Search results for: mechanical models.

Authors: Abdelrahman A. H. Abdelrahim, Gharib Subhi Mahmoud, Sherzod Turaev, Azeddine Messikh

Abstract:

Quantum gates are the basic building blocks in the quantum circuits model. These gates can be implemented using adiabatic or non adiabatic processes. Adiabatic models can be controlled using auxiliary qubits, whereas non adiabatic models can be simplified by using one single-shot implementation. In this paper, the controlled adiabatic evolutions is combined with the single-shot implementation to obtain quantum gates with controlled non adiabatic evolutions. This is an important improvement which can speed the implementation of quantum gates and reduce the errors due to the long run in the adiabatic model. The robustness of our scheme to different types of errors is also investigated.

Keywords: Adiabatic evolutions, non adiabatic evolutions, controlled adiabatic evolutions, quantum rotation gates, dephasing rates, master equation.

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Authors: Fernando Alonso, Rafael Fernandez, Sonia Frutos, Javier Soriano

Abstract:

CIM is the standard formalism for modeling management information developed by the Distributed Management Task Force (DMTF) in the context of its WBEM proposal, designed to provide a conceptual view of the managed environment. In this paper, we propose the inclusion of formal knowledge representation techniques, based on Description Logics (DLs) and the Web Ontology Language (OWL), in CIM-based conceptual modeling, and then we examine the benefits of such a decision. The proposal is specified as a CIM metamodel level mapping to a highly expressive subset of DLs capable of capturing all the semantics of the models. The paper shows how the proposed mapping can be used for automatic reasoning about the management information models, as a design aid, by means of new-generation CASE tools, thanks to the use of state-of-the-art automatic reasoning systems that support the proposed logic and use algorithms that are sound and complete with respect to the semantics. Such a CASE tool framework has been developed by the authors and its architecture is also introduced. The proposed formalization is not only useful at design time, but also at run time through the use of rational autonomous agents, in response to a need recently recognized by the DMTF.

Keywords: CIM, Knowledge-based Information Models, Ontology Languages, OWL, Description Logics, Integrated Network Management, Intelligent Agents, Automatic Reasoning Techniques.

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Authors: Achim Kampker, Peter Burggräf, Moritz Krunke, Hanno Voet

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As a reaction to current challenges in factory planning, many companies think about introducing factory standards to lower planning times and decrease planning costs. If these factory standards are set-up with a high level of modularity, they are defined as modular factory systems. This paper deals with the main current problems in the application of modular factory systems in practice and presents a solution approach with its basic models. The methodology is based on methods from factory planning but also uses the tools of other disciplines like product development or technology management to deal with the high complexity, which the development of modular factory systems implies. The four basic models that such a methodology has to contain are introduced and pointed out.

Keywords: Factory planning, modular factory systems, factory standards, cost-benefit analysis.

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Authors: E. F. Ochulor, S. O. Adeosun, S. A. Balogun

Abstract:

Effect of sprue/metal head height on mould filling, microstructure and mechanical properties of TWDI casting is studied. Results show that metal/sprue height of 50 mm is not sufficient to push the melt through the gating channel, but as it is increased from 100-350 mm, proper mould filling is achieved. However at higher heights between 200 mm and 350 mm, defects associated with incomplete solidification, carbide precipitation and turbulent flow are evident. This research shows that superior UTS, hardness, nodularity and nodule count are obtained at 100 mm sprue height.

Keywords: Melt pressure and velocity, nodularity, nodule count, sprue height.

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Authors: Elisa Pautasso, Matteo Castagno, Michele Osella

Abstract:

In the last decade the emergence of new social needs as an effect of the economic crisis has stimulated the flourishing of business endeavours characterised by explicit social goals. Social start-ups, social enterprises or Corporate Social Responsibility operations carried out by traditional companies are quintessential examples in this regard. This paper analyses these kinds of initiatives in order to discover the main characteristics of social business models and to provide insights to social entrepreneurs for developing or improving their strategies. The research is conducted through the integration of literature review and case study analysis and, thanks to the recognition of the importance of both profits and social impacts as the key success factors for a social business model, proposes a framework for identifying indicators suitable for measuring the social impacts generated.

Keywords: Business model, case study, impacts, social business.

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Authors: Md. Harunur Rashid, S. M. Kamal Uddin, Sobura khatun

Abstract:

The performance of mortar subjected to high temperature and cooled in normal ambient temperature was examined in the laboratory to comply with the situation of burning & cooling of a structure. Four series of cubical (5 X 5 X 5 cm) mortar specimens were made from OPC, and partial replacement (10, 15, 20, 25 & 30%) of OPC by Rice Husk Ash (RHA) produced in the uncontrolled environment. These specimens were heated in electric furnace to 200, 300, 400, 500 and 7000C. The specimens were kept in normal room temperature for cooling. They were then tested for mechanical properties and the results shows that particular 20% RHA mixed mortar shows better fire performance.

Keywords: Fire performance, Rice Husk

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Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte

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This paper proposes a bioprocess optimization procedure based on Relevance Vector Regression models and evolutionary programming technique. Relevance Vector Regression scheme allows developing a compact and stable data-based process model avoiding time-consuming modeling expenses. The model building and process optimization procedure could be done in a half-automated way and repeated after every new cultivation run. The proposed technique was tested in a simulated mammalian cell cultivation process. The obtained results are promising and could be attractive for optimization of industrial bioprocesses.

Keywords: Bioprocess optimization, Evolutionary programming, Relevance Vector Regression.

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Authors: B. Saha Roy, T. Medhi, S. C. Saha

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To understand the friction stir welding process, it is very important to know the nature of the material flow in and around the tool. The process is a combination of both thermal as well as mechanical work i.e. it is a coupled thermo-mechanical process. Numerical simulations are very much essential in order to obtain a complete knowledge of the process as well as the physics underlying it. In the present work a model based approach is adopted in order to study material flow. A thermo-mechanical based CFD model is developed using a Finite Element package, Comsol Multiphysics. The fluid flow analysis is done. The model simultaneously predicts shear strain fields, shear strain rates and shear stress over the entire workpiece for the given conditions. The flow fields generated by the streamline plot give an idea of the material flow. The variation of dynamic viscosity, velocity field and shear strain fields with various welding parameters is studied. Finally the result obtained from the above mentioned conditions is discussed elaborately and concluded.

Keywords: AA6061-T6, friction stir welding, material flow, CFD modelling.

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Authors: Eric Kojo Wu Aikins

Abstract:

This paper contributes to the debate on the proximate causes of climate change. Also, it discusses the impact of the global temperature increases since the beginning of the twentieth century and the effectiveness of climate change models in isolating the primary cause (anthropogenic influences or natural variability in temperature) of the observed temperature increases that occurred within this period. The paper argues that if climate scientist and policymakers ignore the anthropogenic influence (greenhouse gases) on global warming on the pretense of lack of agreement among various climate models and their inability to account for all the necessary factors of global warming at all levels the current efforts of greenhouse emissions control and global warming as a whole could be exacerbated.

Keywords: Anthropogenic Effects, Arctic, Climate Change, Natural Variability.

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Authors: R. Hela, L. Bodnarova

Abstract:

Paper focuses on experimental testing of possibilities of mechanical activation of fly ash and observation of influence of specific surface and granulometry on final properties of fresh and hardened concrete. Mechanical grinding prepared various fineness of fly ash, which was classed by specific surface in accordance with Blain and their granulometry was determined by means of laser granulometer. Then, sets of testing specimens were made from mix designs of identical composition with 25% or Portland cement CEM I 42.5 R replaced with fly ash with various specific surface and granulometry. Mix design with only Portland cement was used as reference. Mix designs were tested on consistency of fresh concrete and compressive strength after 7, 28, 60 and 90 days.

Keywords: Concrete, fly ash, latent hydraulicity, mechanically activated fly ash.

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Authors: Muhibul Haque Bhuyan

Abstract:

This paper reports on the impact study with the variation of the gate insulation material and thickness on different models of pocket implanted sub-100 nm n-MOS device. The gate materials used here are silicon dioxide (SiO₂), aluminum silicate (Al₂SiO₅), silicon nitride (Si₃N₄), alumina (Al₂O₃), hafnium silicate (HfSiO₄), tantalum pentoxide (Ta₂O₅), hafnium dioxide (HfO₂), zirconium dioxide (ZrO₂), and lanthanum oxide (La₂O₃) upon a p-type silicon substrate material. The gate insulation thickness was varied from 2.0 nm to 3.5 nm for a 50 nm channel length pocket implanted n-MOSFET. There are several models available for this device. We have studied and simulated threshold voltage model incorporating drain and substrate bias effects, surface potential, inversion layer charge, pinch-off voltage, effective electric field, inversion layer mobility, and subthreshold drain current models based on two linear symmetric pocket doping profiles. We have changed the values of the two parameters, viz. gate insulation material and thickness gradually fixing the other parameter at their typical values. Then we compared and analyzed the simulation results. This study would be helpful for the nano-scaled MOS device designers for various applications to predict the device behavior.

Keywords: Linear symmetric pocket profile, pocket implanted n-MOS Device, model, impact of gate material, insulator thickness.

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Authors: Benalia Kouini, Aicha Serier

Abstract:

Nanocomposites based on polypropylene/polyamide 66 (PP/PA66) nanoblends containing organophilic montmorillonite (OMMT) and maleic anhydride grafted polypropylene (PP-g-MAH) were prepared by melt compounding method followed by injection molding. Two different types of nanoclays were used in this work. DELLITE LVF is the untreated nanoclay and DELLITE 67G is the treated one. The morphology of the nanocomposites was studied using the XR diffraction (XRD). The results indicate that the incorporation of treated nanoclay has a significant effect on the impact strength of PP/PA66 nanocomposites. Furthermore, it was found that XRD results revealed the intercalation, exfoliation of nanaclays of nanocomposites.

Keywords: Nanoclay, nanocomposites, polypropylene, polyamide, melt processing, mechanical properties.

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Authors: H. B. Mehta, Vipul M. Patel, Jyotirmay Banerjee

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The present paper discusses the prediction of gas-liquid two-phase frictional pressure drop in a 2.12 mm horizontal circular minichannel using Artificial Neural Network (ANN). The experimental results are obtained with air as gas phase and water as liquid phase. The superficial gas velocity is kept in the range of 0.0236 m/s to 0.4722 m/s while the values of 0.0944 m/s, 0.1416 m/s and 0.1889 m/s are considered for superficial liquid velocity. The experimental results are predicted using different Artificial Neural Network (ANN) models. Networks used for prediction are radial basis, generalised regression, linear layer, cascade forward back propagation, feed forward back propagation, feed forward distributed time delay, layer recurrent, and Elman back propagation. Transfer functions used for networks are Linear (PURELIN), Logistic sigmoid (LOGSIG), tangent sigmoid (TANSIG) and Gaussian RBF. Combination of networks and transfer functions give different possible neural network models. These models are compared for Mean Absolute Relative Deviation (MARD) and Mean Relative Deviation (MRD) to identify the best predictive model of ANN.

Keywords: Minichannel, Two-Phase Flow, Frictional Pressure Drop, ANN, MARD, MRD.

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Authors: M. K. Witek-Hajduk, T. M. Napiórkowski

Abstract:

A number of studies discussed the topic of benefits of retailers-manufacturers cooperation and coopetition. However, there are only few publications focused on the benefits of cooperation and coopetition between retailers and their suppliers of durable consumer goods; especially in the context of business model of cooperating partners. This paper aims to provide a clustering approach to segment retailers selling consumer durables according to the benefits they obtain from their cooperation with key manufacturers and differentiate the said retailers’ in term of the business models of cooperating partners. For the purpose of the study, a survey (with a CATI method) collected data on 603 consumer durables retailers present on the Polish market. Retailers are clustered both, with hierarchical and non-hierarchical methods. Five distinctive groups of consumer durables’ retailers are (based on the studied benefits) identified using the two-stage clustering approach. The clusters are then characterized with a set of exogenous variables, key of which are business models employed by the retailer and its partnering key manufacturer. The paper finds that the a combination of a medium sized retailer classified as an Integrator with a chiefly domestic capital and a manufacturer categorized as a Market Player will yield the highest benefits. On the other side of the spectrum is medium sized Distributor retailer with solely domestic capital – in this case, the business model of the cooperating manufactrer appears to be irreleveant. This paper is the one of the first empirical study using cluster analysis on primary data that defines the types of cooperation between consumer durables’ retailers and manufacturers – their key suppliers. The analysis integrates a perspective of both retailers’ and manufacturers’ business models and matches them with individual and joint benefits.

Keywords: Business model, cooperation, cluster analysis, retailer-manufacturer relationships.

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Authors: H. Chaker, T. Slama, N. Elyétim

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This paper analyzes the effects of gender, affiliation, prior work experience, social work, and vicarious learning through family role models on entrepreneurial skills development by students when they followed the teaching through the entrepreneurship method in Tunisia. We suggest that these variables enhance the development of students’ entrepreneurial skills when combined with teaching through entrepreneurship. The article assesses the impact of these combinations by comparing their effects on the development of thirteen students’ entrepreneurial competencies, namely entrepreneurial mindset, core self-evaluation, entrepreneurial attitude, entrepreneurial knowledge, creativity, financial literacy, managing ambiguity, marshaling of resources, planning, teaching methods, entrepreneurial teachers, innovative employee, and entrepreneurial intention. We use a two-sample independent t-test to make the comparison, and the results indicate that, when combined with teaching through the entrepreneurship method, students with prior work experience developed better six entrepreneurial skills; students with social work developed better three entrepreneurial skills, men developed better four entrepreneurial skills than women. However, all students developed their entrepreneurial skills through this practical method regardless of their affiliation and their vicarious learning through family role models.

Keywords: Affiliation, entrepreneurial skills, gender, role models, social work, teaching through entrepreneurship, vicarious learning, work experience.

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Authors: M. Nemissi, H. Seridi, H. Akdag

Abstract:

This paper presents and evaluates a new classification method that aims to improve classifiers performances and speed up their training process. The proposed approach, called labeled classification, seeks to improve convergence of the BP (Back propagation) algorithm through the addition of an extra feature (labels) to all training examples. To classify every new example, tests will be carried out each label. The simplicity of implementation is the main advantage of this approach because no modifications are required in the training algorithms. Therefore, it can be used with others techniques of acceleration and stabilization. In this work, two models of the labeled classification are proposed: the LMLP (Labeled Multi Layered Perceptron) and the LNFC (Labeled Neuro Fuzzy Classifier). These models are tested using Iris, wine, texture and human thigh databases to evaluate their performances.

Keywords: Artificial neural networks, Fusion of neural networkfuzzysystems, Learning theory, Pattern recognition.

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Authors: Jeong-Won Kang

Abstract:

Graphene, a single-atom sheet, has been considered as the most promising material for making future nanoelectromechanical systems as well as purely electrical switching with graphene transistors. Graphene-based devices have advantages in scaled-up device fabrication due to the recent progress in large area graphene growth and lithographic patterning of graphene nanostructures. Here we investigated its mechanical responses of circular graphene nanoflake under the nanoindentation using classical molecular dynamics simulations. A correlation between the load and the indentation depth was constructed. The nanoindented force in this work was applied to the center point of the circular graphene nanoflake and then, the resonance frequency could be tuned by a nanoindented depth. We found the hardening or the softening of the graphene nanoflake during its nanoindented-deflections, and such properties were recognized by the shift of the resonance frequency. The calculated mechanical parameters in the force-vs-deflection plot were in good agreement with previous experimental and theoretical works. This proposed schematics can detect the pressure via the deflection change or/and the resonance frequency shift, and also have great potential for versatile applications in nanoelectromechanical systems.

Keywords: Graphene, pressure sensor, circular graphene nanoflake, molecular dynamics.

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Authors: Yong-Quan Zhou, Deng-Xu He, Zheng Nong

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In this paper two models using a functional network were employed to solving classification problem. Functional networks are generalized neural networks, which permit the specification of their initial topology using knowledge about the problem at hand. In this case, and after analyzing the available data and their relations, we systematically discuss a numerical analysis method used for functional network, and apply two functional network models to solving XOR problem. The XOR problem that cannot be solved with two-layered neural network can be solved by two-layered functional network, which reveals a potent computational power of functional networks, and the performance of the proposed model was validated using classification problems.

Keywords: Functional network, neural network, XOR problem, classification, numerical analysis method.

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Authors: Anastasiia Yu. Timofeeva

Abstract:

Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect.

Keywords: Grade point average, orthogonal regression, penalized regression spline, locally weighted regression.

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Authors: Laurenţiu Militeanu, Cristina Gena Dascâlu, D. Cristea

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The human head representations usually are based on the morphological – structural components of a real model. Over the time became more and more necessary to achieve full virtual models that comply very rigorous with the specifications of the human anatomy. Still, making and using a model perfectly fitted with the real anatomy is a difficult task, because it requires large hardware resources and significant times for processing. That is why it is necessary to choose the best compromise solution, which keeps the right balance between the details perfection and the resources consumption, in order to obtain facial animations with real-time rendering. We will present here the way in which we achieved such a 3D system that we intend to use as a base point in order to create facial animations with real-time rendering, used in medicine to find and to identify different types of pathologies.

Keywords: 3D models, virtual reality.

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Authors: Lely A. Luengas, Pedro R. Vizcaya, Giovanni Sánchez

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In this paper, a methodology is presented to obtain the Static Alignment Model for any transtibial amputee person. The proposed methodology starts from experimental data collected on the Hospital Militar Central, Bogotá, Colombia. The effects of transtibial prosthesis malalignment on amputees were measured in terms of joint angles, center of pressure (COP) and weight distribution. Some statistical tools are used to obtain the model parameters. Mathematical predictive models of prosthetic alignment were created. The proposed models are validated in amputees and finding promising results for the prosthesis Static Alignment. Static alignment process is unique to each subject; nevertheless the proposed methodology can be used in each transtibial amputee.

Keywords: Information theory, prediction model, prosthetic alignment, transtibial prosthesis.

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Authors: Brian A. Smith, Ronald W. McClendon, Gerrit Hoogenboom

Abstract:

The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. An improved model for temperature prediction in Georgia was developed by including information on seasonality and modifying parameters of an existing artificial neural network model. Alternative models were compared by instantiating and training multiple networks for each model. The inclusion of up to 24 hours of prior weather information and inputs reflecting the day of year were among improvements that reduced average four-hour prediction error by 0.18°C compared to the prior model. Results strongly suggest model developers should instantiate and train multiple networks with different initial weights to establish appropriate model parameters.

Keywords: Time-series forecasting, weather modeling.

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Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

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This paper discusses on power spectral density (PSD) characteristics which are extracted from three-dimensional (3D) electroencephalogram (EEG) models. The EEG signal recording was conducted on 150 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, the values of maximum PSD were extracted as features from the model. These features are analyzed using mean relative power (MRP) and different mean relative power (DMRP) technique to observe the pattern among different brain balancing indexes. The results showed that by implementing these techniques, the pattern of brain balancing indexes can be clearly observed. Some patterns are indicates between index 1 to index 5 for left frontal (LF) and right frontal (RF).

Keywords: Power spectral density, 3D EEG model, brain balancing, mean relative power, different mean relative power.

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Authors: Kai-Lin Hsu, Jie-Chung Lou, Jia-Yun Han

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In recent years, the underground water sources in southern Taiwan have become salinized because of saltwater intrusions. This study explores the adsorption characteristics of activated carbon on salinizing inorganic salts using isothermal adsorption experiments and provides a model analysis. The temperature range for the isothermal adsorption experiments ranged between 5 to 45 ℃, and the amount adsorbed varied between 28.21 to 33.87 mg/g. All experimental data of adsorption can be fitted to both the Langmuir and the Freundlich models. The thermodynamic parameters for per chlorate onto granular activated carbon were calculated as -0.99 to -1.11 kcal/mol for DG°, -0.6 kcal/mol for DH°, and 1.21 to 1.84 kcal/mol for DS°. This shows that the adsorption process of granular activated carbon is spontaneously exothermic. The observation of adsorption behaviors under low ionic strength, low pH values, and low temperatures is beneficial to the adsorption removal of perchlorate with granular activated carbon.

Keywords: Water Treatment, Per Chlorate, Adsorption, Granular Activated Carbon

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Authors: Junji Kaneko, Shigeyuki Haruyama, Ken Kaminishi, Tadayuki Kyoutani, Siti Ruhana Omar, Oke Oktavianty

Abstract:

This study is used as a definition method to the value and function in manufacturing sector. In concurrence of discussion about present condition of modeling method, until now definition of 1D-CAE is ambiguity and not conceptual. Across all the physic fields, those methods are defined with the formulation of differential algebraic equation which only applied time derivation and simulation. At the same time, we propose semi-acausal modeling concept and differential algebraic equation method as a newly modeling method which the efficiency has been verified through the comparison of numerical analysis result between the semi-acausal modeling calculation and FEM theory calculation.

Keywords: System Model, Physical Models, Empirical Models, Conservation Law, Differential Algebraic Equation, Object-Oriented.

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Authors: Kahloul Laid, Chaoui Allaoua

Abstract:

Code mobility technologies attract more and more developers and consumers. Numerous domains are concerned, many platforms are developed and interest applications are realized. However, developing good software products requires modeling, analyzing and proving steps. The choice of models and modeling languages is so critical on these steps. Formal tools are powerful in analyzing and proving steps. However, poorness of classical modeling language to model mobility requires proposition of new models. The objective of this paper is to provide a specific formalism “Coloured Reconfigurable Nets" and to show how this one seems to be adequate to model different kinds of code mobility.

Keywords: Code mobility, modelling mobility, labelled reconfigurable nets, Coloured reconfigurable nets, mobile code design paradigms.

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Authors: Yehjune Heo

Abstract:

As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: Anti-spoofing, CNN, fingerprint recognition, loss function, optimizer.

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Authors: O. Eren, N. Ucar, A. Onen, N. Kızıldag, O. F. Vurur, N. Demirsoy, I. Karacan

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PAN nanofibers reinforced with amine functionalized carbon nanotubes. The effect of amine functionalization and the effect of concentration of CNT on the conductivity and mechanical and morphological properties of composite nanofibers were examined. 1%CNT-NH2 loaded PAN/CNT nanofiber showed the best mechanical properties. Conductivity increased with the incorporation of carbon nanotubes. While an increase of concentration of CNT increases the diameter of nanofiber, the use of functionalized CNT results to decrease of diameter of nanofiber.

Keywords: Amine functionalized carbon nanotube, electrospinning, nanofiber, polyacrylonitrile.

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Authors: M. Margarida Costa, Jorge Simão

Abstract:

The minimal condition for symmetry breaking in morphogenesis of cellular population was investigated using cellular automata based on reaction-diffusion dynamics. In particular, the study looked for the possibility of the emergence of branching structures due to mechanical interactions. The model used two types of cells an external gradient. The results showed that the external gradient influenced movement of cell type-I, also revealed that clusters formed by cells type-II worked as barrier to movement of cells type-I.

Keywords: Morphogenesis, branching structures, symmetrybreaking.

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Authors: M. A. Sohaly, M. A. Elfouly

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Parkinson's disease (PD) is a heterogeneous movement disorder that often appears in the elderly. PD is induced by a loss of dopamine secretion. Some drugs increase the secretion of dopamine. In this paper, we will simply study the stability of PD models as a nonlinear delay differential equation. After a period of taking drugs, these act as positive feedback and increase the tremors of patients, and then, the differential equation has positive coefficients and the system is unstable under these conditions. We will present a set of suggested modifications to make the system more compatible with the biodynamic system. When giving a set of numerical examples, this research paper is concerned with the mathematical analysis, and no clinical data have been used.

Keywords: Parkinson's disease, stability, simulation, two delay differential equation.

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