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4th International Conference on Smart Systems: Innovations in computing, SSIC 2023

作者： Ashokkumar, K. Dharshan, K. Ragupathi, T. Pritam, Anem Sagar, Amujuru Gnana Department of Computer Science Engineering Sathyabama Institute of Science and Technology Chennai India School of Computing and Mathematical Sciences University of Leicester Leicester United Kingdom Data Science and Business systems School of Computing SRM Institute of Science and Science and Technology Kattankulathur Chennai India

ISBN: (纸本)9789819736898

Leveraging D-NN trained on neuroimaging data, we can effectively estimate the chronological ages of normal persons;this projected brain age has potential as a biomarker for identifying age-related disorders. The suggested technique employs a CNN cascade network from DL and the Support Vector Machine (SVM) algorithm from ML (SVM). These techniques have been employed to train MRI scans of the brain, classifying them into regular (unaffected by illness), Alzheimer’s disorder (AD), and neurocognitive disability. That we also have the ability to determine ages thanks to the age classifications on the photos. The brain MRI collection is trained using CNN and SVM, on which the classifications and age estimate will be carried out. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Support vector machines

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TOWARDS ROBUST OUT-OF-DISTRIBUTION GENERALIZATION BOUNDS VIA SHARPNESS 12

TOWARDS ROBUST OUT-OF-DISTRIBUTION GENERALIZATION BOUNDS VIA...

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12th International Conference on Learning Representations, ICLR 2024

作者： Zou, Yingtian Kawaguchi, Kenji Liu, Yingnan Liu, Jiashuo Lee, Mong-Li Hsu, Wynne School of Computing National University of Singapore Institute of Data Science National University of Singapore Singapore Department of Computer Science & Technology Tsinghua University China

Generalizing to out-of-distribution (OOD) data or unseen domain, termed OOD generalization, still lacks appropriate theoretical guarantees. Canonical OOD bounds focus on different distance measurements between source and target domains but fail to consider the optimization property of the learned model. As empirically shown in recent work, the sharpness of learned minima influences OOD generalization. To bridge this gap between optimization and OOD generalization, we study the effect of sharpness on how a model tolerates data change in domain shift which is usually captured by "robustness" in generalization. In this paper, we give a rigorous connection between sharpness and robustness, which gives better OOD guarantees for robust algorithms. It also provides a theoretical backing for "flat minima leads to better OOD generalization". Overall, we propose a sharpness-based OOD generalization bound by taking robustness into consideration, resulting in a tighter bound than non-robust guarantees. Our findings are supported by the experiments on a ridge regression model, as well as the experiments on deep learning classification tasks. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Regression analysis

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Implementation of CBDC System for the Customised Development of Finance Service System 5

Implementation of CBDC System for the Customised Development...

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5th IEEE International Conference on computing, Power, and Communication Technologies, IC2PCT 2024

作者： Mehra, Devansh Vamsi, A. Sri Kavin, Prabhu Srm Institute of Science and Technology School of Computing College of Engineering and Technology Faculty of Engineering and Technology Department of Data Science and Business Systems Chennai India

ISBN: (纸本)9798350383522

CBDC-as-a-problem looks like a mania of interest from central banks and financial institutions all over the world. It may describe CBDC technology and CBDC technology development, the positive aspects of CBDC and its future perspectives as follows: The CBDC is linked to the existing banking systems in the past which was based on the past findings of the blockchain, DLT, etc., that possessed the qualities the previous ones did not have - security, trust, and transparency. Innovation, design and CBDC safety that falls below this paper are discussed in this section below. The paper proceeds to show several paths that central banks are taking to CBDC development given the regulation and changing dynamic of the financial world. However, the studies do not end there;information on the potential of CBDC for financial stability, monetary policy formulation trajectories, transaction privacy, and the role of banks is included. Given that in field of finance the CBDCs are becoming more and more important, this research paper shall ensure to provide consistent background to policymakers, financial institutions and society at large on CBDC and its structural implications. This guarantees that everyone is in the know so it will be possible for them to come up with compliant plans and decisions informed by the knowledge in this changing landscape that simply does not stop evolving. © 2024 IEEE.

关键词： CBDC DLT

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PALCT: vehicle-to-vehicle communication based on pseudonym assignment and encryption scheme using delay minimisation cover tree algorithm

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International Journal of Vehicle Information and Communication Systems 2025年第2期10卷 132-147页

作者： Tandon, Righa Gupta, P.K. Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Computer Science and Engineering Jaypee University of Information Technology HP Solan173 234 India Department of Data Science School of Computing Mohan Babu University AP Tirupati517 102 India

Vehicle-to-vehicle communication is one of the new paradigms of networking, which should be secure, fast, and efficient. In this paper, we propose a framework that implements the pseudonym-based authentication scheme in which communication among vehicles is encrypted by using a matrix array symmetric key (MASK), digital signature algorithm (DSA), and intelligent water drop (IWD). The proposed security scheme also ensures the handling of many security attacks like key-guessing, non-repudiation, replay, and modification. In the proposed scheme, to preserve the identity of the vehicle, we have provided the different pseudonyms for each vehicle in the network that ensure secure communication among vehicles. Furthermore, the proposed delay minimisation cover tree algorithm ensures the issue of timed delay during vehicle-to-vehicle communication. In this algorithm, we have used Dijkstra’s algorithm for finding the optimal shortest path during vehicular communication. The results obtained show that the proposed scheme is effective and efficient, as it reduces the time delay by 4% for 140 vehicle nodes and 28.4% for 1000 vehicle nodes. Copyright © 2025 Inderscience Enterprises Ltd.

关键词： Encryption algorithms

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Development of an Enhanced Quality Score Calculation Method for Accurate Assessment of Hotel Quality 5

Development of an Enhanced Quality Score Calculation Method ...

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5th International Conference on Advancements in computing, ICAC 2023

作者： Athurugiriya, A. A. A. Gaweshini Sumathipala, Prasanna Hemachandra, K.M. Tharindu Anupa Sri Lanka Institute of Information Technology Faculty of Computing Department of Data Science Malabe Sri Lanka

ISBN: (纸本)9798350358131

In this research paper, an enhanced hotel quality scoring method (EHQSM), is presented as a revolutionary way to analyze hotel quality. The EHQSM combines sentiment analysis, HOLSERV Plus dimensions classification, and amenity scores to deliver a more thorough review. The study generates an overall sentiment score by doing sentiment analysis on reviews categorized into HOLSERV Plus dimensions then thoughtfully averaging it using dimensionspecific weights collected from a survey. The availability of necessary amenities is considered when calculating the amenity score. The novel feature of this approach is how the amenity score, and sentiment score are carefully combined and efficiently weighted using values from the survey. The result is an improved quality score that accurately and thoroughly describes the quality of hotel services. With the goal of facilitating informed decisions for both hotel owners and attentive tourists, this technique establishes an updated standard for the evaluation of hospitality quality. © 2023 IEEE.

关键词： Sentiment analysis

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Enhancing Hotel Customer Satisfaction Assessment with Semantic Search-based Scoring 5

Enhancing Hotel Customer Satisfaction Assessment with Semant...

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5th International Conference on Advancements in computing, ICAC 2023

作者： Hemachandra, K.M Tharindu Anupa Sumathipala, Prasanna Athurugiriya, A.A.A Gaweshini Sri Lanka Institute of Information Technology Department of Data Science Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798350358131

Within the hospitality sector, ensuring customer satisfaction takes precedence, particularly in economies such as Sri Lanka, where tourism serves as a vital growth catalyst. Interestingly, disparities often arise between customer ratings and their written evaluations. This study presents an innovative strategy that utilizes semantic search techniques to extract comprehensive insights from customer feedback, leading to the development of a robust hotel scoring system. By exploring intricate emotions via advanced linguistic analysis, this method reveals underlying cues that conventional metrics often overlook. The method's effectiveness is validated through a comparative study with established hotel ratings. This advancement not only refines precise customer satisfaction assessment for hotels but also bears strategic significance for countries aiming to fortify their tourism sectors. In this era centered around data, this research provides a pivotal standpoint for optimizing hospitality evaluation, thereby enriching guest experiences, and guiding well-informed operational choices. © 2023 IEEE.

关键词： Sentiment analysis

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AstroFusion: A GAN-Augmented Approach for Exoplanet Detection 4

AstroFusion: A GAN-Augmented Approach for Exoplanet Detectio...

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4th IEEE International Conference on Emerging Techniques in Computational Intelligence, ICETCI 2024

作者： Suresh, Aakash Lakshmi, C. Gopirajan, P.V. Dhanasekaran, K. School of Computing Srm Institute of Science and Technology Chengalpattu Chennai TN Kattankulathur603203 India School of Computing Srm Institute of Science and Technology Department of Computational Intelligence Chengalpattu Chennai TN Kattankulathur603203 India School of Computing Srm Institute of Science and Technology Department of Data Science and Business Systems Chengalpattu Chennai TN Kattankulathur603203 India

ISBN: (纸本)9798350387063

Humanity's exploration of the cosmos spans billions of years, prompting contemplation of our position in the universe. This study advocates for proactive communication with potential intelligent species, driven by uncertainty about their existence. The focus is on exploring Generative Adversarial Networks (GANs) to enhance exoplanet detection through data augmentation. Utilizing the extensive Kepler dataset, the study evaluates the accuracy of conventional machine learning techniques: Logistic Regression, Decision Trees, and Random Forests. (RF)-trained on original data. Subsequently, it assesses the effectiveness of models trained solely on GAN-generated synthetic data and compares their performance with that of models trained on original data. Lastly, it merges original and synthetic data to create a composite dataset, evaluating the ML model's accuracy. The results indicate that models trained solely on synthetic data achieve comparable accuracy to those trained on original data. Furthermore, the combined dataset yields improved accuracy-87%, 95%, and 96% in Logistic Regression, Decision Tree, and RF, respectively-highlighting the potential of GAN-based data augmentation in enhancing exoplanet detection. This study advances space exploration by integrating technology with astronomical research, facilitating more precise and reliable exoplanet detection methods. Leveraging GANs for data augmentation promises novel insights and discoveries about the universe. © 2024 IEEE.

关键词： Generative adversarial networks

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A Modified EACOP Implementation for Real-Parameter Single Objective Optimization Problems 13

A Modified EACOP Implementation for Real-Parameter Single Ob...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Tangherloni, Andrea Coelho, Vasco Buffa, Francesca M. Cazzaniga, Paolo Bocconi Institute for Data Science and Analytics Bocconi University Department of Computing Sciences Milan Italy University of Milano-Bicocca Department of Informatics Systems and Communication Milan Italy Bocconi University Department of Computing Sciences Milan Italy Bocconi Institute for Data Science and Analytics Italy University of Bergamo Department of Human and Social Sciences Bergamo Italy

ISBN: (纸本)9798350308365

Evolutionary algorithms are effective techniques for optimizing non-linear and complex high-dimensional problems. However, most of them require a precise fine-tuning of their functioning settings to achieve satisfactory results. In this work, we propose a modified version of an evolutionary approach called the Evolutionary Algorithm for COmplex-process oPtimization (EACOP), designed to have a limited number of hyper-parameters. The base version of EACOP (bEACOP) combines different strategies, including the scatter search methodology, local searches, and a novel combination method based on path relinking to balance the exploration and exploitation phases. Our improved version (iEACOP) intensifies the exploration phase to escape from suboptimal search space areas where, on the contrary, bEACOP gets stuck. Our results show that iEACOP outperforms bEACOP on 27 out of 29 CEC 2017 test suite benchmark functions, exhibiting comparable performance against the three best algorithms of the CEC 2017 competition on single-objective bound-constrained real-parameter numerical optimization. The source code of bEACOP and iEACOP will be made publicly available on GitHub upon acceptance. © 2024 IEEE.

关键词： Optimization algorithms

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Forest-based Evolutionary Algorithm for Reconstructing Boolean Gene Regulatory Networks 21

Forest-based Evolutionary Algorithm for Reconstructing Boole...

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21st IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2024

作者： Stranieri, Nicolò Buffa, Francesca M. Tangherloni, Andrea Bocconi University Department of Computing Sciences Milan Italy University of Oxford Department of Oncology Oxford United Kingdom Bocconi University Bocconi Institute for Data Science and Analytics Department of Computing Sciences Milan Italy

ISBN: (纸本)9798350356632

Gene Regulatory Networks (GRNs) play a fundamental role in orchestrating the expression of our genes through complex interactions between DNA, RNA, proteins, and other molecules. Accurately reconstructing such networks from gene expression data is a critical yet challenging task in Systems Biology due to their intricate nature and limited data availability. In this work, we introduce a novel Forest-based Evolutionary Algorithm (FP) designed for reconstructing Boolean GRNs from time series data of gene expressions. Unlike traditional methods that struggle with scalability and accurate representation of regulatory interactions, FP utilizes a forest structure where each tree represents the logical relationships between genes, enhancing the model's capacity to depict complex networks efficiently. Our comprehensive testing indicates that FP rapidly converges towards potential solutions within a limited number of generations, although a higher fitness score does not always equate to a more accurate GRN representation. Implementing mini-batching techniques, inspired by their effectiveness in gradient descent optimization, shows promise in improving computational efficiency without sacrificing performance. A comparative analysis against the main state-of-the-art approaches reveals FP's tendency towards conservative predictions, emphasizing precision over recall, making it particularly suitable for contexts where the cost of false positives is high. These initial results suggest that FP is a robust and efficient tool for GRN inference. © 2024 IEEE.

关键词： Genetic programming

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Mobile Malware Attacks, Classification, Propagation, Analysis, Detection, Challenges and Future Directions – A Survey 14

Mobile Malware Attacks, Classification, Propagation, Analysi...

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14th International Conference on Advances in computing, Control, and Telecommunication Technologies, ACT 2023

作者： Senthilkumar, B. Sujithra, M. Mani Barathi, S.P.S. Department of Mechanical Engineering Kumaraguru College of Technology India Department of Computing – Data Science Coimbatore Institute of Technology India

Number of Smartphone users are increasing day by day and mobiles have become an integral part of the society. This is because of the rich variety of mobile devices and essential applications provided by its manufacturers. The increasing number of mobile devices invite skilled developers and hackers to develop malware that invades personal and business information in a very efficient manner. Therefore, mobile devices are an ideal target for various security issues and data privacy threats in a mobile ecosystem. Threats posed by malwares include leaking of private information, financial loss to users, system damage. For better protection on computers, researchers and manufacturers making great efforts to produce anti-malware systems with effective detection methods why the most targeted platform for the malware developers is Android and why and how and when malwares propagate into the mobile system with how they are detected, and protection mechanism is discussed in this paper. © Grenze Scientific Society, 2023.

关键词： Personal computing

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