Abstract: There is need to explore emerging technologies based on carbon nanotube electronics as the MOS technology is approaching its limits. As MOS devices scale to the nano ranges, increased short channel effects and process variations considerably effect device and circuit designs. As a promising new transistor, the Carbon Nanotube Field Effect Transistor(CNTFET) avoids most of the fundamental limitations of the Traditional MOSFET devices. In this paper we present the analysis and comparision of a Carbon Nanotube FET(CNTFET) based 10(A current mirror with MOSFET for 32nm technology node. The comparision shows the superiority of the former in terms of 97% increase in output resistance,24% decrease in power dissipation and 40% decrease in minimum voltage required for constant saturation current. Furthermore the effect on performance of current mirror due to change in chirality vector of CNT has also been investigated. The circuit simulations are carried out using HSPICE model.
Abstract: In this paper we present a new approach to detecting a
flaw in T.O.F.D (Time Of Flight Diffraction) type ultrasonic image
based on texture features. Texture is one of the most important
features used in recognizing patterns in an image. The paper
describes texture features based on 2D Gabor functions, i.e.,
Gaussian shaped band-pass filters, with dyadic treatment of the radial
spatial frequency range and multiple orientations, which represent an
appropriate choice for tasks requiring simultaneous measurement in
both space and frequency domains. The most relevant features are
used as input data on a Fuzzy c-mean clustering classifier. The
classes that exist are only two: 'defects' or 'no defects'. The proposed
approach is tested on the T.O.F.D image achieved at the laboratory
and on the industrial field.
Abstract: The objective of global optimization is to find the
globally best solution of a model. Nonlinear models are ubiquitous
in many applications and their solution often requires a global
search approach; i.e. for a function f from a set A ⊂ Rn to
the real numbers, an element x0 ∈ A is sought-after, such that
∀ x ∈ A : f(x0) ≤ f(x). Depending on the field of application,
the question whether a found solution x0 is not only a local minimum
but a global one is very important.
This article presents a probabilistic approach to determine the
probability of a solution being a global minimum. The approach is
independent of the used global search method and only requires a
limited, convex parameter domain A as well as a Lipschitz continuous
function f whose Lipschitz constant is not needed to be known.
Abstract: This paper considers the integration of assembly
operations and product structure to Cellular Manufacturing System
(CMS) design so that to correct the drawbacks of previous researches
in the literature. For this purpose, a new mathematical model is
developed which dedicates machining and assembly operations to
manufacturing cells while the objective function is to minimize the
intercellular movements resulting due to both of them. A
linearization method is applied to achieve optimum solution through
solving aforementioned nonlinear model by common programming
language such as Lingo. Then, using different examples and
comparing the results, the importance of integrating assembly
considerations is demonstrated.
Abstract: Real-time embedded systems should benefit from
component-based software engineering to handle complexity and
deal with dependability. In these systems, applications should not
only be logically correct but also behave within time windows.
However, in the current component based software engineering
approaches, a few of component models handles time properties in
a manner that allows efficient analysis and checking at the
architectural level. In this paper, we present a meta-model for
component-based software description that integrates timing
issues. To achieve a complete functional model of software
components, our meta-model focuses on four functional aspects:
interface, static behavior, dynamic behavior, and interaction
protocol. With each aspect we have explicitly associated a time
model. Such a time model can be used to check a component-s
design against certain properties and to compute the timing
properties of component assemblies.
Abstract: The stab resistance performance of newly developed
fabric composites composed of hexagonal paper honeycombs, filled
with shear thickening fluid (STF), and woven Kevlar® fabric or
UHMPE was investigated in this study. The STF was prepared by
dispersing submicron SiO2 particles into polyethylene glycol (PEG).
Our results indicate that the STF-Kevlar composite possessed lower
penetration depth than that of neat Kevlar. In other words, the
STF-Kevlar composite can attain the same energy level in
stab-resistance test with fewer layers of Kevlar fabrics than that of the
neat Kevlar fabrics. It also indicates that STF can be used for the
fabrication of flexible body armors and can provide improved
protection against stab threats. We found that the stab resistance of the
STF-Kevlar composite increases with the increase of SiO2
concentration in STF. Moreover, the silica particles functionalized
with silane coupling agent can further improve the stab resistance.
Abstract: Study is on the vibration of thin cylindrical shells made of a functionally gradient material (FGM) composed of stainless steel and nickel is presented. The effects of the FGM configuration are studied by studying the frequencies of FG cylindrical shells. In this case FG cylindrical shell has Nickel on its inner surface and stainless steel on its outer surface. The study is carried out based on third order shear deformation shell theory. The objective is to study the natural frequencies, the influence of constituent volume fractions and the effects of configurations of the constituent materials on the frequencies. The properties are graded in the thickness direction according to the volume fraction power-law distribution. Results are presented on the frequency characteristics, the influence of the constituent various volume fractions on the frequencies.
Abstract: Most of the nonlinear equation solvers do not converge always or they use the derivatives of the function to approximate the
root of such equations. Here, we give a derivative-free algorithm that guarantees the convergence. The proposed two-step method, which
is to some extent like the secant method, is accompanied with some
numerical examples. The illustrative instances manifest that the rate of convergence in proposed algorithm is more than the quadratically
iterative schemes.
Abstract: The k-nearest neighbors (knn) is a simple but effective method of classification. In this paper we present an extended version of this technique for chemical compounds used in High Throughput Screening, where the distances of the nearest neighbors can be taken into account. Our algorithm uses kernel weight functions as guidance for the process of defining activity in screening data. Proposed kernel weight function aims to combine properties of graphical structure and molecule descriptors of screening compounds. We apply the modified knn method on several experimental data from biological screens. The experimental results confirm the effectiveness of the proposed method.
Abstract: Because of importance of energy, optimization of
power generation systems is necessary. Gas turbine cycles are
suitable manner for fast power generation, but their efficiency is
partly low. In order to achieving higher efficiencies, some
propositions are preferred such as recovery of heat from exhaust
gases in a regenerator, utilization of intercooler in a multistage
compressor, steam injection to combustion chamber and etc.
However thermodynamic optimization of gas turbine cycle, even
with above components, is necessary. In this article multi-objective
genetic algorithms are employed for Pareto approach optimization of
Regenerative-Intercooling-Gas Turbine (RIGT) cycle. In the multiobjective
optimization a number of conflicting objective functions
are to be optimized simultaneously. The important objective
functions that have been considered for optimization are entropy
generation of RIGT cycle (Ns) derives using Exergy Analysis and
Gouy-Stodola theorem, thermal efficiency and the net output power
of RIGT Cycle. These objectives are usually conflicting with each
other. The design variables consist of thermodynamic parameters
such as compressor pressure ratio (Rp), excess air in combustion
(EA), turbine inlet temperature (TIT) and inlet air temperature (T0).
At the first stage single objective optimization has been investigated
and the method of Non-dominated Sorting Genetic Algorithm
(NSGA-II) has been used for multi-objective optimization.
Optimization procedures are performed for two and three objective
functions and the results are compared for RIGT Cycle. In order to
investigate the optimal thermodynamic behavior of two objectives,
different set, each including two objectives of output parameters, are
considered individually. For each set Pareto front are depicted. The
sets of selected decision variables based on this Pareto front, will
cause the best possible combination of corresponding objective
functions. There is no superiority for the points on the Pareto front
figure, but they are superior to any other point. In the case of three
objective optimization the results are given in tables.
Abstract: This study was conducted to evaluate the antifungal
activities of Cinnamomum zeylanicum and Origanum vulgare L.
essential oil against Aspergillus flavus in culture media and tomato
paste. 200 ppm of cinnamon and 500 ppm of oregano completely
inhibited A. flavus growth in culture media, while in tomato paste 300
ppm of cinnamon and 200 ppm of oregano had the same effect. Test
panel evaluations revealed that samples with 100 and 200 ppm
cinnamon were acceptable. The results may suggest the potential use
of Cinnamomum zeylanicum essential oil as natural preservative in
tomato paste.
Abstract: A new voltage-mode triple-input single-output multifunction filter using only two current conveyors is presented. The proposed filter which possesses three inputs and single-output can generate all biquadratic filtering functions at the output terminal by selecting different input signal combinations. The validity of the proposed filter is verified through PSPICE simulations.
Abstract: The purpose of the present study is the investigation
of the relationship between knowledge management and enabling
managers based on achieving proper function. This research is
descriptive and investigative. The sample includes all male and
female high school managers of first and second regions of Urmia
including 98 school and accordingly 98 managers. The instrument
applied was a questionnaire. To sum up, there is a statistically
significant relationship between knowledge management and
empowering managers. In the end, several suggestions are provided.
Abstract: In the present work we investigate both the elastic and
electric properties of a chiral material. We consider a composite
structure made from a polymer matrix and anisotropic inclusions of
GaAs taking into account piezoelectric and dielectric properties of
the composite material. The principal task of the work is the
estimation of the functional properties of the composite material.
Abstract: Stair climbing is one of critical issues for field robots to
widen applicable areas. This paper presents optimal design on
kinematic parameters of a new robotic platform for stair climbing. The
robotic platform climbs various stairs by body flip locomotion with
caterpillar type main platform. Kinematic parameters such as platform
length, platform height, and caterpillar rotation speed are optimized to
maximize stair climbing stability. Three types of stairs are used to
simulate typical user conditions. The optimal design process is
conducted based on Taguchi methodology, and resulting parameters
with optimized objective function are presented. In near future, a
prototype is assembled for real environment testing.
Abstract: This paper presents a critical study about the
application of Neural Networks to ion-exchange process. Ionexchange
is a complex non-linear process involving many factors
influencing the ions uptake mechanisms from the pregnant solution.
The following step includes the elution. Published data presents
empirical isotherm equations with definite shortcomings resulting in
unreliable predictions. Although Neural Network simulation
technique encounters a number of disadvantages including its “black
box", and a limited ability to explicitly identify possible causal
relationships, it has the advantage to implicitly handle complex
nonlinear relationships between dependent and independent
variables. In the present paper, the Neural Network model based on
the back-propagation algorithm Levenberg-Marquardt was developed
using a three layer approach with a tangent sigmoid transfer function
(tansig) at hidden layer with 11 neurons and linear transfer function
(purelin) at out layer. The above mentioned approach has been used
to test the effectiveness in simulating ion exchange processes. The
modeling results showed that there is an excellent agreement between
the experimental data and the predicted values of copper ions
removed from aqueous solutions.
Abstract: Environmental awareness and the recent
environmental policies have forced many electric utilities to
restructure their operational practices to account for their emission
impacts. One way to accomplish this is by reformulating the
traditional economic dispatch problem such that emission effects are
included in the mathematical model. This paper presents a Particle
Swarm Optimization (PSO) algorithm to solve the Economic-
Emission Dispatch problem (EED) which gained recent attention due
to the deregulation of the power industry and strict environmental
regulations. The problem is formulated as a multi-objective one with
two competing functions, namely economic cost and emission
functions, subject to different constraints. The inequality constraints
considered are the generating unit capacity limits while the equality
constraint is generation-demand balance. A novel equality constraint
handling mechanism is proposed in this paper. PSO algorithm is
tested on a 30-bus standard test system. Results obtained show that
PSO algorithm has a great potential in handling multi-objective
optimization problems and is capable of capturing Pareto optimal
solution set under different loading conditions.
Abstract: To explore pipelines is one of various bio-mimetic
robot applications. The robot may work in common buildings such as
between ceilings and ducts, in addition to complicated and massive
pipeline systems of large industrial plants. The bio-mimetic robot finds
any troubled area or malfunction and then reports its data. Importantly,
it can not only prepare for but also react to any abnormal routes in the
pipeline. The pipeline monitoring tasks require special types of mobile
robots. For an effective movement along a pipeline, the movement of
the robot will be similar to that of insects or crawling animals. During
its movement along the pipelines, a pipeline monitoring robot has an
important task of finding the shapes of the approaching path on the
pipes. In this paper we propose an effective solution to the pipeline
pattern recognition, based on the fuzzy classification rules for the
measured IR distance data.
Abstract: Response to the public health-related emergencies is analysed here for a rural university in South Africa. The structure of the designated emergency plan covers all the phases of the disaster management cycle. The plan contains elements of the vulnerability model and the technocratic model of emergency management. The response structures are vertically and horizontally integrated, while the planning contains elements of scenario-based and functional planning. The available number of medical professionals at the Rhodes University, along with the medical insurance rates, makes the staff and students potentially more medically vulnerable than the South African population. The main improvements of the emergency management are required in the tornado response and the information dissemination during health emergencies. The latter should involve the increased use of social media and e-mails, following the Taylor model of communication. Infrastructure must be improved in the telecommunication sector in the face of unpredictable electricity outages.
Abstract: Nondestructive testing in engineering is an inverse
Cauchy problem for Laplace equation. In this paper the problem
of nondestructive testing is expressed by a Laplace-s equation with
third-kind boundary conditions. In order to find unknown values on
the boundary, the method of fundamental solution is introduced and
realized. Because of the ill-posedness of studied problems, the TSVD
regularization technique in combination with L-curve criteria and
Generalized Cross Validation criteria is employed. Numerical results
are shown that the TSVD method combined with L-curve criteria is
more efficient than the TSVD method combined with GCV criteria.
The abstract goes here.