Influence of UV Treatment on the Electrooptical Properties of Indium Tin Oxide Films Used in Flexible Displays

Indium-tin oxide films are deposited by low plasma temperature RF sputtering on highly flexible modification of glycol polyethyleneterephtalate substrates. The produced layers are characterized with transparency over 82 % and sheet resistance of 86.9 Ω/square. The film’s conductivity was further improved by additional UV illumination from light source (365 nm), having power of 250 W. The influence of the UV exposure dose on the structural and electro-optical properties of ITO was investigated. It was established that the optimum time of illumination is 10 minutes and further UV treatment leads to polymer substrates degradation. Structural and bonds type analysis show that at longer treatment carbon atoms release and diffuse into ITO films, which worsen their electrical behavior. For the optimum UV dose the minimum sheet resistance was measured to be 19.2 Ω/square, and the maximum transparency remained almost unchanged – above 82 %.

Numerical Investigation on Latent Heat Storage Unit of Different Configurations

The storage of thermal energy as a latent heat of phase change material (PCM) has created considerable interest among researchers in recent times. Here, an attempt is made to carry out numerical investigations to analyze the performance of latent heat storage units (LHSU) employing phase change material. The mathematical model developed is based on an enthalpy formulation. Freezing time of PCM packed in three different shaped containers viz. rectangular, cylindrical and cylindrical shell is compared. The model is validated with the results available in the literature. Results show that for the same mass of PCM and surface area of heat transfer, cylindrical shell container takes the least time for freezing the PCM and this geometric effect is more pronounced with an increase in the thickness of the shell than that of length of the shell.

Analysis of Combustion, Performance and Emission Characteristics of Turbocharged LHR Extended Expansion DI Diesel Engine

The fundamental aim of extended expansion concept is to achieve higher work done which in turn leads to higher thermal efficiency. This concept is compatible with the application of turbocharger and LHR engine. The Low Heat Rejection engine was developed by coating the piston crown, cylinder head inside with valves and cylinder liner with partially stabilized zirconia coating of 0.5 mm thickness. Extended expansion in diesel engines is termed as Miller cycle in which the expansion ratio is increased by reducing the compression ratio by modifying the inlet cam for late inlet valve closing. The specific fuel consumption reduces to an appreciable level and the thermal efficiency of the extended expansion turbocharged LHR engine is improved. In this work, a thermodynamic model was formulated and developed to simulate the LHR based extended expansion turbocharged direct injection diesel engine. It includes a gas flow model, a heat transfer model, and a two zone combustion model. Gas exchange model is modified by incorporating the Miller cycle, by delaying inlet valve closing timing which had resulted in considerable improvement in thermal efficiency of turbocharged LHR engines. The heat transfer model, calculates the convective and radiative heat transfer between the gas and wall by taking into account of the combustion chamber surface temperature swings. Using the two-zone combustion model, the combustion parameters and the chemical equilibrium compositions were determined. The chemical equilibrium compositions were used to calculate the Nitric oxide formation rate by assuming a modified Zeldovich mechanism. The accuracy of this model is scrutinized against actual test results from the engine. The factors which affect thermal efficiency and exhaust emissions were deduced and their influences were discussed. In the final analysis it is seen that there is an excellent agreement in all of these evaluations.

Improvement of Stator Slot Structure based on Insulation Stresses Analysis in HV Generator

High voltage generators are being subject to higher voltage rating and are being designed to operate in harsh conditions. Stator windings are the main component of generators in which Electrical, magnetical and thermal stresses remain major failures for insulation degradation accelerated aging. A large number of generators failed due to stator winding problems, mainly insulation deterioration. Insulation degradation assessment plays vital role in the asset life management. Mostly the stator failure is catastrophic causing significant damage to the plant. Other than generation loss, stator failure involves heavy repair or replacement cost. Electro thermal analysis is the main characteristic for improvement design of stator slot-s insulation. Dielectric parameters such as insulation thickness, spacing, material types, geometry of winding and slot are major design consideration. A very powerful method available to analyze electro thermal performance is Finite Element Method (FEM) which is used in this paper. The analysis of various stator coil and slot configurations are used to design the better dielectric system to reduce electrical and thermal stresses in order to increase the power of generator in the same volume of core. This paper describes the process used to perform classical design and improvement analysis of stator slot-s insulation.

A Design of Array Transcranial Magnetic Stimulation Coil System

This research proposed a new design of helmet-shaped array transcranial magnetic stimulation coil system. It was constructed using several sagittal directional wires and several coronal directional wires. By varying the current direction and strength on each wire, this array coil system could be constructed into the circular coil and figure-eight coil of different size. Also, this proposed coil system can flexibly not only change the stimulation location, range, type and strength, but also change the shape and the channel number of coil dynamically.

Roll of Membership functions in Fuzzy Logic for Prediction of Shoot Length of Mustard Plant Based on Residual Analysis

The selection for plantation of a particular type of mustard plant depending on its productivity (pod yield) at the stage of maturity. The growth of mustard plant dependent on some parameters of that plant, these are shoot length, number of leaves, number of roots and roots length etc. As the plant is growing, some leaves may be fall down and some new leaves may come, so it can not gives the idea to develop the relationship with the seeds weight at mature stage of that plant. It is not possible to find the number of roots and root length of mustard plant at growing stage that will be harmful of this plant as roots goes deeper to deeper inside the land. Only the value of shoot length which increases in course of time can be measured at different time instances. Weather parameters are maximum and minimum humidity, rain fall, maximum and minimum temperature may effect the growth of the plant. The parameters of pollution, water, soil, distance and crop management may be dominant factors of growth of plant and its productivity. Considering all parameters, the growth of the plant is very uncertain, fuzzy environment can be considered for the prediction of shoot length at maturity of the plant. Fuzzification plays a greater role for fuzzification of data, which is based on certain membership functions. Here an effort has been made to fuzzify the original data based on gaussian function, triangular function, s-function, Trapezoidal and L –function. After that all fuzzified data are defuzzified to get normal form. Finally the error analysis (calculation of forecasting error and average error) indicates the membership function appropriate for fuzzification of data and use to predict the shoot length at maturity. The result is also verified using residual (Absolute Residual, Maximum of Absolute Residual, Mean Absolute Residual, Mean of Mean Absolute Residual, Median of Absolute Residual and Standard Deviation) analysis.

Comparison of Compression Ability Using DCT and Fractal Technique on Different Imaging Modalities

Image compression is one of the most important applications Digital Image Processing. Advanced medical imaging requires storage of large quantities of digitized clinical data. Due to the constrained bandwidth and storage capacity, however, a medical image must be compressed before transmission and storage. There are two types of compression methods, lossless and lossy. In Lossless compression method the original image is retrieved without any distortion. In lossy compression method, the reconstructed images contain some distortion. Direct Cosine Transform (DCT) and Fractal Image Compression (FIC) are types of lossy compression methods. This work shows that lossy compression methods can be chosen for medical image compression without significant degradation of the image quality. In this work DCT and Fractal Compression using Partitioned Iterated Function Systems (PIFS) are applied on different modalities of images like CT Scan, Ultrasound, Angiogram, X-ray and mammogram. Approximately 20 images are considered in each modality and the average values of compression ratio and Peak Signal to Noise Ratio (PSNR) are computed and studied. The quality of the reconstructed image is arrived by the PSNR values. Based on the results it can be concluded that the DCT has higher PSNR values and FIC has higher compression ratio. Hence in medical image compression, DCT can be used wherever picture quality is preferred and FIC is used wherever compression of images for storage and transmission is the priority, without loosing picture quality diagnostically.

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.

A Dynamic RGB Intensity Based Steganography Scheme

Steganography meaning covered writing. Steganography includes the concealment of information within computer files [1]. In other words, it is the Secret communication by hiding the existence of message. In this paper, we will refer to cover image, to indicate the images that do not yet contain a secret message, while we will refer to stego images, to indicate an image with an embedded secret message. Moreover, we will refer to the secret message as stego-message or hidden message. In this paper, we proposed a technique called RGB intensity based steganography model as RGB model is the technique used in this field to hide the data. The methods used here are based on the manipulation of the least significant bits of pixel values [3][4] or the rearrangement of colors to create least significant bit or parity bit patterns, which correspond to the message being hidden. The proposed technique attempts to overcome the problem of the sequential fashion and the use of stego-key to select the pixels.

Stability Analysis of Impulsive BAM Fuzzy Cellular Neural Networks with Distributed Delays and Reaction-diffusion Terms

In this paper, a class of impulsive BAM fuzzy cellular neural networks with distributed delays and reaction-diffusion terms is formulated and investigated. By employing the delay differential inequality and inequality technique developed by Xu et al., some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for impulsive BAM fuzzy cellular neural networks with distributed delays and reaction-diffusion terms are obtained. In particular, the estimate of the exponential convergence rate is also provided, which depends on system parameters, diffusion effect and impulsive disturbed intention. It is believed that these results are significant and useful for the design and applications of BAM fuzzy cellular neural networks. An example is given to show the effectiveness of the results obtained here.

Forward Kinematics Analysis of a 3-PRS Parallel Manipulator

In this article the homotopy continuation method (HCM) to solve the forward kinematic problem of the 3-PRS parallel manipulator is used. Since there are many difficulties in solving the system of nonlinear equations in kinematics of manipulators, the numerical solutions like Newton-Raphson are inevitably used. When dealing with any numerical solution, there are two troublesome problems. One is that good initial guesses are not easy to detect and another is related to whether the used method will converge to useful solutions. Results of this paper reveal that the homotopy continuation method can alleviate the drawbacks of traditional numerical techniques.

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.

Measuring the Efficiency of Medical Equipment

the reliability analysis of the medical equipments can help to increase the availability and the efficiency of the systems. In this manuscript we present a simple method of decomposition that could be easily applied on the complex medical systems. Using this method we can easily calculate the effect of the subsystems or components on the reliability of the overall system. Furthermore, to investigate the effect of subsystems or components on system performance, we perform a numerical study varying every time the worst reliability of subsystem or component with another which has higher reliability. It can also be useful to engineers and designers of medical equipment, who wishes to optimize the complex systems.

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.

Approaches and Schemes for Storing DTDIndependent XML Data in Relational Databases

The volume of XML data exchange is explosively increasing, and the need for efficient mechanisms of XML data management is vital. Many XML storage models have been proposed for storing XML DTD-independent documents in relational database systems. Benchmarking is the best way to highlight pros and cons of different approaches. In this study, we use a common benchmarking scheme, known as XMark to compare the most cited and newly proposed DTD-independent methods in terms of logical reads, physical I/O, CPU time and duration. We show the effect of Label Path, extracting values and storing in another table and type of join needed for each method-s query answering.

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.

An Augmented Automatic Choosing Control with Constrained Input Using Weighted Gradient Optimization Automatic Choosing Functions

In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) for nonlinear systems with constrained input using weighted gradient optimization automatic choosing functions. Constant term which arises from linearization of a given nonlinear system is treated as a coefficient of a stable zero dynamics. Parameters of the control are suboptimally selected by maximizing the stable region in the sense of Lyapunov with the aid of a genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.

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.

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.

Exploring the Professional Competency Contents for International Marketer in Taiwan

The main purpose of this study was to establish Professional Competency Contents for International Marketer in Taiwan. To establish these contents a set of interviews with international marketing managers and three rounds of Delphi Technique surveys were employed. Five international marketing managers were interviewed for discussions on definitions, framework, and items of international marketing competency. A questionnaire for the " Delphi Technique Survey " was developed based on the results acquired from the interviews. The resulting questionnaire was distributed to another group of 30 international marketer of trading companies in Taiwan. After three rounds of Delphi Technique Survey with these participants, the "Contents of Professional Competency for International Marketer " was established. Five dimensions and thirty indicators were identified. It is hoped that the proposed contents could be served as a self-evaluation tool for international marketer as well as the basis for staffing and training programs for international marketer in Taiwan.