Growing Zeolite Y on FeCrAlloy Metal

Structured catalysts formed from the growth of zeolites on substrates is an area of increasing interest due to the increased efficiency of the catalytic process, and the ability to provide superior heat transfer and thermal conductivity for both exothermic and endothermic processes. However, the generation of structured catalysts represents a significant challenge when balancing the relationship variables between materials properties and catalytic performance, with the Na2O, H2O and Al2O3 gel composition paying a significant role in this dynamic, thereby affecting the both the type and range of application. The structured catalyst films generated as part of this investigation have been characterised using a range of techniques, including X-ray diffraction (XRD), Electron microscopy (SEM), Energy Dispersive X-ray analysis (EDX) and Thermogravimetric Analysis (TGA), with the transition from oxide-on-alloy wires to hydrothermally synthesised uniformly zeolite coated surfaces being demonstrated using both SEM and XRD. The robustness of the coatings has been ascertained by subjecting these to thermal cycling (ambient to 550oC), with the results indicating that the synthesis time and gel compositions have a crucial effect on the quality of zeolite growth on the FeCrAlloy wires. Finally, the activity of the structured catalyst was verified by a series of comparison experiments with standard zeolite Y catalysts in powdered pelleted forms.

E-government Adoption in Romania

The Romanian government has been making significant attempts to make its services and information available on the Internet. According to the UN e-government survey conducted in 2008, Romania comes under mid range countries by utilization of egovernment (percent of utilization 41%). Romania-s national portal www.e-guvernare.ro aims at progressively making all services and information accessible through the portal. However, the success of these efforts depends, to a great extent, on how well the targeted users for such services, citizens in general, make use of them. For this reason, the purpose of the presented study was to identify what factors could affect the citizens' adoption of e-government services. The study is an extension of the Technology Acceptance Model. The proposed model was validated using data collected from 481 citizens. The results provided substantial support for all proposed hypotheses and showed the significance of the extended constructs.

Comparative Study of Transformed and Concealed Data in Experimental Designs and Analyses

This paper presents the comparative study of coded data methods for finding the benefit of concealing the natural data which is the mercantile secret. Influential parameters of the number of replicates (rep), treatment effects (τ) and standard deviation (σ) against the efficiency of each transformation method are investigated. The experimental data are generated via computer simulations under the specified condition of the process with the completely randomized design (CRD). Three ways of data transformation consist of Box-Cox, arcsine and logit methods. The difference values of F statistic between coded data and natural data (Fc-Fn) and hypothesis testing results were determined. The experimental results indicate that the Box-Cox results are significantly different from natural data in cases of smaller levels of replicates and seem to be improper when the parameter of minus lambda has been assigned. On the other hand, arcsine and logit transformations are more robust and obviously, provide more precise numerical results. In addition, the alternate ways to select the lambda in the power transformation are also offered to achieve much more appropriate outcomes.

An Algorithm for Detecting Seam Cracks in Steel Plates

In this study, we developed an algorithm for detecting seam cracks in a steel plate. Seam cracks are generated in the edge region of a steel plate. We used the Gabor filter and an adaptive double threshold method to detect them. To reduce the number of pseudo defects, features based on the shape of seam cracks were used. To evaluate the performance of the proposed algorithm, we tested 989 images with seam cracks and 9470 defect-free images. Experimental results show that the proposed algorithm is suitable for detecting seam cracks. However, it should be improved to increase the true positive rate.

An Automated Test Setup for the Characterization of Antenna in CATR

This paper describes the development of a fully automated measurement software for antenna radiation pattern measurements in a Compact Antenna Test Range (CATR). The CATR has a frequency range from 2-40 GHz and the measurement hardware includes a Network Analyzer for transmitting and Receiving the microwave signal and a Positioner controller to control the motion of the Styrofoam column. The measurement process includes Calibration of CATR with a Standard Gain Horn (SGH) antenna followed by Gain versus angle measurement of the Antenna under test (AUT). The software is designed to control a variety of microwave transmitter / receiver and two axis Positioner controllers through the standard General Purpose interface bus (GPIB) interface. Addition of new Network Analyzers is supported through a slight modification of hardware control module. Time-domain gating is implemented to remove the unwanted signals and get the isolated response of AUT. The gated response of the AUT is compared with the calibration data in the frequency domain to obtain the desired results. The data acquisition and processing is implemented in Agilent VEE and Matlab. A variety of experimental measurements with SGH antennas were performed to validate the accuracy of software. A comparison of results with existing commercial softwares is presented and the measured results are found to be within .2 dBm.

A Hybrid Fuzzy AGC in a Competitive Electricity Environment

This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.

Towards a Load Balancing Framework for an SMS–Based Service Invocation Environment

The drastic increase in the usage of SMS technology has led service providers to seek for a solution that enable users of mobile devices to access services through SMSs. This has resulted in the proposal of solutions towards SMS-based service invocation in service oriented environments. However, the dynamic nature of service-oriented environments coupled with sudden load peaks generated by service request, poses performance challenges to infrastructures for supporting SMS-based service invocation. To address this problem we adopt load balancing techniques. A load balancing model with adaptive load balancing and load monitoring mechanisms as its key constructs is proposed. The load balancing model then led to realization of Least Loaded Load Balancing Framework (LLLBF). Evaluation of LLLBF benchmarked with round robin (RR) scheme on the queuing approach showed LLLBF outperformed RR in terms of response time and throughput. However, LLLBF achieved better result in the cost of high processing power.

Implementation of TinyHash based on Hash Algorithm for Sensor Network

In recent years, it has been proposed security architecture for sensor network.[2][4]. One of these, TinySec by Chris Kalof, Naveen Sastry, David Wagner had proposed Link layer security architecture, considering some problems of sensor network. (i.e : energy, bandwidth, computation capability,etc). The TinySec employs CBC_mode of encryption and CBC-MAC for authentication based on SkipJack Block Cipher. Currently, This TinySec is incorporated in the TinyOS for sensor network security. This paper introduces TinyHash based on general hash algorithm. TinyHash is the module in order to replace parts of authentication and integrity in the TinySec. it implies that apply hash algorithm on TinySec architecture. For compatibility about TinySec, Components in TinyHash is constructed as similar structure of TinySec. And TinyHash implements the HMAC component for authentication and the Digest component for integrity of messages. Additionally, we define the some interfaces for service associated with hash algorithm.

A TRIZ-based Approach to Generation of Service-supporting Product Concepts

Recently, business environment and customer needs have become rapidly changing, hence it is very difficult to fulfill sophisticated customer needs by product or service innovation only. In practice, to cope with this problem, various manufacturing companies have developed services to combine with their products. Along with this, many academic studies on PSS (Product Service System) which is the integrated system of products and services have been conducted from the viewpoint of manufacturers. On the other hand, service providers are also attempting to develop service-supporting products to increase their service competitiveness and provide differentiated value. However, there is a lack of research based on the service-centric point of view. Accordingly, this paper proposes a concept generation method for service-supporting product development from the service-centric point of view. This method is designed to be executed in five consecutive steps: situation analysis, problem definition, problem resolution, solution evaluation, and concept generation. In the proposed approach, some tools of TRIZ (Theory of Solving Inventive Problem) such as ISQ (Innovative Situation Questionnaire) and 40 inventive principles are employed in order to define problems of the current services and solve them by generating service-supporting product concepts. This research contributes to the development of service-supporting products and service-centric PSSs.

Effect of Non Uniformity Factors and Assignment Factors on Errors in Charge Simulation Method with Point Charge Model

Charge Simulation Method (CSM) is one of the very widely used numerical field computation technique in High Voltage (HV) engineering. The high voltage fields of varying non uniformities are encountered in practice. CSM programs being case specific, the simulation accuracies heavily depend on the user (programmers) experience. Here is an effort to understand CSM errors and evolve some guidelines to setup accurate CSM models, relating non uniformities with assignment factors. The results are for the six-point-charge model of sphere-plane gap geometry. Using genetic algorithm (GA) as tool, optimum assignment factors at different non uniformity factors for this model have been evaluated and analyzed. It is shown that the symmetrically placed six-point-charge models can be good enough to set up CSM programs with potential errors less than 0.1% when the field non uniformity factor is greater than 2.64 (field utilization factor less than 52.76%).

Analysis of Physicochemical Properties on Prediction of R5, X4 and R5X4 HIV-1 Coreceptor Usage

Bioinformatics methods for predicting the T cell coreceptor usage from the array of membrane protein of HIV-1 are investigated. In this study, we aim to propose an effective prediction method for dealing with the three-class classification problem of CXCR4 (X4), CCR5 (R5) and CCR5/CXCR4 (R5X4). We made efforts in investigating the coreceptor prediction problem as follows: 1) proposing a feature set of informative physicochemical properties which is cooperated with SVM to achieve high prediction test accuracy of 81.48%, compared with the existing method with accuracy of 70.00%; 2) establishing a large up-to-date data set by increasing the size from 159 to 1225 sequences to verify the proposed prediction method where the mean test accuracy is 88.59%, and 3) analyzing the set of 14 informative physicochemical properties to further understand the characteristics of HIV-1coreceptors.

Online Learning Activities Kit on Plants in Thai Literature in Compliance with the School Botanical Garden of Plant Genetic Conservation Project under the Royal Initiative of Her Royal Highness Princess Maha Chakri Sirindhorn

This research was aimed to develop and determine the quality of online learning activities kit as well as to examine the learning achievement of students and their satisfaction towards the kit through authentic assessment. The tools in this research contained online learning activities kit on plant in Thai literature in compliance with the School Botanical Garden of Plant Genetic Conservation Project under the Royal Initiative of Her Royal Highness Princess Maha Chakri Sirindhorn, the assessment form, the learning achievement test, the satisfaction form and the authentic assessment form. The population consisted of 40 students in the second range of primary years (Prathomsuksa 4 to 6) at Ban Khao Rak School, Suratthani Province, Thailand. The research results showed that the content quality of the developed online learning activities kit as assessed by the experts was 4.70 on average or at very high level. The pre-test and post-test comparison was made to examine the learning achievement and it revealed that the post-test score was higher than the pre-test score with statistical significance at the .01 level. The satisfaction of the sampling group towards the online learning activities kit was 4.74 or at the highest level. The authentic assessment showed an average of 1.69 or at good level. Therefore, the online learning activities kit on plant in Thai literature in compliance with the School Botanical Garden of Plant Genetic Conservation Project under the Royal Initiative of Her Royal Highness Princess Maha Chakri Sirindhorn could be used in real classroom situations.

Single Frame Supercompression of Still Images,Video, High Definition TV and Digital Cinema

Super-resolution is nowadays used for a high-resolution image produced from several low-resolution noisy frames. In this work, we consider the problem of high-quality interpolation of a single noise-free image. Such images may come from different sources, i.e., they may be frames of videos, individual pictures, etc. On the other hand, in the encoder we apply a downsampling via bidimen-sional interpolation of each frame, and in the decoder we apply a upsampling by which we restore the original size of the image. If the compression ratio is very high, then we use a convolutive mask that restores the edges, eliminating the blur. Finally, both, the encoder and the complete decoder are implemented on General-Purpose computation on Graphics Processing Units (GPGPU) cards. In fact, the mentioned mask is coded inside texture memory of a GPGPU.

Use of Fuzzy Edge Image in Block Truncation Coding for Image Compression

An image compression method has been developed using fuzzy edge image utilizing the basic Block Truncation Coding (BTC) algorithm. The fuzzy edge image has been validated with classical edge detectors on the basis of the results of the well-known Canny edge detector prior to applying to the proposed method. The bit plane generated by the conventional BTC method is replaced with the fuzzy bit plane generated by the logical OR operation between the fuzzy edge image and the corresponding conventional BTC bit plane. The input image is encoded with the block mean and standard deviation and the fuzzy bit plane. The proposed method has been tested with test images of 8 bits/pixel and size 512×512 and found to be superior with better Peak Signal to Noise Ratio (PSNR) when compared to the conventional BTC, and adaptive bit plane selection BTC (ABTC) methods. The raggedness and jagged appearance, and the ringing artifacts at sharp edges are greatly reduced in reconstructed images by the proposed method with the fuzzy bit plane.

Stochastic Programming Model for Power Generation

We consider power system expansion planning under uncertainty. In our approach, integer programming and stochastic programming provide a basic framework. We develop a multistage stochastic programming model in which some of the variables are restricted to integer values. By utilizing the special property of the problem, called block separable recourse, the problem is transformed into a two-stage stochastic program with recourse. The electric power capacity expansion problem is reformulated as the problem with first stage integer variables and continuous second stage variables. The L-shaped algorithm to solve the problem is proposed.

Application of a Similarity Measure for Graphs to Web-based Document Structures

Due to the tremendous amount of information provided by the World Wide Web (WWW) developing methods for mining the structure of web-based documents is of considerable interest. In this paper we present a similarity measure for graphs representing web-based hypertext structures. Our similarity measure is mainly based on a novel representation of a graph as linear integer strings, whose components represent structural properties of the graph. The similarity of two graphs is then defined as the optimal alignment of the underlying property strings. In this paper we apply the well known technique of sequence alignments for solving a novel and challenging problem: Measuring the structural similarity of generalized trees. In other words: We first transform our graphs considered as high dimensional objects in linear structures. Then we derive similarity values from the alignments of the property strings in order to measure the structural similarity of generalized trees. Hence, we transform a graph similarity problem to a string similarity problem for developing a efficient graph similarity measure. We demonstrate that our similarity measure captures important structural information by applying it to two different test sets consisting of graphs representing web-based document structures.

Hutchinson-Barnsley Operator in Intuitionistic Fuzzy Metric Spaces

The main purpose of this paper is to prove the intuitionistic fuzzy contraction properties of the Hutchinson-Barnsley operator on the intuitionistic fuzzy hyperspace with respect to the Hausdorff intuitionistic fuzzy metrics. Also we discuss about the relationships between the Hausdorff intuitionistic fuzzy metrics on the intuitionistic fuzzy hyperspaces. Our theorems generalize and extend some recent results related with Hutchinson-Barnsley operator in the metric spaces to the intuitionistic fuzzy metric spaces.

Exploiting Two Intelligent Models to Predict Water Level: A Field Study of Urmia Lake, Iran

Water level forecasting using records of past time series is of importance in water resources engineering and management. For example, water level affects groundwater tables in low-lying coastal areas, as well as hydrological regimes of some coastal rivers. Then, a reliable prediction of sea-level variations is required in coastal engineering and hydrologic studies. During the past two decades, the approaches based on the Genetic Programming (GP) and Artificial Neural Networks (ANN) were developed. In the present study, the GP is used to forecast daily water level variations for a set of time intervals using observed water levels. The measurements from a single tide gauge at Urmia Lake, Northwest Iran, were used to train and validate the GP approach for the period from January 1997 to July 2008. Statistics, the root mean square error and correlation coefficient, are used to verify model by comparing with a corresponding outputs from Artificial Neural Network model. The results show that both these artificial intelligence methodologies are satisfactory and can be considered as alternatives to the conventional harmonic analysis.

Swarm Intelligence based Optimal Linear Phase FIR High Pass Filter Design using Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach

In this paper, an optimal design of linear phase digital high pass finite impulse response (FIR) filter using Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach (PSO-CFIWA) has been presented. In the design process, the filter length, pass band and stop band frequencies, feasible pass band and stop band ripple sizes are specified. FIR filter design is a multi-modal optimization problem. The conventional gradient based optimization techniques are not efficient for digital filter design. Given the filter specifications to be realized, the PSO-CFIWA algorithm generates a set of optimal filter coefficients and tries to meet the ideal frequency response characteristic. In this paper, for the given problem, the designs of the optimal FIR high pass filters of different orders have been performed. The simulation results have been compared to those obtained by the well accepted algorithms such as Parks and McClellan algorithm (PM), genetic algorithm (GA). The results justify that the proposed optimal filter design approach using PSOCFIWA outperforms PM and GA, not only in the accuracy of the designed filter but also in the convergence speed and solution quality.

Multi-matrix Real-coded Genetic Algorithm for Minimising Total Costs in Logistics Chain Network

The importance of supply chain and logistics management has been widely recognised. Effective management of the supply chain can reduce costs and lead times and improve responsiveness to changing customer demands. This paper proposes a multi-matrix real-coded Generic Algorithm (MRGA) based optimisation tool that minimises total costs associated within supply chain logistics. According to finite capacity constraints of all parties within the chain, Genetic Algorithm (GA) often produces infeasible chromosomes during initialisation and evolution processes. In the proposed algorithm, chromosome initialisation procedure, crossover and mutation operations that always guarantee feasible solutions were embedded. The proposed algorithm was tested using three sizes of benchmarking dataset of logistic chain network, which are typical of those faced by most global manufacturing companies. A half fractional factorial design was carried out to investigate the influence of alternative crossover and mutation operators by varying GA parameters. The analysis of experimental results suggested that the quality of solutions obtained is sensitive to the ways in which the genetic parameters and operators are set.