Abstract: In this study, the powders of Ni and Ti with 50.5 at.%
Ni for 12 h were blended and cold pressed at the different pressures
(50, 75 and100 MPa).The porous product obtained after Ni-Ti
compacts were synthesized by SHS (self-propagating hightemperature
synthesis) in the different preheating temperatures (200,
250 and 300oC) and heating rates (30, 60 and 90oC/min). The effects
of the pressure, preheating temperature and heating rate were
investigated on biocompatibility in vivo. The porosity in the
synthesized products was in the range of 50.7–59.7 vol. %. The
pressure, preheating temperature and heating rate were found to have
an important effect on the biocompatibility in-vivo of the synthesized
products. Max. fibrotic tissue within the porous implant was found in
vivo periods (6 months), in which compacting pressure 100MPa.
Abstract: We report on the development of a model to
understand why the range of experience with respect to HIV
infection is so diverse, especially with respect to the latency period.
To investigate this, an agent-based approach is used to extract highlevel
behaviour which cannot be described analytically from the set
of interaction rules at the cellular level. A network of independent
matrices mimics the chain of lymph nodes. Dealing with massively
multi-agent systems requires major computational effort. However,
parallelisation methods are a natural consequence and advantage of
the multi-agent approach and, using the MPI library, are here
implemented, tested and optimized. Our current focus is on the
various implementations of the data transfer across the network.
Three communications strategies are proposed and tested, showing
that the most efficient approach is communication based on the
natural lymph-network connectivity.
Abstract: Face Recognition has always been a fascinating research area. It has drawn the attention of many researchers because of its various potential applications such as security systems, entertainment, criminal identification etc. Many supervised and unsupervised learning techniques have been reported so far. Principal Component Analysis (PCA), Self Organizing Maps (SOM) and Independent Component Analysis (ICA) are the three techniques among many others as proposed by different researchers for Face Recognition, known as the unsupervised techniques. This paper proposes integration of the two techniques, SOM and PCA, for dimensionality reduction and feature selection. Simulation results show that, though, the individual techniques SOM and PCA itself give excellent performance but the combination of these two can also be utilized for face recognition. Experimental results also indicate that for the given face database and the classifier used, SOM performs better as compared to other unsupervised learning techniques. A comparison of two proposed methodologies of SOM, Local and Global processing, shows the superiority of the later but at the cost of more computational time.
Abstract: In this work, the plate bending formulation of the boundary element method - BEM, based on the Reissner?s hypothesis, is extended to the analysis of plates reinforced by beams taking into account the membrane effects. The formulation is derived by assuming a zoned body where each sub-region defines a beam or a slab and all of them are represented by a chosen reference surface. Equilibrium and compatibility conditions are automatically imposed by the integral equations, which treat this composed structure as a single body. In order to reduce the number of degrees of freedom, the problem values defined on the interfaces are written in terms of their values on the beam axis. Initially are derived separated equations for the bending and stretching problems, but in the final system of equations the two problems are coupled and can not be treated separately. Finally are presented some numerical examples whose analytical results are known to show the accuracy of the proposed model.
Abstract: DS-CDMA system is well known wireless
technology. This system suffers from MAI (Multiple Access
Interference) caused by Direct Sequence users. Multi-User Detection
schemes were introduced to detect the users- data in presence of
MAI. This paper focuses on linear multi-user detection schemes used
for data demodulation. Simulation results depict the performance of
three detectors viz-conventional detector, Decorrelating detector and
Subspace MMSE (Minimum Mean Square Error) detector. It is seen
that the performance of these detectors depends on the number of
paths and the length of Gold code used.
Abstract: In the present communication, we have studied
different variations in the entropy measures in the different states of
queueing processes. In case of steady state queuing process, it has
been shown that as the arrival rate increases, the uncertainty
increases whereas in the case of non-steady birth-death process, it is
shown that the uncertainty varies differently. In this pattern, it first
increases and attains its maximum value and then with the passage of
time, it decreases and attains its minimum value.
Abstract: The Improved Generalized Diversity Index (IGDI)
has been proposed as a tool that can be used to identify areas that
have high conservation value and measure the ecological condition of
an area. IGDI is based on the species relative abundances. This paper
is concerned with particular attention is given to comparisons
involving the MacArthur model of species abundances. The
properties and performance of various species indices were assessed.
Both IGDI and species richness increased with sampling area
according to a power function. IGDI were also found to be acceptable
ecological indicators of conditions and consistently outperformed
coefficient of conservatism indices.
Abstract: The time dependent progress of a chemical reaction over a flat horizontal plate is here considered. The problem is solved through the group similarity transformation method which reduces the number of independent by one and leads to a set of nonlinear ordinary differential equation. The problem shows a singularity at the chemical reaction order n=1 and is analytically solved through the perturbation method. The behavior of the process is then numerically investigated for n≠1 and different Schmidt numbers. Graphical results for the velocity and concentration of chemicals based on the analytical and numerical solutions are presented and discussed.
Abstract: Periodic vortex shedding in pulsating flow inside wavy
channel and the effect it has on heat transfer are studied using the
finite volume method. A sinusoidally-varying component is superimposed
on a uniform flow inside a sinusoidal wavy channel and
the effects on the Nusselt number is analyzed. It was found that a
unique optimum value of the pulsation frequency, represented by the
Strouhal number, exists for Reynolds numbers ranging from 125 to
1000. Results suggest that the gain in heat transfer is related to the
process of vortex formation, movement about the troughs of the wavy
channel, and subsequent ejection/destruction through the converging
section. Heat transfer is the highest when the frequencies of the
pulsation and vortex formation approach being in-phase. Analysis of
Strouhal number effect on Nu over a period of pulsation substantiates
the proposed physical mechanism for enhancement. The effect of
changing the amplitude of pulsation is also presented over a period
of pulsation, showing a monotonic increase in heat transfer with
increasing amplitude. The 60% increase in Nusselt number suggests
that sinusoidal fluid pulsation can an effective method for enhancing
heat transfer in laminar, wavy-channel flows.
Abstract: Contour filter strips planted with perennial vegetation
can be used to improve surface and ground water quality by reducing
pollutant, such as NO3-N, and sediment outflow from cropland to a
river or lake. Meanwhile, the filter strips of perennial grass with biofuel
potentials also have economic benefits of producing ethanol. In
this study, The Soil and Water Assessment Tool (SWAT) model was
applied to the Walnut Creek Watershed to examine the effectiveness
of contour strips in reducing NO3-N outflows from crop fields to the
river or lake. Required input data include watershed topography,
slope, soil type, land-use, management practices in the watershed and
climate parameters (precipitation, maximum/minimum air
temperature, solar radiation, wind speed and relative humidity).
Numerical experiments were conducted to identify potential
subbasins in the watershed that have high water quality impact, and
to examine the effects of strip size and location on NO3-N reduction
in the subbasins under various meteorological conditions (dry,
average and wet). Variable sizes of contour strips (10%, 20%, 30%
and 50%, respectively, of a subbasin area) planted with perennial
switchgrass were selected for simulating the effects of strip size and
location on stream water quality. Simulation results showed that a
filter strip having 10%-50% of the subbasin area could lead to 55%-
90% NO3-N reduction in the subbasin during an average rainfall
year. Strips occupying 10-20% of the subbasin area were found to be
more efficient in reducing NO3-N when placed along the contour
than that when placed along the river. The results of this study can
assist in cost-benefit analysis and decision-making in best water
resources management practices for environmental protection.
Abstract: Cancer classification to their corresponding cohorts has been key area of research in bioinformatics aiming better prognosis of the disease. High dimensionality of gene data has been makes it a complex task and requires significance data identification technique in order to reducing the dimensionality and identification of significant information. In this paper, we have proposed a novel approach for classification of oral cancer into metastasis positive and negative patients. We have used significance analysis of microarrays (SAM) for identifying significant genes which constitutes gene signature. 3 different gene signatures were identified using SAM from 3 different combination of training datasets and their classification accuracy was calculated on corresponding testing datasets using k-Nearest Neighbour (kNN), Fuzzy C-Means Clustering (FCM), Support Vector Machine (SVM) and Backpropagation Neural Network (BPNN). A final gene signature of only 9 genes was obtained from above 3 individual gene signatures. 9 gene signature-s classification capability was compared using same classifiers on same testing datasets. Results obtained from experimentation shows that 9 gene signature classified all samples in testing dataset accurately while individual genes could not classify all accurately.
Abstract: When a high DC voltage is applied to a capacitor with
strongly asymmetrical electrodes, it generates a mechanical force that
affects the whole capacitor. This is caused by the motion of ions generated around the smaller of the two electrodes and their subsequent interaction with the surrounding medium. If one of the electrodes is heated, it changes the conditions around the capacitor
and influences the process of ionisation, thus changing the value of the generated force. This paper describes these changes and gives
reasons behind them. Further the experimental results are given as proof of the ionic mechanism of the phenomenon.
Abstract: Neural networks offer an alternative approach both
for identification and control of nonlinear processes in process
engineering. The lack of software tools for the design of controllers
based on neural network models is particularly pronounced in this
field. SIMULINK is properly a widely used graphical code
development environment which allows system-level developers to
perform rapid prototyping and testing. Such graphical based
programming environment involves block-based code development
and offers a more intuitive approach to modeling and control task in
a great variety of engineering disciplines. In this paper a
SIMULINK based Neural Tool has been developed for analysis and
design of multivariable neural based control systems. This tool has
been applied to the control of a high purity distillation column
including non linear hydrodynamic effects. The proposed control
scheme offers an optimal response for both theoretical and practical
challenges posed in process control task, in particular when both,
the quality improvement of distillation products and the operation
efficiency in economical terms are considered.
Abstract: The paper presents dynamic programming based model as a planning tool for the maintenance of electric power systems. Every distribution component has an exponential age depending reliability function to model the fault risk. In the moment of time when the fault costs exceed the investment costs of the new component the reinvestment of the component should be made. However, in some cases the overhauling of the old component may be more economical than the reinvestment. The comparison between overhauling and reinvestment is made by optimisation process. The goal of the optimisation process is to find the cost minimising maintenance program for electric power distribution system.
Abstract: The liberalization and privatization processes have
forced public utility companies to face new competitive challenges,
implementing strategies to gain market share and, at the same time,
keep the old customers. To this end, many companies have carried
out mergers, acquisitions and conglomerations in order to diversify
their business. This paper focuses on companies operating in the free
energy market in Italy. In the last decade, this sector has undergone
profound changes that have radically changed the competitive
scenario and have led companies to implement diversification
strategies of the business. Our work aims to evaluate the economic
and financial performances obtained by energy companies, following
the beginning of the liberalization process, verifying the possible
relationship with the implemented diversification strategies.
Abstract: Sensorized instruments that accurately measure the interaction forces (between biological tissue and instrument endeffector) during surgical procedures offer surgeons a greater sense of immersion during minimally invasive robotic surgery. Although there is ongoing research into force measurement involving surgical graspers little corresponding effort has been carried out on the measurement of forces between scissor blades and tissue. This paper presents the design and development of a force measurement test apparatus, which will serve as a sensor characterization and evaluation platform. The primary aim of the experiments is to ascertain whether the system can differentiate between tissue samples with differing mechanical properties in a reliable, repeatable manner. Force-angular displacement curves highlight trends in the cutting process as well the forces generated along the blade during a cutting procedure. Future applications of the test equipment will involve the assessment of new direct force sensing technologies for telerobotic surgery.
Abstract: This article presents a voltage-mode universal
biquadratic filter performing simultaneous 3 standard functions: lowpass,
high-pass and band-pass functions, employing differential
different current conveyor (DDCC) and current controlled current
conveyor (CCCII) as active element. The features of the circuit are
that: the quality factor and pole frequency can be tuned independently
via the input bias currents: the circuit description is very simple,
consisting of 1 DDCC, 2 CCCIIs, 2 electronic resistors and 2
grounded capacitors. Without requiring component matching
conditions, the proposed circuit is very appropriate to further develop
into an integrated circuit. The PSPICE simulation results are
depicted. The given results agree well with the theoretical
anticipation.
Abstract: The prologue of new High Voltage (HV) transmission
mains into the community necessitates earthing design to ensure
safety compliance of the system. Conductive structures such as steel
or concrete poles are widely used in HV transmission mains. The
earth potential rise (EPR) generated by a fault on these structures
could result to an unsafe condition. This paper discusses information
on the input impedance of the over head earth wire (OHEW) system
for finite and infinite transmission mains. The definition of finite and
infinite system is discussed, maximum EPR due to pole fault. The
simplified equations for EPR assessments are introduced and
discussed for the finite and infinite conditions. A case study is also
shown.
Abstract: The expansive nature of soils containing high
amounts of clay minerals can be altered through chemical
stabilization, resulting in a material suitable for construction
purposes. The primary objective of this investigation was to
study the changes induced in the molecular structure of
phosphoric acid stabilized bentonite and lateritic soil using
Nuclear Magnetic Resonance (NMR) and Fourier Transform
Infrared (FTIR) spectroscopy. Based on the obtained data, it
was found that a surface alteration mechanism was the main
reason responsible for the improvement of treated soils.
Furthermore, the results indicated that the Al present in the
octahedral layer of clay minerals were more amenable to
chemical attacks and also partly responsible for the formation
of new products.
Abstract: The use of artificial neural network (ANN) modeling
for prediction and forecasting variables in water resources
engineering are being increasing rapidly. Infrastructural applications
of ANN in terms of selection of inputs, architecture of networks,
training algorithms, and selection of training parameters in different
types of neural networks used in water resources engineering have
been reported. ANN modeling conducted for water resources
engineering variables (river sediment and discharge) published in
high impact journals since 2002 to 2011 have been examined and
presented in this review. ANN is a vigorous technique to develop
immense relationship between the input and output variables, and
able to extract complex behavior between the water resources
variables such as river sediment and discharge. It can produce robust
prediction results for many of the water resources engineering
problems by appropriate learning from a set of examples. It is
important to have a good understanding of the input and output
variables from a statistical analysis of the data before network
modeling, which can facilitate to design an efficient network. An
appropriate training based ANN model is able to adopt the physical
understanding between the variables and may generate more effective
results than conventional prediction techniques.