Abstract: Piezoelectric transformers are electronic devices made
from piezoelectric materials. The piezoelectric transformers as the
name implied are used for changing voltage signals from one level to another. Electrical energy carried with signals is transferred by means of mechanical vibration. Characterizing in both electrical and
mechanical properties leads to extensively use and efficiency enhancement of piezoelectric transformers in various applications. In
this paper, study and analysis of electrical and mechanical properties of multi-layer piezoelectric transformers in forms of potential and
displacement distribution throughout the volume, respectively. This
paper proposes a set of quasi-static mathematical model of electromechanical
coupling for piezoelectric transformer by using a set of
partial differential equations. Computer-based simulation utilizing the three-dimensional finite element method (3-D FEM) is exploited
as a tool for visualizing potentials and displacements distribution
within the multi-layer piezoelectric transformer. This simulation was
conducted by varying a number of layers. In this paper 3, 5 and 7 of
the circular ring type were used. The computer simulation based on
the use of the FEM has been developed in MATLAB programming environment.
Abstract: Image convolution similar to the receptive fields
found in mammalian visual pathways has long been used in
conventional image processing in the form of Gabor masks.
However, no VLSI implementation of parallel, multi-layered pulsed
processing has been brought forward which would emulate this
property. We present a technical realization of such a pulsed image
processing scheme. The discussed IC also serves as a general testbed
for VLSI-based pulsed information processing, which is of interest
especially with regard to the robustness of representing an analog
signal in the phase or duration of a pulsed, quasi-digital signal, as
well as the possibility of direct digital manipulation of such an
analog signal. The network connectivity and processing properties
are reconfigurable so as to allow adaptation to various processing
tasks.
Abstract: In this paper, a new formulation for acoustics coupled with linear elasticity is presented. The primary objective of the work is to develop a three dimensional hp adaptive finite element method code destinated for modeling of acoustics of human head. The code will have numerous applications e.g. in designing hearing protection devices for individuals working in high noise environments. The presented work is in the preliminary stage. The variational formulation has been implemented and tested on a sequence of meshes with concentric multi-layer spheres, with material data representing the tissue (the brain), skull and the air. Thus, an efficient solver for coupled elasticity/acoustics problems has been developed, and tested on high contrast material data representing the human head.
Abstract: This study presents a hybrid neural network and Gravitational Search Algorithm (HNGSA) method to solve well known Wessinger's equation. To aim this purpose, gravitational search algorithm (GSA) technique is applied to train a multi-layer perceptron neural network, which is used as approximation solution of the Wessinger's equation. A trial solution of the differential equation is written as sum of two parts. The first part satisfies the initial/ boundary conditions and does not contain any adjustable parameters and the second part which is constructed so as not to affect the initial/boundary conditions. The second part involves adjustable parameters (the weights and biases) for a multi-layer perceptron neural network. In order to demonstrate the presented method, the obtained results of the proposed method are compared with some known numerical methods. The given results show that presented method can introduce a closer form to the analytic solution than other numerical methods. Present method can be easily extended to solve a wide range of problems.
Abstract: The decisions made by admission control algorithms are
based on the availability of network resources viz. bandwidth, energy,
memory buffers, etc., without degrading the Quality-of-Service (QoS)
requirement of applications that are admitted. In this paper, we
present an energy-aware admission control (EAAC) scheme which
provides admission control for flows in an ad hoc network based
on the knowledge of the present and future residual energy of the
intermediate nodes along the routing path. The aim of EAAC is to
quantify the energy that the new flow will consume so that it can
be decided whether the future residual energy of the nodes along
the routing path can satisfy the energy requirement. In other words,
this energy-aware routing admits a new flow iff any node in the
routing path does not run out of its energy during the transmission
of packets. The future residual energy of a node is predicted using
the Multi-layer Neural Network (MNN) model. Simulation results
shows that the proposed scheme increases the network lifetime. Also
the performance of the MNN model is presented.
Abstract: Thermal load calculations have been performed for
multi-layered walls that are composed of three different parts; a
common (sand and cement) plaster, and two types of locally
produced soft and hard bricks. The masonry construction of these
layered walls was based on concrete-backed stone masonry made of
limestone bricks joined by mortar. These multilayered walls are
forming the outer walls of the building envelope of a typical Libyan
house. Based on the periodic seasonal weather conditions, within the
Libyan cost region during summer and winter, measured thermal
conductivity values were used to implement such seasonal variation
of heat flow and the temperature variations through the walls. The
experimental measured thermal conductivity values were obtained
using the Hot Disk technique. The estimation of the thermal
resistance of the wall layers ( R-values) is based on measurements
and calculations. The numerical calculations were done using a
simplified analytical model that considers two different wall
constructions which are characteristics of such houses. According to
the obtained results, the R-values were quite low and therefore,
several suggestions have been proposed to improve the thermal
loading performance that will lead to a reasonable human comfort
and reduce energy consumption.
Abstract: The temperature distribution and the heat transfer
rates through a multi-layer door of a furnace were investigated. The
inside of the door was in contact with hot air and the other side of the
door was in contact with room air. Radiation heat transfer from the
walls of the furnace to the door and the door to the surrounding area
was included in the problem. This work is a two dimensional steady
state problem. The Churchill and Chu correlation was used to find
local convection heat transfer coefficients at the surfaces of the
furnace door. The thermophysical properties of air were the functions
of the temperatures. Polynomial curve fitting for the fluid properties
were carried out. Finite difference method was used to discretize for
conduction heat transfer within the furnace door. The Gauss-Seidel
Iteration was employed to compute the temperature distribution in
the door.
The temperature distribution in the horizontal mid plane of the
furnace door in a two dimensional problem agrees with the one
dimensional problem. The local convection heat transfer coefficients
at the inside and outside surfaces of the furnace door are exhibited.
Abstract: The high temperature degree and uniform
Temperature Distribution (TD) on surface of cookware which contact
with food are effective factors for improving cookware application.
Additionally, the ability of pan material in retaining the heat and nonreactivity
with foods are other significant properties. It is difficult for
single material to meet a wide variety of demands such as superior
thermal and chemical properties. Multi-Layer Plate (MLP) makes
more regular TD. In this study the main objectives are to find the best
structure (single or multi-layer) and materials to provide maximum
temperature degree and uniform TD up side surface of pan. And also
heat retaining of used metals with goal of improving the thermal
quality of pan to economize the energy. To achieve this aim were
employed Finite Element Method (FEM) for analyzing transient
thermal behavior of applied materials. The analysis has been
extended for different metals, we achieved the best temperature
profile and heat retaining in Copper/ Stainless Steel MLP.
Abstract: Active research is underway on virtual touch screens
that complement the physical limitations of conventional touch
screens. This paper discusses a virtual touch screen that uses a
multi-layer perceptron to recognize and control three-dimensional
(3D) depth information from a time of flight (TOF) camera. This
system extracts an object-s area from the image input and compares it
with the trajectory of the object, which is learned in advance, to
recognize gestures. The system enables the maneuvering of content in
virtual space by utilizing human actions.
Abstract: This paper presents Simulation and experimental
study aimed at investigating the effectiveness of an adaptive artificial
neural network stabilizer on enhancing the damping torque of a
synchronous generator. For this purpose, a power system comprising
a synchronous generator feeding a large power system through a
short tie line is considered. The proposed adaptive neuro-control
system consists of two multi-layered feed forward neural networks,
which work as a plant model identifier and a controller. It generates
supplementary control signals to be utilized by conventional
controllers. The details of the interfacing circuits, sensors and
transducers, which have been designed and built for use in tests, are
presented. The synchronous generator is tested to investigate the
effect of tuning a Power System Stabilizer (PSS) on its dynamic
stability. The obtained simulation and experimental results verify the
basic theoretical concepts.
Abstract: In this paper, we develop a Spatio-Temporal graph as
of a key component of our knowledge representation Scheme. We
design an integrated representation Scheme to depict not only present
and past but future in parallel with the spaces in an effective and
intuitive manner. The resulting multi-dimensional comprehensive
knowledge structure accommodates multi-layered virtual world
developing in the time to maximize the diversity of situations in the
historical context. This knowledge representation Scheme is to be used
as the basis for simulation of situations composing the virtual world
and for implementation of virtual agents' knowledge used to judge and
evaluate the situations in the virtual world. To provide natural contexts
for situated learning or simulation games, the virtual stage set by this
Spatio-Temporal graph is to be populated by agents and other objects
interrelated and changing which are abstracted in the ontology.
Abstract: In this paper, the application of neural networks to study the design of short-term load forecasting (STLF) Systems for Illam state located in west of Iran was explored. One important architecture of neural networks named Multi-Layer Perceptron (MLP) to model STLF systems was used. Our study based on MLP was trained and tested using three years (2004-2006) data. The results show that MLP network has the minimum forecasting error and can be considered as a good method to model the STLF systems.