Physical Sciences and Mathematics Commons^™

On The Promotion Of The Social Web Intelligence, Taraneh Khazaei

Electronic Thesis and Dissertation Repository

Given the ever-growing information generated through various online social outlets, analytical research on social media has intensified in the past few years from all walks of life. In particular, works on social Web intelligence foster and benefit from the wisdom of the crowds and attempt to derive actionable information from such data. In the form of collective intelligence, crowds gather together and contribute to solving problems that may be difficult or impossible to solve by individuals and single computers. In addition, the consumer insight revealed from social footprints can be leveraged to build powerful business intelligence tools, enabling efficient and …

Neurosurgical Ultrasound Pose Estimation Using Image-Based Registration And Sensor Fusion - A Feasibility Study, Utsav Pardasani

Electronic Thesis and Dissertation Repository

Modern neurosurgical procedures often rely on computer-assisted real-time guidance using multiple medical imaging modalities. State-of-the-art commercial products enable the fusion of pre-operative with intra-operative images (e.g., magnetic resonance [MR] with ultrasound [US] images), as well as the on-screen visualization of procedures in progress. In so doing, US images can be employed as a template to which pre-operative images can be registered, to correct for anatomical changes, to provide live-image feedback, and consequently to improve confidence when making resection margin decisions near eloquent regions during tumour surgery.

In spite of the potential for tracked ultrasound to improve many neurosurgical procedures, it …

Agora: A Knowledge Marketplace For Machine Learning, Mauro Ribeiro

Electronic Thesis and Dissertation Repository

More and more data are becoming part of people's lives. With the popularization of technologies like sensors, and the Internet of Things, data gathering is becoming possible and accessible for users. With these data in hand, users should be able to extract insights from them, and they want results as soon as possible. Average users have little or no experience in data analytics and machine learning and are not great observers who can collect enough data to build their own machine learning models. With large quantities of similar data being generated around the world and many machine learning models being …

Climbing Up Cloud Nine: Performance Enhancement Techniques For Cloud Computing Environments, Mohamed Abusharkh

Electronic Thesis and Dissertation Repository

With the transformation of cloud computing technologies from an attractive trend to a business reality, the need is more pressing than ever for efficient cloud service management tools and techniques. As cloud technologies continue to mature, the service model, resource allocation methodologies, energy efficiency models and general service management schemes are not yet saturated. The burden of making this all tick perfectly falls on cloud providers. Surely, economy of scale revenues and leveraging existing infrastructure and giant workforce are there as positives, but it is far from straightforward operation from that point. Performance and service delivery will still depend on …

Energy Consumption Prediction With Big Data: Balancing Prediction Accuracy And Computational Resources, Katarina Grolinger, Miriam Am Capretz, Luke Seewald

Electrical and Computer Engineering Publications

In recent years, advances in sensor technologies and expansion of smart meters have resulted in massive growth of energy data sets. These Big Data have created new opportunities for energy prediction, but at the same time, they impose new challenges for traditional technologies. On the other hand, new approaches for handling and processing these Big Data have emerged, such as MapReduce, Spark, Storm, and Oxdata H2O. This paper explores how findings from machine learning with Big Data can benefit energy consumption prediction. An approach based on local learning with support vector regression (SVR) is presented. Although local learning itself is …

An Exercise And Sports Equipment Recognition System, Siddarth Kalra

Electronic Thesis and Dissertation Repository

Most mobile health management applications today require manual input or use sensors like the accelerometer or GPS to record user data. The onboard camera remains underused. We propose an Exercise and Sports Equipment Recognition System (ESRS) that can recognize physical activity equipment from raw image data. This system can be integrated with mobile phones to allow the camera to become a primary input device for recording physical activity. We employ a deep convolutional neural network to train models capable of recognizing 14 different equipment categories. Furthermore, we propose a preprocessing scheme that uses color normalization and denoising techniques to improve …

Advanced Driving Assistance Prediction Systems, Maedeh Hesabgar

Electronic Thesis and Dissertation Repository

Future automobiles are going to experience a fundamental evolution by installing semiotic predictor driver assistance equipment. To meet these equipment, Continuous driving-behavioral data have to be observed and processed to construct powerful predictive driving assistants. In this thesis, we focus on raw driving-behavioral data and present a prediction method which is able to prognosticate the next driving-behavioral state. This method has been constructed based on the unsupervised double articulation analyzer method (DAA) which is able to segment meaningless continuous driving-behavioral data into a meaningful sequence of driving situations. Thereafter, our novel model by mining the sequences of driving situations can …

Machine Learning Of Lifestyle Data For Diabetes, Yan Luo

Electronic Thesis and Dissertation Repository

Self-Monitoring of Blood Glucose (SMBG) for Type-2 Diabetes (T2D) remains highly challenging for both patients and doctors due to the complexities of diabetic lifestyle data logging and insufficient short-term and personalized recommendations/advice. The recent mobile diabetes management systems have been proved clinically effective to facilitate self-management. However, most such systems have poor usability and are limited in data analytic functionalities. These two challenges are connected and affected by each other. The ease of data recording brings better data for applicable data analytic algorithms. On the other hand, the irrelevant or inaccurate data input will certainly commit errors and noises. The …

Feature Encoding Strategies For Multi-View Image Classification, Kyle Doerr

Electronic Thesis and Dissertation Repository

Machine vision systems can vary greatly in size and complexity depending on the task at hand. However, the purpose of inspection, quality and reliability remains the same. This work sets out to bridge the gap between traditional machine vision and computer vision. By applying powerful computer vision techniques, we are able to achieve more robust solutions in manufacturing settings. This thesis presents a framework for applying powerful new image classification techniques used for image retrieval in the Bag of Words (BoW) framework. In addition, an exhaustive evaluation of commonly used feature pooling approaches is conducted with results showing that spatial …