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.

A Proposal of an Automatic Formatting Method for Transforming XML Data

PPX(Pretty Printer for XML) is a query language that offers a concise description method of formatting the XML data into HTML. In this paper, we propose a simple specification of formatting method that is a combination description of automatic layout operators and variables in the layout expression of the GENERATE clause of PPX. This method can automatically format irregular XML data included in a part of XML with layout decision rule that is referred to DTD. In the experiment, a quick comparison shows that PPX requires far less description compared to XSLT or XQuery programs doing same tasks.

Modeling and Simulating Reaction-Diffusion Systems with State-Dependent Diffusion Coefficients

The present models and simulation algorithms of intracellular stochastic kinetics are usually based on the premise that diffusion is so fast that the concentrations of all the involved species are homogeneous in space. However, recents experimental measurements of intracellular diffusion constants indicate that the assumption of a homogeneous well-stirred cytosol is not necessarily valid even for small prokaryotic cells. In this work a mathematical treatment of diffusion that can be incorporated in a stochastic algorithm simulating the dynamics of a reaction-diffusion system is presented. The movement of a molecule A from a region i to a region j of the space is represented as a first order reaction Ai k- ! Aj , where the rate constant k depends on the diffusion coefficient. The diffusion coefficients are modeled as function of the local concentration of the solutes, their intrinsic viscosities, their frictional coefficients and the temperature of the system. The stochastic time evolution of the system is given by the occurrence of diffusion events and chemical reaction events. At each time step an event (reaction or diffusion) is selected from a probability distribution of waiting times determined by the intrinsic reaction kinetics and diffusion dynamics. To demonstrate the method the simulation results of the reaction-diffusion system of chaperoneassisted protein folding in cytoplasm are shown.

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.

Video Mining for Creative Rendering

More and more home videos are being generated with the ever growing popularity of digital cameras and camcorders. For many home videos, a photo rendering, whether capturing a moment or a scene within the video, provides a complementary representation to the video. In this paper, a video motion mining framework for creative rendering is presented. The user-s capture intent is derived by analyzing video motions, and respective metadata is generated for each capture type. The metadata can be used in a number of applications, such as creating video thumbnail, generating panorama posters, and producing slideshows of video.

Cell Growth and Metabolites Produced by Fluorescent Pseudomonad R62 in Modified Chemically Defined Medium

Chemically defined Schlegel-s medium was modified to improve production of cell growth and other metabolites that are produced by fluorescent pseudomonad R62 strain. The modified medium does not require pH control as pH changes are kept within ± 0.2 units of the initial pH 7.1 during fermentation. The siderophore production was optimized for the fluorescent pseudomonad strain in the modified medium containing 1% glycerol as a major carbon source supplemented with 0.05% succinic acid and 0.5% Ltryptophan. Indole-3 acetic acid (IAA) production was higher when L-tryptophan was used at 0.5%. The 2,4- diacetylphloroglucinol (DAPG) was higher with amended three trace elements in medium. The optimized medium produced 2.28 g/l of dry cell mass and 900 mg/l of siderophore at the end of 36 h cultivation, while the production levels of IAA and DAPG were 65 mg/l and 81 mg/l respectively at the end of 48 h cultivation.

Automated Knowledge Engineering

This article outlines conceptualization and implementation of an intelligent system capable of extracting knowledge from databases. Use of hybridized features of both the Rough and Fuzzy Set theory render the developed system flexibility in dealing with discreet as well as continuous datasets. A raw data set provided to the system, is initially transformed in a computer legible format followed by pruning of the data set. The refined data set is then processed through various Rough Set operators which enable discovery of parameter relationships and interdependencies. The discovered knowledge is automatically transformed into a rule base expressed in Fuzzy terms. Two exemplary cancer repository datasets (for Breast and Lung Cancer) have been used to test and implement the proposed framework.

Meta Model Based EA for Complex Optimization

Evolutionary Algorithms are population-based, stochastic search techniques, widely used as efficient global optimizers. However, many real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function evaluations. Use of evolutionary algorithms in such problem domains is thus practically prohibitive. An attractive alternative is to build meta models or use an approximation of the actual fitness functions to be evaluated. These meta models are order of magnitude cheaper to evaluate compared to the actual function evaluation. Many regression and interpolation tools are available to build such meta models. This paper briefly discusses the architectures and use of such meta-modeling tools in an evolutionary optimization context. We further present two evolutionary algorithm frameworks which involve use of meta models for fitness function evaluation. The first framework, namely the Dynamic Approximate Fitness based Hybrid EA (DAFHEA) model [14] reduces computation time by controlled use of meta-models (in this case approximate model generated by Support Vector Machine regression) to partially replace the actual function evaluation by approximate function evaluation. However, the underlying assumption in DAFHEA is that the training samples for the metamodel are generated from a single uniform model. This does not take into account uncertain scenarios involving noisy fitness functions. The second model, DAFHEA-II, an enhanced version of the original DAFHEA framework, incorporates a multiple-model based learning approach for the support vector machine approximator to handle noisy functions [15]. Empirical results obtained by evaluating the frameworks using several benchmark functions demonstrate their efficiency

FT-IR Study of Stabilized PAN Fibers for Fabrication of Carbon Fibers

In this investigation, types of commercial and special polyacrylonitrile (PAN) fibers contain sodium 2-methyl-2- acrylamidopropane sulfonate (SAMPS) and itaconic acid (IA) comonomers were studied by fourier transform infrared (FT-IR) spectroscopy. The study of FT-IR spectra of PAN fibers samples with different comonomers shows that during stabilization of PAN fibers, the peaks related to C≡N bonds and CH2 are reduced sharply. These reductions are related to cyclization of nitrile groups and stabilization procedure. This reduction in PAN fibers contain IA comonomer is very intense in comparison with PAN fibers contain SAMPS comonomer. This fact indicates the cycling and stabilization for sample contain IA comonomer have been conducted more completely. Therefore the carbon fibers produced from this material have higher tensile strength due to suitable stabilization.

An Improved Learning Algorithm based on the Conjugate Gradient Method for Back Propagation Neural Networks

The conjugate gradient optimization algorithm usually used for nonlinear least squares is presented and is combined with the modified back propagation algorithm yielding a new fast training multilayer perceptron (MLP) algorithm (CGFR/AG). The approaches presented in the paper consist of three steps: (1) Modification on standard back propagation algorithm by introducing gain variation term of the activation function, (2) Calculating the gradient descent on error with respect to the weights and gains values and (3) the determination of the new search direction by exploiting the information calculated by gradient descent in step (2) as well as the previous search direction. The proposed method improved the training efficiency of back propagation algorithm by adaptively modifying the initial search direction. Performance of the proposed method is demonstrated by comparing to the conjugate gradient algorithm from neural network toolbox for the chosen benchmark. The results show that the number of iterations required by the proposed method to converge is less than 20% of what is required by the standard conjugate gradient and neural network toolbox algorithm.

Thermal and Mechanical Buckling of Short and Long Functionally Graded Cylindrical Shells Using First Order Shear Deformation Theory

This paper presents the buckling analysis of short and long functionally graded cylindrical shells under thermal and mechanical loads. The shell properties are assumed to vary continuously from the inner surface to the outer surface of the shell. The equilibrium and stability equations are derived using the total potential energy equations, Euler equations and first order shear deformation theory assumptions. The resulting equations are solved for simply supported boundary conditions. The critical temperature and pressure loads are calculated for both short and long cylindrical shells. Comparison studies show the effects of functionally graded index, loading type and shell geometry on critical buckling loads of short and long functionally graded cylindrical shells.

Features of Following the Customs and Traditions in Turkestan in the Late XIXth and Early XXth Centuries

This article discusses the customs and traditions in Turkestan in the late XIXth and early XXth centuries. Having a long history, Turkestan is well-known as the birthplace of many nations and nationalities. The name of Turkestan is also given to it for a reason - the land of the Turkic peoples who inhabited Central Asia and united under together. Currently, nations and nationalities of the Turkestan region formed their own sovereign states, and every year they prove their country names in the world community. Political, economic importance of Turkestan, which became the gold wire between Asia and Europe was always very high. So systematically various aggressive actions were made by several great powers. As a result of expansionary policy of colonization of the Russian Empire - the Turkestan has appeared.

Studies on Determination of the Optimum Distance Between the Tmotes for Optimum Data Transfer in a Network with WLL Capability

Using mini modules of Tmotes, it is possible to automate a small personal area network. This idea can be extended to large networks too by implementing multi-hop routing. Linking the various Tmotes using Programming languages like Nesc, Java and having transmitter and receiver sections, a network can be monitored. It is foreseen that, depending on the application, a long range at a low data transfer rate or average throughput may be an acceptable trade-off. To reduce the overall costs involved, an optimum number of Tmotes to be used under various conditions (Indoor/Outdoor) is to be deduced. By analyzing the data rates or throughputs at various locations of Tmotes, it is possible to deduce an optimal number of Tmotes for a specific network. This paper deals with the determination of optimum distances to reduce the cost and increase the reliability of the entire sensor network with Wireless Local Loop (WLL) capability.

Drying of Papaya (Carica papaya L.) Using a Microwave-vacuum Dryer

In present work, drying characteristics of fresh papaya (Carica papaya L.) was studied to understand the dehydration process and its behavior. Drying experiments were carried out by a laboratory scaled microwave-vacuum oven. The parameters affecting drying characteristics including operating modes (continuous, pulsed), microwave power (400 and 800 W), and vacuum pressure (20, 30, and 40 cmHg) were investigated. For pulsed mode, two levels of power-off time (60 and 120 s) were used while the power-on time was fixed at 60 s and the vacuum pressure was fixed at 40 cmHg. For both operating modes, the effects of drying conditions on drying time, drying rate, and effective diffusivity were investigated. The results showed high microwave power, high vacuum, and pulsed mode of 60 s-on/60 s-off favored drying rate as shown by the shorten drying time and increased effective diffusivity. The drying characteristics were then described by Page-s model, which showed a good agreement with experimental data.

A Systems Approach to Gene Ranking from DNA Microarray Data of Cervical Cancer

In this paper we present a method for gene ranking from DNA microarray data. More precisely, we calculate the correlation networks, which are unweighted and undirected graphs, from microarray data of cervical cancer whereas each network represents a tissue of a certain tumor stage and each node in the network represents a gene. From these networks we extract one tree for each gene by a local decomposition of the correlation network. The interpretation of a tree is that it represents the n-nearest neighbor genes on the n-th level of a tree, measured by the Dijkstra distance, and, hence, gives the local embedding of a gene within the correlation network. For the obtained trees we measure the pairwise similarity between trees rooted by the same gene from normal to cancerous tissues. This evaluates the modification of the tree topology due to progression of the tumor. Finally, we rank the obtained similarity values from all tissue comparisons and select the top ranked genes. For these genes the local neighborhood in the correlation networks changes most between normal and cancerous tissues. As a result we find that the top ranked genes are candidates suspected to be involved in tumor growth and, hence, indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.

Forms of Promotion and Dissemination of Traditional Local Wisdom: Creating Occupations among the Elderly in Noanmueng Community, Muang Sub-District, Baan Doong District, Udonthani Province

This research sought to discover the forms of promotion and dissemination of traditional local wisdom that are used to create occupations among the elderly at Noanmueng Community, Muang Sub-District, Baan Doong District, Udornthani Province. The criteria used to select the research sample group were: having a role involved in the promotion and dissemination of traditional local wisdom to create occupations among the elderly; being an experienced person who the residents of Noanmueng Community find trustworthy; and having lived in Noanmueng Community for a long time so as to be able to see the development and change that occurs. A total of 16 persons were thus selected. Data was gathered through a qualitative study, using semi-structured indepth interviews. The collected data was then summarized and discussed according to the research objectives. Finally, the data was presented in narrative format. Results found that the identifying traditional local wisdom of the community (which grew from the residents’ experience and beneficial usage in daily life, passed down from generation to generation) was the weaving of cloth and basketry. As for the manner of promotion and dissemination of traditional local wisdom, these skills were passed down through teaching by example to family members, relatives and others in the community. This was largely the initiative of the elders or elderly members of the community. In order for the promotion and dissemination of traditional local wisdom to create occupations among the elderly, the traditional local wisdom should be supported in every way through participation of the community members. For example, establish a museum of traditional local wisdom for the collection of traditional local wisdom in various fields, both from the past and present innovations. This would be a source of pride for the community, simultaneously helping traditional local wisdom to become widely known and to create income for the community’s elderly. Additional ways include organizing exhibitions of products made by traditional local wisdom, finding both domestic and international markets, as well as building both domestic and international networks aiming to find opportunities to market products made by traditional local wisdom.

Learning to Recognize Faces by Local Feature Design and Selection

Studies in neuroscience suggest that both global and local feature information are crucial for perception and recognition of faces. It is widely believed that local feature is less sensitive to variations caused by illumination, expression and illumination. In this paper, we target at designing and learning local features for face recognition. We designed three types of local features. They are semi-global feature, local patch feature and tangent shape feature. The designing of semi-global feature aims at taking advantage of global-like feature and meanwhile avoiding suppressing AdaBoost algorithm in boosting weak classifies established from small local patches. The designing of local patch feature targets at automatically selecting discriminative features, and is thus different with traditional ways, in which local patches are usually selected manually to cover the salient facial components. Also, shape feature is considered in this paper for frontal view face recognition. These features are selected and combined under the framework of boosting algorithm and cascade structure. The experimental results demonstrate that the proposed approach outperforms the standard eigenface method and Bayesian method. Moreover, the selected local features and observations in the experiments are enlightening to researches in local feature design in face recognition.

Thermo Mechanical Design and Analysis of PEM Fuel cell Plate

Fuel and oxidant gas delivery plate, or fuel cell plate, is a key component of a Proton Exchange Membrane (PEM) fuel cell. To manufacture low-cost and high performance fuel cell plates, advanced computer modeling and finite element structure analysis are used as virtual prototyping tools for the optimization of the plates at the early design stage. The present study examines thermal stress analysis of the fuel cell plates that are produced using a patented, low-cost fuel cell plate production technique based on screen-printing. Design optimization is applied to minimize the maximum stress within the plate, subject to strain constraint with both geometry and material parameters as design variables. The study reveals the characteristics of the printed plates, and provides guidelines for the structure and material design of the fuel cell plate.

Dynamic Response of Strain Rate Dependent Glass/Epoxy Composite Beams Using Finite Difference Method

This paper deals with a numerical analysis of the transient response of composite beams with strain rate dependent mechanical properties by use of a finite difference method. The equations of motion based on Timoshenko beam theory are derived. The geometric nonlinearity effects are taken into account with von Kármán large deflection theory. The finite difference method in conjunction with Newmark average acceleration method is applied to solve the differential equations. A modified progressive damage model which accounts for strain rate effects is developed based on the material property degradation rules and modified Hashin-type failure criteria and added to the finite difference model. The components of the model are implemented into a computer code in Mathematica 6. Glass/epoxy laminated composite beams with constant and strain rate dependent mechanical properties under dynamic load are analyzed. Effects of strain rate on dynamic response of the beam for various stacking sequences, load and boundary conditions are investigated.

Novel Hybrid Approaches For Real Coded Genetic Algorithm to Compute the Optimal Control of a Single Stage Hybrid Manufacturing Systems

This paper presents a novel two-phase hybrid optimization algorithm with hybrid genetic operators to solve the optimal control problem of a single stage hybrid manufacturing system. The proposed hybrid real coded genetic algorithm (HRCGA) is developed in such a way that a simple real coded GA acts as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method is next employed to do fine tuning. The hybrid genetic operators involved in the proposed algorithm improve both the quality of the solution and convergence speed. The phase–1 uses conventional real coded genetic algorithm (RCGA), while optimisation by direct search and systematic reduction of the size of search region is employed in the phase – 2. A typical numerical example of an optimal control problem with the number of jobs varying from 10 to 50 is included to illustrate the efficacy of the proposed algorithm. Several statistical analyses are done to compare the validity of the proposed algorithm with the conventional RCGA and PSO techniques. Hypothesis t – test and analysis of variance (ANOVA) test are also carried out to validate the effectiveness of the proposed algorithm. The results clearly demonstrate that the proposed algorithm not only improves the quality but also is more efficient in converging to the optimal value faster. They can outperform the conventional real coded GA (RCGA) and the efficient particle swarm optimisation (PSO) algorithm in quality of the optimal solution and also in terms of convergence to the actual optimum value.