Open Access. Powered by Scholars. Published by Universities.®
Artificial Intelligence and Robotics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
Articles 1 - 4 of 4
Full-Text Articles in Artificial Intelligence and Robotics
Sequence Checking And Deduplication For Existing Fingerprint Databases, Tahsin Islam Sakif
Sequence Checking And Deduplication For Existing Fingerprint Databases, Tahsin Islam Sakif
Graduate Theses, Dissertations, and Problem Reports
Biometric technology is a rapidly evolving field with applications that range from access to devices to border crossing and entry/exit processes. Large-scale applications to collect biometric data, such as border crossings result in multimodal biometric databases containing thousands of identities. However, due to human operator error, these databases often contain many instances of image labeling and classification; this is due to the lack of training and throughput pressure that comes with human error. Multiple entries from the same individual may be assigned to a different identity. Rolled fingerprints may be labeled as flat images, a face image entered into a …
Predictive Modeling Of Asynchronous Event Sequence Data, Jin Shang
Predictive Modeling Of Asynchronous Event Sequence Data, Jin Shang
LSU Doctoral Dissertations
Large volumes of temporal event data, such as online check-ins and electronic records of hospital admissions, are becoming increasingly available in a wide variety of applications including healthcare analytics, smart cities, and social network analysis. Those temporal events are often asynchronous, interdependent, and exhibiting self-exciting properties. For example, in the patient's diagnosis events, the elevated risk exists for a patient that has been recently at risk. Machine learning that leverages event sequence data can improve the prediction accuracy of future events and provide valuable services. For example, in e-commerce and network traffic diagnosis, the analysis of user activities can be …
Dish: Democracy In State Houses, Nicholas A. Russo
Dish: Democracy In State Houses, Nicholas A. Russo
Master's Theses
In our current political climate, state level legislators have become increasingly impor- tant. Due to cuts in funding and growing focus at the national level, public oversight for these legislators has drastically decreased. This makes it difficult for citizens and activists to understand the relationships and commonalities between legislators. This thesis provides three contributions to address this issue. First, we created a data set containing over 1200 features focused on a legislator’s activity on bills. Second, we created embeddings that represented a legislator’s level of activity and engagement for a given bill using a custom model called Democracy2Vec. Third, we …
Predicting Post-Procedural Complications Using Neural Networks On Mimic-Iii Data, Namratha Mohan
Predicting Post-Procedural Complications Using Neural Networks On Mimic-Iii Data, Namratha Mohan
LSU Master's Theses
The primary focus of this paper is the creation of a Machine Learning based algorithm for the analysis of large health based data sets. Our input was extracted from MIMIC-III, a large Health Record database of more than 40,000 patients. The main question was to predict if a patient will have complications during certain specified procedures performed in the hospital. These events are denoted by the icd9 code 996 in the individuals' health record. The output of our predictive model is a binary variable which outputs the value 1 if the patient is diagnosed with the specific complication or 0 …