Search results for: gaussian mixture models

Authors: A. Natsir, M. Nadir, S. Syahrir, A. Mujnisa

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In tropical countries such as in Indonesia, rice straw plays an important role in fulfilling the needs of feed for ruminant, especially during the dry season in which the availability of forage is very limited. However, the main problem of using rice straw as a feedstuff is low digestibility due to the existence of the links between lignin and cellulose or hemicellulose, and imbalance of its minerals content. One alternative to solve this problem is by application of biodecomposer (BS) derived from rumen bacterial of the ruminant. This study was designed to assess the effects of BS application on the changes of the chemical composition of rice straw. Four adults local buffalo raised under typical feeding conditions were used as a source of inoculum for BS development. The animal was fed for a month with a diet consisted of rice straw and elephant grass before taking rumen fluid samples. Samples of rumen fluid were inoculated in the carboxymethyl cellulose (CMC) media under anaerobic condition for 48 hours at 37°C. The mixture of CMC media and microbes are ready to be used as a biodecomposer following incubation of the mixture under anaerobic condition for 7 days at 45°C. The effectiveness of BS then assessed by applying the BS on the straw according to completely randomized design consisted of four treatments and three replication. One hundred g of ground coarse rice straw was used as the substrate. The BS was applied to the rice straw substrate with the following composition: Rice straw without BS (P0), rice straw + 5% BS (P1), rice straw +10% BS (P2), and rice straw + 15% BS. The mixture of rice straw and BS then fermented under anaerobic for four weeks. Following the fermentation, the chemical composition of rice straw was evaluated. The results indicated that the crude protein content of rice straw significantly increased (P < 0.05) as the level of BS increased. On the other hand, the concentration of crude fiber of the rice straw was significantly decreased (P < 0.05) as the level of BS increased. Other nutrients such as minerals did not change (P > 0.05) due to the treatments. In conclusion, application of BS developed from rumen bacterial of buffalo has a promising prospect to be used as a biological agent to improve the quality of rice straw as feeding for ruminant.

Keywords: biodecomposer, local buffalo, rumen microbial, chemical composition

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Authors: L. Nevrivova, K. Lang, M. Kotoucek, D. Vsiansky

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This entry concerned with dense silica microstructure was produced as a part of a project within the Technology Agency of the Czech Republic which is being implemented in cooperation of the biggest producer of refractories the P-D Refractories CZ company with the research organisation Brno University of Technology. The paper is focused on the influence of mixture homogenisation and the influence of grain size of the mineraliser on the resulting utility properties of the material as well as its microstructure. It has a decisive influence on the durability of the material in a building structure. This paper is a continuation of a previously published study dealing with the suitability of various types of mineralising agents in terms of density, strength and mineral composition of silica. The entry describes the influence of the method of mixture homogenisation and the influence of granulometry of the applied Fe-mineralising agent on the resulting silica microstructure. Porosity, density, phase composition and microstructure of the experimentally prepared silica samples were examined and the results were discussed in context with the technology of homogenisation and firing temperature used. The properties of silica brick samples were compared to the sample without any Fe-mineraliser.

Keywords: silica bricks, Fe-mineraliser, mineralogical composition, new developed silica material

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Authors: Krishang Surapaneni

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The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

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Authors: H. C. Chinwenyi, H. D. Ibrahim, F. A. Ahmed

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In modern financial mathematics, valuing derivatives such as options is often a tedious task. This is simply because their fair and correct prices in the future are often probabilistic. This paper examines three different Stochastic Differential Equation (SDE) models in finance; the Constant Elasticity of Variance (CEV) model, the Balck-Karasinski model, and the Heston model. The various Martingales option price valuation formulas for these three models were obtained using the replicating portfolio method. Also, the numerical solution of the derived Martingales options price valuation equations for the SDEs models was carried out using the Monte Carlo method which was implemented using MATLAB. Furthermore, results from the numerical examples using published data from the Nigeria Stock Exchange (NSE), all share index data show the effect of increase in the underlying asset value (stock price) on the value of the European Put Option for these models. From the results obtained, we see that an increase in the stock price yields a decrease in the value of the European put option price. Hence, this guides the option holder in making a quality decision by not exercising his right on the option.

Keywords: equivalent martingale measure, European put option, girsanov theorem, martingales, monte carlo method, option price valuation formula

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Authors: Adilson Elias Xavier, Otto Corrêa Rotunno Filho, Paulo Canedo De Magalhães

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This paper addresses the issue of automatic parameter estimation in conceptual rainfall-runoff (CRR) models. Due to threshold structures commonly occurring in CRR models, the associated mathematical optimization problems have the significant characteristic of being strongly non-differentiable. In order to face this enormous task, the resolution method proposed adopts a smoothing strategy using a special C∞ differentiable class function. The final estimation solution is obtained by solving a sequence of differentiable subproblems which gradually approach the original conceptual problem. The use of this technique, called Hyperbolic Smoothing Method (HSM), makes possible the application of the most powerful minimization algorithms, and also allows for the main difficulties presented by the original CRR problem to be overcome. A set of computational experiments is presented for the purpose of illustrating both the reliability and the efficiency of the proposed approach.

Keywords: rainfall-runoff models, automatic calibration, hyperbolic smoothing method

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Authors: Henri El Zakhem, Anthony Dahdah, Lara Frangieh, Jessica Koura

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Nowadays, the removal of whey produced in the dairy processes has been the most important problem in the dairy industry. Every year, about 47% of the 115 million tons of whey produced world-wide are disposed in the environment. Whey is a nutritious liquid, containing whey proteins (β-lactoglobulin, α-lactalbumin, immunoglobulin-G, proteose pepton), lactose, vitamins (B5, B2, C, and B6), minerals (Calcium, Magnesium, Phosphorous, Potassium, Chloride, and Sodium), and trace elements (Zinc, Iron, Iodine, and Copper). The first objective was to increase the economical and commercial value of whey which is considered as by-product. The second objective of this study was to formulate a new baby food with good nutritional, sensory and storage properties and acceptable to consumers using the cheese whey. The creation of the new product must pass through the following stages: idea stage, development stage which includes the business planning and the product development prototype, packaging stage, production stage, test marketing stage, quality control/sanitation. Three types of whey-based food were selected and prepared by mixing whey and apple, whey and banana as well as whey, apple, and banana.To compile with the recommended dietary allowances (RDA) and adequate intakes (AI) for vitamins and minerals, each sample is formed from 114g of sliced and smashed fruits mixed with 8 mL of whey. Mixtures are heated to 72oC for 15 seconds, and filled in pasteurized jars. Jars were conserved at 4oC. Following the experimental part, sensory evaluation made by an experienced panel took place. Hedonic tests results show that the mixture of whey, apple, and banana has the most delicious and sweetness taste followed by the mixture of whey and banana, and finally the mixture of whey and apple. This study was concluded with a managerial and engineering study that reveals that the project is economically profitable to be executed in Lebanon.

Keywords: baby food, by-product, cheese whey, formulation

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Authors: Mehdi Seifbarghy, Zahra Mansouri

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In this paper a few location-allocation models are developed in a multi-echelon supply chain including suppliers, manufacturers, distributors and retailers. The objectives are maximizing demand coverage, minimizing the total distance of distributors from suppliers, minimizing some facility establishment costs and minimizing the environmental effects. Since nature of the given models is multi-objective, we suggest a number of goal-based solution techniques such L-P metric, goal programming, multi-choice goal programming and goal attainment in order to solve the problems.

Keywords: location, multi-echelon supply chain, covering, goal programming

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Authors: Mojtaba Heydarizad, Hamid Ghalibaf Mohammadabadi

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Iran is a semi-arid and arid country in south-western Asia in the Middle East facing intense climatological drought from the early times. Therefore, studying the precipitation events and the moisture sources and air masses causing precipitation has great importance in this region. In this study, the moisture sources and stable isotope content of precipitation moisture in three main events in 2015 have been studied in North-Eastern Iran. HYSPLIT model backward trajectories showed that the Caspian Sea and the mixture of the Caspian and Mediterranean Seas are dominant moisture sources for the studied events. This showed the role of cP (Siberian) and Mediterranean (MedT) air masses. Stable isotope studies showed that precipitation events originated from the Caspian Sea with lower Sea Surface Temperature (SST) have more depleted isotope values. However, precipitation events sourced from the mixture of the Caspian and the Mediterranean Seas (with higher SST) showed more enriched isotope values.

Keywords: HYSPLIT, Iran, Northern Khorasan, stable isotopes

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Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

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Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

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Authors: Nodelman V.

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Despite serious difficulties in the assimilation of the conceptual system of Calculus, software in the educational process is used only occasionally, and even then, mainly for illustration purposes. The following are a few reasons: The non-trivial nature of the studied material, Lack of skills in working with software, Fear of losing time working with software, The variety of the software itself, the corresponding interface, syntax, and the methods of working with the software, The need to find suitable models, and familiarize yourself with working with them, Incomplete compatibility of the found models with the content and teaching methods of the studied material. This paper proposes an active use of the developed non-commercial software VusuMatica, which allows removing these restrictions through Broad support for the studied mathematical material (and not only Calculus). As a result - no need to select the right software, Emphasizing the unity of mathematics, its intrasubject and interdisciplinary relations, User-friendly interface, Absence of special syntax in defining mathematical objects, Ease of building models of the studied material and manipulating them, Unlimited flexibility of models thanks to the ability to redefine objects, which allows exploring objects characteristics, and considering examples and counterexamples of the concepts under study. The construction of models is based on an original approach to the analysis of the structure of the studied concepts. Thanks to the ease of construction, students are able not only to use ready-made models but also to create them on their own and explore the material studied with their help. The presentation includes examples of using VusuMatica in studying the concepts of limit and continuity of a function, its derivative, and integral.

Keywords: counterexamples, limitations and requirements, software, teaching and learning calculus, user-friendly interface and syntax

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Authors: Mateusz Paszko, Konrad Pietrykowski, Krzysztof Skiba

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Due to low-altitude and relatively low flight speed, today’s combat assets like missile weapons equipped with infrared guidance systems are one of the most important threats to the helicopters performing combat missions. Especially meaningful in helicopter aviation is infrared emission by exhaust gases, regressed to the surroundings. Due to high temperature, exhaust gases are a major factor in detectability of a helicopter performing air combat operations. This study presents the results of simulating the flow of the mixture of exhaust and air in the flow duct of an injective exhaust cooler, adapted to cooperate with the PZL 10W turbine engine. The simulation was performed using a numerical model and the ANSYS Fluent software. Simulation computations were conducted for set flight conditions of the PZL W-3 Falcon helicopter. The conclusions resulting from the conducted numerical computations should allow for optimisation of the flow duct geometry in the cooler, in order to achieve the greatest possible temperature reduction of exhaust exiting into the surroundings. It is expected that the obtained results should be useful for further works related to the development of the final version of exhaust cooler for the PZL W-3 Falcon helicopter.

Keywords: exhaust cooler, helicopter, numerical simulation, stealth

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Authors: H. Djebar, L. Khene, M. Boucenna, M. R. Djebar, M. N. Khebbeb, M. Djekoun

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Currently in toxicology, use of alternative models permits to understand the mechanisms of toxicity at different levels of cells. Objectives of our research concern the determination of NPs ZnO, TiO2, AlO2, and FeO2 effect on ciliate protist freshwater Paramecium sp and Helix aspersa. The result obtained show that NPs increased antioxidative enzyme activity like catalase, glutathione –S-transferase and level GSH. Also, cells treated with high concentrations of NPs showed a high level of MDA. In conclusion, observations from growth and enzymatic parameters suggest on one hand that treatment with NPs provokes an oxidative stress and on the other that snale and paramecium are excellent alternatives models for ecotoxicological studies.

Keywords: NPs, GST, catalase, GSH, MDA, toxicity, snale and paramecium

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Authors: Raninder Kaur Dhillon, Mayur Jethwa, Hardeep Singh Rai

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Information technology has made a pivotal progress across disparate disciplines, one of which is AEC (Architecture, Engineering and Construction) industry. CAD is a form of computer-aided building modulation that architects, engineers and contractors use to create and view two- and three-dimensional models. The AEC industry also uses building information modeling (BIM), a newer computerized modeling system that can create four-dimensional models; this software can greatly increase productivity in the AEC industry. BIM models generate open source IFC (Industry Foundation Classes) files which aim for interoperability for exchanging information throughout the project lifecycle among various disciplines. The methods developed in previous studies require either an IFC schema or MVD and software applications, such as an IFC model server or a Building Information Modeling (BIM) authoring tool, to extract a partial or complete IFC instance model. This paper proposes an efficient algorithm for extracting a partial and total model from an Industry Foundation Classes (IFC) instance model without an IFC schema or a complete IFC model view definition (MVD).

Keywords: BIM, CAD, IFC, MVD

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Authors: Daniel Fulus Fom, Gau Patrick Damulak

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In this study, the Autoregressive Fractional Integrated Moving Average (ARFIMA) and Jordan Recurrent Neural Network (JRNN) models were employed to model the forecasting performance of the daily turbidity flow of White Clay Creek (WCC). The two methods were applied to the log difference series of the daily turbidity flow series of WCC. The measurements of error employed to investigate the forecasting performance of the ARFIMA and JRNN models are the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). The outcome of the investigation revealed that the forecasting performance of the JRNN technique is better than the forecasting performance of the ARFIMA technique in the mean square error sense. The results of the ARFIMA and JRNN models were obtained by the simulation of the models using MATLAB version 8.03. The significance of using the log difference series rather than the difference series is that the log difference series stabilizes the turbidity flow series than the difference series on the ARFIMA and JRNN.

Keywords: auto regressive, mean absolute error, neural network, root square mean error

Procedia PDF Downloads 252

Authors: Thiago Victor Cordeiro Marcos, Joao Felipe de Araujo Martos, Ronaldo de Lima Cardoso, David Romanelli Pinto, Paulo Gilberto de Paula Toro, Israel da Silveira Rego, Antonio Carlos de Oliveira

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Currently, the use of 3D rapid prototyping, also known as 3D printing, has been investigated by some universities around the world as an innovative technique, fast, flexible and cheap for a direct plastic models manufacturing that are lighter and with complex geometries to be tested for hypersonic shock tunnel. Initially, the purpose is integrated prototyped parts with metal models that actually are manufactured through of the conventional machining and hereafter replace them with completely prototyped models. The mechanical design models to be tested in hypersonic shock tunnel are based on conventional manufacturing processes, therefore are limited forms and standard geometries. The use of 3D rapid prototyping offers a range of options that enables geometries innovation and ways to be used for the design new models. The conception and project of a prototyped model for hypersonic shock tunnel should be rethought and adapted when comparing the conventional manufacturing processes, in order to fully exploit the creativity and flexibility that are allowed by the 3D prototyping process. The objective of this paper is to compare the conception and project of a 3D rapid prototyping model and a conventional machining model, while showing the advantages and disadvantages of each process and the benefits that 3D prototyping can bring to the manufacture of models to be tested in hypersonic shock tunnel.

Keywords: 3D printing, 3D prototyping, experimental research, hypersonic shock tunnel

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Authors: Enayat Enayati, Reza Behtash

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The purpose of the H2 removal system is to reduce a content of hydrogen and other combustibles in the CO2 feed owing to avoid developing a possible explosive condition in the synthesis. In order to reduce the possibility of forming an explosive gas mixture in the synthesis as much as possible, the hydrogen percent in the fresh CO2, will be removed in hydrogen converter. Therefore the partly compressed CO2/Air mixture is led through Hydrogen converter (Reactor) where the H2, present in the CO2, is reduced by catalytic combustion to values less than 50 ppm (vol). According the following exothermic chemical reaction: 2H2 + O2 → 2H2O + Heat. The catalyst in hydrogen converter consist of platinum on a aluminum oxide carrier. Low catalyst activity maybe due to catalyst poisoning. This will result in an increase of the hydrogen content in the CO2 to the synthesis. It is advised to shut down the plant when the outlet of hydrogen converter increased above 100 ppm, to prevent undesirable gas composition in the plant. Replacement of catalyst will be time exhausting and costly so as to prevent this, we increase the inlet temperature of hydrogen converter according to following Arrhenius' equation: K=K0e (-E_a/RT) K is rate constant of a chemical reaction where K0 is the pre-exponential factor, E_a is the activation energy, and R is the universal gas constant. Increment of inlet temperature of hydrogen converter caused to increase the rate constant of chemical reaction and so declining the amount of hydrogen from 125 ppm to 70 ppm.

Keywords: catalyst, converter, poisoning, temperature

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Authors: Noor Zainab Habib, Ibrahim Kamaruddin, Madzlan Napiah

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This paper present a part of research conducted to investigate the creep behavior of bituminous concrete mixture prepared with well graded using the dynamic creep test. The samples were prepared from unmodified control mix and Polypropylene modified bituminous mix. Unmodified or control mix was prepared with 80/100 grade bitumen while polypropylene modified mix was prepared using polypropylene PP polymer as modifier, blended with 80/100 Pen bitumen. The concentration of polymer in the blend was kept at 1%, 2%, and 3% by weight of bitumen content. For Dynamic Creep Test, Marshall Specimen were prepared at optimum bitumen content and then tested using IPC Global Universal Testing Machine (UTM), in order to investigate the creep stiffness of both modified and control mix. From the results obtained it was found that 1% and 2% PP modified bituminous mix offer better results in comparison to control and 3% PP modified mix samples. The results verify all the findings of empirical and viscosity test results which indicates that polymer modification induces stiffening effect in the binder. Enhanced viscous component of the binder was considered responsible for this change which eventually enhances the mechanical strength of the modified bituminous mixes.

Keywords: polymer modified bitumen, stiffness, creep, viscosity

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Authors: Zahia Aliche, Fatiha Boudjema, Benyoucef Khelidj, Selma Mettai, Zohra Bouriahi, Saliha Mohammed Belkebir, Ridha Mazouz

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The purpose of this work is the study of the viscoelastic behaviour formulating gels based plant extractions. The extracts of Zingibar officinale and Cinnamomum cassia were included in the gel at different concentrations of these plants in order to be applied in anti-inflammatory drugs. The yield of ethanolic extraction of Zingibar o. is 3.98% and for Cinnamomum c., essential oil by hydrodistillation is 1.67 %. The ethanolic extract of Zingibar.o, the essential oil of Cinnamomum c. and the mixture showed an anti-DPPH radicals’ activity, presented by EC50 values of 11.32, 13.48 and 14.39 mg/ml respectively. A gel based on different concentrations of these extracts was prepared. Microbiological tests conducted against Staphylococcus aureus and Escherichia colishowed moderate inhibition of Cinnamomum c. gel and less the gel based on Cinnamomum c./ Zingibar o. (20/80). The yeast Candida albicansis resistant to gels. The viscoelastic formulation property was carried out in dynamic and creep and modeled with the Kelvin-Voigt model. The influence of some parameters on the stability of the gel (time, temperature and applied stress) has been studied.

Keywords: Cinnamomum cassia, Zingibar officinale, antioxidant activity, antimicrobien activity, gel, viscoelastic behaviour

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Authors: Markus Nordlund, Arkadiusz K. Kuczaj

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Philip Morris International (PMI) is developing a range of novel tobacco products with the potential to reduce individual risk and population harm in comparison to smoking cigarettes. One of these products is the Tobacco Heating System 2.2 (THS 2.2), (named as the Electrically Heated Tobacco System (EHTS) in this paper), already commercialized in a number of countries (e.g., Japan, Italy, Switzerland, Russia, Portugal and Romania). During use, the patented EHTS heats a specifically designed tobacco product (Electrically Heated Tobacco Product (EHTP)) when inserted into a Holder (heating device). The EHTP contains tobacco material in the form of a porous plug that undergoes a controlled heating process to release chemical compounds into vapors, from which an aerosol is formed during cooling. The aim of this work was to investigate the aerosol formation characteristics for realistic operating conditions of the EHTS as well as for relevant gas mixture compositions measured in the EHTP aerosol consisting mostly of water, glycerol and nicotine, but also other compounds at much lower concentrations. The nucleation process taking place in the EHTP during use when operated in the Holder has therefore been modeled numerically using an extended Classical Nucleation Theory (CNT) for multicomponent gas mixtures. Results from the performed simulations demonstrate that aerosol droplets are formed only in the presence of an aerosol former being mainly glycerol. Minor compounds in the gas mixture were not able to reach a supersaturated state alone and therefore could not generate aerosol droplets from the multicomponent gas mixture at the operating conditions simulated. For the analytically characterized aerosol composition and estimated operating conditions of the EHTS and EHTP, glycerol was shown to be the main aerosol former triggering the nucleation process in the EHTP. This implies that according to the CNT, an aerosol former, such as glycerol needs to be present in the gas mixture for an aerosol to form under the tested operating conditions. To assess if these conclusions are sensitive to the initial amount of the minor compounds and to include and represent the total mass of the aerosol collected during the analytical aerosol characterization, simulations were carried out with initial masses of the minor compounds increased by as much as a factor of 500. Despite this extreme condition, no aerosol droplets were generated when glycerol, nicotine and water were treated as inert species and therefore not actively contributing to the nucleation process. This implies that according to the CNT, an aerosol cannot be generated without the help of an aerosol former, from the multicomponent gas mixtures at the compositions and operating conditions estimated for the EHTP, even if all minor compounds are released or generated in a single puff.

Keywords: aerosol, classical nucleation theory (CNT), electrically heated tobacco product (EHTP), electrically heated tobacco system (EHTS), modeling, multicomponent, nucleation

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Authors: Cheikh Bamba Dione, Alla Lo, Elhadji Mamadou Nguer, Siley O. Ba

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In this paper, we propose two neural machine translation (NMT) systems (French-to-Wolof and Wolof-to-French) based on sequence-to-sequence with attention and transformer architectures. We trained our models on a parallel French-Wolof corpus of about 83k sentence pairs. Because of the low-resource setting, we experimented with advanced methods for handling data sparsity, including subword segmentation, back translation, and the copied corpus method. We evaluate the models using the BLEU score and find that transformer outperforms the classic seq2seq model in all settings, in addition to being less sensitive to noise. In general, the best scores are achieved when training the models on word-level-based units. For subword-level models, using back translation proves to be slightly beneficial in low-resource (WO) to high-resource (FR) language translation for the transformer (but not for the seq2seq) models. A slight improvement can also be observed when injecting copied monolingual text in the target language. Moreover, combining the copied method data with back translation leads to a substantial improvement of the translation quality.

Keywords: backtranslation, low-resource language, neural machine translation, sequence-to-sequence, transformer, Wolof

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Authors: Charizza D. Montarin, Daryl Jae S. Sigue, Gilford Estores

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Philippines was moderately vulnerable to corrosion and to prevent this problem, surface coating should be applied. The main objective of this research was to develop and optimize a bio-based mixture of Pili Resin and Lime as Coating Materials. There are three (3) factors to be considered in choosing the best coating material such as chemical adhesion, friction, and the bearing/shear against the steel bar-concrete interface. Fortunately, both proportions of the Bio-based coating materials (50:50 and 65:35) do not have red rust formation complying with ASTM B117 but failed in terms of ASTM D 3359. Splitting failures of concrete were observed in the Unconfined Reinforced Concrete Samples. All of the steel bars (uncoated and coated) surpassed the Minimum Bond strength (NSCP 2015) about 203% to 285%. The experiments were about 1% to 3% of the results from the ANSYS Simulations with and without Salt Spray Test. Using the bio-based and epoxy coatings, normal splitting strengths were declined. However, there has no significant difference between the results. Thus, the bio-based coating materials can be used as an alternative for the epoxy coating materials and it was highly recommended for Low – Rise Building only.

Keywords: Canarium luzonicum, calcium oxide, corrosion, finite element simulations

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Authors: Peyman Aela, Lu Zong, Guoqing Jing

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Recently, there has been growing interest in numerical modeling of ballast railway tracks. A commonly used mechanistic modeling approach for ballast is the discrete element method (DEM). Up to now, the effects of the contact model on ballast particle behavior have not been precisely examined. In this regard, selecting the appropriate contact model is mainly associated with the particle characteristics and the loading condition. Since ballast is cohesionless material, different contact models, including the linear spring, Hertz-Mindlin, and Hysteretic models, could be used to calculate particle-particle or wall-particle contact forces. Moreover, the simulation of a dynamic test is vital to investigate the effect of damping parameters on the ballast deformation. In this study, ballast box tests were simulated by DEM to examine the influence of different contact models on the mechanical behavior of the ballast layer under cyclic loading. This paper shows how the contact model can affect the deformation and damping of a ballast layer subjected to cyclic loading in a ballast box.

Keywords: ballast, contact model, cyclic loading, DEM

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Authors: Stuart Bradley, Mathew Legg, Lilyan Panton

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Ultrasonic remote sensing is a useful tool for assessing the interior structure of complex targets. For these methods, significantly enhanced spatial resolution is obtained if the pulse is coded, for example using a linearly changing frequency during the pulse duration. Such pulses have a time-dependent spectral structure. Interpretation of the backscatter from targets is, therefore, complicated if the scattering is frequency-dependent. While analytic models are well established for steady sinusoidal excitations applied to simple shapes such as spheres, such models do not generally exist for temporally evolving excitations. Therefore, models are developed in the current paper for handling such signals so that the properties of the targets can be quantitatively evaluated while maintaining very high spatial resolution. Laboratory measurements on simple shapes are used to confirm the validity of the models.

Keywords: linear FM chirp, time-dependent acoustic scattering, ultrasonic remote sensing, ultrasonic scattering

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Authors: P. Singh, R. M. Banik

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Artificial neural network (ANN) was employed to optimize assay parameters viz., time, temperature, pH of reaction mixture, enzyme volume and substrate concentration of L-glutaminase from Bacillus cereus MTCC 1305. ANN model showed high value of coefficient of determination (0.9999), low value of root mean square error (0.6697) and low value of absolute average deviation. A multilayer perceptron neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model and its topology was obtained as 5-3-1 after applying Levenberg Marquardt (LM) training algorithm. The predicted activity of L-glutaminase was obtained as 633.7349 U/l by considering optimum assay parameters, viz., pH of reaction mixture (7.5), reaction time (20 minutes), incubation temperature (35˚C), substrate concentration (40mM), and enzyme volume (0.5ml). The predicted data was verified by running experiment at simulated optimum assay condition and activity was obtained as 634.00 U/l. The application of ANN model for optimization of assay conditions improved the activity of L-glutaminase by 1.499 fold.

Keywords: Bacillus cereus, L-glutaminase, assay parameters, artificial neural network

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Authors: Anna Zimoch-Korzycka, Dominika Kulig, Andrzej Jarmoluk

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The aim of this study was to obtain chitooligosaccharides from chitosan with better functional properties using three different enzyme preparations and compare the products of enzymatic hydrolysis. Commercially available cellulase (CL), xylanase (X) and chitosanase (CS) preparations were used to investigate hydrolytic activity on chitosan (CH) with low molecular weight and DD of 75-85%. It has been reported that CL and X have side activities of other enzymes, such as β-glucanase or β-glucosidase. CS enzyme has a foreign activity of chitinase. Each preparation was used in 1000 U of activity and in the same reaction conditions. The degree of deacetylation and molecular weight of chitosan were specified using titration and viscometric methods, respectively. The hydrolytic activity of enzymes preparations on chitosan was monitored by dynamic viscosity measurement. After 4 h reaction with stirring, solutions were filtered and chitosan oligomers were isolated by methanol solution into two fractions: precipitate (A) and supernatant (B). A Fourier-transform infrared spectroscopy was used to characterize the structural changes of chitosan oligomers fractions and initial chitosan. Furthermore, the solubility of lyophilized hydrolytic mixture (C) and two chitooligomers fractions (A, B) of each enzyme hydrolysis was assayed. The antioxidant activity of chitosan oligomers was evaluated as DPPH free radical scavenging activity. The dynamic viscosity measured after addition of enzymes preparation to the chitosan solution decreased dramatically over time in the sample with X in comparison to solution without the enzyme. For mixtures with CL and CS, lower viscosities were also recorded but not as low as the ones with X. A and B fractions were characterized by the most similar viscosity obtained by the xylanase hydrolysis and were 15 mPas and 9 mPas, respectively. Structural changes of chitosan oligomers A, B, C and their differences related with various enzyme preparations used were confirmed. Water solubility of A fractions was not possible to filter and the result was not recorded. Solubility of supernatants was approximately 95% and was higher than hydrolytic mixture. It was observed that the DPPH radical scavenging effect of A, B, C samples is the highest for X products and was approximately 13, 17, 19% respectively. In summary, a mixture of chitooligomers may be useful for the design of edible protective coatings due to the improved biophysical properties.

Keywords: cellulase, xylanase, chitosanase, chitosan, chitooligosaccharides

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Authors: Khlifa El Atrash, Gabriel Assaf

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Libya uses a volumetric analysis in designing asphalt mixtures, which can also be upgraded in hot, arid weather. However, in order to be effective, it should include many important aspects which are materials, environment, and method of construction. However, the quality of some roads was below a satisfactory level. This paper examines the factors that contribute to low quality of road performance in Libya. To evaluate these factors, a questionnaire survey and a laboratory comparative study were performed for a few mixes under-represented of temperature and traffic load. In laboratory, rutting test conducted on two different asphalt mixture, these mixes included, an asphalt concrete mix using local aggregate and asphalt binder B(60/70) at the optimum Marshall asphalt content, another mixes designed using Superpave design procedure with the same materials and performance asphalt binder grade PG (70-10). In the survey, the questionnaire was distributed to 55 engineers and specialists in this field. The interview was conducted to a few others, and the factors that were leading to poor performance of asphalt roads were listed as; 1) Owner Experience and technical staff 2) Asphalt characteristics 3) Updating and development of Asphalt Mix Design methods 4) Lack of data collection by authorization Agency 5) Construction and compaction process 6) Mentoring and controlling mixing procedure. Considering and improving these factors will play an important role to improve the pavement performances, longer service life, and lower maintenance costs. This research summarized some recommendations for making asphalt mixtures used in hot, dry areas. Such asphalt mixtures should use asphalt binder which is less affected by pavement temperature change and traffic load. The properties of the mixture, such as durability, deformation, air voids, and performance, largely depend on the type of materials, environment, and mixing method. These properties, in turn, affect the pavement performance.

Keywords: volumetric analysis, pavement performances, hot climate, traffic load, pavement temperature, asphalt mixture, environment, design and construction

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Authors: Nagasamy Venkatesh Dhandapani

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The objective of the present study was to develop sustained release oral matrix tablets of anti epileptic drug levetiracetam. The sustained release matrix tablets of levetiracetam were prepared using hydrophilic matrix hydroxypropyl methylcellulose (HPMC) as a release retarding polymer by wet granulation method. Prior to compression, FTIR studies were performed to understand the compatibility between the drug and excipients. The study revealed that there was no chemical interaction between drug and excipients used in the study. The tablets were characterized by physical and chemical parameters and results were found in acceptable limits. In vitro release study was carried out for the tablets using 0.1 N HCl for 2 hours and in phosphate buffer pH 7.4 for remaining time up to 12 hours. The effect of polymer concentration was studied. Different dissolution models were applied to drug release data in order to evaluate release mechanisms and kinetics. The drug release data fit well to zero order kinetics. Drug release mechanism was found as a complex mixture of diffusion, swelling and erosion.

Keywords: levetiracetam, sustained-release, hydrophilic matrix tablet, HPMC grade K 100 MCR, wet granulation, zero order release kinetics

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Authors: Jessemyn Modiini, Timothy Lynar, Elena Sitnikova

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We present a novel enhanced compartmental model for malware spread analysis in cyber security. This paper applies cyber security data features to epidemiological compartmental models to model the infectious potential of malware. Compartmental models are most efficient for calculating the infectious potential of a disease. In this paper, we discuss and profile epidemiologically relevant data features from a Domain Name System (DNS) dataset. We then apply these features to epidemiological compartmental models to network traffic features. This paper demonstrates how epidemiological principles can be applied to the novel analysis of key cybersecurity behaviours and trends and provides insight into threat modelling above that of kill-chain analysis. In applying deterministic compartmental models to a cyber security use case, the authors analyse the deficiencies and provide an enhanced stochastic model for cyber epidemiology. This enhanced compartmental model (SUEICRN model) is contrasted with the traditional SEIR model to demonstrate its efficacy.

Keywords: cybersecurity, epidemiology, cyber epidemiology, malware

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Authors: Mohd Khairul Bazli Mohd Aziz, Fadhilah Yusof, Zulkifli Yusop, Zalina Mohd Daud, Mohammad Afif Kasno

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Recent developed rainfall network design techniques have been discussed and compared by many researchers worldwide due to the demand of acquiring higher levels of accuracy from collected data. In many studies, rain-gauge networks are designed to provide good estimation for areal rainfall and for flood modelling and prediction. In a certain study, even using lumped models for flood forecasting, a proper gauge network can significantly improve the results. Therefore existing rainfall network in Johor must be optimized and redesigned in order to meet the required level of accuracy preset by rainfall data users. The well-known geostatistics method (variance-reduction method) that is combined with simulated annealing was used as an algorithm of optimization in this study to obtain the optimal number and locations of the rain gauges. Rain gauge network structure is not only dependent on the station density; station location also plays an important role in determining whether information is acquired accurately. The existing network of 84 rain gauges in Johor is optimized and redesigned by using rainfall, humidity, solar radiation, temperature and wind speed data during monsoon season (November – February) for the period of 1975 – 2008. Three different semivariogram models which are Spherical, Gaussian and Exponential were used and their performances were also compared in this study. Cross validation technique was applied to compute the errors and the result showed that exponential model is the best semivariogram. It was found that the proposed method was satisfied by a network of 64 rain gauges with the minimum estimated variance and 20 of the existing ones were removed and relocated. An existing network may consist of redundant stations that may make little or no contribution to the network performance for providing quality data. Therefore, two different cases were considered in this study. The first case considered the removed stations that were optimally relocated into new locations to investigate their influence in the calculated estimated variance and the second case explored the possibility to relocate all 84 existing stations into new locations to determine the optimal position. The relocations of the stations in both cases have shown that the new optimal locations have managed to reduce the estimated variance and it has proven that locations played an important role in determining the optimal network.

Keywords: geostatistics, simulated annealing, semivariogram, optimization

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Authors: Pattra Pukdeekiat, Siriluk Ruangrungrote

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This work was originated to precisely determine direct solar radiation by using atmospheric physics models since the accurate prediction of solar radiation is necessary and useful for solar energy applications including atmospheric research. The possible models and techniques for a calculation of regional direct solar radiation were challenging and compulsory for the case of unavailable instrumental measurement. The investigation was mathematically governed by six astronomical parameters i.e. declination (δ), hour angle (ω), solar time, solar zenith angle (θz), extraterrestrial radiation (Iso) and eccentricity (E0) along with two atmospheric parameters i.e. air mass (mr) and dew point temperature at Bangna meteorological station (13.67° N, 100.61° E) in Bangkok, Thailand. Analyses of five models of solar radiation determination with the assumption of clear sky were applied accompanied by three statistical tests: Mean Bias Difference (MBD), Root Mean Square Difference (RMSD) and Coefficient of determination (R2) in order to validate the accuracy of obtainable results. The calculated direct solar radiation was in a range of 491-505 Watt/m2 with relative percentage error 8.41% for winter and 532-540 Watt/m2 with relative percentage error 4.89% for summer 2014. Additionally, dataset of seven continuous days, representing both seasons were considered with the MBD, RMSD and R2 of -0.08, 0.25, 0.86 and -0.14, 0.35, 3.29, respectively, which belong to Kumar model for winter and CSR model for summer. In summary, the determination of direct solar radiation based on atmospheric models and empirical equations could advantageously provide immediate and reliable values of the solar components for any site in the region without a constraint of actual measurement.

Keywords: atmospheric physics models, astronomical parameters, atmospheric parameters, clear sky condition

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