A Survey of Checkpointing Algorithms in Mobile Ad Hoc Network

Checkpoint is defined as a fault tolerant technique that is a designated place in a program at which normal processing is interrupted specifically to preserve the status information necessary to allow resumption of processing at a later time. If there is a failure, computation may be restarted from the current checkpoint instead of repeating the computation from beginning. Checkpoint based rollback recovery is one of the widely used technique used in various areas like scientific computing, database, telecommunication and critical applications in distributed and mobile ad hoc network. The mobile ad hoc network architecture is one consisting of a set of self configure mobile hosts capable of communicating with each other without the assistance of base stations. The main problems of this environment are insufficient power and limited storage capacity, so the checkpointing is major challenge in mobile ad hoc network. This paper presents the review of the algorithms, which have been reported for checkpointing approaches in mobile ad hoc network

Early Prediction of ‘At-Risk’ Learners on Virtual Platforms using ODFs

This Learning analytics are one of the most important assistance tools used by educators for early identification of at-risk learners. Researchers have used many AI based tools for monitoring learning and improving learner’s performances by using any early intervention strategies to reduce dropout rates on online platforms that lacks face-to-face acknowledgement and feedback. Online platforms have Online Discussion Forums (ODFs) where a learner can post his queries and interact with other learners or the instructor. It becomes one of the useful indicators of tracking participation of a learner in the teaching learning process. Learners who actively participate in interaction on these online discussion platforms and contribute to the learning content required by other users are believed to give better performance as compared to those who do not participate in forum discussion. This paper focuses on the aspects of forum discussion like frequency of posts, sentimental analysis of forum post, number of threads initiated or replied to, and also how recent the post to predict the learners who could be at-risk of dropping out. The prediction model uses a data set from secondary resource. Various metrics like Confusion Matrix and Loss curve are employed to measure the accuracy of the model. Results indicate that data captured using forum posts can help in early identification of At-risk Learners

Perfect Compression Technique in Combination with Training Algorithm and Wavelets

Abstract — Wavelets have emerged as powerful tools for signal coding especially bio-signal processing. Wavelet transform is used to represent the signal to some other time–frequency representation better suited for detecting and removing redundancies The Neural Networks are good alternative for solving many complex problems. In this paper multi-layer neural network has been employed to achieve image compression A novel algorithm for neural network with different techniques is proposed in this paper. Experimental results show that this algorithm outperforms than other coders such as SPIHT EZW STW exits in the literature in terms of simplicity and coding efficiency by successive partition the wavelet coefficients in the space frequency domain and send them using adaptive decimal to binary conversion. Spatial-orientation tree wavelet (STW) and Embedded Zero tree Wavelet (EZW) has been proposed as a method for effective and efficient embedded image coding. This method holds good for au important features like PSNR, MSE, BPP, CR, image size. SPHIT has been successfully used in many applications. (The techniques are compressed by using the performance parameter