Retinal Vessel Extraction Framework Using Modified Adaboost Extreme Learning Machine

An explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages, microaneurysms etc. Manual vessel extraction is a challenging task due to the complicated nature of the retinal vessel structure, which also needs strong skill set and training. In this paper, a supervised technique for blood vessel extraction in retinal images using Modified Adaboost Extreme Learning Machine (MAD-ELM) is proposed. Firstly, the fundus image preprocessing is done for contrast enhancement and in-homogeneity correction. Then, a set of core features is extracted, and the best features are selected using “minimal Redundancy-maximum Relevance (mRmR).” Later, using MAD-ELM method vessels and non vessels are classified. DRIVE and DR-HAGIS datasets are used for the evaluation of the proposed method. The algorithm’s performance is assessed based on accuracy, sensitivity and specificity. The proposed technique attains accuracy of 0.9619 on the DRIVE database and 0.9519 on DR-HAGIS database, which contains pathological images. Our results show that, in addition to healthy retinal images, the proposed method performs well in extracting blood vessels from pathological images and is therefore comparable with state of the art methods.     

Experimental investigation of unconfined spherical and cylindrical flame propagation in hydrogen-air mixtures

This paper presents results of experimental investigations on spherical and cylindrical flame propagation in pre-mixed H₂/air-mixtures in unconfined and semi-confined geometries. The experiments were performed in a facility consisting of two transparent solid walls with 1 m² area and four weak side walls made from thin plastic film. The gap size between the solid walls was varied stepwise from thin layer geometry (6 mm) to cube geometry (1 m). A wide range of H₂/air-mixtures with volumetric hydrogen concentrations from 10% to 45% H₂ was ignited between the transparent solid walls. The propagating flame front and its structure was observed with a large scale high speed shadow system. Results of spherical and cylindrical flame propagation up to a radius of 0.5 m were analyzed. The presented spherical burning velocity model is used to discuss the self-acceleration phenomena in unconfined and unobstructed pre-mixed H₂/air flames.     

Characterizing physical habitat preferences and thermal refuge occupancy of brook trout (Salvelinus fontinalis) and Atlantic salmon (Salmo salar) at high river temperatures

Anthropogenic influences, including climate change, are increasing river temperatures in northern and temperate regions and threatening the thermal habitats of native salmonids. When river temperatures exceed the tolerance levels of brook trout and Atlantic salmon, individuals exhibit behavioural thermoregulation by seeking out cold‐water refugia – often created by tributaries and groundwater discharge. Thermal infrared (TIR) imagery was used to map cold‐water anomalies along a 53 km reach of the Cains River, New Brunswick. Trout and salmon parr did not use all identified thermal anomalies as refugia during higher river temperature periods (>21°C). Most small‐bodied trout (8–30 cm) were observed in 80% of the thermal anomalies sampled. Large‐bodied trout (>35 cm) required a more specific set of physical habitat conditions for suitable refugia, that is, 100% of observed large trout used 30% of the anomalies sampled and required water depths >65 cm within or adjacent to the anomaly. Densities of trout were significantly higher within anomalies compared with areas of ambient river temperature. Salmon parr were less aligned with thermal anomalies at the observed temperatures, that is, 59% were found in 65% of the sampled anomalies; and densities were not significantly different within/ outside anomalies. Salmon parr appeared to aggregate at 27°C, and after several events over 27°C variability in aggregation behaviour was observed – some fish aggregated at 25°C, others did not. We stipulate this is due to variances of thermal fatigue. Habitat suitability curves were developed for velocity, temperature, depth, substrate, and deep water availability to characterize conditions preferred by fish during high‐temperature events. These findings are useful for managers as our climate warms, and can potentially be used as a tool to help conserve and enhance thermal refugia for brook trout and Atlantic salmon in similar systems.     

Towards optimization of the osmotic drying process of alumina-gelatin objects: Regression analysis and verification

In this study, further analysis of the osmotic drying process was conducted to identify the optimum combination of parameters for drying rectangular alumina-gelatin beams. This study was designed to determine the effect of three variables related to the osmotic drying process (osmotic pressure, molecular weight, and immersion time) on the interaction between the liquid desiccant and the submerged alumina-gelatin samples. The water loss from the alumina-gelatin samples was positively correlated with the molecular weight, osmotic pressure, and immersion time. Up to 40% by weight of the initial water content was removed during the osmotic drying process. The samples also experienced solids gain due to the counterflow of solute from the liquid desiccant. The least amount of solids gain resulted from drying for the shortest immersion time at low osmotic pressure and high molecular weight. Evidence of possible interactions between variables was noted for the sintered density metric. Statistical methods were used to form regression equations for the measured responses (water loss, solids gain, bulk density). A verification experiment was conducted to compare the experimental outcomes to the predicted outcomes. The responses were simultaneously optimized to identify the combination of variable settings required to meet specified goals. In order to maximize water loss, minimize solids gain, and maximize bulk density, the ceramic-gelatin object should be immersed for approximately 60?min in an aqueous solution of 100,000?g/mol poly(ethylene oxide) at an osmotic pressure of 2.50?MPa. These values are valid for the range of parameter settings tested and the sample fabrication and drying methods used.