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SSD Technology is used to read/write data to the external device with high speed and low power. A lossless LZ77 data compression technique is used here in order to retain the information content by removing data redundancy and also employs a text window in congestion with look-ahead buffer to serve as a dictionary. In the proposed technique the unmatched string present in the dictionary are encoded...
Network-on-Chip (NoC) based systems are becoming more acceptable nowadays compared to System-on-Chips (SoC) for nanoscale system development due to increasing scaling. The weakness of wired communication leads to insertion of wireless links in NoC Systems to mitigate the multihop problem. Present work provides significant improvements of NoC and Wireless NoC (WNoCs) systems contributing salient techniques...
Analysis of time series data is important. Association rule mining algorithms like Apriori Tid can be implemented over time series to find out the frequent item sets. In this paper, a modified version of Apriori Tid is proposed. Both the association rule mining algorithms Apriori Tid and modified Apriori Tid are implemented over time series data. Rainfall data related to North Eastern India has been...
Wireless ad-hoc network is a resource constrained network applied in many applications. Clustering is considered to be most competent technique in order to attain firm performance and improved utilization of energy. Traditional clustering tactics elect a cluster coordinator commonly known as cluster heads so as to manage the whole cluster in terms of data collection, data fusion and transmission of...
Studies on Flexible-Grid technology reveals that it provides desirable solution for next generation high-speed network design. Multicast Routing and Spectrum assignment (MRSA) in Flexible-Grid Optical Networks (alternately Elastic Optical Networks) generates a multicast tree for each multicast session request and spectrum frequency slots are allocated to each of the edge of the multicast tree. Orthogonal...
WSNs are often besieged with issues related to interference when transmissions of two or more closely located sensor nodes interfere with each other. This forces the data aggregating nodes to receive distorted, faulty or interference ridden signals, which severely affects the fidelity of data being aggregated. If such faults are not arrested at the source, interference laden transmissions or Interference-Faults...
The Software Defined Network (SDN), is the next generation Internet technology, which not only solve the ossification of the Internet, but also creates new innovations and simplify the network management. The key idea behind SDN is separation of control plane from data plane, as a result devices in the data plane becomes the forwarding device and transfer all the decision making activities in a centralized...
It's Big Data era. In this epoch, the terabytes of data are a dime a dozen as well as large metadata size. The large scale metadata size becomes a barrier in the era of exascale computation. However, a fine-tuning, and a well designing of metadata can enhance the performance of a file system. Therefore, the large scale metadata server (MDS) design becomes key research point now-a-days. The designing...
Cloud computing is an emerging computing tool in which resources accessed as a service over Internet on pay for use basis. Most of the organization are changing their storage server to cloud server without any botheration. It is a great challenge for the cloud service provider to attract the customers to store their sensitive data/file in the cloud storage. Service provisioning with respect to privacy...
Cloud computing is an emerging computing tool in which resources accessed as a service over Internet on pay for use basis. Most of the service providers are changing their server storage to cloud storage. It is a great challenge for the service provider to attract the customers to store their sensitive data/file in the cloud storage. Service provisioning with respect to privacy preservation and data...
Matrix Factorization is one of the popular approaches for learning the latent characteristics from the sparse utility matrix of recommendation systems. In recent times, Coordinate Descent based matrix factorization approach (CCD) have outperformed the other existing approaches such as Alternating Least Squares (ALS) and Stochastic Gradient Descent (SGD). While ALS is not scalable due to its cubic...
Sentiment Mining refers to extraction of public sentiment, typically from a set of texts or documents. The present work aims at gaining insights into sentiment mining on tweets using Machine Learning and Natural Language Processing techniques. We propose a lexicon-based sentiment scoring method, and use it in combination with Support Vector Machine (SVM) classifier as a two-step method for sentiment...
Text categorization entails making a decision on whether a document belongs to a set of pre-specified classes of other documents. This can be in a supervised way in classification tasks or unsupervised reminiscent of clustering related tasks. Categorization can be a challenging task especially when the discriminating words are large. K-Nearest Neighbor is an instance based learning algorithm that...
Text Summarization is a way of determining the key concepts that are covered in the given text under consideration. Various techniques have been presented in literature and many are used in commercially available systems. The primary aim of the present work is to find efficacy of using sentiments for text summarization. In this work we present a computationally efficient technique based on sentiments...
Hybrid technique is implemented in this paper to identify the fault location in a 20 KV, 5 km underground cable line with 7.5 MW inductive loads at the delivery end. The projected fault location technique implements properly sampled values of singlecycle post faulty voltage and current signal as of the relayingtermination of the underground cable. Thereafter signaldecomposition has been carried out...
Large amount of data is created and stored in electronic media. Agriculture is no exception. Large unprocessed text are available on the various Government and other websites. Despite of large volume and availability, this data is underutilized. This data should be converted to an effective form so as to facilitate better information dissemination. Ontology is an efficient medium to carry out this...
Each and every company are interested to know about the status of performance in their business. Bankruptcy prediction is an important issue and it plays a vital role in creating decisions in the field of corporate and financial organization. It has its influence on both economic as well as social factors, e.g., investors, creditors, government, managers, employees, etc. So, it is important and useful...
Trademark retrieval systems have been a well researched field however majority of these researches have been done on device trademarks and do not consider the presence of text embedded within trademark images as in case of composite marks. In this work a unified retrieval system has been proposed and implemented for composite trademarks. The technique is invariant to font size, font style and orientations,...
The ever increasing need to provide a suitable derivative of a term governed by context where derivative can either stemmed word or hypernym of a word has spurred a lot of research activities in information retrieval communities. In this paper, we are concerned with providing context centric derivatives of a term which can be useful in any search engine for obtaining better search results. Personalized...
Data mining is an emerging field of research in Information Technology as well as in agriculture. The present study focus on the applications of data mining techniques in tea plantations in the face of climatic change to help the farmer in taking decision for farming and achieving the expected economic return. This paper presents an analysis using data mining techniques for estimating the future yield...
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