Abstract: An adaptive Helmholtz resonator was designed and
adapted to hydraulics. The resonator was controlled by open- and
closed-loop controls so that 20 dB attenuation of the peak-to-peak
value of the pulsating pressure was maintained. The closed-loop
control was noted to be better, albeit it was slower because of its low
pressure and temperature variation, which caused variation in the
effective bulk modulus of the hydraulic system. Low-pressure
hydraulics contains air, which affects the stiffness of the hydraulics,
and temperature variation changes the viscosity of the oil. Thus, an
open-loop control loses its efficiency if a condition such as
temperature or the amount of air changes after calibration. The
instability of the low-pressure hydraulic system reduced the
operational frequency range of the Helmholtz resonator when
compared with the results of an analytical model.
Different dampers for hydraulics are presented. Then analytical
models of a hydraulic pipe and a hydraulic pipe with a Helmholtz
resonator are presented. The analytical models are based on the wave
equation of sound pressure. Finally, control methods and the results
of experiments are presented.
Abstract: As the demand for higher capacity in a cellular environment increases, the cell size decreases. This fact makes the role of suitable handoff algorithms to reduce both number of handoffs and handoff delay more important. In this paper we show that applying the grey prediction technique for handoff leads to considerable decrease in handoff delay with using a small number of handoffs, compared with traditional hystersis based handoff algorithms.
Abstract: An efficient parallel form in digital signal processor can improve the algorithm performance. The butterfly structure is an important role in fast Fourier transform (FFT), because its symmetry form is suitable for hardware implementation. Although it can perform a symmetric structure, the performance will be reduced under the data-dependent flow characteristic. Even though recent research which call as novel memory reference reduction methods (NMRRM) for FFT focus on reduce memory reference in twiddle factor, the data-dependent property still exists. In this paper, we propose a parallel-computing approach for FFT implementation on digital signal processor (DSP) which is based on data-independent property and still hold the property of low-memory reference. The proposed method combines final two steps in NMRRM FFT to perform a novel data-independent structure, besides it is very suitable for multi-operation-unit digital signal processor and dual-core system. We have applied the proposed method of radix-2 FFT algorithm in low memory reference on TI TMSC320C64x DSP. Experimental results show the method can reduce 33.8% clock cycles comparing with the NMRRM FFT implementation and keep the low-memory reference property.
Abstract: The experiment was performed to evaluate the effect
of GA3, 2,4-D on fruit growth and fruit quality of wax apple. The
experiment consisted of Red A, Monulla, Atu, Red B cultivars. GA3
and 2,4-D were applied at the small bud and petal fall stage.
Physiological, biochemical characters of fruit were recoded. The
result showed application of GA3, 2,4-D greatly response in
increasing fruit set for all treatment as compared to control. Fruit
weight, fruit size were increased at 10 ppm 2,4-D in ‘Red A’, ‘Red
B’, however it was also enhancing at 10 ppm GA3 in ‘Monulla’,
‘Atu’. For ‘Monulla’, ‘Atu’ fruit crack reduced by 10 ppm 2,4-D
application, but ‘Red B’, ‘Red A’ gave least fruit crack at 10 and 30
ppm GA3, respectively. ‘Monulla’, ‘Atu’ and ‘Red B’ resulted in
response well to 10 ppm GA3 on improving TSS, whereas
application of 30 ppm GA3 greatly enhancing TSS in ‘Red A’. For
‘Atu’ titratable acidity markedly reduced by 10 ppm GA3
application, but spraying with 30 ppm GA3 greatly response in
reducing titratable acidity in ‘Red A’, ‘Red B’ and ‘Monulla’. It was
concluded that GA3, 2,4-D can be an effective tool to enhancing fruit
set, fruit growth as well as improving fruit quality of wax apple.
Abstract: Pressure driven microscale gas flow-separation has
been investigated by solving the compressible Navier-Stokes (NS)
system of equations. A two dimensional explicit finite volume (FV)
compressible flow solver has been developed using modified
advection upwind splitting methods (AUSM+) with no-slip/first
order Maxwell-s velocity slip conditions to predict the flowseparation
behavior in microdimensions. The effects of scale-factor
of the flow geometry and gas species on the microscale gas flowseparation
have been studied in this work. The intensity of flowseparation
gets reduced with the decrease in scale of the flow
geometry. In reduced dimension, flow-separation may not at all be
present under similar flow conditions compared to the larger flow
geometry. The flow-separation patterns greatly depend on the
properties of the medium under similar flow conditions.
Abstract: Along with forward supply chain organization needs
to consider the impact of reverse logistics due to its economic
advantage, social awareness and strict legislations. In this paper, we
develop a system dynamics framework for a closed-loop supply
chain with fuzzy demand and fuzzy collection rate by incorporating
product exchange policy in forward channel and various recovery
options in reverse channel. The uncertainty issues associated with
acquisition and collection of used product have been quantified using
possibility measures. In the simulation study, we analyze order
variation at both retailer and distributor level and compare bullwhip
effects of different logistics participants over time between the
traditional forward supply chain and the closed-loop supply chain.
Our results suggest that the integration of reverse logistics can reduce
order variation and bullwhip effect of a closed-loop system. Finally,
sensitivity analysis is performed to examine the impact of various
parameters on recovery process and bullwhip effect.
Abstract: Finger spelling is an art of communicating by signs
made with fingers, and has been introduced into sign language to serve
as a bridge between the sign language and the verbal language.
Previous approaches to finger spelling recognition are classified into
two categories: glove-based and vision-based approaches. The
glove-based approach is simpler and more accurate recognizing work
of hand posture than vision-based, yet the interfaces require the user to
wear a cumbersome and carry a load of cables that connected the
device to a computer. In contrast, the vision-based approaches provide
an attractive alternative to the cumbersome interface, and promise
more natural and unobtrusive human-computer interaction. The
vision-based approaches generally consist of two steps: hand
extraction and recognition, and two steps are processed independently.
This paper proposes real-time vision-based Korean finger spelling
recognition system by integrating hand extraction into recognition.
First, we tentatively detect a hand region using CAMShift algorithm.
Then fill factor and aspect ratio estimated by width and height
estimated by CAMShift are used to choose candidate from database,
which can reduce the number of matching in recognition step. To
recognize the finger spelling, we use DTW(dynamic time warping)
based on modified chain codes, to be robust to scale and orientation
variations. In this procedure, since accurate hand regions, without
holes and noises, should be extracted to improve the precision, we use
graph cuts algorithm that globally minimize the energy function
elegantly expressed by Markov random fields (MRFs). In the
experiments, the computational times are less than 130ms, and the
times are not related to the number of templates of finger spellings in
database, as candidate templates are selected in extraction step.
Abstract: Localization is one of the critical issues in the field of
robot navigation. With an accurate estimate of the robot pose, robots will be capable of navigating in the environment autonomously and efficiently. In this paper, a hybrid Distributed Vision System (DVS)
for robot localization is presented. The presented approach integrates
odometry data from robot and images captured from overhead cameras
installed in the environment to help reduce possibilities of fail
localization due to effects of illumination, encoder accumulated errors,
and low quality range data. An odometry-based motion model is applied to predict robot poses, and robot images captured by overhead
cameras are then used to update pose estimates with HSV histogram-based measurement model. Experiment results show the
presented approach could localize robots in a global world coordinate system with localization errors within 100mm.
Abstract: The control of sprayer boom undesired vibrations pose a great challenge to investigators due to various disturbances and conditions. Sprayer boom movements lead to reduce of spread efficiency and crop yield. This paper describes the design of a novel control method for an active suspension system applying proportional-integral-derivative (PID) controller with an active force control (AFC) scheme integration of an iterative learning algorithm employed to a sprayer boom. The iterative learning as an intelligent method is principally used as a method to calculate the best value of the estimated inertia of the sprayer boom needed for the AFC loop. Results show that the proposed AFC-based scheme performs much better than the standard PID control technique. Also, this shows that the system is more robust and accurate.
Abstract: Sparse representation has long been studied and several
dictionary learning methods have been proposed. The dictionary
learning methods are widely used because they are adaptive. In this
paper, a new dictionary learning method for audio is proposed. Signals
are at first decomposed into different degrees of Intrinsic Mode
Functions (IMF) using Empirical Mode Decomposition (EMD)
technique. Then these IMFs form a learned dictionary. To reduce the
size of the dictionary, the K-means method is applied to the dictionary
to generate a K-EMD dictionary. Compared to K-SVD algorithm, the
K-EMD dictionary decomposes audio signals into structured
components, thus the sparsity of the representation is increased by
34.4% and the SNR of the recovered audio signals is increased by
20.9%.
Abstract: Breast cancer detection techniques have been reported
to aid radiologists in analyzing mammograms. We note that most
techniques are performed on uncompressed digital mammograms.
Mammogram images are huge in size necessitating the use of
compression to reduce storage/transmission requirements. In this
paper, we present an algorithm for the detection of
microcalcifications in the JPEG2000 domain. The algorithm is based
on the statistical properties of the wavelet transform that the
JPEG2000 coder employs. Simulation results were carried out at
different compression ratios. The sensitivity of this algorithm ranges
from 92% with a false positive rate of 4.7 down to 66% with a false
positive rate of 2.1 using lossless compression and lossy compression
at a compression ratio of 100:1, respectively.
Abstract: Many algorithms are available for sorting the unordered elements. Most important of them are Bubble sort, Heap sort, Insertion sort and Shell sort. These algorithms have their own pros and cons. Shell Sort which is an enhanced version of insertion sort, reduces the number of swaps of the elements being sorted to minimize the complexity and time as compared to insertion sort. Shell sort improves the efficiency of insertion sort by quickly shifting values to their destination. Average sort time is O(n1.25), while worst-case time is O(n1.5). It performs certain iterations. In each iteration it swaps some elements of the array in such a way that in last iteration when the value of h is one, the number of swaps will be reduced. Donald L. Shell invented a formula to calculate the value of ?h?. this work focuses to identify some improvement in the conventional Shell sort algorithm. ''Enhanced Shell Sort algorithm'' is an improvement in the algorithm to calculate the value of 'h'. It has been observed that by applying this algorithm, number of swaps can be reduced up to 60 percent as compared to the existing algorithm. In some other cases this enhancement was found faster than the existing algorithms available.
Abstract: This paper investigates the solutions of two-point fuzzy boundary value problems as the form x = f(t, x(t)), x(0) = A and x(l) = B, where A and B are fuzzy numbers. There are four different solutions for the problems when the lateral type of H-derivative is employed to solve the problems. As f(t, x) is a monotone function of x, these four solutions are reduced to two different solutions. As f(t, x(t)) = λx(t) or f(t, x(t)) = -λx(t), solutions and several comparison results are presented to indicate advantages of each solution.
Abstract: All the available algorithms for blind estimation namely constant modulus algorithm (CMA), Decision-Directed Algorithm (DDA/DFE) suffer from the problem of convergence to local minima. Also, if the channel drifts considerably, any DDA looses track of the channel. So, their usage is limited in varying channel conditions. The primary limitation in such cases is the requirement of certain overhead bits in the transmit framework which leads to wasteful use of the bandwidth. Also such arrangements fail to use channel state information (CSI) which is an important aid in improving the quality of reception. In this work, the main objective is to reduce the overhead imposed by the pilot symbols, which in effect reduces the system throughput. Also we formulate an arrangement based on certain dynamic Artificial Neural Network (ANN) topologies which not only contributes towards the lowering of the overhead but also facilitates the use of the CSI. A 2×2 Multiple Input Multiple Output (MIMO) system is simulated and the performance variation with different channel estimation schemes are evaluated. A new semi blind approach based on dynamic ANN is proposed for channel tracking in varying channel conditions and the performance is compared with perfectly known CSI and least square (LS) based estimation.
Abstract: In molecular biology, microarray technology is widely and successfully utilized to efficiently measure gene activity. If working with less studied organisms, methods to design custom-made microarray probes are available. One design criterion is to select probes with minimal melting temperature variances thus ensuring similar hybridization properties. If the microarray application focuses on the investigation of metabolic pathways, it is not necessary to cover the whole genome. It is more efficient to cover each metabolic pathway with a limited number of genes. Firstly, an approach is presented which minimizes the overall melting temperature variance of selected probes for all genes of interest. Secondly, the approach is extended to include the additional constraints of covering all pathways with a limited number of genes while minimizing the overall variance. The new optimization problem is solved by a bottom-up programming approach which reduces the complexity to make it computationally feasible. The new method is exemplary applied for the selection of microarray probes in order to cover all fungal secondary metabolite gene clusters for Aspergillus terreus.
Abstract: The geometric errors in the manufacturing process can
be reduced by optimal positioning of the fixture elements in the
fixture to make the workpiece stiff. We propose a new fixture layout
optimization method N-3-2-1 for large metal sheets in this paper that
combines the genetic algorithm and finite element analysis. The
objective function in this method is to minimize the sum of the nodal
deflection normal to the surface of the workpiece. Two different
kinds of case studies are presented, and optimal position of the
fixturing element is obtained for different cases.
Abstract: In this paper, the data correction algorithm is suggested
when the environmental air temperature varies. To correct the infrared
data in this paper, the initial temperature or the initial infrared image
data is used so that a target source system may not be necessary. The
temperature data obtained from infrared detector show nonlinear
property depending on the surface temperature. In order to handle this
nonlinear property, Taylor series approach is adopted. It is shown that
the proposed algorithm can reduce the influence of environmental
temperature on the components in the board. The main advantage of
this algorithm is to use only the initial temperature of the components
on the board rather than using other reference device such as black
body sources in order to get reference temperatures.
Abstract: Pollution emission levels of aircraft engines are a
nowadays high concern. Any technological advance that could reduce
emission levels is always welcome. In what concerns aircraft engines,
a possible solution for this problem could be the use of regenerators
and intercoolers. These components might reduce the specific fuel
consumption, increase efficiency and specific thrust and consequently
reduce the pollution levels of the engine. This is not a novel solution.
These heat exchangers are already is use in stationary engines. For
aircraft engines, the extra weight of the needed hardware could
overcome the fuel saved. This work compares a conventional engine
with configurations that use intercoolers and regenerators.
Abstract: The biological activity of A. pullulans isolates against
species of the genus Fusarium, bacteria of the genus Azotobacter and
pseudomonads colonizing wheat kernels was evaluated. A field
experiment was carried out in 2009-2011, in north-eastern Poland.
Winter wheat (cv. Bogatka) plants were sprayed with a cell
suspension of A. pullulans at a density of 106 - 108 per cm3 water at
the stem elongation stage and the heading stage. Untreated plants
served as control. The abundance of epiphytic yeasts, bacteria of the
genus Azotobacter, pseudomonads and Fusarium pathogens on wheat
grain was estimated at harvest and after six months’ storage. The
average size of yeast communities was significantly greater on wheat
kernels treated with a cell suspension of A. pullulans, compared with
control samples. In 2010-2011, biological control reduced the
abundance of some species of the genus Fusarium.
Abstract: The article examines an opportunity of corruption
restriction exercised by international business community in Russia.
Integration of Russian economy into the international business does
not reduce corruption inside the country. Foreign actors investing in
Russia under the condition of obtaining their required rates of returns
will be reluctant to harm their investments by involving into anticorruption
activities. Furthermore, many Russian firms- competitive
advantage could be directly related to their corruption connections. In
this case, foreign investments would only accentuate corrupt
companies- success by supporting them financially