Image-based Early Detection System for Wildfires

Wildfires are a disastrous phenomenon which cause damage to land, loss of property, air pollution, and even loss of human life. Due to the warmer and drier conditions created by climate change, more severe and uncontrollable wildfires are expected to occur in the coming years. This could lead to a global wildfire crisis and have dire consequences on our planet. Hence, it has become imperative to use technology to help prevent the spread of wildfires. One way to prevent the spread of wildfires before they become too large is to perform early detection i.e, detecting the smoke before the actual fire starts. In this paper, we present our Wildfire Detection and Alert System which use machine learning to detect wildfire smoke with a high degree of accuracy and can send immediate alerts to users. Our technology is currently being used in the USA to monitor data coming in from hundreds of cameras daily. We show that our system has a high true detection rate and a low false detection rate. Our performance evaluation study also shows that on an average our system detects wildfire smoke faster than an actual person.Comment: Published in Tackling Climate Change with Machine Learning workshop, Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022

The risk of stroke according to statin medication compliance in older people with chronic periodontitis: an analysis using the Korea National Health Insurance Service-Senior Cohort Database

OBJECTIVES We investigated the risk of stroke according to statin medication compliance in older people with chronic periodontitis. METHODS Chronic periodontitis patients were extracted from the National Health Insurance Service-Senior Cohort Database from 2002 to 2014. Among 255,056 chronic periodontitis patients, 41,412 patients with statin prescriptions for 28 days or more were included. The study population was divided into the top 25% of medication compliance group (TSG) and the lower 25% of medication compliance group (BSG). After 1:1 propensity score matching was performed, the final number of patients in the BSG and TSG was 6,172 each. To analyze the risk of stroke, a Cox proportional hazard model was performed to calculate hazard ratios (HRs) and 95% confidence intervals (95% CIs) after adjusting for age, sex, income level, hypertension, diabetes, and Charlson comorbidity index. RESULTS In the Kaplan-Meier curve, the disease-free probability was prominently lower in the BSG than in the TSG (p for log-rank= 0.001). The HR in the multivariable-adjusted model for stroke occurrence in the TSG compared to the BSG was 0.79 (95% CI, 0.67 to 0.92; p=0.002). Subgroup analyses showed significant associations between compliance to statin medication and stroke, especially in female, people 85 years or older, and patients with comorbidities. CONCLUSIONS Increasing compliance to statins may reduce stroke risk in older adults with chronic periodontitis. Therefore, in order to increase medication compliance among older people with chronic periodontitis, it is necessary for medical staff to make efforts to provide effective medication guidance

Risk of chronic periodontitis in patients with obstructive sleep apnea in Korea: a nationwide retrospective cohort study

OBJECTIVES The aim of this study was to determine whether the development of chronic periodontitis is more likely among patients who have been newly diagnosed with obstructive sleep apnea (OSA) through an analysis of representative data from the general population. METHODS A nationwide, population-based, retrospective cohort study was conducted using patient records from the Korean National Health Insurance Service database. For the period 2004-2019, patient data were categorized into 2 groups: a diagnosis of OSA (747 subjects) and no diagnosis of OSA (1,494 subjects). Subsequently, 1:2 propensity score matching was performed to ensure the homogeneity of the 2 groups. To analyze the risk of incident chronic periodontitis, a Cox proportional-hazards model was used to calculate hazard ratios (HRs) with 95% confidence intervals (CIs). RESULTS In the Kaplan-Meier curve, the disease-free probability was significantly lower in the OSA group than in the non-OSA group (p for log-rank test=0.001). The crude HR for the association between OSA and chronic periodontitis was 1.29 (95% CI, 1.16 to 1.43). The multivariable-adjusted HR was calculated at 1.28 (95% CI, 1.15 to 1.42). CONCLUSIONS This study confirmed a relationship between OSA and chronic periodontitis. Therefore, OSA patients require oral care to prevent the progression of chronic periodontitis from mild to severe

Validation of a novel cardiac motion correction algorithm for x-ray computed tomography: From phantom experiments to initial clinical experience.

A novel cardiac motion correction algorithm has been introduced recently. Unlike other segmentation-based approaches it is fully automatic and capable of correcting motion artifacts of myocardial wall and other moving structures as well as coronary arteries of the heart. In addition, it requires raw data of only less than a single rotation for motion estimation and correction, which is a significant advantage from the perspective of x-ray exposure and workflow. The aim of this study is to explore the capability of the proposed method through phantoms and in-vivo experiments. Motion correction of coronary arteries and other heart structures including myocardial wall is the main focus of the evaluation. First, we provide a brief introduction to the concept of the motion correction algorithm. Next we address the procedure of our studies using an XCAT phantom and commercially available physical phantoms. Results of XCAT phantom demonstrate that our solution significantly improves the structural similarity of coronary arteries compared to FBP (proposed: 0.94, FBP: 0.77, p<0.001). Besides, it provides significantly lower root mean square error (proposed: 20.27, FBP: 25.33, p = 0.01) of the whole heart image. Mocomo phantom study shows that the proposed method improves the visualization of coronary arteries estimated based on motion score (1: worst, 5: best) from two experienced radiologists (proposed: 3.5, FBP: 2.1, p<0.001). The results of these phantom studies reveal that the proposed has a great potential in handling motion artifacts of other heart structures as well as coronary arteries. Finally, we provide the results of in-vivo animal and human studies. The 3D and 4D heart images show a consistently superior performance in the visualization of coronary arteries along with myocardial wall and other cardiothoracic structures. Based on these findings of our studies, we are of the opinion that our solution has a considerable potential to improve temporal resolution of cardiac CT imaging. This would open the door to innovations in structural or functional diagnosis of the heart

Risk of dementia according to the severity of chronic periodontitis in Korea: a nationwide retrospective cohort study

OBJECTIVES We investigated the risk of dementia in older adults with chronic periodontitis according to the severity of periodontitis. METHODS Data on patients with chronic periodontitis were extracted from the National Health Insurance Service-Senior cohort database from 2002 to 2014. Among 52,728 subjects eligible for inclusion, 11,953 subjects had newly diagnosed mild chronic periodontitis (MCP), and 40,775 subjects had newly diagnosed severe chronic periodontitis (SCP). Two 1:1 propensity score matched cohorts were created with 8,624 patients each in the MCP and SCP groups. To analyze the risk of dementia, a Cox proportional-hazard model was used to calculate hazard ratios with 95% confidence intervals (CIs). RESULTS In the Kaplan-Meier curve, the disease-free probability was significantly lower in the SCP group than in the MCP group (p for log-rank=0.001). In the multivariable-adjusted model, the HR for the occurrence of dementia in the SCP group compared to the MCP group was 1.15 (95% CI, 1.04 to 1.27; p=0.009). A subgroup analysis revealed a significant association between dementia and the severity of periodontitis, especially in subjects who were male, aged ≥70 years, and had comorbidities. CONCLUSIONS Reducing the severity of chronic periodontitis can help to reduce the risk of dementia. Therefore, it is necessary to aggressively conduct early dementia-prevention programs for males under the age of 70 that include dental health to prevent the progression of periodontitis from mild to severe

Development of a neuron-inspired tactile information processing model

Tactile information processing is essential to robotic manipulation such as grasping, lifting and sliding. We developed a tactile signal processing model by mimicking the firing activity of sensory afferents including slowly adapting (SA) and fast adapting (FA) afferents. This model was validated in publically available data by the classification of the type of nine objects from tactile sensor pressure signals while a robot grasped and releases each object. The classification performance of the developed model was compared with traditional methods based on raw sensor signals, spectral analysis, or statistical analysis. Our model performed better than other models when only one of the tactile sensor data were used and similar to the best model when all the tactile sensor data were used. The proposed model could provide an alternative means to process tactile information in a robotic hand

Ultrahigh strength and modulus of polyimide-carbon nanotube based carbon and graphitic fibers with superior electrical and thermal conductivities for advanced composite applications

Development of carbon fibers (CFs) with high strength and high modulus for structural applications in CF-reinforced polymer (CFRP) industry has been a challenge. Herein, we propose a method for manufacturing highly oriented polymer???carbon nanotube (CNT) composite fibers having high strength (4.8 ?? 0.2 GPa), modulus (390 ?? 48 GPa), and electrical conductivity (5.75 ?? 0.84 MS m-1) by a liquid crystalline wet-spinning process. The use of chlorosulfonic acid (CSA) as a solvent for CNTs and polyimide (PI) promotes dispersion and enables the production of high-performance composite fibers. In addition, the functional groups of PI in composite fibers improve the interfacial shear strength with epoxy resin without sizing additives by 72% compared to that of CNT fibers. Carbonization and graphitization of the composite fibers with an optimal ratio of PI (30%) and CNT cause significant improvement in their mechanical (tensile strength; 6.21 ?? 0.3 GPa and modulus; 701 ?? 47 GPa) and thermal properties (496 ?? 38 W m???1 K???1) by reducing voids and improving orientation. We believe that the polymer???CNT composites and their CFs with high strength and high modulus would be the next-generation CFs for aerospace and defense industry