Search results for: Adaptive Fourier decomposition

Authors: Peerapong Uthansakul, Sakkarin Chaokuntod, Monthippa Uthansakul

Abstract:

In literatures, many researches proposed various methods to reduce PAPR (Peak to Average Power Ratio). Among those, DSI (Dummy Sequence Insertion) is one of the most attractive methods for WiMAX systems because it does not require side information transmitted along with user data. However, the conventional DSI methods find dummy sequence by performing an iterative procedure until achieving PAPR under a desired threshold. This causes a significant delay on finding dummy sequence and also effects to the overall performances in WiMAX systems. In this paper, the new method based on DSI is proposed by finding dummy sequence without the need of iterative procedure. The fast DSI method can reduce PAPR without either delays or required side information. The simulation results confirm that the proposed method is able to carry out PAPR performances as similar to the other methods without any delays. In addition, the simulations of WiMAX system with adaptive modulations are also investigated to realize the use of proposed methods on various fading schemes. The results suggest the WiMAX designers to modify a new Signal to Noise Ratio (SNR) criteria for adaptation.

Keywords: WiMAX, OFDM, PAPR, Dummy SequenceInsertion method.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1518

Authors: S. Shanthi, V. Muralibhaskaran

Abstract:

Mammography has been one of the most reliable methods for early detection of breast cancer. There are different lesions which are breast cancer characteristic such as microcalcifications, masses, architectural distortions and bilateral asymmetry. One of the major challenges of analysing digital mammogram is how to extract efficient features from it for accurate cancer classification. In this paper we proposed a hybrid feature extraction method to detect and classify all four signs of breast cancer. The proposed method is based on multiscale surrounding region dependence method, Gabor filters, multi fractal analysis, directional and morphological analysis. The extracted features are input to self adaptive resource allocation network (SRAN) classifier for classification. The validity of our approach is extensively demonstrated using the two benchmark data sets Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammograph (DDSM) and the results have been proved to be progressive.

Keywords: Feature extraction, fractal analysis, Gabor filters, multiscale surrounding region dependence method, SRAN.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2897

Authors: Dewan Md. Farid, Nguyen Huu Hoa, Jerome Darmont, Nouria Harbi, Mohammad Zahidur Rahman

Abstract:

In this paper, we present a new learning algorithm for anomaly based network intrusion detection using improved self adaptive naïve Bayesian tree (NBTree), which induces a hybrid of decision tree and naïve Bayesian classifier. The proposed approach scales up the balance detections for different attack types and keeps the false positives at acceptable level in intrusion detection. In complex and dynamic large intrusion detection dataset, the detection accuracy of naïve Bayesian classifier does not scale up as well as decision tree. It has been successfully tested in other problem domains that naïve Bayesian tree improves the classification rates in large dataset. In naïve Bayesian tree nodes contain and split as regular decision-trees, but the leaves contain naïve Bayesian classifiers. The experimental results on KDD99 benchmark network intrusion detection dataset demonstrate that this new approach scales up the detection rates for different attack types and reduces false positives in network intrusion detection.

Keywords: Detection rates, false positives, network intrusiondetection, naïve Bayesian tree.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2235

Authors: Dionisios Panagiotaras, Elias Stathatos, Dimitrios Papoulis

Abstract:

 Sol-gel method has been used to fabricate nanocomposite films on glass substrates composed halloysite clay mineral and nanocrystalline TiO2. The methodology for the synthesis involves a simple chemistry method utilized nonionic surfactant molecule as pore directing agent along with the acetic acid-based solgel route with the absence of water molecules. The thermal treatment of composite films at 450oC ensures elimination of organic material and lead to the formation of TiO2 nanoparticles onto the surface of the halloysite nanotubes. Microscopy techniques and porosimetry methods used in order to delineate the structural characteristics of the materials. The nanocomposite films produced have no cracks and active anatase crystal phase with small crystallite size were deposited on halloysite nanotubes. The photocatalytic properties for the new materials were examined for the decomposition of the Basic Blue 41 azo dye in solution. These, nanotechnology based composite films show high efficiency for dye’s discoloration in spite of different halloysite quantities and small amount of halloysite/TiO2 catalyst immobilized onto glass substrates. Moreover, we examined the modification of the halloysite/TiO2 films with silver particles in order to improve the photocatalytic properties of the films. Indeed, the presence of silver nanoparticles enhances the discoloration rate of the Basic Blue 41 compared to the efficiencies obtained for unmodified films.

Keywords: Clay mineral, nanotubular Halloysite, Photocatalysis, Titanium Dioxide, Silver modification.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2491

Authors: H. Shareef, A. Mohamed, S. A. Khalid, Aziah Khamis

Abstract:

This paper presents application artificial intelligent (AI) techniques, namely artificial neural network (ANN), adaptive neuro fuzzy interface system (ANFIS), to estimate the real power transfer between generators and loads. Since these AI techniques adopt supervised learning, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of both AI methods compared to that of the MNE method. The mean squared error of the estimate of ANN and ANFIS power transfer allocation methods are 1.19E-05 and 2.97E-05, respectively. Furthermore, when compared to MNE method, ANN and ANFIS methods computes generator contribution to loads within 20.99 and 39.37msec respectively whereas the MNE method took 360msec for the calculation of same real power transfer allocation. 

Keywords: Artificial intelligence, Power tracing, Artificial neural network, ANFIS, Power system deregulation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2540

Authors: Thejaswi H. Raya, Vineetha Bettaiah, Heggere S. Ranganath

Abstract:

For over a decade, the Pulse Coupled Neural Network (PCNN) based algorithms have been successfully used in image interpretation applications including image segmentation. There are several versions of the PCNN based image segmentation methods, and the segmentation accuracy of all of them is very sensitive to the values of the network parameters. Most methods treat PCNN parameters like linking coefficient and primary firing threshold as global parameters, and determine them by trial-and-error. The automatic determination of appropriate values for linking coefficient, and primary firing threshold is a challenging problem and deserves further research. This paper presents a method for obtaining global as well as local values for the linking coefficient and the primary firing threshold for neurons directly from the image statistics. Extensive simulation results show that the proposed approach achieves excellent segmentation accuracy comparable to the best accuracy obtainable by trial-and-error for a variety of images.

Keywords: Automatic Selection of PCNN Parameters, Image Segmentation, Neural Networks, Pulse Coupled Neural Network

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2254

Authors: S. Sharma, U. Batra, S. Kapoor, A. Dua

Abstract:

In this study, the effects and interactions of reaction time and capping agent assistance during sol-gel synthesis of magnesium substituted hydroxyapatite nanopowder (MgHA) on hydroxyapatite (HA) to β-tricalcium phosphate (β-TCP) ratio, Ca/P ratio and mean crystallite size was examined experimentally as well as through statistical analysis. MgHA nanopowders were synthesized by sol-gel technique at room temperature using aqueous solution of calcium nitrate tetrahydrate, magnesium nitrate hexahydrate and potassium dihydrogen phosphate as starting materials. The reaction time for sol-gel synthesis was varied between 15 to 60 minutes. Two process routes were followed with and without addition of triethanolamine (TEA) in the solutions. The elemental compositions of as-synthesized powders were determined using X-ray fluorescence (XRF) spectroscopy. The functional groups present in the assynthesized MgHA nanopowders were established through Fourier Transform Infrared Spectroscopy (FTIR). The amounts of phases present, Ca/P ratio and mean crystallite sizes of MgHA nanopowders were determined using X-ray diffraction (XRD). The HA content in biphasic mixture of HA and β-TCP and Ca/P ratio in as-synthesized MgHA nanopowders increased effectively with reaction time of sols (p<0.0001, two way ANOVA), however, these were independent of TEA addition (p>0.15, two way ANOVA). The MgHA nanopowders synthesized with TEA assistance exhibited 14 nm lower crystallite size (p<0.018, 2 sample t-test) compared to the powder synthesized without TEA assistance.

Keywords: Capping agent, hydroxyapatite, regression analysis, sol-gel, 2- sample t-test, two-way ANOVA.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1583

Authors: A.Venkadesan, S.Himavathi, A.Muthuramalingam

Abstract:

Rotor Flux based Model Reference Adaptive System (RF-MRAS) is the most popularly used conventional speed estimation scheme for sensor-less IM drives. In this scheme, the voltage model equations are used for the reference model. This encounters major drawbacks at low frequencies/speed which leads to the poor performance of RF-MRAS. Replacing the reference model using Neural Network (NN) based flux estimator provides an alternate solution and addresses such drawbacks. This paper identifies an NN based flux estimator using Single Neuron Cascaded (SNC) Architecture. The proposed SNC-NN model replaces the conventional voltage model in RF-MRAS to form a novel MRAS scheme named as SNC-NN-MRAS. Through simulation the proposed SNC-NN-MRAS is shown to be promising in terms of all major issues and robustness to parameter variation. The suitability of the proposed SNC-NN-MRAS based speed estimator and its advantages over RF-MRAS for sensor-less induction motor drives is comprehensively presented through extensive simulations.

Keywords: Sensor-less operation, vector-controlled IM drives, SNC-NN-MRAS, single neuron cascaded architecture, RF-MRAS, artificial neural network

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1848

Authors: Nahid Ardalani, Ahmadreza Khoogar, H. Roohi

Abstract:

In this paper we compare the response of linear and nonlinear neural network-based prediction schemes in prediction of received Signal-to-Interference Power Ratio (SIR) in Direct Sequence Code Division Multiple Access (DS/CDMA) systems. The nonlinear predictor is Multilayer Perceptron MLP and the linear predictor is an Adaptive Linear (Adaline) predictor. We solve the problem of complexity by using the Minimum Mean Squared Error (MMSE) principle to select the optimal predictors. The optimized Adaline predictor is compared to optimized MLP by employing noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an urban environment. The results show that the Adaline predictor can estimates SIR with the same error as MLP when the user has the velocity of 5 km/h and 60 km/h but by increasing the velocity up-to 120 km/h the mean squared error of MLP is two times more than Adaline predictor. This makes the Adaline predictor (with lower complexity) more suitable than MLP for closed-loop power control where efficient and accurate identification of the time-varying inverse dynamics of the multi path fading channel is required.

Keywords: Power control, neural networks, DS/CDMA mobilecommunication systems.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2477

Authors: S. K. Satpathy, S. Panda, K. K. Nagwanshi, S. K. Nayak, C. Ardil

Abstract:

Removing noise from the any processed images is very important. Noise should be removed in such a way that important information of image should be preserved. A decisionbased nonlinear algorithm for elimination of band lines, drop lines, mark, band lost and impulses in images is presented in this paper. The algorithm performs two simultaneous operations, namely, detection of corrupted pixels and evaluation of new pixels for replacing the corrupted pixels. Removal of these artifacts is achieved without damaging edges and details. However, the restricted window size renders median operation less effective whenever noise is excessive in that case the proposed algorithm automatically switches to mean filtering. The performance of the algorithm is analyzed in terms of Mean Square Error [MSE], Peak-Signal-to-Noise Ratio [PSNR], Signal-to-Noise Ratio Improved [SNRI], Percentage Of Noise Attenuated [PONA], and Percentage Of Spoiled Pixels [POSP]. This is compared with standard algorithms already in use and improved performance of the proposed algorithm is presented. The advantage of the proposed algorithm is that a single algorithm can replace several independent algorithms which are required for removal of different artifacts.

Keywords: Filtering, Decision Based Algorithm, noise, imagerestoration.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2123

Authors: A. Bajit, M. Nahid, A. Tamtaoui, E. H. Bouyakhf

Abstract:

In this paper, we propose a Perceptually Optimized Foveation based Embedded ZeroTree Image Coder (POEFIC) that introduces a perceptual weighting to wavelet coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to a given bit rate a fixation point which determines the region of interest ROI. The paper also, introduces a new objective quality metric based on a Psychovisual model that integrates the properties of the HVS that plays an important role in our POEFIC quality assessment. Our POEFIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and attempts to increase the perceptual quality for a given bit rate and observation distance. The perceptual weights for all wavelet subbands are computed based on 1) foveation masking to remove or reduce considerable high frequencies from peripheral regions 2) luminance and Contrast masking, 3) the contrast sensitivity function CSF to achieve the perceptual decomposition weighting. The new perceptually optimized codec has the same complexity as the original SPIHT techniques. However, the experiments results show that our coder demonstrates very good performance in terms of quality measurement.

Keywords: DWT, linear-phase 9/7 filter, Foveation Filtering, CSF implementation approaches, 9/7 Wavelet JND Thresholds and Wavelet Error Sensitivity WES, Luminance and Contrast masking, standard SPIHT, Objective Quality Measure, Probability Score PS.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1764

Authors: Jong Han Joo, Jeong Hun Lee, Young Sun Kim, Jae Young Kang, Seung Ho Choi

Abstract:

In this study, we propose a novel technique for acoustic echo suppression (AES) during speech recognition under barge-in conditions. Conventional AES methods based on spectral subtraction apply fixed weights to the estimated echo path transfer function (EPTF) at the current signal segment and to the EPTF estimated until the previous time interval. However, the effects of echo path changes should be considered for eliminating the undesired echoes. We describe a new approach that adaptively updates weight parameters in response to abrupt changes in the acoustic environment due to background noises or double-talk. Furthermore, we devised a voice activity detector and an initial time-delay estimator for barge-in speech recognition in communication networks. The initial time delay is estimated using log-spectral distance measure, as well as cross-correlation coefficients. The experimental results show that the developed techniques can be successfully applied in barge-in speech recognition systems.

Keywords: Acoustic echo suppression, barge-in, speech recognition, echo path transfer function, initial delay estimator, voice activity detector.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2277

Authors: Navdeep Goel, Salvador Gabarda

Abstract:

Digital images are widely used in computer applications. To store or transmit the uncompressed images requires considerable storage capacity and transmission bandwidth. Image compression is a means to perform transmission or storage of visual data in the most economical way. This paper explains about how images can be encoded to be transmitted in a multiplexing time-frequency domain channel. Multiplexing involves packing signals together whose representations are compact in the working domain. In order to optimize transmission resources each 4 × 4 pixel block of the image is transformed by a suitable polynomial approximation, into a minimal number of coefficients. Less than 4 × 4 coefficients in one block spares a significant amount of transmitted information, but some information is lost. Different approximations for image transformation have been evaluated as polynomial representation (Vandermonde matrix), least squares + gradient descent, 1-D Chebyshev polynomials, 2-D Chebyshev polynomials or singular value decomposition (SVD). Results have been compared in terms of nominal compression rate (NCR), compression ratio (CR) and peak signal-to-noise ratio (PSNR) in order to minimize the error function defined as the difference between the original pixel gray levels and the approximated polynomial output. Polynomial coefficients have been later encoded and handled for generating chirps in a target rate of about two chirps per 4 × 4 pixel block and then submitted to a transmission multiplexing operation in the time-frequency domain.

Keywords: Chirp signals, Image multiplexing, Image transformation, Linear canonical transform, Polynomial approximation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2094

Authors: M. Elkhoury

Abstract:

A recently developed one-equation turbulence model has been successfully applied to simulate turbulent flows with various complexities. The model, which is based on the transformation of the k-ε closure, is wall-distance free and equipped with lagging destruction/dissipation terms. Test cases included shockboundary- layer interaction flows over the NACA 0012 airfoil, an axisymmetric bump, and the ONERA M6 wing. The capability of the model to operate in a Scale Resolved Simulation (SRS) mode is demonstrated through the simulation of a massive flow separation over a circular cylinder at Re= 1.2 x106. An assessment of the results against available experiments Menter (k-ε)1Eq and the Spalart- Allmaras model that belongs to the single equation closure family is made.

Keywords: Turbulence modeling, complex flow simulation, scale adaptive simulation, one-equation turbulence model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1441

Authors: Xu Han, Shanxiong Chen, Shiyu Zhu, Xiaoyu Lin, Fujia Zhao, Dingwang Wang

Abstract:

Character detection is an important issue for character recognition of ancient Yi books. The accuracy of detection directly affects the recognition effect of ancient Yi books. Considering the complex layout, the lack of standard typesetting and the mixed arrangement between images and texts, we propose a character detection method for ancient Yi books based on connected components and regressive character segmentation. First, the scanned images of ancient Yi books are preprocessed with nonlocal mean filtering, and then a modified local adaptive threshold binarization algorithm is used to obtain the binary images to segment the foreground and background for the images. Second, the non-text areas are removed by the method based on connected components. Finally, the single character in the ancient Yi books is segmented by our method. The experimental results show that the method can effectively separate the text areas and non-text areas for ancient Yi books and achieve higher accuracy and recall rate in the experiment of character detection, and effectively solve the problem of character detection and segmentation in character recognition of ancient books.

Keywords: Computing methodologies, interest point, salient region detections, image segmentation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 805

Authors: Mohd Aftar Abu Bakar, Noratiqah Mohd Ariff, Abdul Aziz Jemain

Abstract:

Storm Event Analysis (SEA) provides a method to define rainfalls events as storms where each storm has its own amount and duration. By modelling daily probability of different types of storms, the onset, offset and cycle of rainfall seasons can be determined and investigated. Furthermore, researchers from the field of meteorology will be able to study the dynamical characteristics of rainfalls and make predictions for future reference. In this study, four categories of storms; short, intermediate, long and very long storms; are introduced based on the length of storm duration. Daily probability models of storms are built for these four categories of storms in Peninsular Malaysia. The models are constructed by using Bernoulli distribution and by applying linear regression on the first Fourier harmonic equation. From the models obtained, it is found that daily probability of storms at the Eastern part of Peninsular Malaysia shows a unimodal pattern with high probability of rain beginning at the end of the year and lasting until early the next year. This is very likely due to the Northeast monsoon season which occurs from November to March every year. Meanwhile, short and intermediate storms at other regions of Peninsular Malaysia experience a bimodal cycle due to the two inter-monsoon seasons. Overall, these models indicate that Peninsular Malaysia can be divided into four distinct regions based on the daily pattern for the probability of various storm events.

Keywords: Daily probability model, monsoon seasons, regions, storm events.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1596

Authors: Usman Ghani

Abstract:

Feedback is a vital element for improving student learning in a simulation-based training as it guides and refines learning through scaffolding. A number of studies in literature have shown that students’ learning is enhanced when feedback is provided with personalized tutoring that offers specific guidance and adapts feedback to the learner in a one-to-one environment. Thus, emulating these adaptive aspects of human tutoring in simulation provides an effective methodology to train individuals. This paper presents the results of a study that investigated the effectiveness of automating different types of feedback techniques such as Knowledge-of-Correct-Response (KCR) and Answer-Until- Correct (AUC) in software simulation for learning basic information technology concepts. For the purpose of comparison, techniques like simulation with zero or no-feedback (NFB) and traditional hands-on (HON) learning environments are also examined. The paper presents the summary of findings based on quantitative analyses which reveal that the simulation based instructional strategies are at least as effective as hands-on teaching methodologies for the purpose of learning of IT concepts. The paper also compares the results of the study with the earlier studies and recommends strategies for using feedback mechanism to improve students’ learning in designing and simulation-based IT training.

Keywords: Simulation, feedback, training, hands-on, labs.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1531

Authors: S. H. R. Sadeghi, A. Sadoddin, A. Najafinejad

Abstract:

Expansionism and ever-increasing population menace all different resources worldwide. The issue, hence, is critical in developing countries like Iran where new technologies are rapidly luxuriated and unguardedly applied, resulting in unexpected outcomes. However, uncommon and comprehensive approaches are introduced to take all the different aspects involved into consideration. In the last decade, few approaches such as community-based, stakeholders-oriented, adaptive and ultimately integrated management, have emerged and are developing for efficient, Co-management or best management, economic and sustainable development and management of watershed resources in Iran. In the present paper, an attempt has been made to focus on state-of-the-art approaches for the management of watershed resources applied in Iran. The study has been then supported by reports of some case studies conducted throughout the country involving previously mentioned approaches. Scrutinizing results of the researches verified a progressive tendency of the managerial approaches in watershed management strategies leading to a general approaching balance situation. The approaches are firmly rooted in educational, research, executive, legal and policy-making sectors leading to some recuperation at different levels. However, there is a long way ahead to naturalize detrimental effects of unscientific, illegal and over exploitation of the watershed resources in Iran.

Keywords: Comprehensive management, ecosystem balance, integrated watershed management, land resources optimization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 979

Authors: S. Zeković, M. Vujošević, T. Maričić

Abstract:

The paper provides a comprehensive analysis of the sustainable development in the Belgrade Metropolitan Region - BMA (level NUTS 2) preliminary evaluating the three chosen components: 1) economic growth and developmental changes; 2) competitiveness; and 3) territorial concentration and industrial specialization. First, we identified the main results of development changes and economic growth by applying Shift-share analysis on the metropolitan level. Second, the empirical evaluation of competitiveness in the BMA is based on the analysis of absolute and relative values of eight indicators by Spider method. Paper shows that the consideration of the national share, industrial mix and metropolitan/regional share in total Shift share of the BMA, as well as economic/functional specialization of the BMA indicate very strong process of deindustrialization. Allocative component of the BMA economic growth has positive value, reflecting the above-average sector productivity compared to the national average. Third, the important positive role of metropolitan/regional component in decomposition of the BMA economic growth is highlighted as one of the key results. Finally, comparative analysis of the industrial territorial concentration in the BMA in relation to Serbia is based on location quotient (LQ) or Balassa index as a valid measure. The results indicate absolute and relative differences in decrease of industry territorial concentration as well as inefficiency of utilizing territorial capital in the BMA. Results are important for the increase of regional competitiveness and territorial distribution in this area as well as for improvement of sustainable metropolitan and sector policies, planning and governance on this level.

Keywords: Belgrade Metropolitan Area (BMA), Comprehensive analysis/evaluation, economic growth and competitiveness, sustainable development.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1718

Authors: Abed Sami Qawasme, Sameer Khader

Abstract:

This paper describes the effects of photovoltaic voltage changes on Multi-level inverter (MLI) due to solar irradiation variations, and methods to overcome these changes. The irradiation variation affects the generated voltage, which in turn varies the switching angles required to turn-on the inverter power switches in order to obtain minimum harmonic content in the output voltage profile. Genetic Algorithm (GA) is used to solve harmonics elimination equations of eleven level inverters with equal and non-equal dc sources. After that artificial neural network (ANN) algorithm is proposed to generate appropriate set of switching angles for MLI at any level of input dc sources voltage causing minimization of the total harmonic distortion (THD) to an acceptable limit. MATLAB/Simulink platform is used as a simulation tool and Fast Fourier Transform (FFT) analyses are carried out for output voltage profile to verify the reliability and accuracy of the applied technique for controlling the MLI harmonic distortion. According to the simulation results, the obtained THD for equal dc source is 9.38%, while for variable or unequal dc sources it varies between 10.26% and 12.93% as the input dc voltage varies between 4.47V nd 11.43V respectively. The proposed ANN algorithm provides satisfied simulation results that match with results obtained by alternative algorithms.

Keywords: Multi level inverter, genetic algorithm, artificial neural network, total harmonic distortion.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 580

Authors: Yi-Haur Shiau, Sun-In Lin, Shi-Wei Lo, Hsiu-Mei Chou, Yi-Hsuan Chen

Abstract:

This paper proposes a novel multi-format stream grid architecture for real-time image monitoring system. The system, based on a three-tier architecture, includes stream receiving unit, stream processor unit, and presentation unit. It is a distributed computing and a loose coupling architecture. The benefit is the amount of required servers can be adjusted depending on the loading of the image monitoring system. The stream receive unit supports multi capture source devices and multi-format stream compress encoder. Stream processor unit includes three modules; they are stream clipping module, image processing module and image management module. Presentation unit can display image data on several different platforms. We verified the proposed grid architecture with an actual test of image monitoring. We used a fast image matching method with the adjustable parameters for different monitoring situations. Background subtraction method is also implemented in the system. Experimental results showed that the proposed architecture is robust, adaptive, and powerful in the image monitoring system.

Keywords: Motion detection, grid architecture, image monitoring system, and background subtraction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1558

Authors: M. Zerikat, S. Chekroun

Abstract:

This paper proposes an effective adaptation learning algorithm based on artificial neural networks for speed control of an induction motor assumed to operate in a high-performance drives environment. The structure scheme consists of a neural network controller and an algorithm for changing the NN weights in order that the motor speed can accurately track of the reference command. This paper also makes uses a very realistic and practical scheme to estimate and adaptively learn the noise content in the speed load torque characteristic of the motor. The availability of the proposed controller is verified by through a laboratory implementation and under computation simulations with Matlab-software. The process is also tested for the tracking property using different types of reference signals. The performance and robustness of the proposed control scheme have evaluated under a variety of operating conditions of the induction motor drives. The obtained results demonstrate the effectiveness of the proposed control scheme system performances, both in steady state error in speed and dynamic conditions, was found to be excellent and those is not overshoot.

Keywords: Electric drive, Induction motor, speed control, Adaptive control, neural network, High Performance.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2001

Authors: G.T. Cirella, L. Tao

Abstract:

The index of sustainable functionality (ISF) is an adaptive, multi-criteria technique that is used to measure sustainability; it is a concept that can be transposed to many regions throughout the world. An ISF application of the Southern Regional Organisation of Councils (SouthROC) in South East Queensland (SEQ) – the fastest growing region in Australia – indicated over a 25 year period an increase of over 10% level of functionality from 58.0% to 68.3%. The ISF of SouthROC utilised methodologies that derived from an expert panel based approach. The overall results attained an intermediate level of functionality which amounted to related concerns of economic progress and lack of social awareness. Within the region, a solid basis for future testing by way of measured changes and developed trends can be established. In this regard as management tool, the ISF record offers support for regional sustainability practice and decision making alike. This research adaptively analyses sustainability – a concept that is lacking throughout much of the academic literature and any reciprocal experimentation. This lack of knowledge base has been the emphasis of where future sustainability research can grow from and prove useful in rapidly growing regions. It is the intentions of this research to help further develop the notions of index-based quantitative sustainability.

Keywords: Environmental engineering, index of sustainable functionality, sustainability indicators, sustainable development.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2337

Authors: Zulhamsyah Imran, Masahiro Yamao

Abstract:

Social resilience has role to govern the local community and coastal fisheries resources toward sustainable fisheries development in tsunami affected area. This paper asses, explore and investigates of indigenous institutions, external and internal facilitators toward strengthening social resilience. Identification of the genuine organizations role had been conducted twice by using Rapid Assessment Appraisal, Focus Group Discussion, and in-depth interview for collecting primary and secondary data. Local wisdom had a contribution and adaptable to rebound social resilience. The Panglima Laot Lhok (sea commander) had determined and adapted role on recovery of the fishing community, particularly facilitated aid delivery to fishermen, as shown in anchovy fisheries relief case in Krueng Raya Bay. Toke Bangku (financial trader) had stimulated for reinforcement of advance payment and market channel. The other institutions supported upon linking and bridging connectivity among stakeholders. Collaborative governance can avoid conflict, reduce donor dependency and strengthen social resilience within fishing community.

Keywords: Fishing community, indigenous institution, adaptive role, collaborative, social resilience.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2566

Authors: Rajesh Kumar, Puneet Aggarwal

Abstract:

In context of understanding problems faced by undergraduate students while carrying out laboratory experiments dealing with high voltages, it was found that most of the students are hesitant to work directly on machine. The reason is that error in the circuitry might lead to deterioration of machine and laboratory instruments. So, it has become inevitable to include modern pedagogic techniques for undergraduate students, which would help them to first carry out experiment in virtual system and then to work on live circuit. Further advantages include that students can try out their intuitive ideas and perform in virtual environment, hence leading to new research and innovations. In this paper, virtual environment used is of MATLAB/Simulink for three-phase induction machines. The performance analysis of three-phase induction machine is carried out using virtual environment which includes Direct Current (DC) Test, No-Load Test, and Block Rotor Test along with speed torque characteristics for different rotor resistances and input voltage, respectively. Further, this paper carries out computer aided teaching of basic Voltage Source Inverter (VSI) drive circuitry. Hence, this paper gave undergraduates a clearer view of experiments performed on virtual machine (No-Load test, Block Rotor test and DC test, respectively). After successful implementation of basic tests, VSI circuitry is implemented, and related harmonic distortion (THD) and Fast Fourier Transform (FFT) of current and voltage waveform are studied.

Keywords: Block rotor test, DC test, no-load test, virtual environment, VSI.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 857

Authors: Muhammad R. Islam, Mohammad Dalour H. Beg, Saidatul S. Jamari

Abstract:

Considering palm oil as non-drying oil owing to its low iodine value, an attempt was taken to increase the unsaturation in the fatty acid chains of palm oil for the preparation of alkyds. To increase the unsaturation in the palm oil, sulphuric acid (SA) and para-toluene sulphonic acid (PTSA) was used prior to alcoholysis for the dehydration process. The iodine number of the oil samples was checked for the unsaturation measurement by Wijs method. Alkyd resin was prepared using the dehydrated palm oil by following alcoholysis and esterification reaction. To improve the film properties 0.5wt.% multi-wall carbon nano tubes (MWCNTs) were used to manufacture polymeric film. The properties of the resins were characterized by various physico-chemical properties such as density, viscosity, iodine value, saponification value, etc. Structural elucidation was confirmed by Fourier transform of infrared spectroscopy and proton nuclear magnetic resonance; surfaces of the films were examined by field-emission scanning electron microscope. In addition, pencil hardness and chemical resistivity was also measured by using standard methods. The effect of enhancement of the unsaturation in the fatty acid chain found significant and motivational. The resin prepared with dehydrated palm oil showed improved properties regarding hardness and chemical resistivity testing. The incorporation of MWCNTs enhanced the thermal stability and hardness of the films as well.

Keywords: Alkyd resin, nano-coatings, dehydration, palm oil.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2407

Authors: Rainer Schneider, Stephan Lau, Levin Kuhlmann, Simon Vogrin, Maciej Gratkowski, Mark Cook, Jens Haueisen

Abstract:

Cardiac pulse-related artifacts in the EEG recorded simultaneously with fMRI are complex and highly variable. Their effective removal is an unsolved problem. Our aim is to develop an adaptive removal algorithm based on the matching pursuit (MP) technique and to compare it to established methods using a visual evoked potential (VEP). We recorded the VEP inside the static magnetic field of an MR scanner (with artifacts) as well as in an electrically shielded room (artifact free). The MP-based artifact removal outperformed average artifact subtraction (AAS) and optimal basis set removal (OBS) in terms of restoring the EEG field map topography of the VEP. Subsequently, a dipole model was fitted to the VEP under each condition using a realistic boundary element head model. The source location of the VEP recorded inside the MR scanner was closest to that of the artifact free VEP after cleaning with the MP-based algorithm as well as with AAS. While none of the tested algorithms offered complete removal, MP showed promising results due to its ability to adapt to variations of latency, frequency and amplitude of individual artifact occurrences while still utilizing a common template.

Keywords: matching pursuit, ballistocardiogram, artifactremoval, EEG/fMRI.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1655

Authors: Ruchi Vyas, Sanjay Singh, Rashmi Sisodia

Abstract:

Chlorophytum borivillianum root extract (CBE) was chosen as a reducing agent to fabricate silver nanoparticles with the aim of studying its radioprotective efficacy. The formation of synthesized nanoparticles was characterized by UV–visible analysis (UV–vis), Fourier transform infra-red (FT-IR), Transmission electron microscopy (TEM), Scanning electron microscope (SEM). TEM analysis showed particles size in the range of 20-30 nm. For this study, Swiss albino mice were selected from inbred colony and were divided into 4 groups: group I- control (irradiated-6 Gy), group II- normal (vehicle treated), group III- plant extract alone and group IV- CB-AgNPs (dose of 50 mg/kg body wt./day) administered orally for 7 consecutive days before irradiation to serve as experimental. CB-AgNPs pretreatment rendered significant increase in body weight and testes weight at various post irradiation intervals in comparison to irradiated group. Supplementation of CB-AgNPs reversed the adverse effects of gamma radiation on biochemical parameters as it notably ameliorated the elevation in lipid peroxidation and decline in glutathione concentration in testes. These observations indicate the radio-protective potential of CB-AgNPs in testicular constituents against gamma irradiation in mice.

Keywords: Chlorophytum borivillianum, gamma radiation, radioprotective, silver nanoparticles.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 894

Authors: Sunita Jahirabadkar, Parag Kulkarni

Abstract:

Many real-world data sets consist of a very high dimensional feature space. Most clustering techniques use the distance or similarity between objects as a measure to build clusters. But in high dimensional spaces, distances between points become relatively uniform. In such cases, density based approaches may give better results. Subspace Clustering algorithms automatically identify lower dimensional subspaces of the higher dimensional feature space in which clusters exist. In this paper, we propose a new clustering algorithm, ISC – Intelligent Subspace Clustering, which tries to overcome three major limitations of the existing state-of-art techniques. ISC determines the input parameter such as є – distance at various levels of Subspace Clustering which helps in finding meaningful clusters. The uniform parameters approach is not suitable for different kind of databases. ISC implements dynamic and adaptive determination of Meaningful clustering parameters based on hierarchical filtering approach. Third and most important feature of ISC is the ability of incremental learning and dynamic inclusion and exclusions of subspaces which lead to better cluster formation.

Keywords: Density based clustering, high dimensional data, subspace clustering, dynamic parameter setting.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1984

Authors: Parvinder S. Sandhu, Hardeep Singh

Abstract:

The requirement to improve software productivity has promoted the research on software metric technology. There are metrics for identifying the quality of reusable components but the function that makes use of these metrics to find reusability of software components is still not clear. These metrics if identified in the design phase or even in the coding phase can help us to reduce the rework by improving quality of reuse of the component and hence improve the productivity due to probabilistic increase in the reuse level. CK metric suit is most widely used metrics for the objectoriented (OO) software; we critically analyzed the CK metrics, tried to remove the inconsistencies and devised the framework of metrics to obtain the structural analysis of OO-based software components. Neural network can learn new relationships with new input data and can be used to refine fuzzy rules to create fuzzy adaptive system. Hence, Neuro-fuzzy inference engine can be used to evaluate the reusability of OO-based component using its structural attributes as inputs. In this paper, an algorithm has been proposed in which the inputs can be given to Neuro-fuzzy system in form of tuned WMC, DIT, NOC, CBO , LCOM values of the OO software component and output can be obtained in terms of reusability. The developed reusability model has produced high precision results as expected by the human experts.

Keywords: CK-Metric, ID3, Neuro-fuzzy, Reusability.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1783