Evaluation of two NASA biological isolation garments

Biological isolation garments for spacemen returning from lunar flights to prevent contamination from potential lunar microorganisms - evaluation test

Feature Selection on Permissions, Intents and APIs for Android Malware Detection

Malicious applications pose an enormous security threat to mobile computing devices. Currently 85% of all smartphones run Android, Google’s open-source operating system, making that platform the primary threat vector for malware attacks. Android is a platform that hosts roughly 99% of known malware to date, and is the focus of most research efforts in mobile malware detection due to its open source nature. One of the main tools used in this effort is supervised machine learning. While a decade of work has made a lot of progress in detection accuracy, there is an obstacle that each stream of research is forced to overcome, feature selection, i.e., determining which attributes of Android are most effective as inputs into machine learning models. This dissertation aims to address that problem by providing the community with an exhaustive analysis of the three primary types of Android features used by researchers: Permissions, Intents and API Calls. The intent of the report is not to describe a best performing feature set or a best performing machine learning model, nor to explain why certain Permissions, Intents or API Calls get selected above others, but rather to provide a holistic methodology to help guide feature selection for Android malware detection. The experiments used eleven different feature selection techniques covering filter methods, wrapper methods and embedded methods. Each feature selection technique was applied to seven different datasets based on the seven combinations available of Permissions, Intents and API Calls. Each of those seven datasets are from a base set of 119k Android apps. All of the result sets were then validated against three different machine learning models, Random Forest, SVM and a Neural Net, to test applicability across algorithm type. The experiments show that using a combination of Permissions, Intents and API Calls produced higher accuracy than using any of those alone or in any other combination and that feature selection should be performed on the combined dataset, not by feature type and then combined. The data also shows that, in general, a feature set size of 200 or more attributes is required for optimal results. Finally, the feature selection methods Relief, Correlation-based Feature Selection (CFS) and Recursive Feature Elimination (RFE) using a Neural Net are not satisfactory approaches for Android malware detection work. Based on the proposed methodology and experiments, this research provided insights into feature selection – a significant but often overlooked issue in Android malware detection. We believe the results reported herein is an important step for effective feature evaluation and selection in assisting malware detection especially for datasets with a large number of features. The methodology also has the potential to be applied to similar malware detection tasks or even in broader domains such as pattern recognition

Using Toys to Support Infant-Toddler Learning and Development

Being mindful of the basic principles of child development and the role of play, teachers can intentionally select toys to meet young children\u27s unique needs and interests, supporting learning.https://educate.bankstreet.edu/faculty-staff/1006/thumbnail.jp

MANAGERIAL HUMAN CAPITAL AND ORGANIZATIONAL PERFORMANCE

This dissertation focuses on the relationship between the human capital qualities of frontline managers and organizational performance. I draw upon human capital concepts developed in the fields of economics, management, and strategic human resource management (strategic human resources management) to clarify the relationships between human capital and organizational performance for public organizations. I develop a theoretical framework to facilitate a more effective use of human capital concepts for public administration scholars and empirically evaluate several aspects of this framework by assessing the influence of frontline manager human capital on organizational performance. The organizational setting I use to examine this relationship is New York City (NYC) public schools in grades 3-8 (elementary-middle schools) and grades 9-12 (high schools). I focus on principals as the frontline managers in these organizations and examine the influence of a principal’s human capital on organizational performance using structural equation modeling and random effects regression. The most significant results of the model, both statistically and substantively, are a positive association between a principal’s tenure and internal management skills and school performance. The relationship between tenure and school performance is quadratic, however, with the positive effects of tenure diminishing more quickly for high school principals than elementary/middle school principals. The effects of six principal human capital skills in the model differ by contextual factors such as the type of school, the characteristics of the student body, and the interactive effects of these skills

The Birthing Effect

In the United States obstetric care is the most common used provider method for prenatal and labor services currently. Often women are not aware of the various options they may have, or that they have an option other than an obstetrician at all. This thesis explores the various options that women have for their prenatal and childbirth care. As the use of midwives becomes more common, the benefits of their care are being explored. This thesis takes an in-depth look at the benefits and risks of four types of pregnancy-related care providers (obstetricians, midwives, doulas and birthing partners) and discusses why women should consider using a midwife for their pregnancy-related care

Using Communication Techniques In The Low-performing Mathematics Classroom: A Study Of Fractions,decimals,performance And Attitu

Within a low-performing seventh grade mathematics classroom, communication techniques including discourse, collaborative groups, listening, reading, and writing were implemented during a six week period. This study shows how the use of these techniques led to the twenty four students\u27 conceptual understanding of fraction and decimal concepts. This research study provides insight to the deep-seeded beliefs of low-performing students. It provides a record of how the teacher used communication techniques in the classroom and had a strong positive impact on the attitudes and performance of these struggling students

Oral History Interview: Susie H. Guyton

This interview is one of series conducted concerning Oral Histories of African-American women who taught in West Virginia public schools. Susie H. Guyton began teaching in at Bramwell School in West Virginia. She gives us detailed information about her family throughout the interview, including family life during her childhood, her husband and her children, and her family history (which includes family members of different ethnicities). She grew up in Pocahontas County (WV), and tells us about community and social activities in the area. She also gives us detailed information about her education, which includes Bluefield State College, and she tells the interviewers about a bombing at Bluefield State. Her career is a major focus, and this includes problems she faced at school--partially because she was working in the same school as her husband--race relations at the school, and changes she sees in modern students. Race relations in her life is discussed, and she recalls the desegregation of schools and discusses interracial dating. She discusses women\u27s rights and the Women\u27s Movement as well. There are also numerous other topics, such as: church; her self-perceptions; her beliefs on what is proper for women; class divisions among African-Americans; the achievements of her and her family; her thoughts on her life is general and how she has changed over her life; her belief that African- Americans need to be proud of their heritage and work to better their race; as well as many other subjects.https://mds.marshall.edu/oral_history/1578/thumbnail.jp

The Impact of Automation Etiquette on User Performance and Trust in Non-Personified Technology

Previous research has shown that good automation etiquette can yield positive effects on user performance, trust, satisfaction, and motivation. Automation etiquette is especially influential in personified technologies – users have increased etiquette expectations from technology that has human characteristics. Designers deliberately integrate etiquette into personified technologies to account for users’ anthropomorphization and meet user needs. The current study examined the impact of etiquette in non-personified technologies. The study aimed to demonstrate that automation etiquette also affects performance, trust, perceived workload, and motivation in technologies that possess little to no human characteristics. The study used a computer-based automation task to examine good and bad etiquette models and different domain-based perceived task-importance, or “criticality” levels (between-subjects) that contained various stages of automation and automation reliability levels (within-subjects). The study found that bad etiquette automation produced better performance in certain conditions. Confirming previous research, we found that users trust good etiquette automation more than bad etiquette automation in some trust categories. This study provides evidence that automation complexity correlates with automation etiquette’s impact – as automation complexity increases, so does automation etiquette’s impact on performance and in some cases trust. We found that bad automation etiquette can increase user’s subjective workload. Last, we confirmed that our domain-based task criticality manipulation was effective. Future research should examine additional domains, tasks, etiquette delivery mechanisms, and etiquette scales coupled with varied degrees of automation complexity to better understand etiquette’s role in human-automation interaction