检索结果-内蒙古大学图书馆

Optimization of Binary Randomized Response Based on Lanke Privacy and Utility Analysis

Chinese Journal of Electronics 2025年第1期34卷 242-256页

作者： Yihui Zhou Wenli Wang Jun Yan Zhenqiang Wu Laifeng Lu School of Computer Science Shaanxi Normal University School of Mathematics and Statistics Shaanxi Normal University School of Mathematics and Computer Applications Shangluo College

Currently, it has become a consensus to enhance privacy protection. Randomized response(RR) technique, as the mainstream perturbation mechanism for local differential privacy, has been widely studied. However,most of the research in literature managed to modify existing RR schemes and propose new mechanisms with better privacy protection and utility, which are illustrated only by numerical experiments. We study the properties of generalized binary randomized response mechanisms from the perspectives of Lanke privacy and utility. The mathematical expressions of privacy and utility for the binary RR mechanism are given respectively. Moreover, the comparison principle for privacy and utility of any two mechanisms is proved. Finally, the optimization problem of the binary RR mechanism is discussed. Our work is based on a rigorous mathematical proof of privacy and utility for the general binary RR mechanism, and numerical verification illustrates the correctness of the conclusions. It can provide theoretical support for the design of binary RR mechanism and can be applied in data collection, analysis and publishing.

关键词： Privacy Differential privacy Publishing Perturbation methods Data collection Protection Optimization

来源：评论

学校读者我要写书评

暂无评论

Enhancing Entity Relationship Extraction in Dialogue Texts Using Hypergraph and Heterogeneous Graph

引用

Chinese Journal of Electronics 2025年第1期34卷 295-308页

作者： Shunmiao Zhang Siyuan Zheng Degen Huang Dan Li School of Computer Science and Mathematics Fujian University of Technology Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology School of Computer Science and Technology Dalian University of Technology Elsevier

Dialogue-based relation extraction(DialogRE) aims to predict relationships between two entities in dialogue. Current approaches to dialogue relationship extraction grapple with long-distance entity relationships in dialogue data as well as complex entity relationships, such as a single entity with multiple types of connections. To address these issues, this paper presents a novel approach for dialogue relationship extraction termed the hypergraphs and heterogeneous graphs model(HG2G). This model introduces a two-tiered structure, comprising dialogue hypergraphs and dialogue heterogeneous graphs, to address the shortcomings of existing methods. The dialogue hypergraph establishes connections between similar nodes using hyper-edges and utilizes hypergraph convolution to capture multi-level features. Simultaneously, the dialogue heterogeneous graph connects nodes and edges of different types, employing heterogeneous graph convolution to aggregate cross-sentence information. Ultimately, the integrated nodes from both graphs capture the semantic nuances inherent in dialogue. Experimental results on the DialogRE dataset demonstrate that the HG2G model outperforms existing state-of-the-art methods.

关键词： Convolution Aggregates Semantics Feature extraction Data mining

来源：评论

学校读者我要写书评

暂无评论

Acyclic coloring of two operations of graphs 8

Acyclic coloring of two operations of graphs

引用

2024 8th International Conference on Mechanics, mathematics and Applied Physics, ICMMAP 2024

作者： Jin, Xinze Tian, Shuangliang School of Mathematics and Computer Science Northwest for Minzu University Lanzhou730030 China Key Laboratory of Streaming Data Computing Technologies and Applications Northwest for Minzu University Lanzhou730030 China

The coloring theory of graphs is a very important direction in graph theory. The graph coloring problem has a strong application background. Many practical problems such as timetabling problems, frequency allocation problems, traffic arrangements, circuit design, and storage problems can be transformed into graph coloring problems. A substantial amount of scholarly work has been dedicated to the exploration of acyclic coloring, resulting in a plethora of significant findings that significantly contribute to the theoretical framework of vertex coloring in graphs. An acyclic coloring of a graph G refers to a proper vertex coloring where the subgraph resulting from any pair of color classes does not encompass any cycles. We analyze acyclic coloring in splitting graphs and Cartesian products of paths and cycles by using the method of structural coloring, reductive proof, and mathematical induction. Moreover, we present the precise acyclic chromatic numbers for splitting graphs of cycles and Cartesian products of paths and cycles. © Published under licence by IOP Publishing Ltd.

关键词： Integrated circuit design

来源：评论

学校读者我要写书评

暂无评论

Injective coloring of edge corona product of graphs 8

Injective coloring of edge corona product of graphs

引用

2024 8th International Conference on Mechanics, mathematics and Applied Physics, ICMMAP 2024

作者： Zhao, Wenying Tian, Shuangliang School of Mathematics and Computer Science Northwest for Minzu University Lanzhou730030 China Key Laboratory of Streaming Data Computing Technologies and Applications Northwest for Minzu University Lanzhou730030 China

The injective chromatic number χi(G) of a graph G is the minimum number of colors needed to color the vertices of G such that different vertices with the same neighbor are colored differently. In this here, we get some exact values of the injective chromatic number of the edge corona product of some graphs. © Published under licence by IOP Publishing Ltd.

关键词： Graph theory

来源：评论

学校读者我要写书评

暂无评论

ForBac: A Static Analysis Approach with Forward and Backward Analysis for Precision in Floating-Point Computations

引用

IEEE Access 2025年 13卷 80705-80722页

作者： Thushara, M.G. Somasundaram, K. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science & Applications Amritapuri India Amrita Vishwa Vidyapeetham Amrita School of Physical Sciences Department of Mathematics Coimbatore India

Accuracy in floating-point computations is critical for reliable software, especially in systems where precision impacts safety and performance. Inaccuracies from rounding errors and precision loss can lead to significant issues in applications like scientific computing and engineering simulations. To address these challenges, we introduce ForBac, a static analysis model designed to enhance floating-point precision by combining forward and backward analysis techniques. This dual approach improves the accuracy of floating-point computations compared to traditional methods. We evaluated ForBac on standard benchmarks, including Newton-Raphson and Jacobi Iteration methods, demonstrating its ability to maintain accuracy across complex computations. Results show that ForBac not only improves precision but also offers a scalable solution for analyzing floating-point operations in varied computational contexts. © 2013 IEEE.

关键词： Precision engineering

来源：评论

学校读者我要写书评

暂无评论

Wavelet-Enhanced Deep Learning Ensemble for Accurate Stock Market Forecasting: A case study of Nifty 50 Index

引用

IEEE Access 2025年 13卷 87036-87047页

作者： Singh, Priya Jha, Manoj Patel, Harshita Maulana Azad National Institute of Technology Department of Mathematics Bioinformatics & Computer Applications Bhopal 462003 India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India

Portfolio theory underpins portfolio management, a much-researched yet uncharted field. Stock market prediction is a challenging and essential endeavour in financial research, owing to the nonlinear, volatile, and stochastic characteristics of financial time series data. Conventional statistical techniques often fall short to encapsulate complex interdependencies, resulting in diminished predictive accuracy. This research proposes an ensemble model that integrates Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and Temporal Convolutional Networks (TCN) for effective stock market prediction. The Nifty 50 index dataset is utilized for the empirical evidences. Wavelet-based denoising is utilised as a preprocessing measure to mitigate the intrinsic noise in stock market data. The model’s efficacy is assessed utilising error metrics, such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared (R²). The five-fold cross-validation is utilized to establish the robustness of the models. Furthermore, we ascertain the statistical significance of performance enhancements by parametric t-tests, including normality assessments via the Shapiro-Wilk test. Moreover, current state-of-the-art models advocates in favour of proposed study. © 2013 IEEE.

关键词： CNN Ensemble learning LSTM Random Forest Statistical Analysis Stock Market TCN

来源：评论

学校读者我要写书评

暂无评论

Graph-Based Generation and Validation of Use Case Diagrams

引用

Procedia computer Science 2025年 259卷 1356-1365页

作者： Reshma P Nair M G Thushara K Somasundaram Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Amrita School of Computing Amritapuri Kerala India Department of Computer Science and Applications Amrita Vishwa Vidyapeetham Amrita School of Computing Amritapuri Kerala India Department of Mathematics Amrita School of Physical Sciences Amrita Vishwa Vidyapeetham Coimbatore India

As we know in today’s modern software engineering, use case diagrams for representing the functionalities of the system act significantly in mediating the gap between the stakeholder and the developer. Some of the earlier techniques used in constructing such diagrams can be problematic when these diagrams are to be employed in large systems where there are many actors and activities. That is why every limitation outlined above might be resolved further with the help of NLP and developments in graphs theory. The proposed method makes improvements by reducing the human interference; it can handle increase in system size and the number of actors and their interactions; it also provides highly accurate shortest-path identification through use of validation methods. In addition, shortest-path algorithms are incorporated to improve the validation exercise, thereby minimizing errors common in presenting the system functionalities. Hence, the results indicate that the proposed method is more effective not only for generating use case diagrams with increased precision and scalability but also for constructing the necessary framework for checking system interactions’ correctness. This work provides a foundation for future studies aimed at enhancing the automation of the use case diagram especially for complex systems.

关键词： NLP Graph Theory Use case Diagrams Automatic Generation Shortest-Path Algorithms

来源：评论

学校读者我要写书评

暂无评论

SkyRover: A Modular Simulator for Cross-Domain Pathfinding

arXiv

引用

arXiv 2025年

作者： Ma, Wenhui Li, Wenhao Jin, Bo Lu, Changhong Wang, Xiangfeng School of Computer Science and Technology East China Normal University China School of Computer Science and Technology Tongji University China School of Mathematical Sciences East China Normal University China Key Laboratory of Mathematics and Engineering Applications MoE China

Unmanned Aerial Vehicles (UAVs) and Automated Guided Vehicles (AGVs) increasingly collaborate in logistics, surveillance, inspection tasks and etc. However, existing simulators often focus on a single domain, limiting cross-domain study. This paper presents the SkyRover, a modular simulator for UAV-AGV multi-agent pathfinding (MAPF). SkyRover supports realistic agent dynamics, configurable 3D environments, and convenient APIs for external solvers and learning methods. By unifying ground and aerial operations, it facilitates cross-domain algorithm design, testing, and benchmarking. Experiments highlight SkyRover’s capacity for efficient pathfinding and high-fidelity simulations in UAV-AGV coordination. Project is available at https://***/view/mapf3d/home. © 2025, CC BY.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

nPGSAO: A Hybrid Particle Swarm Optimization and Genetic Algorithm with Niching Technology for Edge Server Placement

引用

IEEE Internet of Things Journal 2025年

作者： Wang, Bo Zhang, Zhifeng Song, Ying Chen, Ming Liu, Dongqing Software Engineering College Zhengzhou University of Light Industry Zhengzhou China Computer School Beijing Information Science and Technology University Beijing China School of Mathematics and Computer Science Tongling University Tongling China National Engineering Laboratory for Internet Medical Systems and Applications the First Affiliated Hospital of Zhengzhou University Zhengzhou China

In this paper, we focus on the edge server placement problem (ESPP). ESPP is to decide positions (edge stations) where purchased edge servers (ESs) are placed when a service provider builds or upgrades its edge computing solution. The decision of ESPP largely determines the overall service quality and resource efficiency. We aim at providing ESPP solutions for optimizing the service quality in terms of the system response time, given a set of purchased ESs. To achieve this aim, we first deduce the optimal request dispatch for each edge station based on queue theory and Binomial theorem. Then, based on the deduced result, we formulate ESPP into a discrete nonlinear constrained optimization model. Because ESPP is NP-hard and generally multi-modality, we designed a hybrid metaheuristic algorithm to combine advantages of particle swarm optimization (PSO) and genetic algorithm (GA) as well as the niching technology, which is named nPGSAO. The basic idea of nPGSAO is grouping similar individuals into a niche and finding the niche best. Then, nPGSAO evolves each individual by integrating the swarm intelligence of PSO into the evolutionary process of GA based on its personal and niching best. To evaluate the performance of nPGSAO, we conducted extensive simulated experiments. The results show that nPGSAO achieves 5.78%–40.4% better response time with varied ESPP scale, compared to 11 up-to-date algorithms, and has a linear time complexity with the ESPP scale. These confirm the superior performance and scalability of nPGSAO. © 2014 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Personalized Deep Brain Stimulation Parameter Optimization using Deep Learning with Dimensionality Reduction and Data Augmentation 1

Personalized Deep Brain Stimulation Parameter Optimization u...

引用

1st International Conference on Intelligent Systems and Computational Networks, ICISCN 2025

作者： Parimala, S. Iram, Faiza Kishore, Gudipudi Sivaraman, R. Srimathi, S. Jegajothi, B. Srm Institute of Science and Technology Department of Computer Science and Applications Vadapalani India Sr University School of Cs&ai Hasanparthy India University College of Arts and Science Krishna University Department of Biosciences and Biotechnology Machilipatnam India Dwaraka Doss Goverdhan Doss Vaishnav College Department of Mathematics Arumbakkam Chennai India Saveetha School of Engineering Simats Department of Bio Technology Chennai India Srs Tech Solutions Chennai India

ISBN: (纸本)9798331529246

Deep Brain Stimulation (DBS) is a recognized treatment for managing motor symptoms associated with various movement disorders. However, traditional DBS settings often rely on fixed parameters that do not address individual patient needs, leading to suboptimal outcomes and increased clinical visits. This research introduces a novel hybrid approach that employs Convolutional Neural Networks (CNN) combined with Reinforcement Learning (RL) to dynamically optimize DBS parameters using real-time patient feedback. The proposed model significantly enhances symptom management, achieving an 85% improvement compared to the 65% improvement seen with conventional DBS settings. Additionally, the time to reach optimal stimulation settings was reduced from twelve hours to five, and annual clinical visits decreased from five to two. These findings underscore the potential of integrating machine learning techniques into DBS therapy, paving the way for more personalized and effective treatment strategies for movement disorders, ultimately revolutionizing patient-centered care in this field. © 2025 IEEE.

关键词： Deep reinforcement learning

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：