Search results for: back propagation algorithm
5356 Optimal Planning of Dispatchable Distributed Generators for Power Loss Reduction in Unbalanced Distribution Networks
Authors: Mahmoud M. Othman, Y. G. Hegazy, A. Y. Abdelaziz
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This paper proposes a novel heuristic algorithm that aims to determine the best size and location of distributed generators in unbalanced distribution networks. The proposed heuristic algorithm can deal with the planning cases where power loss is to be optimized without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power factor node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37 -node feeder. The results obtained show the effectiveness of the proposed algorithm.Keywords: distributed generation, heuristic approach, optimization, planning
Procedia PDF Downloads 5245355 The Effects of Functionality Level on Gait in Subjects with Low Back Pain
Authors: Vedat Kurt, Tansel Koyunoglu, Gamze Kurt, Ozgen Aras
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Low back pain is one of the most common health problem in public. Common symptoms that can be associated with low back pain include; pain, functional disability, gait disturbances. The aim of the study was to investigate the differences between disability scores and gait parameters in subjects with low back pain. Sixty participants are included in our study, (35 men, 25 women, mean age: 37.65±10.02 years). Demographic characteristics of participants were recorded. Pain (visual analog scale) and disability level (Oswestry Disability Index(ODI)) were evaluated. Gait parameters were measured with Zebris-FDM-2 platform. Independent samples t-test was used to analyse the differences between subjects with under 40 points (n=31, mean age:35.8±11.3) and above 40 points (n=29, mean age:39.6±8.1) of ODI scores. Significant level in statistical analysis was accepted as 0.05. There was no significant difference between the ODI scores and groups’ ages. Statistically significant differences were found in step width between subjects with under 40 points of ODI and above 40 points of ODI score(p < 0.05). But there were non-significant differences with other gait parameters (p > 0.05). The differences between gait parameters and pain scores were not statistically significant (p > 0.05). Researchers generally agree that individuals with LBP walk slower and take shorter steps and have asymmetric step lengths when compared with than their age-matched pain-free counterparts. Also perceived general disability may have moderate correlation with walking performance. In the current study, the patients classified as minimal/moderate and severe disability level by using ODI scores. As a result, a patient with LBP who have higher disability level tends to increase support surface. On the other hand, we did not find any relation between pain intensity and gait parameters. It may be caused by the classification system of pain scores. Additional research is needed to investigate the effects of functionality level and pain intensity on gait in subjects with low back pain under different classification types.Keywords: functionality, low back pain, gait, pain
Procedia PDF Downloads 2855354 Soliton Solutions of the Higher-Order Nonlinear Schrödinger Equation with Dispersion Effects
Authors: H. Triki, Y. Hamaizi, A. El-Akrmi
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We consider the higher order nonlinear Schrödinger equation model with fourth-order dispersion, cubic-quintic terms, and self-steepening. This equation governs the propagation of fem to second pulses in optical fibers. We present new bright and dark solitary wave type solutions for such a model under certain parametric conditions. This kind of solution may be useful to explain some physical phenomena related to wave propagation in a nonlinear optical fiber systems supporting high-order nonlinear and dispersive effects.Keywords: nonlinear Schrödinger equation, high-order effects, soliton solution
Procedia PDF Downloads 6355353 Prediction of Fatigue Crack Propagation in Bonded Joints Using Fracture Mechanics
Authors: Reza Hedayati, Meysam Jahanbakhshi
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Fracture Mechanics is used to predict debonding propagation in adhesive joint between aluminum and composite plates. Three types of loadings and two types of glass-epoxy composite sequences: [0/90]2s and [0/45/-45/90]s are considered for the composite plate and their results are compared. It was seen that generally the cases with stacking sequence of [0/45/-45/90]s have much shorter lives than cases with [0/90]2s. It was also seen that in cases with λ=0 the ends of the debonding front propagates forward more than its middle, while in cases with λ=0.5 or λ=1 it is vice versa. Moreover, regardless of value of λ, the difference between the debonding propagations of the ends and the middle of the debonding front is very close in cases λ=0.5 and λ=1. Another main conclusion was the non-dimensionalized debonding front profile is almost independent of sequence type or the applied load value.Keywords: fatigue, debonding, Paris law, APDL, adhesive
Procedia PDF Downloads 3635352 Design, Control and Implementation of 300Wp Single Phase Photovoltaic Micro Inverter for Village Nano Grid Application
Authors: Ramesh P., Aby Joseph
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Micro Inverters provide Module Embedded Solution for harvesting energy from small-scale solar photovoltaic (PV) panels. In addition to higher modularity & reliability (25 years of life), the MicroInverter has inherent advantages such as avoidance of long DC cables, eliminates module mismatch losses, minimizes partial shading effect, improves safety and flexibility in installations etc. Due to the above-stated benefits, the renewable energy technology with Solar Photovoltaic (PV) Micro Inverter becomes more widespread in Village Nano Grid application ensuring grid independence for rural communities and areas without access to electricity. While the primary objective of this paper is to discuss the problems related to rural electrification, this concept can also be extended to urban installation with grid connectivity. This work presents a comprehensive analysis of the power circuit design, control methodologies and prototyping of 300Wₚ Single Phase PV Micro Inverter. This paper investigates two different topologies for PV Micro Inverters, based on the first hand on Single Stage Flyback/ Forward PV Micro-Inverter configuration and the other hand on the Double stage configuration including DC-DC converter, H bridge DC-AC Inverter. This work covers Power Decoupling techniques to reduce the input filter capacitor size to buffer double line (100 Hz) ripple energy and eliminates the use of electrolytic capacitors. The propagation of the double line oscillation reflected back to PV module will affect the Maximum Power Point Tracking (MPPT) performance. Also, the grid current will be distorted. To mitigate this issue, an independent MPPT control algorithm is developed in this work to reject the propagation of this double line ripple oscillation to PV side to improve the MPPT performance and grid side to improve current quality. Here, the power hardware topology accepts wide input voltage variation and consists of suitably rated MOSFET switches, Galvanically Isolated gate drivers, high-frequency magnetics and Film capacitors with a long lifespan. The digital controller hardware platform inbuilt with the external peripheral interface is developed using floating point microcontroller TMS320F2806x from Texas Instruments. The firmware governing the operation of the PV Micro Inverter is written in C language and was developed using code composer studio Integrated Development Environment (IDE). In this work, the prototype hardware for the Single Phase Photovoltaic Micro Inverter with Double stage configuration was developed and the comparative analysis between the above mentioned configurations with experimental results will be presented.Keywords: double line oscillation, micro inverter, MPPT, nano grid, power decoupling
Procedia PDF Downloads 1335351 Control of Grid Connected PMSG-Based Wind Turbine System with Back-To-Back Converter Topology Using Resonant Controller
Authors: Fekkak Bouazza, Menaa Mohamed, Loukriz Abdelhamid, Krim Mohamed L.
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This paper presents modeling and control strategy for the grid connected wind turbine system based on Permanent Magnet Synchronous Generator (PMSG). The considered system is based on back-to-back converter topology. The Grid Side Converter (GSC) achieves the DC bus voltage control and unity power factor. The Machine Side Converter (MSC) assures the PMSG speed control. The PMSG is used as a variable speed generator and connected directly to the turbine without gearbox. The pitch angle control is not either considered in this study. Further, Optimal Tip Speed Ratio (OTSR) based MPPT control strategy is used to ensure the most energy efficiency whatever the wind speed variations. A filter (L) is put between the GSC and the grid to reduce current ripple and to improve the injected power quality. The proposed grid connected wind system is built under MATLAB/Simulink environment. The simulation results show the feasibility of the proposed topology and performance of its control strategies.Keywords: wind, grid, PMSG, MPPT, OTSR
Procedia PDF Downloads 3625350 Block Based Imperial Competitive Algorithm with Greedy Search for Traveling Salesman Problem
Authors: Meng-Hui Chen, Chiao-Wei Yu, Pei-Chann Chang
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Imperial competitive algorithm (ICA) simulates a multi-agent algorithm. Each agent is like a kingdom has its country, and the strongest country in each agent is called imperialist, others are colony. Countries are competitive with imperialist which in the same kingdom by evolving. So this country will move in the search space to find better solutions with higher fitness to be a new imperialist. The main idea in this paper is using the peculiarity of ICA to explore the search space to solve the kinds of combinational problems. Otherwise, we also study to use the greed search to increase the local search ability. To verify the proposed algorithm in this paper, the experimental results of traveling salesman problem (TSP) is according to the traveling salesman problem library (TSPLIB). The results show that the proposed algorithm has higher performance than the other known methods.Keywords: traveling salesman problem, artificial chromosomes, greedy search, imperial competitive algorithm
Procedia PDF Downloads 4585349 Genetic Algorithm for Bi-Objective Hub Covering Problem
Authors: Abbas Mirakhorli
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A hub covering problem is a type of hub location problem that tries to maximize the coverage area with the least amount of installed hubs. There have not been many studies in the literature about multi-objective hubs covering location problems. Thus, in this paper, a bi-objective model for the hub covering problem is presented. The two objectives that are considered in this paper are the minimization of total transportation costs and the maximization of coverage of origin-destination nodes. A genetic algorithm is presented to solve the model when the number of nodes is increased. The genetic algorithm is capable of solving the model when the number of nodes increases by more than 20. Moreover, the genetic algorithm solves the model in less amount of time.Keywords: facility location, hub covering, multi-objective optimization, genetic algorithm
Procedia PDF Downloads 605348 Channel Sounding and PAPR Reduction in OFDM for WiMAX Using Software Defined Radio
Authors: B. Siva Kumar Reddy, B. Lakshmi
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WiMAX is a high speed broadband wireless access technology that adopted OFDM/OFDMA techniques to supply higher data rates with high spectral efficiency. However, OFDM suffers in view of high Peak to Average Power Ratio (PAPR) and high affect to synchronization errors. In this paper, the high PAPR problem is solved by using phase modulation to get Constant Envelop Orthogonal Frequency Division Multiplexing (CE-OFDM). The synchronization failures are brought down by employing a frequency lock loop, Poly phase clock synchronizer, Costas loop and blind equalizers such as Constant Modulus Algorithm (CMA) equalizer and Sign Kurtosis Maximization Adaptive Algorithm (SKMAA) equalizers. The WiMAX physical layer is executed on Software Defined Radio (SDR) prototype by utilizing USRP N210 as hardware and GNU Radio as software plat-forms. A SNR estimation is performed on the signal received through USRP N210. To empathize wireless propagation in specific environments, a sliding correlator wireless channel sounding system is designed by using SDR testbed.Keywords: BER, CMA equalizer, Kurtosis equalizer, GNU Radio, OFDM/OFDMA, USRP N210
Procedia PDF Downloads 3495347 Scheduling in Cloud Networks Using Chakoos Algorithm
Authors: Masoumeh Ali Pouri, Hamid Haj Seyyed Javadi
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Nowadays, cloud processing is one of the important issues in information technology. Since scheduling of tasks graph is an NP-hard problem, considering approaches based on undeterminisitic methods such as evolutionary processing, mostly genetic and cuckoo algorithms, will be effective. Therefore, an efficient algorithm has been proposed for scheduling of tasks graph to obtain an appropriate scheduling with minimum time. In this algorithm, the new approach is based on making the length of the critical path shorter and reducing the cost of communication. Finally, the results obtained from the implementation of the presented method show that this algorithm acts the same as other algorithms when it faces graphs without communication cost. It performs quicker and better than some algorithms like DSC and MCP algorithms when it faces the graphs involving communication cost.Keywords: cloud computing, scheduling, tasks graph, chakoos algorithm
Procedia PDF Downloads 645346 Single Item Presenteeism Question Reliability and Validity of Persian Version in Low Back Pain Patients
Authors: Mohammadreza Khanmohammadi, Noureddin Nakhostin Ansari, Soofia Naghdi
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Purpose: Our study aimed to validate single item presenteeism question (SIPQ) into the Persian language for patients with low back pain. Background information: low back pain is a common health problem, and it is one of the most prevalent disorder in working people. There are the different subjective way to evaluate the effect of back pain on work productivity that one of them is by implementing single item presenteeism question. This question has not been validated into the Persian language. Method: Patients were asked to answer SIPQ and pain from 0 to 10 according to numerical rating scale (NRS). The functional rating index was administrated to evaluate construct validity. For test-retest reliability, almost 50 patients re-completed the Persian SIPQ. The construct validity of SIPQ was assessed by analyzing Spearman rank correlation between this question and the Persian version of Functional rating index questionnaire. To analyze test-retest reliability, we assessed intraclass correlation coefficient (agreement) (ICC agreement) (two-way random effects model, single measure). Results: The SIPQ score of two groups of patients (84 males, 16 females, mean age ±SD: 33.85±11.16 years, range: 19-67 years) and healthy subjects (48 male, 2 female ones, mean age ±SD: 24.24 ±8.07 years) was statistically significant. (Mann-Whitney U =198.00, P<.001). The Spearman correlation of data showed that there is a significant correlation between Persian SIPQ score and Persian FRI band (r= .559, P<.001). The ICC was .62. So, the analysis indicated good, test-retest reliability. Conclusion: This study showed that Persian version of SIPQ is reliable and valid when applied to back pain patients.Keywords: cross cultural adaptation, economic burden, low back pain, Persian language, translation
Procedia PDF Downloads 4115345 Effect of Therapeutic Exercises with or without Positional Release Technique in Treatment of Chronic Mechanical Low Back Pain Patients a Randomized Controlled Trial
Authors: Ghada M. R. Koura, Mohamed N. Mohamed, Ahmed M. F. El Shiwi
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Chronic mechanical Low back dysfunction (CMLBD) is the most common problem of the working-age population in modern industrial sociaty; it causes a substantial economic burden due to the wide use of medical services and absence from work. Aim of work: the aim of this study was to investigate the effect of positional release technique on patients with chronic mechanical low back pain. Materials and Methods: Thirty two patients from both sexes were diagnosed with CMLBP, aged 20 to 45 years and were divided randomly into two equal groups; sixteen patients each; group A (control group) received therapeutic exercises that include (Stretch and Strength exercises for back and abdominal muscles). Group B (experimental group) received therapeutic exercises with positional release technique; treatment was applied 3 days/week for 4 weeks. Pain was measured by Visual Analogue Scale, Lumbar range of motion was measured by Inclinometer and Functional disability was measured by Oswestry disability scale. Measurements were taken at two intervals pre-treatment and post-treatment. Results: Data obtained was analyzed via paired and unpaired t-Test. There were statistical differences between the 2 groups, where the experimental group showed greater improvement than control group. Conclusion: Positional release technique is considered as an effective treatment for reducing pain, functional disability and increasing lumbar range of motion in individuals with chronic mechanical low back pain.Keywords: chronic mechanical low back pain, traditional physical therapy program, positional release technique, randomized controlled trial
Procedia PDF Downloads 5965344 Gene Prediction in DNA Sequences Using an Ensemble Algorithm Based on Goertzel Algorithm and Anti-Notch Filter
Authors: Hamidreza Saberkari, Mousa Shamsi, Hossein Ahmadi, Saeed Vaali, , MohammadHossein Sedaaghi
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In the recent years, using signal processing tools for accurate identification of the protein coding regions has become a challenge in bioinformatics. Most of the genomic signal processing methods is based on the period-3 characteristics of the nucleoids in DNA strands and consequently, spectral analysis is applied to the numerical sequences of DNA to find the location of periodical components. In this paper, a novel ensemble algorithm for gene selection in DNA sequences has been presented which is based on the combination of Goertzel algorithm and anti-notch filter (ANF). The proposed algorithm has many advantages when compared to other conventional methods. Firstly, it leads to identify the coding protein regions more accurate due to using the Goertzel algorithm which is tuned at the desired frequency. Secondly, faster detection time is achieved. The proposed algorithm is applied on several genes, including genes available in databases BG570 and HMR195 and their results are compared to other methods based on the nucleotide level evaluation criteria. Implementation results show the excellent performance of the proposed algorithm in identifying protein coding regions, specifically in identification of small-scale gene areas.Keywords: protein coding regions, period-3, anti-notch filter, Goertzel algorithm
Procedia PDF Downloads 3875343 ICanny: CNN Modulation Recognition Algorithm
Authors: Jingpeng Gao, Xinrui Mao, Zhibin Deng
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Aiming at the low recognition rate on the composite signal modulation in low signal to noise ratio (SNR), this paper proposes a modulation recognition algorithm based on ICanny-CNN. Firstly, the radar signal is transformed into the time-frequency image by Choi-Williams Distribution (CWD). Secondly, we propose an image processing algorithm using the Guided Filter and the threshold selection method, which is combined with the hole filling and the mask operation. Finally, the shallow convolutional neural network (CNN) is combined with the idea of the depth-wise convolution (Dw Conv) and the point-wise convolution (Pw Conv). The proposed CNN is designed to complete image classification and realize modulation recognition of radar signal. The simulation results show that the proposed algorithm can reach 90.83% at 0dB and 71.52% at -8dB. Therefore, the proposed algorithm has a good classification and anti-noise performance in radar signal modulation recognition and other fields.Keywords: modulation recognition, image processing, composite signal, improved Canny algorithm
Procedia PDF Downloads 1915342 Set-point Performance Evaluation of Robust Back-Stepping Control Design for a Nonlinear Electro-Hydraulic Servo System
Authors: Maria Ahmadnezhad, Seyedgharani Ghoreishi
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Electrohydraulic servo system have been used in industry in a wide number of applications. Its dynamics are highly nonlinear and also have large extent of model uncertainties and external disturbances. In this thesis, a robust back-stepping control (RBSC) scheme is proposed to overcome the problem of disturbances and system uncertainties effectively and to improve the set-point performance of EHS systems. In order to implement the proposed control scheme, the system uncertainties in EHS systems are considered as total leakage coefficient and effective oil volume. In addition, in order to obtain the virtual controls for stabilizing system, the update rule for the system uncertainty term is induced by the Lyapunov control function (LCF). To verify the performance and robustness of the proposed control system, computer simulation of the proposed control system using Matlab/Simulink Software is executed. From the computer simulation, it was found that the RBSC system produces the desired set-point performance and has robustness to the disturbances and system uncertainties of EHS systems.Keywords: electro hydraulic servo system, back-stepping control, robust back-stepping control, Lyapunov redesign
Procedia PDF Downloads 10045341 Recognition of Noisy Words Using the Time Delay Neural Networks Approach
Authors: Khenfer-Koummich Fatima, Mesbahi Larbi, Hendel Fatiha
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This paper presents a recognition system for isolated words like robot commands. It’s carried out by Time Delay Neural Networks; TDNN. To teleoperate a robot for specific tasks as turn, close, etc… In industrial environment and taking into account the noise coming from the machine. The choice of TDNN is based on its generalization in terms of accuracy, in more it acts as a filter that allows the passage of certain desirable frequency characteristics of speech; the goal is to determine the parameters of this filter for making an adaptable system to the variability of speech signal and to noise especially, for this the back propagation technique was used in learning phase. The approach was applied on commands pronounced in two languages separately: The French and Arabic. The results for two test bases of 300 spoken words for each one are 87%, 97.6% in neutral environment and 77.67%, 92.67% when the white Gaussian noisy was added with a SNR of 35 dB.Keywords: TDNN, neural networks, noise, speech recognition
Procedia PDF Downloads 2895340 Anisotropic Approach for Discontinuity Preserving in Optical Flow Estimation
Authors: Pushpendra Kumar, Sanjeev Kumar, R. Balasubramanian
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Estimation of optical flow from a sequence of images using variational methods is one of the most successful approach. Discontinuity between different motions is one of the challenging problem in flow estimation. In this paper, we design a new anisotropic diffusion operator, which is able to provide smooth flow over a region and efficiently preserve discontinuity in optical flow. This operator is designed on the basis of intensity differences of the pixels and isotropic operator using exponential function. The combination of these are used to control the propagation of flow. Experimental results on the different datasets verify the robustness and accuracy of the algorithm and also validate the effect of anisotropic operator in the discontinuity preserving.Keywords: optical flow, variational methods, computer vision, anisotropic operator
Procedia PDF Downloads 8735339 Robotic Arm Control with Neural Networks Using Genetic Algorithm Optimization Approach
Authors: Arbnor Pajaziti, Hasan Cana
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In this paper, the structural genetic algorithm is used to optimize the neural network to control the joint movements of robotic arm. The robotic arm has also been modeled in 3D and simulated in real-time in MATLAB. It is found that Neural Networks provide a simple and effective way to control the robot tasks. Computer simulation examples are given to illustrate the significance of this method. By combining Genetic Algorithm optimization method and Neural Networks for the given robotic arm with 5 D.O.F. the obtained the results shown that the base joint movements overshooting time without controller was about 0.5 seconds, while with Neural Network controller (optimized with Genetic Algorithm) was about 0.2 seconds, and the population size of 150 gave best results.Keywords: robotic arm, neural network, genetic algorithm, optimization
Procedia PDF Downloads 5235338 An Integrated Label Propagation Network for Structural Condition Assessment
Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong
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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation
Procedia PDF Downloads 975337 A Hybrid Method for Determination of Effective Poles Using Clustering Dominant Pole Algorithm
Authors: Anuj Abraham, N. Pappa, Daniel Honc, Rahul Sharma
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In this paper, an analysis of some model order reduction techniques is presented. A new hybrid algorithm for model order reduction of linear time invariant systems is compared with the conventional techniques namely Balanced Truncation, Hankel Norm reduction and Dominant Pole Algorithm (DPA). The proposed hybrid algorithm is known as Clustering Dominant Pole Algorithm (CDPA) is able to compute the full set of dominant poles and its cluster center efficiently. The dominant poles of a transfer function are specific eigenvalues of the state space matrix of the corresponding dynamical system. The effectiveness of this novel technique is shown through the simulation results.Keywords: balanced truncation, clustering, dominant pole, Hankel norm, model reduction
Procedia PDF Downloads 5995336 Influence Maximization in Dynamic Social Networks and Graphs
Authors: Gkolfo I. Smani, Vasileios Megalooikonomou
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Social influence and influence diffusion have been studied in social networks. However, most existing tasks on this subject focus on static networks. In this paper, the problem of maximizing influence diffusion in dynamic social networks, i.e., the case of networks that change over time, is studied. The DM algorithm is an extension of the MATI algorithm and solves the influence maximization (IM) problem in dynamic networks and is proposed under the linear threshold (LT) and independent cascade (IC) models. Experimental results show that our proposed algorithm achieves a diffusion performance better by 1.5 times than several state-of-the-art algorithms and comparable results in diffusion scale with the Greedy algorithm. Also, the proposed algorithm is 2.4 times faster than previous methods.Keywords: influence maximization, dynamic social networks, diffusion, social influence, graphs
Procedia PDF Downloads 2395335 Tracking Performance Evaluation of Robust Back-Stepping Control Design for a Nonlinear Electro-Hydraulic Servo System
Authors: Maria Ahmadnezhad, Mohammad Reza Soltanpour
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Electrohydraulic servo systems have been used in industry in a wide number of applications. Its dynamics are highly nonlinear and also have large extent of model uncertainties and external disturbances. In this thesis, a robust back-stepping control (RBSC) scheme is proposed to overcome the problem of disturbances and system uncertainties effectively and to improve the tracking performance of EHS systems. In order to implement the proposed control scheme, the system uncertainties in EHS systems are considered as total leakage coefficient and effective oil volume. In addition, in order to obtain the virtual controls for stabilizing system, the update rule for the system uncertainty term is induced by the Lyapunov control function (LCF). To verify the performance and robustness of the proposed control system, computer simulation of the proposed control system using Matlab/Simulink Software is executed. From the computer simulation, it was found that the RBSC system produces the desired tracking performance and has robustness to the disturbances and system uncertainties of EHS systems.Keywords: electro hydraulic servo system, back-stepping control, robust back-stepping control, Lyapunov redesign
Procedia PDF Downloads 2965334 Pavement Management for a Metropolitan Area: A Case Study of Montreal
Authors: Luis Amador Jimenez, Md. Shohel Amin
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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization
Procedia PDF Downloads 4605333 Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries
Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi
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Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery
Procedia PDF Downloads 5865332 Optimizing the Probabilistic Neural Network Training Algorithm for Multi-Class Identification
Authors: Abdelhadi Lotfi, Abdelkader Benyettou
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In this work, a training algorithm for probabilistic neural networks (PNN) is presented. The algorithm addresses one of the major drawbacks of PNN, which is the size of the hidden layer in the network. By using a cross-validation training algorithm, the number of hidden neurons is shrunk to a smaller number consisting of the most representative samples of the training set. This is done without affecting the overall architecture of the network. Performance of the network is compared against performance of standard PNN for different databases from the UCI database repository. Results show an important gain in network size and performance.Keywords: classification, probabilistic neural networks, network optimization, pattern recognition
Procedia PDF Downloads 2625331 Hexagonal Honeycomb Sandwich Plate Optimization Using Gravitational Search Algorithm
Authors: A. Boudjemai, A. Zafrane, R. Hocine
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Honeycomb sandwich panels are increasingly used in the construction of space vehicles because of their outstanding strength, stiffness and light weight properties. However, the use of honeycomb sandwich plates comes with difficulties in the design process as a result of the large number of design variables involved, including composite material design, shape and geometry. Hence, this work deals with the presentation of an optimal design of hexagonal honeycomb sandwich structures subjected to space environment. The optimization process is performed using a set of algorithms including the gravitational search algorithm (GSA). Numerical results are obtained and presented for a set of algorithms. The results obtained by the GSA algorithm are much better compared to other algorithms used in this study.Keywords: optimization, gravitational search algorithm, genetic algorithm, honeycomb plate
Procedia PDF Downloads 3775330 Disruption Coordination of Supply Chain with Loss-Averse Retailer Under Buy-Back Contract
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This paper aims to investigate a two stage supply chain of one leading supplier and one following retailer that experiences two factors perturbation out of supplier's production cost, retailer's marginal cost and retail price in stochastic demand environment. Granted that risk neutral condition has long been discussed, little attention has been given to disruptions under the premise of risk neutral supplier and risk aversion retailer. We establish the optimal order quantity and revealed the profit distribution coefficient in risk-neutral static model, make adjustment under disruption scenario, and then select utility function method for risk aversion model. Using buy-back contract policy, the improvement of parameters can achieve channel coordination where Pareto optimal is realized.Keywords: supply chain coordination, disruption management, buy-back contract, lose aversion
Procedia PDF Downloads 3275329 Off-Body Sub-GHz Wireless Channel Characterization for Dairy Cows in Barns
Authors: Said Benaissa, David Plets, Emmeric Tanghe, Jens Trogh, Luc Martens, Leen Vandaele, Annelies Van Nuffel, Frank A. M. Tuyttens, Bart Sonck, Wout Joseph
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The herd monitoring and managing - in particular the detection of ‘attention animals’ that require care, treatment or assistance is crucial for effective reproduction status, health, and overall well-being of dairy cows. In large sized farms, traditional methods based on direct observation or analysis of video recordings become labour-intensive and time-consuming. Thus, automatic monitoring systems using sensors have become increasingly important to continuously and accurately track the health status of dairy cows. Wireless sensor networks (WSNs) and internet-of-things (IoT) can be effectively used in health tracking of dairy cows to facilitate herd management and enhance the cow welfare. Since on-cow measuring devices are energy-constrained, a proper characterization of the off-body wireless channel between the on-cow sensor nodes and the back-end base station is required for a power-optimized deployment of these networks in barns. The aim of this study was to characterize the off-body wireless channel in indoor (barns) environment at 868 MHz using LoRa nodes. LoRa is an emerging wireless technology mainly targeted at WSNs and IoT networks. Both large scale fading (i.e., path loss) and temporal fading were investigated. The obtained path loss values as a function of the transmitter-receiver separation were well fitted by a lognormal path loss model. The path loss showed an additional increase of 4 dB when the wireless node was actually worn by the cow. The temporal fading due to movement of other cows was well described by Rician distributions with a K-factor of 8.5 dB. Based on this characterization, network planning and energy consumption optimization of the on-body wireless nodes could be performed, which enables the deployment of reliable dairy cow monitoring systems.Keywords: channel, channel modelling, cow monitoring, dairy cows, health monitoring, IoT, LoRa, off-body propagation, PLF, propagation
Procedia PDF Downloads 3185328 Least Support Orthogonal Matching Pursuit (LS-OMP) Recovery Method for Invisible Watermarking Image
Authors: Israa Sh. Tawfic, Sema Koc Kayhan
Abstract:
In this paper, first, we propose least support orthogonal matching pursuit (LS-OMP) algorithm to improve the performance, of the OMP (orthogonal matching pursuit) algorithm. LS-OMP algorithm adaptively chooses optimum L (least part of support), at each iteration. This modification helps to reduce the computational complexity significantly and performs better than OMP algorithm. Second, we give the procedure for the invisible image watermarking in the presence of compressive sampling. The image reconstruction based on a set of watermarked measurements is performed using LS-OMP.Keywords: compressed sensing, orthogonal matching pursuit, restricted isometry property, signal reconstruction, least support orthogonal matching pursuit, watermark
Procedia PDF Downloads 3385327 Predictive Analysis of Personnel Relationship in Graph Database
Authors: Kay Thi Yar, Khin Mar Lar Tun
Abstract:
Nowadays, social networks are so popular and widely used in all over the world. In addition, searching personal information of each person and searching connection between them (peoples’ relation in real world) becomes interesting issue in our society. In this paper, we propose a framework with three portions for exploring peoples’ relations from their connected information. The first portion focuses on the Graph database structure to store the connected data of peoples’ information. The second one proposes the graph database searching algorithm, the Modified-SoS-ACO (Sense of Smell-Ant Colony Optimization). The last portion proposes the Deductive Reasoning Algorithm to define two persons’ relationship. This study reveals the proper storage structure for connected information, graph searching algorithm and deductive reasoning algorithm to predict and analyze the personnel relationship from peoples’ relation in their connected information.Keywords: personnel information, graph storage structure, graph searching algorithm, deductive reasoning algorithm
Procedia PDF Downloads 450