CNN and Transfer Learning Methods for Enhanced Dermatological Disease Detection

Since skin diseases generally badly affect lives, the earlier and more accurate the diagnosis, the better the chances of effective treatment and a better prognosis. Deep learning applications, especially CNNs, has revolutionized the domain of disease classification, significantly increasing the accuracy of diagnoses for such common conditions and facilitating early interventions. The huge success behind the ongoing project motivated advancements of the developing in CNN techniques towards detection of skin disease by using the concept of Transfer Learning. So, the older models, which had employed it for detecting Eczema and Psoriasis based on the architectures involving deep CNNs. The Inception ResNet v2 architecture improved the accuracy of that model, with some practical implementations via smartphone integration and web server integration. Some of those innovations are as follows in our project. The earlier work used different CNN architectures. Our approach involved Transfer Learning with a pre-trained ResNet50 model to try to improve performance and efficiency using features learned from large-scale datasets. This reduce the complexity and enhance the accuracy. Besides Transfer Learning adaptation, our project encompasses elaborate preprocessing techniques like resizing, normalization, and data augmentation in fine-tuning the dataset for further model fine-tuning. It has 97.6% accuracy, 95% precision, 99.4% recall, and 97.4% F1-score. rad-CAM techniques have been employed to visualize and interpret model predictions. This final model has been a pragmatic and accessible tool for early detection and diagnosis of skin disease. The feature here is an attempt to provide a more accurate, efficient, and user-friendly diagnostic solution through the incorporation of advanced methods of Transfer Learning and visualization

First insights Into the fine-scale movements of the Sandbar Shark, Carcharhinus plumbeus

The expanding use of biologging tags in studies of shark movement provides an opportunity to elucidate the context and drivers of fine-scale movement patterns of these predators. In May 2017, we deployed high-resolution biologging tags on four mature female sandbar sharks Carcharhinus plumbeus at Ningaloo Reef for durations ranging between 13 and 25.5 h. Pressure and tri-axial motion sensors within these tags enabled the calculation of dive geometry, swimming kinematics and path tortuosity at fine spatial scales (m-km) and concurrent validation of these behaviors from video recordings. Sandbar sharks oscillated through the water column at shallow dive angles, with gliding behavior observed in the descent phase for all sharks. Continual V-shaped oscillatory movements were occasionally interspersed by U-shaped dives that predominately occurred around dusk. The bottom phase of these U-shaped dives likely occurred on the seabed, with dead-reckoning revealing a highly tortuous, circling track. By combining these fine-scale behavioral observations with existing ecological knowledge of sandbar habitat and diet, we argue that these U-shaped dives are likely to be a strategy for bentho-pelagic foraging. Comparing the diving geometry of sandbar sharks with those of other shark species reveals common patterns in oscillatory swimming. Collectively, the fine-scale movement patterns of sandbar sharks reported here are consistent with results of previous biologging studies that emphasize the role of cost-efficient foraging in sharks

Comparison of Material Properties Made by 3D-Printing Process Using Two Different Materials

3D Printing Process: refers to processes in which material is joined or solidified under computer control to create a three-dimensional object, with material being added together. In this Study, a Prototype model is designed using solid works software and have 3d printed the prototype using two different materials like PLA (Poly-Lactic Acid) and ABS (Acrylonitrile butadiene styrene). The 3D printed prototypes are then tested by using compression testing machine to find out there mechanical properties

Some old movies become classics - a case study determining the scientific value of ROV inspection footage on a platform on Australia's North West Shelf

© 2018 Thomson, Fowler, Davis, Pattiaratchi and Booth. The global oil and gas industry holds a vast archive of Remotely Operated Vehicle (ROV) inspection footage potentially containing useful long-term data on marine biological communities. With the upcoming era of decommissioning of oil and gas structures, it is timely to assess the usefulness of this footage for researching these communities. We used ROV inspection footage to characterize the sessile invertebrates and fishes associated with the Goodwyn Alpha Production Platform (GWA) on the North West Shelf of Australia between depths of 10 and 125 m during 2006 and 2008. Depth was a major driver of invertebrate assemblages, most likely due to specific requirements such as light, and differences between years were most likely from the physical detachment of species by cyclones and internal waves. Phototrophic species were mostly limited to the upper 50 m of the platform, including the hard coral Pocillopora sp. and the soft corals Nephthea sp. and Scleronephthya sp. In contrast, heterotrophic species including sponges, anemones, bryozoans, hydroids, bivalves such as Lopha folium and the hard coral Tubastrea spp., were distributed across all depths. We observed 1791 fish from at least 10 families and 19 species, including commercial species such as crimson seaperch (Lutjanus erythropterus), red emperor (L. sebae), saddle-tailed seaperch (L. malabaricus), mangrove jack (L. argentimaculatus) and trevally (Caranx spp.). Fish density increased significantly with depth during 2008, from a mean of 23 fish/50 m2 between 10 and 25 m to 3373 fish/50 m2 at 125 m, where small unidentified baitfish were abundant. The highest densities of commercial species occurred between 25 and 75 m depth, suggesting that mid-depth platform sections had high habitat value, a consideration when selecting decommissioning options. The greatest difficulties using the video were the poor lighting and resolution that inhibited our ability to identify sessile species with high taxonomic precision. However, the footage was useful for evaluating high-level biodiversity of the platform, understanding how fish and invertebrate communities changed with depth and comprehending the dynamic nature of the invertebrate community over time. Understanding the habitat value of structures will be necessary for making environmentally sound decommissioning decisions in the future

Modeling & Analysis of Cylinder Block for V8 Engine

Heat losses are a major limiting factor for the efficiency of internal combustion engines. Furthermore, heat transfer phenomena cause thermally induced mechanical stresses compromising the reliability of engine components. The ability to predict heat transfer in engines plays an important role in engine development. Today, predictions are increasingly being done with numerical simulations at an ever earlier stage of engine development. These methods must be based on the understanding of the principles of heat transfer.In the present work  V type multi cylinder engine assembly is modeled by CATIA V5. This model is imported to ANSYS and done the steady state Thermal and Structural analysis for predicting thermal stress, temperature distribution by comparing with advance carbon material. (FU4270) from existing material (Aluminum).design a better cooling system. Fast transient heat flux between the combustion chamber and the solid wall must be investigated to understand the effects of the non-steady thermal environment. combustion (IC) engines. Locating hot spots in a solid wall can be used as an impetus to Heat transfer is one major important aspect of energy transformation in internal

The influence of reef topography on storm-driven sand flux

Natural formations of rock and coral can support geologically controlled beaches, where the beach dynamics are significantly influenced by these structures. However, little is known about how alongshore variations in geological controls influence beach morphodynamics. Therefore, in this study we focus on the storm response of a beach (Yanchep in south Western Australia) that has strong alongshore variation in the level of geological control because of the heterogeneous calcarenite limestone reef. We used a modified version of XBeach to simulate the beach morphodynamics during a significant winter storm event. We find that the longshore variation in topography of the reef resulted in: (1) strong spatial difference in current distribution, including areas with strong currents jets; and (2) significant alongshore differences in sand flux, with larger fluxes in areas strongly geologically controlled by reefs. In particular, this resulted in enhanced beach erosion at the boundary of the reef where strong currents jet-exited the nearshore

CNN and Transfer Learning methods for enhanced dermatological disease detection

Since skin diseases generally badly affect lives, the earlier and more accurate the diagnosis, the better the chances of effective treatment and a better prognosis. Deep learning applications, especially CNNs, has revolutionized the domain of disease classification, significantly increasing the accuracy of diagnoses for such common conditions and facilitating early interventions. The huge success behind the ongoing project motivated advancements of the developing in CNN techniques towards detection of skin disease by using the concept of Transfer Learning. So, the older models, which had employed it for detecting Eczema and Psoriasis based on the architectures involving deep CNNs. The Inception ResNet v2 architecture improved the accuracy of that model, with some practical implementations via smartphone integration and web server integration. Some of those innovations are as follows in our project. The earlier work used different CNN architectures. Our approach involved Transfer Learning with a pre-trained ResNet50 model to try to improve performance and efficiency using features learned from large-scale datasets. This reduce the complexity and enhance the accuracy. Besides Transfer Learning adaptation, our project encompasses elaborate preprocessing techniques like resizing, normalization, and data augmentation in fine-tuning the dataset for further model fine-tuning. It has 97.6% accuracy, 95% precision, 99.4% recall, and 97.4% F1-score. rad-CAM techniques have been employed to visualize and interpret model predictions. This final model has been a pragmatic and accessible tool for early detection and diagnosis of skin disease. The feature here is an attempt to provide a more accurate, efficient, and user-friendly diagnostic solution through the incorporation of advanced methods of Transfer Learnin3g and visualization

Links between the three-dimensional movements of whale sharks (Rhincodon typus) and the bio-physical environment off a coral reef

Funding: This research was supported by funding from Santos Ltd and The Australian Institute of Marine Science (AIMS).Background Measuring coastal-pelagic prey fields at scales relevant to the movements of marine predators is challenging due to the dynamic and ephemeral nature of these environments. Whale sharks (Rhincodon typus) are thought to aggregate in nearshore tropical waters due to seasonally enhanced foraging opportunities. This implies that the three-dimensional movements of these animals may be associated with bio-physical properties that enhance prey availability. To date, few studies have tested this hypothesis. Methods Here, we conducted ship-based acoustic surveys, net tows and water column profiling (salinity, temperature, chlorophyll fluorescence) to determine the volumetric density, distribution and community composition of mesozooplankton (predominantly euphausiids and copepods) and oceanographic properties of the water column in the vicinity of whale sharks that were tracked simultaneously using satellite-linked tags at Ningaloo Reef, Western Australia. Generalised linear mixed effect models were used to explore relationships between the 3-dimensional movement behaviours of tracked sharks and surrounding prey fields at a spatial scale of ~ 1 km. Results We identified prey density as a significant driver of horizontal space use, with sharks occupying areas along the reef edge where densities were highest. These areas were characterised by complex bathymetry such as reef gutters and pinnacles. Temperature and salinity profiles revealed a well-mixed water column above the height of the bathymetry (top 40 m of the water column). Regions of stronger stratification were associated with reef gutters and pinnacles that concentrated prey near the seabed, and entrained productivity at local scales (~ 1 km). We found no quantitative relationship between the depth use of sharks and vertical distributions of horizontally averaged prey density. Whale sharks repeatedly dove to depths where spatially averaged prey concentration was highest but did not extend the time spent at these depth layers. Conclusions Our work reveals previously unrecognized complexity in interactions between whale sharks and their zooplankton prey.Publisher PDFPeer reviewe

Some Old Movies Become Classics – A Case Study Determining the Scientific Value of ROV Inspection Footage on a Platform on Australia’s North West Shelf

The global oil and gas industry holds a vast archive of Remotely Operated Vehicle (ROV) inspection footage potentially containing useful long-term data on marine biological communities. With the upcoming era of decommissioning of oil and gas structures, it is timely to assess the usefulness of this footage for researching these communities. We used ROV inspection footage to characterize the sessile invertebrates and fishes associated with the Goodwyn Alpha Production Platform (GWA) on the North West Shelf of Australia between depths of 10 and 125 m during 2006 and 2008. Depth was a major driver of invertebrate assemblages, most likely due to specific requirements such as light, and differences between years were most likely from the physical detachment of species by cyclones and internal waves. Phototrophic species were mostly limited to the upper 50 m of the platform, including the hard coral Pocillopora sp. and the soft corals Nephthea sp. and Scleronephthya sp. In contrast, heterotrophic species including sponges, anemones, bryozoans, hydroids, bivalves such as Lopha folium and the hard coral Tubastrea spp., were distributed across all depths. We observed 1791 fish from at least 10 families and 19 species, including commercial species such as crimson seaperch (Lutjanus erythropterus), red emperor (L. sebae), saddle-tailed seaperch (L. malabaricus), mangrove jack (L. argentimaculatus) and trevally (Caranx spp.). Fish density increased significantly with depth during 2008, from a mean of 23 fish/50 m2 between 10 and 25 m to 3373 fish/50 m2 at 125 m, where small unidentified baitfish were abundant. The highest densities of commercial species occurred between 25 and 75 m depth, suggesting that mid-depth platform sections had high habitat value, a consideration when selecting decommissioning options. The greatest difficulties using the video were the poor lighting and resolution that inhibited our ability to identify sessile species with high taxonomic precision. However, the footage was useful for evaluating high-level biodiversity of the platform, understanding how fish and invertebrate communities changed with depth and comprehending the dynamic nature of the invertebrate community over time. Understanding the habitat value of structures will be necessary for making environmentally sound decommissioning decisions in the future

Biologging Tags Reveal Links Between Fine-Scale Horizontal and Vertical Movement Behaviors in Tiger Sharks (Galeocerdo cuvier)

An understanding of the role that large marine predators play in structuring trophic flow and nutrient cycling in marine ecosystems requires knowledge of their fine-scale (m-km) movement behaviors. In this study, biologging tags were used to reveal new insights into the three-dimensional fine-scale movement ecology of tiger sharks (Galeocerdo cuvier) at Ningaloo Reef, Western Australia. Tags deployed on 21 sharks in April-May 2017 for durations of 5–48 h recorded both physical parameters such as depth and temperature, and, through the use of accelerometers, gyroscopes and compasses, in-situ measurements of animal trajectory and locomotion. Animal-borne-video enabled the validation of behavioral signatures, mapping of habitat, and recording of interactions with prey. Collectively, these data were used to examine the link between vertical (oscillations) and horizontal (tortuosity) movements, and link sensor data to prey interactions recorded by the video. This biologging approach revealed complex movements that would otherwise be invisible within the time-depth records provided by traditional tagging techniques. The rate of horizontal turning was not related to vertical oscillations, suggesting that vertical movements occur independently of searching behaviors in tiger sharks. These animals displayed tortuous movements possibly associated with prey searching for 27% of their tracks, and interactions with prey elicited varied responses including highly tortuous paths and burst movements. Accurate speed measurements and GPS anchor points will considerably enhance the value of magnetometer data in future studies by facilitating more accurate dead-reckoning and geo-referencing of area-restricted search behaviors