Abstract: In this paper, a fiber based Fabry-Perot interferometer
is proposed and demonstrated for a non-contact displacement
measurement. A piece of micro-prism which attached to the
mechanical vibrator is served as the target reflector. Interference
signal is generated from the superposition between the sensing beam
and the reference beam within the sensing arm of the fiber sensor.
This signal is then converted to the displacement value by using a
developed program written in visual Cµ programming with a
resolution of λ/8. A classical function generator is operated for
controlling the vibrator. By fixing an excitation frequency of 100 Hz
and varying the excitation amplitude range of 0.1 – 3 Volts, the
output displacements measured by the fiber sensor are obtained from
1.55 μm to 30.225 μm. A reference displacement sensor with a
sensitivity of ~0.4 μm is also employed for comparing the
displacement errors between both sensors. We found that over the
entire displacement range, a maximum and average measurement
error are obtained of 0.977% and 0.44% respectively.
Abstract: In a none-super-competitive environment the concepts
of closed system, management control remains to be the dominant
guiding concept to management. The merits of closed loop have been
the sources of most of the management literature and culture for
many decades. It is a useful exercise to investigate and poke into the
dynamics of the control loop phenomenon and draws some lessons to
use for refining the practice of management. This paper examines the
multitude of lessons abstracted from the behavior of the Input /output
/feedback control loop model, which is the core of control theory.
There are numerous lessons that can be learned from the insights this
model would provide and how it parallels the management dynamics
of the organization. It is assumed that an organization is basically a
living system that interacts with the internal and external variables. A
viable control loop is the one that reacts to the variation in the
environment and provide or exert a corrective action. In managing
organizations this is reflected in organizational structure and
management control practices. This paper will report findings that
were a result of examining several abstract scenarios that are
exhibited in the design, operation, and dynamics of the control loop
and how they are projected on the functioning of the organization.
Valuable lessons are drawn in trying to find parallels and new
paradigms, and how the control theory science is reflected in the
design of the organizational structure and management practices. The
paper is structured in a logical and perceptive format. Further
research is needed to extend these findings.
Abstract: The objective of this research is to develop an advanced driver assistance system characterized with the functions of lane departure warning (LDW), forward collision warning (FCW) and adaptive front-lighting system (AFS). The system is mainly configured a CCD/CMOS camera to acquire the images of roadway ahead in association with the analysis made by an image-processing unit concerning the lane ahead and the preceding vehicles. The input image captured by a camera is used to recognize the lane and the preceding vehicle positions by image detection and DROI (Dynamic Range of Interesting) algorithms. Therefore, the system is able to issue real-time auditory and visual outputs of warning when a driver is departing the lane or driving too close to approach the preceding vehicle unwittingly so that the danger could be prevented from occurring. During the nighttime, in addition to the foregoing warning functions, the system is able to control the bending light of headlamp to provide an immediate light illumination when making a turn at a curved lane and adjust the level automatically to reduce the lighting interference against the oncoming vehicles driving in the opposite direction by the curvature of lane and the vanishing point estimations. The experimental results show that the integrated vehicle image system is robust to most environments such as the lane detection and preceding vehicle detection average accuracy performances are both above 90 %.
Abstract: Design of Converter transformer insulation is a major
challenge. The insulation of these transformers is stressed by both
AC and DC voltages. Particle contamination is one of the major
problems in insulation structures, as they generate partial discharges
leading it to major failure of insulation. Similarly corona discharges
occur in transformer insulation. This partial discharge due to particle
movement / corona formation in insulation structure under different
voltage wave shapes, are different. In the present study, UHF
technique is adopted to understand the discharge activity and could
be realized that the characteristics of UHF signal generated under
low and high fields are different. In the case of corona generated
signal, the frequency content of the UHF sensor output lies in the
range 0.3-1.2 GHz and is not much varied except for its increase in
magnitude of discharge with the increase in applied voltage. It is
realized that the current signal injected due to partial
discharges/corona is about 4ns duration measured for first one half
cycle. Wavelet technique is adopted in the present study. It allows
one to identify the frequency content present in the signal at different
instant of time. The STD-MRA analysis helps one to identify the
frequency band in which the energy content of the UHF signal is
maximum.
Abstract: Carbon dioxide capture process has been simulated
and studied under different process conditions. It has been shown
that several process parameters such as lean amine temperature,
number of adsorber stages, number of stripper stages and stripper
pressure affect different process conditions and outputs such as
carbon dioxide removal and reboiler duty. It may be concluded that
the simulation of carbon dioxide capture process can help to estimate
the best process conditions.
Abstract: Microwave energy can be used for drying purpose. It is unique process. It is distinctly different from conventional drying process. It is advantageous over conventional drying / heating processes. When microwave energy is used for drying purpose, the process can be accelerated with a better control to achieve uniform heating, more conversion efficiency, selective drying and ultimately improved product quality of the output. Also, less floor space and compact system are the added advantages. Existing low power microwave drying system is to be modified with suitable applicator. Appropriate sensors are to be used to measure parameters like moisture, temperature, weight of sample. Suitable high tech controller is to be used to control microwave power continuously from minimum to maximum. Phase - controller, cycle - controller and PWM - controller are some of the advanced power control techniques. It has been proposed to work on turmeric using high-tech phase controller to control the microwave power conveniently. The drying of turmeric with microwave energy employing phase controller gives better results as formulated in this paper and hence new approach of processing turmeric will open future doors of profit making to allied industries and the farmers.
Abstract: Scheduling algorithm is a key technology in satellite
switching system with input-buffer. In this paper, a new scheduling
algorithm and its realization are proposed. Based on Crossbar
switching fabric, the algorithm adopts serial scheduling strategy and
adjusts the output port arbitrating strategy for the better equity of every
port. Consequently, it increases the matching probability. The
algorithm can greatly reduce the scheduling delay and cell loss rate.
The analysis and simulation results by OPNET show that the proposed
algorithm has the better performance than others in average delay and
cell loss rate, and has the equivalent complexity. On the basis of these
results, the hardware realization and simulation based on FPGA are
completed, which validate the feasibility of the new scheduling
algorithm.
Abstract: The requirement to improve software productivity has
promoted the research on software metric technology. There are
metrics for identifying the quality of reusable components but the
function that makes use of these metrics to find reusability of
software components is still not clear. These metrics if identified in
the design phase or even in the coding phase can help us to reduce the
rework by improving quality of reuse of the component and hence
improve the productivity due to probabilistic increase in the reuse
level. CK metric suit is most widely used metrics for the objectoriented
(OO) software; we critically analyzed the CK metrics, tried
to remove the inconsistencies and devised the framework of metrics
to obtain the structural analysis of OO-based software components.
Neural network can learn new relationships with new input data and
can be used to refine fuzzy rules to create fuzzy adaptive system.
Hence, Neuro-fuzzy inference engine can be used to evaluate the
reusability of OO-based component using its structural attributes as
inputs. In this paper, an algorithm has been proposed in which the
inputs can be given to Neuro-fuzzy system in form of tuned WMC,
DIT, NOC, CBO , LCOM values of the OO software component and
output can be obtained in terms of reusability. The developed
reusability model has produced high precision results as expected by
the human experts.
Abstract: In this paper multi-objective genetic algorithms are
employed for Pareto approach optimization of ideal Turboshaft
engines. In the multi-objective optimization a number of conflicting
objective functions are to be optimized simultaneously. The
important objective functions that have been considered for
optimization are specific thrust (F/m& 0), specific fuel consumption
( P S ), output shaft power 0 (& /&) shaft W m and overall efficiency( ) O
η .
These objectives are usually conflicting with each other. The design
variables consist of thermodynamic parameters (compressor pressure
ratio, turbine temperature ratio and Mach number).
At the first stage single objective optimization has been
investigated and the method of NSGA-II has been used for multiobjective
optimization. Optimization procedures are performed for
two and four objective functions and the results are compared for
ideal Turboshaft engine. 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 four objective
optimization the results are given in tables.
Abstract: The stem cells have ability to differentiated
themselves through mitotic cell division and various range of
specialized cell types. Cellular differentiation is a way by which few
specialized cell develops into more specialized.This paper studies the
fundamental problem of computational schema for an artificial neural
network based on chemical, physical and biological variables of
state. By doing this type of study system could be model for a viable
propagation of various economically important stem cells
differentiation. This paper proposes various differentiation outcomes
of artificial neural network into variety of potential specialized cells
on implementing MATLAB version 2009. A feed-forward back
propagation kind of network was created to input vector (five input
elements) with single hidden layer and one output unit in output
layer. The efficiency of neural network was done by the assessment
of results achieved from this study with that of experimental data
input and chosen target data. The propose solution for the efficiency
of artificial neural network assessed by the comparatative analysis of
“Mean Square Error" at zero epochs. There are different variables of
data in order to test the targeted results.
Abstract: In this paper we propose a robust environmental sound classification approach, based on spectrograms features driven from log-Gabor filters. This approach includes two methods. In the first methods, the spectrograms are passed through an appropriate log-Gabor filter banks and the outputs are averaged and underwent an optimal feature selection procedure based on a mutual information criteria. The second method uses the same steps but applied only to three patches extracted from each spectrogram.
To investigate the accuracy of the proposed methods, we conduct experiments using a large database containing 10 environmental sound classes. The classification results based on Multiclass Support Vector Machines show that the second method is the most efficient with an average classification accuracy of 89.62 %.
Abstract: In this paper a controller for the pitch angle of an
aircraft regarding to the elevator deflection angle is designed.
The way how the elevator angle affects pitching motion of the
aircraft is pointed out, as well as, how a pitch controller can be
applied for the aircraft to reach certain pitch angle. In this digital
optimal system, the elevator deflection angle and pitching angle
of the plane are considered to be input and output respectively.
A single input single output (SISO) system is presented. A
digital pitch aircraft control is demonstrated. A simulation for
the whole system has been performed. The optimal control
weighting vectors, Q and R have been determined.
Abstract: Biological data has several characteristics that strongly differentiate it from typical business data. It is much more complex, usually large in size, and continuously changes. Until recently business data has been the main target for discovering trends, patterns or future expectations. However, with the recent rise in biotechnology, the powerful technology that was used for analyzing business data is now being applied to biological data. With the advanced technology at hand, the main trend in biological research is rapidly changing from structural DNA analysis to understanding cellular functions of the DNA sequences. DNA chips are now being used to perform experiments and DNA analysis processes are being used by researchers. Clustering is one of the important processes used for grouping together similar entities. There are many clustering algorithms such as hierarchical clustering, self-organizing maps, K-means clustering and so on. In this paper, we propose a clustering algorithm that imitates the ecosystem taking into account the features of biological data. We implemented the system using an Ant-Colony clustering algorithm. The system decides the number of clusters automatically. The system processes the input biological data, runs the Ant-Colony algorithm, draws the Topic Map, assigns clusters to the genes and displays the output. We tested the algorithm with a test data of 100 to1000 genes and 24 samples and show promising results for applying this algorithm to clustering DNA chip data.
Abstract: This paper deals with new concept of using compressed atmospheric air as a zero pollution power source for running motorbikes. The motorbike is equipped with an air turbine in place of an internal combustion engine, and transforms the energy of the compressed air into shaft work. The mathematical modeling and performance evaluation of a small capacity compressed air driven vaned type novel air turbine is presented in this paper. The effect of isobaric admission and adiabatic expansion of high pressure air for different rotor to casing diameter ratios with respect to different vane angles (number of vanes) have been considered and analyzed. It is found that the shaft work output is optimum for some typical values of rotor / casing diameter ratios at a particular value of vane angle (no. of vanes). In this study, the maximum power is obtained as 4.5kW - 5.3kW (5.5-6.25 HP) when casing diameter is taken 100 mm, and rotor to casing diameter ratios are kept from 0.65 to 0.55. This value of output is sufficient to run motorbike.
Abstract: This paper proposes the method combining artificial
neural network (ANN) with particle swarm optimization (PSO) to
implement the maximum power point tracking (MPPT) by controlling
the rotor speed of the wind generator. First, the measurements of wind
speed, rotor speed of wind power generator and output power of wind
power generator are applied to train artificial neural network and to
estimate the wind speed. Second, the method mentioned above is
applied to estimate and control the optimal rotor speed of the wind
turbine so as to output the maximum power. Finally, the result reveals
that the control system discussed in this paper extracts the maximum
output power of wind generator within the short duration even in the
conditions of wind speed and load impedance variation.
Abstract: The purpose of this paper is to highlight the
importance of the concept of competitiveness in the supply chain and
to present a conceptual framework for Supply Chain Competitiveness
(SCC). The framework is based on supply chain activities, which are
inputs, necessary for SCC and the benefits which are the outputs of
SCC. A literature review is conducted on key supply chain
competitiveness issues, its determinants, its various dimensions
followed by exploration for SCC. Based on the insights gained, a
conceptual framework for SCC is presented based on activities for
SCC, SCC environment and outcomes of SCC. The information flow
in the conceptual framework is bi-directional at all levels and the
activities are interrelated in a global competitive environment. The
activities include the activities of suppliers, manufacturers and
distributors, giving more emphasis on manufacturers- activities.
Further, implications of various factors such as economic, politicolegal,
technical, socio-cultural, competition, demographic etc. are
also highlighted. The SCC framework is an attempt to cover the
relatively less explored area of supply chain competitiveness. It is
expected that this work will further motivate researchers,
academicians and practitioners to work in this area and offers
conceptual help in providing a directions for supply chain
competitiveness which leads to improvement in the supply chain and
supply chain performance.
Abstract: A new current-mode multifunction filter using minimum number of passive elements is proposed. The proposed filter has single-input and four high-impedance outputs. It uses four passive elements (two capacitors and two resistors) and four dual output second generation current conveyors. Each output provides a different filter response, namely, low-pass, high-pass, band-pass and band-reject. The sensitivity analysis is also carried out on both ideal and non-ideal filter configurations. The validity of the proposed filter is verified through PSPICE simulations.
Abstract: The general idea behind the filter is to average a pixel
using other pixel values from its neighborhood, but simultaneously to
take care of important image structures such as edges. The main
concern of the proposed filter is to distinguish between any variations
of the captured digital image due to noise and due to image structure.
The edges give the image the appearance depth and sharpness. A
loss of edges makes the image appear blurred or unfocused.
However, noise smoothing and edge enhancement are traditionally
conflicting tasks. Since most noise filtering behaves like a low pass
filter, the blurring of edges and loss of detail seems a natural
consequence. Techniques to remedy this inherent conflict often
encompass generation of new noise due to enhancement.
In this work a new fuzzy filter is presented for the noise reduction
of images corrupted with additive noise. The filter consists of three
stages. (1) Define fuzzy sets in the input space to computes a fuzzy
derivative for eight different directions (2) construct a set of IFTHEN
rules by to perform fuzzy smoothing according to
contributions of neighboring pixel values and (3) define fuzzy sets in
the output space to get the filtered and edged image.
Experimental results are obtained to show the feasibility of the
proposed approach with two dimensional objects.
Abstract: The capturing of gel electrophoresis image represents
the output of a DNA computing algorithm. Before this image is being
captured, DNA computing involves parallel overlap assembly (POA)
and polymerase chain reaction (PCR) that is the main of this
computing algorithm. However, the design of the DNA
oligonucleotides to represent a problem is quite complicated and is
prone to errors. In order to reduce these errors during the design stage
before the actual in-vitro experiment is carried out; a simulation
software capable of simulating the POA and PCR processes is
developed. This simulation software capability is unlimited where
problem of any size and complexity can be simulated, thus saving
cost due to possible errors during the design process. Information
regarding the DNA sequence during the computing process as well as
the computing output can be extracted at the same time using the
simulation software.
Abstract: In many cases, there are some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in evaluating the performance of organizations. Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. Multi-periods input(MpI) and Multi-periods output(MpO) models are integrate models to calculate simple efficiency considering time lag effect. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. That is, efficient DMUs can’t be discriminated because their efficiency scores are same. Thus, this paper suggests a super-efficiency model for efficiency evaluation under the consideration of time lag effect based on the MpO model. A case example using a long term research project is given to compare the suggested model with the MpO model.