Abstract: This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.
Abstract: The aim of this article is to narrate the utility of novel simulation approach i.e. convolution method to predict blood concentration of drug utilizing dissolution data of salbutamol sulphate microparticulate formulations with different release patterns (1:1, 1:2 and 1:3, drug:polymer). Dissolution apparatus II USP 2007 and 900 ml double distilled water stirrd at 50 rpm was employed for dissolution analysis. From dissolution data, blood drug concentration was determined, and in return predicted blood drug concentration data was used to calculate the pharmacokinetic parameters i.e. Cmax, Tmax, and AUC. Convolution is a good biwaiver technique; however its better utility needs it application in the conditions where biorelevant dissolution media are used.
Abstract: A new generation of manufacturing machines
so-called MIMCA (modular and integrated machine control
architecture) capable of handling much increased complexity in
manufacturing control-systems is presented. Requirement for more
flexible and effective control systems for manufacturing machine
systems is investigated and dimensioned-which highlights a need for
improved means of coordinating and monitoring production
machinery and equipment used to- transport material. The MIMCA
supports simulation based on machine modeling, was conceived by
the authors to address the issues. Essentially MIMCA comprises an
organized unification of selected architectural frameworks and
modeling methods, which include: NISTRCS, UMC and Colored
Timed Petri nets (CTPN). The unification has been achieved; to
support the design and construction of hierarchical and distributed
machine control which realized the concurrent operation of reusable
and distributed machine control components; ability to handle
growing complexity; and support requirements for real- time control
systems. Thus MIMCA enables mapping between 'what a machine
should do' and 'how the machine does it' in a well-defined but
flexible way designed to facilitate reconfiguration of machine
systems.
Abstract: A macroscopic constitutive equation is developed for a high-density cellulose insulation material with emphasis on the outof- plane stress relaxation behavior. A hypothesis is proposed where the total stress is additively composed by an out-of-plane visco-elastic isotropic contribution and an in-plane elastic orthotropic response. The theory is validated against out-of-plane stress relaxation, compressive experiments and in-plane tensile hysteresis, respectively. For large scale finite element simulations, the presented model provides a balance between simplicity and capturing the materials constitutive behaviour.
Abstract: Raw wood vinegar was purified by both standing and
filtering methods. Toxicity tests were conducted under laboratory
conditions by the topical application method (contact poison) and
feeding method (stomach poison). Larvicidal activities of wood
vinegar at four different concentrations (10, 15, 20, 25 and 30 %)
were studied against second instar larvae of housefly (Musca
domestica L.). Four replicates were maintained for all treatments and
controls. Larval mortality was recorded up to 96 hours and compared
with the larval survivability by two methods of larvicidal bioassay.
Percent pupation and percent adult emergence were observed in
treated M. domestica. The study revealed that the feeding method
gave higher efficiency compared with the topical application method.
Larval mortality increased with increasing concentration of wood
vinegar and the duration of exposure. No mortality was found in
treated M. domestica larvae at minimum 10% concentration of wood
vinegar through the experiments. The treated larvae were maintained
up to pupa and adult emergence. At 30% maximum concentration
larval duration was extended to 11 days in M. domestica for topical
application method and 9 days for feeding method. Similarly the
pupal durations were also increased with increased concentrations
(16 and 24 days for topical application method and feeding method
respectively at 30% concentration) of the treatments.
Abstract: To achieve reliable solutions, today-s numerical and
experimental activities need developing more accurate methods and
utilizing expensive facilities, respectfully in microchannels. The analytical
study can be considered as an alternative approach to alleviate
the preceding difficulties. Among the analytical solutions, those with
high robustness and low complexities are certainly more attractive.
The perturbation theory has been used by many researchers to analyze
microflows. In present work, a compressible microflow with constant
heat flux boundary condition is analyzed. The flow is assumed to be
fully developed and steady. The Mach and Reynolds numbers are also
assumed to be very small. For this case, the creeping phenomenon
may have some effect on the velocity profile. To achieve robustness
solution it is assumed that the flow is quasi-isothermal. In this study,
the creeping term which appears in the slip boundary condition
is formulated by different mathematical formulas. The difference
between this work and the previous ones is that the creeping term
is taken into account and presented in non-dimensionalized form.
The results obtained from perturbation theory are presented based
on four non-dimensionalized parameters including the Reynolds,
Mach, Prandtl and Brinkman numbers. The axial velocity, normal
velocity and pressure profiles are obtained. Solutions for velocities
and pressure for two cases with different Br numbers are compared
with each other and the results show that the effect of creeping
phenomenon on the velocity profile becomes more important when
Br number is less than O(ε).
Abstract: The contribution is dealing with the influence of high speed parameters on the quality of machined surface. In general the principle of high speed cutting lies in achieving faster machine times with concurrent increase in accuracy and quality of the machined areas in largely irregular, mathematically hard to define shapes. High speed machining is a highly effective method of machining with the following goals: increasing of machining productivity, increasing of quality of the machined surface, improving of machining economy, improving of ecological aspects of machining. This article is based on an experiment performed by the Department of Machining and Assembly of the Faculty of Mechanical Engineering of VŠBTechnical University of Ostrava.
Abstract: The present work describes an experimental
investigation concerning the determination of viscosity behavior with
shear rate and temperature of edible oils: canola; sunflower; corn;
soybean and the no edible oil: Jatropha curcas. Besides these, it was
tested a blend of canola, corn and sunflower oils as well as sunflower
and soybean biodiesel. Based on experiments, it was obtained shear
stress and viscosity at different shear rates of each sample at 40ºC, as
well as viscosity of each sample at various temperatures in the range
of 24 to 85ºC. Furthermore, it was compared the curves obtained for
the viscosity versus temperature with the curves obtained by
modeling the viscosity dependency on temperature using the Vogel
equation. Also a test in a stationary engine was performed in order to
study the energy generation using blends of soybean oil and soybean
biodiesel with diesel.
Abstract: The present work describes a computational study of
aerodynamic characteristics of GLC305 airfoil clean and with 16.7
min ice shape (rime 212) and 22.5 min ice shape (glaze 944).The
performance of turbulence models SA, Kε, Kω Std, and Kω SST
model are observed against experimental flow fields at different
Mach numbers 0.12, 0.21, 0.28 in a range of Reynolds numbers
3x106, 6x106, and 10.5x106 on clean and iced aircraft airfoil
GLC305. Numerical predictions include lift, drag and pitching
moment coefficients at different Mach numbers and at different angle
of attacks were done. Accuracy of solutions with respect to the
effects of turbulence models, variation of Mach number, initial
conditions, grid resolution and grid spacing near the wall made the
study much sensitive. Navier Stokes equation based computational
technique is used. Results are very close to the experimental results.
It has seen that SA and SST models are more efficient than Kε and
Kω standard in under study problem.
Abstract: The paper addresses a problem of optimal staffing in
open shop environment. The problem is to determine the optimal
number of operators serving a given number of machines to fulfill the
number of independent operations while minimizing staff idle. Using
a Gantt chart presentation of the problem it is modeled as twodimensional
cutting stock problem. A mixed-integer programming
model is used to get minimal job processing time (makespan) for
fixed number of machines' operators. An algorithm for optimal openshop
staffing is developed based on iterative solving of the
formulated optimization task. The execution of the developed
algorithm provides optimal number of machines' operators in the
sense of minimum staff idle and optimal makespan for that number of
operators. The proposed algorithm is tested numerically for a real life
staffing problem. The testing results show the practical applicability
for similar open shop staffing problems.
Abstract: This paper presents a systematic approach for
designing Static Synchronous Series Compensator (SSSC) based
supplementary damping controllers for damping low frequency
oscillations in a single-machine infinite-bus power system. The
design problem of the proposed controller is formulated as an
optimization problem and RCGA is employed to search for optimal
controller parameters. By minimizing the time-domain based
objective function, in which the deviation in the oscillatory rotor
speed of the generator is involved; stability performance of the
system is improved. Simulation results are presented and compared
with a conventional method of tuning the damping controller
parameters to show the effectiveness and robustness of the proposed
design approach.
Abstract: Recently, we have presented an initial implementation
of a model agent-based e-commerce system, which utilized a simple
price negotiation mechanism–English Auction. In this note we
discuss how a Dutch Auction involving multiple units of a product
can be included in our system. We present UML diagrams of
agents involved in price negotiations and briefly discuss rule-based
mechanism exemplifying Dutch Auction.
Abstract: The machining of Carbon Fiber Reinforced Plastics
has come to constitute a significant challenge for many fields of
industry. The resulting surface finish of machined parts is of primary
concern for several reasons, including contact quality and impact on
the assembly. Therefore, the characterization and prediction of
roughness based on machining parameters are crucial for costeffective
operations. In this study, a PCD tool comprised of two
straight flutes was used to trim 32-ply carbon fiber laminates in a bid
to analyze the effects of the feed rate and the cutting speed on the
surface roughness. The results show that while the speed has but a
slight impact on the surface finish, the feed rate for its part affects it
strongly. A detailed study was also conducted on the effect of fiber
orientation on surface roughness, for quasi-isotropic laminates used
in aerospace. The resulting roughness profiles for the four-ply
orientation lay-up were compared, and it was found that fiber angle is
a critical parameter relating to surface roughness. One of the four
orientations studied led to very poor surface finishes, and
characteristic roughness profiles were identified and found to only
relate to the ply orientations of multilayer carbon fiber laminates.
Abstract: The pyrolysis characteristics and kinetics of seven marine biomass, which are fixed Enteromorpha clathrata, floating Enteromorpha clathrata, Ulva lactuca L., Zosterae Marinae L., Thallus Laminariae, Asparagus schoberioides kunth and Undaria pinnatifida (Harv.), were studied with thermogravimetric analysis method. Simultaneously, cornstalk, which is a grass biomass, and sawdust, which is a lignocellulosic biomass, were references. The basic pyrolysis characteristics were studied by using TG- DTG-DTA curves. The results showed that there were three stages (dehydration, dramatic weight loss and slow weight loss) during the whole pyrolysis process of samples. The Tmax of marine biomass was significantly lower than two kinds of terrestrial biomass. Zosterae Marinae L. had a relatively high stability of pyrolysis, but floating Enteromorpha clathrata had lowest stability of pyrolysis and a good combustion characteristics. The corresponding activation energy E and frequency factor A were obtained by Coats-Redfern method. It was found that the pyrolysis reaction mechanism functions of three kinds of biomass are different.
Abstract: Transient Stability is an important issue in power systems planning, operation and extension. The objective of transient stability analysis problem is not satisfied with mere transient instability detection or evaluation and it is most important to complement it by defining fast and efficient control measures in order to ensure system security. This paper presents a new Fuzzy Support Vector Machines (FSVM) to investigate the stability status of power systems and a modified generation rescheduling scheme to bring back the identified unstable cases to a more economical and stable operating point. FSVM improves the traditional SVM (Support Vector Machines) by adding fuzzy membership to each training sample to indicate the degree of membership of this sample to different classes. The preventive control based on economic generator rescheduling avoids the instability of the power systems with minimum change in operating cost under disturbed conditions. Numerical results on the New England 39 bus test system show the effectiveness of the proposed method.
Abstract: In the modern manufacturing systems, the use of
thermal cutting techniques using oxyfuel, plasma and laser have
become indispensable for the shape forming of high quality complex
components; however, the conventional chip removal production
techniques still have its widespread space in the manufacturing
industry. Both these types of machining operations require the
positioning of end effector tool at the edge where the cutting process
commences. This repositioning of the cutting tool in every machining
operation is repeated several times and is termed as non-productive
time or airtime motion. Minimization of this non-productive
machining time plays an important role in mass production with high
speed machining. As, the tool moves from one region to the other by
rapid movement and visits a meticulous region once in the whole
operation, hence the non-productive time can be minimized by
synchronizing the tool movements. In this work, this problem is
being formulated as a general travelling salesman problem (TSP) and
a genetic algorithm approach has been applied to solve the same. For
improving the efficiency of the algorithm, the GA has been
hybridized with a noble special heuristic and simulating annealing
(SA). In the present work a novel heuristic in the combination of GA
has been developed for synchronization of toolpath movements
during repositioning of the tool. A comparative analysis of new Meta
heuristic techniques with simple genetic algorithm has been
performed. The proposed metaheuristic approach shows better
performance than simple genetic algorithm for minimization of nonproductive
toolpath length. Also, the results obtained with the help of
hybrid simulated annealing genetic algorithm (HSAGA) are also
found better than the results using simple genetic algorithm only.
Abstract: Pharmacology curriculum plays an integral role in
medical education. Learning pharmacology to choose and prescribe
drugs is a major challenge encountered by students. We developed
pharmacology applied learning activities for first year medical
students that included realistic clinical situations with escalating
complications which required the students to analyze the situation
and think critically to choose a safe drug. Tutor feedback was
provided at the end of session. Evaluation was done to assess the
students- level of interest and usefulness of the sessions in rational
selection of drugs. Majority (98 %) of the students agreed that the
session was an extremely useful learning exercise and agreed that
similar sessions would help in rational selection of drugs. Applied
learning sessions in the early years of medical program may promote
deep learning and bridge the gap between pharmacology theory and
clinical practice. Besides, it may also enhance safe prescribing skills.
Abstract: Accurately predicting non-peak traffic is crucial to
daily traffic for all forecasting models. In the paper, least squares
support vector machines (LS-SVMs) are investigated to solve such a
practical problem. It is the first time to apply the approach and analyze
the forecast performance in the domain. For comparison purpose, two
parametric and two non-parametric techniques are selected because of
their effectiveness proved in past research. Having good
generalization ability and guaranteeing global minima, LS-SVMs
perform better than the others. Providing sufficient improvement in
stability and robustness reveals that the approach is practically
promising.
Abstract: Instead of traditional (nominal) classification we investigate
the subject of ordinal classification or ranking. An enhanced
method based on an ensemble of Support Vector Machines (SVM-s)
is proposed. Each binary classifier is trained with specific weights
for each object in the training data set. Experiments on benchmark
datasets and synthetic data indicate that the performance of our
approach is comparable to state of the art kernel methods for
ordinal regression. The ensemble method, which is straightforward
to implement, provides a very good sensitivity-specificity trade-off
for the highest and lowest rank.
Abstract: This paper presents Simulation and experimental
study aimed at investigating the effectiveness of an adaptive artificial
neural network stabilizer on enhancing the damping torque of a
synchronous generator. For this purpose, a power system comprising
a synchronous generator feeding a large power system through a
short tie line is considered. The proposed adaptive neuro-control
system consists of two multi-layered feed forward neural networks,
which work as a plant model identifier and a controller. It generates
supplementary control signals to be utilized by conventional
controllers. The details of the interfacing circuits, sensors and
transducers, which have been designed and built for use in tests, are
presented. The synchronous generator is tested to investigate the
effect of tuning a Power System Stabilizer (PSS) on its dynamic
stability. The obtained simulation and experimental results verify the
basic theoretical concepts.