Abstract: The characterization and modeling of the dynamic
behavior of many built-up structures under vibration conditions is still
a subject of current research. The present study emphasizes the
theoretical investigation of slip damping in layered and jointed
welded cantilever structures using finite element approach.
Application of finite element method in damping analysis is relatively
recent, as such, some problems particularly slip damping analysis has
not received enough attention. To validate the finite element model
developed, experiments have been conducted on a number of mild
steel specimens under different initial conditions of vibration. Finite
element model developed affirms that the damping capacity of such
structures is influenced by a number of vital parameters such as;
pressure distribution, kinematic coefficient of friction and micro-slip
at the interfaces, amplitude, frequency of vibration, length and
thickness of the specimen. Finite element model developed can be
utilized effectively in the design of machine tools, automobiles,
aerodynamic and space structures, frames and machine members for
enhancing their damping capacity.
Abstract: In this paper, some experiments of liquid dispersion flow driven by explosion in vertical plane were carried out using a liquid explosive dispersion device with film cylindrical constraints. The separated time series describing the breakup shape and dispersion process of liquid were recorded with high speed CMOS camera. The experimental results were analyzed and some essential characteristics of liquid dispersing flow are presented.
Abstract: In this work, new experimental data for slugging
frequency in inclined gas-liquid flow are reported, and a new
correlation is proposed. Scale experiments were carried out using a
mixture of air and water in a 6 m long pipe. Two different pipe
diameters were used, namely, 38 and 67 mm. The data were taken
with capacitance type sensors at a data acquisition frequency of 200
Hz over an interval of 60 seconds. For the range of flow conditions
studied, the liquid superficial velocity is observed to influence the
frequency strongly. A comparison of the present data with
correlations available in the literature reveals a lack of agreement. A
new correlation for slug frequency has been proposed for the inclined
flow, which represents the main contribution of this work.
Abstract: Cattle manure and mineral fertilizers are two source
of Nitrogen, which can affect the growth and quantity of potato. In
this research the effects of the use of cattle manure (5, 10, 15 and 20
ton ha-1), Nitrogen fertilizer (50, 100 and 150 kg N ha-1) and their
interaction on potato growth were evaluated during field
experiments in 2008 with the help of Randomized Complete Block
(RCB) with the factorial arrangement of three experimental
replications in Iran. At the 75 th day after emergence, dry weight of
Shoots, leaf area index (LAI) and plant height were recorded. Results
showed that, dry weight of Shoots, LAI and plant height increased
linearly and very significantly in response to the application of
manure and Nitrogen fertilizer. While the interaction between
manure and Nitrogen fertilizer just on the LAI and plant height was
significant, somehow the maximum amount of plant height( 73 cm)
was obtained by using 150 kg Nitrogen + 15 tons of manure per
hectare, and maximum LAI ( 5.36) was obtained by using 150 kg
Nitrogen + 20 tons of manure per hectare. Also in this experiment
maximum tuber yield (36.8 tons ha-1) was obtained by the utilization
of 150 kg Nitrogen per hectare + 20 tons manure.
Abstract: HIV-1 genome is highly heterogeneous. Due to this
variation, features of HIV-I genome is in a wide range. For this
reason, the ability to infection of the virus changes depending on
different chemokine receptors. From this point of view, R5 HIV
viruses use CCR5 coreceptor while X4 viruses use CXCR5 and
R5X4 viruses can utilize both coreceptors. Recently, in
Bioinformatics, R5X4 viruses have been studied to classify by using
the experiments on HIV-1 genome.
In this study, R5X4 type of HIV viruses were classified using
Auto Regressive (AR) model through Artificial Neural Networks
(ANNs). The statistical data of R5X4, R5 and X4 viruses was
analyzed by using signal processing methods and ANNs. Accessible
residues of these virus sequences were obtained and modeled by AR
model since the dimension of residues is large and different from
each other. Finally the pre-processed data was used to evolve various
ANN structures for determining R5X4 viruses. Furthermore ROC
analysis was applied to ANNs to show their real performances. The
results indicate that R5X4 viruses successfully classified with high
sensitivity and specificity values training and testing ROC analysis
for RBF, which gives the best performance among ANN structures.
Abstract: This study presents energy saving in general-purpose
pumps widely used in industrial applications. Such pumps are
normally driven by a constant-speed electrical motor which in most
applications must support varying load conditions. This is equivalent
to saying the loading conditions mismatch the designed optimal
energy consumption requirements of the intended application thus
resulting in substantial energy losses. In the held experiments it was
indicated that combination of mechanical and electrical speed drives
can contribute to lower energy consumption in the pump without
negatively distorting the required performance indices of a typical
centrifugal pump at substantially lower energy consumption. The
registered energy savings were recorded to be within the 15-40%
margin. It was also indicated that although VSDs are installed at a
cost, the financial burden is balanced against the earnings resulting
from the associated energy savings.
Abstract: Structured catalysts formed from the growth of
zeolites on substrates is an area of increasing interest due to the
increased efficiency of the catalytic process, and the ability to
provide superior heat transfer and thermal conductivity for both
exothermic and endothermic processes.
However, the generation of structured catalysts represents a
significant challenge when balancing the relationship variables
between materials properties and catalytic performance, with the
Na2O, H2O and Al2O3 gel composition paying a significant role in
this dynamic, thereby affecting the both the type and range of
application.
The structured catalyst films generated as part of this
investigation have been characterised using a range of techniques,
including X-ray diffraction (XRD), Electron microscopy (SEM),
Energy Dispersive X-ray analysis (EDX) and Thermogravimetric
Analysis (TGA), with the transition from oxide-on-alloy wires to
hydrothermally synthesised uniformly zeolite coated surfaces being
demonstrated using both SEM and XRD. The robustness of the
coatings has been ascertained by subjecting these to thermal cycling
(ambient to 550oC), with the results indicating that the synthesis time
and gel compositions have a crucial effect on the quality of zeolite
growth on the FeCrAlloy wires.
Finally, the activity of the structured catalyst was verified by a
series of comparison experiments with standard zeolite Y catalysts in
powdered pelleted forms.
Abstract: In any trust model, the two information sources that a peer relies on to predict trustworthiness of another peer are direct experience as well as reputation. These two vital components evolve over time. Trust evolution is an important issue, where the objective is to observe a sequence of past values of a trust parameter and determine the future estimates. Unfortunately, trust evolution algorithms received little attention and the proposed algorithms in the literature do not comply with the conditions and the nature of trust. This paper contributes to this important problem in the following ways: (a) presents an algorithm that manages and models trust evolution in a P2P environment, (b) devises new mechanisms for effectively maintaining trust values based on the conditions that influence trust evolution , and (c) introduces a new methodology for incorporating trust-nurture incentives into the trust evolution algorithm. Simulation experiments are carried out to evaluate our trust evolution algorithm.
Abstract: Deoxyribonucleic Acid or DNA computing has
emerged as an interdisciplinary field that draws together chemistry,
molecular biology, computer science and mathematics. Thus, in this
paper, the possibility of DNA-based computing to solve an absolute
1-center problem by molecular manipulations is presented. This is
truly the first attempt to solve such a problem by DNA-based
computing approach. Since, part of the procedures involve with
shortest path computation, research works on DNA computing for
shortest path Traveling Salesman Problem, in short, TSP are reviewed.
These approaches are studied and only the appropriate one is adapted
in designing the computation procedures. This DNA-based
computation is designed in such a way that every path is encoded by
oligonucleotides and the path-s length is directly proportional to the
length of oligonucleotides. Using these properties, gel electrophoresis
is performed in order to separate the respective DNA molecules
according to their length. One expectation arise from this paper is that
it is possible to verify the instance absolute 1-center problem using
DNA computing by laboratory experiments.
Abstract: In this paper is being described a possible use of
virtualization technology in teaching computer networks. The
virtualization can be used as a suitable tool for creating virtual
network laboratories, supplementing the real laboratories and
network simulation software in teaching networking concepts. It will
be given a short description of characteristic projects in the area of
virtualization technology usage in network simulation, network
experiments and engineering education. A method for implementing
laboratory has also been explained, together with possible laboratory
usage and design of laboratory exercises. At the end, the laboratory
test results of virtual laboratory are presented as well.
Abstract: In this paper we present a GP-based method for automatically evolve projections, so that data can be more easily classified in the projected spaces. At the same time, our approach can reduce dimensionality by constructing more relevant attributes. Fitness of each projection measures how easy is to classify the dataset after applying the projection. This is quickly computed by a Simple Linear Perceptron. We have tested our approach in three domains. The experiments show that it obtains good results, compared to other Machine Learning approaches, while reducing dimensionality in many cases.
Abstract: Accurate modeling of high speed RLC interconnects
has become a necessity to address signal integrity issues in current
VLSI design. To accurately model a dispersive system of interconnects
at higher frequencies; a full-wave analysis is required.
However, conventional circuit simulation of interconnects with full
wave models is extremely CPU expensive. We present an algorithm
for reducing large VLSI circuits to much smaller ones with similar
input-output behavior. A key feature of our method, called Frequency
Shift Technique, is that it is capable of reducing linear time-varying
systems. This enables it to capture frequency-translation and sampling
behavior, important in communication subsystems such as mixers,
RF components and switched-capacitor filters. Reduction is obtained
by projecting the original system described by linear differential
equations into a lower dimension. Experiments have been carried out
using Cadence Design Simulator cwhich indicates that the proposed
technique achieves more % reduction with less CPU time than the
other model order reduction techniques existing in literature. We
also present applications to RF circuit subsystems, obtaining size
reductions and evaluation speedups of orders of magnitude with
insignificant loss of accuracy.
Abstract: Iris-based biometric system is gaining its importance in several applications. However, processing of iris biometric is a challenging and time consuming task. Detection of iris part in an eye image poses a number of challenges such as, inferior image quality, occlusion of eyelids and eyelashes etc. Due to these problems it is not possible to achieve 100% accuracy rate in any iris-based biometric authentication systems. Further, iris detection is a computationally intensive task in the overall iris biometric processing. In this paper, we address these two problems and propose a technique to localize iris part efficiently and accurately. We propose scaling and color level transform followed by thresholding, finding pupil boundary points for pupil boundary detection and dilation, thresholding, vertical edge detection and removal of unnecessary edges present in the eye images for iris boundary detection. Scaling reduces the search space significantly and intensity level transform is helpful for image thresholding. Experimental results show that our approach is comparable with the existing approaches. Following our approach it is possible to detect iris part with 95-99% accuracy as substantiated by our experiments on CASIA Ver-3.0, ICE 2005, UBIRIS, Bath and MMU iris image databases.
Abstract: Microaneurysm is a key indicator of diabetic retinopathy that can potentially cause damage to retina. Early detection and automatic quantification are the keys to prevent further damage. In this paper, which focuses on automatic microaneurysm detection in images acquired through non-dilated pupils, we present a series of experiments on feature selection and automatic microaneurysm pixel classification. We found that the best feature set is a combination of 10 features: the pixel-s intensity of shade corrected image, the pixel hue, the standard deviation of shade corrected image, DoG4, the area of the candidate MA, the perimeter of the candidate MA, the eccentricity of the candidate MA, the circularity of the candidate MA, the mean intensity of the candidate MA on shade corrected image and the ratio of the major axis length and minor length of the candidate MA. The overall sensitivity, specificity, precision, and accuracy are 84.82%, 99.99%, 89.01%, and 99.99%, respectively.
Abstract: Treatment of tar-containing wastewater is necessary
for the successful operation of biomass gasification plants (BGPs). In
the present study, tar-containing wastewater was treated using lime
and alum for the removal of in-organics, followed by adsorption on
powdered activated carbon (PAC) for the removal of organics. Limealum
experiments were performed in a jar apparatus and activated
carbon studies were performed in an orbital shaker. At optimum
concentrations, both lime and alum individually proved to be capable
of removing color, total suspended solids (TSS) and total dissolved
solids (TDS), but in both cases, pH adjustment had to be carried out
after treatment. The combination of lime and alum at the dose ratio
of 0.8:0.8 g/L was found to be optimum for the removal of inorganics.
The removal efficiency achieved at optimum
concentrations were 78.6, 62.0, 62.5 and 52.8% for color, alkalinity,
TSS and TDS, respectively. The major advantages of the lime-alum
combination were observed to be as follows: no requirement of pH
adjustment before and after treatment and good settleability of
sludge. Coagulation-precipitation followed by adsorption on PAC
resulted in 92.3% chemical oxygen demand (COD) removal and
100% phenol removal at equilibrium. Ammonia removal efficiency
was found to be 11.7% during coagulation-flocculation and 36.2%
during adsorption on PAC. Adsorption of organics on PAC in terms
of COD and phenol followed Freundlich isotherm with Kf = 0.55 &
18.47 mg/g and n = 1.01 & 1.45, respectively. This technology may
prove to be one of the fastest and most techno-economically feasible
methods for the treatment of tar-containing wastewater generated
from BGPs.
Abstract: The paper presents the multi-element synthetic
transmit aperture (MSTA) method with a small number of elements
transmitting and all elements apertures in medical ultrasound
imaging. As compared to the other methods MSTA allows to
increase the system frame rate and provides the best compromise
between penetration depth and lateral resolution.
In the experiments a 128-element linear transducer array with
0.3 mm pitch excited by a burst pulse of 125 ns duration were used.
The comparison of 2D ultrasound images of tissue mimicking
phantom obtained using the STA and the MSTA methods is
presented to demonstrate the benefits of the second approach. The
results were obtained using SA algorithm with transmit and receive
signals correction based on a single element directivity function.
Abstract: In this paper, we propose a fast and efficient method for drawing very large-scale graph data. The conventional force-directed method proposed by Fruchterman and Rheingold (FR method) is well-known. It defines repulsive forces between every pair of nodes and attractive forces between connected nodes on a edge and calculates corresponding potential energy. An optimal layout is obtained by iteratively updating node positions to minimize the potential energy. Here, the positions of the nodes are updated every global timestep at the same time. In the proposed method, each node has its own individual time and time step, and nodes are updated at different frequencies depending on the local situation. The proposed method is inspired by the hierarchical individual time step method used for the high accuracy calculations for dense particle fields such as star clusters in astrophysical dynamics. Experiments show that the proposed method outperforms the original FR method in both speed and accuracy. We implement the proposed method on the MDGRAPE-3 PCI-X special purpose parallel computer and realize a speed enhancement of several hundred times.
Abstract: Machine Translation (MT) between the Thai and English languages has been a challenging research topic in natural language processing. Most research has been done on English to Thai machine translation, but not the other way around. This paper presents a Thai to English Machine Translation System that translates a Thai sentence into interlingua of a Thai LFG tree using LFG grammar and a bottom up parser. The Thai LFG tree is then transformed into the corresponding English LFG tree by pattern matching and node transformation. Finally, an equivalent English sentence is created using structural information prescribed by the English LFG tree. Based on results of experiments designed to evaluate the performance of the proposed system, it can be stated that the system has been proven to be effective in providing a useful translation from Thai to English.
Abstract: In the paper, a fast high-resolution range profile synthetic algorithm called orthogonal matching pursuit with sensing dictionary (OMP-SD) is proposed. It formulates the traditional HRRP synthetic to be a sparse approximation problem over redundant dictionary. As it employs a priori that the synthetic range profile (SRP) of targets are sparse, SRP can be accomplished even in presence of data lost. Besides, the computation complexity decreases from O(MNDK) flops for OMP to O(M(N + D)K) flops for OMP-SD by introducing sensing dictionary (SD). Simulation experiments illustrate its advantages both in additive white Gaussian noise (AWGN) and noiseless situation, respectively.
Abstract: This paper addresses the problem of determining the current 3D location of a moving object and robustly tracking it from a sequence of camera images. The approach presented here uses a particle filter and does not perform any explicit triangulation. Only the color of the object to be tracked is required, but not any precisemotion model. The observation model we have developed avoids the color filtering of the entire image. That and the Monte Carlotechniques inside the particle filter provide real time performance.Experiments with two real cameras are presented and lessons learned are commented. The approach scales easily to more than two cameras and new sensor cues.