Search results for: models synthesis

Authors: Z. Nemec, R. Matousek

Abstract:

The paper describes the evaluation of quality of control for cases of controlled non-minimal phase plants. Control circuits containing non-minimal phase plants have different properties, they manifest reversed reaction at the beginning of unit step response. For these types of plants are developed special criterion of quality of control, which considers the difference and can be helpful for synthesis of optimal controller tuning. All results are clearly presented using Matlab/Simulink models.

Keywords: control design, non-minimal phase system, optimalcriteria, power plant, heating plant, water turbine, Matlab, Simulink.

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Authors: Yehjune Heo

Abstract:

Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Keywords: Anti-spoofing, CNN, fingerprint recognition, GAN.

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Authors: Dursun Aydin

Abstract:

This paper study about using of nonparametric models for Gross National Product data in Turkey and Stanford heart transplant data. It is discussed two nonparametric techniques called smoothing spline and kernel regression. The main goal is to compare the techniques used for prediction of the nonparametric regression models. According to the results of numerical studies, it is concluded that smoothing spline regression estimators are better than those of the kernel regression.

Keywords: Kernel regression, Nonparametric models, Prediction, Smoothing spline.

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Authors: Flora Elvistia Firdaus

Abstract:

Soy polyol obtained from hydroxylation of soy epoxide with ethylene glycol were prepared as pre-polyurethane. The two step process method were applied in the polyurethane synthesis. The blending of soy polyol with synthetic polyol then simultaneously carried out to TDI (2,4): MDI (4,4-) (80:20), blowing agent, and surfactant. Ethylene glycol were not taking part in the polyurethane synthesis. The inclusion of ethylene glycol were used as a control. Characterization of polyurethane foam through impact resillience, indentation deflection, and density can visualize the polyurethane classifications.

Keywords: Ethylene glycol, polyurethane foam, soy polyol, synthetic polyol

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Authors: I. Erins, J. Erina

Abstract:

The aim of this article is to assess the existing business models used by the banks operating in the CEE countries in the time period from 2006 till 2011. In order to obtain research results, the authors performed qualitative analysis of the scientific literature on bank business models, which have been grouped into clusters that consist of such components as: 1) capital and reserves; 2) assets; 3) deposits, and 4) loans. In their turn, bank business models have been developed based on the types of core activities of the banks, and have been divided into four groups: Wholesale, Investment, Retail and Universal Banks. Descriptive statistics have been used to analyse the models, determining mean, minimal and maximal values of constituent cluster components, as well as standard deviation. The analysis of the data is based on such bank variable indices as Return on Assets (ROA) and Return on Equity (ROE).

Keywords: Banks, Business model, CEE, ROA, ROE.

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Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

Abstract:

Many quality models have been used to measure egovernment portals quality. However, the absence of an international consensus for e-government portals quality models results in many differences in terms of quality attributes and measures. The aim of this paper is to compare and analyze the existing e-government quality models proposed in literature (those that are based on ISO standards and those that are not) in order to propose guidelines to build a good and useful e-government portals quality model. Our findings show that, there is no e-government portal quality model based on the new international standard ISO 25010. Besides that, the quality models are not based on a best practice model to allow agencies to both; measure e-government portals quality and identify missing best practices for those portals.

Keywords: E-government, portal, best practices, quality model, ISO, standard, ISO 25010, ISO 9126.

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Authors: Özlen Altun, Zeliha Yoruç

Abstract:

In the present study, the reactions involving 4-bromo-2,6-bis-hydroxymethyl-phenol (BBHMP) and nicotinamide (NA) in the presence of Pd(II) ions were investigated. Optimum conditions for the reactions were established as pH = 7 and λ = 450 nm. According to absorbance measurements, the molar ratio of BBHMP: NA: Pd²⁺ was found to be 1: 2: 2. As a result of physicochemical, spectrophotometric and thermal analyses, the reactions of BBHMP and NA with Pd(II) are complexation reactions and one molecule of BBHMP and two molecules of NA react with two molecules of the Pd(II) ion.

Keywords: Nicotinamide, 4-bromo-2, 6-bis-hydroxymethyl-phenol, Pd(II), spectral analysis, synthesis.

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Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

Abstract:

This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: Ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling.

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Authors: Mogari I. Rapoo, Diteboho Xaba

Abstract:

This paper examines the forecasting performance of Autoregressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANN) models with the published exchange rate obtained from South African Reserve Bank (SARB). ARIMA is one of the popular linear models in time series forecasting for the past decades. ARIMA and ANN models are often compared and literature revealed mixed results in terms of forecasting performance. The study used the MSE and MAE to measure the forecasting performance of the models. The empirical results obtained reveal the superiority of ARIMA model over ANN model. The findings further resolve and clarify the contradiction reported in literature over the superiority of ARIMA and ANN models.

Keywords: ARIMA, artificial neural networks models, error metrics, exchange rates.

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Authors: Mohammad Seifi, Azura Bt. Che Soh, Noor Izzrib. Abd. Wahab, Mohd Khair B. Hassan

Abstract:

Solar energy has a major role in renewable energy resources. Solar Cell as a basement of solar system has attracted lots of research. To conduct a study about solar energy system, an authenticated model is required. Diode base PV models are widely used by researchers. These models are classified based on the number of diodes used in them. Single and two-diode models are well studied. Single-diode models may have two, three or four elements. In this study, these solar cell models are examined and the simulation results are compared to each other. All PV models are re-designed in the Matlab/Simulink software and they examined by certain test conditions and parameters. This paper provides comparative studies of these models and it tries to compare the simulation results with manufacturer-s data sheet to investigate model validity and accuracy. The results show a four- element single-diode model is accurate and has moderate complexity in contrast to the two-diode model with higher complexity and accuracy

Keywords: Fill Factor (FF), Matlab/Simulink, Maximum PowerPoint (MPP), Maximum Power Point Tracker (MPPT), Photo Voltaic(PV), Solar cell, Standard Test Condition (STC).

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Authors: Iyad F. Jafar, Sandra J. Alrawashdeh, Ban K. Alhamayel

Abstract:

High level synthesis (HLS) is a process which generates register-transfer level design for digital systems from behavioral description. There are many HLS algorithms and commercial tools. However, most of these algorithms consider a behavioral description for the system when a single token is presented to the system. This approach does not exploit extra hardware efficiently, especially in the design of digital filters where common operations may exist between successive tokens. In this paper, we modify the behavioral description to process multiple tokens in parallel. However, this approach is unlike the full processing that requires full hardware replication. It exploits the presence of common operations between successive tokens. The performance of the proposed approach is better than sequential processing and approaches that of full parallel processing as the hardware resources are increased.

Keywords: Digital filters, High level synthesis, Sub-token forwarding

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Authors: Mohammad Taha, Dia abu al Nadi

Abstract:

In this paper, the phase control antenna array synthesis is presented. The problem is formulated as a constrained optimization problem that imposes nulls with prescribed level while maintaining the sidelobe at a prescribed level. For efficient use of the algorithm memory, compared to the well known Particle Swarm Optimization (PSO), the Accelerated Particle Swarm Optimization (APSO) is used to estimate the phase parameters of the synthesized array. The objective function is formed using a main objective and set of constraints with penalty factors that measure the violation of each feasible solution in the search space to each constraint. In this case the obtained feasible solution is guaranteed to satisfy all the constraints. Simulation results have shown significant performance increases and a decreased randomness in the parameter search space compared to a single objective conventional particle swarm optimization.

Keywords: Array synthesis, Sidelobe level control, Constrainedoptimization, Accelerated Particle Swarm Optimization.

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Authors: Alexander Efremov

Abstract:

A system for market identification (SMI) is presented. The resulting representations are multivariable dynamic demand models. The market specifics are analyzed. Appropriate models and identification techniques are chosen. Multivariate static and dynamic models are used to represent the market behavior. The steps of the first stage of SMI, named data preprocessing, are mentioned. Next, the second stage, which is the model estimation, is considered in more details. Stepwise linear regression (SWR) is used to determine the significant cross-effects and the orders of the model polynomials. The estimates of the model parameters are obtained by a numerically stable estimator. Real market data is used to analyze SMI performance. The main conclusion is related to the applicability of multivariate dynamic models for representation of market systems.

Keywords: market identification, dynamic models, stepwise regression.

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Authors: Ziaddin Daie Koozekanani, Mina Zolfy Lighvan

Abstract:

One of the most challengeable issues in ESL (Electronic System Level) design is the lack of a general modeling scheme for on chip communication architecture. In this paper some of the mostly used methodologies for modeling and representation of on chip communication are investigated. Our goal is studying the existing methods to extract the requirements of a general representation scheme for communication architecture synthesis. The next step, will be introducing a modeling and representation method for being used in automatically synthesis process of on chip communication architecture.

Keywords: Communication architecture, System on Chip, Communication Modeling and Representation

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Authors: Alcínia Z. Sampaio, Pedro G. Henriques

Abstract:

Three-dimensional geometric models have been used to present architectural and engineering works, showing their final configuration. When the clarification of a detail or the constitution of a construction step in needed, these models are not appropriate. They do not allow the observation of the construction progress of a building. Models that could present dynamically changes of the building geometry are a good support to the elaboration of projects. Techniques of geometric modeling and virtual reality were used to obtain models that could visually simulate the construction activity. The applications explain the construction work of a cavity wall and a bridge. These models allow the visualization of the physical progression of the work following a planned construction sequence, the observation of details of the form of every component of the works and support the study of the type and method of operation of the equipment applied in the construction. These models presented distinct advantage as educational aids in first-degree courses in Civil Engineering. The use of Virtual Reality techniques in the development of educational applications brings new perspectives to the teaching of subjects related to the field of civil construction.

Keywords: Education, Engineering, virtual reality, visualsimulation.

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Authors: Megha Gupta, Nupur Prakash

Abstract:

Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: A. Ippolito, C. Bartolomei

Abstract:

A growing demand is felt today for realistic 3D models enabling the cognition and popularization of historical-artistic heritage. Evaluation and preservation of Cultural Heritage is inextricably connected with the innovative processes of gaining, managing, and using knowledge. The development and perfecting of techniques for acquiring and elaborating photorealistic 3D models, made them pivotal elements for popularizing information of objects on the scale of architectonic structures.

Keywords: Cultural heritage, databases, non-contact survey, 2D- 3D models.

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Authors: Hamdi Muhyuddin D. Barra, Henry J. Ramos

Abstract:

Titanium nitride (TiN) has been synthesized using the sheet plasma negative ion source (SPNIS). The parameters used for its effective synthesis has been determined from previous experiments and studies. In this study, further enhancement of the deposition rate of TiN synthesis and advancement of the SPNIS operation is presented. This is primarily achieved by the addition of Sm-Co permanent magnets and a modification of the configuration in the TiN deposition process. The magnetic enhancement is aimed at optimizing the sputtering rate and the sputtering yield of the process. The Sm-Co permanent magnets are placed below the Ti target for better sputtering by argon. The Ti target is biased from –250V to – 350V and is sputtered by Ar plasma produced at discharge current of 2.5–4A and discharge potential of 60–90V. Steel substrates of dimensions 20x20x0.5mm3 were prepared with N2:Ar volumetric ratios of 1:3, 1:5 and 1:10. Ocular inspection of samples exhibit bright gold color associated with TiN. XRD characterization confirmed the effective TiN synthesis as all samples exhibit the (200) and (311) peaks of TiN and the non-stoichiometric Ti2N (220) facet. Cross-sectional SEM results showed increase in the TiN deposition rate of up to 0.35μm/min. This doubles what was previously obtained [1]. Scanning electron micrograph results give a comparative morphological picture of the samples. Vickers hardness results gave the largest hardness value of 21.094GPa.

Keywords: Chemical vapor deposition, Magnetized sheetplasma, Thin-film synthesis, Titanium nitride.

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Authors: Samy M. El-Behery, Mofreh H. Hamed

Abstract:

This paper presents a computational study of the separated flow in a planer asymmetric diffuser. The steady RANS equations for turbulent incompressible fluid flow and six turbulence closures are used in the present study. The commercial software code, FLUENT 6.3.26, was used for solving the set of governing equations using various turbulence models. Five of the used turbulence models are available directly in the code while the v2-f turbulence model was implemented via User Defined Scalars (UDS) and User Defined Functions (UDF). A series of computational analysis is performed to assess the performance of turbulence models at different grid density. The results show that the standard k-ω, SST k-ω and v2-f models clearly performed better than other models when an adverse pressure gradient was present. The RSM model shows an acceptable agreement with the velocity and turbulent kinetic energy profiles but it failed to predict the location of separation and attachment points. The standard k-ε and the low-Re k- ε delivered very poor results.

Keywords: Turbulence models, turbulent flow, wall functions, separation, reattachment, diffuser.

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Authors: E. Moroydor Derun, A. S. Kipcak, A. Kaplan, S. Piskin

Abstract:

Magnesium wastes are produced by many industrial activities. This waste problem is becoming a future problem for the world. Magnesium borates have many advantages such as; high corrosion resistance, heat resistance, high coefficient of elasticity and can also be used in the production of material against radiation. Addition, magnesium borates have great potential in sectors including ceramic and detergents industry and superconducting materials. In this study, using the starting materials of waste magnesium and H3BO3 the hydrothermal method was applied at a moderate temperature of 70oC. Several mole ratios of waste magnesium to H3BO3 are selected as; 1:2, 1:4, 1:6, 1:8, 1:10. Reaction time was determined as 1 hour. After the synthesis, X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR) techniques are applied to products. As a result the forms of mcallisterite “Mg2(B6O7(OH)6)2.9(H2O)”, admontite “MgO(B2O3)3.7(H2O)” and magnesium boron hydrate (MgO(B2O3)3.6(H2O)” are obtained. 

Keywords: Hydrothermal synthesis, magnesium borates, waste magnesium.

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Authors: Marina Velikova, Hennie Daniels, Ad Feelders

Abstract:

In many applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. Here we consider partially monotone problems, where the target variable depends monotonically on some of the predictor variables but not all. We propose an approach to build partially monotone models based on the convolution of monotone neural networks and kernel functions. The results from simulations and a real case study on house pricing show that our approach has significantly better performance than partially monotone linear models. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.

Keywords: Mixture models, monotone neural networks, partially monotone models, partially monotone problems.

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Authors: Elina Bakhtieva

Abstract:

The variety of available digital tools, strategies and activities might confuse and disorient even an experienced marketer. This applies in particular to B2B companies, which are usually less flexible in uptaking of digital technology than B2C companies. B2B companies are lacking a framework that corresponds to the specifics of the B2B business, and which helps to evaluate a company’s capabilities and to choose an appropriate path. A B2B digital marketing maturity model helps to fill this gap. However, modern marketing offers no widely approved digital marketing maturity model, and thus, some marketing institutions provide their own tools. The purpose of this paper is building an optimized B2B digital marketing maturity model based on a SWOT (strengths, weaknesses, opportunities, and threats) analysis of existing models. The current study provides an analytical review of the existing digital marketing maturity models with open access. The results of the research are twofold. First, the provided SWOT analysis outlines the main advantages and disadvantages of existing models. Secondly, the strengths of existing digital marketing maturity models, helps to identify the main characteristics and the structure of an optimized B2B digital marketing maturity model. The research findings indicate that only one out of three analyzed models could be used as a separate tool. This study is among the first examining the use of maturity models in digital marketing. It helps businesses to choose between the existing digital marketing models, the most effective one. Moreover, it creates a base for future research on digital marketing maturity models. This study contributes to the emerging B2B digital marketing literature by providing a SWOT analysis of the existing digital marketing maturity models and suggesting a structure and main characteristics of an optimized B2B digital marketing maturity model.

Keywords: B2B digital marketing strategy, digital marketing, digital marketing maturity model, SWOT analysis.

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Authors: Indah Kurniawaty, Yoki Yulizar, Haryo Satrya Oktaviano, Adam Kusuma Rianto

Abstract:

Magnesium oxide nanoparticles (MgO NP) were successfully synthesized in this study using a one-pot green synthesis mediated by Calliandra calothyrsus leaf extract (CLE). CLE was prepared by maceration of the leaf using methanol with a ratio of 1:5 for 7 days. Secondary metabolites in CLE, such as alkaloids and flavonoids, served as a weak base provider and capping agent in the formation of MgO NP. CLE Fourier Transform Infra-Red (FTIR) spectra peak at 3255 cm-1, 1600 cm-1, 1384 cm-1, 1205 cm-1, 1041 cm-1, and 667 cm-1 showing the presence of vibrations O-H stretching, N-H bending, C-C stretching, C-N stretching and N-H wagging. During the experiment, different CLE volumes and calcined temperatures were used, resulting in a variety of structures. Energy Dispersive X-ray Spectrometer (EDS) and FTIR were used to characterize metal oxide particles. MgO diffraction patterns at 2θ of 36.9°; 42.9°; 62.2°; 74.6°; and 78.5° can be assigned to crystal planes (111), (200), (220), (311), and (222), respectively. Scanning Electron Microscopy (SEM) was used to characterize the surface morphology. The morphology ranged from sphere to flower-like resulting in crystallite sizes of 28 nm, 23 nm, 12 nm, and 9 nm.

Keywords: Calliandra calothyrsus, green-synthesis, magnesium oxide, nanoparticle.

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Authors: Majdi M. Alomari, Nafesah I. Alshdaifat, Mohammad S. Widyan

Abstract:

Different countries have introduced different schemes and policies to counter global warming. The rationale behind the proposed policies and the potential barriers to successful implementation of the policies adopted by the countries were analyzed and estimated based on different models. It is argued that these models enhance the transparency and provide a better understanding to the policy makers. However, these models are underpinned with several structural and baseline assumptions. These assumptions, modeling features and future prediction of emission reductions and other implication such as cost and benefits of a transition to a low-carbon economy and its economy wide impacts were discussed. On the other hand, there are potential barriers in the form political, financial, and cultural and many others that pose a threat to the mitigation options.

Keywords: Economic wide impact, energy models, environmental policy instruments, mitigating CO2 emission.

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Authors: Jerneja Žganec Gros, Aleš Mihelič, Nikola Pavešić, Mario Žganec, Stanislav Gruden

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The paper presents the design concept of a unitselection text-to-speech synthesis system for the Slovenian language. Due to its modular and upgradable architecture, the system can be used in a variety of speech user interface applications, ranging from server carrier-grade voice portal applications, desktop user interfaces to specialized embedded devices. Since memory and processing power requirements are important factors for a possible implementation in embedded devices, lexica and speech corpora need to be reduced. We describe a simple and efficient implementation of a greedy subset selection algorithm that extracts a compact subset of high coverage text sentences. The experiment on a reference text corpus showed that the subset selection algorithm produced a compact sentence subset with a small redundancy. The adequacy of the spoken output was evaluated by several subjective tests as they are recommended by the International Telecommunication Union ITU.

Keywords: text-to-speech synthesis, prosody modeling, speech user interface.

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Authors: F. Gholami, M. Torabi Angaji, Z. Gholami

Abstract:

Fischer-Tropsch synthesis is one of the most important catalytic reactions that convert the synthetic gas to light and heavy hydrocarbons. One of the main issues is selecting the type of reactor. The slurry bubble reactor is suitable choice for Fischer- Tropsch synthesis because of its good qualification to transfer heat and mass, high durability of catalyst, low cost maintenance and repair. The more common catalysts for Fischer-Tropsch synthesis are Iron-based and Cobalt-based catalysts, the advantage of these catalysts on each other depends on which type of hydrocarbons we desire to produce. In this study, Fischer-Tropsch synthesis is modeled with Iron and Cobalt catalysts in a slurry bubble reactor considering mass and momentum balance and the hydrodynamic relations effect on the reactor behavior. Profiles of reactant conversion and reactant concentration in gas and liquid phases were determined as the functions of residence time in the reactor. The effects of temperature, pressure, liquid velocity, reactor diameter, catalyst diameter, gasliquid and liquid-solid mass transfer coefficients and kinetic coefficients on the reactant conversion have been studied. With 5% increase of liquid velocity (with Iron catalyst), H2 conversions increase about 6% and CO conversion increase about 4%, With 8% increase of liquid velocity (with Cobalt catalyst), H2 conversions increase about 26% and CO conversion increase about 4%. With 20% increase of gas-liquid mass transfer coefficient (with Iron catalyst), H2 conversions increase about 12% and CO conversion increase about 10% and with Cobalt catalyst H2 conversions increase about 10% and CO conversion increase about 6%. Results show that the process is sensitive to gas-liquid mass transfer coefficient and optimum condition operation occurs in maximum possible liquid velocity. This velocity must be more than minimum fluidization velocity and less than terminal velocity in such a way that avoid catalysts particles from leaving the fluidized bed.

Keywords: Modeling, Fischer-Tropsch Synthesis, Slurry Bubble Column Reactor.

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Authors: Zhen Chen, Haitao Zhang, Weiyong Ying, Dingye Fang

Abstract:

Based on a global kinetics of direct dimethyl ether (DME) synthesis process from syngas, a steady-state one-dimensional mathematical model for the bubble column slurry reactor (BCSR) has been established. It was built on the assumption of plug flow of gas phase, sedimentation-dispersion model of catalyst grains and isothermal chamber regardless of reaction heats and rates for the design of an industrial scale bubble column slurry reactor. The simulation results indicate that higher pressure and lower temperature were favorable to the increase of CO conversion, DME selectivity, products yield and the height of slurry bed, which has a coincidence with the characteristic of DME synthesis reaction system, and that the height of slurry bed is lessen with the increasing of operation temperature in the range of 220-260℃. CO conversion, the optimal operation conditions in BCSR were proposed. 

Keywords: Alcohol/ether fuel, bubble column slurry reactor, global kinetics, mathematical model.

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Authors: F. Kurtuluş, G. Çelik Gül

Abstract:

Cesium molybdates with general formula CsMIII(MoO4)2, where MIII = Bi, Dy, Pr, Er, exhibit rich polymorphism, and crystallize in a layered structure. These properties cause intensive studies on cesium molybdates. CsBi(MoO4)2 was synthesized by microwave method by using cerium sulphate, bismuth oxide and molybdenum (VI) oxide in an appropriate molar ratio. Characterizations were done by x-ray diffraction (XRD), fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy/energy dispersive analyze (SEM/EDS), thermo gravimetric/differantial thermal analysis (TG/DTA).

Keywords: Cesium bismuth dimolybdate, microwave synthesis, powder x-ray diffraction, rare earth dimolybdates.

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Authors: Abdulkareem Hamid, Adam Daïch

Abstract:

Camptothecin (CPT) is a cytotoxic quinoline alkaloid, which inhibits the DNA enzyme topoisomerase I (topo I). It was discovered in 1966 by M. E. Wall and M. C. Wani in systematic screening of natural products for anticancer drugs. It was isolated from the bark and stem of Camptotheca acuminata (Camptotheca, Happy tree), a tree native in China. CPT showed remarkable anticancer activity in preliminary clinical trials but also low solubility and (high) adverse drug reaction. Because of these disadvantages synthetic and medicinal chemists have developed numerous syntheses of Camptothecine [1][2][3] and various derivatives to increase the benefits of the chemical, with good results. In our method CPT analogues has be six steps starting from available material DL Malic acid.

Keywords: Camptothecine, synthesis, analogue.

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Authors: Razieh Arian, Hadi Adibi-Asl

Abstract:

This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.

Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine.

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