33 research outputs found
Keyword Extraction Using Particle Swarm Optimization
No full textAbstractWithout 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
No full textThe 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
Molecular docking and spectroscopic investigations aided by density functional theory of Parkinson’s drug 2-(3,4-dihydroxyphenyl)ethylamine
No full textSurface modification of CZTS nanoparticles using reflux method for effective utilizing absorber material
No full textNeutrosophic graph cut-based segmentation scheme for efficient cervical cancer detection
No full textCervical cancer is the most serious category of cancer that has very low survival rate in the women’s community around the globe. This survival probability of women society affected by this cervical cancer can be potentially enhanced if it is detected at an early stage as they do not provide any realizable degree of symptoms in the early phase
Neutrosophic graph cut-based segmentation scheme for efficient cervical cancer detection
No full textCervical cancer is the most serious category of cancer that has very low survival rate in the women’s community around the globe. This survival probability of women society affected by this cervical cancer can be potentially enhanced if it is detected at an early stage as they do not provide any realizable degree of symptoms in the early phase. This cervical cancer needs to be detected at an early stage through periodical checkups. Hence, the objective of the proposed work focuses on the merits of Neutrosophic Graph Cut-based Segmentation (NGCS) facilitated over the pre-processed cervical images. This NGCS-based segmentation is mainly employed for investigating the overlapping contexts of cervical smear pre-processed images for better classification accuracy. This NGCS-based segmentation is responsible for partitioning the input preprocessed image into a diversified number of non-overlapping regions that aids in better perception at the convenience. In NGCS-based segmentation, the preprocessed input image is transformed into a Neutrosophic set and indeterminacy filter depending on the estimated indeterminacy value that integrates the intensity and spatial information the preprocessed image. The utilized indeterminacy filter plays the anchor role in minimizing the indeterminacy value associated with each intensity and spatial information. Then a graph is defined over the image with unique weights are assigned to each of the image pixels based on the estimated indeterminacy value. Finally, the maximum flow graph approach is applied over the graph for determining optimal segmentation results. The results of this NGCS-based cervical cancer detection technique is proved to be excellent on an average by 13% compared to the traditional graph cut oriented cancer detection approaches
Axillary galactocele of ectopic breast: Ultrasound and mammography correlation
No full textEctopic or accessory breast tissue may occur anywhere along the milk line or mammary ridge extending from axilla to groin. The most common location of the ectopic breast is axilla. This article reviews a case of 35-year-old female patient who presented to our hospital with left axillary lump. Mammography and ultrasonography were performed. Imaging findings were further confirmed with fine-needle aspiration cytology revealing left axillary galactocele
Performance Analysis of Farrow Structure Based FBMC-OQAM System
No full textAbstractFarrow 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
No full textAbstractThe 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
