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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. -
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. -
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. -
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 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 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 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 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 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 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 biofuel from industrial waste organic pupae-silkworm /
International Journal of Recent Technology And Engineering, Vol.8, Issue 3, pp.1603-1607, ISSN No: 2277-3878. -
Extraction and characterization of biofuel from industrial waste organic pupae-silkworm
The current work carted out of analysis on the production of fuel from pupae fat extracted from silkworm, and exhaustive investigations were conducted to determine the characteristics of obtained fuel and its blends. The oily organic compounds derived from silkworm is effectively adopted to produce biofuel. The soxhlet extractor is utilized here to separate the oil content from pupae and obtained oil processed into biofuel by undertaking the transesterification process using NaOH as a fast reactive agent along with methanol. The rate of biofuel derived from pupae oil has been noticed to be 65-70 by vol%. The extracted fuels from the transesterification process were mixed with high-speed diesel at a rate of B10, B20, B30 and B40 on volume base. The most important physical and chemical characteristics of generated fuel and their mixture with conventional diesel were examined. The investigation results reveal that the fuel sample B20 satisfies all the requirements of ASTM standards. Pure biofuel shows that the lesser heating value, higher KV, flash point, fire point and density than that of conventional diesel. The blended samples reveal that all the properties are keep moving towards higher value with an increasing percentage of biofuel presence except calorific value. Finally results in evidence that, well suitable biofuel can be generated from organic waste material like silkworm and effectively use it in practical applications. BEIESP. -
Extensive long-term verbal memory training is associated with brain plasticity
The human brain has a remarkable capacity to store a lifetime of information through visual or auditory routes. It excels and exceeds any artificial memory system in mixing and integrating multiple pieces of information encoded. In this study, a group of verbal memory experts was evaluated by multiple structural brain analysis methods to record the changes in the brain structure. The participants were professional Hindu pandits (priests/scholars) trained in reciting Vedas and other forms of Hindu scriptures. These professional Vedic priests are experts in memorization and recitation of oral texts with precise diction. Vedas are a collection of hymns. It is estimated that there are more than 20,000 mantras and shlokas in the four Vedas. The analysis included the measurement of the grey and white matter density, gyrification, and cortical thickness in a group of Vedic pandits and comparing these measures with a matched control group. The results revealed an increased grey matter (GM) and white matter (WM) in the midbrain, pons, thalamus, parahippocampus, and orbitofrontal regions in pandits. The whole-brain corelation analysis using length ofpost-training teachingduration showed significant correlation with the left angular gyrus. We also found increased gyrification in the insula, supplementary motor area, medial frontal areas, and increased cortical thickness (CT) in the right temporal pole and caudate regions of the brain. These findings, collectively, provide unique information regarding the association between crucial memory regions in the brain and long-term practice of oral recitation of scriptures from memory with the proper diction that also involved controlled breathing. 2021, The Author(s). -
Extensible Business Reporting Language (XBRL)- A Modern Age Business Language System and its Developments Scenario within India & Abroad
International Journal of Applied Financial Management Perspectives Vol. 1, No. 1, pp. 60-65, ISSN No. 2279-0896 -
Extending schizophrenia diagnostic model to predict schizotypy in first-degree relatives
Recently, we developed a machine-learning algorithm EMPaSchiz that learns, from a training set of schizophrenia patients and healthy individuals, a model that predicts if a novel individual has schizophrenia, based on features extracted from his/her resting-state functional magnetic resonance imaging. In this study, we apply this learned model to first-degree relatives of schizophrenia patients, who were found to not have active psychosis or schizophrenia. We observe that the participants that this model classified as schizophrenia patients had significantly higher schizotypal personality scores than those who were not. Further, the EMPaSchiz probability score for schizophrenia status was significantly correlated with schizotypal personality score. This demonstrates the potential of machine-learned diagnostic models to predict state-independent vulnerability, even when symptoms do not meet the full criteria for clinical diagnosis. 2020, The Author(s). -
Extended virtual reality based memory enhancement model for autistic children using linear regression
Extended Virtual Reality has expanded its wings to almost each and every sector enabling immersive experience in various fields and has found applications in gamification, learning, healthcare, etc. This technology has aided in providing solutions to various problems in different fields, and healthcare is the most prominent one among them. Children suffering from ASD which is a developmental disorder affecting the brain that impacts how a person perceives external responses, are finding it increasingly difficult to get treated as the treatment methods are tedious. There are very few methods which are regarded as standardized means of treating autistic children but there are a few common traits that can be found in children affected by ASD which can be grouped under three common categories. They are lack of communication skills, lack of basic mathematical knowledge and low levels of remembrance. With the help of Gamification, which provides therapy by means of games to those affected, the kids affected by ASD can be treated, powered by the concept of Extended Virtual Reality. In this paper, we have developed a model to provide autistic children a real world experience of playing games which will help them in enhancing their skills without any external interferences. Children who play these Extended Virtual Reality based games show gradual improvement, for which the results can be facilitated with the help of a Linear Regression model, helping us predict future response times. The proposed model results in enhancement of memory levels of the kids as a result of the game and classifies kids based on their enhancement in memory into high, medium and low. The mean absolute error of the linear regression model is found to be 0.0394. 2024, The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden. -
Extended Slash Modified Lindley Distribution to Model Economic Variables Showing Asymmetry
This article introduces a novel probability distribution to model economic variables with high kurtosis and heavy tails showing a decreasing trend. From a mathematical viewpoint, it corresponds to the distribution of the ratio of two independent random variables, one with the modified Lindley distribution and another with the beta distribution. In some sense, it can be described as an extended three-parameter version of the Lindley distribution that has the ability to model data with high kurtosis. After presenting this distribution in more in-depth details, a comprehensive analysis is given, including its associated functions, moments, skewness, and kurtosis characteristics. Furthermore, a parametric estimation work is carried out. A simulation approach is used to validate the performance of the obtained estimates. The applicability of the proposed distribution is demonstrated by fitting real-world data into various socioeconomic scenarios. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Expressions of Women Survivors of Domestic Violence: Idioms of Distress
Domestic violence is prevalent worldwide; however, there are cultural differences in womens experiences of this phenomenon. This study used the concept of idioms of distress, to understand the impact of domestic violence on women survivors in India. A qualitative method was adopted, and semi-structured interviews were conducted with six women survivors of domestic violence. Using thematic network analysis, one global theme, four organizing themes and 19 basic themes emerged. The idioms of distress identified included, physiological idioms (such as aches and pains, nutritional deficiencies, reproductive), psychological idioms (such as depression, low self-confidence, change in aspirations and ambitions, mistrust, rumination) and behavioral idioms (such as crying, withdrawal, irritability, disturbed sleep). Of all the idioms, only nutritional deficiencies and the reproductive idioms were of concern to the survivors and their marital family. Implications for improving the screening of domestic violence are discussed based on the identified idioms and the responses toward them. 2019, National Academy of Psychology (NAOP) India. -
Expression of dissatisfaction in relation to managerial leadership strategies and its impact in Iinformation technology organizations /
Skyline Business Journal, Vol.8, Issue 1, pp.29-35, ISSN: 1998-3425. -
Export performance of Indian textile industry in the post multi fibre agreement regime /
Artha Journal Of Social Science, Vol.13, Issue 4, pp.63-86, ISSN No: 0975-329X.