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Traffic and Energy Saving Encrypted Search on Mobile Cloud

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To effectively support an encrypted search scheme with a high security level over cloud data, this paper introduces a new architecture, called TEES traffic and energy saving encrypted search, a bandwidth and energy efficient encrypted search architecture over mobile cloud. The proposed architecture offloads the computation from mobile devices to the cloud, and we further […]

Gray Scale and YCbCr Color Image Decompression and Denoising for JPEG 2017 ieee projects

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Digital color images are compressed using common standards such as JPEG. The JPEG compression is a lossy process, which means that most of the compression is obtained by loss of data, and the original image cannot be restored completely from the compressed object. The compression technique is used in various applications such as imaging and […]

A Scalable Data Chunk Similarity Based Compression Approach for Efficient Big Sensing Data Processing on Cloud

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Big sensing data is prevalent in both industry and scientific research applications where the data is generated with high volume and velocity. Cloud computing provides a promising platform for big sensing data processing and storage as it provides a flexible stack of massive computing, storage, and software services in a scalable manner. Current big sensing […]

Energy-Efficient Query Processing in Web Search Engines

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Web search engines are composed by thousands of query processing nodes, i.e., servers dedicated to process user queries. Such many servers consume a significant amount of energy, mostly accountable to their CPUs, but they are necessary to ensure low latencies, since users expect sub-second response times (e.g., 500 ms). However, users can hardly notice response […]

Collaboratively Training Sentiment Classifiers for Multiple Domains

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We propose a collaborative multi-domain sentiment classification approach to train sentiment classifiers for multiple domains simultaneously. In our approach, the sentiment information in different domains is shared to train more accurate and robust sentiment classifiers for each domain when labeled data is scarce. Specifically, we decompose the sentiment classifier of each domain into two components, […]

Query Expansion with Enriched User Profiles for Personalized Search Utilizing Folksonomy Data

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Query expansion has been widely adopted in Web search as a way of tackling the ambiguity of queries. Personalized search utilizing folksonomy data has demonstrated an extreme vocabulary mismatch problem that requires even more effective query expansion methods. Co-occurrence statistics, tag-tag relationships, and semantic matching approaches are among those favored by previous research. However, user […]

Enabling Kernel-Based Attribute-Aware Matrix Factorization for Rating Prediction

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In recommender systems, one key task is to predict the personalized rating of a user to a new item and then return the new items having the top predicted ratings to the user. Recommender systems usually apply collaborative filtering techniques (e.g., matrix factorization) over a sparse user-item rating matrix to make rating prediction. However, the […]

IEEE Projects 2016 Dot Net Information and Forensic Title Topics Abstract List

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  S. No.      IEEE TITLE                      ABSTRACT    IEEE YEAR 1 Fast Detection of Transformed Data Leaks The leak of sensitive data on computer systems poses a serious threat to organizational security. Statistics show that the lack of proper encryption on files and communications due to human errors is one of the leading causes […]

IEEE Projects 2016 Java Network Security Title Topics Abstract

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  S. No.      IEEE TITLE                      ABSTRACT    IEEE YEAR 1 A Pseudonym Management System to Achieve Anonymity in Vehicular Ad Hoc Networks In this paper we propose a framework for providing anonymity to communicating cars in VANETs. The anonymity is accomplished based on a system of pseudonym generation, distribution, and replenishing. The road […]