Abstract: One of the best ways for achievement of conventional
vehicle changing to hybrid case is trustworthy simulation result and
using of driving realities. For this object, in this paper, at first sevendegree-
of-freedom dynamical model of vehicle will be shown. Then
by using of statically model of engine, gear box, clutch, differential,
electrical machine and battery, the hybrid automobile modeling will
be down and forward simulation of vehicle for pedals to wheels
power transformation will be obtained. Then by design of a fuzzy
controller and using the proper rule base, fuel economy and
regenerative braking will be marked. Finally a series of
MATLAB/SIMULINK simulation results will be proved the
effectiveness of proposed structure.
Abstract: Relay based communication has gained considerable importance in the recent years. In this paper we find the end-toend statistics of a two hop non-regenerative relay branch, each hop being Nakagami-m faded. Closed form expressions for the probability density functions of the signal envelope at the output of a selection combiner and a maximal ratio combiner at the destination node are also derived and analytical formulations are verified through computer simulation. These density functions are useful in evaluating the system performance in terms of bit error rate and outage probability.
Abstract: The development and application of wind power for
renewable energy has attracted growing interest in recent years. Renewable energy sources are attracting much alteration as they can
reduce both environmental damage and dependence on fossil fuels. With the growing need for sustainable energy supplies, a case is made
for decentralized, stand-alone power supplies (SAPS) as an alternative to power grids. In the era which traditional petroleum energy resource
decreasing and the green house affect significant increasing, the development and usage of regenerative resources is inevitable. Due to the contribution of the pioneers, the development of regenerative resources already has a remarkable achievement; however, in the view of economy and quantity, it is still a long road for regenerative energy
to replace traditional petroleum energy. In our prospective, in stead of
investigate larger regenerative energy equipment, it is much wiser to
think about the blind side and breakthrough of the current technique.
Abstract: Impaired fertility may be the result of indirect
consumption of anti-fertility agents through food. Monosodium
glutamate (MSG) has been widely used as food additive, flavour
enhancer and included in vaccines. This study focuses in determining
the gonadotoxic and cytotoxic effect of MSG on selected sperm
parameters such as sperm viability, sperm membrane integrity and
testes cytoarchitecture of male mice via histological examination to
determine its effect on spermatogenesis. Twenty-four Mus musculus
were randomly divided into 4 groups and given intraperitoneal
injections (IP) daily for 14 days of different MSG concentrations at
250, 500 and 1000mg/kg MSG to body weight to induce obesity.
Saline was given to control group. Mice were sacrificed and analysis
revealed abnormalities in values for sperm parameters and damages
to testes cytoarchitecture of male mice. The results recorded
decreased viability (p0.05) with degenerative structures in seminiferous tubule of
testes. The results indicated various implications of MSG on male
mice reproductive system which has consequences in fertility
potential.
Abstract: Obtaining labeled data in supervised learning is often
difficult and expensive, and thus the trained learning algorithm tends
to be overfitting due to small number of training data. As a result,
some researchers have focused on using unlabeled data which may
not necessary to follow the same generative distribution as the labeled
data to construct a high-level feature for improving performance on
supervised learning tasks. In this paper, we investigate the impact of
the relationship between unlabeled and labeled data for classification
performance. Specifically, we will apply difference unlabeled data
which have different degrees of relation to the labeled data for
handwritten digit classification task based on MNIST dataset. Our
experimental results show that the higher the degree of relation
between unlabeled and labeled data, the better the classification
performance. Although the unlabeled data that is completely from
different generative distribution to the labeled data provides the lowest
classification performance, we still achieve high classification performance.
This leads to expanding the applicability of the supervised
learning algorithms using unsupervised learning.
Abstract: Fuel cell's system requires regulating circuit for
voltage and current in order to control power in case of connecting to
other generative devices or load. In this paper Fuel cell system and
convertor, which is a multi-variable system, are controlled using
sliding mode method. Use of weighting matrix in design procedure
made it possible to regulate speed of control. Simulation results show
the robustness and accuracy of proposed controller for controlling
desired of outputs.
Abstract: An effective approach for realizing the binary tree structure, representing a combinational logic functionality with enhanced throughput, is discussed in this paper. The optimization in maximum operating frequency was achieved through delay minimization, which in turn was possible by means of reducing the depth of the binary network. The proposed synthesis methodology has been validated by experimentation with FPGA as the target technology. Though our proposal is technology independent, yet the heuristic enables better optimization in throughput even after technology mapping for such Boolean functionality; whose reduced CNF form is associated with a lesser literal cost than its reduced DNF form at the Boolean equation level. For cases otherwise, our method converges to similar results as that of [12]. The practical results obtained for a variety of case studies demonstrate an improvement in the maximum throughput rate for Spartan IIE (XC2S50E-7FT256) and Spartan 3 (XC3S50-4PQ144) FPGA logic families by 10.49% and 13.68% respectively. With respect to the LUTs and IOBUFs required for physical implementation of the requisite non-regenerative logic functionality, the proposed method enabled savings to the tune of 44.35% and 44.67% respectively, over the existing efficient method available in literature [12].
Abstract: Extracellular ubiquitin in vivo effect on regenerative liver cells and liver histoarchitectonics has been studied. Experiments were performed on mature female white rats. Partial hepatectomy was made using the modified method of Higgins and Anderson. Standard histopathological assessment of liver tissue was used. Proliferative activity of hepatocytes was analyzed by colchicine mitotic index and immunohistochemical staining on ki67. We have found that regardless of number of injections and dose of extracellular ubiquitin liver histology has not been changed, so at tissue level no effect was observed. In vivo double injection of ubiquitin significantly decreases the mitotic activity at 32 hour point after partial hepatectomy. Thus, we can conclude that in vivo injected extracellular ubiquitin inhibits proliferative activity of hepatocytes in partially hepatectomyzed rats.
Abstract: Because of importance of energy, optimization of
power generation systems is necessary. Gas turbine cycles are
suitable manner for fast power generation, but their efficiency is
partly low. In order to achieving higher efficiencies, some
propositions are preferred such as recovery of heat from exhaust
gases in a regenerator, utilization of intercooler in a multistage
compressor, steam injection to combustion chamber and etc.
However thermodynamic optimization of gas turbine cycle, even
with above components, is necessary. In this article multi-objective
genetic algorithms are employed for Pareto approach optimization of
Regenerative-Intercooling-Gas Turbine (RIGT) cycle. In the multiobjective
optimization a number of conflicting objective functions
are to be optimized simultaneously. The important objective
functions that have been considered for optimization are entropy
generation of RIGT cycle (Ns) derives using Exergy Analysis and
Gouy-Stodola theorem, thermal efficiency and the net output power
of RIGT Cycle. These objectives are usually conflicting with each
other. The design variables consist of thermodynamic parameters
such as compressor pressure ratio (Rp), excess air in combustion
(EA), turbine inlet temperature (TIT) and inlet air temperature (T0).
At the first stage single objective optimization has been investigated
and the method of Non-dominated Sorting Genetic Algorithm
(NSGA-II) has been used for multi-objective optimization.
Optimization procedures are performed for two and three objective
functions and the results are compared for RIGT Cycle. In order to
investigate the optimal thermodynamic behavior of two objectives,
different set, each including two objectives of output parameters, are
considered individually. For each set Pareto front are depicted. The
sets of selected decision variables based on this Pareto front, will
cause the best possible combination of corresponding objective
functions. There is no superiority for the points on the Pareto front
figure, but they are superior to any other point. In the case of three
objective optimization the results are given in tables.
Abstract: Chemical reaction and diffusion are important phenomena in quantitative neurobiology and biophysics. The knowledge of the dynamics of calcium Ca2+ is very important in cellular physiology because Ca2+ binds to many proteins and regulates their activity and interactions Calcium waves propagate inside cells due to a regenerative mechanism known as calcium-induced calcium release. Buffer-mediated calcium diffusion in the cytosol plays a crucial role in the process. A mathematical model has been developed for calcium waves by assuming the buffers are in equilibrium with calcium i.e., the rapid buffering approximation for a one dimensional unsteady state case. This model incorporates important physical and physiological parameters like dissociation rate, diffusion rate, total buffer concentration and influx. The finite difference method has been employed to predict [Ca2+] and buffer concentration time course regardless of the calcium influx. The comparative studies of the effect of the rapid buffered diffusion and kinetic parameters of the model on the concentration time course have been performed.
Abstract: Osteoarthritis (OA) is the most prevalent and far common debilitating form of arthritis which can be defined as a degenerative condition affecting synovial joint. Patients suffering from osteoarthritis often complain of dull ache pain on movement.
Physical agents can fight the painful process when correctly indicated and used such as heat or cold therapy Aim. This study was carried out to: Compare the effect of cold, warm and contrast therapy on controlling knee osteoarthritis associated problems. Setting: The study was carried out in orthopedic outpatient clinics of Menoufia University and teaching Hospitals, Egypt. Sample: A convenient sample of 60 adult patients with unilateral knee osteoarthritis. Tools: three tools were utilized to collect the data. Tool I : An interviewing questionnaire. It comprised of three parts covering sociodemographic data, medical data and adverse effects of the treatment protocol. Tool II : Knee Injury and Osteoarthritis Outcome Score (KOOS) It consists of five main parts. Tool II1 : 0-10 Numeric pain rating scale. Results: reveled that the total knee symptoms score was decreased from moderate symptoms pre intervention to mild symptoms after warm and contrast method of therapy, but the contrast therapy had significant effect in reducing the knee symptoms and pain than the other symptoms. Conclusions: all of the three
methods of therapy resulted in improvement in all knee symptoms and pain but the most appropriate protocol of treatment to relive symptoms and pain was contrast therapy.
Abstract: This paper discusses a new, systematic approach to
the synthesis of a NP-hard class of non-regenerative Boolean
networks, described by FON[FOFF]={mi}[{Mi}], where for every
mj[Mj]∈{mi}[{Mi}], there exists another mk[Mk]∈{mi}[{Mi}], such
that their Hamming distance HD(mj, mk)=HD(Mj, Mk)=O(n), (where
'n' represents the number of distinct primary inputs). The method
automatically ensures exact minimization for certain important selfdual
functions with 2n-1 points in its one-set. The elements meant for
grouping are determined from a newly proposed weighted incidence
matrix. Then the binary value corresponding to the candidate pair is
correlated with the proposed binary value matrix to enable direct
synthesis. We recommend algebraic factorization operations as a post
processing step to enable reduction in literal count. The algorithm
can be implemented in any high level language and achieves best
cost optimization for the problem dealt with, irrespective of the
number of inputs. For other cases, the method is iterated to
subsequently reduce it to a problem of O(n-1), O(n-2),.... and then
solved. In addition, it leads to optimal results for problems exhibiting
higher degree of adjacency, with a different interpretation of the
heuristic, and the results are comparable with other methods.
In terms of literal cost, at the technology independent stage, the
circuits synthesized using our algorithm enabled net savings over
AOI (AND-OR-Invert) logic, AND-EXOR logic (EXOR Sum-of-
Products or ESOP forms) and AND-OR-EXOR logic by 45.57%,
41.78% and 41.78% respectively for the various problems.
Circuit level simulations were performed for a wide variety of
case studies at 3.3V and 2.5V supply to validate the performance of
the proposed method and the quality of the resulting synthesized
circuits at two different voltage corners. Power estimation was
carried out for a 0.35micron TSMC CMOS process technology. In
comparison with AOI logic, the proposed method enabled mean
savings in power by 42.46%. With respect to AND-EXOR logic, the
proposed method yielded power savings to the tune of 31.88%, while
in comparison with AND-OR-EXOR level networks; average power
savings of 33.23% was obtained.
Abstract: The system is made with main distributed components:
First Level: Industrial Computers placed in Control Room (monitors thermal and electrical processes based on the data provided by the second level); Second Level: PLCs which collects data from process and transmits information on the first level; also takes commands from this level which are further, passed to execution elements from third
level; Third Level: field elements consisting in 3 categories: data collecting elements; data transfer elements from the third level to the second; execution elements which take commands from the second
level PLCs and executes them after which transmits the confirmation of execution to them. The purpose of the automatic functioning is the optimization of the co-generative electrical energy commissioning in the national
energy system and the commissioning of thermal energy to the consumers.
The integrated system treats the functioning of all the equipments and devices as a whole: Gas Turbine Units (GTU); MT 20kV Medium Voltage Station (MVS); 0,4 kV Low Voltage Station (LVS); Main Hot Water Boilers (MHW); Auxiliary Hot Water Boilers (AHW); Gas Compressor Unit (GCU); Thermal Agent Circulation
Pumping Unit (TPU); Water Treating Station (WTS).
Abstract: Reactiondiffusion systems are mathematical models that describe how the concentration of one or more substances distributed in space changes under the influence of local chemical reactions in which the substances are converted into each other, and diffusion which causes the substances to spread out in space. The classical representation of a reaction-diffusion system is given by semi-linear parabolic partial differential equations, whose general form is ÔêétX(x, t) = DΔX(x, t), where X(x, t) is the state vector, D is the matrix of the diffusion coefficients and Δ is the Laplace operator. If the solute move in an homogeneous system in thermal equilibrium, the diffusion coefficients are constants that do not depend on the local concentration of solvent and of solutes and on local temperature of the medium. In this paper a new stochastic reaction-diffusion model in which the diffusion coefficients are function of the local concentration, viscosity and frictional forces of solvent and solute is presented. Such a model provides a more realistic description of the molecular kinetics in non-homogenoeus and highly structured media as the intra- and inter-cellular spaces. The movement of a molecule A from a region i to a region j of the space is described as a first order reaction Ai k- → Aj , where the rate constant k depends on the diffusion coefficient. Representing the diffusional motion as a chemical reaction allows to assimilate a reaction-diffusion system to a pure reaction system and to simulate it with Gillespie-inspired stochastic simulation algorithms. The stochastic time evolution of the system is given by the occurrence of diffusion events and chemical reaction events. At each time step an event (reaction or diffusion) is selected from a probability distribution of waiting times determined by the specific speed of reaction and diffusion events. Redi is the software tool, developed to implement the model of reaction-diffusion kinetics and dynamics. It is a free software, that can be downloaded from http://www.cosbi.eu. To demonstrate the validity of the new reaction-diffusion model, the simulation results of the chaperone-assisted protein folding in cytoplasm obtained with Redi are reported. This case study is redrawing the attention of the scientific community due to current interests on protein aggregation as a potential cause for neurodegenerative diseases.
Abstract: These This paper looks into frameworks which aim at
furthering the discussion of the role of regenerative design practices
in a city-s historic core and the tool of urban design to achieve urban
revitalization on the island of Cyprus. It also examines the region-s
demographic mix, the effectiveness of its governmental coordination
and the strategies of adaptive reuse and strategic investments in older
areas with existing infrastructure. The two main prongs of
investigation will consider the effect of the existing and proposed
changes in the physical infrastructure and fabric of the city, as well as
the catalytic effect of sustainable urban design practices. Through this
process, the work hopes to integrate the contained potential within
the existing historic core and the contributions and participation of
the migrant and immigrant populations to the local economy. It also
examines ways in which this coupling of factors can bring to the front
the positive effects of this combined effort on an otherwise sluggish
local redevelopment effort. The data for this study is being collected
and organized as part of ongoing urban design and development
student workshop efforts in urban planning and design education.
The work is presented in graphic form and includes data collected
from interviews with study area organizations and the community at
large. Planning work is also based on best practices initiated by the
staff of the Nicosia Master Plan task force, which coordinates holistic
planning efforts for the historic center of the city of Nicosia.
Abstract: Sleep spindles are the most interesting hallmark of
stage 2 sleep EEG. Their accurate identification in a
polysomnographic signal is essential for sleep professionals to help
them mark Stage 2 sleep. Sleep Spindles are also promising objective
indicators for neurodegenerative disorders. Visual spindle scoring
however is a tedious workload. In this paper three different
approaches are used for the automatic detection of sleep spindles:
Short Time Fourier Transform, Wavelet Transform and Wave
Morphology for Spindle Detection. In order to improve the results, a
combination of the three detectors is presented and comparison with
human expert scorers is performed. The best performance is obtained
with a combination of the three algorithms which resulted in a
sensitivity and specificity of 94% when compared to human expert
scorers.
Abstract: In this paper, an analysis is presented, which
demonstrates the effect pre-logic factoring could have on an
automated combinational logic synthesis process succeeding it. The
impact of pre-logic factoring for some arbitrary combinatorial
circuits synthesized within a FPGA based logic design environment
has been analyzed previously. This paper explores a similar effect,
but with the non-regenerative logic synthesized using elements of a
commercial standard cell library. On an overall basis, the results
obtained pertaining to the analysis on a variety of MCNC/IWLS
combinational logic benchmark circuits indicate that pre-logic
factoring has the potential to facilitate simultaneous power, delay and
area optimized synthesis solutions in many cases.
Abstract: Regenerative Thermal Oxidizer (RTO) is one of the
best solutions for removal of Volatile Organic Compounds (VOC)
from industrial processes. In the RTO, VOC in a raw gas are usually
decomposed at 950-1300 K and the combustion heat of VOC is
recovered by regenerative heat exchangers charged with ceramic
honeycombs. The optimization of the treatment of VOC leads to the
reduction of fuel addition to VOC decomposition, the minimization of
CO2 emission and operating cost as well.
In the present work, the thermal efficiency of the RTO was
investigated experimentally in a pilot-scale RTO unit using toluene as
a typical representative of VOC. As a result, it was recognized that the
radiative heat transfer was dominant in the preheating process of a raw
gas when the gas flow rate was relatively low. Further, it was found
that a minimum heat exchanger volume to achieve self combustion of
toluene without additional heating of the RTO by fuel combustion was
dependent on both the flow rate of a raw gas and the concentration of
toluene. The thermal efficiency calculated from fuel consumption and
the decomposed toluene ratio, was found to have a maximum value of
0.95 at a raw gas mass flow rate of 1810 kg·h-1 and honeycombs height
of 1.5m.
Abstract: ORC (Organic Rankine Cycle) has potential of
reducing consumption of fossil fuels and has many favorable
characteristics to exploit low-temperature heat sources. In this work
thermodynamic performance of ORC with regeneration is
comparatively assessed for various working fluids. Special attention is
paid to the effects of system parameters such as the turbine inlet
pressure on the characteristics of the system such as net work
production, heat input, volumetric flow rate per 1 MW of net work and
quality of the working fluid at turbine exit as well as thermal
efficiency. Results show that for a given source the thermal efficiency
generally increases with increasing of the turbine inlet pressure
however has optimal condition for working fluids of low critical
pressure such as iso-pentane or n-pentane.
Abstract: The effect of Alumina nanoparticle size on thermophysical
properties, heat transfer performance and pressure loss characteristics of
Aviation Turbine Fuel (ATF)-Al2O3 nanofluids is studied experimentally for
the proposed application of regenerative cooling of semi-cryogenic rocket
engine thrust chambers. Al2O3 particles with mean diameters of 50 nm or 150
nm are dispersed in ATF. At 500C and 0.3% particle volume concentration,
the bigger particles show increases of 17% in thermal conductivity and 55% in
viscosity, whereas the smaller particles show corresponding increases of 21%
and 22% for thermal conductivity and viscosity respectively. Contrary to these
results, experiments to study the heat transfer performance and pressure loss
characteristics show that at the same pumping power, the maximum
enhancement in heat transfer coefficient at 500C and 0.3% concentration is
approximately 47% using bigger particles, whereas it is only 36% using
smaller particles.