Search results for: optimal reaction network

Authors: Mahmoud Karimi, Golmohammad Khoobbakht

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This study focuses on the exergy flow analysis in the transesterification of waste cooking oil with methanol to decrease the consumption of materials and energy and promote the use of renewable resources. The exergy analysis performed is based on the thermodynamic performance parameters namely exergy destruction and exergy efficiency to investigate the effects of variable parameters on renewability of transesterification. The experiment variables were methanol to WCO ratio, catalyst concentration and reaction temperature in the transesterification reaction. The optimum condition with yield of 90.2% and exergy efficiency of 95.2% was obtained at methanol to oil molar ratio of 8:1, 1 wt.% of KOH, at 55 °C. In this condition, the total waste exergy was found to be 45.4 MJ for 1 kg biodiesel production. However high yield in the optimal condition resulted high exergy efficiency in the transesterification of WCO with methanol.

Keywords: biodiesel, exergy, thermodynamic analysis, transesterification, waste cooking oil

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Authors: Hong-Fang Ma, Cong-yi He, Hai-Tao Zhang, Wei-Yong Ying, Ding-Ye Fang

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A Ni-based catalyst supported by γ-Al2O3 was prepared by impregnation method, and the catalyst was used in a low CO and CO2 concentration methanation system. The effect of temperature, pressure and space velocity on the methanation reaction was investigated in an experimental fixed-bed reactor. The methanation reaction was operated at the conditions of 190-240°C, 3000-24000ml•g-1•h-1 and 1.5-3.5MPa. The results show that temperature and space velocity play important role on the reaction. With the increase of reaction temperature the CO and CO2 conversion increase and the selectivity of CH4 increase. And with the increase of the space velocity the conversion of CO and CO2 and the selectivity of CH4 decrease sharply.

Keywords: coke oven gas, methanntion, catalyst, fixed bed, performance

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Authors: Shu-Bo Yang, Wei Wu, Yuan-Heng Liu

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This research aims to design a heat-exchanger type of methanol reformer coupled with a preheating design in gPROMS® environment. The endothermic methanol steam reforming reaction (MSR) and the exothermic preferential oxidation reaction (PROX) occur in the inner tube and the outer tube of the reformer, respectively. The effective heat transfer manner between the inner and outer tubes is investigated. It is verified that the countercurrent-flow type reformer provides the higher hydrogen yield than the cocurrent-flow type. Since the hot spot temperature appears in the outer tube, an improved scheme is proposed to suppress the hot spot temperature by splitting the excess air flowing into two sites. Finally, an optimization algorithm for maximizing the hydrogen yield is employed to determine optimal operating conditions.

Keywords: methanol reformer, methanol steam reforming, optimization, simulation

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Authors: Gyeongbeom Yi

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The purpose of this study is to introduce the analytic solution for determining the optimal capacity (lot-size) of a multiproduct, multistage production and inventory system to meet the finished product demand. Reasonable decision-making about the capacity of processes and storage units is an important subject for industry. The industrial solution for this subject is to use the classical economic lot sizing method, EOQ/EPQ (Economic Order Quantity/Economic Production Quantity) model, incorporated with practical experience. However, the unrealistic material flow assumption of the EOQ/EPQ model is not suitable for chemical plant design with highly interlinked processes and storage units. This study overcomes the limitation of the classical lot sizing method developed on the basis of the single product and single stage assumption. The superstructure of the plant considered consists of a network of serially and/or parallelly interlinked processes and storage units. The processes involve chemical reactions with multiple feedstock materials and multiple products as well as mixing, splitting or transportation of materials. The objective function for optimization is minimizing the total cost composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis method, PSW (Periodic Square Wave) model, is applied. The advantage of the PSW model comes from the fact that the model provides a set of simple analytic solutions in spite of a realistic description of the material flow between processes and storage units. The resulting simple analytic solution can greatly enhance the proper and quick investment decision for plant design and operation problem confronted in diverse economic situations.

Keywords: analytic solution, optimal design, process-storage network

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Authors: Andrey V. Osipov, Sergey A. Kukushkin, Andrey V. Luk’yanov

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A method is developed for the solid-phase synthesis of epitaxial layers when the substrate itself is involved into a topochemical reaction and the reaction product grows in the interior of substrate layer. It opens up new possibilities for the relaxation of the elastic energy due to the attraction of point defects formed during the topochemical reaction in anisotropic media. The presented method of silicon carbide (SiC) formation employs a topochemical reaction between the single-crystalline silicon (Si) substrate and gaseous carbon monoxide (CO). The corresponding theory of interaction of point dilatation centers in anisotropic crystals is developed. It is eliminated that the most advantageous location of the point defects is the direction (111) in crystals with cubic symmetry. The single-crystal SiC films with the thickness up to 200 nm have been grown on Si (111) substrates owing to the topochemical reaction with CO. Grown high-quality single-crystal SiC films do not contain misfit dislocations despite the huge lattice mismatch value of ~20%. Also the possibility of growing of thick wide-gap semiconductor films on these templates SiC/Si(111) and, accordingly, its integration into Si electronics, is demonstrated. Finally, the ab initio theory of SiC formation due to the topochemical reaction has been developed.

Keywords: epitaxy, silicon carbide, topochemical reaction, wide-bandgap semiconductors

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Authors: Kriengkrai Assawamartbunlue, Channarong Wantha

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This paper presents the effects of the mean operating pressure on the optimal operating frequency based on temperature differences across stack ends in a thermoacoustic refrigerator. In addition to the length of the resonance tube, components of the thermoacoustic refrigerator have an influence on the operating frequency due to their acoustic properties, i.e. absorptivity, reflectivity and transmissivity. The interference of waves incurs and distorts the original frequency generated by the driver so that the optimal operating frequency differs from the designs. These acoustic properties are not parameters in the designs and it is very complicated to infer their responses. A prototype thermoacoustic refrigerator is constructed and used to investigate its optimal operating frequency compared to the design at various operating pressures. Helium and air are used as working fluids during the experiments. The results indicate that the optimal operating frequency of the prototype thermoacoustic refrigerator using helium is at 6 bar and 490Hz or approximately 20% away from the design frequency. The optimal operating frequency at other mean pressures differs from the design in an unpredictable manner, however, the optimal operating frequency and pressure can be identified by testing.

Keywords: acoustic properties, Carnot’s efficiency, interference of waves, operating pressure, optimal operating frequency, stack performance, standing wave, thermoacoustic refrigerator

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Authors: Jessica Achebe, Susan Tighe

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The reduction of material consumption and greenhouse gas emission when maintain and rehabilitating road networks can achieve added benefits including improved life cycle performance of pavements, reduced climate change impacts and human health effect due to less air pollution, improved productivity due to an optimal allocation of resources and reduced road user cost. This is the essence of incorporating environmental sustainability into pavement management. The functionality of performance measurement approach has made it one of the most valuable tool to Pavement Management Systems (PMSs) to account for different criteria in the decision-making process. However measuring the environmental performance of road network is still a far-fetched practice in road network management, more so an ostensive agency-wide environmental sustainability or sustainable maintenance specifications is missing. To address this challenge, this present research focuses on the environmental sustainability performance of network-level pavement management. The ultimate goal is to develop a framework to incorporate environmental sustainability in pavement management systems for network-level maintenance programming. In order to achieve this goal, this paper present the first step, the intention is to review the previous studies that employed environmental performance measures, as well as the suitability of environmental performance indicators for the evaluation of the sustainability of network-level pavement maintenance strategies. Through an industry practice survey, this paper provides a brief forward regarding the pavement manager motivations and barriers to making more sustainable decisions, and data needed to support the network-level environmental sustainability. The trends in network-level sustainable pavement management are also presented, existing gaps are highlighted, and ideas are proposed for network-level sustainable maintenance and rehabilitation programming.

Keywords: pavement management, environment sustainability, network-level evaluation, performance measures

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Authors: Ernesto Linan, Linda Cruz, Lucero Becerra

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In this paper, a new hybridized algorithm based on Chemical Reaction Optimization and Simulated Annealing is proposed to solve the alignment sequence Problem. The Chemical Reaction Optimization is a population-based meta-heuristic algorithm based on the principles of a chemical reaction. Simulated Annealing is applied to solve a large number of combinatorial optimization problems of general-purpose. In this paper, we propose hybridization between Chemical Reaction Optimization algorithm and Simulated Annealing in order to solve the Sequence Alignment Problem. An initial population of molecules is defined at beginning of the proposed algorithm, where each molecule represents a sequence alignment problem. In order to simulate inter-molecule collisions, the process of Chemical Reaction is placed inside the Metropolis Cycle at certain values of temperature. Inside this cycle, change of molecules is done due to collisions; some molecules are accepted by applying Boltzmann probability. The results with the hybrid scheme are better than the results obtained separately.

Keywords: chemical reaction optimization, sequence alignment problem, simulated annealing algorithm, metaheuristics

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Authors: Mostafa Sefidgar, Kaamran Raahemifar, Hossein Bazmara, Madjid Soltani

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The computational methods provide condition for investigation related to the process of drug delivery, such as convection and diffusion of drug in extracellular matrices, and drug extravasation from microvascular. The information of this process clarifies the mechanisms of drug delivery from the injection site to absorption by a solid tumor. In this study, an advanced numerical method is used to solve fluid flow and solute transport equations simultaneously to show how capillary network structure induced by tumor affects drug delivery. The effect of heterogeneous capillary network induced by tumor on interstitial fluid flow and drug delivery is investigated by this multi scale method. The sprouting angiogenesis model is used for generating capillary network induced by tumor. Fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network and fluid flow in normal and tumor tissues. The Starling’s law is used for closing this system of equations and coupling the intravascular and extravascular flows. Finally, convection-diffusion-reaction equation is used to simulate drug delivery. The dynamic approach which changes the capillary network structure based on signals sent by hemodynamic and metabolic stimuli is used in this study for more realistic assumption. The study indicates that drug delivery to solid tumors depends on the tumor induced capillary network structure. The dynamic approach generates the irregular capillary network around the tumor and predicts a higher interstitial pressure in the tumor region. This elevated interstitial pressure with irregular capillary network leads to a heterogeneous distribution of drug in the tumor region similar to in vivo observations. The investigation indicates that the drug transport properties have a significant role against the physiological barrier of drug delivery to a solid tumor.

Keywords: solid tumor, physiological barriers to drug delivery, angiogenesis, microvascular network, solute transport

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Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus

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Authors: Mohammad Imani, JabraeilNasl Seraji, Abolfazl Zakerian

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Background: Reaction time is the amount of time it takes to respond to a stimulus. In fact The time that passes between the introduction of a stimulus and the reaction by the subject to that stimulus. The aim of this interventional study is evaluation of bright light effects on concentration and diffuse attention reaction time, tension, angry, fatigue and alertness among shift workers. There are several incentives that can reduce the reaction time or added. Bright light as one of the environmental factors can reduce reaction time. Material &Method: This cross-sectional descriptive study was conducted in 1391, in 88 subjects (44 Fixed morning worker and 44 shift worker ) In a 24 h time (13-16-19-22-1-4-7-10) in an ordinary light situation after a randomly selected sample size calculation, concentration and diffuse attention test (reaction time) has been done. After intervention and using of bright light (4500lux), again reaction time test was done. After analyzing by ElISA method obtained data were analyzed by statistical software SPSS 19 and using T-test and ANOVA statistical analysis. Results: Between average of reaction time tests in ordinary light exposed to fixed morning workers and bright light exposed to shift worker, with 95% CI, (P>%5) there was no significant relationship. After the intervention and the use of bright light (4500 lux),between average of concentration and diffused attention reaction time tests in ordinary light exposure on the fixed morning workers and bright light exposure shift workers with 95% CI, (P<5%) there was significant relationship. Conclusion: In sometimes of 24 h during ordinary light exposure concentration and diffused attention reaction time has changed in shift workers. After intervention, during bright light (4500lux) exposure as a light shower, focused and diffuse attention reaction time, tension ,angry and fatigue decreased.

Keywords: bright light, reaction time, tension, angry, fatigue, alertness

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Authors: Ashwini Gowda K. S, Archana M. R, Anjaneyappa V

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This paper presents pavement maintenance and management system (PMMS) to obtain optimum pavement maintenance and rehabilitation strategies and maintenance scheduling for a network using a multi-objective genetic algorithm (MOGA). Optimal pavement maintenance & rehabilitation strategy is to maximize the pavement condition index of the road section in a network with minimum maintenance and rehabilitation cost during the planning period. In this paper, NSGA-II is applied to perform maintenance optimization; this maintenance approach was expected to preserve and improve the existing condition of the highway network in a cost-effective way. The proposed PMMS is applied to a network that assessed pavement based on the pavement condition index (PCI). The minimum and maximum maintenance cost for a planning period of 20 years obtained from the non-dominated solution was found to be 5.190x10¹⁰ ₹ and 4.81x10¹⁰ ₹, respectively.

Keywords: genetic algorithm, maintenance and rehabilitation, optimization technique, pavement condition index

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Authors: Huang Xiaoling, Liu Lufeng

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In this paper, we seek to determine one reasonable local hub port and optimal routes for a containership fleet, performing pick-ups and deliveries, between the hub and spoke ports in a same region. The relationship between a hub port, and traffic in feeder lines is analyzed. A new network planning method is proposed, an integrated hub port location and route design, a capacitated vehicle routing problem with pick-ups, deliveries and time deadlines are formulated and solved using an improved genetic algorithm for positioning the hub port and establishing routes for a containership fleet. Results on the performance of the algorithm and the feasibility of the approach show that a relatively small fleet of containerships could provide efficient services within deadlines.

Keywords: route planning, hub port location, container feeder service, regional transportation network

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Authors: Kuheli Chakrabarty, Animesh Ghosh, Atanu Roy, Gourab Kanti Das

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Aldol reaction is an important class of carbon-carbon bond forming reactions. One of the popular ways to impose asymmetry in aldol reaction is the introduction of chiral auxiliary that binds the approaching reactants and create dissymmetry in the reaction environment, which finally evolves to enantiomeric excess in the aldol products. The last decade witnesses the usage of natural amino acids as chiral auxiliary to control the stereoselectivity in various carbon-carbon bond forming processes. In this context, L-proline was found to be an effective organocatalyst in asymmetric aldol additions. In last few decades the use of water as solvent or co-solvent in asymmetric organocatalytic reaction is increased sharply. Simple amino acids like L-proline does not catalyze asymmetric aldol reaction in aqueous medium not only that, In organic solvent medium high catalytic loading (~30 mol%) is required to achieve moderate to high asymmetric induction. In this context, huge efforts have been made to modify L-proline and 4-hydroxy-L-proline to prepare organocatalyst for aqueous medium asymmetric aldol reaction. Here, we report the result of our DFT calculations on asymmetric aldol reaction of benzaldehyde, p-NO2 benzaldehyde and t-butyraldehyde with a number of ketones using L-proline hydrazide as organocatalyst in wet solvent free condition. Gaussian 09 program package and Gauss View program were used for the present work. Geometry optimizations were performed using B3LYP hybrid functional and 6-31G(d,p) basis set. Transition structures were confirmed by hessian calculation and IRC calculation. As the reactions were carried out in solvent free condition, No solvent effect were studied theoretically. Present study has revealed for the first time, the direct involvement of two water molecules in the aldol transition structures. In the TS, the enamine and the aldehyde is connected through hydrogen bonding by the assistance of two intervening water molecules forming a supramolecular network. Formation of this type of supramolecular assembly is possible due to the presence of protonated -NH2 group in the L-proline hydrazide moiety, which is responsible for the favorable entropy contribution to the aldol reaction. It is also revealed from the present study that, water assisted TS is energetically more favorable than the TS without involving any water molecule. It can be concluded from this study that, insertion of polar group capable of hydrogen bond formation in the L-proline skeleton can lead to a favorable aldol reaction with significantly high enantiomeric excess in wet solvent free condition by reducing the activation barrier of this reaction.

Keywords: aldol reaction, DFT, organocatalysis, transition structure

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Authors: Nabi Ullah

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The energy crisis of the current society has attracted research attention for alternative energy sources. Methanol oxidation is the source of energy but needs efficient electrocatalysts like Pt. However, their practical ability is hindered due to cost and poisoning effects. In this regard, an efficient catalyst is required for methanol oxidation. Herein, high temperature, pressure, and diethylenetryamine (DETA) as reaction medium/structure directing agent during the solvothermal method are used for nanobelt Cu₃Se₂/Cu₁.₈Se (mostly hexagonal appearance) formation. The electrocatalyst shows optimized methanol electrooxidation reaction (MOR) response in 1 M KOH and 0.5 M methanol at a scan rate of 50 mV/s and delivers a current density of 7.12 mA/mg at a potential of 0.65 V (vs Ag/AgCl). The catalyst exhibits high electrochemical active surface area (ECSA) (0.088 mF/cm²) and low Rct with good stability for 3600 s, which favors its high MOR performance. This high response is due to its 2D hexagonal nanobelt morphology, which provides a large surface area for reaction. The space among nanobelts reduces diffusion kinetics, and the rough/irregular edge increases the reaction site to improve the methanol oxidation reaction overall.

Keywords: energy application, electrocatalysis, MOR, nanobelt

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion Detection System (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw data set for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. These optimal feature subset used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP)

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Authors: Edafe Lucky Okotie, Emmanuel Osawaru Omosigho

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This paper examines the impacts of the introduction of distributed energy generation (DEG) technology into the Nigerian power system as an alternative means of energy generation at distribution ends using Otovwodo 15 MVA, 33/11kV injection substation as a case study. The overall idea is to increase the generated energy in the system, improve the voltage profile and reduce system losses. A photovoltaic-based distributed energy generator (PV-DEG) was considered and was optimally placed in the network using Genetic Algorithm (GA) in Mat. Lab/Simulink environment. The results of simulation obtained shows that the dynamic performance of the network was optimized with DEG-grid integration.

Keywords: distributed energy generation (DEG), genetic algorithm (GA), power quality, total load demand, voltage profile

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Authors: Manasi Roy, Raju Mondal

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During last two decades the synthesis and design of MOFs or novel coordination polymers (CPs) has flourished as an emerging area of research due to their role as functional materials. Accordingly, ten new cobalt-based MOFs have been synthesized using a simple bispyrazole ligand, 4,4′-methylene-bispyrazole (H2MBP), and isophthalic acid (H2IPA) and its four 5-substituted derivatives R-H2IPA (R = COOH, OH, tBu, NH2). The major aim of this study was to validate the mutual influence of temperature and substitutions on the final structural self-assembly. Five different isophthalic acid derivatives were used to study the influence of substituents while each reaction was carried out at two different temperatures to assess the temperature effect. A clear correlation was observed between the reaction temperature and the coordination number of the cobalt atoms which consequently changes the self assembly pattern. Another fact that the periodical change in coordination number did bring about some systematic changes in the structural network via secondary building unit selectivity. With the presence of a tunable cavity inside the network, and unsaturated metal centers, MOFs show highly encouraging photocatalytic degradation of toxic dye with a potential application in waste water purification. Another fascinating aspect of this work is the construction of magnetic coordination polymers with the occurrence of a not-so-common MCE behavior of cobalt-based MOF.

Keywords: MOFs, temperature effect, MCE, dye degradation

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Authors: S. Curteanu, F. Leon, M. Gavrilescu, S. A. Floria

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Optimization algorithms inspired from human behavior were applied in this approach, associated with neural networks models. The algorithms belong to human behaviors of learning and cooperation and human competitive behavior classes. For the first class, the main strategies include: random learning, individual learning, and social learning, and the selected algorithms are: simplified human learning optimization (SHLO), social learning optimization (SLO), and teaching-learning based optimization (TLBO). For the second class, the concept of learning is associated with competitiveness, and the selected algorithms are sports-inspired algorithms (with Football Game Algorithm, FGA and Volleyball Premier League, VPL) and Imperialist Competitive Algorithm (ICA). A real process, the synthesis of polyacrylamide-based multicomponent hydrogels, where some parameters are difficult to obtain experimentally, is considered as a case study. Reaction yield and swelling degree are predicted as a function of reaction conditions (acrylamide concentration, initiator concentration, crosslinking agent concentration, temperature, reaction time, and amount of inclusion polymer, which could be starch, poly(vinyl alcohol) or gelatin). The experimental results contain 175 data. Artificial neural networks are obtained in optimal form with biologically inspired algorithm; the optimization being perform at two level: structural and parametric. Feedforward neural networks with one or two hidden layers and no more than 25 neurons in intermediate layers were obtained with values of correlation coefficient in the validation phase over 0.90. The best results were obtained with TLBO algorithm, correlation coefficient being 0.94 for an MLP(6:9:20:2) – a feedforward neural network with two hidden layers and 9 and 20, respectively, intermediate neurons. Good results obtained prove the efficiency of the optimization algorithms. More than the good results, what is important in this approach is the simulation methodology, including neural networks and optimization biologically inspired algorithms, which provide satisfactory results. In addition, the methodology developed in this approach is general and has flexibility so that it can be easily adapted to other processes in association with different types of models.

Keywords: artificial neural networks, human behaviors of learning and cooperation, human competitive behavior, optimization algorithms

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Authors: S. Mat Radzi, N. J. Abd Rahman, H. Mohd Noor, N. Ariffin

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Ferulic acid has widespread industrial potential by virtue of its antioxidant properties. However, it is partially soluble in aqueous media, limiting their usefulness in oil-based processes in food, cosmetic, pharmaceutical, and material industry. Therefore, modification of ferulic acid should be made by producing of more lipophilic derivatives. In this study, a preliminary investigation of lipase-catalyzed trans-esterification reaction of ethyl ferulate and olive oil was investigated. The reaction was catalyzed by immobilized lipase from Candida antarctica (Novozym 435), to produce ferulate ester, a sunscreen agent. A statistical approach of Response surface methodology (RSM) was used to evaluate the interactive effects of reaction temperature (40-80°C), reaction time (4-12 hours), and amount of enzyme (0.1-0.5 g). The optimum conditions derived via RSM were reaction temperature 60°C, reaction time 2.34 hours, and amount of enzyme 0.3 g. The actual experimental yield was 59.6% ferulate ester under optimum condition, which compared well to the maximum predicted value of 58.0%.

Keywords: ferulic acid, enzymatic synthesis, esters, RSM

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Authors: Naveed Ghani

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With the arrival of higher speed communication links and mature application running over the internet, the requirement for reliable, efficient and robust network designs rising day by day. Multi-Protocol Label Switching technology (MPLS) Virtual Private Networks (VPNs) have committed to provide optimal network services. They are gaining popularity in industry day by day. Enterprise customers are moving to service providers that offer MPLS VPNs. The main reason for this shifting is the capability of MPLS VPN to provide built in security features and any-to-any connectivity. MPLS VPNs improved the network performance due to fast label switching as compare to traditional IP Forwarding but traffic classification and policing was still required on per hop basis to enhance the performance of real time traffic which is delay sensitive (particularly voice and video). QoS (Quality of service) is the most important factor to prioritize enterprise networks’ real time traffic such as voice and video. This thesis is focused on the study of QoS parameters (e.g. delay, jitter and MOS (Mean Opinion Score)) for the real time traffic over MPLS VPNs. DiffServ (Differentiated Services) QoS model will be used over MPLS VPN network to get end-to-end service quality.

Keywords: network, MPLS, VPN, DiffServ, MPLS VPN, DiffServ QoS, QoS Model, GNS2

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Authors: R. Andreola, O. A. A. Santos, L. M. M. Jorge

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An industrial system for the production of white liquor of a paper industry, Klabin Paraná Papé is, formed by ten reactors was modeled, simulated, and analyzed. The developed model considered possible water losses by evaporation and reaction, in addition to variations in volumetric flow of lime mud across the reactors due to composition variations. The model predictions agreed well with the process measurements at the plant and the results showed that the slaking reaction is nearly complete at the third causticizing reactor, while causticizing ends by the seventh reactor. Water loss due to slaking reaction and evaporation occurs more pronouncedly in the slaking reaction than in the final causticizing reactors; nevertheless, the lime mud flow remains nearly constant across the reactors.

Keywords: causticizing, lime, prediction, process

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Authors: Syed Umair Aziz, Muhammad Faheem, Sameer Hussain, Faraz Idris

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Content centric network is the network based on the mechanism of sending and receiving the data based on the interest and data request to the specified node (which has cached data). In this network, the security is bind with the content not with the host hence making it host independent and secure. In this network security is applied by taking content’s MAC (message authentication code) and encrypting it with the public key of the receiver. On the receiver end, the message is first verified and after verification message is saved and decrypted using the receiver's private key.

Keywords: content centric network, client-server, host security threats, message authentication code, named data network, network caching, peer-to-peer

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Authors: Eiji Okano, Kazuyuki Inagaki

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We revisit Uribe's `Fiscal Theory of Sovereign Risk' advocating that there is a trade-off between stabilizing inflation and suppressing default. We develop a class of dynamic stochastic general equilibrium (DSGE) model with nominal rigidities and compare two de facto inflation stabilization policies, optimal monetary policy and optimal monetary and fiscal policy with the minimizing interest rate spread policy which completely suppress the default. Under the optimal monetary and fiscal policy, not only the nominal interest rate but also the tax rate work to minimize welfare costs through stabilizing inflation. Under the optimal monetary both inflation and output gap are completely stabilized although those are fluctuating under the optimal monetary policy. In addition, volatility in the default rate under the optimal monetary policy is considerably lower than one under the optimal monetary policy. Thus, there is not the SI-SD trade-off. In addition, while the minimizing interest rate spread policy makes inflation rate severely volatile, the optimal monetary and fiscal policy stabilize both the inflation and the default. A trade-off between stabilizing inflation and suppressing default is not so severe what pointed out by Uribe.

Keywords: sovereign risk, optimal monetary policy, fiscal theory of the price level, DSGE

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Authors: Kimaya Subhash Gaikwad, S. B. Waykar

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The mobile ad-hoc network (MANET) is collection of various types of nodes. In MANET various protocols are used for communication. In OLSR protocol, a node is selected as multipoint relay (MPR) node which broadcast the messages. As the MANET is open kind of network any malicious node can easily enter into the network and affect the performance of the network. The performance of network mainly depends on the components which are taking part into the communication. If the proper nodes are not selected for the communication then the probability of network being attacked is more. Therefore, it is important to select the more reliable and secure components in the network. MANET does not have any filtering so that only selected nodes can be used for communication. The openness of the MANET makes it easier to attack the communication. The most of the attack are on the Quality of service (QoS) of the network. This paper gives the overview of the various attacks that are possible on OLSR protocol and some solutions. The papers focus mainly on the OLSR protocol.

Keywords: communication, MANET, OLSR, QoS

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Authors: Hassan M. H. Mustafa

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This piece of research addresses an interesting comparative analytical study. Which considers two concepts of diverse algorithmic computational intelligence approaches related tightly with Neural and Non-Neural Systems. The first algorithmic intelligent approach concerned with observed obtained practical results after three neural animal systems’ activities. Namely, they are Pavlov’s, and Thorndike’s experimental work. Besides a mouse’s trial during its movement inside figure of eight (8) maze, to reach an optimal solution for reconstruction problem. Conversely, second algorithmic intelligent approach originated from observed activities’ results for Non-Neural Ant Colony System (ACS). These results obtained after reaching an optimal solution while solving Traveling Sales-man Problem (TSP). Interestingly, the effect of increasing number of agents (either neurons or ants) on learning performance shown to be similar for both introduced systems. Finally, performance of both intelligent learning paradigms shown to be in agreement with learning convergence process searching for least mean square error LMS algorithm. While its application for training some Artificial Neural Network (ANN) models. Accordingly, adopted ANN modeling is a relevant and realistic tool to investigate observations and analyze performance for both selected computational intelligence (biological behavioral learning) systems.

Keywords: artificial neural network modeling, animal learning, ant colony system, traveling salesman problem, computational biology

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Authors: X. S. Wu, H. Jia, P. H. Qian, Z. Zhang, H. L. Cai, F. M. Zhang

Abstract:

A bipolar resistance switching behaviour is detected for a Ti/TiO2-x/Au memristor device, which is fabricated by a masked designed magnetic sputtering. The current dependence of voltage indicates the curve changes slowly and continuously. When voltage pulses are applied to the device, the set and reset processes maintains linearity, which is used to simulate the synapses. We argue that the conduction mechanism of the device is from the oxygen vacancy channel model, and the resistance of the device change slowly due to the reaction between the titanium electrode and the intermediate layer and the existence of a large number of oxygen vacancies in the intermediate layer. Then, Hopfield neural network is constructed to simulate the behaviour of neural network in image processing, and the accuracy rate is more than 98%. This shows that titanium dioxide memristor has a broad application prospect in high performance neural network simulation.

Keywords: memristor fabrication, neuromorphic computing, bionic synaptic application, TiO₂-based

Procedia PDF Downloads 44

Authors: Maath M. Musleh

Abstract:

This research aims to study recent trends in the Palestinian feminist movement through the case study of Tal3at. The study uses social network analysis as its primary method to analyze Twitter data. It attempts to interpret results through the lens of network theories and Parson’s AGIL paradigm. The study reveals major structural weaknesses in the Tal3at network. Our findings suggest that the movement will decline soon as sentiments of alienation amongst Palestinian women increases. These findings were validated by a couple of central actors in the network. This study contributes an SNA approach to the understanding of the understudied Palestinian feminism.

Keywords: feminism, Palestine, social network analysis, Tal3at

Procedia PDF Downloads 218

Authors: Anjali N. Shete, G. D. Mahajan, Nanda Somwanshi

Abstract:

Context: Smartphones are the new generation of mobile phones; they have emerged over the last few years. Technology has developed so much that it has become part of our life and mobile phones are one of them. These smartphones are equipped with the capabilities to display photos, play games, watch videos and navigation, etc. The advances have a huge impact on many walks of life. The adoption of new technology has been challenging for the elderly. But, the elder population is also moving towards digitally connected lives. As age advances, there is a decline in the motor and cognitive functions of the brain, and hence the reaction time is affected. The study was undertaken to assess the usefulness of smartphones in improving cognitive functions. Aims and Objectives: The aim of the study was to observe the effects of smartphone addiction on reaction time in elderly population Material and Methods: This is an experimental study. 100 elderly subjects were enrolled in this study randomly from urban areas. They all were using smartphones for several hours a day. They were divided into two groups according to the scores of the mobile phone addiction scale (MPAS). Simple reaction time was estimated by the Ruler drop method. The reaction time was then calculated for each subject in both groups. The data were analyzed using mean, standard deviation, and Pearson correlation test. Results: The mean reaction time in Group A is 0.27+ 0.040 and in Group B is 0.20 + 0.032. The values show a statistically significant change in reaction time. Conclusion: Group A with a high MPAS score has a low reaction time compared to Group B with a low MPAS score. Hence, it can be concluded that the use of smartphones in the elderly is useful, delaying the neurological decline, and smarten the brain.

Keywords: smartphones, MPAS, reaction time, elderly population

Procedia PDF Downloads 147

Authors: C. B. Masera, M. Imprialou, L. Budd, C. Morton

Abstract:

Even though signalised intersections are necessary for urban road traffic management, they can act as bottlenecks and disrupt traffic operations. Interrupted traffic flow causes congestion, delays, stop-and-go conditions (i.e. excessive acceleration/deceleration) and longer journey times. Vehicle and infrastructure connectivity offers the potential to provide improved new services with additional functions of assisting drivers. This paper focuses on one of the applications of vehicle-to-infrastructure communication namely Green Light Optimal Speed Advisory (GLOSA). To assess the effectiveness of GLOSA in the urban road network, an integrated microscopic traffic simulation framework is built into VISSIM software. Vehicle movements and vehicle-infrastructure communications are simulated through the interface of External Driver Model. A control algorithm is developed for recommending an optimal speed that is continuously updated in every time step for all vehicles approaching a signal-controlled point. This algorithm allows vehicles to pass a traffic signal without stopping or to minimise stopping times at a red phase. This study is performed with all connected vehicles at 100% penetration rate. Conventional vehicles are also simulated in the same network as a reference. A straight road segment composed of two opposite directions with two traffic lights per lane is studied. The simulation is implemented under 150 vehicles per hour and 200 per hour traffic volume conditions to identify how different traffic densities influence the benefits of GLOSA. The results indicate that traffic flow is improved by the application of GLOSA. According to this study, vehicles passed through the traffic lights more smoothly, and waiting times were reduced by up to 28 seconds. Average delays decreased for the entire network by 86.46% and 83.84% under traffic densities of 150 vehicles per hour per lane and 200 vehicles per hour per lane, respectively.

Keywords: connected vehicles, GLOSA, intelligent transport systems, vehicle-to-infrastructure communication

Procedia PDF Downloads 131