Abstract: Flow forming is widely used in many industries, especially in defence technology industries. Pressure vessels requirements are high precision, light weight, seamless and optimum strength. For large pressure vessels, flow forming by 3 rollers machine were used. In case of long range rocket motor case flow forming and welding of pressure vessels have been used for manufacturing. Due to complication of welding process, researchers had developed 4 meters length pressure vessels without weldment by 4 rollers flow forming machine. Design and preparation of preform work pieces are performed. The optimization of flow forming parameter such as feed rate, spindle speed and depth of cut will be discussed. The experimental result shown relation of flow forming parameters to quality of flow formed tube and prototype pressure vessels have been made.
Abstract: This paper outlines the application of Knowledge Management (KM) principles in the context of Educational institutions. The paper caters to the needs of the engineering institutions for imparting quality education by delineating the instruction delivery process in a highly structured, controlled and quantified manner. This is done using a software tool EDULOGIC+. The central idea has been based on the engineering education pattern in Indian Universities/ Institutions. The data, contents and results produced over contiguous years build the necessary ground for managing the related accumulated knowledge. Application of KM has been explained using certain examples of data analysis and knowledge extraction.
Abstract: A technique proposed for the automatic detection
of spikes in electroencephalograms (EEG). A multi-resolution
approach and a non-linear energy operator are exploited. The
signal on each EEG channel is decomposed into three sub bands
using a non-decimated wavelet transform (WT). The WT is a
powerful tool for multi-resolution analysis of non-stationary signal
as well as for signal compression, recognition and restoration.
Each sub band is analyzed by using a non-linear energy operator,
in order to detect spikes. A decision rule detects the presence of
spikes in the EEG, relying upon the energy of the three sub-bands.
The effectiveness of the proposed technique was confirmed by
analyzing both test signals and EEG layouts.
Abstract: The power system network is becoming more
complex nowadays and it is very difficult to maintain the stability
of the system. Today-s enhancement of technology makes it
possible to include new energy storage devices in the electric
power system. In addition, with the aid of power electronic
devices, it is possible to independently exchange active and
reactive power flow with the utility grid. The main purpose of this
paper proposes a Proportional – Integral (PI) control based 48 –
pulse Inverter based Static Synchronous Series Compensator
(SSSC) with and without Superconducting Magnetic Energy
Storage (SMES) used for enhancing the transient stability and
regulating power flow in automatic mode. Using a test power
system through the dynamic simulation in Matlab/Simulink
platform validates the performance of the proposed SSSC with and
without SMES system.
Abstract: Microstrip lines, widely used for good reason, are
broadband in frequency and provide circuits that are compact and
light in weight. They are generally economical to produce since they
are readily adaptable to hybrid and monolithic integrated circuit (IC)
fabrication technologies at RF and microwave frequencies. Although,
the existing EM simulation models used for the synthesis and
analysis of microstrip lines are reasonably accurate, they are
computationally intensive and time consuming. Neural networks
recently gained attention as fast and flexible vehicles to microwave
modeling, simulation and optimization. After learning and
abstracting from microwave data, through a process called training,
neural network models are used during microwave design to provide
instant answers to the task learned.This paper presents simple and
accurate ANN models for the synthesis and analysis of Microstrip
lines to more accurately compute the characteristic parameters and
the physical dimensions respectively for the required design
specifications.
Abstract: Estimation of runoff water quality parameters is required to determine appropriate water quality management options. Various models are used to estimate runoff water quality parameters. However, most models provide event-based estimates of water quality parameters for specific sites. The work presented in this paper describes the development of a model that continuously simulates the accumulation and wash-off of water quality pollutants in a catchment. The model allows estimation of pollutants build-up during dry periods and pollutants wash-off during storm events. The model was developed by integrating two individual models; rainfall-runoff model, and catchment water quality model. The rainfall-runoff model is based on the time-area runoff estimation method. The model allows users to estimate the time of concentration using a range of established methods. The model also allows estimation of the continuing runoff losses using any of the available estimation methods (i.e., constant, linearly varying or exponentially varying). Pollutants build-up in a catchment was represented by one of three pre-defined functions; power, exponential, or saturation. Similarly, pollutants wash-off was represented by one of three different functions; power, rating-curve, or exponential. The developed runoff water quality model was set-up to simulate the build-up and wash-off of total suspended solids (TSS), total phosphorus (TP) and total nitrogen (TN). The application of the model was demonstrated using available runoff and TSS field data from road and roof surfaces in the Gold Coast, Australia. The model provided excellent representation of the field data demonstrating the simplicity yet effectiveness of the proposed model.
Abstract: This research focuses on the effect of weight
percentage variation and size variation of MgFeSi added,
gating system design and reaction chamber design on inmold
process. By using inmold process, well-known problem of
fading is avoided because the liquid iron reacts with
magnesium in the mold and not, as usual, in the ladle. During
the pouring operation, liquid metal passes through the
chamber containing the magnesium, where the reaction of the
metal with magnesium proceeds in the absence of atmospheric
oxygen [1].In this paper, the results of microstructural
characteristic of ductile iron on this parameters are mentioned.
The mechanisms of the inmold process are also described [2].
The data obtained from this research will assist in producing
the vehicle parts and other machinery parts for different
industrial zones and government industries and in transferring
the technology to all industrial zones in Myanmar. Therefore,
the inmold technology offers many advantages over traditional
treatment methods both from a technical and environmental,
as well as an economical point of view. The main objective of
this research is to produce ductile iron castings in all industrial
sectors in Myanmar more easily with lower costs. It will also
assist the sharing of knowledge and experience related to the
ductile iron production.
Abstract: Facial expression analysis plays a significant role for
human computer interaction. Automatic analysis of human facial
expression is still a challenging problem with many applications. In
this paper, we propose neuro-fuzzy based automatic facial expression
recognition system to recognize the human facial expressions like
happy, fear, sad, angry, disgust and surprise. Initially facial image is
segmented into three regions from which the uniform Local Binary
Pattern (LBP) texture features distributions are extracted and
represented as a histogram descriptor. The facial expressions are
recognized using Multiple Adaptive Neuro Fuzzy Inference System
(MANFIS). The proposed system designed and tested with JAFFE
face database. The proposed model reports 94.29% of classification
accuracy.
Abstract: In the world of Peer-to-Peer (P2P) networking
different protocols have been developed to make the resource sharing
or information retrieval more efficient. The SemPeer protocol is a
new layer on Gnutella that transforms the connections of the nodes
based on semantic information to make information retrieval more
efficient. However, this transformation causes high clustering in the
network that decreases the number of nodes reached, therefore the
probability of finding a document is also decreased. In this paper we
describe a mathematical model for the Gnutella and SemPeer
protocols that captures clustering-related issues, followed by a
proposition to modify the SemPeer protocol to achieve moderate
clustering. This modification is a sort of link management for the
individual nodes that allows the SemPeer protocol to be more
efficient, because the probability of a successful query in the P2P
network is reasonably increased. For the validation of the models, we
evaluated a series of simulations that supported our results.
Abstract: The various applications of VLSI circuits in highperformance
computing, telecommunications, and consumer
electronics has been expanding progressively, and at a very hasty
pace. This paper describes a new model for partitioning a circuit
using DBSCAN and fuzzy ARTMAP neural network. The first step
is concerned with feature extraction, where we had make use
DBSCAN algorithm. The second step is the classification and is
composed of a fuzzy ARTMAP neural network. The performance of
both approaches is compared using benchmark data provided by
MCNC standard cell placement benchmark netlists. Analysis of the
investigational results proved that the fuzzy ARTMAP with
DBSCAN model achieves greater performance then only fuzzy
ARTMAP in recognizing sub-circuits with lowest amount of
interconnections between them The recognition rate using fuzzy
ARTMAP with DBSCAN is 97.7% compared to only fuzzy
ARTMAP.
Abstract: Intrapreneurship, a term used to describe
entrepreneurship within existing organizations, has been
acknowledged in international literature and practice as a vital
element of economic and organizational growth, success and
competitiveness and can be considered as a unique competitive
advantage. The purpose of the paper is, first, to provide a
comprehensive analysis of the concept of intrapreneurship, and,
second, to highlight the need for a different approach in the research
on the field of intrapreneurship. Concluding, the paper suggests
directions for future research.
Abstract: The experimental and theoretical results of a ZVS
(Zero Voltage Switching) isolated flyback DC-DC converter using
multilayered coreless PCB step down 2:1 transformer are presented.
The performance characteristics of the transformer are shown which
are useful for the parameters extraction. The measured energy
efficiency of the transformer is found to be more than 94% with the
sinusoidal input voltage excitation. The designed flyback converter
has been tested successfully upto the output power level of 10W,
with a switching frequency in the range of 2.7MHz-4.3MHz. The
input voltage of the converter is varied from 25V-40V DC.
Frequency modulation technique is employed by maintaining
constant off time to regulate the output voltage of the converter. The
energy efficiency of the isolated flyback converter circuit under ZVS
condition in the MHz frequency region is found to be approximately
in the range of 72-84%. This paper gives the comparative results in
terms of the energy efficiency of the hard switched and soft switched
flyback converter in the MHz frequency region.
Abstract: Generalized Center String (GCS) problem are
generalized from Common Approximate Substring problem
and Common substring problems. GCS are known to be
NP-hard allowing the problems lies in the explosion of
potential candidates. Finding longest center string without
concerning the sequence that may not contain any motifs is
not known in advance in any particular biological gene
process. GCS solved by frequent pattern-mining techniques
and known to be fixed parameter tractable based on the
fixed input sequence length and symbol set size. Efficient
method known as Bpriori algorithms can solve GCS with
reasonable time/space complexities. Bpriori 2 and Bpriori
3-2 algorithm are been proposed of any length and any
positions of all their instances in input sequences. In this
paper, we reduced the time/space complexity of Bpriori
algorithm by Constrained Based Frequent Pattern mining
(CBFP) technique which integrates the idea of Constraint
Based Mining and FP-tree mining. CBFP mining technique
solves the GCS problem works for all center string of any
length, but also for the positions of all their mutated copies
of input sequence. CBFP mining technique construct TRIE
like with FP tree to represent the mutated copies of center
string of any length, along with constraints to restraint
growth of the consensus tree. The complexity analysis for
Constrained Based FP mining technique and Bpriori
algorithm is done based on the worst case and average case
approach. Algorithm's correctness compared with the
Bpriori algorithm using artificial data is shown.
Abstract: How to efficiently assign system resource to route the
Client demand by Gateway servers is a tricky predicament. In this
paper, we tender an enhanced proposal for autonomous recital of
Gateway servers under highly vibrant traffic loads. We devise a
methodology to calculate Queue Length and Waiting Time utilizing
Gateway Server information to reduce response time variance in
presence of bursty traffic.
The most widespread contemplation is performance, because
Gateway Servers must offer cost-effective and high-availability
services in the elongated period, thus they have to be scaled to meet
the expected load. Performance measurements can be the base for
performance modeling and prediction. With the help of performance
models, the performance metrics (like buffer estimation, waiting
time) can be determined at the development process.
This paper describes the possible queue models those can be
applied in the estimation of queue length to estimate the final value
of the memory size. Both simulation and experimental studies using
synthesized workloads and analysis of real-world Gateway Servers
demonstrate the effectiveness of the proposed system.
Abstract: This paper deals with the application of Principal Component Analysis (PCA) and the Hotelling-s T2 Chart, using data collected from a drinking water treatment process. PCA is applied primarily for the dimensional reduction of the collected data. The Hotelling-s T2 control chart was used for the fault detection of the process. The data was taken from a United Utilities Multistage Water Treatment Works downloaded from an Integrated Program Management (IPM) dashboard system. The analysis of the results show that Multivariate Statistical Process Control (MSPC) techniques such as PCA, and control charts such as Hotelling-s T2, can be effectively applied for the early fault detection of continuous multivariable processes such as Drinking Water Treatment. The software package SIMCA-P was used to develop the MSPC models and Hotelling-s T2 Chart from the collected data.
Abstract: In this paper a novel approach for generalized image
retrieval based on semantic contents is presented. A combination of
three feature extraction methods namely color, texture, and edge
histogram descriptor. There is a provision to add new features in
future for better retrieval efficiency. Any combination of these
methods, which is more appropriate for the application, can be used
for retrieval. This is provided through User Interface (UI) in the
form of relevance feedback. The image properties analyzed in this
work are by using computer vision and image processing algorithms.
For color the histogram of images are computed, for texture cooccurrence
matrix based entropy, energy, etc, are calculated and for
edge density it is Edge Histogram Descriptor (EHD) that is found.
For retrieval of images, a novel idea is developed based on greedy
strategy to reduce the computational complexity. The entire system
was developed using AForge.Imaging (an open source product),
MATLAB .NET Builder, C#, and Oracle 10g. The system was tested
with Coral Image database containing 1000 natural images and
achieved better results.
Abstract: Facial recognition and expression analysis is rapidly
becoming an area of intense interest in computer science and humancomputer
interaction design communities. The most expressive way
humans display emotions is through facial expressions. In this paper
skin and non-skin pixels were separated. Face regions were extracted
from the detected skin regions. Facial expressions are analyzed from
facial images by applying Gabor wavelet transform (GWT) and
Discrete Cosine Transform (DCT) on face images. Radial Basis
Function (RBF) Network is used to identify the person and to classify
the facial expressions. Our method reliably works even with faces,
which carry heavy expressions.
Abstract: The impact of OO design on software quality
characteristics such as defect density and rework by mean of
experimental validation. Encapsulation, inheritance, polymorphism,
reusability, Data hiding and message-passing are the major attribute
of an Object Oriented system. In order to evaluate the quality of an
Object oriented system the above said attributes can act as indicators.
The metrics are the well known quantifiable approach to express any
attribute. Hence, in this paper we tried to formulate a framework of
metrics representing the attributes of object oriented system.
Empirical Data is collected from three different projects based on
object oriented paradigms to calculate the metrics.
Abstract: Twist drills are geometrical complex tools and thus various researchers have adopted different mathematical and experimental approaches for their simulation. The present paper acknowledges the increasing use of modern CAD systems and using the API (Application Programming Interface) of a CAD system, drilling simulations are carried out. The developed DRILL3D software routine, creates parametrically controlled tool geometries and using different cutting conditions, achieves the generation of solid models for all the relevant data involved (drilling tool, cut workpiece, undeformed chip). The final data derived, consist a platform for further direct simulations regarding the determination of cutting forces, tool wear, drilling optimizations etc.
Abstract: This paper proposes an active soft-switching circuit for
bridge converters aiming to improve the power conversion efficiency.
The proposed circuit achieves loss-less switching for both main and
auxiliary switches without increasing the main switch current/voltage
rating. A winding coupled to the primary of power transformer
ensures ZCS for the auxiliary switches during their turn-off. A 350 W,
100 kHz phase shifted full bridge (PSFB) converter is built to validate
the analysis and design. Theoretical loss calculations for proposed
circuit is presented. The proposed circuit is compared with passive
soft switched PSFB in terms of efficiency and loss in duty cycle.