Search results for: modified model
16516 From the Sharing Economy to Social Manufacturing: Analyzing Collaborative Service Networks in the Manufacturing Domain
Authors: Babak Mohajeri
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In recent years, the conventional business model of ownership has been changed towards accessibility in a variety of markets. Two trends can be observed in the evolution of this rental-like business model. Firstly, the technological development that enables the emergence of new business models. These new business models increasingly become agile and flexible. For example Spotify, an online music stream company provides consumers access to over millions of music tracks, conveniently through the smartphone, tablet or computer. Similarly, Car2Go, the car sharing company accesses its members with flexible and nearby sharing cars. The second trend is the increasing communication and connections via social networks. This trend enables a shift to peer-to-peer accessibility based business models. Conventionally, companies provide access for their customers to own companies products or services. In peer-to-peer model, nonetheless, companies facilitate access and connection across their customers to use other customers owned property or skills, competencies or services .The is so-called the sharing economy business model. The aim of this study is to investigate into a new and emerging type of the sharing economy model in which role of customers and service providers may dramatically change. This new model is called Collaborative Service Networks. We propose a mechanism for Collaborative Service Networks business model. Uber and Airbnb, two successful growing companies, have been selected for our case studies and their business models are analyzed. Finally, we study the emergence of the collaborative service networks in the manufacturing domain. Our finding results to a new manufacturing paradigm called social manufacturing.Keywords: sharing economy, collaborative service networks, social manufacturing, manufacturing development
Procedia PDF Downloads 31716515 Two-Component Biocompartible Material for Reconstruction of Articular Hyaline Cartilage
Authors: Alena O. Stepanova, Vera S. Chernonosova, Tatyana S. Godovikova, Konstantin A. Bulatov, Andrey Y. Patrushev, Pavel P. Laktionov
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Trauma and arthrosis, not to mention cartilage destruction in overweight and elders put hyaline cartilage lesion among the most frequent diseases of locomotor system. These problems combined with low regeneration potential of the cartilage make regeneration of articular cartilage a high-priority task of tissue engineering. Many types of matrices, the procedures of their installation and autologous chondrocyte implantation protocols were offered, but certain aspects including adhesion of the implant with surrounding cartilage/bone, prevention of the ossification and fibrosis were not resolved. Simplification and acceleration of the procedures resulting in restoration of normal cartilage are also required. We have demonstrated that human chondroblasts can be successfully cultivated at the surface of electrospun scaffolds and produce extracellular matrix components in contrast to chondroblasts grown in homogeneous hydrogels. To restore cartilage we offer to use stacks of electrospun scaffolds fixed with photopolymerized solution of prepared from gelatin and chondroitin-4-sulfate both modified by glycidyl methacrylate and non-toxic photoinitator Darocur 2959. Scaffolds were prepared from nylon 6, polylactide-co-glicolide and their mixtures with modified gelatin. Illumination of chondroblasts in photopolymerized solution using 365 nm LED light had no effect on cell viability at compressive strength of the gel less than0,12 MPa. Stacks of electrospun scaffolds provide good compressive strength and have the potential for substitution with cartilage when biodegradable scaffolds are used. Vascularization can be prevented by introduction of biostable scaffolds in the layers contacting the subchondral bone. Studies of two-component materials (2-3 sheets of electrospun scaffold) implanted in the knee-joints of rabbits and fixed by photopolymerization demonstrated good crush resistance, biocompatibility and good adhesion of the implant with surrounding cartilage. Histological examination of the implants 3 month after implantation demonstrates absence of any inflammation and signs of replacement of the biodegradable scaffolds with normal cartilage. The possibility of intraoperative population of the implants with autologous cells is being investigated.Keywords: chondroblasts, electrospun scaffolds, hyaline cartilage, photopolymerized gel
Procedia PDF Downloads 28416514 Volatility Model with Markov Regime Switching to Forecast Baht/USD
Authors: Nop Sopipan
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In this paper, we forecast the volatility of Baht/USDs using Markov Regime Switching GARCH (MRS-GARCH) models. These models allow volatility to have different dynamics according to unobserved regime variables. The main purpose of this paper is to find out whether MRS-GARCH models are an improvement on the GARCH type models in terms of modeling and forecasting Baht/USD volatility. The MRS-GARCH is the best performance model for Baht/USD volatility in short term but the GARCH model is best perform for long term.Keywords: volatility, Markov Regime Switching, forecasting, Baht/USD
Procedia PDF Downloads 30216513 Implementation of Free-Field Boundary Condition for 2D Site Response Analysis in OpenSees
Authors: M. Eskandarighadi, C. R. McGann
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It is observed from past experiences of earthquakes that local site conditions can significantly affect the strong ground motion characteristics experience at the site. One-dimensional seismic site response analysis is the most common approach for investigating site response. This approach assumes that soil is homogeneous and infinitely extended in the horizontal direction. Therefore, tying side boundaries together is one way to model this behavior, as the wave passage is assumed to be only vertical. However, 1D analysis cannot capture the 2D nature of wave propagation, soil heterogeneity, and 2D soil profile with features such as inclined layer boundaries. In contrast, 2D seismic site response modeling can consider all of the mentioned factors to better understand local site effects on strong ground motions. 2D wave propagation and considering that the soil profile on the two sides of the model may not be identical clarifies the importance of a boundary condition on each side that can minimize the unwanted reflections from the edges of the model and input appropriate loading conditions. Ideally, the model size should be sufficiently large to minimize the wave reflection, however, due to computational limitations, increasing the model size is impractical in some cases. Another approach is to employ free-field boundary conditions that take into account the free-field motion that would exist far from the model domain and apply this to the sides of the model. This research focuses on implementing free-field boundary conditions in OpenSees for 2D site response analysisComparisons are made between 1D models and 2D models with various boundary conditions, and details and limitations of the developed free-field boundary modeling approach are discussed.Keywords: boundary condition, free-field, opensees, site response analysis, wave propagation
Procedia PDF Downloads 15816512 Cuckoo Search Optimization for Black Scholes Option Pricing
Authors: Manas Shah
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Black Scholes option pricing model is one of the most important concepts in modern world of computational finance. However, its practical use can be challenging as one of the input parameters must be estimated; implied volatility of the underlying security. The more precisely these values are estimated, the more accurate their corresponding estimates of theoretical option prices would be. Here, we present a novel model based on Cuckoo Search Optimization (CS) which finds more precise estimates of implied volatility than Particle Swarm Optimization (PSO) and Genetic Algorithm (GA).Keywords: black scholes model, cuckoo search optimization, particle swarm optimization, genetic algorithm
Procedia PDF Downloads 45316511 Solar Energy Applications in Seawater Distillation
Authors: Yousef Abdulaziz Almolhem
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Geographically, the most Arabic countries locate in areas confined to arid or semiarid regions. For this reason, most of our countries have adopted the seawater desalination as a strategy to overcome this problem. For example, the water supply of AUE, Kuwait, and Saudi Arabia is almost 100% from the seawater desalination plants. Many areas in Saudia Arabia and other countries in the world suffer from lack of fresh water which hinders the development of these areas, despite the availability of saline water and high solar radiation intensity. Furthermore, most developing countries do not have sufficient meteorological data to evaluate if the solar radiation is enough to meet the solar desalination. A mathematical model was developed to simulate and predict the thermal behavior of the solar still which used direct solar energy for distillation of seawater. Measurement data were measured in the Environment and Natural Resources Department, Faculty of Agricultural and Food sciences, King Faisal University, Saudi Arabia, in order to evaluate the present model. The simulation results obtained from this model were compared with the measured data. The main results of this research showed that there are slight differences between the measured and predicted values of the elements studied, which is resultant from the change of some factors considered constants in the model such as the sky clearance, wind velocity and the salt concentration in the water in the basin of the solar still. It can be concluded that the present model can be used to estimate the average total solar radiation and the thermal behavior of the solar still in any area with consideration to the geographical location.Keywords: mathematical model, sea water, distillation, solar radiation
Procedia PDF Downloads 28316510 Lineup Optimization Model of Basketball Players Based on the Prediction of Recursive Neural Networks
Authors: Wang Yichen, Haruka Yamashita
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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.Keywords: recurrent neural network, players lineup, basketball data, decision making model
Procedia PDF Downloads 13316509 Elasto-Plastic Behavior of Rock during Temperature Drop
Authors: N. Reppas, Y. L. Gui, B. Wetenhall, C. T. Davie, J. Ma
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A theoretical constitutive model describing the stress-strain behavior of rock subjected to different confining pressures is presented. A bounding surface plastic model with hardening effects is proposed which includes the effect of temperature drop. The bounding surface is based on a mapping rule and the temperature effect on rock is controlled by Poisson’s ratio. Validation of the results against available experimental data is also presented. The relation of deviatoric stress and axial strain is illustrated at different temperatures to analyze the effect of temperature decrease in terms of stiffness of the material.Keywords: bounding surface, cooling of rock, plasticity model, rock deformation, elasto-plastic behavior
Procedia PDF Downloads 12816508 Application of Artificial Neural Network in Initiating Cleaning Of Photovoltaic Solar Panels
Authors: Mohamed Mokhtar, Mostafa F. Shaaban
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Among the challenges facing solar photovoltaic (PV) systems in the United Arab Emirates (UAE), dust accumulation on solar panels is considered the most severe problem that faces the growth of solar power plants. The accumulation of dust on the solar panels significantly degrades output from these panels. Hence, solar PV panels have to be cleaned manually or using costly automated cleaning methods. This paper focuses on initiating cleaning actions when required to reduce maintenance costs. The cleaning actions are triggered only when the dust level exceeds a threshold value. The amount of dust accumulated on the PV panels is estimated using an artificial neural network (ANN). Experiments are conducted to collect the required data, which are used in the training of the ANN model. Then, this ANN model will be fed by the output power from solar panels, ambient temperature, and solar irradiance, and thus, it will be able to estimate the amount of dust accumulated on solar panels at these conditions. The model was tested on different case studies to confirm the accuracy of the developed model.Keywords: machine learning, dust, PV panels, renewable energy
Procedia PDF Downloads 14416507 A Bayesian Multivariate Microeconometric Model for Estimation of Price Elasticity of Demand
Authors: Jefferson Hernandez, Juan Padilla
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Estimation of price elasticity of demand is a valuable tool for the task of price settling. Given its relevance, it is an active field for microeconomic and statistical research. Price elasticity in the industry of oil and gas, in particular for fuels sold in gas stations, has shown to be a challenging topic given the market and state restrictions, and underlying correlations structures between the types of fuels sold by the same gas station. This paper explores the Lotka-Volterra model for the problem for price elasticity estimation in the context of fuels; in addition, it is introduced multivariate random effects with the purpose of dealing with errors, e.g., measurement or missing data errors. In order to model the underlying correlation structures, the Inverse-Wishart, Hierarchical Half-t and LKJ distributions are studied. Here, the Bayesian paradigm through Markov Chain Monte Carlo (MCMC) algorithms for model estimation is considered. Simulation studies covering a wide range of situations were performed in order to evaluate parameter recovery for the proposed models and algorithms. Results revealed that the proposed algorithms recovered quite well all model parameters. Also, a real data set analysis was performed in order to illustrate the proposed approach.Keywords: price elasticity, volume, correlation structures, Bayesian models
Procedia PDF Downloads 16516506 Physicochemical Characterization of Coastal Aerosols over the Mediterranean Comparison with Weather Research and Forecasting-Chem Simulations
Authors: Stephane Laussac, Jacques Piazzola, Gilles Tedeschi
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Estimation of the impact of atmospheric aerosols on the climate evolution is an important scientific challenge. One of a major source of particles is constituted by the oceans through the generation of sea-spray aerosols. In coastal areas, marine aerosols can affect air quality through their ability to interact chemically and physically with other aerosol species and gases. The integration of accurate sea-spray emission terms in modeling studies is then required. However, it was found that sea-spray concentrations are not represented with the necessary accuracy in some situations, more particularly at short fetch. In this study, the WRF-Chem model was implemented on a North-Western Mediterranean coastal region. WRF-Chem is the Weather Research and Forecasting (WRF) model online-coupled with chemistry for investigation of regional-scale air quality which simulates the emission, transport, mixing, and chemical transformation of trace gases and aerosols simultaneously with the meteorology. One of the objectives was to test the ability of the WRF-Chem model to represent the fine details of the coastal geography to provide accurate predictions of sea spray evolution for different fetches and the anthropogenic aerosols. To assess the performance of the model, a comparison between the model predictions using a local emission inventory and the physicochemical analysis of aerosol concentrations measured for different wind direction on the island of Porquerolles located 10 km south of the French Riviera is proposed.Keywords: sea-spray aerosols, coastal areas, sea-spray concentrations, short fetch, WRF-Chem model
Procedia PDF Downloads 19616505 Mathematical Model for Defection between Two Political Parties
Authors: Abdullahi Mohammed Auwal
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Formation and change or decamping from one political party to another have now become a common trend in Nigeria. Many of the parties’ members who could not secure positions and or win elections in their parties or are not very much satisfied with the trends occurring in the party’s internal democratic principles and mechanisms, change their respective parties. This paper developed/presented and analyzed the used of non linear mathematical model for defections between two political parties using epidemiological approach. The whole population was assumed to be a constant and homogeneously mixed. Equilibria have been analytically obtained and their local and global stability discussed. Conditions for the co-existence of both the political parties have been determined, in the study of defections between People Democratic Party (PDP) and All Progressive Congress (APC) in Nigeria using numerical simulations to support the analytical results.Keywords: model, political parties, deffection, stability, equilibrium, epidemiology
Procedia PDF Downloads 63816504 Analysis of Brain Signals Using Neural Networks Optimized by Co-Evolution Algorithms
Authors: Zahra Abdolkarimi, Naser Zourikalatehsamad,
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Up to 40 years ago, after recognition of epilepsy, it was generally believed that these attacks occurred randomly and suddenly. However, thanks to the advance of mathematics and engineering, such attacks can be predicted within a few minutes or hours. In this way, various algorithms for long-term prediction of the time and frequency of the first attack are presented. In this paper, by considering the nonlinear nature of brain signals and dynamic recorded brain signals, ANFIS model is presented to predict the brain signals, since according to physiologic structure of the onset of attacks, more complex neural structures can better model the signal during attacks. Contribution of this work is the co-evolution algorithm for optimization of ANFIS network parameters. Our objective is to predict brain signals based on time series obtained from brain signals of the people suffering from epilepsy using ANFIS. Results reveal that compared to other methods, this method has less sensitivity to uncertainties such as presence of noise and interruption in recorded signals of the brain as well as more accuracy. Long-term prediction capacity of the model illustrates the usage of planted systems for warning medication and preventing brain signals.Keywords: co-evolution algorithms, brain signals, time series, neural networks, ANFIS model, physiologic structure, time prediction, epilepsy suffering, illustrates model
Procedia PDF Downloads 28216503 Fuzzy Logic Based Fault Tolerant Model Predictive MLI Topology
Authors: Abhimanyu Kumar, Chirag Gupta
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This work presents a comprehensive study on the employment of Model Predictive Control (MPC) for a three-phase voltage-source inverter to regulate the output voltage efficiently. The inverter is modeled via the Clarke Transformation, considering a scenario where the load is unknown. An LC filter model is developed, demonstrating its efficacy in Total Harmonic Distortion (THD) reduction. The system, when implemented with fault-tolerant multilevel inverter topologies, ensures reliable operation even under fault conditions, a requirement that is paramount with the increasing dependence on renewable energy sources. The research also integrates a Fuzzy Logic based fault tolerance system which identifies and manages faults, ensuring consistent inverter performance. The efficacy of the proposed methodology is substantiated through rigorous simulations and comparative results, shedding light on the voltage prediction efficiency and the robustness of the model even under fault conditions.Keywords: total harmonic distortion, fuzzy logic, renewable energy sources, MLI
Procedia PDF Downloads 13116502 Calibration and Validation of ArcSWAT Model for Estimation of Surface Runoff and Sediment Yield from Dhangaon Watershed
Authors: M. P. Tripathi, Priti Tiwari
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Soil and Water Assessment Tool (SWAT) is a distributed parameter continuous time model and was tested on daily and fortnightly basis for a small agricultural watershed (Dhangaon) of Chhattisgarh state in India. The SWAT model recently interfaced with ArcGIS and called as ArcSWAT. The watershed and sub-watershed boundaries, drainage networks, slope and texture maps were generated in the environment of ArcGIS of ArcSWAT. Supervised classification method was used for land use/cover classification from satellite imageries of the years 2009 and 2012. Manning's roughness coefficient 'n' for overland flow and channel flow and Fraction of Field Capacity (FFC) were calibrated for monsoon season of the years 2009 and 2010. The model was validated on a daily basis for the years 2011 and 2012 by using the observed daily rainfall and temperature data. Calibration and validation results revealed that the model was predicting the daily surface runoff and sediment yield satisfactorily. Sensitivity analysis showed that the annual sediment yield was inversely proportional to the overland and channel 'n' values whereas; annual runoff and sediment yields were directly proportional to the FFC. The model was also tested (calibrated and validated) for the fortnightly runoff and sediment yield for the year 2009-10 and 2011-12, respectively. Simulated values of fortnightly runoff and sediment yield for the calibration and validation years compared well with their observed counterparts. The calibration and validation results revealed that the ArcSWAT model could be used for identification of critical sub-watershed and for developing management scenarios for the Dhangaon watershed. Further, the model should be tested for simulating the surface runoff and sediment yield using generated rainfall and temperature before applying it for developing the management scenario for the critical or priority sub-watersheds.Keywords: watershed, hydrologic and water quality, ArcSWAT model, remote sensing, GIS, runoff and sediment yield
Procedia PDF Downloads 37916501 Enhancement of Morphogenetic Potential to Obtain Elite Varities of Sauropus androgynous (L.) Merr. through Somatic Embryogenesis
Authors: S. Padma, D. H. Tejavathi
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Somatic embryogenesis is a remarkable illustration of the dictum of plant totipotency where developmental reconstruction of somatic cells takes place towards the embryogenic pathway. It recapitulates the morphological and developmental process that occurs in zygotic embryogenesis. S. androgynous commonly called as multivitamin plant. The leaves are consumed as green leafy vegetable by the Southeast Asian communities due to their rich nutritional profile. Despite being a good nutritional vegetable with proteins, vitamins, minerals, amino acids, it is warned for excessive intake due to the presence of alkoloid called papaverine. Papaverine at higher concentrations is toxic and leads to a syndrome called Bronchiolitis Obliterans. In the present study, morphogenetic potential of shoot tip, leaf and nodal explants of Sauropus androgynous was investigated to develop and enhance the reliable plant regeneration protocol via somatic embryogenesis. Somatic embryos were derived directly from the embryogenic callus derived from shoot tip, node and leaf cultures on Phillips and Collins (L2) medium supplemented with NAA at various concentrations ranging from 5.3 µM/l to 26.85 µM/l within two months of inoculation. Thus obtained embryos were sub cultured to modified L2 media supplemented with increased vitamin level for the further growth. Somatic embryos with well-developed cotyledons were transferred to normal and modified L2 basal medium for conversion. The plantlets thus obtained were subjected to brief acclimatization before transferring them to land. About 95% of survival rate was recorded. The augmentation process of culturing various explants through somatic embryogenesis using synthetic medium with various plant growth regulators under controlled conditions have aggrandized the commercial production of Sauropus making it easily available over the conventional propagation methods. In addition, regeneration process through somatic embryogenesis has ameliorated the development of desired character in Sauropus with low papaverine content thereby providing a valuable resource to the food and pharmaceutical industry. Based on this research, plant tissue culture techniques have shown promise for economical and convenient application in Sauropus androgynous breeding.Keywords: L2 medium, multivitamin plant, NAA, papaverine
Procedia PDF Downloads 20716500 Experimental Evaluation of UDP in Wireless LAN
Authors: Omar Imhemed Alramli
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As Transmission Control Protocol (TCP), User Datagram Protocol (UDP) is transfer protocol in the transportation layer in Open Systems Interconnection model (OSI model) or in TCP/IP model of networks. The UDP aspects evaluation were not recognized by using the pcattcp tool on the windows operating system platform like TCP. The study has been carried out to find a tool which supports UDP aspects evolution. After the information collection about different tools, iperf tool was chosen and implemented on Cygwin tool which is installed on both Windows XP platform and also on Windows XP on virtual box machine on one computer only. Iperf is used to make experimental evaluation of UDP and to see what will happen during the sending the packets between the Host and Guest in wired and wireless networks. Many test scenarios have been done and the major UDP aspects such as jitter, packet losses, and throughput are evaluated.Keywords: TCP, UDP, IPERF, wireless LAN
Procedia PDF Downloads 35416499 Create a Dynamic Model in Project Control and Management
Authors: Hamed Saremi, Shahla Saremi
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In this study, control and management of construction projects is evaluated through developing a dynamic model in which some means are used in order to evaluating planning assumptions and reviewing the effectiveness of some project control policies based on previous researches about time, cost, project schedule pressure management, source management, project control, adding elements and sub-systems from cost management such as estimating consumption budget from budget due to costs, budget shortage effects and etc. using sensitivity analysis, researcher has evaluated introduced model that during model simulation by VENSIM software and assuming optimistic times and adding information about doing job and changes rate and project is forecasted with 373 days (2 days sooner than forecasted) and final profit $ 1,960,670 (23% amount of contract) assuming 15% inflation rate in year and costs rate accordance with planned amounts and other input information and final profit.Keywords: dynamic planning, cost, time, performance, project management
Procedia PDF Downloads 47816498 Proposal of a Model Supporting Decision-Making Based on Multi-Objective Optimization Analysis on Information Security Risk Treatment
Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu
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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization
Procedia PDF Downloads 46116497 Design and Analysis of Flexible Slider Crank Mechanism
Authors: Thanh-Phong Dao, Shyh-Chour Huang
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This study presents the optimal design and formulation of a kinematic model of a flexible slider crank mechanism. The objective of the proposed innovative design is to take extra advantage of the compliant mechanism and maximize the fatigue life by applying the Taguchi method. A formulated kinematic model is developed using a Pseudo-Rigid-Body Model (PRBM). By means of mathematic models, the kinematic behaviors of the flexible slider crank mechanism are captured using MATLAB software. Finite Element Analysis (FEA) is used to show the stress distribution. The results show that the optimal shape of the flexible hinge includes a force of 8.5N, a width of 9mm and a thickness of 1.1mm. Analysis of variance shows that the thickness of the proposed hinge is the most significant parameter, with an F test of 15.5. Finally, a prototype is manufactured to prepare for testing the kinematic and dynamic behaviors.Keywords: kinematic behavior, fatigue life, pseudo-rigid-body model, flexible slider crank mechanism
Procedia PDF Downloads 46016496 Sampled-Data Model Predictive Tracking Control for Mobile Robot
Authors: Wookyong Kwon, Sangmoon Lee
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In this paper, a sampled-data model predictive tracking control method is presented for mobile robots which is modeled as constrained continuous-time linear parameter varying (LPV) systems. The presented sampled-data predictive controller is designed by linear matrix inequality approach. Based on the input delay approach, a controller design condition is derived by constructing a new Lyapunov function. Finally, a numerical example is given to demonstrate the effectiveness of the presented method.Keywords: model predictive control, sampled-data control, linear parameter varying systems, LPV
Procedia PDF Downloads 30916495 Study on Constitutive Model of Particle Filling Material Considering Volume Expansion
Authors: Xu Jinsheng, Tong Xin, Zheng Jian, Zhou Changsheng
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The NEPE (nitrate ester plasticized polyether) propellant is a kind of particle filling material with relatively high filling fraction. The experimental results show that the microcracks, microvoids and dewetting can cause the stress softening of the material. In this paper, a series of mechanical testing in inclusion with CCD technique were conducted to analyze the evolution of internal defects of propellant. The volume expansion function of the particle filling material was established by measuring of longitudinal and transverse strain with optical deformation measurement system. By analyzing the defects and internal damages of the material, a visco-hyperelastic constitutive model based on free energy theory was proposed incorporating damage function. The proposed constitutive model could accurately predict the mechanical properties of uniaxial tensile tests and tensile-relaxation tests.Keywords: dewetting, constitutive model, uniaxial tensile tests, visco-hyperelastic, nonlinear
Procedia PDF Downloads 30116494 Integrated Evaluation of Green Design and Green Manufacturing Processes Using a Mathematical Model
Authors: Yuan-Jye Tseng, Shin-Han Lin
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In this research, a mathematical model for integrated evaluation of green design and green manufacturing processes is presented. To design a product, there can be alternative options to design the detailed components to fulfill the same product requirement. In the design alternative cases, the components of the product can be designed with different materials and detailed specifications. If several design alternative cases are proposed, the different materials and specifications can affect the manufacturing processes. In this paper, a new concept for integrating green design and green manufacturing processes is presented. A green design can be determined based the manufacturing processes of the designed product by evaluating the green criteria including energy usage and environmental impact, in addition to the traditional criteria of manufacturing cost. With this concept, a mathematical model is developed to find the green design and the associated green manufacturing processes. In the mathematical model, the cost items include material cost, manufacturing cost, and green related cost. The green related cost items include energy cost and environmental cost. The objective is to find the decisions of green design and green manufacturing processes to achieve the minimized total cost. In practical applications, the decision-making can be made to select a good green design case and its green manufacturing processes. In this presentation, an example product is illustrated. It shows that the model is practical and useful for integrated evaluation of green design and green manufacturing processes.Keywords: supply chain management, green supply chain, green design, green manufacturing, mathematical model
Procedia PDF Downloads 80716493 Facility Data Model as Integration and Interoperability Platform
Authors: Nikola Tomasevic, Marko Batic, Sanja Vranes
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Emerging Semantic Web technologies can be seen as the next step in evolution of the intelligent facility management systems. Particularly, this considers increased usage of open source and/or standardized concepts for data classification and semantic interpretation. To deliver such facility management systems, providing the comprehensive integration and interoperability platform in from of the facility data model is a prerequisite. In this paper, one of the possible modelling approaches to provide such integrative facility data model which was based on the ontology modelling concept was presented. Complete ontology development process, starting from the input data acquisition, ontology concepts definition and finally ontology concepts population, was described. At the beginning, the core facility ontology was developed representing the generic facility infrastructure comprised of the common facility concepts relevant from the facility management perspective. To develop the data model of a specific facility infrastructure, first extension and then population of the core facility ontology was performed. For the development of the full-blown facility data models, Malpensa and Fiumicino airports in Italy, two major European air-traffic hubs, were chosen as a test-bed platform. Furthermore, the way how these ontology models supported the integration and interoperability of the overall airport energy management system was analyzed as well.Keywords: airport ontology, energy management, facility data model, ontology modeling
Procedia PDF Downloads 44816492 Global Stability Analysis of a Coupled Model for Healthy and Cancerous Cells Dynamics in Acute Myeloid Leukemia
Authors: Abdelhafid Zenati, Mohamed Tadjine
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The mathematical formulation of biomedical problems is an important phase to understand and predict the dynamic of the controlled population. In this paper we perform a stability analysis of a coupled model for healthy and cancerous cells dynamics in Acute Myeloid Leukemia, this represents our first aim. Second, we illustrate the effect of the interconnection between healthy and cancer cells. The PDE-based model is transformed to a nonlinear distributed state space model (delay system). For an equilibrium point of interest, necessary and sufficient conditions of global asymptotic stability are given. Thus, we came up to give necessary and sufficient conditions of global asymptotic stability of the origin and the healthy situation and control of the dynamics of normal hematopoietic stem cells and cancerous during myelode Acute leukemia. Simulation studies are given to illustrate the developed results.Keywords: distributed delay, global stability, modelling, nonlinear models, PDE, state space
Procedia PDF Downloads 25216491 The Impacts of Local Decision Making on Customisation Process Speed across Distributed Boundaries
Authors: Abdulrahman M. Qahtani, Gary. B. Wills, Andy. M. Gravell
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Communicating and managing customers’ requirements in software development projects play a vital role in the software development process. While it is difficult to do so locally, it is even more difficult to communicate these requirements over distributed boundaries and to convey them to multiple distribution customers. This paper discusses the communication of multiple distribution customers’ requirements in the context of customised software products. The main purpose is to understand the challenges of communicating and managing customisation requirements across distributed boundaries. We propose a model for Communicating Customisation Requirements of Multi-Clients in a Distributed Domain (CCRD). Thereafter, we evaluate that model by presenting the findings of a case study conducted with a company with customisation projects for 18 distributed customers. Then, we compare the outputs of the real case process and the outputs of the CCRD model using simulation methods. Our conjecture is that the CCRD model can reduce the challenge of communication requirements over distributed organisational boundaries, and the delay in decision making and in the entire customisation process time.Keywords: customisation software products, global software engineering, local decision making, requirement engineering, simulation model
Procedia PDF Downloads 43016490 Study of the Relationship between the Roughness Configuration of Channel Bottom and the Creation of Vortices at the Rough Area: Numerical Modelling
Authors: Youb Said, Fourar Ali
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To describe the influence of bottom roughness on the free surface flows by numerical modeling, a two-dimensional model was developed. The equations of continuity and momentum (Naviers Stokes equations) are solved by the finite volume method. We considered a turbulent flow in an open channel with a bottom roughness. For our simulations, the K-ε model was used. After setting the initial and boundary conditions and solve the equations set, we were able to achieve the following results: vortex forming in the hollow causing substantial energy dissipation in the obstacle areas that form the bottom roughness. The comparison of our results with experimental ones shows a good agreement in terms of the results in the rough area. However, in other areas, differences were more or less important. These differences are in areas far from the bottom, especially the free surface area just after the bottom. These disagreements are probably due to experimental constants used by the k-ε model.Keywords: modeling, free surface flow, turbulence, bottom roughness, finite volume, K-ε model, energy dissipation
Procedia PDF Downloads 38216489 Using of Particle Swarm Optimization for Loss Minimization of Vector-Controlled Induction Motors
Authors: V. Rashtchi, H. Bizhani, F. R. Tatari
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This paper presents a new online loss minimization for an induction motor drive. Among the many loss minimization algorithms (LMAs) for an induction motor, a particle swarm optimization (PSO) has the advantages of fast response and high accuracy. However, the performance of the PSO and other optimization algorithms depend on the accuracy of the modeling of the motor drive and losses. In the development of the loss model, there is always a trade off between accuracy and complexity. This paper presents a new online optimization to determine an optimum flux level for the efficiency optimization of the vector-controlled induction motor drive. An induction motor (IM) model in d-q coordinates is referenced to the rotor magnetizing current. This transformation results in no leakage inductance on the rotor side, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the motor loss model. The suggested algorithm is simple for implementation.Keywords: induction machine, loss minimization, magnetizing current, particle swarm optimization
Procedia PDF Downloads 63316488 Estimation of the Length and Location of Ground Surface Deformation Caused by the Reverse Faulting
Authors: Nader Khalafian, Mohsen Ghaderi
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Field observations have revealed many examples of structures which were damaged due to ground surface deformation caused by the faulting phenomena. In this paper some efforts were made in order to estimate the length and location of the ground surface where large displacements were created due to the reverse faulting. This research has conducted in two steps; (1) in the first step, a 2D explicit finite element model were developed using ABAQUS software. A subroutine for Mohr-Coulomb failure criterion with strain softening model was developed by the authors in order to properly model the stress strain behavior of the soil in the fault rapture zone. The results of the numerical analysis were verified with the results of available centrifuge experiments. Reasonable coincidence was found between the numerical and experimental data. (2) In the second step, the effects of the fault dip angle (δ), depth of soil layer (H), dilation and friction angle of sand (ψ and φ) and the amount of fault offset (d) on the soil surface displacement and fault rupture path were investigated. An artificial neural network-based model (ANN), as a powerful prediction tool, was developed to generate a general model for predicting faulting characteristics. A properly sized database was created to train and test network. It was found that the length and location of the zone of displaced ground surface can be accurately estimated using the proposed model.Keywords: reverse faulting, surface deformation, numerical, neural network
Procedia PDF Downloads 42116487 A Convolutional Neural Network-Based Model for Lassa fever Virus Prediction Using Patient Blood Smear Image
Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa
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A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever
Procedia PDF Downloads 120