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Articles 1 - 6 of 6
Full-Text Articles in Engineering
Quorum Blockchain Stress Evaluation In Different Environments, Daniel P. Mera
Quorum Blockchain Stress Evaluation In Different Environments, Daniel P. Mera
Student Theses
In today’s world, the Blockchain technology is used for different purposes has brought an increment in the development of different Blockchain platforms, services, and utilities for storing data securely and efficiently. Quorum Blockchain, an Ethereum fork created by JPMorgan Chase, has placed itself in one of the widely used, efficient and trustful Blockchain platforms available today. Because of the importance which Quorum is contributing to the world, it is important to test and measure different aspects of the platform, not only to prove how efficient the software can be but as well as to have a clear view on what …
Efficient Private Information Retrieval, Konstantinos Nikolopoulos
Efficient Private Information Retrieval, Konstantinos Nikolopoulos
Dissertations, Theses, and Capstone Projects
A vast amount of today's Internet users' on line activities consists of queries to various types of databases. From traditional search engines to modern cloud based services, a person's everyday queries over a period of time on various data sources, will leave a trail visible to the query processor, which can reveal significant and possibly sensitive information about her. Private Information Retrieval (PIR) algorithms can be leveraged for providing perfect privacy to users' queries, though at a restrictive computational cost. In this work, we consider today's highly distributed computing environments, as well as certain secure-hardware devices, for optimizing existing PIR …
Fashion Merchandising: An Augmented Reality, Naeha A. Sayed
Fashion Merchandising: An Augmented Reality, Naeha A. Sayed
Dissertations, Theses, and Capstone Projects
There is a continuous and constant transformation in the field of Augmented Reality (AR), both in the Retail, and the Manufacturing sector. It has started to influence everything from fashion runway shows to online shopping. Consumers dynamics have shifted in the fashion industry, the ways becoming more dominant than the old observant ones- the simple buying experience no longer satisfies them. Due to the emergence of the new digital platforms and technological enhancements, the consumers are looking for more- be it a more exciting buying experience or more user interaction or more enhanced products. This technological change starts with the …
A Purely Defeasible Argumentation Framework, Zimi Li
A Purely Defeasible Argumentation Framework, Zimi Li
Dissertations, Theses, and Capstone Projects
Argumentation theory is concerned with the way that intelligent agents discuss whether some statement holds. It is a claim-based theory that is widely used in many areas, such as law, linguistics and computer science. In the past few years, formal argumentation frameworks have been heavily studied and applications have been proposed in fields such as natural language processing, the semantic web and multi-agent systems. Studying argumentation provides results which help in developing tools and applications in these areas. Argumentation is interesting as a logic-based approach to deal with inconsistent information. Arguments are constructed using a process like logical inference, with …
Unsupervised Feature Learning For Point Cloud By Contrasting And Clustering With Graph Convolutional Neural Network, Ling Zhang
Dissertations and Theses
Recently, deep graph neural networks (GNNs) have attracted significant attention for point cloud understanding tasks, including classification, segmentation, and detection. However, the training of such deep networks still requires a large amount of annotated data, which is both expensive and time-consuming. To alleviate the cost of collecting and annotating large-scale point cloud datasets, we propose an unsupervised learning approach to learn features from unlabeled point cloud ”3D object” dataset by using part contrasting and object clustering with GNNs. In the contrast learning step, all the samples in the 3D object dataset are cut into two parts and put into a …
Integrating Multi-Source Weather Data For Deep Learning, Haidar A. Alanbari Mr
Integrating Multi-Source Weather Data For Deep Learning, Haidar A. Alanbari Mr
Dissertations and Theses
Big Data has been playing a major role in the domain of Deep Learning applications as many companies and institutions continue to find solutions and extract certain trends in fields of climate change, weather forecasting and meteorology. This project extracts weather events data from multiple data sources that are supported by National Centers for Environmental information (NCEI) [1] and Amazon Web Services (AWS) [2]. Data sources include Next-Generation NEXRAD [3] Doppler radar reflectivity, GOES-16 [4] multi-channel satellite imagery and NCEI [1] storm events. Then, it integrates and refines data in proper formats to be fed to the open-source Detectron [5] …