IIR Filter design with Craziness based Particle Swarm Optimization Technique

This paper demonstrates the application of craziness based particle swarm optimization (CRPSO) technique for designing the 8th order low pass Infinite Impulse Response (IIR) filter. CRPSO, the much improved version of PSO, is a population based global heuristic search algorithm which finds near optimal solution in terms of a set of filter coefficients. Effectiveness of this algorithm is justified with a comparative study of some well established algorithms, namely, real coded genetic algorithm (RGA) and particle swarm optimization (PSO). Simulation results affirm that the proposed algorithm CRPSO, outperforms over its counterparts not only in terms of quality output i.e. sharpness at cut-off, pass band ripple, stop band ripple, and stop band attenuation but also in convergence speed with assured stability.

On-line and Off-line POD Assisted Projective Integral for Non-linear Problems: A Case Study with Burgers-Equation

The POD-assisted projective integration method based on the equation-free framework is presented in this paper. The method is essentially based on the slow manifold governing of given system. We have applied two variants which are the “on-line" and “off-line" methods for solving the one-dimensional viscous Bergers- equation. For the on-line method, we have computed the slow manifold by extracting the POD modes and used them on-the-fly along the projective integration process without assuming knowledge of the underlying slow manifold. In contrast, the underlying slow manifold must be computed prior to the projective integration process for the off-line method. The projective step is performed by the forward Euler method. Numerical experiments show that for the case of nonperiodic system, the on-line method is more efficient than the off-line method. Besides, the online approach is more realistic when apply the POD-assisted projective integration method to solve any systems. The critical value of the projective time step which directly limits the efficiency of both methods is also shown.

Improvement of MLLR Speaker Adaptation Using a Novel Method

This paper presents a technical speaker adaptation method called WMLLR, which is based on maximum likelihood linear regression (MLLR). In MLLR, a linear regression-based transform which adapted the HMM mean vectors was calculated to maximize the likelihood of adaptation data. In this paper, the prior knowledge of the initial model is adequately incorporated into the adaptation. A series of speaker adaptation experiments are carried out at a 30 famous city names database to investigate the efficiency of the proposed method. Experimental results show that the WMLLR method outperforms the conventional MLLR method, especially when only few utterances from a new speaker are available for adaptation.

Person Identification using Gait by Combined Features of Width and Shape of the Binary Silhouette

Current image-based individual human recognition methods, such as fingerprints, face, or iris biometric modalities generally require a cooperative subject, views from certain aspects, and physical contact or close proximity. These methods cannot reliably recognize non-cooperating individuals at a distance in the real world under changing environmental conditions. Gait, which concerns recognizing individuals by the way they walk, is a relatively new biometric without these disadvantages. The inherent gait characteristic of an individual makes it irreplaceable and useful in visual surveillance. In this paper, an efficient gait recognition system for human identification by extracting two features namely width vector of the binary silhouette and the MPEG-7-based region-based shape descriptors is proposed. In the proposed method, foreground objects i.e., human and other moving objects are extracted by estimating background information by a Gaussian Mixture Model (GMM) and subsequently, median filtering operation is performed for removing noises in the background subtracted image. A moving target classification algorithm is used to separate human being (i.e., pedestrian) from other foreground objects (viz., vehicles). Shape and boundary information is used in the moving target classification algorithm. Subsequently, width vector of the outer contour of binary silhouette and the MPEG-7 Angular Radial Transform coefficients are taken as the feature vector. Next, the Principal Component Analysis (PCA) is applied to the selected feature vector to reduce its dimensionality. These extracted feature vectors are used to train an Hidden Markov Model (HMM) for identification of some individuals. The proposed system is evaluated using some gait sequences and the experimental results show the efficacy of the proposed algorithm.

Beneficial Use of Coal Combustion By-products in the Rehabilitation of Failed Asphalt Pavements

This study demonstrates the use of Class F fly ash in combination with lime or lime kiln dust in the full depth reclamation (FDR) of asphalt pavements. FDR, in the context of this paper, is a process of pulverizing a predetermined amount of flexible pavement that is structurally deficient, blending it with chemical additives and water, and compacting it in place to construct a new stabilized base course. Test sections of two structurally deficient asphalt pavements were reclaimed using Class F fly ash in combination with lime and lime kiln dust. In addition, control sections were constructed using cement, cement and emulsion, lime kiln dust and emulsion, and mill and fill. The service performance and structural behavior of the FDR pavement test sections were monitored to determine how the fly ash sections compared to other more traditional pavement rehabilitation techniques. Service performance and structural behavior were determined with the use of sensors embedded in the road and Falling Weight Deflectometer (FWD) tests. Monitoring results of the FWD tests conducted up to 2 years after reclamation show that the cement, fly ash+LKD, and fly ash+lime sections exhibited two year resilient modulus values comparable to open graded cement stabilized aggregates (more than 750 ksi). The cement treatment resulted in a significant increase in resilient modulus within 3 weeks of construction and beyond this curing time, the stiffness increase was slow. On the other hand, the fly ash+LKD and fly ash+lime test sections indicated slower shorter-term increase in stiffness. The fly ash+LKD and fly ash+lime section average resilient modulus values at two years after construction were in excess of 800 ksi. Additional longer-term testing data will be available from ongoing pavement performance and environmental condition data collection at the two pavement sites.

Comparative Study on Production of Fructooligosaccharides by p. Simplicissimum Using Immobilized Cells and Conventional Reactor System

Fructooligosaccharides derived from microbial enzyme especially from fungal sources has been received particular attention due to its beneficial effects as prebiotics and mass production. However, fungal fermentation is always cumbersome due to its broth rheology problem that will eventually affect the production of FOS. This study investigated the efficiency of immobilized cell system using rotating fibrous bed bioreactor (RFBB) in producing fructooligosaccharides (FOS). A comparative picture with respect to conventional stirred tank bioreactor (CSTB) and RFBB has been presented. To demonstrate the effect of agitation intensity and aeration rate, a laboratory-scale bioreactor 2.5 L was operated in three phases (high, medium, low) for 48 hours. Agitation speed has a great influence on P. simplicissimum fermentation for FOS production, where the volumetric FOS productivity using RFBB is increased with almost 4 fold compared to the FOS productivity in CSTB that only 0.319 g/L/h. Rate of FOS production increased up to 1.2 fold when immobilized cells system was employed at aeration rate similar to the freely suspended cells at 2.0 vvm.

Gene Selection Guided by Feature Interdependence

Cancers could normally be marked by a number of differentially expressed genes which show enormous potential as biomarkers for a certain disease. Recent years, cancer classification based on the investigation of gene expression profiles derived by high-throughput microarrays has widely been used. The selection of discriminative genes is, therefore, an essential preprocess step in carcinogenesis studies. In this paper, we have proposed a novel gene selector using information-theoretic measures for biological discovery. This multivariate filter is a four-stage framework through the analyses of feature relevance, feature interdependence, feature redundancy-dependence and subset rankings, and having been examined on the colon cancer data set. Our experimental result show that the proposed method outperformed other information theorem based filters in all aspect of classification errors and classification performance.

TiO2-Zeolite Y Catalyst Prepared Using Impregnation and Ion-Exchange Method for Sonocatalytic Degradation of Amaranth Dye in Aqueous Solution

Characteristics and sonocatalytic activity of zeolite Y catalysts loaded with TiO2 using impregnation and ion exchange methods for the degradation of amaranth dye were investigated. The Ion-exchange method was used to encapsulate the TiO2 into the internal pores of the zeolite while the incorporation of TiO2 mostly on the external surface of zeolite was carried out using the impregnation method. Different characterization techniques were used to elucidate the physicochemical properties of the produced catalysts. The framework of zeolite Y remained virtually unchanged after the encapsulation of TiO2 while the crystallinity of zeolite decreased significantly after the incorporation of 15 wt% of TiO2. The sonocatalytic activity was enhanced by TiO2 incorporation with maximum degradation efficiencies of 50% and 68% for the encapsulated titanium and titanium loaded onto the zeolite, respectively after 120min of reaction. Catalysts characteristics and sonocatalytic behaviors were significantly affected by the preparation method and the location of TiO2 introduced with zeolite structure. Behaviors in the sonocatalytic process were successfully correlated with the characteristics of the catalysts used.

Transmit Sub-aperture Optimization in MSTA Ultrasound Imaging Method

The paper presents the optimization problem for the multi-element synthetic transmit aperture method (MSTA) in ultrasound imaging applications. The optimal choice of the transmit aperture size is performed as a trade-off between the lateral resolution, penetration depth and the frame rate. Results of the analysis obtained by a developed optimization algorithm are presented. Maximum penetration depth and the best lateral resolution at given depths are chosen as the optimization criteria. The optimization algorithm was tested using synthetic aperture data of point reflectors simulated by Filed II program for Matlab® for the case of 5MHz 128-element linear transducer array with 0.48 mm pitch are presented. The visualization of experimentally obtained synthetic aperture data of a tissue mimicking phantom and in vitro measurements of the beef liver are also shown. The data were obtained using the SonixTOUCH Research systemequipped with a linear 4MHz 128 element transducerwith 0.3 mm element pitch, 0.28 mm element width and 70% fractional bandwidth was excited by one sine cycle pulse burst of transducer's center frequency.

Surface Flattening Assisted with 3D Mannequin Based On Minimum Energy

The topic of surface flattening plays a vital role in the field of computer aided design and manufacture. Surface flattening enables the production of 2D patterns and it can be used in design and manufacturing for developing a 3D surface to a 2D platform, especially in fashion design. This study describes surface flattening based on minimum energy methods according to the property of different fabrics. Firstly, through the geometric feature of a 3D surface, the less transformed area can be flattened on a 2D platform by geodesic. Then, strain energy that has accumulated in mesh can be stably released by an approximate implicit method and revised error function. In some cases, cutting mesh to further release the energy is a common way to fix the situation and enhance the accuracy of the surface flattening, and this makes the obtained 2D pattern naturally generate significant cracks. When this methodology is applied to a 3D mannequin constructed with feature lines, it enhances the level of computer-aided fashion design. Besides, when different fabrics are applied to fashion design, it is necessary to revise the shape of a 2D pattern according to the properties of the fabric. With this model, the outline of 2D patterns can be revised by distributing the strain energy with different results according to different fabric properties. Finally, this research uses some common design cases to illustrate and verify the feasibility of this methodology.

Motivated Support Vector Regression using Structural Prior Knowledge

It-s known that incorporating prior knowledge into support vector regression (SVR) can help to improve the approximation performance. Most of researches are concerned with the incorporation of knowledge in the form of numerical relationships. Little work, however, has been done to incorporate the prior knowledge on the structural relationships among the variables (referred as to Structural Prior Knowledge, SPK). This paper explores the incorporation of SPK in SVR by constructing appropriate admissible support vector kernel (SV kernel) based on the properties of reproducing kernel (R.K). Three-levels specifications of SPK are studied with the corresponding sub-levels of prior knowledge that can be considered for the method. These include Hierarchical SPK (HSPK), Interactional SPK (ISPK) consisting of independence, global and local interaction, Functional SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A convenient tool for describing the SPK, namely Description Matrix of SPK is introduced. Subsequently, a new SVR, namely Motivated Support Vector Regression (MSVR) whose structure is motivated in part by SPK, is proposed. Synthetic examples show that it is possible to incorporate a wide variety of SPK and helpful to improve the approximation performance in complex cases. The benefits of MSVR are finally shown on a real-life military application, Air-toground battle simulation, which shows great potential for MSVR to the complex military applications.

The Effect of Soil Surface Slope on Splash Distribution under Water Drop Impact

The effects of down slope steepness on soil splash distribution under a water drop impact have been investigated in this study. The equipment used are the burette to simulate a water drop, a splash cup filled with sandy soil which forms the source area and a splash board to collect the ejected particles. The results found in this study have shown that the apparent mass increased with increasing downslope angle following a linear regression equation with high coefficient of determination. In the same way, the radial soil splash distribution over the distance has been analyzed statistically, and an exponential function was the best fit of the relationship for the different slope angles. The curves and the regressions equations validate the well known FSDF and extend the theory of Van Dijk.

Canonical PSO based Nanorobot Control for Blood Vessel Repair

As nanotechnology advances, the use of nanotechnology for medical purposes in the field of nanomedicine seems more promising; the rise of nanorobots for medical diagnostics and treatments could be arriving in the near future. This study proposes a swarm intelligence based control mechanism for swarm nanorobots that operate as artificial platelets to search for wounds. The canonical particle swarm optimization algorithm is employed in this study. A simulation in the circulatory system is constructed and used for demonstrating the movement of nanorobots with essential characteristics to examine the performance of proposed control mechanism. The effects of three nanorobot capabilities including their perception range, maximum velocity and respond time are investigated. The results show that canonical particle swarm optimization can be used to control the early version nanorobots with simple behaviors and actions.

Performance Evaluation of an Online Text-Based Strategy Game

Text-based game is supposed to be a low resource consumption application that delivers good performances when compared to graphical-intensive type of games. But, nowadays, some of the online text-based games are not offering performances that are acceptable to the users. Therefore, an online text-based game called Star_Quest has been developed in order to analyze its behavior under different performance measurements. Performance metrics such as throughput, scalability, response time and page loading time are captured to yield the performance of the game. The techniques in performing the load testing are also disclosed to exhibit the viability of our work. The comparative assessment between the results obtained and the accepted level of performances are conducted as to determine the performance level of the game. The study reveals that the developed game managed to meet all the performance objectives set forth.

Using Data Mining Methodology to Build the Predictive Model of Gold Passbook Price

Gold passbook is an investing tool that is especially suitable for investors to do small investment in the solid gold. The gold passbook has the lower risk than other ways investing in gold, but its price is still affected by gold price. However, there are many factors can cause influences on gold price. Therefore, building a model to predict the price of gold passbook can both reduce the risk of investment and increase the benefits. This study investigates the important factors that influence the gold passbook price, and utilize the Group Method of Data Handling (GMDH) to build the predictive model. This method can not only obtain the significant variables but also perform well in prediction. Finally, the significant variables of gold passbook price, which can be predicted by GMDH, are US dollar exchange rate, international petroleum price, unemployment rate, whole sale price index, rediscount rate, foreign exchange reserves, misery index, prosperity coincident index and industrial index.

An Improved Integer Frequency Offset Estimator using the P1 Symbol for OFDM System

This paper suggests an improved integer frequency offset (IFO) estimation scheme using P1 symbol for orthogonal frequency division multiplexing (OFDM) based the second generation terrestrial digital video broadcasting (DVB-T2) system. Proposed IFO estimator is designed by a low-complexity blind IFO estimation scheme, which is implemented with complex additions. Also, we propose active carriers (ACs) selection scheme in order to prevent performance degradation in blind IFO estimation. The simulation results show that under the AWGN and TU6 channels, the proposed method has low complexity than conventional method and almost similar performance in comparison with the conventional method.

Linear-Operator Formalism in the Analysis of Omega Planar Layered Waveguides

A complete spectral representation for the electromagnetic field of planar multilayered waveguides inhomogeneously filled with omega media is presented. The problem of guided electromagnetic propagation is reduced to an eigenvalue equation related to a 2 ´ 2 matrix differential operator. Using the concept of adjoint waveguide, general bi-orthogonality relations for the hybrid modes (either from the discrete or from the continuous spectrum) are derived. For the special case of homogeneous layers the linear operator formalism is reduced to a simple 2 ´ 2 coupling matrix eigenvalue problem. Finally, as an example of application, the surface and the radiation modes of a grounded omega slab waveguide are analyzed.

Thermodynamic Performance of a Combined Power and Ejector Refrigeration Cycle

In this study thermodynamic performance analysis of a combined organic Rankine cycle and ejector refrigeration cycle is carried out for use of low-grade heat source in the form of sensible energy. Special attention is paid to the effects of system parameters including the turbine inlet temperature and turbine inlet pressure on the characteristics of the system such as ratios of mass flow rate, net work production, and refrigeration capacity as well as the coefficient of performance and exergy efficiency of the system. Results show that for a given source the coefficient of performance increases with increasing of the turbine inlet pressure. However, the exergy efficiency has an optimal condition with respect to the turbine inlet pressure.

Footbridge Response on Single Pedestrian Induced Vibration Analysis

Many footbridges have natural frequencies that coincide with the dominant frequencies of the pedestrian-induced load and therefore they have a potential to suffer excessive vibrations under dynamic loads induced by pedestrians. Some of the design standards introduce load models for pedestrian loads applicable for simple structures. Load modeling for more complex structures, on the other hand, is most often left to the designer. The main focus of this paper is on the human induced forces transmitted to a footbridge and on the ways these loads can be modeled to be used in the dynamic design of footbridges. Also design criteria and load models proposed by widely used standards were introduced and a comparison was made. The dynamic analysis of the suspension bridge in Kolin in the Czech Republic was performed on detailed FEM model using the ANSYS program system. An attempt to model the load imposed by a single person and a crowd of pedestrians resulted in displacements and accelerations that are compared with serviceability criteria.

A Fast Code Acquisition Scheme for O-CDMA Systems

This paper proposes a fast code acquisition scheme for optical code division multiple access (O-CDMA) systems. Unlike the conventional scheme, the proposed scheme employs multiple thresholds providing a shorter mean acquisition time (MAT) performance. The simulation results show that the MAT of the proposed scheme is shorter than that of the conventional scheme.