https://onlineresource.ucsy.edu.mm/handle/123456789/683 Mon, 08 Jun 2026 10:28:23 GMT 2026-06-08T10:28:23Z 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. Wed, 30 Dec 2009 00:00:00 GMT https://onlineresource.ucsy.edu.mm/handle/123456789/1924 2009-12-30T00:00:00Z 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. Wed, 30 Dec 2009 00:00:00 GMT https://onlineresource.ucsy.edu.mm/handle/123456789/1923 2009-12-30T00:00:00Z 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. Wed, 30 Dec 2009 00:00:00 GMT https://onlineresource.ucsy.edu.mm/handle/123456789/1922 2009-12-30T00:00:00Z 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. Wed, 30 Dec 2009 00:00:00 GMT https://onlineresource.ucsy.edu.mm/handle/123456789/1921 2009-12-30T00:00:00Z