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Future Machine Learning and Data Science (FMLDS), IEEE International Conference on

作者： Selahattin Hürol Türen Rafiqul Islam Kenneth Eustace Geoffrey Fellows School of Computing Mathematics & Engineering (Charles Sturt University) Wagga Wagga Australia School of Computing Mathematics & Engineering (Charles Sturt University) Albury Australia

ISBN: (数字)9798350391213

ISBN: (纸本)9798350391220

Cybersecurity is crucial in mitigating illegal access and hacking of online resources and network systems, and with the protection of network traffic vital by various detection and prevention techniques against cyber-attacks. Internet communication that occurs on the Dark Web in particular, contains sensitive data that should remain inaccessible to unauthorized users. However, threat actors are empowered by anonymous browsing on the Dark Web. This paper investigates browser fingerprint attacks on the Dark Web, focusing on identifying attack patterns. A detection model based on traditional machine learning techniques is developed using a large sample of fingerprint data. Feature selection techniques are applied to create optimized training and test datasets for classification. The model is validated using cross-validation methods to minimize overfitting and underfitting. Empirical results demonstrate that the proposed model effectively identifies malicious browsers on the Dark Web.

关键词： Training Dark Web Accuracy Machine learning Telecommunication traffic Fingerprint recognition Browsers Protection Overfitting Testing

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A Deep Drive Analysis Framework on Emotions of Users in Attention Driven Systems 8

A Deep Drive Analysis Framework on Emotions of Users in Atte...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Dharshini, S. Akshita, Ravula Panigrahi, Suman Varma, Nadimpalli Sai Kiran Kumar Thangavel, Senthil Somasudaram, K. Abel Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Tamil Nadu Coimbatore India Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Coimbatore India Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Mathematics Tamil Nadu India Cape Peninsula University of Technology Faculty of Informatic and Design Department of Information Technology South Africa

ISBN: (纸本)9798350376425

One of the ways humans communicate is by using facial expressions. In psychology, the detection of emotions or facial expressions requires analysis and assessment of decisions in predicting a person's emotions or group of people in communicating. Emotion is powerful in many ways because it can influence a decision and urge people to act. This emotion like anger, happiness, sadness, disgust, fear, surprise, and neutral detection is used for human behaviour and understanding, action of mental disorders, and synthetic human expressions. This can be used in healthcare, marketing, and manufacturing. Here the paper is based on marketing where we can detect the emotions of the people watching the ads. This emotion detection for the ads can be used for predictions like whether customers will like the product or not, whether the sales will increase or not, etc. The methodology used to predict human emotion through the face is CNN and MobileNetV2 with LSTM which is a pretrained model. The architecture involves pre-processing of the data, feature detection, face detection, and detection of emotion. There are various datasets used for detecting emotions like FER-2013, JAFFE, CK+, etc. Here the FER-2013 is used. The performance of the model is measured by using confusion matrix, recall, precision, f1-score, and accuracy. © 2024 IEEE.

关键词： Face recognition

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Maximum Independent Sets and Supervised Learning

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Journal of the Operations Research Society of China 2023年第4期11卷 957-972页

作者： Roberto Montemanni Derek H.Smith Xiao-Chen Chou Department of Sciences and Methods for Engineering University of Modena and Reggio EmiliaVia Amendola 242122Reggio EmiliaItaly School of Computing and Mathematics University of South WalesPontypriddCF371DLWalesUK

The paper discusses an enhancement to a recently presented supervised learning algorithm to solve the Maximum Independent Set *** particular,it is shown that the algorithm can be improved by simplifying the task learnt by the neural network adopted,with measurable effects on the quality of the solutions provided on unseen *** results are presented to validate the idea..

关键词： Maximum Clique problem Maximum Independent Set problem Machine learning Graph theory

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INERTIAL BREGMAN EXTRAGRADIENT-LIKE ALGORITHMS FOR VARIATIONAL INEQUALITIES AND FIXED POINT PROBLEMS IN BANACH SPACES

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UPB Scientific Bulletin, Series A: Applied mathematics and Physics 2024年第4期86卷 49-60页

作者： Ceng, Lu-Chuan Yao, Zhangsong Yin, Tzu-Chien Department of Mathematics Shanghai Normal University Shanghai200234 China School of Information Engineering Nanjing Xiaozhuang University Nanjing211171 China Research Center for Interneural Computing China Medical University Hospital China Medical University Taichung40402 Taiwan

In this paper, we design an inertial Bregman extragradient-like algorithm with linesearch process for solving two pseudomonotone variational inequalities (VIPs) and the common fixed point problem (CFPP) of a Bregman relatively asymptotically non-expansive mapping and finitely many Bregman relatively nonexpansive mappings in p-uniformly convex and uniformly smooth Banach spaces, which are more general than Hilbert spaces. Under mild conditions, we prove weak convergence of the suggested algorithm to a common solution of two pseudomonotone VIPs and the CFPP. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Banach spaces

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Stochastic SEIR epidemic models with virus mutation and logistic growth of susceptible populations

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mathematics and Computers in Simulation 2023年第1期212卷 289-309页

作者： Wang, Qi Xiang, Kainan Zhu, Chunhui Zou, Lang Hunan Key Laboratory for Computation and Simulation in Science and Engineering & Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education & School of Mathematics and Computational Science Xiangtan University Hunan Province Xiangtan City411105 China National Center for Applied Mathematics in Hunan China

This article introduces a kind of stochastic SEIR models containing virus mutation and logistic growth of susceptible populations, whose deterministic versions have a positively invariant set and globally asymptotically stable equilibrium points. For these stochastic SEIR epidemic models, we prove they have a unique global positive solution, and also obtain sufficient conditions respectively for survival and extinction of the infectious disease. Eventually, we validate our theoretical findings using numerical simulations. © 2023 International Association for mathematics and Computers in Simulation (IMACS)

关键词： Viruses

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Boundary Control of Coupled Wave Systems with Spatially-Varying Coefficients

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Journal of Systems Science & Complexity 2022年第4期35卷 1310-1329页

作者： FENG Xiaodan ZHANG Zhifei School of Mathematics and Statistics Huazhong University of Science and TechnologyWuhan430074China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and TechnologyWuhan430074China

This paper considers the stabilization of the coupled wave systems with spatially-varying *** authors design a state feedback controller by backstepping *** contrast to the previous work in the literature,the kernel equations become more complicated and the main difficulty lies in proving the existence and uniqueness of the solution to the kernel ***,using the backstepping approach,the authors verify the kernel equations,which is a system of coupled hyperbolic equations with spatially-varying ***,the existence and uniqueness of the kernel matrices is ***,the authors use a Lyapunov function to get the exponential stabilization of the closed-loop system.A numerical example is presented to illustrate the effectiveness of the proposed controller.

关键词： Backstepping boundary control coupled wave systems exponential stabilization spatially-varying coefficients

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Mixed finite element methods for biharmonic obstacle problems

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SeMA Journal 2025年 1-10页

作者： Piersanti, Paolo Sun, Tianyu School of Science and Engineering The Chinese University of Hong Kong (Shenzhen) 2001 Longxiang Blvd. Longgang District Shenzhen China Department of Mathematics and Institute for Scientific Computing and Applied Mathematics Indiana University Bloomington 729 East Third Street Bloomington IN United States

This paper is devoted to the study of an alternative Finite Element Method to the one originally proposed by Ciarlet & Raviart, and then complemented by Ciarlet & Glowinski, for studying the numerical approximation of the solution of the biharmonic problem. In addition to providing an alternative way of approximating the solution of the biharmonic problem, the method here presented is valid also in the context where the solution to the biharmonic problem is subjected to a constraint. The theoretical results we derived are complemented by a series of numerical experiments. © The Author(s), under exclusive licence to Sociedad Española de Matemática Aplicada 2025.

关键词： Elasticity theory Finite element method Obstacle problems Penalty method Variational inequalities

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Real Time Identification of Harmful Birds in Agriculture Field using Computer Vision 7

Real Time Identification of Harmful Birds in Agriculture Fie...

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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Sudhesh, K.M. Akhila, T. Thangavel, Senthil Kumar Shanmugam, Selvanayaki Kolandapalayam Amrita Vishwa Vidhyapeetham Amrita School of Computing Department of Computer Science And Engineering Coimbatore India Ashland University Department of Mathematics And Computer Science OH United States

ISBN: (纸本)9798350359299

Agriculture is essential to the global economy and food security. Insect and bird attacks have now been found in recent research that could cause crop loss. Crops are prone to bird attacks throughout the early stages of crop production and are particularly sensitive from the milky stages up to maturation. Observing such birds, which are harmful to agriculture, is an expensive, time-consuming, and possibly error-prone operation. Furthermore, a vast area necessitates a huge labour force for bird scaring. The concept of automated monitoring through computer vision holds significant appeal. This is because it has the potential to facilitate the collection of comprehensive data on a much larger scale than is currently feasible. In this work, we leverage effective characteristics from images of 10 different hazardous birds, Especially in the realm of identification we employing transfer-learned deep learning models which holds promise. The resemblance of various bird features, as well as the difficulty of distinguishing them at a glimpse, has become a significant challenge. We used more than 1000 images of harmful birds from various species for model training. In experiments on two different transfer learned deep CNN models, the xceptionNet model showed the best performance with a test accuracy of 94% when compared to the relatively low memory model VGG19, which had a test accuracy of 80%.The analysis also revealed that the xception model performed better in terms of accuracy, precision, recall, and F1-score. © 2024 IEEE.

关键词： Birds

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Future BANs - DTN Applications and Requirements 28

Future BANs - DTN Applications and Requirements

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28. VDE ITG-Fachtagung Mobilkommunikation: Technologien und Anwendungen - 28th VDE ITG Conference on Mobile Communication: Technologies and Applications

作者： Khaldi, Rami Lehmann, Armin Ghita, Bogdan Trick, Ulrich Research Group for Telecommunication Networks Frankfurt University of Applied Sciences Frankfurt am Main Germany School of Engineering Computing and Mathematics University of Plymouth Plymouth United Kingdom

ISBN: (纸本)9783800763832

With the anticipated development of 6G technology, the scope of Body Area Network (BAN) applications is undergoing significant expansion, enhancing capabilities for a wider range of sophisticated scenarios, including augmented/virtual reality, holographic-type communication, and in particular integrated sensing and communication. This evolution introduces more stringent requirements, such as high data rates, low latency, precise synchronization, and advanced sensing capabilities. Given these advancements, traditional simulators, constrained by their inability to provide a real-time bidirectional connection with the actual network, fall short of addressing these complexities. A Digital Twin Network (DTN), serving as a real-time virtual replica of the physical network, can bridge this gap by simulating and testing BANs in order to troubleshoot, predict, and optimize their functionality and performance. This paper aims to present advanced BAN use cases with a special focus on sensing along with their stringent demands and demonstrates how DTN plays a crucial role in addressing these requirements through tailored DTN applications. Additionally, it will elaborate on the specific requirements for the digital twin that emerge from these applications. This work also involves identifying potential models that need to be considered to construct a comprehensive BAN digital twin framework. © 2024 Mobilkommunikation: Technologien und Anwendungen - 28. VDE ITG-Fachtagung. All rights reserved.

关键词： 5G mobile communication systems

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Domination Number in Sierpiński Networks

Domination Number in Sierpiński Networks

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International Conference on Computational engineering, ICCE 2023

作者： Anitha, J. Rajasingh, Indra Sharon, Jane Olive Department of Mathematics Rajalakshmi Institute of Technology Chennai India Department of Mathematics for Excellence Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computing Technologies SRM Institute of Science and Technology Chennai India

ISBN: (纸本)9783031777639

If there is at least one neighbour in K for each vertex in V that is not in K, then a set K⊆V(G) is a dominating set (DS) in G(V,E). The minimal cardinality of a DS of G is the domination number(DN) of G, represented by γ(G). In this paper, we determine the γ(G) for Sierpiński networks, Str and the divide-and-swap cubic networks, DSCr. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： 68R10 81Q30 82B20 82C20 Divide-and-swap cubic networks Dominating set Sierpiński Networks

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