28 research outputs found

    Keyword Extraction Using Particle Swarm Optimization

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    AbstractWithout formal structure data are those that have no prearranged form or structure and are full of textual data. Typical unstructured systems include emails, reports, telephone or messaging conversations, etc. The main goal of this work is to extract the keywords from a conversation using particle swarm optimization. Keywords are grouped together under their classification and then suggested to the user. In existing work, using diverse keyword extraction, to find topic modelling information, representation of the main topics of transcript and diverse keyword selection. It maximizes the coverage of topics that are automatically recognized in transcript of conversation fragment. Once a set of keywords is extracted, it is clustered according to their user queries and recommended to the user. At the end of result, a single implicit query cannot improve user's satisfaction with the recommended documents. So, swarm intelligence technique is to be applied, it will minimize redundancy in a short list of Keywords and provide accurate query result compared to greedy algorithm

    Technological Singularity in Sujatha Ranganathan’s En Iniya Iyanthira and Meendum Jeeno

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    The research paper aims at exploring the narrative aesthetics of Tamil science fiction in which the author takes twenty-first-century politics in India within the context of technological singularity. The article presents the political situation and totalitarianism in the age of technological singularity. The research focuses on the social impacts of artificial intelligence’s ability to read, learn, think, and act against its pre-programmed mechanism. A robotic dog struggles to restore a democratic political system from autocracy. The dystopian fictions “En Iniya Iyanthira” and “Meendum Jeeno” written by Sujatha Ranganathan depict the cognitive power of super intelligence behind a woman’s political actions to protect the people of India from exploitation, and corruption to create a better future. The paper demonstrates what a world without individual freedom looks like under the digital surveillance system of a totalitarian regime. The paper raises the question of what happens when a robot develops its rationality and mimics human behaviour. In these fictions, humans attempt to destroy the robotic dog. The robotic dog reaches a standard where nothing can destroy it. The paper explores the ways the robotic dog gains the knowledge to understand and practice the concept of humanity. The paper concludes with the post-humanistic conflicts between a woman and a robotic dog in emotional, ethical, and political aspects

    Performance Analysis of Farrow Structure Based FBMC-OQAM System

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    AbstractFarrow structure is used in the efficient implementation of high order filters. The number of unknown coefficients is much less in Farrow structure based implementation, in comparison with the direct form implementation of FIR filters. Some predefined multipliers can also be used in this method. Since they are known apriori they will not add much to the complexity of the system. It is seen that a relatively strong correlation exists among the adjacent impulse response coefficients of the frequency selective filters. This fact is exploited in the Farrow structure to reduce the number of multipliers required for the implementation of desired filter. And these Farrow coefficients are used for representing the polyphase components of the desired filter. This Farrow structure based prototype filter is used for implementing an FBMC-OQAM system. BER performance of Farrow structure based FBMC-OQAM system is studied and found comparable with that of existing FBMC-OQAM system

    Performance Improvement of Multicarrier Systems Using Wavelet Filter Banks

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    AbstractThe need for higher data rates with increased bandwidth efficiency has focussed the search for techniques which deliver better results than conventional Orthogonal Frequency Division Multiplexing (OFDM) system. A wavelet filter bank system is investigated as a multicarrier modulation system (MCM). Such a system is found to be flexible, efficient and has many advantages over the present OFDM systems. This paper deals with identifying the suitability of different wavelet families, which can be used to improve the performance parameters of existing systems. Different wavelets families Daubechies, Meyer and Battle-Lemarie, are used as filter coefficients for wavelet based OFDM system and it is found that Daubechies wavelet (Db4) based multicarrier system outperforms the other two

    Immunogenicity of SARS-CoV-2 vaccines in patients with cancer

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    Transmission of the SARS-CoV-2 virus and its corresponding disease (COVID-19) has been shown to impose a higher burden on cancer patients than on the general population. Approved vaccines for use include new technology mRNA vaccines such as BNT162b2 (Pfizer–BioNTech) and mRNA-1273 (Moderna), and nonreplicating viral vector vaccines such as Ad26.COV2.S (Johnson & Johnson) and AZD1222 (AstraZeneca). Impaired or delayed humoral and diminished T-cell responses are evident in patients with cancer, especially in patients with haematological cancers or those under active chemotherapy. Herein we review the current data on vaccine immunogenicity in cancer patients, including recommendations for current practice and future research

    Linkages between Climate Change and Coastal Tourism: A Bibliometric Analysis

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    Tourism and climate are inextricably linked to several interactions. In recent years, there has been a greater focus on the linkages between climate change and coastal tourism. This study aims to provide an overview of the literature on climate change and coastal tourism, identify core areas of interest and important sources and authors, and examine the thematic evolution of the field. A bibliometric analysis of 92 documents related to climate change and coastal tourism published in the Web of Science Core Collection database was carried out. The analysis provides information on the most cited papers, most leading authors, the most productive countries, and the most leading institutions in this field. The study utilized the Visualization of Similarities Viewer program (VOS) to map author keyword co-occurrences, co-citations, and bibliographic coupling. The study showed that, with some fluctuations since 2008, the number of publications in this field had increased significantly. The most influential authors and most productive institutions are from the United States of America, England, Canada, and other European countries. The findings of this study will assist researchers conducting climate change and coastal tourism-related studies to understand which papers, academics, organizations, countries, and journals have a dominant influence on climate change and coastal tourism research

    Smart analysis of learners performance using learning analytics for improving academic progression: a case study model.

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    In the current COVID-19 pandemic era, Learning Management Systems (LMS) are commonly used in e-learning for various learning activities in Higher Education. Learning Analytics (LA) is an emerging area of LMS, which plays a vital role in tracking and storing learners’ activities in the online environment in Higher Education. LA treats the collections of students’ digital footprints and evaluates this data to improve teaching and learning quality. LA measures the analysis and reports learners’ data and their activities to predict decisions on every tier of the education system. This promising area, which both teachers and students can use during this pandemic outbreak, converges LA, Artificial Intelligence, and Human-Centered Design in data visualization techniques, semantic and educational data mining techniques, feature data extraction, etc. Different learning activities of learners for each course are analysed with the help of LA plug-ins. The progression of learners can be monitored and predicted with the help of this intelligent analysis, which aids in improving the academic progress of each learner in a secured manner. The Object-Oriented Programming course and Data Communication Network are used to implement our case studies and to collect the analysis reports. Two plug-ins, local and log store plug-ins, are added to the sample course, and reports are observed. This research collected and monitored the data of the activities each students are involved in. This analysis provides the distribution of access to contents from which the number of active students and students’ activities can be inferred. This analysis provides insight into how many assignment submissions and quiz submissions were on time. The hits distribution is also provided in the analytical chart. Our findings show that teaching methods can be improved based on these inferences as it reflects the students’ learning preferences, especially during this COVID-19 era. Furthermore, each student’s academic progression can be marked and planned in the department
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