Exploration of Machine Learning Classification Models Used for Behavioral Biometrics Authentication

Mobile devices have been manufactured and enhanced at growing rates in the past decades. While this growth has significantly evolved the capability of these devices, their security has been falling behind. This contrast in development between capability and security of mobile devices is a significant problem with the sensitive information of the public at risk. Continuing the previous work in this field, this study identifies key Machine Learning algorithms currently being used for behavioral biometric mobile authentication schemes and aims to provide a comprehensive review of these algorithms when used with touch dynamics and phone movement. Throughout this paper the benefits, limitations, and recommendations for future work will be discussed

The influence of humidity fluxes on offshore wind speed profiles

Abstract. Wind energy developments offshore focus on larger turbines to keep the relative cost of the foundation per MW of installed capacity low. Hence typical wind tur-bine hub-heights are extending to 100 m and potentially be-yond. However, measurements to these heights are not usu-ally available, requiring extrapolation from lower measure-ments. With humid conditions and low mechanical turbu-lence offshore, deviations from the traditional logarithmic wind speed profile become significant and stability correc-tions are required. This research focuses on quantifying the effect of humidity fluxes on stability corrected wind speed profiles. The effect on wind speed profiles is found to be im-portant in stable conditions where including humidity fluxes forces conditions towards neutral. Our results show that excluding humidity fluxes leads to average predicted wind speeds at 150 m from 10 m which are up to 4 % higher than if humidity fluxes are included, and the results are not very sensitive to the method selected to estimate humidity fluxes

Hyperostosis Frontalis Interna: Irregular Skull Ossification in Cadaveric Dissection

Hyperostosis Frontalis Interna (HFI) is an unusual condition characterized by the thickening of the frontal bone of the skull. HFI has been found most often in post-menopausal women, with incidence rates surpassing men by nearly nine times. This abnormal thickening of the skull may compress the cerebrum leading to atrophy, frequent headaches, and cognitive impairment. In this case report, we describe an 88-year-old Caucasian female cadaver that originated with the Body Donor Program of PCOM Georgia with an extensive presentation of HFI. A distinct irregular ossification of the internal surface of the frontal bone was noted bilaterally with visibly demarcated borders. Furthermore, it is of interest to note that HFI may be linked to conditions of kidney disease and this cadaver also displayed another unusual anatomical defect, commonly referred to as a “horse-shoe” kidney. Despite being labeled as a benign entity with no clinical significance, the etiopathology of HFI is not well established. Our group aims to investigate these relationships further with the hopes of providing insight into a condition that may affect as many as 12 percent of the female population

Anatomical investigation following incidental horseshoe kidney finding

Horseshoe kidneys are congenital anomalies that result from the fusion of the right and left kidneys across the midline of the abdomen after both kidneys failed to ascend during fetal development. During a standard educational dissection of 12 donor bodies from the Body Donor Program at PCOM Georgia, a horseshoe kidney was discovered in an 88-year-old female with a reported fatality related to left lung carcinoma, encephalopathy, and hypercalcemia. The circumstances of this discovery presents an opportunity to explore the anatomical arrangement of the congenital malformation in detail. Anatomical dissection and analysis of the neurovascular and renal organization was documented with marked differences from traditional structural arrangement. A parenchymatous isthmus was formed superficial to the abdominal aorta by the fusion of the lower poles of the right and left kidneys. Additionally, other anatomical abnormalities present were identified and recorded. This study could be utilized to inform providers of best practices regarding patients with horseshoe kidneys

Developing and Diagnosing Climate Change Indicators of Regional Aerosol Optical Properties

Given the importance of aerosol particles to radiative transfer via aerosol-radiation interactions, a methodology for tracking and diagnosing causes of temporal changes in regional-scale aerosol populations is illustrated. The aerosol optical properties tracked include estimates of total columnar burden (aerosol optical depth, AOD), dominant size mode (ngstrm exponent, AE), and relative magnitude of radiation scattering versus absorption (single scattering albedo, SSA), along with metrics of the structure of the spatial field of these properties. Over well-defined regions of North America, there are generally negative temporal trends in mean and extreme AOD, and SSA. These are consistent with lower aerosol burdens and transition towards a relatively absorbing aerosol, driven primarily by declining sulfur dioxide emissions. Conversely, more remote regions are characterized by increasing mean and extreme AOD that is attributed to increased local wildfire emissions and long-range (transcontinental) transport. Regional and national reductions in anthropogenic emissions of aerosol precursors are leading to declining spatial autocorrelation in the aerosol fields and increased importance of local anthropogenic emissions in dictating aerosol burdens. However, synoptic types associated with high aerosol burdens are intensifying (becoming more warm and humid), and thus changes in synoptic meteorology may be offsetting aerosol burden reductions associated with emissions legislation

Particle nucleation in a forested environment

Peer reviewe

Atmospheric Drivers of Wind Turbine Blade Leading Edge Erosion: Review and Recommendations for Future Research

Leading edge erosion (LEE) of wind turbine blades causes decreased aerodynamic performance leading to lower power production and revenue and increased operations and maintenance costs. LEE is caused primarily by materials stresses when hydrometeors (rain and hail) impact on rotating blades. The kinetic energy transferred by these impacts is a function of the precipitation intensity, droplet size distributions (DSD), hydrometeor phase and the wind turbine rotational speed which in turn depends on the wind speed at hub-height. Hence, there is a need to better understand the hydrometeor properties and the joint probability distributions of precipitation and wind speeds at prospective and operating wind farms in order to quantify the potential for LEE and the financial efficacy of LEE mitigation measures. However, there are relatively few observational datasets of hydrometeor DSD available for such locations. Here, we analyze six observational datasets from spatially dispersed locations and compare them with existing literature and assumed DSD used in laboratory experiments of material fatigue. We show that the so-called Best DSD being recommended for use in whirling arm experiments does not represent the observational data. Neither does the Marshall Palmer approximation. We also use these data to derive and compare joint probability distributions of drivers of LEE; precipitation intensity (and phase) and wind speed. We further review and summarize observational metrologies for hydrometeor DSD, provide information regarding measurement uncertainty in the parameters of critical importance to kinetic energy transfer and closure of data sets from different instruments. A series of recommendations are made about research needed to evolve towards the required fidelity for a priori estimates of LEE potential.publishedVersio