Linear Elasticity Problems Solved by Using the Fictitious Domain Method and Total - FETI Domain Decomposition

The main goal of this paper is to show a possibility, how to solve numerically elliptic boundary value problems arising in 2D linear elasticity by using the fictitious domain method (FDM) and the Total-FETI domain decomposition method. We briefly mention the theoretical background of these methods and demonstrate their performance on a benchmark.

PIELG: A Protein Interaction Extraction Systemusing a Link Grammar Parser from Biomedical Abstracts

Due to the ever growing amount of publications about protein-protein interactions, information extraction from text is increasingly recognized as one of crucial technologies in bioinformatics. This paper presents a Protein Interaction Extraction System using a Link Grammar Parser from biomedical abstracts (PIELG). PIELG uses linkage given by the Link Grammar Parser to start a case based analysis of contents of various syntactic roles as well as their linguistically significant and meaningful combinations. The system uses phrasal-prepositional verbs patterns to overcome preposition combinations problems. The recall and precision are 74.4% and 62.65%, respectively. Experimental evaluations with two other state-of-the-art extraction systems indicate that PIELG system achieves better performance. For further evaluation, the system is augmented with a graphical package (Cytoscape) for extracting protein interaction information from sequence databases. The result shows that the performance is remarkably promising.

A Laboratory Assistance Module

We propose that Virtual Learning Environments (VLEs) should be designed by taking into account the characteristics, the special needs and the specific operating rules of the academic institutions in which they are employed. In this context, we describe a VLE module that extends the support of the organization and delivery of course material by including administration activities related to the various stages of teaching. These include the co-ordination, collaboration and monitoring of the course material development process and institution-specific course material delivery modes. Our specialized module, which enhances VLE capabilities by Helping Educators and Learners through a Laboratory Assistance System, is willing to assist the Greek tertiary technological sector, which includes Technological Educational Institutes (T.E.I.).

A New Approach to Face Recognition Using Dual Dimension Reduction

In this paper a new approach to face recognition is presented that achieves double dimension reduction, making the system computationally efficient with better recognition results and out perform common DCT technique of face recognition. In pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results change with change in face image resolution and provide optimal results when arriving at a certain resolution level. In the proposed model of face recognition, initially image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Due to increased computational speed and feature extraction potential of Discrete Cosine Transform (DCT), it is applied on face image. A subset of coefficients of DCT from low to mid frequencies that represent the face adequately and provides best recognition results is retained. A tradeoff between decimation factor, number of DCT coefficients retained and recognition rate with minimum computation is obtained. Preprocessing of the image is carried out to increase its robustness against variations in poses and illumination level. This new model has been tested on different databases which include ORL , Yale and EME color database.

An Algorithm Proposed for FIR Filter Coefficients Representation

Finite impulse response (FIR) filters have the advantage of linear phase, guaranteed stability, fewer finite precision errors, and efficient implementation. In contrast, they have a major disadvantage of high order need (more coefficients) than IIR counterpart with comparable performance. The high order demand imposes more hardware requirements, arithmetic operations, area usage, and power consumption when designing and fabricating the filter. Therefore, minimizing or reducing these parameters, is a major goal or target in digital filter design task. This paper presents an algorithm proposed for modifying values and the number of non-zero coefficients used to represent the FIR digital pulse shaping filter response. With this algorithm, the FIR filter frequency and phase response can be represented with a minimum number of non-zero coefficients. Therefore, reducing the arithmetic complexity needed to get the filter output. Consequently, the system characteristic i.e. power consumption, area usage, and processing time are also reduced. The proposed algorithm is more powerful when integrated with multiplierless algorithms such as distributed arithmetic (DA) in designing high order digital FIR filters. Here the DA usage eliminates the need for multipliers when implementing the multiply and accumulate unit (MAC) and the proposed algorithm will reduce the number of adders and addition operations needed through the minimization of the non-zero values coefficients to get the filter output.

Neuro-fuzzy Model and Regression Model a Comparison Study of MRR in Electrical Discharge Machining of D2 Tool Steel

In the current research, neuro-fuzzy model and regression model was developed to predict Material Removal Rate in Electrical Discharge Machining process for AISI D2 tool steel with copper electrode. Extensive experiments were conducted with various levels of discharge current, pulse duration and duty cycle. The experimental data are split into two sets, one for training and the other for validation of the model. The training data were used to develop the above models and the test data, which was not used earlier to develop these models were used for validation the models. Subsequently, the models are compared. It was found that the predicted and experimental results were in good agreement and the coefficients of correlation were found to be 0.999 and 0.974 for neuro fuzzy and regression model respectively

Some Solid Transportation Models with Crisp and Rough Costs

In this paper, some practical solid transportation models are formulated considering per trip capacity of each type of conveyances with crisp and rough unit transportation costs. This is applicable for the system in which full vehicles, e.g. trucks, rail coaches are to be booked for transportation of products so that transportation cost is determined on the full of the conveyances. The models with unit transportation costs as rough variables are transformed into deterministic forms using rough chance constrained programming with the help of trust measure. Numerical examples are provided to illustrate the proposed models in crisp environment as well as with unit transportation costs as rough variables.

Uniformity of Dose Distribution in Radiation Fields Surrounding the Spine using Film Dosimetry and Comparison with 3D Treatment Planning Software

The overall penumbra is usually defined as the distance, p20–80, separating the 20% and 80% of the dose on the beam axis at the depth of interest. This overall penumbra accounts also for the fact that some photons emitted by the distal parts of the source are only partially attenuated by the collimator. Medulloblastoma is the most common type of childhood brain tumor and often spreads to the spine. Current guidelines call for surgery to remove as much of the tumor as possible, followed by radiation of the brain and spinal cord, and finally treatment with chemotherapy. The purpose of this paper was to present results on an Uniformity of dose distribution in radiation fields surrounding the spine using film dosimetry and comparison with 3D treatment planning software.

Empirical Analyses of Determinants of D.J.S.I.US Mean Returns

This study investigates the relationship between 10 year bond value, Yen/U.S dollar exchange rate, non-farm payrolls (all employs) and crude oil to U.S. Dow Jones Sustainability Index. A GARCH model is used to test these relationships for the period January 1st 1999 to January 31st 2008 using monthly data. Results show that an increase of the 10 year bond and non farm payrolls (all employs) lead to an increase of the D.J.S.I returns. On the contrary the volatility of the Yen/U.S dollar exchange rates as well as the increase of crude oil returns has negative effects on the U.S D.J.S.I returns. This study aims at assisting investors to understand the influences certain macroeconomic indicators have on the companies- stock returns as reported by the D.J.S.I.

Ranking Genes from DNA Microarray Data of Cervical Cancer by a local Tree Comparison

The major objective of this paper is to introduce a new method to select genes from DNA microarray data. As criterion to select genes we suggest to measure the local changes in the correlation graph of each gene and to select those genes whose local changes are largest. More precisely, we calculate the correlation networks from DNA 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 tumor progression. 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. This indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.

Influence of Hydrocarbons on Plant Cell Ultrastructure and Main Metabolic Enzymes

Influence of octane and benzene on plant cell ultrastructure and enzymes of basic metabolism, such as nitrogen assimilation and energy generation have been studied. Different plants: perennial ryegrass (Lolium perenne) and alfalfa (Medicago sativa); crops- maize (Zea mays L.) and bean (Phaseolus vulgaris); shrubs – privet (Ligustrum sempervirens) and trifoliate orange (Poncirus trifoliate); trees - poplar (Populus deltoides) and white mulberry (Morus alba L.) were exposed to hydrocarbons of different concentrations (1, 10 and 100 mM). Destructive changes in bean and maize leaves cells ultrastructure under the influence of benzene vapour were revealed at the level of photosynthetic and energy generation subcellular organells. Different deviations at the level of subcellular organelles structure and distribution were observed in alfalfa and ryegrass root cells under the influence of benzene and octane, absorbed through roots. The level of destructive changes is concentration dependent. Benzene at low 1 and 10 mM concentration caused the increase in glutamate dehydrogenase (GDH) activity in maize roots and leaves and in poplar and mulberry shoots, though to higher extent in case of lower, 1mM concentration. The induction was more intensive in plant roots. The highest tested 100mM concentration of benzene was inhibitory to the enzyme in all plants. Octane caused induction of GDH in all grassy plants at all tested concentrations; however the rate of induction decreased parallel to increase of the hydrocarbon concentration. Octane at concentration 1 mM caused induction of GDH in privet, trifoliate and white mulberry shoots. The highest, 100mM octane was characterized by inhibitory effect to GDH activity in all plants. Octane had inductive effect on malate dehydrogenase in almost all plants and tested concentrations, indicating the intensification of Trycarboxylic Acid Cycle. The data could be suggested for elaboration of criteria for plant selection for phytoremediation of oil hydrocarbons contaminated soils.

Thermal Modeling of Dry-Transformers and Estimating Temperature Rise

Temperature rise in a transformer depends on variety of parameters such as ambient temperature, output current and type of the core. Considering these parameters, temperature rise estimation is still complicated procedure. In this paper, we present a new model based on simple electrical equivalent circuit. This method avoids the complication associated to accurate estimation and is in very good agreement with practice.

Ageing Deterioration of Silicone Rubber Polymer Insulator under Salt Water Dip Wheel Test

This paper presents the experimental results of silicone rubber polymer insulators for 22 kV systems under salt water dip wheel test based on IEC 62217. Straight shed silicone rubber polymer insulators having leakage distance 685 mm were tested continuously 30,000 cycles. One test cycle includes 4 positions, energized, de-energized, salt water dip and deenergized, respectively. For one test cycle, each test specimen remains stationary for about 40 second in each position and takes 8 second for rotate to next position. By visual observation, sever surface erosion was observed on the trunk near the energized end of tested specimen. Puncture was observed on the upper shed near the energized end. In addition, decreasing in hydrophobicity and increasing in hardness were measured on tested specimen comparing with new specimen. Furthermore, chemical analysis by ATR-FTIR was conducted in order to elucidate the chemical change of tested specimens comparing with new specimen.

Size Control of Nanoparticles Using a Microfluidic Device

We have developed a microfluidic device system for the continuous producting of nanoparticles, and we have clarified the relationship between the mixing performance of reactors and the particle size. First, we evaluated the mixing performance of reactors by carring out the Villermaux–Dushman reaction and determined the experimental conditions for producing AgCl nanoparticles. Next, we produced AgCl nanoparticles and evaluated the mixing performance and the particle size. We found that as the mixing performance improves the size of produced particles decreases and the particle size distribution becomes sharper. We produced AgCl nanoparticles with a size of 86 nm using the microfluidic device that had the best mixing performance among the three reactors we tested in this study; the coefficient of variation (Cv) of the size distribution of the produced nanoparticles was 26.1%.

A New Measure of Herding Behavior: Derivation and Implications

If price and quantity are the fundamental building blocks of any theory of market interactions, the importance of trading volume in understanding the behavior of financial markets is clear. However, while many economic models of financial markets have been developed to explain the behavior of prices -predictability, variability, and information content- far less attention has been devoted to explaining the behavior of trading volume. In this article, we hope to expand our understanding of trading volume by developing a new measure of herding behavior based on a cross sectional dispersion of volumes betas. We apply our measure to the Toronto stock exchange using monthly data from January 2000 to December 2002. Our findings show that the herd phenomenon consists of three essential components: stationary herding, intentional herding and the feedback herding.

Enhancing K-Means Algorithm with Initial Cluster Centers Derived from Data Partitioning along the Data Axis with the Highest Variance

In this paper, we propose an algorithm to compute initial cluster centers for K-means clustering. Data in a cell is partitioned using a cutting plane that divides cell in two smaller cells. The plane is perpendicular to the data axis with the highest variance and is designed to reduce the sum squared errors of the two cells as much as possible, while at the same time keep the two cells far apart as possible. Cells are partitioned one at a time until the number of cells equals to the predefined number of clusters, K. The centers of the K cells become the initial cluster centers for K-means. The experimental results suggest that the proposed algorithm is effective, converge to better clustering results than those of the random initialization method. The research also indicated the proposed algorithm would greatly improve the likelihood of every cluster containing some data in it.

Spatial Variability in Human Development Patterns in Assiut, Egypt

Given the motivation of maps impact in enhancing the perception of the quality of life in a region, this work examines the use of spatial analytical techniques in exploring the role of space in shaping human development patterns in Assiut governorate. Variations of human development index (HDI) of the governorate-s villages, districts and cities are mapped using geographic information systems (GIS). Global and local spatial autocorrelation measures are employed to assess the levels of spatial dependency in the data and to map clusters of human development. Results show prominent disparities in HDI between regions of Assiut. Strong patterns of spatial association were found proving the presence of clusters on the distribution of HDI. Finally, the study indicates several "hot-spots" in the governorate to be area of more investigations to explore the attributes of such levels of human development. This is very important for accomplishing the development plan of poorest regions currently adopted in Egypt.

The Management in Large Emergency Situations – A Best Practise Case Study based on GIS for Management of Evacuation

In most of the cases, natural disasters lead to the necessity of evacuating people. The quality of evacuation management is dramatically improved by the use of information provided by decision support systems, which become indispensable in case of large scale evacuation operations. This paper presents a best practice case study. In November 2007, officers from the Emergency Situations Inspectorate “Crisana" of Bihor County from Romania participated to a cross-border evacuation exercise, when 700 people have been evacuated from Netherlands to Belgium. One of the main objectives of the exercise was the test of four different decision support systems. Afterwards, based on that experience, software system called TEVAC (Trans Border Evacuation) has been developed “in house" by the experts of this institution. This original software system was successfully tested in September 2008, during the deployment of the international exercise EU-HUROMEX 2008, the scenario involving real evacuation of 200 persons from Hungary to Romania. Based on the lessons learned and results, starting from April 2009, the TEVAC software is used by all Emergency Situations Inspectorates all over Romania.

A Comparison between Heterogeneous and Homogeneous Gas Flow Model in Slurry Bubble Column Reactor for Direct Synthesis of DME

In the present study, a heterogeneous and homogeneous gas flow dispersion model for simulation and optimisation of a large-scale catalytic slurry reactor for the direct synthesis of dimethyl ether (DME) from syngas and CO2, using a churn-turbulent regime was developed. In the heterogeneous gas flow model the gas phase was distributed into two bubble phases: small and large, however in the homogeneous one, the gas phase was distributed into only one large bubble phase. The results indicated that the heterogeneous gas flow model was in more agreement with experimental pilot plant data than the homogeneous one.

Using Visual Technologies to Promote Excellence in Computer Science Education

The purposes of this paper are to (1) promote excellence in computer science by suggesting a cohesive innovative approach to fill well documented deficiencies in current computer science education, (2) justify (using the authors' and others anecdotal evidence from both the classroom and the real world) why this approach holds great potential to successfully eliminate the deficiencies, (3) invite other professionals to join the authors in proof of concept research. The authors' experiences, though anecdotal, strongly suggest that a new approach involving visual modeling technologies should allow computer science programs to retain a greater percentage of prospective and declared majors as students become more engaged learners, more successful problem-solvers, and better prepared as programmers. In addition, the graduates of such computer science programs will make greater contributions to the profession as skilled problem-solvers. Instead of wearily rememorizing code as they move to the next course, students will have the problem-solving skills to think and work in more sophisticated and creative ways.