The Air Force Institute of Technology

The Abilities of Man, Their Nature and Measurement.

Author(s): Holm, Stephanie M; Balmes, John; Gillette, Dan; Hartin, Kris; Seto, Edmund; Lindeman, David; Polanco, Dianna; Fong, Edward | Abstract: BackgroundAsthma is a common childhood disease that leads to many missed days of school and parents' work. There are multiple environmental contributors to asthma symptoms and understanding the potential factors inside children's homes is crucial.MethodsThis is a dual cohort study measuring household particulate matter (PM2.5), behaviors, and factors that influence air quality and asthma symptoms in the urban homes of children (ages 6-10) with asthma; one cohort had cigarette smoke exposure in the home (n = 13) and the other did not (n = 22). Exposure data included measurements every 5 minutes for a month.ResultsIn the entire study population, a large contributor to elevations in indoor PM2.5 above 35 μg/m3 was not using the stove hood when cooking (8.5% higher, CI 3.1-13.9%, pl0.005). Median PM values during cooking times were 0.88 μg/m3 higher than those during non-cooking times (95% CI 0.33-1.42). Mean monthly household PM2.5 level was significantly related to the presence of a cigarette smoker in the home (10.1 μg/m3 higher, 95% CI 5.2-15.1, pl0.001) when controlling for use of the stove hood and proximity to major roadway. There was a trend toward increased odds of persistent asthma with increases in average monthly PM2.5 (OR 1.1, 95% CI 0.97-1.3, p = 0.16).ConclusionsConsideration of only outdoor PM2.5 may obscure potentially modifiable risks for asthma symptoms. Specifically, this preliminary study suggests that cooking behaviors may contribute to the burden of PM2.5 in the homes of children with asthma and thus to asthma symptoms.

/pdf/cooking-behaviors-are-related-to-household-particulate-675i8fsuav.pdf

Cooking behaviors are related to household particulate matter exposure in children with asthma in the urban East Bay Area of Northern California.

According to a study by Cybersecurity Ventures, cybercrime is expected to cost $6 trillion annually by 2021. Most cybersecurity threats access internal networks through infected endpoints. Recently, various endpoint environments such as smartphones, tablets, and Internet of things (IoT) devices have been configured, and security issues caused by malware targeting them are intensifying. Event logs-based detection technology for endpoint security is detected using rules or patterns. Therefore, known attacks can respond, but unknown attacks can be difficult to respond to immediately. To solve this problem, in this paper, local outlier factor (LOF) and Autoencoder detect suspicious behavior that deviates from normal behavior. It also detects threats and shows the corresponding threats when suspicious events corresponding to the rules created through the attack profile are constantly occurring. Experimental results detected eight new suspicious processes that were not previously detected, and four malicious processes and one suspicious process were judged using Hybrid Analysis and VirusTotal. Based on the experiment results, it is expected that the use of operational policies such as allowlists in the proposed model will significantly improve performance by minimizing false positives.

https://www.mdpi.com/2079-9292/9/6/1022/pdf

Anomaly Based Unknown Intrusion Detection in Endpoint Environments

Strategies for Small Business Sustainability by Victor Adoukonou MBA, Strayer University, 2012 MSc, University Montesquieu Bordeaux IV, 2007 MPS, University of Reduit/IFE, 2007 BA, University of Lomé, 2003 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Business Administration Walden University March 2019 Abstract Small businesses represent more than 99% of all employers in the United States, but more than 50% of small businesses have failed before 5 years. Climate change, digitization, and social media contribute to a paradigm shift in consumers’ habits, as more consumers have become environmentally and social justice conscious. Business leaders who are unable to follow the consumers’ trends and changes of habit may notSmall businesses represent more than 99% of all employers in the United States, but more than 50% of small businesses have failed before 5 years. Climate change, digitization, and social media contribute to a paradigm shift in consumers’ habits, as more consumers have become environmentally and social justice conscious. Business leaders who are unable to follow the consumers’ trends and changes of habit may not succeed in sustaining their businesses. The purpose of this multiple case study was to explore strategies owners of small businesses in the District of Columbia use to sustain their businesses for longer than 5 years while fulfilling their firms’ social responsibility obligations. The conceptual framework was the sustainability development theory. Data were collected from 5 small retailers through face-to-face, semistructured interviews, observations, field notes, and reviews of documents related to business sustainability. Data analysis was based on the thematic analysis model, which involved a process of organizing, coding, arranging data into common themes relevant to the research question and interpreting of the information. Member checking was used to enhance the credibility and validity of the data. Emerging themes included business establishment planning, sustainability planning, and sustainability factors use. The results of this study may contribute to positive social change by providing information to entrepreneurs about successful strategies for small business sustainability, which can lead to business owners, employees, and communities living and working in a human-oriented, prosperous, and healthy environment. Strategies for Small Business Sustainability by Victor Adoukonou MBA, Strayer University, 2012 MSc, University Montesquieu Bordeaux IV, 2007 MPS, University of Reduit/IFE, 2007 BA, University of Lomé, 2003 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Business Administration Walden University March 2019 Dedication I dedicate this doctoral study to my mother, Comfort Kossiwa Alagbe, and late father, Ognandon Adoukonou, for being my heroes and my inspirers who taught me to dream big and the sky is not the limit but another step. I also dedicate this study to my family, especially my children. To my children, I urge you to put God first in everything, surround yourselves with positivity, love knowledge, and strive for excellence. Trust in God but believe in yourself. Dream big, chase your dream with hard work and know that you are limitless. May the Lord guide you, bless you, make his face shine upon you, and be gracious to you always. Acknowledgments I am grateful to the Lord for his unending mercy and immeasurable grace. I am very thankful to my chair, Dr. Isabel Wan for the support, patience, and guidance toward the successful completion of this study. I owe a moral debt to Dr. Greg Uche who boosted my confidence at a critical moment of this study. I use this opportunity to thank my URR, Dr. Peter Anthony, my program director, Dr. Susan Davis, and my assigned editor, Ms. Angie Drennen for reviews, corrections, instructions, and words of encouragement. To others not mentioned here, the memories of all your contributions remain in my heart forever. Finally, I pay a special tribute to the Togolese community for giving me the opportunity to lead the Togolese Diaspora in the United States (DTUSA) to the historic milestone of Congressional Recognition. Together, we saved lives, provided jobs, housing, scholarships, and healthcare opportunities and contributed to our community well-being.

/pdf/strategies-for-small-business-sustainability-451ceav1al.pdf

Strategies for Small Business Sustainability

As the number of cyber-attacks continues to grow on a daily basis, so does the delay in threat detection. For instance, in 2015, the Office of Personnel Management discovered that approximately 21.5 million individual records of Federal employees and contractors had been stolen. On average, the time between an attack and its discovery is more than 200 days. In the case of the OPM breach, the attack had been going on for almost a year. Currently, cyber analysts inspect numerous potential incidents on a daily basis, but have neither the time nor the resources available to perform such a task. anomalyDetection aims to curtail the time frame in which anomalous cyber activities go unnoticed and to aid in the efficient discovery of these anomalous transactions among the millions of daily logged events by i) providing an efficient means for pre-processing and aggregating cyber data for analysis by employing a tabular vector transformation and handling multicollinearity concerns; ii) offering numerous built-in multivariate statistical functions such as Mahalanobis distance, factor analysis, principal components analysis to identify anomalous activity, iii) incorporating the pipe operator (%>%) to allow it to work well in the tidyverse workflow. Combined, anomalyDetection offers cyber analysts an efficient and simplified approach to break up network events into time-segment blocks and identify periods associated with suspected anomalies for further evaluation.

/pdf/anomalydetection-implementation-of-augmented-network-log-52tjiupcf8.pdf

anomalyDetection: Implementation of Augmented Network Log Anomaly Detection Procedures

Firewalls, especially at large organizations, process high velocity internet traffic and flag suspicious events and activities. Flagged events can be benign, such as misconfigured routers, or malig...

/pdf/cyber-anomaly-detection-using-tabulated-vectors-and-embedded-2kmyh8q171.pdf

Cyber anomaly detection: Using tabulated vectors and embedded analytics for efficient data mining:

Forensic analysis of logs is one responsibility of an enterprise cyber defense team; inherently, this is a big data task with thousands of events possibly logged in minutes of activity. Logged events range from authorized users typing incorrect passwords to malignant threats. Log analysis is necessary to understand current threats, be proactive against emerging threats, and develop new firewall rules. This paper describes embedded analytics for log analysis, which incorporates five mechanisms: numerical, similarity, graph-based, graphical analysis, and interactive feedback. Topological Data Analysis (TDA) is introduced for log analysis with TDA providing novel graph-based similarity understanding of threats which additionally enables a feedback mechanism to further analyze log files. Using real-world firewall log data from an enterprise-level organization, our end-to-end evaluation shows the effective detection and interpretation of log anomalies via the proposed process, many of which would have otherwise been missed by traditional means.

/pdf/topological-data-analysis-for-enhancing-embedded-analytics-5dxroe5655.pdf

Topological Data Analysis for Enhancing Embedded Analytics for Enterprise Cyber Log Analysis and Forensics

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Cade M. Saie

Author Tools

Chat about Author

Papers

anomalyDetection: Implementation of Augmented Network Log Anomaly Detection Procedures

Cyber anomaly detection: Using tabulated vectors and embedded analytics for efficient data mining:

Topological Data Analysis for Enhancing Embedded Analytics for Enterprise Cyber Log Analysis and Forensics