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Extraction and characterization of preformed mixed phase graphene sheets from graphitized sub-bituminous coal
In present paper, a facile method is reported to extract mixed phase nanometre-sized carbon sheets from sub-bituminous coal. The lattice constants (La and Lc) of sub-bituminous coal were calculated to be 4.82 and 1.41 nm, respectively. The aromatic layers and average number of carbon atoms in the aromatic lamellae were estimated as 5 and 8, respectively. The obtained graphene sheets exhibits broadened D and G band in addition to a very broad 2D bump. Defect to graphitic ratio is found to be 0.54 indicating less disorder in graphene nanomaterial formed. This is further corroborated by (ID/ID') ratio which was observed to be 3.40, confirming the defect has originated from boundary. The SEM analysis reveals the formation of large number of carbon layers with different shape in the nanometer scale range. Formation of graphene dots in the shape of hexagonal, spherical, graphene layers and corn shaped carbon nanotubes are noticed in the TEM image. -
Extraction and characterization of wrinkled graphene nanolayers from commercial graphite
A report on the synthesis of wrinkled graphene nano carbon from bulk graphite is presented here. The obtained graphene nano carbon comprises mixed phase, sp2-sp3 bonded disordered carbon network. The as synthesized samples were intercalated by Hummer's method and are separated by centrifugation and sonication to obtain few layer graphene sheets. The structural and chemical changes of the nanostructure was elucidated by Raman spectroscopy, XRD, SEM-EDS, XPS, FTIR and UV-Vis-NIR spectroscopy. Raman spectra confirmed the existence of highly graphitized amorphous carbon with five peaks in the deconvoluted first order Raman spectrum. The IR and XPS analysis confirms the incorporation of functional groups to graphitic basal plane. There was a shift in the peaks position and intensity with intercalation. The synthesized graphene sheet is found to be in the graphite to nanocrystalline graphitic trajectory. The SEM analysis revealed the formation of large area wrinkled graphene sheets. The nanostructure formed is effortlessly scalable and ideally suitable for nano carbon composites based nano electronic devices and switches. -
Extraction of features from video files using different image algebraic point operations
In the human-computer interaction (HCI) field, facial feature analysis and extraction are the most decisive stages which can lead to a robust and efficient classification system like facial expression recognition, emotion classification. In this paper, an approach to the problem of automatic facial feature extraction from different videos are presented using several image algebraic operations. These operations deal with pixel intensity values individually through some mathematical theory involved in image analysis and transformations. In this paper, 11 operations (point subtraction, point addition, point multiplication, point division, edge detecting, average neighborhood filtering, image stretching, log operation, exponential operation, inverse filtering, and image thresholding) are implemented and tested on the images (video frames) extracted from three different self-recorded videos named as video1, video2, video3. The videos are in .avi, .mp4 and .wmv format respectively. The work is tested on two types of data: grayscale and RGB (Red, Green, Blue). To assess the efficiency of each operation, three factors are considered: processing time, frames per second (FPS) and sharpness of edges of feature points based on image gradients. The implementation has been done in MATLAB R2017a. 2019 Association for Computing Machinery. -
Extraction of Fungal Chitosan by Leveraging Pineapple Peel Substrate for Sustainable Biopolymer Production
The cost-effective production of commercially important biopolymers, such as chitosan, has gained momentum in recent decades owing to its versatile material properties. The seasonal variability in the availability of crustacean waste and fish waste, routinely used for chitosan extraction, has triggered a focus on fungal chitosan as a sustainable alternative. This study demonstrates a cost-effective strategy for cultivating an endophytic fungus isolated from Pichavaram mangrove soil in a pineapple peel-based medium for harvesting fungal biomass. Chitosan was extracted using alkali and acid treatment methods from various combinations of media. The highest chitosan yield (139 0.25 mg/L) was obtained from the pineapple peel waste-derived medium supplemented with peptone. The extracted polymer was characterized by FTIR, XRD, DSC, and TGA analysis. The antioxidant activity of the fungal chitosan was evaluated using DPPH assay and showed an IC50 value of 0.22 mg/L. Subsequently, a transparent chitosan film was fabricated using the extracted fungal chitosan, and its biodegradability was assessed using a soil burial test for 50 days. Biodegradation tests revealed that, after 50 days, a degradation rate of 28.92 0.75% (w/w) was recorded. Thus, this study emphasizes a cost-effective strategy for the production of biopolymers with significant antioxidant activity, which may have promising applications in food packaging if additional investigations are carried out in the future. 2024 by the authors. -
Extraction of Graphene Nanostructures from Colocasia esculenta and Nelumbo nucifera Leaves and Surface Functionalization with Tin Oxide: Evaluation of Their Antibacterial Properties
Expeditious evolution of antimicrobial resistance in recent years has been identified as a growing concern by various health organizations around the world. Herein, facile and environmentally benign production of highly antibacterial carbonaceous nanomaterials from Colocasia esculenta and Nelumbo nucifera leaves is reported. After carbonization and oxidative treatment, smaller graphene domains are formed in Colocasia esculenta derivatives, whereas larger sheetlike structures are observed in the case of Nelumbo nucifera. Smaller particle size makes quantum confinement effects more prominent, as is evident in fine-tuning of the photoluminescence emission after each stage of treatment. The influence of precursor materials on the antibacterial properties of the nanosystems is also demonstrated. When microbiocidal activity was tested against model bacteria Pseudomonas aeruginosa, the nanocomposite derived from Colocasia esculenta leaves showed higher activity than the antibiotic drug clarithromycin (control) with a measured zone of inhibition of 400.5 mm. This is one of the highest values reported in comparison with plant-based carbonsilver nanosystems. Quantitative analysis revealed that the nanocomposite obtained from Colocasia esculenta leaves has antimicrobial efficacy equivalent to those of commercial antibiotic drugs and is able to eradicate bacteria at much lower concentrations than that obtained from Nelumbo nucifera leaves. 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim -
Extraction of preformed mixed phase graphene sheets from graphitized coal by fungal leaching
The potential use of coal as source of carbon nano structure is seldom investigated. Herein we report a facile fungal solubilization method to extract mixed phase carbon structure from low grade coal. Coal had been used as a primary source for the production of carbon nanostructure with novel property, in addition to its main utility as a fuel. The major hurdle in its application is the inherent mineral embedded in it. An environmentally benign demineralization procedure make coal as a widely accepted precursor for the novel carbon materials. With Aspergiilus niger leaching, the randomly oriented preformed crystalline mixed phase nanocarbon in coal can be extracted. Raman studies revealed the presence of E2g scattering mode of graphite. The sp3 domains at ~1355 cm-1 (D band) is an indication of diamond like structure with disorder or defect. In the 2D region, multilayer stacking of graphene layers is noticed. The ratio of the defect to graphitic bands was found to be decreasing with increasing rank of coal. Bio leaching of coal enhances the carbon content in coal while eliminating the associated minerals in it. These defected carbon is an ideal material for graphene quantum dots and carbon dots, which are useful in drug delivery and bio imaging applications. 2017, IGI Global. All rights reserved. -
Extraction of Web News from Web Pages Using a Ternary Tree Approach
The spread of information available in the World Wide Web, it appears that the pursuit of quality data is effortless and simple but it has been a significant matter of concern. Various extractors, wrappers systems with advanced techniques have been studied that retrieves the desired data from a collection of web pages. In this paper we propose a method for extracting the news content from multiple news web sites considering the occurrence of similar pattern in their representation such as date, place and the content of the news that overcomes the cost and space constraint observed in previous studies which work on single web document at a time. The method is an unsupervised web extraction technique which builds a pattern representing the structure of the pages using the extraction rules learned from the web pages by creating a ternary tree which expands when a series of common tags are found in the web pages. The pattern can then be used to extract news from other new web pages. The analysis and the results on real time web sites validate the effectiveness of our approach. 2015 IEEE. -
Extraction, characterization, and fabrication of cellulose biopolymer sheets from Pistia stratiotes as a biodegradative coating material: an unique strategy for the conversion of invasive weeds into value-added products
This study explores the possibility of using Water lettuce (Pistia stratiotes) as a cost-effective substrate for the commercial extraction of cellulose biopolymer using a wide variety of physicochemical treatment methods to compare their efficiency in cellulose extraction. The extraction of cellulose from water lettuce, although promising due to their high cellulose content, was less explored as per the available literature. In this study, functional properties like bulk density-packed density, hydrated density, water retention capacity, oil retention capacity, emulsifying activity and setting volume of the extracted cellulose were studied. The cellulose content from water lettuce was found to be 38.94 0.10% by anthrone method. Preliminary confirmation of cellulose biopolymer was done using the study of functional groups using Fourier Transform Infrared (FT-IR) analysis. Further characterization studies like Scanning Electron Microscopy (SEM), X- Ray Diffraction (XRD), Differential Scanning Calorimetry (DSC) and thermogravimetric analysis (TGA) were conducted to understand the molecular architecture and purity of the cellulose extracted. Fabrication of cellulose sheets was carried out using starch as the plasticizer. Biodegradation studies were conducted in garden soil for four weeks and a high degradation rate of 78.22 0.71% was observed in the fourth week of soil burial. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Extractive Text Summarization Using Sentence Ranking
Automatic Text summarization is the technique to identify the most useful and necessary information in a text. It has two approaches 1)Abstractive text summarization and 2)Extractive text summarization. An extractive text summarization means an important information or sentence are extracted from the given text file or original document. In this paper, a novel statistical method to perform an extractive text summarization on single document is demonstrated. The method extraction of sentences, which gives the idea of the input text in a short form, is presented. Sentences are ranked by assigning weights and they are ranked based on their weights. Highly ranked sentences are extracted from the input document so it extracts important sentences which directs to a high-quality summary of the input document and store summary as audio. 2019 IEEE. -
Extremal reformulated forgotten index of trees, unicyclic and bicyclic graphs
The reformulated forgotten index (RF) is the edge version of the ordinary forgotten index. We describe graph transformations, by means of which RF increases or decreases. Using these transformations, the trees, unicyclic, and bicyclic graphs extremal w.r.t. RF are characterized. 2024, University of Nis. All rights reserved. -
Extremal Trees oftheReformulated andtheEntire Zagreb Indices
The first reformulated Zagreb index of trees can take any even positive integer greater than 8, whereas the second reformulated Zagreb index of trees can take all positive integers greater than 47 with a few exceptional values less than 8 and 47, respectively. The entire Zagreb index is defined in terms of edge degrees and incorporates the idea of intermolecular forces between atoms along with atoms and bonds. This intricate significance of studying the entire Zagreb index led to the generalization of the first entire Zagreb index of trees. The inverse problem on the first entire Zagreb of trees gives the existence of a tree for any even positive integer greater than 46. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024. -
Extreme photometric and polarimetric variability of blazar S4 0954+65 at its maximum optical and ?-ray brightness levels
In 2022 the BL Lac object S4 0954+65 underwent a major variability phase, reaching its historical maximum brightness in the optical and ?-ray bands. We present optical photometric and polarimetric data acquired by the Whole Earth Blazar Telescope (WEBT) Collaboration from 2022 April 6 to July 6. Many episodes of unprecedented fast variability were detected, implying an upper limit to the size of the emitting region as low as parsec. The WEBT data show rapid variability in both the degree and angle of polarization. We analyse different models to explain the polarization behaviour in the framework of a twisting jet model, which assumes that the long-term trend of the flux is produced by variations in the emitting region viewing angle. All the models can reproduce the average trend of the polarization degree, and can account for its general anticorrelation with the flux, but the dispersion of the data requires the presence of intrinsic mechanisms, such as turbulence, shocks, or magnetic reconnection. The WEBT optical data are compared to ?-ray data from the Fermi satellite. These are analysed with both fixed and adaptive binning procedures. We show that the strong correlation between optical and ?-ray data without measurable delay assumes different slopes in faint and high brightness states, and this is compatible with a scenario where in faint states we mainly see the imprint of the geometrical effects, while in bright states the synchrotron self-Compton process dominates. 2023 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. -
Extricating the Association Between the Prognostic Factors of Colorectal Cancer
Purpose: Colorectal cancer (CRC) is one of the recurring and lethal gastrointestinal tract disease rankings as the primary cause of worldwide morbidity and mortality. In general, the tumour node metastasis (TNM) and Dukes classification assist in diagnosis, prognosis and treatments of CRC along with haematological examinations and tumour demographic characterisations in patients. Methods: The present investigation is carried out on clinically acknowledged sixty-five CRC patients based on haematological findings and are sorted into stages using TNM and Dukes. The present study is to find the association between haematological findings, demographic characters, differentiation position, lymph node invasion and tumour node metastasis in CRC patients in accordance with their age. Results: We observed significant (p < 0.05) nexus between lymph node metastasis and tumour node metastasis on the basis of tumours differentiation demographic positioning and age of the individuals. Conclusion: Earlier location tracing and medicinal treatment or surgery lessen the chance of CRC morbidity and mortality along with prolonging survival rate via prognostic factors and disease position determination. 2020, Springer Science+Business Media, LLC, part of Springer Nature. -
Extrinsic electronic states to tune the luminescence and bonding nature of Cs2NaInCl6 double perovskite
Halide double perovskites have been extensively investigated in recent years as more stable and environmentally friendly materials with significant optoelectronic properties. Herein, we introduce Mn2+ ions in the Cs2NaInCl6 lattice to impart new electronic pathways to the otherwise weak optically active double perovskite for tuning its luminescent behaviour. X-ray diffraction, Raman, UVvisible, Photoluminescence (PL), and timeresolved PL (TRPL) spectroscopy are used to investigate the effect of Mn 2+ feed ratio on structural, vibrational, and optical properties. The chemical environment and surface morphology of the Mn2+ ions doped Cs2NaInCl6 double perovskite were investigated using X-ray photoelectron (XPS), energy dispersive X-ray (EDS) spectroscopies, and scanning electron microscopy. Results of the Rietveld refinement and Raman spectra divulge a decrease in In-Cl and Na-Cl bond length upon Mn2+ incorporation. The microstructure of the Cs2NaInCl6 double perovskite system was also studied using HRTEM analysis. UVvisible studies demonstrated a tremendous increase in absorption and a slight increase in band gap upon Mn2+ doping. PL and TRPL measurements of Mn2+: Cs2NaInCl6 discloses its red luminescence at 614 nm corresponding to the d-d atomic transition of Mn2+ with a long lifetime of 2.1 ms. Electron density investigations using maximum entropy method (MEM) demonstrate clear evolution of In-Cl and Na-Cl bonds from a highly ionic nature in pure Cs2NaInCl6 to strong covalent nature in Mn2+: Cs2NaInCl6 double perovskites. This affirms the simultaneous replacement of In, Na ions by Mn2+ to maintain charge neutrality in the compound and tune the electronic states of the Cs2NaInCl6 system. 2023 Elsevier B.V. -
Extrinsic pseudocapacitance: Tapering the borderline between pseudocapacitive and battery type electrode materials for energy storage applications
Extrinsic pseudocapacitance, which can also be referred to as induced pseudocapacitance, is, at present, one of the most widely explored fields in energy storage. Extrinsic pseudocapacitive mechanism can be imparted to an otherwise diffusion-controlled faradaic energy storage material by external methods like size engineering, compositional modification, doping, anion intercalation, and morphological modifications. As a significant mechanism that plays a borderline role between battery-type and pseudocapacitive nature of energy storage, extrinsic pseudocapacitance tends to narrow down the boundary between these conventionally diverse systems, which in turn would contribute a lot to the development of hybrid energy storage technologies. For effective utilization in upcoming energy storage technologies, a critical analysis on the effect of this mechanism on reported devices shall turn into a valid account. This review gives a detailed insight into extrinsic pseudocapacitance, its significance, and recently reported materials, methods, and devices. The future outlook and challenges in transforming extrinsic pseudocapacitive mechanisms into a promising strategy for next-generation energy storage devices are also discussed. 2023 Elsevier Ltd -
Eye blink detection using CNN to detect drowsiness level in drivers for road safety
Blinking is a regular bodily function and it is the semiautomatic fast closing of the eyelid. A specific blink is examined by dynamic folding of the eyelid. It is a vital function of the eye which helps in spread of tears across and eliminates irritants from the shallow of cornea. In this research work we made use of convolution neural network, the deep learning concepts and image processing to detect drowsiness level in drivers. To train the blink detection model the mobilenet V2 is used as base. The loss function used for training was RMSprop and the optimizer is binary cross entropy. The dlib facial landmark was exploited to perceive and pre-process the detected faces. The dataset used for the training model is selected from the Xiaoyang Tan of nanjing university of aeronautics and astronautics. Based on the experimental outcome the projected method achieves an accuracy of 97%. The prototype developed serves as a base for further development of this process to achieve better road safety. 2021 Institute of Advanced Engineering and Science. All rights reserved. -
Eye-Tracking Measures in Aviation: A Selective Literature Review
Objective: The aim of this article is to present a comprehensive review of eye-tracking measures and discuss different application areas of the method of eye tracking in the field of aviation. Background: Psychophysiological measures such as eye tracking in pilots are useful for detecting fatigue or high-workload conditions, for investigating motion sickness and hypoxia, or for assessing display improvements and expertise. Method: We review the uses of eye tracking on pilots and include eye-tracking studies published in aviation journals, with both a historical and contemporary view. We include 79 papers and assign the results to the following three categories: Human performance, aircraft design, health and physiological factors affecting performance. We then summarize the different uses of eye tracking in each category and highlight metrics which turned out to be useful in each area. Our review is complementary to that of Ziv (2016). Results: On the basis of these analyses, we propose useful application areas for the measurement of eye tracking. Eye tracking has the potential to be effective in terms of preventing errors or injuries by detecting, for example, fatigue or performance decrements. Applied in an appropriate manner in simulated or real flight it can help to ensure optimal functioning of manmachine systems. Conclusion: Further aviation psychology and aerospace medicine research will benefit from measurement of eye movements. 2018, 2018 The Author(s). Published with license by Taylor and Francis Group, LLC. -
Eye-Vision Net: Cataract Detection and Classification in Retinal and Slit Lamp Images using Deep Network
In the modern world, cataracts are the predominant cause of blindness. Early treatment and detection can reduce the number of cataract patients and prevent surgery. However, cataract grade classification is necessary to control risk and avoid blindness. Previously, various studies focused on developing a system to detect cataract type and grade. However, the existing works on cataract detection does not provide optimal results because of high detection error, lack of learning ability, computational complexity issues, etc. Therefore, the proposed work aims to develop an effective deep learning techniques for detecting and classifying cataracts from the given input samples. Here, the cataract detection and classification are performed using two phases. In order to provide an accurate cataract detection, the proposed study introduced Deep Optimized Convolutional Recurrent Network_Improved Aquila Optimization (Deep OCRN_IAO) model in phase I. Here, both retinal and slit lamp images are utilized for cataract detection. Then, the performance of these two image datasets are analysed, and the best one is chosen for cataract type and grade classification. By analysing the performance, the slit lamp images attain higher results. Therefore, phase II uses slit lamp images and detects the type and grade of cataracts through the proposed Batch Equivalence ResNet-101 (BE_ResNet101) model. The proposed classification model is highly efficient to classify the type and grades of cataracts. The experimental setup is done using MATLAB software, and the datasets used for simulation purposes are DRIMDB (Diabetic Retinopathy Images Database) and real-time slit lamp images. The proposed type and grade detection model has an accuracy of 98.87%, specificity of 99.66%, the sensitivity of 98.28%, Youden index of 95.04%, Kappa of 97.83%, and F1-score is 95.68%. The obtained results and comparative analysis proves that the proposed model is highly suitable for cataract detection and classification. 2022, International Journal of Advanced Computer Science and Applications. All Rights Reserved. -
Fabrication and Applications of Wrinkled Soft Substrates: An Overview
Morphology of soft materials, including those of natural systems has great influence in controlling their surface functionalities and responses to external stimuli. Surface morphological features of natural soft systems are produced through controlled cell growth and tissue growth. Artificial systems capable of emulating the morphology-dependent physicochemical responses of natural soft substrates can be prepared through various methods such as surface oxidation, thermal stress, compressive stress, etc. Wrinkling is an important morphological irregularity on soft substrates which can be leveraged in this direction. Wrinkling in artificial soft systems can be achieved through several experimental strategies such as compressive stress, thermal stress, surface oxidation, etc. The tunable, reversible and responsive nature of wrinkled soft substrates make them a potential tool for numerous applications in electronics, optics, adhesives, etc. In this review, have briefly summarized and commented on recent developments in different types of wrinkled soft substrates, their preparation, and emergent applications. 2022 Wiley-VCH GmbH. -
Fabrication and Characterization of AA7050 Nano Composites by Enhancing Directional Properties for High Impact Load Applications
The demand for materials with superior strength and impact resistance has driven the exploration of innovative composite materials. In this research, Al 7050 is chosen as the matrix material due to its excellent mechanical properties, whereas SiC and graphene nanoparticles are incorporated to tailor its directional strength characteristics. The fabrication process involves the synthesis of Al7050 nanocomposites through a meticulous blending of nanoparticles with the matrix material. The characterization phase encompasses a comprehensive analysis of various techniques, including scanning electron microscopy, X-ray diffraction, and mechanical testing. The results shows that the directional strength improvements achieved through SiC and graphene nanoparticle reinforcement with Al7050. The tensile strength of the aluminum in the AA7050-7.5g composite rose from 185.3 to 256.1MPa upon the addition of SiC and graphene. The findings of this study contribute to the evolving field of nanocomposite materials, offering insights into the design and development of advanced materials tailored for specific directional strength requirements. The Institution of Engineers (India) 2024.