Search results for: emission modeling
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5254

Search results for: emission modeling

2434 Rational Probabilistic Method for Calculating Thermal Cracking Risk of Mass Concrete Structures

Authors: Naoyuki Sugihashi, Toshiharu Kishi

Abstract:

The probability of occurrence of thermal cracks in mass concrete in Japan is evaluated by the cracking probability diagram that represents the relationship between the thermal cracking index and the probability of occurrence of cracks in the actual structure. In this paper, we propose a method to directly calculate the cracking probability, following a probabilistic theory by modeling the variance of tensile stress and tensile strength. In this method, the relationship between the variance of tensile stress and tensile strength, the thermal cracking index, and the cracking probability are formulated and presented. In addition, standard deviation of tensile stress and tensile strength was identified, and the method of calculating cracking probability in a general construction controlled environment was also demonstrated.

Keywords: thermal crack control, mass concrete, thermal cracking probability, durability of concrete, calculating method of cracking probability

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2433 Topic Sentiments toward the COVID-19 Vaccine on Twitter

Authors: Melissa Vang, Raheyma Khan, Haihua Chen

Abstract:

The coronavirus disease 2019 (COVID‐19) pandemic has changed people's lives from all over the world. More people have turned to Twitter to engage online and discuss the COVID-19 vaccine. This study aims to present a text mining approach to identify people's attitudes towards the COVID-19 vaccine on Twitter. To achieve this purpose, we collected 54,268 COVID-19 vaccine tweets from September 01, 2020, to November 01, 2020, then the BERT model is used for the sentiment and topic analysis. The results show that people had more negative than positive attitudes about the vaccine, and countries with an increasing number of confirmed cases had a higher percentage of negative attitudes. Additionally, the topics discussed in positive and negative tweets are different. The tweet datasets can be helpful to information professionals to inform the public about vaccine-related informational resources. Our findings may have implications for understanding people's cognitions and feelings about the vaccine.

Keywords: BERT, COVID-19 vaccine, sentiment analysis, topic modeling

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2432 Evaluation of Elements Impurities in Drugs According to Pharmacopoeia by use FESEM-EDS Technique

Authors: Rafid Doulab

Abstract:

Elemental Impurities in the Pharmaceuticals industryis are indispensable to ensure pharmaceuticalssafety for 24 elements. Although atomic absorption and inductively coupled plasma are used in the U.S Pharmacopeia and the European Pharmacopoeia, FESEM with energy dispersive spectrometers can be applied as an alternative analysis method for quantitative and qualitative results for a variety of elements without chemical pretreatment, unlike other techniques. This technique characterizes by shortest time, with more less contamination, no reagent consumption, and generation of minimal residue or waste, as well as sample preparations time limiting, with minimal analysis error. Simple dilution for powder or direct analysis for liquid, we analyzed the usefulness of EDS method in testing with field emission scanning electron microscopy (FESEM, SUPRA 55 Carl Zeiss Germany) with an X-ray energy dispersion (XFlash6l10 Bruker Germany). The samples analyzed directly without coating by applied 5µ of known concentrated diluted sample on carbon stub with accelerated voltage according to sample thickness, the result for this spot was in atomic percentage, and by Avogadro converted factor, the final result will be in microgram. Conclusion and recommendation: The conclusion of this study is application of FESEM-EDS in US pharmacopeia and ICH /Q3D guideline to reach a high-precision and accurate method in element impurities analysis of drugs or bulk materials to determine the permitted daily exposure PDE in liquid or solid specimens, and to obtain better results than other techniques, by the way it does not require complex methods or chemicals for digestion, which interfere with the final results with the possibility of to keep the sample at any time for re analysis. The recommendation is to use this technique in pharmacopeia as standard methods like inductively coupled plasma both ICP-AES, ICP-OES, and ICP-MS.

Keywords: pharmacopoeia, FESEM-EDS, element impurities, atomic concentration

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2431 Assessing Social Vulnerability and Policy Adaption Application Responses Based on Landslide Risk Map

Authors: Z. A. Ahmad, R. C. Omar, I. Z. Baharuddin, R. Roslan

Abstract:

Assessments of social vulnerability, carried out holistically, can provide an important guide to the planning process and to decisions on resource allocation at various levels, and can help to raise public awareness of geo-hazard risks. The assessments can help to provide answers for basic questions such as the human vulnerability at the geo-hazard prone or disaster areas causing health damage, economic loss, loss of natural heritage and vulnerability impact of extreme natural hazard event. To overcome these issues, integrated framework for assessing the increasing human vulnerability to environmental changes caused by geo-hazards will be introduced using an indicator from landslide risk map that is related to agent based modeling platform. The indicators represent the underlying factors, which influence a community’s ability to deal with and recover from the damage associated with geo-hazards. Scope of this paper is particularly limited to landslides.

Keywords: social, vulnerability, geo-hazard, methodology, indicators

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2430 Single Cell Rna Sequencing Operating from Benchside to Bedside: An Interesting Entry into Translational Genomics

Authors: Leo Nnamdi Ozurumba-Dwight

Abstract:

Single-cell genomic analytical systems have proved to be a platform to isolate bulk cells into selected single cells for genomic, proteomic, and related metabolomic studies. This is enabling systematic investigations of the level of heterogeneity in a diverse and wide pool of cell populations. Single cell technologies, embracing techniques such as high parameter flow cytometry, single-cell sequencing, and high-resolution images are playing vital roles in these investigations on messenger ribonucleic acid (mRNA) molecules and related gene expressions in tracking the nature and course of disease conditions. This entails targeted molecular investigations on unit cells that help us understand cell behavoiur and expressions, which can be examined for their health implications on the health state of patients. One of the vital good sides of single-cell RNA sequencing (scRNA seq) is its probing capacity to detect deranged or abnormal cell populations present within homogenously perceived pooled cells, which would have evaded cursory screening on the pooled cell populations of biological samples obtained as part of diagnostic procedures. Despite conduction of just single-cell transcriptome analysis, scRNAseq now permits comparison of the transcriptome of the individual cells, which can be evaluated for gene expressional patterns that depict areas of heterogeneity with pharmaceutical drug discovery and clinical treatment applications. It is vital to strictly work through the tools of investigations from wet lab to bioinformatics and computational tooled analyses. In the precise steps for scRNAseq, it is critical to do thorough and effective isolation of viable single cells from the tissues of interest using dependable techniques (such as FACS) before proceeding to lysis, as this enhances the appropriate picking of quality mRNA molecules for subsequent sequencing (such as by the use of Polymerase Chain Reaction machine). Interestingly, scRNAseq can be deployed to analyze various types of biological samples such as embryos, nervous systems, tumour cells, stem cells, lymphocytes, and haematopoietic cells. In haematopoietic cells, it can be used to stratify acute myeloid leukemia patterns in patients, sorting them out into cohorts that enable re-modeling of treatment regimens based on stratified presentations. In immunotherapy, it can furnish specialist clinician-immunologist with tools to re-model treatment for each patient, an attribute of precision medicine. Finally, the good predictive attribute of scRNAseq can help reduce the cost of treatment for patients, thus attracting more patients who would have otherwise been discouraged from seeking quality clinical consultation help due to perceived high cost. This is a positive paradigm shift for patients’ attitudes primed towards seeking treatment.

Keywords: immunotherapy, transcriptome, re-modeling, mRNA, scRNA-seq

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2429 Two-Dimensional Modeling of Spent Nuclear Fuel Using FLUENT

Authors: Imane Khalil, Quinn Pratt

Abstract:

In a nuclear reactor, an array of fuel rods containing stacked uranium dioxide pellets clad with zircalloy is the heat source for a thermodynamic cycle of energy conversion from heat to electricity. After fuel is used in a nuclear reactor, the assemblies are stored underwater in a spent nuclear fuel pool at the nuclear power plant while heat generation and radioactive decay rates decrease before it is placed in packages for dry storage or transportation. A computational model of a Boiling Water Reactor spent fuel assembly is modeled using FLUENT, the computational fluid dynamics package. Heat transfer simulations were performed on the two-dimensional 9x9 spent fuel assembly to predict the maximum cladding temperature for different input to the FLUENT model. Uncertainty quantification is used to predict the heat transfer and the maximum temperature profile inside the assembly.

Keywords: spent nuclear fuel, conduction, heat transfer, uncertainty quantification

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2428 Using Probabilistic Neural Network (PNN) for Extracting Acoustic Microwaves (Bulk Acoustic Waves) in Piezoelectric Material

Authors: Hafdaoui Hichem, Mehadjebia Cherifa, Benatia Djamel

Abstract:

In this paper, we propose a new method for Bulk detection of an acoustic microwave signal during the propagation of acoustic microwaves in a piezoelectric substrate (Lithium Niobate LiNbO3). We have used the classification by probabilistic neural network (PNN) as a means of numerical analysis in which we classify all the values of the real part and the imaginary part of the coefficient attenuation with the acoustic velocity in order to build a model from which we note the Bulk waves easily. These singularities inform us of presence of Bulk waves in piezoelectric materials. By which we obtain accurate values for each of the coefficient attenuation and acoustic velocity for Bulk waves. This study will be very interesting in modeling and realization of acoustic microwaves devices (ultrasound) based on the propagation of acoustic microwaves.

Keywords: piezoelectric material, probabilistic neural network (PNN), classification, acoustic microwaves, bulk waves, the attenuation coefficient

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2427 Measuring Banking Risk

Authors: Mike Tsionas

Abstract:

The paper develops new indices of financial stability based on an explicit model of expected utility maximization by financial institutions subject to the classical technology restrictions of neoclassical production theory. The model can be estimated using standard econometric techniques, like GMM for dynamic panel data and latent factor analysis for the estimation of co-variance matrices. An explicit functional form for the utility function is not needed and we show how measures of risk aversion and prudence (downside risk aversion) can be derived and estimated from the model. The model is estimated using data for Eurozone countries and we focus particularly on (i) the use of the modeling approach as an “early warning mechanism”, (ii) the bank- and country-specific estimates of risk aversion and prudence (downside risk aversion), and (iii) the derivation of a generalized measure of risk that relies on loan-price uncertainty.

Keywords: financial stability, banking, expected utility maximization, sub-prime crisis, financial crisis, eurozone, PIIGS

Procedia PDF Downloads 344
2426 Characterization of Single-Walled Carbon Nano Tubes Forest Decorated with Chromium

Authors: Ana Paula Mousinho, Ronaldo D. Mansano, Nelson Ordonez

Abstract:

Carbon nanotubes are one of the main elements in nanotechnologies; their applications are in microelectronics, nano-electronics devices (photonics, spintronic), chemical sensors, structural material and currently in clean energy devices (supercapacitors and fuel cells). The use of magnetic particle decorated carbon nanotubes increases the applications in magnetic devices, magnetic memory, and magnetic oriented drug delivery. In this work, single-walled carbon nanotubes (CNTs) forest decorated with chromium were deposited at room temperature by high-density plasma chemical vapor deposition (HDPCVD) system. The CNTs forest was obtained using pure methane plasmas and chromium, as precursor material (seed) and for decorating the CNTs. Magnetron sputtering deposited the chromium on silicon wafers before the CNTs' growth. Scanning electron microscopy, atomic force microscopy, micro-Raman spectroscopy, and X-ray diffraction characterized the single-walled CNTs forest decorated with chromium. In general, the CNTs' spectra show a unique emission band, but due to the presence of the chromium, the spectra obtained in this work showed many bands that are related to the CNTs with different diameters. The CNTs obtained by the HDPCVD system are highly aligned and showed metallic features, and they can be used as photonic material, due to the unique structural and electrical properties. The results of this work proved the possibility of obtaining the controlled deposition of aligned single-walled CNTs forest films decorated with chromium by high-density plasma chemical vapor deposition system.

Keywords: CNTs forest, high density plasma deposition, high-aligned CNTs, nanomaterials

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2425 Nonparametric Specification Testing for the Drift of the Short Rate Diffusion Process Using a Panel of Yields

Authors: John Knight, Fuchun Li, Yan Xu

Abstract:

Based on a new method of the nonparametric estimator of the drift function, we propose a consistent test for the parametric specification of the drift function in the short rate diffusion process using observations from a panel of yields. The test statistic is shown to follow an asymptotic normal distribution under the null hypothesis that the parametric drift function is correctly specified, and converges to infinity under the alternative. Taking the daily 7-day European rates as a proxy of the short rate, we use our test to examine whether the drift of the short rate diffusion process is linear or nonlinear, which is an unresolved important issue in the short rate modeling literature. The testing results indicate that none of the drift functions in this literature adequately captures the dynamics of the drift, but nonlinear specification performs better than the linear specification.

Keywords: diffusion process, nonparametric estimation, derivative security price, drift function and volatility function

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2424 Text Similarity in Vector Space Models: A Comparative Study

Authors: Omid Shahmirzadi, Adam Lugowski, Kenneth Younge

Abstract:

Automatic measurement of semantic text similarity is an important task in natural language processing. In this paper, we evaluate the performance of different vector space models to perform this task. We address the real-world problem of modeling patent-to-patent similarity and compare TFIDF (and related extensions), topic models (e.g., latent semantic indexing), and neural models (e.g., paragraph vectors). Contrary to expectations, the added computational cost of text embedding methods is justified only when: 1) the target text is condensed; and 2) the similarity comparison is trivial. Otherwise, TFIDF performs surprisingly well in other cases: in particular for longer and more technical texts or for making finer-grained distinctions between nearest neighbors. Unexpectedly, extensions to the TFIDF method, such as adding noun phrases or calculating term weights incrementally, were not helpful in our context.

Keywords: big data, patent, text embedding, text similarity, vector space model

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2423 Risk Management of Water Derivatives: A New Commodity in The Market

Authors: Daniel Mokatsanyane, Johnny Jansen Van Rensburg

Abstract:

This paper is a concise introduction of the risk management on the water derivatives market. Water, a new commodity in the market, is one of the most important commodity on earth. As important to life and planet as crops, metals, and energy, none of them matters without water. This paper presents a brief overview of water as a tradable commodity via a new first of its kind futures contract on the Nasdaq Veles California Water Index (NQH2O) derivative instrument, TheGeneralised Autoregressive Conditional Heteroscedasticity (GARCH) statistical model will be the used to measure the water price volatility of the instrument and its performance since it’s been traded. describe the main products and illustrate their usage in risk management and also discuss key challenges with modeling and valuation of water as a traded commodity and finally discuss how water derivatives may be taken as an alternative asset investment class.

Keywords: water derivatives, commodity market, nasdaq veles california water Index (NQH2O, water price, risk management

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2422 Vibration Propagation in Body-in-White Structures Through Structural Intensity Analysis

Authors: Jamal Takhchi

Abstract:

The understanding of vibration propagation in complex structures such as automotive body in white remains a challenging issue in car design regarding NVH performances. The current analysis is limited to the low frequency range where modal concepts are dominant. Higher frequencies, between 200 and 1000 Hz, will become critical With the rise of electrification. EVs annoying sounds are mostly whines created by either Gears or e-motors between 300 Hz and 2 kHz. Structural intensity analysis was Experienced a few years ago on finite element models. The application was promising but limited by the fact that the propagating 3D intensity vector field is masked by a rotational Intensity field. This rotational field should be filtered using a differential operator. The expression of this operator in the framework of finite element modeling is not yet known. The aim of the proposed work is to implement this operator in the current dynamic solver (NASTRAN) of Stellantis and develop the Expected methodology for the mid-frequency structural analysis of electrified vehicles.

Keywords: structural intensity, NVH, body in white, irrotatational intensity

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2421 Study on Novel Reburning Process for NOx Reduction by Oscillating Injection of Reburn Fuel

Authors: Changyeop Lee, Sewon Kim, Jongho Lee

Abstract:

Reburning technology has been developed to adopt various commercial combustion systems. Fuel lean reburning is an advanced reburning method to reduce NOx economically without using burnout air, however it is not easy to get high NOx reduction efficiency. In the fuel lean reburning system, the localized fuel rich eddies are used to establish partial fuel rich regions so that the NOx can react with hydrocarbon radical restrictively. In this paper, a new advanced reburning method which supplies reburn fuel with oscillatory motion is introduced to increase NOx reduction rate effectively. To clarify whether forced oscillating injection of reburn fuel can effectively reduce NOx emission, experimental tests were conducted in vertical combustion furnace. Experiments were performed in flames stabilized by a gas burner, which was mounted at the bottom of the furnace. The natural gas is used as both main and reburn fuel and total thermal input is about 40kW. The forced oscillating injection of reburn fuel is realized by electronic solenoid valve, so that fuel rich region and fuel lean region is established alternately. In the fuel rich region, NOx is converted to N2 by reburning reaction, however unburned hydrocarbon and CO is oxidized in fuel lean zone and mixing zone at downstream where slightly fuel lean region is formed by mixing of two regions. This paper reports data on flue gas emissions and temperature distribution in the furnace for a wide range of experimental conditions. All experimental data has been measured at steady state. The NOx reduction rate increases up to 41% by forced oscillating reburn motion. The CO emissions were shown to be kept at very low level. And this paper makes clear that in order to decrease NOx concentration in the exhaust when oscillating reburn fuel injection system is adopted, the control of factors such as frequency and duty ratio is very important.

Keywords: NOx, CO, reburning, pollutant

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2420 Study of the Physicochemical Characteristics of Liquid Effluents from the El Jadida Wastewater Treatment Plant

Authors: Aicha Assal, El Mostapha Lotfi

Abstract:

Rapid industrialization and population growth are currently the main causes of energy and environmental problems associated with wastewater treatment. Wastewater treatment plants (WWTPs) aim to treat wastewater before discharging it into the environment, but they are not yet capable of treating non-biodegradable contaminants such as heavy metals. Toxic heavy metals can disrupt biological processes in WWTPs. Consequently, it is crucial to combine additional physico-chemical treatments with WWTPs to ensure effective wastewater treatment. In this study, the authors examined the pretreatment process for urban wastewater generated by the El Jadida WWTP in order to assess its treatment efficiency. Various physicochemical and spatiotemporal parameters of the WWTP's raw and treated water were studied, including temperature, pH, conductivity, biochemical oxygen demand (BOD5), chemical oxygen demand (COD), suspended solids (SS), total nitrogen, and total phosphorus. The results showed an improvement in treatment yields, with measured performance values of 77% for BOD5, 63% for COD, and 66% for TSS. However, spectroscopic analyses revealed persistent coloration in wastewater samples leaving the WWTP, as well as the presence of heavy metals such as Zn, cadmium, chromium, and cobalt, detected by inductively coupled plasma optical emission spectroscopy (ICP-OES). To remedy these staining problems and reduce the presence of heavy metals, a new low-cost, environmentally-friendly eggshell-based solution was proposed. This method eliminated most heavy metals such as cobalt, beryllium, silver, and copper and significantly reduced the amount of cadmium, lead, chromium, manganese, aluminium, and Zn. In addition, the bioadsorbent was able to decolorize wastewater by up to 84%. This adsorption process is, therefore, of great interest for ensuring the quality of wastewater and promoting its reuse in irrigation.

Keywords: WWTP, wastewater, heavy metals, decoloration, depollution, COD, BOD5

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2419 Lung Cancer Detection and Multi Level Classification Using Discrete Wavelet Transform Approach

Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

Abstract:

Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: artificial neural networks, ANN, discrete wavelet transform, DWT, gray-level co-occurrence matrix, GLCM, k-nearest neighbor, KNN, region of interest, ROI

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2418 Modeling and Control Design of a Centralized Adaptive Cruise Control System

Authors: Markus Mazzola, Gunther Schaaf

Abstract:

A vehicle driving with an Adaptive Cruise Control System (ACC) is usually controlled decentrally, based on the information of radar systems and in some publications based on C2X-Communication (CACC) to guarantee stable platoons. In this paper, we present a Model Predictive Control (MPC) design of a centralized, server-based ACC-System, whereby the vehicular platoon is modeled and controlled as a whole. It is then proven that the proposed MPC design guarantees asymptotic stability and hence string stability of the platoon. The Networked MPC design is chosen to be able to integrate system constraints optimally as well as to reduce the effects of communication delay and packet loss. The performance of the proposed controller is then simulated and analyzed in an LTE communication scenario using the LTE/EPC Network Simulator LENA, which is based on the ns-3 network simulator.

Keywords: adaptive cruise control, centralized server, networked model predictive control, string stability

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2417 An Analysis of the Influence of Employee Readiness for Change on TQM Implementation

Authors: Mohamed Haffar, Khalil Al-Hyari, Mohammed Khair Abu Zaid, Ramadane Djbarni, Mohammed Hamdan

Abstract:

While employee readiness for change (ERFC) is recognised as critical for total quality management (TQM) implementation, there is a lack of systematic and empirical studies regarding the relationship between ERFC dimensions and TQM. Therefore, this study proposes to fill this gap by providing empirical evidence leading to advancement in the understanding of the influences of ERFC components on TQM implementation. The empirical data for this study was drawn from a survey of 400 middle and senior managers of Jordanian firms. The analysis of the collected data, which was conducted using Structural Equation Modeling technique, revealed that three of the ERFC components, namely personally beneficial, change self-efficacy and management support are the most supportive ERFC dimensions for TQM implementation. Therefore, this paper makes a novel contribution by providing a refined and deeper comprehension of the relationships between ERFCs and TQM implementation.

Keywords: total quality management, employee readiness for change, manufacturing organisations, Jordan

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2416 Screening of Rice Genotypes in Methane and Carbon Dioxide Emissions Under Different Water Regimes

Authors: Mthiyane Pretty, Mitsui Toshiake, Nagano Hirohiko, Aycan Murat

Abstract:

Among the most significant greenhouse gases released from rice fields are methane and carbon dioxide. The primary focus of this research was to quantify CH₄ and CO₂ gas using different 4 rice cultivars, two water regimes, and a recording of soil moisture and temperature. In this study, we hypothesized that paddy field soils may directly affect soil enzymatic activities and physicochemical properties in the rhizosphere soil of paddy fields and subsequently indirectly affect the activity, abundance, diversity, and community composition of methanogens, ultimately affecting CH₄ flux. The experiment was laid out in the randomized block design with two treatments and three replications for each genotype. In two treatments, paddy fields and artificial soil were used. 35 days after planting (DAP), continuous flooding irrigation, Alternate wetting, and drying (AWD) were applied during the vegetative stage. The highest recorded measurements of soil and environmental parameters were soil moisture at 76%, soil temperature at 28.3℃, Bulk EC at 0.99 ds/m, and pore water EC at 1,25, using HydraGO portable soil sensor system. Gas samples were carried out once on a weekly basis at 09:00 am and 12: 00 pm to obtain the mean GHG flux. Gas Chromatography (GC, Shimadzu, GC-2010, Japan) was used for the analysis of CH4 and CO₂. The treatments with paddy field soil had a 1.3℃ higher temperature than artificial soil. The overall changes in Bulk EC were not significant across the treatment. The CH₄ emission patterns were observed in all rice genotypes, although they were less in treatments with AWD with artificial soil. This shows that AWD creates oxic conditions in the rice soil. CO₂ was also quantified, but it was in minute quantities, as rice plants were using CO₂ for photosynthesis. The highest tillering number was 7, and the lowest was 3 in cultivars grown. The rice varieties to be used for breeding are Norin 24, with showed a high number of tillers with less CH₄.

Keywords: greenhouse gases, methane, morphological characterization, alternating wetting and drying

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2415 Understanding the Dynamics of Linker Histone Using Mathematical Modeling and FRAP Experiments

Authors: G. Carrero, C. Contreras, M. J. Hendzel

Abstract:

Linker histones or histones H1 are highly mobile nuclear proteins that regulate the organization of chromatin and limit DNA accessibility by binding to the chromatin structure (DNA and associated proteins). It is known that this binding process is driven by both slow (strong binding) and rapid (weak binding) interactions. However, the exact binding mechanism has not been fully described. Moreover, the existing models only account for one type of bound population that does not distinguish explicitly between the weakly and strongly bound proteins. Thus, we propose different systems of reaction-diffusion equations to describe explicitly the rapid and slow interactions during a FRAP (Fluorescence Recovery After Photobleaching) experiment. We perform a model comparison analysis to characterize the binding mechanism of histone H1 and provide new meaningful biophysical information on the kinetics of histone H1.

Keywords: FRAP (Fluorescence Recovery After Photobleaching), histone H1, histone H1 binding kinetics, linker histone, reaction-diffusion equation

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2414 Oxidation and Reduction Kinetics of Ni-Based Oxygen Carrier for Chemical Looping Combustion

Authors: J. H. Park, R. H. Hwang, K. B. Yi

Abstract:

Carbon Capture and Storage (CCS) is one of the important technology to reduce the CO₂ emission from large stationary sources such as a power plant. Among the carbon technologies for power plants, chemical looping combustion (CLC) has attracted much attention due to a higher thermal efficiency and a lower cost of electricity. A CLC process is consists of a fuel reactor and an air reactor which are interconnected fluidized bed reactor. In the fuel reactor, an oxygen carrier (OC) is reduced by fuel gas such as CH₄, H₂, CO. And the OC is send to air reactor and oxidized by air or O₂ gas. The oxidation and reduction reaction of OC occurs between the two reactors repeatedly. In the CLC system, high concentration of CO₂ can be easily obtained by steam condensation only from the fuel reactor. It is very important to understand the oxidation and reduction characteristics of oxygen carrier in the CLC system to determine the solids circulation rate between the air and fuel reactors, and the amount of solid bed materials. In this study, we have conducted the experiment and interpreted oxidation and reduction reaction characteristics via observing weight change of Ni-based oxygen carrier using the TGA with varying as concentration and temperature. Characterizations of the oxygen carrier were carried out with BET, SEM. The reaction rate increased with increasing the temperature and increasing the inlet gas concentration. We also compared experimental results and adapted basic reaction kinetic model (JMA model). JAM model is one of the nucleation and nuclei growth models, and this model can explain the delay time at the early part of reaction. As a result, the model data and experimental data agree over the arranged conversion and time with overall variance (R²) greater than 98%. Also, we calculated activation energy, pre-exponential factor, and reaction order through the Arrhenius plot and compared with previous Ni-based oxygen carriers.

Keywords: chemical looping combustion, kinetic, nickel-based, oxygen carrier, spray drying method

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2413 Modeling and Tracking of Deformable Structures in Medical Images

Authors: Said Ettaieb, Kamel Hamrouni, Su Ruan

Abstract:

This paper presents a new method based both on Active Shape Model and a priori knowledge about the spatio-temporal shape variation for tracking deformable structures in medical imaging. The main idea is to exploit the a priori knowledge of shape that exists in ASM and introduce new knowledge about the shape variation over time. The aim is to define a new more stable method, allowing the reliable detection of structures whose shape changes considerably in time. This method can also be used for the three-dimensional segmentation by replacing the temporal component by the third spatial axis (z). The proposed method is applied for the functional and morphological study of the heart pump. The functional aspect was studied through temporal sequences of scintigraphic images and morphology was studied through MRI volumes. The obtained results are encouraging and show the performance of the proposed method.

Keywords: active shape model, a priori knowledge, spatiotemporal shape variation, deformable structures, medical images

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2412 Simulation Modeling and Analysis of In-Plant Logistics at a Cement Manufacturing Plant in India

Authors: Sachin Kamble, Shradha Gawankar

Abstract:

This paper presents the findings of successful implementation of Business Process Reengineering (BPR) of cement dispatch activities in a cement manufacturing plant located in India. Simulation model was developed for the purpose of identifying and analyzing the areas for improvement. The company was facing a problem of low throughput rate and subsequent forced stoppages of the plant leading to a high production loss of 15000MT per month. It was found from the study that the present systems and procedures related to the in-plant logistics plant required significant changes. The major recommendations included process improvement at the entry gate, reducing the cycle time at the security gate and installation of an additional weigh bridge. This paper demonstrates how BPR can be implemented for improving the in-plant logistics process. Various recommendations helped the plant to increase its throughput by 14%.

Keywords: in-plant logistics, cement logistics, simulation modelling, business process re-engineering, supply chain management

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2411 Modelling and Optimization of a Combined Sorption Enhanced Biomass Gasification with Hydrothermal Carbonization, Hot Gas Cleaning and Dielectric Barrier Discharge Plasma Reactor to Produce Pure H₂ and Methanol Synthesis

Authors: Vera Marcantonio, Marcello De Falco, Mauro Capocelli, Álvaro Amado-Fierro, Teresa A. Centeno, Enrico Bocci

Abstract:

Concerns about energy security, energy prices, and climate change led scientific research towards sustainable solutions to fossil fuel as renewable energy sources coupled with hydrogen as an energy vector and carbon capture and conversion technologies. Among the technologies investigated in the last decades, biomass gasification acquired great interest owing to the possibility of obtaining low-cost and CO₂ negative emission hydrogen production from a large variety of everywhere available organic wastes. Upstream and downstream treatment were then studied in order to maximize hydrogen yield, reduce the content of organic and inorganic contaminants under the admissible levels for the technologies which are coupled with, capture, and convert carbon dioxide. However, studies which analyse a whole process made of all those technologies are still missing. In order to fill this lack, the present paper investigated the coexistence of hydrothermal carbonization (HTC), sorption enhance gasification (SEG), hot gas cleaning (HGC), and CO₂ conversion by dielectric barrier discharge (DBD) plasma reactor for H₂ production from biomass waste by means of Aspen Plus software. The proposed model aimed to identify and optimise the performance of the plant by varying operating parameters (such as temperature, CaO/biomass ratio, separation efficiency, etc.). The carbon footprint of the global plant is 2.3 kg CO₂/kg H₂, lower than the latest limit value imposed by the European Commission to consider hydrogen as “clean”, that was set to 3 kg CO₂/kg H₂. The hydrogen yield referred to the whole plant is 250 gH₂/kgBIOMASS.

Keywords: biomass gasification, hydrogen, aspen plus, sorption enhance gasification

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2410 A Novel Approach of Power Transformer Diagnostic Using 3D FEM Parametrical Model

Authors: M. Brandt, A. Peniak, J. Makarovič, P. Rafajdus

Abstract:

This paper deals with a novel approach of power transformers diagnostics. This approach identifies the exact location and the range of a fault in the transformer and helps to reduce operation costs related to handling of the faulty transformer, its disassembly and repair. The advantage of the approach is a possibility to simulate healthy transformer and also all faults, which can occur in transformer during its operation without its disassembling, which is very expensive in practice. The approach is based on creating frequency dependent impedance of the transformer by sweep frequency response analysis measurements and by 3D FE parametrical modeling of the fault in the transformer. The parameters of the 3D FE model are the position and the range of the axial short circuit. Then, by comparing the frequency dependent impedances of the parametrical models with the measured ones, the location and the range of the fault is identified. The approach was tested on a real transformer and showed high coincidence between the real fault and the simulated one.

Keywords: transformer, parametrical model of transformer, fault, sweep frequency response analysis, finite element method

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2409 Identification of Nonlinear Systems Using Radial Basis Function Neural Network

Authors: C. Pislaru, A. Shebani

Abstract:

This paper uses the radial basis function neural network (RBFNN) for system identification of nonlinear systems. Five nonlinear systems are used to examine the activity of RBFNN in system modeling of nonlinear systems; the five nonlinear systems are dual tank system, single tank system, DC motor system, and two academic models. The feed forward method is considered in this work for modelling the non-linear dynamic models, where the K-Means clustering algorithm used in this paper to select the centers of radial basis function network, because it is reliable, offers fast convergence and can handle large data sets. The least mean square method is used to adjust the weights to the output layer, and Euclidean distance method used to measure the width of the Gaussian function.

Keywords: system identification, nonlinear systems, neural networks, radial basis function, K-means clustering algorithm

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2408 Study on the Integration Schemes and Performance Comparisons of Different Integrated Solar Combined Cycle-Direct Steam Generation Systems

Authors: Liqiang Duan, Ma Jingkai, Lv Zhipeng, Haifan Cai

Abstract:

The integrated solar combined cycle (ISCC) system has a series of advantages such as increasing the system power generation, reducing the cost of solar power generation, less pollutant and CO2 emission. In this paper, the parabolic trough collectors with direct steam generation (DSG) technology are considered to replace the heat load of heating surfaces in heat regenerator steam generation (HRSG) of a conventional natural gas combined cycle (NGCC) system containing a PG9351FA gas turbine and a triple pressure HRSG with reheat. The detailed model of the NGCC system is built in ASPEN PLUS software and the parabolic trough collectors with DSG technology is modeled in EBSILON software. ISCC-DSG systems with the replacement of single, two, three and four heating surfaces are studied in this paper. Results show that: (1) the ISCC-DSG systems with the replacement heat load of HPB, HPB+LPE, HPE2+HPB+HPS, HPE1+HPE2+ HPB+HPS are the best integration schemes when single, two, three and four stages of heating surfaces are partly replaced by the parabolic trough solar energy collectors with DSG technology. (2) Both the changes of feed water flow and the heat load of the heating surfaces in ISCC-DSG systems with the replacement of multi-stage heating surfaces are smaller than those in ISCC-DSG systems with the replacement of single heating surface. (3) ISCC-DSG systems with the replacement of HPB+LPE heating surfaces can increase the solar power output significantly. (4) The ISCC-DSG systems with the replacement of HPB heating surfaces has the highest solar-thermal-to-electricity efficiency (47.45%) and the solar radiation energy-to-electricity efficiency (30.37%), as well as the highest exergy efficiency of solar field (33.61%).

Keywords: HRSG, integration scheme, parabolic trough collectors with DSG technology, solar power generation

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2407 Impact Assessment of Lean Practices on Social Sustainability Indicators: An Approach Using ISM Method

Authors: Aline F. Marcon, Eduardo F. da Silva, Marina Bouzon

Abstract:

The impact of lean management on environmental sustainability is the research line that receives the most attention from academicians. Therefore, the social dimension of sustainable development has so far received less attention. This paper aims to evaluate the impact of intra-plant lean manufacturing practices on social sustainability indicators extracted from the Global Reporting Initiative (GRI) parameters. The method is two-phased, including MCDM approach to uncover the most relevant practices regarding social performance and Interpretive Structural Modeling (ISM) method to reveal the structural relationship among lean practices. Professionals from the academic and industrial fields answered the questionnaires. From the results of this paper, it is possible to verify that practices such as “Safety Improvement Programs”, “Total Quality Management” and “Cross-functional Workforce” are the ones which have the most positive influence on the set of GRI social indicators.

Keywords: indicators, ISM, lean, social, sustainability

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2406 Modeling and Performance Evaluation of Three Power Generation and Refrigeration Energy Recovery Systems from Thermal Loss of a Diesel Engine in Different Driving Conditions

Authors: H. Golchoobian, M. H. Taheri, S. Saedodin, A. Sarafraz

Abstract:

This paper investigates the possibility of using three systems of organic Rankine auxiliary power generation, ejector refrigeration and absorption to recover energy from a diesel car. The analysis is done for both urban and suburban driving modes that vary from 60 to 120 km/h. Various refrigerants have also been used for organic Rankine and Ejector refrigeration cycles. The capacity was evaluated by Organic Rankine Cycle (ORC) system in both urban and suburban conditions for cyclopentane and ammonia as refrigerants. Also, for these two driving plans, produced cooling by absorption refrigeration system under variable ambient temperature conditions and in ejector refrigeration system for R123, R134a and R141b refrigerants were investigated.

Keywords: absorption system, diesel engine, ejector refrigeration, energy recovery, organic Rankine cycle

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2405 Bayesian Prospective Detection of Small Area Health Anomalies Using Kullback Leibler Divergence

Authors: Chawarat Rotejanaprasert, Andrew Lawson

Abstract:

Early detection of unusual health events depends on the ability to detect rapidly any substantial changes in disease, thus facilitating timely public health interventions. To assist public health practitioners to make decisions, statistical methods are adopted to assess unusual events in real time. We introduce a surveillance Kullback-Leibler (SKL) measure for timely detection of disease outbreaks for small area health data. The detection methods are compared with the surveillance conditional predictive ordinate (SCPO) within the framework of Bayesian hierarchical Poisson modeling and applied to a case study of a group of respiratory system diseases observed weekly in South Carolina counties. Properties of the proposed surveillance techniques including timeliness and detection precision are investigated using a simulation study.

Keywords: Bayesian, spatial, temporal, surveillance, prospective

Procedia PDF Downloads 308