Search results for: current vector

Authors: A. El Kachani, E. Chakir, A. Ait Laachir, A. Niaaniaa, J. Zerouaoui

Abstract:

This document presents an adaptive controller based on recursive parametric identification applied to a wind turbine based on the doubly-fed induction machine (DFIG), to compensate the faults and guarantee efficient of the DFIG. The proposed adaptive controller is based on the recursive least square algorithm which considers that the best estimator for the vector parameter is the vector x minimizing a quadratic criterion. Furthermore, this method can improve the rapidity and precision of the controller based on a model. The proposed controller is validated via simulation on a 5.5 kW DFIG-based wind turbine. The results obtained seem to be good. In addition, they show the advantages of an adaptive controller based on recursive least square algorithm.

Keywords: adaptive controller, recursive least squares algorithm, wind turbine, doubly fed induction generator

Procedia PDF Downloads 257

Authors: Mohd Shazad, K. K. Gupta

Abstract:

Vector borne diseases are a serious global concern. Aedes aegypti, the primary vector for viruses that cause dengue fever, dengue haemorrhagic fever, chikungunya and yellow fever is widespread over large areas of the tropics and subtropics. In last decade, diseases transmitted by Aedes aegypti are of serious concern. In past decade, number of cases of dengue fever, dengue hemorrhagic fever, and chikungunya has increased multifold. Present research work focused on impact of ethanol extract of Ocimum sanctum on dengue vector Aedes aegypti. 0-24 hr. old fourth instar larvae of lab-bred population of Aedes aegypti were exposed to ethanol leaf extract of Ocimum with concentrations ranging from 50 ppm to 400 ppm. Survival and development and the treated larvae and reproductive behaviour of the adults emerged from the treated larvae was evaluated. Our results indicated larvicidal potential of the leaf ethanol extract. The influence of the extract was dose dependent. 77.2% mortality was observed in the larvae exposed to 400 ppm for 24 hr. Treatment at lower concentrations revealed delayed toxicity. The larvae survived after treatment showed severe developmental anomalies. Consequently, there was the significant increase in duration of fourth instar larva. The L4 treated with 400-ppm extract moulted after 4.6 days; this was in sharp contrast to control where the larval period of the fourth instar lasts three days. The treated fourth instar larvae in many cases transformed into larva-pupa intermediates with the combination of larva, pupa characters. The larva-pupa intermediates had reduced life span and failed to moult successfully. The adults emerged from the larvae treated with lower doses had reduced reproductive potential. The females exhibited longer preoviposition period, reduced oviposition rate, abnormal oviposition behaviour and decreased fertility. Our studies indicated the possibility of the presence of JH mimic or JH analogue in the leaf ethanol extract of Ocimum. The present research work explored the potentials of Ocimum sanctum, also known as the queen of herbs, in integrated vector management programme of Aedes aegypti, which is a serious threat to human health.

Keywords: Aedes aegypti, development, mortality, Ocimum sanctum reproduction

Procedia PDF Downloads 212

Authors: Shivani Singh, Shantanu Nakhare, Kalyani Nair, Rohan Shetty

Abstract:

As social networking is growing at a rapid pace today it is vital that we work on improving its management. Research has shown that the content present in online social networks may have significant influence on impressionable minds. If such platforms are misused, it will lead to negative consequences. Detecting insults or inappropriate messages continues to be one of the most challenging aspects of Online Social Networks (OSNs) today. We address this problem through a Machine Learning Based Soft Text Classifier approach using Support Vector Machine algorithm. The proposed system acts as a screening mechanism the alerts the user about such messages. The messages are classified according to their subject matter and each comment is labeled for the presence of profanity and insults.

Keywords: machine learning, online social networks, soft text classifier, support vector machine

Procedia PDF Downloads 474

Authors: Temitope L. A. Leshoro

Abstract:

This study explored several variables that enhance economic growth in South Africa, based on different growth theories while using the vector error correction model (VECM) technique. The impacts and contributions of each of these variables on GDP in South Africa were investigated. The motivation for this study was as a result of the weak economic growth that the country has been experiencing lately, as well as the continuous increase in unemployment rate and deteriorating health care system. Annual data spanning over the period 1974 to 2013 was employed. The results showed that the major determinants of GDP are trade openness, government spending, and health indicator; as these variables are not only economically significant but also statistically significant in explaining the changes in GDP in South Africa. Policy recommendations for economic growth enhancement are suggested based on the findings of this study.

Keywords: economic growth, GDP, investment, health indicator, VECM

Procedia PDF Downloads 250

Authors: Jamilatuzzahro, Rezzy Eko Caraka

Abstract:

The yield curve is the plot of the yield to maturity of zero-coupon bonds against maturity. In practice, the yield curve is not observed but must be extracted from observed bond prices for a set of (usually) incomplete maturities. There exist many methodologies and theory to analyze of yield curve. We use two methods (the Nelson-Siegel Method, the Svensson Method, and the SVR method) in order to construct and compare our zero-coupon yield curves. The objectives of this research were: (i) to study the adequacy of NSS model and SVR to Indonesian government bonds data, (ii) to choose the best optimization or estimation method for NSS model and SVR. To obtain that objective, this research was done by the following steps: data preparation, cleaning or filtering data, modeling, and model evaluation.

Keywords: support vector regression, Nelson-Siegel-Svensson, yield curve, Indonesian government

Procedia PDF Downloads 215

Authors: R. K. Chaurasiya, N. D. Londhe, S. Ghosh

Abstract:

The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. In this paper, we propose an automatic and efficient EEG signal classification approach. The proposed approach is used to classify the EEG signal into two classes: epileptic seizure or not. In the proposed approach, we start with extracting the features by applying Discrete Wavelet Transform (DWT) in order to decompose the EEG signals into sub-bands. These features, extracted from details and approximation coefficients of DWT sub-bands, are used as input to Principal Component Analysis (PCA). The classification is based on reducing the feature dimension using PCA and deriving the support-vectors using Support Vector Machine (SVM). The experimental are performed on real and standard dataset. A very high level of classification accuracy is obtained in the result of classification.

Keywords: discrete wavelet transform, electroencephalogram, pattern recognition, principal component analysis, support vector machine

Procedia PDF Downloads 604

Authors: Kbab H, Hamitouche T

Abstract:

In recent years, significant progress has been accomplished in the field of aerospace propulsion and propulsion systems. These developments are associated with efforts to enhance the accuracy of the analysis of aerothermodynamic phenomena in the engine. This applies in particular to the flow in the nozzles used. One of the most remarkable processes in this field is thrust vectoring by means of devices able to orientate the thrust vector and control the deflection of the exit jet in the engine nozzle. In the study proposed, we are interested in the fluid thrust vectoring using a second injection in the nozzle divergence. This fluid injection causes complex phenomena, such as boundary layer separation, which generates a shock wave in the primary jet upstream of the fluid interacting zone (primary jet - secondary jet). This will cause the deviation of the main flow, and therefore of the thrust vector with reference to the axis nozzle. In the modeling of the fluidic thrust vector, various parameters can be used. The Mach number of the primary jet and the injected fluid, the total pressures ratio, the injection rate, the thickness of the upstream boundary layer, the injector position in the divergent part, and the nozzle geometry are decisive factors in this type of phenomenon. The complexity of the latter challenges researchers to understand the physical phenomena of the turbulent boundary layer encountered in supersonic nozzles, as well as the calculation of its thickness and the friction forces induced on the walls. The present study aims to numerically simulate the thrust vectoring by secondary injection using the ANSYS-FLUENT, then to analyze and validate the results and the performances obtained (angle of deflection, efficiency...), which will then be compared with those obtained by other authors.

Keywords: CD Nozzle, TVC, SVC, NPR, CFD, NPR, SPR

Procedia PDF Downloads 112

Authors: Fatima Zohra Mahi, Luca Varani

Abstract:

We present an analytical model for the calculation of the sensitivity, the spectral current noise and the detectivity for an optically illuminated In0.53Ga0.47As n+nn+ diode. The photocurrent due to the excess carrier is obtained by solving the continuity equation. Moreover, the current noise level is evaluated at room temperature and under a constant voltage applied between the diode terminals. The analytical calculation of the current noise in the n+nn+ structure is developed. The responsivity and the detectivity are discussed as functions of the doping concentrations and the emitter layer thickness in one-dimensional homogeneous n+nn+ structure.

Keywords: detectivity, photodetectors, continuity equation, current noise

Procedia PDF Downloads 610

Authors: Mohammad Salah Abdullatif, Salam Hajjar, Paul Khanna

Abstract:

The development of instrument grade mmWave transceivers comes with many challenges. A general rule of thumb is that the performance of the instrument must be higher than the performance of the unit under test in terms of accuracy and stability. The calibration and characterizing of mmWave transceivers are important pillars for testing commercial products. Using a Vector Network Analyzer (VNA) with a mixer option has proven a high performance as an approach to calibrate mmWave transceivers. However, this approach comes with a high cost. In this work, a reduced-cost method to calibrate mmWave transceivers is proposed. A comparison between the proposed method and the VNA technology is provided. A demonstration of significant challenges is discussed, and an approach to meet the requirements is proposed.

Keywords: mmWave transceiver, scalar characterization, coupler connection, magic tee connection, calibration, VNA, vector network analyzer

Procedia PDF Downloads 81

Authors: Ju-Hong Lee, Ching-Wei Liao

Abstract:

Owing to close antenna spacing between antenna sensors within a compact space, a part of data in one antenna sensor would outflow to other antenna sensors when the antenna sensors in an antenna array operate simultaneously. This phenomenon is called mutual coupling effect (MCE). It has been shown that the performance of antenna array systems can be degraded when the antenna sensors are in close proximity. Especially, in a systems equipped with massive antenna sensors, the degradation of beamforming performance due to the MCE is significantly inevitable. Moreover, it has been shown that even a small angle error between the true direction angle of the desired signal and the steering angle deteriorates the effectiveness of an array beamforming system. However, the true direction vector of the desired signal may not be exactly known in some applications, e.g., the application in land mobile-cellular wireless systems. Therefore, it is worth developing robust techniques to deal with the problem due to the MCE and steering angle error for array beamforming systems. In this paper, we present an efficient technique for performing adaptive beamforming with robust capabilities against the MCE and the steering angle error. Only the data vector received by an antenna array is required by the proposed technique. By using the received array data vector, a correlation matrix is constructed to replace the original correlation matrix associated with the received array data vector. Then, the mutual coupling matrix due to the MCE on the antenna array is estimated through a recursive algorithm. An appropriate estimate of the direction angle of the desired signal can also be obtained during the recursive process. Based on the estimated mutual coupling matrix, the estimated direction angle, and the reconstructed correlation matrix, the proposed technique can effectively cure the performance degradation due to steering angle error and MCE. The novelty of the proposed technique is that the implementation procedure is very simple and the resulting adaptive beamforming performance is satisfactory. Simulation results show that the proposed technique provides much better beamforming performance without requiring complicated complexity as compared with the existing robust techniques.

Keywords: adaptive beamforming, mutual coupling effect, recursive algorithm, steering angle error

Procedia PDF Downloads 294

Authors: Yuan Huang, Xiangping Chen, Xiaonan Luo

Abstract:

Current software are continuously updating. The change between two versions usually involves multiple program entities (e.g., packages, classes, methods, attributes) with multiple purposes (e.g., changed requirements, bug fixing). It is hard for developers to understand which changes are made for the same purpose. Whether two changes are related is not decided by the relationship between this two entities in the program. In this paper, we summarized 4 coupling rules(16 instances) and 4 state-combination types at the class, method and attribute levels for software change. Related Change Vector (RCV) are defined based on coupling rules and state-combination types, and applied to classify related software changes by using Probabilistic Neural Network during a software updating.

Keywords: PNN, related change, state-combination, logical coupling, software entity

Procedia PDF Downloads 410

Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

Abstract:

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 classifying the RBCs 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-alaysia, 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 respectively.

Keywords: K-nearest neighbors algorithm, radial basis function neural network, red blood cells, support vector machine

Procedia PDF Downloads 373

Authors: Nicholas D. Assimakis

Abstract:

In linear estimation, the traditional Kalman filter uses the Kalman filter gain in order to produce estimation and prediction of the n-dimensional state vector using the m-dimensional measurement vector. The computation of the Kalman filter gain requires the inversion of an m x m matrix in every iteration. In this paper, a variation of the Kalman filter eliminating the Kalman filter gain is proposed. In the time varying case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix and the inversion of an m x m matrix in every iteration. In the time invariant case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix in every iteration. The proposed Kalman filter gain elimination algorithm may be faster than the conventional Kalman filter, depending on the model dimensions.

Keywords: discrete time, estimation, Kalman filter, Kalman filter gain

Procedia PDF Downloads 160

Authors: S. Summart, C. Saetiaw, T. Thosdeekoraphat, C. Thongsopa

Abstract:

This article presents new current-mode oscillator circuits using CDTAs which is designed from block diagram. The proposed circuits consist of two CDTAs and two grounded capacitors. The condition of oscillation and the frequency of oscillation can be adjusted by electronic method. The circuits have high output impedance and use only grounded capacitors without any external resistor which is very appropriate to future development into an integrated circuit. The results of PSPICE simulation program are corresponding to the theoretical analysis.

Keywords: current-mode, quadrature oscillator, block diagram, CDTA

Procedia PDF Downloads 424

Authors: A. Nachour, L. Ouzizi, Y. Aoura

Abstract:

Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge.

Keywords: edge detection, medical MRImages, multi-agent systems, vector field convolution

Procedia PDF Downloads 360

Authors: Hassan H. Abuelhassan, M. Ali Badawi, Abdelrahman A. Elbadawi, Adam A. Elbashir

Abstract:

In this paper, the effect of the injected current and temperature into the output power of the laser diode module operating at 808nm were applied, studied and discussed. Low power diode laser was employed as a source. The experimental results were demonstrated and then the output power of laser diode module operating at 808nm was clearly changed by the thermal temperature and injected current. The output power increases by the increasing the injected current and temperature. We also showed that the increasing of the injected current results rising in heat, which also, results into decreasing of the laser diode output power during the highest temperature as well. The best ranges of characteristics made by diode module operating at 808nm were carefully handled and determined.

Keywords: laser diode, light amplification, injected current, output power

Procedia PDF Downloads 360

Authors: S. Meguenni, A. Djahbar, K. Tounsi

Abstract:

Electric railway traction systems are complex; they have electrical couplings, magnetic and solid mechanics. These couplings impose several constraints that complicate the modeling and analysis of these systems. An example of drive systems, which combine the advantages of the use of multiphase machines, power electronics and computing means, is mono convert isseur multi-machine system which can control a fully decoupled so many machines whose electric windings are connected in series. In this approach, our attention especially on modeling and independent control of two five phase synchronous machine with permanent magnet connected in series and fed by a matrix converter application to the rail traction (bogie of a locomotive BB 36000).

Keywords: synchronous machine, vector control Multi-machine/ Multi-inverter, matrix inverter, Railway traction

Procedia PDF Downloads 344

Authors: Abdel Hadi N. Ebraheim, Eman Azomi, Nefisa A. Fahmy

Abstract:

This paper designs and implements a computer-aided system (CAS) to help detect and diagnose liver cirrhosis in patients with Chronic Hepatitis C. Our system reduces the required features (tests) the patient is asked to do to tests to their minimal best most informative subset of tests, with a diagnostic accuracy above 99%, and hence saving both time and costs. We use the Support Vector Machine (SVM) with cross-validation, a Multilayer Perceptron Neural Network (MLP), and a Generalized Regression Neural Network (GRNN) that employs a base of radial functions for functional approximation, as classifiers. Our system is tested on 199 subjects, of them 99 Chronic Hepatitis C.The subjects were selected from among the outpatient clinic in National Herpetology and Tropical Medicine Research Institute (NHTMRI).

Keywords: liver cirrhosis, artificial neural network, support vector machine, multi-layer perceptron, classification, accuracy

Procedia PDF Downloads 420

Authors: Rahul Malhotra

Abstract:

The field of wireless sensor networks (WSN) engages a lot of associates in the research community as an interdisciplinary field of interest. This type of network is inexpensive, multifunctionally attributable to advances in micro-electromechanical systems and conjointly the explosion and expansion of wireless communications. A mobile ad hoc network is a wireless network without fastened infrastructure or federal management. Due to the infrastructure-less mode of operation, mobile ad-hoc networks are gaining quality. During this work, we have performed an efficient performance study of the two major routing protocols: Ad hoc On-Demand Distance Vector Routing (AODV) and Dynamic Source Routing (DSR) protocols. We have used an accurate simulation model supported NS2 for this purpose. Our simulation results showed that AODV mitigates the drawbacks of the DSDV and provides better performance as compared to DSDV.

Keywords: routing protocol, MANET, AODV, On Demand Distance Vector Routing, DSR, Dynamic Source Routing

Procedia PDF Downloads 247

Authors: Andrew Youssef, David Matthews, Jie Pan

Abstract:

Identifying the magnitude and direction of a force on an elastic solid is highly desirable, as this allows for investigation and continual monitoring of the dynamic loading. This was traditionally conducted by connecting the solid to the supporting structure by multi-axial force transducer, providing that the transducer will not change the mounting conditions. Polyvinylidene fluoride (PVDF) film is a versatile force transducer that can be easily embedded in structures. Here a PVDF sensor array is embedded inside a simple structure in an effort to determine the force vector applied to the structure is an inverse problem. In this paper, forces of different magnitudes and directions where applied to the structure with an impact hammer, and the output of the PVDF was captured and processed to gain an estimate of the forces applied by the hammer. The outcome extends the scope of application of PVDF sensors for measuring the external or contact force vectors.

Keywords: embedded sensor, monitoring, PVDF, vibration

Procedia PDF Downloads 299

Authors: Kamel Belammi, Houria Fatrim

Abstract:

imbalanced data set, a problem often found in real world application, can cause seriously negative effect on classification performance of machine learning algorithms. There have been many attempts at dealing with classification of imbalanced data sets. In medical diagnosis classification, we often face the imbalanced number of data samples between the classes in which there are not enough samples in rare classes. In this paper, we proposed a learning method based on a cost sensitive extension of Least Mean Square (LMS) algorithm that penalizes errors of different samples with different weight and some rules of thumb to determine those weights. After the balancing phase, we applythe different classifiers (support vector machine (SVM), k- nearest neighbor (KNN) and multilayer neuronal networks (MNN)) for balanced data set. We have also compared the obtained results before and after balancing method.

Keywords: multilayer neural networks, k- nearest neighbor, support vector machine, imbalanced medical data, least mean square algorithm, diabetes

Procedia PDF Downloads 496

Authors: Devineni Vijay Bhaskar, Yendluri Raja

Abstract:

We recommend a model for traffic sign detection stranded on Convolutional Neural Networks (CNN). We first renovate the unique image into the gray scale image through with support vector machines, then use convolutional neural networks with fixed and learnable layers for revealing and understanding. The permanent layer can reduction the amount of attention areas to notice and crop the limits very close to the boundaries of traffic signs. The learnable coverings can rise the accuracy of detection significantly. Besides, we use bootstrap procedures to progress the accuracy and avoid overfitting problem. In the German Traffic Sign Detection Benchmark, we obtained modest results, with an area under the precision-recall curve (AUC) of 99.49% in the group “Risk”, and an AUC of 96.62% in the group “Obligatory”.

Keywords: convolutional neural network, support vector machine, detection, traffic signs, bootstrap procedures, precision-recall curve

Procedia PDF Downloads 86

Authors: Cristian Chacha, David Asiain, Jesús Ponce de León, José Ramón Beltrán

Abstract:

This work explores and characterizes the behavior of the AFE AD5941 in impedance measurement using an embedded algorithm with a constant current AC source. The main aim of this research is to improve the exact measurement of impedance values for their application in EDA-focused wearable devices. Through comprehensive study and characterization, it has been observed that employing a measurement sequence with a constant current source produces results with increased dispersion but higher accuracy. As a result, this approach leads to a more accurate system for impedance measurement.

Keywords: EDA, constant current AC source, wearable, precision, accuracy, impedance

Procedia PDF Downloads 65

Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

Abstract:

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 respectively

Keywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm

Procedia PDF Downloads 438

Authors: Na Li, Samuel Simon Araya, Søren Knudsen Kær

Abstract:

This study investigates the effects of operating parameters of different current density, temperature and pressure on the performance of a proton exchange membrane (PEM) water electrolysis stack. A 7-cell PEM water electrolysis stack was assembled and tested under different operation modules. The voltage change and polarization curves under different test conditions, namely current density, temperature and pressure, were recorded. Results show that higher temperature has positive effect on overall stack performance, where temperature of 80 ℃ improved the cell performance greatly. However, the cathode pressure and current density has little effect on stack performance.

Keywords: PEM electrolysis stack, current density, temperature, pressure

Procedia PDF Downloads 168

Authors: Bangwon Seo

Abstract:

In this paper, we consider multicast device-to-device (D2D) direct communication systems in cellular networks. In multicast D2D communications, nearby mobile devices exchanges, their data directly without going through a base station and a D2D transmitter send its data to multiple D2D receivers that compose of D2D multicast group. We consider wiretap channel where there is an eavesdropper that attempts to overhear the transmitted data of the D2D transmitter. In this paper, we propose a secure transmission scheme in D2D multicast communications in cellular networks. In order to prevent the eavesdropper from overhearing the transmitted data of the D2D transmitter, a precoding vector is employed at the D2D transmitter in the proposed scheme. We perform computer simulations to evaluate the performance of the proposed scheme. Through the simulation, we show that the secrecy rate performance can be improved by selecting an appropriate precoding vector.

Keywords: device-to-device communications, wiretap channel, secure transmission, precoding

Procedia PDF Downloads 259

Authors: L. Lakhdari, B. Bouchiba, M. Bechar

Abstract:

The multi-level inverters present an important novelty in the field of energy control with high voltage and power. The major advantage of all multi-level inverters is the improvement and spectral quality of its generated output signals. In recent years, various pulse width modulation techniques have been developed. From these technics we have: Sinusoidal Pulse Width Modulation (SPWM) and Space Vector Pulse Width Modulation (SVPWM). This work presents a detailed analysis of the comparative advantage of space vector pulse width modulation (SVPWM) and the standard SPWM technique for Three Level Diode Clamped Inverter fed Induction Motor. The comparison is based on the evaluation of harmonic distortion THD.

Keywords: induction motor, multilevel inverters, SVPWM, SPWM, THD

Procedia PDF Downloads 309

Authors: Slim Chokri

Abstract:

Load forecasting is one of the central functions in power systems operations. Electricity cannot be stored, which means that for electric utility, the estimate of the future demand is necessary in managing the production and purchasing in an economically reasonable way. A majority of the recently reported approaches are based on neural network. The attraction of the methods lies in the assumption that neural networks are able to learn properties of the load. However, the development of the methods is not finished, and the lack of comparative results on different model variations is a problem. This paper presents a new approach in order to predict the Tunisia daily peak load. The proposed method employs a computational intelligence scheme based on the Fuzzy neural network (FNN) and support vector regression (SVR). Experimental results obtained indicate that our proposed FNN-SVR technique gives significantly good prediction accuracy compared to some classical techniques.

Keywords: neural network, load forecasting, fuzzy inference, machine learning, fuzzy modeling and rule extraction, support vector regression

Procedia PDF Downloads 404

Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao

Abstract:

In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.

Keywords: evolving learning, knowledge extraction, knowledge graph, text mining

Procedia PDF Downloads 434

Authors: Olofintoye Lawrence Kayode, Olorunniyi Omojola Felix

Abstract:

Schistosomiasis is a vector-borne water-based disease transmitted by Bulinus globosus, causing haematuria in the urine of man, while fascioliasis is a trematode zoonosis infectious transmitted by Lymnaea natalensis causing liver disease in man and animals. Adult Bulinus globosus and Lymnaea natalensis were used for the experiment. Aqueous leaf extract of Ageratum conyzoides and Datura stramonium were prepared into 25, 50, 75, 100, 200 and 400 ppm concentrations. Ten snails of each species were exposed to different concentrations in triplicates, and dechlorinated water was used as control at 24h, 48h, and 72h exposure. The results revealed that 100 ppm of both plants leaves extracts indicated mortality rates between 76.7% and 100% at 24h, 48h, and 72h for both snail species. (P<0.05). In conclusion, the extract exercised molluscicidal activity to control the snail vector at lethal doses LC₅₀ (66.611- 72.021 ppm), CI = 63.083-77.90ppm and LC₉₀ (92.623-102.350), CI = 87.715 -110.12 ppm.

Keywords: snail, plant leaf, aqueous extract, mortality

Procedia PDF Downloads 40