to pretend the diseases related to heart. Accordingly, delineation of ECG signal is an important task. Whereas delineation of P and T waves is a complex task. This paper deals with the Study of ECG signal and analysis of signal by means of Verilog Design of efficient filters and MATLAB tool effectively. It includes generation and simulation of ECG signal, by means of real time ECG data, ECG signal filtering and processing by analysis of different algorithms and techniques. In this paper, we design a basic particle filter which generates a dynamic model depending on the present and past input samples and then produces the desired output. Afterwards, the output will be processed by MATLAB to get the actual shape and accurate values of the ranges of P-wave and T-wave of ECG signal. In this paper, Questasim is a tool of mentor graphics which is being used for simulation and functional verification. The same design is again verified using Xilinx ISE which will be also used for synthesis, mapping and bit file generation. Xilinx FPGA board will be used for implementation of system. The final results of FPGA shall be verified with ChipScope Pro where the output data can be observed.

Keywords: ECG, MATLAB, Bayesian filtering, particle filter, Verilog hardware descriptive language

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Authors: Danielle M. Barna, Kolbjørn Engeland, Thordis Thorarinsdottir, Chong-Yu Xu

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Design flood values give estimates of flood magnitude within a given return period and are essential to making adaptive decisions around land use planning, infrastructure design, and disaster mitigation. Often design flood values are needed at locations with insufficient data. Additionally, in hydrologic applications where flood retention is important (e.g., floodplain management and reservoir design), design flood values are required at different flood durations. A statistical approach to this problem is a development of a regression model for extremes where some of the parameters are dependent on flood duration in addition to being covariate-dependent. In hydrology, this is called a regional flood-duration-frequency (regional-QDF) model. Typically, the underlying statistical distribution is chosen to be the Generalized Extreme Value (GEV) distribution. However, as the support of the GEV distribution depends on both its parameters and the range of the data, special care must be taken with the development of the regional model. In particular, we find that the GEV is problematic when developing a GAMLSS-type analysis due to the difficulty of proposing a link function that is independent of the unknown parameters and the observed data. We discuss these challenges in the context of developing a regional QDF model for Norway.

Keywords: design flood values, bayesian statistics, regression modeling of extremes, extreme value analysis, GEV

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Authors: Yiming Jin, Ping Dong

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The primary resonance of a pipeline close to a plane boundary is investigated in this paper. Based on classic Van der Pol equation and added a nonlinear item, a new wake oscillator model is proposed to predict the vortex-induced vibration (VIV) of a circular cylinder close to a plane boundary. Then, with the multi-scale method, the approximate solution for the case of the primary resonance is obtained. Besides, to study the characteristic of the primary resonance, the effects of the mass ration, frequency, damp ratio and gap ratio on the frequency-response curves of the pipeline are analysed. On the whole, the trend of the numerical results match up with that of the experimental data well and the mass ration, frequency, damp ratio and gap ratio play an important role in the vortex-induced vibration (VIV) of a circular cylinder close to a plane boundary, especially, the smaller is the mass ratio, the larger impact the gap ratio has on the frequency-response curves of the primary resonance.

Keywords: primary resonance, gap ratio, vortex-induced vibration, multi-scale method

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Authors: Mohammad Farid

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In this paper, we introduce and study an explicit iterative method based on hybrid extragradient method to approximate a common solution of generalized mixed equilibrium problem and fixed point problem for a nonexpansive semigroup in Hilbert space. Further, we prove that the sequence generated by the proposed iterative scheme converge strongly to the common solution of generalized mixed equilibrium problem and fixed point problem for a nonexpansive semigroup. This common solution is the unique solution of a variational inequality problem and is the optimality condition for a minimization problem. The results presented in this paper are the supplement, extension and generalization of the previously known results in this area.

Keywords: generalized mixed equilibrium problem, fixed-point problem, nonexpansive semigroup, variational inequality problem, iterative algorithms, hybrid extragradient method

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Authors: J. J. Vargas, N. Prieto, L. A. Toro

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Control charts are commonly used to monitor processes involving either variable or attribute of quality characteristics and determining the control limits as a critical task for quality engineers to improve the processes. Nonetheless, in some applications it is necessary to include an estimation of efficiency. In this paper, the ability to define the efficiency of an industrial process was added to a control chart by means of incorporating a data envelopment analysis (DEA) approach. In depth, a Bayesian estimation was performed to calculate the posterior probability distribution of parameters as means and variance and covariance matrix. This technique allows to analyse the data set without the need of using the hypothetical large sample implied in the problem and to be treated as an approximation to the finite sample distribution. A rejection simulation method was carried out to generate random variables from the parameter functions. Each resulting vector was used by stochastic DEA model during several cycles for establishing the distribution of each efficiency measures for each DMU (decision making units). A control limit was calculated with model obtained and if a condition of a low level efficiency of DMU is presented, system efficiency is out of control. In the efficiency calculated a global optimum was reached, which ensures model reliability.

Keywords: data envelopment analysis, DEA, Multivariate control chart, rejection simulation method

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Authors: Reda Abdel Azim, Tariq Shehab

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The main objective of this study is to develop a subsurface fracture map of naturally fractured reservoirs by overcoming the limitations associated with different data sources in characterising fracture properties. Some of these limitations are overcome by employing a nested neuro-stochastic technique to establish inter-relationship between different data, as conventional well logs, borehole images (FMI), core description, seismic attributes, and etc. and then characterise fracture properties in terms of fracture density and fractal dimension for each data source. Fracture density is an important property of a system of fracture network as it is a measure of the cumulative area of all the fractures in a unit volume of a fracture network system and Fractal dimension is also used to characterize self-similar objects such as fractures. At the wellbore locations, fracture density and fractal dimension can only be estimated for limited sections where FMI data are available. Therefore, artificial intelligence technique is applied to approximate the quantities at locations along the wellbore, where the hard data is not available. It should be noted that Artificial intelligence techniques have proven their effectiveness in this domain of applications.

Keywords: naturally fractured reservoirs, artificial intelligence, fracture intensity, fractal dimension

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Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

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Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

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Authors: Dang Thuy Binh, Truong Thi Oanh, Le Phan Khanh Hung, Luong thi Tuong Vy

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One of the greatest environmental challenges facing Asia is the management and conservation of the marine biodiversity threaten by fisheries overexploitation, pollution, habitat destruction, and climate change. To date, a few molecular taxonomical studies has been conducted on marine fauna in Vietnam. The purpose of this study was to clarify the phylogeny of economic and ecological reef fish species in Vietnam Reef fish species covering Labridae, Scaridae, Nemipteridae, Serranidae, Acanthuridae, Lutjanidae, Lethrinidae, Mullidae, Balistidae, Pseudochromidae, Pinguipedidae, Fistulariidae, Holocentridae, Synodontidae, and Pomacentridae representing 28 genera were collected from South and Center, Vietnam. Combine with Genbank sequences, a phylogenetic tree was constructed based on 16S gene of mitochondrial DNA using maximum parsimony, maximum likelihood, and Bayesian inference approaches. The phylogram showed the well-resolved clades at genus and family level. Perciformes is the major order of reef fish species in Vietnam. The monophyly of Perciformes is not strongly supported as it was clustered in the same clade with Tetraodontiformes syngnathiformes and Beryciformes. Continue sampling of commercial fish species and classification based on morphology and genetics to build DNA barcoding of fish species in Vietnam is really necessary.

Keywords: reef fish, 16s rDNA, Vietnam, phylogeny

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Authors: Jiaqi Huang, Lu Jin

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Pervious concrete features with high water permeability rate. However, due to the lack of fine aggregates, the compressive strength is usually lower than other conventional concrete products. Optimization of pervious concrete mix design has long been recognized as an effective mechanism to achieve high compressive strength while maintaining desired permeability rate. In this paper, a Gibbs Sampling based algorithm is proposed to approximate the optimal mix design to achieve a high compressive strength of pervious concrete. We prove that the proposed algorithm efficiently converges to the set of global optimal solutions. The convergence rate and accuracy depend on a control parameter employed in the proposed algorithm. The simulation results show that, by using the proposed approach, the system converges to the optimal solution quickly and the derived optimal mix design achieves the maximum compressive strength while maintaining the desired permeability rate.

Keywords: convergence, Gibbs Sampling, high compressive strength, optimal mix design, pervious concrete

Procedia PDF Downloads 176

Authors: M. N. Hanina, M. Hairul Shahril, I. Ismatul Nurul Asyikin, A. K. Abdul Jalil, M. R. Salina, M. R. Maryam, M. Rosfarizan

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The extracellular proteins secreted by bacteria may be increased in stressful surroundings, such as in the presence of antibiotics. It appears that many antibiotics, when used at low concentrations, have in common the ability to activate or repress gene transcription, which is distinct from their inhibitory effect. There have been comparatively few studies on the potential of antibiotics as a specific chemical signal that can trigger a variety of biological functions. Therefore, this study was carried out to determine the effect of Streptomycin Sulfate in regulating extracellular proteins secreted by Bacillus subtilis ATCC21332. Results of Microdilution assay showed that the Minimum Inhibition Concentration (MIC) of Streptomycin Sulfate on B. subtilis ATCC21332 was 2.5 mg/ml. The bacteria cells were then exposed to Streptomycin Sulfate at concentration of 0.01 MIC before being further incubated for 48h to 72 h. The extracellular proteins secreted were then isolated and analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Proteins profile revealed that three additional bands with approximate sizes of 30 kDa, 22 kDa and 23 kDa were appeared for the treated bacteria with Streptomycin Sulfate. Thus, B. subtilis ATCC21332 in stressful condition with the presence of Streptomycin Sulfate at low concentration could induce the extracellular proteins secretion.

Keywords: Bacillus subtilis ATCC21332, streptomycin sulfate, extracellular proteins, antibiotics

Procedia PDF Downloads 279

Authors: Caglayan Hizal, Hasan Emre Demirci, Engin Aktas, Alper Sezer

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Offshore wind turbines consist of a long slender tower with a heavy fixed mass on the top of the tower (nacelle), together with a heavy rotating mass (blades and hub). They are always subjected to environmental loads including wind and wave loads in their service life. This study presents a three-stage methodology for reliability-based condition assessment of offshore wind-turbines against the seismic, wave and wind induced effects considering the soil-structure interaction. In this context, failure criterions are considered as serviceability limits of a monopile supporting an Offshore Wind Turbine: (a) allowable horizontal displacement at pile head should not exceed 0.2 m, (b) rotations at pile head should not exceed 0.5°. A Bayesian system identification framework is adapted to the classical reliability analysis procedure. Using this framework, a reliability assessment can be directly implemented to the updated finite element model without performing time-consuming methods. For numerical verification, simulation data of the finite model of a real offshore wind-turbine structure is investigated using the three-stage methodology.

Keywords: Offshore wind turbines, SHM, reliability assessment, soil-structure interaction

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Authors: Bel G Raggad

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An e-Learning setting is a distributed computing environment where information resources can be connected to any public network. Public networks are very unsecure which can compromise the reliability of an e-Learning environment. This study is only concerned with the intrusion detection aspect of e-Learning security and how incident responses are planned. The literature reported great advances in intrusion detection system (ids) but neglected to study an important ids weakness: suspected events are detected but an intrusion is not determined because it is not defined in ids databases. We propose an incident response generator (DIRG) that produces incident responses when the working ids system suspects an event that does not correspond to a known intrusion. Data involved in intrusion detection when ample uncertainty is present is often not suitable to formal statistical models including Bayesian. We instead adopt Dempster and Shafer theory to process intrusion data for the unknown event. The DIRG engine transforms data into a belief structure using incident scenarios deduced by the security administrator. Belief values associated with various incident scenarios are then derived and evaluated to choose the most appropriate scenario for which an automatic incident response is generated. This article provides a numerical example demonstrating the working of the DIRG system.

Keywords: decision support system, distributed computing, e-Learning security, incident response, intrusion detection, security risk, statefull inspection

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Authors: Samanwita Paul

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Borrowing from Kabeer’s framework of empowerment, participation of women at Panchayat level politics (grassroots level of politics in India) has been conceptualized as a resource in the study and the impact of the same in influencing the policies at the grassroots as an agency. The study attempts to examine such intricacies in the dynamics of participation and policy formulation at the Panchayat level and to assess its overall impact in altering the recognition and redistribution of women. A conscious attempt has been made to go beyond formal politics and consider participants of the informal political processes as subjects of the study. Primary surveys were conducted for data collection in 4 Panchayat villages (from Jalpaiguri district in West Bengal) of which 2 wards from each were selected based on the nature of reservation of the panchayat seats. In-depth interviews with the Panchayat members and an approximate of 80 voters from each of the villages were conducted. This has been further analyzed with the aid of appropriate statistical tools and narratives. Preliminary findings show that women from vulnerable sections tend to participate more in the political process since it offers them a means of negotiating with their vulnerabilities however in case of its impact on policy formulation, the effect of women’s participation does to appear to be as profound.

Keywords: recognition, redistribution, political participation, women

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Authors: Yousefali Ziari, Hamidreza Joudaki

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Humans have regularly been interacting with their environment, and have a close relation with their environment. House as a shelter which protects us against hot and cold weather and the other climatic occurrences in the environment has a close relation with climate. Before human could have access to the fossil fuels, preparing the comfort for the house was done by adjusting the building according to the climate conditions, and the help of natural resources. However after the man could access the fossil fuel, this way was forgotten, and caused much use of energy for heating & cooling. This research is trying to find some methods for designing suitable building that create comfort fitting with the zone by studying the climate condition of Arak city and as a result to find a way to reduce the use of energy and improving the design. So for the aim of this research we have used the statistics and information such as temperature, rain, wind and the approximate moisture from a period of 40 years from synoptic station of Arak. After specifying the climate of Arak by the use of effective temperature, Ulgi, Guni, Mahani and Ovenz indicator, we investigated the climate comfort conditions and the harmonious architecture with the climate and then some suggestion was given according to the climate situation of each month of the year and quality of human comfort according to this indicators.

Keywords: climate, architecture, traditional and modern architecture, comfort indicator, Arak city

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Authors: Jiya Mohammed, Ibrahim Ismail Giwa

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Unsteady squeezing flow of a viscous fluid between parallel plates is considered. The two plates are considered to be approaching each other symmetrically, causing the squeezing flow. Two-dimensional rectangular Cartesian coordinate is considered. The Navier-Stokes equation was reduced using similarity transformation to a single fourth order non-linear ordinary differential equation. The energy equation was transformed to a second order coupled differential equation. We obtained solution to the resulting ordinary differential equations via Homotopy Perturbation Method (HPM). HPM deforms a differential problem into a set of problem that are easier to solve and it produces analytic approximate expression in the form of an infinite power series by using only sixth and fifth terms for the velocity and temperature respectively. The results reveal that the proposed method is very effective and simple. Comparisons among present and existing solutions were provided and it is shown that the proposed method is in good agreement with Variation of Parameter Method (VPM). The effects of appropriate dimensionless parameters on the velocity profiles and temperature field are demonstrated with the aid of comprehensive graphs and tables.

Keywords: coupled differential equation, Homotopy Perturbation Method, plates, squeezing flow

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Authors: Md. Ruhul Amin

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The effects of CB1, CB3, CB5, CB8 and CB12 cotton varieties on the nutritional indices and biological parameters of armyworm Spodoptera litura were studied under laboratory conditions. The armyworm larvae showed the highest and lowest food consumption rates on CB8 and CB1 variety, respectively. The efficiency of the conversion of digested food, efficiency of conversion of ingested food, approximate digestibility rates were statistically higher and similar on CB5 and CB8, and lowest on CB1. The larvae reared on CB12 variety exerted the lowest feeding and growth indices, and the relative growth rate was highest on CB8. The survival rates of egg, larva, pupa and adult moths were found highest on CB8 and lowest on CB12. The development durations of the immature stages of the insect differed significantly and the time elapsed from egg-to-adult emergence, longevity of both male and female moths, and their lifecycle were shortest on CB12 variety. The nutritional indices and biological parameters of the armyworm indicated that the varieties CB5 and CB8 were suitable host plants for feeding and development of S. litura.

Keywords: gossypium hirsutum, spodoptera litura, food consumption, life history

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Authors: Shivani Saini

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The effect of vertical throughflow on the onset of convection in Rivlin-Ericksen Elastico-Viscous nanofluid with convective boundary condition is investigated. The flow is stimulated with modified Darcy model under the assumption that the nanoparticle volume fraction is not actively managed on the boundaries. The heat conservation equation is formulated by introducing the convective term of nanoparticle flux. A linear stability analysis based upon normal mode is performed, and an approximate solution of eigenvalue problems is obtained using the Galerkin weighted residual method. Investigation of the dependence of the Rayleigh number on various viscous and nanofluid parameter is performed. It is found that through flow and nanofluid parameters hasten the convection while capacity ratio, kinematics viscoelasticity, and Vadasz number do not govern the stationary convection. Using the convective component of nanoparticle flux, critical wave number is the function of nanofluid parameters as well as the throughflow parameter. The obtained solution provides important physical insight into the behavior of this model.

Keywords: Darcy model, nanofluid, porous layer, throughflow

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Authors: Edward Schwalb, Matthias Dehmer, Michael Schlenkrich, Farzaneh Taslimi, Ketron Mitchell-Wynne, Horen Kuecuekyan

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We present a generalized feature extraction approach for supporting Machine Learning (ML) algorithms which perform tasks similar to Finite-Element Analysis (FEA). We report results for estimating the Head Injury Categorization (HIC) of vehicle engine compartments across various impact scenarios. Our experiments demonstrate that models learned using features derived with a simple discretization approach provide a reasonable approximation of a full simulation. We observe that Decision Trees could be as effective as Neural Networks for the HIC task. The simplicity and performance of the learned Decision Trees could offer a trade-off of a multiple order of magnitude increase in speed and cost improvement over full simulation for a reasonable approximation. When used as a complement to full simulation, the approach enables rapid approximate feedback to engineering teams before submission for full analysis. The approach produces mesh independent features and is further agnostic of the assembly structure.

Keywords: mechanical design validation, FEA, supervised decision tree, convolutional neural network.

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Authors: O. Abiodun Adeyinka, B. Adeyemo Adesesan

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The forensic use of handwriting depends on the analysis, comparison, and evaluation decisions made by forensic document examiners. When using biometric technology in forensic applications, it is necessary to compute Likelihood Ratio (LR) for quantifying strength of evidence under two competing hypotheses, namely the prosecution and the defense hypotheses wherein a set of assumptions and methods for a given data set will be made. It is therefore important to know how repeatable and reproducible our estimated LR is. This paper evaluated the accuracy and reproducibility of examiners' decisions. Confidence interval for the estimated LR were presented so as not get an incorrect estimate that will be used to deliver wrong judgment in the court of Law. The estimate of LR is fundamentally a Bayesian concept and we used two LR estimators, namely Logistic Regression (LoR) and Kernel Density Estimator (KDE) for this paper. The repeatability evaluation was carried out by retesting the initial experiment after an interval of six months to observe whether examiners would repeat their decisions for the estimated LR. The experimental results, which are based on handwriting dataset, show that LR has different confidence intervals which therefore implies that LR cannot be estimated with the same certainty everywhere. Though the LoR performed better than the KDE when tested using the same dataset, the two LR estimators investigated showed a consistent region in which LR value can be estimated confidently. These two findings advance our understanding of LR when used in computing the strength of evidence in handwriting using forensics.

Keywords: confidence interval, handwriting, kernel density estimator, KDE, logistic regression LoR, repeatability, reproducibility

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Authors: Mafarja Majdi, Salwani Abdullah, Najmeh S. Jaddi

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One of the global combinatorial optimization problems in machine learning is feature selection. It concerned with removing the irrelevant, noisy, and redundant data, along with keeping the original meaning of the original data. Attribute reduction in rough set theory is an important feature selection method. Since attribute reduction is an NP-hard problem, it is necessary to investigate fast and effective approximate algorithms. In this paper, we proposed two feature selection mechanisms based on memetic algorithms (MAs) which combine the genetic algorithm with a fuzzy record to record travel algorithm and a fuzzy controlled great deluge algorithm to identify a good balance between local search and genetic search. In order to verify the proposed approaches, numerical experiments are carried out on thirteen datasets. The results show that the MAs approaches are efficient in solving attribute reduction problems when compared with other meta-heuristic approaches.

Keywords: rough set theory, attribute reduction, fuzzy logic, memetic algorithms, record to record algorithm, great deluge algorithm

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Authors: Ayadi Aya, Ghorbel Oussama, M. Obeid Abdulfattah, Abid Mohamed

Abstract:

Nowadays, many wireless sensor networks have been distributed in the real world to collect valuable raw sensed data. The challenge is to extract high-level knowledge from this huge amount of data. However, the identification of outliers can lead to the discovery of useful and meaningful knowledge. In the field of wireless sensor networks, an outlier is defined as a measurement that deviates from the normal behavior of sensed data. Many detection techniques of outliers in WSNs have been extensively studied in the past decade and have focused on classic based algorithms. These techniques identify outlier in the real transaction dataset. This survey aims at providing a structured and comprehensive overview of the existing researches on classification based outlier detection techniques as applicable to WSNs. Thus, we have identified key hypotheses, which are used by these approaches to differentiate between normal and outlier behavior. In addition, this paper tries to provide an easier and a succinct understanding of the classification based techniques. Furthermore, we identified the advantages and disadvantages of different classification based techniques and we presented a comparative guide with useful paradigms for promoting outliers detection research in various WSN applications and suggested further opportunities for future research.

Keywords: bayesian networks, classification-based approaches, KPCA, neural networks, one-class SVM, outlier detection, wireless sensor networks

Procedia PDF Downloads 494

Authors: Daniel Suárez, Jesús Tomas, Sandra Sendra, Sandra Viciano-Tudela, Luis Felipe Calle, Javier Urios, Jaime Lloret

Abstract:

Our study is to develop a tool for the mobile phone to an assessment of body damage or determination of the degree of disability. This is a field of action of legal medicine and insurance with obvious economic implications. Those people who have suffered an accident or bodily harm demand a quantification of it. The assessment of bodily harm or disability by the expert medical professional is not exempt from complexity. Sometimes it is difficult to quantify pain; other times, the doctor faces simulators or exaggerators, and on many occasions, it is difficult to remember the extensive tables of scales whose details are complex to remember and apply. We present a tool, as a mobile application, that allows entering the sociodemographic date of the patient as well as the characteristics of the accident suffered by the person. With these preliminary data and introducing bodily damage, an approximate calculation of the compensation that the injured party should receive can be made. One of the results of this study is that it allows calculating joint mobility angles without the need to use a goniometer.

Keywords: mobile tool, body damage, personal injury and disability, telemedicine

Procedia PDF Downloads 85