The Implementation of Machine Learning In The Insurance Industry With Big Data Analytics

This study demonstrates how Machine Learning techniques and Big Data Analytics can be used in the insurance sector. Due to various web technologies, mobile devices, and sensor devices, the amount of data in the insurance sector is currently growing daily. Large amounts of data are known as big data as a result. Volume, Velocity, and volume are three characteristics of big data. Machine Learning plays a significant role in converting data into information. Because Machine Learning has the ability to learn from the input data and is a fundamental part of data analytics tools, it learns from data to provide new insights, predictions, and decisions from vast amounts of data. In the insurance sector, machine learning has a wide range of uses, such as customer segmentation, fraud detection, customer retention, claim processing, and claim review. As a result of this study, machine learning creates various prediction models for the insurance industry such as AdaBoost, Naïve Bay, K-Nearest Neighbor, and Decision Tree. As a result, Machine Learning is currently seen as a fundamental game changer for insurance businesses. The potential use of machine learning in insurance businesses will be further investigated by integrating big data tools

Woody Plant Invasion into the Freshwater Marl Prairie Habitat of the Cape Sable Seaside Sparrow: Final Report

In the fall of 2005, U.S. Fish and Wildlife Services (USFWS) contracted with Florida International University (FIU) to study the physical and biological drivers underlying the distribution of woody plant species in the marl prairie habitat of the Cape Sable Seaside Sparrow (CSSS). This report presents what we have learned about woody plant encroachment based on studies carried out during the period 2006-2008. The freshwater marl prairie habitat currently occupied by the Cape Sable seaside sparrow (CSSS; Ammodramus maritimus mirabilis) is a dynamic mosaic comprised of species-rich grassland communities and tree islands of various sizes, densities and compositions. Landscape heterogeneity and the scale of vegetative components across the marl prairie is primarily determined by hydrologic conditions, biological factors (e.g. dispersal and growth morphology), and disturbances such as fire. The woody component of the marl prairie landscape is subject to expansion through multiple positive feedback mechanisms, which may be initiated by recent land use change (e.g. drainage). Because sparrows are known to avoid areas where the woody component is too extensive, a better understanding of invasion dynamics is needed to ensure proper management

Effect of Hydrologic Restoration on the Habitat of The Cape Sable Seaside Sparrow, Annual Report of 2003-2004

Following on our previous year’s work on ‘Effect of hydrologic restoration on the habitat of the Cape Sable seaside sparrow (CSSS)’, we presented first year results at the Cape Sable seaside sparrow – fire planning workshop at Everglades National Park in December 2003. Later, with almost the same set of crews as in the previous year, we started field work in the first week of January and continued till May 26, 2004. Protocols for sampling topography and vegetation in 2004 were identical to the previous year. In the early season, we completed topographic surveys along two remaining transects, B and E (~16.5 km), and vegetation surveys along three transects, D, E and F (~10.8 km), leaving only the vegetation sampling on transects B and C to be completed in 2005. During April and May, vegetation sampling was completed at 230 census sites, making the total of 409 CSSS census sites for which we have complete vegetation data. We updated data sets from both 2003 and 2004, and analyzed them together using cluster analysis, ordination, weighted-averaging regression and analysis of variance, as we had in 2003. Additionally, we used logistic regression to examine the effect of vegetation structural parameters on the recent occurrence of CSSS. We also analyzed vegetation observations recorded by the sparrow census team in 1981 and annually between 1992 and 2004 to assess historical patterns of vegetation change in CSSS habitat

Effect of Hydrologic Restoration on the Habitat of The Cape Sable Seaside Sparrow, Annual Report of 2002-2003

After developing field sampling protocols and making a series of consultations with investigators involved in research in CSSS habitat, we determined that vegetationhydrology interactions within this landscape are best sampled at a combination of scales. At the finer scale, we decided to sample at 100 m intervals along transects that cross the range of habitats present, and at the coarser scale, to conduct an extensive survey of vegetation at sites of known sparrow density dispersed throughout the range of the CSSS. We initiated sampling in the first week of January 2003 and continued it through the last week of May. During this period, we established 6 transects, one in each CSSS subpopulation, completed topographic survey along the Transects A, C, D, and F, and sampled herb and shrub stratum vegetation, soil depth and periphyton along Transects A, and at 179 census points. We also conducted topographic surveys and completed vegetation and soil depth sampling along two of five transects used by ENP researchers for monitoring long-term vegetation change in Taylor Slough. We analyzed the data by summarizing the compositional and structural measures and by using cluster analysis, ordination, weighted averaging regression, and weighted averaging calibration. The mean elevation of transects decreased from north to south, and Transect F had greater variation than other transects. We identified eight vegetation assemblages that can be grouped into two broad categories, ‘wet prairie’ and ‘marsh’. In the 2003 survey, wet prairies were most dominant in the northeastern sub-populations, and had shorter inferred-hydroperiod, higher species richness and shallower soils than marshes, which were common in Subpopulations A, D, and the southernmost regions of Sub-population B. Most of the sites at which birds were observed during 2001 or 2002 had an inferred-hydroperiod of 120-150 days, while no birds were observed at sites with an inferred-hydroperiod less than 120 days or more than 300 days. Management-induced water level changes in Taylor Slought during the 1980’s and 1990’s appeared to elicit parallel changes in vegetation. The results described in detail in the following pages serve as a basis for evaluating and modifying, if necessary, the sampling design and analytical techniques to be used in the next three years of the project

Effect of Hydrologic Restoration on the Habitat of The Cape Sable Seaside Sparrow, Annual Report of 2004-2005

The major activities in Year 3 on ‘Effect of hydrologic restoration on the habitat of the Cape Sable seaside sparrow (CSSS)’ included presentations, field work, data analysis, and report preparation. During this period, we made 4 presentations, two at the CSSS – fire planning workshops at Everglades National Park (ENP), one at the Society of Wetland Scientists’ meeting in Charleston, SC, and a fourth at the Marl Prairie/CSSS performance measure workshop at ENP. We started field work in the third week of January and continued till June 3, 2005. Early in the field season, we completed vegetation surveys along two transects, B and C (~15.1 km). During April and May, vegetation sampling was completed at 199 census sites, bringing to 608 the total number of CSSS census sites with quantitative vegetation data. We updated data sets from all three years, 2003-05, and analyzed them using cluster analysis and ordination as in previous two years. However, instead of weighted averaging, we used weighted-averaging partial least square regression (WA-PLS) model, as this method is considered an improvement over WA for inferring values of environmental variables from biological species composition. We also validated the predictive power of the WA-PLS regression model by applying it to a sub-set of 100 census sites for which hydroperiods were “known” from two sources, i.e., from elevations calculated from concurrent water depth measurements onsite and at nearby water level recorders, and from USGS digital elevation data. Additionally, we collected biomass samples at 88 census sites, and determined live and dead aboveground plant biomass. Using vegetation structure and biomass data from those sites, we developed a regression model that we used to predict aboveground biomass at all transects and census sites. Finally, biomass data was analyzed in relation to hydroperiod and fire frequency

Optoelectronics with electrically tunable PN diodes in a monolayer dichalcogenide

One of the most fundamental devices for electronics and optoelectronics is the PN junction, which provides the functional element of diodes, bipolar transistors, photodetectors, LEDs, and solar cells, among many other devices. In conventional PN junctions, the adjacent p- and n-type regions of a semiconductor are formed by chemical doping. Materials with ambipolar conductance, however, allow for PN junctions to be configured and modified by electrostatic gating. This electrical control enables a single device to have multiple functionalities. Here we report ambipolar monolayer WSe2 devices in which two local gates are used to define a PN junction exclusively within the sheet of WSe2. With these electrically tunable PN junctions, we demonstrate both PN and NP diodes with ideality factors better than 2. Under excitation with light, the diodes show photodetection responsivity of 210 mA/W and photovoltaic power generation with a peak external quantum efficiency of 0.2%, promising numbers for a nearly transparent monolayer sheet in a lateral device geometry. Finally, we demonstrate a light-emitting diode based on monolayer WSe2. These devices provide a fundamental building block for ubiquitous, ultra-thin, flexible, and nearly transparent optoelectronic and electronic applications based on ambipolar dichalcogenide materials.Comment: 14 pages, 4 figure

Validation of digital pathology imaging for primary histopathological diagnosis

Aims: Digital pathology (DP) offers advantages over glass slide microscopy (GS), but data demonstrating a statistically valid equivalent (i.e. non-inferior) performance of DP against GS are required to permit its use in diagnosis. The aim of this study is to provide evidence of non-inferiority. Methods and results: Seventeen pathologists re-reported 3017 cases by DP. Of these, 1009 were re-reported by the same pathologist, and 2008 by a different pathologist. Re-examination of 10 138 scanned slides (2.22 terabytes) produced 72 variances between GS and DP reports, including 21 clinically significant variances. Ground truth lay with GS in 12 cases and with DP in nine cases. These results are within the 95% confidence interval for existing intraobserver and interobserver variability, proving that DP is non-inferior to GS. In three cases, the digital platform was deemed to be responsible for the variance, including a gastric biopsy, where Helicobacter pylori only became visible on slides scanned at the ×60 setting, and a bronchial biopsy and penile biopsy, where dysplasia was reported on DP but was not present on GS. Conclusions: This is one of the largest studies proving that DP is equivalent to GS for the diagnosis of histopathology specimens. Error rates are similar in both platforms, although some problems e.g. detection of bacteria, are predictable