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Using Hybrid Machine Learning Models For Stock Price Forecasting And Trading., Ahmed Khalil
Using Hybrid Machine Learning Models For Stock Price Forecasting And Trading., Ahmed Khalil
Theses and Dissertations
Trading stocks of publicly traded companies in stock markets is a challenging topic since investors are researching what tools can be used to maximize their profits while minimizing risks, which encouraged all researchers to research and test different methods to reach such a goal. As a result, the use of both fundamental analysis and technical analysis started to evolve to support traders in buying and selling stocks. Recently, the focus increased on using Machine learning models to predict stock prices and algorithmic trading as currently there is a huge amount of data that can be processed and used to forecast …
User Profiling Through Zero-Permission Sensors And Machine Learning, Ahmed Elhussiny
User Profiling Through Zero-Permission Sensors And Machine Learning, Ahmed Elhussiny
Theses and Dissertations
With the rise of mobile and pervasive computing, users are often ingesting content on the go. Services are constantly competing for attention in a very crowded field. It is only logical that users would allot their attention to the services that are most likely to adapt to their needs and interests. This matter becomes trivial when users create accounts and explicitly inform the services of their demographics and interests. Unfortunately, due to privacy and security concerns, and due to the fast nature of computing today, users see the registration process as an unnecessary hurdle to bypass, effectively refusing to provide …
Enhanced Data Sampling And Feature Generation For Machine Learning-Based Lithography Hotspot Detection, Mohamed Ismail
Enhanced Data Sampling And Feature Generation For Machine Learning-Based Lithography Hotspot Detection, Mohamed Ismail
Theses and Dissertations
Technology scaling has increased the complexity of integrated circuit design. It has also led to more challenges in the field of Design for Manufacturing (DFM). One of these challenges is lithography hotspot detection. Hotspots (HS) are design patterns that negatively affect the output yield. Identifying these patterns early in the design phase is crucial for high yield fabrication. Machine Learning-based (ML) hotspot detection techniques are promising since they have shown superior results to other methods such as pattern matching. Training ML models is a challenging task due two main reasons. Firstly, industrial training designs contain millions of unique patterns. It …
Network Management, Optimization And Security With Machine Learning Applications In Wireless Networks, Mariam Nabil
Network Management, Optimization And Security With Machine Learning Applications In Wireless Networks, Mariam Nabil
Theses and Dissertations
Wireless communication networks are emerging fast with a lot of challenges and ambitions. Requirements that are expected to be delivered by modern wireless networks are complex, multi-dimensional, and sometimes contradicting. In this thesis, we investigate several types of emerging wireless networks and tackle some challenges of these various networks. We focus on three main challenges. Those are Resource Optimization, Network Management, and Cyber Security. We present multiple views of these three aspects and propose solutions to probable scenarios. The first challenge (Resource Optimization) is studied in Wireless Powered Communication Networks (WPCNs). WPCNs are considered a very promising approach towards sustainable, …
Off-Chain Transaction Routing In Payment Channel Networks: A Machine Learning Approach, Heba Kadry
Off-Chain Transaction Routing In Payment Channel Networks: A Machine Learning Approach, Heba Kadry
Theses and Dissertations
Blockchain is a foundational technology that has the potential to create new prospects for our economic and social systems. However, the scalability problem limits the capability to deliver a target throughput and latency, compared to the traditional financial systems, with increasing workload. Layer-two is a collective term for solutions designed to help solve the scalability by handling transactions off the main chain, also known as layer one. These solutions have the capability to achieve high throughput, fast settlement, and cost efficiency without sacrificing network security. For example, bidirectional payment channels are utilized to allow the execution of fast transactions between …