Thermal Stability Boundary of FG Panel under Aerodynamic Load

In this study, it is investigated the stability boundary of Functionally Graded (FG) panel under the heats and supersonic airflows. Material properties are assumed to be temperature dependent, and a simple power law distribution is taken. First-order shear deformation theory (FSDT) of plate is applied to model the panel, and the von-Karman strain- displacement relations are adopted to consider the geometric nonlinearity due to large deformation. Further, the first-order piston theory is used to model the supersonic aerodynamic load acting on a panel and Rayleigh damping coefficient is used to present the structural damping. In order to find a critical value of the speed, linear flutter analysis of FG panels is performed. Numerical results are compared with the previous works, and present results for the temperature dependent material are discussed in detail for stability boundary of the panel with various volume fractions, and aerodynamic pressures.

Architecture of Speech-based Registration System

In this era of technology, fueled by the pervasive usage of the internet, security is a prime concern. The number of new attacks by the so-called “bots", which are automated programs, is increasing at an alarming rate. They are most likely to attack online registration systems. Technology, called “CAPTCHA" (Completely Automated Public Turing test to tell Computers and Humans Apart) do exist, which can differentiate between automated programs and humans and prevent replay attacks. Traditionally CAPTCHA-s have been implemented with the challenge involved in recognizing textual images and reproducing the same. We propose an approach where the visual challenge has to be read out from which randomly selected keywords are used to verify the correctness of spoken text and in turn detect the presence of human. This is supplemented with a speaker recognition system which can identify the speaker also. Thus, this framework fulfills both the objectives – it can determine whether the user is a human or not and if it is a human, it can verify its identity.

Auto-Parking System via Intelligent Computation Intelligence

In this paper, an intelligent automatic parking control method is proposed. First, the dynamical equation of the rear parking control is derived. Then a fuzzy logic control is proposed to perform the parking planning process. Further, a rear neural network is proposed for the steering control. Through the simulations and experiments, the intelligent auto-parking mode controllers have been shown to achieve the demanded goals with satisfactory control performance and to guarantee the system robustness under parametric variations and external disturbances. To improve some shortcomings and limitations in conventional parking mode control and further to reduce consumption time and prime cost.

Production of Spherical Ag/ZnO Nanocomposite Particles for Photocatalytic Applications

Noble metal participation in nanostructured semiconductor catalysts has drawn much interest because of their improved properties. Recently, it has been discussed by many researchers that Ag participation in TiO2, CuO, ZnO semiconductors showed improved photocatalytic and optical properties. In this research, Ag/ZnO nanocomposite particles were prepared by Ultrasonic Spray Pyrolysis(USP) Method. 0.1M silver and zinc nitrate aqueous solutions were used as precursor solutions. The Ag:Zn atomic ratio of the solution was selected 1:1. Experiments were taken place under constant air flow of 400 mL/min at 800°C furnace temperature. Particles were characterized by X-Ray Diffraction (XRD), Scanning Electron Microscope (SEM) and Energy Dispersive Spectroscopy (EDS). The crystallite sizes of Ag and ZnO in composite particles are 24.6 nm, 19.7 nm respectively. Although, spherical nanocomposite particles are in a range of 300- 800 nm, these particles are formed by the aggregation of primary particles which are in a range of 20-60 nm.

System Identification with General Dynamic Neural Networks and Network Pruning

This paper presents an exact pruning algorithm with adaptive pruning interval for general dynamic neural networks (GDNN). GDNNs are artificial neural networks with internal dynamics. All layers have feedback connections with time delays to the same and to all other layers. The structure of the plant is unknown, so the identification process is started with a larger network architecture than necessary. During parameter optimization with the Levenberg- Marquardt (LM) algorithm irrelevant weights of the dynamic neural network are deleted in order to find a model for the plant as simple as possible. The weights to be pruned are found by direct evaluation of the training data within a sliding time window. The influence of pruning on the identification system depends on the network architecture at pruning time and the selected weight to be deleted. As the architecture of the model is changed drastically during the identification and pruning process, it is suggested to adapt the pruning interval online. Two system identification examples show the architecture selection ability of the proposed pruning approach.

Gas-Liquid Interaction on Perforated Plates

The paper deals with hydrodynamics of liquid-gas layers under gas streaming through liquid layer on perforated plates in column apparatuses. The plates with large apertures have been investigated especially. It was shown that hydrodynamic regularities for these plates are essentially different from known laws for foam forming on fine-perforated plates. Main regularities of liquid-gas interaction on plates with large apertures have been established.

Application of Artificial Neural Network to Forecast Actual Cost of a Project to Improve Earned Value Management System

This paper presents an application of Artificial Neural Network (ANN) to forecast actual cost of a project based on the earned value management system (EVMS). For this purpose, some projects randomly selected based on the standard data set , and it is produced necessary progress data such as actual cost ,actual percent complete , baseline cost and percent complete for five periods of project. Then an ANN with five inputs and five outputs and one hidden layer is trained to produce forecasted actual costs. The comparison between real and forecasted data show better performance based on the Mean Absolute Percentage Error (MAPE) criterion. This approach could be applicable to better forecasting the project cost and result in decreasing the risk of project cost overrun, and therefore it is beneficial for planning preventive actions.

Bangla Vowel Characterization Based on Analysis by Synthesis

Bangla Vowel characterization determines the spectral properties of Bangla vowels for efficient synthesis as well as recognition of Bangla vowels. In this paper, Bangla vowels in isolated word have been analyzed based on speech production model within the framework of Analysis-by-Synthesis. This has led to the extraction of spectral parameters for the production model in order to produce different Bangla vowel sounds. The real and synthetic spectra are compared and a weighted square error has been computed along with the error in the formant bandwidths for efficient representation of Bangla vowels. The extracted features produced good representation of targeted Bangla vowel. Such a representation also plays essential role in low bit rate speech coding and vocoders.

Factors Influencing the Success of Mobile Phone Entrepreneurs at Central Plaza

The purpose of this research was to study the factors that influenced the success of mobile phone entrepreneurs at Central Plaza. The sample group included 187 entrepreneurs at Central Plaza. A questionnaire was utilized as a tool to collect data. Statistics used in this research included frequency, percentage, mean, and standard deviation. Independent- sample t- test, one way ANOVA, and multiple regression analysis. Data were analyzed by using Statistical Package for the Social Sciences.The findings disclosed that the majority of respondents were male between 25-40 years old, and held an undergraduate degree. The average income of respondents was between 15,001-25,000 baht. The majority of respondents had less than 5 years of working experience. In terms of personality, the findings revealed that expression and agreement were ranked at the highest level. Whereas, emotion stability, consciousness, open to new experience were ranked at high. From the hypotheses testing, the findings revealed that different genders had different success in their mobile phone business with different income from the last 6 months. However, difference in age, income, level of education, and experience affected the success in terms of income, number of customers, and overall success of business. Moreover, the factors of personalities included expression, agreement, emotion stability, consciousness, open to new experience, and competitive strategy. From the findings, these factors were able to predict mobile phone business success at 66.9 percent.

The Biomechanical Properties of the Different Modalities of Surgically Corrected Coarctation of the Aorta in Neonates and Infants

Biomechanical properties of infantile aorta in vitro in cases of different standard anastomoses: end-to-end (ETE), extended anastomosis end-to-end (EETE) and subclavian flap aortoplasty (SFA) used for surgical correction of coarctation were analyzed to detect the influence of the method on the biomechanics of infantile aorta and possible changes in haemodinamics. 10 specimens of native aorta, 3 specimens with ETE, 4 EEET and 3 SFA were investigated. The experiments showed a non-linear relationship between stress and strain in the infantile aorta, the modulus of elasticity of the aortic wall increased with the increase of inner pressure. In the case of anastomosis end-to-end the modulus was almost constant, relevant to the modulus of elasticity of the aorta with the inner pressure 100-120 mmHg. The anastomoses EETE and SFA showed elastic properties closer to native aorta, the stiffness of ETE did not change with the changes in inner pressure.

Structural Basis of Resistance of Helicobacterpylori DnaK to Antimicrobial Peptide Pyrrhocoricin

Bacterial molecular chaperone DnaK plays an essential role in protein folding, stress response and transmembrane targeting of proteins. DnaKs from many bacterial species, including Escherichia coli, Salmonella typhimurium and Haemophilus infleunzae are the molecular targets for the insect-derived antimicrobial peptide pyrrhocoricin. Pyrrhocoricin-like peptides bind in the substrate recognition tunnel. Despite the high degree of crossspecies sequence conservation in the substrate-binding tunnel, some bacteria are not sensitive to pyrrhocoricin. This work addresses the molecular mechanism of resistance of Helicobacter pylori DnaK to pyrrhocoricin. Homology modelling, structural and sequence analysis identify a single aminoacid substitution at the interface between the lid and the β-sandwich subdomains of the DnaK substrate-binding domain as the major determinant for its resistance.

Pharmaceutical Applications and Clinical Efficiency of Anti-Inflammatory Ramon Preparation

The Ramon preparation is received from a plant; it is destined for external treatment of inflammations in post-surgery period. The Ramon is a biogenic immune stimulator accelerating metabolism, contributing to improvement of blood indexes, having general tonic, anti-inflammatory and bactericidal effect.

Finite Volume Model to Study the Effect of Buffer on Cytosolic Ca2+ Advection Diffusion

Calcium [Ca2+] is an important second messenger which plays an important role in signal transduction. There are several parameters that affect its concentration profile like buffer source etc. The effect of stationary immobile buffer on Ca2+ concentration has been incorporated which is a very important parameter needed to be taken into account in order to make the model more realistic. Interdependence of all the important parameters like diffusion coefficient and influx over [Ca2+] profile has been studied. Model is developed in the form of advection diffusion equation together with buffer concentration. A program has been developed using finite volume method for the entire problem and simulated on an AMD-Turion 32-bit machine to compute the numerical results.

Processes Simulation Study of Coal to Methanol Based on Gasification Technology

This study presents a simulation model for converting coal to methanol, based on gasification technology with the commercial chemical process simulator, Pro/II® V8.1.1. The methanol plant consists of air separation unit (ASU), gasification unit, gas clean-up unit, and methanol synthetic unit. The clean syngas is produced with the first three operating units, and the model has been verified with the reference data from United States Environment Protection Agency. The liquid phase methanol (LPMEOHTM) process is adopted in the methanol synthetic unit. Clean syngas goes through gas handing section to reach the reaction requirement, reactor loop/catalyst to generate methanol, and methanol distillation to get desired purity over 99.9 wt%. The ratio of the total energy combined with methanol and dimethyl ether to that of feed coal is 78.5% (gross efficiency). The net efficiency is 64.2% with the internal power consumption taken into account, based on the assumption that the efficiency of electricity generation is 40%.

Genetic-Based Planning with Recursive Subgoals

In this paper, we introduce an effective strategy for subgoal division and ordering based upon recursive subgoals and combine this strategy with a genetic-based planning approach. This strategy can be applied to domains with conjunctive goals. The main idea is to recursively decompose a goal into a set of serializable subgoals and to specify a strict ordering among the subgoals. Empirical results show that the recursive subgoal strategy reduces the size of the search space and improves the quality of solutions to planning problems.

Simulation of Increased Ambient Ozone to Estimate Nutrient Content and Genetic Change in Two Thai Soybean Cultivars

This research studied the simulation of increased ambient ozone to estimate nutrient content and genetic changes in two Thai soybean cultivars (Chiang Mai 60 and Srisumrong 1). Ozone stress conditions affected proteins and lipids. It was found that proteins decreased, but lipids increased. Srisumrong 1 cultivars were more sensitive to ozone stress than Chiang Mai 60 cultivars. The effect of ozone stress conditions on plant phenotype and genotype was analyzed using the AFLP technique for the 2 Thai soybean cultivars (Chiang Mai 60 and Srisumrong 1).

The Effect of Alternative Fuel Combustion in the Cement Kiln Main Burner on Production Capacity and Improvement with Oxygen Enrichment

A mathematical model based on a mass and energy balance for the combustion in a cement rotary kiln was developed. The model was used to investigate the impact of replacing about 45 % of the primary coal energy by different alternative fuels. Refuse derived fuel, waste wood, solid hazardous waste and liquid hazardous waste were used in the modeling. The results showed that in order to keep the kiln temperature unchanged, and thereby maintain the required clinker quality, the production capacity had to be reduced by 1-15 %, depending on the fuel type. The reason for the reduction is increased exhaust gas flow rates caused by the fuel characteristics. The model, which has been successfully validated in a full-scale experiment, was also used to show that the negative impact on the production capacity can be avoided if a relatively small part of the combustion air is replaced by pure oxygen.

Hybrid Markov Game Controller Design Algorithms for Nonlinear Systems

Markov games can be effectively used to design controllers for nonlinear systems. The paper presents two novel controller design algorithms by incorporating ideas from gametheory literature that address safety and consistency issues of the 'learned' control strategy. A more widely used approach for controller design is the H∞ optimal control, which suffers from high computational demand and at times, may be infeasible. We generate an optimal control policy for the agent (controller) via a simple Linear Program enabling the controller to learn about the unknown environment. The controller is facing an unknown environment and in our formulation this environment corresponds to the behavior rules of the noise modeled as the opponent. Proposed approaches aim to achieve 'safe-consistent' and 'safe-universally consistent' controller behavior by hybridizing 'min-max', 'fictitious play' and 'cautious fictitious play' approaches drawn from game theory. We empirically evaluate the approaches on a simulated Inverted Pendulum swing-up task and compare its performance against standard Q learning.

Magnesium Waste Evaluation in Moderate Temperature (70oC) Magnesium Borate Synthesis

Waste problem is becoming a future problem all over the world. Magnesium wastes which can be used in recycling processes are produced by many industrial activities. Magnesium borates which have useful properties such as; high heat resistance, corrosion resistance, supermechanical strength, superinsulation, light weight, high coefficient of elasticity and so on. Addition, magnesium borates have great potential in the development of ceramic and detergents industry, whisker-reinforced composites, antiwear, and reducing friction additives. In this study, using the starting materials of waste magnesium and H3BO3 the hydrothermal method was applied at a moderate temperature of 70oC with different reaction times. Several reaction times of waste magnesium to H3BO3 were selected as; 30, 60, 120, 240 minutes. After the synthesis, X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR) techniques were applied to products. As a result, the forms of Admontite [MgO(B2O3)3.7(H2O)] and Mcallisterite [Mg2(B6O7(OH)6)2.9(H2O)] were synthesized.

A Novel Implementation of Application Specific Instruction-set Processor (ASIP) using Verilog

The general purpose processors that are used in embedded systems must support constraints like execution time, power consumption, code size and so on. On the other hand an Application Specific Instruction-set Processor (ASIP) has advantages in terms of power consumption, performance and flexibility. In this paper, a 16-bit Application Specific Instruction-set processor for the sensor data transfer is proposed. The designed processor architecture consists of on-chip transmitter and receiver modules along with the processing and controlling units to enable the data transmission and reception on a single die. The data transfer is accomplished with less number of instructions as compared with the general purpose processor. The ASIP core operates at a maximum clock frequency of 1.132GHz with a delay of 0.883ns and consumes 569.63mW power at an operating voltage of 1.2V. The ASIP is implemented in Verilog HDL using the Xilinx platform on Virtex4.