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Articles 1 - 8 of 8
Full-Text Articles in Physical Sciences and Mathematics
Wrinkles In Time : An Exploration Of Non-Uniform Temporal Resolution In Network Data, Daniel John Ditursi
Wrinkles In Time : An Exploration Of Non-Uniform Temporal Resolution In Network Data, Daniel John Ditursi
Legacy Theses & Dissertations (2009 - 2024)
The continued proliferation of timestamped network data demands increasing sophistication in the analysis of that data. In particular, the literature amply demonstrates that the choice of temporal resolution has a profound impact on the solutions produced by many different methods in this domain -- answers differ when data is viewed second-by-second as opposed to week-by-week. Additionally, research also shows quite clearly that the rates at which network events happen are not constant -- some times are "faster" or "slower" than others, and these variations are not necessarily predictable. Given the above, it is clear that there must be problem settings …
Pose Based Human Activity Recognition, Wenbo Li
Pose Based Human Activity Recognition, Wenbo Li
Legacy Theses & Dissertations (2009 - 2024)
Pose based human activity recognition is an important step towards video understanding. The last decade has witnessed the great progress in this field which is driven by multiple technical innovations, i.e., kinect, pose estimation techniques, deep learning, etc.
Towards The Development Of A Concurrent Programming Language, Marrium Ayesha
Towards The Development Of A Concurrent Programming Language, Marrium Ayesha
Legacy Theses & Dissertations (2009 - 2024)
In order to fully utilize the potential of current architectures, programmers must program withconcurrency in mind. Concurrent processes can be extremely challenging to reason about due tounexpected program behavior that may emerge from interaction between processes. One approachto deal with this difficulty is to study new programming languages that offer an abstraction forconcurrency. This thesis focuses on developing a logical interpretation for concurrent processesand incorporating it in an existing functional programming language called SML. We developthis feature upon the fact that a proof of a theorem in logic can be expressed as a program in aprogramming language. This relation allows …
Efficient Algorithms For Mining Healthcare Data :, Yan Hu
Efficient Algorithms For Mining Healthcare Data :, Yan Hu
Legacy Theses & Dissertations (2009 - 2024)
Data-Driven Healthcare (DDH) is defined as the usage of available medical big data to provide the best and most personalized care, which is believed to be one of the most promising directions for transforming healthcare. The healthcare data includes claims and cost data, clinical data, pharmaceutical R&D data, patient behavior and sentiment data, and health data on the web. There has been a remarkable upsurge in the adoption of healthcare data over the past several years. In particular, it has been used for medical concept extraction, patient trajectory modeling, disease inference, etc.
Efficient Detection Of Diseases By Feature Engineering Approach From Chest Radiograph, Avishek Mukherjee
Efficient Detection Of Diseases By Feature Engineering Approach From Chest Radiograph, Avishek Mukherjee
Legacy Theses & Dissertations (2009 - 2024)
Deep Learning is the new state-of-the-art technology in Image Processing. We applied Deep Learning techniques for identification of diseases from Radiographs made publicly available by NIH. We applied some Feature Engineering approach to augment the data from Anterior-Posterior position to Posterior-Anterior position and vice-versa for all the diseases, at the same point we suppressed ‘No Finding’ radiographs which contributed to more than 50% (approximately 60,000) of the dataset to top 1000 images. We also prepared a model by adding a huge amount of noise to the augmented data, which if need be can be deployed at rural locations which lack …
Emotion Forecasting In Dyadic Conversation : Characterizing And Predicting Future Emotion With Audio-Visual Information Using Deep Learning, Sadat Shahriar
Emotion Forecasting In Dyadic Conversation : Characterizing And Predicting Future Emotion With Audio-Visual Information Using Deep Learning, Sadat Shahriar
Legacy Theses & Dissertations (2009 - 2024)
Emotion forecasting is the task of predicting the future emotion of a speaker, i.e., the emotion label of the future speaking turn–based on the speaker’s past and current audio-visual cues. Emotion forecasting systems require new problem formulations that differ from traditional emotion recognition systems. In this thesis, we first explore two types of forecasting windows(i.e., analysis windows for which the speaker’s emotion is being forecasted): utterance forecasting and time forecasting. Utterance forecasting is based on speaking turns and forecasts what the speaker’s emotion will be after one, two, or three speaking turns. Time forecasting forecasts what the speaker’s emotion will …
Optimization Methods For Learning Graph-Structured Sparse Models, Baojian Zhou
Optimization Methods For Learning Graph-Structured Sparse Models, Baojian Zhou
Legacy Theses & Dissertations (2009 - 2024)
Learning graph-structured sparse models has recently received significant attention thanks to their broad applicability to many important real-world problems. However, such models, of more effective and stronger interpretability compared with their counterparts, are difficult to learn due to optimization challenges. This thesis presents optimization algorithms for learning graph-structured sparse models under three different problem settings. Firstly, under the batch learning setting, we develop methods that can be applied to different objective functions that enjoy linear convergence guarantees up to constant errors. They can effectively optimize the statistical score functions in the task of subgraph detection; Secondly, under stochastic learning setting, …
Autonomous Spectrum Enforcement : A Blockchain Approach, Maqsood Ahamed Abdul Careem
Autonomous Spectrum Enforcement : A Blockchain Approach, Maqsood Ahamed Abdul Careem
Legacy Theses & Dissertations (2009 - 2024)
A core limitation in existing wireless technologies is the scarcity of spectrum, to support the exponential increase in Internet-connected and multimedia-capable mobile devices and the increasing demand for bandwidth-intensive services. As a solution, Dynamic Spectrum Access policies are being ratified to promote spectrum sharing for various spectrum bands and to improve the spectrum utilization. This poses an equally challenging problem of enforcing these spectrum policies. The distributed and dynamic nature of policy violations necessitates the use of autonomous agents to implement efficient and agile enforcement systems. The design of such a fully autonomous enforcement system is complicated due to the …