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Text summarization using residual-based temporal attention convolutional neural network
To address the computational complexity and limited to large data Enhanced Residual based Temporal Attention Convolutional Neural Network (ERTACNN) with Improved Initialization strategy-based Aquila Optimization Algorithm (IIAOA) is proposed. Initially the document is pre-processed to get structured data and given to feature extraction. Then the features are selected with Aquila Optimization Algorithm to remove redundant or unrelated features from high-dimensional data, from which the entropy values are calculated and given to proposed classifier. In this classification, the temporal attention mechanism is combined with classifier to compute attention weight and accompanied with important time points for classifying the documents. Finally, the proposed method is implemented in python and evaluated against existing works which achieves 70.34, 55.6 and 72.4 Recall Oriented Understudy for Gisting Evaluation (ROUGE) score than existing approaches. 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management. -
Text Summarization Using Combination of Sequence-To-Sequence Model with Attention Approach
In daily life, we come across tons and tons of information which can be related to news articles or any kind of social media posts or customer reviews related to product. It is difficult to read all the content due to time constraint. Being able to develop the software that can identify and automatically extract the important information. There are two types of summarization methods. Extractive text summarization is the method where it picks the important content from the source text and gives same in the form of short summary, and on the other hand, abstractive summarization is the technique where it gets the context of the source text, and based on that context, it regenerates small and crisps summary. In this paper, we use the concept of neural network with attention layer to deal with abstractive text summarization that generates short summary of a long piece of text using review dataset. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Text Summarization Techniques for Kannada Language
Text Summarization is summarizing the original text document into a shorter description. This short version should retain the meaning and information content of the original text document. A concise summary can help humans quickly understand a large original document better in a short time. Summarization can be used in many text documents, such as reviews of books, movies, newspaper articles, content, and huge documents. Text summarization is broadly classified into extractive Text Summarization (ETS) and Abstractive Text Summarization (ATS). Even though more research works are carried out using extractive methods, meaningful summaries can be attained using abstractive summary techniques, which are more complex. In Indian languages, very few works are carried out in abstract summarization, and there is a high need for research in this area. The paper aims to generate extractive and abstractive summaries of the text by using deep learning and extractive summaries and comparisons between them in the Kannada language. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Text Mining-A Comparative Review of Twitter Sentiments Analysis
Background: Text mining derives information and patterns from textual data. Online social media platforms, which have recently acquired great interest, generate vast text data about human behaviors based on their interactions. This data is generally ambiguous and unstructured. The data includes typing errors and errors in grammar that cause lexical, syntactic, and semantic uncertainties. This results in incorrect pattern detection and analysis. Researchers are employing various text mining techniques that can aid in Topic Modeling, the detection of Trending Topics, the identification of Hate Speeches, and the growth of communities in online social media net-works. Objective: This review paper compares the performance of ten machine learning classification techniques on a Twitter data set for analyzing users' sentiments on posts related to airline usage. Methods: Review and comparative analysis of Gaussian Naive Bayes, Random Forest, Multinomial Naive Bayes, Multinomial Naive Bayes with Bagging, Adaptive Boosting (AdaBoost), Optimized AdaBoost, Support Vector Machine (SVM), Optimized SVM, Logistic Regression, and Long-Short Term Memory (LSTM) for sentiment analysis. Results: The results of the experimental study showed that the Optimized SVM performed better than the other classifiers, with a training accuracy of 99.73% and testing accuracy of 89.74% compared to other models. Conclusion: Optimized SVM uses the RBF kernel function and nonlinear hyperplanes to split the dataset into classes, correctly classifying the dataset into distinct polarity. This, together with Feature Engineering utilizing Forward Trigrams and Weighted TF-IDF, has improved Optimized SVM classifier performance regarding train and test accuracy. Therefore, the train and test accuracy of Optimized SVM are 99.73% and 89.74% respectively. When compared to Random Forest, a mar-ginal of 0.09% and 1.73% performance enhancement is observed in terms of train and test accuracy and 1.29% (train accuracy) and 3.63% (test accuracy) of improved performance when compared with LSTM. Likewise, Optimized SVM, gave more than 10% of enhanced performance in terms of train accuracy when compared with Gaussian Nae Bayes, Multinomial Nae Bayes, Multinomial Nae Bayes with Bagging, Logistic Regression and a similar enhancement is observed with Ada-Boost and Optimized AdaBoost which are ensemble models during the experimental process. Optimized SVM also has outperformed all the classification models in terms of AUC-ROC train and test scores.. 2024 Bentham Science Publishers. -
Text extraction from video images
Video data contains beneficial textual information such as scene text and caption text. The different types of videos like movies, news videos, and TV programs video etc. are created by various video frames based on its purpose. In a country like India, there are only fewer studies has done on text extraction from video data especially in south Indian languages like Malayalam, Telugu, Kannada, and Tamil. The extracted text has many useful applications in video indexing, video key searching and assisting visually challenged people. Malayalam news channel named Mathrubhumi News videos data are considered for the proposed study. It is very beneficial to Kerala people as it is one of the most media-centric regions in the world. In this proposed paper, a new method for text extraction experiments. The anticipated method extracts 13 different features for classifying the image consists of text or not. Both spatial and frequency domain features are extracted to classify. The different types of classification techniques are used to validate the algorithm. Simple Logistic, J48 and Random Forest classification techniques are giving a good result when compared to other methods. Results are encouraging, the average success rate found to be 98%. Research India Publications. -
Testing the Diversifying Asset Hypothesis between Clean Energy Stock Indices and Oil Price
In theory, geopolitical risk and political uncertainty can directly affect energy markets. Fluctuations lead to the cost of clean energy sources as they compete with traditional energy. The purpose of this study is to analyse financial integration and test the diversifying asset hypothesis between clean energy indices, specifically the Clean Energy Fuels (CLNE), Nasdaq Clean Edge Green Energy (CELS), S&P Global Clean Energy (SPGTCLEN), TISDALE Clean Energy (TCEC.CN), Wilderhill (ECO) and West Texas Intermediate (WTI) stock indices, over the period from 1 January 2018 to 23 November 2023. Analysing the results reveals a scenario where most of the clean energy indices show cointegration with each other, indicating long-term relationships that reflect common trends in the clean energy sector. However, the relative independence of the WTI suggests that Oil still acts as an important and potentially diversifying external factor for investors focused on sustainable energy. Structural breaks in 2021 and 2022 in several indices point to significant events that have altered market dynamics, possibly including changes in environmental policies, technological innovations and the impacts of the COVID-19 pandemic. The cointegration evidence and structural breaks provide valuable information for building investment portfolios. Investors can consider the WTI to diversify portfolios dominated by clean energy assets, taking advantage of Oils relative independence. On the other hand, the high correlation between clean energy indices suggests that, within this sector, diversification options are more limited, requiring careful analysis of the specific characteristics of each index and the macroeconomic forces affecting them. 2024, Econjournals. All rights reserved. -
Testing The Causal Link Between Perceived Fee Fairness and Student Loyalty-Empirical Assessment in the Context of Service Marketing in Higher Education
Journal of Global Management Outlook, Vol-1 (5), pp. 43-55. ISSN-2277-3789 -
Testing of long run association between crude oil and gold commodities: An empirical study in India /
Test engineering & Management, Vol.82, pp.2902-2906, ISSN No: 0193-4120. -
Testing for the Bidirectional Relationship Between FDI in Services and Trade in Services: Evidence from Emerging Economies
We examine the two-way links between foreign direct investments (FDI) in services and trade in services for 26 emerging economies from 2003 to 2015 using sectoral and sectoral disaggregated FDI data. Within a multivariate framework, we use panel unit root tests, recently developed heterogeneous panel cointegration and panel vector error correction model (VECM). Our results confirmed the cointegrating relationship between trade in services, FDI in services, financial services FDI and nonfinancial services FDI. We find the existence of long-run unidirectional causality from trade in services to FDI in services. However, the disaggregated analysis shows a bidirectional link between nonfinancial services FDI and trade in services in the short run. Still, there is no causality between financial services FDI and trade in services both in the short run and long run. The result also shows the evidence of unidirectional causality running from trade in services to nonfinancial services FDI in the long run. It implies that sectoral decomposition matters in the FDItrade nexus in emerging economies. JEL Codes: G20, F14, G20, F23 2022 Indian Institute of Foreign Trade. -
Test case reduction and SWOA optimization for distributed agile software development using regression testing
Regression testing is a well-established practice in software development, but its position and importance have shifted in recent years as agile approaches have grown in popularity, emphasizing the fundamental role of regression testing in preserving software quality. In previous techniques, the challenge to address is determining the number and size of clusters and optimization to stabilize the cost and efficacy of the strategy. To overcome all the existing drawbacks; this research study proposes test case reduction and Support-based Whale Optimization Algorithm (SWOA) for distributed agile software development using regression testing. The purpose of this research study is to look into regression testing strategies in agile development teams and to find out what they are optimum clustered test cases. The proposed strategy is divided into two stages: prioritization as well as selection. Prioritization and selection are carried out once the test instances have been retrieved and grouped. The test case clusters are sorted and prioritized in this stage to ensure that the most critical instances are chosen first. During this stage, the test case clusters undergo sorting and prioritization to guarantee that the most essential cases are selected initially. Second, the SWOA is used to choose test cases with a greater frequency of failure or coverage criterion. The results of the assessment metrics show that the proposed approach outperforms other current regression testing strategies substantially. Based on experimental findings, our proposed approach betters existing methods in terms of information performance. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Tertiary Packaging Issues and Their Influence on Repurchase Intention and Loyalty of Customers Towards E-Retailers
his thesis investigates the significance of tertiary packaging in the context of e-retail business and its influence on customer preference, repurchase intention, and loyalty towards e-retailers. With the rapid growth of e-retail, it is expected to become the dominant form of retail worldwide, surpassing traditional brick and mortar establishments. While e-retail offers convenience and flexibility to customers, intensifying competition among e- retailers raises concerns about how they will effectively manage it. As e- retailers resort to increased marketing efforts to attract customers, certain aspects, including tertiary packaging, may be inadvertently overlooked. Tertiary packaging plays a critical role in the e-retail process, and this study analyses its impact on customer perception and satisfaction. By exploring the issues related to tertiary packaging that affect customers, this research aims to provide insights to e-retailers for developing a more efficient and sustainable tertiary packaging model. The anticipated outcomes of this research are expected to enhance e-retailers' ability to attract customers, increase repurchase intention, and foster loyalty towards the e-retailer, ultimately contributing to their long-term success in the evolving e-commerce landscape. -
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Terrorism And Regional Cooperation: What is SAARC up to?
South Asia has the distinction of being one of the most affected regions by terrorism and political violence. It is also one of the least integrated regions in the world. Terrorist threats have been diverse, characterised by religious fundamentalism, separatism, left-wing extremism and transnationalism. Interestingly, the countries of the region, under the umbrella of the South Asian Association for Regional Cooperation (SAARC), possess various regional arrangements to counter terrorism. Yet, the problem of terrorism continues unabated in the region. The principal question is, despite the existence of numerous arrangements, what factors hinder counter-terrorism cooperation among the countries at the regional level?. 2022 selection and editorial matter, Adluri Subramanyam Raju. -
Ternary Blended Geo-Polymer Concrete - A Review
The manufacturing of ordinary Portland cement produces carbon di oxide which is responsible for global warming. Geopolymer concrete in the field of construction leads to economic sustainability and reduces adverse effects on environment. Geopolymers are inorganic polymers obtained from chemical reaction between an alkaline activator's solution and an alumina-silicate material without using cement. Alkali activators are Homogeneous mixture consisting of two (NaOH and Na2SO3) or more chemicals in different proportions are highly corrosive and difficult to handle. There are still some limitations with respect to the alkaline activators in geopolymer concrete. To overcome ordinary portland cement, many wastes materials such as Silica-fume, GGBS, fly ash etc. have been used in recent studies to create eco-friendly cements by geo-polymerization reactions. Geopolymers are economic & good alternative construction material in making concrete This review paper briefly explains on previous literatures, properties, materials of geopolymer concrete, testing and practical applications of geopolymer concrete. Published under licence by IOP Publishing Ltd. -
Terahertz-based optoelectronic properties of ZnS quantum dot-polymer composites: For device applications
Terahertz (THz) technology integration with nanomaterials is receiving excellent attention for next-generation applications, including enhanced imaging and communication. The excellent optical properties in THz domain can lead to preparation of low-cost CMOS camera which can convert THz radiation into optical signal in very efficient manner. In the present study, we have studied the properties of Zinc Sulfide quantum dots (ZnS QDs) embedded with Polyvinyl Alcohol (PVA) composites films using THz Signal at room temperature. The optical characterizations such as refractive index, absorption coefficients and dielectric constants of these samples were measured in the 0.12.0 THz range. Additionally, optical impedance, surface roughness, and reflection coefficient in TE and TM mode between 0.1 and 2.0 THz range were determined for these samples based on surface roughness-based reflection and scattering properties. The surface roughness factor was used to measure the optical impedance of the ZnS QDs based polymer films. The measured values of the absorption coefficient at 266 nm are compared with THz radiation, and the refractive indices of these samples range from 1.75 to 2.0. Finally, these samples were subjected to UV light excitation (?exe = 266 nm) of 0.15 ns duration and 400 nm for the fluorescence and corresponding life time measurements. We observed two numbers of fluorescence lines in nanosecond based excited domain whereas 400 nm excitation-based fluorescence life time lies between 13.811.39 ns range along with shift in fluorescence lines between 538.7 to 560.7 nm, respectively. 2024 -
TenzinNet for handwritten Tibetan numeral recognition
Tibet is known for its enumerable collection of Nalanda based Buddhism manuscripts that need to be digitized for immortalization of the teachings of Buddha and various Buddhist scholars. Handwritten Tibetan numeral recognition is relatively unexplored as compared to Roman and Chinese numerals. Recognition of handwritten documents for digitalization has been under study from past many years. This work proposes a novel model using convolutional neural networks architecture named as TenzinNet to recognize handwritten Tibetan numerals. TenzinNet achieved an accuracy of 90.76% in recognizing Tibetan numerals using the proposed model. 2021, Bharati Vidyapeeth's Institute of Computer Applications and Management. -
Temporal correlation between the optical and ? -ray flux variations in the blazar 3C 454.3
Blazars show optical and ? -ray flux variations that are generally correlated, although there are exceptions. Here we present anomalous behaviour seen in the blazar 3C 454.3 based on an analysis of quasi-simultaneous data at optical, ultraviolet, X-ray, and ? -ray energies, spanning about 9 yr from 2008 August to 2017 February.We have identified four time intervals (epochs), A, B, D, and E, when the source showed large-amplitude optical flares. In epochs A and B the optical and ? -ray flares are correlated, while in D and E corresponding flares in ? -rays are weak or absent. In epoch B the degree of optical polarization strongly correlates with changes in optical flux during a short-duration optical flare superimposed on one of long duration. In epoch E the optical flux and degree of polarization are anticorrelated during both the rising and declining phases of the optical flare. We carried out broad-band spectral energy distribution (SED) modelling of the source for the flaring epochs A,B, D, and E, and a quiescent epoch, C. Our SED modelling indicates that optical flares with absent or weak corresponding ? -ray flares in epochs D and E could arise from changes in a combination of parameters, such as the bulk Lorentz factor, magnetic field, and electron energy density, or be due to changes in the location of the ? -ray-emitting regions. 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. -
TEMPO-Mediated Aqueous Phase Electrooxidation of Pyridyl Methanol at Palladium-Decorated PANI on Carbon Fiber Paper Electrode
Palladium nanoparticles decorated on polyaniline coated carbon fiber paper electrode (Pd-PANI/CFP) was employed for TEMPO ((2,2,6,6-tetramethylpiperidin-1-yl)oxyl) mediated electrocatalytic oxidation of pyridyl methanol to pyridyl carboxaldehyde using cyclic voltammetry in aqueous acidic media using a surfactant. The electrochemical properties of the modified electrodes were studied by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The physicochemical properties of the modified electrodes were studied using Scanning electron microscopy (SEM) with Energy dispersive X-ray spectroscopy (EDS), Transmission electron microscopy (TEM), Optical profilometry, X-ray diffraction (XRD) spectroscopy, Raman spectroscopy and Fourier transform infrared (FTIR) spectroscopy. Pd-PANI/CFP electrode has exhibited enhanced electrocatalytic activity towards TEMPO mediated oxidation of pyridyl methanol owing to higher electrochemically active surface area of the modified electrode. CV studies suggested higher electrochemical activity for Pd-PANI/CFP electrode when compared to PANI/CFP and bare CFP electrodes towards TEMPO mediated oxidation of pyridyl methanol. 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim -
TEMPO mediated electrochemical oxidation of 4-pyridinemethanol using Pd and Pt Co-deposited polyaniline modified carbon fiber paper
Co-deposition of palladium and platinum (PdPt) nanoparticles on the conducting polymeric ?lm of Polyaniline (PAn) modified carbon fiber paper (CFP) electrode was carried out by using eletrochemical method. The modified electrode has been used for the oxidation of 4-pyridinemethanol. The electrochemical properties of fabricated multi-layered ?lms on carbon fiber paper (Pd-Pt/PAn/CFP) were studied by electrochemical AC impedance spectroscopy and cyclic voltammetry (CV). Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) characterization technics were environmentally benign and sustainable are used to analyze the structural properties of modified multi-layered electrode. The relative sizes and distribution of the nanoparticles on the electrode surface were analyzed using Scanning electron microscopy (SEM) and optical profilometry characterization techniques. Electrochemical studies by CV showed that the PdPt/PAn/CFP electrode had better electrochemical activity similar to PAn/CFP and Bare CFP electrode towards extensive electrochemical oxidation of 4-pyridinemethanol in presence of TEMPO (2,2,6,6-Tetramethylpiperidinyl-1-oxyl) in aqueous acidic medium. 2021 -
TEMPO mediated electrocatalytic oxidation of pyridyl carbinol using palladium nanoparticles dispersed on biomass derived porous nanoparticles
Remarkable electrocatalytic property of Pd nanostructures dispersed on CNSareca coated CFP electrode towards TEMPO mediated electrooxidation of pyridyl carbinol was reported for the first time. Carbon nanospheres (CNSs) derived from Areca catechu decorated with Pd nanoparticles were coated on carbon fiber paper (CFP) and was employed for electrooxidation of pyridyl carbinol in aqueous acidic medium. An environmentally benign and economic strategy was utilized for the preparation of CNSs obtained from Areca catechu. The physical characterizations, electronic state and chemical composition of the modified electrode were studied using Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD) spectroscopy and X-ray photoelectron spectroscopy (XPS). Scanning electron microscopy (SEM), Transmission electron microscopy (TEM) and high resolution transmission electron microscopy (HRTEM) techniques were used for analyzing the morphology of modified electrode. The electrochemical characterizations of the modified electrodes were performed by Cyclic voltammetry (CV) and Electrochemical impedance spectroscopy (EIS). Pd decorated CNSareca dispersed on CFP electrode has exhibited strong electrocatalytic activity towards TEMPO mediated oxidation of pyridyl carbinol. 2020 Elsevier Ltd