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STOCK MARKET FORECASTING: AN APPLICATION OF LONG SHORT TERM MEMORY (LSTM) RECURRENT NEURAL NETWORK
(Computing, 2018 , Professional Masters Project)
Predicting stock market prices is regarded as a challenging task of financial time series, due to its chaotic, non-linear, non-stationary and dynamic nature. In this project we address the problem of stock market forecasting ...
Automated Segmentation of Cerebral Aneurysm Using a Novel Statistical Multiresolution Approach
(Computing, 2018 , Master Thesis)
Cerebral Aneurysm (CA) is a vascular disease that threatens the lives of
many adults. It a ects almost 1:5 - 5% of the general population. Sub-
Arachnoid Hemorrhage (SAH), resulted by a ruptured CA, has high rates ...
Optimal Resource Allocation Using Deep Learning-Based Adaptive Compression For Mhealth Applications
(Computing, 2018 , Master Thesis)
In the last few years the number of patients with chronic diseases that require constant monitoring increases rapidly; which motivates the researchers to develop scalable remote health applications. Nevertheless, transmitting ...
EVALUATION OF 2D AND 3D TECHNIQUES FOR SENTIMENT VISUALIZATION
(Computing, 2018 , Master Thesis)
With the rise of user generated content on the Internet, sentiment visualization is being highly researched and practiced. Advances in information visualization, such as the use of three-dimensional visualizations need to ...
QUEUEING THEORY BASED KUBERNETES AUTOSCALER
(Computing, 2018 , Professional Masters Project)
The microservices architecture is emerging as a new architectural style for designing and developing applications by composing loosely coupled services that exchange standard messages using standard interfaces and protocols. ...
Real-time Tweet Summarization Mobile Application
(Computing, 2018 , Professional Masters Project)
With the emergence of the massive volume of content through social media platforms,
users are getting overwhelmed with information, though searching for the topic
will give you filtered information that interests you. ...
EFFICIENT SKYLINE SYSTEM DEVELOPMENT FOR NORMAL AND HIDDEN DATABASES: APPLICATION FOR GOOGLE FLIGHTS
(Computing, 2018 , Professional Masters Project)
Deep web databases provide strict search interface and limited web access with top-k results based on a pre-defined ranking function. However, top-k results may not be suitable for multi-criteria decision making because ...
An Ontology based Text-to-Picture Multimedia m-Learning System
(Computer Science, 2018 , Dissertation)
Multimedia Text-to-Picture is the process of building mental representation from words associated with images. From the research aspect, multimedia instructional message items are illustrations of material using words and ...
ON RELEVANCE FILTERING FOR REAL-TIME TWEET SUMMARIZATION
(Computer Science, 2018 , Master Thesis)
Real-time tweet summarization systems (RTS) require mechanisms for capturing relevant tweets, identifying novel tweets, and capturing timely tweets. In this thesis, we tackle the RTS problem with a main focus on the relevance ...
Latent Semantic Indexing (LSI) Based Distributed System and Search On Encrypted Data
(Computing, 2018 , Master Thesis)
Latent semantic indexing (LSI) was initially introduced to overcome the issues of synonymy and polysemy of the traditional vector space model (VSM). LSI, however, has challenges of its own, mainly scalability. Despite being ...