Fourth Local Conference on Parallel and Soft Computing
https://onlineresource.ucsy.edu.mm/handle/123456789/683
2024-03-28T18:38:01ZQuality of Service Routing in Mobile Ad-hoc Networks Using Multiple Parameters
https://onlineresource.ucsy.edu.mm/handle/123456789/1924
Quality of Service Routing in Mobile Ad-hoc Networks Using Multiple Parameters
Thaw, Mie Mie; Naing, Thinn
Mobile Ad-hoc network is an autonomous system
of mobile wireless nodes connected dynamically
without any preexisting infrastructure. Since the
nodes are mobile, the network topology changes
rapidly and unpredictably over time. The QoS
routing has challenging problems due to the
network’s dynamic topology and limited resources.
If only one single constraint condition is considered
when making routing decision, QoS can’t be
guaranteed because the constraint conditions may
change during a session and other factors can also
affect network performance. In this paper, hopcount,
bandwidth, and mobile speed are considered
for routing decision. Accounting for the uncertainty
of route information in ad-hoc networks, fuzzy logic
is adopted. The simulation is based upon Ad-hoc on
demand Distance Vector and considers that data are
always transmitted through the route with the lowest
delay for real-time traffic. The performance of
proposed scheme is evaluated with NS-2 simulator
in-terms of packet delivery ratio, and end-to-end
delay.
2009-12-30T00:00:00ZFeature Extraction and Recognition of Handwritten English Character Using Artificial Neural Network
https://onlineresource.ucsy.edu.mm/handle/123456789/1923
Feature Extraction and Recognition of Handwritten English Character Using Artificial Neural Network
Min, Ei Phyo; Thein, Yadana
This paper presents the development of English
Handwritten character recognition system, which
uses local and global features of English characters
by applying the concept of feature feeding. After each
character is extracted, the features are fed to the
recognition engine. A well-known Multi-layer
Feedforward neural network with backpropagation
learning algorithm is chosen for its fast processing
time and its good performance for pattern
recognition problems. Backpropagation Learning
algorithm is prefered for training of neural network.
Training set occurs of various English characters
collected from different people. The characters are
presented directly to the network and correctly sized
in pre-processing. In applying with free-hand
English single characters, the average recognition
rate of 91% has been achieved this confirms that the
proposed approach is suitable for the development of
English handwritten character recognition system.
Recognition percentage of the system is higher than
acceptable level. Input data, network parameters and
training period affect the result.
2009-12-30T00:00:00ZInformation Encryption Scheme Based on Visual Cryptography and Nonlinear Pseudorandom Sequence
https://onlineresource.ucsy.edu.mm/handle/123456789/1922
Information Encryption Scheme Based on Visual Cryptography and Nonlinear Pseudorandom Sequence
Yu, Thin Thin; Mya, Khin Than
Security requires the integration of people,
process, and technology. Strong information
encryption and decryption scheme are crucially
important for information technology. Nowadays,
secret sharing is one popular method for distributing
a secret amongst a group of participants, each of
which is allocated a share of the secret. This paper
presents a scheme which is derived from the
substitution of bits in the image by using nonlinear
pseudorandom sequence and visual cryptography
method and triple data encryption method. In our
method each participant has a unique modified cover
image called stego-image. Therefore these
participants are required to reconstruct the
encrypted secret data without destroying of its
secrecy. After that administrator decrypt the original
data. Therefore the administrator is the central
authority of the process. Experiments show the good
quality of the stego-image. The proposed scheme
also prevents anyone if steal all the shares will not
gaining information about the secret data.
2009-12-30T00:00:00ZAvailability Analysis on Virtualized Two-Node Cluster System: Ratio of Restoration Rate and Failure Rate
https://onlineresource.ucsy.edu.mm/handle/123456789/1921
Availability Analysis on Virtualized Two-Node Cluster System: Ratio of Restoration Rate and Failure Rate
Lwin, Thi Tar; Thein, Thandar
Worldwide, businesses continually increase
their dependence on IT systems for routine business
processes. The business processes which directly
rely on information systems and the supporting IT
infrastructure often require high levels of
availability and recovery in the case of planned
and unplanned outage. High availability has
achieved by host per host redundancy, a highly
expensive method with hardware and human costs.
Virtualization technologies promise cost reduction
through resource consolidation. By combining
virtualization and HA clustering, it is possible to
benefit from increased manageability and saving
from server consolidation through virtualization
without decreasing uptime of critical services.
Using analytical modeling, we analyze multiple
design choices when dual physical servers are used
to host multiple virtual machines. We use Markov
decision process when we are concerned about
optimal decision at any arbitrary time. Numerical
examples are presented to illustrate the
applicability of the model.
2009-12-30T00:00:00Z