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.

Interactive Distance Learning in Teacher Education

Abstract: V a r i o u s d i s t ance l ea rn ing a p p r o a c h e s have been successful in meet ing the educat ional needs of teachers . Distance learning provides opportuni t ies for on-going professional growth for those teachers who would otherwise be unab le to a t tend classes because of travel and time const ra ints . Success of a dis tance learning course depends on providing meaningful and motivat ional learning experiences for teachers in the campus s tudio as well as for teachers at remote sites. This article focuses on dis tance learning courses I t each at the Universi ty of Sou th Florida, Lakeland Campus . Distance learning, as described in this article, is providing live t r ansmiss ion of ins t ruc t ion to teachers at geographically dispersed sites while s imul taneous ly conduct ing the course with teachers in a c a m p u s s tudio classroom. Ins t ruc t ion is t ransmit ted to each site via one-way video, so t ha t the teachers see the instructor, alt hough the ins t ruc tor is unable to view teachers at the sites. Telephones provide on-going two-way audio communica t ion between the instructor, t eachers in the s tudio, and teachers at the sites. Teachers meet for three hours one night a week at central ly located sites for a th ree -hour semes te r course. During the semester, procDr Wynn is assistant professor of education at the University of South Florida, Lakeland.

A Robotic Control System for Fault Tolerance and Safety using Human Robot Interaction

Abstract: In Robotics, fault tolerant control is an essential aspect for the robot to be fully autonomous without running into errors. One error could lead to another thereby quickly cascading out of control causing the system to behave anomaly. Fault tolerant and self-healing robotic control systems help detect the errors and based on the type of the error the robot automatically can self-heal or self-correct itself. The current paper is a work in progress and provides an outline of such a robotic systems mentioned in literature. A Robotic Control System using human in the loop is proposed to facilitate self-adjusting capability within the robot. Such as system will also help with the safety of the robot and the environment where it is deployed.

Employing machine learning techniques to assess requirement change volatility

Abstract: Lack of planning when changing requirements to reflect stakeholders’ expectations can lead to propagated changes that can cause project failures. Existing tools cannot provide the formal reasoning required to manage requirement change and minimize unanticipated change propagation. This research explores machine learning techniques to predict requirement change volatility (RCV) using complex network metrics based on the premise that requirement networks can be utilized to study change propagation. Three research questions (RQs) are addressed: (1) Can RCV be measured through four classes namely, multiplier, absorber, transmitter, and robust, during every instance of change? (2) Can complex network metrics be explored and computed for each requirement during every instance of change? (3) Can machine learning techniques, specifically, multilabel learning (MLL) methods be employed to predict RCV using complex network metrics? RCV in this paper quantifies volatility for change propagation, that is, how requirements behave in response to the initial change. A multiplier is a requirement that is changed by an initial change and propagates change to other requirements. An absorber is a requirement that is changed by an initial change, but does not propagate change to other requirements. A transmitter is a requirement that is not changed by an initial change, but propagates change to other requirements. A robust requirement is a requirement that is not changed by an initial change and does not propagate change to other requirements. RCV is determined using industrial data and requirement network relationships obtained from previously developed Refined Automated Requirement Change Propagation Prediction (R-ARCPP) tool. Useful complex network metrics in highest performing machine learning models are discussed along with the limitations and future directions of this research.

The Session Inventory Module within an Intelligent Tutoring System for Data Normalization

Abstract: The knowledge acquisition of data normalization has been commonly perceived as a hurdle that is challenging students in the beginning database classes. As an effort to provide students with additional assistance while learning this topic, an intelligent tutoring system is proposed and implemented that can be used as a virtual private tutor to teach students in a one-on-one manner. This paper describes the strategically design and management of the tutorial sessions within this system. These sessions are designed and maintained according to their theme topics and difficulty levels so that the virtual tutor can dynamically select sessions based on the assessment of a student’s knowledge level and progress.

Hierarchical task analysis of endoscopic sleeve gastroplasty.

Abstract: BACKGROUND Endoscopic sleeve gastroplasty (ESG) is a minimally invasive endoscopic weight loss procedure used to treat obesity. The long-term goal of this project is to develop a Virtual Bariatric Endoscopy (ViBE) simulator for training and assessment of the ESG procedure. The objectives of this current work are to: (a) perform a task analysis of ESG and (b) create metrics to be validated in the created simulator. METHODS We performed a hierarchical task analysis (HTA) by identifying the significant tasks of the ESG procedure. We created the HTA to show the breakdown and connection of the tasks of the procedure. Utilizing the HTA and input from ESG experts, performance metrics were derived for objective measurement of the ESG procedure. Three blinded video raters analyzed seven recorded ESG procedures according to the proposed performance metrics. RESULTS Based on the seven videos, there was a positive correlation between total task times and total performance scores (R = 0.886, P = 0.008). Endoscopists expert were found to be more skilled in reducing the area of the stomach compared to endoscopists novice (34.6% reduction versus 9.4% reduction, P = 0.01). The mean novice performance score was significantly lower than the mean expert performance score (34.7 vs. 23.8, P = 0.047). The inter-rater reliability test showed a perfect agreement among three raters for all tasks except for the suturing task. The suturing task had a significant agreement (Inter-rater Correlation = 0.84, Cronbach's alpha = 0.88). Suturing was determined to be a critical task that is positively correlated with the total score (R = 0.962, P = 0.0005). CONCLUSION The task analysis and metrics development are critical for the development of the ViBE simulator. This preliminary assessment demonstrates that the performance metrics provide an accurate assessment of the endoscopist's performance. Further validation testing and refinement of the performance metrics are anticipated.