Search results for: Modified Kent Eisenberg model

Authors: Jolanta Tamošaitienė

Abstract:

The article focuses on a developed comprehensive model to be used in an agile environment for the risk assessment and selection based on multi-attribute methods. The model is based on a multi-attribute evaluation of risk in construction, and the determination of their optimality criterion values are calculated using complex Multiple Criteria Decision-Making methods. The model may be further applied to risk assessment in an agile construction environment. The attributes of risk in a construction project are selected by applying the risk assessment condition to the construction sector, and the construction process efficiency in the construction industry accounts for the agile environment. The paper presents the comprehensive risk assessment model in an agile construction environment. It provides a background and a description of the proposed model and the developed analysis of the comprehensive risk assessment model in an agile construction environment with the criteria.

Keywords: Assessment, environment, agile, model, risk.

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Authors: Akan C. Offong, E. J. Anthony, Vasilije Manovic

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A modified steady-state numerical model is developed for the electrochemical reduction of CO₂ to formic acid. The numerical model achieves a CD (current density) (~60 mA/cm²), FE-faradaic efficiency (~98%) and conversion (~80%) for CO₂ electro-reduction to formic acid in a microfluidic cell. The model integrates charge and species transport, mass conservation, and momentum with electrochemistry. Specifically, the influences of Bi-Sn based nanoparticle catalyst (on the cathode surface) at different mole fractions and 1-ethyl-3-methyl imidazolium tetra-fluoroborate ([EMIM][BF₄]) electrolyte, on CD, FE and CO₂ conversion to formic acid is studied. The reaction is carried out at a constant concentration of electrolyte (85% v/v., [EMIM][BF₄]). Based on the mass transfer characteristics analysis (concentration contours), mole ratio 0.5:0.5 Bi-Sn catalyst displays the highest CO₂ mole consumption in the cathode gas channel. After validating with experimental data (polarisation curves) from literature, extensive simulations reveal performance measure: CD, FE and CO₂ conversion. Increasing the negative cathode potential increases the current densities for both formic acid and H₂ formations. However, H₂ formations are minimal as a result of insufficient hydrogen ions in the ionic liquid electrolyte. Moreover, the limited hydrogen ions have a negative effect on formic acid CD. As CO₂ flow rate increases, CD, FE and CO₂ conversion increases.

Keywords: Carbon dioxide, electro-chemical reduction, microfluidics, ionic liquids, modelling.

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Authors: Tamara Nestorović, Jean Lefèvre, Stefan Ringwelski, Ulrich Gabbert

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Two approaches for model development of a smart acoustic box are suggested in this paper: the finite element (FE) approach and the subspace identification. Both approaches result in a state-space model, which can be used for obtaining the frequency responses and for the controller design. In order to validate the developed FE model and to perform the subspace identification, an experimental set-up with the acoustic box and dSPACE system was used. Experimentally obtained frequency responses show good agreement with the frequency responses obtained from the FE model and from the identified model.

Keywords: Acoustic box, experimental verification, finite element model, subspace identification.

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Authors: Wararat Rungworawut, Twittie Senivongse

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Business process model describes process flow of a business and can be seen as the requirement for developing a software application. This paper discusses a BPM2CD guideline which complements the Model Driven Architecture concept by suggesting how to create a platform-independent software model in the form of a UML class diagram from a business process model. An important step is the identification of UML classes from the business process model. A technique for object-oriented analysis called domain analysis is borrowed and key concepts in the business process model will be discovered and proposed as candidate classes for the class diagram. The paper enhances this step by using ontology search to help identify important classes for the business domain. As ontology is a source of knowledge for a particular domain which itself can link to ontologies of related domains, the search can give a refined set of candidate classes for the resulting class diagram.

Keywords: Business Process Model, Model DrivenArchitecture, Ontology, UML Class Diagram.

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Authors: Yongsuk Jang Kim, Sun-Tae Chung, Boogyun Kim, Seongwon Cho

Abstract:

Realistic 3D face model is more precise in representing pose, illumination, and expression of face than 2D face model so that it can be utilized usefully in various applications such as face recognition, games, avatars, animations, and etc. In this paper, we propose a 3D face modeling method based on 3D dense morphable shape model. The proposed 3D modeling method first constructs a 3D dense morphable shape model from 3D face scan data obtained using a 3D scanner. Next, the proposed method extracts and matches facial landmarks from 2D image sequence containing a face to be modeled, and then reconstructs 3D vertices coordinates of the landmarks using a factorization-based SfM technique. Then, the proposed method obtains a 3D dense shape model of the face to be modeled by fitting the constructed 3D dense morphable shape model into the reconstructed 3D vertices. Also, the proposed method makes a cylindrical texture map using 2D face image sequence. Finally, the proposed method generates a 3D face model by rendering the 3D dense face shape model using the cylindrical texture map. Through building processes of 3D face model by the proposed method, it is shown that the proposed method is relatively easy, fast and precise.

Keywords: 3D Face Modeling, 3D Morphable Shape Model, 3DReconstruction, 3D Correspondence.

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Authors: D. Mowla, N. Rasti, P. Keshavarz

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Reduction of fossil fuels sources, increasing of pollution gases emission, and global warming effects increase the demand of renewable fuels. One of the main candidates of alternative fuels is biodiesel. Biodiesel limits greenhouse gas effects due to the closed CO₂ cycle. Biodiesel has more biodegradability, lower combustion emissions such as CO, SO_x, HC, PM and lower toxicity than petro diesel. However, biodiesel has high production cost due to high price of plant oils as raw material. So, the utilization of waste cooking oils (WCOs) as feedstock, due to their low price and disposal problems reduce biodiesel production cost. In this study, production of biodiesel by transesterification of methanol and WCO using modified sodic potassic (SP) clinoptilolite zeolite and sodic potassic calcic (SPC) clinoptilolite zeolite as heterogeneous catalysts have been investigated. These natural clinoptilolite zeolites were modified by KOH solution to increase the site activity. The optimum biodiesel yields for SP clinoptilolite and SPC clinoptilolite were 95.8% and 94.8%, respectively. Produced biodiesel were analyzed and compared with petro diesel and ASTM limits. The properties of produced biodiesel confirm well with ASTM limits. The density, kinematic viscosity, cetane index, flash point, cloud point, and pour point of produced biodiesel were all higher than petro diesel but its acid value was lower than petro diesel. Finally, the reusability and regeneration of catalysts were investigated. The results indicated that the spent zeolites cannot be reused directly for the transesterification, but they can be regenerated easily and can obtain high activity.

Keywords: Biodiesel, renewable fuel, transesterification, waste cooking oil.

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Authors: Ahmad F. Subahi, Anthony J. H. Simons

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This Paper presents an on-going research in the area of Model-Driven Engineering (MDE). The premise is that UML is too unwieldy to serve as the basis for model-driven engineering. We need a smaller, simpler notation with a cleaner semantics. We propose some ideas for a simpler notation with a clean semantics. The result is known as μML, or the Micro-Modelling Language.

Keywords: Model-driven engineering, model transformations, domain-specific languages, end-user development.

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Authors: Yu-Syuan Chang, Li-Chun Huang

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Genetically modified (GM) technology in food production continued to generate controversies. Consumers were concerned with the GM foods about the healthy and environmental risks. While consumers- acceptance was a critical factor affecting how widely this technology be used. According to the research review, consumers- lack of information was one of the reasons to explain consumers- low acceptance toward GM foods. The objective for this study wanted to find out would informative product package affect consumers- behavior toward GM foods. An experiment was designed to investigate consumer behavior toward different product package information. The results indicated that the product package information influenced consumer product trust toward GM foods. Compared with the traceability production system information, the information about the GM rice was approved by authorized organizations could increase consumers product trust in GM foods. Consumers in Taiwan saw the information provided by authorized organizations more credible than other information.

Keywords: product package information, genetically modifiedfood, consumer product trust, risk perception, benefit perception.

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Authors: Catherine Maware, Olufemi Adetunji

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The paper is aimed at developing a model to measure the impact of Lean manufacturing deployment on organizational performance. The model will help industry practitioners to assess the impact of implementing Lean constructs on organizational performance. It will also harmonize the measurement models of Lean performance with the house of Lean that seems to have become the industry standard. The sheer number of measurement models for impact assessment of Lean implementation makes it difficult for new adopters to select an appropriate assessment model or deployment methodology. A literature review is conducted to classify the Lean performance model. Pareto analysis is used to select the Lean constructs for the development of the model. The model is further formalized through the use of Structural Equation Modeling (SEM) in defining the underlying latent structure of a Lean system. An impact assessment measurement model developed can be used to measure Lean performance and can be adopted by different industries.

Keywords: Impact measurement model, lean bundles, lean manufacturing, organizational performance.

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Authors: Y. Boutiche, N. Ramou, M. Ben Gharsallah

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This paper is devoted to present and discuss a model that allows a local segmentation by using statistical information of a given image. It is based on Chan-Vese model, curve evolution, partial differential equations and binary level sets method. The proposed model uses the piecewise constant approximation of Chan-Vese model to compute Signed Pressure Force (SPF) function, this one attracts the curve to the true object(s)-s boundaries. The implemented model is used to extract weld defects from weld radiographic images in the aim to calculate the perimeter and surfaces of those weld defects; encouraged resultants are obtained on synthetic and real radiographic images.

Keywords: Active contour, Chan-Vese Model, local segmentation, weld radiographic images.

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Authors: Pham Van Nha, Le Cam Binh

Abstract:

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: Analysis of optimization, artificial intelligence-based optimization, optimization for learning and data analysis, global optimization.

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Authors: Guowei Hou, Lixin Yu, Wei Zhuang, Hui Qin, Xue Yang

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Formal verification is proposed to ensure the correctness of the design and make functional verification more efficient. As cache plays a vital role in the design of System on Chip (SoC), and cache with Memory Management Unit (MMU) and cache memory unit makes the state space too large for simulation to verify, then a formal verification is presented for such system design. In the paper, a formal model checking verification flow is suggested and a new cache memory model which is called “exhaustive search model” is proposed. Instead of using large size ram to denote the whole cache memory, exhaustive search model employs just two cache blocks. For cache system contains data cache (Dcache) and instruction cache (Icache), Dcache memory model and Icache memory model are established separately using the same mechanism. At last, the novel model is employed to the verification of a cache which is module of a custom-built SoC system that has been applied in practical, and the result shows that the cache system is verified correctly using the exhaustive search model, and it makes the verification much more manageable and flexible.

Keywords: Cache system, formal verification, novel model, System on Chip (SoC).

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Authors: Pichet Sriyanyong

Abstract:

This paper presents the application of an enhanced Particle Swarm Optimization (EPSO) combined with Gaussian Mutation (GM) for solving the Dynamic Economic Dispatch (DED) problem considering the operating constraints of generators. The EPSO consists of the standard PSO and a modified heuristic search approaches. Namely, the ability of the traditional PSO is enhanced by applying the modified heuristic search approach to prevent the solutions from violating the constraints. In addition, Gaussian Mutation is aimed at increasing the diversity of global search, whilst it also prevents being trapped in suboptimal points during search. To illustrate its efficiency and effectiveness, the developed EPSO-GM approach is tested on the 3-unit and 10-unit 24-hour systems considering valve-point effect. From the experimental results, it can be concluded that the proposed EPSO-GM provides, the accurate solution, the efficiency, and the feature of robust computation compared with other algorithms under consideration.

Keywords: Particle Swarm Optimization (PSO), GaussianMutation (GM), Dynamic Economic Dispatch (DED).

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Authors: Widad Jakjoud, Mohamed Bahaj, Jamal Bakkas

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Through this paper we present a method for automatic generation of ontological model from any data source using Model Driven Architecture (MDA), this generation is dedicated to the cooperation of the knowledge engineering and software engineering. Indeed, reverse engineering of a data source generates a software model (schema of data) that will undergo transformations to generate the ontological model. This method uses the meta-models to validate software and ontological models.

Keywords: Meta model, model, ontology, data source.

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Authors: Y. N. Phang, E. F. Loh

Abstract:

Zero inflated strict arcsine model is a newly developed model which is found to be appropriate in modeling overdispersed count data. In this study, we extend zero inflated strict arcsine model to zero inflated strict arcsine regression model by taking into consideration the extra variability caused by extra zeros and covariates in count data. Maximum likelihood estimation method is used in estimating the parameters for this zero inflated strict arcsine regression model.

Keywords: Overdispersed count data, maximum likelihood estimation, simulated annealing.

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Authors: Laima Silina, Ilze Gramatina, Lija Dukalska, Liga Skudra, Tatjana Rakcejeva, Dace Klava, Anita Blija

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The objective of the present study was to determine quality parameters changes of red wine marinade marinated venison during storage. Beef as a control was analysed. Protein, fat, moisture and pH content dynamics as well microbiological quality was analyzed. The meat pieces were marinated in red wine marinade at 4±2ºC temperature for 48±1h. Marinated meat was placed in polypropylene trays, hermetically sealed with high barrier polymer film Multibarrier 60 under modified atmosphere (CO₂ 40%+N₂ 60%) without and with oxygen absorber sachets, as a control packaging in air ambiance packed marinated venison and beef was used. Meat samples were analyzed after 0, 4, 7, 11 and 14 days of storage. During the storage of meat, protein and moisture content significantly (p<0.05) decreased, pH and colony forming units significantly (p<0.05) increased, fat content does not change in all treatments irrespective of the packaging method.

Keywords: Marinating, modified atmosphere, quality, venison.

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Authors: P. Abachi, T. W. Coyle, P. S. Musavi Gharavi

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By applying coating onto a structural component, the corrosion and/or wear resistance requirements of the surface can be fulfilled. Since the layer adhesion of the coating influences the mechanical integrity of the coat/substrate interface during the service time, it should be examined accurately. At the present work, the tensile bonding strength of the 316 stainless steel plasma sprayed coating on aluminum substrate was determined by using tensile adhesion test, TAT, specimen. The interfacial fracture toughness was specified using four-point bend specimen containing a saw notch and modified chevron-notched short-bar (SB) specimen. The coating microstructure and fractured specimen surface were examined by using scanning electron- and optical-microscopy. The investigation of coated surface after tensile adhesion test indicates that the failure mechanism is mostly cohesive and rarely adhesive type. The calculated value of critical strain energy release rate proposes relatively good interface status. It seems that four-point bending test offers a potentially more sensitive means for evaluation of mechanical integrity of coating/substrate interfaces than is possible with the tensile test. The fracture toughness value reported for the modified chevron-notched short-bar specimen testing cannot be taken as absolute value because its calculation is based on the minimum stress intensity coefficient value which has been suggested for the fracture toughness determination of homogeneous parts in the ASTM E1304-97 standard. 

Keywords: Bonding strength, four-point bend test, interfacial fracture toughness, modified chevron-notched short-bar specimen, plasma sprayed coating.

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Authors: Hidehiko Okada

Abstract:

The author previously proposed an extension of differential evolution. The proposed method extends the processes of DE to handle interval numbers as genotype values so that DE can be applied to interval-valued optimization problems. The interval DE can employ either of two interval models, the lower and upper model or the center and width model, for specifying genotype values. Ability of the interval DE in searching for solutions may depend on the model. In this paper, the author compares the two models to investigate which model contributes better for the interval DE to find better solutions. Application of the interval DE is evolutionary training of interval-valued neural networks. A result of preliminary study indicates that the CW model is better than the LU model: the interval DE with the CW model could evolve better neural networks. 

Keywords: Evolutionary algorithms, differential evolution, neural network, neuroevolution, interval arithmetic.

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Authors: B.Rajendra Prasath, P.Tamilporai, Mohd.F.Shabir

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An effort has been taken to simulate the combustion and performance characteristics of biodiesel fuel in direct injection (D.I) low heat rejection (LHR) diesel engine. Comprehensive analyses on combustion characteristics such as cylinder pressure, peak cylinder pressure, heat release and performance characteristics such as specific fuel consumption and brake thermal efficiency are carried out. Compression ignition (C.I) engine cycle simulation was developed and modified in to LHR engine for both diesel and biodiesel fuel. On the basis of first law of thermodynamics the properties at each degree crank angle was calculated. Preparation and reaction rate model was used to calculate the instantaneous heat release rate. A gas-wall heat transfer calculations are based on the ANNAND-s combined heat transfer model with instantaneous wall temperature to analyze the effect of coating on heat transfer. The simulated results are validated by conducting the experiments on the test engine under identical operating condition on a turbocharged D.I diesel engine. In this analysis 20% of biodiesel (derived from Jatropha oil) blended with diesel and used in both conventional and LHR engine. The simulated combustion and performance characteristics results are found satisfactory with the experimental value.

Keywords: Biodiesel, Direct injection, Low heat rejection, Turbocharged engine

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Authors: Benalia Kouini, Aicha Serier

Abstract:

This work aims to investigate the structure–property relationship in ternary nanocomposites consisting of polypropylene as the matrix, polyamide 66 as the minor phase and treated nanoclay DELLITE 67G as the reinforcement. All PP/PA66/Nanoclay systems with polypropylene grafted maleic anhydride PP-g-MAH as a compatibilizer were prepared via melt compounding and characterized in terms of nanoclay content. Morphological structure was investigated by scanning electron microscopy. The rheological behavior of the nanocomposites was determined by various methods, viz melt flow index (MFI) and parallel plate rheological measurements. The PP/PP-g-MAH/PA66 nanocomposites showed a homogeneous morphology supporting the compatibility improvement between PP, PA66, and nanoclay. SEM results revealed the formation of nanocomposites as the nanoclay was intercalated and exfoliated. In the ternary nanocomposites, the rheological behavior showed that, the complex viscosity is increased with increasing the nanoclay. The results showed that the use of nanoclay affects the variations of storage modulus (G′), loss modulus (G″) and the melt elasticity.

Keywords: Nanocomposites, polypropylene, polyamide66, modified nanoclay, rheology.

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Authors: Jiuyang Lin, Wenyuan Ye, Arcadio Sotto, Bart Van der Bruggen

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Application of nanoparticles as additives in membrane synthesis for improving the resistance of membranes against fouling has triggered recent interest in new membrane types. However, most nanoparticle-enhanced membranes suffer from the tradeoff between permeability and selectivity. In this study, nano-WS2 was explored as the additive in membrane synthesis by non-solvent induced phase separation. Blended PES-WS2 flat-sheet membranes with the incorporation of ultra-low concentrations of nanoparticles (from 0.025 to 0.25%, WS2/PES ratio) were manufactured and investigated in terms of permeability, fouling resistance and solute rejection. Remarkably, a significant enhancement in the permeability was observed as a result of the incorporation of ultra-low fractions of nano-WS2 to the membrane structure. Optimal permeability values were obtained for modified membranes with 0.10% nanoparticle/polymer concentration ratios. Furthermore, fouling resistance and solute rejection were significantly improved by the incorporation of nanoparticles into the membrane matrix. Specifically, fouling resistance of modified membrane can increase by around 50%.

Keywords: Nano-WS2, Nanoparticle enhanced hybrid membrane, Ultralow concentration, Antifouling.

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Authors: M.C.S. Ribeiro, J.P. Meixedo, A. Fiúza, M.L. Dinis, Ana C. Meira Castro, F.J.G. Silva, C. Costa, F. Ferreira, M.R. Alvim

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In this study the effect of incorporation of recycled glass-fibre reinforced polymer (GFRP) waste materials, obtained by means of milling processes, on mechanical behaviour of polyester polymer mortars was assessed. For this purpose, different contents of recycled GFRP waste powder and fibres, with distinct size gradings, were incorporated into polyester based mortars as sand aggregates and filler replacements. Flexural and compressive loading capacities were evaluated and found better than unmodified polymer mortars. GFRP modified polyester based mortars also show a less brittle behaviour, with retention of some loading capacity after peak load. Obtained results highlight the high potential of recycled GFRP waste materials as efficient and sustainable reinforcement and admixture for polymer concrete and mortars composites, constituting an emergent waste management solution.

Keywords: GFRP waste, Mechanical behaviour, Polymer mortars, Recyclability.

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Authors: Venny, S. Gan, H. K. Ng

Abstract:

The performance of modified Fenton (MF) treatment to promote PAH oxidation in artificially contaminated soil was investigated in packed soil column with a hydrogen peroxide (H2O2) delivery system simulating in situ injection. Soil samples were spiked with phenanthrene (low molecular weight PAH) and fluoranthene (high molecular weight PAH) to an initial concentration of 500 mg/kg dried soil each. The effectiveness of process parameters H2O2/soil, iron/soil, chelating agent/soil weight ratios and reaction time were studied using a 24 three level factorial design experiments. Statistically significant quadratic models were developed using Response Surface Methodology (RSM) for degrading PAHs from the soil samples. Optimum operating condition was achieved at mild range of H2O2/soil, iron/soil and chelating agent/soil weight ratios, indicating cost efficient method for treating highly contaminated lands.

Keywords: Fenton, polycyclic aromatic hydrocarbon, chelate, response surface methodology

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Authors: Defu Zhang, Qingshan Jiang, Xin Li

Abstract:

This paper deals with the application of a well-known neural network technique, multilayer back-propagation (BP) neural network, in financial data mining. A modified neural network forecasting model is presented, and an intelligent mining system is developed. The system can forecast the buying and selling signs according to the prediction of future trends to stock market, and provide decision-making for stock investors. The simulation result of seven years to Shanghai Composite Index shows that the return achieved by this mining system is about three times as large as that achieved by the buy and hold strategy, so it is advantageous to apply neural networks to forecast financial time series, the different investors could benefit from it.

Keywords: Data mining, neural network, stock forecasting.

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Authors: V. Pérez-Herranz, C. González-Buch, E. M. Ortega, S. Mestre

Abstract:

In this work new macroporous Ni electrodes modified with Au nanoparticles for hydrogen production have been developed. The supporting macroporous Ni electrodes have been obtained by means of the electrodeposition at high current densities. Then, the Au nanoparticles were synthesized and added to the electrode surface. The electrocatalytic behaviour of the developed electrocatalysts was studied by means of pseudo-steady-state polarization curves, electrochemical impedance spectroscopy (EIS) and hydrogen discharge curves. The size of the Au synthetized nanoparticles shows a monomodal distribution, with a very sharp band between 10 and 50 nm. The characteristic parameters d10, d50 and d90 were 14, 20 and 31 nm respectively. From Tafel polarization data has been concluded that the Au nanoparticles improve the catalytic activity of the developed electrodes towards the HER respect to the macroporous Ni electrodes. EIS permits to obtain the electrochemically active area by means of the roughness factor value. All the developed electrodes show roughness factor values in the same order of magnitude. From the activation energy results it can be concluded that the Au nanoparticles improve the intrinsic catalytic activity of the macroporous Ni electrodes.

Keywords: Au nanoparticles, hydrogen evolution reaction, porous Ni electrodes.

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Authors: Entisar A. Elgmati

Abstract:

Martingale model diagnostic for assessing the fit of logistic regression model to recurrent events data are studied. One way of assessing the fit is by plotting the empirical standard deviation of the standardized martingale residual processes. Here we used another diagnostic plot based on martingale residual covariance. We investigated the plot performance under several types of model misspecification. Clearly the method has correctly picked up the wrong model. Also we present a test statistic that supplement the inspection of the two diagnostic. The test statistic power agrees with what we have seen in the plots of the estimated martingale covariance.

Keywords: Covariance, logistic model, misspecification, recurrent events.

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Authors: Naiqin Feng, Yuhui Qiu, Yingshan Zhang, Fang Wang

Abstract:

A logic model for analyzing complex systems- stability is very useful to many areas of sciences. In the real world, we are enlightened from some natural phenomena such as “biosphere", “food chain", “ecological balance" etc. By research and practice, and taking advantage of the orthogonality and symmetry defined by the theory of multilateral matrices, we put forward a logic analysis model of stability of complex systems with three relations, and prove it by means of mathematics. This logic model is usually successful in analyzing stability of a complex system. The structure of the logic model is not only clear and simple, but also can be easily used to research and solve many stability problems of complex systems. As an application, some examples are given.

Keywords: Complex system, logic model, relation, stability.

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Authors: Daniela Elena Marinescu, Ioana Manafi, Dumitru Marin

Abstract:

We consider a Principal-Agent model with the Principal being a seller who does not know perfectly how much the buyer (the Agent) is willing to pay for the good. The buyer-s preferences are hence his private information. The model corresponds to the nonlinear pricing problem of Maskin and Riley. We assume there are three types of Agents. The model is solved using “informational rents" as variables. In the last section we present the main characteristics of the optimal contracts in asymmetric information and some possible extensions of the model.

Keywords: Adverse selection, asymmetric information, informational rent, nonlinear pricing, optimal contract

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Authors: A. A. Penin, A. S. Sidorenko

Abstract:

A convenient and physically sound mathematical model of the external or I - V characteristic of solar cells generators is presented in this paper. This model is compared with the traditional model of p-n junction. The direct analytical calculation of load regime leads to a quadratic equation, which is importantly to simplify the calculations in the real time.

Keywords: A solar cell generator, I−V characteristic, activetwo-pole.

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Authors: Kartika S. Hamdan, Zainiharyati M. Zain, Mohamed I. A. Halim, Jafri M. Abdullah, Robert D. O'Neill

Abstract:

This work attempts to improve the permselectivity of poly-ortho-phenylenediamine (PPD) coating for glutamate biosensor applications on Pt microelectrode, using constant potential amperometry and cyclic voltammetry. Percentage permeability of the modified PPD microelectrode was carried out towards hydrogen peroxide (H2O2) and ascorbic acid (AA) whereas permselectivity represents the percentage interference by AA in H2O2 detection. The 50-μm diameter Pt disk microelectrode showed a good permeability value toward H2O2 (95%) and selectivity against AA (0.01%) compared to other sizes of electrode studied here. The electrode was further modified with glutamate oxidase (GluOx) that was immobilized and cross linked with glutaraldehyde (GA, 0.125%), resulting in Pt/PPD/GluOx-GA electrode design. The maximum current density Jmax and apparent Michaelis constant, KM, obtained on Pt/PPD/GluOx-GA electrodes were 48 μA cm-2 and 50 μM, respectively. The linear region slope (LRS) was 0.96 μA cm-2 mM-1. The detection limit (LOD) for glutamate was 3.0 ± 0.6 μM. This study shows a promising glutamate microbiosensor for brain glutamate detection. 

Keywords: Brain, Glutamate, Microbiosensor.

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