Brain tumors are considered one of the most serious, prominent and life-threatening diseases globally. Brain tumors cause thousands of deaths every year around the globe because of the rapid growth of tumor cells. Therefore, timely analysis and automatic detection of brain tumors are required to save the lives of thousands of people around the globe. Recently, deep transfer learning (TL) approaches are most widely used to detect and classify the three most prominent types of brain tumors, i.e., glioma, meningioma and pituitary. For this purpose, we employ state-of-the-art pre-trained TL techniques to identify and detect glioma, meningioma and pituitary brain tumors. The aim is to identify the performance of nine pre-trained TL classifiers, i.e., Inceptionresnetv2, Inceptionv3, Xception, Resnet18, Resnet50, Resnet101, Shufflenet, Densenet201 and Mobilenetv2, by automatically identifying and detecting brain tumors using a fine-grained classification approach. For this, the TL algorithms are evaluated on a baseline brain tumor classification (MRI) dataset, which is freely available on Kaggle. Additionally, all deep learning (DL) models are fine-tuned with their default values. The fine-grained classification experiment demonstrates that the inceptionresnetv2 TL algorithm performs better and achieves the highest accuracy in detecting and classifying glioma, meningioma and pituitary brain tumors, and hence it can be classified as the best classification algorithm. We achieve 98.91% accuracy, 98.28% precision, 99.75% recall and 99% F-measure values with the inceptionresnetv2 TL algorithm, which out-performs the other DL algorithms. Additionally, to ensure and validate the performance of TL classifiers, we compare the efficacy of the inceptionresnetv2 TL algorithm with hybrid approaches, in which we use convolutional neural networks (CNN) for deep feature extraction and a Support Vector Machine (SVM) for classification. Similarly, the experiment’s results show that TL algorithms, and inceptionresnetv2 in particular, out-perform the state-of-the-art DL algorithms in classifying brain MRI images into glioma, meningioma, and pituitary. The hybrid DL approaches used in the experiments are Mobilnetv2, Densenet201, Squeeznet, Alexnet, Googlenet, Inceptionv3, Resnet50, Resnet18, Resnet101, Xception, Inceptionresnetv3, VGG19 and Shufflenet.
Abstract. Tribological properties of Ethylene-Propylene-Diene-rubber (EPDM) containing electron modified Polytetrafluoroethylene (PTFE) have been investiagted with the help of pin on disk tribometer without lubrication for a testing time of 2 hrs in atmospheric conditions at a sliding speed and applied normal load of 0.05 m·s -1 and FN = 1 N, respectively. Radiation-induced chemical changes in electron modified PTFE powders were analyzed using Electron Spin Resonance (ESR) and Fourier Transform Infrared (FTIR) specroscopy to characterize the effects of compatibility and chemical coupling of modified PTFE powders with EPDM on mechanical, friction and wear properties. The composites showed different friction and wear behaviour due to unique morphology, dispersion behaviour and radiation functionalization of PTFE powders. In general, EPDM reinforced with electron modified PTFE powder demonstrated improvement both in mechanical and tribological properties. However, the enhanced compatibility of PTFE powder resulting from the specific chemical coupling of PTFE powder with EPDM has been found crucial for mechanical, friction and wear properties. Vol.3, No.1 (2009) [39][40][41][42][43][44][45][46][47][48] Available online at www.expresspolymlett.com DOI: 10.3144/expresspolymlett.2009.7 ene (PTFE) with its remarkably low friction coefficient has also gained interest for use in tribological applications [9][10][11][12]. In rubbers, PTFE was initially used as a reinforcing additive in Silicone and Fluorosilicone rubbers [13][14][15] and afterwards in Styrene-butadiene-rubber, Acrylonitrile-butadienerubber and Butyl rubber [16]. New PTFE-based rubber compounds and compounding procedures have been introduced in improving mechanical properties of both low-strength (ethylene propylene, silicone) and high-strength (nitrile) rubbers for O-rings, sealing and valves etc. [17]. However, PTFE especially in rubbers have not been achieved with any commercially significant success. This is mainly due to the intractability of PTFE in providing homogeneous formulation because of its poor wetting and dispersion characteristic. This problem results from the unique properties of PTFE, most probably its highly hydrophobic surface which resists wetting. There is indeed a strong motivation to investigate new techniques and procedures for the use of PTFE powder in rubber compound as solid lubricant for tribological applications. More recently, chemically coupled PTFE-polyamide [18] and PTFE-rubber [19] compounds based on the modification of PTFE powder by high energy electrons has opened a new way in producing materials for tribological applications. Radiation functionalization produces PTFE micropowders containing persistent trapped-radicals radicals and functional groups on the surface of PTFE powder can be easily compounded into elastomers such as EPDM rubber. A detailed characterization related to the mechanical, friction and wear properties of PTFE-based EPDM compounds have been presented by the authors in [20,21]. In previous attemp...
Abstract. Low-temperature reactive mixing of controlled electron beam modified Polytetrafluoroethylene (PTFE) nanopowder with Ethylene-Propylene-Diene-Monomer (EPDM) rubber produced PTFE coupled EPDM rubber compounds with desired physical properties. The radiation-induced chemical alterations in PTFE nanopowder, determined by electron spin resonance (ESR) and Fourier transform infrared (FTIR) spectroscopy, showed increasing concentration of radicals and carboxylic groups (-COOH) with increasing irradiation dose. The morphological variations of the PTFE nanopowder including its decreasing mean agglomerate size with the absorbed dose was investigated by particle size and scanning electron microscopy (SEM) analysis. With increasing absorbed dose the wettability of the modified PTFE nanopowder determined by contact angle method increased in accordance with the (-COOH) concentration. Transmission electron microscopy (TEM) showed that modified PTFE nanopowder is obviously enwrapped by EPDM. This leads to a characteristic compatible interphase around the modified PTFE. Crystallization studies by differential scanning calorimetry (DSC) also revealed the existence of a compatible interphase in the modified PTFE coupled EPDM. Vol.2, No.4 (2008) [284][285][286][287][288][289][290][291][292][293] Available online at www.expresspolymlett.com DOI: 10.3144/expresspolymlett.2008.34 powder was specially utilized in NBR to expand its utility as wear-resistant material for sealing applications [25]. PTFE micropowders produced by emulsion polymerization are low-molecular weight fine coagulated powder commonly used as an additive in variety of applications [26][27]. In the previous study, PTFE coupled EPDM compounds were produced by reactive mixing of pre-modified PTFE nanopowder with EPDM [28]. In the present work the influence of dose-controlled agglomerate size, structural morphology and interfacial compatibility of PTFE nanopowder on the physical properties of the resulting modified PTFE-EPDM blends are presented. These investigations are of extreme importance especially in the development of new rubber compounds which require optimization of both the physical and tribological properties [29][30]. It has been shown that the desired physical properties can be achieved simply by controlled modification of PTFE nanopowder. Keywords: mechanical properties, PTFE nanopowder, EPDM, electron beam irradiation, compatibility eXPRESS Polymer Letters Materials and experimental MaterialsBoth EPDM (Buna EP G 6850) with ethylidene norbornene (ENB) content 7.7 wt%; ethylene content 51 wt%; Mooney viscosity, ML (1+4) at 125°C, 60; ash content 0.2 wt%; specific gravity, 0.86; and peroxide (Perkadox 14-40 MB GR) were supplied from Lanxess Deutschland GmbH, Germany while coagent (R-20S/Saret 634C) was used from Sartomer, USA. Algoflon L100X an emulsion grade received from Solvay Solexis S.p.A, Italy is an agglomerated white PTFE nanopowder with the bulk density and surface area of 0.25-0.44 g·cm -3 and 26 g·m -2 , respectively. Modification of...
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