Abstract: Cosmic showers, from their places of origin in space,
after entering earth generate secondary particles called Extensive Air
Shower (EAS). Detection and analysis of EAS and similar High
Energy Particle Showers involve a plethora of experimental setups
with certain constraints for which soft-computational tools like
Artificial Neural Network (ANN)s can be adopted. The optimality
of ANN classifiers can be enhanced further by the use of Multiple
Classifier System (MCS) and certain data - dimension reduction
techniques. This work describes the performance of certain data
dimension reduction techniques like Principal Component Analysis
(PCA), Independent Component Analysis (ICA) and Self Organizing
Map (SOM) approximators for application with an MCS formed
using Multi Layer Perceptron (MLP), Recurrent Neural Network
(RNN) and Probabilistic Neural Network (PNN). The data inputs are
obtained from an array of detectors placed in a circular arrangement
resembling a practical detector grid which have a higher dimension
and greater correlation among themselves. The PCA, ICA and SOM
blocks reduce the correlation and generate a form suitable for real
time practical applications for prediction of primary energy and
location of EAS from density values captured using detectors in a
circular grid.
Abstract: Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.
Abstract: Discrimination between different classes of environmental
sounds is the goal of our work. The use of a sound recognition
system can offer concrete potentialities for surveillance and
security applications. The first paper contribution to this research
field is represented by a thorough investigation of the applicability
of state-of-the-art audio features in the domain of environmental
sound recognition. Additionally, a set of novel features obtained by
combining the basic parameters is introduced. The quality of the
features investigated is evaluated by a HMM-based classifier to which
a great interest was done. In fact, we propose to use a Multi-Style
training system based on HMMs: one recognizer is trained on a
database including different levels of background noises and is used
as a universal recognizer for every environment. In order to enhance
the system robustness by reducing the environmental variability, we
explore different adaptation algorithms including Maximum Likelihood
Linear Regression (MLLR), Maximum A Posteriori (MAP)
and the MAP/MLLR algorithm that combines MAP and MLLR.
Experimental evaluation shows that a rather good recognition rate
can be reached, even under important noise degradation conditions
when the system is fed by the convenient set of features.
Abstract: This paper presents a study on the thermodynamics
and transport properties of hot potassium carbonate aqueous system
(HPC) using electrolyte non-random two liquid, (ELECNRTL)
model. The operation conditions are varied to determine the system
liquid phase stability range at the standard and critical conditions. A
case study involving 30 wt% K2CO3, H2O standard system at
pressure of 1 bar and temperature range from 280.15 to 366.15 K has
been studied. The estimated solubility index, viscosity, water
activity, and density which obtained from the simulation showed a
good agreement with the experimental work. Furthermore, the
saturation temperature of the solution has been estimated.
Abstract: This paper presents the doping profile measurement
and characterization technique for the pocket implanted nano scale
n-MOSFET. Scanning capacitance microscopy and atomic force
microscopy have been used to image the extent of lateral dopant
diffusion in MOS structures. The data are capacitance vs. voltage
measurements made on a nano scale device. The technique is nondestructive
when imaging uncleaved samples. Experimental data from
the published literature are presented here on actual, cleaved device
structures which clearly indicate the two-dimensional dopant profile
in terms of a spatially varying modulated capacitance signal. Firstorder
deconvolution indicates the technique has much promise for
the quantitative characterization of lateral dopant profiles. The pocket
profile is modeled assuming the linear pocket profiles at the source
and drain edges. From the model, the effective doping concentration
is found to use in modeling and simulation results of the various
parameters of the pocket implanted nano scale n-MOSFET. The
potential of the technique to characterize important device related
phenomena on a local scale is also discussed.
Abstract: This paper presents an experimental investigation on
the machinability of laser-sintered material using small ball end mill focusing on wear mechanisms. Laser-sintered material was produced
by irradiating a laser beam on a layer of loose fine SCM-Ni-Cu powder. Bulk carbon steel JIS S55C was selected as a reference steel.
The effects of powder consolidation mechanisms and unsintered
powder on the tool life and wear mechanisms were carried out. Results indicated that tool life in cutting laser-sintered material is
lower than that in cutting JIS S55C. Adhesion of the work material and chipping were the main wear mechanisms of the ball end mill in
cutting laser-sintered material. Cutting with the unsintered powder
surrounding the tool and laser-sintered material had caused major fracture on the cutting edge.
Abstract: In the upstream we place a piece of ring and rotate
it with 83Hz, 166Hz, 333Hz,and 666H to find the effect of the
periodic distortion.In the experiment this type of the perturbation
will not allow since the mechanical failure of any parts of the
equipment in the upstream will destroy the blade system. This type of
study will be only possible by CFD. We use two pumps NS32
(ENSAM) and three blades pump (Tamagawa Univ). The benchmark
computations were performed without perturbation parts, and confirm
the computational results well agreement in head-flow rate. We
obtained the pressure fluctuation growth rate that is representing the
global instability of the turbo-system. The fluctuating torque
components were 0.01Nm(5000rpm), 0.1Nm(10000rmp),
0.04Nm(20000rmp), 0.15Nm( 40000rmp) respectively. Only for
10000rpm(166Hz) the output toque was random, and it implies that it
creates unsteady flow by separations on the blades, and will reduce the
pressure loss significantly
Abstract: Reinforced concrete crash barriers used in road traffic
must meet a number of criteria. Crash barriers are laid lengthwise,
one behind another, and joined using specially designed steel locks.
While developing BSV reinforced concrete crash barriers (type
ŽPSV), experiments and calculations aimed to optimize the shape of
a newly designed lock and the reinforcement quantity and
distribution in a crash barrier were carried out. The tension carrying
capacity of two parallelly joined locks was solved experimentally.
Based on the performed experiments, adjustments of nonlinear
properties of steel were performed in the calculations. The obtained
results served as a basis to optimize the lock design using a
computational model that takes into account the plastic behaviour of
steel and the influence of the surrounding concrete [6]. The response
to the vehicle impact has been analyzed using a specially elaborated
complex computational model, comprising both the nonlinear model
of the damping wall or crash barrier and the detailed model of the
vehicle [7].
Abstract: Color image segmentation can be considered as a
cluster procedure in feature space. k-means and its adaptive
version, i.e. competitive learning approach are powerful tools
for data clustering. But k-means and competitive learning suffer
from several drawbacks such as dead-unit problem and need to
pre-specify number of cluster. In this paper, we will explore to
use competitive and cooperative learning approach to perform
color image segmentation. In competitive and cooperative
learning approach, seed points not only compete each other, but
also the winner will dynamically select several nearest
competitors to form a cooperative team to adapt to the input
together, finally it can automatically select the correct number
of cluster and avoid the dead-units problem. Experimental
results show that CCL can obtain better segmentation result.
Abstract: The Maximum Weighted Independent Set (MWIS)
problem is a classic graph optimization NP-hard problem. Given an
undirected graph G = (V, E) and weighting function defined on the
vertex set, the MWIS problem is to find a vertex set S V whose total
weight is maximum subject to no two vertices in S are adjacent. This
paper presents a novel approach to approximate the MWIS of a graph
using minimum weighted vertex cover of the graph. Computational
experiments are designed and conducted to study the performance
of our proposed algorithm. Extensive simulation results show that
the proposed algorithm can yield better solutions than other existing
algorithms found in the literature for solving the MWIS.
Abstract: The present study attempted to improve the Mercury
(Hg) sorption capacity of kanuma volcanic ash soil (KVAS) by
impregnating the cupper (Cu). Impregnation was executed by 1 and
5% Cu powder and sorption characterization of optimum Hg
removing Cu impregnated KVAS was performed under different
operational conditions, contact time, solution pH, sorbent dosage and
Hg concentration using the batch operation studies. The 1% Cu
impregnated KVAS pronounced optimum improvement (79%) in
removing Hg from water compare to control. The present
investigation determined the equilibrium state of maximum Hg
adsorption at 6 h contact period. The adsorption revealed a pH
dependent response and pH 3.5 showed maximum sorption capacity
of Hg. Freundlich isotherm model is well fitted with the experimental
data than that of Langmuir isotherm. It can be concluded that the Cu
impregnation improves the Hg sorption capacity of KVAS and 1%
Cu impregnated KVAS could be employed as cost-effective
adsorbent media for treating Hg contaminated water.
Abstract: This paper deals with the problem of thermal and
mechanical shocks, which rising during operation, mostly at
interrupted cut. Here will be solved their impact on the cutting edge
tool life, the impact of coating technology on resistance to shocks
and experimental determination of tool life in heating flame.
Resistance of removable cutting edges against thermal and
mechanical shock is an important indicator of quality as well as its
abrasion resistance. Breach of the edge or its crumble may occur due
to cyclic loading. We can observe it not only during the interrupted
cutting (milling, turning areas abandoned hole or slot), but also in
continuous cutting. This is due to the volatility of cutting force on
cutting. Frequency of the volatility in this case depends on the type
of rising chips (chip size element). For difficult-to-machine materials
such as austenitic steel particularly happened at higher cutting speeds
for the localization of plastic deformation in the shear plane and for
the inception of separate elements substantially continuous chips.
This leads to variations of cutting forces substantially greater than for
other types of steel.
Abstract: This paper presents a new approach for the prob-ability density function estimation using the Support Vector Ma-chines (SVM) and the Expectation Maximization (EM) algorithms.In the proposed approach, an advanced algorithm for the SVM den-sity estimation which incorporates the Mean Field theory in the learning process is used. Instead of using ad-hoc values for the para-meters of the kernel function which is used by the SVM algorithm,the proposed approach uses the EM algorithm for an automatic optimization of the kernel. Experimental evaluation using simulated data set shows encouraging results.
Abstract: Offset Double-Disk Opener (DDO) is a popular
furrow opener in conservation tillage. It has some limitations such as
negative suction to penetrate in the soil, hair pinning and mixing seed
and fertilizer in the slot. Because of importance of separation of seed
and fertilizer in the slot, by adding two horizontal mini disks to DDO
a modified opener was made (MDO) which placed the fertilizer
between and under two rows of seed. To consider performance of
novel opener an indoor comparison test between DDO and MDO was
performed at soil bin. The experiment was conducted with three
working speeds (3, 6 and 8 km h-1), two bulk densities of soil (1.1
and 1.4 Mg m-3) and two levels of residues (1 and 2 ton ha-1). The
experimental design consisted in a (3×2×2) complete randomized
factorial with three replicates for each test. Moisture of seed furrow,
separation of seed and fertilizer, hair pinning and resultant forces
acting on the openers were used as assessing indexes. There was no
significant difference between soil moisture content in slots created
by DDO and MDO at 0-4 cm depth, but at 4-8 cm the in the slot
created by MDO moisture content was higher about 9%. Horizontal
force for both openers increased with increasing speed and soil bulk
density. Vertical force for DDO was negative so it needed additional
weight for penetrating in the soil, but vertical force for MDO was
positive and, which can solve the challenge of penetration in the soil
in DDO. In soft soil with heavy residues some trash was pushed by
DDO into seed furrow (hair pinning) but at MDO seed were placed at
clean groove. Lateral and vertical separation of seed and fertilizer
was performed effectively by MDO (4.5 and 5 cm, respectively)
while DDO put seed and fertilizer close to each other. Overall, the
Modified Offset Double-disks (MDO) had better performance. So by
adapting this opener with no-tillage drillers it would possible to have
higher yield in conservation tillage where the most appropriate
opener is disk type.
Abstract: The fractal-shaped orifices are assumed to have a
significant effect on the pressure drop downstream pipe flow due to
their edge self-similarity shape which enhances the mixing
properties. Here, we investigate the pressure drop after these fractals
using a digital micro-manometer at different stations downstream a
turbulent flow pipe then a direct comparison has been made with the
pressure drop measured from regular orifices with the same flow
area. Our results showed that the fractal-shaped orifices have a
significant effect on the pressure drop downstream the flow. Also
the pressure drop measured across the fractal-shaped orifices is
noticed to be lower that that from ordinary orifices of the same flow
areas. This result could be important in designing piping systems
from point of view of losses consideration with the same flow
control area. This is promising to use the fractal-shaped orifices as
flowmeters as they can sense the pressure drop across them
accurately with minimum losses than the regular ones.
Abstract: This paper explores the scalability issues associated
with solving the Named Entity Recognition (NER) problem using
Support Vector Machines (SVM) and high-dimensional features. The
performance results of a set of experiments conducted using binary
and multi-class SVM with increasing training data sizes are
examined. The NER domain chosen for these experiments is the
biomedical publications domain, especially selected due to its
importance and inherent challenges. A simple machine learning
approach is used that eliminates prior language knowledge such as
part-of-speech or noun phrase tagging thereby allowing for its
applicability across languages. No domain-specific knowledge is
included. The accuracy measures achieved are comparable to those
obtained using more complex approaches, which constitutes a
motivation to investigate ways to improve the scalability of multiclass
SVM in order to make the solution more practical and useable.
Improving training time of multi-class SVM would make support
vector machines a more viable and practical machine learning
solution for real-world problems with large datasets. An initial
prototype results in great improvement of the training time at the
expense of memory requirements.
Abstract: Dynamic location referencing method is an important technology to shield map differences. These method references objects of the road network by utilizing condensed selection of its real-world geographic properties stored in a digital map database, which overcomes the defections existing in pre-coded location referencing methods. The high attributes completeness requirements and complicated reference point selection algorithm are the main problems of recent researches. Therefore, a dynamic location referencing algorithm combining intersection points selected at the extremities compulsively and road link points selected according to link partition principle was proposed. An experimental system based on this theory was implemented. The tests using Beijing digital map database showed satisfied results and thus verified the feasibility and practicability of this method.
Abstract: In this study, the adhesion of ice to solid substrates
with different surface properties is compared. Clear ice, similar to
atmospheric in-flight icing encounters, is accreted on the different
substrates under controlled conditions. The ice adhesion behavior is
investigated by means of a dynamic vibration testing technique with
an electromagnetic shaker initiating ice de-bonding in the interface
between the substrate and the ice. The results of the experiments
reveal that the affinity for ice accretion is significantly influenced by
the water contact angle of the respective sample.
Abstract: In this paper, the application of sliding-mode control to a permanent-magnet synchronous motor (PMSM) is presented. The control design is based on a generic mathematical model of the motor. Some dynamics of the motor and of the power amplification stage remain unmodelled. This model uncertainty is estimated in realtime. The estimation is based on the differentiation of measured signals using the ideas of robust exact differentiator (RED). The control law is implemented on an industrial servo drive. Simulations and experimental results are presented and compared to the same control strategy without uncertainty estimation. It turns out that the proposed concept is superior to the same control strategy without uncertainty estimation especially in the case of non-smooth reference signals.
Abstract: The influence of flakes from biologically activated
hull-less barley grain and malt extract on chemical composition of
yoghurt was studied.
Pasteurized milk, freeze-dried yoghurt culture YF-L811 (Chr.
Hansen, Denmark), flakes from biologically activated hull-less
barley grain (Latvia) and malt extract (Ilgezeem, Latvia) were used
for experiments. Yoghurt samples with and without flakes from
biologically activated hull-less barley grain and malt extract were
analyzed for content of total solids, total proteins, fats, amino acids
and riboflavin.
The addition of flakes from biologically activated hull-less barley
grain and malt extract allowed increase of nutritional value of
yoghurt samples. There was obtained the increase of total proteins
(p>0.05) and the decrease of fat (p>0.05). The presence of flakes
from biologically activated hull-less barley grain and malt extract in
yoghurt samples provided significant increase of amino acids amount
(p