Abstract: Decision support systems are usually based on
multidimensional structures which use the concept of hypercube.
Dimensions are the axes on which facts are analyzed and form a
space where a fact is located by a set of coordinates at the
intersections of members of dimensions. Conventional
multidimensional structures deal with discrete facts linked to discrete
dimensions. However, when dealing with natural continuous
phenomena the discrete representation is not adequate. There is a
need to integrate spatiotemporal continuity within multidimensional
structures to enable analysis and exploration of continuous field data.
Research issues that lead to the integration of spatiotemporal
continuity in multidimensional structures are numerous. In this paper,
we discuss research issues related to the integration of continuity in
multidimensional structures, present briefly a multidimensional
model for continuous field data. We also define new aggregation
operations. The model and the associated operations and measures
are validated by a prototype.
Abstract: The paper deals with results of a project “Interoperability Workplaces to Support Teaching of Security Management in a Computer Network". This project is focused on the perspectives and possibilities of "new approaches" to education, training and crisis communication of rescue teams in the Czech Republic. It means that common technologies considering new perspectives are used to educate selected members of crisis management. The main part concentrates on possibilities of application of new technology and computer-aided tools to education and training of Integrated Rescue System teams.This project uses the COST principle for the creation of specialized centers and for all communication between these workplaces.
Abstract: For collecting data from all sensor nodes, some
changes in Dynamic Source Routing (DSR) protocol is proposed. At
each hop level, route-ranking technique is used for distributing
packets to different selected routes dynamically. For calculating rank
of a route, different parameters like: delay, residual energy and
probability of packet loss are used. A hybrid topology of
DMPR(Disjoint Multi Path Routing) and MMPR(Meshed Multi Path
Routing) is formed, where braided topology is used in different
faulty zones of network. For reducing energy consumption, variant
transmission ranges is used instead of fixed transmission range. For
reducing number of packet drop, a fuzzy logic inference scheme is
used to insert different types of delays dynamically. A rule based
system infers membership function strength which is used to
calculate the final delay amount to be inserted into each of the node
at different clusters.
In braided path, a proposed 'Dual Line ACK Link'scheme is
proposed for sending ACK signal from a damaged node or link to a
parent node to ensure that any error in link or any node-failure
message may not be lost anyway. This paper tries to design the
theoretical aspects of a model which may be applied for collecting
data from any large hanging iron structure with the help of wireless
sensor network. But analyzing these data is the subject of material
science and civil structural construction technology, that part is out
of scope of this paper.
Abstract: In this study, a fuzzy similarity approach for Arabic web pages classification is presented. The approach uses a fuzzy term-category relation by manipulating membership degree for the training data and the degree value for a test web page. Six measures are used and compared in this study. These measures include: Einstein, Algebraic, Hamacher, MinMax, Special case fuzzy and Bounded Difference approaches. These measures are applied and compared using 50 different Arabic web-pages. Einstein measure was gave best performance among the other measures. An analysis of these measures and concluding remarks are drawn in this study.
Abstract: Innovations, especially technological, are considered
key-drivers for sustainable economic growth and competitiveness in
the globalised world. As such they should also play an important role
in the process of economical convergence inside the EU.
Unfortunately, the problem of insufficient innovation performance
concerns around half of the EU countries. Poland shows that a lack of
a consistent high-tech financing system constitutes a serious obstacle
for the development of innovative firms. In this article we will
evaluate these questions referring to the example of Ammono S.A., a
Polish company established to develop and commercialise an original
technology for the production of bulk GaN crystals. We will focus on
its efforts to accumulate the financial resources necessary at different
stages of its development. The purpose of this article is to suggest
possible ways to improve the national innovative system, which
would make it more competent in generating high-tech leaders.
Abstract: In this article we present a methodology which
enables preschool and primary school unlanguaged children to
remember words, phrases and texts with the help of graphic signs -
letters, syllables and words. Reading for a child becomes a support
for speech development. Teaching is based on the principle "from
simple to complex", "a letter - a syllable - a word - a proposal - a
text." Availability of multi-level texts allows using this methodology
for working with children who have different levels of speech
development.
Abstract: The Neuro-Fuzzy hybridization scheme has become
of research interest in pattern classification over the past decade. The
present paper proposes a novel Modified Adaptive Fuzzy Inference
Engine (MAFIE) for pattern classification. A modified Apriori
algorithm technique is utilized to reduce a minimal set of decision
rules based on input output data sets. A TSK type fuzzy inference
system is constructed by the automatic generation of membership
functions and rules by the fuzzy c-means clustering and Apriori
algorithm technique, respectively. The generated adaptive fuzzy
inference engine is adjusted by the least-squares fit and a conjugate
gradient descent algorithm towards better performance with a
minimal set of rules. The proposed MAFIE is able to reduce the
number of rules which increases exponentially when more input
variables are involved. The performance of the proposed MAFIE is
compared with other existing applications of pattern classification
schemes using Fisher-s Iris and Wisconsin breast cancer data sets and
shown to be very competitive.
Abstract: In this study, communities of ammonia-oxidizing
archaea (AOA) and ammonia-oxidizing bacteria (AOB) in nitrifying
activated sludge (NAS) prepared by enriching sludge from a
municipal wastewater treatment plant in three continuous-flow
reactors receiving an inorganic medium containing different
ammonium concentrations of 2, 10, and 30 mM NH4
+-N (NAS2,
NAS10, and NAS30, respectively) were investigated using molecular
analysis. Results suggested that almost all AOA clones from NAS2,
NAS10, and NAS30 fell into the same AOA cluster and AOA
communities in NAS2 and NAS10 were more diverse than those of
NAS30. In contrast to AOA, AOB communities obviously shifted
from the seed sludge to enriched NASs and in each enriched NAS,
communities of AOB varied particularly. The seed sludge contained
members of N. communis cluster and N. oligotropha cluster. After it
was enriched under various ammonium loads, members of N.
communis cluster disappeared from all enriched NASs. AOB with
high affinity to ammonia presented in NAS 2, AOB with low affinity
to ammonia presented in NAS 30, and both types of AOB survived in
NAS 10. These demonstrated that ammonium load significantly
influenced AOB communities, but not AOA communities in enriched
NASs.
Abstract: The cellular network is one of the emerging areas of
communication, in which the mobile nodes act as member for one
base station. The cluster based communication is now an emerging
area of wireless cellular multimedia networks. The cluster renders
fast communication and also a convenient way to work with
connectivity. In our scheme we have proposed an optimization
technique for the fuzzy cluster nodes, by categorizing the group
members into three categories like long refreshable member, medium
refreshable member and short refreshable member. By considering
long refreshable nodes as static nodes, we compute the new
membership values for the other nodes in the cluster. We compare
their previous and present membership value with the threshold value
to categorize them into three different members. By which, we
optimize the nodes in the fuzzy clusters. The simulation results show
that there is reduction in the cluster computational time and
iterational time after optimization.
Abstract: The paper shows how the CASMAS modeling language,
and its associated pervasive computing architecture, can be
used to facilitate continuity of care by providing members of patientcentered
communities of care with a support to cooperation and
knowledge sharing through the usage of electronic documents and
digital devices. We consider a scenario of clearly fragmented care to
show how proper mechanisms can be defined to facilitate a better
integration of practices and information across heterogeneous care
networks. The scenario is declined in terms of architectural components
and cooperation-oriented mechanisms that make the support
reactive to the evolution of the context where these communities
operate.
Abstract: An induced acyclic graphoidal cover of a graph G is a
collection ψ of open paths in G such that every path in ψ has atleast
two vertices, every vertex of G is an internal vertex of at most one
path in ψ, every edge of G is in exactly one path in ψ and every
member of ψ is an induced path. The minimum cardinality of an
induced acyclic graphoidal cover of G is called the induced acyclic
graphoidal covering number of G and is denoted by ηia(G) or ηia.
Here we find induced acyclic graphoidal cover for some classes of
graphs.
Abstract: Formulation of biological profile is one of the modern roles of forensic anthropologist. The present study was conducted to estimate height using foot and shoeprint length of Malaysian population. The present work can be very useful information in the process of identification of individual in forensic cases based on shoeprint evidence. It can help to narrow down suspects and ease the police investigation. Besides, stature is important parameters in determining the partial identify of unidentified and mutilated bodies. Thus, this study can help the problem encountered in cases of mass disaster, massacre, explosions and assault cases. This is because it is very hard to identify parts of bodies in these cases where people are dismembered and become unrecognizable. Samples in this research were collected from 200 Malaysian adults (100 males and 100 females) with age ranging from 20 to 45 years old. In this research, shoeprint length were measured based on the print of the shoes made from the flat shoes. Other information like gender, foot length and height of subject were also recorded. The data was analyzed using IBM® SPSS Statistics 19 software. Results indicated that, foot length has a strong correlation with stature than shoeprint length for both sides of the feet. However, in the unknown, where the gender was undetermined have shown a better correlation in foot length and shoeprint length parameter compared to males and females analyzed separately. In addition, prediction equations are developed to estimate the stature using linear regression analysis of foot length and shoeprint length. However, foot lengths give better prediction than shoeprint length.
Abstract: Dichotomization of the outcome by a single cut-off point is an important part of various medical studies. Usually the relationship between the resulted dichotomized dependent variable and explanatory variables is analyzed with linear regression, probit regression or logistic regression. However, in many real-life situations, a certain cut-off point dividing the outcome into two groups is unknown and can be specified only approximately, i.e. surrounded by some (small) uncertainty. It means that in order to have any practical meaning the regression model must be robust to this uncertainty. In this paper, we show that neither the beta in the linear regression model, nor its significance level is robust to the small variations in the dichotomization cut-off point. As an alternative robust approach to the problem of uncertain medical categories, we propose to use the linear regression model with the fuzzy membership function as a dependent variable. This fuzzy membership function denotes to what degree the value of the underlying (continuous) outcome falls below or above the dichotomization cut-off point. In the paper, we demonstrate that the linear regression model of the fuzzy dependent variable can be insensitive against the uncertainty in the cut-off point location. In the paper we present the modeling results from the real study of low hemoglobin levels in infants. We systematically test the robustness of the binomial regression model and the linear regression model with the fuzzy dependent variable by changing the boundary for the category Anemia and show that the behavior of the latter model persists over a quite wide interval.
Abstract: The IFRS for Small and Medium-sized Entities
(SMEs) was issued in July 2009 and currently regulators are
considering various implementation strategies of this standard.
Romania is a member of the European Union since 2007, thus
accounting regulations were issued in order to ensure compliance
with the European Accounting Directives. As the European
Commission rejected recently the mandatory use of IFRS for SMEs,
regulatory bodies from the Member States have to decide if the
standard will affect or not the accounting practices of SMEs from
their countries. Recently IASB invited stakeholders to discuss the
revision of IFRS for SMEs. Empirical studies on the differences and
similarities between national standards and IFRS for SMEs could
inform decision makers on the actual level of convergence in
different countries. The purpose of this paper is to provide empirical
evidences on the convergence of the Romanian regulations with IFRS
for SMEs analyzing the results in the context of the last revisions
proposed to the EU Accounting Directives.
Abstract: The objective of this research was to study the factors
related to the satisfaction of consumers who purchased a Toyota
SUV Fortuner. This paper was a survey data which collected 400
samples from 65 car dealerships. The survey was conducted mainly
in Bangkok, Thailand. The statistics utilized in this paper included
percentage, mean, standard deviation and Pearson Product-Moment.
The findings revealed that the majority of respondent were male with
an undergraduate degree, married and live together. The average
income of the respondents was between 20,001 - 30,000 baht. Most
of them worked for private companies. Most of them had a family
with the average of 4 members. The hypotheses testing revealed that
the factors of marketing mix in terms of product (ability, gas
mileage, and safety) were related to overall satisfaction at the
medium level. However, the findings also revealed that the factors of
marketing mix in terms of product (image), price, and promotion, and
service center were related to the overall satisfaction at the low level.
Abstract: Human perceives color in categories, which may be
identified using color name such as red, blue, etc. The categorization
is unique for each human being. However despite the individual
differences, the categorization is shared among members in society.
This allows communication among them, especially when using
color name. Sociable robot, to live coexist with human and become
part of human society, must also have the shared color
categorization, which can be achieved through learning. Many
works have been done to enable computer, as brain of robot, to learn
color categorization. Most of them rely on modeling of human color
perception and mathematical complexities. Differently, in this work,
the computer learns color categorization through interaction with
humans. This work aims at developing the innate ability of the
computer to learn the human-like color categorization. It focuses on
the representation of color categorization and how it is built and
developed without much mathematical complexity.
Abstract: Trauma in early life is widely regarded as a cause for
adult mental health problems. This study explores the role of
secondary trauma on later functioning in a sample of 359 university
students enrolled in undergraduate psychology classes in the United
States. Participants were initially divided into four groups based on
1) having directly experienced trauma (assaultive violence), 2)
having directly experienced trauma and secondary traumatization
through the unanticipated death of a close friend or family member
or witnessing of an injury or shocking even), 3) having no
experience of direct trauma but having experienced indirect trauma
(secondary trauma), or 4) reporting no exposure. Participants
completed a battery of measures on concepts associated with
psychological functioning which included measures of
psychological well-being, problem solving, coping and resiliency.
Findings discuss differences in psychological functioning and
resilience based on participants who experienced secondary
traumatization and assaultive violence versus secondary
traumatization alone.
Abstract: In Data mining, Fuzzy clustering algorithms have
demonstrated advantage over crisp clustering algorithms in dealing
with the challenges posed by large collections of vague and uncertain
natural data. This paper reviews concept of fuzzy logic and fuzzy
clustering. The classical fuzzy c-means algorithm is presented and its
limitations are highlighted. Based on the study of the fuzzy c-means
algorithm and its extensions, we propose a modification to the cmeans
algorithm to overcome the limitations of it in calculating the
new cluster centers and in finding the membership values with
natural data. The efficiency of the new modified method is
demonstrated on real data collected for Bhutan-s Gross National
Happiness (GNH) program.
Abstract: In data mining, the association rules are used to find
for the associations between the different items of the transactions
database. As the data collected and stored, rules of value can be found
through association rules, which can be applied to help managers
execute marketing strategies and establish sound market frameworks.
This paper aims to use Fuzzy Frequent Pattern growth (FFP-growth)
to derive from fuzzy association rules. At first, we apply fuzzy
partition methods and decide a membership function of quantitative
value for each transaction item. Next, we implement FFP-growth
to deal with the process of data mining. In addition, in order to
understand the impact of Apriori algorithm and FFP-growth algorithm
on the execution time and the number of generated association
rules, the experiment will be performed by using different sizes of
databases and thresholds. Lastly, the experiment results show FFPgrowth
algorithm is more efficient than other existing methods.
Abstract: The theory of rough sets is generalized by using a
filter. The filter is induced by binary relations and it is used to
generalize the basic rough set concepts. The knowledge
representations and processing of binary relations in the style of
rough set theory are investigated.