Search results for: mathematical models.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3264

Search results for: mathematical models.

2694 Adopting Procedural Animation Technology to Generate Locomotion of Quadruped Characters in Dynamic Environments

Authors: Zongyou He, Bashu Tsai, Chinhung Ko, Tainchi Lu

Abstract:

A procedural-animation-based approach which rapidly synthesize the adaptive locomotion for quadruped characters that they can walk or run in any directions on an uneven terrain within a dynamic environment was proposed. We devise practical motion models of the quadruped animals for adapting to a varied terrain in a real-time manner. While synthesizing locomotion, we choose the corresponding motion models by means of the footstep prediction of the current state in the dynamic environment, adjust the key-frames of the motion models relying on the terrain-s attributes, calculate the collision-free legs- trajectories, and interpolate the key-frames according to the legs- trajectories. Finally, we apply dynamic time warping to each part of motion for seamlessly concatenating all desired transition motions to complete the whole locomotion. We reduce the time cost of producing the locomotion and takes virtual characters to fit in with dynamic environments no matter when the environments are changed by users.

Keywords: Dynamic environment, motion synthesis, procedural animation, quadruped locomotion

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2693 Evaluation of Hydrogen Particle Volume on Surfaces of Selected Nanocarbons

Authors: M. Ziółkowska, J. T. Duda, J. Milewska-Duda

Abstract:

This paper describes an approach to the adsorption phenomena modeling aimed at specifying the adsorption mechanisms on localized or nonlocalized adsorbent sites, when applied to the nanocarbons. The concept comes from the fundamental thermodynamic description of adsorption equilibrium and is based on numerical calculations of the hydrogen adsorbed particles volume on the surface of selected nanocarbons: single-walled nanotube and nanocone. This approach enables to obtain information on adsorption mechanism and then as a consequence to take appropriate mathematical adsorption model, thus allowing for a more reliable identification of the material porous structure. Theoretical basis of the approach is discussed and newly derived results of the numerical calculations are presented for the selected nanocarbons.

Keywords: Adsorption, mathematical modeling, nanocarbons, numerical analysis.

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2692 On the Learning of Causal Relationships between Banks in Saudi Equities Market Using Ensemble Feature Selection Methods

Authors: Adel Aloraini

Abstract:

Financial forecasting using machine learning techniques has received great efforts in the last decide . In this ongoing work, we show how machine learning of graphical models will be able to infer a visualized causal interactions between different banks in the Saudi equities market. One important discovery from such learned causal graphs is how companies influence each other and to what extend. In this work, a set of graphical models named Gaussian graphical models with developed ensemble penalized feature selection methods that combine ; filtering method, wrapper method and a regularizer will be shown. A comparison between these different developed ensemble combinations will also be shown. The best ensemble method will be used to infer the causal relationships between banks in Saudi equities market.

Keywords: Causal interactions , banks, feature selection, regularizere,

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2691 Equilibrium Modeling of Carbon Dioxide Adsorption on Zeolites

Authors: Alireza Behvandi, Somayeh Tourani

Abstract:

High pressure adsorption of carbon dioxide on zeolite 13X was investigated in the pressure range (0 to 4) Mpa and temperatures 298, 308 and 323K. The data fitting is accomplished with the Toth, UNILAN, Dubinin-Astakhov and virial adsorption models which are generally used for micro porous adsorbents such as zeolites. Comparison with experimental data from the literature indicated that the virial model would best determine results. These results may be partly attributed to the flexibility of the virial model which can accommodate as many constants as the data warrants.

Keywords: adsorption models, zeolite, carbon dioxide

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2690 An Investigation into Turbine Blade Tip Leakage Flows at High Speeds

Authors: Z. Saleh, E. J. Avital, T. Korakianitis

Abstract:

The effect of the blade tip geometry of a high pressure gas turbine is studied experimentally and computationally for high speed leakage flows. For this purpose two simplified models are constructed, one models a flat tip of the blade and the second models a cavity tip of the blade. Experimental results are obtained from a transonic wind tunnel to show the static pressure distribution along the tip wall and provide flow visualization. RANS computations were carried to provide further insight into the mean flow behavior and to calculate the discharge coefficient which is a measure of the flow leaking over the tip. It is shown that in both geometries of tip the flow separates over the tip to form a separation bubble. The bubble is higher for the cavity tip while a complete shock wave system of oblique waves ending with a normal wave can be seen for the flat tip. The discharge coefficient for the flat tip shows less dependence on the pressure ratio over the blade tip than the cavity tip. However, the discharge coefficient for the cavity tip is lower than that of the flat tip, showing a better ability to reduce the leakage flow and thus increase the turbine efficiency.

Keywords: Gas turbine, blade tip leakage flow, transonic flow.

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2689 Metabolic Analysis of Fibroblast Conditioned Media and Comparison with Theoretical Modeling

Authors: Priyanka Gupta, Paul Verma, Kerry Hourigan, Jayesh Bellare, Sameer Jadhav

Abstract:

Understanding the consumption and production of various metabolites of fibroblast conditioned media is needed for its proper and optimized use in expansion of pluripotent stem cells. For this purpose, we have used the HPLC method to analyse the consumption of glucose and the production of lactate over time by mouse embryonic fibroblasts. The experimental data have also been compared with mathematical model fits. 0.025 moles of lactate was produced after 72 hrs while the glucose concentration decreased from 0.017 moles to 0.011 moles. The mathematical model was able to predict the trends of glucose consumption and lactate production.

Keywords: Conditioned media, HPLC, metabolite analysis, mouse embryonic fibroblast.

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2688 Daily Probability Model of Storm Events in Peninsular Malaysia

Authors: Mohd Aftar Abu Bakar, Noratiqah Mohd Ariff, Abdul Aziz Jemain

Abstract:

Storm Event Analysis (SEA) provides a method to define rainfalls events as storms where each storm has its own amount and duration. By modelling daily probability of different types of storms, the onset, offset and cycle of rainfall seasons can be determined and investigated. Furthermore, researchers from the field of meteorology will be able to study the dynamical characteristics of rainfalls and make predictions for future reference. In this study, four categories of storms; short, intermediate, long and very long storms; are introduced based on the length of storm duration. Daily probability models of storms are built for these four categories of storms in Peninsular Malaysia. The models are constructed by using Bernoulli distribution and by applying linear regression on the first Fourier harmonic equation. From the models obtained, it is found that daily probability of storms at the Eastern part of Peninsular Malaysia shows a unimodal pattern with high probability of rain beginning at the end of the year and lasting until early the next year. This is very likely due to the Northeast monsoon season which occurs from November to March every year. Meanwhile, short and intermediate storms at other regions of Peninsular Malaysia experience a bimodal cycle due to the two inter-monsoon seasons. Overall, these models indicate that Peninsular Malaysia can be divided into four distinct regions based on the daily pattern for the probability of various storm events.

Keywords: Daily probability model, monsoon seasons, regions, storm events.

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2687 Comparative Study of Bending Angle in Laser Forming Process Using Artificial Neural Network and Fuzzy Logic System

Authors: M. Hassani, Y. Hassani, N. Ajudanioskooei, N. N. Benvid

Abstract:

Laser Forming process as a non-contact thermal forming process is widely used to forming and bending of metallic and non-metallic sheets. In this process, according to laser irradiation along a specific path, sheet is bent. One of the most important output parameters in laser forming is bending angle that depends on process parameters such as physical and mechanical properties of materials, laser power, laser travel speed and the number of scan passes. In this paper, Artificial Neural Network and Fuzzy Logic System were used to predict of bending angle in laser forming process. Inputs to these models were laser travel speed and laser power. The comparison between artificial neural network and fuzzy logic models with experimental results has been shown both of these models have high ability to prediction of bending angles with minimum errors.

Keywords: Artificial neural network, bending angle, fuzzy logic, laser forming.

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2686 Application Methodology for the Generation of 3D Thermal Models Using UAV Photogrammety and Dual Sensors for Mining/Industrial Facilities Inspection

Authors: Javier Sedano-Cibrián, Julio Manuel de Luis-Ruiz, Rubén Pérez-Álvarez, Raúl Pereda-García, Beatriz Malagón-Picón

Abstract:

Structural inspection activities are necessary to ensure the correct functioning of infrastructures. UAV techniques have become more popular than traditional techniques. Specifically, UAV Photogrammetry allows time and cost savings. The development of this technology has permitted the use of low-cost thermal sensors in UAVs. The representation of 3D thermal models with this type of equipment is in continuous evolution. The direct processing of thermal images usually leads to errors and inaccurate results. In this paper, a methodology is proposed for the generation of 3D thermal models using dual sensors, which involves the application of RGB and thermal images in parallel. Hence, the RGB images are used as the basis for the generation of the model geometry, and the thermal images are the source of the surface temperature information that is projected onto the model. Mining/industrial facilities representations that are obtained can be used for inspection activities.

Keywords: Aerial thermography, data processing, drone, low-cost, point cloud.

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2685 3D Point Cloud Model Color Adjustment by Combining Terrestrial Laser Scanner and Close Range Photogrammetry Datasets

Authors: M. Pepe, S. Ackermann, L. Fregonese, C. Achille

Abstract:

3D models obtained with advanced survey techniques such as close-range photogrammetry and laser scanner are nowadays particularly appreciated in Cultural Heritage and Archaeology fields. In order to produce high quality models representing archaeological evidences and anthropological artifacts, the appearance of the model (i.e. color) beyond the geometric accuracy, is not a negligible aspect. The integration of the close-range photogrammetry survey techniques with the laser scanner is still a topic of study and research. By combining point cloud data sets of the same object generated with both technologies, or with the same technology but registered in different moment and/or natural light condition, could construct a final point cloud with accentuated color dissimilarities. In this paper, a methodology to uniform the different data sets, to improve the chromatic quality and to highlight further details by balancing the point color will be presented.

Keywords: Color models, cultural heritage, laser scanner, photogrammetry, point cloud color.

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2684 Stability Analysis for an Extended Model of the Hypothalamus-Pituitary-Thyroid Axis

Authors: Beata Jackowska-Zduniak

Abstract:

We formulate and analyze a mathematical model describing dynamics of the hypothalamus-pituitary-thyroid homoeostatic mechanism in endocrine system. We introduce to this system two types of couplings and delay. In our model, feedback controls the secretion of thyroid hormones and delay reflects time lags required for transportation of the hormones. The influence of delayed feedback on the stability behaviour of the system is discussed. Analytical results are illustrated by numerical examples of the model dynamics. This system of equations describes normal activity of the thyroid and also a couple of types of malfunctions (e.g. hyperthyroidism).

Keywords: Mathematical modeling, ordinary differential equations, endocrine system, stability analysis.

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2683 Efficient Solution for a Class of Markov Chain Models of Tandem Queueing Networks

Authors: Chun Wen, Tingzhu Huang

Abstract:

We present a new numerical method for the computation of the steady-state solution of Markov chains. Theoretical analyses show that the proposed method, with a contraction factor α, converges to the one-dimensional null space of singular linear systems of the form Ax = 0. Numerical experiments are used to illustrate the effectiveness of the proposed method, with applications to a class of interesting models in the domain of tandem queueing networks.

Keywords: Markov chains, tandem queueing networks, convergence, effectiveness.

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2682 Modeling and Simulating Human Arm Movement Using a 2 Dimensional 3 Segments Coupled Pendulum System

Authors: Loay A. Al-Zu'be, Asma A. Al-Tamimi, Thakir D. Al-Momani, Ayat J. Alkarala, Maryam A. Alzawahreh

Abstract:

A two dimensional three segments coupled pendulum system that mathematically models human arm configuration was developed along with constructing and solving the equations of motions for this model using the energy (work) based approach of Lagrange. The equations of motion of the model were solved iteratively both as an initial value problem and as a two point boundary value problem. In the initial value problem solutions, both the initial system configuration (segment angles) and initial system velocity (segment angular velocities) were used as inputs, whereas, in the two point boundary value problem solutions initial and final configurations and time were used as inputs to solve for the trajectory of motion. The results suggest that the model solutions are sensitive to small changes in the dynamic forces applied to the system as well as to the initial and boundary conditions used. To overcome the system sensitivity a new approach is suggested.

Keywords: Body Configurations, Equations of Motion, Mathematical Modeling, Movement Trajectories.

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2681 Modeling of a Small Unmanned Aerial Vehicle

Authors: A. Elsayed Ahmed, A. Hafez, A. N. Ouda, H. Eldin Hussein Ahmed, H. Mohamed Abd-Elkader

Abstract:

Unmanned aircraft systems (UAS) are playing increasingly prominent roles in defense programs and defense strategies around the world. Technology advancements have enabled the development of it to do many excellent jobs as reconnaissance, surveillance, battle fighters, and communications relays. Simulating a small unmanned aerial vehicle (SUAV) dynamics and analyzing its behavior at the preflight stage is too important and more efficient. The first step in the UAV design is the mathematical modeling of the nonlinear equations of motion. . In this paper, a survey with a standard method to obtain the full non-linear equations of motion is utilized, and then the linearization of the equations according to a steady state flight condition (trimming) is derived. This modeling technique is applied to an Ultrastick-25e fixed wing UAV to obtain the valued linear longitudinal and lateral models. At the end the model is checked by matching between the behavior of the states of the nonlinear UAV and the resulted linear model with doublet at the control surfaces.

Keywords: Equations of motion, linearization, modeling, nonlinear model, UAV.

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2680 A Bi-Objective Preventive Healthcare Facility Network Design with Incorporating Cost and Time Saving

Authors: Mehdi Seifbarghy, Keyvan Roshan

Abstract:

Main goal of preventive healthcare problems are at decreasing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. The levels of establishment and staffing costs along with summation of the travel and waiting time that clients spent are considered as objectives functions of the proposed nonlinear integer programming model. In this paper, we have proposed a bi-objective mathematical model for designing a network of preventive healthcare facilities so as to minimize aforementioned objectives, simultaneously. Moreover, each facility acts as M/M/1 queuing system. The number of facilities to be established, the location of each facility, and the level of technology for each facility to be chosen are provided as the main determinants of a healthcare facility network. Finally, to demonstrate performance of the proposed model, four multi-objective decision making techniques are presented to solve the model.

Keywords: Preventive healthcare problems, Non-linear integer programming models, Multi-objective decision making techniques

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2679 Developing Pedotransfer Functions for Estimating Some Soil Properties using Artificial Neural Network and Multivariate Regression Approaches

Authors: Fereydoon Sarmadian, Ali Keshavarzi

Abstract:

Study of soil properties like field capacity (F.C.) and permanent wilting point (P.W.P.) play important roles in study of soil moisture retention curve. Although these parameters can be measured directly, their measurement is difficult and expensive. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. In this investigation, 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. The data set was divided into two subsets for calibration (80%) and testing (20%) of the models and their normality were tested by Kolmogorov-Smirnov method. Both multivariate regression and artificial neural network (ANN) techniques were employed to develop the appropriate PTFs for predicting soil parameters using easily measurable characteristics of clay, silt, O.C, S.P, B.D and CaCO3. The performance of the multivariate regression and ANN models was evaluated using an independent test data set. In order to evaluate the models, root mean square error (RMSE) and R2 were used. The comparison of RSME for two mentioned models showed that the ANN model gives better estimates of F.C and P.W.P than the multivariate regression model. The value of RMSE and R2 derived by ANN model for F.C and P.W.P were (2.35, 0.77) and (2.83, 0.72), respectively. The corresponding values for multivariate regression model were (4.46, 0.68) and (5.21, 0.64), respectively. Results showed that ANN with five neurons in hidden layer had better performance in predicting soil properties than multivariate regression.

Keywords: Artificial neural network, Field capacity, Permanentwilting point, Pedotransfer functions.

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2678 A Recommendation to Oncologists for Cancer Treatment by Immunotherapy: Quantitative and Qualitative Analysis

Authors: Mandana Kariminejad, Ali Ghaffari

Abstract:

Today, the treatment of cancer, in a relatively short period, with minimum adverse effects is a great concern for oncologists. In this paper, based on a recently used mathematical model for cancer, a guideline has been proposed for the amount and duration of drug doses for cancer treatment by immunotherapy. Dynamically speaking, the mathematical ordinary differential equation (ODE) model of cancer has different equilibrium points; one of them is unstable, which is called the no tumor equilibrium point. In this paper, based on the number of tumor cells an intelligent soft computing controller (a combination of fuzzy logic controller and genetic algorithm), decides regarding the amount and duration of drug doses, to eliminate the tumor cells and stabilize the unstable point in a relatively short time. Two different immunotherapy approaches; active and adoptive, have been studied and presented. It is shown that the rate of decay of tumor cells is faster and the doses of drug are lower in comparison with the result of some other literatures. It is also shown that the period of treatment and the doses of drug in adoptive immunotherapy are significantly less than the active method. A recommendation to oncologists has also been presented.

Keywords: Tumor, immunotherapy, fuzzy controller, Genetic algorithm, mathematical model.

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2677 Sentiment Analysis of Fake Health News Using Naive Bayes Classification Models

Authors: Danielle Shackley, Yetunde Folajimi

Abstract:

As more people turn to the internet seeking health related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores of text, ranging from positive, neutral and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing, tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process, and substituting the Naive Bayes for a deep learning neural network model.

Keywords: Sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model.

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2676 Business Model Topology in Emerging Business Ecosystem

Authors: Olga Novikova, Timo Vuori

Abstract:

This paper describes topology of business models in market ecosystem of the emerging electric mobility industry. The business model topology shows that firm-s participation in the ecosystem is associated with different requirements on resources and capabilities, and different levels of risk. Business model concept is used together with concepts of networked value creation and shows that firms can achieve higher levels of sustainable advantage by cooperation, not competition. Hybrid business models provide companies a viable alternative possibility for participation in the market ecosystem.

Keywords: Business model, ecosystem, topology.

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2675 Multiple Sensors and JPDA-IMM-UKF Algorithm for Tracking Multiple Maneuvering Targets

Authors: Wissem Saidani, Yacine Morsly, Mohand Saïd Djouadi

Abstract:

In this paper, we consider the problem of tracking multiple maneuvering targets using switching multiple target motion models. With this paper, we aim to contribute in solving the problem of model-based body motion estimation by using data coming from visual sensors. The Interacting Multiple Model (IMM) algorithm is specially designed to track accurately targets whose state and/or measurement (assumed to be linear) models changes during motion transition. However, when these models are nonlinear, the IMM algorithm must be modified in order to guarantee an accurate track. In this paper we propose to avoid the Extended Kalman filter because of its limitations and substitute it with the Unscented Kalman filter which seems to be more efficient especially according to the simulation results obtained with the nonlinear IMM algorithm (IMMUKF). To resolve the problem of data association, the JPDA approach is combined with the IMM-UKF algorithm, the derived algorithm is noted JPDA-IMM-UKF.

Keywords: Estimation, Kalman filtering, Multi-Target Tracking, Visual servoing, data association.

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2674 Vaccinated Susceptible Infected and Recovered (VSIR) Mathematical Model to Study the Effect of Bacillus Calmette-Guerin (BCG) Vaccine and the Disease Stability Analysis

Authors: Muhammad Shahid, Nasir-uddin Khan, Mushtaq Hussain, Muhammad Liaquat Ali, Asif Mansoor

Abstract:

Tuberculosis (TB) remains a leading cause of infectious mortality. It is primarily transmitted by the respiratory route, individuals with active disease may infect others through airborne particles which releases when they cough, talk, or sing and subsequently inhale by others. In order to study the effect of the Bacilli Calmette-Guerin (BCG) vaccine after vaccination of TB patient, a Vaccinated Susceptible Infected and Recovered (VSIR) mathematical model is being developed to achieve the desired objectives. The mathematical model, so developed, shall be used to quantify the effect of BCG Vaccine to protect the immigrant young adult person. Moreover, equations are to be established for the disease endemic and free equilibrium states and subsequently utilized in disease stability analysis. The stability analysis will give a complete picture of disease annihilation from the total population if the total removal rate from the infectious group should be greater than total number of dormant infections produced throughout infectious period.

Keywords: Bacillus Calmette-Guerin vaccine, disease-free equilibrium state, VSIR Quantification, disease stability analysis.

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2673 Seismic Assessment of Old Existing RC Buildings on Madinah with Masonry Infilled Using Ambient Vibration Measurements

Authors: Tarek M. Alguhane, Ayman H. Khalil, M. N. Fayed, Ayman M. Ismail

Abstract:

Early pre-code reinforced concrete structures present undetermined resistance to earthquakes. This situation is particularly unacceptable in the case of essential structures, such as healthcare structures and pilgrims' houses. Amongst these, an existing old RC building in Madinah city (KSA) is seismically evaluated with and without infill wall and their dynamic characteristics are compared with measured values in the field using ambient vibration measurements (AVM). After updating the mathematical models for this building with the experimental results, three dimensional pushover analysis (Nonlinear static analysis) was carried out using commercial structural analysis software incorporating inelastic material properties for concrete, infill and steel. The purpose of this analysis is to evaluate the expected performance of structural systems by estimating, strength and deformation demands in design, and comparing these demands to available capacities at the performance levels of interest. The results summarized and discussed.

Keywords: Seismic Assessment, Pushover Analysis, Ambient vibration, Modal update.

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2672 Learning Human-Like Color Categorization through Interaction

Authors: Rinaldo Christian Tanumara, Ming Xie, Chi Kit Au

Abstract:

Human perceives color in categories, which may be identified using color name such as red, blue, etc. The categorization is unique for each human being. However despite the individual differences, the categorization is shared among members in society. This allows communication among them, especially when using color name. Sociable robot, to live coexist with human and become part of human society, must also have the shared color categorization, which can be achieved through learning. Many works have been done to enable computer, as brain of robot, to learn color categorization. Most of them rely on modeling of human color perception and mathematical complexities. Differently, in this work, the computer learns color categorization through interaction with humans. This work aims at developing the innate ability of the computer to learn the human-like color categorization. It focuses on the representation of color categorization and how it is built and developed without much mathematical complexity.

Keywords: Color categorization, color learning, machinelearning, color naming.

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2671 A Graphical Environment for Petri Nets INA Tool Based on Meta-Modelling and Graph Grammars

Authors: Raida El Mansouri, Elhillali Kerkouche, Allaoua Chaoui

Abstract:

The Petri net tool INA is a well known tool by the Petri net community. However, it lacks a graphical environment to cerate and analyse INA models. Building a modelling tool for the design and analysis from scratch (for INA tool for example) is generally a prohibitive task. Meta-Modelling approach is useful to deal with such problems since it allows the modelling of the formalisms themselves. In this paper, we propose an approach based on the combined use of Meta-modelling and Graph Grammars to automatically generate a visual modelling tool for INA for analysis purposes. In our approach, the UML Class diagram formalism is used to define a meta-model of INA models. The meta-modelling tool ATOM3 is used to generate a visual modelling tool according to the proposed INA meta-model. We have also proposed a graph grammar to automatically generate INA description of the graphically specified Petri net models. This allows the user to avoid the errors when this description is done manually. Then the INA tool is used to perform the simulation and the analysis of the resulted INA description. Our environment is illustrated through an example.

Keywords: INA, Meta-modelling, Graph Grammars, AToM3, Automatic Code Generation.

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2670 Analysis of the Interference from Risk-Determining Factors of Cooperative and Conventional Construction Contracts

Authors: E. Harrer, M. Mauerhofer, T. Werginz

Abstract:

As a result of intensive competition, the building sector is suffering from a high degree of rivalry. Furthermore, there can be observed an unbalanced distribution of project risks. Clients are aimed to shift their own risks into the sphere of the constructors or planners. The consequence of this is that the number of conflicts between the involved parties is inordinately high or even increasing; an alternative approach to counter on that developments are cooperative project forms in the construction sector. This research compares conventional contract models and models with partnering agreements to examine the influence on project risks by an early integration of the involved parties. The goal is to show up deviations in different project stages from the design phase to the project transfer phase. These deviations are evaluated by a survey of experts from the three spheres: clients, contractors and planners. By rating the influence of the participants on specific risk factors it is possible to identify factors which are relevant for a smooth project execution.

Keywords: Collaborative work, construction industry, contract-models, influence, partnering, project management, risk.

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2669 Practical Problems as Tools for the Development of Secondary School Students’ Motivation to Learn Mathematics

Authors: M. Rodionov, Z. Dedovets

Abstract:

This article discusses plausible reasoning use for solution to practical problems. Such reasoning is the major driver of motivation and implementation of mathematical, scientific and educational research activity. A general, practical problem solving algorithm is presented which includes an analysis of specific problem content to build, solve and interpret the underlying mathematical model. The author explores the role of practical problems such as the stimulation of students' interest, the development of their world outlook and their orientation in the modern world at the different stages of learning mathematics in secondary school. Particular attention is paid to the characteristics of those problems which were systematized and presented in the conclusions.

Keywords: Mathematics, motivation, secondary school, student, practical problem.

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2668 A Study on Removal of Toluidine Blue Dye from Aqueous Solution by Adsorption onto Neem Leaf Powder

Authors: Himanshu Patel, R. T. Vashi

Abstract:

Adsorption of Toluidine blue dye from aqueous solutions onto Neem Leaf Powder (NLP) has been investigated. The surface characterization of this natural material was examined by Particle size analysis, Scanning Electron Microscopy (SEM), Fourier Transform Infrared (FTIR) spectroscopy and X-Ray Diffraction (XRD). The effects of process parameters such as initial concentration, pH, temperature and contact duration on the adsorption capacities have been evaluated, in which pH has been found to be most effective parameter among all. The data were analyzed using the Langmuir and Freundlich for explaining the equilibrium characteristics of adsorption. And kinetic models like pseudo first- order, second-order model and Elovich equation were utilized to describe the kinetic data. The experimental data were well fitted with Langmuir adsorption isotherm model and pseudo second order kinetic model. The thermodynamic parameters, such as Free energy of adsorption (AG"), enthalpy change (AH') and entropy change (AS°) were also determined and evaluated.

Keywords: Adsorption, isotherm models, kinetic models, temperature, toluidine blue dye, surface chemistry.

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2667 Validation of Reverse Engineered Web Application Models

Authors: Carlo Bellettini, Alessandro Marchetto, Andrea Trentini

Abstract:

Web applications have become complex and crucial for many firms, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering). The scientific community has focused attention to Web application design, development, analysis, testing, by studying and proposing methodologies and tools. Static and dynamic techniques may be used to analyze existing Web applications. The use of traditional static source code analysis may be very difficult, for the presence of dynamically generated code, and for the multi-language nature of the Web. Dynamic analysis may be useful, but it has an intrinsic limitation, the low number of program executions used to extract information. Our reverse engineering analysis, used into our WAAT (Web Applications Analysis and Testing) project, applies mutational techniques in order to exploit server side execution engines to accomplish part of the dynamic analysis. This paper studies the effects of mutation source code analysis applied to Web software to build application models. Mutation-based generated models may contain more information then necessary, so we need a pruning mechanism.

Keywords: Validation, Dynamic Analysis, MutationAnalysis, Reverse Engineering, Web Applications

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2666 Swine Flu Transmission Model in Risk and Non-Risk Human Population

Authors: P. Pongsumpun

Abstract:

The Swine flu outbreak in humans is due to a new strain of influenza A virus subtype H1N1 that derives in part from human influenza, avian influenza, and two separated strains of swine influenza. It can be transmitted from human to human. A mathematical model for the transmission of Swine flu is developed in which the human populations are divided into two classes, the risk and non-risk human classes. Each class is separated into susceptible, exposed, infectious, quarantine and recovered sub-classes. In this paper, we formulate the dynamical model of Swine flu transmission and the repetitive contacts between the people are also considered. We analyze the behavior for the transmission of this disease. The Threshold condition of this disease is found and numerical results are shown to confirm our theoretical predictions.

Keywords: Mathematical model, Steady state, Swine flu, threshold condition.

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2665 Building a Service-Centric Business Model in SMEs in the Business-to-Business Context

Authors: Päivi J. Tossavainen , Leena Alakoski, Katri Ojasalo

Abstract:

Building a service-centric business model requires new knowledge and capabilities in companies. This paper enlightens the challenges small and medium sized firms (SMEs) face when developing their service-centric business models. This paper examines the premise for knowledge transfer and capability development required. The objective of this paper is to increase knowledge about SME-s transformation to service-centric business models.This paper reports an action research based case study. The paper provides empirical evidence from three case companies. The empirical data was collected through multiple methods. The findings of the paper are: First, the developed model to analyze the current state in companies. Second, the process of building the service – centric business models. Third, the selection of suitable service development methods. The lack of a holistic understanding on service logic suggests that SMEs need practical and easy to use methods to improve their business

Keywords: service-centric business model, service development, action research, case study

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