检索结果-内蒙古大学图书馆

3rd World Conference on Intelligent and 3D Technologies, WCI3DT 2024

作者： Su, Jianna Department of Mathematics and Computer Engineering Ordos Institute of Applied Technology Inner Mongolia Erdos017010 China

ISBN: (纸本)9789819791231

This article explores the application of computer vision technology in user interface design, particularly through gesture recognition to enhance human–computer interaction. Gestures offer natural and versatile advantages in the process of human–computer interaction. Vision-based gesture recognition technology has broad application potential in virtual environments, sign language recognition, machine control, and other fields. In the task of gesture recognition in user interface design, the recognition results are affected by some irrelevant factors, such as dynamic backgrounds and close-fitting clothing. The attention mechanism is a good way to address the above problems, as it applies weights to key areas to extract essential features, thereby improving the model's performance. Several commonly used attention mechanisms, such as spatial attention, channel attention, and mixed attention mechanisms, can only apply attention to a single-frame image, focusing on specific regions. However, gestures consist of sequences of multiple-frame images, and the recognition results are collectively influenced by multiple-frame gesture images. The aforementioned attention mechanisms cannot meet the requirements effectively. To address this issue, a joint intra-frame and inter-frame attention module has been investigated. The model is able to prevent the impact of irrelevant elements during the gesture identification process because of this module's ability to apply attention concurrently across many consecutive frames and inside a single frame. In order to further user interface design, this study employs convolutional neural networks to include gesture recognition. These results shed light on how computer vision technology may revolutionize UI design and enhance user experiences. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Monolithic 3-D Integration of Diverse Memories: Resistive Switching (RRAM) and Gain Cell (GC) Memory Integrated on Si CMOS

引用

IEEE Transactions on Electron Devices 2025年第5期72卷 2685-2690页

作者： Liu, Shuhan Radway, Robert M. Wang, Xinxin Moro, Filippo Nodin, Jean-Francois Jana, Koustav Yan, Lixian Du, Shuting Upton, Luke R. Chen, Wei-Chen Kang, Jimin Chen, Jian Li, Haitong Andrieu, Francois Vianello, Elisa Raina, Priyanka Mitra, Subhasish Wong, H.-S. Philip Stanford University Department of Electrical Engineering StanfordCA94305 United States University of Pennsylvania School of Engineering and Applied Science Department of Electrical and Systems Engineering PhiladelphiaPA19104 United States Université Grenoble Alpes CEA-Leti Grenoble38058 France Purdue University Department of Electrical and Computer Engineering West LafayetteIN47907 United States

The future memory is massive, diverse, and tightly integrated with computing. This research presents tight integration, both physically and architecturally, of two on-chip memory technologies, resistive switching random access memory (RRAM) and gain cell (GC) memory. HfO2 RRAM and indium tin oxide (ITO) GC memory are monolithically integrated on 130-nm Si CMOS technology to form a joint memory that enables low-energy training and low-standby-power inference for edge devices. High-bandwidth on-chip data transfer can have a bandwidth that is 90x state-of-the-art (SoTA) HBM3E and 211x PCIe 7.0, enabled by high-density monolithic 3-D interconnections between memory arrays and high-speed transfer circuit within the integrated joint memory macro. Fabricated atomic layer deposition (ALD) ITO FET exhibits positive VTHof 0.67 V, excellent subthreshold slope (SS) of 65 mV/dec, high ON-current of 20 μA/μm, and low OFF-current of 5 x 10-18 A/μm, as extracted from >5000 s retention. The joint memory macro consumes 78% less standby power and 95% less training energy for MobileBERT compared to SRAM with iso-capacity. This RRAM-GC joint memory facilitates efficient continual learning in edge devices, addressing the challenges of a resource-constrained environment while supporting adaptive artificial intelligence (AI) model updates. © 1963-2012 IEEE.

关键词： RRAM

来源：评论

学校读者我要写书评

暂无评论

Privacy-preserving explainable AI: a survey

引用

Science China(Information Sciences) 2025年第1期68卷 23-56页

作者： Thanh Tam NGUYEN Thanh Trung HUYNH Zhao REN Thanh Toan NGUYEN Phi Le NGUYEN Hongzhi YIN Quoc Viet Hung NGUYEN School of Information and Communication Technology Griffith University School of Computer and Communication Sciences Ecole Polytechnique Federale de Lausanne Faculty of Mathematics and Computer Science University of Bremen Faculty of Information Technology HUTECH University Department of Computer Science Hanoi University of Science and Technology School of Electrical Engineering and Computer Science The University of Queensland

As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model explanations. This article presents the first thorough survey about privacy attacks on model explanations and their countermeasures. Our contribution to this field comprises a thorough analysis of research papers with a connected taxonomy that facilitates the categorization of privacy attacks and countermeasures based on the targeted explanations. This work also includes an initial investigation into the causes of privacy leaks. Finally, we discuss unresolved issues and prospective research directions uncovered in our analysis. This survey aims to be a valuable resource for the research community and offers clear insights for those new to this domain. To support ongoing research, we have established an online resource repository, which will be continuously updated with new and relevant findings.

关键词： privacy-preserving explainable AI privacy attacks privacy defences PrivEx PPXAI

来源：评论

学校读者我要写书评

暂无评论

Addressing Imbalance in Health Datasets: A New Method NR-Clustering SMOTE and Distance Metric Modification

引用

computers, Materials & Continua 2025年第2期82卷 2931-2949页

作者： Hairani Hairani Triyanna Widiyaningtyas Didik Dwi Prasetya Afrig Aminuddin Department of Electrical Engineering and Informatics Faculty of EngineeringUniversitas Negeri MalangMalang65145Indonesia Department of Computer Science Universitas BumigoraMataram83127Indonesia Department of Computer Graphic and Multimedia Faculty of ComputingCollege of Computing and Applied SciencesUniversiti Malaysia Pahang Al-Sultan AbdullahPekan26600Malaysia

An imbalanced dataset often challenges machine learning, particularly classification methods. Underrepresented minority classes can result in biased and inaccurate models. The Synthetic Minority Over-Sampling Technique (SMOTE) was developed to address the problem of imbalanced data. Over time, several weaknesses of the SMOTE method have been identified in generating synthetic minority class data, such as overlapping, noise, and small disjuncts. However, these studies generally focus on only one of SMOTE’s weaknesses: noise or overlapping. Therefore, this study addresses both issues simultaneously by tackling noise and overlapping in SMOTE-generated data. This study proposes a combined approach of filtering, clustering, and distance modification to reduce noise and overlapping produced by SMOTE. Filtering removes minority class data (noise) located in majority class regions, with the k-nn method applied for filtering. The use of Noise Reduction (NR), which removes data that is considered noise before applying SMOTE, has a positive impact in overcoming data imbalance. Clustering establishes decision boundaries by partitioning data into clusters, allowing SMOTE with modified distance metrics to generate minority class data within each cluster. This SMOTE clustering and distance modification approach aims to minimize overlap in synthetic minority data that could introduce noise. The proposed method is called “NR-Clustering SMOTE,” which has several stages in balancing data: (1) filtering by removing minority classes close to majority classes (data noise) using the k-nn method;(2) clustering data using K-means aims to establish decision boundaries by partitioning data into several clusters;(3) applying SMOTE oversampling with Manhattan distance within each cluster. Test results indicate that the proposed NR-Clustering SMOTE method achieves the best performance across all evaluation metrics for classification methods such as Random Forest, SVM, and Naїve Bayes, compared t

关键词： SMOTE modification Clustering-SMOTE manhattan distance

来源：评论

学校读者我要写书评

暂无评论

Development of Mechatronic Solution on Hot-Stamping Heads 33rd

Development of Mechatronic Solution on Hot-Stamping Heads

引用

33rd International Conference on Organization and Technology of Maintenance, OTO 2024

作者： Ostojić, Ivan Velimirović, Mirjana Kovačević, Nada Ratković Dihovicni, Djordje Computer-Mechanical Engineering Section Department of Electrical and Computer Engineering Academy of Technical Applied Studies Belgrade Belgrade Serbia Urban Technics Valjevo Serbia

ISBN: (纸本)9783031805967

The general goal of the research is to reduce loss of productivity, failure and downtime and the percentage of waste in production in the company, which is already committed to and successful in applying standards, raising the quality of service, as well as occupational safety and environmental protection. In this scientific paper a mechatronic subsystem is designed and implemented, as an addition to the hot-stamping production line, which would monitor whether there are present (and whether there are in quantities enough of) each of the three thermoplastic, metallized strips, which line the product - profiled lath. When it is detected and recognized that the tape will soon be used up, the sub-system automatically signals this with turning off heating of the slat and activating a sound alarm, attracting attention of the human operator. The heater switches off automatically if the strip loss has occurred (event driven system), in order to prevent deformation of the slat profile. The subsystem includes automatic monitoring of the remaining amount of tape, alarm notification in case of imminent disappearance of the tape, with the heater turned off and alarming the operator. The human operator then has enough time to replace the tape (approximately five to ten minutes, depending on the product). The subsystem described above is designed, built, implemented, tested and put in operation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Quality of service

来源：评论

学校读者我要写书评

暂无评论

Federated Blockchain-Based Clustering Protocol for Enhanced Security and Connectivity in FANETs With CF-mMIMO

引用

IEEE Internet of Things Journal 2025年第10期12卷 14016-14035页

作者： Pramitarini, Yushintia Perdana, Ridho Hendra Yoga Shim, Kyusung An, Beongku Hongik University Graduate School Department of Software and Communications Engineering Sejong30016 Korea Republic of Hankyong National University School of Computer Engineering and Applied Mathematics Korea Republic of Hongik University Department of Software and Communications Engineering Sejong30016 Korea Republic of

In this paper, we propose a novel federated blockchain (FedChain)-based clustering protocol to enhance network security and connectivity in flying ad hoc networks (FANETs) with cell-free massive MIMO (CF-mMIMO). By leveraging blockchain technology and federated learning (FL), the cluster can be protected against Sybil attacks, enabling secure cluster formation without increasing the number of control packets. We formulate the cost function maximization problem based on cross-layer design, which integrates physical layer information (mobility, position, channel capacity, and remaining energy) and network layer parameters (connectivity) to optimize the formation of stable clusters with minimal control overhead. Furthermore, we select the optimal cluster heads (CHs) based on the highest remaining energy and velocity-constrained criteria, ensuring long-term stability. To solve the security issue, blockchain technology is adopted to validate transactions among nodes and ensure secure formation by distinguishing legitimate users and Sybil attack nodes. Additionally, we develop a novel FL framework to predict and distinguish node status in real time without additional control packets, improving security and control overhead performance during cluster formation. Simulation results demonstrate that the proposed FedChain-based clustering protocol outperforms the lowest ID (LI), high connectivity degree (HCD), and conventional blockchain-based clustering (CBC) protocols in terms of connectivity, control overhead, and security performance. The results highlight that the FedChain-based clustering protocol provides robust security and connectivity, making it well-suited for dynamic FANET environments. © 2014 IEEE.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

Learned, uncertainty-driven adaptive acquisition for photon-efficient scanning microscopy

引用

Optics Express 2025年第6期33卷 12269-12287页

作者： Ye, Cassandra Tong Han, Jiashu Liu, Kunzan Angelopoulos, Anastasios Griffith, Linda Monakhova, Kristina You, Sixian The Department of Electrical Engineering and Computer Science CambridgeMA02139 United States Fu Foundation School of Engineering and Applied Science Columbia University in The City of New York New YorkNY10027 United States University of California Berkeley Department of Electrical Engineering and Computer Science BerkeleyCA94720 United States Department of Biological Engineering Massachusetts Institute of Technology CambridgeMA02139 United States

Scanning microscopy systems, such as confocal and multiphoton microscopy, are powerful imaging tools for probing deep into biological tissue. However, scanning systems have an inherent trade-off between acquisition time, field of view, phototoxicity, and image quality. This often results in noisy measurements when fast, large field of view, and/or gentle imaging is needed. Deep learning could be used to denoise noisy microscopy measurements, but these algorithms can be prone to hallucination, which can be disastrous for medical and scientific applications. We propose a method to simultaneously denoise and predict pixel-wise uncertainty for scanning microscopy systems, improving algorithm trustworthiness and providing statistical guarantees for deep learning predictions. Furthermore, we propose to leverage this learned, pixel-wise uncertainty to drive an adaptive acquisition technique that rescans only the most uncertain regions of a sample, saving time and reducing the total light dose to the sample. We demonstrate our method on experimental confocal and multiphoton microscopy systems, showing that our uncertainty maps can pinpoint hallucinations in the deep learned predictions. Finally, with our adaptive acquisition technique, we demonstrate up to 16× reduction in acquisition time and total light dose while successfully recovering fine features in the sample and reducing hallucinations. We are the first to demonstrate distribution-free uncertainty quantification for a denoising task with real experimental data and the first to propose adaptive acquisition based on reconstruction uncertainty. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

Quantum X-Secure E-Eavesdropped T-Colluding Symmetric Private Information Retrieval

引用

IEEE Transactions on Information Theory 2025年第5期71卷 3974-3988页

作者： Aytekin, Alptug Nomeir, Mohamed Vithana, Sajani Ulukus, Sennur University of Maryland Department of Electrical and Computer Engineering College ParkMD20742 United States Harvard University John A. Paulson School of Engineering and Applied Sciences BostonMA02134 United States

We consider both classical and quantum variations of X-secure, E-eavesdropped and T-colluding symmetric private information retrieval (SPIR). This is the first work to study SPIR with X-security in classical or quantum variations. We first develop a scheme for classical X-secure, E-eavesdropped and T-colluding SPIR (XSETSPIR) based on a modified version of cross subspace alignment (CSA), which achieves a rate of (Formula Presented). The modified scheme achieves the same rate as the scheme used for X-secure PIR with the extra benefit of symmetric privacy, i.e., user-privacy as well as database-privacy. Next, we extend this scheme to its quantum counterpart based on the N-sum box abstraction. This is the first work to consider the presence of eavesdroppers in quantum private information retrieval (QPIR). In the quantum variation, the eavesdroppers have better access to information over the quantum channel compared to the classical channel due to the over-the-air decodability. To that end, we develop two different schemes for quantum X-secure, E-eavesdropped and T-colluding SPIR (QXSETSPIR) with secure over-the-air decoding. The first scheme achieves the highest possible super-dense coding gain, i.e., (Formula Presented), which requires additional uploads from the user. The second scheme on the other hand requires no extra uploads. However, it does not achieve the super-dense coding gain in some cases based on the relation between the number of eavesdropped links and the number of interference terms. The second scheme is based on the idea that there exist some special entanglement states that can be used to hide the contents of the user-required messages from the eavesdroppers using the interference symbols. © 1963-2012 IEEE.

关键词： Quantum channel

来源：评论

学校读者我要写书评

暂无评论

End-To-End Encryption Enabled Lightweight Mutual Authentication Scheme for Resource Constrained IoT Network

引用

computers, Materials & Continua 2025年第2期82卷 3223-3249页

作者： Shafi Ullah Haidawati Muhammad Nasir Kushsairy Kadir Akbar Khan Ahsanullah Memon Shanila Azhar Ilyas Khan Muhammad Ashraf Department of Computer Engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Computer Engineering Section Malaysian Institute of Technology Universiti Kuala LumpurKuala Lumpur50250Malaysia Electrical Engineering Section Universiti Kuala LumpurBritish Malaysian InstituteSalengor53100Malaysia Electrical Engineering Department Mehran UniversityKhairpur-Mirs76062Pakistan Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication networks consist of resource-constrained autonomous devices, also known as autonomous Internet of things (IoTs) or machine-type communication devices (MTCDs) which act as a backbone for Industrial IoT, smart cities, and other autonomous systems. Due to the limited computing and memory capacity, these devices cannot maintain strong security if conventional security methods are applied such as heavy encryption. This article proposed a novel lightweight mutual authentication scheme including elliptic curve cryptography (ECC) driven end-to-end encryption through curve25519 such as (i): efficient end-to-end encrypted communication with pre-calculation strategy using curve25519;and (ii): elliptic curve Diffie-Hellman (ECDH) based mutual authentication technique through a novel lightweight hash function. The proposed scheme attempts to efficiently counter all known perception layer security threats. Moreover, the pre-calculated key generation strategy resulted in cost-effective encryption with 192-bit curve security. It showed comparative efficiency in key strength, and curve strength compared with similar authentication schemes in terms of computational and memory cost, communication performance and encryption robustness.

关键词： Mutual authentication lightweight end-to-end encryption elliptic curve cryptography industrial internet of things curve25519 machine-to-machine communication

来源：评论

学校读者我要写书评

暂无评论

SEPARABLE PHYSICS-INFORMED NEURAL NETWORKS FOR SOLVING THE BGK MODEL OF THE BOLTZMANN EQUATION

引用

SIAM Journal on Scientific Computing 2025年第2期47卷 C451-C474页

作者： Oh, Jaemin Cho, Seung Yeon Yun, Seok-Bae Park, Eunbyung Hong, Youngjoon Department of Electrical and Computer Engineering Texas A&M University United States Department of Mathematics Gyeongsang National University Jinju Korea Republic of Department of Mathematics Sungkyunkwan University Suwon Korea Republic of Department of Artificial Intelligence Yonsei University Korea Republic of Department of Mathematical Sciences Research Institute of Mathematics Seoul National University Korea Republic of

In this study, we present a new approach based on separable physics-informed neural networks (SPINNs), specifically designed to efficiently solve the Bhatnagar-Gross-Krook (BGK) model. While the mesh-free nature of physics-informed neural networks (PINNs) offers significant advantages for handling high-dimensional partial differential equations, applying quadrature rules for accurate integral evaluation in the BGK operator can compromise these benefits and increase computational costs. To address this issue, we leverage the canonical polyadic decomposition structure of SPINNs and the linear nature of moment calculation to significantly reduce the computational expense associated with quadrature rules. However, the multiscale nature of the particle density function poses challenges for precisely approximating macroscopic moments using neural networks. To overcome this, we introduce SPINN-BGK, a specialized variant of SPINNs that fuses SPINNs with Gaussian functions and utilizes a relative loss approach. This modification enables SPINNs to decay as rapidly as Maxwellian distributions, enhancing the accuracy of macroscopic moment approximations. The relative loss design ensures that both large- and small-scale features are effectively captured by the SPINNs. The effectiveness of our approach is validated through six numerical experiments, including a complex three-dimensional Riemann problem. These experiments demonstrate the potential of our method to efficiently and accurately tackle intricate challenges in computational physics, offering significant improvements in computational efficiency and solution accuracy. © 2025 Society for Industrial and applied mathematics.

关键词： Boltzmann equation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：