Fat-Tree-Based Optical Interconnection Networks Under Crosstalk Noise Constraint Abstract? Fat-Tree-Based Optical Interconnection Networks Under Crosstalk Noise Constraint. Optical networks-on-chip < Final Year Projects 2016 > ONoCs have shown the potential to be substituted for electronic networks-on-chip (NoCs) to bring substantially higher bandwidth and more efficient power consumption in both on- and off-chip communication. However, basic…
Fault based Test Minimization Using Genetic Algorithm for Two Stage Combinational Circuits Abstract? Fault based Test Minimization Using Genetic Algorithm for Two Stage Combinational Circuits. The field of digital systems has undergone a major revolution in recent decades. Circuits are shrinking in physical size while growing both in speed and range of capabilities. This rapid…
Fault Tolerant Localization and Tracking of Multiple Sources in WSNs using Binary Data Abstract?Fault Tolerant Localization and Tracking of Multiple Sources in WSNs using Binary Data This paper investigates the use of a Wireless Sensor Network for localizing and tracking multiple event sources (targets) using only binary data. Due to the simple nature of the…
Feature Based opinion mining through ontologies Abstract?Feature Based opinion mining through ontologies. As e-commerce is becoming more and more popular, the number of customer reviews about a product grows rapidly. So it is difficult for a potential customer to browse through large numbers of reviews for items of interest and make a decision about some…
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Feature Selection and Classification of Microarray Data using MapReduce based ANOVA and K-Nearest Neighbor Abstract? Feature Selection and Classification of Microarray Data using MapReduce based ANOVA and K-Nearest Neighbor. The major drawback of microarray data is the ?curse of dimensionality problem?, this hinders the useful information of dataset and leads to computational instability. Therefore, selecting…
Feature Selection for Machine Learning: Comparing a Correlation based Filter Approach to the Wrapper Abstract? Feature selection is often an essential data processing step prior to applying a learning algorithm. The removal of irrelevant and redundant information often improves the performance of machine learning algorithms. There are two common approaches:< Final Year Projects >…
Feature Selection via Global Redundancy Minimization Abstract? Feature Selection via Global Redundancy Minimization. Feature selection has been an important research topic in data mining, because the real data sets often have high dimensional features, such as the bioinformatics and text mining applications. Many existing ?lter feature selection methods rank features by optimizing certain feature ranking…
Feature selection with dynamic mutual information Abstract? Feature selection with dynamic mutual information.Feature selection plays an important role in data mining and pattern recognition, especially for large scale data. During past years, various metrics have been proposed to measure the relevance between different features. Since mutual information is nonlinear and can effectively represent the dependencies…
Feature-Based Image Patch Approximation for Lung Tissue Classification Abstract? Feature-Based Image Patch Approximation for Lung Tissue Classification. In this paper, we propose a new classification method for five categories of lung tissues in high-resolution computed tomography (HRCT) images, with feature-based image patch approximation. We design two new feature descriptors for higher feature descriptiveness, namely…
Fertilizer and Pestiside Management Abstract? Fertilizer and Pestiside Management. This study highlights energy savings that could be realized in a fertilizer plant through application of various energy management options to reduce energy expenditure through efficient use of available energy resources. Energy audits were done as reference point for monitoring progress of measures put in place….
Filtering Image-based Spam Using Multifractal Analysis and Active Learning Feedback-Driven Semi-Supervised Support Vector Machine Abstract?Filtering Image-based Spam Using Multifractal Analysis and Active Learning Feedback-Driven Semi-Supervised Support Vector Machine. Traditional anti-spam technologies can’t block image-based spam because spammers employ a variety of image creation and randomization algorithms to make the message fully legible by the…
Finding Usability And Communicapility Problems For Transactional Web Application Abstract?Finding Usability And Communicapility Problems For Transactional Web Application. Today the amount of web applications has grown exponentially and the number of both novice and experienced users decided to experiment with these applications has increased. However, there has been a large increase in problems when the…
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