Active Learning of Constraints for Semi-Supervised Clustering Abstract?Active Learning of Constraints for Semi-Supervised Clustering. Semi-supervised clustering aims to improve clustering performance by considering user supervision in the form of pairwise constraints. In this paper, we study the active learning problem of selecting pairwise must-link and cannot-link constraints for semi-supervised clustering. We consider active learning in…
Active Mode Sub-Clock Power Gating Abstract?This paper presents a new technique, called sub-clock power gating, for reducing leakage power in digital circuits. The proposed technique works concurrently with voltage and frequency scaling and power reduction is achieved by power gating within the clock cycle during active mode unlike traditional power gating which is applied during…
Adaptive and Channel Aware Detection of Selective Forwarding Attacks in Wireless Sensor Networks Abstract?Wireless sensor networks (WSNs) are vulnerable to selective forwarding attacks that can maliciously drop a subset of forwarding packets to degrade network performance and jeop-ardize the information integrity. < final year projects > [numbers_sections number=”1″ title=”Including =Packages=” last=”no” ] Complete Source Code…
Adaptive and Energy Efficient Context Abstract? Adaptive and Energy Efficient Context. This paper presents a novel framework that includes an inhomogeneous (time-variant) Hidden Markov Model (HMM) and learning from data concepts. The framework either recognizes or estimates user contextual inferences called `user states’ within the concept of Human Activity Recognition (HAR) for future context-aware <...
Adaptive and Random Partitioning Software Testing Abstract?Random testing (RT) and subdomain testing are two major software testing strategies. Their simplicity makes them likely the most efficient testing strategies with respect to the time required for test case selection. However, the disadvantage of RT is its defect detection effectiveness. Adaptive testing (AT) is a feedback-based software…
Adaptive Image Denoising by Targeted Databases Abstract? Adaptive Image Denoising by Targeted Databases. A data-dependent denoising procedure to restore noisy images. Different from existing denoising algorithms which search for patches from either the noisy image or a generic database, the new algorithm ?nds patches from a database that contains relevant patches. We formulate the denoising…
Adaptive Processing for Distributed Skyline Queries over Uncertain Data Abstract? Query processing over uncertain data has gained growing attention, because it is necessary to deal with uncertain data in many real-life applications. In this paper, we investigate skyline queries over uncertain data in distributed environments < Final Year Projects 2016 > DSUD query whose research…
Adaptive SLA-Aware Algorithms for Provisioning Shared Mesh Optical Networks Abstract? Adaptive SLA-Aware Algorithms for Provisioning Shared Mesh Optical Networks. The paper presents a priority-aware algorithm to preserve higher priority requests over optical mesh networks. The paper discusses an algorithm to improve resource utilization and availability performance of shared mesh optical networks. The algorithm benefits from…
Adding Geospatial Data Provenance into SDI?A Service-Oriented Approach Abstract? Geospatial data provenance records the derivation history of a geospatial data product. It is important in evaluating the quality of data products. In a Geospatial Web Service environment where data are often disseminated and processed widely and frequently in an unpredictable way, it is even more…
ADR coverage organization Abstract?New drugs are regularly introduced for treatment, diagnosis or prevention of diseases. Adverse drug reactions < Final Year Projects 2016 > can be seen in clinical practice with both new as well as marketed medicines. Spontaneous reporting of Adverse drug reactions is commonly practiced method for monitoring of Adverse drug reactions. Healthcare…
ADR Reporting Abstract?Spontaneous reporting systems of adverse drug events have been widely established in many countries to collect as could as possible all adverse drug events to facilitate the detection of suspected ADR signals via some statistical or data mining methods. Unfortunately, due to privacy concern or other reasons, the reporters sometimes may omit consciously…
Advanced probabilistic approach for network intrusion forecasting and detection Abstract? Advanced probabilistic approach for network intrusion forecasting and detection. This study aims to propose a probabilistic approach for detecting network intrusions using Bayesian Networks (BNs). Three variations of BN, namely, Na?ve Bayesian Network (NBC), Learned BN, and hand-crafted BN, were evaluated and from which, an…
