Innovative Design of Fire Training Simulator

This project outlines the innovative design of a fire detections training simulator. Fire protection systems are updated and changed rapidly as technology grows; training and guidelines for inspectors and safety professionals are crucial for the development of these systems. This project\u27s purpose is to design a fire inspection simulator to enhance awareness of and training fire safety professionals in the workplace. This interactive system uses specific devices that are not only cost effective but are widely accepted and used in multiple industries. OSHA 1910 Subpart L and NFPA 101 were used with NFPA 72 to inform the design of this system. The training provided will allow instructors and safety professionals an opportunity to review current fire protection devices as well as keep up to date with the most used fire protection devices in manufacturing. The outcome is to have proficient trainees with a basic understanding of how systems are implemented, designed, and maintained. By creating this innovative training system, we will have a tool up to date in the modern era that can be used by safety professionals for years to come. Our system can guarantee that trained individuals will be able to improve their knowledge and refine the skills required to operate the various kinds of alarm system that they may encounter in the workplace

UC-36 Using Machine Learning Techniques to Predict RT-PCR Results for COVID-19 Patients.

With the COVID-19 pandemic still a threat, healthcare professionals and medical industries keep searching for better ways to mitigate the spread of COVID-19. While Machine Learning has been applied in many other domains, there is now a high demand for diagnosis systems that utilize Machine Learning techniques in the healthcare domain and in particular combating COVID-19. In this project, we explore the role of Machine Learning models in combating COVID-19, using WEKA as the main tool for analysis.Advisors(s): Dr. Ming Yang - IT 4983 Capstone Professor Dr. Seyedamin Pouriyeh - Project OwnerTopic(s): Data/Data AnalyticsIT 498

Effect of a tart cherry juice supplement on arterial stiffness and inflammation in healthy adults: a randomised controlled trial.

Tart cherries are a particularly rich source of anthocyanins. Evidence indicates that dietary intake of anthocyanins is inversely associated with arterial stiffness. We conducted an open-label randomised placebo controlled study to determine whether a tart cherry juice concentrate (Cherry Active®) reduced arterial stiffness, inflammation and risk markers for cardiovascular disease in 47 healthy adults (30 – 50 y). Participants consumed 30 ml of cherry concentrate diluted to a volume of 250 ml with water or the same volume of an energy matched control drink daily for 6 weeks. Measurements were taken at baseline and at the end of the intervention. There was no effect of the intervention on arterial stiffness (P=0.218), c-reactive protein (P=0.220), systolic blood pressure (P=0.163), diastolic blood pressure (P=0.121), total cholesterol (P=0.342) and high density lipoprotein cholesterol (P=0.127). At the end of the intervention, plasma antioxidant capacity (measured as the ferric reducing ability of plasma (FRAP) was significantly higher in the intervention group than the control group (P=0.012). We conclude that a tart cherry juice concentrate rich in anthocyanins has no effect on arterial stiffness, c-reactive protein and risk markers for cardiovascular disease, but evokes a minor increase in antioxidant status in healthy adults

Juicer: A Weighted Finite-State Transducer speech decoder

A major component in the development of any speech recognition system is the decoder. As task complexities and, consequently, system complexities have continued to increase the decoding problem has become an increasingly significant component in the overall speech recognition system development effort, with efficient decoder design contributing to significantly improve the trade-off between decoding time and search errors. In this paper we present the ``Juicer'' (from trans\textbf{\emph{ducer}}) large vocabulary continuous speech recognition (LVCSR) decoder based on weighted finite-State transducer (WFST). We begin with a discussion of the need for open source, state-of-the-art decoding software in LVCSR research and how this lead to the development of Juicer, followed by a brief overview of decoding techniques and major issues in decoder design. We present Juicer and its major features, emphasising its potential not only as a critical component in the development of LVCSR systems, but also as an important research tool in itself, being based around the flexible WFST paradigm. We also provide results of benchmarking tests that have been carried out to date, demonstrating that in many respects Juicer, while still in its early development, is already achieving state-of-the-art. These benchmarking tests serve to not only demonstrate the utility of Juicer in its present state, but are also being used to guide future development, hence, we conclude with a brief discussion of some of the extensions that are currently under way or being considered for Juicer

Model reduction of homogeneous-in-the-state bilinear systems with input constraints

Accepted versio

FISH as an effective diagnostic tool for the management of challenging melanocytic lesions

<p>Abstract</p> <p>Background</p> <p>The accuracy of melanoma diagnosis continues to challenge the pathology community, even today with sophisticated histopathologic techniques. Melanocytic lesions exhibit significant morphological heterogeneity. While the majority of biopsies can be classified as benign (nevus) or malignant (melanoma) using well-established histopathologic criteria, there exists a cohort for which the prediction of clinical behaviour and invasive or metastatic potential is difficult if not impossible to ascertain on the basis of morphological features alone. Multiple studies have shown that there is significant disagreement between pathologists and even expert dermatopathologists in the diagnosis of this subgroup of difficult melanocytic lesions.</p> <p>Methods</p> <p>A four probe FISH assay was utilized to analyse a cohort of 500 samples including 157 nevus, 176 dysplastic nevus and 167 melanoma specimens.</p> <p>Results</p> <p>Review of the lesions determined the assay identified genetic abnormalities in a total of 83.8% of melanomas, and 1.9% of nevus without atypia, while genetic abnormalities were identified in 6.3%, 6.7%, and 10.3% of nevus identified with mild, moderate and severe atypia, respectively.</p> <p>Conclusions</p> <p>Based on this study, inheritable genetic damage/instability identified by FISH testing is a hallmark of a progressive malignant process, and a valuable diagnostic tool for the identification of high risk lesions.</p