Search results for: union model
16315 Modeling of Global Solar Radiation on a Horizontal Surface Using Artificial Neural Network: A Case Study
Authors: Laidi Maamar, Hanini Salah
Abstract:
The present work investigates the potential of artificial neural network (ANN) model to predict the horizontal global solar radiation (HGSR). The ANN is developed and optimized using three years meteorological database from 2011 to 2013 available at the meteorological station of Blida (Blida 1 university, Algeria, Latitude 36.5°, Longitude 2.81° and 163 m above mean sea level). Optimal configuration of the ANN model has been determined by minimizing the Root Means Square Error (RMSE) and maximizing the correlation coefficient (R2) between observed and predicted data with the ANN model. To select the best ANN architecture, we have conducted several tests by using different combinations of parameters. A two-layer ANN model with six hidden neurons has been found as an optimal topology with (RMSE=4.036 W/m²) and (R²=0.999). A graphical user interface (GUI), was designed based on the best network structure and training algorithm, to enhance the users’ friendliness application of the model.Keywords: artificial neural network, global solar radiation, solar energy, prediction, Algeria
Procedia PDF Downloads 49016314 Checking Energy Efficiency by Simulation Tools: The Case of Algerian Ksourian Models
Authors: Khadidja Rahmani, Nahla Bouaziz
Abstract:
Algeria is known for its rich heritage. It owns an immense historical heritage with a universal reputation. Unfortunately, this wealth is withered because of abundance. This research focuses on the Ksourian model, which constitutes a large portion of this wealth. In fact, the Ksourian model is not just a witness to a great part of history or a vernacular culture, but also it includes a panoply of assets in terms of energetic efficiency. In this context, the purpose of our work is to evaluate the performance of the old techniques which are derived from the Ksourian model , and that using the simulation tools. The proposed method is decomposed in two steps; the first consists of isolate and reintroduce each device into a basic model, then run a simulation series on acquired models. And this in order to test the contribution of each of these dialectal processes. In another scale of development, the second step consists of aggregating all these processes in an aboriginal model, then we restart the simulation, to see what it will give this mosaic on the environmental and energetic plan .The model chosen for this study is one of the ksar units of Knadsa city of Bechar (Algeria). This study does not only show the ingenuity of our ancestors in their know-how, and their adapting power to the aridity of the climate, but also proves that their conceptions subscribe in the current concerns of energy efficiency, and respond to the requirements of sustainable development.Keywords: dialectal processes, energy efficiency, evaluation, Ksourian model, simulation tools
Procedia PDF Downloads 18716313 Seismic Response of Moment Resisting Steel Frame with Hysteresis Envelope Model of Joints
Authors: Krolo Paulina
Abstract:
The seismic response of moment-resisting steel frames depends on the behavior of the joints, especially when they are considered as ductile zones. The aim of this research is to provide a realistic assessment of the moment-resisting steel frame behavior under seismic loading using nonlinear static pushover analysis (N2 method). The hysteresis behavior of the joints in the frame model was described using a new hysteresis envelope model. The obtained seismic response was compared with the results of the seismic analysis obtained for the same steel frame that takes into account the monotonic model of the joints.Keywords: beam-to-column joints, hysteresis envelope model, moment-resisting frame, nonlinear static pushover analysis, N2 method
Procedia PDF Downloads 25916312 Models of Copyrights System
Authors: A. G. Matveev
Abstract:
The copyrights system is a combination of different elements. The number, content and the correlation of these elements are different for different legal orders. The models of copyrights systems display this system in terms of the interaction of economic and author's moral rights. Monistic and dualistic models are the most popular ones. The article deals with different points of view on the monism and dualism in copyright system. A specific model of the copyright in Switzerland in the XXth century is analyzed. The evolution of a French dualistic model of copyright is shown. The author believes that one should talk not about one, but rather about a number of dualism forms of copyright system.Keywords: copyright, exclusive copyright, economic rights, author's moral rights, rights of personality, monistic model, dualistic model
Procedia PDF Downloads 41316311 Seismic Safety Evaluation of Weir Structures Using the Finite and Infinite Element Method
Authors: Ho Young Son, Bu Seog Ju, Woo Young Jung
Abstract:
This study presents the seismic safety evaluation of weir structure subjected to strong earthquake ground motions, as a flood defense structure in civil engineering structures. The seismic safety analysis procedure was illustrated through development of Finite Element (FE) and InFinite Element (IFE) method in ABAQUS platform. The IFE model was generated by CINPS4, 4-node linear one-way infinite model as a sold continuum infinite element in foundation areas of the weir structure and then nonlinear FE model using friction model for soil-structure interactions was applied in this study. In order to understand the complex behavior of weir structures, nonlinear time history analysis was carried out. Consequently, it was interesting to note that the compressive stress gave more vulnerability to the weir structure, in comparison to the tensile stress, during an earthquake. The stress concentration of the weir structure was shown at the connection area between the weir body and stilling basin area. The stress both tension and compression was reduced in IFE model rather than FE model of weir structures.Keywords: seismic, numerical analysis, FEM, weir, boundary condition
Procedia PDF Downloads 44416310 Sliding Mode Controller for Active Suspension System on a Passenger Car Model
Authors: Nouby M. Ghazaly, Ahmed O. Moaaz, Mostafa Makrahy
Abstract:
The main purpose of a car suspension system is to reduce the vibrations resulting from road roughness. The main objective of this research paper is to decrease vibration and improve passenger comfort through controlling car suspension system using sliding mode control techniques. The mathematical model for passive and active suspensions systems for quarter car model which subject to excitation from different road profiles is obtained. The active suspension system is synthesized based on sliding mode control for a quarter car model. The performance of the sliding mode control is determined through computer simulations using MATLAB and SIMULINK toolbox. The simulated results plotted in time domain, and root mean square values. It is found that active suspension system using sliding mode control improves the ride comfort and decrease vibration.Keywords: quarter car model, active suspension system, sliding mode control, road profile
Procedia PDF Downloads 30016309 Resolution and Experimental Validation of the Asymptotic Model of a Viscous Laminar Supersonic Flow around a Thin Airfoil
Authors: Eddegdag Nasser, Naamane Azzeddine, Radouani Mohammed, Ensam Meknes
Abstract:
In this study, we are interested in the asymptotic modeling of the two-dimensional stationary supersonic flow of a viscous compressible fluid around wing airfoil. The aim of this article is to solve the partial differential equations of the flow far from the leading edge and near the wall using the triple-deck technique is what brought again in precision according to the principle of least degeneration. In order to validate our theoretical model, these obtained results will be compared with the experimental results. The comparison of the results of our model with experimentation has shown that they are quantitatively acceptable compared to the obtained experimental results. The experimental study was conducted using the AF300 supersonic wind tunnel and a NACA Reduced airfoil model with two pressure Taps on extrados. In this experiment, we have considered the incident upstream supersonic Mach number over a dissymmetric NACA airfoil wing. The validation and the accuracy of the results support our model.Keywords: supersonic, viscous, triple deck technique, asymptotic methods, AF300 supersonic wind tunnel, reduced airfoil model
Procedia PDF Downloads 22816308 Stability Analysis for an Extended Model of the Hypothalamus-Pituitary-Thyroid Axis
Authors: Beata Jackowska-Zduniak
Abstract:
We formulate and analyze a mathematical model describing dynamics of the hypothalamus-pituitary-thyroid homoeostatic mechanism in endocrine system. We introduce to this system two types of couplings and delay. In our model, feedback controls the secretion of thyroid hormones and delay reflects time lags required for transportation of the hormones. The influence of delayed feedback on the stability behaviour of the system is discussed. Analytical results are illustrated by numerical examples of the model dynamics. This system of equations describes normal activity of the thyroid and also a couple of types of malfunctions (e.g. hyperthyroidism).Keywords: mathematical modeling, ordinary differential equations, endocrine system, delay differential equation
Procedia PDF Downloads 32916307 Safe and Efficient Deep Reinforcement Learning Control Model: A Hydroponics Case Study
Authors: Almutasim Billa A. Alanazi, Hal S. Tharp
Abstract:
Safe performance and efficient energy consumption are essential factors for designing a control system. This paper presents a reinforcement learning (RL) model that can be applied to control applications to improve safety and reduce energy consumption. As hardware constraints and environmental disturbances are imprecise and unpredictable, conventional control methods may not always be effective in optimizing control designs. However, RL has demonstrated its value in several artificial intelligence (AI) applications, especially in the field of control systems. The proposed model intelligently monitors a system's success by observing the rewards from the environment, with positive rewards counting as a success when the controlled reference is within the desired operating zone. Thus, the model can determine whether the system is safe to continue operating based on the designer/user specifications, which can be adjusted as needed. Additionally, the controller keeps track of energy consumption to improve energy efficiency by enabling the idle mode when the controlled reference is within the desired operating zone, thus reducing the system energy consumption during the controlling operation. Water temperature control for a hydroponic system is taken as a case study for the RL model, adjusting the variance of disturbances to show the model’s robustness and efficiency. On average, the model showed safety improvement by up to 15% and energy efficiency improvements by 35%- 40% compared to a traditional RL model.Keywords: control system, hydroponics, machine learning, reinforcement learning
Procedia PDF Downloads 16916306 Prediction of Coronary Heart Disease Using Fuzzy Logic
Authors: Elda Maraj, Shkelqim Kuka
Abstract:
Coronary heart disease causes many deaths in the world. Unfortunately, this problem will continue to increase in the future. In this paper, a fuzzy logic model to predict coronary heart disease is presented. This model has been developed with seven input variables and one output variable that was implemented for 30 patients in Albania. Here fuzzy logic toolbox of MATLAB is used. Fuzzy model inputs are considered as cholesterol, blood pressure, physical activity, age, BMI, smoking, and diabetes, whereas the output is the disease classification. The fuzzy sets and membership functions are chosen in an appropriate manner. Centroid method is used for defuzzification. The database is taken from University Hospital Center "Mother Teresa" in Tirana, Albania.Keywords: coronary heart disease, fuzzy logic toolbox, membership function, prediction model
Procedia PDF Downloads 14816305 A Boundary Fitted Nested Grid Model for Tsunami Computation along Penang Island in Peninsular Malaysia
Authors: Md. Fazlul Karim, Ahmad Izani Md. Ismail, Mohammed Ashaque Meah
Abstract:
This paper focuses on the development of a 2-D Boundary Fitted and Nested Grid (BFNG) model to compute the tsunami propagation of Indonesian tsunami 2004 along the coastal region of Penang in Peninsular Malaysia. In the presence of a curvilinear coastline, boundary fitted grids are suitable to represent the model boundaries accurately. On the other hand, when large gradient of velocity within a confined area is expected, the use of a nested grid system is appropriate to improve the numerical accuracy with the least grid numbers. This paper constructs a shallow water nested and orthogonal boundary fitted grid model and presents computational results of the tsunami impact on the Penang coast due to the Indonesian tsunami of 2004. The results of the numerical simulations are compared with available data.Keywords: boundary fitted nested model, tsunami, Penang Island, 2004 Indonesian Tsunami
Procedia PDF Downloads 31116304 The Status of BIM Adoption in Six Continents
Authors: Wooyoung Jung, Ghang Lee
Abstract:
This paper paper reports the worldwide status of building information modeling (BIM) adoption from the perspectives of the engagement level, the Hype Cycle model, the technology diffusion model, and BIM-uses. An online survey was distributed, and 156 experts from six continents responded. Overall, North America was the most advanced continent, followed by Oceania and Europe. Countries in Asia perceived their phase mainly as slope of enlightenment (mature) in the Hype Cycle model. In the technology diffusion model, the main BIM-users worldwide were “early majority” (third phase), but those in the Middle East/Africa and South America were “early adopters” (second phase). In addition, the more advanced the country, the more number of BIM services employed in general. In summary, North America, Europe, Oceania, and Asia were advancing rapidly toward the mature stage of BIM, whereas the Middle East/Africa and South America were still in the early phase. The simple indexes used in this study may be used to track the worldwide status of BIM adoption in long-term surveys.Keywords: BIM adoption, BIM services, hype cycle model, technology diffusion model
Procedia PDF Downloads 55016303 Estimation of the Road Traffic Emissions and Dispersion in the Developing Countries Conditions
Authors: Hicham Gourgue, Ahmed Aharoune, Ahmed Ihlal
Abstract:
We present in this work our model of road traffic emissions (line sources) and dispersion of these emissions, named DISPOLSPEM (Dispersion of Poly Sources and Pollutants Emission Model). In its emission part, this model was designed to keep the consistent bottom-up and top-down approaches. It also allows to generate emission inventories from reduced input parameters being adapted to existing conditions in Morocco and in the other developing countries. While several simplifications are made, all the performance of the model results are kept. A further important advantage of the model is that it allows the uncertainty calculation and emission rate uncertainty according to each of the input parameters. In the dispersion part of the model, an improved line source model has been developed, implemented and tested against a reference solution. It provides improvement in accuracy over previous formulas of line source Gaussian plume model, without being too demanding in terms of computational resources. In the case study presented here, the biggest errors were associated with the ends of line source sections; these errors will be canceled by adjacent sections of line sources during the simulation of a road network. In cases where the wind is parallel to the source line, the use of the combination discretized source and analytical line source formulas minimizes remarkably the error. Because this combination is applied only for a small number of wind directions, it should not excessively increase the calculation time.Keywords: air pollution, dispersion, emissions, line sources, road traffic, urban transport
Procedia PDF Downloads 43316302 A Model to Assist Military Mission Planners in Identifying and Assessing Variables Impacting Food Security
Authors: Lynndee Kemmet
Abstract:
The U.S. military plays an increasing role in supporting political stability efforts, and this includes efforts to prevent the food insecurity that can trigger political and social instability. This paper presents a model that assists military commanders in identifying variables that impact food production and distribution in their areas of operation (AO), in identifying connections between variables and in assessing the impacts of those variables on food production and distribution. Through use of the model, military units can better target their data collection efforts and can categorize and analyze data within the data categorization framework most widely-used by military forces—PMESII-PT (Political, Military, Economic, Infrastructure, Information, Physical Environment and Time). The model provides flexibility of analysis in that commanders can target analysis to be highly focused on a specific PMESII-PT domain or variable or conduct analysis across multiple PMESII-PT domains. The model is also designed to assist commanders in mapping food systems in their AOs and then identifying components of those systems that must be strengthened or protected.Keywords: food security, food system model, political stability, US Military
Procedia PDF Downloads 18616301 New Segmentation of Piecewise Moving-Average Model by Using Reversible Jump MCMC Algorithm
Authors: Suparman
Abstract:
This paper addresses the problem of the signal segmentation within a Bayesian framework by using reversible jump MCMC algorithm. The signal is modelled by piecewise constant Moving-Average (MA) model where the numbers of segments, the position of change-point, the order and the coefficient of the MA model for each segment are unknown. The reversible jump MCMC algorithm is then used to generate samples distributed according to the joint posterior distribution of the unknown parameters. These samples allow calculating some interesting features of the posterior distribution. The performance of the methodology is illustrated via several simulation results.Keywords: piecewise, moving-average model, reversible jump MCMC, signal segmentation
Procedia PDF Downloads 21616300 A Study on Automotive Attack Database and Data Flow Diagram for Concretization of HEAVENS: A Car Security Model
Authors: Se-Han Lee, Kwang-Woo Go, Gwang-Hyun Ahn, Hee-Sung Park, Cheol-Kyu Han, Jun-Bo Shim, Geun-Chul Kang, Hyun-Jung Lee
Abstract:
In recent years, with the advent of smart cars and the expansion of the market, the announcement of 'Adventures in Automotive Networks and Control Units' at the DEFCON21 conference in 2013 revealed that cars are not safe from hacking. As a result, the HEAVENS model considering not only the functional safety of the vehicle but also the security has been suggested. However, the HEAVENS model only presents a simple process, and there are no detailed procedures and activities for each process, making it difficult to apply it to the actual vehicle security vulnerability check. In this paper, we propose an automated attack database that systematically summarizes attack vectors, attack types, and vulnerable vehicle models to prepare for various car hacking attacks, and data flow diagrams that can detect various vulnerabilities and suggest a way to materialize the HEAVENS model.Keywords: automotive security, HEAVENS, car hacking, security model, information security
Procedia PDF Downloads 34616299 A TgCNN-Based Surrogate Model for Subsurface Oil-Water Phase Flow under Multi-Well Conditions
Authors: Jian Li
Abstract:
The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase
Procedia PDF Downloads 7616298 Applicability of Linearized Model of Synchronous Generator for Power System Stability Analysis
Authors: J. Ritonja, B. Grcar
Abstract:
For the synchronous generator simulation and analysis and for the power system stabilizer design and synthesis a mathematical model of synchronous generator is needed. The model has to accurately describe dynamics of oscillations, while at the same time has to be transparent enough for an analysis and sufficiently simplified for design of control system. To study the oscillations of the synchronous generator against to the rest of the power system, the model of the synchronous machine connected to an infinite bus through a transmission line having resistance and inductance is needed. In this paper, the linearized reduced order dynamic model of the synchronous generator connected to the infinite bus is presented and analysed in details. This model accurately describes dynamics of the synchronous generator only in a small vicinity of an equilibrium state. With the digression from the selected equilibrium point the accuracy of this model is decreasing considerably. In this paper, the equations’ descriptions and the parameters’ determinations for the linearized reduced order mathematical model of the synchronous generator are explained and summarized and represent the useful origin for works in the areas of synchronous generators’ dynamic behaviour analysis and synchronous generator’s control systems design and synthesis. The main contribution of this paper represents the detailed analysis of the accuracy of the linearized reduced order dynamic model in the entire synchronous generator’s operating range. Borders of the areas where the linearized reduced order mathematical model represents accurate description of the synchronous generator’s dynamics are determined with the systemic numerical analysis. The thorough eigenvalue analysis of the linearized models in the entire operating range is performed. In the paper, the parameters of the linearized reduced order dynamic model of the laboratory salient poles synchronous generator were determined and used for the analysis. The theoretical conclusions were confirmed with the agreement of experimental and simulation results.Keywords: eigenvalue analysis, mathematical model, power system stability, synchronous generator
Procedia PDF Downloads 23616297 Diesel Fault Prediction Based on Optimized Gray Neural Network
Authors: Han Bing, Yin Zhenjie
Abstract:
In order to analyze the status of a diesel engine, as well as conduct fault prediction, a new prediction model based on a gray system is proposed in this paper, which takes advantage of the neural network and the genetic algorithm. The proposed GBPGA prediction model builds on the GM (1.5) model and uses a neural network, which is optimized by a genetic algorithm to construct the error compensator. We verify our proposed model on the diesel faulty simulation data and the experimental results show that GBPGA has the potential to employ fault prediction on diesel.Keywords: fault prediction, neural network, GM(1, 5) genetic algorithm, GBPGA
Procedia PDF Downloads 29416296 Further Investigation of α+12C and α+16O Elastic Scattering
Authors: Sh. Hamada
Abstract:
The current work aims to study the rainbow like-structure observed in the elastic scattering of alpha particles on both 12C and 16O nuclei. We reanalyzed the experimental elastic scattering angular distributions data for α+12C and α+16O nuclear systems at different energies using both optical model and double folding potential of different interaction models such as: CDM3Y1, DDM3Y1, CDM3Y6 and BDM3Y1. Potential created by BDM3Y1 interaction model has the shallowest depth which reflects the necessity to use higher renormalization factor (Nr). Both optical model and double folding potential of different interaction models fairly reproduce the experimental data.Keywords: density distribution, double folding, elastic scattering, nuclear rainbow, optical model
Procedia PDF Downloads 22816295 Computational Model of Human Cardiopulmonary System
Authors: Julian Thrash, Douglas Folk, Michael Ciracy, Audrey C. Tseng, Kristen M. Stromsodt, Amber Younggren, Christopher Maciolek
Abstract:
The cardiopulmonary system is comprised of the heart, lungs, and many dynamic feedback mechanisms that control its function based on a multitude of variables. The next generation of cardiopulmonary medical devices will involve adaptive control and smart pacing techniques. However, testing these smart devices on living systems may be unethical and exceedingly expensive. As a solution, a comprehensive computational model of the cardiopulmonary system was implemented in Simulink. The model contains over 240 state variables and over 100 equations previously described in a series of published articles. Simulink was chosen because of its ease of introducing machine learning elements. Initial results indicate that physiologically correct waveforms of pressures and volumes were obtained in the simulation. With the development of a comprehensive computational model, we hope to pioneer the future of predictive medicine by applying our research towards the initial stages of smart devices. After validation, we will introduce and train reinforcement learning agents using the cardiopulmonary model to assist in adaptive control system design. With our cardiopulmonary model, we will accelerate the design and testing of smart and adaptive medical devices to better serve those with cardiovascular disease.Keywords: adaptive control, cardiopulmonary, computational model, machine learning, predictive medicine
Procedia PDF Downloads 16316294 AMF activates PDH 45 and G-proteins Genes to Alleviate Abiotic Stress in Tomato Plants
Authors: Deepak Bhardwaj, Narendra Tuteja
Abstract:
Global climate change is impacting large agrarian societies, especially those in countries located near the equator. Agriculture, and consequently, plant-based food, is the hardest hit in tropical and sub-tropical countries such as India due to an increased incidence of drought as well as an increase in soil salinity. One method that holds promise is AMF-rich biofertilizers which assist in activating proteins which in turn help alleviate abiotic stress in plants. In the present study, we identified two important species of (arbuscular mycorrhizal fungus) AMF belonging to Glomus and Gigaspora from the rhizosphere of the important medicinal plant Justicia adathoda. These two species have been found to be responsible for the abundance of Justicia adathoda in the semi-arid areas of the Jammu valley located in northern India, namely, the Union Territory of Jammu and Kashmir. We isolated the species of Glomus and Gigaspora from the rhizosphere of Justicia adathoda and used them as biofertilizers for the tomato plant. Significant improvements in the growth parameters were observed in the tomato plants inoculated with Glomus sp. and Gigaspora sp. in comparison with the tomato plants that were grown without AMF treatments. Tomato plants grown along with Glomus sp. and Gigaspora sp. have been observed to withstand 200 mM of salinity and 25% PEG stress. AMF also resulted in an increased concentration of proline and antioxidant enzymes in tomato plants. We also examined the expression levels of salinity and drought stress-inducible genes such as pea DNA helicase 45 (PDH 45) and genes of G-protein subunits of the tomato plants inoculated with and without AMF under stress and normal conditions. All the stress-inducible genes showed a significant increase in their gene expression under stress and AMF inoculation, while their levels were found to be normal under AMF inoculation without stress. We propose a model of abiotic stress alleviation in tomato plants with the help of external factors such as AMF and internally with the help of proteins like PDH 45 and G-proteins.Keywords: AMF, abiotic stress, g-proteins, PDH-45
Procedia PDF Downloads 16516293 Functional Instruction Set Simulator (ISS) of a Neural Network (NN) IP with Native BF-16 Generator
Authors: Debajyoti Mukherjee, Arathy B. S., Arpita Sahu, Saranga P. Pogula
Abstract:
A Functional Model to mimic the functional correctness of a Neural Network Compute Accelerator IP is very crucial for design validation. Neural network workloads are based on a Brain Floating Point (BF-16) data type. The major challenge we were facing was the incompatibility of gcc compilers to BF-16 datatype, which we addressed with a native BF-16 generator integrated to our functional model. Moreover, working with big GEMM (General Matrix Multiplication) or SpMM (Sparse Matrix Multiplication) Work Loads (Dense or Sparse) and debugging the failures related to data integrity is highly painstaking. In this paper, we are addressing the quality challenge of such a complex Neural Network Accelerator design by proposing a Functional Model-based scoreboard or Software model using SystemC. The proposed Functional Model executes the assembly code based on the ISA of the processor IP, decodes all instructions, and executes as expected to be done by the DUT. The said model would give a lot of visibility and debug capability in the DUT bringing up micro-steps of execution.Keywords: ISA (instruction set architecture), NN (neural network), TLM (transaction-level modeling), GEMM (general matrix multiplication)
Procedia PDF Downloads 7516292 Prediction of Bubbly Plume Characteristics Using the Self-Similarity Model
Authors: Li Chen, Alex Skvortsov, Chris Norwood
Abstract:
Gas releasing into water can be found in for many industrial situations. This process results in the formation of bubbles and acoustic emission which depends upon the bubble characteristics. If the bubble creation rates (bubble volume flow rate) are of interest, an inverse method has to be used based on the measurement of acoustic emission. However, there will be sound attenuation through the bubbly plume which will influence the measurement and should be taken into consideration in the model. The sound transmission through the bubbly plume depends on the characteristics of the bubbly plume, such as the shape and the bubble distributions. In this study, the bubbly plume shape is modelled using a self-similarity model, which has been normally applied for a single phase buoyant plume. The prediction is compared with the experimental data. It has been found the model can be applied to a buoyant plume of gas-liquid mixture. The influence of the gas flow rate and discharge nozzle size is studied.Keywords: bubbly plume, buoyant plume, bubble acoustics, self-similarity model
Procedia PDF Downloads 27816291 End-to-End Spanish-English Sequence Learning Translation Model
Authors: Vidhu Mitha Goutham, Ruma Mukherjee
Abstract:
The low availability of well-trained, unlimited, dynamic-access models for specific languages makes it hard for corporate users to adopt quick translation techniques and incorporate them into product solutions. As translation tasks increasingly require a dynamic sequence learning curve; stable, cost-free opensource models are scarce. We survey and compare current translation techniques and propose a modified sequence to sequence model repurposed with attention techniques. Sequence learning using an encoder-decoder model is now paving the path for higher precision levels in translation. Using a Convolutional Neural Network (CNN) encoder and a Recurrent Neural Network (RNN) decoder background, we use Fairseq tools to produce an end-to-end bilingually trained Spanish-English machine translation model including source language detection. We acquire competitive results using a duo-lingo-corpus trained model to provide for prospective, ready-made plug-in use for compound sentences and document translations. Our model serves a decent system for large, organizational data translation needs. While acknowledging its shortcomings and future scope, it also identifies itself as a well-optimized deep neural network model and solution.Keywords: attention, encoder-decoder, Fairseq, Seq2Seq, Spanish, translation
Procedia PDF Downloads 16616290 Interoperable Design Coordination Method for Sharing Communication Information Using Building Information Model Collaboration Format
Authors: Jin Gang Lee, Hyun-Soo Lee, Moonseo Park
Abstract:
The utilization of BIM and IFC allows project participants to collaborate across different areas by consistently sharing interoperable product information represented in a model. Comments or markups generated during the coordination process can be categorized as communication information, which can be shared in less standardized manner. It can be difficult to manage and reuse such information compared to the product information in a model. The present study proposes an interoperable coordination method using BCF (the BIM Collaboration Format) for managing and sharing the communication information during BIM based coordination process. A management function for coordination in the BIM collaboration system is developed to assess its ability to share the communication information in BIM collaboration projects. This approach systematically links communication information during the coordination process to the building model and serves as a type of storage system for retrieving knowledge created during BIM collaboration projects.Keywords: design coordination, building information model, BIM collaboration format, industry foundation classes
Procedia PDF Downloads 41716289 Economical Dependency Evolution and Complexity
Authors: Allé Dieng, Mamadou Bousso, Latif Dramani
Abstract:
The purpose of this work is to show the complexity behind economical interrelations in a country and provide a linear dynamic model of economical dependency evolution in a country. The model is based on National Transfer Account which is one of the most robust methodology developed in order to measure a level of demographic dividend captured in a country. It is built upon three major factors: demography, economical dependency and migration. The established mathematical model has been simulated using Netlogo software. The innovation of this study is in describing economical dependency as a complex system and simulating using mathematical equation the evolution of the two populations: the economical dependent and the non-economical dependent as defined in the National Transfer Account methodology. It also allows us to see the interactions and behaviors of both populations. The model can track individual characteristics and look at the effect of birth and death rates on the evolution of these two populations. The developed model is useful to understand how demographic and economic phenomenon are relatedKeywords: ABM, demographic dividend, National Transfer Accounts (NTA), ODE
Procedia PDF Downloads 18916288 Analysis of the Contribution of Drude and Brendel Model Terms to the Dielectric Function
Authors: Christopher Mkirema Maghanga, Maurice Mghendi Mwamburi
Abstract:
Parametric modeling provides a means to deeper understand the properties of materials. Drude, Brendel, Lorentz and OJL incorporated in SCOUT® software are some of the models used to study dielectric films. In our work, we utilized Brendel and Drude models to extract the optical constants from spectroscopic data of fabricated undoped and niobium doped titanium oxide thin films. The individual contributions by the two models were studied to establish how they influence the dielectric function. The effect of dopants on their influences was also analyzed. For the undoped films, results indicate minimal contribution from the Drude term due to the dielectric nature of the films. However as doping levels increase, the rise in the concentration of free electrons favors the use of Drude model. Brendel model was confirmed to work well with dielectric films - the undoped titanium Oxide films in our case.Keywords: modeling, Brendel model, optical constants, titanium oxide, Drude Model
Procedia PDF Downloads 17316287 A Comparative Analysis of E-Government Quality Models
Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri
Abstract:
Many quality models have been used to measure e-government portals quality. However, the absence of an international consensus for e-government portals quality models results in many differences in terms of quality attributes and measures. The aim of this paper is to compare and analyze the existing e-government quality models proposed in literature (those that are based on ISO standards and those that are not) in order to propose guidelines to build a good and useful e-government portals quality model. Our findings show that, there is no e-government portal quality model based on the new international standard ISO 25010. Besides that, the quality models are not based on a best practice model to allow agencies to both; measure e-government portals quality and identify missing best practices for those portals.Keywords: e-government, portal, best practices, quality model, ISO, standard, ISO 25010, ISO 9126
Procedia PDF Downloads 54716286 Predicting Options Prices Using Machine Learning
Authors: Krishang Surapaneni
Abstract:
The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%Keywords: finance, linear regression model, machine learning model, neural network, stock price
Procedia PDF Downloads 68