Search results for: modified simplex algorithm
4695 An Optimized Approach to Generate the Possible States of Football Tournaments Final Table
Authors: Mouslem Damkhi
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This paper focuses on possible states of a football tournament final table according to the number of participating teams. Each team holds a position in the table with which it is possible to determine the highest and lowest points for that team. This paper proposes an optimized search space based on the minimum and maximum number of points which can be gained by each team to produce and enumerate the possible states for a football tournament final table. The proposed search space minimizes producing the invalid states which cannot occur during a football tournament. The generated states are filtered by a validity checking algorithm which seeks to reach a tournament graph based on a generated state. Thus, the algorithm provides a way to determine which team’s wins, draws and loses values guarantee a particular table position. The paper also presents and discusses the experimental results of the approach on the tournaments with up to eight teams. Comparing with a blind search algorithm, our proposed approach reduces generating the invalid states up to 99.99%, which results in a considerable optimization in term of the execution time.Keywords: combinatorics, enumeration, graph, tournament
Procedia PDF Downloads 1254694 A Novel Photocrosslinkable and Cytocompatible Chitosan Coating for TI6AL4V Surfaces
Authors: D. Zujur, J. Moret, D. Rodriguez, L. Cruz, J. Lira, L. Gil, E. Dominguez, J. F. Alvarez-Barreto
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In this work, chitosan (CH) has been used to produce a novel coating for Ti6Al4V, the most widely used alloy in orthopedic implants, so as to improve the biological tissue response at the metallic surface. The Ti6Al4V surface was sandblasted with alumina particles and observed by SEM. Chitosan was chemically modified, via crodiimide chemistry, with lactobionic and 4-azidebenzoic acid to make it soluble at physiological pH and photo-crosslinkable, respectively. The reaction was verified by FTIR, NMR, and UV/vis spectroscopy. Ti6Al4V surfaces were coated with solutions of the modified CH and exposed to UV light, causing the polymer crosslinking, and formation of a hydrogel on the surface. The crosslinking reaction was monitored by FTIR at different exposure times. Coating morphology was observed by SEM. The coating´s cytocompatibility was determined in vitro through the culture of rat bone marrow´s mesenchymal stem cells, using an MTT assay. The results show that the developed coating is cytocompatible, easy to apply and could be used for further studies in the encapsulation of bioactive molecules to improve osteogenic potential at the tissue-implant interface.Keywords: chitosan, photo-crosslinking, Ti6Al4V, bioactive coating, hydrogel
Procedia PDF Downloads 3294693 Fast Return Path Planning for Agricultural Autonomous Terrestrial Robot in a Known Field
Authors: Carlo Cernicchiaro, Pedro D. Gaspar, Martim L. Aguiar
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The agricultural sector is becoming more critical than ever in view of the expected overpopulation of the Earth. The introduction of robotic solutions in this field is an increasingly researched topic to make the most of the Earth's resources, thus going to avoid the problems of wear and tear of the human body due to the harsh agricultural work, and open the possibility of a constant careful processing 24 hours a day. This project is realized for a terrestrial autonomous robot aimed to navigate in an orchard collecting fallen peaches below the trees. When it receives the signal indicating the low battery, it has to return to the docking station where it will replace its battery and then return to the last work point and resume its routine. Considering a preset path in orchards with tree rows with variable length by which the robot goes iteratively using the algorithm D*. In case of low battery, the D* algorithm is still used to determine the fastest return path to the docking station as well as to come back from the docking station to the last work point. MATLAB simulations were performed to analyze the flexibility and adaptability of the developed algorithm. The simulation results show an enormous potential for adaptability, particularly in view of the irregularity of orchard field, since it is not flat and undergoes modifications over time from fallen branch as well as from other obstacles and constraints. The D* algorithm determines the best route in spite of the irregularity of the terrain. Moreover, in this work, it will be shown a possible solution to improve the initial points tracking and reduce time between movements.Keywords: path planning, fastest return path, agricultural autonomous terrestrial robot, docking station
Procedia PDF Downloads 1374692 Implementation of Invisible Digital Watermarking
Authors: V. Monisha, D. Sindhuja, M. Sowmiya
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Over the decade, the applications about multimedia have been developed rapidly. The advancement in the communication field at the faster pace, it is necessary to protect the data during transmission. Thus, security of multimedia contents becomes a vital issue, and it is a need for protecting the digital content against malfunctions. Digital watermarking becomes the solution for the copyright protection and authentication of data in the network. In multimedia applications, embedded watermarks should be robust, and imperceptible. For improving robustness, the discrete wavelet transform is used. Both encoding and extraction algorithm can be done using MATLAB R2012a. In this Discrete wavelet transform (DWT) domain of digital image, watermarking algorithm is used, and hardware implementation can be done on Xilinx based FPGA.Keywords: digital watermarking, DWT, robustness, FPGA
Procedia PDF Downloads 4164691 Convergence Analysis of a Gibbs Sampling Based Mix Design Optimization Approach for High Compressive Strength Pervious Concrete
Authors: Jiaqi Huang, Lu Jin
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Pervious concrete features with high water permeability rate. However, due to the lack of fine aggregates, the compressive strength is usually lower than other conventional concrete products. Optimization of pervious concrete mix design has long been recognized as an effective mechanism to achieve high compressive strength while maintaining desired permeability rate. In this paper, a Gibbs Sampling based algorithm is proposed to approximate the optimal mix design to achieve a high compressive strength of pervious concrete. We prove that the proposed algorithm efficiently converges to the set of global optimal solutions. The convergence rate and accuracy depend on a control parameter employed in the proposed algorithm. The simulation results show that, by using the proposed approach, the system converges to the optimal solution quickly and the derived optimal mix design achieves the maximum compressive strength while maintaining the desired permeability rate.Keywords: convergence, Gibbs Sampling, high compressive strength, optimal mix design, pervious concrete
Procedia PDF Downloads 1834690 Combination of Electrochemical Impedance Spectroscopy and Electromembrane Extraction for the Determination of Zolpidem Using Modified Screen-Printed Electrode
Authors: Ali Naeemy, Mir Ghasem Hoseini
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In this study, for the first time, an analytical method developed and validated by combining electrochemical impedance spectroscopy and electromembrane extraction (EIS-EME) by Vulcan/poly pyrrole nanocomposite modified screen-printed electrode (PPY–VU/SPE) for accurately quantifying zolpidem. EME parameters optimized, including solvent composition, voltage, pH adjustments and extraction time. Zolpidem was transferred from a donor solution (pH 5) to an acceptor solution (pH 13) using a hollow fiber in 1-octanol as a membrane, driven by a 60 V voltage for 25 minutes, ensuring precise and selective extraction. In comparison with SPE, VU/SPE and PPY/SPE, the PPY–VU/SPE was much more efficient for ZP oxidation. Calibration curves with good linearity were obtained in the concentration range of 2-75 µmol L-1 using the EIS-EME with the detection limit of 0.5 µmol L-1 . Finally, the EIS-EME by using the PPY– VU/SPE was successfully used to determine ZP in tablet dosage form, urine and plasma samples. Keywords: Electrochemical impedance spectroscopy, Electromembrane extraction, Zolpidem, Vulcan, poly pyrrole, Screen printed electrodeKeywords: electrochemical impedance spectroscopy, electromembrane extraction, screen printed electrode, zolpidem
Procedia PDF Downloads 434689 Performance Investigation of UAV Attitude Control Based on Modified PI-D and Nonlinear Dynamic Inversion
Authors: Ebrahim Hassan Kapeel, Ahmed Mohsen Kamel, Hossan Hendy, Yehia Z. Elhalwagy
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Interest in autopilot design has been raised intensely as a result of recent advancements in Unmanned Aerial vehicles (UAVs). Due to the enormous number of applications that UAVs can achieve, the number of applied control theories used for them has increased in recent years. These small fixed-wing UAVs are suffering high non-linearity, sensitivity to disturbances, and coupling effects between their channels. In this work, the nonlinear dynamic inversion (NDI) control lawisdesigned for a nonlinear small fixed-wing UAV model. The NDI is preferable for varied operating conditions, there is no need for a scheduling controller. Moreover, it’s applicable for high angles of attack. For the designed flight controller validation, a nonlinear Modified PI-D controller is performed with our model. A comparative study between both controllers is achieved to evaluate the NDI performance. Simulation results and analysis are proposed to illustrate the effectiveness of the designed controller based on NDI.Keywords: UAV dynamic model, attitude control, nonlinear PID, dynamic inversion
Procedia PDF Downloads 1144688 Internet of Things Networks: Denial of Service Detection in Constrained Application Protocol Using Machine Learning Algorithm
Authors: Adamu Abdullahi, On Francisca, Saidu Isah Rambo, G. N. Obunadike, D. T. Chinyio
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The paper discusses the potential threat of Denial of Service (DoS) attacks in the Internet of Things (IoT) networks on constrained application protocols (CoAP). As billions of IoT devices are expected to be connected to the internet in the coming years, the security of these devices is vulnerable to attacks, disrupting their functioning. This research aims to tackle this issue by applying mixed methods of qualitative and quantitative for feature selection, extraction, and cluster algorithms to detect DoS attacks in the Constrained Application Protocol (CoAP) using the Machine Learning Algorithm (MLA). The main objective of the research is to enhance the security scheme for CoAP in the IoT environment by analyzing the nature of DoS attacks and identifying a new set of features for detecting them in the IoT network environment. The aim is to demonstrate the effectiveness of the MLA in detecting DoS attacks and compare it with conventional intrusion detection systems for securing the CoAP in the IoT environment. Findings: The research identifies the appropriate node to detect DoS attacks in the IoT network environment and demonstrates how to detect the attacks through the MLA. The accuracy detection in both classification and network simulation environments shows that the k-means algorithm scored the highest percentage in the training and testing of the evaluation. The network simulation platform also achieved the highest percentage of 99.93% in overall accuracy. This work reviews conventional intrusion detection systems for securing the CoAP in the IoT environment. The DoS security issues associated with the CoAP are discussed.Keywords: algorithm, CoAP, DoS, IoT, machine learning
Procedia PDF Downloads 824687 Forensic Speaker Verification in Noisy Environmental by Enhancing the Speech Signal Using ICA Approach
Authors: Ahmed Kamil Hasan Al-Ali, Bouchra Senadji, Ganesh Naik
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We propose a system to real environmental noise and channel mismatch for forensic speaker verification systems. This method is based on suppressing various types of real environmental noise by using independent component analysis (ICA) algorithm. The enhanced speech signal is applied to mel frequency cepstral coefficients (MFCC) or MFCC feature warping to extract the essential characteristics of the speech signal. Channel effects are reduced using an intermediate vector (i-vector) and probabilistic linear discriminant analysis (PLDA) approach for classification. The proposed algorithm is evaluated by using an Australian forensic voice comparison database, combined with car, street and home noises from QUT-NOISE at a signal to noise ratio (SNR) ranging from -10 dB to 10 dB. Experimental results indicate that the MFCC feature warping-ICA achieves a reduction in equal error rate about (48.22%, 44.66%, and 50.07%) over using MFCC feature warping when the test speech signals are corrupted with random sessions of street, car, and home noises at -10 dB SNR.Keywords: noisy forensic speaker verification, ICA algorithm, MFCC, MFCC feature warping
Procedia PDF Downloads 4094686 Spontaneous Message Detection of Annoying Situation in Community Networks Using Mining Algorithm
Authors: P. Senthil Kumari
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Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.Keywords: text mining, data classification, community network, learning algorithm
Procedia PDF Downloads 5104685 Machine Learning Invariants to Detect Anomalies in Secure Water Treatment
Authors: Jonathan Heng, Yoong Cheah Huei
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A strategic model that does not trigger any false alarms to detect anomalies in Secure Water Treatment (SWaT) test bed is presented. This model uses machine learning invariants formulated from streamlining the general form of Auto-Regressive models with eXogenous input. A creative generalized CUSUM algorithm to integrate the invariants and the detection strategy technique is successfully developed and tested in the SWaT Programmable Logic Controllers (PLCs). Three steps to fine-tune parameters, b and τ in the generalized algorithm are stated and an example used to demonstrate the tuning process is discussed. This approach can swiftly and effectively detect various scopes of cyber-attacks such as multiple points single stage and multiple points multiple stages in SWaT. This technique can be applied in water treatment plants and other cyber physical systems like power and gas plants too.Keywords: machine learning invariants, generalized CUSUM algorithm with invariants and detection strategy, scope of cyber attacks, strategic model, tuning parameters
Procedia PDF Downloads 1844684 Real Time Lidar and Radar High-Level Fusion for Obstacle Detection and Tracking with Evaluation on a Ground Truth
Authors: Hatem Hajri, Mohamed-Cherif Rahal
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Both Lidars and Radars are sensors for obstacle detection. While Lidars are very accurate on obstacles positions and less accurate on their velocities, Radars are more precise on obstacles velocities and less precise on their positions. Sensor fusion between Lidar and Radar aims at improving obstacle detection using advantages of the two sensors. The present paper proposes a real-time Lidar/Radar data fusion algorithm for obstacle detection and tracking based on the global nearest neighbour standard filter (GNN). This algorithm is implemented and embedded in an automative vehicle as a component generated by a real-time multisensor software. The benefits of data fusion comparing with the use of a single sensor are illustrated through several tracking scenarios (on a highway and on a bend) and using real-time kinematic sensors mounted on the ego and tracked vehicles as a ground truth.Keywords: ground truth, Hungarian algorithm, lidar Radar data fusion, global nearest neighbor filter
Procedia PDF Downloads 1764683 Partial Knowledge Transfer Between the Source Problem and the Target Problem in Genetic Algorithms
Authors: Terence Soule, Tami Al Ghamdi
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To study how the partial knowledge transfer may affect the Genetic Algorithm (GA) performance, we model the Transfer Learning (TL) process using GA as the model solver. The objective of the TL is to transfer the knowledge from one problem to another related problem. This process imitates how humans think in their daily life. In this paper, we proposed to study a case where the knowledge transferred from the S problem has less information than what the T problem needs. We sampled the transferred population using different strategies of TL. The results showed transfer part of the knowledge is helpful and speeds the GA process of finding a solution to the problem.Keywords: transfer learning, partial transfer, evolutionary computation, genetic algorithm
Procedia PDF Downloads 1344682 Water Detection in Aerial Images Using Fuzzy Sets
Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho
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This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.Keywords: aerial images, fuzzy clustering, image processing, pattern recognition
Procedia PDF Downloads 4854681 A Comparative Study for Various Techniques Using WEKA for Red Blood Cells Classification
Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy
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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifyig the red blood cells as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectivelyKeywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm
Procedia PDF Downloads 4814680 Electronic and Optical Properties of Orthorhombic NdMnO3 with the Modified Becke-Johnson Potential
Authors: B. Bouadjemi, S. Bentata, T. Lantri, A. Abbad, W. Benstaali, A. Zitouni, S. Cherid
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We investigate the electronic structure, magnetic and optical properties of the orthorhombic NdMnO3 through density-functional-theory (DFT) calculations using both generalized gradient approximation GGA and GGA+U approaches, the exchange and correlation effects are taken into account by an orbital independent modified Becke Johnson (MBJ). The predicted band gaps using the MBJ exchange approximation show a significant improvement over previous theoretical work with the common GGA and GGA+U very closer to the experimental results. Band gap dependent optical parameters like dielectric constant, index of refraction, absorption coefficient, reflectivity and conductivity are calculated and analyzed. We find that when using MBJ we have obtained better results for band gap of NdMnO3 than in the case of GGA and GGA+U. The values of band gap founded in this work by MBJ are in a very good agreement with corresponding experimental values compared to other calculations. This comprehensive theoretical study of the optoelectronic properties predicts that this material can be effectively used in optical devices.Keywords: DFT, optical properties, absorption coefficient, strong correlation, MBJ, orthorhombic NdMnO3, optoelectronic
Procedia PDF Downloads 9124679 Liver and Liver Lesion Segmentation From Abdominal CT Scans
Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid
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The interpretation of medical images benefits from anatomical and physiological priors to optimize computer- aided diagnosis applications. Segmentation of liver and liver lesion is regarded as a major primary step in computer aided diagnosis of liver diseases. Precise liver segmentation in abdominal CT images is one of the most important steps for the computer-aided diagnosis of liver pathology. In this papers, a semi- automated method for medical image data is presented for the liver and liver lesion segmentation data using mathematical morphology. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological filters to extract the liver. The second step consists to detect the liver lesion. In this task; we proposed a new method developed for the semi-automatic segmentation of the liver and hepatic lesions. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to improve the quality of the original image and image gradient by applying the spatial filter followed by the morphological filters. The second step consists to calculate the internal and external markers of the liver and hepatic lesions. Thereafter we proceed to the liver and hepatic lesions segmentation by the watershed transform controlled by markers. The validation of the developed algorithm is done using several images. Obtained results show the good performances of our proposed algorithmKeywords: anisotropic diffusion filter, CT images, hepatic lesion segmentation, Liver segmentation, morphological filter, the watershed algorithm
Procedia PDF Downloads 4544678 Adaptive Control Approach for an Unmanned Aerial Manipulator
Authors: Samah Riache, Madjid Kidouche
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In this paper, we propose a nonlinear controller for Aerial Manipulator (AM) consists of a Quadrotor equipped with two degrees of freedom robotic arm. The kinematic and dynamic models were developed by considering the aerial manipulator as a coupled system. The proposed controller was designed using Nonsingular Terminal Sliding Mode Control. The objective of our approach is to improve performances and attenuate the chattering drawback using an adaptive algorithm in the discontinuous control part. Simulation results prove the effectiveness of the proposed control strategy compared with Sliding Mode Controller.Keywords: adaptive algorithm, quadrotor, robotic arm, sliding mode control
Procedia PDF Downloads 1884677 Dual-Band Microwave Metamaterial Absorber Using Modified Circular Ring Resonator for Sensor Applications
Authors: Ramesh Amugothu, Vakula Damera, Narasimha Sarma N. V. S.
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This study presents a dual-band metamaterial microwave absorber that functions at frequencies of 3.5 GHz and 5.7 GHz. The design comprises modified ring and rectangular patch resonators fabricated on an FR4 dielectric substrate with a ground layer beneath it, emphasizing simplicity. Each absorption frequency is independent and can be individually adjusted by altering the dimensions of the respective resonator structures. The unit cell of the absorber is simulated and optimized parametrically using high-frequency structure simulator (HFSS) software. The mechanism behind the absorption is examined through surface current analysis as well as the symmetric model method. The absorber demonstrates over 97% absorption at both resonant frequencies and is shown to be suitable for sensing applications related to dielectric constant measurement. With its straightforward design, wide-angle acceptance, and polarization-insensitive characteristics, the proposed absorber is likely to be beneficial for both absorption and sensing purposes.Keywords: absorption, dielectric permittivity, metamaterials, metasurfaces, resonant structures, sensor devices
Procedia PDF Downloads 154676 Genetic Algorithm Based Node Fault Detection and Recovery in Distributed Sensor Networks
Authors: N. Nalini, Lokesh B. Bhajantri
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In Distributed Sensor Networks, the sensor nodes are prone to failure due to energy depletion and some other reasons. In this regard, fault tolerance of network is essential in distributed sensor environment. Energy efficiency, network or topology control and fault-tolerance are the most important issues in the development of next-generation Distributed Sensor Networks (DSNs). This paper proposes a node fault detection and recovery using Genetic Algorithm (GA) in DSN when some of the sensor nodes are faulty. The main objective of this work is to provide fault tolerance mechanism which is energy efficient and responsive to network using GA, which is used to detect the faulty nodes in the network based on the energy depletion of node and link failure between nodes. The proposed fault detection model is used to detect faults at node level and network level faults (link failure and packet error). Finally, the performance parameters for the proposed scheme are evaluated.Keywords: distributed sensor networks, genetic algorithm, fault detection and recovery, information technology
Procedia PDF Downloads 4534675 Probability-Based Damage Detection of Structures Using Model Updating with Enhanced Ideal Gas Molecular Movement Algorithm
Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee
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Model updating method has received increasing attention in damage detection structures based on measured modal parameters. Therefore, a probability-based damage detection (PBDD) procedure based on a model updating procedure is presented in this paper, in which a one-stage model-based damage identification technique based on the dynamic features of a structure is investigated. The presented framework uses a finite element updating method with a Monte Carlo simulation that considers the uncertainty caused by measurement noise. Enhanced ideal gas molecular movement (EIGMM) is used as the main algorithm for model updating. Ideal gas molecular movement (IGMM) is a multiagent algorithm based on the ideal gas molecular movement. Ideal gas molecules disperse rapidly in different directions and cover all the space inside. This is embedded in the high speed of molecules, collisions between them and with the surrounding barriers. In IGMM algorithm to accomplish the optimal solutions, the initial population of gas molecules is randomly generated and the governing equations related to the velocity of gas molecules and collisions between those are utilized. In this paper, an enhanced version of IGMM, which removes unchanged variables after specified iterations, is developed. The proposed method is implemented on two numerical examples in the field of structural damage detection. The results show that the proposed method can perform well and competitive in PBDD of structures.Keywords: enhanced ideal gas molecular movement (EIGMM), ideal gas molecular movement (IGMM), model updating method, probability-based damage detection (PBDD), uncertainty quantification
Procedia PDF Downloads 2804674 Pilot Induced Oscillations Adaptive Suppression in Fly-By-Wire Systems
Authors: Herlandson C. Moura, Jorge H. Bidinotto, Eduardo M. Belo
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The present work proposes the development of an adaptive control system which enables the suppression of Pilot Induced Oscillations (PIO) in Digital Fly-By-Wire (DFBW) aircrafts. The proposed system consists of a Modified Model Reference Adaptive Control (M-MRAC) integrated with the Gain Scheduling technique. The PIO oscillations are detected using a Real Time Oscillation Verifier (ROVER) algorithm, which then enables the system to switch between two reference models; one in PIO condition, with low proneness to the phenomenon and another one in normal condition, with high (or medium) proneness. The reference models are defined in a closed loop condition using the Linear Quadratic Regulator (LQR) control methodology for Multiple-Input-Multiple-Output (MIMO) systems. The implemented algorithms are simulated in software implementations with state space models and commercial flight simulators as the controlled elements and with pilot dynamics models. A sequence of pitch angles is considered as the reference signal, named as Synthetic Task (Syntask), which must be tracked by the pilot models. The initial outcomes show that the proposed system can detect and suppress (or mitigate) the PIO oscillations in real time before it reaches high amplitudes.Keywords: adaptive control, digital Fly-By-Wire, oscillations suppression, PIO
Procedia PDF Downloads 1364673 Thermo-Mechanical Characterization of MWCNTs-Modified Epoxy Resin
Authors: M. Dehghan, R. Al-Mahaidi, I. Sbarski
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An industrial epoxy adhesive used in Carbon Fiber Reinforced Polymer (CFRP)-strengthening systems was modified by dispersing multi-walled carbon nanotubes (MWCNTs). Nanocomposites were fabricated using solvent-assisted dispersion method and ultrasonic mixing. Thermogravimetric analysis (TGA), dynamic mechanical analysis (DMA) and tensile tests were conducted to study the effect of nanotubes dispersion on the thermal and mechanical properties of the epoxy composite. Experimental results showed a substantial enhancement in the decomposition temperature and tensile properties of epoxy composite, while, the glass transition temperature (Tg) was slightly reduced due to the solvent effect. The morphology of the epoxy nanocomposites was investigated by SEM. It was proved that using solvent improves the nanotubes dispersion. However, at contents higher than 2 wt. %, nanotubes started to re-bundle in the epoxy matrix which negatively affected the final properties of epoxy composite.Keywords: carbon fiber reinforced polymer, epoxy, multi-walled carbon nanotube, DMA, glass transition temperature
Procedia PDF Downloads 3484672 Seismic Behavior of Self-Balancing Post-Tensioned Reinforced Concrete Spatial Structure
Authors: Mircea Pastrav, Horia Constantinescu
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The construction industry is currently trying to develop sustainable reinforced concrete structures. In trying to aid in the effort, the research presented in this paper aims to prove the efficiency of modified special hybrid moment frames composed of discretely jointed precast and post-tensioned concrete members. This aim is due to the fact that current design standards do not cover the spatial design of moment frame structures assembled by post-tensioning with special hybrid joints. This lack of standardization is coupled with the fact that previous experimental programs, available in scientific literature, deal mainly with plane structures and offer little information regarding spatial behavior. A spatial model of a modified hybrid moment frame is experimentally analyzed. The experimental results of a natural scale model test of a corner column-beams sub-structure, cut from an actual multilevel building tested to seismic type loading are presented in order to highlight the behavior of this type of structure. The test is performed under alternative cycles of imposed lateral displacements, up to a storey drift ratio of 0.035. Seismic response of the spatial model is discussed considering the acceptance criteria for reinforced concrete frame structures designed based on experimental tests, as well as some of its major sustainability features. The results obtained show an overall excellent behavior of the system. The joint detailing allows for quick and cheap repairs after an accidental event and a self-balancing behavior of the system that ensures it can be used almost immediately after an accidental event it.Keywords: modified hybrid joint, seismic type loading response, self-balancing structure, acceptance criteria
Procedia PDF Downloads 2424671 Investigation of the Properties of Epoxy Modified Binders Based on Epoxy Oligomer with Improved Deformation and Strength Properties
Authors: Hlaing Zaw Oo, N. Kostromina, V. Osipchik, T. Kravchenko, K. Yakovleva
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The process of modification of ed-20 epoxy resin synthesized by vinyl-containing compounds is considered. It is shown that the introduction of vinyl-containing compounds into the composition based on epoxy resin ED-20 allows adjusting the technological and operational characteristics of the binder. For improvement of the properties of epoxy resin, following modifiers were selected: polyvinylformalethyl, polyvinyl butyral and composition of linear and aromatic amines (Аramine) as a hardener. Now the big range of hardeners of epoxy resins exists that allows varying technological properties of compositions, and also thermophysical and strength indicators. The nature of the aramin type hardener has a significant impact on the spatial parameters of the mesh, glass transition temperature, and strength characteristics. Epoxy composite materials based on ED-20 modified with polyvinyl butyral were obtained and investigated. It is shown that the composition of resins based on derivatives of polyvinyl butyral and ED-20 allows obtaining composite materials with a higher complex of deformation-strength, adhesion and thermal properties, better water resistance, frost resistance, chemical resistance, and impact strength. The magnitude of the effect depends on the chemical structure, temperature and curing time. In the area of concentrations, where the effect of composite synergy is appearing, the values of strength and stiffness significantly exceed the similar parameters of the individual components of the mixture. The polymer-polymer compositions form their class of materials with diverse specific properties that ensure their competitive application. Coatings with high performance under cyclic loading have been obtained based on epoxy oligomers modified with vinyl-containing compounds.Keywords: epoxy resins, modification, vinyl-containing compounds, deformation, strength properties
Procedia PDF Downloads 1134670 Metaheuristic to Align Multiple Sequences
Authors: Lamiche Chaabane
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In this study, a new method for solving sequence alignment problem is proposed, which is named ITS (Improved Tabu Search). This algorithm is based on the classical Tabu Search (TS). ITS is implemented in order to obtain results of multiple sequence alignment. Several ideas concerning neighbourhood generation, move selection mechanisms and intensification/diversification strategies for our proposed ITS is investigated. ITS have generated high-quality results in terms of measure of scores in comparison with the classical TS and simple iterative search algorithm.Keywords: multiple sequence alignment, tabu search, improved tabu search, neighbourhood generation, selection mechanisms
Procedia PDF Downloads 3064669 Assessment of the Electrical, Mechanical, and Thermal Nociceptive Thresholds for Stimulation and Pain Measurements at the Bovine Hind Limb
Authors: Samaneh Yavari, Christiane Pferrer, Elisabeth Engelke, Alexander Starke, Juergen Rehage
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Background: Three nociceptive thresholds of thermal, electrical, and mechanical thresholds commonly use to evaluate the local anesthesia in many species, for instance, cow, horse, cat, dog, rabbit, and so on. Due to the lack of investigations to evaluate and/or validate such those nociceptive thresholds, our plan was the comparison of two-foot local anesthesia methods of Intravenous Regional Anesthesia (IVRA) and our modified four-point Nerve Block Anesthesia (NBA). Materials and Methods: Eight healthy nonpregnant nondairy Holstein Frisian cows in a cross-over study design were selected for this study. All cows divided into two different groups to receive two local anesthesia techniques of IVRA and our modified four-point NBA. Three thermal, electrical, and mechanical force and pinpricks were applied to evaluate the quality of local anesthesia methods before and after local anesthesia application. Results: The statistical evaluation demonstrated that our four-point NBA has a qualification to select as a standard foot local anesthesia. However, the recorded results of our study revealed no significant difference between two groups of local anesthesia techniques of IVRA and modified four-point NBA related to quality and duration of anesthesia stimulated by electrical, mechanical and thermal nociceptive stimuli. Conclusion and discussion: All three nociceptive threshold stimuli of electrical, mechanical and heat nociceptive thresholds can be applied to measure and evaluate the efficacy of foot local anesthesia of dairy cows. However, our study revealed no superiority of those three nociceptive methods to evaluate the duration and quality of bovine foot local anesthesia methods. Veterinarians to investigate the duration and quality of their selected anesthesia method can use any of those heat, mechanical, and electrical methods.Keywords: mechanical, thermal, electrical threshold, IVRA, NBA, hind limb, dairy cow
Procedia PDF Downloads 2494668 Performance Investigation of Unmanned Aerial Vehicles Attitude Control Based on Modified PI-D and Nonlinear Dynamic Inversion
Authors: Ebrahim H. Kapeel, Ahmed M. Kamel, Hossam Hendy, Yehia Z. Elhalwagy
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Interest in autopilot design has been raised intensely as a result of recent advancements in Unmanned Aerial vehicles (UAVs). Due to the enormous number of applications that UAVs can achieve, the number of applied control theories used for them has increased in recent years. These small fixed-wing UAVs are suffering high non-linearity, sensitivity to disturbances, and coupling effects between their channels. In this work, the nonlinear dynamic inversion (NDI) control law is designed for a nonlinear small fixed-wing UAV model. The NDI is preferable for varied operating conditions, there is no need for a scheduling controller. Moreover, it’s applicable for high angles of attack. For the designed flight controller validation, a nonlinear Modified PI-D controller is performed with our model. A comparative study between both controllers is achieved to evaluate the NDI performance. Simulation results and analysis are proposed to illustrate the effectiveness of the designed controller based on NDI.Keywords: attitude control, nonlinear PID, dynamic inversion
Procedia PDF Downloads 1154667 Superhydrophobic Behavior of SnO₂-TiO₂ Composite Thin Films
Authors: Debarun Dhar Purkayastha, Talinungsang
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SnO₂-TiO₂ nanocomposite thin films were prepared by the sol-gel method on borosilicate glass substrate. The films were annealed at a temperature of 300ᵒC, 400ᵒC, and 500ᵒC respectively for 2h in the air. The films obtained were further modified with stearic acid in order to decrease the surface energy. The X-ray diffraction patterns for the SnO₂-TiO₂ thin films after annealing at different temperatures can be indexed to the mixture of TiO₂ (rutile and anatase) and SnO₂ (tetragonal) phases. The average crystallite size calculated from Scherrer’s formula is found to be 6 nm. The SnO₂-TiO₂ thin films were hydrophilic which on modification with stearic acid exhibit superhydrophobic behavior. The increase in hydrophobicity of SnO₂ film with stearic acid modification is attributed to the change in surface energy of the film. The films exhibit superhydrophilic behavior under UV irradiation for 1h. Thus, it is observed that stearic acid modified surfaces are superhydrophobic but convert into superhydrophilic on being subjected to UV irradiation. SnO₂-TiO₂ thin films have potential for self-cleaning applications because of photoinduced hydrophilicity under UV irradiation.Keywords: nanocomposite, self-cleaning, superhydrophobic, surface energy
Procedia PDF Downloads 1824666 An Approach to Maximize the Influence Spread in the Social Networks
Authors: Gaye Ibrahima, Mendy Gervais, Seck Diaraf, Ouya Samuel
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In this paper, we consider the influence maximization in social networks. Here we give importance to initial diffuser called the seeds. The goal is to find efficiently a subset of k elements in the social network that will begin and maximize the information diffusion process. A new approach which treats the social network before to determine the seeds, is proposed. This treatment eliminates the information feedback toward a considered element as seed by extracting an acyclic spanning social network. At first, we propose two algorithm versions called SCG − algoritm (v1 and v2) (Spanning Connected Graphalgorithm). This algorithm takes as input data a connected social network directed or no. And finally, a generalization of the SCG − algoritm is proposed. It is called SG − algoritm (Spanning Graph-algorithm) and takes as input data any graph. These two algorithms are effective and have each one a polynomial complexity. To show the pertinence of our approach, two seeds set are determined and those given by our approach give a better results. The performances of this approach are very perceptible through the simulation carried out by the R software and the igraph package.Keywords: acyclic spanning graph, centrality measures, information feedback, influence maximization, social network
Procedia PDF Downloads 252