Abstract: This paper addresses the development of an intelligent vision system for human-robot interaction. The two novel contributions of this paper are 1) Detection of human faces and 2) Localizing the eye. The method is based on visual attributes of human skin colors and geometrical analysis of face skeleton. This paper introduces a spatial domain filtering method named ?Fuzzily skewed filter' which incorporates Fuzzy rules for deciding the gray level of pixels in the image in their neighborhoods and takes advantages of both the median and averaging filters. The effectiveness of the method has been justified over implementing the eye tracking commands to an entertainment robot, named ''AIBO''.
Abstract: Perceptions of quality from both designers and users
perspective have now stretched beyond the traditional usability,
incorporating abstract and subjective concepts. This has led to a shift
in human computer interaction research communities- focus; a shift
that focuses on achieving user experience (UX) by not only fulfilling
conventional usability needs but also those that go beyond them. The
term UX, although widely spread and given significant importance,
lacks consensus in its unified definition. In this paper, we survey
various UX definitions and modeling frameworks and examine them
as the foundation for proposing a UX evolution lifecycle framework
for understanding UX in detail. In the proposed framework we identify
the building blocks of UX and discuss how UX evolves in various
phases. The framework can be used as a tool to understand experience
requirements and evaluate them, resulting in better UX design and
hence improved user satisfaction.
Abstract: Covering-based rough sets is an extension of rough
sets and it is based on a covering instead of a partition of the
universe. Therefore it is more powerful in describing some practical
problems than rough sets. However, by extending the rough sets,
covering-based rough sets can increase the roughness of each model
in recognizing objects. How to obtain better approximations from
the models of a covering-based rough sets is an important issue.
In this paper, two concepts, determinate elements and indeterminate
elements in a universe, are proposed and given precise definitions
respectively. This research makes a reasonable refinement of the
covering-element from a new viewpoint. And the refinement may
generate better approximations of covering-based rough sets models.
To prove the theory above, it is applied to eight major coveringbased
rough sets models which are adapted from other literature.
The result is, in all these models, the lower approximation increases
effectively. Correspondingly, in all models, the upper approximation
decreases with exceptions of two models in some special situations.
Therefore, the roughness of recognizing objects is reduced. This
research provides a new approach to the study and application of
covering-based rough sets.
Abstract: In the proposed method for Web page-ranking, a
novel theoretic model is introduced and tested by examples of order
relationships among IP addresses. Ranking is induced using a
convexity feature, which is learned according to these examples
using a self-organizing procedure. We consider the problem of selforganizing
learning from IP data to be represented by a semi-random
convex polygon procedure, in which the vertices correspond to IP
addresses. Based on recent developments in our regularization
theory for convex polygons and corresponding Euclidean distance
based methods for classification, we develop an algorithmic
framework for learning ranking functions based on a Computational
Geometric Theory. We show that our algorithm is generic, and
present experimental results explaining the potential of our approach.
In addition, we explain the generality of our approach by showing its
possible use as a visualization tool for data obtained from diverse
domains, such as Public Administration and Education.
Abstract: With the intention of screening for heavy metal
tolerance, a number of bacteria were isolated and characterized from
a pristine soil. Two Gram positive isolates were identified as
Paenibacillus sp. and Bacillus thuringeinsis. Tolerance of Cd2+, Cu2+
and Zn2+ by these bacteria was studied and found that both bacteria
were highly sensitive to Cu2+ compared to other two metals. Both
bacteria showed the same pattern of metal tolerance in the order Zn+
> Cd2+ > Cu2+. When the metal tolerance in both bacteria was
compared, Paenibacillus sp. showed the highest sensitivity to Cu2+
where as B. thuringiensis showed highest sensitivity to Cd2+ and Zn2+
.These findings revealed the potential of Paenibacillus sp. in
developing a biosensor to detect Cu2+ in environmental samples.
Abstract: Photoselective plastic films with thermic properties
are now available so that greenhouses clad with such plastics exhibit
a higher degree of “Greenhouse Effect” with a consequent increase in
night time temperature. In this study, we investigate the potential
benefits of a range of thermic plastic films used as greenhouse cover
materials on the vegetative and reproductive growth and development
of Iceberg lettuce (Lactuca sativa L). Transplants were grown under
thermic films and destructively harvested 4, 5, and 6 weeks after
transplanting. Thermic films can increase night temperatures up to 2
⁰C reducing the wide fluctuation in greenhouse temperature during
winter compared to the standard commercial film and consequently
increased the yield (leaf number, fresh weight, and dry weight) of
lettuce plants. Lettuce plants grown under Clear film respond to cold
stress by the accumulation of secondary products (phenolics, and
flavonoids).
Abstract: This paper investigates the effect of International
Financial Reporting Standards (IFRS) adoption on the frequency of
earnings managements towards small positive profits. We focus on
two emerging markets IFRS adopters: South Africa and Turkey.
We tested our logistic regression using appropriate panelestimation
techniques over a sample of 330 South African and 210
Turkish firm-year observations over the period 2002-2008. Our
results document that mandatory adoption of IFRS is not associated
with a reduction in earnings management towards small positive
profits in emerging markets. These results contradict most of the
previous findings of the studies conducted in developed countries.
Based on the legal system factor, we compare the intensity of
earnings management between a code law country (Turkey) and a
common law country (South Africa) over the pre and post-adoption
periods. Our findings show that the frequency of such earnings
management practice increases significantly for the code law
country.
Abstract: Little research has examined working memory
capacity (WMC) in signed language interpreters and deaf signers.
This paper presents the findings of a study that investigated WMC in
professional Australian Sign Language (Auslan)/English interpreters
and deaf signers. Thirty-one professional Auslan/English interpreters
(14 hearing native signers and 17 hearing non-native signers)
completed an English listening span task and then an Auslan working
memory span task, which tested their English WMC and their Auslan
WMC, respectively. Moreover, 26 deaf signers (6 deaf native signers
and 20 deaf non-native signers) completed the Auslan working
memory span task. The results revealed a non-significant difference
between the hearing native signers and the hearing non-native signers
in their English WMC, and a non-significant difference between the
hearing native signers and the hearing non-native signers in their
Auslan WMC. Moreover, the results yielded a non-significant
difference between the hearing native signers- English WMC and
their Auslan WMC, and a non-significant difference between the
hearing non-native signers- English WMC and their Auslan WMC.
Furthermore, a non-significant difference was found between the deaf
native signers and the deaf non-native signers in their Auslan WMC.
Abstract: The purpose of this paper is to study Database Models
to use them efficiently in E-commerce websites. In this paper we are
going to find a method which can save and retrieve information in Ecommerce
websites. Thus, semantic web applications can work with,
and we are also going to study different technologies of E-commerce
databases and we know that one of the most important deficits in
semantic web is the shortage of semantic data, since most of the
information is still stored in relational databases, we present an
approach to map legacy data stored in relational databases into the
Semantic Web using virtually any modern RDF query language, as
long as it is closed within RDF. To achieve this goal we study XML
structures for relational data bases of old websites and eventually we
will come up one level over XML and look for a map from relational
model (RDM) to RDF. Noting that a large number of semantic webs
get advantage of relational model, opening the ways which can be
converted to XML and RDF in modern systems (semantic web) is
important.
Abstract: Sweet cherries (Prunus avium L.) contain various
phenolic compounds which contribute to total antioxidant activity.
Total polyphenols, tannins, flavonoids and anthocyanins, and
antioxidant capacity in a fruits of a number of selected sweet cherry
genotypes were investigated. Total polyphenols content ranged from
4.12 to 8.34 mg gallic acid equivantents/g dry fruit weight and total
tannins content ranged from 0.19 to 1.95 mg gallic acid equivalent/g
dry fruit weight. Total flavonoids were within the range 0.42-1.56 mg
of rutin equivalents/g dry fruit weight and total anthocyanins content
were between 0.35 and 0.69 mg cyanidin 3-glucoside equivalent/ g
dry fruit weight. Although sweet cherry fruits are a significant source
of different phenolic compounds, antioxidant activity of sweet
cherries is not related only with the total polyphenolics, flavonoids or
anthocyanins.
Abstract: Microarray data profiles gene expression on a whole
genome scale, therefore, it provides a good way to study associations
between gene expression and occurrence or progression of cancer.
More and more researchers realized that microarray data is helpful
to predict cancer sample. However, the high dimension of gene
expressions is much larger than the sample size, which makes this
task very difficult. Therefore, how to identify the significant genes
causing cancer becomes emergency and also a hot and hard research
topic. Many feature selection algorithms have been proposed in
the past focusing on improving cancer predictive accuracy at the
expense of ignoring the correlations between the features. In this
work, a novel framework (named by SGS) is presented for stable gene
selection and efficient cancer prediction . The proposed framework
first performs clustering algorithm to find the gene groups where
genes in each group have higher correlation coefficient, and then
selects the significant genes in each group with Bayesian Lasso and
important gene groups with group Lasso, and finally builds prediction
model based on the shrinkage gene space with efficient classification
algorithm (such as, SVM, 1NN, Regression and etc.). Experiment
results on real world data show that the proposed framework often
outperforms the existing feature selection and prediction methods,
say SAM, IG and Lasso-type prediction model.
Abstract: Traditionally, VLSI implementations of spiking
neural nets have featured large neuron counts for fixed computations
or small exploratory, configurable nets. This paper presents the
system architecture of a large configurable neural net system
employing a dedicated mapping algorithm for projecting the targeted
biology-analog nets and dynamics onto the hardware with its
attendant constraints.
Abstract: The aim of this paper is to know the sociodemographic
and operational-financial determinants of the services
quality perceived by users of the national health services. Through
the use of an inquiry conducted by the Ministry of Health,
comprehending 16.936 interviews in 2006, we intend to find out if
there is any characteristic that determines the 2006 inquiry results.
With the revision of the literature we also want to know if the
operational-financial results have implications in hospitals users-
perception on the quality of the received services. In order to achieve
our main goals we will make use of the regression analysis to find out
the possible dimensions that determine those results.
Abstract: Fruits and vegetables are the essentials of a healthy
diet, mainly because of their antioxidant properties contributing to
disease blockage especially for some certain types of cancer. Being a
favourite fruit, citrus are produced for economic and commercial
purposes worldwide. Particularly, lemon fruit (Citrus limon L.), has
an important place in export products of Turkey. Lemon has a great
importance on human nutrition with regard to being a source of
nutrients, flavonoids, vitamin C and minerals. It is used for food
flavouring and pickling and also processed for lemonade. By
processing citrus into fruit juices, consumption may increase and also
become easier. Like many fruits and vegetables lemons are cheap and
abundant during harvesting period, while they are quite expensive in
other seasons. Lemon juice and concentrate production allows
consumers to get benefits from lemon fruit in any time of the year.
Lemonade is getting in to the focus of consumers’ attention
preferring non-carbonated drinks. The demand of healthy, convenient
functional foods affects consumer trends through innovative
products. For this reason, lemonade could be enriched with different
natural herb extracts such as ginger (Zingiber officinale), linden (Tilia
cordata), and mint (Mentha piperita).
Abstract: To determine the length of engagement threads of a bolt installed in a tapped part in order to avoid the threads stripping remains a very current problem in the design of the thread assemblies. It does not exist a calculation method formalized for the cases where the bolt is screwed directly in a ductile material. In this article, we study the behavior of the threads stripping of a loaded assembly by using a modelling by finite elements and a rupture criterion by damage. This modelling enables us to study the different parameters likely to influence the behavior of this bolted connection. We study in particular, the influence of couple of materials constituting the connection, of the bolt-s diameter and the geometrical characteristics of the tapped part, like the external diameter and the length of engagement threads. We established an experiments design to know the most significant parameters. That enables us to propose a simple expression making possible to calculate the resistance of the threads whatever the metallic materials of the bolt and the tapped part. We carried out stripping tests in order to validate our model. The estimated results are very close to those obtained by the tests.
Abstract: Names are important in many societies, even in technologically oriented ones which use e.g. ID systems to identify individual people. Names such as surnames are the most important as they are used in many processes, such as identifying of people and genealogical research. On the other hand variation of names can be a major problem for the identification and search for people, e.g. web search or security reasons. Name matching presumes a-priori that the recorded name written in one alphabet reflects the phonetic identity of two samples or some transcription error in copying a previously recorded name. We add to this the lode that the two names imply the same person. This paper describes name variations and some basic description of various name matching algorithms developed to overcome name variation and to find reasonable variants of names which can be used to further increasing mismatches for record linkage and name search. The implementation contains algorithms for computing a range of fuzzy matching based on different types of algorithms, e.g. composite and hybrid methods and allowing us to test and measure algorithms for accuracy. NYSIIS, LIG2 and Phonex have been shown to perform well and provided sufficient flexibility to be included in the linkage/matching process for optimising name searching.
Abstract: This paper presents a hybrid association control
scheme that can maintain load balancing among access points in the
wireless LANs and can satisfy the quality of service requirements of
the multimedia traffic applications. The proposed model is
mathematically described as a linear programming model. Simulation
study and analysis were conducted in order to demonstrate the
performance of the proposed hybrid load balancing and association
control scheme. Simulation results shows that the proposed scheme
outperforms the other schemes in term of the percentage of blocking
and the quality of the data transfer rate providing to the multimedia
and real-time applications.
Abstract: Decision support based upon risk analysis into
comparison of the electricity generation from different renewable
energy technologies can provide information about their effects on
the environment and society. The aim of this paper is to develop the
assessment framework regarding risks to health and environment,
and the society-s benefits of the electric power plant generation from
different renewable sources. The multicriteria framework to
multiattribute risk analysis technique and the decision analysis
interview technique are applied in order to support the decisionmaking
process for the implementing renewable energy projects to
the Bangkok case study. Having analyses the local conditions and
appropriate technologies, five renewable power plants are postulated
as options. As this work demonstrates, the analysis can provide a tool
to aid decision-makers for achieving targets related to promote
sustainable energy system.
Abstract: Developing an accurate classifier for high dimensional microarray datasets is a challenging task due to availability of small sample size. Therefore, it is important to determine a set of relevant genes that classify the data well. Traditionally, gene selection method often selects the top ranked genes according to their discriminatory power. Often these genes are correlated with each other resulting in redundancy. In this paper, we have proposed a hybrid method using feature ranking and wrapper method (Genetic Algorithm with multiclass SVM) to identify a set of relevant genes that classify the data more accurately. A new fitness function for genetic algorithm is defined that focuses on selecting the smallest set of genes that provides maximum accuracy. Experiments have been carried on four well-known datasets1. The proposed method provides better results in comparison to the results found in the literature in terms of both classification accuracy and number of genes selected.
Abstract: An attempt in this paper proposes a re-modification to
the minimum moment approach of resource leveling which is a modified minimum moment approach to the traditional method by
Harris. The method is based on critical path method. The new approach suggests the difference between the methods in the
selection criteria of activity which needs to be shifted for leveling resource histogram. In traditional method, the improvement factor
found first to select the activity for each possible day of shifting. In
modified method maximum value of the product of Resources Rate
and Free Float was found first and improvement factor is then
calculated for that activity which needs to be shifted. In the proposed
method the activity to be selected first for shifting is based on the largest value of resource rate. The process is repeated for all the
remaining activities for possible shifting to get updated histogram.
The proposed method significantly reduces the number of iterations
and is easier for manual computations.