Search results for: Markov chain Monte Carlo method
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 20376

Search results for: Markov chain Monte Carlo method

16116 Decoration of Multi-Walled Carbon Nanotubes by CdS Nanoparticles Using Magnetron Sputtering Method

Authors: Z. Ghorannevis, E. Akbarnejad, B. Aghazadeh, M. Ghoranneviss

Abstract:

Carbon nanotubes (CNTs) modified with semiconductor nanocrystalline particles may find wide applications due to their unique properties. Here Cadmium Sulfide (CdS) nanoparticles were successfully grown on Multi-Walled Carbon Nanotubes (MWNTs) via a magnetron sputtering method for the first time. The CdS/MWNTs sample was characterized with X-ray diffraction (XRD), Field Emission Scanning and High Resolution Transmission Electron Microscopies (SEM/TEM) and four point probe. The obtained images show clearly the decoration of the MWNTs by the CdS nanoparticles, and the XRD measurements indicate the CdS structure as hexagonal type. Moreover, the physical properties of the CdS/MWNTs were compared with the physical properties of the CdS nanoparticles grown on the silicon. Electrical measurements of CdS and CdS/MWNTs reveal that CdS/MWNTs has lower resistivity than the CdS sample which may be due to the higher carrier concentrations.

Keywords: CdS, MWNTs, HRTEM, magnetron sputtering

Procedia PDF Downloads 385
16115 Quality Fabric Optimization Using Genetic Algorithms

Authors: Halimi Mohamed Taher, Kordoghli Bassem, Ben Hassen Mohamed, Sakli Faouzi

Abstract:

Textile industry has been an important part of many developing countries economies such as Tunisia. This industry is confronted with a challenging and increasing competitive environment. Good quality management in production process is the key factor for retaining existence especially in raw material exploitation. The present work aims to develop an intelligent system for fabric inspection. In the first step, we have studied the method used for fabric control which takes into account the default length and localization in woven. In the second step, we have used a method based on the fuzzy logic to minimize the Demerit point indicator with appropriate total rollers length, so that the quality problem becomes multi-objective. In order to optimize the total fabric quality, we have applied the genetic algorithm (GA).

Keywords: fabric control, Fuzzy logic, genetic algorithm, quality management

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16114 Developing a Rational Database Management System (RDBMS) Supporting Product Life Cycle Appications

Authors: Yusri Yusof, Chen Wong Keong

Abstract:

This paper presents the implementation details of a Relational Database Management System of a STEP-technology product model repository. It is able support the implementation of any EXPRESS language schema, although it has been primarily implemented to support mechanical product life cycle applications. This database support the input of STEP part 21 file format from CAD in geometrical and topological data format and support a range of queries for mechanical product life cycle applications. This proposed relational database management system uses entity-to-table method (R1) rather than type-to-table method (R4). The two mapping methods have their own strengths and drawbacks.

Keywords: RDBMS, CAD, ISO 10303, part-21 file

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16113 A New Framework for ECG Signal Modeling and Compression Based on Compressed Sensing Theory

Authors: Siavash Eftekharifar, Tohid Yousefi Rezaii, Mahdi Shamsi

Abstract:

The purpose of this paper is to exploit compressed sensing (CS) method in order to model and compress the electrocardiogram (ECG) signals at a high compression ratio. In order to obtain a sparse representation of the ECG signals, first a suitable basis matrix with Gaussian kernels, which are shown to nicely fit the ECG signals, is constructed. Then the sparse model is extracted by applying some optimization technique. Finally, the CS theory is utilized to obtain a compressed version of the sparse signal. Reconstruction of the ECG signal from the compressed version is also done to prove the reliability of the algorithm. At this stage, a greedy optimization technique is used to reconstruct the ECG signal and the Mean Square Error (MSE) is calculated to evaluate the precision of the proposed compression method.

Keywords: compressed sensing, ECG compression, Gaussian kernel, sparse representation

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16112 Antibacterial Activity of Melaleuca Cajuputi Oil against Resistant Strain Bacteria

Authors: R. M. Noah, N. M. Nasir, M. R. Jais, M. S. S. Wahab, M. H. Abdullah, A. S. S. Raj

Abstract:

Infectious diseases are getting more difficult to treat due to the resistant strains of bacteria. Current generations of antibiotics are most likely ineffective against multi-drug resistant strains bacteria. Thus, there is an urgent need in search of natural antibiotics in particular from medicinal plants. One of the common medicinal plants, Melaleuca cajuputi, has been reported to possess antibacterial properties. The study was conducted to evaluate and justify the presence of antibacterial activity of Melaleuca cajuputi essential oil (EO) against the multi-drug resistant bacteria. Clinical isolates obtained from the teaching hospital were re-assessed to confirm the exact identity of the bacteria to be tested, namely methicillin-resistant staphylococcus aureus (MRSA), carbapenem-resistant enterobacteriaceae (CRE), and extended-spectrum beta-lactamases producer (ESBLs). A well diffusion method was done to observe the inhibition zones of the essential oil against the bacteria. Minimum inhibitory concentration (MIC) was determined using the microdilution method in 96-well flat microplate. The absorbance was measured using a microplate reader. Minimum bactericidal concentration (MBC) was performed using the agar medium method. The zones of inhibition produced by the EO against MRSA, CRE, and ESBL were comparable to that of generic antibiotics used, gentamicin and augmentin. The MIC and MBC results highlighted the antimicrobial efficacy of the EO. The outcome of this study indicated that the EO of Melaleuca cajuputi had antibacterial activity on the multi-drug resistant bacteria. This finding was eventually substantiated by electron microscopy work.

Keywords: melaleuca cajuputi, antibacterial, resistant bacteria, essential oil

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16111 Applying Critical Realism to Qualitative Social Work Research: A Critical Realist Approach for Social Work Thematic Analysis Method

Authors: Lynne Soon-Chean Park

Abstract:

Critical Realism (CR) has emerged as an alternative to both the positivist and constructivist perspectives that have long dominated social work research. By unpacking the epistemic weakness of two dogmatic perspectives, CR provides a useful philosophical approach that incorporates the ontological objectivist and subjectivist stance. The CR perspective suggests an alternative approach for social work researchers who have long been looking to engage in the complex interplay between perceived reality at the empirical level and the objective reality that lies behind the empirical event as a causal mechanism. However, despite the usefulness of CR in informing social work research, little practical guidance is available about how CR can inform methodological considerations in social work research studies. This presentation aims to provide a detailed description of CR-informed thematic analysis by drawing examples from a social work doctoral research of Korean migrants’ experiences and understanding of trust associated with their settlement experience in New Zealand. Because of its theoretical flexibility and accessibility as a qualitative analysis method, thematic analysis can be applied as a method that works both to search for the demi-regularities of the collected data and to identify the causal mechanisms that lay behind the empirical data. In so doing, this presentation seeks to provide a concrete and detailed exemplar for social work researchers wishing to employ CR in their qualitative thematic analysis process.

Keywords: critical Realism, data analysis, epistemology, research methodology, social work research, thematic analysis

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16110 Calibration of the Discrete Element Method Using a Large Shear Box

Authors: C. J. Coetzee, E. Horn

Abstract:

One of the main challenges in using the Discrete Element Method (DEM) is to specify the correct input parameter values. In general, the models are sensitive to the input parameter values and accurate results can only be achieved if the correct values are specified. For the linear contact model, micro-parameters such as the particle density, stiffness, coefficient of friction, as well as the particle size and shape distributions are required. There is a need for a procedure to accurately calibrate these parameters before any attempt can be made to accurately model a complete bulk materials handling system. Since DEM is often used to model applications in the mining and quarrying industries, a calibration procedure was developed for materials that consist of relatively large (up to 40 mm in size) particles. A coarse crushed aggregate was used as the test material. Using a specially designed large shear box with a diameter of 590 mm, the confined Young’s modulus (bulk stiffness) and internal friction angle of the material were measured by means of the confined compression test and the direct shear test respectively. DEM models of the experimental setup were developed and the input parameter values were varied iteratively until a close correlation between the experimental and numerical results was achieved. The calibration process was validated by modelling the pull-out of an anchor from a bed of material. The model results compared well with experimental measurement.

Keywords: Discrete Element Method (DEM), calibration, shear box, anchor pull-out

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16109 A DFT-Based QSARs Study of Kovats Retention Indices of Adamantane Derivatives

Authors: Z. Bayat

Abstract:

A quantitative structure–property relationship (QSPR) study was performed to develop models those relate the structures of 65 Kovats retention index (RI) of adamantane derivatives. Molecular descriptors derived solely from 3D structures of the molecular compounds. The usefulness of the quantum chemical descriptors, calculated at the level of the DFT theories using 6-311+G** basis set for QSAR study of adamantane derivatives was examined. The use of descriptors calculated only from molecular structure eliminates the need to experimental determination of properties for use in the correlation and allows for the estimation of RI for molecules not yet synthesized. The prediction results are in good agreement with the experimental value. A multi-parametric equation containing maximum Four descriptors at B3LYP/6-31+G** method with good statistical qualities (R2train=0.913, Ftrain=97.67, R2test=0.770, Ftest=3.21, Q2LOO=0.895, R2adj=0.904, Q2LGO=0.844) was obtained by Multiple Linear Regression using stepwise method.

Keywords: DFT, adamantane, QSAR, Kovat

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16108 Improving Fingerprinting-Based Localization System Using Generative Artificial Intelligence

Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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16107 Magnetic, Magnetocaloric, and Electrical Properties of Pr0.7Ca0.3Mn0.9M0.1O3

Authors: A. Selmi, A. Bettaibi, H. Rahmouni, R. M’nassri, N. Chniba Boudjada, A. Chiekhrouhou, K. Khirouni

Abstract:

Investigation of magnetic and magnetocaloric properties of Pr₀.₇Ca₀.₃Mn₀.₉M₀.₁O₃ perovskite manganites (M=Cr and Ni) has been carried out. Our compounds were prepared by the conventional solid-state reaction method at high temperatures. Rietveld refinement of X-ray diffraction pattern using FULLPROF method shows that all compounds adopt the orthorhombic structure with Pnma space group. The partial substitution of Mn-site drives the system from charge order state to ferromagnetic one with a Curie temperature T𝒸=150K, 118k and 116K for M=Cr and Ni, respectively. Magnetization measurements versus temperature in a magnetic applied field of 0.05T show that all our samples exhibit a paramagnetic–ferromagnetic transition with decreasing temperature. From M(H) isotherms, we have deduced the magnetic entropy change, which present maximum values of 2.37 J/kg.K and 2.94 J/kg.K, in a magnetic field change of 5T for M=Cr and Ni, respectively.

Keywords: manganites, magnetocaloric, magnetic, refrigeration

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16106 The Analysis of Defects Prediction in Injection Molding

Authors: Mehdi Moayyedian, Kazem Abhary, Romeo Marian

Abstract:

This paper presents an evaluation of a plastic defect in injection molding before it occurs in the process; it is known as the short shot defect. The evaluation of different parameters which affect the possibility of short shot defect is the aim of this paper. The analysis of short shot possibility is conducted via SolidWorks Plastics and Taguchi method to determine the most significant parameters. Finite Element Method (FEM) is employed to analyze two circular flat polypropylene plates of 1 mm thickness. Filling time, part cooling time, pressure holding time, melt temperature and gate type are chosen as process and geometric parameters, respectively. A methodology is presented herein to predict the possibility of the short-shot occurrence. The analysis determined melt temperature is the most influential parameter affecting the possibility of short shot defect with a contribution of 74.25%, and filling time with a contribution of 22%, followed by gate type with a contribution of 3.69%. It was also determined the optimum level of each parameter leading to a reduction in the possibility of short shot are gate type at level 1, filling time at level 3 and melt temperature at level 3. Finally, the most significant parameters affecting the possibility of short shot were determined to be melt temperature, filling time, and gate type.

Keywords: injection molding, plastic defects, short shot, Taguchi method

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16105 Feature Analysis of Predictive Maintenance Models

Authors: Zhaoan Wang

Abstract:

Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation

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16104 Concentration of D-Pinitol from Carob Kibble Using Submerged Fermentation by Saccharomyces cerevisiae

Authors: Thi Huong Vu, Vijay Jayasena, Zhongxiang Fang, Gary Dykes

Abstract:

D-pinitol (3-O-methyl ether of D-chiro-inosito) has been known to have health benefits for diabetic patients. Carob kibble has received attention due to the presence of high value D-pinitol and polyphenol antioxidants. D-pinitol was concentrated from carob kibble using submerged fermentation with Saccharomyces cerevisiae. Total carbohydrates and D-pinitol were determined by the phenol-sulphuric acid method and HPLC, respectively. The content of D-pinitol increased from approximately 43 to 70 mg/g dry weight after fermentation. The yeast consumed over 70% of total carbohydrates in carob kibble without any negative effect on D-pinitol content. A range of substrate medium pH’s from 5.0 – 7.0 had no significant effect on the removal of carbohydrates and D-pinitol. This method may provide a practical solution for production of D-pinitol from carob in a cost effective manner.

Keywords: carob kibble, d-pinitol, saccharomyces cerevisiae, submerged fermentation, total carbohydrates

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16103 Studies on Separation of Scandium from Sulfate Environment Using Ion Exchange Technique

Authors: H. Hajmohammadi , A. H. Jafari, M. Eskandari Nasab

Abstract:

The ion exchange method was used to assess the absorption of sulfate media from laboratory-grade materials. The Taguchi method was employed for determining the optimum conditions for scandium adsorption. Results show that optimum conditions for scandium adsorption from sulfate were obtained by Purolite C100 cationic resin in 0.1 g/l sulfuric acid and scandium concentration of 2 g/l at 25 °C. Studies also showed that lowering H₂SO₄ concentration and aqueous phase temperature leads to an increase in Sc adsorption. Visual Minteq software was used to ascertain the various possible cation types and the effect of concentration of scandium ion species on scandium adsorption by cationic resins. The simulation results of the above software show that scandium ion species are often cationic species that are consistent with experimental data.

Keywords: scandium, ion exchange resin, simulation, leach copper

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16102 Spectroscopic Characterization of Indium-Tin Laser Ablated Plasma

Authors: Muhammad Hanif, Muhammad Salik

Abstract:

In the present research work we present the optical emission studies of the Indium (In)-Tin (Sn) plasma produced by the first (1064 nm) harmonic of an Nd: YAG nanosecond pulsed laser. The experimentally observed line profiles of neutral Indium (InI) and Tin (SnI) are used to extract the electron temperature (Te) using the Boltzmann plot method. Whereas, the electron number density (Ne) has been determined from the Stark broadening line profile method. The Te is calculated by varying the distance from the target surface along the line of propagation of plasma plume and also by varying the laser irradiance. Beside we have studied the variation of Ne as a function of laser irradiance as well as its variation with distance from the target surface.

Keywords: indium-tin plasma, laser ablation, optical emission spectroscopy, electron temperature, electron number density

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16101 Effect of Design Parameters on Porpoising Instability of a High Speed Planing Craft

Authors: Lokeswara Rao P., Naga Venkata Rakesh N., V. Anantha Subramanian

Abstract:

It is important to estimate, predict, and avoid the dynamic instability of high speed planing crafts. It is known that design parameters like relative location of center of gravity with respect to the dynamic lift centre and length to beam ratio of the craft have influence on the tendency to porpoise. This paper analyzes the hydrodynamic performance on the basis of the semi-empirical Savitsky method and also estimates the same by numerical simulations based on Reynolds Averaged Navier Stokes (RANS) equations using a commercial code namely, STAR- CCM+. The paper examines through the same numerical simulation considering dynamic equilibrium, the changing running trim, which results in porpoising. Some interesting results emerge from the study and this leads to early detection of the instability.

Keywords: CFD, planing hull, porpoising, Savitsky method

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16100 Structural-Geotechnical Effects of the Foundation of a Medium-Height Structure

Authors: Valentina Rodas, Luis Almache

Abstract:

The interaction effects between the existing soil and the substructure of a 5-story building with an underground one were evaluated in such a way that the structural-geotechnical concepts were validated through the method of impedance factors with a program based on the method of the finite elements. The continuous wall-type foundation had a constant thickness and followed inclined and orthogonal directions, while the ground had homogeneous and medium-type characteristics. The soil considered was type C according to the Ecuadorian Construction Standard (NEC) and the corresponding foundation comprised a depth of 4.00 meters and a basement wall thickness of 40 centimeters. This project is part of a mid-rise building in the city of Azogues (Ecuador). The hypotheses raised responded to the objectives in such a way that the model implemented with springs had a variation with respect to the embedded base, obtaining conservative results.

Keywords: interaction, soil, substructure, springs, effects, modeling , embedment

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16099 [Keynote Talk]: Analysis of One Dimensional Advection Diffusion Model Using Finite Difference Method

Authors: Vijay Kumar Kukreja, Ravneet Kaur

Abstract:

In this paper, one dimensional advection diffusion model is analyzed using finite difference method based on Crank-Nicolson scheme. A practical problem of filter cake washing of chemical engineering is analyzed. The model is converted into dimensionless form. For the grid Ω × ω = [0, 1] × [0, T], the Crank-Nicolson spatial derivative scheme is used in space domain and forward difference scheme is used in time domain. The scheme is found to be unconditionally convergent, stable, first order accurate in time and second order accurate in space domain. For a test problem, numerical results are compared with the analytical ones for different values of parameter.

Keywords: Crank-Nicolson scheme, Lax-Richtmyer theorem, stability, consistency, Peclet number, Greschgorin circle

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16098 The Inversion of Helical Twist Sense in Liquid Crystal by Spectroscopy Methods

Authors: Anna Drzewicz, Marzena Tykarska

Abstract:

The chiral liquid crystal phases form the helicoidal structure, which is characterized by the helical pitch and the helical twist sense. In anticlinic smectic phase with antiferroelectric properties three types of helix temperature dependence have been obtained: increased helical pitch with temperature and right-handed helix, decreased helical pitch with temperature and left-handed helix and the inversion of both. The change of helical twist sense may be observed during the transition from one liquid crystal phase to another or within one phase for the same substance. According to Gray and McDonnell theory, the helical handedness depends on the absolute configuration of the assymetric carbon atom and its position related to the rigid core of the molecule. However, this theory does not explain the inversion of helical twist sense phenomenon. It is supposed, that it may be caused by the presence of different conformers with opposite handendess, which concentration may change with temperature. In this work, the inversion of helical twist sense in the chiral liquid crystals differing in the length of alkyl chain, in the substitution the benzene ring by fluorine atoms and in the type of helix handedness was tested by vibrational spectroscopy (infrared and raman spectroscopy) and by nuclear magnetic resonance spectroscopy. The results obtained from the vibrational spectroscopy confirm the presence of different conformers. Moreover, the analysis of nuclear magnetic resonance spectra is very useful to check, on which structural fragments the change of conformations are important for the change of helical twist sense.

Keywords: helical twist sense, liquid crystals, nuclear magnetic resonance spectroscopy, vibrational spectroscopy

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16097 The Treatment of Nitrate Polluted Groundwater Using Bio-electrochemical Systems Inoculated with Local Groundwater Sediments

Authors: Danish Laidin, Peter Gostomski, Aaron Marshall, Carlo Carere

Abstract:

Groundwater contamination of nitrate (NO3-) is becoming more prevalent in regions of intensive and extensive agricultural activities. Household nitrate removal involves using ion exchange membranes and reverse osmosis (RO) systems, whereas industrial nitrate removal may use organic carbon substrates (e.g. methanol) for heterotrophic microbial denitrification. However, these approaches both require high capital investment and operating costs. In this study, denitrification was demonstrated using bio-electrochemical systems (BESs) inoculated from sediments and microbial enrichment cultures. The BES reactors were operated continuously as microbial electrolytic cells (MECs) with a poised potential of -0.7V and -1.1V vs Ag/AgCl. Three parallel MECs were inoculated using hydrogen-driven denitrifying enrichments, stream sediments, and biofilm harvested from a denitrifying biotrickling filter, respectively. These reactors were continuously operated for over a year as various operating conditions were investigated to determine the optimal conditions for electroactive denitrification. The mass loading rate of nitrate was varied between 10 – 70 mg NO3-/d, and the maximum observed nitrate removal rate was 22 mg NO3- /(cm2∙d) with a current of 2.1 mA. For volumetric load experiments, the dilution rate of 1 mM NO3- feed was varied between 0.01 – 0.1 hr-1 to achieve a nitrate loading rate similar to the mass loading rate experiments. Under these conditions, the maximum rate of denitrification observed was 15.8 mg NO3- /(cm2∙d) with a current of 1.7mA. Hydrogen (H2) was supplied intermittently to investigate the hydrogenotrophic potential of the denitrifying biofilm electrodes. H2 supplementation at 0.1 mL/min resulted in an increase of nitrate removal from 0.3 mg NO3- /(cm2∙d) to 3.4 mg NO3- /(cm2∙d) in the hydrogenotrophically subcultured reactor but had no impact on the reactors which exhibited direct electron transfer properties. Results from this study depict the denitrification performance of the immobilized biofilm electrodes, either by direct electron transfer or hydrogen-driven denitrification, and the contribution of the planktonic cells present in the growth medium. Other results will include the microbial community analysis via 16s rDNA amplicon sequencing, varying the effect of poising cathodic potential from 0.7V to 1.3V vs Ag/AgCl, investigating the potential of using in-situ electrochemically produced hydrogen for autotrophic denitrification and adjusting the conductivity of the feed solution to mimic groundwater conditions. These findings highlight the overall performance of sediment inoculated MECs in removing nitrate and will be used for the future development of sustainable solutions for the treatment of nitrate polluted groundwater.

Keywords: bio-electrochemical systems, groundwater, electroactive denitrification, microbial electrolytic cell

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16096 Application of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Multipoint Optimal Minimum Entropy Deconvolution in Railway Bearings Fault Diagnosis

Authors: Yao Cheng, Weihua Zhang

Abstract:

Although the measured vibration signal contains rich information on machine health conditions, the white noise interferences and the discrete harmonic coming from blade, shaft and mash make the fault diagnosis of rolling element bearings difficult. In order to overcome the interferences of useless signals, a new fault diagnosis method combining Complete Ensemble Empirical Mode Decomposition with adaptive noise (CEEMDAN) and Multipoint Optimal Minimum Entropy Deconvolution (MOMED) is proposed for the fault diagnosis of high-speed train bearings. Firstly, the CEEMDAN technique is applied to adaptively decompose the raw vibration signal into a series of finite intrinsic mode functions (IMFs) and a residue. Compared with Ensemble Empirical Mode Decomposition (EEMD), the CEEMDAN can provide an exact reconstruction of the original signal and a better spectral separation of the modes, which improves the accuracy of fault diagnosis. An effective sensitivity index based on the Pearson's correlation coefficients between IMFs and raw signal is adopted to select sensitive IMFs that contain bearing fault information. The composite signal of the sensitive IMFs is applied to further analysis of fault identification. Next, for propose of identifying the fault information precisely, the MOMED is utilized to enhance the periodic impulses in composite signal. As a non-iterative method, the MOMED has better deconvolution performance than the classical deconvolution methods such Minimum Entropy Deconvolution (MED) and Maximum Correlated Kurtosis Deconvolution (MCKD). Third, the envelope spectrum analysis is applied to detect the existence of bearing fault. The simulated bearing fault signals with white noise and discrete harmonic interferences are used to validate the effectiveness of the proposed method. Finally, the superiorities of the proposed method are further demonstrated by high-speed train bearing fault datasets measured from test rig. The analysis results indicate that the proposed method has strong practicability.

Keywords: bearing, complete ensemble empirical mode decomposition with adaptive noise, fault diagnosis, multipoint optimal minimum entropy deconvolution

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16095 The Wellness Wheel: A Tool to Reimagine Schooling

Authors: Jennifer F. Moore

Abstract:

The wellness wheel as a tool for school growth and change is currently being piloted by a startup school in Chicago, IL. In this case study, members of the school community engaged in the appreciative inquiry process to plan their organizational development around the wellness wheel. The wellness wheel (comprised of physical, emotional, social, spiritual, environmental, cognitive, and financial wellness) is used as a planning tool by teachers, students, parents, and administrators. Through the appreciative inquiry method of change, the community is reflecting on their individual level of wellness and developing organizational structures to ensure the well being of children and adults. The goal of the case study is to test the appropriateness of the use of appreciative inquiry (as a method) and the wellness wheel (as a tool) for school growth and development. Findings of the case study will be realized by the conference. The research is in process now.

Keywords: education, schools, well being, wellness

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16094 An Assessment of Vegetable Farmers’ Perceptions about Post-harvest Loss Sources in Ghana

Authors: Kofi Kyei, Kenchi Matsui

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Loss of vegetable products has been a major constraint in the post-harvest chain. Sources of post-harvest loss in the vegetable industry start from the time of harvesting to its handling and at the various market centers. Identifying vegetable farmers’ perceptions about post-harvest loss sources is one way of addressing this issue. In this paper, we assessed farmers’ perceptions about sources of post-harvest losses in the Ashanti Region of Ghana. We also identified the factors that influence their perceptions. To clearly understand farmers’ perceptions, we selected Sekyere-Kumawu District in the Ashanti Region. Sekyere-Kumawu District is one of the major producers of vegetables in the Region. Based on a questionnaire survey, 100 vegetable farmers growing tomato, pepper, okra, cabbage, and garden egg were purposely selected from five communities in Sekyere-Kumawu District. For farmers’ perceptions, the five points Likert scale was employed. On a scale from 1 (no loss) to 5 (extremely high loss), we processed the scores for each vegetable harvest. To clarify factors influencing farmers’ perceptions, the Pearson Correlation analysis was used. Our findings revealed that farmers perceive post-harvest loss by pest infestation as the most extreme loss. However, vegetable farmers did not perceive loss during transportation as a serious source of post-harvest loss. The Pearson Correlation analysis results further revealed that farmers’ age, gender, level of education, and years of experience had an influence on their perceptions. This paper then discusses some recommendations to minimize the post-harvest loss in the region.

Keywords: Ashanti Region, pest infestation, post-harvest loss, vegetable farmers

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16093 The Complete Modal Derivatives

Authors: Sebastian Andersen, Peter N. Poulsen

Abstract:

The use of basis projection in the structural dynamic analysis is frequently applied. The purpose of the method is to improve the computational efficiency, while maintaining a high solution accuracy, by projection the governing equations onto a small set of carefully selected basis vectors. The present work considers basis projection in kinematic nonlinear systems with a focus on two widely used basis vectors; the system mode shapes and their modal derivatives. Particularly the latter basis vectors are given special attention since only approximate modal derivatives have been used until now. In the present work the complete modal derivatives, derived from perturbation methods, are presented and compared to the previously applied approximate modal derivatives. The correctness of the complete modal derivatives is illustrated by use of an example of a harmonically loaded kinematic nonlinear structure modeled by beam elements.

Keywords: basis projection, finite element method, kinematic nonlinearities, modal derivatives

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16092 Stress Variation of Underground Building Structure during Top-Down Construction

Authors: Soo-yeon Seo, Seol-ki Kim, Su-jin Jung

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In the construction of a building, it is necessary to minimize construction period and secure enough work space for stacking of materials during the construction especially in city area. In this manner, various top-down construction methods have been developed and widely used in Korea. This paper investigates the stress variation of underground structure of a building constructed by using SPS (Strut as Permanent System) known as a top-down method in Korea through an analytical approach. Various types of earth pressure distribution related to ground condition were considered in the structural analysis of an example structure at each step of the excavation. From the analysis, the most high member force acting on beams was found when the ground type was medium sandy soil and a stress concentration was found in corner area.

Keywords: construction of building, top-down construction method, earth pressure distribution, member force, stress concentration

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16091 Effect of Zinc-Lysine on Growth, Photosynthesis, Oxidative Stress and Antioxidant System and Chromium Uptake in Rice under Cr Stress

Authors: Shafaqat Ali, Afzal Hussain, Muhammad Rizwan, Longhua Wu

Abstract:

Chromium (Cr) is one of the widespread and toxic trace elements present in the agricultural land. Chromium can enter into the food chain mainly through agricultural crops grown on Cr-contaminated soils such as rice (Oryza sativa L.). The current study was done to evaluate the effects of increasing concentrations foliar applied zinc (Zn) chelated with lysine (Zn-lys) (0, 10, 20, and 30 mg L⁻¹) on rice biomass, photosynthesis, oxidative stress, key antioxidant enzyme activities and Cr uptake under increasing levels of Cr in the soil (0, 100, 500 mg kg⁻¹). Cr-induced toxicity reduced the height of plants, biomass, chlorophyll contents, gas exchange parameters, and antioxidant enzyme activities while increased the Cr concentrations and oxidative stress (malondialdehyde, electrolyte leakage, and H₂O₂) in shoots and roots than control plants. Foliar application of Zn-lys increased the plant growth, photosynthesis, Zn concentrations, and enzyme activities in rice seedlings. In addition, Zn-lys reduced the Cr concentrations and oxidative stress compared to the respective Cr treatments alone. The present results indicate that foliar Zn-lys stimulates the antioxidant defense system in rice, increase the rice growth while reduced the Cr concentrations in plants by promoting the Zn uptake and photosynthesis. Taken together, foliar spray of Zn-lys chelate can efficiently be employed for improving plant growth and Zn contents while reducing Cr concentration in rice grown in Cr-contaminated and Zn-deficient soils.

Keywords: antioxidants, chromium, zinc-lysine, oxidative stress, photosynthesis, tolerance

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16090 Method of Cluster Based Cross-Domain Knowledge Acquisition for Biologically Inspired Design

Authors: Shen Jian, Hu Jie, Ma Jin, Peng Ying Hong, Fang Yi, Liu Wen Hai

Abstract:

Biologically inspired design inspires inventions and new technologies in the field of engineering by mimicking functions, principles, and structures in the biological domain. To deal with the obstacles of cross-domain knowledge acquisition in the existing biologically inspired design process, functional semantic clustering based on functional feature semantic correlation and environmental constraint clustering composition based on environmental characteristic constraining adaptability are proposed. A knowledge cell clustering algorithm and the corresponding prototype system is developed. Finally, the effectiveness of the method is verified by the visual prosthetic device design.

Keywords: knowledge clustering, knowledge acquisition, knowledge based engineering, knowledge cell, biologically inspired design

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16089 Theoretical Modeling of Self-Healing Polymers Crosslinked by Dynamic Bonds

Authors: Qiming Wang

Abstract:

Dynamic polymer networks (DPNs) crosslinked by dynamic bonds have received intensive attention because of their special crack-healing capability. Diverse DPNs have been synthesized using a number of dynamic bonds, including dynamic covalent bond, hydrogen bond, ionic bond, metal-ligand coordination, hydrophobic interaction, and others. Despite the promising success in the polymer synthesis, the fundamental understanding of their self-healing mechanics is still at the very beginning. Especially, a general analytical model to understand the interfacial self-healing behaviors of DPNs has not been established. Here, we develop polymer-network based analytical theories that can mechanistically model the constitutive behaviors and interfacial self-healing behaviors of DPNs. We consider that the DPN is composed of interpenetrating networks crosslinked by dynamic bonds. bonds obey a force-dependent chemical kinetics. During the self-healing process, we consider the The network chains follow inhomogeneous chain-length distributions and the dynamic polymer chains diffuse across the interface to reform the dynamic bonds, being modeled by a diffusion-reaction theory. The theories can predict the stress-stretch behaviors of original and self-healed DPNs, as well as the healing strength in a function of healing time. We show that the theoretically predicted healing behaviors can consistently match the documented experimental results of DPNs with various dynamic bonds, including dynamic covalent bonds (diarylbibenzofuranone and olefin metathesis), hydrogen bonds, and ionic bonds. We expect our model to be a powerful tool for the self-healing community to invent, design, understand, and optimize self-healing DPNs with various dynamic bonds.

Keywords: self-healing polymers, dynamic covalent bonds, hydrogen bonds, ionic bonds

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16088 Farmers’ Use of Indigenous Knowledge System (IKS) for Selected Arable Crops Production in Ondo State

Authors: A. M. Omoare, E. O. Fakoya

Abstract:

This study sought to determine the use of indigenous knowledge for selected arable crops production in Ondo Sate. A multistage sampling method was used and 112 arable crops farmers were systematically selected. Data were analyzed using both descriptive and inferential statistics. The results showed that majority of the sampled farmers were male (75.90%) About 75% were married with children. Large proportion of them (62.61%) were within the ages of 30-49 years. Most of them have spent about 10 years in farming (58.92%). The highest raw scores of use of indigenous knowledge were found in planting on mound in yam production, use of native medicine and scare-crow method in controlling birds in rice production, timely planting of locally developed resistant varieties in cassava production and soaking of maize seeds in water to determine their viability with raw scores of 313, 310, 305, 303, and 300 respectively, while the lowest raw scores was obtained in use of bell method in controlling birds in rice production with raw scores of 210. The findings established that proverbs (59.8%) and taboos (55.36%) were the most commonly used media in transmitting indigenous knowledge by arable crop farmers. The multiple regression analysis result revealed that age of the farmers and farming experience had a significant relationship with the use of indigenous knowledge of the farmers which gave R2=0.83 for semi-log function form of equation which is the land equation. The policy implication is that indigenous knowledge should provide a basis for designing modern technologies to enhance sustainable agricultural development.

Keywords: Arable Crop Production, extent of use, indigenous knowledge, farming experience

Procedia PDF Downloads 556
16087 Automatic Identification of Pectoral Muscle

Authors: Ana L. M. Pavan, Guilherme Giacomini, Allan F. F. Alves, Marcela De Oliveira, Fernando A. B. Neto, Maria E. D. Rosa, Andre P. Trindade, Diana R. De Pina

Abstract:

Mammography is a worldwide image modality used to diagnose breast cancer, even in asymptomatic women. Due to its large availability, mammograms can be used to measure breast density and to predict cancer development. Women with increased mammographic density have a four- to sixfold increase in their risk of developing breast cancer. Therefore, studies have been made to accurately quantify mammographic breast density. In clinical routine, radiologists perform image evaluations through BIRADS (Breast Imaging Reporting and Data System) assessment. However, this method has inter and intraindividual variability. An automatic objective method to measure breast density could relieve radiologist’s workload by providing a first aid opinion. However, pectoral muscle is a high density tissue, with similar characteristics of fibroglandular tissues. It is consequently hard to automatically quantify mammographic breast density. Therefore, a pre-processing is needed to segment the pectoral muscle which may erroneously be quantified as fibroglandular tissue. The aim of this work was to develop an automatic algorithm to segment and extract pectoral muscle in digital mammograms. The database consisted of thirty medio-lateral oblique incidence digital mammography from São Paulo Medical School. This study was developed with ethical approval from the authors’ institutions and national review panels under protocol number 3720-2010. An algorithm was developed, in Matlab® platform, for the pre-processing of images. The algorithm uses image processing tools to automatically segment and extract the pectoral muscle of mammograms. Firstly, it was applied thresholding technique to remove non-biological information from image. Then, the Hough transform is applied, to find the limit of the pectoral muscle, followed by active contour method. Seed of active contour is applied in the limit of pectoral muscle found by Hough transform. An experienced radiologist also manually performed the pectoral muscle segmentation. Both methods, manual and automatic, were compared using the Jaccard index and Bland-Altman statistics. The comparison between manual and the developed automatic method presented a Jaccard similarity coefficient greater than 90% for all analyzed images, showing the efficiency and accuracy of segmentation of the proposed method. The Bland-Altman statistics compared both methods in relation to area (mm²) of segmented pectoral muscle. The statistic showed data within the 95% confidence interval, enhancing the accuracy of segmentation compared to the manual method. Thus, the method proved to be accurate and robust, segmenting rapidly and freely from intra and inter-observer variability. It is concluded that the proposed method may be used reliably to segment pectoral muscle in digital mammography in clinical routine. The segmentation of the pectoral muscle is very important for further quantifications of fibroglandular tissue volume present in the breast.

Keywords: active contour, fibroglandular tissue, hough transform, pectoral muscle

Procedia PDF Downloads 337