Abstract: An ordered porous antimony-doped tin oxide (ATO) film was successfully prepared using a simple coating process with colloidal templates. The facile production was effective when a combination of 16-nm ATO (as a model of an inorganic nanoparticle) and polystyrene (PS) spheres (as a model of the template) weresimply coated to produce a composite ATO/PS film. Heat treatment was then used to remove the PS and produce the porous film. The porous film with a spherical pore shape and a highly ordered porous structure could be obtained. A potential way for the control of pore size could be also achieved by changing initial template size. The theoretical explanation and mechanism of porous formation were also added, which would be important for the scaling-up prediction and estimation.
Abstract: Nowadays there are many methods for representing
knowledge such as semantic network, neural network, and conceptual
graphs. Nonetheless, these methods are not sufficiently efficient
when applied to perform and deduce on knowledge domains about
supporting in general education such as algebra, analysis or plane
geometry. This leads to the introduction of computational network
which is a useful tool for representation knowledge base, especially
for computational knowledge, especially knowledge domain about
general education. However, when dealing with a practical problem,
we often do not immediately find a new solution, but we search
related problems which have been solved before and then proposing
an appropriate solution for the problem. Besides that, when finding
related problems, we have to determine whether the result of them
can be used to solve the practical problem or not. In this paper, the
extension model of computational network has been presented. In this
model, Sample Problems, which are related problems, will be used
like the experience of human about practical problem, simulate the
way of human thinking, and give the good solution for the practical
problem faster and more effectively. This extension model is applied
to construct an automatic system for solving algebraic problems in
middle school.
Abstract: All climate models agree that the temperature in
Greece will increase in the range of 1° to 2°C by the year 2030 and
mean sea level in Mediterranean is expected to rise at the rate of 5
cm/decade. The aim of the present paper is the estimation of the
coastline displacement driven by the climate change and sea level
rise. In order to achieve that, all known statistical and non-statistical
computational methods are employed on some Greek coastal areas.
Furthermore, Kalman filtering techniques are for the first time
introduced, formulated and tested. Based on all the above, shoreline
change signals and noises are computed and an inter-comparison
between the different methods can be deduced to help evaluating
which method is most promising as far as the retrieve of shoreline
change rate is concerned.
Abstract: Principally, plants grown in soilless culture may be
attacked by the same pests and diseases as cultivated traditionally in
soil. The most destructive phytopathogens are fungi, such as
Phythium, Phytophthora and Fusarium, followed by viruses, bacteria
and nematodes. We investigated effect of carbon nanotube filters on
disease management of soilless culture. Tomato seedlings transplant
in plastic pots filled with a soilless media of vermiculite. The crop
irrigated and fertilized using a hydroponic nutrient solution. We used
carbon nanotube filters for nutrient solution disinfection. Our results
show that carbon nanotube filtration significantly reduces pathogens
on tomato plants. Fungal elimination (Fusarium oxysporum and
Pythium spp.) was usually successful at about 96 to 99.9% all over
the cultural season. It is seem that in tomato soilless culture,
nanofiltration constitutes a reliable method that allows control of the
development of diseases caused by pathogenic fungi
Abstract: Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.
Abstract: A multi-rate discrete-time model, whose response
agrees exactly with that of a continuous-time original at all sampling
instants for any sampling periods, is developed for a linear system,
which is assumed to have multiple real eigenvalues. The sampling
rates can be chosen arbitrarily and individually, so that their ratios
can even be irrational. The state space model is obtained as a
combination of a linear diagonal state equation and a nonlinear output
equation. Unlike the usual lifted model, the order of the proposed
model is the same as the number of sampling rates, which is less than
or equal to the order of the original continuous-time system. The
method is based on a nonlinear variable transformation, which can be
considered as a generalization of linear similarity transformation,
which cannot be applied to systems with multiple eigenvalues in
general. An example and its simulation result show that the proposed
multi-rate model gives exact responses at all sampling instants.
Abstract: The winding hot-spot temperature is one of the most
critical parameters that affect the useful life of the power
transformers. The winding hot-spot temperature can be calculated as
function of the top-oil temperature that can estimated by using the
ambient temperature and transformer loading measured data. This
paper proposes the estimation of the top-oil temperature by using a
method based on Least Squares Support Vector Machines approach.
The estimated top-oil temperature is compared with measured data of
a power transformer in operation. The results are also compared with
methods based on the IEEE Standard C57.91-1995/2000 and
Artificial Neural Networks. It is shown that the Least Squares
Support Vector Machines approach presents better performance than
the methods based in the IEEE Standard C57.91-1995/2000 and
artificial neural networks.
Abstract: Time interleaved sigma-delta (TIΣΔ) architecture is a
potential candidate for high bandwidth analog to digital converters
(ADC) which remains a bottleneck for software and cognitive radio
receivers. However, the performance of the TIΣΔ architecture is
limited by the unavoidable gain and offset mismatches resulting
from the manufacturing process. This paper presents a novel digital
calibration method to compensate the gain and offset mismatch
effect. The proposed method takes advantage of the reconstruction
digital signal processing on each channel and requires only few logic
components for implementation. The run time calibration is estimated
to 10 and 15 clock cycles for offset cancellation and gain mismatch
calibration respectively.
Abstract: In this paper, the innovative intelligent fuzzy weighted
input estimation method (FWIEM) can be applied to the inverse heat
transfer conduction problem (IHCP) to estimate the unknown
time-varying heat flux efficiently as presented. The feasibility of this
method can be verified by adopting the temperature measurement
experiment. We would like to focus attention on the heat flux
estimation to three kinds of samples (Copper, Iron and Steel/AISI 304)
with the same 3mm thickness. The temperature measurements are then
regarded as the inputs into the FWIEM to estimate the heat flux. The
experiment results show that the proposed algorithm can estimate the
unknown time-varying heat flux on-line.
Abstract: Organizational communication is an administrative
function crucial especially for executives in the implementation of
organizational and administrative functions. Executives spend a
significant part of their time on communicative activities. Doing his or her daily routine, arranging meeting schedules, speaking on the telephone, reading or replying to business correspondence, or
fulfilling the control functions within the organization, an executive typically engages in communication processes.
Efficient communication is the principal device for the adequate implementation of administrative and organizational activities. For
this purpose, management needs to specify the kind of
communication system to be set up and the kind of communication
devices to be used. Communication is vital for any organization.
In conventional offices, communication takes place within the hierarchical pyramid called the organizational structure, and is known as formal or informal communication. Formal communication
is the type that works in specified structures within the organizational rules and towards the organizational goals. Informal communication, on the other hand, is the unofficial type taking place among staff as
face-to-face or telephone interaction.
Communication in virtual as well as conventional offices is
essential for obtaining the right information in administrative
activities and decision-making. Virtual communication technologies
increase the efficiency of communication especially in virtual teams.
Group communication is strengthened through an inter-group central
channel. Further, ease of information transmission makes it possible
to reach the information at the source, allowing efficient and correct decisions. Virtual offices can present as a whole the elements of information which conventional offices produce in different
environments.
At present, virtual work has become a reality with its pros and
cons, and will probably spread very rapidly in coming years, in line
with the growth in information technologies.
Abstract: Performance of any continuous speech recognition system is highly dependent on performance of the acoustic models. Generally, development of the robust spoken language technology relies on the availability of large amounts of data. Common way to cope with little data for training each state of Markov models is treebased state tying. This tying method applies contextual questions to tie states. Manual procedure for question generation suffers from human errors and is time consuming. Various automatically generated questions are used to construct decision tree. There are three approaches to generate questions to construct HMMs based on decision tree. One approach is based on misrecognized phonemes, another approach basically uses feature table and the other is based on state distributions corresponding to context-independent subword units. In this paper, all these methods of automatic question generation are applied to the decision tree on FARSDAT corpus in Persian language and their results are compared with those of manually generated questions. The results show that automatically generated questions yield much better results and can replace manually generated questions in Persian language.
Abstract: In this paper, we study the formation control problem
for car-like mobile robots. A team of nonholonomic mobile robots navigate in a terrain with obstacles, while maintaining a desired
formation, using a leader-following strategy. A set of artificial potential field functions is proposed using the direct Lyapunov
method for the avoidance of obstacles and attraction to their designated targets. The effectiveness of the proposed control laws to verify the feasibility of the model is demonstrated through computer simulations
Abstract: Improving the reactive power and voltage profile of a
distribution substation is investigated in this paper. The purpose is to
properly determination of the shunt capacitors on/off status and
suitable tap changer (TC) position of a substation transformer. In
addition, the limitation of secondary bus voltage, the maximum
allowable number of switching operation in a day for on load tap
changer and on/off status of capacitors are taken into account. To
achieve these goals, an artificial neural network (ANN) is designed to
provide preliminary scheduling. Input of ANN is active and reactive
powers of transformer and its primary and secondary bus voltages.
The output of ANN is capacitors on/off status and TC position. The
preliminary schedule is further refined by fuzzy dynamic
programming in order to reach the final schedule. The operation of
proposed method in Q/V improving is compared with the results
obtained by operator operation in a distribution substation.
Abstract: Lattice Monte Carlo methods are an excellent
choice for the simulation of non-linear thermal diffusion
problems. In this paper, and for the first time, Lattice Monte
Carlo analysis is performed on thermal diffusion combined
with convective heat transfer. Laminar flow of water modeled
as an incompressible fluid inside a copper pipe with a constant
surface temperature is considered. For the simulation of
thermal conduction, the temperature dependence of the
thermal conductivity of the water is accounted for. Using the
novel Lattice Monte Carlo approach, temperature distributions
and energy fluxes are obtained.
Abstract: The paper presents a new hybridization methodology involving Neural, Fuzzy and Rough Computing. A Rough Sets based approximation technique has been proposed based on a certain Neuro – Fuzzy architecture. A New Rough Neuron composition consisting of a combination of a Lower Bound neuron and a Boundary neuron has also been described. The conventional convergence of error in back propagation has been given away for a new framework based on 'Output Excitation Factor' and an inverse input transfer function. The paper also presents a brief comparison of performances, of the existing Rough Neural Networks and ANFIS architecture against the proposed methodology. It can be observed that the rough approximation based neuro-fuzzy architecture is superior to its counterparts.
Abstract: In this paper, four carbazole-based D-D-π-A organic
dyes code as CCT2A, CCT3A, CCT1PA and CCT2PA were reported.
A series of these organic dyes containing identical donor and
acceptor group but different π-system. The effect of replacing of
thiophene by phenyl thiophene as π-system on the physical
properties has been focused. The structural, energetic properties and
absorption spectra were theoretically investigated by means of
Density Functional Theory (DFT) and Time-Dependent Density
Functional Theory (TD-DFT). The results show that nonplanar
conformation due to steric hindrance in donor part (cabazolecarbazole
unit) of dye molecule can prevent unfavorable dye
aggregation. By means of the TD-DFT method, the absorption
spectra were calculated by B3LYP and BHandHLYP to study the
affect of hybrid functional on the excitation energy (Eg). The results
revealed the increasing of thiophene units not only resulted in
decreasing of Eg, but also found the shifting of absorption spectra to
higher wavelength. TD-DFT/BHandHLYP calculated results are
more strongly agreed with the experimental data than B3LYP
functions. Furthermore, the adsorptions of CCT2A and CCT3A on the
TiO2 anatase (101) surface were carried out by mean of the chemical
periodic calculation. The result exhibit the strong adsorption energy.
The calculated results provide our new organic dyes can be
effectively used as dye for Dye Sensitized Solar Cell (DSC).
Abstract: A simple but effective digital watermarking scheme
utilizing a context adaptive variable length coding (CAVLC) method
is presented for wireless communication system. In the proposed
approach, the watermark bits are embedded in the final non-zero
quantized coefficient of each DCT block, thereby yielding a potential
reduction in the length of the coded block. As a result, the
watermarking scheme not only provides the means to check the
authenticity and integrity of the video stream, but also improves the
compression ratio and therefore reduces both the transmission time
and the storage space requirements of the coded video sequence. The
results confirm that the proposed scheme enables the detection of
malicious tampering attacks and reduces the size of the coded H.264
file. Therefore, the current study is feasible to apply in the video
applications of wireless communication such as 3G system
Abstract: In this paper, we intend to study the synthesis of the
multibeam arrays. The synthesis implementation-s method for this
type of arrays permits to approach the appropriated radiance-s
diagram. The used approach is based on neural network that are
capable to model the multibeam arrays, consider predetermined
general criteria-s, and finally it permits to predict the appropriated
diagram from the neural model. Our main contribution in this paper is
the extension of a synthesis model of these multibeam arrays.
Abstract: Silver/polylactide nanocomposites (Ag/PLA-NCs) were
synthesized via chemical reduction method in diphase solvent. Silver
nitrate and sodium borohydride were used as a silver precursor
and reducing agent in the polylactide (PLA). The properties of
Ag/PLA-NCs were studied as a function of the weight percentages
of silver nanoparticles (8, 16 and 32 wt% of Ag-NPs) relative to
the weight of PLA. The Ag/PLA-NCs were characterized by Xray
diffraction (XRD), transmission electron microscopy (TEM),
electro-optical microscopy (EOM), UV-visible spectroscopy (UV-vis)
and Fourier transform infrared spectroscopy (FT-IR). XRD patterns
confirmed that Ag-NPs crystallographic planes were face centered
cubic (fcc) type. TEM images showed that mean diameters of Ag-NPs
were 3.30, 3.80 and 4.80 nm. Electro-optical microscopy revealed
excellent dispersion and interaction between Ag-NPs and PLA films.
The generation of silver nanoparticles was confirmed from the UVvisible
spectra. FT-IR spectra showed that there were no significant
differences between PLA and Ag/PLA-NCs films. The synthesized
Ag/PLA-NCs were stable in organic solution over a long period of
time without sign of precipitation.
Abstract: Activity-Based Costing (ABC) which has become an important aspect of manufacturing/service organizations can be defined as a methodology that measures the cost and performance of activities, resources and cost objects. It can be considered as an alternative paradigm to traditional cost-based accounting systems. The objective of this paper is to illustrate an application of ABC method and to compare the results of ABC with traditional costing methods. The results of the application highlight the weak points of traditional costing methods and an S-Curve obtained is used to identify the undercosted and overcosted products of the firm.