Search results for: dynamic Bayesian networks

Authors: Kyaw Zin Htut

Abstract:

In this article, the synthesis of the efficiency of intelligent diagnostic system in the aircraft measuring devices is described. The technology developments of the diagnostic system are considered based on the model errors of the gyro instruments, which are used to measure the parameters of the aircraft. The synthesis of the diagnostic intelligent system is considered on the example of the problem of assessment and forecasting errors of the gyroscope devices on the onboard aircraft. The result of the system is to detect of faults of the aircraft measuring devices as well as the analysis of the measuring equipment to improve the efficiency of its work.

Keywords: diagnostic, dynamic system, errors of gyro instruments, model errors, assessment, prognosis

Procedia PDF Downloads 379

Authors: Sumit Kumar, Sunil Kumar, Chandan Deep Singh

Abstract:

This paper presents modeling and simulation of flexible robot in an underwater environment. The underwater environment completely contrasts with ground or space environment. The robot in an underwater situation is subjected to various dynamic forces like buoyancy forces, hydrostatic and hydrodynamic forces. The underwater robot is modeled as Rayleigh beam. The developed model further allows estimating the deflection of tip in two directions. The complete dynamics of the underwater robot is analyzed, which is the main focus of this investigation. The control of robot trajectory is not discussed in this paper. Simulation is performed using Symbol Shakti software.

Keywords: bond graph modeling, dynamics. modeling, rayleigh beam, underwater robot

Procedia PDF Downloads 562

Authors: Jisong Zhang, Yinghua Zhao

Abstract:

The present study investigated the mechanical properties and microstructure of Ultra-High Performance Concrete (UHPC) containing supplementary cementitious materials (SCMs), such as fly ash (FA) and silica fume (SF), and to verify the synergistic effect in the ternary system. On the basis of 30% fly ash replacement, the incorporation of either 10% SF or 20% SF show a better performance compared to the reference sample. The efficiency factor (k-value) was calculated as a synergistic effect to predict the compressive strength of UHPC with these SCMs. The SEM of micrographs and pore volume from BJH method indicate a high correlation with compressive strength. Further, an artificial neural networks model was constructed for prediction of the compressive strength of UHPC containing these SCMs.

Keywords: artificial neural network, fly ash, mechanical properties, ultra-high performance concrete

Procedia PDF Downloads 392

Authors: Aleksei Samarin, Artyom Nazarenko, Valentin Malykh

Abstract:

Image enhancement is becoming more and more popular, especially on mobile devices. Nowadays, it is a common approach to enhance an image using a convolutional neural network (CNN). Such a network should be of significant size; otherwise, a possibility for the artifacts to occur is overgrowing. The existing large CNNs are computationally expensive, which could be crucial for mobile devices. Another important flaw of such models is they are poorly interpretable. There is another approach to image enhancement, namely, the usage of predefined filters in combination with the prediction of their applicability. We present an approach following this paradigm, which outperforms both existing CNN-based and filter-based approaches in the image enhancement task. It is easily adaptable for mobile devices since it has only 47 thousand parameters. It shows the best SSIM 0.919 on RANDOM250 (MIT Adobe FiveK) among small models and is thrice faster than previous models.

Keywords: universal filter, image enhancement, neural networks, computer vision

Procedia PDF Downloads 84

Authors: Johan Loeckx, Joeri Bultheel

Abstract:

Recently, the application of deep learning to music has gained popularity. Its true potential, however, has been largely unexplored. In this paper, a new idea for representing the dynamic behavior of music is proposed. A ”forward” conditional RBM takes into account not only preceding but also future samples during training. Though this may sound controversial at first sight, it will be shown that it makes sense from a musical and neuro-cognitive perspective. The model is applied to reconstruct music based upon the first notes and to improvise in the musical style of a composer. Different to expectations, reconstruction accuracy with respect to a regular CRBM with the same order, was not significantly improved. More research is needed to test the performance on unseen data.

Keywords: deep learning, restricted boltzmann machine, music generation, conditional restricted boltzmann machine (CRBM)

Procedia PDF Downloads 503

Authors: Rafal Sochaczewski, Ksenia Siadkowska, Tytus Tulwin

Abstract:

The paper describes the modeling of a fuel injector for common rail systems. A one-dimensional model of a solenoid-valve-controlled injector with Valve Closes Orifice (VCO) spray was modelled in the AVL Hydsim. This model shows the dynamic phenomena that occur in the injector. The accuracy of the calibration, based on a regulation of the parameters of the control valve and the nozzle needle lift, was verified by comparing the numerical results of injector flow rate. Our model is capable of a precise simulation of injector operating parameters in relation to injection time and fuel pressure in a fuel rail. As a result, there were made characteristics of the injector flow rate and backflow.

Keywords: common rail, diesel engine, fuel injector, modeling

Procedia PDF Downloads 397

Authors: H. M. Avanesyan

Abstract:

Economists have been discussing the importance of intangible assets for the success of organization for many years. The term intellectual capital was popularized in the 1990s by Thomas Stewart. “Intellectual capital is the knowledge, applied experience, enterprise processes and technology customer relationship and professional skills which are valuable assets to an organization.” Human capital – includes employee brainpower, competence, skills, experience and knowledge. Customer capital – includes relations and networks with partners, suppliers, distributors, and customers. The objective of the article is to assess one of the key components of organizational culture – organizational values. The focus of the survey was on assessing how intellectual capital presented in these values of the organization. In the conclusion section the article refers to underestimation of intellectual capital by the organization management and the various possible negative effects of the latter.

Keywords: human capital, intellectual capital, organizational culture, management, social identity, organization

Procedia PDF Downloads 437

Authors: Yew Mun Yip, Dawei Zhang

Abstract:

Proteins are the biological machinery that executes specific vital functions in every cell of the human body by folding into their 3D structures. When a protein misfolds from its native structure, the machinery will malfunction and lead to misfolding diseases. Although in vitro experiments are able to conclude that the mutations of the amino acid sequence lead to incorrectly folded protein structures, these experiments are unable to decipher the folding process. Therefore, molecular dynamic (MD) simulations are employed to simulate the folding process so that our improved understanding of the folding process will enable us to contemplate better treatments for misfolding diseases. MD simulations make use of force fields to simulate the folding process of peptides. Secondary structures are formed via the hydrogen bonds formed between the backbone atoms (C, O, N, H). It is important that the hydrogen bond energy computed during the MD simulation is accurate in order to direct the folding process to the native structure. Since the atoms involved in a hydrogen bond possess very dissimilar electronegativities, the more electronegative atom will attract greater electron density from the less electronegative atom towards itself. This is known as the polarization effect. Since the polarization effect changes the electron density of the two atoms in close proximity, the atomic charges of the two atoms should also vary based on the strength of the polarization effect. However, the fixed atomic charge scheme in force fields does not account for the polarization effect. In this study, we introduce the polarized structure-specific backbone charge (PSBC) model. The PSBC model accounts for the polarization effect in MD simulation by updating the atomic charges of the backbone hydrogen bond atoms according to equations derived between the amount of charge transferred to the atom and the length of the hydrogen bond, which are calculated from quantum-mechanical calculations. Compared to other polarizable models, the PSBC model does not require quantum-mechanical calculations of the peptide simulated at every time-step of the simulation and maintains the dynamic update of atomic charges, thereby reducing the computational cost and time while accounting for the polarization effect dynamically at the same time. The PSBC model is applied to two different β-peptides, namely the Beta3s/GS peptide, a de novo designed three-stranded β-sheet whose structure is folded in vitro and studied by NMR, and the trpzip peptides, a double-stranded β-sheet where a correlation is found between the type of amino acids that constitute the β-turn and the β-propensity.

Keywords: hydrogen bond, polarization effect, protein folding, PSBC

Procedia PDF Downloads 244

Authors: Ioannis P. Panapakidis, Marios N. Moschakis

Abstract:

The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.

Keywords: deregulated energy market, forecasting, machine learning, system marginal price

Procedia PDF Downloads 189

Authors: Sivaraman Karthikeyan

Abstract:

Due to rapidly developing power electronics devices and technologies such as power line communication or self-commutating converters, voltage and current distortion, as well as interferences, have increased in the frequency range of 2 kHz to 150 kHz; there is an urgent need for regulation of electromagnetic compatibility (EMC) standards in this frequency range. Measuring or testing compliance with emission and immunity limitations necessitates the use of precise, repeatable measuring methods. Appropriate filters to minimize the fundamental component and its harmonics below 2 kHz in the measuring signal would improve the measurement accuracy in this frequency range leading to better analysis. This paper discusses filter suggestions in the current measurement standard and proposes an infinite impulse response (IIR) filter design that is optimized for a low number of poles, strong fundamental damping, and high accuracy above 2 kHz. The new filter’s transfer function is delivered as a result. An analog implementation is derived from the overall design.

Keywords: supraharmonics, 2 kHz, 150 kHz, filter, analog filter

Procedia PDF Downloads 119

Authors: Victor Emeli, Akansel Cosgun

Abstract:

This paper explores the navigation among movable obstacles (NAMO) problem and proposes joint path and push planning: which path to take and in what direction the obstacles should be pushed at, given a start and goal position. We present a planning algorithm for selecting a path and the obstacles to be pushed, where a rapidly-exploring random tree (RRT)-based heuristic is employed to calculate a minimal collision path. When it is necessary to apply a pushing force to slide an obstacle out of the way, the planners leverage means-end analysis through a dynamic physics simulation to determine the sequence of linear pushes to clear the necessary space. Simulation experiments show that our approach finds solutions in higher clutter percentages (up to 49%) compared to the straight-line push planner (37%) and RRT without pushing (18%).

Keywords: motion planning, path planning, push planning, robot navigation

Procedia PDF Downloads 150

Authors: Parveen Banu Ansari, Venkatraman Chinnappan, Paramasivam Shankar

Abstract:

Contract testing plays a pivotal role in the current landscape of microservices architecture. Testing microservices at the initial stages of development helps to identify and rectify issues before they escalate to higher levels, such as UI testing. By validating microservices through contract testing, you ensure the integration quality of APIs, enhancing the overall reliability and performance of the application. Contract testing, being a collaborative effort between testers and developers, ensures that the microservices adhere to the specified contracts or agreements. This proactive approach significantly reduces defects, streamlines the development process, and contributes to the overall efficiency and robustness of the application. In the dynamic and fast-paced world of digital applications, where microservices are the building blocks, embracing contract testing is indeed a strategic move for ensuring the quality and reliability of the entire system.

Keywords: validation, testing, contract, agreement, microservices

Procedia PDF Downloads 40

Authors: Abdul Haq

Abstract:

The goal of this research is to better understand how wind loads affect bridges and develop strategies for designing bridges that are more stable and resistant to wind. The effect of wind on bridges is essential to their safety and functionality, especially in areas that are prone to high wind speeds or violent wind conditions. The study looks at the aerodynamic forces and vibrations caused by wind and how they affect bridge construction. Part of the research method involves first understanding the underlying ideas influencing wind flow near bridges. Computational fluid dynamics (CFD) simulations are used to model and forecast the aerodynamic behaviour of bridges under different wind conditions. These models incorporate several factors, such as wind directionality, wind speed, turbulence intensity, and the influence of nearby structures or topography. The results provide significant new insights into the loads and pressures that wind places on different bridge elements, such as decks, pylons, and connections. Following the determination of the wind loads, the structural response of bridges is assessed. By simulating their dynamic behavior under wind-induced forces, Finite Element Analysis (FEA) is used to model the bridge's component parts. This work contributes to the understanding of which areas are at risk of experiencing excessive stresses, vibrations, or oscillations due to wind excitations. Because the bridge has inherent modes and frequencies, the study considers both static and dynamic responses. Various strategies are examined to maximize the design of bridges to withstand wind. It is possible to alter the bridge's geometry, add aerodynamic components, add dampers or tuned mass dampers to lessen vibrations, and boost structural rigidity. Through an analysis of several design modifications and their effectiveness, the study aims to offer guidelines and recommendations for wind-resistant bridge design. In addition to the numerical simulations and analyses, there are experimental studies. In order to assess the computational models and validate the practicality of proposed design strategies, scaled bridge models are tested in a wind tunnel. These investigations help to improve numerical models and prediction precision by providing valuable information on wind-induced forces, pressures, and flow patterns. Using a combination of numerical models, actual testing, and long-term performance evaluation, the project aims to offer practical insights and recommendations for building wind-resistant bridges that are secure, long-lasting, and comfortable for users.

Keywords: wind effects, aerodynamic forces, computational fluid dynamics, finite element analysis

Procedia PDF Downloads 49

Authors: Kamal, Adil Ahmad

Abstract:

Earthquakes are among the most versatile natural and dynamic processes, and hence a fractal model is considered to be the best representative of the same. We present a novel method to process and analyse information hidden in earthquake sequences using Fractal Dimensions and Iterative Function Systems (IFS). Spatial and temporal variations in the fractal dimensions of seismicity observed around the Indian peninsula in last 30 years are studied. This was used as a possible precursor before large earthquakes in the region. IFS images for observed seismicity in the Himalayan belt were also obtained. We scan the whole data set and coarse grain of a selected window to reduce it to four bins. A critical analysis of four-cornered chaos-game clearly shows that the spatial variation in earthquake occurrences in Himalayan range is not random. Two subzones of Himalaya have a tendency to follow each other in time.

Keywords: earthquakes, fractals, Himalaya, iterated function systems

Procedia PDF Downloads 281

Authors: Gram Y. Rivas Sanchez

Abstract:

The seismic design codes in the world allow the analysis of structures considering an elastic-linear behavior; however, against earthquakes, the structures exhibit non-linear behaviors that induce damage to their elements. For this reason, it is necessary to use non-linear methods to analyze these structures, being the dynamic methods that provide more reliable results but require a lot of computational costs; on the other hand, non-linear static methods do not have this disadvantage and are being used more and more. In the present work, the nonlinear static analysis (pushover) of RC frame buildings of three, five, and seven stories is carried out considering models of concentrated plasticity using plastic hinges; and the seismic performance points are determined using ATC-40, FEMA 356, and FEMA 440 guidelines. Using this last standard, the highest inelastic displacements and basal shears are obtained, providing designs that are more conservative.

Keywords: pushover, nonlinear, RC building, FEMA 440, ATC 40

Procedia PDF Downloads 133

Authors: B. Casper

Abstract:

The energy transition towards renewable energies and drastically reduced carbon dioxide emissions in Germany drives multiple sectors into a transformation process. Photovoltaic and on-shore wind power are predominantly feeding in the low and medium-voltage grids. The electricity grid is not laid out to allow an increasing feed-in of power in low and medium voltage grids. Electric mobility is currently in the run-up phase in Germany and still lacks a significant amount of charging stations. The additional power demand by e-mobility cannot be supplied by the existing electric grids in most cases. The future demands in heating and cooling of commercial and residential buildings are increasingly generated by heat-pumps. Yet the most important part in the energy transition is the storage of surplus energy generated by photovoltaic and wind power sources. Water electrolysis is one way to store surplus energy known as power-to-gas. With the vehicle-to-grid technology, the upcoming fleet of electric cars could be used as energy storage to stabilize the grid. All these processes use direct current (DC). The demand of bi-directional flow and higher efficiency in the future grids can be met by using DC. The Flexible Electrical Networks (FEN) research campus at RWTH Aachen investigates interdisciplinary about the advantages, opportunities, and limitations of DC grids. This paper investigates the impact of DC grids as a technological innovation on the urban form and urban life. Applying explorative scenario development, analyzation of mapped open data sources on grid networks and research-by-design as a conceptual design method, possible starting points for a transformation to DC medium voltage grids could be found. Several fields of action have emerged in which DC technology could become a catalyst for future urban development: energy transition in urban areas, e-mobility, and transformation of the network infrastructure. The investigation shows a significant potential to increase renewable energy production within cities with DC grids. The charging infrastructure for electric vehicles will predominantly be using DC in the future because fast and ultra fast charging can only be achieved with DC. Our research shows that e-mobility, combined with autonomous driving has the potential to change the urban space and urban logistics fundamentally. Furthermore, there are possible win-win-win solutions for the municipality, the grid operator and the inhabitants: replacing overhead transmission lines by underground DC cables to open up spaces in contested urban areas can lead to a positive example of how the energy transition can contribute to a more sustainable urban structure. The outlook makes clear that target grid planning and urban planning will increasingly need to be synchronized.

Keywords: direct current, e-mobility, energy transition, grid planning, renewable energy, urban planning

Procedia PDF Downloads 106

Authors: Pongsawee Supanonth

Abstract:

This research is the study of Spectrum Management and the increase in efficiency of Spectrum Utilization. It also proves that Cognitive Radio is a newer technology that will change the face of e-communications network today. This study used qualitative research methods by using in-depth interviews to collect data from a sample specific to those who work in Radio channel from 6 key informant and literature review from the related documents in online database. The result is the technique of Dynamic Spectrum Allocation that is the most suitable for Thailand. We conduct in-depth research for future purposes. Moreover, we can also develop a model that can be used in regulating and managing spectrum that is most suitable for Thailand. And also develop an important tool which can be of importance to allocation of spectrum as a natural resource appropriately. It will also guarantee quality and high benefit in a substantial way.

Keywords: cognitive radio, management of radio spectrum, spectrum management, spectrum scarcity

Procedia PDF Downloads 295

Authors: Alshehri Sultan

Abstract:

Organizational change has remained an important subject for many researchers in the field of organizations theory. We propose the importance of organizational liability of renewal through a model that examines how an organization can overcome potential rigidities in organizational capabilities from learning by changing capabilities. We examine whether an established organization can overcome liability of renewal by changes in organizational capabilities and how the organizational renewal process reflect on the balance between the dynamic aspect of organizational learning as demonstrated by changes in capabilities and the stabilizing aspects of organizational inertia. We found both positive relationship between organizational learning and performance, and between legitimacy and performance. Performance and legitimacy have, however, a negative relationship on the pressure for change.

Keywords: organizational capabilities, organizational liability, liability of renewal, pressure for change

Procedia PDF Downloads 503

Authors: Narin Salehiyan

Abstract:

The three iodothyronine selenodeiodinases catalyze the start and end of thyroid hormone impacts in vertebrates. Auxiliary examinations of these proteins have been prevented by their indispensably film nature and the wasteful eukaryotic-specific pathway for selenoprotein blend. Hydrophobic cluster examination utilized in combination with Position-specific Iterated Impact uncovers that their extramembrane parcel has a place to the thioredoxin-fold superfamily for which test structure data exists. Besides, a expansive deiodinase locale imbedded within the thioredoxin overlay offers solid similitudes with the dynamic location of iduronidase, a part of the clan GH-A-fold of glycoside hydrolases. This show can clarify a number of comes about from past mutagenesis examinations and grants unused irrefutable experiences into the auxiliary and utilitarian properties of these proteins.

Keywords: glycoside, hydrolase, GH-A-like structure, catalyze

Procedia PDF Downloads 50

Authors: Ibrahim Ozkan

Abstract:

In this study, a cross-layer design which combines adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ) techniques for a cooperative wireless network is investigated analytically. Previous analyses of such systems in the literature are confined to the case where the fading channel is independent at each retransmission, which can be unrealistic unless the channel is varying very fast. On the other hand, temporal channel correlation can have a significant impact on the performance of HARQ systems. In this study, utilizing a Markov channel model which accounts for the temporal correlation, the performance of non-cooperative and cooperative networks are investigated in terms of packet loss rate and throughput metrics for Chase combining HARQ strategy.

Keywords: cooperative network, adaptive modulation and coding, hybrid ARQ, correlated fading

Procedia PDF Downloads 121

Authors: Nestor A. Garcia Fragoso, Tetyana Baydyk, Ernst Kussul

Abstract:

This article contains information from our investigation in the field of voice recognition. For this purpose, we created a voice database that contains different phrases in two languages, English and Spanish, for men and women. As a classifier, the LIRA (Limited Receptive Area) grayscale neural classifier was selected. The LIRA grayscale neural classifier was developed for image recognition tasks and demonstrated good results. Therefore, we decided to develop a recognition system using this classifier for voice recognition. From a specific set of speakers, we can recognize the speaker’s voice. For this purpose, the system uses spectrograms of the voice signals as input to the system, extracts the characteristics and identifies the speaker. The results are described and analyzed in this article. The classifier can be used for speaker identification in security system or smart buildings for different types of intelligent devices.

Keywords: extreme learning, LIRA neural classifier, speaker identification, voice recognition

Procedia PDF Downloads 154

Authors: Magdi. M. Nabi, Ding-Li Yu

Abstract:

Control of a semi-batch polymerization reactor using an adaptive radial basis function (RBF) neural network method is investigated in this paper. A neural network inverse model is used to estimate the valve position of the reactor; this method can identify the controlled system with the RBF neural network identifier. The weights of the adaptive PID controller are timely adjusted based on the identification of the plant and self-learning capability of RBFNN. A PID controller is used in the feedback control to regulate the actual temperature by compensating the neural network inverse model output. Simulation results show that the proposed control has strong adaptability, robustness and satisfactory control performance and the nonlinear system is achieved.

Keywords: Chylla-Haase polymerization reactor, RBF neural networks, feed-forward, feedback control

Procedia PDF Downloads 680

Authors: Emil Mathew

Abstract:

Liberalisation policies adopted by a large number of countries, implementation of technological innovations with development in communication networks and continuous reduction in transport costs contributed towards the growth of international transportation of goods over the last 50 to 60 years. The present paper examines the environmental externalities of maritime transportation, that is, externalities associated with the movement of cargoes, as distinct from those emanate from production and consumption of goods. Though shipping is less polluting compared to other modes of transportation, considering the huge volume of goods transported and future growth prospects, it is important to examine environmental externalities of maritime transportation. It focuses on varied types of environmental externalities of maritime transportation and suggests that appropriate policies may be adopted by international agencies to address this issue without adversely affecting the course of international trade and also its possibility to get diverted to alternate modes of transportation.

Keywords: externalities of globalisation, maritime environment, maritime externality, transportation externality

Procedia PDF Downloads 264

Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

Abstract:

To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

Procedia PDF Downloads 118

Authors: Mohammad Javad Mollakazemi, Farhad Asadi

Abstract:

In this paper a real-time obstacle avoidance approach for both autonomous and non-autonomous dynamical systems (DS) is presented. In this approach the original dynamics of the controller which allow us to determine safety margin can be modulated. Different common types of DS increase the robot’s reactiveness in the face of uncertainty in the localization of the obstacle especially when robot moves very fast in changeable complex environments. The method is validated by simulation and influence of different autonomous and non-autonomous DS such as important characteristics of limit cycles and unstable DS. Furthermore, the position of different obstacles in complex environment is explained. Finally, the verification of avoidance trajectories is described through different parameters such as safety factor.

Keywords: limit cycles, nonlinear dynamical system, real time obstacle avoidance, safety margin

Procedia PDF Downloads 425

Authors: Lihua Zhu, Jianfeng Du, Yu Wang, Zhiqiang Wu

Abstract:

Collision avoidance problems of a swarm of unmanned air vehicles (UAVs) flying in an obstacle-laden environment are investigated in this paper. Given that the UAV swarm needs to adapt to the obstacle distribution in dynamic operation, a priority configuration is designed to guide the UAVs to pass through the obstacles in turn. Based on the collision cone approach and the prediction of the collision time, a collision evaluation model is established to judge the urgency of the imminent collision of each UAV, and the evaluation result is used to assign the priority of each UAV to further instruct them going through the obstacles in descending order. At last, the simulation results provide the promising validation in terms of the efficiency and scalability of the proposed approach.

Keywords: UAV swarm, collision avoidance, complex environment, online priority design

Procedia PDF Downloads 196

Authors: Hadj Miloua, Abbes Azzi

Abstract:

The objective of the present paper is to understand, predict and modeled the fire behavior in confined and open area in different conditions and diverse fuels such as liquid pool fire and the vegetative materials. The distinctive problems are a ventilated road tunnel used for urban transport, by the characterization installations of ventilation and his influence in the mode of smoke dispersion and the flame shape. A general investigation is relatively traditional, based on the modeling and simulation the scenario of the pool fire interacted with wind ventilation by the use of numerical software fire dynamic simulator FDS ver.5 to simulate the fire in ventilated tunnel. The second simulation by WFDS.5 is Wildland fire which is always occurs in forest and rangeland fire environments and will thus have an impact on people, property and resources.

Keywords: fire, road tunnel, simulation, vegetation, wildland

Procedia PDF Downloads 490

Authors: Azzedine Abdedou, Khedidja Bouhadef

Abstract:

The present study is an analysis of the forced convection heat transfer in porous channel with an oriented jet at the inlet with uniform velocity and temperature distributions. The upper wall is insulated when the bottom one is kept at constant temperature higher than that of the fluid at the entrance. The dynamic field is analysed by the Brinkman-Forchheimer extended Darcy model and the thermal field is traduced by the energy one equation model. The numerical solution of the governing equations is obtained by using the finite volume method. The results mainly concern the effect of Reynolds number, jet angle and thermal conductivity ratio on the flow structure and local and average Nusselt numbers evolutions.

Keywords: forced convection, porous media, oriented confined jet, fluid mechanics

Procedia PDF Downloads 365

Authors: M. Caramihai, Irina Severin

Abstract:

This paper deals with the design of an intelligent control structure for a bioprocess of Hansenula polymorpha yeast cultivation. The objective of the process control is to produce biomass in a desired physiological state. The work demonstrates that the designed Hybrid Control Techniques (HCT) are able to recognize specific evolution bioprocess trajectories using neural networks trained specifically for this purpose, in order to estimate the model parameters and to adjust the overall bioprocess evolution through an expert system and a fuzzy structure. The design of the control algorithm as well as its tuning through realistic simulations is presented. Taking into consideration the synergism of different paradigms like fuzzy logic, neural network, and symbolic artificial intelligence (AI), in this paper we present a real and fulfilled intelligent control architecture with application in bioprocess control.

Keywords: bioprocess, intelligent control, neural nets, fuzzy structure, hybrid techniques

Procedia PDF Downloads 392

Authors: Kevin De Castro Cogle, Mirian Kubo, Maria Anastasiadi, Fady Mohareb, Claire Rossi

Abstract:

Background: The bioaccessibility of bioactive compounds is a critical determinant of the nutritional quality of various food products. Despite its importance, there is a limited number of comprehensive studies aimed at assessing how the composition of a food matrix influences the bioaccessibility of a compound of interest. This knowledge gap has prompted a growing need to investigate the intricate relationship between food matrix formulations and the bioaccessibility of bioactive compounds. One such class of bioactive compounds that has attracted considerable attention is curcuminoids. These naturally occurring phytochemicals, extracted from the roots of Curcuma longa, have gained popularity owing to their purported health benefits and also well known for their poor bioaccessibility Project aim: The primary objective of this research project is to systematically assess the influence of matrix composition on the bioaccessibility of curcuminoids. Additionally, this study aimed to develop a series of predictive models for bioaccessibility, providing valuable insights for optimising the formula for functional foods and provide more descriptive nutritional information to potential consumers. Methods: Food formulations enriched with curcuminoids were subjected to in vitro digestion simulation, and their bioaccessibility was characterized with chromatographic and spectrophotometric techniques. The resulting data served as the foundation for the development of predictive models capable of estimating bioaccessibility based on specific physicochemical properties of the food matrices. Results: One striking finding of this study was the strong correlation observed between the concentration of macronutrients within the food formulations and the bioaccessibility of curcuminoids. In fact, macronutrient content emerged as a very informative explanatory variable of bioaccessibility and was used, alongside other variables, as predictors in a Bayesian hierarchical model that predicted curcuminoid bioaccessibility accurately (optimisation performance of 0.97 R2) for the majority of cross-validated test formulations (LOOCV of 0.92 R2). These preliminary results open the door to further exploration, enabling researchers to investigate a broader spectrum of food matrix types and additional properties that may influence bioaccessibility. Conclusions: This research sheds light on the intricate interplay between food matrix composition and the bioaccessibility of curcuminoids. This study lays a foundation for future investigations, offering a promising avenue for advancing our understanding of bioactive compound bioaccessibility and its implications for the food industry and informed consumer choices.

Keywords: bioactive bioaccessibility, food formulation, food matrix, machine learning, probabilistic modelling

Procedia PDF Downloads 55