Search results for: discrete latent variable modeling
6541 A New Multi-Target, Multi-Agent Search and Rescue Path Planning Approach
Authors: Jean Berger, Nassirou Lo, Martin Noel
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Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.Keywords: search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization
Procedia PDF Downloads 3666540 Optimization of Multi Commodities Consumer Supply Chain: Part 1-Modelling
Authors: Zeinab Haji Abolhasani, Romeo Marian, Lee Luong
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This paper and its companions (Part II, Part III) will concentrate on optimizing a class of supply chain problems known as Multi- Commodities Consumer Supply Chain (MCCSC) problem. MCCSC problem belongs to production-distribution (P-D) planning category. It aims to determine facilities location, consumers’ allocation, and facilities configuration to minimize total cost (CT) of the entire network. These facilities can be manufacturer units (MUs), distribution centres (DCs), and retailers/end-users (REs) but not limited to them. To address this problem, three major tasks should be undertaken. At the first place, a mixed integer non-linear programming (MINP) mathematical model is developed. Then, system’s behaviors under different conditions will be observed using a simulation modeling tool. Finally, the most optimum solution (minimum CT) of the system will be obtained using a multi-objective optimization technique. Due to the large size of the problem, and the uncertainties in finding the most optimum solution, integration of modeling and simulation methodologies is proposed followed by developing new approach known as GASG. It is a genetic algorithm on the basis of granular simulation which is the subject of the methodology of this research. In part II, MCCSC is simulated using discrete-event simulation (DES) device within an integrated environment of SimEvents and Simulink of MATLAB® software package followed by a comprehensive case study to examine the given strategy. Also, the effect of genetic operators on the obtained optimal/near optimal solution by the simulation model will be discussed in part III.Keywords: supply chain, genetic algorithm, optimization, simulation, discrete event system
Procedia PDF Downloads 3076539 Characterization of Group Dynamics for Fostering Mathematical Modeling Competencies
Authors: Ayse Ozturk
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The study extends the prior research on modeling competencies by positioning students’ cognitive and language resources as the fundamentals for pursuing their own inquiry and expression lines through mathematical modeling. This strategy aims to answer the question that guides this study, “How do students’ group approaches to modeling tasks affect their modeling competencies over a unit of instruction?” Six bilingual tenth-grade students worked on open-ended modeling problems along with the content focused on quantities over six weeks. Each group was found to have a unique cognitive approach for solving these problems. Three different problem-solving strategies affected how the groups’ modeling competencies changed. The results provide evidence that the discussion around groups’ solutions, coupled with their reflections, advances group interpreting and validating competencies in the mathematical modeling processKeywords: cognition, collective learning, mathematical modeling competencies, problem-solving
Procedia PDF Downloads 1536538 Adversarial Disentanglement Using Latent Classifier for Pose-Independent Representation
Authors: Hamed Alqahtani, Manolya Kavakli-Thorne
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The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses.Keywords: disentanglement, face detection, generative adversarial networks, video surveillance
Procedia PDF Downloads 1206537 Item-Trait Pattern Recognition of Replenished Items in Multidimensional Computerized Adaptive Testing
Authors: Jianan Sun, Ziwen Ye
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Multidimensional computerized adaptive testing (MCAT) is a popular research topic in psychometrics. It is important for practitioners to clearly know the item-trait patterns of administered items when a test like MCAT is operated. Item-trait pattern recognition refers to detecting which latent traits in a psychological test are measured by each of the specified items. If the item-trait patterns of the replenished items in MCAT item pool are well detected, the interpretability of the items can be improved, which can further promote the abilities of the examinees who attending the MCAT to be accurately estimated. This research explores to solve the item-trait pattern recognition problem of the replenished items in MCAT item pool from the perspective of statistical variable selection. The popular multidimensional item response theory model, multidimensional two-parameter logistic model, is assumed to fit the response data of MCAT. The proposed method uses the least absolute shrinkage and selection operator (LASSO) to detect item-trait patterns of replenished items based on the essential information of item responses and ability estimates of examinees collected from a designed MCAT procedure. Several advantages of the proposed method are outlined. First, the proposed method does not strictly depend on the relative order between the replenished items and the selected operational items, so it allows the replenished items to be mixed into the operational items in reasonable order such as considering content constraints or other test requirements. Second, the LASSO used in this research improves the interpretability of the multidimensional replenished items in MCAT. Third, the proposed method can exert the advantage of shrinkage method idea for variable selection, so it can help to check item quality and key dimension features of replenished items and saves more costs of time and labors in response data collection than traditional factor analysis method. Moreover, the proposed method makes sure the dimensions of replenished items are recognized to be consistent with the dimensions of operational items in MCAT item pool. Simulation studies are conducted to investigate the performance of the proposed method under different conditions for varying dimensionality of item pool, latent trait correlation, item discrimination, test lengths and item selection criteria in MCAT. Results show that the proposed method can accurately detect the item-trait patterns of the replenished items in the two-dimensional and the three-dimensional item pool. Selecting enough operational items from the item pool consisting of high discriminating items by Bayesian A-optimality in MCAT can improve the recognition accuracy of item-trait patterns of replenished items for the proposed method. The pattern recognition accuracy for the conditions with correlated traits is better than those with independent traits especially for the item pool consisting of comparatively low discriminating items. To sum up, the proposed data-driven method based on the LASSO can accurately and efficiently detect the item-trait patterns of replenished items in MCAT.Keywords: item-trait pattern recognition, least absolute shrinkage and selection operator, multidimensional computerized adaptive testing, variable selection
Procedia PDF Downloads 1246536 A Two-Stage Airport Ground Movement Speed Profile Design Methodology Using Particle Swarm Optimization
Authors: Zhang Tianci, Ding Meng, Zuo Hongfu, Zeng Lina, Sun Zejun
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Automation of airport operations can greatly improve ground movement efficiency. In this paper, we study the speed profile design problem for advanced airport ground movement control and guidance. The problem is constrained by the surface four-dimensional trajectory generated in taxi planning. A decomposed approach of two stages is presented to solve this problem efficiently. In the first stage, speeds are allocated at control points which ensure smooth speed profiles can be found later. In the second stage, detailed speed profiles of each taxi interval are generated according to the allocated control point speeds with the objective of minimizing the overall fuel consumption. We present a swarm intelligence based algorithm for the first-stage problem and a discrete variable driven enumeration method for the second-stage problem since it only has a small set of discrete variables. Experimental results demonstrate the presented methodology performs well on real world speed profile design problems.Keywords: airport ground movement, fuel consumption, particle swarm optimization, smoothness, speed profile design
Procedia PDF Downloads 5786535 Application of Simulation of Discrete Events in Resource Management of Massive Concreting
Authors: Mohammad Amin Hamedirad, Seyed Javad Vaziri Kang Olyaei
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Project planning and control are one of the most critical issues in the management of construction projects. Traditional methods of project planning and control, such as the critical path method or Gantt chart, are not widely used for planning projects with discrete and repetitive activities, and one of the problems of project managers is planning the implementation process and optimal allocation of its resources. Massive concreting projects is also a project with discrete and repetitive activities. This study uses the concept of simulating discrete events to manage resources, which includes finding the optimal number of resources considering various limitations such as limitations of machinery, equipment, human resources and even technical, time and implementation limitations using analysis of resource consumption rate, project completion time and critical points analysis of the implementation process. For this purpose, the concept of discrete-event simulation has been used to model different stages of implementation. After reviewing the various scenarios, the optimal number of allocations for each resource is finally determined to reach the maximum utilization rate and also to reduce the project completion time or reduce its cost according to the existing constraints. The results showed that with the optimal allocation of resources, the project completion time could be reduced by 90%, and the resulting costs can be reduced by up to 49%. Thus, allocating the optimal number of project resources using this method will reduce its time and cost.Keywords: simulation, massive concreting, discrete event simulation, resource management
Procedia PDF Downloads 1416534 Efficient Variable Modulation Scheme Based on Codebook in the MIMO-OFDM System
Authors: Yong-Jun Kim, Jae-Hyun Ro, Chang-Bin Ha, Hyoung-Kyu Song
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Because current wireless communication requires high reliability in a limited bandwidth environment, this paper proposes the variable modulation scheme based on the codebook. The variable modulation scheme adjusts transmission power using the codebook in accordance with hannel state. Also, if the codebook is composed of many bits, the reliability is more improved by the proposed scheme. The simulation results show that the performance of proposed scheme has better reliability than the the performance of conventional scheme.Keywords: MIMO-OFDM, variable modulation, codebook, channel state
Procedia PDF Downloads 5796533 Optimizing Coal Yard Management Using Discrete Event Simulation
Authors: Iqbal Felani
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A Coal-Fired Power Plant has some integrated facilities to handle coal from three separated coal yards to eight units power plant’s bunker. But nowadays the facilities are not reliable enough for supporting the system. Management planned to invest some facilities to increase the reliability. They also had a plan to make single spesification of coal used all of the units, called Single Quality Coal (SQC). This simulation would compare before and after improvement with two scenarios i.e First In First Out (FIFO) and Last In First Out (LIFO). Some parameters like stay time, reorder point and safety stock is determined by the simulation. Discrete event simulation based software, Flexsim 5.0, is used to help the simulation. Based on the simulation, Single Quality Coal with FIFO scenario has the shortest staytime with 8.38 days.Keywords: Coal Yard Management, Discrete event simulation First In First Out, Last In First Out.
Procedia PDF Downloads 6626532 Decomposition of Third-Order Discrete-Time Linear Time-Varying Systems into Its Second- and First-Order Pairs
Authors: Mohamed Hassan Abdullahi
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Decomposition is used as a synthesis tool in several physical systems. It can also be used for tearing and restructuring, which is large-scale system analysis. On the other hand, the commutativity of series-connected systems has fascinated the interest of researchers, and its advantages have been emphasized in the literature. The presentation looks into the necessary conditions for decomposing any third-order discrete-time linear time-varying system into a commutative pair of first- and second-order systems. Additional requirements are derived in the case of nonzero initial conditions. MATLAB simulations are used to verify the findings. The work is unique and is being published for the first time. It is critical from the standpoints of synthesis and/or design. Because many design techniques in engineering systems rely on tearing and reconstruction, this is the process of putting together simple components to create a finished product. Furthermore, it is demonstrated that regarding sensitivity to initial conditions, some combinations may be better than others. The results of this work can be extended for the decomposition of fourth-order discrete-time linear time-varying systems into lower-order commutative pairs, as two second-order commutative subsystems or one first-order and one third-order commutative subsystems.Keywords: commutativity, decomposition, discrete time-varying systems, systems
Procedia PDF Downloads 1006531 Continuous Plug Flow and Discrete Particle Phase Coupling Using Triangular Parcels
Authors: Anders Schou Simonsen, Thomas Condra, Kim Sørensen
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Various processes are modelled using a discrete phase, where particles are seeded from a source. Such particles can represent liquid water droplets, which are affecting the continuous phase by exchanging thermal energy, momentum, species etc. Discrete phases are typically modelled using parcel, which represents a collection of particles, which share properties such as temperature, velocity etc. When coupling the phases, the exchange rates are integrated over the cell, in which the parcel is located. This can cause spikes and fluctuating exchange rates. This paper presents an alternative method of coupling a discrete and a continuous plug flow phase. This is done using triangular parcels, which span between nodes following the dynamics of single droplets. Thus, the triangular parcels are propagated using the corner nodes. At each time step, the exchange rates are spatially integrated over the surface of the triangular parcels, which yields a smooth continuous exchange rate to the continuous phase. The results shows that the method is more stable, converges slightly faster and yields smooth exchange rates compared with the steam tube approach. However, the computational requirements are about five times greater, so the applicability of the alternative method should be limited to processes, where the exchange rates are important. The overall balances of the exchanged properties did not change significantly using the new approach.Keywords: CFD, coupling, discrete phase, parcel
Procedia PDF Downloads 2606530 Theoretical Framework for Value Creation in Project Oriented Companies
Authors: Mariusz Hofman
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The paper ‘Theoretical framework for value creation in Project-Oriented Companies’ is designed to determine, how organisations create value and whether this allows them to achieve market success. An assumption has been made that there are two routes to achieving this value. The first one is to create intangible assets (i.e. the resources of human, structural and relational capital), while the other one is to create added value (understood as the surplus of revenue over costs). It has also been assumed that the combination of the achieved added value and unique intangible assets translates to the success of a project-oriented company. The purpose of the paper is to present hypothetical and deductive model which describing the modus operandi of such companies and approach to model operationalisation. All the latent variables included in the model are theoretical constructs with observational indicators (measures). The existence of a latent variable (construct) and also submodels will be confirmed based on a covariance matrix which in turn is based on empirical data, being a set of observational indicators (measures). This will be achieved with a confirmatory factor analysis (CFA). Due to this statistical procedure, it will be verified whether the matrix arising from the adopted theoretical model differs statistically from the empirical matrix of covariance arising from the system of equations. The fit of the model with the empirical data will be evaluated using χ2, RMSEA and CFI (Comparative Fit Index). How well the theoretical model fits the empirical data is assessed through a number of indicators. If the theoretical conjectures are confirmed, an interesting development path can be defined for project-oriented companies. This will let such organisations perform efficiently in the face of the growing competition and pressure on innovation.Keywords: value creation, project-oriented company, structural equation modelling
Procedia PDF Downloads 2866529 Financial Assets Return, Economic Factors and Investor's Behavioral Indicators Relationships Modeling: A Bayesian Networks Approach
Authors: Nada Souissi, Mourad Mroua
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The main purpose of this study is to examine the interaction between financial asset volatility, economic factors and investor's behavioral indicators related to both the company's and the markets stocks for the period from January 2000 to January2020. Using multiple linear regression and Bayesian Networks modeling, results show a positive and negative relationship between investor's psychology index, economic factors and predicted stock market return. We reveal that the application of the Bayesian Discrete Network contributes to identify the different cause and effect relationships between all economic, financial variables and psychology index.Keywords: Financial asset return predictability, Economic factors, Investor's psychology index, Bayesian approach, Probabilistic networks, Parametric learning
Procedia PDF Downloads 1386528 Integrated Passive Cooling Systems for Tropical Residential Buildings: A Review through the Lens of Latent Heat Assessment
Authors: O. Eso, M. Mohammadi, J. Darkwa, J. Calautit
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Residential buildings are responsible for 22% of the global end-use energy demand and 17% of global CO₂ emissions. Tropical climates particularly present higher latent heat gains, leading to more cooling loads. However, the cooling processes are all based on conventional mechanical air conditioning systems which are energy and carbon intensive technologies. Passive cooling systems have in the past been considered as alternative technologies for minimizing energy consumption in buildings. Nevertheless, replacing mechanical cooling systems with passive ones will require a careful assessment of the passive cooling system heat transfer to determine if suitable to outperform their conventional counterparts. This is because internal heat gains, indoor-outdoor heat transfer, and heat transfer through envelope affects the performance of passive cooling systems. While many studies have investigated sensible heat transfer in passive cooling systems, not many studies have focused on their latent heat transfer capabilities. Furthermore, combining heat prevention, heat modulation and heat dissipation to passively cool indoor spaces in the tropical climates is critical to achieve thermal comfort. Since passive cooling systems use only one of these three approaches at a time, integrating more than one passive cooling system for effective indoor latent heat removal while still saving energy is studied. This study is a systematic review of recently published peer review journals on integrated passive cooling systems for tropical residential buildings. The missing links in the experimental and numerical studies with regards to latent heat reduction interventions are presented. Energy simulation studies of integrated passive cooling systems in tropical residential buildings are also discussed. The review has shown that comfortable indoor environment is attainable when two or more passive cooling systems are integrated in tropical residential buildings. Improvement occurs in the heat transfer rate and cooling performance of the passive cooling systems when thermal energy storage systems like phase change materials are included. Integrating passive cooling systems in tropical residential buildings can reduce energy consumption by 6-87% while achieving up to 17.55% reduction in indoor heat flux. The review has highlighted a lack of numerical studies regarding passive cooling system performance in tropical savannah climates. In addition, detailed studies are required to establish suitable latent heat transfer rate in passive cooling ventilation devices under this climate category. This should be considered in subsequent studies. The conclusions and outcomes of this study will help researchers understand the overall energy performance of integrated passive cooling systems in tropical climates and help them identify and design suitable climate specific options for residential buildings.Keywords: energy savings, latent heat, passive cooling systems, residential buildings, tropical residential buildings
Procedia PDF Downloads 1406527 Technical Assessment of Utilizing Electrical Variable Transmission Systems in Hybrid Electric Vehicles
Authors: Majid Vafaeipour, Mohamed El Baghdadi, Florian Verbelen, Peter Sergeant, Joeri Van Mierlo, Kurt Stockman, Omar Hegazy
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The Electrical Variable Transmission (EVT), an electromechanical device, can be considered as an alternative solution to the conventional transmission system utilized in Hybrid Electric Vehicles (HEVs). This study present comparisons in terms of fuel consumption, power split, and state of charge (SoC) of an HEV containing an EVT to a conventional parallel topology and a series topology. To this end, corresponding simulations of these topologies are all performed in presence of control strategies enabling battery charge-sustaining and efficient power split. The power flow through the components of the vehicle are attained, and fuel consumption results of the considered cases are compared. The investigation of the results indicates utilizing EVT can provide significant added values in HEV configurations. The outcome of the current research paves its path for implementation of design optimization approaches on such systems in further research directions.Keywords: Electrical Variable Transmission (EVT), Hybrid Electric Vehicle (HEV), parallel, series, modeling
Procedia PDF Downloads 2316526 Using Gaussian Process in Wind Power Forecasting
Authors: Hacene Benkhoula, Mohamed Badreddine Benabdella, Hamid Bouzeboudja, Abderrahmane Asraoui
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The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.Keywords: wind power, Gaussien process, modelling, forecasting
Procedia PDF Downloads 4056525 A Variable Stiffness Approach to Vibration Control
Authors: S. A. Alotaibi, M. A. Al-Ajmi
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This work introduces a new concept for controlling the mechanical vibrations via variable stiffness coil spring. The concept relies on fitting a screw though the spring to change the number of active spring coils. A prototype has been built and tested with promising results toward an innovation in the field of vibration control.Keywords: variable stiffness, coil spring, vibration control, computer science
Procedia PDF Downloads 3976524 Dynamic Analysis of Composite Doubly Curved Panels with Variable Thickness
Authors: I. Algul, G. Akgun, H. Kurtaran
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Dynamic analysis of composite doubly curved panels with variable thickness subjected to different pulse types using Generalized Differential Quadrature method (GDQ) is presented in this study. Panels with variable thickness are used in the construction of aerospace and marine industry. Giving variable thickness to panels can allow the designer to get optimum structural efficiency. For this reason, estimating the response of variable thickness panels is very important to design more reliable structures under dynamic loads. Dynamic equations for composite panels with variable thickness are obtained using virtual work principle. Partial derivatives in the equation of motion are expressed with GDQ and Newmark average acceleration scheme is used for temporal discretization. Several examples are used to highlight the effectiveness of the proposed method. Results are compared with finite element method. Effects of taper ratios, boundary conditions and loading type on the response of composite panel are investigated.Keywords: differential quadrature method, doubly curved panels, laminated composite materials, small displacement
Procedia PDF Downloads 3516523 System Response of a Variable-Rate Aerial Application System
Authors: Daniel E. Martin, Chenghai Yang
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Variable-rate aerial application systems are becoming more readily available; however, aerial applicators typically only use the systems for constant-rate application of materials, allowing the systems to compensate for upwind and downwind ground speed variations. Much of the resistance to variable-rate aerial application system adoption in the U.S. pertains to applicator’s trust in the systems to turn on and off automatically as desired. The objectives of this study were to evaluate a commercially available variable-rate aerial application system under field conditions to demonstrate both the response and accuracy of the system to desired application rate inputs. This study involved planting oats in a 35-acre fallow field during the winter months to establish a uniform green backdrop in early spring. A binary (on/off) prescription application map was generated and a variable-rate aerial application of glyphosate was made to the field. Airborne multispectral imagery taken before and two weeks after the application documented actual field deposition and efficacy of the glyphosate. When compared to the prescription application map, these data provided application system response and accuracy information. The results of this study will be useful for quantifying and documenting the response and accuracy of a commercially available variable-rate aerial application system so that aerial applicators can be more confident in their capabilities and the use of these systems can increase, taking advantage of all that aerial variable-rate technologies have to offer.Keywords: variable-rate, aerial application, remote sensing, precision application
Procedia PDF Downloads 4676522 Proposing an Architecture for Drug Response Prediction by Integrating Multiomics Data and Utilizing Graph Transformers
Authors: Nishank Raisinghani
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Efficiently predicting drug response remains a challenge in the realm of drug discovery. To address this issue, we propose four model architectures that combine graphical representation with varying positions of multiheaded self-attention mechanisms. By leveraging two types of multi-omics data, transcriptomics and genomics, we create a comprehensive representation of target cells and enable drug response prediction in precision medicine. A majority of our architectures utilize multiple transformer models, one with a graph attention mechanism and the other with a multiheaded self-attention mechanism, to generate latent representations of both drug and omics data, respectively. Our model architectures apply an attention mechanism to both drug and multiomics data, with the goal of procuring more comprehensive latent representations. The latent representations are then concatenated and input into a fully connected network to predict the IC-50 score, a measure of cell drug response. We experiment with all four of these architectures and extract results from all of them. Our study greatly contributes to the future of drug discovery and precision medicine by looking to optimize the time and accuracy of drug response prediction.Keywords: drug discovery, transformers, graph neural networks, multiomics
Procedia PDF Downloads 1426521 Assessment of Seismic Behavior of Masonry Minarets by Discrete Element Method
Authors: Ozden Saygili, Eser Cakti
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Mosques and minarets can be severely damaged as a result of earthquakes. Non-linear behavior of minarets of Mihrimah Sultan and Süleymaniye Mosques and the minaret of St. Sophia are analyzed to investigate seismic response, damage and failure mechanisms of minarets during earthquake. Selected minarets have different height and diameter. Discrete elements method was used to create the numerical minaret models. Analyses were performed using sine waves. Two parameters were used for evaluating the results: the maximum relative dislocation of adjacent drums and the maximum displacement at the top of the minaret. Both parameters were normalized by the drum diameter. The effects of minaret geometry on seismic behavior were evaluated by comparing the results of analyses.Keywords: discrete element method, earthquake safety, nonlinear analysis, masonry structures
Procedia PDF Downloads 3056520 Paraffin/Expanded Perlite Composite as a Novel Form-Stable Phase Change Material for Latent Heat Energy Storage
Authors: Awni Alkhazaleh
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Latent heat storage using Phase Change Materials (PCMs) has attracted growing attention recently in the renewable energy utilization and building energy efficiency. Paraffin (PA) of low melting temperature, which is close to human comfort temperature in the range of 24-28 °C has been considered to be used in building applications. A form-stable composite Paraffin/Expanded perlite (PA-EP) has been prepared by retaining PA into porous particles of EP. DSC (Differential scanning calorimeter) is used to measure the thermal properties of PA in the form-stable composite with/without building materials. TGA (Thermal gravimetric analysis) shows that the composite is thermally stable. SEM (Scanning electron microscope) demonstrates that the layer structure of the EP particles is uniformly absorbed by PA. The mechanical properties in flexural mode have been discussed. The thermal energy storage performance has been evaluated using a small test room (100 mm ×100 mm ×100 mm) with thickness 10 mm. The flammability test of modified sample has been discussed using a cone calorimeter. The results confirm that the form-stable composite PA has the function of reducing building energy consumption.Keywords: flammability, latent heat storage, paraffin, plasterboard
Procedia PDF Downloads 2126519 Integral Form Solutions of the Linearized Navier-Stokes Equations without Deviatoric Stress Tensor Term in the Forward Modeling for FWI
Authors: Anyeres N. Atehortua Jimenez, J. David Lambraño, Juan Carlos Muñoz
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Navier-Stokes equations (NSE), which describe the dynamics of a fluid, have an important application on modeling waves used for data inversion techniques as full waveform inversion (FWI). In this work a linearized version of NSE and its variables, neglecting deviatoric terms of stress tensor, is presented. In order to get a theoretical modeling of pressure p(x,t) and wave velocity profile c(x,t), a wave equation of visco-acoustic medium (VAE) is written. A change of variables p(x,t)=q(x,t)h(ρ), is made on the equation for the VAE leading to a well known Klein-Gordon equation (KGE) describing waves propagating in variable density medium (ρ) with dispersive term α^2(x). KGE is reduced to a Poisson equation and solved by proposing a specific function for α^2(x) accounting for the energy dissipation and dispersion. Finally, an integral form solution is derived for p(x,t), c(x,t) and kinematics variables like particle velocity v(x,t), displacement u(x,t) and bulk modulus function k_b(x,t). Further, it is compared this visco-acoustic formulation with another form broadly used in the geophysics; it is argued that this formalism is more general and, given its integral form, it may offer several advantages from the modern parallel computing point of view. Applications to minimize the errors in modeling for FWI applied to oils resources in geophysics are discussed.Keywords: Navier-Stokes equations, modeling, visco-acoustic, inversion FWI
Procedia PDF Downloads 5116518 DISGAN: Efficient Generative Adversarial Network-Based Method for Cyber-Intrusion Detection
Authors: Hongyu Chen, Li Jiang
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Ubiquitous anomalies endanger the security of our system con- stantly. They may bring irreversible damages to the system and cause leakage of privacy. Thus, it is of vital importance to promptly detect these anomalies. Traditional supervised methods such as Decision Trees and Support Vector Machine (SVM) are used to classify normality and abnormality. However, in some case, the abnormal status are largely rarer than normal status, which leads to decision bias of these methods. Generative adversarial network (GAN) has been proposed to handle the case. With its strong generative ability, it only needs to learn the distribution of normal status, and identify the abnormal status through the gap between it and the learned distribution. Nevertheless, existing GAN-based models are not suitable to process data with discrete values, leading to immense degradation of detection performance. To cope with the discrete features, in this paper, we propose an efficient GAN-based model with specifically-designed loss function. Experiment results show that our model outperforms state-of-the-art models on discrete dataset and remarkably reduce the overhead.Keywords: GAN, discrete feature, Wasserstein distance, multiple intermediate layers
Procedia PDF Downloads 1236517 Modeling and Analysis of DFIG Based Wind Power System Using Instantaneous Power Components
Authors: Jaimala Ghambir, Tilak Thakur, Puneet Chawla
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As per the statistical data, the Doubly-fed Induction Generator (DFIG) based wind turbine with variable speed and variable pitch control is the most common wind turbine in the growing wind market. This machine is usually used on the grid connected wind energy conversion system to satisfy grid code requirements such as grid stability, fault ride through (FRT), power quality improvement, grid synchronization and power control etc. Though the requirements are not fulfilled directly by the machine, the control strategy is used in both the stator as well as rotor side along with power electronic converters to fulfil the requirements stated above. To satisfy the grid code requirements of wind turbine, usually grid side converter is playing a major role. So in order to improve the operation capacity of wind turbine under critical situation, the intensive study of both machine side converter control and grid side converter control is necessary In this paper DFIG is modeled using power components as variables and the performance of the DFIG system is analysed under grid voltage fluctuations. The voltage fluctuations are made by lowering and raising the voltage values in the utility grid intentionally for the purpose of simulation keeping in view of different grid disturbances.Keywords: DFIG, dynamic modeling, DPC, sag, swell, voltage fluctuations, FRT
Procedia PDF Downloads 4596516 Secure Proxy Signature Based on Factoring and Discrete Logarithm
Authors: H. El-Kamchouchi, Heba Gaber, Fatma Ahmed, Dalia H. El-Kamchouchi
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A digital signature is an electronic signature form used by an original signer to sign a specific document. When the original signer is not in his office or when he/she travels outside, he/she delegates his signing capability to a proxy signer and then the proxy signer generates a signing message on behalf of the original signer. The two parties must be able to authenticate one another and agree on a secret encryption key, in order to communicate securely over an unreliable public network. Authenticated key agreement protocols have an important role in building a secure communications network between the two parties. In this paper, we present a secure proxy signature scheme over an efficient and secure authenticated key agreement protocol based on factoring and discrete logarithm problem.Keywords: discrete logarithm, factoring, proxy signature, key agreement
Procedia PDF Downloads 3006515 High Performance Electrocardiogram Steganography Based on Fast Discrete Cosine Transform
Authors: Liang-Ta Cheng, Ching-Yu Yang
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Based on fast discrete cosine transform (FDCT), the authors present a high capacity and high perceived quality method for electrocardiogram (ECG) signal. By using a simple adjusting policy to the 1-dimentional (1-D) DCT coefficients, a large volume of secret message can be effectively embedded in an ECG host signal and be successfully extracted at the intended receiver. Simulations confirmed that the resulting perceived quality is good, while the hiding capability of the proposed method significantly outperforms that of existing techniques. In addition, our proposed method has a certain degree of robustness. Since the computational complexity is low, it is feasible for our method being employed in real-time applications.Keywords: data hiding, ECG steganography, fast discrete cosine transform, 1-D DCT bundle, real-time applications
Procedia PDF Downloads 1876514 Numerical Modeling the Cavitating Flow in Injection Nozzle Holes
Authors: Ridha Zgolli, Hatem Kanfoudi
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Cavitating flows inside a diesel injection nozzle hole were simulated using a mixture model. A 2D numerical model is proposed in this paper to simulate steady cavitating flows. The Reynolds-averaged Navier-Stokes equations are solved for the liquid and vapor mixture, which is considered as a single fluid with variable density which is expressed as function of the vapor volume fraction. The closure of this variable is provided by the transport equation with a source term TEM. The processes of evaporation and condensation are governed by changes in pressure within the flow. The source term is implanted in the CFD code ANSYS CFX. The influence of numerical and physical parameters is presented in details. The numerical simulations are in good agreement with the experimental data for steady flow.Keywords: cavitation, injection nozzle, numerical simulation, k–ω
Procedia PDF Downloads 3916513 Bridging the Gap between Different Interfaces for Business Process Modeling
Authors: Katalina Grigorova, Kaloyan Mironov
Abstract:
The paper focuses on the benefits of business process modeling. Although this discipline is developing for many years, there is still necessity of creating new opportunities to meet the ever-increasing users’ needs. Because one of these needs is related to the conversion of business process models from one standard to another, the authors have developed a converter between BPMN and EPC standards using workflow patterns as intermediate tool. Nowadays there are too many systems for business process modeling. The variety of output formats is almost the same as the systems themselves. This diversity additionally hampers the conversion of the models. The presented study is aimed at discussing problems due to differences in the output formats of various modeling environments.Keywords: business process modeling, business process modeling standards, workflow patterns, converting models
Procedia PDF Downloads 5736512 Airline Choice Model for Domestic Flights: The Role of Airline Flexibility
Authors: Camila Amin-Puello, Lina Vasco-Diaz, Juan Ramirez-Arias, Claudia Munoz, Carlos Gonzalez-Calderon
Abstract:
Operational flexibility is a fundamental aspect in the field of airlines because although demand is constantly changing, it is the duty of companies to provide a service to users that satisfies their needs in an efficient manner without sacrificing factors such as comfort, safety and other perception variables. The objective of this research is to understand the factors that describe and explain operational flexibility by implementing advanced analytical methods such as exploratory factor analysis and structural equation modeling, examining multiple levels of operational flexibility and understanding how these variable influences users' decision-making when choosing an airline and in turn how it affects the airlines themselves. The use of a hybrid model and latent variables improves the efficiency and accuracy of airline performance prediction in the unpredictable Colombian market. This pioneering study delves into traveler motivations and their impact on domestic flight demand, offering valuable insights to optimize resources and improve the overall traveler experience. Applying the methods, it was identified that low-cost airlines are not useful for flexibility, while users, especially women, found airlines with greater flexibility in terms of ticket costs and flight schedules to be more useful. All of this allows airlines to anticipate and adapt to their customers' needs efficiently: to plan flight capacity appropriately, adjust pricing strategies and improve the overall passenger experience.Keywords: hybrid choice model, airline, business travelers, domestic flights
Procedia PDF Downloads 4