Abstract: This paper presents general results on the Java source
code snippet detection problem. We propose the tool which uses
graph and subgraph isomorphism detection. A number of solutions
for all of these tasks have been proposed in the literature. However,
although that all these solutions are really fast, they compare just the
constant static trees. Our solution offers to enter an input sample
dynamically with the Scripthon language while preserving an
acceptable speed. We used several optimizations to achieve very low
number of comparisons during the matching algorithm.
Abstract: This paper deals with the issue of biomass and sorted
municipal waste gasification and cogeneration using hot-air turbo-set.
It brings description of designed pilot plant with electrical output 80
kWe. The generated gas is burned in secondary combustion chamber
located beyond the gas generator. Flue gas flows through the heat
exchanger where the compressed air is heated and consequently
brought to a micro turbine. Except description, this paper brings our
basic experiences from operating of pilot plant (operating parameters,
contributions, problems during operating, etc.). The principal
advantage of the given cycle is the fact that there is no contact
between the generated gas and the turbine. So there is no need for
costly and complicated gas cleaning which is the main source of
operating problems in direct use in combustion engines because the
content of impurities in the gas causes operation problems to the units
due to clogging and tarring of working surfaces of engines and
turbines, which may lead as far as serious damage to the equipment
under operation. Another merit is the compact container package
making installation of the facility easier or making it relatively more
mobile. We imagine, this solution of cogeneration from biomass or
waste can be suitable for small industrial or communal applications,
for low output cogeneration.
Abstract: The aim of this work is to present a theoretical analysis of a 2D ultrasound transducer comprised of crossed arrays of metal strips placed on both sides of thin piezoelectric layer (a). Such a structure is capable of electronic beam-steering of generated wavebeam both in elevation and azimuth. In this paper a semi-analytical model of the considered transducer is developed. It is based on generalization of the well-known BIS-expansion method. Specifically, applying the electrostatic approximation, the electric field components on the surface of the layer are expanded into fast converging series of double periodic spatial harmonics with corresponding amplitudes represented by the properly chosen Legendre polynomials. The problem is reduced to numerical solving of certain system of linear equations for unknown expansion coefficients.
Abstract: This paper presents a comparison of the reference
management software between Zotero and Mendeley and the results
were drawn by comparing the two software’s. The novelty of this
paper is the comparative analysis of the software and it has shown
that Mendeley can import more information from the Google Scholar
for the researchers. This finding can help to know researchers to use
the reference management software.
Abstract: A method which allows a diabetic quadriplegic patient
that has had four limb amputations (above the knee and elbow) to
self-administer injections of insulin has been designed. The aim of
this research project is to improve a quadriplegic patient’s selfmanagement,
affected by diabetes, by designing a suitable device for
self-administering insulin.
The quadriplegic patient affected by diabetes has to be able to selfadminister
insulin safely and independently to guarantee stable
healthy conditions. The device also should be designed to adapt to a
number of different varying personal characteristics such as height
and body weight.
Abstract: In this research work, neural networks were applied to
classify two types of hip joint implants based on the relative hip joint
implant side speed and three components of each ground reaction
force. The condition of walking gait at normal velocity was used and
carried out with each of the two hip joint implants assessed. Ground
reaction forces’ kinetic temporal changes were considered in the first
approach followed but discarded in the second one. Ground reaction
force components were obtained from eighteen patients under such
gait condition, half of which had a hip implant type I-II, whilst the
other half had the hip implant, defined as type III by Orthoload®.
After pre-processing raw gait kinetic data and selecting the time
frames needed for the analysis, the ground reaction force components
were used to train a MLP neural network, which learnt to distinguish
the two hip joint implants in the abovementioned condition. Further
to training, unknown hip implant side and ground reaction force
components were presented to the neural networks, which assigned
those features into the right class with a reasonably high accuracy for
the hip implant type I-II and the type III. The results suggest that
neural networks could be successfully applied in the performance
assessment of hip joint implants.
Abstract: Over the past era, there have been a lot of efforts and
studies are carried out in growing proficient tools for performing
various tasks in big data. Recently big data have gotten a lot of
publicity for their good reasons. Due to the large and complex
collection of datasets it is difficult to process on traditional data
processing applications. This concern turns to be further mandatory
for producing various tools in big data. Moreover, the main aim of
big data analytics is to utilize the advanced analytic techniques
besides very huge, different datasets which contain diverse sizes from
terabytes to zettabytes and diverse types such as structured or
unstructured and batch or streaming. Big data is useful for data sets
where their size or type is away from the capability of traditional
relational databases for capturing, managing and processing the data
with low-latency. Thus the out coming challenges tend to the
occurrence of powerful big data tools. In this survey, a various
collection of big data tools are illustrated and also compared with the
salient features.
Abstract: In this study, a three dimensional numerical heat
transfer model has been used to simulate the laser structuring of
polymer substrate material in the Three-Dimensional Molded
Interconnect Device (3D MID) which is used in the advanced multifunctional
applications. A finite element method (FEM) transient
thermal analysis is performed using APDL (ANSYS Parametric
Design Language) provided by ANSYS. In this model, the effect of
surface heat source was modeled with Gaussian distribution, also the
effect of the mixed boundary conditions which consist of convection
and radiation heat transfers have been considered in this analysis. The
model provides a full description of the temperature distribution, as
well as calculates the depth and the width of the groove upon material
removal at different set of laser parameters such as laser power and
laser speed. This study also includes the experimental procedure to
study the effect of laser parameters on the depth and width of the
removal groove metal as verification to the modeled results. Good
agreement between the experimental and the model results is
achieved for a wide range of laser powers. It is found that the quality
of the laser structure process is affected by the laser scan speed and
laser power. For a high laser structured quality, it is suggested to use
laser with high speed and moderate to high laser power.
Abstract: With demand for primary energy continuously
growing, search for renewable and efficient energy sources has been
high on agenda of our society. One of the most promising energy
sources is biogas technology. Residues coming from dairy industry
and milk processing could be used in biogas production; however,
low efficiency and high cost impede wide application of such
technology. One of the main problems is management and conversion
of organic residues through the anaerobic digestion process which is
characterized by acidic environment due to the low whey pH (
Abstract: The measured data obtained from sensors in
continuous monitoring of civil structures are mainly used for modal
identification and damage detection. Therefore, when modal
identification analysis is carried out the quality in the identification of
the modes will highly influence the damage detection results. It is
also widely recognized that the usefulness of the measured data used
for modal identification and damage detection is significantly
influenced by the number and locations of sensors. The objective of
this study is the numerical implementation of two widely known
optimum sensor placement methods in beam-like structures.
Abstract: In order to investigate the effect of Plant Growth
Promoting Rhizobacteria (PGPR) and rhizobium bacteria on grain
yield and some agronomic traits of mungbean (Vigna radiate L.), an
experiment was carried out based on randomized complete block
design with three replications in Malekshahi, Ilam province, Iran
during 2012-2013 cropping season. Experimental treatments
consisted of control treatment, inoculation with rhizobium bacteria,
rhizobium bacteria and Azotobacter, rhizobium bacteria and
Azospirillum, rhizobium bacteria and Pseudomonas, rhizobium
bacteria, Azotobacter and Azospirillum, rhizobium bacteria,
Azotobacter and Pseudomonas, rhizobium bacteria, Azospirillum and
Pseudomonas and rhizobium bacteria, Azotobacter, Azospirillum and
Pseudomonas. The results showed that the effect of PGPR and
rhizobium bacteria were significant affect on grain and its
components in mungbean plant. Grain yield significantly increased
by PGPR and rhizobium bacteria, so that the maximum grain yield
was obtained from rhizobium bacteria + Azospirillum +
Pseudomonas with the amount of 2287 kg.ha-1 as compared to
control treatment. Excessive application of chemical fertilizers causes
environmental and economic problems. That is, the overfertilization
of P and N leads to pollution due to soil erosion and runoff water, so
the use of PGPR and rhizobium bacteria can be justified due to
reduce input costs, increase in grain yield and environmental friendly.
Abstract: This paper aims at introducing finite automata theory,
the different ways to describe regular languages and create a program
to implement the subset construction algorithms to convert
nondeterministic finite automata (NFA) to deterministic finite
automata (DFA). This program is written in c++ programming
language. The program reads FA 5tuples from text file and then
classifies it into either DFA or NFA. For DFA, the program will read
the string w and decide whether it is acceptable or not. If accepted, the
program will save the tracking path and point it out. On the other hand,
when the automation is NFA, the program will change the Automation
to DFA so that it is easy to track and it can decide whether the w exists
in the regular language or not.
Abstract: In this paper, we propose a multi-agent intelligent
system that is used for monitoring the health conditions of elderly
people. Monitoring the health condition of elderly people is a
complex problem that involves different medical units and requires
continuous monitoring. Such expert system is highly needed in rural
areas because of inadequate number of available specialized
physicians or nurses. Such monitoring must have autonomous
interactions between these medical units in order to be effective. A
multi-agent system is formed by a community of agents that
exchange information and proactively help one another to achieve the
goal of elderly monitoring. The agents in the developed system are
equipped with intelligent decision maker that arms them with the
rule-based reasoning capability that can assist the physicians in
making decisions regarding the medical condition of elderly people.
Abstract: This paper aims at finding a suitable neural network
for monitoring congestion level in electrical power systems. In this
paper, the input data has been framed properly to meet the target
objective through supervised learning mechanism by defining normal
and abnormal operating conditions for the system under study. The
congestion level, expressed as line congestion index (LCI), is
evaluated for each operating condition and is presented to the NN
along with the bus voltages to represent the input and target data.
Once, the training goes successful, the NN learns how to deal with a
set of newly presented data through validation and testing
mechanism. The crux of the results presented in this paper rests on
performance comparison of a multi-layered feed forward neural
network with eleven types of back propagation techniques so as to
evolve the best training criteria. The proposed methodology has been
tested on the standard IEEE-14 bus test system with the support of
MATLAB based NN toolbox. The results presented in this paper
signify that the Levenberg-Marquardt backpropagation algorithm
gives best training performance of all the eleven cases considered in
this paper, thus validating the proposed methodology.
Abstract: The system is designed to show images which are
related to the query image. Extracting color, texture, and shape
features from an image plays a vital role in content-based image
retrieval (CBIR). Initially RGB image is converted into HSV color
space due to its perceptual uniformity. From the HSV image, Color
features are extracted using block color histogram, texture features
using Haar transform and shape feature using Fuzzy C-means
Algorithm. Then, the characteristics of the global and local color
histogram, texture features through co-occurrence matrix and Haar
wavelet transform and shape are compared and analyzed for CBIR.
Finally, the best method of each feature is fused during similarity
measure to improve image retrieval effectiveness and accuracy.
Abstract: In healthy humans, the cortical brain rhythm shows
specific mu (~6-14 Hz) and beta (~18-24 Hz) band patterns in the
cases of both real and imaginary motor movements. As cerebellar
ataxia is associated with impairment of precise motor movement
control as well as motor imagery, ataxia is an ideal model system in
which to study the role of the cerebellocortical circuit in rhythm
control. We hypothesize that the EEG characteristics of ataxic patients
differ from those of controls during the performance of a
Brain-Computer Interface (BCI) task. Ataxia and control subjects
showed a similar distribution of mu power during cued relaxation.
During cued motor imagery, however, the ataxia group showed
significant spatial distribution of the response, while the control group
showed the expected decrease in mu-band power (localized to the
motor cortex).
Abstract: Currently, biological control programs in greenhouse
crops involve the use, at the same time, several natural enemies
during the crop cycle. Also, large number of plant species grown in
greenhouses, among them, the used cultivars are also wide. However,
the cultivar effects on entomophagous species efficacy (predators and
parasitoids) have been scarcely studied. A new method had been
developed, using the factitious prey or host Ephestia kuehniella. It
allow us to evaluate, under greenhouse or controlled conditions
(semi-field), the cultivar effects on the entomophagous species
effectiveness. The work was carried out in greenhouse tomato crop. It
has been found the biological and ecological activities of predatory
species (Nesidiocoris tenuis) and egg-parasitoid (Trichogramma
achaeae) can be well represented with the use of the factitious prey
or host; being better in the former than the latter. The data found in
the trial are shown and discussed. The developed method could be
applied to evaluate new plant materials before making available to
farmers as commercial varieties, at low costs and easy use.
Abstract: Composite materials have important assets compared
to traditional materials. They bring many functional advantages:
lightness, mechanical resistance and chemical, etc. In the present
study we examine the effect of a circular central notch and a precrack
on the tensile fracture of two woven composite materials. The tensile
tests were applied to a standardized specimen, notched and a
precarcked (orientation of the crack 0°, 45° and 90°). These tensile
tests were elaborated according to an experimental planning design of
the type 23.31 requiring 24 experiments with three repetitions. By the
analysis of regression, we obtained a mathematical model describing
the maximum load according to the influential parameters (hole
diameter, precrack length, angle of a precrack orientation). The
specimens precracked at 90° have a better behavior than those having
a precrack at 45° and still better than those having of the precracks
oriented at 0°. In addition the maximum load is inversely
proportional to the notch size.
Abstract: This research proposes a novel reconstruction protocol
for restoring missing surfaces and low-quality edges and shapes in
photos of artifacts at historical sites. The protocol starts with the
extraction of a cloud of points. This extraction process is based on
four subordinate algorithms, which differ in the robustness and
amount of resultant. Moreover, they use different -but
complementary- accuracy to some related features and to the way
they build a quality mesh. The performance of our proposed protocol
is compared with other state-of-the-art algorithms and toolkits. The
statistical analysis shows that our algorithm significantly outperforms
its rivals in the resultant quality of its object files used to reconstruct
the desired model.
Abstract: In this study, a comparative analysis of the approaches
associated with the use of neural network algorithms for effective
solution of a complex inverse problem – the problem of identifying
and determining the individual concentrations of inorganic salts in
multicomponent aqueous solutions by the spectra of Raman
scattering of light – is performed. It is shown that application of
artificial neural networks provides the average accuracy of
determination of concentration of each salt no worse than 0.025 M.
The results of comparative analysis of input data compression
methods are presented. It is demonstrated that use of uniform
aggregation of input features allows decreasing the error of
determination of individual concentrations of components by 16-18%
on the average.