Search results for: multicarrier signal processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2496

Search results for: multicarrier signal processing

1806 Vibroacoustic Modulation of Wideband Vibrations and Its Possible Application for Windmill Blade Diagnostics

Authors: Abdullah Alnutayfat, Alexander Sutin, Dong Liu

Abstract:

Wind turbine has become one of the most popular energy production methods. However, failure of blades and maintenance costs evolve into significant issues in the wind power industry, so it is essential to detect the initial blade defects to avoid the collapse of the blades and structure. This paper aims to apply modulation of high-frequency blade vibrations by low-frequency blade rotation, which is close to the known Vibro-Acoustic Modulation (VAM) method. The high-frequency wideband blade vibration is produced by the interaction of the surface blades with the environment air turbulence, and the low-frequency modulation is produced by alternating bending stress due to gravity. The low-frequency load of rotational wind turbine blades ranges between 0.2-0.4 Hz and can reach up to 2 Hz for strong wind. The main difference between this study and previous ones on VAM methods is the use of a wideband vibration signal from the blade's natural vibrations. Different features of the VAM are considered using a simple model of breathing crack. This model considers the simple mechanical oscillator, where the parameters of the oscillator are varied due to low-frequency blade rotation. During the blade's operation, the internal stress caused by the weight of the blade modifies the crack's elasticity and damping. The laboratory experiment using steel samples demonstrates the possibility of VAM using a probe wideband noise signal. A cycle load with a small amplitude was used as a pump wave to damage the tested sample, and a small transducer generated a wideband probe wave. The received signal demodulation was conducted using the Detecting of Envelope Modulation on Noise (DEMON) approach. In addition, the experimental results were compared with the modulation index (MI) technique regarding the harmonic pump wave. The wideband and traditional VAM methods demonstrated similar sensitivity for earlier detection of invisible cracks. Importantly, employing a wideband probe signal with the DEMON approach speeds up and simplifies testing since it eliminates the need to conduct tests repeatedly for various harmonic probe frequencies and to adjust the probe frequency.

Keywords: Damage detection, turbine blades, Vibro-Acoustic Structural Health Monitoring, SHM, Detecting of Envelope Modulation on Noise.

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1805 SNR Classification Using Multiple CNNs

Authors: Thinh Ngo, Paul Rad, Brian Kelley

Abstract:

Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: Classification, classifier fusion, CNN, Deep Learning, prediction, SNR.

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1804 Non-destructive Watermelon Ripeness Determination Using Image Processing and Artificial Neural Network (ANN)

Authors: Shah Rizam M. S. B., Farah Yasmin A.R., Ahmad Ihsan M. Y., Shazana K.

Abstract:

Agriculture products are being more demanding in market today. To increase its productivity, automation to produce these products will be very helpful. The purpose of this work is to measure and determine the ripeness and quality of watermelon. The textures on watermelon skin will be captured using digital camera. These images will be filtered using image processing technique. All these information gathered will be trained using ANN to determine the watermelon ripeness accuracy. Initial results showed that the best model has produced percentage accuracy of 86.51%, when measured at 32 hidden units with a balanced percentage rate of training dataset.

Keywords: Artificial Neural Network (ANN), Digital ImageProcessing, YCbCr Colour Space, Watermelon Ripeness.

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1803 Expression of Tissue Plasminogen Activator in Transgenic Tobacco Plants by Signal Peptides Targeting for Delivery to Apoplast, Endoplasmic Reticulum and Cytosol Spaces

Authors: Sadegh Lotfieblisofla, Arash Khodabakhshi

Abstract:

Tissue plasminogen activator (tPA) as a serine protease plays an important role in the fibrinolytic system and the dissolution of fibrin clots in human body. The production of this drug in plants such as tobacco could reduce its production costs. In this study, expression of tPA gene and protein targeting to different plant cell compartments, using various signal peptides has been investigated. For high level of expression, Kozak sequence was used after CaMV35S in the beginning of the gene. In order to design the final construction, Extensin, KDEL (amino acid sequence including Lys-Asp-Glu-Leu) and SP (γ-zein signal peptide coding sequence) were used as leader signals to conduct this protein into apoplast, endoplasmic reticulum and cytosol spaces, respectively. Cloned human tPA gene under the CaMV (Cauliflower mosaic virus) 35S promoter and NOS (Nopaline Synthase) terminator into pBI121 plasmid was transferred into tobacco explants by Agrobacterium tumefaciens strain LBA4404. The presence and copy number of genes in transgenic tobacco was proved by Southern blotting. Enzymatic activity of the rt-PA protein in transgenic plants compared to non-transgenic plants was confirmed by Zymography assay. The presence and amount of rt-PA recombinant protein in plants was estimated by ELISA analysis on crude protein extract of transgenic tobacco using a specific antibody. The yield of recombinant tPA in transgenic tobacco for SP, KDEL, Extensin signals were counted 0.50, 0.68, 0.69 microgram per milligram of total soluble proteins.

Keywords: Recombinant tissue plasminogen activator, plant cell comportment, leader signals, transgenic tobacco.

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1802 GSM-Based Approach for Indoor Localization

Authors: M.Stella, M. Russo, D. Begušić

Abstract:

Ability of accurate and reliable location estimation in indoor environment is the key issue in developing great number of context aware applications and Location Based Services (LBS). Today, the most viable solution for localization is the Received Signal Strength (RSS) fingerprinting based approach using wireless local area network (WLAN). This paper presents two RSS fingerprinting based approaches – first we employ widely used WLAN based positioning as a reference system and then investigate the possibility of using GSM signals for positioning. To compare them, we developed a positioning system in real world environment, where realistic RSS measurements were collected. Multi-Layer Perceptron (MLP) neural network was used as the approximation function that maps RSS fingerprints and locations. Experimental results indicate advantage of WLAN based approach in the sense of lower localization error compared to GSM based approach, but GSM signal coverage by far outreaches WLAN coverage and for some LBS services requiring less precise accuracy our results indicate that GSM positioning can also be a viable solution.

Keywords: Indoor positioning, WLAN, GSM, RSS, location fingerprints, neural network.

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1801 Topological Queries on Graph-structured XML Data: Models and Implementations

Authors: Hongzhi Wang, Jianzhong Li, Jizhou Luo

Abstract:

In many applications, data is in graph structure, which can be naturally represented as graph-structured XML. Existing queries defined on tree-structured and graph-structured XML data mainly focus on subgraph matching, which can not cover all the requirements of querying on graph. In this paper, a new kind of queries, topological query on graph-structured XML is presented. This kind of queries consider not only the structure of subgraph but also the topological relationship between subgraphs. With existing subgraph query processing algorithms, efficient algorithms for topological query processing are designed. Experimental results show the efficiency of implementation algorithms.

Keywords: XML, Graph Structure, Topological query.

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1800 A Trainable Neural Network Ensemble for ECG Beat Classification

Authors: Atena Sajedin, Shokoufeh Zakernejad, Soheil Faridi, Mehrdad Javadi, Reza Ebrahimpour

Abstract:

This paper illustrates the use of a combined neural network model for classification of electrocardiogram (ECG) beats. We present a trainable neural network ensemble approach to develop customized electrocardiogram beat classifier in an effort to further improve the performance of ECG processing and to offer individualized health care. We process a three stage technique for detection of premature ventricular contraction (PVC) from normal beats and other heart diseases. This method includes a denoising, a feature extraction and a classification. At first we investigate the application of stationary wavelet transform (SWT) for noise reduction of the electrocardiogram (ECG) signals. Then feature extraction module extracts 10 ECG morphological features and one timing interval feature. Then a number of multilayer perceptrons (MLPs) neural networks with different topologies are designed. The performance of the different combination methods as well as the efficiency of the whole system is presented. Among them, Stacked Generalization as a proposed trainable combined neural network model possesses the highest recognition rate of around 95%. Therefore, this network proves to be a suitable candidate in ECG signal diagnosis systems. ECG samples attributing to the different ECG beat types were extracted from the MIT-BIH arrhythmia database for the study.

Keywords: ECG beat Classification; Combining Classifiers;Premature Ventricular Contraction (PVC); Multi Layer Perceptrons;Wavelet Transform

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1799 Reverse Engineering of Agricultural Machinery: A Key to Food Sufficiency in Nigeria

Authors: Williams S. Ebhota, Virginia Chika Ebhota, Samuel A. Ilupeju

Abstract:

Agriculture employs about three-quarter of Nigeria's workforce and yet food sufficiency is a challenge in the country. This is largely due to poor and outdated pre-harvest and post-harvest farming practices. The land fallow system is still been practised as fertiliser production in the country is grossly inadequate and expensive. The few available post-harvest processing facilities are faced with ageing and are inefficient. Also, use of modern processing equipment is limited by farmers' lack of fund, adequate capacity to operate and maintain modern farming equipment. This paper, therefore, examines key barriers to agricultural products processing equipment in the country. These barriers include over-dependence on foreign technologies and expertise; poor and inadequate manufacturing infrastructure; and lack of political will by political leaders; lack of funds; and lack of adequate technical skills. This paper, however, sees the increase in the domestic manufacturing of pre-harvest and post-harvest machinery and equipment through reverse engineering approach as a key to food production sufficiency in Nigeria.

Keywords: Agricultural machinery, domestic manufacturing, forward engineering, production reverse engineering, technology.

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1798 Comparison of Processing Conditions for Plasticized PVC and PVB

Authors: Michael Tupý, Jaroslav Císař, Pavel Mokrejš, Dagmar Měřínská, Alice Tesaříková-Svobodová

Abstract:

It is the worldwide problem that the recycled PVB is not recycled and it is wildly stored in landfills. However, PVB has similar chemical properties such as PVC. Moreover, both of these polymers are plasticized. Therefore, the study of thermal properties of plasticized PVC and the recycled PVB obtained by recycling of windshields is carried out. This work has done in order to find nondegradable processing conditions applicable for both polymers. Tested PVC contained 38% of plasticizer diisononyl phthalate (DINP) and PVB was plasticized with 28% of triethylene glycol, bis(2-ethylhexanoate) (3GO). The thermal and thermo-oxidative decomposition of both vinyl polymers are compared by calorimetric analysis and by tensile strength analysis.

Keywords: Poly(vinyl chloride), Poly(vinyl butyral), Recycling, Reprocessing, Thermal analysis, Decomposition.

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1797 SySRA: A System of a Continuous Speech Recognition in Arab Language

Authors: Samir Abdelhamid, Noureddine Bouguechal

Abstract:

We report in this paper the model adopted by our system of continuous speech recognition in Arab language SySRA and the results obtained until now. This system uses the database Arabdic-10 which is a corpus of word for the Arab language and which was manually segmented. Phonetic decoding is represented by an expert system where the knowledge base is translated in the form of production rules. This expert system transforms a vocal signal into a phonetic lattice. The higher level of the system takes care of the recognition of the lattice thus obtained by deferring it in the form of written sentences (orthographical Form). This level contains initially the lexical analyzer which is not other than the module of recognition. We subjected this analyzer to a set of spectrograms obtained by dictating a score of sentences in Arab language. The rate of recognition of these sentences is about 70% which is, to our knowledge, the best result for the recognition of the Arab language. The test set consists of twenty sentences from four speakers not having taken part in the training.

Keywords: Continuous speech recognition, lexical analyzer, phonetic decoding, phonetic lattice, vocal signal.

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1796 Adaptive Filtering of Heart Rate Signals for an Improved Measure of Cardiac Autonomic Control

Authors: Desmond B. Keenan, Paul Grossman

Abstract:

In order to provide accurate heart rate variability indices of sympathetic and parasympathetic activity, the low frequency and high frequency components of an RR heart rate signal must be adequately separated. This is not always possible by just applying spectral analysis, as power from the high and low frequency components often leak into their adjacent bands. Furthermore, without the respiratory spectra it is not obvious that the low frequency component is not another respiratory component, which can appear in the lower band. This paper describes an adaptive filter, which aids the separation of the low frequency sympathetic and high frequency parasympathetic components from an ECG R-R interval signal, enabling the attainment of more accurate heart rate variability measures. The algorithm is applied to simulated signals and heart rate and respiratory signals acquired from an ambulatory monitor incorporating single lead ECG and inductive plethysmography sensors embedded in a garment. The results show an improvement over standard heart rate variability spectral measurements.

Keywords: Heart rate variability, vagal tone, sympathetic, parasympathetic, spectral analysis, adaptive filter.

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1795 Comparison of Compression Ability Using DCT and Fractal Technique on Different Imaging Modalities

Authors: Sumathi Poobal, G. Ravindran

Abstract:

Image compression is one of the most important applications Digital Image Processing. Advanced medical imaging requires storage of large quantities of digitized clinical data. Due to the constrained bandwidth and storage capacity, however, a medical image must be compressed before transmission and storage. There are two types of compression methods, lossless and lossy. In Lossless compression method the original image is retrieved without any distortion. In lossy compression method, the reconstructed images contain some distortion. Direct Cosine Transform (DCT) and Fractal Image Compression (FIC) are types of lossy compression methods. This work shows that lossy compression methods can be chosen for medical image compression without significant degradation of the image quality. In this work DCT and Fractal Compression using Partitioned Iterated Function Systems (PIFS) are applied on different modalities of images like CT Scan, Ultrasound, Angiogram, X-ray and mammogram. Approximately 20 images are considered in each modality and the average values of compression ratio and Peak Signal to Noise Ratio (PSNR) are computed and studied. The quality of the reconstructed image is arrived by the PSNR values. Based on the results it can be concluded that the DCT has higher PSNR values and FIC has higher compression ratio. Hence in medical image compression, DCT can be used wherever picture quality is preferred and FIC is used wherever compression of images for storage and transmission is the priority, without loosing picture quality diagnostically.

Keywords: DCT, FIC, PIFS, PSNR.

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1794 Are Economic Crises and Government Changes Related? A Descriptive Statistic Analysis

Authors: Şakir Görmüş, Ali Kabasakal

Abstract:

The main purpose of this study is to provide a detailed statistical overview of the time and regional distribution, relative timing occurrence of economic crises and government changes in 51 economies over the 1990–2007 periods. At the same time, the predictive power of the economic crises on set government changes will be examined using “signal approach". The result showed that the percentage of government changes is highest in transition economies (86 percent of observations) and lowest in Latin American economies (39 percent of observations). The percentages of government changes are same in both developed and developing countries (43 percent of observations). However, average crises per year (frequency of crises) are higher (lower) in developing (developed) countries than developed (developing) countries. Also, the predictive power of economic crises about the onset of a government change is highest in Transition economies (81 percent) and lowest in Latin American countries (30 percent). The predictive power of economic crises in developing countries (43 percent) is lower than developed countries (55 percent).

Keywords: Economic crises, Government Changes, PoliticalEconomy, Signal Approach.

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1793 Analysis of Control by Flattening of the Welded Tubes

Authors: Hannachi Med Tahar, H. Djebaili, B. Daheche

Abstract:

In this approach, we have tried to describe the flattening of welded tubes, and its experimental application. The test is carried out at the (National product processing company dishes and tubes production). Usually, the final products (tubes) undergo a series of non-destructive inspection online and offline welding, and obviously destructive mechanical testing (bending, flattening, flaring, etc.). For this and for the purpose of implementing the flattening test, which applies to the processing of round tubes in other forms, it took four sections of welded tubes draft (before stretching hot) and welded tubes finished (after drawing hot and annealing), it was also noted the report 'health' flattened tubes must not show or crack or tear. The test is considered poor if it reveals a lack of ductility of the metal.

Keywords: Flattening, destructive testing, tube drafts, finished tube, Castem 2001.

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1792 Motor Imaginary Signal Classification Using Adaptive Recursive Bandpass Filter and Adaptive Autoregressive Models for Brain Machine Interface Designs

Authors: Vickneswaran Jeyabalan, Andrews Samraj, Loo Chu Kiong

Abstract:

The noteworthy point in the advancement of Brain Machine Interface (BMI) research is the ability to accurately extract features of the brain signals and to classify them into targeted control action with the easiest procedures since the expected beneficiaries are of disabled. In this paper, a new feature extraction method using the combination of adaptive band pass filters and adaptive autoregressive (AAR) modelling is proposed and applied to the classification of right and left motor imagery signals extracted from the brain. The introduction of the adaptive bandpass filter improves the characterization process of the autocorrelation functions of the AAR models, as it enhances and strengthens the EEG signal, which is noisy and stochastic in nature. The experimental results on the Graz BCI data set have shown that by implementing the proposed feature extraction method, a LDA and SVM classifier outperforms other AAR approaches of the BCI 2003 competition in terms of the mutual information, the competition criterion, or misclassification rate.

Keywords: Adaptive autoregressive, adaptive bandpass filter, brain machine Interface, EEG, motor imaginary.

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1791 A Novel Web Metric for the Evaluation of Internet Trends

Authors: Radek Malinský, Ivan Jelínek

Abstract:

Web 2.0 (social networking, blogging and online forums) can serve as a data source for social science research because it contains vast amount of information from many different users. The volume of that information has been growing at a very high rate and becoming a network of heterogeneous data; this makes things difficult to find and is therefore not almost useful. We have proposed a novel theoretical model for gathering and processing data from Web 2.0, which would reflect semantic content of web pages in better way. This article deals with the analysis part of the model and its usage for content analysis of blogs. The introductory part of the article describes methodology for the gathering and processing data from blogs. The next part of the article is focused on the evaluation and content analysis of blogs, which write about specific trend.

Keywords: Blog, Sentiment Analysis, Web 2.0, Webometrics

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1790 IMDC: An Image-Mapped Data Clustering Technique for Large Datasets

Authors: Faruq A. Al-Omari, Nabeel I. Al-Fayoumi

Abstract:

In this paper, we present a new algorithm for clustering data in large datasets using image processing approaches. First the dataset is mapped into a binary image plane. The synthesized image is then processed utilizing efficient image processing techniques to cluster the data in the dataset. Henceforth, the algorithm avoids exhaustive search to identify clusters. The algorithm considers only a small set of the data that contains critical boundary information sufficient to identify contained clusters. Compared to available data clustering techniques, the proposed algorithm produces similar quality results and outperforms them in execution time and storage requirements.

Keywords: Data clustering, Data mining, Image-mapping, Pattern discovery, Predictive analysis.

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1789 Optimized Data Fusion in an Intelligent Integrated GPS/INS System Using Genetic Algorithm

Authors: Ali Asadian, Behzad Moshiri, Ali Khaki Sedigh, Caro Lucas

Abstract:

Most integrated inertial navigation systems (INS) and global positioning systems (GPS) have been implemented using the Kalman filtering technique with its drawbacks related to the need for predefined INS error model and observability of at least four satellites. Most recently, a method using a hybrid-adaptive network based fuzzy inference system (ANFIS) has been proposed which is trained during the availability of GPS signal to map the error between the GPS and the INS. Then it will be used to predict the error of the INS position components during GPS signal blockage. This paper introduces a genetic optimization algorithm that is used to update the ANFIS parameters with respect to the INS/GPS error function used as the objective function to be minimized. The results demonstrate the advantages of the genetically optimized ANFIS for INS/GPS integration in comparison with conventional ANFIS specially in the cases of satellites- outages. Coping with this problem plays an important role in assessment of the fusion approach in land navigation.

Keywords: Adaptive Network based Fuzzy Inference System (ANFIS), Genetic optimization, Global Positioning System (GPS), Inertial Navigation System (INS).

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1788 Reduced Dynamic Time Warping for Handwriting Recognition Based on Multidimensional Time Series of a Novel Pen Device

Authors: Muzaffar Bashir, Jürgen Kempf

Abstract:

The purpose of this paper is to present a Dynamic Time Warping technique which reduces significantly the data processing time and memory size of multi-dimensional time series sampled by the biometric smart pen device BiSP. The acquisition device is a novel ballpoint pen equipped with a diversity of sensors for monitoring the kinematics and dynamics of handwriting movement. The DTW algorithm has been applied for time series analysis of five different sensor channels providing pressure, acceleration and tilt data of the pen generated during handwriting on a paper pad. But the standard DTW has processing time and memory space problems which limit its practical use for online handwriting recognition. To face with this problem the DTW has been applied to the sum of the five sensor signals after an adequate down-sampling of the data. Preliminary results have shown that processing time and memory size could significantly be reduced without deterioration of performance in single character and word recognition. Further excellent accuracy in recognition was achieved which is mainly due to the reduced dynamic time warping RDTW technique and a novel pen device BiSP.

Keywords: Biometric character recognition, biometric person authentication, biometric smart pen BiSP, dynamic time warping DTW, online-handwriting recognition, multidimensional time series.

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1787 Comparing the Durability of Saudi Silica Sands for Use in Foundry Processing

Authors: Mahdi Alsagour, Sam Ramrattan

Abstract:

This paper was developed to investigate two types of sands from the Kingdom of Saudi Arabia (KSA) for potential use in the global metal casting industry. Four types of sands were selected for study, two of the sand systems investigated are natural sands from the KSA. The third sand sample is a heat processed synthetic sand and the last sample is commercially available US silica sand that is used as a control in the study. The purpose of this study is to define the durability of the four sand systems selected for foundry usage. Additionally, chemical analysis of the sand systems is presented before and after elevated temperature exposure. Results show that Saudi silica sands are durable and can be used in foundry processing.

Keywords: Alternative molding media, foundry sand, reclamation, silica sand, specialty sand.

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1786 Pre-Deflection Routing with Control Packet Signal Scheme in Optical Burst Switch Networks

Authors: Jaipal Bisht, Aditya Goel

Abstract:

Optical Burst Switching (OBS) is a promising technology for the future generation Internet. Control architecture and Contention resolution are the main issues faced by the Optical Burst Switching networks. In this paper we are only taking care of the Contention problem and to overcome this issue we propose Pre-Deflection Routing with Control Packet Signal Scheme for Contention Resolution in Optical Burst Switch Networks. In this paper Pre-deflection routing approach has been proposed in which routing is carried out in two ways, Shortest Path First (SPF) and Least Hop First (LHF) Routing to forward the clusters and canoes respectively. Hereafter Burst Offset Time Control Algorithm has been proposed where a forward control packet (FCP) collects the congestion price and contention price along its paths. Thereafter a reverse-direction control packet (RCP) sent by destination node which delivers the information of FCP to the source node, and source node uses this information to revise its offset time and burst length.

Keywords: Contention Resolution, FCP, OBS, Offset Time, PST, RCP.

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1785 High Level Synthesis of Kahn Process Networks(KPN) for Streaming Applications

Authors: Attiya Mahmood, Syed Ali Abbas, Shoab A. Khan

Abstract:

Streaming Applications usually run in parallel or in series that incrementally transform a stream of input data. It poses a design challenge to break such an application into distinguishable blocks and then to map them into independent hardware processing elements. For this, there is required a generic controller that automatically maps such a stream of data into independent processing elements without any dependencies and manual considerations. In this paper, Kahn Process Networks (KPN) for such streaming applications is designed and developed that will be mapped on MPSoC. This is designed in such a way that there is a generic Cbased compiler that will take the mapping specifications as an input from the user and then it will automate these design constraints and automatically generate the synthesized RTL optimized code for specified application.

Keywords: KPN, DFG, FPGA

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1784 Influence of Some Technological Parameters on the Content of Voids in Composite during On-Line Consolidation with Filament Winding Technology

Authors: M. Stefanovska, B. Samakoski, S. Risteska, G. Maneski

Abstract:

In this study was performed in situ consolidation of polypropylene matrix/glass reinforced roving by combining heating systems and roll pressing. The commingled roving during hoop winding was winded on a cylindrical mandrel. The work also presents the advances made in the processing of these materials into composites by conventional technique filament winding. Experimental studies were performed with changing parameters – temperature, pressure and speed. Finally, it describes the investigation of the optimal processing conditions that maximize the mechanical properties of the composites. These properties are good enough for composites to be used as engineering materials in many structural applications.

Keywords: Commingled fiber, consolidation heat, filament winding, voids.

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1783 Classification of Discharges Initiated by Liquid Droplet on Insulation Material under AC Voltages Adopting UHF Technique

Authors: R. Sarathi, G. Nagesh, K. Vasudevan

Abstract:

In the present work, an attempt has been made to understand the feasibility of using UHF technique for identification of any corona discharges/ arcing in insulating material due to water droplets. The sensors of broadband type are useful for identification of such discharges. It is realised that arcing initiated by liquid droplet radiates UHF signals in the entire bandwidth up to 2 GHz. The frequency content of the UHF signal generated due to corona/arcing is not much varied in epoxy nanocomposites with different weight percentage of clay content. The exfoliated/intercalated properties were analysed through TEM studies. It is realized that corona initiated discharges are of intermittent process. The hydrophobicity of the material characterized through contact angle measurement. It is realized that low Wt % of nanoclay content in epoxy resin reduces the surface carbonization due to arcing/corona discharges. The results of the study with gamma irradiated specimen indicates that contact angle, discharge inception time and evaporation time of the liquid are much lower than the virgin epoxy nanocomposite material.

Keywords: Arcing, Corona, epoxy resin, insulation, nanocomposites, UHF signal, water droplet.

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1782 Vehicle Velocity Estimation for Traffic Surveillance System

Authors: H. A. Rahim, U. U. Sheikh, R. B. Ahmad, A. S. M. Zain

Abstract:

This paper describes an algorithm to estimate realtime vehicle velocity using image processing technique from the known camera calibration parameters. The presented algorithm involves several main steps. First, the moving object is extracted by utilizing frame differencing technique. Second, the object tracking method is applied and the speed is estimated based on the displacement of the object-s centroid. Several assumptions are listed to simplify the transformation of 2D images from 3D real-world images. The results obtained from the experiment have been compared to the estimated ground truth. From this experiment, it exhibits that the proposed algorithm has achieved the velocity accuracy estimation of about ± 1.7 km/h.

Keywords: camera calibration, object tracking, velocity estimation, video image processing

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1781 Evaluating 8D Reports Using Text-Mining

Authors: Benjamin Kuester, Bjoern Eilert, Malte Stonis, Ludger Overmeyer

Abstract:

Increasing quality requirements make reliable and effective quality management indispensable. This includes the complaint handling in which the 8D method is widely used. The 8D report as a written documentation of the 8D method is one of the key quality documents as it internally secures the quality standards and acts as a communication medium to the customer. In practice, however, the 8D report is mostly faulty and of poor quality. There is no quality control of 8D reports today. This paper describes the use of natural language processing for the automated evaluation of 8D reports. Based on semantic analysis and text-mining algorithms the presented system is able to uncover content and formal quality deficiencies and thus increases the quality of the complaint processing in the long term.

Keywords: 8D report, complaint management, evaluation system, text-mining.

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1780 A Novel RLS Based Adaptive Filtering Method for Speech Enhancement

Authors: Pogula Rakesh, T. Kishore Kumar

Abstract:

Speech enhancement is a long standing problem with numerous applications like teleconferencing, VoIP, hearing aids and speech recognition. The motivation behind this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. Real-time adaptive filtering algorithms seem to be the best candidate among all categories of the speech enhancement methods. In this paper, we propose a speech enhancement method based on Recursive Least Squares (RLS) adaptive filter of speech signals. Experiments were performed on noisy data which was prepared by adding AWGN, Babble and Pink noise to clean speech samples at -5dB, 0dB, 5dB and 10dB SNR levels. We then compare the noise cancellation performance of proposed RLS algorithm with existing NLMS algorithm in terms of Mean Squared Error (MSE), Signal to Noise ratio (SNR) and SNR Loss. Based on the performance evaluation, the proposed RLS algorithm was found to be a better optimal noise cancellation technique for speech signals.

Keywords: Adaptive filter, Adaptive Noise Canceller, Mean Squared Error, Noise reduction, NLMS, RLS, SNR, SNR Loss.

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1779 Implementing a Database from a Requirement Specification

Authors: M. Omer, D. Wilson

Abstract:

Creating a database scheme is essentially a manual process. From a requirement specification the information contained within has to be analyzed and reduced into a set of tables, attributes and relationships. This is a time consuming process that has to go through several stages before an acceptable database schema is achieved. The purpose of this paper is to implement a Natural Language Processing (NLP) based tool to produce a relational database from a requirement specification. The Stanford CoreNLP version 3.3.1 and the Java programming were used to implement the proposed model. The outcome of this study indicates that a first draft of a relational database schema can be extracted from a requirement specification by using NLP tools and techniques with minimum user intervention. Therefore this method is a step forward in finding a solution that requires little or no user intervention.

Keywords: Information Extraction, Natural Language Processing, Relation Extraction.

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1778 Enhancement of Mechanical and Dissolution Properties of a Cast Magnesium Alloy via Equal Angular Channel Processing

Authors: Tim Dunne, Jiaxiang Ren, Lei Zhao, Peng Cheng, Yi Song, Yu Liu, Wenhan Yue, Xiongwen Yang

Abstract:

Two decades of the Shale Revolution has transforming transformed the global energy market, in part by the adaption of multi-stage dissolvable frac plugs. Magnesium has been favored for the bulk of plugs, requiring development of materials to suit specific field requirements. Herein, the mechanical and dissolution results from equal channel angular pressing (ECAP) of two cast dissolvable magnesium alloy are described. ECAP was selected as a route to increase the mechanical properties of two formulations of dissolvable magnesium, as solutionizing failed. In this study, 1” square cross section samples cast Mg alloys formulations containing rare earth were processed at temperatures ranging from 200 to 350 °C, at a rate of 0.005”/s, with a backpressure from 0 to 70 MPa, in a brass, or brass + graphite sheet. Generally, the yield and ultimate tensile strength (UTS) doubled for all. For formulation DM-2, the yield increased from 100 MPa to 250 MPa; UTS from 175 MPa to 325 MPa, but the strain fell from 2 to 1%. Formulation DM-3 yield increased from 75 MPa to 200 MPa, UTS from 150 MPa to 275 MPa, with strain increasing from 1 to 3%. Meanwhile, ECAP has also been found to reduce the dissolution rate significantly. A microstructural analysis showed grain refinement of the alloy and the movement of secondary phases away from the grain boundary. It is believed that reconfiguration of the grain boundary phases increased the mechanical properties and decreased the dissolution rate. ECAP processing of dissolvable high rare earth content magnesium is possible despite the brittleness of the material. ECAP is a possible processing route to increase mechanical properties for dissolvable aluminum alloys that do not extrude.

Keywords: Equal channel angular processing, dissolvable magnesium, frac plug, mechanical properties.

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1777 Paddy/Rice Singulation for Determination of Husking Efficiency and Damage Using Machine Vision

Authors: M. Shaker, S. Minaei, M. H. Khoshtaghaza, A. Banakar, A. Jafari

Abstract:

In this study a system of machine vision and singulation was developed to separate paddy from rice and determine paddy husking and rice breakage percentages. The machine vision system consists of three main components including an imaging chamber, a digital camera, a computer equipped with image processing software. The singulation device consists of a kernel holding surface, a motor with vacuum fan, and a dimmer. For separation of paddy from rice (in the image), it was necessary to set a threshold. Therefore, some images of paddy and rice were sampled and the RGB values of the images were extracted using MATLAB software. Then mean and standard deviation of the data were determined. An Image processing algorithm was developed using MATLAB to determine paddy/rice separation and rice breakage and paddy husking percentages, using blue to red ratio. Tests showed that, a threshold of 0.75 is suitable for separating paddy from rice kernels. Results from the evaluation of the image processing algorithm showed that the accuracies obtained with the algorithm were 98.36% and 91.81% for paddy husking and rice breakage percentage, respectively. Analysis also showed that a suction of 45 mmHg to 50 mmHg yielding 81.3% separation efficiency is appropriate for operation of the kernel singulation system.

Keywords: Computer vision, rice kernel, husking, breakage.

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