Search results for: equivalent model
13461 Computational Experiment on Evolution of E-Business Service Ecosystem
Authors: Xue Xiao, Sun Hao, Liu Donghua
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E-commerce is experiencing rapid development and evolution, but traditional research methods are difficult to fully demonstrate the relationship between micro factors and macro evolution in the development process of e-commerce, which cannot provide accurate assessment for the existing strategies and predict the future evolution trends. To solve these problems, this paper presents the concept of e-commerce service ecosystem based on the characteristics of e-commerce and business ecosystem theory, describes e-commerce environment as a complex adaptive system from the perspective of ecology, constructs a e-commerce service ecosystem model by using Agent-based modeling method and Java language in RePast simulation platform and conduct experiment through the way of computational experiment, attempt to provide a suitable and effective researching method for the research on e-commerce evolution. By two experiments, it can be found that system model built in this paper is able to show the evolution process of e-commerce service ecosystem and the relationship between micro factors and macro emergence. Therefore, the system model constructed by Agent-based method and computational experiment provides proper means to study the evolution of e-commerce ecosystem.Keywords: e-commerce service ecosystem, complex system, agent-based modeling, computational experiment
Procedia PDF Downloads 35713460 Modeling and Simulation for Infection Processes of Bird Flu within a Poultry Farm
Authors: Tertia Delia Nova, Masaji Watanabge
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Infection of bird flu within a poultry farm involves hosts, virus, and medium. Intrusion of bird flu into a poultry farm divides the population into two groups; healthy and susceptible chickens and infected chickens. A healthy and susceptible bird is infected to become an infected bird. Bird flu viruses spread among chickens through medium such as air and droppings, and increase in hosts. A model for an infection process of bird flu within a poultry farm is described, numerical techniques are illustrated, and numerical results are introduced.Keywords: bird flu, poultry farm, model for an infection process, flu viruses
Procedia PDF Downloads 25413459 The Pyrolysis of Leather and Textile Waste in Carbonised Materials as an Element of the Circular Economy Model
Authors: Anna Kowalik-Klimczak, Maciej żYcki, Monika łOżYńska, Wioletta Barszcz, Jolanta Drabik
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The rapidly changing fashion trends generate huge amounts of leather and textile waste globally. The complexity of these types of waste makes recycling difficult in economic terms. Pyrolysis is suggested for this purpose, which transforms heterogeneous and complex waste into added-value products e.g. active carbons and soil fertilizer. The possibility of using pyrolysis for the valorization of leather and textile waste has been analyzed in this paper. In the first stage, leather and textile waste were subjected to TG/DTG thermogravimetric and DSC calorimetric analysis. These analyses provided basic information about thermochemical transformations and degradation rates during the pyrolysis of these types of waste and enabled the selection of the pyrolysis temperature. In the next stage, the effect of gas type using pyrolysis was investigated on the physicochemical properties, composition, structure, and formation of the specific surfaces of carbonized materials produced by means of a thermal treatment without oxygen access to the reaction chamber. These studies contribute some data about the thermal management and pyrolytic processing of leather and textile waste into useful carbonized materials, according to the circular economy model.Keywords: pyrolysis, leather and textiles waste, composition and structure of carbonized materials, valorisation of waste, circular economy model
Procedia PDF Downloads 513458 Development of PSS/E Dynamic Model for Controlling Battery Output to Improve Frequency Stability in Power Systems
Authors: Dae-Hee Son, Soon-Ryul Nam
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The power system frequency falls when disturbance such as rapid increase of system load or loss of a generating unit occurs in power systems. Especially, increase in the number of renewable generating units has a bad influence on the power system because of loss of generating unit depending on the circumstance. Conventional technologies use frequency droop control battery output for the frequency regulation and balance between supply and demand. If power is supplied using the fast output characteristic of the battery, power system stability can be further more improved. To improve the power system stability, we propose battery output control using ROCOF (Rate of Change of Frequency) in this paper. The bigger the power difference between the supply and the demand, the bigger the ROCOF drops. Battery output is controlled proportionally to the magnitude of the ROCOF, allowing for faster response to power imbalances. To simulate the control method of battery output system, we develop the user defined model using PSS/E and confirm that power system stability is improved by comparing with frequency droop control.Keywords: PSS/E user defined model, power deviation, frequency droop control, ROCOF (rate of change of frequency)
Procedia PDF Downloads 40813457 Uranium Adsorption Using a Composite Material Based on Platelet SBA-15 Supported Tin Salt Tungstomolybdophosphoric Acid
Authors: H. Aghayan, F. A. Hashemi, R. Yavari, S. Zolghadri
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In this work, a new composite adsorbent based on a mesoporous silica SBA-15 with platelet morphology and tin salt of tungstomolybdophosphoric (TWMP) acid was synthesized and applied for uranium adsorption from aqueous solution. The sample was characterized by X-ray diffraction, Fourier transfer infra-red, and N2 adsorption-desorption analysis, and then, effect of various parameters such as concentration of metal ions and contact time on adsorption behavior was examined. The experimental result showed that the adsorption process was explained by the Langmuir isotherm model very well, and predominant reaction mechanism is physisorption. Kinetic data of adsorption suggest that the adsorption process can be described by the pseudo second-order reaction rate model.Keywords: platelet SBA-15, tungstomolybdophosphoric acid, adsorption, uranium ion
Procedia PDF Downloads 18513456 Investigation of Dry Ice Mixed Novel Hybrid Lubri-Coolant in Sustainable Machining of Ti-6AL-4V Alloy: A Comparison of Experimental and Modelling
Authors: Muhammad Jamil, Ning He, Aqib Mashood Khan, Munish Kumar Gupta
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Ti-6Al-4V has numerous applications in the medical, automobile, and aerospace industries due to corrosion resistivity, structural stability, and chemical inertness to most fluids at room temperature. These peculiar characteristics are beneficial for their application and present formidable challenges during machining. Machining of Ti-6Al-4V produces an elevated cutting temperature above 1000oC at dry conditions. This accelerates tool wear and reduces product quality. Therefore, there is always a need to employ sustainable/effective coolant/lubricant when machining such alloy. In this study, Finite Element Modeling (FEM) and experimental analysis when cutting Ti-6Al-4V under a distinctly developed dry ice mixed hybrid lubri-coolant are presented. This study aims to model the milling process of Ti-6Al-4V under a proposed novel hybrid lubri-coolant using different cutting speeds and feed per tooth DEFORM® software package was used to conduct the FEM and the numerical model was experimentally validated. A comparison of experimental and simulation results showed a maximum error of no more than 6% for all experimental conditions. In a nutshell, it can be said that the proposed model is effective in predicting the machining temperature precisely.Keywords: friction coefficient, heat transfer, finite element modeling (FEM), milling Ti-6Al-4V
Procedia PDF Downloads 5613455 Wound Healing and Antioxidant Properties of 80% Methanol Leaf Extract of Verbascum sinaiticum (Scrophulariaceae), an Ethiopian Medicinal Plant
Authors: Solomon Assefa Huluka
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Wounds account for severe morbidity, socioeconomic distress, and mortality around the globe.For several years, various herbal products are used to expediteand augment the innate wound healing process. In Ethiopian folkloricmedicine, Verbascum sinaiticum L. (V. sinaiticum) is commonlyapplied as a wound-healing agent. The present study investigated the potential wound healing and antioxidant properties of hydroalcoholic leaf extract of V. sinaiticum. The 80% methanol extract, formulated as 5% (w/w) and 10% (w/w) ointments, was evaluated in excision and incision wound models using nitrofurazone and simple ointment as positive and negative controls, respectively. Parameters such as wound contraction, period of epithelialization, and tensile strength were determined. Moreover, its in vitro antioxidant property was evaluated using a DPPH assay. In the excision model, both doses (5% and 10% w/w) of the extract showed a significant (p<0.001) wound healing efficacy compared to the negative control, as evidenced by enhanced wound contraction rate and shorter epithelialization time records. In the incision model, the lower dose (5% w/w) ointment formulation of the extract exhibited the maximum increment in tensile strength (85.6%) that was significant (p<0.001)compared to negative and untreated controls. Animals treated with 5% w/wointment, furthermore, showed a significantly (p < 0.05) higher percentage of tensile strength than nitrofurazone treated ones. Moreover, the hydroalcoholic extract of the plant showed a noticeable free radical scavenging property. The result of the present study upholds the folkloric use of V. sinaiticum in the treatment of wounds.Keywords: wound healing, antioxidant, excision wound model, incision wound model, verbascum sinaiticum
Procedia PDF Downloads 8513454 A Multilayer Perceptron Neural Network Model Optimized by Genetic Algorithm for Significant Wave Height Prediction
Authors: Luis C. Parra
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The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms
Procedia PDF Downloads 10613453 Thermodynamic Behaviour of Binary Mixtures of 1, 2-Dichloroethane with Some Cyclic Ethers: Experimental Results and Modelling
Authors: Fouzia Amireche-Ziar, Ilham Mokbel, Jacques Jose
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The vapour pressures of the three binary mixtures: 1, 2- dichloroethane + 1,3-dioxolane, + 1,4-dioxane or + tetrahydropyrane, are carried out at ten temperatures ranging from 273 to 353.15 K. An accurate static device was employed for these measurements. The VLE data were reduced using the Redlich-Kister equation by taking into consideration the vapour pressure non-ideality in terms of the second molar virial coefficient. The experimental data were compared to the results predicted with the DISQUAC and Dortmund UNIFAC group contribution models for the total pressures P and the excess molar Gibbs energies GE.Keywords: disquac model, dortmund UNIFAC model, excess molar Gibbs energies GE, VLE
Procedia PDF Downloads 25713452 Coupled Hydro-Geomechanical Modeling of Oil Reservoir Considering Non-Newtonian Fluid through a Fracture
Authors: Juan Huang, Hugo Ninanya
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Oil has been used as a source of energy and supply to make materials, such as asphalt or rubber for many years. This is the reason why new technologies have been implemented through time. However, research still needs to continue increasing due to new challenges engineers face every day, just like unconventional reservoirs. Various numerical methodologies have been applied in petroleum engineering as tools in order to optimize the production of reservoirs before drilling a wellbore, although not all of these have the same efficiency when talking about studying fracture propagation. Analytical methods like those based on linear elastic fractures mechanics fail to give a reasonable prediction when simulating fracture propagation in ductile materials whereas numerical methods based on the cohesive zone method (CZM) allow to represent the elastoplastic behavior in a reservoir based on a constitutive model; therefore, predictions in terms of displacements and pressure will be more reliable. In this work, a hydro-geomechanical coupled model of horizontal wells in fractured rock was developed using ABAQUS; both extended element method and cohesive elements were used to represent predefined fractures in a model (2-D). A power law for representing the rheological behavior of fluid (shear-thinning, power index <1) through fractures and leak-off rate permeating to the matrix was considered. Results have been showed in terms of aperture and length of the fracture, pressure within fracture and fluid loss. It was showed a high infiltration rate to the matrix as power index decreases. A sensitivity analysis is conclusively performed to identify the most influential factor of fluid loss.Keywords: fracture, hydro-geomechanical model, non-Newtonian fluid, numerical analysis, sensitivity analysis
Procedia PDF Downloads 20113451 Modelling Structural Breaks in Stock Price Time Series Using Stochastic Differential Equations
Authors: Daniil Karzanov
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This paper studies the effect of quarterly earnings reports on the stock price. The profitability of the stock is modeled by geometric Brownian diffusion and the Constant Elasticity of Variance model. We fit several variations of stochastic differential equations to the pre-and after-report period using the Maximum Likelihood Estimation and Grid Search of parameters method. By examining the change in the model parameters after reports’ publication, the study reveals that the reports have enough evidence to be a structural breakpoint, meaning that all the forecast models exploited are not applicable for forecasting and should be refitted shortly.Keywords: stock market, earnings reports, financial time series, structural breaks, stochastic differential equations
Procedia PDF Downloads 20413450 Research on the Online Learning Activities Design and Students’ Experience Based on APT Model
Authors: Wang Yanli, Cheng Yun, Yang Jiarui
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Due to the separation of teachers and students, online teaching during the COVID-19 epidemic was faced with many problems, such as low enthusiasm of students, distraction, low learning atmosphere, and insufficient interaction between teachers and students. The essay designed the elaborate online learning activities of the course 'Research Methods of Educational Science' based on the APT model from three aspects of multiple assessment methods, a variety of teaching methods, and online learning environment and technology. Student's online learning experience was examined from the perception of online course, the perception of the online learning environment, and satisfaction after the course’s implementation. The research results showed that students have a positive overall evaluation of online courses, a high degree of engagement in learning, positive acceptance of online learning, and high satisfaction with it, but students hold a relatively neutral attitude toward online learning. And some dimensions in online learning experience were found to have positive influence on students' satisfaction with online learning. We suggest making the good design of online courses, selecting proper learning platforms, and conducting blended learning to improve students’ learning experience. This study has both theoretical and practical significance for the design, implementation, effect feedback, and sustainable development of online teaching in the post-epidemic era.Keywords: APT model, online learning, online learning activities, learning experience
Procedia PDF Downloads 13313449 Optimization in Locating Firefighting Stations Using GIS Data and AHP Model; A Case Study on Arak City
Authors: Hasan Heydari
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In recent decades, locating urban services is one of the significant discussions in urban planning. Among these considerations, cities require more accurate planning in order to supply citizen needs, especially part of urban safety. In order to gain this goal, one of the main tasks of urban planners and managers is specifying suitable sites to locate firefighting stations. This study has been done to reach this purpose. Therefore effective criteria consist of coverage radius, population density, proximity to pathway network, land use (compatible and incompatible neighborhood) have been specified. After that, descriptive and local information of the criteria was provided and their layers were created in ArcGIS 9.3. Using Analytic Hierarchy Process (AHP) these criteria and their sub-criteria got the weights. These layers were classified regarding their weights and finally were overlaid by Index Overlay Model and provided the final site selection map for firefighting stations of Arak city. The results gained by analyzing in GIS environment indicate the existing fire station don’t cover the whole city sufficiently and some of the stations have established on the unsuitable sites. The output map indicates the best sites to locate firefighting stations of Arak.Keywords: site-selection, firefighting stations, analytic hierarchy process (AHP), GIS, index overlay model
Procedia PDF Downloads 34713448 Supervisor Controller-Based Colored Petri Nets for Deadlock Control and Machine Failures in Automated Manufacturing Systems
Authors: Husam Kaid, Abdulrahman Al-Ahmari, Zhiwu Li
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This paper develops a robust deadlock control technique for shared and unreliable resources in automated manufacturing systems (AMSs) based on structural analysis and colored Petri nets, which consists of three steps. The first step involves using strict minimal siphon control to create a live (deadlock-free) system that does not consider resource failure. The second step uses an approach based on colored Petri net, in which all monitors designed in the first step are merged into a single monitor. The third step addresses the deadlock control problems caused by resource failures. For all resource failures in the Petri net model a common recovery subnet based on colored petri net is proposed. The common recovery subnet is added to the obtained system at the second step to make the system reliable. The proposed approach is evaluated using an AMS from the literature. The results show that the proposed approach can be applied to an unreliable complex Petri net model, has a simpler structure and less computational complexity, and can obtain one common recovery subnet to model all resource failures.Keywords: automated manufacturing system, colored Petri net, deadlocks, siphon
Procedia PDF Downloads 12713447 Heat Transfer and Trajectory Models for a Cloud of Spray over a Marine Vessel
Authors: S. R. Dehghani, G. F. Naterer, Y. S. Muzychka
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Wave-impact sea spray creates many droplets which form a spray cloud traveling over marine objects same as marine vessels and offshore structures. In cold climates such as Arctic reigns, sea spray icing, which is ice accretion on cold substrates, is strongly dependent on the wave-impact sea spray. The rate of cooling of droplets affects the process of icing that can yield to dry or wet ice accretion. Trajectories of droplets determine the potential places for ice accretion. Combining two models of trajectories and heat transfer for droplets can predict the risk of ice accretion reasonably. The majority of the cooling of droplets is because of droplet evaporations. In this study, a combined model using trajectory and heat transfer evaluate the situation of a cloud of spray from the generation to impingement. The model uses some known geometry and initial information from the previous case studies. The 3D model is solved numerically using a standard numerical scheme. Droplets are generated in various size ranges from 7 mm to 0.07 mm which is a suggested range for sea spray icing. The initial temperature of droplets is considered to be the sea water temperature. Wind velocities are assumed same as that of the field observations. Evaluations are conducted using some important heading angles and wind velocities. The characteristic of size-velocity dependence is used to establish a relation between initial sizes and velocities of droplets. Time intervals are chosen properly to maintain a stable and fast numerical solution. A statistical process is conducted to evaluate the probability of expected occurrences. The medium size droplets can reach the highest heights. Very small and very large droplets are limited to lower heights. Results show that higher initial velocities create the most expanded cloud of spray. Wind velocities affect the extent of the spray cloud. The rate of droplet cooling at the start of spray formation is higher than the rest of the process. This is because of higher relative velocities and also higher temperature differences. The amount of water delivery and overall temperature for some sample surfaces over a marine vessel are calculated. Comparing results and some field observations show that the model works accurately. This model is suggested as a primary model for ice accretion on marine vessels.Keywords: evaporation, sea spray, marine icing, numerical solution, trajectory
Procedia PDF Downloads 21913446 Modeling of Hydraulic Networking of Water Supply Subsystem Case of Addis Ababa
Authors: Solomon Weldegebriel Gebrelibanos
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Water is one of the most important substances in human life that can give a human liberality with its cost and availability. Water comes from rainfall and runoff and reaches the ground as runoff that is stored in a river, ponds, and big water bodies, including sea and ocean and the remaining water portion is infiltrated into the ground to store in the aquifer. Water can serve human beings in various ways, including irrigation, water supply, hydropower and soon. Water supply is the main pillar of the water service to the human being. Water supply distribution in Addis Ababa arises from Legedadi, Akakai, and Gefersa. The objective of the study is to measure the performance of the water supply distribution in Addis Ababa city. The water supply distribution model is developed by computer-aided design software. The model can analyze the operational change, loss of water, and performance of the network. The two design criteria that have been employed to analyze the network system are velocity and pressure. The result shows that the customers are using the water at high pressure with low demand. The water distribution system is older than the expected service life with more leakage. Hence the study recommended that fixing Pressure valves and new distribution facilities can resolve the performance of the water supply systemKeywords: distribution, model, pressure, velocity
Procedia PDF Downloads 13513445 Forecasting Residential Water Consumption in Hamilton, New Zealand
Authors: Farnaz Farhangi
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Many people in New Zealand believe that the access to water is inexhaustible, and it comes from a history of virtually unrestricted access to it. For the region like Hamilton which is one of New Zealand’s fastest growing cities, it is crucial for policy makers to know about the future water consumption and implementation of rules and regulation such as universal water metering. Hamilton residents use water freely and they do not have any idea about how much water they use. Hence, one of proposed objectives of this research is focusing on forecasting water consumption using different methods. Residential water consumption time series exhibits seasonal and trend variations. Seasonality is the pattern caused by repeating events such as weather conditions in summer and winter, public holidays, etc. The problem with this seasonal fluctuation is that, it dominates other time series components and makes difficulties in determining other variations (such as educational campaign’s effect, regulation, etc.) in time series. Apart from seasonality, a stochastic trend is also combined with seasonality and makes different effects on results of forecasting. According to the forecasting literature, preprocessing (de-trending and de-seasonalization) is essential to have more performed forecasting results, while some other researchers mention that seasonally non-adjusted data should be used. Hence, I answer the question that is pre-processing essential? A wide range of forecasting methods exists with different pros and cons. In this research, I apply double seasonal ARIMA and Artificial Neural Network (ANN), considering diverse elements such as seasonality and calendar effects (public and school holidays) and combine their results to find the best predicted values. My hypothesis is the examination the results of combined method (hybrid model) and individual methods and comparing the accuracy and robustness. In order to use ARIMA, the data should be stationary. Also, ANN has successful forecasting applications in terms of forecasting seasonal and trend time series. Using a hybrid model is a way to improve the accuracy of the methods. Due to the fact that water demand is dominated by different seasonality, in order to find their sensitivity to weather conditions or calendar effects or other seasonal patterns, I combine different methods. The advantage of this combination is reduction of errors by averaging of each individual model. It is also useful when we are not sure about the accuracy of each forecasting model and it can ease the problem of model selection. Using daily residential water consumption data from January 2000 to July 2015 in Hamilton, I indicate how prediction by different methods varies. ANN has more accurate forecasting results than other method and preprocessing is essential when we use seasonal time series. Using hybrid model reduces forecasting average errors and increases the performance.Keywords: artificial neural network (ANN), double seasonal ARIMA, forecasting, hybrid model
Procedia PDF Downloads 33613444 Two Dimensional Finite Element Model to Study Calcium Dynamics in Fibroblast Cell with Excess Buffer Approximation Involving ER Flux and SERCA Pump
Authors: Mansha Kotwani
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The specific spatio-temporal calcium concentration patterns are required by the fibroblasts to maintain its structure and functions. Thus, calcium concentration is regulated in cell at different levels in various activities of the cell. The variations in cytosolic calcium concentration largely depend on the buffers present in cytosol and influx of calcium into cytosol from ER through IP3Rs or Raynodine receptors followed by reuptake of calcium into ER through sarcoplasmic/endoplasmic reticulum ATPs (SERCA) pump. In order to understand the mechanisms of wound repair, tissue remodeling and growth performed by fibroblasts, it is of crucial importance to understand the mechanisms of calcium concentration regulation in fibroblasts. In this paper, a model has been developed to study calcium distribution in NRK fibroblast in the presence of buffers and ER flux with SERCA pump. The model has been developed for two dimensional unsteady state case. Appropriate initial and boundary conditions have been framed along with physiology of the cell. Finite element technique has been employed to obtain the solution. The numerical results have been used to study the effect of buffers, ER flux and source amplitude on calcium distribution in fibroblast cell.Keywords: buffers, IP3R, ER flux, SERCA pump, source amplitude
Procedia PDF Downloads 24213443 Predictions of Values in a Causticizing Process
Authors: R. Andreola, O. A. A. Santos, L. M. M. Jorge
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An industrial system for the production of white liquor of a paper industry, Klabin Paraná Papé is, formed by ten reactors was modeled, simulated, and analyzed. The developed model considered possible water losses by evaporation and reaction, in addition to variations in volumetric flow of lime mud across the reactors due to composition variations. The model predictions agreed well with the process measurements at the plant and the results showed that the slaking reaction is nearly complete at the third causticizing reactor, while causticizing ends by the seventh reactor. Water loss due to slaking reaction and evaporation occurs more pronouncedly in the slaking reaction than in the final causticizing reactors; nevertheless, the lime mud flow remains nearly constant across the reactors.Keywords: causticizing, lime, prediction, process
Procedia PDF Downloads 35213442 Enhancement of Capacity in a MC-CDMA based Cognitive Radio Network Using Non-Cooperative Game Model
Authors: Kalyani Kulkarni, Bharat Chaudhari
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This paper addresses the issue of resource allocation in the emerging cognitive technology. Focusing the quality of service (QoS) of primary users (PU), a novel method is proposed for the resource allocation of secondary users (SU). In this paper, we propose the unique utility function in the game theoretic model of Cognitive Radio which can be maximized to increase the capacity of the cognitive radio network (CRN) and to minimize the interference scenario. The utility function is formulated to cater the need of PUs by observing Signal to Noise ratio. The existence of Nash equilibrium is for the postulated game is established.Keywords: cognitive networks, game theory, Nash equilibrium, resource allocation
Procedia PDF Downloads 47713441 Consumer Behaviour Model for Apparel E-Tailers Using Structural Equation Modelling
Authors: Halima Akhtar, Abhijeet Chandra
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The paper attempts to analyze the factors that influence the Consumer Behavior to purchase apparel through the internet. The intentions to buy apparels online were based on in terms of user style, orientation, size and reputation of the merchant, social influence, perceived information utility, perceived ease of use, perceived pleasure and attractiveness and perceived trust and risk. The basic framework used was Technology acceptance model to explain apparels acceptance. A survey was conducted to gather the data from 200 people. The measures and hypotheses were analyzed using Correlation testing and would be further validated by the Structural Equation Modelling. The implications of the findings for theory and practice could be used by marketers of online apparel websites. Based on the values obtained, we can conclude that the factors such as social influence, Perceived information utility, attractiveness and trust influence the decision for a user to buy apparels online. The major factors which are found to influence an online apparel buying decision are ease of use, attractiveness that a website can offer and the trust factor which a user shares with the website.Keywords: E-tailers, consumer behaviour, technology acceptance model, structural modelling
Procedia PDF Downloads 18513440 State Estimation of a Biotechnological Process Using Extended Kalman Filter and Particle Filter
Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte, V. Grincas
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This paper deals with advanced state estimation algorithms for estimation of biomass concentration and specific growth rate in a typical fed-batch biotechnological process. This biotechnological process was represented by a nonlinear mass-balance based process model. Extended Kalman Filter (EKF) and Particle Filter (PF) was used to estimate the unmeasured state variables from oxygen uptake rate (OUR) and base consumption (BC) measurements. To obtain more general results, a simplified process model was involved in EKF and PF estimation algorithms. This model doesn’t require any special growth kinetic equations and could be applied for state estimation in various bioprocesses. The focus of this investigation was concentrated on the comparison of the estimation quality of the EKF and PF estimators by applying different measurement noises. The simulation results show that Particle Filter algorithm requires significantly more computation time for state estimation but gives lower estimation errors both for biomass concentration and specific growth rate. Also the tuning procedure for Particle Filter is simpler than for EKF. Consequently, Particle Filter should be preferred in real applications, especially for monitoring of industrial bioprocesses where the simplified implementation procedures are always desirable.Keywords: biomass concentration, extended Kalman filter, particle filter, state estimation, specific growth rate
Procedia PDF Downloads 42513439 Proactive Change or Adaptive Response: A Study on the Impact of Digital Transformation Strategy Modes on Enterprise Profitability From a Configuration Perspective
Authors: Jing-Ma
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Digital transformation (DT) is an important way for manufacturing enterprises to shape new competitive advantages, and how to choose an effective DT strategy is crucial for enterprise growth and sustainable development. Rooted in strategic change theory, this paper incorporates the dimensions of managers' digital cognition, organizational conditions, and external environment into the same strategic analysis framework and integrates the dynamic QCA method and PSM method to study the antecedent grouping of the DT strategy mode of manufacturing enterprises and its impact on corporate profitability based on the data of listed manufacturing companies in China from 2015 to 2019. We find that the synergistic linkage of different dimensional elements can form six equivalent paths of high-level DT, which can be summarized as the proactive change mode of resource-capability dominated as well as adaptive response mode such as industry-guided resource replenishment. Capacity building under complex environments, market-industry synergy-driven, forced adaptation under peer pressure, and the managers' digital cognition play a non-essential but crucial role in this process. Except for individual differences in the market industry collaborative driving mode, other modes are more stable in terms of individual and temporal changes. However, it is worth noting that not all paths that result in high levels of DT can contribute to enterprise profitability, but only high levels of DT that result from matching the optimization of internal conditions with the external environment, such as industry technology and macro policies, can have a significant positive impact on corporate profitability.Keywords: digital transformation, strategy mode, enterprise profitability, dynamic QCA, PSM approach
Procedia PDF Downloads 2113438 Using Vulnerability to Reduce False Positive Rate in Intrusion Detection Systems
Authors: Nadjah Chergui, Narhimene Boustia
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Intrusion Detection Systems are an essential tool for network security infrastructure. However, IDSs have a serious problem which is the generating of massive number of alerts, most of them are false positive ones which can hide true alerts and make the analyst confused to analyze the right alerts for report the true attacks. The purpose behind this paper is to present a formalism model to perform correlation engine by the reduction of false positive alerts basing on vulnerability contextual information. For that, we propose a formalism model based on non-monotonic JClassicδє description logic augmented with a default (δ) and an exception (є) operator that allows a dynamic inference according to contextual information.Keywords: context, default, exception, vulnerability
Procedia PDF Downloads 25813437 Prediction of Deformations of Concrete Structures
Authors: A. Brahma
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Drying is a phenomenon that accompanies the hardening of hydraulic materials. It can, if it is not prevented, lead to significant spontaneous dimensional variations, which the cracking is one of events. In this context, cracking promotes the transport of aggressive agents in the material, which can affect the durability of concrete structures. Drying shrinkage develops over a long period almost 30 years although most occurred during the first three years. Drying shrinkage stabilizes when the material is water balance with the external environment. The drying shrinkage of cementitious materials is due to the formation of capillary tensions in the pores of the material, which has the consequences of bringing the solid walls of each other. Knowledge of the shrinkage characteristics of concrete is a necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable shrinkage movement in reinforced or prestressed concrete and the appropriate steps can be taken in design to accommodate this movement. This study is concerned the modelling of drying shrinkage of the hydraulic materials and the prediction of the rate of spontaneous deformations of hydraulic materials during hardening. The model developed takes in consideration the main factors affecting drying shrinkage. There was agreement between drying shrinkage predicted by the developed model and experimental results. In last we show that developed model describe the evolution of the drying shrinkage of high performances concretes correctly.Keywords: drying, hydraulic concretes, shrinkage, modeling, prediction
Procedia PDF Downloads 33413436 The Impact of Artificial Intelligence on Spare Parts Technology
Authors: Amir Andria Gad Shehata
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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management
Procedia PDF Downloads 6213435 Computational Fluid Dynamics Simulation on Heat Transfer of Hot Air Bubble Injection into Water Column
Authors: Jae-Yeong Choi, Gyu-Mok Jeon, Jong-Chun Park, Yong-Jin Cho, Seok-Tae Yoon
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When air flow is injected into water, bubbles are formed in various types inside the water pool along with the air flow rate. The bubbles are floated in equilibrium with forces such as buoyancy, surface tension and shear force. Single bubble generated at low flow rate maintains shape, but bubbles with high flow rate break up to make mixing and turbulence. In addition to this phenomenon, as the hot air bubbles are injected into the water, heat affects the interface of phases. Therefore, the main scope of the present work reveals how to proceed heat transfer between water and hot air bubbles injected into water. In the present study, a series of CFD simulation for the heat transfer of hot bubbles injected through a nozzle near the bottom in a cylindrical water column are performed using a commercial CFD software, STAR-CCM+. The governing equations for incompressible and viscous flow are the continuous and the RaNS (Reynolds- averaged Navier-Stokes) equations and discretized by the FVM (Finite Volume Method) manner. For solving multi-phase flow, the Eulerian multiphase model is employed and the interface is defined by VOF (Volume-of-Fluid) technique. As a turbulence model, the SST k-w model considering the buoyancy effects is introduced. For spatial differencing the 3th-order MUSCL scheme is adopted and the 2nd-order implicit scheme for time integration. As the results, the dynamic behavior of the rising hot bubbles with the flow rate injected and regarding heat transfer mechanism are discussed based on the simulation results.Keywords: heat transfer, hot bubble injection, eulerian multiphase model, flow rate, CFD (Computational Fluid Dynamics)
Procedia PDF Downloads 15113434 A Global Business Network Built on Hive: Two Use Cases: Buying and Selling of Products and Services and Carrying Out of Social Impact Projects
Authors: Gheyzer Villegas, Edgardo Cedeño, Veruska Mata, Edmundo Chauran
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One of the most significant changes that occurred in global commerce was the emergence of cryptocurrencies and blockchain technology. There is still much debate about the adoption of the economic model based on crypto assets, and myriad international projects and initiatives are being carried out to try and explore the potential that this new field offers. The Hive blockchain is a prime example of this, featuring two use cases: of how trade based on its native currencies can give successful results in the exchange of goods and services and in the financing of social impact projects. Its decentralized management model and visionary administration of its development fund have become a key part of its success.Keywords: Hive, business, network, blockchain
Procedia PDF Downloads 6613433 Estimation of Snow and Ice Melt Contributions to Discharge from the Glacierized Hunza River Basin, Karakoram, Pakistan
Authors: Syed Hammad Ali, Rijan Bhakta Kayastha, Danial Hashmi, Richard Armstrong, Ahuti Shrestha, Iram Bano, Javed Hassan
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This paper presents the results of a semi-distributed modified positive degree-day model (MPDDM) for estimating snow and ice melt contributions to discharge from the glacierized Hunza River basin, Pakistan. The model uses daily temperature data, daily precipitation data, and positive degree day factors for snow and ice melt. The model is calibrated for the period 1995-2001 and validated for 2002-2013, and demonstrates close agreements between observed and simulated discharge with Nash–Sutcliffe Efficiencies of 0.90 and 0.88, respectively. Furthermore, the Weather Research and Forecasting model projected temperature, and precipitation data from 2016-2050 are used for representative concentration pathways RCP4.5 and RCP8.5, and bias correction was done using a statistical approach for future discharge estimation. No drastic changes in future discharge are predicted for the emissions scenarios. The aggregate snow-ice melt contribution is 39% of total discharge in the period 1993-2013. Snow-ice melt contribution ranges from 35% to 63% during the high flow period (May to October), which constitutes 89% of annual discharge; in the low flow period (November to April) it ranges from 0.02% to 17%, which constitutes 11 % of the annual discharge. The snow-ice melt contribution to total discharge will increase gradually in the future and reach up to 45% in 2041-2050. From a sensitivity analysis, it is found that the combination of a 2°C temperature rise and 20% increase in precipitation shows a 10% increase in discharge. The study allows us to evaluate the impact of climate change in such basins and is also useful for the future prediction of discharge to define hydropower potential, inform other water resource management in the area, to understand future changes in snow-ice melt contribution to discharge, and offer a possible evaluation of future water quantity and availability.Keywords: climate variability, future discharge projection, positive degree day, regional climate model, water resource management
Procedia PDF Downloads 29013432 Nurse-Patient Assignment: Case of Pediatrics Department
Authors: Jihene Jlassi, Ahmed Frikha, Wazna Kortli
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The objectives of Nurse-Patient Assignment are the minimization of the overall hospital cost and the maximization of nurses ‘preferences. This paper aims to assess nurses' satisfaction related to the implementation of patient acuity tool-based assignments. So, we used an integer linear program that assigns patients to nurses while balancing nurse workloads. Then, the proposed model is applied to the Paediatrics Department at Kasserine Hospital Tunisia. Where patients need special acuities and high-level nursing skills and care. Hence, numerical results suggested that proposed nurse-patient assignment models can achieve a balanced assignmentKeywords: nurse-patient assignment, mathematical model, logistics, pediatrics department, balanced assignment
Procedia PDF Downloads 145