26400 research outputs found
Sort by
Improving Cyber Defense Using Detailed Bayesian Models Of Attacker Reconnaissance.
Get PDFThe continued success of cyber-attacks motivates the need for continued innovation in cyber defense. In particular, there is a need for novel methods to mitigate attacker reconnaissance, usually the first stage in planning an attack. One of the few general approaches in this stage is using deception and information manipulation to affect what the attacker can learn about a system or network. Existing work in moving target defense, game-theoretic models of cyber deception/camouflage, and adversarial learning has provided a framework for optimizing deception strategies. However, most of the current literature is based on limited models of how attackers actually perform reconnaissance and form beliefs about key information. These models lack the detail and realism necessary to make the best use of deception strategies and resources. I propose a framework for more targeted deception strategies to counter reconnaissance, based on developing more detailed Bayesian models of attacker reconnaissance and belief formation.
My proposed approach has three main components. First, I focus on the problem of detecting reconnaissance activities. I discuss difficulties in detection and introduce new techniques to improve the feasibility of detecting specific types of reconnaissance. Second, I address network traffic analysis and propose new methods for identifying the specific features of network traffic that are most useful for attackers in predicting specific network characteristics. I analyze how adversaries interpret and infer information from the collected features and propose a specific process to construct detailed Bayesian belief networks to model how attackers form specific beliefs based on available network observations. I demonstrate this approach on a case study using real network traffic data. Finally, I show how these models can be used to improve defense, specifically optimizing feature deception strategies that select specific targeted features and values for cyber deception. I propose a methodology using Bayesian Multinomial Logistic Regression (BMLR) and optimize feature deception for specific cases, and show an initial evaluation based on a case study using feature deception to mask operating system types.
The key findings of this study are multifaceted. First, the study observed a significant decline in the F1-score for identifying various operating systems such as Linux, Mac, Windows 10, and Windows Vista when these systems were mimicked to appear as different operating systems. The F1-scores dropped below 0.2, indicating a substantial impact of feature changes on operating system identification. This decline validates the algorithm\u27s effectiveness in influencing and altering the perceived identity of different operating systems through targeted feature manipulation. Moreover, the time efficiency of the algorithm was assessed by measuring the time required to identify and modify feature values to achieve deception for larger datasets. The results underscore the computational efficiency of the deception algorithm in processing substantial data volumes. However, for extremely large datasets, the study suggests that there might be a need for more advanced and efficient processing techniques to maintain the algorithm\u27s performance and effectiveness. This analysis demonstrates the algorithm\u27s robust capability to effectively modify system appearances, making it a powerful tool in cyber defense strategies
Prevalence of and Influences for Incorporating Clinically-Relevant Spanish into Doctor of Physical Therapy Programs
Get PDFIntroduction. The United States has 63.7 million Hispanic/Latino individuals, and approximately 40% of Spanish speakers have limited English proficiency (LEP). Patient-provider language discordance is a major contributor towards health disparities. Hence, many health professions educators offer clinically-relevant Spanish. The primary study purposes were to: 1) identify the prevalence of Doctor of Physical Therapy (DPT) programs in the United States that incorporate clinically-relevant Spanish language learning in their curriculum; and 2) describe how DPT programs incorporate Spanish language learning in their curriculum.
Review of Literature. Researchers in a 2014 report identified 12 DPT programs offering Spanish; however, the current prevalence is unknown. Additionally, a gap exists in the literature regarding Spanish language instruction approaches, and if the methods align with Second-Language Acquisition (SLA) best practices.
Subjects. Program directors or full-time core faculty from 27 accredited US-based DPT programs.
Methods. The researchers sent an email request to complete a 31-question survey to 270 accredited DPT programs, and then searched DPT curricular plans on the non-responding programs’ websites. Descriptive statistics were used for analysis.
Results. Six of 27 responding programs (22.2%) offered Spanish. Additionally, 35 programs were identified via website search, totaling 41 programs offering Spanish (15.2%). Twenty-five of the total 41 programs (61%) incorporated Spanish via elective course. Five of 6 responding programs that offered Spanish (83.3%) stated they desired to serve the program’s community and 3 (50%) were influenced by the growing Spanish-speaking population. Five of the 6 (83.3%) assessed oral/aural proficiency with a post-test. The 6 responding programs offering Spanish averaged 7.2 of 13 principles of SLA best practices (range=4-11).
Discussion and Conclusion. There has been over a 3-fold increase in DPT programs offering Spanish, but more attention is warranted regarding standardized assessment of Spanish proficiency. Improving physical therapists’ Spanish proficiency may help reduce health disparities caused by language barriers
Effects of using external biofeedback in improving ankle kinematics in those with chronic ankle instability compared to conventional therapy without external biofeedback: A systematic review
Get PDFI. Introduction: Lateral ankle sprains are amongst the most common injuries to occur in athletes and the general population alike. While most can recover without complications, there exists a considerable risk of recurrent injury which can result in ongoing difficulties related to pain, function, and overall quality of life. This high recurrence rate is due to excessive lateral deviations in the location of pressure-related variables in the foot. Ongoing instability of the foot, known as chronic ankle instability (CAI), results due to these abnormal gait and ankle kinematics which causes significantly greater inversion of the foot during initial contact of gait. Several rehabilitation options are available for those with this debilitating condition, with external biofeedback being one of these. Though previous work has outlined the use that this intervention has on gait mechanics, there is yet to be a systematic review which gathers results from previous studies to draw thorough conclusions about its use in CAI. This article systematically reviews trials that summarize and evaluate the effectiveness of this treatment for the rehabilitation of this condition to draw such conclusions.
II. Methods: A combination of literature from peer-reviewed scientific journals were analyzed to assess the effect sizes of using conservative treatment for chronic ankle instability with and without the addition of external biofeedback. A systematic review of chronic ankle instability will help identify whether the addition of this intervention alongside other treatments contributes to a clinically significant change in abnormal gait deviations and kinematics, which in turn may lead to positive change in symptoms for those involved.
III. Results: A total of 8 studies, including 155 participants, were collected for review. Compared to control groups, patients with CAI who engaged in external biofeedback treatments had clinically significant alterations in center of pressure, peak pressure, and pressure time integral measurements towards the medial side of the foot away from inversion (p \u3c 0.05); the position often associated with CAI.
IV. Discussion: The provision of external biofeedback resulted in positive changes in several important gait and weight bearing variables, with this likely due to the provision of an external focus of attention for those displaying severe deficits in proprioceptive ability which enabled the activation of evertor musculature. The resulting medial shift in the variables discussed alongside greater activation of the evertor muscles caused participants with CAI to employ a greater degree of protective eversion during gait activities. This change in gait kinematics and ankle positioning is more consistent with healthy individuals who have a greater proportion of pressure data points in the posteromedial foot quadrant, with this being correlated with less frequent recurrence of ankle sprains and thus instability at the ankle.
V. Conclusion: The results of this systematic review indicate clinically significant improvements in ankle kinematics with the use of external biofeedback such as visual, auditory, and vibration/tactile feedback. The studies within this SR demonstrated findings of alterations in center of pressure (COP), peak pressure, and pressure time integral of the ankle. It is possible to conclude that the utilization of external biofeedback may improve ankle kinematics in individuals with CAI by enabling medial shifts in the variables discussed and therefore reducing the causal impact that excessive inversion and lateral pressure shifts have on causing recurrent lateral ankle sprains
The Effects of Mediterranean Diet on the Epileptic Population with Depression
Get PDFBackground: People with epilepsy often develop depression during the course of their disease progression. This condition is multifactorial, often related to the unpredictability of their disease, the lack of control on their symptoms, and the medications they use to treat their seizures. Mental health services continue to be insufficient for our growing border region, and patients with epilepsy, often will lack the proper mental health management due to mental health provider shortage. Multiple medications can be used to successfully treat depression in the general population, however people with epilepsy often will struggle as anti-seizure drugs can interact with antidepressants. Also, the financial burden of multiple medications makes it more challenging for these patients to receive successful care.
Aims/Methods: Bayes et al., 2022, showed the implementation of a low inflammation diet like the Mediterranean Diet (MD) can decrease symptoms of depression if properly followed. At a mainly Hispanic border town’s Neurology clinic, a quality improvement (QI) project was implemented to address depression-like symptoms on epileptic patients. Patients were screened for depression with the Neurological Disorders Depression Inventory in Epilepsy (NDDIE) tool. If they scored 15 points or higher, they were referred to a mental health provider and prescribed the MD while waiting for their appointment. The project was implemented over 6 weeks.
Results: Results revealed most patients remained stable on their depressive symptomology, and furthermore some improved on their scores after a short period of implementation of the MD.
Conclusions/ Implications for practice: If more time were allowed for these patients to follow the MD, the project will most likely demonstrate that, a more significant improvement can be achieved
What a pain in the BACK!!!
Get PDFBackground: After reviewing my 10-day Practice Assessment Log (PAL) and documenting a clinical needs assessment of my practice, I documented, reviewed, and reflected upon my findings. In my current practice we address low back pain with Gabapentin 300mg TID and Methocarbamol 500mg BID. The present outcome is that most patients do not experience much in relief.
Aims/Methods: My Practice Improvement Project (PIP), validated via research, points to adding Celebrex 100mg BID, an anti-inflammatory, to patient’s regimen. I carried out this project for 30 days with a 2-week follow-up. The Translational Framework Knowledge-to-Action model was used to help me prepare the implementation of my new found knowledge to my PIP. Using the PDSA QI model allowed for me to be able to achieve the implementation. At the start of the project, January 2024, I assessed patients with complaints of, diagnosis of low back pain and added Celebrex 100mg BID to their medication regimen (after ensuring there are no contra indications), this concluded to be 13 patients in total.
Results: After the 2-week follow up I found that three patients were not able to complete the prescribed regimen because the medication was too expensive or they stopped/did not take as indicated prior to follow up. Out of the ten patients that remained the data showed that 8 out of the 10 patient’s numeric rating scale (NRS) pain scores showed great improvement from scores collected at initial assessment.
Conclusions: The conclusion is then that adding Celebrex (NSAID) to patient’s medication regimen does indeed help to better control patient’s back pain. Implications for practice: This will allow for patient to have less days lost to not being able to perform tasks due to pain getting in the way of everyday activities that may include but not limited to house chores, exercise, work, school, family, and just personal hygiene
Initiating Early Review of Paxlovid Criteria with Suspected COVID + patients to Reduce Disqualification of Anti-Viral Therapy
Get PDFIntroduction: Nearly 742 million cases of COVID have been detected since the beginning of the COVID-19 pandemic and over 6 million people have lost their lives due to COVID or a COVID related illness. While Arizona’s COVID-19 emergency declaration ended on March 30, 2022, there are still nearly 100,000 new cases each week as of September 2023. Nirmatrelvir-ritonavir (Paxlovid) is an outpatient antiviral medication recommended for adults with mild-to-moderate COVID-19 who have elevated risk of severe illness.
Aim/Methods: Regardless of vaccination status, taking Paxlovid within 5 days of diagnosis reduces the hospitalization rate by 51%. The majority of COVID positive patients not eligible to take Paxlovid is due to the missed 5-day window from symptom onset in which Paxlovid treatment must be initiated. This often happens because of delayed lab results or an inability to provide education and screen potential participants.
Results/Conclusion: Specifically, the Native American population is at high risk for hospitalization or severe progression of COVID infection due to the numerous comorbidities including hypertension, diabetes, obesity, alcoholism, and mental health disorders. By improving the process regarding screening for Paxlovid and ensuring necessary labs are done and patient meets criteria, it will allow more patients within the Gila River Indian Community to benefit from Paxlovid treatment and will decrease the disqualification rate due to the missed 5-day initiation window for Paxlovid start from date of symptom onset.
Implication to Practice: With these changes, the expected outcome is to increase the number of patients who qualify and accept Paxlovid treatment and report a positive response to the anti-viral regimen and report no hospitalization or worsening progression of symptoms due to COVID-19
Analysis Of Additively Manufactured Inconel 718 Combustion Behavior In Promoted Oxygen Environments
Get PDFPromoted combustion testing is a vital tool for engineers to establish the combustion and flammability characteristics of materials (metallic or otherwise) in oxygen enriched environments. Historically, much of the established data for metallic promoted combustion has been with regards to materials in their cast and wrought forms. However, with the emergence of additive manufacturing as a preferred method of fabrication, the need exists to evaluate how metals in that form behave. Recent testing has demonstrated that even if a metal or alloy is nominally the same with regards to chemistry, flammability between samples in the wrought form can differ significantly from those which were additively manufactured. This has provided a rationale to evaluate what underlying principles and conditions may be driving such a variability in flammability response. This work will serve as an analysis and characterization of one specific alloy (the nickel-based superalloy Inconel 718), a material popular for aerospace applications such as liquid fueled rocket components and turbine engines. Promoted combustion testing (per the ASTM G124 standard) was conducted on samples of both wrought and selective laser melted (SLM) fabrication, to provide comparison of flammability response between materials produced by each manufacturing method. Additionally, post-build treatments were applied to test samples to identify any effects on performance provided by hot isostatic pressing (HIP), oxygen-getting wrapping during HIP, stress relieving, and solutionizing/aging heat treatments. This project will utilize optical and scanning electron microscopy, energy dispersive spectroscopy, x-ray diffraction, and metallography to identify the differences between flammability behavior of additively manufactured and wrought Inconel 718. This information is key for engineers to understand the safety and oxygen compatibility of this material while in use by an industry which will undoubtedly increase the adoption and use of additive manufacturing as a primary means for fabrication
How to Make a Neural Network Learn from a Small Number of Examples -- and Learn Fast: An Idea
Get PDFCurrent deep learning techniques have led to spectacular results, but they still have limitations. One of them is that, in contrast to humans who can learn from a few examples and learn fast, modern deep learning techniques require a large amount of data to learn, and they take a long time to train. In this paper, we show that neural networks do have a potential to learn from a small number of examples -- and learn fast. We speculate that the corresponding idea may already be implicitly implemented in Large Language Models -- which may partially explain their (somewhat mysterious) success
In-Between Frame Generation for 2D Animation Using Generative Adversarial Networks
No full textTraditional 2D animation remains a largely manual process where each frame in a video is hand-drawn, as no robust algorithmic solutions exist to assist in this process. This project introduces a system that generates intermediate frames in an uncolored 2D animated video sequence using Generative Adversarial Networks (GAN), a deep learning approach widely used for tasks within the creative realm. We treat the task as a frame interpolation problem, and show that adding a GAN dynamic to a system significantly improves the perceptual fidelity of the generated images, as measured by perceptual oriented metrics that aim to capture human judgment of image quality. Moreover, this thesis proposes a simple end-to-end training framework that avoids domain transferability issues that arise when leveraging components pre-trained on natural video. Lastly, we show that the two main challenges for frame interpolation in this domain, large motion and information sparsity, interact such that the magnitude of objects\u27 motion across frames conditions the appearance of artifacts associated with information sparsity