Search results for: material model
20683 Predicting the Effect of Silicon Electrode Design Parameters on Thermal Performance of a Lithium-Ion Battery
Authors: Harika Dasari, Eric Eisenbraun
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The present study models the role of electrode structural characteristics on the thermal behavior of lithium-ion batteries. Preliminary modeling runs have employed a 1D lithium-ion battery coupled to a two-dimensional axisymmetric model using silicon as the battery anode material. The two models are coupled by the heat generated and the average temperature. Our study is focused on the silicon anode particle sizes and it is observed that silicon anodes with nano-sized particles reduced the temperature of the battery in comparison to anodes with larger particles. These results are discussed in the context of the relationship between particle size and thermal transport properties in the electrode.Keywords: particle size, NMC, silicon, heat generation, separator
Procedia PDF Downloads 28520682 Wind Turbine Wake Prediction and Validation under a Stably-Stratified Atmospheric Boundary Layer
Authors: Yilei Song, Linlin Tian, Ning Zhao
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Turbulence energetics and structures in the wake of large-scale wind turbines under the stably-stratified atmospheric boundary layer (SABL) can be complicated due to the presence of low-level jets (LLJs), a region of higher wind speeds than the geostrophic wind speed. With a modified one-k-equation, eddy viscosity model specified for atmospheric flows as the sub-grid scale (SGS) model, a realistic atmospheric state of the stable ABL is well reproduced by large-eddy simulation (LES) techniques. Corresponding to the precursor stably stratification, the detailed wake properties of a standard 5-MW wind turbine represented as an actuator line model are provided. An engineering model is proposed for wake prediction based on the simulation statistics and gets validated. Results confirm that the proposed wake model can provide good predictions for wind turbines under the SABL.Keywords: large-eddy simulation, stably-stratified atmospheric boundary layer, wake model, wind turbine wake
Procedia PDF Downloads 17220681 Basic One-Dimensional Modelica®-Model for Simulation of Gas-Phase Adsorber Dynamics
Authors: Adrian Rettig, Silvan Schneider, Reto Tamburini, Mirko Kleingries, Ulf Christian Muller
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Industrial adsorption processes are, mainly due to si-multaneous heat and mass transfer, characterized by a high level of complexity. The conception of such processes often does not take place systematically; instead scale-up/down respectively number-up/down methods based on existing systems are used. This paper shows how Modelica® can be used to develop a transient model enabling a more systematic design of such ad- and desorption components and processes. The core of this model is a lumped-element submodel of a single adsorbent grain, where the thermodynamic equilibria and the kinetics of the ad- and desorption processes are implemented and solved on the basis of mass-, momentum and energy balances. For validation of this submodel, a fixed bed adsorber, whose characteristics are described in detail in the literature, was modeled and simulated. The simulation results are in good agreement with the experimental results from the literature. Therefore, the model development will be continued, and the extended model will be applied to further adsorber types like rotor adsorbers and moving bed adsorbers.Keywords: adsorption, desorption, linear driving force, dynamic model, Modelica®, integral equation approach
Procedia PDF Downloads 37020680 Forecasting Stock Prices Based on the Residual Income Valuation Model: Evidence from a Time-Series Approach
Authors: Chen-Yin Kuo, Yung-Hsin Lee
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Previous studies applying residual income valuation (RIV) model generally use panel data and single-equation model to forecast stock prices. Unlike these, this paper uses Taiwan longitudinal data to estimate multi-equation time-series models such as Vector Autoregressive (VAR), Vector Error Correction Model (VECM), and conduct out-of-sample forecasting. Further, this work assesses their forecasting performance by two instruments. In favor of extant research, the major finding shows that VECM outperforms other three models in forecasting for three stock sectors over entire horizons. It implies that an error correction term containing long-run information contributes to improve forecasting accuracy. Moreover, the pattern of composite shows that at longer horizon, VECM produces the greater reduction in errors, and performs substantially better than VAR.Keywords: residual income valuation model, vector error correction model, out of sample forecasting, forecasting accuracy
Procedia PDF Downloads 31420679 PLA Plastic as Biodegradable Material for 3D Printers
Authors: Juraj Beniak, Ľubomír Šooš, Peter Križan, Miloš Matúš
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Within Rapid Prototyping technologies are used many types of materials. Many of them are recyclable but there are still as plastic like, so practically they do not degrade in the landfill. Polylactic acid (PLA) is one of the special plastic materials which are biodegradable and also available for 3D printing within Fused Deposition Modelling (FDM) technology. The question is, if the mechanical properties of produced models are comparable to similar technical plastic materials which are usual for prototype production. Presented paper shows the experiments results for tensile strength measurements for specimens prepared with different 3D printer settings and model orientation. Paper contains also the comparison of tensile strength values with values measured on specimens produced by conventional technologies as injection moulding.Keywords: 3D printing, biodegradable plastic, fused deposition modeling, PLA plastic, rapid prototyping
Procedia PDF Downloads 41420678 Modeling of a Pendulum Test Including Skin and Muscles under Compression
Authors: M. J. Kang, Y. N. Jo, H. H. Yoo
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Pendulum tests were used to identify a stretch reflex and diagnose spasticity. Some researches tried to make a mathematical model to simulate the motions. Thighs are subject to compressive forces due to gravity during a pendulum test. Therefore, it affects knee trajectories. However, the most studies on the pendulum tests did not consider that conditions. We used Kelvin-Voight model as compression model of skin and muscles. In this study, we investigated viscoelastic behaviors of skin and muscles using gelatin blocks from experiments of the vibration of the compliantly supported beam. Then we calculated a dynamic stiffness and loss factors from the experiment and estimated a damping coefficient of the model. We also did pendulum tests of human lower limbs to validate the stiffness and damping coefficient of a skin model. To simulate the pendulum motion, we derive equations of motion. We used stretch reflex activation model to estimate muscle forces induced by the stretch reflex. To validate the results, we compared the activation with electromyography signals during experiments. The compression behavior of skin and muscles in this study can be applied to analyze sitting posture as wee as developing surgical techniques.Keywords: Kelvin-Voight model, pendulum test, skin and muscles under compression, stretch reflex
Procedia PDF Downloads 44420677 Fabrication and Characterization of PPy/rGO|PPy/ZnO Composite with Varying Zno Concentration as Anode for Fuel Cell Applications
Authors: Bryan D. Llenarizas, Maria Carla F. Manzano
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The rapid growth of electricity demand has led to a pursuit of alternative energy sources with high power output and not harmful to the environment. The fuel cell is a device that generates electricity via chemical reactions between the fuel and oxidant. Fuel cells have been known for decades, but the development of high-power output and durability was still one of the drawbacks of this energy source. This study investigates the potential of layer-by-layer composite for fuel cell applications. A two-electrode electrochemical cell was used for the galvanostatic electrochemical deposition method to fabricate a Polypyrrole/rGO|Polypyrrole/ZnO layer-by-layer composite material for fuel cell applications. In the synthesis, the first layer comprised 0.1M pyrrole monomer and 1mg of rGO, while the second layer had 0.1M pyrrole monomer and variations of ZnO concentration ranging from 0.08M up to 0.12M. A constant current density of 8mA/cm² was applied for 1 hour in fabricating each layer. Scanning electron microscopy (SEM) for the fabricated LBL material shows a globular surface with white spots. These white spots are the ZnO particles confirmed by energy-dispersive X-ray spectroscopy, indicating a successful deposition of the second layer onto the first layer. The observed surface morphology was consistent for each variation of ZnO concentrations. AC measurements were conducted to obtain the AC resistance of the fabricated film. Results show a decrease in AC resistance as the concentration of ZnO increases.Keywords: anode, composite material, electropolymerization, fuel cell, galvanostatic, polypyrrole
Procedia PDF Downloads 7720676 Application of Fractional Model Predictive Control to Thermal System
Authors: Aymen Rhouma, Khaled Hcheichi, Sami Hafsi
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The article presents an application of Fractional Model Predictive Control (FMPC) to a fractional order thermal system using Controlled Auto Regressive Integrated Moving Average (CARIMA) model obtained by discretization of a continuous fractional differential equation. Moreover, the output deviation approach is exploited to design the K -step ahead output predictor, and the corresponding control law is obtained by solving a quadratic cost function. Experiment results onto a thermal system are presented to emphasize the performances and the effectiveness of the proposed predictive controller.Keywords: fractional model predictive control, fractional order systems, thermal system, predictive control
Procedia PDF Downloads 40920675 Modelling Sudden Deaths from Myocardial Infarction and Stroke
Authors: Y. S. Yusoff, G. Streftaris, H. R Waters
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Death within 30 days is an important factor to be looked into, as there is a significant risk of deaths immediately following or soon after, Myocardial Infarction (MI) or stroke. In this paper, we will model the deaths within 30 days following a Myocardial Infarction (MI) or stroke in the UK. We will see how the probabilities of sudden deaths from MI or stroke have changed over the period 1981-2000. We will model the sudden deaths using a Generalized Linear Model (GLM), fitted using the R statistical package, under a Binomial distribution for the number of sudden deaths. We parameterize our model using the extensive and detailed data from the Framingham Heart Study, adjusted to match UK rates. The results show that there is a reduction for the sudden deaths following a MI over time but no significant improvement for sudden deaths following a stroke.Keywords: sudden deaths, myocardial infarction, stroke, ischemic heart disease
Procedia PDF Downloads 28420674 3D Modelling and Numerical Analysis of Human Inner Ear by Means of Finite Elements Method
Authors: C. Castro-Egler, A. Durán-Escalante, A. García-González
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This paper presents a method to generate a finite element model of the human auditory inner ear system. The geometric model has been realized using 2D images from a virtual model of temporal bones. A point cloud has been gotten manually from those images to construct a whole mesh with hexahedral elements. The main difference with the predecessor models is the spiral shape of the cochlea with its three scales completely defined: scala tympani, scala media and scala vestibuli; which are separate by basilar membrane and Reissner membrane. To validate this model, numerical simulations have been realised with two models: an isolated inner ear and a whole model of human auditory system. Ideal conditions of displacement are applied over the oval window in the isolated Inner Ear model. The whole model is made up of the outer auditory channel, the tympani, the ossicular chain, and the inner ear. The boundary condition for the whole model is 1Pa over the auditory channel entrance. The numerical simulations by FEM have been done using a harmonic analysis with a frequency range between 100-10.000 Hz with an interval of 100Hz. The following results have been carried out: basilar membrane displacement; the scala media pressure according to the cochlea length and the transfer function of the middle ear normalized with the pressure in the tympanic membrane. The basilar membrane displacements and the pressure in the scala media make it possible to validate the response in frequency of the basilar membrane.Keywords: finite elements method, human auditory system model, numerical analysis, 3D modelling cochlea
Procedia PDF Downloads 36220673 Documents Emotions Classification Model Based on TF-IDF Weighting Measure
Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees
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Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.Keywords: emotion detection, TF-IDF, WEKA tool, classification algorithms
Procedia PDF Downloads 48220672 An Automatic Speech Recognition Tool for the Filipino Language Using the HTK System
Authors: John Lorenzo Bautista, Yoon-Joong Kim
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This paper presents the development of a Filipino speech recognition tool using the HTK System. The system was trained from a subset of the Filipino Speech Corpus developed by the DSP Laboratory of the University of the Philippines-Diliman. The speech corpus was both used in training and testing the system by estimating the parameters for phonetic HMM-based (Hidden-Markov Model) acoustic models. Experiments on different mixture-weights were incorporated in the study. The phoneme-level word-based recognition of a 5-state HMM resulted in an average accuracy rate of 80.13 for a single-Gaussian mixture model, 81.13 after implementing a phoneme-alignment, and 87.19 for the increased Gaussian-mixture weight model. The highest accuracy rate of 88.70% was obtained from a 5-state model with 6 Gaussian mixtures.Keywords: Filipino language, Hidden Markov Model, HTK system, speech recognition
Procedia PDF Downloads 47820671 Prediction of the Torsional Vibration Characteristics of a Rotor-Shaft System Using Its Scale Model and Scaling Laws
Authors: Jia-Jang Wu
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This paper presents the scaling laws that provide the criteria of geometry and dynamic similitude between the full-size rotor-shaft system and its scale model, and can be used to predict the torsional vibration characteristics of the full-size rotor-shaft system by manipulating the corresponding data of its scale model. The scaling factors, which play fundamental roles in predicting the geometry and dynamic relationships between the full-size rotor-shaft system and its scale model, for torsional free vibration problems between scale and full-size rotor-shaft systems are firstly obtained from the equation of motion of torsional free vibration. Then, the scaling factor of external force (i.e., torque) required for the torsional forced vibration problems is determined based on the Newton’s second law. Numerical results show that the torsional free and forced vibration characteristics of a full-size rotor-shaft system can be accurately predicted from those of its scale models by using the foregoing scaling factors. For this reason, it is believed that the presented approach will be significant for investigating the relevant phenomenon in the scale model tests.Keywords: torsional vibration, full-size model, scale model, scaling laws
Procedia PDF Downloads 39320670 Modeling and Behavior of Structural Walls
Authors: Salima Djehaichia, Rachid Lassoued
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Reinforced concrete structural walls are very efficient elements for protecting buildings against excessive early damage and against collapse under earthquake actions. It is therefore of interest to develop a numerical model which simulates the typical behavior of these units, this paper presents and describes different modeling techniques that have been used by researchers and their advantages and limitations mentioned. The earthquake of Boumerdes in 2003 has demonstrated the fragility of structures and total neglect of sismique design rules in the realization of old buildings. Significant damage and destruction of buildings caused by this earthquake are not due to the choice of type of material, but the design and the study does not congruent with seismic code requirements and bad quality of materials. For idealizing the failure of rules, a parametric study focuses on: low rate of reinforcements, type of reinforcement, resistance moderate of concrete. As an application the modeling strategy based on finite elements combined with a discretization of wall more solicited by successive thin layers. The estimated performance level achieved during a seismic action is obtained from capacity curves under incrementally increasing loads. Using a pushover analysis, a characteristic non linear force-displacement relationship can be determined. The results of numeric model are confronted with those of Algerian Para seismic Rules (RPA) in force have allowed the determination of profits in terms of displacement, shearing action, ductility.Keywords: modeling, old building, pushover analysis, structural walls
Procedia PDF Downloads 24520669 Effect of the Nature of Silica Precursor in Zeolite ZSM-22 Synthesis
Authors: Nyiko M. Chauke, James Ramontja, Richard M. Moutloali
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The zeolite ZSM-22 material demonstrated effective hydrophilic character as a nanoadditive filler in the preparation of nanocomposite membranes. In this study, nanorods ZSM-22 zeolite materials were hydrothermally synthesised from a homogenous gel mixture prepared using different silica precursors: colloidal silica, fumed silica, tetraethylorthosilicate (TEOS), and aluminium precursor: aluminium sulphate octadecahydrate (Al₂(SO₄)₃.18H₂O to Si/Al of 60. This was focused on developing a defect-free zeolite framework for effective use in applications such as membrane separation process, adsorption, and catalysis. The obtained ZSM-22 zeolite materials with 60 Si/Al ratio exhibits high crystallinity, hydrophilicity, and needle-like morphologies, suggesting successful synthesis as shown by X-ray Diffraction (XRD), Brunauer-Emmett-Teller (BET), Fourier-Transform Infrared Spectroscopy (FTIR), Transmission Electron Microscopy (TEM) and Scanning Electron Microscopy (SEM) physicochemical analysis. It was revealed that the use of different nature of silica precursors significantly influenced the properties of the final product and contributed to the development of defect-free zeolite material. As such, the crystalline nanorods of Theta-1 (TON) ZSM-22 obtained from TEOS silica showed high phase purity, defect-free, and narrow particle size distribution. Morphological analysis exhibited that the use of TEOS as silica precursor was effective than its counterparts and produced high crystalline need-like agglomerated particles.Keywords: silica precursor, hydrothermal synthesis, zeolite material, ZSM-22
Procedia PDF Downloads 13620668 Assessing Firm Readiness to Implement Cloud Computing: Toward a Comprehensive Model
Authors: Seyed Mohammadbagher Jafari, Elahe Mahdizadeh, Masomeh Ghahremani
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Nowadays almost all organizations depend on information systems to run their businesses. Investment on information systems and their maintenance to keep them always in best situation to support firm business is one of the main issues for every organization. The new concept of cloud computing was developed as a technical and economic model to address this issue. In cloud computing the computing resources, including networks, applications, hardwares and services are configured as needed and are available at the moment of request. However, migration to cloud is not an easy task and there are many issues that should be taken into account. This study tries to provide a comprehensive model to assess a firm readiness to implement cloud computing. By conducting a systematic literature review, four dimensions of readiness were extracted which include technological, human, organizational and environmental dimensions. Every dimension has various criteria that have been discussed in details. This model provides a framework for cloud computing readiness assessment. Organizations that intend to migrate to cloud can use this model as a tool to assess their firm readiness before making any decision on cloud implementation.Keywords: cloud computing, human readiness, organizational readiness, readiness assessment model
Procedia PDF Downloads 39420667 Overview of a Quantum Model for Decision Support in a Sensor Network
Authors: Shahram Payandeh
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This paper presents an overview of a model which can be used as a part of a decision support system when fusing information from multiple sensing environment. Data fusion has been widely studied in the past few decades and numerous frameworks have been proposed to facilitate decision making process under uncertainties. Multi-sensor data fusion technology plays an increasingly significant role during people tracking and activity recognition. This paper presents an overview of a quantum model as a part of a decision-making process in the context of multi-sensor data fusion. The paper presents basic definitions and relationships associating the decision-making process and quantum model formulation in the presence of uncertainties.Keywords: quantum model, sensor space, sensor network, decision support
Procedia PDF Downloads 22520666 Model Order Reduction for Frequency Response and Effect of Order of Method for Matching Condition
Authors: Aref Ghafouri, Mohammad javad Mollakazemi, Farhad Asadi
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In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further.Keywords: frequency response, order of model reduction, frequency matching condition, nonlinear experimental data
Procedia PDF Downloads 40020665 A Dynamic Model for Circularity Assessment of Nutrient Recovery from Domestic Sewage
Authors: Anurag Bhambhani, Jan Peter Van Der Hoek, Zoran Kapelan
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The food system depends on the availability of Phosphorus (P) and Nitrogen (N). Growing population, depleting Phosphorus reserves and energy-intensive industrial nitrogen fixation are threats to their future availability. Recovering P and N from domestic sewage water offers a solution. Recovered P and N can be applied to agricultural land, replacing virgin P and N. Thus, recovery from sewage water offers a solution befitting a circular economy. To ensure minimum waste and maximum resource efficiency a circularity assessment method is crucial to optimize nutrient flows and minimize losses. Material Circularity Indicator (MCI) is a useful method to quantify the circularity of materials. It was developed for materials that remain within the market and recently extended to include biotic materials that may be composted or used for energy recovery after end-of-use. However, MCI has not been used in the context of nutrient recovery. Besides, MCI is time-static, i.e., it cannot account for dynamic systems such as the terrestrial nutrient cycles. Nutrient application to agricultural land is a highly dynamic process wherein flows and stocks change with time. The rate of recycling of nutrients in nature can depend on numerous factors such as prevailing soil conditions, local hydrology, the presence of animals, etc. Therefore, a dynamic model of nutrient flows with indicators is needed for the circularity assessment. A simple substance flow model of P and N will be developed with the help of flow equations and transfer coefficients that incorporate the nutrient recovery step along with the agricultural application, the volatilization and leaching processes, plant uptake and subsequent animal and human uptake. The model is then used for calculating the proportions of linear and restorative flows (coming from reused/recycled sources). The model will simulate the adsorption process based on the quantity of adsorbent and nutrient concentration in the water. Thereafter, the application of the adsorbed nutrients to agricultural land will be simulated based on adsorbate release kinetics, local soil conditions, hydrology, vegetation, etc. Based on the model, the restorative nutrient flow (returning to the sewage plant following human consumption) will be calculated. The developed methodology will be applied to a case study of resource recovery from wastewater. In the aforementioned case study located in Italy, biochar or zeolite is to be used for recovery of P and N from domestic sewage through adsorption and thereafter, used as a slow-release fertilizer in agriculture. Using this model, information regarding the efficiency of nutrient recovery and application can be generated. This can help to optimize the recovery process and application of the nutrients. Consequently, this will help to optimize nutrient recovery and application and reduce the dependence of the food system on the virgin extraction of P and N.Keywords: circular economy, dynamic substance flow, nutrient cycles, resource recovery from water
Procedia PDF Downloads 19620664 Nonlinear Modeling of the PEMFC Based on NNARX Approach
Authors: Shan-Jen Cheng, Te-Jen Chang, Kuang-Hsiung Tan, Shou-Ling Kuo
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Polymer Electrolyte Membrane Fuel Cell (PEMFC) is such a time-vary nonlinear dynamic system. The traditional linear modeling approach is hard to estimate structure correctly of PEMFC system. From this reason, this paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-regressive model with eXogenous inputs (NNARX) approach. The multilayer perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The validity and accuracy of NNARX model are tested by one step ahead relating output voltage to input current from measured experimental of PEMFC. The results show that the obtained nonlinear NNARX model can efficiently approximate the dynamic mode of the PEMFC and model output and system measured output consistently.Keywords: PEMFC, neural network, nonlinear modeling, NNARX
Procedia PDF Downloads 38020663 The Profit Trend of Cosmetics Products Using Bootstrap Edgeworth Approximation
Authors: Edlira Donefski, Lorenc Ekonomi, Tina Donefski
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Edgeworth approximation is one of the most important statistical methods that has a considered contribution in the reduction of the sum of standard deviation of the independent variables’ coefficients in a Quantile Regression Model. This model estimates the conditional median or other quantiles. In this paper, we have applied approximating statistical methods in an economical problem. We have created and generated a quantile regression model to see how the profit gained is connected with the realized sales of the cosmetic products in a real data, taken from a local business. The Linear Regression of the generated profit and the realized sales was not free of autocorrelation and heteroscedasticity, so this is the reason that we have used this model instead of Linear Regression. Our aim is to analyze in more details the relation between the variables taken into study: the profit and the finalized sales and how to minimize the standard errors of the independent variable involved in this study, the level of realized sales. The statistical methods that we have applied in our work are Edgeworth Approximation for Independent and Identical distributed (IID) cases, Bootstrap version of the Model and the Edgeworth approximation for Bootstrap Quantile Regression Model. The graphics and the results that we have presented here identify the best approximating model of our study.Keywords: bootstrap, edgeworth approximation, IID, quantile
Procedia PDF Downloads 15820662 A Location-Allocation-Routing Model for a Home Health Care Supply Chain Problem
Authors: Amir Mohammad Fathollahi Fard, Mostafa Hajiaghaei-Keshteli, Mohammad Mahdi Paydar
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With increasing life expectancy in developed countries, the role of home care services is highlighted by both academia and industrial contributors in Home Health Care Supply Chain (HHCSC) companies. The main decisions in such supply chain systems are the location of pharmacies, the allocation of patients to these pharmacies and also the routing and scheduling decisions of nurses to visit their patients. In this study, for the first time, an integrated model is proposed to consist of all preliminary and necessary decisions in these companies, namely, location-allocation-routing model. This model is a type of NP-hard one. Therefore, an Imperialist Competitive Algorithm (ICA) is utilized to solve the model, especially in large sizes. Results confirm the efficiency of the developed model for HHCSC companies as well as the performance of employed ICA.Keywords: home health care supply chain, location-allocation-routing problem, imperialist competitive algorithm, optimization
Procedia PDF Downloads 39720661 Efficient Frequent Itemset Mining Methods over Real-Time Spatial Big Data
Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz
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In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query
Procedia PDF Downloads 16020660 Masked Candlestick Model: A Pre-Trained Model for Trading Prediction
Authors: Ling Qi, Matloob Khushi, Josiah Poon
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This paper introduces a pre-trained Masked Candlestick Model (MCM) for trading time-series data. The pre-trained model is based on three core designs. First, we convert trading price data at each data point as a set of normalized elements and produce embeddings of each element. Second, we generate a masked sequence of such embedded elements as inputs for self-supervised learning. Third, we use the encoder mechanism from the transformer to train the inputs. The masked model learns the contextual relations among the sequence of embedded elements, which can aid downstream classification tasks. To evaluate the performance of the pre-trained model, we fine-tune MCM for three different downstream classification tasks to predict future price trends. The fine-tuned models achieved better accuracy rates for all three tasks than the baseline models. To better analyze the effectiveness of MCM, we test the same architecture for three currency pairs, namely EUR/GBP, AUD/USD, and EUR/JPY. The experimentation results demonstrate MCM’s effectiveness on all three currency pairs and indicate the MCM’s capability for signal extraction from trading data.Keywords: masked language model, transformer, time series prediction, trading prediction, embedding, transfer learning, self-supervised learning
Procedia PDF Downloads 12320659 Conditions for Model Matching of Switched Asynchronous Sequential Machines with Output Feedback
Authors: Jung–Min Yang
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Solvability of the model matching problem for input/output switched asynchronous sequential machines is discussed in this paper. The control objective is to determine the existence condition and design algorithm for a corrective controller that can match the stable-state behavior of the closed-loop system to that of a reference model. Switching operations and correction procedures are incorporated using output feedback so that the controlled switched machine can show the desired input/output behavior. A matrix expression is presented to address reachability of switched asynchronous sequential machines with output equivalence with respect to a model. The presented reachability condition for the controller design is validated in a simple example.Keywords: asynchronous sequential machines, corrective control, model matching, input/output control
Procedia PDF Downloads 34220658 Large Strain Creep Analysis of Composite Thick-Walled Anisotropic Cylinders
Authors: Vinod Kumar Arya
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Creep analysis of a thick-walled composite anisotropic cylinder under internal pressure and considering large strains is presented. Using a threshold creep law for composite materials, expressions for stresses, strains, and strain rates are derived for several anisotropic cases. Numerical results, presented through several graphs and tables, depict the effect of anisotropy on the stress, strain, and strain rate distributions. Since for a specific type of material anisotropy described in the paper, these quantities are found to have the lowest values at the inner radius (the potential location of cylinder failure), it is concluded that by employing such an anisotropic material for the design of a thick-walled cylinder a longer service life for the cylinder may be achieved.Keywords: creep, composites, large strains, thick-walled cylinders, anisotropy
Procedia PDF Downloads 14720657 Defining a Holistic Approach for Model-Based System Engineering: Paradigm and Modeling Requirements
Authors: Hycham Aboutaleb, Bruno Monsuez
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Current systems complexity has reached a degree that requires addressing conception and design issues while taking into account all the necessary aspects. Therefore, one of the main challenges is the way complex systems are specified and designed. The exponential growing effort, cost and time investment of complex systems in modeling phase emphasize the need for a paradigm, a framework and a environment to handle the system model complexity. For that, it is necessary to understand the expectations of the human user of the model and his limits. This paper presents a generic framework for designing complex systems, highlights the requirements a system model needs to fulfill to meet human user expectations, and defines the refined functional as well as non functional requirements modeling tools needs to meet to be useful in model-based system engineering.Keywords: system modeling, modeling language, modeling requirements, framework
Procedia PDF Downloads 52920656 Effect of Quenching Medium on the Hardness of Dual Phase Steel Heat Treated at a High Temperature
Authors: Tebogo Mabotsa, Tamba Jamiru, David Ibrahim
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Dual phase(DP) steel consists essentially of fine grained equiaxial ferrite and a dispersion of martensite. Martensite is the primary precipitate in DP steels, it is the main resistance to dislocation motion within the material. The objective of this paper is to present a relation between the intercritical annealing holding time and the hardness of a dual phase steel. The initial heat treatment involved heating the specimens to 1000oC and holding the sample at that temperature for 30 minutes. After the initial heat treatment, the samples were heated to 770oC and held for a varying amount of time at constant temperature. The samples were held at 30, 60, and 90 minutes respectively. After heating and holding the samples at the austenite-ferrite phase field, the samples were quenched in water, brine, and oil for each holding time. The experimental results proved that an equation for predicting the hardness of a dual phase steel as a function of the intercritical holding time is possible. The relation between intercritical annealing holding time and hardness of a dual phase steel heat treated at high temperatures is parabolic in nature. Theoretically, the model isdependent on the cooling rate because the model differs for each quenching medium; therefore, a universal hardness equation can be derived where the cooling rate is a variable factor.Keywords: quenching medium, annealing temperature, dual phase steel, martensite
Procedia PDF Downloads 8120655 A Stochastic Analytic Hierarchy Process Based Weighting Model for Sustainability Measurement in an Organization
Authors: Faramarz Khosravi, Gokhan Izbirak
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A weighted statistical stochastic based Analytical Hierarchy Process (AHP) model for modeling the potential barriers and enablers of sustainability for measuring and assessing the sustainability level is proposed. For context-dependent potential barriers and enablers, the proposed model takes the basis of the properties of the variables describing the sustainability functions and was developed into a realistic analytical model for the sustainable behavior of an organization. This thus serves as a means for measuring the sustainability of the organization. The main focus of this paper was the application of the AHP tool in a statistically-based model for measuring sustainability. Hence a strong weighted stochastic AHP based procedure was achieved. A case study scenario of a widely reported major Canadian electric utility was adopted to demonstrate the applicability of the developed model and comparatively examined its results with those of an equal-weighted model method. Variations in the sustainability of a company, as fluctuations, were figured out during the time. In the results obtained, sustainability index for successive years changed form 73.12%, 79.02%, 74.31%, 76.65%, 80.49%, 79.81%, 79.83% to more exact values 73.32%, 77.72%, 76.76%, 79.41%, 81.93%, 79.72%, and 80,45% according to priorities of factors that have found by expert views, respectively. By obtaining relatively necessary informative measurement indicators, the model can practically and effectively evaluate the sustainability extent of any organization and also to determine fluctuations in the organization over time.Keywords: AHP, sustainability fluctuation, environmental indicators, performance measurement
Procedia PDF Downloads 12020654 A Robust Theoretical Elastoplastic Continuum Damage T-H-M Model for Rock Surrounding a Wellbore
Authors: Nikolaos Reppas, Yilin Gui, Ben Wetenhall, Colin Davie
Abstract:
Injection of CO2 inside wellbore can induce different kind of loadings that can lead to thermal, hydraulic, and mechanical changes on the surrounding rock. A dual-porosity theoretical constitutive model will be presented for the stability analysis of the wellbore during CO2 injection. An elastoplastic damage response will be considered. A bounding yield surface will be presented considering damage effects on sandstone. The main target of the research paper is to present a theoretical constitutive model that can help industries to safely store CO2 in geological rock formations and forecast any changes on the surrounding rock of the wellbore. The fully coupled elasto-plastic damage Thermo-Hydraulic-Mechanical theoretical model will be validated from existing experimental data for sandstone after simulating some scenarios by using FEM on MATLAB software.Keywords: carbon capture and storage, rock mechanics, THM effects on rock, constitutive model
Procedia PDF Downloads 151