Abstract: Increasing growth of information volume in the
internet causes an increasing need to develop new (semi)automatic
methods for retrieval of documents and ranking them according to
their relevance to the user query. In this paper, after a brief review
on ranking models, a new ontology based approach for ranking
HTML documents is proposed and evaluated in various
circumstances. Our approach is a combination of conceptual,
statistical and linguistic methods. This combination reserves the
precision of ranking without loosing the speed. Our approach
exploits natural language processing techniques to extract phrases
from documents and the query and doing stemming on words. Then
an ontology based conceptual method will be used to annotate
documents and expand the query. To expand a query the spread
activation algorithm is improved so that the expansion can be done
flexible and in various aspects. The annotated documents and the
expanded query will be processed to compute the relevance degree
exploiting statistical methods. The outstanding features of our
approach are (1) combining conceptual, statistical and linguistic
features of documents, (2) expanding the query with its related
concepts before comparing to documents, (3) extracting and using
both words and phrases to compute relevance degree, (4) improving
the spread activation algorithm to do the expansion based on
weighted combination of different conceptual relationships and (5)
allowing variable document vector dimensions. A ranking system
called ORank is developed to implement and test the proposed
model. The test results will be included at the end of the paper.
Abstract: 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.).
Abstract: The bit error rate (BER) performance for ultra-wide
band (UWB) indoor communication with impact of metallic furniture
is investigated. The impulse responses of different indoor
environments for any transmitter and receiver location are computed
by shooting and bouncing ray/image and inverse Fourier transform
techniques. By using the impulse responses of these multipath
channels, the BER performance for binary pulse amplitude
modulation (BPAM) impulse radio UWB communication system are
calculated. Numerical results have shown that the multi-path effect
by the metallic cabinets is an important factor for BER performance.
Also the outage probability for the UWB multipath environment with
metallic cabinets is more serious (about 18%) than with wooden
cabinets. Finally, it is worth noting that in these cases the present
work provides not only comparative information but also quantitative
information on the performance reduction.
Abstract: 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
Abstract: 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.
Abstract: 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.
Abstract: 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.
Abstract: Soil washing process with a surfactant solution is a potential technology for the rapid removal of hydrophobic organic compound (HOC) from soil. However, large amount of washed water would be produced during operation and this should be treated effectively by proper methods. The soil washed water for complex contaminated site with HOC and heavy metals might contain high amount of pollutants such as HOC and heavy metals as well as used surfactant. The heavy metals in the soil washed water have toxic effects on microbial activities thus these should be removed from the washed water before proceeding to a biological waste-water treatment system. Moreover, the used surfactant solutions are necessary to be recovered for reducing the soil washing operation cost. In order to simultaneously remove the heavy metals and HOC from soil-washed water, activated carbon (AC) was used in the present study. In an anionic-nonionic surfactant mixed solution, the Cd(II) and phenanthrene (PHE) were effectively removed by adsorption on activated carbon. The removal efficiency for Cd(II) was increased from 0.027 mmol-Cd/g-AC to 0.142 mmol-Cd/g-AC as the mole ratio of SDS increased in the presence of PHE. The adsorptive capacity of PHE was also increased according to the SDS mole ratio due to the decrement of molar solubilization ratios (MSR) for PHE in an anionic-nonionic surfactant mixture. The simultaneous adsorption of HOC and cationic heavy metals using activated carbon could be a useful method for surfactant recovery and the reduction of heavy metal toxicity in a surfactant-enhanced soil washing process.
Abstract: In order to perform on-line measuring and detection
of PD signals, a total solution composing of an HFCT, A/D
converter and a complete software package is proposed. The
software package includes compensation of HFCT contribution,
filtering and noise reduction using wavelet transform and soft
calibration routines. The results have shown good performance and
high accuracy.
Abstract: In a particular case of behavioural model reduction by ANNs, a validity domain shortening has been found. In mechanics, as in other domains, the notion of validity domain allows the engineer to choose a valid model for a particular analysis or simulation. In the study of mechanical behaviour for a cantilever beam (using linear and non-linear models), Multi-Layer Perceptron (MLP) Backpropagation (BP) networks have been applied as model reduction technique. This reduced model is constructed to be more efficient than the non-reduced model. Within a less extended domain, the ANN reduced model estimates correctly the non-linear response, with a lower computational cost. It has been found that the neural network model is not able to approximate the linear behaviour while it does approximate the non-linear behaviour very well. The details of the case are provided with an example of the cantilever beam behaviour modelling.
Abstract: 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.
Abstract: 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.
Abstract: The main aim of this research is to study the possible
use of recycled fine aggregate made from waste rubble wall to
substitute partially for the natural sand used in the production of
cement and sand bricks. The bricks specimens were prepared by
using 100% natural sand; they were then replaced by recycled fine
aggregate at 25, 50, 75, and 100% by weight of natural sand. A series
of tests was carried out to study the effect of using recycled aggregate
on the physical and mechanical properties of bricks, such as density,
drying shrinkage, water absorption characteristic, compressive and
flexural strength. Test results indicate that it is possible to
manufacture bricks containing recycled fine aggregate with good
characteristics that are similar in physical and mechanical properties
to those of bricks with natural aggregate, provided that the percentage
of recycled fine aggregates is limited up to 50-75%.
Abstract: A new concept for long-term reagent storage for Labon- a-Chip (LoC) devices is described. Here we present a polymer multilayer stack with integrated stick packs for long-term storage of several liquid reagents, which are necessary for many diagnostic applications. Stick packs are widely used in packaging industry for storing solids and liquids for long time. The storage concept fulfills two main requirements: First, a long-term storage of reagents in stick packs without significant losses and interaction with surroundings, second, on demand releasing of liquids, which is realized by pushing a membrane against the stick pack through pneumatic pressure. This concept enables long-term on-chip storage of liquid reagents at room temperature and allows an easy implementation in different LoC devices.
Abstract: The purpose of research was to know the role of
immunogenic protein of 49 kDa from V.alginolyticus which capable
to initiate molecule expression of MHC Class II in receptor of
Cromileptes altivelis. The method used was in vivo experimental
research through testing of immunogenic protein 49 kDa from
V.alginolyticus at Cromileptes altivelis (size of 250 - 300 grams)
using 3 times booster by injecting an immunogenic protein in a
intramuscular manner. Response of expressed MHC molecule was
shown using immunocytochemistry method and SEM. Results
indicated that adhesin V.alginolyticus 49 kDa which have
immunogenic character could trigger expression of MHC class II on
receptor of grouper and has been proven by staining using
immunocytochemistry and SEM with labeling using antibody anti
MHC (anti mouse). This visible expression based on binding between
epitopes antigen and antibody anti MHC in the receptor. Using
immunocytochemistry, intracellular response of MHC to in vivo
induction of immunogenic adhesin from V.alginolyticus was shown.
Abstract: 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.
Abstract: 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.
Abstract: 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.
Abstract: Although in sustainable development field, innovative
solutions have been sought worldwide by environmental groups,
academia, governments and companies for many years, recently,
citizens and communities have emerged as a new group and taken
more and more active role in this field. Many scholars call for more
research on the role of community and community innovation in
sustainable development. This paper is to respond to the calls. In
this paper, we first summarize a comprehensive set of innovation
principles. Then, we do a qualitative cross case study by comparing
three community innovation cases in three different areas of sustainable
development according to the innovation principles. Finally,
we summarize the case comparison and discuss the implications
to sustainable development. A unified role model and innovation
distribution map of community innovation are developed to better
understand community innovation in sustainable development..
Abstract: Using neural network we try to model the unknown function f for given input-output data pairs. The connection strength of each neuron is updated through learning. Repeated simulations of crisp neural network produce different values of weight factors that are directly affected by the change of different parameters. We propose the idea that for each neuron in the network, we can obtain quasi-fuzzy weight sets (QFWS) using repeated simulation of the crisp neural network. Such type of fuzzy weight functions may be applied where we have multivariate crisp input that needs to be adjusted after iterative learning, like claim amount distribution analysis. As real data is subjected to noise and uncertainty, therefore, QFWS may be helpful in the simplification of such complex problems. Secondly, these QFWS provide good initial solution for training of fuzzy neural networks with reduced computational complexity.