Search results for: Caputo-type fuzzy fractional derivative

Authors: M. N. Amrani, H. Abanou, A. Dib

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In this paper, we proposed a strategy for optimizing the performance for a pumping structure constituted by an induction motor coupled to a centrifugal pump and improving existing results in this context. The considered system is supplied by a photovoltaic generator (GPV) through two static converters piloted in an independent manner. We opted for a maximum power point tracking (MPPT) control method based on the Neuro - Fuzzy, which is well known for its stability and robustness. To improve the induction motor performance, we use the concept of Direct Torque Control (DTC) and PID controller for motor speed to pilot the working of the induction motor. Simulations of the proposed approach give interesting results compared to the existing control strategies in this field. The model of the proposed system is simulated by MATLAB/Simulink.

Keywords: solar energy, pumping photovoltaic system, maximum power point tracking, direct torque Control (DTC), PID regulator

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Authors: Franziska Kaiser, Alexander Cuntz

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When copyrighted comic characters are also protected under trademark laws, intellectual property (IP) rights can overlap. Arguably, registering a trademark can increase transaction costs for cross-media uses of characters, or it can favor advertise across a number of sales channels. In an application to book, movie, and video game publishing industries, we thus ask how creative reuse is affected in situations of overlapping rights and whether ‘fuzzy boundaries’ of right frameworks are, in fact, enhancing or decreasing content sales. We use a major U.S. Supreme Court decision as a quasi-natural experiment to apply an IV estimation in our analysis. We find that overlapping rights frameworks negatively affect creative reuses. At large, when copyright-protected comic characters are additionally registered as U.S. trademarks, they are less often reprinted and enter fewer video game productions while generating less revenue from game sales.

Keywords: copyright, fictional characters, trademark, reuse

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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: Y. T. Gebreslassie, Abrha Tadesse, R. C. Saini, Rishi Pal

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Caffeine, known chemically as 3,7-dihydro-1,3,7-trimethyl-1H-purine-2,6-dione, is a naturally occurring alkaloid classified as an N-methyl derivative of xanthine. Given its widespread use in coffee and other caffeine-containing products, it is the most commonly consumed psychoactive substance in everyday human life. This research aimed to develop a cost-effective, sensitive, and easily manufacturable sensor for the detection of caffeine. Antraquinone-modified carbon paste electrode (AQMCPE) was fabricated, and the electrochemical behavior of caffeine on this electrode was investigated using cyclic voltammetry (CV) and square wave voltammetry (SWV) in a solution of 0.1M perchloric acid at pH 0.56. The modified electrode displayed enhanced electrocatalytic activity towards caffeine oxidation, exhibiting a two-fold increase in peak current and an 82 mV shift of the peak potential in the negative direction compared to an unmodified carbon paste electrode (UMCPE). Exploiting the electrocatalytic properties of the modified electrode, SWV was employed for the quantitative determination of caffeine. Under optimized experimental conditions, a linear relationship between peak current and concentration was observed within the range of 2.0 x 10⁻⁶ to 1.0× 10⁻⁴ M, with a correlation coefficient of 0.998 and a detection limit of 1.47× 10⁻⁷ M (signal-to-noise ratio = 3). Finally, the proposed method was successfully applied to the quantitative analysis of caffeine in pharmaceutical formulations, yielding recovery percentages ranging from 95.27% to 106.75%.

Keywords: antraquinone-modified carbon paste electrode, caffeine, detection, electrochemical sensor, quantitative analysis

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Authors: Selim Kermasha

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A process for the synthesis of structured lipids (SLs) by the lipase-catalyzed interesterification of selected endogenous edible oils such as flaxseed oil (FO) and medium-chain triacylglyceols such as tricaprylin (TC) in non-conventional media (NCM), including organic solvent media (OSM) and solvent-free medium (SFM), was developed. The bioconversion yield of the medium-long-medium-type SLs (MLM-SLs were monitored as the responses with use of selected commercial lipases. In order to optimize the interesterification reaction and to establish a model system, a wide range of reaction parameters, including TC to FO molar ratio, reaction temperature, enzyme concentration, reaction time, agitation speed and initial water activity, were investigated to establish the a model system. The model system was monitored with the use of multiple response surface methodology (RSM) was used to obtain significant models for the responses and to optimize the interesterification reaction, on the basis of selected levels and variable fractional factorial design (FFD) with centre points. Based on the objective of each response, the appropriate level combination of the process parameters and the solutions that met the defined criteria were also provided by means of desirability function. The synthesized novel molecules were structurally characterized, using silver-ion reversed-phase high-performance liquid chromatography (RP-HPLC) atmospheric pressure chemical ionization-mass spectrophotometry (APCI-MS) analyses. The overall experimental findings confirmed the formation of dicaprylyl-linolenyl glycerol, dicaprylyl-oleyl glycerol and dicaprylyl-linoleyl glycerol resulted from the lipase-catalyzed interesterification of FO and TC.

Keywords: enzymatic interesterification, non-conventinal media, nutraceuticals, structured lipids

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Authors: Nana Adjoah Mbroh, Suares Clovis Oukouomi Noutchie

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Singularly perturbed problems are parameter dependent problems, and they play major roles in the modelling of real-life situational problems in applied sciences. Thus, designing efficient numerical schemes to solve these problems is of much interest since the exact solutions of such problems may not even exist. Generally, singularly perturbed problems are identified by a small parameter multiplying at least the highest derivative in the equation. The presence of this parameter causes the solution of these problems to be characterized by rapid oscillations. This unique feature renders classical numerical schemes inefficient since they are unable to capture the behaviour of the exact solution in the part of the domain where the rapid oscillations are present. In this paper, a numerical scheme is proposed to solve a singularly perturbed Volterra Integro-differential equation. The scheme is based on the midpoint rule and employs the non-standard finite difference scheme to solve the differential part whilst the composite trapezoidal rule is used for the integral part. A fully fledged error estimate is performed, and Richardson extrapolation is applied to accelerate the convergence of the scheme. Numerical simulations are conducted to confirm the theoretical findings before and after extrapolation.

Keywords: midpoint rule, non-standard finite difference schemes, Richardson extrapolation, singularly perturbed problems, trapezoidal rule, uniform convergence

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Authors: Yuan-Jye Tseng, Jia-Shu Li

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To design a product with the given product requirement and design objective, there can be alternative ways to propose the detailed design specifications of the product. In the design modeling stage, alternative design cases with detailed specifications can be modeled to fulfill the product requirement and design objective. Therefore, in the design evaluation stage, it is required to perform an evaluation of the alternative design cases for deciding the final design. The purpose of this research is to develop a product evaluation model for evaluating the alternative design cases by integrated evaluating the criteria of functional design, Kansei design, and design for supply chain. The criteria in the functional design group include primary function, expansion function, improved function, and new function. The criteria in the Kansei group include geometric shape, dimension, surface finish, and layout. The criteria in the design for supply chain group include material, manufacturing process, assembly, and supply chain operation. From the point of view of value and cost, the criteria in the functional design group and Kansei design group represent the design value of the product. The criteria in the design for supply chain group represent the supply chain and manufacturing cost of the product. It is required to evaluate the design value and the supply chain cost to determine the final design. For the purpose of evaluating the criteria in the three criteria groups, a fuzzy analytic network process (FANP) method is presented to evaluate a weighted index by calculating the total relational values among the three groups. A method using the technique for order preference by similarity to ideal solution (TOPSIS) is used to compare and rank the design alternative cases according to the weighted index using the total relational values of the criteria. The final decision of a design case can be determined by using the ordered ranking. For example, the design case with the top ranking can be selected as the final design case. Based on the criteria in the evaluation, the design objective can be achieved with a combined and weighted effect of the design value and manufacturing cost. An example product is demonstrated and illustrated in the presentation. It shows that the design evaluation model is useful for integrated evaluation of functional design, Kansei design, and design for supply chain to determine the best design case and achieve the design objective.

Keywords: design for supply chain, design evaluation, functional design, Kansei design, fuzzy analytic network process, technique for order preference by similarity to ideal solution

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Authors: Yike Lamu, Jieyu Tang, Jialin Wu, Jianyun Huang

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With the development of economy and science and technology, the urban heat island effect becomes more and more serious. Taking Beijing city as an example, this paper divides the value of each influence index of heat island intensity and establishes a mathematical model – neural network system based on the fuzzy comprehensive evaluation index of heat island effect. After data preprocessing, the algorithm of weight of each factor affecting heat island effect is generated, and the data of sex indexes affecting heat island intensity of Shenyang City and Shanghai City, Beijing, and Hangzhou City are input, and the result is automatically output by the neural network system. It is of practical significance to show the intensity of heat island effect by visual method, which is simple, intuitive and can be dynamically monitored.

Keywords: heat island effect, neural network, comprehensive evaluation, visualization

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Authors: Michael R. Phangtriastu, Herriyandi Herriyandi, Diaz D. Santika

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This paper presents a comparison of the implementation of metaheuristic algorithms to train the antecedent parameters and consequence parameters in the adaptive network-based fuzzy inference system (ANFIS). The algorithms compared are genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC). The objective of this paper is to benchmark well-known metaheuristic algorithms. The algorithms are applied to several data set with different nature. The combinations of the algorithms' parameters are tested. In all algorithms, a different number of populations are tested. In PSO, combinations of velocity are tested. In ABC, a different number of limit abandonment are tested. Experiments find out that ABC is more reliable than other algorithms, ABC manages to get better mean square error (MSE) than other algorithms in all data set.

Keywords: ANFIS, artificial bee colony, genetic algorithm, metaheuristic algorithm, particle swarm optimization

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Authors: Sang Kompiang Wirawan, Pandu Prabowo Jati, I Wayan Warmada

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Klaten Indonesian natural zeolite can be used as powder or pellet adsorbent. Pellet adsorbent has been made from activated natural zeolite powder by a conventional pressing method. Starch and formaldehyde were added as binder to strengthen the construction of zeolite pellet. To increase the absorptivity and its capacity, natural zeolite was activated first chemically and thermally. This research examined adsorption process of water from Isopropyl Alcohol (IPA)-water system using zeolite adsorbent pellet from natural zeolite powder which has been activated with H2SO4 0.1 M and 0.3 M. Adsorbent was pelleted by pressing apparatus at certain pressure to make specification in 1.96 cm diameter, 0.68 cm thickness which the natural zeolite powder (-80 mesh). The system of isopropyl-alcohol water contained 80% isopropyl-alcohol. Adsorption process was held in close-loop continuous apparatus which the zeolite pellet was put inside a column and the solution of IPA-water was circulated at certain flow. Concentration changing was examined thoroughly at a certain time. This adsorption process included mass transfer from bulk liquid into film layer and from film layer into the solid particle. Analysis of rate constant was using first order isotherm model that simulated with MATLAB. Besides using first order isotherm, intra-particle diffusion model was proposed by using pore diffusion model. The study shows that adsorbent activated by H2SO4 0.1 M has good absorptivity with mass transfer constant at 0.1286 min-1.

Keywords: intra-particle diffusion, fractional attainment, first order isotherm, zeolite

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Authors: Henry Lau, Dilupa Nakandala, Li Zhao

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In today’s business, it is well-recognized that risk is an important factor that needs to be taken into consideration before a decision is made. Studies indicate that both the number of risks faced by organizations and their potential consequences are growing. Supply chain risk management has become one of the major concerns for practitioners and researchers. Supply chain leaders and scholars are now focusing on the importance of managing supply chain risk. In order to meet the challenge of managing and mitigating supply chain risk (SCR), we must first identify the different dimensions of SCR and assess its relevant probability and severity. SCR has been classified in many different ways, and there are no consistently accepted dimensions of SCRs and several different classifications are reported in the literature. Basically, supply chain risks can be classified into two dimensions namely disruption risk and operational risk. Disruption risks are those caused by events such as bankruptcy, natural disasters and terrorist attack. Operational risks are related to supply and demand coordination and uncertainty, such as uncertain demand and uncertain supply. Disruption risks are rare but severe and hard to manage, while operational risk can be reduced through effective SCM activities. Other SCRs include supply risk, process risk, demand risk and technology risk. In fact, the disorganized classification of SCR has created confusion for SCR scholars. Moreover, practitioners need to identify and assess SCR. As such, it is important to have an overarching framework tying all these SCR dimensions together for two reasons. First, it helps researchers use these terms for communication of ideas based on the same concept. Second, a shared understanding of the SCR dimensions will support the researchers to focus on the more important research objective: operationalization of SCR, which is very important for assessing SCR. In general, fresh food supply chain is subject to certain level of risks, such as supply risk (low quality, delivery failure, hot weather etc.) and demand risk (season food imbalance, new competitors). Effective strategies to mitigate fresh food supply chain risk are required to enhance operations. Before implementing effective mitigation strategies, we need to identify the risk sources and evaluate the risk level. However, assessing the supply chain risk is not an easy matter, and existing research mainly use qualitative method, such as risk assessment matrix. To address the relevant issues, this paper aims to analyze the risk factor of the fresh food supply chain using an approach comprising both fuzzy logic and hierarchical holographic modeling techniques. This novel approach is able to take advantage the benefits of both of these well-known techniques and at the same time offset their drawbacks in certain aspects. In order to develop this integrated approach, substantial research work is needed to effectively combine these two techniques in a seamless way, To validate the proposed integrated approach, a case study in a fresh food supply chain company was conducted to verify the feasibility of its functionality in a real environment.

Keywords: fresh food supply chain, fuzzy logic, hierarchical holographic modelling, operationalization, supply chain risk

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Authors: Dixon, Lieh-Chi Su, Hsiao-Ling Yu, Ren-Yi Huang, Yung-Tan Lee

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The present paper analyzed the major, trace elements, rare earth elements of these Cenozoic basalts and combined with Sr-Nd isotopic compositions to discuss the petrogenesis of these basalts and the tectonic setting of the study area. Based on major, trace elements and fractional crystallization model we suggest that the basaltic magma has experienced olivine, clinopyroxene, and plagioclase fractionation during its evolution. Spidergrams and REE patterns reveal that Cenozoic basalts found in the Jiashan County, Anhui Province have geochemical characteristics similar to those of ocean island basalts(OIB) suggesting a derivation related to OIB-like mantle source. The slight positive Nb and Ti anomalies found in basaltic rocks of this study suggest the presence of Ti-bearing minerals in the mantle source and these Ti-bearing minerals had contributed to basaltic magma during partial melting, indicating a metasomatic event might have occurred before the partial melting. Based on 143Nd/144Nd vs. 87Sr/86Sr diagram we suggest that basalts of this study can be produced by MORB and EM-I components mixing and small degree of partial melting may be the major controlling factor during generation of basaltic magma. Some basaltic magma may be derived from partial melting of EM-Ⅰ heated by the upwelling asthenospheric mantle. The basalts fall within the WPB field in the discriminant plot of 2Nb-Zr/4-Y indicate that the volcanic activities in this region may be closely related to deep continental rifting process.

Keywords: geochemistry, cenozoic basalts, Anhui Province, Nushan Geopark, tectonic setting, fractionation

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Authors: Chaima Zoulikha Tabet Zatla, Nihel Dib, Sumeya Bedrane, Juan Carlos Hernandez Garrido, Redouane Bachir, Miguel Angel Cauqui, Jose Juan Calvino Gamez

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These last year's our planet has witnessed global warming, which is a serious threat to our lives; it has many causes, such as the CO₂ excess in the atmosphere that results from our activity, for the purpose of living in a neater and better environment, working and improving an eco-responsible energy system is a must. Valorization of biomass to produce biofuels is among the most compelling routes to decrease air pollution without considerable modification in current vehicle technology. Effective transformation of lignocellulosic biomass-derived compounds into liquid fuels and value-added chemicals is an economically viable solution. Presently, very competitive technics for the conversion of lignocellulosic biomass into platform chemicals, such as furfural and Hydroxymethylfurfural (HMF), are used. Furfural (C₅H₄O₂) is a major hemi cellulosic biomass-derived platform molecule. In our work, we focus on the valorization of lignocellulosic biomass derivative furfural that is transformed into biofuel through a hydrodeoxygenation reaction in general and involving a catalytic process. In order to get to this point, we are synthesizing and characterizing a series of catalysts with different amounts of Ru (0.5%, 1% and 2%) supported on alumina-silica mixed oxides with various molar ratios (Si/Al = 2.5; 5; 7; 10; 15). These catalysts will be characterized by numerous technics such as N₂ adsorption/desorption, Pyridine adsorption (acidity measure), FTIR, X-rays diffraction, AAS, TEM and SEM.

Keywords: furfural, ruthenium, silica-alumina, biomass, biofuel

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Authors: Azzeddine Abdelalim, Fatiha Rogti

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The degradation phenomenon in polymer solar cells (PCSs) has not been clearly explained yet. In fact, there are many causes that show up and influence these cells in a variety of ways. Also, there has been a growing concern over this degradation in the photovoltaic community. One of the main variables deciding PSCs photovoltaic output is defect states. In this research, devices modeling is carried out to analyze the multiple effects of degradation by applying high defect states (HDS) on ideal PSCs, mainly poly(3-hexylthiophene) (P3HT) absorber layer. Besides, a comparative study is conducted between P3HT and other PSCs by a simulation program called Solar Cell Capacitance Simulator (SCAPS). The adjustments to the defect parameters in several absorber layers explain the effect of HDS on the total output properties of PSCs. The performance parameters for HDS, quantum efficiency, and energy band were therefore examined. This research attempts to explain the degradation process of PSCs and the causes of their low efficiency. It was found that the defects often affect PSCs performance, but defect states have a little effect on output when the defect level is less than 1014cm-3, which gives similar performance values with P3HT cells when these defects is about 1019cm-3. The high defect states can cause up to 11% relative reduction in conversion efficiency of ideal P3HT. In the center of the band gap, defect states become more noxious. This approach is for one of the degradation processes potential of PSCs especially that use fullerene derivative acceptors.

Keywords: degradation, high defect states, polymer solar cells, SCAPS-1D

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Authors: S. A. Naeini, A. Khalili

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Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.

Keywords: settlement, Subway Line, FLAC3D, ANFIS Method

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Authors: Ying Shen, Weihua Zhu

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Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.

Keywords: magnetic resonance image (MRI), c-means model, image segmentation, information entropy

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Authors: Shiuh-Jer Huang, Yu-Sheng Hsu

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On-board available parking space detecting system, parking trajectory planning and tracking control mechanism are the key components of vehicle backward auto-parking system. Firstly, pair of ultrasonic sensors is installed on each side of vehicle body surface to detect the relative distance between ego-car and surrounding obstacle. The dimension of a found empty space can be calculated based on vehicle speed and the time history of ultrasonic sensor detecting information. This result can be used for constructing the 2D vehicle environmental map and available parking type judgment. Finally, the auto-parking controller executes the on-line optimal parking trajectory planning based on this 2D environmental map, and monitors the real-time vehicle parking trajectory tracking control. This low cost auto-parking system was tested on a model car.

Keywords: vehicle auto-parking, parking space detection, parking path tracking control, intelligent fuzzy controller

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Authors: Ehab El-Dabaa, Omnia Ali, Mohamed Abd El-Hady, Ahmed Osman

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Recombinant human interferon alpha 2 (rhIFN-α2) is FDA approved for treatment of some viral and malignant diseases. Approved pegylated rhIFN-α2 drugs have highly improved pharmacokinetics, pharmacodynamics and therapeutic efficiency compared to native protein. In this work, we studied the pegylation of purified properly refolded rhIFN-α2b using linear 20kDa PEG-NHS (polyethylene glycol- N-hydroxysuccinimidyl ester) to prepare pegylated rhIFN-α2b with high stability and activity. The effect of different parameters like rhIFN-α2b final concentration, pH, rhIFN-α2b/PEG molar ratios and reaction time on the efficiency of pegylation (high percentage of monopegylated rhIFN-α2b) have been studied in small scale (100µl) pegylation reaction trials. Study of the percentages of different components of these reactions (mono, di, polypegylated rhIFN-α2b and unpegylated rhIFN-α2b) indicated that 2h is optimum time to complete the reaction. The pegylation efficiency increased at pH 8 (57.9%) by reducing the protein concentration to 1mg/ml and reducing the rhIFN-α2b/PEG ratio to 1:2. Using larger scale pegylation reaction (65% pegylation efficiency), ion exchange chromatography method has been optimized to prepare and purify the monopegylated rhIFN-α2b with high purity (96%). The prepared monopegylated rhIFN-α2b had apparent Mwt of approximately 65 kDa and high in vitro antiviral activity (2.1x10⁷ ± 0.8 x10⁷ IU/mg). Although it retained approximately 8.4 % of the antiviral activity of the unpegylated rhIFN-α2b, its activity is high compared to other pegylated rhIFN-α2 developed by using similar approach or higher molecular weight branched PEG.

Keywords: antiviral activity, rhIFN-α2b, pegylation, pegylation efficiency

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Authors: Roshanak Khodabakhsh Jolfaei, Javad Akbari Torkestani

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As a cooperative environment for problem-solving, it is necessary that grids develop efficient job scheduling patterns with regard to their goals, domains and structure. Since the Grid environments facilitate distributed calculations, job scheduling appears in the form of a critical problem for the management of Grid sources that influences severely on the efficiency for the whole Grid environment. Due to the existence of some specifications such as sources dynamicity and conditions of the network in Grid, some algorithm should be presented to be adjustable and scalable with increasing the network growth. For this purpose, in this paper a job scheduling algorithm has been presented on the basis of learning automata in computational Grid which the performance of its results were compared with FPSO algorithm (Fuzzy Particle Swarm Optimization algorithm) and GJS algorithm (Grid Job Scheduling algorithm). The obtained numerical results indicated the superiority of suggested algorithm in comparison with FPSO and GJS. In addition, the obtained results classified FPSO and GJS in the second and third position respectively after the mentioned algorithm.

Keywords: computational grid, job scheduling, learning automata, dynamic scheduling

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Authors: I Made Ginarsa, Agung Budi Muljono, I Made Ari Nrartha

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Transient voltage response appears in power system operation when an additional loading is forced to load bus of power systems. In this research, improvement of transient voltage response is done by using power system stabilizer-static var compensator (PSS-SVC) based on adaptive neuro-fuzzy inference system (ANFIS)-algorithm. The main function of the PSS is to add damping component to damp rotor oscillation through automatic voltage regulator (AVR) and excitation system. Learning process of the ANFIS is done by using off-line method where data learning that is used to train the ANFIS model are obtained by simulating the PSS-SVC conventional. The ANFIS model uses 7 Gaussian membership functions at two inputs and 49 rules at an output. Then, the ANFIS-PSS and ANFIS-SVC models are applied to power systems. Simulation result shows that the response of transient voltage is improved with settling time at the time of 4.25 s.

Keywords: improvement, transient voltage, PSS-SVC, ANFIS, settling time

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Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi

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Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.

Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery

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Authors: Abdulmalik Altuwayjiri, Milad Pirhadi, Sina Taghvaee, Constantinos Sioutas

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A significant portion of PM₂.₅ mass concentration is carbonaceous matter (CM), which majorly exists in the form of organic carbon (OC). Ambient OC originates from a multitude of sources and plays an important role in global climate effects, visibility degradation, and human health. In this study, positive matrix factorization (PMF) was utilized to identify and quantify the long-term contribution of PM₂.₅ sources to total OC mass concentration in central Los Angeles (CELA) and Riverside (i.e., receptor site), using the chemical speciation network (CSN) database between 2005 and 2015, a period during which several state and local regulations on tailpipe emissions were implemented in the area. Our PMF resolved five different factors, including tailpipe emissions, non-tailpipe emissions, biomass burning, secondary organic aerosol (SOA), and local industrial activities for both sampling sites. The contribution of vehicular exhaust emissions to the OC mass concentrations significantly decreased from 3.5 µg/m³ in 2005 to 1.5 µg/m³ in 2015 (by about 58%) at CELA, and from 3.3 µg/m³ in 2005 to 1.2 µg/m³ in 2015 (by nearly 62%) at Riverside. Additionally, SOA contribution to the total OC mass, showing higher levels at the receptor site, increased from 23% in 2005 to 33% and 29% in 2010 and 2015, respectively, in Riverside, whereas the corresponding contribution at the CELA site was 16%, 21% and 19% during the same period. The biomass burning maintained an almost constant relative contribution over the whole period. Moreover, while the adopted regulations and policies were very effective at reducing the contribution of tailpipe emissions, they have led to an overall increase in the fractional contributions of non-tailpipe emissions to total OC in CELA (about 14%, 28%, and 28% in 2005, 2010 and 2015, respectively) and Riverside (22%, 27% and 26% in 2005, 2010 and 2015), underscoring the necessity to develop equally effective mitigation policies targeting non-tailpipe PM emissions.

Keywords: PM₂.₅, organic carbon, Los Angeles megacity, PMF, source apportionment, non-tailpipe emissions

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Authors: D. Pinto, L. Castro, M. L. Cruzat, S. Barros, J. Gironás, C. Oberli, M. Torres, C. Escauriaza, A. Cipriano

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Flash floods, together with landslides, are a common natural threat for people living in mountainous regions and foothills. One way to deal with this constant menace is the use of Early Warning Systems, which have become a very important mitigation strategy for natural disasters. In this work, we present our proposal for a pilot Flash Flood Early Warning System for Santiago, Chile, the first stage of a more ambitious project that in a future stage shall also include early warning of landslides. To give a context for our approach, we first analyze three existing Flash Flood Early Warning Systems, focusing on their general architectures. We then present our proposed system, with main focus on the decision support system, a system that integrates empirical models and fuzzy expert systems to achieve reliable risk estimations.

Keywords: decision support systems, early warning systems, flash flood, natural hazard

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Authors: Gagandeep Singh, Navdeep Singh

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Due to limited battery of sensor nodes, so energy efficiency found to be main constraint in WSN. Therefore the main focus of the present work is to find the ways to minimize the energy consumption problem and will results; enhancement in the network stability period and life time. Many researchers have proposed different kind of the protocols to enhance the network lifetime further. This paper has evaluated the issues which have been neglected in the field of the WSNs. WSNs are composed of multiple unattended ultra-small, limited-power sensor nodes. Sensor nodes are deployed randomly in the area of interest. Sensor nodes have limited processing, wireless communication and power resource capabilities Sensor nodes send sensed data to sink or Base Station (BS). I-LEACH gives adaptive clustering mechanism which very efficiently deals with energy conservations. This paper ends up with the shortcomings of various adaptive clustering based WSNs protocols.

Keywords: WSN, I-Leach, MATLAB, sensor

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Authors: Soroush Hooshyar, Mohamadali Masoudian, Natalie Germann

Abstract:

Many soft materials such as polymer solutions can develop localized bands with different shear rates, which are known as shear bands. Using the generalized bracket approach of nonequilibrium thermodynamics, we recently developed a new two-fluid model to study shear banding for semi-dilute polymer solutions. The two-fluid approach is an appropriate means for describing diffusion processes such as Fickian diffusion and stress-induced migration. In this approach, it is assumed that the local gradients in concentration and, if accounted for, also stress generate a nontrivial velocity difference between the components. Since the differential velocity is treated as a state variable in our model, the implementation of the boundary conditions arising from the derivative diffusive terms is straightforward. Our model is a good candidate for benchmark simulations because of its simplicity. We analyzed its behavior in cylindrical Couette flow, a rectilinear channel flow, and a 4:1 planar contraction flow. The latter problem was solved using the OpenFOAM finite volume package and the impact of shear banding on the lip and salient vortices was investigated. For the other smooth geometries, we employed a standard Chebyshev pseudospectral collocation method. The results showed that the steady-state solution is unique with respect to initial conditions, deformation history, and the value of the diffusivity constant. However, smaller the value of the diffusivity constant is, the more time it takes to reach the steady state.

Keywords: nonequilibrium thermodynamics, planar contraction, polymer solutions, shear banding, two-fluid approach

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Authors: Vahid Anari, Leila Shahmohammadi

Abstract:

Diagnosing and interpreting manually from a large cohort dataset of immunohistochemically stained tissue of tumors using an optical microscope involves subjectivity and also is tedious for pathologist specialists. Moreover, digital pathology today represents more of an evolution than a revolution in pathology. In this paper, we develop and test an unsupervised algorithm that can automatically enhance the IHC image of a meningioma tumor and classify cells into positive (proliferative) and negative (normal) cells. A dataset including 150 images is used to test the scheme. In addition, a new adaptive color image enhancement method is proposed based on a vector directional filter (VDF) and statistical properties of filtering the window. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: digital pathology, cell segmentation, immunohistochemically, noise reduction

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Authors: Szymon Kugler, Krzysztof Kowalczyk, Tadeusz Spychaj

Abstract:

An addition of carbon nanotubes (CNT) can simultaneously improve many features of epoxy coatings, i.e. electrical, mechanical, functional and thermal. Unfortunately, this nanofiller negatively affects visual properties of the coatings, such as transparency and gloss. The main reason for the low visual performance of CNT-modified epoxy coatings is the lack of compatibility between CNT and popular amine curing agents, although epoxy resins based on bisphenol A are indisputable good CNT dispersants. This is a serious obstacle in utilization of the coatings in advanced applications, demanding both high transparency and electrical conductivity. The aim of performed investigations was to find amine curing agents exhibiting affinity for CNT, and ensuring good performance of epoxy coatings with them. Commercially available CNT was dispersed in epoxy resin, as well as in different aliphatic, cycloaliphatic and aromatic amines, using one of two dispergation methods: ultrasonic or mechanical. The CNT dispersions were subsequently used in the preparation of epoxy coating compositions and coatings on a transparent substrate. It was found that amine derivative of bio-based cardanol, as well as modified o-tolylbiguanide exhibit significant CNT, dispersing properties, resulting in improved transparent/electroconductive performance of epoxy coatings. In one of prepared coating systems just 0.025 wt.% (250 ppm) of CNT was enough to obtain coatings with semi conductive properties, 83% of transparency as well as perfect chemical resistance to methyl-ethyl ketone and improved thermal stability. Additionally, a theory of the influence of amine chemical structure on CNT dispersing properties was proposed.

Keywords: bio-based cardanol, carbon nanotubes, epoxy coatings, tolylbiguanide

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Authors: P. Venu, Joeju M. Issac

Abstract:

Quality Function Deployment (QFD) is a systematic technique that creates a platform where the customer responses can be positively converted to design attributes. The accuracy of a QFD process heavily depends on the data that it is handling which is captured from customers or QFD team members. Customized computer programs that perform Quality Function Deployment within a stipulated time have been used by various companies across the globe. These programs heavily rely on storage and retrieval of the data on a common database. This database must act as a perfect source with minimum missing values or error values in order perform actual prioritization. This paper introduces a missing/error data handler module which uses Genetic Algorithm and Fuzzy numbers. The prioritization of customer requirements of sesame oil is illustrated and a comparison is made between proposed data handler module-based deployment and manual deployment.

Keywords: hybrid data handler, QFD, prioritization, module-based deployment

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Authors: Ahmad Ghanem, Mohamad Yasin, Mona Abdel Rehim, Fabrice Gouanve, Eliane Espuche

Abstract:

Biodegradable polymers are of great interest, especially for biomedical and packaging applications. Current research efforts are focused on the development of biopolymers with the purpose of reducing the plastic pollution induced by the widely used in biodegradable polyolefins. The main challenge is focused on the elaboration of biopolymers having properties competitive to those of polyolefins. On the other hand, graphene oxide (GO), a graphene derivative, is characterized by the presence of several functional groups on the surface such as carboxylic, hydroxyl and epoxide. This feature enables modification of GO surface with different modifiers to obtain versatile surface properties and overcome the problem of graphene sheets aggregations during inclusion in a polymer matrix. In this context, poly (butylene succinate) (PBS) as promising biopolyester is modified through blending with different ratios of functionalized (GO) to improve its barrier properties. Modification of GO has been carried out using different hyperbranched polymeric structures in order to increase miscibility of the nanosheets in the hosting polymeric matrix. Films have been prepared from the modified PBS and their mechanical, thermal and gas barrier properties were investigated. The results reveal enhancement in the thermal and mechanical properties beside observed improvement of the barrier properties for the films prepared from the modified PBS. This improvement is related to the strong dependence on tortuosity effects of dispersion, exfoliation levels of fillers into the polymer matrix and interactions between the fillers and the polymer matrix.

Keywords: gas barrier properties, graphene oxide, food packaging, transport properties

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Authors: A. A. Behroozpoor, M. M. Mazarei

Abstract:

In this paper, a fuzzy recurrent neural network is proposed for solving the classical quadratic control problem subject to linear equality and bound constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed.

Keywords: REFERENCES [1] Xia, Y, A new neural network for solving linear and quadratic programming problems. IEEE Transactions on Neural Networks, 7(6), 1996, pp.1544–1548. [2] Xia, Y., & Wang, J, A recurrent neural network for solving nonlinear convex programs subject to linear constraints. IEEE Transactions on Neural Networks, 16(2), 2005, pp. 379–386. [3] Xia, Y., H, Leung, & J, Wang, A projection neural network and its application to constrained optimization problems. IEEE Transactions Circuits and Systems-I, 49(4), 2002, pp.447–458.B. [4] Q. Liu, Z. Guo, J. Wang, A one-layer recurrent neural network for constrained seudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks, 26, 2012, pp. 99-109.

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