Hybrid Method Using Wavelets and Predictive Method for Compression of Speech Signal

The development of the signal compression algorithms is having compressive progress. These algorithms are continuously improved by new tools and aim to reduce, an average, the number of bits necessary to the signal representation by means of minimizing the reconstruction error. The following article proposes the compression of Arabic speech signal by a hybrid method combining the wavelet transform and the linear prediction. The adopted approach rests, on one hand, on the original signal decomposition by ways of analysis filters, which is followed by the compression stage, and on the other hand, on the application of the order 5, as well as, the compression signal coefficients. The aim of this approach is the estimation of the predicted error, which will be coded and transmitted. The decoding operation is then used to reconstitute the original signal. Thus, the adequate choice of the bench of filters is useful to the transform in necessary to increase the compression rate and induce an impercevable distortion from an auditive point of view.

A Nonoblivious Image Watermarking System Based on Singular Value Decomposition and Texture Segmentation

In this paper, a robust digital image watermarking scheme for copyright protection applications using the singular value decomposition (SVD) is proposed. In this scheme, an entropy masking model has been applied on the host image for the texture segmentation. Moreover, the local luminance and textures of the host image are considered for watermark embedding procedure to increase the robustness of the watermarking scheme. In contrast to all existing SVD-based watermarking systems that have been designed to embed visual watermarks, our system uses a pseudo-random sequence as a watermark. We have tested the performance of our method using a wide variety of image processing attacks on different test images. A comparison is made between the results of our proposed algorithm with those of a wavelet-based method to demonstrate the superior performance of our algorithm.

Preparation and Bioactivity Evaluation of Bone like Hydroxyapatite - Bioglass Composite

In this study, hydroxyapatite (HA) composites are prepared on addition of 30%CaO-30%P2O5-40%Na2 O based glass to pure HA, in proportion of 2, 5, and 10 wt %. Each composition was sintered over a range of temperatures. The quantitative phase analysis was carried out using XRD and the microstructures were studied using SEM. The density, microhardness, and compressive strength have shown increase with the increasing amount of glass addition. The resulting composites have chemical compositions that are similar to the inorganic constituent of the mineral part of bone, and constitutes trace elements like Na. X-ray diffraction showed no decomposition of HA to secondary phases, however, the glass reinforced-HA composites contained a HA phase and variable amounts of tricalcium phosphate phase, depending on the amount of bioglass added. The HA-composite material exhibited higher compressive strength compared to sintered HA. The HA composite reinforced with 10 wt % bioglass showed highest bioactivity level.

Effect of Scene Changing on Image Sequences Compression Using Zero Tree Coding

We study in this paper the effect of the scene changing on image sequences coding system using Embedded Zerotree Wavelet (EZW). The scene changing considered here is the full motion which may occurs. A special image sequence is generated where the scene changing occurs randomly. Two scenarios are considered: In the first scenario, the system must provide the reconstruction quality as best as possible by the management of the bit rate (BR) while the scene changing occurs. In the second scenario, the system must keep the bit rate as constant as possible by the management of the reconstruction quality. The first scenario may be motivated by the availability of a large band pass transmission channel where an increase of the bit rate may be possible to keep the reconstruction quality up to a given threshold. The second scenario may be concerned by the narrow band pass transmission channel where an increase of the bit rate is not possible. In this last case, applications for which the reconstruction quality is not a constraint may be considered. The simulations are performed with five scales wavelet decomposition using the 9/7-tap filter bank biorthogonal wavelet. The entropy coding is performed using a specific defined binary code book and EZW algorithm. Experimental results are presented and compared to LEAD H263 EVAL. It is shown that if the reconstruction quality is the constraint, the system increases the bit rate to obtain the required quality. In the case where the bit rate must be constant, the system is unable to provide the required quality if the scene change occurs; however, the system is able to improve the quality while the scene changing disappears.

Pathway to Reduce Industrial Energy Intensity for Energy Conservation at Chinese Provincial Level

Using logarithmic mean Divisia decomposition technique, this paper analyzes the change in industrial energy intensity of Fujian Province in China, based on data sets of added value and energy consumption for 35 selected industrial sub-sectors from 1999 to 2009. The change in industrial energy intensity is decomposed into intensity effect and structure effect. Results show that the industrial energy intensity of Fujian Province has achieved a reduction of 51% over the past ten years. The structural change, a shift in the mix of industrial sub-sectors, made overwhelming contribution to the reduction. The impact of energy efficiency’s improvement was relatively small. However, the aggregate industrial energy intensity was very sensitive to both the changes in energy intensity and in production share of energy-intensive sub-sectors, such as production and supply of electric power, steam and hot water. Pathway to reduce industrial energy intensity for energy conservation in Fujian Province is proposed in the end.

Characterization of Acetogenic and Methanogenic Leachates Generated from a Sanitary Landfill Site

Decomposition processes take place in landfill generate leachates that can be categorized mainly of acetogenic and methanogenic in nature. BOD:COD ratio computed in this study for a landfill site over a 3 years duration revealed as a good indicator to identify acetogenic leachate from methanogenic leachate. Correlation relationships to predict pollutant level taking into consideration of climatic condition are derived.

Microbial Production of Levan using Date Syrup and Investigation of Its Properties

Levan, an exopolysaccharide, was produced by Microbacterium laevaniformans and its yield was characterized as a function of concentrations of date syrup, sucrose and the fermentation time. The optimum condition for levan production from sucrose was at concentration of 20% sucrose for 48 h and for date syrup was 25% for 48 h. The results show that an increase in fermentation time caused a decrease in the levan production at all concentrations of date syrup tested. Under these conditions after 48 h in sucrose medium, levan production reached 48.9 g/L and for date syrup reached 10.48 g/L . The effect of pH on the yield of the purified levan was examined and the optimum pH for levan production was determined to be 6.0. Levan was composed mainly of fructose residues when analyzed by TLC and FT-IR spectroscopy. Date syrup is a cheap substrate widely available in Iran and has potential for levan production. The thermal stability of levan was assessed by Thermo Gravimetric Analysis (TGA) that revealed the onset of decomposition near to 49°C for the levan produced from sucrose and 51°C for the levan from date syrup. DSC results showed a single Tg at 98°C for levan produced from sucrose and 206 °C for levan from date syrup.

Adaptive Fourier Decomposition Based Signal Instantaneous Frequency Computation Approach

There have been different approaches to compute the analytic instantaneous frequency with a variety of background reasoning and applicability in practice, as well as restrictions. This paper presents an adaptive Fourier decomposition and (α-counting) based instantaneous frequency computation approach. The adaptive Fourier decomposition is a recently proposed new signal decomposition approach. The instantaneous frequency can be computed through the so called mono-components decomposed by it. Due to the fast energy convergency, the highest frequency of the signal will be discarded by the adaptive Fourier decomposition, which represents the noise of the signal in most of the situation. A new instantaneous frequency definition for a large class of so-called simple waves is also proposed in this paper. Simple wave contains a wide range of signals for which the concept instantaneous frequency has a perfect physical sense. The α-counting instantaneous frequency can be used to compute the highest frequency for a signal. Combination of these two approaches one can obtain the IFs of the whole signal. An experiment is demonstrated the computation procedure with promising results.

The Utility of Wavelet Transform in Surface Electromyography Feature Extraction -A Comparative Study of Different Mother Wavelets

Electromyography (EMG) signal processing has been investigated remarkably regarding various applications such as in rehabilitation systems. Specifically, wavelet transform has served as a powerful technique to scrutinize EMG signals since wavelet transform is consistent with the nature of EMG as a non-stationary signal. In this paper, the efficiency of wavelet transform in surface EMG feature extraction is investigated from four levels of wavelet decomposition and a comparative study between different mother wavelets had been done. To recognize the best function and level of wavelet analysis, two evaluation criteria, scatter plot and RES index are recruited. Hereupon, four wavelet families, namely, Daubechies, Coiflets, Symlets and Biorthogonal are studied in wavelet decomposition stage. Consequently, the results show that only features from first and second level of wavelet decomposition yields good performance and some functions of various wavelet families can lead to an improvement in separability class of different hand movements.

Teager-Huang Analysis Applied to Sonar Target Recognition

In this paper, a new approach for target recognition based on the Empirical mode decomposition (EMD) algorithm of Huang etal. [11] and the energy tracking operator of Teager [13]-[14] is introduced. The conjunction of these two methods is called Teager-Huang analysis. This approach is well suited for nonstationary signals analysis. The impulse response (IR) of target is first band pass filtered into subsignals (components) called Intrinsic mode functions (IMFs) with well defined Instantaneous frequency (IF) and Instantaneous amplitude (IA). Each IMF is a zero-mean AM-FM component. In second step, the energy of each IMF is tracked using the Teager energy operator (TEO). IF and IA, useful to describe the time-varying characteristics of the signal, are estimated using the Energy separation algorithm (ESA) algorithm of Maragos et al .[16]-[17]. In third step, a set of features such as skewness and kurtosis are extracted from the IF, IA and IMF energy functions. The Teager-Huang analysis is tested on set of synthetic IRs of Sonar targets with different physical characteristics (density, velocity, shape,? ). PCA is first applied to features to discriminate between manufactured and natural targets. The manufactured patterns are classified into spheres and cylinders. One hundred percent of correct recognition is achieved with twenty three echoes where sixteen IRs, used for training, are free noise and seven IRs, used for testing phase, are corrupted with white Gaussian noise.

N-Sun Decomposition of Complete Graphs and Complete Bipartite Graphs

Graph decompositions are vital in the study of combinatorial design theory. Given two graphs G and H, an H-decomposition of G is a partition of the edge set of G into disjoint isomorphic copies of H. An n-sun is a cycle Cn with an edge terminating in a vertex of degree one attached to each vertex. In this paper we have proved that the complete graph of order 2n, K2n can be decomposed into n-2 n-suns, a Hamilton cycle and a perfect matching, when n is even and for odd case, the decomposition is n-1 n-suns and a perfect matching. For an odd order complete graph K2n+1, delete the star subgraph K1, 2n and the resultant graph K2n is decomposed as in the case of even order. The method of building n-suns uses Walecki's construction for the Hamilton decomposition of complete graphs. A spanning tree decomposition of even order complete graphs is also discussed using the labeling scheme of n-sun decomposition. A complete bipartite graph Kn, n can be decomposed into n/2 n-suns when n/2 is even. When n/2 is odd, Kn, n can be decomposed into (n-2)/2 n-suns and a Hamilton cycle.

Semi-Blind Two-Dimensional Code Acquisition in CDMA Communications

In this paper, we propose a new algorithm for joint time-delay and direction-of-arrival (DOA) estimation, here called two-dimensional code acquisition, in an asynchronous directsequence code-division multiple-access (DS-CDMA) array system. This algorithm depends on eigenvector-eigenvalue decomposition of sample correlation matrix, and requires to know desired user-s training sequence. The performance of the algorithm is analyzed both analytically and numerically in uncorrelated and coherent multipath environment. Numerical examples show that the algorithm is robust with unknown number of coherent signals.

Transmission Pricing based on Voltage Angle Decomposition

In this paper a new approach for transmission pricing is presented. The main idea is voltage angle allocation, i.e. determining the contribution of each contract on the voltage angle of each bus. DC power flow is used to compute a primary solution for angle decomposition. To consider the impacts of system non-linearity on angle decomposition, the primary solution is corrected in different iterations of decoupled Newton-Raphson power flow. Then, the contribution of each contract on power flow of each transmission line is computed based on angle decomposition. Contract-related flows are used as a measure for “extent of use" of transmission network capacity and consequently transmission pricing. The presented approach is applied to a 4-bus test system and IEEE 30-bus test system.

Generalized Morphological 3D Shape Decomposition Grayscale Interframe Interpolation Method

One of the main image representations in Mathematical Morphology is the 3D Shape Decomposition Representation, useful for Image Compression and Representation,and Pattern Recognition. The 3D Morphological Shape Decomposition representation can be generalized a number of times,to extend the scope of its algebraic characteristics as much as possible. With these generalizations, the Morphological Shape Decomposition 's role to serve as an efficient image decomposition tool is extended to grayscale images.This work follows the above line, and further develops it. Anew evolutionary branch is added to the 3D Morphological Shape Decomposition's development, by the introduction of a 3D Multi Structuring Element Morphological Shape Decomposition, which permits 3D Morphological Shape Decomposition of 3D binary images (grayscale images) into "multiparameter" families of elements. At the beginning, 3D Morphological Shape Decomposition representations are based only on "1 parameter" families of elements for image decomposition.This paper addresses the gray scale inter frame interpolation by means of mathematical morphology. The new interframe interpolation method is based on generalized morphological 3D Shape Decomposition. This article will present the theoretical background of the morphological interframe interpolation, deduce the new representation and show some application examples.Computer simulations could illustrate results.

Analysis of Temperature Change under Global Warming Impact using Empirical Mode Decomposition

The empirical mode decomposition (EMD) represents any time series into a finite set of basis functions. The bases are termed as intrinsic mode functions (IMFs) which are mutually orthogonal containing minimum amount of cross-information. The EMD successively extracts the IMFs with the highest local frequencies in a recursive way, which yields effectively a set low-pass filters based entirely on the properties exhibited by the data. In this paper, EMD is applied to explore the properties of the multi-year air temperature and to observe its effects on climate change under global warming. This method decomposes the original time-series into intrinsic time scale. It is capable of analyzing nonlinear, non-stationary climatic time series that cause problems to many linear statistical methods and their users. The analysis results show that the mode of EMD presents seasonal variability. The most of the IMFs have normal distribution and the energy density distribution of the IMFs satisfies Chi-square distribution. The IMFs are more effective in isolating physical processes of various time-scales and also statistically significant. The analysis results also show that the EMD method provides a good job to find many characteristics on inter annual climate. The results suggest that climate fluctuations of every single element such as temperature are the results of variations in the global atmospheric circulation.

Molecular Dynamics Simulation of Lubricant Adsorption and Thermal Depletion Instability

In this work, we incorporated a quartic bond potential into a coarse-grained bead-spring model to study lubricant adsorption on a solid surface as well as depletion instability. The surface tension density and the number density profiles were examined to verify the solid-liquid and liquid-vapor interfaces during heat treatment. It was found that both the liquid-vapor interfacial thickness and the solid-vapor separation increase with the temperatureT* when T*is below the phase transition temperature Tc *. At high temperatures (T*>Tc *), the solid-vapor separation decreases gradually as the temperature increases. In addition, we evaluated the lubricant weight and bond loss profiles at different temperatures. It was observed that the lubricant desorption is favored over decomposition and is the main cause of the lubricant failure at the head disk interface in our simulations.

Optimum Conditions for Effective Decomposition of Toluene as VOC Gas by Pilot-Scale Regenerative Thermal Oxidizer

Regenerative Thermal Oxidizer (RTO) is one of the best solutions for removal of Volatile Organic Compounds (VOC) from industrial processes. In the RTO, VOC in a raw gas are usually decomposed at 950-1300 K and the combustion heat of VOC is recovered by regenerative heat exchangers charged with ceramic honeycombs. The optimization of the treatment of VOC leads to the reduction of fuel addition to VOC decomposition, the minimization of CO2 emission and operating cost as well. In the present work, the thermal efficiency of the RTO was investigated experimentally in a pilot-scale RTO unit using toluene as a typical representative of VOC. As a result, it was recognized that the radiative heat transfer was dominant in the preheating process of a raw gas when the gas flow rate was relatively low. Further, it was found that a minimum heat exchanger volume to achieve self combustion of toluene without additional heating of the RTO by fuel combustion was dependent on both the flow rate of a raw gas and the concentration of toluene. The thermal efficiency calculated from fuel consumption and the decomposed toluene ratio, was found to have a maximum value of 0.95 at a raw gas mass flow rate of 1810 kg·h-1 and honeycombs height of 1.5m.

Catalytical Effect of Fluka 05120 on Methane Decomposition

Carboneous catalytical methane decomposition is an attractive process because it produces two valuable products: hydrogen and carbon. Furthermore, this reaction does not emit any green house or hazardous gases. In the present study, experiments were conducted in a thermo gravimetric analyzer using Fluka 05120 as carboneous catalyst to analyze its effectiveness in methane decomposition. Various temperatures and methane partial pressures were chosen and carbon mass gain was observed as a function of time. Results are presented in terms of carbon formation rate, hydrogen production and catalytical activity. It is observed that there is linearity in carbon deposition amount by time at lower reaction temperature (780 °C). On the other hand, it is observed that carbon and hydrogen formation rates are increased with increasing temperature. Finally, we observed that the carbon formation rate is highest at 950 °C within the range of temperatures studied.

Comparison between Higher-Order SVD and Third-order Orthogonal Tensor Product Expansion

In digital signal processing it is important to approximate multi-dimensional data by the method called rank reduction, in which we reduce the rank of multi-dimensional data from higher to lower. For 2-dimennsional data, singular value decomposition (SVD) is one of the most known rank reduction techniques. Additional, outer product expansion expanded from SVD was proposed and implemented for multi-dimensional data, which has been widely applied to image processing and pattern recognition. However, the multi-dimensional outer product expansion has behavior of great computation complex and has not orthogonally between the expansion terms. Therefore we have proposed an alterative method, Third-order Orthogonal Tensor Product Expansion short for 3-OTPE. 3-OTPE uses the power method instead of nonlinear optimization method for decreasing at computing time. At the same time the group of B. D. Lathauwer proposed Higher-Order SVD (HOSVD) that is also developed with SVD extensions for multi-dimensional data. 3-OTPE and HOSVD are similarly on the rank reduction of multi-dimensional data. Using these two methods we can obtain computation results respectively, some ones are the same while some ones are slight different. In this paper, we compare 3-OTPE to HOSVD in accuracy of calculation and computing time of resolution, and clarify the difference between these two methods.

Quadrilateral Decomposition by Two-Ear Property Resulting in CAD Segmentation

The objective is to split a simply connected polygon into a set of convex quadrilaterals without inserting new boundary nodes. The presented approach consists in repeatedly removing quadrilaterals from the polygon. Theoretical results pertaining to quadrangulation of simply connected polygons are derived from the usual 2-ear theorem. It produces a quadrangulation technique with O(n) number of quadrilaterals. The theoretical methodology is supplemented by practical results and CAD surface segmentation.