Search results for: Fourier transform infrared spectroscopy
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1250

Search results for: Fourier transform infrared spectroscopy

710 Wind Speed Data Analysis using Wavelet Transform

Authors: S. Avdakovic, A. Lukac, A. Nuhanovic, M. Music

Abstract:

Renewable energy systems are becoming a topic of great interest and investment in the world. In recent years wind power generation has experienced a very fast development in the whole world. For planning and successful implementations of good wind power plant projects, wind potential measurements are required. In these projects, of great importance is the effective choice of the micro location for wind potential measurements, installation of the measurement station with the appropriate measuring equipment, its maintenance and analysis of the gained data on wind potential characteristics. In this paper, a wavelet transform has been applied to analyze the wind speed data in the context of insight in the characteristics of the wind and the selection of suitable locations that could be the subject of a wind farm construction. This approach shows that it can be a useful tool in investigation of wind potential.

Keywords: Wind potential, Wind speed data, Wavelettransform.

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709 Analyzing Transformation of 1D-Functions for Frequency Domain based Video Classification

Authors: Kahraman Ayyildiz, Stefan Conrad

Abstract:

In this paper we illuminate a frequency domain based classification method for video scenes. Videos from certain topical areas often contain activities with repeating movements. Sports videos, home improvement videos, or videos showing mechanical motion are some example areas. Assessing main and side frequencies of each repeating movement gives rise to the motion type. We obtain the frequency domain by transforming spatio-temporal motion trajectories. Further on we explain how to compute frequency features for video clips and how to use them for classifying. The focus of the experimental phase is on transforms utilized for our system. By comparing various transforms, experiments show the optimal transform for a motion frequency based approach.

Keywords: action recognition, frequency, transform, motion recognition, repeating movement, video classification

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708 Enhancement of Pulsed Eddy Current Response Based on Power Spectral Density after Continuous Wavelet Transform Decomposition

Authors: A. Benyahia, M. Zergoug, M. Amir, M. Fodil

Abstract:

The main objective of this work is to enhance the Pulsed Eddy Current (PEC) response from the aluminum structure using signal processing. Cracks and metal loss in different structures cause changes in PEC response measurements. In this paper, time-frequency analysis is used to represent PEC response, which generates a large quantity of data and reduce the noise due to measurement. Power Spectral Density (PSD) after Wavelet Decomposition (PSD-WD) is proposed for defect detection. The experimental results demonstrate that the cracks in the surface can be extracted satisfactorily by the proposed methods. The validity of the proposed method is discussed.

Keywords: NDT, pulsed eddy current, continuous wavelet transform, Mexican hat wavelet mother, defect detection, power spectral density.

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707 Identifying Dynamic Structural Parameters of Soil-Structure System Based on Data Recorded during Strong Earthquakes

Authors: Vahidreza Mahmoudabadi, Omid Bahar, Mohammad Kazem Jafari

Abstract:

In many applied engineering problems, structural analysis is usually conducted by assuming a rigid bed, while imposing the effect of structure bed flexibility can affect significantly on the structure response. This article focuses on investigation and evaluation of the effects arising from considering a soil-structure system in evaluation of dynamic characteristics of a steel structure with respect to elastic and inelastic behaviors. The recorded structure acceleration during Taiwan’s strong Chi-Chi earthquake on different floors of the structure was our evaluation criteria. The respective structure is an eight-story steel bending frame structure designed using a displacement-based direct method assuring weak beam - strong column function. The results indicated that different identification methods i.e. reverse Fourier transform or transfer functions, is capable to determine some of the dynamic parameters of the structure precisely, rather than evaluating all of them at once (mode frequencies, mode shapes, structure damping, structure rigidity, etc.). Response evaluation based on the input and output data elucidated that the structure first mode is not significantly affected, even considering the soil-structure interaction effect, but the upper modes have been changed. Also, it was found that the response transfer function of the different stories, in which plastic hinges have occurred in the structure components, provides similar results.

Keywords: System identification, dynamic characteristics, soil-structure system, bending steel frame structure, displacement-based design.

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706 Dimension Free Rigid Point Set Registration in Linear Time

Authors: Jianqin Qu

Abstract:

This paper proposes a rigid point set matching algorithm in arbitrary dimensions based on the idea of symmetric covariant function. A group of functions of the points in the set are formulated using rigid invariants. Each of these functions computes a pair of correspondence from the given point set. Then the computed correspondences are used to recover the unknown rigid transform parameters. Each computed point can be geometrically interpreted as the weighted mean center of the point set. The algorithm is compact, fast, and dimension free without any optimization process. It either computes the desired transform for noiseless data in linear time, or fails quickly in exceptional cases. Experimental results for synthetic data and 2D/3D real data are provided, which demonstrate potential applications of the algorithm to a wide range of problems.

Keywords: Covariant point, point matching, dimension free, rigid registration.

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705 Target Detection using Adaptive Progressive Thresholding Based Shifted Phase-Encoded Fringe-Adjusted Joint Transform Correlator

Authors: Inder K. Purohit, M. Nazrul Islam, K. Vijayan Asari, Mohammad A. Karim

Abstract:

A new target detection technique is presented in this paper for the identification of small boats in coastal surveillance. The proposed technique employs an adaptive progressive thresholding (APT) scheme to first process the given input scene to separate any objects present in the scene from the background. The preprocessing step results in an image having only the foreground objects, such as boats, trees and other cluttered regions, and hence reduces the search region for the correlation step significantly. The processed image is then fed to the shifted phase-encoded fringe-adjusted joint transform correlator (SPFJTC) technique which produces single and delta-like correlation peak for a potential target present in the input scene. A post-processing step involves using a peak-to-clutter ratio (PCR) to determine whether the boat in the input scene is authorized or unauthorized. Simulation results are presented to show that the proposed technique can successfully determine the presence of an authorized boat and identify any intruding boat present in the given input scene.

Keywords: Adaptive progressive thresholding, fringe adjusted filters, image segmentation, joint transform correlation, synthetic discriminant function

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704 Improved Small-Signal Characteristics of Infrared 850 nm Top-Emitting Vertical-Cavity Lasers

Authors: Ahmad Al-Omari, Osama Khreis, Ahmad M. K. Dagamseh, Abdullah Ababneh, Kevin Lear

Abstract:

High-speed infrared vertical-cavity surface-emitting laser diodes (VCSELs) with Cu-plated heat sinks were fabricated and tested. VCSELs with 10 mm aperture diameter and 4 mm of electroplated copper demonstrated a -3dB modulation bandwidth (f-3dB) of 14 GHz and a resonance frequency (fR) of 9.5 GHz at a bias current density (Jbias) of only 4.3 kA/cm2, which corresponds to an improved f-3dB2/Jbias ratio of 44 GHz2/kA/cm2. At higher and lower bias current densities, the f-3dB2/ Jbias ratio decreased to about 30 GHz2/kA/cm2 and 18 GHz2/kA/cm2, respectively. Examination of the analogue modulation response demonstrated that the presented VCSELs displayed a steady f-3dB/ fR ratio of 1.41±10% over the whole range of the bias current (1.3Ith to 6.2Ith). The devices also demonstrated a maximum modulation bandwidth (f-3dB max) of more than 16 GHz at a bias current less than the industrial bias current standard for reliability by 25%.

Keywords: Current density, High-speed VCSELs, Modulation bandwidth, Small-Signal Characteristics, Thermal impedance, Vertical-cavity surface-emitting lasers.

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703 Synthesis of SnO Novel Cabbage Nanostructure and Its Electrochemical Property as an Anode Material for Lithium Ion Battery

Authors: Yongkui Cui, Fengping Wang, Hailai Zhao, Muhammad Zubair Iqbal, Ziya Wang, Yan Li, Pengpeng L. V.

Abstract:

The novel 3D SnO cabbages self-assembled by nanosheets were successfully synthesized via template-free hydrothermal growth method under facile conditions. The XRD results manifest that the as-prepared SnO is tetragonal phase. The TEM and HRTEM results show that the cabbage nanosheets are polycrystalline structure consisted of considerable single-crystalline nanoparticles. Two typical Raman modes A1g=210 and Eg=112 cm-1 of SnO are observed by Raman spectroscopy. Moreover, galvanostatic cycling tests has been performed using the SnO cabbages as anode material of lithium ion battery and the electrochemical results suggest that the synthesized SnO cabbage structures are a promising anode material for lithium ion batteries.

Keywords: Hydrothermal process, lithium ion battery, Raman spectroscopy, stannous oxide.

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702 Object Recognition Approach Based on Generalized Hough Transform and Color Distribution Serving in Generating Arabic Sentences

Authors: Nada Farhani, Naim Terbeh, Mounir Zrigui

Abstract:

The recognition of the objects contained in images has always presented a challenge in the field of research because of several difficulties that the researcher can envisage because of the variability of shape, position, contrast of objects, etc. In this paper, we will be interested in the recognition of objects. The classical Hough Transform (HT) presented a tool for detecting straight line segments in images. The technique of HT has been generalized (GHT) for the detection of arbitrary forms. With GHT, the forms sought are not necessarily defined analytically but rather by a particular silhouette. For more precision, we proposed to combine the results from the GHT with the results from a calculation of similarity between the histograms and the spatiograms of the images. The main purpose of our work is to use the concepts from recognition to generate sentences in Arabic that summarize the content of the image.

Keywords: Recognition of shape, generalized hough transformation, histogram, Spatiogram, learning.

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701 Computation of Probability Coefficients using Binary Decision Diagram and their Application in Test Vector Generation

Authors: Ashutosh Kumar Singh, Anand Mohan

Abstract:

This paper deals with efficient computation of probability coefficients which offers computational simplicity as compared to spectral coefficients. It eliminates the need of inner product evaluations in determination of signature of a combinational circuit realizing given Boolean function. The method for computation of probability coefficients using transform matrix, fast transform method and using BDD is given. Theoretical relations for achievable computational advantage in terms of required additions in computing all 2n probability coefficients of n variable function have been developed. It is shown that for n ≥ 5, only 50% additions are needed to compute all probability coefficients as compared to spectral coefficients. The fault detection techniques based on spectral signature can be used with probability signature also to offer computational advantage.

Keywords: Binary Decision Diagrams, Spectral Coefficients, Fault detection

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700 Optimal Image Compression Based on Sign and Magnitude Coding of Wavelet Coefficients

Authors: Mbainaibeye Jérôme, Noureddine Ellouze

Abstract:

Wavelet transforms is a very powerful tools for image compression. One of its advantage is the provision of both spatial and frequency localization of image energy. However, wavelet transform coefficients are defined by both a magnitude and sign. While algorithms exist for efficiently coding the magnitude of the transform coefficients, they are not efficient for the coding of their sign. It is generally assumed that there is no compression gain to be obtained from the coding of the sign. Only recently have some authors begun to investigate the sign of wavelet coefficients in image coding. Some authors have assumed that the sign information bit of wavelet coefficients may be encoded with the estimated probability of 0.5; the same assumption concerns the refinement information bit. In this paper, we propose a new method for Separate Sign Coding (SSC) of wavelet image coefficients. The sign and the magnitude of wavelet image coefficients are examined to obtain their online probabilities. We use the scalar quantization in which the information of the wavelet coefficient to belong to the lower or to the upper sub-interval in the uncertainly interval is also examined. We show that the sign information and the refinement information may be encoded by the probability of approximately 0.5 only after about five bit planes. Two maps are separately entropy encoded: the sign map and the magnitude map. The refinement information of the wavelet coefficient to belong to the lower or to the upper sub-interval in the uncertainly interval is also entropy encoded. An algorithm is developed and simulations are performed on three standard images in grey scale: Lena, Barbara and Cameraman. Five scales are performed using the biorthogonal wavelet transform 9/7 filter bank. The obtained results are compared to JPEG2000 standard in terms of peak signal to noise ration (PSNR) for the three images and in terms of subjective quality (visual quality). It is shown that the proposed method outperforms the JPEG2000. The proposed method is also compared to other codec in the literature. It is shown that the proposed method is very successful and shows its performance in term of PSNR.

Keywords: Image compression, wavelet transform, sign coding, magnitude coding.

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699 Scintigraphic Image Coding of Region of Interest Based On SPIHT Algorithm Using Global Thresholding and Huffman Coding

Authors: A. Seddiki, M. Djebbouri, D. Guerchi

Abstract:

Medical imaging produces human body pictures in digital form. Since these imaging techniques produce prohibitive amounts of data, compression is necessary for storage and communication purposes. Many current compression schemes provide a very high compression rate but with considerable loss of quality. On the other hand, in some areas in medicine, it may be sufficient to maintain high image quality only in region of interest (ROI). This paper discusses a contribution to the lossless compression in the region of interest of Scintigraphic images based on SPIHT algorithm and global transform thresholding using Huffman coding.

Keywords: Global Thresholding Transform, Huffman Coding, Region of Interest, SPIHT Coding, Scintigraphic images.

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698 Low-Temperature Luminescence Spectroscopy of Violet Sr-Al-O:Eu2+ Phosphor Particles

Authors: Keiji Komatsu, Hayato Maruyama, Ariyuki Kato, Atsushi Nakamura, Shigeo Ohshio, Hiroki Akasaka, Hidetoshi Saitoh

Abstract:

Violet Sr–Al–O:Eu2+ phosphor particles were synthesized from a metal–ethylenediaminetetraacetic acid (EDTA) solution of Sr, Al, Eu, and particulate alumina via spray drying and sintering in a reducing atmosphere. The crystal structures and emission properties at 85–300 K were investigated. The composition of the violet Sr–Al–O:Eu2+ phosphor particles was determined from various Sr–Al–O:Eu2+ phosphors by their emission properties’ dependence on temperature. The highly crystalline SrAl12O19:Eu2+ emission phases were confirmed by their crystallite sizes and the activation energies for the 4f5d–8S7/2 transition of the Eu2+ ion. These results showed that the material identification for the violet Sr–Al–O:Eu2+ phosphor was accomplished by the low-temperature luminescence measurements.

Keywords: Low temperature luminescence spectroscopy, Material Identification, Strontium aluminates phosphor.

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697 Optical Characterization of a Microwave Plasma Torch for Hydrogen Production

Authors: Babajide O. Ogungbesan, Rajneesh Kumar, Mohamed Sassi

Abstract:

Hydrogen sulfide (H2S) is a very toxic gas that is produced in very large quantities in the oil and gas industry. It cannot be flared to the atmosphere and Claus process based gas plants are used to recover the sulfur and convert the hydrogen to water. In this paper, we present optical characterization of an atmospheric pressure microwave plasma torch for H2S dissociation into hydrogen and sulfur. The torch is operated at 2.45 GHz with power up to 2 kW. Three different gases can simultaneously be injected in the plasma torch. Visual imaging and optical emission spectroscopy are used to characterize the plasma for varying gas flow rates and microwave power. The plasma length, emission spectra and temperature are presented. The obtained experimental results validate our earlier published simulation results of plasma torch.

Keywords: Atmospheric pressure microwave plasma, gas dissociation, optical emission spectroscopy.

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696 Extracting Tongue Shape Dynamics from Magnetic Resonance Image Sequences

Authors: María S. Avila-García, John N. Carter, Robert I. Damper

Abstract:

An important problem in speech research is the automatic extraction of information about the shape and dimensions of the vocal tract during real-time speech production. We have previously developed Southampton dynamic magnetic resonance imaging (SDMRI) as an approach to the solution of this problem.However, the SDMRI images are very noisy so that shape extraction is a major challenge. In this paper, we address the problem of tongue shape extraction, which poses difficulties because this is a highly deforming non-parametric shape. We show that combining active shape models with the dynamic Hough transform allows the tongue shape to be reliably tracked in the image sequence.

Keywords: Vocal tract imaging, speech production, active shapemodels, dynamic Hough transform, object tracking.

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695 The Study on the Stationarity of Housing Price-to-Rent and Housing Price-to-Income Ratios in China

Authors: Wen-Chi Liu

Abstract:

This paper aims to examine whether a bubble is present in the housing market of China. Thus, we use the housing  price-to-income ratios and housing price-to-rent ratios of 35 cities from 1998 to 2010. The methods of the panel KSS unit root test with a  Fourier function and the SPSM process are likewise used. The panel  KSS unit root test with a Fourier function considers the problem of  non-linearity and structural changes, and the SPSM process can avoid  the stationary time series from dominating the result-generated bias.  Through a rigorous empirical study, we determine that the housing  price-to-income ratios are stationary in 34 of the 35 cities in China.  Only Xining is non-stationary. The housing price-to-rent ratios are  stationary in 32 of the 35 cities in China. Chengdu, Fuzhou, and  Zhengzhou are non-stationary. Overall, the housing bubbles are not a  serious problem in China at the time.

 

Keywords: Housing Price-to-Income Ratio, Housing Price-to-Rent Ratio, Housing Bubbles, Panel Unit-Root Test.

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694 Visualization and Indexing of Spectral Databases

Authors: Tibor Kulcsar, Gabor Sarossy, Gabor Bereznai, Robert Auer, Janos Abonyi

Abstract:

On-line (near infrared) spectroscopy is widely used to support the operation of complex process systems. Information extracted from spectral database can be used to estimate unmeasured product properties and monitor the operation of the process. These techniques are based on looking for similar spectra by nearest neighborhood algorithms and distance based searching methods. Search for nearest neighbors in the spectral space is an NP-hard problem, the computational complexity increases by the number of points in the discrete spectrum and the number of samples in the database. To reduce the calculation time some kind of indexing could be used. The main idea presented in this paper is to combine indexing and visualization techniques to reduce the computational requirement of estimation algorithms by providing a two dimensional indexing that can also be used to visualize the structure of the spectral database. This 2D visualization of spectral database does not only support application of distance and similarity based techniques but enables the utilization of advanced clustering and prediction algorithms based on the Delaunay tessellation of the mapped spectral space. This means the prediction has not to use the high dimension space but can be based on the mapped space too. The results illustrate that the proposed method is able to segment (cluster) spectral databases and detect outliers that are not suitable for instance based learning algorithms.

Keywords: indexing high dimensional databases, dimensional reduction, clustering, similarity, k-nn algorithm.

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693 Complex Wavelet Transform Based Image Denoising and Zooming Under the LMMSE Framework

Authors: T. P. Athira, Gibin Chacko George

Abstract:

This paper proposes a dual tree complex wavelet transform (DT-CWT) based directional interpolation scheme for noisy images. The problems of denoising and interpolation are modelled as to estimate the noiseless and missing samples under the same framework of optimal estimation. Initially, DT-CWT is used to decompose an input low-resolution noisy image into low and high frequency subbands. The high-frequency subband images are interpolated by linear minimum mean square estimation (LMMSE) based interpolation, which preserves the edges of the interpolated images. For each noisy LR image sample, we compute multiple estimates of it along different directions and then fuse those directional estimates for a more accurate denoised LR image. The estimation parameters calculated in the denoising processing can be readily used to interpolate the missing samples. The inverse DT-CWT is applied on the denoised input and interpolated high frequency subband images to obtain the high resolution image. Compared with the conventional schemes that perform denoising and interpolation in tandem, the proposed DT-CWT based noisy image interpolation method can reduce many noise-caused interpolation artifacts and preserve well the image edge structures. The visual and quantitative results show that the proposed technique outperforms many of the existing denoising and interpolation methods.

Keywords: Dual-tree complex wavelet transform (DT-CWT), denoising, interpolation, optimal estimation, super resolution.

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692 Detecting Cavitation in a Vertical Sea water Centrifugal Lift Pump Related to Iran Oil Industry Cooling Water Circulation System

Authors: Omid A. Zargar

Abstract:

Cavitation is one of the most well-known process faults that may occur in different industrial equipment especially centrifugal pumps. Cavitation also may happen in water pumps and turbines. Sometimes cavitation has been severe enough to wear holes in the impeller and damage the vanes to such a degree that the impeller becomes very ineffective. More commonly, the pump efficiency will decrease significantly during cavitation and continue to decrease as damage to the impeller increases. Typically, when cavitation occurs, an audible sound similar to ‘marbles’ or ‘crackling’ is reported to be emitted from the pump. In this paper, the most effective monitoring items and techniques in detecting cavitation discussed in details. Besides, some successful solutions for solving this problem for sea water vertical Centrifugal lift Pump discussed through a case history related to Iran oil industry. Furthermore, balance line modification, strainer choking and random resonance in sea water pumps discussed. In addition, a new Method for diagnosing mechanical conditions of sea water vertical Centrifugal lift Pumps introduced. This method involves disaggregating bus current by device into disaggregated currents having correspondences with operating currents in response to measured bus current. Moreover, some new patents and innovations in mechanical sea water pumping and cooling systems discussed in this paper.

Keywords: Cavitation, Vibration Analysis, Centrifugal Pump, Vertical Pump, Sea Water Pump, Balance Line, Strainer, Time Wave Form (TWF), Fast Fourier Transform (FFT)

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691 ANFIS Approach for Locating Faults in Underground Cables

Authors: Magdy B. Eteiba, Wael Ismael Wahba, Shimaa Barakat

Abstract:

This paper presents a fault identification, classification and fault location estimation method based on Discrete Wavelet Transform and Adaptive Network Fuzzy Inference System (ANFIS) for medium voltage cable in the distribution system.

Different faults and locations are simulated by ATP/EMTP, and then certain selected features of the wavelet transformed signals are used as an input for a training process on the ANFIS. Then an accurate fault classifier and locator algorithm was designed, trained and tested using current samples only. The results obtained from ANFIS output were compared with the real output. From the results, it was found that the percentage error between ANFIS output and real output is less than three percent. Hence, it can be concluded that the proposed technique is able to offer high accuracy in both of the fault classification and fault location.

Keywords: ANFIS, Fault location, Underground Cable, Wavelet Transform.

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690 A Motion Dictionary to Real-Time Recognition of Sign Language Alphabet Using Dynamic Time Warping and Artificial Neural Network

Authors: Marcio Leal, Marta Villamil

Abstract:

Computacional recognition of sign languages aims to allow a greater social and digital inclusion of deaf people through interpretation of their language by computer. This article presents a model of recognition of two of global parameters from sign languages; hand configurations and hand movements. Hand motion is captured through an infrared technology and its joints are built into a virtual three-dimensional space. A Multilayer Perceptron Neural Network (MLP) was used to classify hand configurations and Dynamic Time Warping (DWT) recognizes hand motion. Beyond of the method of sign recognition, we provide a dataset of hand configurations and motion capture built with help of fluent professionals in sign languages. Despite this technology can be used to translate any sign from any signs dictionary, Brazilian Sign Language (Libras) was used as case study. Finally, the model presented in this paper achieved a recognition rate of 80.4%.

Keywords: Sign language recognition, computer vision, infrared, artificial neural network, dynamic time warping.

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689 An Approach Based on Statistics and Multi-Resolution Representation to Classify Mammograms

Authors: Nebi Gedik

Abstract:

One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).

Keywords: Wave atom transform, statistical features, multi-resolution representation, mammogram.

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688 New Wavelet Indices to Assess Muscle Fatigue during Dynamic Contractions

Authors: González-Izal M., Rodríguez-Carreño I, Mallor-Giménez F, Malanda A, Izquierdo M

Abstract:

The purpose of this study was to evaluate and compare new indices based on the discrete wavelet transform with another spectral parameters proposed in the literature as mean average voltage, median frequency and ratios between spectral moments applied to estimate acute exercise-induced changes in power output, i.e., to assess peripheral muscle fatigue during a dynamic fatiguing protocol. 15 trained subjects performed 5 sets consisting of 10 leg press, with 2 minutes rest between sets. Surface electromyography was recorded from vastus medialis (VM) muscle. Several surface electromyographic parameters were compared to detect peripheral muscle fatigue. These were: mean average voltage (MAV), median spectral frequency (Fmed), Dimitrov spectral index of muscle fatigue (FInsm5), as well as other five parameters obtained from the discrete wavelet transform (DWT) as ratios between different scales. The new wavelet indices achieved the best results in Pearson correlation coefficients with power output changes during acute dynamic contractions. Their regressions were significantly different from MAV and Fmed. On the other hand, they showed the highest robustness in presence of additive white gaussian noise for different signal to noise ratios (SNRs). Therefore, peripheral impairments assessed by sEMG wavelet indices may be a relevant factor involved in the loss of power output after dynamic high-loading fatiguing task.

Keywords: Median Frequency, EMG, wavelet transform, muscle fatigue

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687 A Novel Compression Algorithm for Electrocardiogram Signals based on Wavelet Transform and SPIHT

Authors: Sana Ktata, Kaïs Ouni, Noureddine Ellouze

Abstract:

Electrocardiogram (ECG) data compression algorithm is needed that will reduce the amount of data to be transmitted, stored and analyzed, but without losing the clinical information content. A wavelet ECG data codec based on the Set Partitioning In Hierarchical Trees (SPIHT) compression algorithm is proposed in this paper. The SPIHT algorithm has achieved notable success in still image coding. We modified the algorithm for the one-dimensional (1-D) case and applied it to compression of ECG data. By this compression method, small percent root mean square difference (PRD) and high compression ratio with low implementation complexity are achieved. Experiments on selected records from the MIT-BIH arrhythmia database revealed that the proposed codec is significantly more efficient in compression and in computation than previously proposed ECG compression schemes. Compression ratios of up to 48:1 for ECG signals lead to acceptable results for visual inspection.

Keywords: Discrete Wavelet Transform, ECG compression, SPIHT.

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686 Transform to Succeed: An Empirical Analysis of Digital Transformation in Firms

Authors: Sarah E. Stief, Anne Theresa Eidhoff, Markus Voeth

Abstract:

Despite all progress firms are facing the increasing need to adapt and assimilate digital technologies to transform their business activities in order to pursue business development. By using new digital technologies, firms can implement major business improvements in order to stay competitive and foster new growth potentials. The corresponding phenomenon of digital transformation has received some attention in previous literature in respect to industries such as media and publishing. Nevertheless, there is a lack of understanding of the concept and its organization within firms. With the help of twenty-three in-depth field interviews with German experts responsible for their company’s digital transformation, we examined what digital transformation encompasses, how it is organized and which opportunities and challenges arise within firms. Our results indicate that digital transformation is an inevitable task for all firms, as it bears the potential to comprehensively optimize and reshape established business activities and can thus be seen as a strategy of business development.

Keywords: Business development, digitalization, digital strategies, digital transformation.

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685 Turbine Compressor Vibration Analysis and Rotor Movement Evaluation by Shaft Center Line Method (The Case History Related to Main Turbine Compressor of an Olefin Plant in Iran Oil Industries)

Authors: Omid A. Zargar

Abstract:

Vibration monitoring methods of most critical equipment like main turbine and compressors always plays important role in preventive maintenance and management consideration in big industrial plants. There are a number of traditional methods like monitoring the overall vibration data from Bently Nevada panel and the time wave form (TWF) or fast Fourier transform (FFT) monitoring. Besides, Shaft centerline monitoring method developed too much in recent years. There are a number of arguments both in favor of and against this method between people who work in preventive maintenance and condition monitoring systems (vibration analysts). In this paper basic principal of Turbine compressor vibration analysis and rotor movement evaluation by shaft centerline method discussed in details through a case history. This case history is related to main turbine compressor of an olefin plant in Iran oil industry. In addition, some common mistakes that may occur by vibration analyst during the process discussed in details. It is worthy to know that, these mistakes may one of the reasons that sometimes this method seems to be not effective. Furthermore, recent patent and innovation in shaft position and movement evaluation are discussed in this paper.

Keywords: Shaft centerline position, attitude angle, journal bearing, sleeve bearing, tilting pad, steam turbine, main compressor, multistage compressor, condition monitoring, non-contact probe

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684 Comparison of Fricative Vocal Tract Transfer Functions Derived using Two Different Segmentation Techniques

Authors: K. S. Subari, C. H. Shadle, A. Barney, R. I. Damper

Abstract:

The acoustic and articulatory properties of fricative speech sounds are being studied using magnetic resonance imaging (MRI) and acoustic recordings from a single subject. Area functions were derived from a complete set of axial and coronal MR slices using two different methods: the Mermelstein technique and the Blum transform. Area functions derived from the two techniques were shown to differ significantly in some cases. Such differences will lead to different acoustic predictions and it is important to know which is the more accurate. The vocal tract acoustic transfer function (VTTF) was derived from these area functions for each fricative and compared with measured speech signals for the same fricative and same subject. The VTTFs for /f/ in two vowel contexts and the corresponding acoustic spectra are derived here; the Blum transform appears to show a better match between prediction and measurement than the Mermelstein technique.

Keywords: Area functions, fricatives, vocal tract transferfunction, MRI, speech.

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683 Utilizing Fly Ash Cenosphere and Aerogel for Lightweight Thermal Insulating Cement-Based Composites

Authors: Asad Hanif, Pavithra Parthasarathy, Zongjin Li

Abstract:

Thermal insulating composites help to reduce the total power consumption in a building by creating a barrier between external and internal environment. Such composites can be used in the roofing tiles or wall panels for exterior surfaces. This study purposes to develop lightweight cement-based composites for thermal insulating applications. Waste materials like silica fume (an industrial by-product) and fly ash cenosphere (FAC) (hollow micro-spherical shells obtained as a waste residue from coal fired power plants) were used as partial replacement of cement and lightweight filler, respectively. Moreover, aerogel, a nano-porous material made of silica, was also used in different dosages for improved thermal insulating behavior, while poly vinyl alcohol (PVA) fibers were added for enhanced toughness. The raw materials including binders and fillers were characterized by X-Ray Diffraction (XRD), X-Ray Fluorescence spectroscopy (XRF), and Brunauer–Emmett–Teller (BET) analysis techniques in which various physical and chemical properties of the raw materials were evaluated like specific surface area, chemical composition (oxide form), and pore size distribution (if any). Ultra-lightweight cementitious composites were developed by varying the amounts of FAC and aerogel with 28-day unit weight ranging from 1551.28 kg/m3 to 1027.85 kg/m3. Excellent mechanical and thermal insulating properties of the resulting composites were obtained ranging from 53.62 MPa to 8.66 MPa compressive strength, 9.77 MPa to 3.98 MPa flexural strength, and 0.3025 W/m-K to 0.2009 W/m-K as thermal conductivity coefficient (QTM-500). The composites were also tested for peak temperature difference between outer and inner surfaces when subjected to heating (in a specially designed experimental set-up) by a 275W infrared lamp. The temperature difference up to 16.78 oC was achieved, which indicated outstanding properties of the developed composites to act as a thermal barrier for building envelopes. Microstructural studies were carried out by Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) for characterizing the inner structure of the composite specimen. Also, the hydration products were quantified using the surface area mapping and line scale technique in EDS. The microstructural analyses indicated excellent bonding of FAC and aerogel in the cementitious system. Also, selective reactivity of FAC was ascertained from the SEM imagery where the partially consumed FAC shells were observed. All in all, the lightweight fillers, FAC, and aerogel helped to produce the lightweight composites due to their physical characteristics, while exceptional mechanical properties, owing to FAC partial reactivity, were achieved.

Keywords: Sustainable development, fly ash cenosphere, aerogel, lightweight, cement, composite.

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682 Analysis of Brain Activities due to Differences in Running Shoe Properties

Authors: K. Okubo, Y. Kurihara, T. Kaburagi, K. Watanabe

Abstract:

Many of the ever-growing elderly population require exercise, such as running, for health management. One important element of a runner’s training is the choice of shoes for exercise; shoes are important because they provide the interface between the feet and road. When we purchase shoes, we may instinctively choose a pair after trying on many different pairs of shoes. Selecting the shoes instinctively may work, but it does not guarantee a suitable fit for running activities. Therefore, if we could select suitable shoes for each runner from the viewpoint of brain activities, it would be helpful for validating shoe selection. In this paper, we describe how brain activities show different characteristics during particular task, corresponding to different properties of shoes. Using five subjects, we performed a verification experiment, applying weight, softness, and flexibility as shoe properties. In order to affect the shoe property’s differences to the brain, subjects run for 10 min. Before and after running, subjects conducted a paced auditory serial addition task (PASAT) as the particular task; and the subjects’ brain activities during the PASAT are evaluated based on oxyhemoglobin and deoxyhemoglobin relative concentration changes, measured by near-infrared spectroscopy (NIRS). When the brain works actively, oxihemoglobin and deoxyhemoglobin concentration drastically changes; therefore, we calculate the maximum values of concentration changes. In order to normalize relative concentration changes after running, the maximum value are divided by before running maximum value as evaluation parameters. The classification of the groups of shoes is expressed on a self-organizing map (SOM). As a result, deoxyhemoglobin can make clusters for two of the three types of shoes.

Keywords: Brain activities, NIRS, PASAT, running shoes.

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681 Robust and Transparent Spread Spectrum Audio Watermarking

Authors: Ali Akbar Attari, Ali Asghar Beheshti Shirazi

Abstract:

In this paper, we propose a blind and robust audio watermarking scheme based on spread spectrum in Discrete Wavelet Transform (DWT) domain. Watermarks are embedded in the low-frequency coefficients, which is less audible. The key idea is dividing the audio signal into small frames, and magnitude of the 6th level of DWT approximation coefficients is modifying based upon the Direct Sequence Spread Spectrum (DSSS) technique. Also, the psychoacoustic model for enhancing in imperceptibility, as well as Savitsky-Golay filter for increasing accuracy in extraction, is used. The experimental results illustrate high robustness against most common attacks, i.e. Gaussian noise addition, Low pass filter, Resampling, Requantizing, MP3 compression, without significant perceptual distortion (ODG is higher than -1). The proposed scheme has about 83 bps data payload.

Keywords: Audio watermarking, spread spectrum, discrete wavelet transform, psychoacoustic, Savitsky-Golay filter.

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