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GC-059 Large-Scale Cybersecurity Threat Detection
Get PDFCybersecurity threats are becoming more sophisticated, posing serious risks to critical systems. Traditional intrusion detection systems often fail to manage the scale and complexity of network traffic. This study investigates large-scale threat detection using machine learning in PySpark, utilizing the UNSW-NB15 dataset. It focuses on building scalable models through preprocessing, feature selection, and implementing algorithms like Decision Trees, Naïve Bayes, Random Forest, and Gradient Boosting. Evaluation metrics include accuracy, precision, recall, F1-score, and ROC-AUC, with emphasis on hyperparameter tuning and minimizing false positives. Leveraging PySpark’s distributed computing, the system ensures efficient real-time analysis of vast network data. The research supports modern cybersecurity strategies by enhancing detection reliability and reducing risks from emerging cyber threats
UR-112 Monarch: A Privacy-focused NLP Model for Emotional Pattern Detection
Get PDFIntroducing: Monarch — a privacy-focused deep learning model that interprets emotional patterns in text. Monarch is trained on large, lexicon-based datasets and uses fine-tuned NLP models (BERT) to identify patterns associated with sadness, worry, anger, and distress. It runs entirely offline with no data collection, making it ideal for private use. Monarch evaluates text and returns clear, readable probability scores across emotional categories, giving users insight into emotional trends. Monarch is interpretive, not diagnostic, displaying results based on scientifically backed linguistic patterns. Its potential use in schools could help flag early signs of distress, giving educators a chance to support those in need. Monarch is also suitable for research in linguistics, mental health, and ethical AI implementations
THE POLITICAL GEOGRAPHY OF THE MARINE ENVIRONMENT
Get PDFThe paucity of research .articles by geographers on the political and planning aspects of the marine environment is evident from review of the geographical literature. It is undoubtedly true that there are some geographers who are involved at all levels of policy making in this region, but the fruits of their efforts have not been made available to a professional audience - fifteen articles in three major U.S. geographical journals in the past 16 years is not very commendable. Since 1958 (the year of the first Geneva Law of the Sea Conference), only five articles have appeared in the Annals which relate to policy making in the marine region. Three of the articles focussed on the international law of sea issues1 ,2,3, while land use on the coastal region of the Great Lakes was the topic of one article.4 Minghi mentioned offshore boundaries only in the context of an overall discussion on types of political boundarie
Remembering Dr. Linda Most
Get PDFFeatured article collecting tributes to Dr. Linda Most, who passed away in December 2024. Dr. Most was an associate professor and the former head of the Valdosta State University MLIS program, longtime chair of the Georgia State Board for the Certification of Librarians, and a trustee for the South Georgia Regional Library
Designing an Aerodynamic Shell for the Kennesaw all Weather Autonomous Drone III
No full textThis research details the creation of shell for the Kennesaw all Weather Autonomous Drone III (KWAD III) that is designed to be both aerodynamic and weatherproof, suited for KWAD III’s mission profile as a large, eight-rotor unmanned aerial vehicle. Several airfoil-based and real-world designs are tested using computational fluid dynamics to determine which has the highest aerodynamic efficiency (lift/drag), and then this most efficient design is adjusted for even greater aerodynamic efficiency. Once an acceptable design is reached, a prototype is created with considerations for material choice, manufacturability, mission parameters, and water-resistance. After these requirements are completed, this data is shared with the rest of the KWAD III team to create a functioning shell for KWAD III
Effects of Shorter Blood Flow Restriction Cycles on Perceptual and Cardiovascular Responses
No full textA typical 5-min blood flow restriction (BFR) protocol has been reported as painful, which may limit adherence. PURPOSE: To determine whether shorter and more frequent cuff inflations are preferable to the 5-min BFR protocol. METHODS: Using a within-subject design, participants completed 4 visits. Visit 1 included familiarization. For visits 2-4, participants had 1 of 3 conditions applied on the dominant arm while supine: 5-min (BFR5, 5 cycles), 3-min (BFR3, 7 cycles), or 0-min (CON, 7 cycles) of cuff inflation at 80% arterial occlusion pressure (AOP). After a 5-min rest with the dominant arm abducted 90 degrees, AOP was measured with an automated device. Ratings of pain and perceived discomfort were reported with separate 10-point scales. Heart rate (HR) and oxygen saturation (OSat) were measured with pulse oximetry. At baseline, and in the last 60 seconds of cuff inflation, perceived pain, discomfort, HR, and OSat were recorded. For statistical analysis, change scores (Δ, last cycle-baseline) were compared using one-way Bayesian Repeated Measures ANOVAs. Data reported as mean±standard deviation. RESULTS: 17 participants (22±3yr, 78.0±12.7kg, 171.2±11.7cm) completed this study. ΔPain (A.U., BF10=8.341) was higher in BFR5 (1±2) than both BFR3 (1±1, BF10=2.430) and CON (0±0, BF10=2.700). BFR3 was higher than CON (BF10=1.163). ΔDiscomfort (A.U., BF10=23432.433) was higher for BFR5 (2±2) than BFR3 (1±1, BF10=11.268) and CON (0±0, BF10=3044.322). CON was lower than BFR3 (BF10=5.298). ΔHR (bpm, BF10=1.012) had anecdotal evidence for a difference across BFR5 (4±9), BFR3 (-1±4), and CON (-1±5). ΔOSat (%, BF10=15.700) was similar between BFR5 (-10.750±11.498) and BFR3 (-6.500±8.827, BF10=0.487). CON (0.500±1.624) was higher than BFR5 (BF10=11.393) and BFR3 (BF10=4.160). ΔAOP (mm Hg, BF10=0.296 was similar across BFR5 (-1.375±5.795), BFR3 (1.688±12.552), and CON (1.625±4.843). CONCLUSION: Shorter cuff inflations with additional cycles may improve perceptions, and 3- or 5-min cycles elicit similar changes to the cardiovascular response
Matching Algorithm for More Effective Faculty-Class Schedule Pairings
No full textAssigning faculty to courses is a crucial part of academic planning, as both parts are needed to run a class. However, many factors limit the pairings which makes forming a cohesive schedule more difficult and different from semester to semester. This project aimed to use graph theory to create a scheduling solution using past schedule data to algorithmically assign faculty to courses. We built a bipartite graph with weights being assigned based on prior experiences teaching and use maximal weight matching to distribute course load evenly across faculty. This method improves scheduling efficiency and adapts dynamically, making the process more flexible and effective
Evaluating the Impact of a Mentorship Program on Stress Levels and Transition to Practice Readiness in Nurse Practitioner Students
No full textNurse Practitioners (NPs) transitioning from registered nurses to autonomous practice face numerous challenges, including lack of confidence, job dissatisfaction, high stress, and burnout. Research indicates that mentorship offers crucial guidance, support, and skill development; however, structured programs for NP students remain scarce. A regional NP organization, including both NP students and experienced NPs, presents an ideal setting for a structured mentorship program. The purpose of this study is to develop and implement a mentorship program for NP students through a regional organization and evaluate the effectiveness in reducing stress levels and improving readiness for practice. Participants were recruited from a convenience sample of regional NP organization members as either mentors (NPs with \u3e1 year experience) or mentees (in NP school). After considering inclusion and exclusion criteria, fifteen mentors and fifteen mentees were selected and paired based on mutual interests. For training, participants completed an online “Mentorship Nursing CE Course” and attended virtual orientation. For the 12-week program, mentors were instructed to communicate with mentees online at least weekly and to meet in-person at least monthly to offer guidance and support. Participants completed pre- and post-program PSS and Casey-Fink surveys depending on their role. Quantitative data will be analyzed to compare pre- and post-intervention results. Qualitative data will be gathered through focus interviews and analyzed using thematic analysis. Results are pending program completion. It is hypothesized that participation will reduce stress levels for both roles. Additionally, mentees are expected to show improved readiness for clinical practice, based on Casey-Fink survey scores for role transition experience. The study aims to demonstrate the value of structured mentorship programs in supporting the transition from education to practice for NPs. The findings could inform future initiatives to develop programs to improve NP transition and professional growth, fostering a culture of support and collaboration in practice
Comparative Analysis of Turmerone Compounds in Various Turmeric Food Samples and Supplemental Products using GC/MS
No full textTurmeric (Curcuma longa) is a plant belonging to the ginger family Zingiberaceae. Native to South and Southeast Asia, the golden-yellow spice has been cultivated for dyes, spices, and a variety of health benefits since ancient civilization. Turmerones are responsible for turmeric’s vibrant color, anti-inflammatory and antioxidant properties. With these medicinal properties, turmeric has been added into supplement capsules, immunity shots, and pain relief topical solutions. Turmeric is also widely used in traditional herbal medicine to help with diseases such as asthma and arthritis. We are interested in identifying and evaluating turmerone compounds in ground turmeric, turmeric supplement capsules, and turmeric rhizomes. Ethanol was selected as the extracting solvent. Sonification for 10 minutes was used to improve extraction. Extracted solutions from various samples have been analyzed using gas chromatography-mass spectroscopy (GCMS, Agilent-QP2010). Ar-tumerone, nonaromatic tumerone), and curlone have been identified as the three major turmerone compounds across all samples. They were eluted at 16.01 minutes, 16.23 minutes, and 17.71 minutes, respectively. Nonaromatic turmerone is relatively more abundant in ground turmeric, whereas aromatic turmerone has a higher abundance in turmeric supplement capsules