Search results for: Deterioration modeling
1641 Using Structural Equation Modeling in Causal Relationship Design for Balanced-Scorecards' Strategic Map
Authors: A. Saghaei, R. Ghasemi
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Through 1980s, management accounting researchers described the increasing irrelevance of traditional control and performance measurement systems. The Balanced Scorecard (BSC) is a critical business tool for a lot of organizations. It is a performance measurement system which translates mission and strategy into objectives. Strategy map approach is a development variant of BSC in which some necessary causal relations must be established. To recognize these relations, experts usually use experience. It is also possible to utilize regression for the same purpose. Structural Equation Modeling (SEM), which is one of the most powerful methods of multivariate data analysis, obtains more appropriate results than traditional methods such as regression. In the present paper, we propose SEM for the first time to identify the relations between objectives in the strategy map, and a test to measure the importance of relations. In SEM, factor analysis and test of hypotheses are done in the same analysis. SEM is known to be better than other techniques at supporting analysis and reporting. Our approach provides a framework which permits the experts to design the strategy map by applying a comprehensive and scientific method together with their experience. Therefore this scheme is a more reliable method in comparison with the previously established methods.Keywords: BSC, SEM, Strategy map.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26931640 Modeling of Oxygen Supply Profiles in Stirred-Tank Aggregated Stem Cells Cultivation Process
Authors: Vytautas Galvanauskas, Vykantas Grincas, Rimvydas Simutis
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This paper investigates a possible practical solution for reasonable oxygen supply during the pluripotent stem cells expansion processes, where the stem cells propagate as aggregates in stirred-suspension bioreactors. Low glucose and low oxygen concentrations are preferred for efficient proliferation of pluripotent stem cells. However, strong oxygen limitation, especially inside of cell aggregates, can lead to cell starvation and death. In this research, the oxygen concentration profile inside of stem cell aggregates in a stem cell expansion process was predicted using a modified oxygen diffusion model. This profile can be realized during the stem cells cultivation process by manipulating the oxygen concentration in inlet gas or inlet gas flow. The proposed approach is relatively simple and may be attractive for installation in a real pluripotent stem cell expansion processes.Keywords: Aggregated stem cells, dissolved oxygen profiles, modeling, stirred-tank, 3D expansion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18521639 A Study of Various Numerical Turbulence Modeling Methods in Boundary Layer Excitation of a Square Ribbed Channel
Authors: Hojjat Saberinejad, Adel Hashiehbaf, Ehsan Afrasiabian
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Among the various cooling processes in industrial applications such as: electronic devices, heat exchangers, gas turbines, etc. Gas turbine blades cooling is the most challenging one. One of the most common practices is using ribbed wall because of the boundary layer excitation and therefore making the ultimate cooling. Vortex formation between rib and channel wall will result in a complicated behavior of flow regime. At the other hand, selecting the most efficient method for capturing the best results comparing to experimental works would be a fascinating issue. In this paper 4 common methods in turbulence modeling: standard k-e, rationalized k-e with enhanced wall boundary layer treatment, k-w and RSM (Reynolds stress model) are employed to a square ribbed channel to investigate the separation and thermal behavior of the flow in the channel. Finally all results from different methods which are used in this paper will be compared with experimental data available in literature to ensure the numerical method accuracy.Keywords: boundary layer, turbulence, numerical method, rib cooling
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16801638 The Effect of Nose Radius on Cutting Force and Temperature during Machining Titanium Alloy (Ti-6Al-4V)
Authors: Moaz H. Ali, M. N. M. Ansari
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This paper presents a study the effect of nose radius (Rz-mm) on cutting force components and temperatures during the machining simulation in an orthogonal cutting process for titanium alloy (Ti-6Al-4V). The cutting process was performed at various nose radiuses (Rz-mm) while the depth of cut (d-mm), feed rate (fmm/ tooth) and cutting speed (vc-m/ min) were remained constant. The main cutting force (Fc), feed cutting force (Ft) and temperatures were estimated by using finite element modeling (FEM) through ABAQUS/EXPLICIT software and the simulation was developed the two-dimension via an orthogonal cutting process during machining titanium alloy (Ti-6Al-4V). The results led to the conclusion that the nose radius (Rz-mm) has affected directly on the cutting force components. However, temperature gave no indication or has no significant relation with nose radius during machining titanium alloy (Ti-6Al-4V). Hence, any increase or decrease in the nose radius (Rzmm) during machining operation led to effect on the cutting forces and thus it will be effective on surface finish, quality, and quantity of products.
Keywords: Finite element modeling (FEM), nose radius, cutting force, temperature, titanium alloy (Ti-6Al-4V).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29981637 Optimal Maintenance and Improvement Policies in Water Distribution System: Markov Decision Process Approach
Authors: Jong Woo Kim, Go Bong Choi, Sang Hwan Son, Dae Shik Kim, Jung Chul Suh, Jong Min Lee
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The Markov decision process (MDP) based methodology is implemented in order to establish the optimal schedule which minimizes the cost. Formulation of MDP problem is presented using the information about the current state of pipe, improvement cost, failure cost and pipe deterioration model. The objective function and detailed algorithm of dynamic programming (DP) are modified due to the difficulty of implementing the conventional DP approaches. The optimal schedule derived from suggested model is compared to several policies via Monte Carlo simulation. Validity of the solution and improvement in computational time are proved.
Keywords: Markov decision processes, Dynamic Programming, Monte Carlo simulation, Periodic replacement, Weibull distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28031636 Influence of IMV on Space Station
Authors: Fu Shiming, Pei Yifei
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To study the impact of the inter-module ventilation (IMV) on the space station, the Computational Fluid Dynamic (CFD) model under the influence of IMV, the mathematical model, boundary conditions and calculation method are established and determined to analyze the influence of IMV on cabin air flow characteristics and velocity distribution firstly; and then an integrated overall thermal mathematical model of the space station is used to consider the impact of IMV on thermal management. The results show that: the IMV has a significant influence on the cabin air flow, the flowrate of IMV within a certain range can effectively improve the air velocity distribution in cabin, if too much may lead to its deterioration; IMV can affect the heat deployment of the different modules in space station, thus affecting its thermal management, the use of IMV can effectively maintain the temperature levels of the different modules and help the space station to dissipate the waste heat.
Keywords: CFD, Environment control and life support, Space station, Thermal management, Thermal mathematical model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20381635 The Impact of Gamification on Self-Assessment for English Language Learners in Saudi Arabia
Authors: Wala A. Bagunaid, Maram Meccawy, Arwa Allinjawi, Zilal Meccawy
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Continuous self-assessment becomes crucial in self-paced online learning environments. Students often depend on themselves to assess their progress; which is considered an essential requirement for any successful learning process. Today’s education institutions face major problems around student motivation and engagement. Thus, personalized e-learning systems aim to help and guide the students. Gamification provides an opportunity to help students for self-assessment and social comparison with other students through attempting to harness the motivational power of games and apply it to the learning environment. Furthermore, Open Social Student Modeling (OSSM) as considered as the latest user modeling technologies is believed to improve students’ self-assessment and to allow them to social comparison with other students. This research integrates OSSM approach and gamification concepts in order to provide self-assessment for English language learners at King Abdulaziz University (KAU). This is achieved through an interactive visual representation of their learning progress.Keywords: E-learning system, gamification, motivation, social comparison, visualization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14881634 Business-Intelligence Mining of Large Decentralized Multimedia Datasets with a Distributed Multi-Agent System
Authors: Karima Qayumi, Alex Norta
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The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.
Keywords: Agent-oriented modeling, business Intelligence management, distributed data mining, multi-agent system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13641633 Modeling and Simulation of Utility Interfaced PV/Hydro Hybrid Electric Power System
Authors: P. V. V. Rama Rao, B. Kali Prasanna, Y. T. R. Palleswari
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Renewable energy is derived from natural processes that are replenished constantly. Included in the definition is electricity and heat generated from solar, wind, ocean, hydropower, biomass, geothermal resources, and bio-fuels and hydrogen derived from renewable resources. Each of these sources has unique characteristics which influence how and where they are used. This paper presents the modeling the simulation of solar and hydro hybrid energy sources in MATLAB/SIMULINK environment. It simulates all quantities of Hybrid Electrical Power system (HEPS) such as AC output current of the inverter that injected to the load/grid, load current, grid current. It also simulates power output from PV and Hydraulic Turbine Generator (HTG), power delivered to or from grid and finally power factor of the inverter for PV, HTG and grid. The proposed circuit uses instantaneous p-q (real-imaginary) power theory.
Keywords: Photovoltaic Array, Hydraulic Turbine Generator, Electrical Utility (EU), Hybrid Electrical Power Supply.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34791632 An Extended Domain-Specific Modeling Language for Marine Observatory Relying on Enterprise Architecture
Authors: Charbel Geryes Aoun, Loic Lagadec
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A Sensor Network (SN) is considered as an operation of two phases: (1) the observation/measuring, which means the accumulation of the gathered data at each sensor node; (2) transferring the collected data to some processing center (e.g. Fusion Servers) within the SN. Therefore, an underwater sensor network can be defined as a sensor network deployed underwater that monitors underwater activity. The deployed sensors, such as hydrophones, are responsible for registering underwater activity and transferring it to more advanced components. The process of data exchange between the aforementioned components perfectly defines the Marine Observatory (MO) concept which provides information on ocean state, phenomena and processes. The first step towards the implementation of this concept is defining the environmental constraints and the required tools and components (Marine Cables, Smart Sensors, Data Fusion Server, etc). The logical and physical components that are used in these observatories perform some critical functions such as the localization of underwater moving objects. These functions can be orchestrated with other services (e.g. military or civilian reaction). In this paper, we present an extension to our MO meta-model that is used to generate a design tool (ArchiMO). We propose constraints to be taken into consideration at design time. We illustrate our proposal with an example from the MO domain. Additionally, we generate the corresponding simulation code using our self-developed domain-specific model compiler. On the one hand, this illustrates our approach in relying on Enterprise Architecture (EA) framework that respects: multiple-views, perspectives of stakeholders, and domain specificity. On the other hand, it helps reducing both complexity and time spent in design activity, while preventing from design modeling errors during porting this activity in the MO domain. As conclusion, this work aims to demonstrate that we can improve the design activity of complex system based on the use of MDE technologies and a domain-specific modeling language with the associated tooling. The major improvement is to provide an early validation step via models and simulation approach to consolidate the system design.
Keywords: Smart sensors, data fusion, distributed fusion architecture, sensor networks, domain specific modeling language, enterprise architecture, underwater moving object, localization, marine observatory, NS-3, IMS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2061631 Hydrodynamic Modeling of Infinite Reservoir using Finite Element Method
Authors: M. A. Ghorbani, M. Pasbani Khiavi
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In this paper, the dam-reservoir interaction is analyzed using a finite element approach. The fluid is assumed to be incompressible, irrotational and inviscid. The assumed boundary conditions are that the interface of the dam and reservoir is vertical and the bottom of reservoir is rigid and horizontal. The governing equation for these boundary conditions is implemented in the developed finite element code considering the horizontal and vertical earthquake components. The weighted residual standard Galerkin finite element technique with 8-node elements is used to discretize the equation that produces a symmetric matrix equation for the damreservoir system. A new boundary condition is proposed for truncating surface of unbounded fluid domain to show the energy dissipation in the reservoir, through radiation in the infinite upstream direction. The Sommerfeld-s and perfect damping boundary conditions are also implemented for a truncated boundary to compare with the proposed far end boundary. The results are compared with an analytical solution to demonstrate the accuracy of the proposed formulation and other truncated boundary conditions in modeling the hydrodynamic response of an infinite reservoir.Keywords: Reservoir, finite element, truncated boundary, hydrodynamic pressure
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22971630 Forecasting Electricity Spot Price with Generalized Long Memory Modeling: Wavelet and Neural Network
Authors: Souhir Ben Amor, Heni Boubaker, Lotfi Belkacem
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This aims of this paper is to forecast the electricity spot prices. First, we focus on modeling the conditional mean of the series so we adopt a generalized fractional -factor Gegenbauer process (k-factor GARMA). Secondly, the residual from the -factor GARMA model has used as a proxy for the conditional variance; these residuals were predicted using two different approaches. In the first approach, a local linear wavelet neural network model (LLWNN) has developed to predict the conditional variance using the Back Propagation learning algorithms. In the second approach, the Gegenbauer generalized autoregressive conditional heteroscedasticity process (G-GARCH) has adopted, and the parameters of the k-factor GARMA-G-GARCH model has estimated using the wavelet methodology based on the discrete wavelet packet transform (DWPT) approach. The empirical results have shown that the k-factor GARMA-G-GARCH model outperform the hybrid k-factor GARMA-LLWNN model, and find it is more appropriate for forecasts.Keywords: k-factor, GARMA, LLWNN, G-GARCH, electricity price, forecasting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9781629 Modeling and Investigation of Volume Strain at Large Deformation under Uniaxial Cyclic Loading in Semi Crystalline Polymer
Authors: Rida B. Arieby
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This study deals with the experimental investigation and theoretical modeling of Semi crystalline polymeric materials with a rubbery amorphous phase (HDPE) subjected to a uniaxial cyclic tests with various maximum strain levels, even at large deformation. Each cycle is loaded in tension up to certain maximum strain and then unloaded down to zero stress with N number of cycles. This work is focuses on the measure of the volume strain due to the phenomena of damage during this kind of tests. On the basis of thermodynamics of relaxation processes, a constitutive model for large strain deformation has been developed, taking into account the damage effect, to predict the complex elasto-viscoelastic-viscoplastic behavior of material. A direct comparison between the model predictions and the experimental data show that the model accurately captures the material response. The model is also capable of predicting the influence damage causing volume variation.Keywords: Cyclic test, large strain, polymers semi-crystalline, Volume strain, Thermodynamics of Irreversible Processes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22951628 Numerical Modeling of Flow in USBR II Stilling Basin with End Adverse Slope
Authors: Hamidreza Babaali, Alireza Mojtahedi, Nasim Soori, Saba Soori
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Hydraulic jump is one of the effective ways of energy dissipation in stilling basins that the energy is highly dissipated by jumping. Adverse slope surface at the end stilling basin is caused to increase energy dissipation and stability of the hydraulic jump. In this study, the adverse slope has been added to end of United States Bureau of Reclamation (USBR) II stilling basin in hydraulic model of Nazloochay dam with scale 1:40, and flow simulated into stilling basin using Flow-3D software. The numerical model is verified by experimental data of water depth in stilling basin. Then, the parameters of water level profile, Froude Number, pressure, air entrainment and turbulent dissipation investigated for discharging 300 m3/s using K-Ɛ and Re-Normalization Group (RNG) turbulence models. The results showed a good agreement between numerical and experimental model as numerical model can be used to optimize of stilling basins.
Keywords: Experimental and numerical modeling, end adverse slope, flow parameters, USBR II Stilling Basin.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9681627 PM10 Prediction and Forecasting Using CART: A Case Study for Pleven, Bulgaria
Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova
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Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.Keywords: Cross-validation, decision tree, lagged variables, short-term forecasting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7111626 Evaluation of the ANN Based Nonlinear System Models in the MSE and CRLB Senses
Authors: M.V Rajesh, Archana R, A Unnikrishnan, R Gopikakumari, Jeevamma Jacob
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The System Identification problem looks for a suitably parameterized model, representing a given process. The parameters of the model are adjusted to optimize a performance function based on error between the given process output and identified process output. The linear system identification field is well established with many classical approaches whereas most of those methods cannot be applied for nonlinear systems. The problem becomes tougher if the system is completely unknown with only the output time series is available. It has been reported that the capability of Artificial Neural Network to approximate all linear and nonlinear input-output maps makes it predominantly suitable for the identification of nonlinear systems, where only the output time series is available. [1][2][4][5]. The work reported here is an attempt to implement few of the well known algorithms in the context of modeling of nonlinear systems, and to make a performance comparison to establish the relative merits and demerits.Keywords: Multilayer neural networks, Radial Basis Functions, Clustering algorithm, Back Propagation training, Extended Kalmanfiltering, Mean Square Error, Nonlinear Modeling, Cramer RaoLower Bound.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16351625 2D-Modeling with Lego Mindstorms
Authors: Miroslav Popelka, Jakub Nožička
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The whole work is based on possibility to use Lego Mindstorms robotics systems to reduce costs. Lego Mindstorms consists of a wide variety of hardware components necessary to simulate, programme and test of robotics systems in practice. To programme algorithm, which simulates space using the ultrasonic sensor, was used development environment supplied with kit. Software Matlab was used to render values afterwards they were measured by ultrasonic sensor. The algorithm created for this paper uses theoretical knowledge from area of signal processing. Data being processed by algorithm are collected by ultrasonic sensor that scans 2D space in front of it. Ultrasonic sensor is placed on moving arm of robot which provides horizontal moving of sensor. Vertical movement of sensor is provided by wheel drive. The robot follows map in order to get correct positioning of measured data. Based on discovered facts it is possible to consider Lego Mindstorm for low-cost and capable kit for real-time modelling.
Keywords: LEGO Mindstorms, ultrasonic sensor, Real-time modeling, 2D object, low-cost robotics systems, sensors, Matlab, EV3 Home Edition Software.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30931624 Study on the Variation Effects of Diverging Angleon Characteristics of Flow in Converging and Diverging Ducts by Numerical Method
Authors: Moghiman Mohammad, Amiri Maryam, Amiri Amirhosein
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The present paper develops and validates a numerical procedure for the calculation of turbulent combustive flow in converging and diverging ducts and throuh simulation of the heat transfer processes, the amount of production and spread of Nox pollutant has been measured. A marching integration solution procedure employing the TDMA is used to solve the discretized equations. The turbulence model is the Prandtl Mixing Length method. Modeling the combustion process is done by the use of Arrhenius and Eddy Dissipation method. Thermal mechanism has been utilized for modeling the process of forming the nitrogen oxides. Finite difference method and Genmix numerical code are used for numerical solution of equations. Our results indicate the important influence of the limiting diverging angle of diffuser on the coefficient of recovering of pressure. Moreover, due to the intense dependence of Nox pollutant to the maximum temperature in the domain with this feature, the Nox pollutant amount is also in maximum level.
Keywords: Converging and Diverging Duct, Combustion, Diffuser, Diverging Angle, Nox
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15251623 Application of Feed Forward Neural Networks in Modeling and Control of a Fed-Batch Crystallization Process
Authors: Petia Georgieva, Sebastião Feyo de Azevedo
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This paper is focused on issues of nonlinear dynamic process modeling and model-based predictive control of a fed-batch sugar crystallization process applying the concept of artificial neural networks as computational tools. The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. A feed forward neural network (FFNN) model of the process is first built as part of the controller structure to predict the process response over a specified (prediction) horizon. The predictions are supplied to an optimization procedure to determine the values of the control action over a specified (control) horizon that minimizes a predefined performance index. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. However, the simulation results demonstrated smooth behavior of the control actions and satisfactory reference tracking.
Keywords: Feed forward neural network, process modelling, model predictive control, crystallization process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18591622 Kinematic Parameter-Independent Modeling and Measuring of Three-Axis Machine Tools
Authors: Yung-Yuan Hsu
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The primary objective of this paper was to construct a “kinematic parameter-independent modeling of three-axis machine tools for geometric error measurement" technique. Improving the accuracy of the geometric error for three-axis machine tools is one of the machine tools- core techniques. This paper first applied the traditional method of HTM to deduce the geometric error model for three-axis machine tools. This geometric error model was related to the three-axis kinematic parameters where the overall errors was relative to the machine reference coordinate system. Given that the measurement of the linear axis in this model should be on the ideal motion axis, there were practical difficulties. Through a measurement method consolidating translational errors and rotational errors in the geometric error model, we simplified the three-axis geometric error model to a kinematic parameter-independent model. Finally, based on the new measurement method corresponding to this error model, we established a truly practical and more accurate error measuring technique for three-axis machine tools.Keywords: Three-axis machine tool, Geometric error, HTM, Error measuring
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21131621 Development of a Multi-Factorial Instrument for Accident Analysis Based on Systemic Methods
Authors: C. V. Pietreanu, S. E. Zaharia, C. Dinu
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The present research is built on three major pillars, commencing by making some considerations on accident investigation methods and pointing out both defining aspects and differences between linear and non-linear analysis. The traditional linear focus on accident analysis describes accidents as a sequence of events, while the latest systemic models outline interdependencies between different factors and define the processes evolution related to a specific (normal) situation. Linear and non-linear accident analysis methods have specific limitations, so the second point of interest is mirrored by the aim to discover the drawbacks of systemic models which becomes a starting point for developing new directions to identify risks or data closer to the cause of incidents/accidents. Since communication represents a critical issue in the interaction of human factor and has been proved to be the answer of the problems made by possible breakdowns in different communication procedures, from this focus point, on the third pylon a new error-modeling instrument suitable for risk assessment/accident analysis will be elaborated.
Keywords: Accident analysis, multi-factorial error modeling, risk, systemic methods.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10221620 Modeling Brand Alliance Effects Professional Services
Authors: Kristina Maiksteniene
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Various formal and informal brand alliances are being formed in professional service firms. Professional service corporate brand is heavily dependent on brands of professional employees who comprise them, and professional employee brands are in turn dependent on the corporate brand. Prior work provides limited scientific evidence of brand alliance effects in professional service area – i.e., how professional service corporate-employee brand allies are affected by an alliance, what are brand attitude effects after alliance formation and how these effects vary with different strengths of an ally. Scientific literature analysis and theoretical modeling are the main methods of the current study. As a result, a theoretical model is constructed for estimating spillover effects of professional service corporate-employee brand alliances and for comparison among different professional service firm expertise practice models – from “brains" to “procedure" model. The resulting theoretical model lays basis for future experimental studies.
Keywords: Brand alliances, professional services, corporatebrand, employee brand.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17471619 Ageing Deterioration of Hi gh-Density Polyethylene Cable Spacer under Salt Water Dip Wheel Test
Authors: P. Kaewchanthuek, R. Rawonghad, B. Marungsri
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This paper presents the experimental results of high-density polyethylene cable spacers for 22 kV distribution systems under salt water dip wheel test based on IEC 62217. The strength of anti-tracking and anti-erosion of cable spacer surface was studied in this study. During the test, dry band arc and corona discharge were observed on cable spacer surface. After 30,000 cycles of salt water dip wheel test, obviously surface erosion and tracking were observed especially on the ground end. Chemical analysis results by fourier transforms infrared spectroscopy showed chemical changed from oxidation and carbonization reaction on tested cable spacer. Increasing of C=O and C=C bonds confirmed occurrence of these reactions.
Keywords: Cable spacer, HDPE, ageing of cable spacer, salt water dip wheel test.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31851618 Identification of Regulatory Mechanism of Orthostatic Response
Authors: E. Hlavacova, J. Chrenova, Z. Rausova, M. Vlcek, A. Penesova, L. Dedik
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En bloc assumes modeling all phases of the orthostatic test with the only one mathematical model, which allows the complex parametric view of orthostatic response. The work presents the implementation of a mathematical model for processing of the measurements of systolic, diastolic blood pressure and heart rate performed on volunteers during orthostatic test. The original assumption of model hypothesis that every postural change means only one Stressor, did not complying with the measurements of physiological circulation factor-time profiles. Results of the identification support the hypothesis that second postural change of orthostatic test causes induced Stressors, with the observation of a physiological regulation mechanism. Maximal demonstrations are on the heart rate and diastolic blood pressure-time profile, minimal are for the measurements of the systolic blood pressure. Presented study gives a new view on orthostatic test with impact on clinical practice.
Keywords: En bloc modeling, physiological circulatory factor, postural change, stressor
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14181617 Finite Element Modeling of two-dimensional Nanoscale Structures with Surface Effects
Authors: Weifeng Wang, Xianwei Zeng, Jianping Ding
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Nanomaterials have attracted considerable attention during the last two decades, due to their unusual electrical, mechanical and other physical properties as compared with their bulky counterparts. The mechanical properties of nanostructured materials show strong size dependency, which has been explained within the framework of continuum mechanics by including the effects of surface stress. The size-dependent deformations of two-dimensional nanosized structures with surface effects are investigated in the paper by the finite element method. Truss element is used to evaluate the contribution of surface stress to the total potential energy and the Gurtin and Murdoch surface stress model is implemented with ANSYS through its user programmable features. The proposed approach is used to investigate size-dependent stress concentration around a nanosized circular hole and the size-dependent effective moduli of nanoporous materials. Numerical results are compared with available analytical results to validate the proposed modeling approach.Keywords: Nanomaterials, finite element method, sizedependency, surface stress
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27651616 Development of Autonomous Cable Inspection Robot for Nuclear Power Plant
Authors: Jae-Kyung LEE, Byung-Hak CHO, Kyung-Nam Jang, Sun-Chul Jung, Ki-Yong OH, Joon-Young PARK, Jong-Seog Kim
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The cables in a nuclear power plant are designed to be used for about 40 years in safe operation environment. However, the heat and radiation in the nuclear power plant causes the rapid performance deterioration of cables in nuclear vessels and heat exchangers, which requires cable lifetime estimation. The most accurate method of estimating the cable lifetime is to evaluate the cables in a laboratory. However, removing cables while the plant is operating is not allowed because of its safety and cost. In this paper, a robot system to estimate the cable lifetime in nuclear power plants is developed and tested. The developed robot system can calculate a modulus value to estimate the cable lifetime even when the nuclear power plant is in operation.Keywords: Autonomous robot, Cable Inspection, Indenter, Nuclear Power Plant
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19941615 The Mechanistic Deconvolutive Image Sensor Model for an Arbitrary Pan–Tilt Plane of View
Authors: S. H. Lim, T. Furukawa
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This paper presents a generalized form of the mechanistic deconvolution technique (GMD) to modeling image sensors applicable in various pan–tilt planes of view. The mechanistic deconvolution technique (UMD) is modified with the given angles of a pan–tilt plane of view to formulate constraint parameters and characterize distortion effects, and thereby, determine the corrected image data. This, as a result, does not require experimental setup or calibration. Due to the mechanistic nature of the sensor model, the necessity for the sensor image plane to be orthogonal to its z-axis is eliminated, and it reduces the dependency on image data. An experiment was constructed to evaluate the accuracy of a model created by GMD and its insensitivity to changes in sensor properties and in pan and tilt angles. This was compared with a pre-calibrated model and a model created by UMD using two sensors with different specifications. It achieved similar accuracy with one-seventh the number of iterations and attained lower mean error by a factor of 2.4 when compared to the pre-calibrated and UMD model respectively. The model has also shown itself to be robust and, in comparison to pre-calibrated and UMD model, improved the accuracy significantly.Keywords: Image sensor modeling, mechanistic deconvolution, calibration, lens distortion
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15131614 Improved Predictive Models for the IRMA Network Using Nonlinear Optimisation
Authors: Vishwesh Kulkarni, Nikhil Bellarykar
Abstract:
Cellular complexity stems from the interactions among thousands of different molecular species. Thanks to the emerging fields of systems and synthetic biology, scientists are beginning to unravel these regulatory, signaling, and metabolic interactions and to understand their coordinated action. Reverse engineering of biological networks has has several benefits but a poor quality of data combined with the difficulty in reproducing it limits the applicability of these methods. A few years back, many of the commonly used predictive algorithms were tested on a network constructed in the yeast Saccharomyces cerevisiae (S. cerevisiae) to resolve this issue. The network was a synthetic network of five genes regulating each other for the so-called in vivo reverse-engineering and modeling assessment (IRMA). The network was constructed in S. cereviase since it is a simple and well characterized organism. The synthetic network included a variety of regulatory interactions, thus capturing the behaviour of larger eukaryotic gene networks on a smaller scale. We derive a new set of algorithms by solving a nonlinear optimization problem and show how these algorithms outperform other algorithms on these datasets.Keywords: Synthetic gene network, network identification, nonlinear modeling, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7791613 System-Level Energy Estimation for SoC based on the Dynamic Behavior of Embedded Software
Authors: Yoshifumi Sakamoto, Kouichi Ono, Takeo Nakada, Yousuke Kubo, Hiroto Yasuura
Abstract:
This paper describes a system-level SoC energy consumption estimation method based on a dynamic behavior of embedded software in the early stages of the SoC development. A major problem of SOC development is development rework caused by unreliable energy consumption estimation at the early stages. The energy consumption of an SoC used in embedded systems is strongly affected by the dynamic behavior of the software. At the early stages of SoC development, modeling with a high level of abstraction is required for both the dynamic behavior of the software, and the behavior of the SoC. We estimate the energy consumption by a UML model-based simulation. The proposed method is applied for an actual embedded system in an MFP. The energy consumption estimation of the SoC is more accurate than conventional methods and this proposed method is promising to reduce the chance of development rework in the SoC development. ∈Keywords: SoC, Embedded Sytem, Energy Consumption, Dynamic behavior, UML, Modeling, Model-based simulation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24401612 Understanding Physical Activity Behavior of Type 2 Diabetics Using the Theory of Planned Behavior and Structural Equation Modeling
Authors: D. O. Omondi, M. K. Walingo, G. M. Mbagaya, L. O. A. Othuon
Abstract:
Understanding patient factors related to physical activity behavior is important in the management of Type 2 Diabetes. This study applied the Theory of Planned Behavior model to understand physical activity behavior among sampled Type 2 diabetics in Kenya. The study was conducted within the diabetic clinic at Kisii Level 5 Hospital and adopted sequential mixed methods design beginning with qualitative phase and ending with quantitative phase. Qualitative data was analyzed using grounded theory analysis method. Structural equation modeling using maximum likelihood was used to analyze quantitative data. The common fit indices revealed that the theory of planned behavior fitted the data acceptably well among the Type 2 diabetes and within physical activity behavior {¤ç2 = 213, df = 84, n=230, p = .061, ¤ç2/df = 2.53; TLI = .97; CFI =.96; RMSEA (90CI) = .073(.029, .08)}. This theory proved to be useful in understanding physical activity behavior among Type 2 diabetics.
Keywords: Physical activity, Theory of Planned Behavior, Type2 diabetes, Kenya.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1970