scholarly journals Mining Enrollment Data Using Descriptive and Predictive Approaches

10.5772/14210 ◽  
2011 ◽  
Author(s):  
Fadzilah Siraj ◽  
Mansour Ali
Keyword(s):  
Predictive Approaches ◽  
Enrollment Data

Voice In Ear

2021 ◽  
Vol 5 (1) ◽  
pp. 1-25
Author(s):  
Yang Gao ◽  
Yincheng Jin ◽  
Jagmohan Chauhan ◽  
Seokmin Choi ◽  
Jiyang Li ◽  
...  
Keyword(s):  
User Authentication ◽  
Low Cost ◽  
The Body ◽  
Ear Canal ◽  
Replay Attacks ◽  
Increasing Demand ◽  
The Right ◽  
Sound Conduction ◽  
Enrollment Data ◽  
Secure Authentication

With the rapid growth of wearable computing and increasing demand for mobile authentication scenarios, voiceprint-based authentication has become one of the prevalent technologies and has already presented tremendous potentials to the public. However, it is vulnerable to voice spoofing attacks (e.g., replay attacks and synthetic voice attacks). To address this threat, we propose a new biometric authentication approach, named EarPrint, which aims to extend voiceprint and build a hidden and secure user authentication scheme on earphones. EarPrint builds on the speaking-induced body sound transmission from the throat to the ear canal, i.e., different users will have different body sound conduction patterns on both sides of ears. As the first exploratory study, extensive experiments on 23 subjects show the EarPrint is robust against ambient noises and body motions. EarPrint achieves an Equal Error Rate (EER) of 3.64% with 75 seconds enrollment data. We also evaluate the resilience of EarPrint against replay attacks. A major contribution of EarPrint is that it leverages two-level uniqueness, including the body sound conduction from the throat to the ear canal and the body asymmetry between the left and the right ears, taking advantage of earphones' paring form-factor. Compared with other mobile and wearable biometric modalities, EarPrint is a low-cost, accurate, and secure authentication solution for earphone users.

Predictive approaches to increase absorption of compounds during lead optimisation

2013 ◽  
Vol 8 (10) ◽  
pp. 1225-1238 ◽  
Author(s):  
Klara Valko ◽  
James Butler ◽  
Peter Eddershaw
Keyword(s):  
Lead Optimisation ◽  
Predictive Approaches

Enrollment disparities in cancer clinical trials leading to FDA approvals between 2008 and 2020.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18501-e18501
Author(s):  
Ryan Huu-Tuan Nguyen ◽  
Yomaira Silva ◽  
Vijayakrishna K. Gadi
Keyword(s):  
Prostate Cancer ◽  
United States ◽  
Clinical Trials ◽  
Drug Approval ◽  
The United States ◽  
Cancer Clinical Trials ◽  
Cancer Prevalence ◽  
Fda Approval ◽  
The Us ◽  
Enrollment Data

e18501 Background: Cancer clinical trials based in the United States (US) have lacked adequate representation of racial and ethnic minorities, the elderly, and women. Pivotal clinical trials leading to United States Food and Drug Administration (FDA) approval are often multi-national trials and may also lack generalizability to underrepresented populations in the United States. We determined the racial, ethnic, age, and sex enrollment in pivotal trials relative to the US cancer population. Methods: We reviewed the FDA’s Drug Approvals and Databases for novel and new use drug approvals for breast, colorectal, lung, and prostate cancer indications from 2008 through 2020. Drugs@FDA was searched for drug approval summaries and FDA labels to identify clinical trials used to justify clinical efficacy that led to FDA approval. For eligible trials, enrollment data were obtained from FDA approval summaries, FDA labels, ClinicalTrials.gov, and corresponding journal manuscripts. Enrollment Fraction (EF) was calculated as enrollment in identified clinical trials divided by 2017 SEER cancer prevalence. All data sources were publicly available. Results: From 2008 through 2020, 60 drugs received novel or new use drug approval for breast, colorectal, lung, or prostate cancer indications based on 66 clinical trials with a total enrollment of 36,830. North America accounted for 9,259 (31%) enrollees of the 73% of trials reporting location of enrollment. Racial demographics were reported in 78% of manuscripts, 66% of ClinicalTrials.gov pages, and 98% of FDA labels or approval summaries. Compared with a 0.4% enrollment fraction among White patients, lower enrollment fractions were noted in Hispanic (0.2%, odds ratio [OR] vs White, 0.46; 95% confidence interval [CI], 0.43 to 0.49, P< 0.001) and Black (0.1%, OR 0.29; 95% CI 0.28 to 0.31, P< 0.001) patients. Elderly patients (age ≥ 65 years) were less likely than younger patients to be enrollees (EF 0.3% vs 0.9%, OR 0.27; 95% CI 0.26 to 0.27, P< 0.001) despite accounting for 61.3% of cancer prevalence. For colorectal and lung cancer trials, females were less likely than males (EF 0.7% vs 1.1%, OR 0.66; 95% CI 0.63 to 0.68, P< 0.001) to be enrolled. Conclusions: Black, Hispanic, elderly, and female patients were less likely to enroll in cancer clinical trials leading to FDA approvals from 2008 to 2020. Race and geographic enrollment data were inconsistently reported in journal manuscripts and ClinicalTrials.gov. The lack of appropriate representation of specific patient populations in these key clinical trials limits their generalizability. Future efforts must be made to ensure equitable access, representation, and reporting of enrollees that adequately represent the US population of patients with cancer.

scholarly journals Racial Integration, White Appropriation, and School Choice: The Demise of the Colored Schools of Late Nineteenth Century Brooklyn

2020 ◽  
pp. 009614422093322
Author(s):  
Judith Kafka ◽  
Cici Matheny
Keyword(s):  
Nineteenth Century ◽  
School Choice ◽  
School Desegregation ◽  
Black Families ◽  
Late Nineteenth Century ◽  
Black Schools ◽  
White Families ◽  
Policy Debates ◽  
Late Nineteenth ◽  
Enrollment Data

This study examines school desegregation in late-nineteenth-century Brooklyn from a spatial perspective, analyzing enrollment data and policy debates within the context of the shifting racial and geographic contours of the city. We argue that “choice” on the part of black families only partially explains the demise of designated-black schools during this period. White interests also played a role in the closing of these institutions, as white families and developers sought, and ultimately acquired, control over formerly black spaces. This study contributes to a growing body of research on school desegregation in northern U.S. cities by exploring the perceived benefits of school desegregation for white families and property owners, and by examining how the end of official school segregation may have helped to shape the racial contours of nineteenth-century urban development.

scholarly journals Resuming In-Person Classes under COVID-19: Evaluating Assigned Seating Protocols in Limiting Contacts at Postsecondary Institutions

2021 ◽  
Author(s):  
Daniel Daly-Grafstein ◽  
Patricia Daly ◽  
Reka Gustafson
Keyword(s):  
Returning Students ◽  
Postsecondary Institutions ◽  
Contact Tracing ◽  
Severe Illness ◽  
Post Secondary ◽  
Pandemic Response ◽  
Enrollment Data ◽  
The Impact ◽  
Academic Year ◽  
Reducing Potential

In order to limit the spread of COVID-19, Canadian postsecondary institutions are offering the majority of classes online for the 2020-21 academic year. The goal of Canada's public health pandemic response is to reduce severe illness and mortality from COVID-19 while minimizing social disruption. To achieve this goal, post secondary institutions need practical tools to limit COVID-19 spread and facilitate contact tracing while returning students to in-person instruction. In this paper, we explore the impact of assigned seating for students attending in-person classes in reducing potential contacts. We conduct a variety of seating simulations using student enrollment data and measure the number of potential contacts under each scenario. We find that assigning seats to students significantly reduces the expected number of contacts relative to random seating, making the return to in-person classes more feasible under these scenarios.

Prediction and the aquatic sciences

2001 ◽  
Vol 58 (1) ◽  
pp. 63-72 ◽  
Author(s):  
Michael L Pace
Keyword(s):  
Predictive Models ◽  
Probabilistic Models ◽  
Aquatic Systems ◽  
Environmental Concerns ◽  
Predictive Capability ◽  
Aquatic Science ◽  
Scientific Context ◽  
Key Features ◽  
Predictive Approaches ◽  
Aquatic Sciences

The need for prediction is now widely recognized and frequently articulated as an objective of research programs in aquatic science. This recognition is partly the legacy of earlier advocacy by the school of empirical limnologists. This school, however, presented prediction narrowly and failed to account for the diversity of predictive approaches as well to set prediction within the proper scientific context. Examples from time series analysis and probabilistic models oriented toward management provide an expanded view of approaches and prospects for prediction. The context and rationale for prediction is enhanced understanding. Thus, prediction is correctly viewed as an aid to building scientific knowledge with better understanding leading to improved predictions. Experience, however, suggests that the most effective predictive models represent condensed models of key features in aquatic systems. Prediction remains important for the future of aquatic sciences. Predictions are required in the assessment of environmental concerns and for testing scientific fundamentals. Technology is driving enormous advances in the ability to study aquatic systems. If these advances are not accompanied by improvements in predictive capability, aquatic research will have failed in delivering on promised objectives. This situation should spark discomfort in aquatic scientists and foster creative approaches toward prediction.

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