Abstract: Proper orthogonal decomposition (POD) is used to reconstruct spatio-temporal data of a fully developed turbulent channel flow with density variation at Reynolds number of 150, based on the friction velocity and the channel half-width, and Prandtl number of 0.71. To apply POD to the fully developed turbulent channel flow with density variation, the flow field (velocities, density, and temperature) is scaled by the corresponding root mean square values (rms) so that the flow field becomes dimensionless. A five-vector POD problem is solved numerically. The reconstructed second-order moments of velocity, temperature, and density from POD eigenfunctions compare favorably to the original Direct Numerical Simulation (DNS) data.
Abstract: In this paper, a generalized form of the Banzhaf-Owen value for cooperative fuzzy games with a coalition structure is proposed. Its axiomatic system is given by extending crisp case. In order to better understand the Banzhaf-Owen value for fuzzy games with a coalition structure, we briefly introduce the Banzhaf-Owen values for two special kinds of fuzzy games with a coalition structure, and give their explicit forms.
Abstract: Reduction of Single Input Single Output (SISO) discrete systems into lower order model, using a conventional and an evolutionary technique is presented in this paper. In the conventional technique, the mixed advantages of Modified Cauer Form (MCF) and differentiation are used. In this method the original discrete system is, first, converted into equivalent continuous system by applying bilinear transformation. The denominator of the equivalent continuous system and its reciprocal are differentiated successively, the reduced denominator of the desired order is obtained by combining the differentiated polynomials. The numerator is obtained by matching the quotients of MCF. The reduced continuous system is converted back into discrete system using inverse bilinear transformation. In the evolutionary technique method, Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example.
Abstract: Internet computer games turn to be more and more
attractive within the context of technology enhanced learning.
Educational games as quizzes and quests have gained significant
success in appealing and motivating learners to study in a different
way and provoke steadily increasing interest in new methods of
application. Board games are specific group of games where figures
are manipulated in competitive play mode with race conditions on a
surface according predefined rules. The article represents a new,
formalized model of traditional quizzes, puzzles and quests shown as
multimedia board games which facilitates the construction process of
such games. Authors provide different examples of quizzes and their
models in order to demonstrate the model is quite general and does
support not only quizzes, mazes and quests but also any set of
teaching activities. The execution process of such models is
explained and, as well, how they can be useful for creation and
delivery of adaptive e-learning courseware.
Abstract: In this paper, position vector of a partially null unit speed curve with respect to standard frame of Minkowski space-time is studied. First, it is proven that position vector of every partially null unit speed curve satisfies a vector differential equation of fourth order. In terms of solution of the differential equation, position vector of a partially null unit speed curve is expressed.
Abstract: Most CT reconstruction system x-ray computed
tomography (CT) is a well established visualization technique in
medicine and nondestructive testing. However, since CT scanning
requires sampling of radiographic projections from different viewing
angles, common CT systems with mechanically moving parts are too
slow for dynamic imaging, for instance of multiphase flows or live
animals. A large number of X-ray projections are needed to
reconstruct CT images, so the collection and calculation of the
projection data consume too much time and harmful for patient. For
the purpose of solving the problem, in this study, we proposed a
method for tomographic reconstruction of a sample from a limited
number of x-ray projections by using linear interpolation method. In
simulation, we presented reconstruction from an experimental x-ray
CT scan of a Aluminum phantom that follows to two steps: X-ray
projections will be interpolated using linear interpolation method and
using it for CT reconstruction based upon Ordered Subsets
Expectation Maximization (OSEM) method.
Abstract: This paper explores gender related barriers to interagency collaboration in statutory children safeguard partnerships against a theoretical framework that considers individuals, professions and organisations interacting as part of a complex adaptive system. We argue that gender-framed obstacles to effective communication between culturally discrepant agencies can ultimately impact on the effectiveness of policy delivery,. We focused our research on three partnership structures in Sefton Metropolitan Borough in order to observe how interactions occur, whether the agencies involved perceive their occupational environment as being gender affected and whether they believe this can hinder effective collaboration with other biased organisations. Our principal empirical findings indicate that there is a general awareness amongst professionals of the role that gender plays in each of the agencies reviewed, that gender may well constitute a barrier to effective communication, but there is a sense in which there is little scope for change in the short term. We aim to signal here, however, the need to change against the risk of service failure.
Abstract: The article describes a case study on one of Czech
Republic-s manufacturing middle size enterprises (ME), where due to
the European financial crisis, production lines had to be redesigned
and optimized in order to minimize the total costs of the production
of goods. It is considered an optimization problem of minimizing the
total cost of the work load, according to the costs of the possible
locations of the workplaces, with an application of the Greedy
algorithm and a partial analogy to a Set Packing Problem. The
displacement of working tables in a company should be as a one-toone
monotone increasing function in order for the total costs of
production of the goods to be at minimum. We use a heuristic
approach with greedy algorithm for solving this linear optimization
problem, regardless the possible greediness which may appear and
we apply it in a Czech ME.
Abstract: This paper addresses the problem of building a unified
structure to describe a peer-to-peer system. Our approach uses the
well-known notations in the P2P area, and provides a global
architecture that puts a separation between the platform specific
characteristics and the logical ones. In order to enable the navigation
of the peer across platforms, a roaming layer is added. The latter
provides a capability to define a unique identification of peer and
assures the mapping between this identification and those used in
each platform. The mapping task is assured by special wrapper. In
addition, ontology is proposed to give a clear presentation of the
structure of the P2P system without interesting in the content and the
resource managed by the peer. The ontology is created according to
the web semantic paradigm and using OWL language; so, the
structure of the system is considered as a web resource.
Abstract: Our study proposes an alternative method in building
Fuzzy Rule-Based System (FRB) from Support Vector Machine
(SVM). The first set of fuzzy IF-THEN rules is obtained through
an equivalence of the SVM decision network and the zero-ordered
Sugeno FRB type of the Adaptive Network Fuzzy Inference System
(ANFIS). The second set of rules is generated by combining the
first set based on strength of firing signals of support vectors using
Gaussian kernel. The final set of rules is then obtained from the
second set through input scatter partitioning. A distinctive advantage
of our method is the guarantee that the number of final fuzzy IFTHEN
rules is not more than the number of support vectors in the
trained SVM. The final FRB system obtained is capable of performing
classification with results comparable to its SVM counterpart, but it
has an advantage over the black-boxed SVM in that it may reveal
human comprehensible patterns.
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: Least Significant Bit (LSB) technique is the earliest
developed technique in watermarking and it is also the most simple,
direct and common technique. It essentially involves embedding the
watermark by replacing the least significant bit of the image data with
a bit of the watermark data. The disadvantage of LSB is that it is not
robust against attacks. In this study intermediate significant bit (ISB)
has been used in order to improve the robustness of the watermarking
system. The aim of this model is to replace the watermarked image
pixels by new pixels that can protect the watermark data against
attacks and at the same time keeping the new pixels very close to the
original pixels in order to protect the quality of watermarked image.
The technique is based on testing the value of the watermark pixel
according to the range of each bit-plane.
Abstract: Support Vector Domain Description (SVDD) is one of the best-known one-class support vector learning methods, in which one tries the strategy of using balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. As all kernel-based learning algorithms its performance depends heavily on the proper choice of the kernel parameter. This paper proposes a new approach to select kernel's parameter based on maximizing the distance between both gravity centers of normal and abnormal classes, and at the same time minimizing the variance within each class. The performance of the proposed algorithm is evaluated on several benchmarks. The experimental results demonstrate the feasibility and the effectiveness of the presented method.
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: Wind farms (WFs) with high level of penetration are
being established in power systems worldwide more rapidly than
other renewable resources. The Independent System Operator (ISO),
as a policy maker, should propose appropriate places for WF
installation in order to maximize the benefits for the investors. There
is also a possibility of congestion relief using the new installation of
WFs which should be taken into account by the ISO when proposing
the locations for WF installation. In this context, efficient wind farm
(WF) placement method is proposed in order to reduce burdens on
congested lines. Since the wind speed is a random variable and load
forecasts also contain uncertainties, probabilistic approaches are used
for this type of study. AC probabilistic optimal power flow (P-OPF)
is formulated and solved using Monte Carlo Simulations (MCS). In
order to reduce computation time, point estimate methods (PEM) are
introduced as efficient alternative for time-demanding MCS.
Subsequently, WF optimal placement is determined using generation
shift distribution factors (GSDF) considering a new parameter
entitled, wind availability factor (WAF). In order to obtain more
realistic results, N-1 contingency analysis is employed to find the
optimal size of WF, by means of line outage distribution factors
(LODF). The IEEE 30-bus test system is used to show and compare
the accuracy of proposed methodology.
Abstract: Diagnosis can be achieved by building a model of a
certain organ under surveillance and comparing it with the real time
physiological measurements taken from the patient. This paper deals
with the presentation of the benefits of using Data Mining techniques
in the computer-aided diagnosis (CAD), focusing on the cancer
detection, in order to help doctors to make optimal decisions quickly
and accurately. In the field of the noninvasive diagnosis techniques,
the endoscopic ultrasound elastography (EUSE) is a recent elasticity
imaging technique, allowing characterizing the difference between
malignant and benign tumors. Digitalizing and summarizing the main
EUSE sample movies features in a vector form concern with the use
of the exploratory data analysis (EDA). Neural networks are then
trained on the corresponding EUSE sample movies vector input in
such a way that these intelligent systems are able to offer a very
precise and objective diagnosis, discriminating between benign and
malignant tumors. A concrete application of these Data Mining
techniques illustrates the suitability and the reliability of this
methodology in CAD.
Abstract: Tourism and coastal lines are the business sectors
since centuries especially in the European Nations and Albania is one
such spots. However, in recent decades tourism is experienced as
vulnerability of the surrounding ecological conditions of air, soil,
water, land and the communities that are dependant and sharing the
ecosystem among flora and fauna. Experts opine that apart from the
maintenance of near-originality of ecological biodiversity the tourism
rather known as ecotourism an indigenous socio-cultural
maintenance of indigenous/traditional knowledge of the local people
must be well cared in order to sustain on sustainable grounds. As a
general tendency, growth of tourism has been affected by the deterioration in the economic conditions on one aspect and unsustainable ecological areas affected since human interventions
earlier to this has negative impact on futuristic tourist spots. However, tourism in Albania as of now is 11% of GDP and coastal regions accounting to 2-4%. An amicable Mediterranean
climate with 300 sunny days similar parameters of Greece and Spain
throws up sustainable ecotourism in future decades provided public services namely, transportation, road safety, lodging, food
availability, recreational regiments, banking accessibility are as per
the World Tourism Organizations- protocols. Thus as of Albanian
situation, classification of ecotourism activities to safe-guard the localities with its maintenance of ecological land, water and climate
has become a paramount importance with a wanting and satisfactory options through harnessing human energy for profit and fitness of
ecological flora and fauna. A check on anthropogenic wastes and
their safer utilizations inclusive of agricultural and industrial
operations in line with Lalzi Bay Coastal Line are of utmost importance for the reason that the Adriatic Sea Coast is the one long
stretch of Albanian Lifeline. The present work is based on the methodology of the sustainable management of the same issue.
Abstract: The present work is concerned with the effect of turning process parameters (cutting speed, feed rate, and depth of cut) and distance from the center of work piece as input variables on the chip micro-hardness as response or output. Three experiments were conducted; they were used to investigate the chip micro-hardness behavior at diameter of work piece for 30[mm], 40[mm], and 50[mm]. Response surface methodology (R.S.M) is used to determine and present the cause and effect of the relationship between true mean response and input control variables influencing the response as a two or three dimensional hyper surface. R.S.M has been used for designing a three factor with five level central composite rotatable factors design in order to construct statistical models capable of accurate prediction of responses. The results obtained showed that the application of R.S.M can predict the effect of machining parameters on chip micro-hardness. The five level factorial designs can be employed easily for developing statistical models to predict chip micro-hardness by controllable machining parameters. Results obtained showed that the combined effect of cutting speed at it?s lower level, feed rate and depth of cut at their higher values, and larger work piece diameter can result increasing chi micro-hardness.
Abstract: The multiple traveling salesman problem (mTSP) can be used to model many practical problems. The mTSP is more complicated than the traveling salesman problem (TSP) because it requires determining which cities to assign to each salesman, as well as the optimal ordering of the cities within each salesman's tour. Previous studies proposed that Genetic Algorithm (GA), Integer Programming (IP) and several neural network (NN) approaches could be used to solve mTSP. This paper compared the results for mTSP, solved with Genetic Algorithm (GA) and Nearest Neighbor Algorithm (NNA). The number of cities is clustered into a few groups using k-means clustering technique. The number of groups depends on the number of salesman. Then, each group is solved with NNA and GA as an independent TSP. It is found that k-means clustering and NNA are superior to GA in terms of performance (evaluated by fitness function) and computing time.
Abstract: Chemical detection is still a continuous challenge when
it comes to designing single-walled carbon nanotube (SWCNT)
sensors with high selectivity, especially in complex chemical
environments. A perfect example of such an environment would be in
thermally oxidized soybean oil. At elevated temperatures, oil oxidizes
through a series of chemical reactions which results in the formation of
monoacylglycerols, diacylglycerols, oxidized triacylglycerols, dimers,
trimers, polymers, free fatty acids, ketones, aldehydes, alcohols,
esters, and other minor products. In order to detect the rancidity of
oxidized soybean oil, carbon nanotube chemiresistor sensors have
been coated with polyethylenimine (PEI) to enhance the sensitivity
and selectivity. PEI functionalized SWCNTs are known to have a high
selectivity towards strong electron withdrawing molecules. The
sensors were very responsive to different oil oxidation levels and
furthermore, displayed a rapid recovery in ambient air without the
need of heating or UV exposure.