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Face Identification with Feature Learning Using Quasilinear Partial Differential Equation 1

15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Muthukumaran, V. Satheesh Kumar, S. Radhika, E.K. Arpana, G.K. Nalini, R. Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Chennai India Department of Computer Science School of Applied Sciences REVA University Bangalore India Department of Computer Science Sindhi College Bangalore India Department of ECE East West College of Engineering Bangalore India

ISBN: (数字)9783031810862

ISBN: (纸本)9783031810855

This study suggests a novel soft computing approach for enhancing face recognition performance using the feature learning methodology. The suggested system of Quasi-linear Partial Differential Equations (QPDE) based face recognition model is used to increase the accuracy of facial identification. The webcam first catches the user's image and saves it to the user's computer. The inference model receives the captured image. The input image is pre-processed to enhance the image, and then the image is split into numerous integral images at the inference model. Using speed-up robust features, an intriguing point is constructed for each integral image. The computed interest point is converted into a QPDE based weight matrix by representing the strength of features at all the regions of the face. With the generated weighted matrix of features extracted from the facial image, the method generates a Fast Artificial intelligence (AI) network with many layers. Each layer of the neural network has many neurons with dedicated functions to compute the similarity and feature weight using QPDE. The proposed approach has produced efficient results compared to earlier methods for the Flickr-Faces-HQ database (FFHQ) datasets. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Soft computing

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Analysis of Viral and Non-viral Categories of Video Through Social Media Using Machine Learning Techniques 15th

Analysis of Viral and Non-viral Categories of Video Through ...

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15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Nagashree, B.A. Satheesh Kumar, S. Muthukumaran, V. Joseph, P. Rose Bindu Amrita Vishwa Vidyapeetham Mysuru Campus Mysuru570026 India Department of Computer Science School of Applied Sciences REVA University Bangalore India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Chennai India Department of Mathematics Dayananda Sagar College of Engineering Bangalore India

ISBN: (纸本)9783031889912

People frequently use technological means to collect information from many sources, share it with others on social media, and communicate with friends on these platforms. Social media is therefore a crucial new tool for communication. Collaborative wikis, blogs, and content communities are just a few of the tools and technologies that make up social media. YouTube is the most widely used of these. The influencer’s content gets visible to the users of such platforms. The expansion of social media use has enabled massive and rapid spread ability of content, often called virality. This paper aims to examine the virality of different categories of YouTube videos using machine learning technique, where it plays a major role in analysis of YouTube data such as likes, dislikes, comment count and views. YouTube can serve as a path to virality and fabricate online videos, hence finding the correlation analysis among the videos, which enables us to classify the viral and non-viral video categories, thereby analysing the linear relationship among the features (likes, dislike, views and comment count. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Tweets

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Optimizing HCV Diagnosis and Hospital Resource Management Using Machine Learning Techniques 3

Optimizing HCV Diagnosis and Hospital Resource Management Us...

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Bisht, Shilpi Bisht, Neeraj Pandey, Bishwajeet Patil, Vedant Srivastava, Sonalika Srivastava, Anshul Birla Institute of Applied Sciences Department of Mathematics Bhimtal India Birla Institute of Applied Sciences Department of Computer Science Bhimtal India Astana It University Department of Information Technology Kazakhstan Amity International Business School Amity University Noida India King George Medical University Department of Oral Medicine and Radiology Lucknow India

ISBN: (纸本)9798331518592

The aim of this research effort is to improve hospital profitability and management by using cutting-edge machine learning algorithms to accurately diagnose the Hepatitis C virus (HCV). Given that over 80% of individuals have no symptoms and that HCV can induce potentially fatal liver malignancies, this virus poses a serious threat to public health. Efficient hospital administration and resource optimization depend on timely and reliable HCV prediction. The study we conducted makes use of the 'HCV' dataset from the UCI Machine Learning Repository, which contains laboratory results from 615 cases involving HCV patients and blood donors, some of which have missing values. The dataset includes 13 attributes altogether and includes 533 instances of blood donors, 7 suspected cases, and 75 instances of HCV patients. We used Linear Regression to fill in the missing data to keep our predictive models accurate and reliable. We selected to use Analysis of Variance (ANOV A) for feature selection since it is a powerful tool for evaluating the correlations between features, which allowed us to increase model efficiency and decrease computation time. The decision tree algorithm, which is resilient in HCV identification, attained the greatest accuracy of 98.78% among the many machine learning techniques used, both before and after applying ANOV A. This paper presents novel strategies that can greatly increase diagnostic efficiency and accuracy in hospital settings. Examples of these strategies include the use of ANOV A for feature selection and Linear Regression for managing missing data. We tried to improve patient outcomes and maximize hospital resource use by utilizing machine learning for improved HCV prediction, which ultimately drives profitability. To determine which machine learning algorithm is the most successful, future research and real-world applications in comparable medical situations can benefit greatly from a comparative examination of several algorithms. © 2024 I

关键词： Efficiency

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Use of Polygram Substitution in Spotting the Swindler in Secret Sharing 11th

Use of Polygram Substitution in Spotting the Swindler in Sec...

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11th International Conference on Intelligent Computing and Applications, ICRTC 2023

作者： Yadav, Poonam Satheesh Kumar, S. Muthukumaran, V. Sandeep Kumar, Mathivanan Radhika, E.K. Department of Computer Science School of Applied Sciences Reva University Bangalore India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur 603203 India School of Computer Science and Engineering Galgotias University Uttar Pradesh Greater Noida203201 India Department of Computer Science and Applications Sindhi College Bangalore560024 India

ISBN: (纸本)9789819717231

In the polygram substitution, one set of characters is replaced by another set based on algorithm. The model is proposed for calculating and estimating secure online secret shares, where dynamic modification in any of the shares will be identified if number of the shares are more than specified threshold value. The security is based on the intractability of factoring as it uses Lagrange polynomial function. This is further enhanced by a graphical masking and unmasking technique;it includes two phases: encryption of the individual secrets and sharing of the data. The generation of the shares is done by masking using Polygram substitution, and the shares are regenerated and unmasking of the qualified shares is done to find original secret. Masking is done on original secret, then shares are generated. Each encrypted share contains information which is different than original secret. Masking by Polygram substitution gives additional protection of secret data on the Internet. Moreover, we achieve efficient recovery of the original secret data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Polynomials

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Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

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computer Systems Science & Engineering 2023年第3期44卷 1939-1950页

作者： Dhanalakshmi R Sovan Samanta Arun Kumar Sivaraman Jeong Gon Lee Balasundaram A Sanamdikar Sanjay Tanaji Priya Ravindran Department of Computer Science and Engineering KCG College of TechnologyChennai600097Tamil NaduIndia Department of Mathematics Tamralipta MahavidyalayaWest Bengal721636India School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127Tamil NaduIndia Division of Applied Mathematics Wonkwang UniversityIksan-SiJeonbuk54538Korea School of Computer Science and Engineering Center for Cyber Physical SystemsVellore Institute of TechnologyChennai600127Tamil NaduIndia Department of Instrumentation Engineering PDEAs College of EngineeringManjari412307PuneIndia Engineering and Research Services HCL TechnologiesChennai600119India

Fuzzy sets have undergone several expansions and generalisations in the literature,including Atanasov’s intuitionistic fuzzy sets,type 2 fuzzy sets,and fuzzy multisets,to name a *** can be regarded as fuzzy multisets from a formal standpoint;nevertheless,their interpretation differs from the two other approaches to fuzzy multisets that are currently *** fuzzy sets(HFS)are very useful if consultants have hesitation in dealing with group decision-making problems between several possible ***,these possible memberships can be not only crisp values in[0,1],but also interval values during a practical evaluation *** bipolar valued fuzzy set(HBVFS)is a generalization of *** paper aims to introduce a general framework of multi-attribute group decision-making using social *** propose two types of decision-making processes:Type-1 decision-making process and Type-2 decision-making *** the Type-1 decision-making process,the experts’original opinion is proces for thefinal ranking of *** Type-2 decision making processs,there are two major aspects we ***,consistency tests and checking of consensus models are given for detecting that the judgments are logically ***,the framework demands(partial)decision-makers to review their ***,the coherence and consensus of several HBVFSs are established forfinal ranking of *** proposed framework is clarified by an example of software packages selection of a university.

关键词： Group decision-making aggregation operators hesitant bipolar-valued fuzzy set

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Development of Virtual Reality Platform through Human computer Interaction using Artificial Intelligence 3

Development of Virtual Reality Platform through Human Comput...

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3rd International Conference on applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Saranya, S. Channarayapriya, B. Harshavardhini, U. Nandhini, A.Sunitha Revathi, J. Venkatesan, R. New Horizon College of Engineering Department of Computer Science and Engineering Bangalore India Vel Tech Multi Tech Dr.Rangarajan Dr Sakunthala Engineering College Deparment of Information Technology Chennai India Psg Institute of Technology and Applied Research Department of Computer Science and Engineering Coimbatore India Kongu Engineering College Department of Mathematics Erode India Bannari Amman Institute of Technology Deparment of Information Technology Erode India

ISBN: (纸本)9798350375190

The development of a virtual reality platform through human-computer interaction (HCI) is obtained using deep learning with a genetic algorithm. The human-computer interaction forms a bridge between users and the VR system. This helps in providing a natural interaction experience to the users. Deep learning techniques help in obtaining the realistic nature of the physical world in the virtual platform. The personalized experiences are obtained using the integration of deep learning with VR platforms. The optimization algorithm helps in achieving user interaction in a real-time platform. The adaptive learning helps in increasing the overall immersion with a user-friendly interface. The VR development process is done using a genetic algorithm. This helps to evolve and optimize themselves within the period of time. This helps the VR platform to iteratively improve its performance and complete design through adopting successful combinations of various parameters. The proposed approach helps the VR system to evolve towards an optimal condition. This helps to satisfy the various needs and preferences of the users. Thus the proposed system helps in obtaining adaptive and intelligent virtual environments. This helps in overcoming various challenges in designing immersive VR experiences with personalized digital environments. © 2024 IEEE.

关键词： Virtual reality

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Encoding of Algebraic Geometry Codes with Quasi-linear Complexity O(NlogN)

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IEEE Transactions on Information Theory 2025年第7期71卷 5013-5026页

作者： Li, Songsong Liu, Shu Ma, Liming Wan, Yunqi Xing, Chaoping Shanghai Jiao Tong University School of Computer Science Shanghai200240 China Hubei University Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and Statistics Wuhan430062 China State Key Laboratory of Integrated Services and Networks Xi'an710071 China University of Electronic Science and Technology of China National Key Laboratory on Wireless Communications Chengdu611731 China University of Science and Technology of China School of Mathematical Sciences Hefei230026 China 2012 Labs Huawei Technology Co. Ltd Theory Lab Central Research Institute China

Fast encoding and decoding of codes have always been an important topic in coding theory as well as complexity theory. Although encoding is easier than decoding in general, designing an encoding algorithm of codes of length N with quasi-linear complexity O(N log N) is not an easy task. Despite of the fact that algebraic geometry codes (AG codes) were discovered in the early 1980s, encoding algorithms of algebraic geometry codes with quasi-linear complexity O(N log N) have not been found except for the simplest algebraic geometry codes-Reed-Solomon codes. The best-known encoding algorithm of algebraic geometry codes based on a class of plane curves has quasi-linear complexity at least O(N log2 N) (Beelen et al. IEEE Trans. Inf. Theory 2021). In this paper, we design an encoding algorithm for algebraic geometry codes with quasi-linear complexity O(N log N). Moreover, for these fast encodable AG codes, the inverse of encoding, that is, interpolating the message function from the corresponding codeword, can be computed with the same complexity O(N log N). Our algorithms are applicable to a large class of algebraic geometry codes based on both plane and non-plane curves, including Kummer extensions, Artin-Schreier extensions, and Hermitian field towers. © 1963-2012 IEEE.

关键词： Reed-Solomon codes

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On the Security Related Properties of Randomly Constructed Combinatorial Structures 8th

On the Security Related Properties of Randomly Constructed...

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8th International Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2024

作者： Liagkou, V. Nastou, P.E. Spirakis, P. Stamatiou, Y.C. Computer Technology Institute and Press - "Diophantus" University of Patras Campus Patras26504 Greece Department of Computer Science University of Liverpool Liverpool United Kingdom Department of Business Administration University of Patras Patras26504 Greece Department of Informatics and Telecommunications University of Ioannina Koatakioi Arta47100 Greece Department of Mathematics Applied Mathematics and Mathematical Modeling Laboratory University of the Aegean Samos Greece

ISBN: (纸本)9783031769337

This paper explores the interplay between randomly generated structures, namely set families as well as second-order logic 0-1 laws, in security-related settings. The paper investigates how randomly generated structures can serve as powerful models for representing security properties of complex systems. By examining the 0-1 properties of these structures, conditions are stated which determine the presence or absence of specific security issues. The stated results provide a generic framework for studying insights into the probabilistic behavior of security attributes modeled by set families and mathematical logic with application potential in designing more robust systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： computer circuits

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Subjective weight determination methods in multi-criteria decision-making: a systematic review 28th

Subjective weight determination methods in multi-criteria de...

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28th International Conference on Knowledge Based and Intelligent information and Engineering Systems, KES 2024

作者： Kizielewicz, Bartlomiej Tomczyk, Tomasz Gandor, Michal Salabun, Wojciech National Institute of Telecommunications National Research Institute ul. Szachowa 1 Warsaw04-894 Poland Department of Computer Science Faculty of Computer Science and Telecommunications Cracow University of Technology Warszawska 24 Krakow31-155 Poland Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Zolnierska 49 Szczecin71-210 Poland

The determination of weights is a critical step in Multi-Criteria Decision-Making (MCDM) processes, and subjective methods play a significant role in this area. This paper provides a comprehensive review of subjective weight determination methodologies, focusing primarily on sources from the Scopus database. Through a systematic literature review, this study analyzes 33,434 publications related to subjective weight determination, providing insights into the trends, advancements, and applications of these methodologies. The review underscores the importance of expert knowledge in contemporary decision-making and suggests potential areas for future research, including the integration of subjective methods with emerging technologies and the development of more robust and consistent weighting frameworks. This paper aims to serve as a valuable resource for researchers and practitioners in the field of MCDM, offering a detailed overview of the current state of subjective weight determination methods and their practical implications. © 2024 The Authors.

关键词： Decision making

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Semi-Markov Telecommunication Networks Model

Semi-Markov Telecommunication Networks Model

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2024 International Conference on Actual Problems of Electron Devices Engineering, APEDE 2024

作者： Svetlov, Mikhail S. L’vov, Alexey A. Martirosyan, Arman M. Martirosyan, David M. Bagaev, Igor S. Khasanov, Semen T. Laboratory of Control and Automation Problems in Mechanical Engineering Institute of Precision Mechanics and Control of RAS Saratov Russia Institute of Institute of Electronic Engineering and Instrumentation Yuri Gagarin State Technical University of Saratov Saratov Russia Institute of Applied Information Technologies and Communications Yuri Gagarin State Technical University of Saratov Saratov Russia Phystech-School of Applied Mathematics and Computer Science Moscow Institute of Physics and Technology Moscow Russia

ISBN: (纸本)9798350393316

This paper proposes a semi-Markov model of telecommunication network (TCN). The variant of dynamic traffic adaptive control of queuing system as a special case of TCN is considered. The main purpose of control is to minimize the average cost per unit of time to service the incoming flow of information (packets). This takes into account the different bandwidth of the channels, the processing speed of information in the channel and the information capacity of the buffers. The approach to the organization of dynamic control taking into account noise immunity (information reliability) and information security is discussed. © 2024 IEEE.

关键词： Bandwidth

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