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Regularization Mixup Adversarial Training: A Defense Strategy for Membership Privacy with Model Availability Assurance

Regularization Mixup Adversarial Training: A Defense Strateg...

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Big Data and Privacy Computing (BDPC), international conference on

作者： Zehua Ding Youliang Tian Guorong Wang Jinbo Xiong State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang China Fujian Provincial Key Laboratory of Network Security and Cryptology College of Computer and Cyber Security Fujian Normal University Fuzhou China

ISBN: (数字)9798350307597

ISBN: (纸本)9798350307603

Neural network models face two highly destructive threats in real-world applications: membership inference attacks (MIAs) and adversarial attacks (AAs). One compromises the model's confidentiality, leading to membership privacy breaches, while the other disrupts the model's availability, rendering it dysfunctional. Recent work has shown that adversarial examples can pose dual threats to neural network models, both MIAs and AAs, so that these two different types of attacks have a certain degree of intersection. However, existing defense methods typically focus on defending against one of the two attacks and cannot simultaneously address both. To address the above issues, we propose a defense method called regularization mixup adversarial training (RMAT), aiming to protect model membership privacy while ensuring model availability. The core idea of RMAT is to use a continuous augmentation strategy during training to generate mixup adversarial examples, weakening attackers' understanding of membership data, and updating the model with a new membership-weighted loss strategy to improve its generalization ability for handling unknown samples. This approach can further protect the model's membership privacy and ensure model availability. Experimental results demonstrate that compared to single defense strategies, RMAT can simultaneously protect the model's membership privacy and availability.

关键词： Training Privacy Data privacy Neural networks computer architecture Rendering (computer graphics) Privacy breach

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Orthogonal Polynomials and Their Engineering applications 2nd

Orthogonal Polynomials and Their Engineering Applications

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2nd international conference on Business Data Analytics, ICBDA 2023

作者： Sayal, Anu Jha, Janhvi Chaithra, N. Nithin, Allagari Shankar, Bhavani Gupta, Ashulekha School of Accounting and Finance Taylor’s Business School Taylor’s University Selango Malaysia Karnataka Bangalore India Uttarakhand Dehradun India

ISBN: (纸本)9783031807770

When solving mathematical and physical problems, orthogonal polynomials provide a number of beneficial qualities. Orthogonal polynomials offer a natural approach to solving, expanding, and comprehending solutions to many different kinds of significant differential equations, just as the Fourier series offer a practical way of breaking down a periodic function into a sequence of linearly independent components. Gram-Schmidt orthonormalization makes it extremely simple to create orthogonal polynomials. Orthogonal polynomials are mathematical functions that are used in a variety of engineering applications. These polynomials have the property that the integral of the product of two different orthogonal polynomials over a given interval is equal to zero. This property makes orthogonal polynomials particularly useful in the field of approximation theory, where they are used to approximate continuous functions with a series of polynomials. They are also used in the field of control theory, where they are used to design control systems that are stable and achieve good performance. In addition, orthogonal polynomials are used in the field of signal processing, where they are used to analyse and manipulate signal. In summary, orthogonal polynomials are important mathematical functions that have a wide range of engineering applications. They are used in fields such as numerical analysis, control theory, and signal processing, and have proven to be powerful tools for solving complex problems in these fields. In the contribution, we will discuss the relationship between the research of orthogonal polynomials and its potential applications to undergraduate, graduate, and doctorate engineering study programs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Fourier series

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Research on the Prediction of Rockburst Risk in Deep Coal Mining Based on Random Forest and Support Vector Machine Models

Research on the Prediction of Rockburst Risk in Deep Coal Mi...

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Sensors, Electronics and computer Engineering (ICSECE), IEEE international conference on

作者： Zhaozhuo Qu Hongyou Zhuo Zijing Ye Huiling Tao Minglong Li Anhui University of Science and Technology Chuzhou China

ISBN: (数字)9798350373646

ISBN: (纸本)9798350373653

This article studies and develops a prediction model that combines random forest and support vector machine (SVM), aiming to solve the safety problems caused by rockburst during deep coal mining in China. This model accurately extracts precursor characteristic signals from acoustic emission (AE) and electromagnetic radiation (EMR) monitoring data, achieving accurate warning of rockburst. Data preprocessing includes using summary functions and K-S tests to ensure data integrity and distribution characteristics, as well as using box plots to handle outliers. The feature extraction stage focuses on extracting key information from the statistical and frequency characteristics of the signal, and using Fourier transform to analyze the signal. The identification of interference signals adopts a logistic regression model, and the random forest model is used to enhance the recognition ability of precursor characteristic signals. Support Vector Machine (SVM) processes nonlinear relationships and displays prediction results through visualization. Research has shown that the model is innovative in theory and demonstrates high accuracy and reliability in practical applications, providing a new technical approach for early warning of coal mine rockburst and leading the way in mining engineering safety management.

关键词： Support vector machines Accuracy Safety management Predictive models Reliability theory Feature extraction Data models Coal mining Data mining Monitoring

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Clustering Permutations: New Techniques with Streaming applications 14

Clustering Permutations: New Techniques with Streaming Appli...

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14th Innovations in Theoretical computer Science conference, ITCS 2023

作者： Chakraborty, Diptarka Das, Debarati Krauthgamer, Robert National University of Singapore Singapore Pennsylvania State University University ParkPA United States Weizmann Institute of Science Rehovot Israel

ISBN: (纸本)9783959772631

We study the classical metric k-median clustering problem over a set of input rankings (i.e., permutations), which has myriad applications, from social-choice theory to web search and databases. A folklore algorithm provides a 2-approximate solution in polynomial time for all k = O(1), and works irrespective of the underlying distance measure, so long it is a metric;however, going below the 2-factor is a notorious challenge. We consider the Ulam distance, a variant of the well-known edit-distance metric, where strings are restricted to be permutations. For this metric, Chakraborty, Das, and Krauthgamer [SODA, 2021] provided a (2 − δ)-approximation algorithm for k = 1, where δ ≈ 2−40. Our primary contribution is a new algorithmic framework for clustering a set of permutations. Our first result is a 1.999-approximation algorithm for the metric k-median problem under the Ulam metric, that runs in time (k log(nd))O(k)nd3 for an input consisting of n permutations over [d]. In fact, our framework is powerful enough to extend this result to the streaming model (where the n input permutations arrive one by one) using only polylogarithmic (in n) space. Additionally, we show that similar results can be obtained even in the presence of outliers, which is presumably a more difficult problem. © Diptarka Chakraborty, Debarati Das, and Robert Krauthgamer;licensed under Creative Commons License CC-BY 4.0.

关键词： Approximation algorithms

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A theory of Topological Derivatives for Inverse Rendering of Geometry

A Theory of Topological Derivatives for Inverse Rendering of...

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international conference on computer Vision (ICCV)

作者： Ishit Mehta Manmohan Chandraker Ravi Ramamoorthi University of California San Diego

We introduce a theoretical framework for differentiable surface evolution that allows discrete topology changes through the use of topological derivatives for variational optimization of image functionals. While prior methods for inverse rendering of geometry rely on silhouette gradients for topology changes, such signals are sparse. In contrast, our theory derives topological derivatives that relate the introduction of vanishing holes and phases to changes in image intensity. As a result, we enable differentiable shape perturbations in the form of hole or phase nucleation. We validate the proposed theory with optimization of closed curves in 2D and surfaces in 3D to lend insights into limitations of current methods and enable improved applications such as image vectorization, vector-graphics generation from text prompts, single-image reconstruction of shape ambigrams and multiview 3D reconstruction.

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A computer Presentation of the Analytical and Numerical Study of Nonlinear Vibration Response for Porous Functionally Graded Cylindrical Panel 2nd

A Computer Presentation of the Analytical and Numerical Stud...

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2nd international conference on Advanced Engineering, Technology and applications, ICAETA 2023

作者： Mouthanna, Ahmed Bakhy, Sadeq H. Al-Waily, Muhannad College of Engineering University of Anbar Anbar Ramadi Iraq Mechanical Engineering Department University of Technology Baghdad Iraq Department of Mechanical Engineering Faculty of Engineering University of Kufa Kufa Iraq

ISBN: (纸本)9783031509193

The current study uses a new analytical model and numerical method to present a study of free vibration carried out on a cylindrical shell panel that is simply supported and functionally graded. It is anticipated that the FG thickness attributes will be dependent on the porosity level and will change along the thickness axis in accordance with a distribution that follows a power-law. This work makes a contribution by analyzing the performance of porous FGMs, which are employed in a particularly wide variety of biomedical applications. For the purpose of determining the free vibration characteristics as well as the nonlinear vibration response, the governing equations are constructed on a first-order shear deformation theory by utilizing the Galerkin technique with the fourth-order Runge Kutta a close encounter with an incomplete FGM cylindrical shell panel and include different parameters. Parameters included are the power-law index, graded distributions of porosity, and FG thickness. With the help of both the ANSYS 2021-R1 software, a numerical investigation was carried out making use of the finite element approach, and a modal investigation was carried out. This was done in order to verify the analytical strategy. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Analytical Investigation Frequency Materials with a Functional Grading Nonlinear Dynamic Response Porous theory of First-Order Shear Deformation

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Design and Implementation of Authentication for Remote Sensing Images in Traffic Congestion Control System using Hash Function in Graph theory

Design and Implementation of Authentication for Remote Sensi...

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international conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN)

作者： Ramya S Manivannan Doraipandian Kannan Krithivasan Madhubala P School of Computing Sastra Deemed University Tanjore India

Internet of Things (IoT) is a system that combines many technologies and devices, eliminating the need for human intervention. IoT envisions a world of networked, intelligent things that can exchange data digitally. The implementation of IoT paradigm in the urban setting has been one of the most fascinating application areas since the IoT paradigm's debut, creating the so-called Smart City idea. The transportation industry is using connected and smart devices more and more, which finally exposes security concerns from the external world without any constraints. Cryptography has become a crucial area of study and development as a result of the increased usage of telecommunications technology in recent years, especially when it comes to data transfer securely between two or more different entities when that data is deemed to be critical. Authenticity, confidentiality, security and privacy are crucial components of smart city applications and are prominent in the data management interface of the infrastructure. Authentication and Data integrity are made possible through the use of hashing, a method for providing a type of computer security. A hash function is a mathematical procedure that converts one input numeric value into the other. This paper provides a solution to secure traffic data problems and avoid identity theft by implementing message hashing and image hashing.

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Framework-based Middle Layer Implementation Technology for 5G Communication Modules for Embedded System applications

Framework-based Middle Layer Implementation Technology for 5...

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computer graphics, Image and Virtualization (ICCGIV), international conference on

作者： Lei Chen Sicheng An Lei Wang Zhejiang Electric Power CO.LTD Zhejiang State Grid China Control and Computer Engeering School North China Electric Power University Beijing China

The base station network and terminal of 5G communication are developing rapidly, and the way of applying 5G communication in intelligent embedded terminal has continued to develop from baseband and baseband chip to the form of standalone module with higher integration degree. Compared to the baseband approach of self-designed hardware and software, the 5G module simplifies the design and decouples the system by perfecting the integration of 5G communication functions and providing only serial AT instructions to the caller side. But the module hardware interact with high level application is also hard due to soft function and module instruction could not directly call and execute. AT instructions abstractly define the transmission mode and format of instructions and data in communication in a more concise way, but in the application there are still complex and high- dimensional logic and timing relationships of the instruction execution combination. This article design and propose a middle layer software framework to solve interaction between application and 5G module, and it simply the communication function running for application caller and decouple the hardware module from specification data and protocol. The experiment shows the framework software could efficiently running and improve application communication efficiency to 30%, and compare with construct communication function according to specific application and protocol data, it simply the module embedding and enable module AT instruction to execute fully efficient more 23% to before.

关键词： Baseband Protocols Software design 5G mobile communication Memory management Software Hardware

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applications of Artificial Intelligence in Structural Engineering

Applications of Artificial Intelligence in Structural Engine...

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Multidisciplinary Engineering and Applied Science (ICMEAS), international conference on

作者： Temitope Olatunji Sadiq Thomas Nyangwarimam Ali Obadiah Oluseun Oyeleke Chinomso Odimba Shariff Lawal Computer Engineering Nile University of Nigeria Abuja Nigeria Industrial Chemistry Nile University of Nigeria Abuja Nigeria Mechanical Engineering Airforce Institute of Technology Kaduna Nigeria

ISBN: (数字)9798350358834

ISBN: (纸本)9798350358841

AI has the potential to revolutionize the way we design, build, and maintain our built environment. The paper provides an overview of various AI branches, including deep learning, neural networks, swarm optimization, fuzzy logic, machine learning, pattern recognition, probability theory, and metaheuristic optimization. It highlights the applications of AI in structural engineering, such as structural health monitoring, modular construction decision making, and vibration control. The paper also examines the limitations, challenges, and opportunities associated with the adoption of AI in the industry. The paper concludes that AI has enormous potential to enhance the efficiency, safety, and sustainability of structural engineering, and that further research and collaboration between academia and industry are necessary to fully realize the benefits of this technology.

关键词： Industries Modular construction Decision making Vibration control Structural engineering Artificial intelligence Monitoring

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An Overview of the theory and Application of Reinforcement Learning 2

An Overview of the Theory and Application of Reinforcement L...

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2021 2nd international conference on Machine Learning and computer Application, ICMLCA 2021

作者： Zhang, Yumeng Faculty of Applied Science Integrated Engineering University of British Columbia VancouverBCV6T 1Z4 Canada

ISBN: (纸本)9783800757398

As an important branch of machine learning research, reinforcement learning can obtain strategy improvement through the interaction of trial and environment and is widely applied in various fields. Research on reinforcement learning theory is helpful for subsequent multidisciplinary projects. However, related researches are still relatively scattered. Thus, this paper introduces the theory and application of reinforcement learning by literature analysis and comprehensively introduces the main algorithms theory of reinforcement learning, including temporal difference learning, Q-learning and Sarsa learning, as well as their combination and effect comparison. Besides, this paper also summarizes the current applications of reinforcement learning that have received more attention, namely control systems, autonomous driving, and robots. Moreover, the current research issues and future work directions of reinforcement learning are discussed. Overall, this article concludes that the current basic algorithm construction of reinforcement learning is relatively complete, but the method of combining multiple algorithms remains to be discussed. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Reinforcement learning

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