Abstract: In the literature of fuzzy measures, there exist many
well known parametric and non-parametric measures, each with its
own merits and limitations. But our main emphasis is on
applications of these measures to a variety of disciplines. To extend
the scope of applications of these fuzzy measures to geometry, we
need some special fuzzy measures. In this communication, we have
introduced two new fuzzy measures involving trigonometric
functions and simultaneously provided their applications to obtain
the basic results already existing in the literature of geometry.
Abstract: One of the criteria in production scheduling is Make
Span, minimizing this criteria causes more efficiently use of the
resources specially machinery and manpower. By assigning some
budget to some of the operations the operation time of these activities
reduces and affects the total completion time of all the operations
(Make Span). In this paper this issue is practiced in parallel flow
shops. At first we convert parallel flow shop to a network model and
by using a linear programming approach it is identified in order to
minimize make span (the completion time of the network) which
activities (operations) are better to absorb the predetermined and
limited budget. Minimizing the total completion time of all the
activities in the network is equivalent to minimizing make span in
production scheduling.
Abstract: In-core memory requirement is a bottleneck in solving
large three dimensional Navier-Stokes finite element problem
formulations using sparse direct solvers. Out-of-core solution
strategy is a viable alternative to reduce the in-core memory
requirements while solving large scale problems. This study
evaluates the performance of various out-of-core sequential solvers
based on multifrontal or supernodal techniques in the context of
finite element formulations for three dimensional problems on a
Windows platform. Here three different solvers, HSL_MA78,
MUMPS and PARDISO are compared. The performance of these
solvers is evaluated on a 64-bit machine with 16GB RAM for finite
element formulation of flow through a rectangular channel. It is
observed that using out-of-core PARDISO solver, relatively large
problems can be solved. The implementation of Newton and
modified Newton's iteration is also discussed.
Abstract: The research objective of the project and article
“European Ecological Network Natura 2000 – opportunities and
threats” Natura 2000 sites constitute a form of environmental
protection, several legal problems are likely to result. Most
controversially, certain sites will be subject to two regimes of
protection: as national parks and as Natura 2000 sites. This dualism
of the legal regulation makes it difficult to perform certain legal
obligations related to the regimes envisaged under each form of
environmental protection. Which regime and which obligations
resulting from the particular form of environmental protection have
priority and should prevail? What should be done if these obligations
are contradictory? Furthermore, an institutional problem consists in
that no public administration authority has the power to resolve legal
conflicts concerning the application of a particular regime on a given
site. There are also no criteria to decide priority and superiority of
one form of environmental protection over the other. Which
regulations are more important, those that pertain to national parks or
to Natura 2000 sites? In the light of the current regulations, it is
impossible to give a decisive answer to these questions. The internal
hierarchy of forms of environmental protection has not been
determined, and all such forms should be treated equally.
Abstract: This paper presents the significant factor and give
some suggestion that should know before design. The main objective of this paper is guide the first step for someone who attends to design of grounding system before study in details later. The overview of
grounding system can protect damage from fault such as can save a human life and power system equipment. The unsafe conditions have
three cases. Case 1) maximum touch voltage exceeds the safety
criteria. In this case, the conductor compression ratio of the ground gird should be first adjusted to have optimal spacing of ground grid
conductors. If it still over limit, earth resistivity should be consider afterward. Case 2) maximum step voltage exceeds the safety criteria.
In this case, increasing the number of ground grid conductors around
the boundary can solve this problem. Case 3) both of maximum touch
and step voltage exceed the safety criteria. In this case, follow the solutions explained in case 1 and case 2. Another suggestion, vary depth of ground grid until maximum step and touch voltage do not
exceed the safety criteria.
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: 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: Basic objective of this study is to create a regression
analysis method that can estimate the length of a plastic hinge which
is an important design parameter, by making use of the outcomes of
(lateral load-lateral displacement hysteretic curves) the experimental
studies conducted for the reinforced square concrete columns. For
this aim, 170 different square reinforced concrete column tests results
have been collected from the existing literature. The parameters
which are thought affecting the plastic hinge length such as crosssection
properties, features of material used, axial loading level,
confinement of the column, longitudinal reinforcement bars in the
columns etc. have been obtained from these 170 different square
reinforced concrete column tests. In the study, when determining the
length of plastic hinge, using the experimental test results, a
regression analysis have been separately tested and compared with
each other. In addition, the outcome of mentioned methods on
determination of plastic hinge length of the reinforced concrete
columns has been compared to other methods available in the
literature.
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.
Abstract: Artifact rejection plays a key role in many signal processing applications. The artifacts are disturbance that can occur during the signal acquisition and that can alter the analysis of the signals themselves. Our aim is to automatically remove the artifacts, in particular from the Electroencephalographic (EEG) recordings. A technique for the automatic artifact rejection, based on the Independent Component Analysis (ICA) for the artifact extraction and on some high order statistics such as kurtosis and Shannon-s entropy, was proposed some years ago in literature. In this paper we try to enhance this technique proposing a new method based on the Renyi-s entropy. The performance of our method was tested and compared to the performance of the method in literature and the former proved to outperform the latter.
Abstract: HSDPA is a new feature which is introduced in
Release-5 specifications of the 3GPP WCDMA/UTRA standard to
realize higher speed data rate together with lower round-trip times.
Moreover, the HSDPA concept offers outstanding improvement of
packet throughput and also significantly reduces the packet call
transfer delay as compared to Release -99 DSCH. Till now the
HSDPA system uses turbo coding which is the best coding technique
to achieve the Shannon limit. However, the main drawbacks of turbo
coding are high decoding complexity and high latency which makes
it unsuitable for some applications like satellite communications,
since the transmission distance itself introduces latency due to
limited speed of light. Hence in this paper it is proposed to use LDPC
coding in place of Turbo coding for HSDPA system which decreases
the latency and decoding complexity. But LDPC coding increases the
Encoding complexity. Though the complexity of transmitter
increases at NodeB, the End user is at an advantage in terms of
receiver complexity and Bit- error rate. In this paper LDPC Encoder
is implemented using “sparse parity check matrix" H to generate a
codeword at Encoder and “Belief Propagation algorithm "for LDPC
decoding .Simulation results shows that in LDPC coding the BER
suddenly drops as the number of iterations increase with a small
increase in Eb/No. Which is not possible in Turbo coding. Also same
BER was achieved using less number of iterations and hence the
latency and receiver complexity has decreased for LDPC coding.
HSDPA increases the downlink data rate within a cell to a theoretical
maximum of 14Mbps, with 2Mbps on the uplink. The changes that
HSDPA enables includes better quality, more reliable and more
robust data services. In other words, while realistic data rates are
only a few Mbps, the actual quality and number of users achieved
will improve significantly.
Abstract: The effective machine-job assignment of injection
molding machines is very important for industry because it is not
only directly affects the quality of the product but also the
performance and lifetime of the machine as well. The phase of
machine selection was mostly done by professionals or experienced
planners, so the possibility of matching a job with an inappropriate
machine might occur when it was conducted by an inexperienced
person. It could lead to an uneconomical plan and defects. This
research aimed to develop a machine selection system for plastic
injection machines as a tool to help in decision making of the user.
This proposed system could be used both in normal times and in
times of emergency. Fuzzy logic principle is applied to deal with
uncertainty and mechanical factors in the selection of both quantity
and quality criteria. The six criteria were obtained from a plastic
manufacturer's case study to construct a system based on fuzzy logic
theory using MATLAB. The results showed that the system was able
to reduce the defects of Short Shot and Sink Mark to 24.0% and
8.0% and the total defects was reduced around 8.7% per month.
Abstract: The transformation of vocal characteristics aims at
modifying voice such that the intelligibility of aphonic voice is
increased or the voice characteristics of a speaker (source speaker) to
be perceived as if another speaker (target speaker) had uttered it. In
this paper, the current state-of-the-art voice characteristics
transformation methodology is reviewed. Special emphasis is placed
on voice transformation methodology and issues for improving the
transformed speech quality in intelligibility and naturalness are
discussed. In particular, it is suggested to use the modulation theory
of speech as a base for research on high quality voice transformation.
This approach allows one to separate linguistic, expressive, organic
and perspective information of speech, based on an analysis of how
they are fused when speech is produced. Therefore, this theory
provides the fundamentals not only for manipulating non-linguistic,
extra-/paralinguistic and intra-linguistic variables for voice
transformation, but also for paving the way for easily transposing the
existing voice transformation methods to emotion-related voice
quality transformation and speaking style transformation. From the
perspectives of human speech production and perception, the popular
voice transformation techniques are described and classified them
based on the underlying principles either from the speech production
or perception mechanisms or from both. In addition, the advantages
and limitations of voice transformation techniques and the
experimental manipulation of vocal cues are discussed through
examples from past and present research. Finally, a conclusion and
road map are pointed out for more natural voice transformation
algorithms in the future.
Abstract: Sharing motivations of viral advertisements by
consumers and the impacts of these advertisements on the
perceptions for brand will be questioned in this study. Three
fundamental questions are answered in the study. These are
advertisement watching and sharing motivations of individuals,
criteria of liking viral advertisement and the impact of individual
attitudes for viral advertisement on brand perception respectively.
This study will be carried out via a viral advertisement which was
practiced in Turkey. The data will be collected by survey method and
the sample of the study consists of individuals who experienced the
practice of sample advertisement. Data will be collected by online
survey method and will be analyzed by using SPSS statistical
package program.
Recently traditional advertisement mind have been changing. New
advertising approaches which have significant impacts on consumers
have been argued. Viral advertising is a modernist advertisement
mind which offers significant advantages to brands apart from
traditional advertising channels such as television, radio and
magazines. Viral advertising also known as Electronic Word-of-
Mouth (eWOM) consists of free spread of convincing messages sent
by brands among interpersonal communication. When compared to
the traditional advertising, a more provocative thematic approach is
argued.
The foundation of this approach is to create advertisements that
are worth sharing with others by consumers. When that fact is taken
into consideration, in a manner of speaking it can also be stated that
viral advertising is media engineering.
The content worth sharing makes people being a volunteer
spokesman of a brand and strengthens the emotional bonds among
brand and consumer. Especially for some sectors in countries which
are having traditional advertising channel limitations, viral
advertising creates vital advantages.
Abstract: This paper aims to present the main instruments used
in the economic literature for measuring the price risk, pointing out
on the advantages brought by the conditional variance in this respect.
The theoretical approach will be exemplified by elaborating an
EGARCH model for the price returns of wheat, both on Romanian
and on international market. To our knowledge, no previous
empirical research, either on price risk measurement for the
Romanian markets or studies that use the ARIMA-EGARCH
methodology, have been conducted. After estimating the
corresponding models, the paper will compare the estimated
conditional variance on the two markets.
Abstract: Ontology Matching is a task needed in various applica-tions, for example for comparison or merging purposes. In literature,many algorithms solving the matching problem can be found, butmost of them do not consider instances at all. Mappings are deter-mined by calculating the string-similarity of labels, by recognizinglinguistic word relations (synonyms, subsumptions etc.) or by ana-lyzing the (graph) structure. Due to the facts that instances are oftenmodeled within the ontology and that the set of instances describesthe meaning of the concepts better than their meta information,instances should definitely be incorporated into the matching process.In this paper several novel instance-based matching algorithms arepresented which enhance the quality of matching results obtainedwith common concept-based methods. Different kinds of formalismsare use to classify concepts on account of their instances and finallyto compare the concepts directly.KeywordsInstances, Ontology Matching, Semantic Web
Abstract: This research deals with a flexible flowshop
scheduling problem with arrival and delivery of jobs in groups and
processing them individually. Due to the special characteristics of
each job, only a subset of machines in each stage is eligible to
process that job. The objective function deals with minimization of
sum of the completion time of groups on one hand and minimization
of sum of the differences between completion time of jobs and
delivery time of the group containing that job (waiting period) on the
other hand. The problem can be stated as FFc / rj , Mj / irreg which
has many applications in production and service industries. A
mathematical model is proposed, the problem is proved to be NPcomplete,
and an effective heuristic method is presented to schedule
the jobs efficiently. This algorithm can then be used within the body
of any metaheuristic algorithm for solving the problem.
Abstract: The prevalence of non organic constipation differs
from country to country and the reliability of the estimate rates is
uncertain. Moreover, the clinical relevance of subdividing the
heterogeneous functional constipation disorders into pre-defined
subgroups is largely unknown.. Aim: to estimate the prevalence of
constipation in a population-based sample and determine whether
clinical subgroups can be identified. An age and gender stratified
sample population from 5 Italian cities was evaluated using a
previously validated questionnaire. Data mining by cluster analysis
was used to determine constipation subgroups. Results: 1,500
complete interviews were obtained from 2,083 contacted households
(72%). Self-reported constipation correlated poorly with symptombased
constipation found in 496 subjects (33.1%). Cluster analysis
identified four constipation subgroups which correlated to subgroups
identified according to pre-defined symptom criteria. Significant
differences in socio-demographics and lifestyle were observed
among subgroups.
Abstract: In this paper, by exploiting a single semiconductor
optical amplifier-Mach Zehnder Interferometer (SOA-MZI), an
integratable all-optical flip-flop (AOFF) is proposed. It is composed
of a SOA-MZI with a bidirectional coupler at the output. Output
signals of both bar and crossbar of the SOA-MZI is fed back to SOAs
located in the arms of the Mach-Zehnder Interferometer (MZI). The
injected photon-rates to the SOAs are modulated by feedback signals
in order to form optical flip-flop. According to numerical analysis,
Gaussian optical pulses with the energy of 15.2 fJ and 20 ps duration
with the full width at half-maximum criterion, can switch the states of
the SR-AOFF. Also simulation results show that the SR-AOFF has
the contrast ratio of 8.5 dB between two states with the transition
time of nearly 20 ps.
Abstract: The need in cognitive radio system for a simple, fast, and independent technique to sense the spectrum occupancy has led to the energy detection approach. Energy detector is known by its dependency on noise variation in the system which is one of its major drawbacks. In this paper, we are aiming to improve its performance by utilizing a weighted collaborative spectrum sensing, it is similar to the collaborative spectrum sensing methods introduced previously in the literature. These weighting methods give more improvement for collaborative spectrum sensing as compared to no weighting case. There is two method proposed in this paper: the first one depends on the channel status between each sensor and the primary user while the second depends on the value of the energy measured in each sensor.