Abstract: Within the realm of e-government, the development has moved towards testing new means for democratic decisionmaking, like e-panels, electronic discussion forums, and polls. Although such new developments seem promising, they are not problem-free, and the outcomes are seldom used in the subsequent formal political procedures. Nevertheless, process models offer promising potential when it comes to structuring and supporting transparency of decision processes in order to facilitate the integration of the public into decision-making procedures in a reasonable and manageable way. Based on real-life cases of urban planning processes in Sweden, we present an outline for an integrated framework for public decision making to: a) provide tools for citizens to organize discussion and create opinions; b) enable governments, authorities, and institutions to better analyse these opinions; and c) enable governments to account for this information in planning and societal decision making by employing a process model for structured public decision making.
Abstract: Glutathione S-transferase was purified from human
erythrocytes and effects of some polyphenols were investigated on
the enzyme activity. The purification procedure was performed on
Glutathione-Agarose affinity chromatography after preparation of
erythrocytes hemolysate with a yield of 81%. The purified enzyme
showed a single band on the SDS-PAGE. The effects of some
poliphenolic compounds such as catechin, dopa, dopamine, progallol
and catechol were examined on the in vitro GST activity. Catechin
was determined to be inhibitor for the enzyme, but others were not
effective on the enzyme as inhibitors or activators. IC50 value -the
concentration of inhibitor which reduces enzyme activity by 50%-
was estimated to be 10 mM. Ki constants were also calculated as 6.38
± 0,70 mM with GSH substrate, and 3.86 ± 0,78 mM with CDNB
substrate using the equations of graphs for the inhibitor, and its
inhibition type was determined as non-competitive.
Abstract: A precision CMOS chopping amplifier is adopted in this work to improve a CMOS temperature sensor high sensitive enough for intracranial temperature monitoring. An amplified temperature sensitivity of 18.8 ± 3*0.2 mV/oC is attained over the temperature range from 20 oC to 80 oC from a given 10 samples of the same wafer. The analog frontend design outputs the temperature dependent and the temperature independent signals which can be directly interfaced to a 10 bit ADC to accomplish an accurate temperature instrumentation system.
Abstract: This paper investigates the occurrence of regenerative
chatter vibrations in facing and turning processes. Orthogonal turning
(facing) and normal turning experiments are carried out under stable
as well as in the presence of controlled chatter vibrations. The effects
of chatter vibrations on various sensor signals are captured and
analyzed using frequency domain methods, which successfully
detected the chatter vibrations close to the dominant mode of the
machine tool system.
Abstract: The source voltage of high-power fuel cell shows strong load dependence at comparatively low voltage levels. In order to provide the voltage of 750V on the DC-link for feeding electrical energy into the mains via a three phase inverter a step-up converter with a large step-up ratio is required. The output voltage of this DC/DC-converter must be stabile during variations of the load current and the voltage of the fuel cell. This paper presents the methods and results of the calculation of the efficiency and the expense for the realization for the circuits of the DC/DC-converter that meet these requirements.
Abstract: In this work, the condensation fraction and transition
temperature of neutral many bosonic system are studied within the
static fluctuation approximation (SFA). The effect of the potential
parameters such as the strength and range on the condensate fraction
was investigated. A model potential consisting of a repulsive step
potential and an attractive potential well was used. As the potential
strength or the core radius of the repulsive part increases, the
condensation fraction is found to be decreased at the same
temperature. Also, as the potential depth or the range of the attractive
part increases, the condensation fraction is found to be increased. The
transition temperature is decreased as the potential strength or the
core radius of the repulsive part increases, and it increases as the
potential depth or the range of the attractive part increases.
Abstract: The effects of seawater and slurry ice bleeding methods on the sensory, microbiological and chemical quality changes of cod fillets during chilled storage were examined in this study. The results from sensory evaluation showed that slurry ice bleeding method prolonged the shelf life of cod fillets up to 13-14 days compared to 10-11 days for fish bled in seawater. Slurry ice bleeding method also led to a slower microbial growth and biochemical developments, resulting lower total plate count (TPC), H2S-producing bacteria count, total volatile basic nitrogen (TVB-N), trimethylamine (TMA), free fatty acid (FFA) content and higher phospholipid content (PL) compared to those of samples bled in seawater. The results of principle component analysis revealed that TPC, H2S-producing bacteria, TVB-N, TMA and FFA were in significant correlation. They were also in negative correlation with sensory evaluation (Torry score), PL and water holding capacity (WHC).
Abstract: The present work was conducted for the synthesis of
nano size zerovalent iron (nZVI) and hexavalent chromium (Cr(VI))
removal as a highly toxic pollutant by using this nanoparticles. Batch
experiments were performed to investigate the effects of Cr(VI),
nZVI concentration, pH of solution and contact time variation on
the removal efficiency of Cr(VI). nZVI was synthesized by
reduction of ferric chloride using sodium borohydrid. SEM and
XRD examinations applied for determination of particle size and
characterization of produced nanoparticles. The results showed that
the removal efficiency decreased with Cr(VI) concentration and pH
of solution and increased with adsorbent dosage and contact time.
The Langmuir and Freundlich isotherm models were used for the
adsorption equilibrium data and the Langmuir isotherm model was
well fitted. Nanoparticle ZVI presented an outstanding ability to
remove Cr(VI) due to high surface area, low particle size and high
inherent activity.
Abstract: This research tries to analyze the role that knowledge
about foreign markets has in increasing firms- exports in clustered
spaces. We consider two interrelated sources of knowledge: firms-
direct experience and indirect experience from other clustered firms –
export externalities. In particular, it is proposed that firms would
improve their export performance by accessing to export externalities
if they have some previous direct experience that allows them to
identify, understand and exploit them. Also, we propose that this
positive influence of previous direct experience on export
externalities keeps only up to a point, where it becomes negative,
creating an inverted “U" shape. Empirical evidence gathered among
wine producers located in La Rioja tends to confirm that firms enjoy
of export externalities if they have export experience along several
years and countries increase their export performance. While this
relationship becomes less relevant as they develop a higher
experience, we could not confirm the existence of a curvilinear
relationship in their influence on export externalities and export
performance.
Abstract: This study evaluates the performance of horizontal
subsurface flow constructed wetland (HSSF-CW) for the removal of
chlorinated resin and fatty acids (RFAs) from pulp and paper mill
wastewater. The dimensions of the treatment system were 3.5 m x 1.5
m x 0.28 m with surface area of 5.25 m2, filled with fine sand and
gravel. The cell was planted with an ornamental plant species Canna
indica. The removal efficiency of chlorinated RFAs was in the range
of 92-96% at the hydraulic retention time (HRT) of 5.9 days. Plant
biomass and soil (sand and gravel) were analyzed for chlorinated
RFAs content. No chlorinated RFAs were detected in plant biomass
but detected in soil samples. Mass balance studies of chlorinated
RFAs in HSSF-CW were also carried out.
Abstract: Computer modeling has played a unique role in
understanding electrocardiography. Modeling and simulating cardiac
action potential propagation is suitable for studying normal and
pathological cardiac activation. This paper presents a 2-D Cellular
Automata model for simulating action potential propagation in
cardiac tissue. We demonstrate a novel algorithm in order to use
minimum neighbors. This algorithm uses the summation of the
excitability attributes of excited neighboring cells. We try to
eliminate flat edges in the result patterns by inserting probability to
the model. We also preserve the real shape of action potential by
using linear curve fitting of one well known electrophysiological
model.
Abstract: Landslide susceptibility map delineates the potential
zones for landslide occurrence. Previous works have applied
multivariate methods and neural networks for mapping landslide
susceptibility. This study proposed a new approach to integrate
decision tree model and spatial cluster statistic for assessing landslide
susceptibility spatially. A total of 2057 landslide cells were digitized
for developing the landslide decision tree model. The relationships of
landslides and instability factors were explicitly represented by using
tree graphs in the model. The local Getis-Ord statistics were used to
cluster cells with high landslide probability. The analytic result from
the local Getis-Ord statistics was classed to create a map of landslide
susceptibility zones. The map was validated using new landslide data
with 482 cells. Results of validation show an accuracy rate of 86.1% in
predicting new landslide occurrence. This indicates that the proposed
approach is useful for improving landslide susceptibility mapping.
Abstract: In this study the mixed convection heat transfer in a
coil-in-shell heat exchanger for various Reynolds numbers and
various dimensionless coil pitch was experimentally investigated.
The experiments were conducted for both laminar and turbulent flow
inside coil and the effects of coil pitch on shell-side heat transfer
coefficient of the heat exchanger were studied. The particular
difference in this study in comparison with the other similar studies
was the boundary conditions for the helical coils. The results indicate
that with the increase of coil pitch, shell-side heat transfer coefficient
is increased.
Abstract: In this paper, we have compared the performance of a Turbo and Trellis coded optical code division multiple access (OCDMA) system. The comparison of the two codes has been accomplished by employing optical orthogonal codes (OOCs). The Bit Error Rate (BER) performances have been compared by varying the code weights of address codes employed by the system. We have considered the effects of optical multiple access interference (OMAI), thermal noise and avalanche photodiode (APD) detector noise. Analysis has been carried out for the system with and without double optical hard limiter (DHL). From the simulation results it is observed that a better and distinct comparison can be drawn between the performance of Trellis and Turbo coded systems, at lower code weights of optical orthogonal codes for a fixed number of users. The BER performance of the Turbo coded system is found to be better than the Trellis coded system for all code weights that have been considered for the simulation. Nevertheless, the Trellis coded OCDMA system is found to be better than the uncoded OCDMA system. Trellis coded OCDMA can be used in systems where decoding time has to be kept low, bandwidth is limited and high reliability is not a crucial factor as in local area networks. Also the system hardware is less complex in comparison to the Turbo coded system. Trellis coded OCDMA system can be used without significant modification of the existing chipsets. Turbo-coded OCDMA can however be employed in systems where high reliability is needed and bandwidth is not a limiting factor.
Abstract: The aim of this contribution is to present a new
approach in modeling the electrical activity of the human heart. A
recurrent artificial neural network is being used in order to exhibit a
subset of the dynamics of the electrical behavior of the human heart.
The proposed model can also be used, when integrated, as a
diagnostic tool of the human heart system.
What makes this approach unique is the fact that every model is
being developed from physiological measurements of an individual.
This kind of approach is very difficult to apply successfully in many
modeling problems, because of the complexity and entropy of the
free variables describing the complex system. Differences between
the modeled variables and the variables of an individual, measured at
specific moments, can be used for diagnostic purposes. The sensor
fusion used in order to optimize the utilization of biomedical sensors
is another point that this paper focuses on. Sensor fusion has been
known for its advantages in applications such as control and
diagnostics of mechanical and chemical processes.
Abstract: Shape optimization of the airfoil with high aspect ratio
of long endurance unmanned aerial vehicle (UAV) is performed by the
multi-objective optimization technology coupled with computational
fluid dynamics (CFD). For predicting the aerodynamic characteristics
around the airfoil the high-fidelity Navier-Stokes solver is employed
and SMOGA (Simple Multi-Objective Genetic Algorithm), which is
developed by authors, is used for solving the multi-objective
optimization problem. To obtain the optimal solutions of the design
variable (i.e., sectional airfoil profile, wing taper ratio and sweep) for
high performance of UAVs, both the lift and lift-to-drag ratio are
maximized whereas the pitching moment should be minimized,
simultaneously. It is found that the lift force and lift-to-drag ratio are
linearly dependent and a unique and dominant solution are existed.
However, a trade-off phenomenon is observed between the lift-to-drag
ratio and pitching moment. As the result of optimization, sixty-five
(65) non-dominated Pareto individuals at the cutting edge of design
spaces that is decided by airfoil shapes can be obtained.
Abstract: Proteomics is one of the largest areas of research for
bioinformatics and medical science. An ambitious goal of proteomics
is to elucidate the structure, interactions and functions of all proteins
within cells and organisms. Predicting Protein-Protein Interaction
(PPI) is one of the crucial and decisive problems in current research.
Genomic data offer a great opportunity and at the same time a lot of
challenges for the identification of these interactions. Many methods
have already been proposed in this regard. In case of in-silico
identification, most of the methods require both positive and negative
examples of protein interaction and the perfection of these examples
are very much crucial for the final prediction accuracy. Positive
examples are relatively easy to obtain from well known databases. But
the generation of negative examples is not a trivial task. Current PPI
identification methods generate negative examples based on some
assumptions, which are likely to affect their prediction accuracy.
Hence, if more reliable negative examples are used, the PPI prediction
methods may achieve even more accuracy. Focusing on this issue, a
graph based negative example generation method is proposed, which
is simple and more accurate than the existing approaches. An
interaction graph of the protein sequences is created. The basic
assumption is that the longer the shortest path between two
protein-sequences in the interaction graph, the less is the possibility of
their interaction. A well established PPI detection algorithm is
employed with our negative examples and in most cases it increases
the accuracy more than 10% in comparison with the negative pair
selection method in that paper.
Abstract: In this paper, Optimum adaptive loading algorithms
are applied to multicarrier system with Space-Time Block Coding
(STBC) scheme associated with space-time processing based on
singular-value decomposition (SVD) of the channel matrix over
Rayleigh fading channels. SVD method has been employed in
MIMO-OFDM system in order to overcome subchannel interference.
Chaw-s and Compello-s algorithms have been implemented to obtain
a bit and power allocation for each subcarrier assuming instantaneous
channel knowledge. The adaptive loaded SVD-STBC scheme is
capable of providing both full-rate and full-diversity for any number
of transmit antennas. The effectiveness of these techniques has
demonstrated through the simulation of an Adaptive loaded SVDSTBC
system, and the comparison shown that the proposed
algorithms ensure better performance in the case of MIMO.
Abstract: In this paper; we are interested principally in dynamic modelling of quadrotor while taking into account the high-order nonholonomic constraints in order to develop a new control scheme as well as the various physical phenomena, which can influence the dynamics of a flying structure. These permit us to introduce a new state-space representation. After, the use of Backstepping approach for the synthesis of tracking errors and Lyapunov functions, a sliding mode controller is developed in order to ensure Lyapunov stability, the handling of all system nonlinearities and desired tracking trajectories. Finally simulation results are also provided in order to illustrate the performances of the proposed controller.
Abstract: This paper presents a supervised clustering algorithm,
namely Grid-Based Supervised Clustering (GBSC), which is able to
identify clusters of any shapes and sizes without presuming any
canonical form for data distribution. The GBSC needs no prespecified
number of clusters, is insensitive to the order of the input
data objects, and is capable of handling outliers. Built on the
combination of grid-based clustering and density-based clustering,
under the assistance of the downward closure property of density
used in bottom-up subspace clustering, the GBSC can notably reduce
its search space to avoid the memory confinement situation during its
execution. On two-dimension synthetic datasets, the GBSC can
identify clusters with different shapes and sizes correctly. The GBSC
also outperforms other five supervised clustering algorithms when
the experiments are performed on some UCI datasets.