Florida Polytechnic University

About: Florida Polytechnic University is a education organization based out in Lakeland, Florida, United States. It is known for research contribution in the topics: Computer science & Catalysis. The organization has 302 authors who have published 538 publications receiving 6549 citations. The organization is also known as: Florida Poly.

An Improved Approach in Fingerprint Recognition Algorithm

Abstract: There are several reasons like displacement of finger during scanning, environmental conditions, behavior of user, etc., which causes the reduction in acceptance rate during fingerprint recognition. The result and accuracy of fingerprint recognition depends on the presence of valid minutiae. This paper proposed an algorithm, which identify the valid minutiae and increase the acceptance rate and accuracy level. The work of the proposed algorithm is categorized into two parts: preprocessing and post-processing. The proposed algorithm enhanced most of the phases of preprocessing for removing the noise, and make the clear fingerprint image for feature extraction and enhanced the post-processing phases for eliminating the false extracted minutiae, to extract exact core point detection, and matching valid minutiae. The developed proposed algorithm is tested using FVC2000 and FingerDOS databases for measuring the average FMR = 1% and FNMR = 1.43% and accuracy 98.7% for both databases.

Future stress, forecasting physiological signals

Abstract: Work-related stress is normal and at low levels it can actually increase productivity. However, the accumulation of stress may have significant long-term behavioral and physical health consequences such as sleep deprivation, and anxiety disorder. According to the American Psychological Association, around 49% of the U.S. population suffers from chronic daily stress. In this paper, we explore the use of Hidden Markov Models (HMM), and exponential smoothing forecasting for the prediction of future stress episodes. Existing research on wearable sensors, data processing, and real time stress inferencing allow for collection of a ‘stress history’ time series which is used to train the methods presented here. A brief overview of methods is given, and prediction results are presented. Extensive simulations show promising results on stress forecasting, and potential future work on preventive stress interventions.

Evaluating the agreement and reliability of a web-based facial analysis tool for rhinoplasty.

Abstract: Rhinoplasty is one of the most common and challenging plastic surgery procedures. Facial analysis is a crucial step in planning. Utilizing three-dimensional (3D) model of a patient’s face is an emerging way of performing facial analysis. This paper evaluates the agreement and reliability of facial measurements taken using a web app, located at digitized-rhinoplasty.com, that utilizes 3D models of the patient’s face. Eleven measurements were calculated on 16 human subjects. Three methods of measurements were performed: direct measurements on human subjects’ faces, measurements on 2D photographs, and measurements on 3D models of face scans. The Bland–Altman plot is used for testing the agreement between the web app and the well-known Blender 3D modeling software. Intra-rater and inter-rater reliability was calculated and compared for 2D and 3D methods using the intraclass correlation coefficient (ICC) method. The statistical analysis methods were checked for the normality and homoscedasticity assumptions. The results indicate that the web app and Blender software show agreement within 95% confidence limits. The web app performs well in intra-rater and inter-rater reliability statistical analysis. The web app’s reliability scores are consistently better than facial analysis software which was found highly reliable in a previous study. We also compare the methods of measurements in terms of time, ease of use, and cost. The utilization of 3D computer modeling for facial analysis has its advantages and started to become more common due to recent advances in technology. The web app utilizes 3D face scans for pre-operative planning and post-operative evaluation of facial surgeries. The web app performs well in agreement and inter-/intra-reliability analysis and performs consistently better than software that works utilizing 2D photographs. The web app provides accurate, repeatable, affordable, and fast facial measurements for facial analysis when compared to direct and 2D methods.

A Platform-Based Incentive Mechanism for Autonomous Vehicle Crowdsensing

Abstract: In this article, we present an incentive mechanism for Vehicular Crowdsensing in the context of autonomous vehicles (AVs). In particular, we propose a solution to the problem of sensing coverage of regions located out of the AVs’ planned trajectories. We tackle this problem by dynamically modifying the AVs’ trajectories and collecting sensing samples from regions otherwise unreachable by originally planned routes. We model this problem as a non-cooperative game in which a set of AVs equipped with sensors are the players and their trajectories are the strategies. Thus, our solution corresponds to a model in which expected individual utility drives the mobility decision of participants. Using open-street maps, SUMO vehicular traffic simulator, and extensive simulations, we show our algorithm significantly outperforms traditional approaches for trajectory generation. In particular, our performance evaluation shows a significant lift in crowdsourcer coverage, road utilization, and average participant utility.