Abstract: The present work is concerned with sulfidation of Cu,
Zn and Ni containing plating wastewater with CaS. The sulfidation
experiments were carried out at a room temperature by adding solid
CaS to simulated metal solution containing either single-metal of Ni,
Zn and Cu, or Ni-Zn-Cu mixture. At first, the experiments were
conducted without pH adjustment and it was found that the complete
sulfidation of Zn and Ni was achieved at an equimolar ratio of CaS to a
particular metal. However, in the case of Cu, a complete copper
sulfidation was achieved at CaS to Cu molar ratio of about 2. In the
case of the selective sulfidation, a simulated plating solution
containing Cu, Zn and Ni at the concentration of 100 mg/dm3 was
treated with CaS under various pH conditions. As a result, selective
precipitation of metal sulfides was achieved by a sulfidation treatment
at different pH values. Further, the precipitation agents of NaOH,
Na2S and CaS were compared in terms of the average specific
filtration resistance and compressibility coefficients of metal sulfide
slurry. Consequently, based on the lowest filtration parameters of the
produced metal sulfides, it was concluded that CaS was the most
effective precipitation agent for separation and recovery of Cu, Zn and
Ni.
Abstract: The main goal of the present work is to decrease the
computational burden for optimum design of steel frames with
frequency constraints using a new type of neural networks called
Wavelet Neural Network. It is contested to train a suitable neural
network for frequency approximation work as the analysis program.
The combination of wavelet theory and Neural Networks (NN)
has lead to the development of wavelet neural networks.
Wavelet neural networks are feed-forward networks using
wavelet as activation function. Wavelets are mathematical
functions within suitable inner parameters, which help them to
approximate arbitrary functions. WNN was used to predict the
frequency of the structures. In WNN a RAtional function with
Second order Poles (RASP) wavelet was used as a transfer
function. It is shown that the convergence speed was faster
than other neural networks. Also comparisons of WNN with
the embedded Artificial Neural Network (ANN) and with
approximate techniques and also with analytical solutions are
available in the literature.
Abstract: In cellular networks, limited availability of resources
has to be tapped to its fullest potential. In view of this aspect, a
sophisticated averaging and voting technique has been discussed in
this paper, wherein the radio resources available are utilized to the
fullest value by taking into consideration, several network and radio
parameters which decide on when the handover has to be made and
thereby reducing the load on Base station .The increase in the load
on the Base station might be due to several unnecessary handover
taking place which can be eliminated by making judicious use of the
radio and network parameters.
Abstract: Zero inflated strict arcsine model is a newly developed
model which is found to be appropriate in modeling overdispersed
count data. In this study, we extend zero inflated strict arcsine model
to zero inflated strict arcsine regression model by taking into
consideration the extra variability caused by extra zeros and
covariates in count data. Maximum likelihood estimation method is
used in estimating the parameters for this zero inflated strict arcsine
regression model.
Abstract: The so-called all-pass filter circuits are commonly
used in the field of signal processing, control and measurement.
Being connected to capacitive loads, these circuits tend to loose their
stability; therefore the elaborate analysis of their dynamic behavior is
necessary. The compensation methods intending to increase the
stability of such circuits are discussed in this paper, including the socalled
lead-lag compensation technique being treated in detail. For
the dynamic modeling, a two-port network model of the all-pass filter
is being derived. The results of the model analysis show, that
effective lead-lag compensation can be achieved, alone by the
optimization of the circuit parameters; therefore the application of
additional electric components are not needed to fulfill the stability
requirement.
Abstract: Paper presents simple sixport principle and its frequency bandwidth. The novel multisixport approach is presented with its possibilities, typical parameters and frequency bandwidth. Practical implementation is shown with its measurement parameters and calibration. The bandwidth circa 1:100 is obtained.
Abstract: Complex engineering design problems consist of
numerous factors of varying criticalities. Considering fundamental features of design and inferior details alike will result in an extensive
waste of time and effort. Design parameters should be introduced gradually as appropriate based on their significance relevant to the
problem context. This motivates the representation of design parameters at multiple levels of an abstraction hierarchy. However, developing abstraction hierarchies is an area that is not well
understood. Our research proposes a novel hierarchical abstraction methodology to plan effective engineering designs and processes. It
provides a theoretically sound foundation to represent, abstract and stratify engineering design parameters and tasks according to causality and criticality. The methodology creates abstraction
hierarchies in a recursive and bottom-up approach that guarantees no
backtracking across any of the abstraction levels. The methodology consists of three main phases, representation, abstraction, and layering to multiple hierarchical levels. The effectiveness of the
developed methodology is demonstrated by a design problem.
Abstract: The output beam quality of multi transverse modes of
laser, are relatively poor. In order to obtain better beam quality, one
may use an aperture inside the laser resonator. In this case, various
transverse modes can be selected. We have selected various
transverse modes both by simulation and doing experiment. By
inserting a circular aperture inside the diode end-pumped Nd:YAG
pulsed laser resonator, we have obtained 00 TEM , 01 TEM
, 20 TEM and have studied which parameters, can change the mode
shape. Then, we have determined the beam quality factor of TEM00
gaussian mode.
Abstract: Non-saturated soils that while saturation greatly
decrease their volume, have sudden settlement due to increasing
humidity, fracture and structural crack are called loess soils. Whereas
importance of civil projects including: dams, canals and
constructions bearing this type of soil and thereof problems, it is
required for carrying out more research and study in relation to loess
soils. This research studies shear strength parameters by using
grading test, Atterberg limit, compression, direct shear and
consolidation and then effect of using cement and lime additives on
stability of loess soils is studied. In related tests, lime and cement are
separately added to mixed ratios under different percentages of soil
and for different times the stabilized samples are processed and effect
of aforesaid additives on shear strength parameters of soil is studied.
Results show that upon passing time the effect of additives and
collapsible potential is greatly decreased and upon increasing
percentage of cement and lime the maximum dry density is
decreased; however, optimum humidity is increased. In addition,
liquid limit and plastic index is decreased; however, plastic index
limit is increased. It is to be noted that results of direct shear test
reveal increasing shear strength of soil due to increasing cohesion
parameter and soil friction angle.
Abstract: Time varying network induced delays in networked
control systems (NCS) are known for degrading control system-s
quality of performance (QoP) and causing stability problems. In
literature, a control method employing modeling of communication
delays as probability distribution, proves to be a better method. This
paper focuses on modeling of network induced delays as probability
distribution.
CAN and MIL-STD-1553B are extensively used to carry periodic
control and monitoring data in networked control systems.
In literature, methods to estimate only the worst-case delays for
these networks are available. In this paper probabilistic network
delay model for CAN and MIL-STD-1553B networks are given.
A systematic method to estimate values to model parameters from
network parameters is given. A method to predict network delay in
next cycle based on the present network delay is presented. Effect of
active network redundancy and redundancy at node level on network
delay and system response-time is also analyzed.
Abstract: The aim of this paper to characterize a larger set of
wavelet functions for implementation in a still image compression
system using SPIHT algorithm. This paper discusses important
features of wavelet functions and filters used in sub band coding to
convert image into wavelet coefficients in MATLAB. Image quality
is measured objectively using peak signal to noise ratio (PSNR) and
its variation with bit rate (bpp). The effect of different parameters is
studied on different wavelet functions. Our results provide a good
reference for application designers of wavelet based coder.
Abstract: The present work compares the performance of three
turbulence modeling approach (based on the two-equation k -ε
model) in predicting erosive wear in multi-size dense slurry flow
through rotating channel. All three turbulence models include
rotation modification to the production term in the turbulent kineticenergy
equation. The two-phase flow field obtained numerically
using Galerkin finite element methodology relates the local flow
velocity and concentration to the wear rate via a suitable wear model.
The wear models for both sliding wear and impact wear mechanisms
account for the particle size dependence. Results of predicted wear
rates using the three turbulence models are compared for a large
number of cases spanning such operating parameters as rotation rate,
solids concentration, flow rate, particle size distribution and so forth.
The root-mean-square error between FE-generated data and the
correlation between maximum wear rate and the operating
parameters is found less than 2.5% for all the three models.
Abstract: The paper presents the potential of fuzzy logic (FL-I)
and neural network techniques (ANN-I) for predicting the
compressive strength, for SCC mixtures. Six input parameters that is
contents of cement, sand, coarse aggregate, fly ash, superplasticizer
percentage and water-to-binder ratio and an output parameter i.e. 28-
day compressive strength for ANN-I and FL-I are used for modeling.
The fuzzy logic model showed better performance than neural
network model.
Abstract: A steady two-dimensional magnetohydrodynamics
flow and heat transfer over a stretching vertical sheet influenced by
radiation and porosity is studied. The governing boundary layer
equations of partial differential equations are reduced to a system of
ordinary differential equations using similarity transformation. The
system is solved numerically by using a finite difference scheme
known as the Keller-box method for some values of parameters,
namely the radiation parameter N, magnetic parameter M, buoyancy
parameter l , Prandtl number Pr and permeability parameter K. The
effects of the parameters on the heat transfer characteristics are
analyzed and discussed. It is found that both the skin friction
coefficient and the local Nusselt number decrease as the magnetic
parameter M and permeability parameter K increase. Heat transfer
rate at the surface decreases as the radiation parameter increases.
Abstract: In this study, effects of premixed and equivalence
ratios on CO and HC emissions of a dual fuel HCCI engine are
investigated. Tests were conducted on a single-cylinder engine with
compression ratio of 17.5. Premixed gasoline is provided by a
carburetor connected to intake manifold and equipped with a screw
to adjust premixed air-fuel ratio, and diesel fuel is injected directly
into the cylinder through an injector at pressure of 250 bars. A heater
placed at inlet manifold is used to control the intake charge
temperature. Optimal intake charge temperature results in better
HCCI combustion due to formation of a homogeneous mixture,
therefore, all tests were carried out over the optimum intake
temperature of 110-115 ºC. Timing of diesel fuel injection has a great
effect on stratification of in-cylinder charge and plays an important
role in HCCI combustion phasing. Experiments indicated 35 BTDC
as the optimum injection timing. Varying the coolant temperature in
a range of 40 to 70 ºC, better HCCI combustion was achieved at 50
ºC. Therefore, coolant temperature was maintained 50 ºC during all
tests. Simultaneous investigation of effective parameters on HCCI
combustion was conducted to determine optimum parameters
resulting in fast transition to HCCI combustion. One of the
advantages of the method studied in this study is feasibility of easy
and fast transition of typical diesel engine to a dual fuel HCCI
engine. Results show that increasing premixed ratio, while keeping
EGR rate constant, increases unburned hydrocarbon (UHC)
emissions due to quenching phenomena and trapping of premixed
fuel in crevices, but CO emission decreases due to increase in CO to
CO2 reactions.
Abstract: This paper presents three models which enable the
customisation of Universal Description, Discovery and Integration
(UDDI) query results, based on some pre-defined and/or real-time
changing parameters. These proposed models detail the requirements,
design and techniques which make ranking of Web service discovery
results from a service registry possible. Our contribution is two fold:
First, we present an extension to the UDDI inquiry capabilities. This
enables a private UDDI registry owner to customise or rank the query
results, based on its business requirements. Second, our proposal
utilises existing technologies and standards which require minimal
changes to existing UDDI interfaces or its data structures. We believe
these models will serve as valuable reference for enhancing the
service discovery methods within a private UDDI registry
environment.
Abstract: Integration of process planning and scheduling
functions is necessary to achieve superior overall system
performance. This paper proposes a methodology for integration of
process planning and scheduling for prismatic component that can be
implemented in a company with existing departments. The developed
model considers technological constraints whereas available time for
machining in shop floor is the limiting factor to produce multiple
process plan (MPP). It takes advantage of MPP while guarantied the
fulfillment of the due dates via using overtime. This study has been
proposed to determinate machining parameters, tools, machine and
amount of over time within the minimum cost objective while
overtime is considered for this. At last the illustration shows that the
system performance is improved by as measured by cost and
compatible with due date.
Abstract: In this paper we discuss the behaviour of the longitudinal modes of a magnetized non collisional plasma subjected to an external electromagnetic field. We apply a semiclassical formalism, with the electrons being studied in a quantum mechanical viewpoint whereas the electromagnetic field in the classical context. We calculate the dielectric function in order to obtains the modes and found that, unlike the Bernstein modes, the presence of radiation induces oscillations around the cyclotron harmonics, which are smoothed as the energy stored in the radiation field becomes small compared to the thermal energy of the electrons. We analyze the influence of the number of photon involved in the electronic transitions between the Landau levels and how the parameters such as the external fields strength, plasma density and temperature affect the dispersion relation
Abstract: This paper discusses EM algorithm and Bootstrap
approach combination applied for the improvement of the satellite
image fusion process. This novel satellite image fusion method based
on estimation theory EM algorithm and reinforced by Bootstrap
approach was successfully implemented and tested. The sensor
images are firstly split by a Bayesian segmentation method to
determine a joint region map for the fused image. Then, we use the
EM algorithm in conjunction with the Bootstrap approach to develop
the bootstrap EM fusion algorithm, hence producing the fused
targeted image. We proposed in this research to estimate the
statistical parameters from some iterative equations of the EM
algorithm relying on a reference of representative Bootstrap samples
of images. Sizes of those samples are determined from a new
criterion called 'hybrid criterion'. Consequently, the obtained results
of our work show that using the Bootstrap EM (BEM) in image
fusion improve performances of estimated parameters which involve
amelioration of the fused image quality; and reduce the computing
time during the fusion process.
Abstract: This paper presents a new approach using Combined Artificial Neural Network (CANN) module for daily peak load forecasting. Five different computational techniques –Constrained method, Unconstrained method, Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) – have been used to identify the CANN module for peak load forecasting. In this paper, a set of neural networks has been trained with different architecture and training parameters. The networks are trained and tested for the actual load data of Chennai city (India). A set of better trained conventional ANNs are selected to develop a CANN module using different algorithms instead of using one best conventional ANN. Obtained results using CANN module confirm its validity.