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Algorithm For Premature Ventricular Contraction Detection From A Subcutaneous Electrocardiogram Signal, Iris Lynn Shelly

Dissertations and Theses

Cardiac arrhythmias occur when the normal pattern of electrical signals in the heart breaks down. A premature ventricular contraction (PVC) is a common type of arrhythmia that occurs when a heartbeat originates from an ectopic focus within the ventricles rather than from the sinus node in the right atrium. This and other arrhythmias are often diagnosed with the help of an electrocardiogram, or ECG, which records the electrical activity of the heart using electrodes placed on the skin. In an ECG signal, a PVC is characterized by both timing and morphological differences from a normal sinus beat.

An implantable cardiac …

Task And Participant Scheduling Of Trading Platforms In Vehicular Participatory Sensing Networks, Heyuan Shi, Xiaoyu Song, Ming Gu, Jiaguang Sun

Electrical and Computer Engineering Faculty Publications and Presentations

The vehicular participatory sensing network (VPSN) is now becoming more and more prevalent, and additionally has shown its great potential in various applications. A general VPSN consists of many tasks from task, publishers, trading platforms and a crowd of participants. Some literature treats publishers and the trading platform as a whole, which is impractical since they are two independent economic entities with respective purposes. For a trading platform in markets, its purpose is to maximize the profit by selecting tasks and recruiting participants who satisfy the requirements of accepted tasks, rather than to improve the quality of each task. This …

The Dc Algorithm & The Constrained Fermat-Torricelli Problem, Nathan Peron Lawrence, George Blikas

Student Research Symposium

The theory of functions expressible as the Difference of Convex (DC) functions has led to the development of a rich field in applied mathematics known as DC Programming.We survey the work of Pham Dinh Tao and Le Thi Hoai An in order to understand the DC Algorithm (DCA) and its use in solving clustering problems. Further, we present several other methods that generalize the DCA for any norm. These powerful tools enable researchers to reformulate objective functions, not necessarily convex, into DC Programs.

The Fermat-Torricelli problem is visited in light of convex analysis and various norms. Pierre de Fermat proposed …

Hydrologic Modeling In Dynamic Catchments: A Data Assimilation Approach, Sahani Darshika Pathiraja, Ashish Sharma, Lucy Marshall, Hamid Moradkhani

Civil and Environmental Engineering Faculty Publications and Presentations

The transferability of conceptual hydrologic models in time is often limited by both their structural deficiencies and adopted parameterizations. Adopting a stationary set of model parameters ignores biases introduced by the data used to derive them, as well as any future changes to catchment conditions. Although time invariance of model parameters is one of the hallmarks of a high quality hydrologic model, very few (if any) models can achieve this due to their inherent limitations. It is therefore proposed to consider parameters as potentially time varying quantities, which can evolve according to signals in hydrologic observations. In this paper, we …

The Log-Exponential Smoothing Technique And Nesterov’S Accelerated Gradient Method For Generalized Sylvester Problems, N. T. An, Daniel J. Giles, Nguyen Mau Nam, R. Blake Rector

Mathematics and Statistics Faculty Publications and Presentations

The Sylvester or smallest enclosing circle problem involves finding the smallest circle enclosing a finite number of points in the plane. We consider generalized versions of the Sylvester problem in which the points are replaced by sets. Based on the log-exponential smoothing technique and Nesterov’s accelerated gradient method, we present an effective numerical algorithm for solving these problems.

Minimizing Differences Of Convex Functions With Applications To Facility Location And Clustering, Mau Nam Nguyen, R. Blake Rector, Daniel J. Giles

Mathematics and Statistics Faculty Publications and Presentations

In this paper we develop algorithms to solve generalized Fermat-Torricelli problems with both positive and negative weights and multifacility location problems involving distances generated by Minkowski gauges. We also introduce a new model of clustering based on squared distances to convex sets. Using the Nesterov smoothing technique and an algorithm for minimizing differences of convex functions called the DCA introduced by Tao and An, we develop effective algorithms for solving these problems. We demonstrate the algorithms with a variety of numerical examples.