检索结果-内蒙古大学图书馆

Efficient Bit-Plane Based Medical Image Cryptosystem Using Novel and Robust Sine-Cosine Chaotic Map

Computers, Materials & Continua 2025年第4期83卷 917-933页

作者： Zeric Tabekoueng Njitacke Louai A.Maghrabi Musheer Ahmad Turki Althaqafi Department of Electrical and Electronic Engineering College of Technology(COT)University of BueaBueaP.O.Box 63Cameroon Department of Software Engineering College of EngineeringUniversity of Business and TechnologyJeddah22246Saudi Arabia Department of Computer Engineering Jamia Millia IslamiaNew Delhi110025India Department of Computer Science School of EngineeringComputing and DesignDar Al-Hekma UniversityJeddah22246Saudi Arabia

This paper presents a high-security medical image encryption method that leverages a novel and robust sine-cosine *** map demonstrates remarkable chaotic dynamics over a wide range of *** employ nonlinear analytical tools to thoroughly investigate the dynamics of the chaotic map,which allows us to select optimal parameter configurations for the encryption *** findings indicate that the proposed sine-cosine map is capable of generating a rich variety of chaotic attractors,an essential characteristic for effective *** encryption technique is based on bit-plane decomposition,wherein a plain image is divided into distinct bit *** planes are organized into two matrices:one containing the most significant bit planes and the other housing the least significant *** subsequent phases of chaotic confusion and diffusion utilize these matrices to enhance *** auxiliary matrix is then generated,comprising the combined bit planes that yield the final encrypted *** results demonstrate that our proposed technique achieves a commendable level of security for safeguarding sensitive patient information in medical *** a result,image quality is evaluated using the Structural Similarity Index(SSIM),yielding values close to zero for encrypted images and approaching one for decrypted ***,the entropy values of the encrypted images are near 8,with a Number of Pixel Change Rate(NPCR)and Unified Average Change Intensity(UACI)exceeding 99.50%and 33%,***,quantitative assessments of occlusion attacks,along with comparisons to leading algorithms,validate the integrity and efficacy of our medical image encryption approach.

关键词： Image cryptosystem robust chaos sine-cosine map nonlinear analysis tools medical images

来源：评论

学校读者我要写书评

暂无评论

SMP-NoC: A Flexible and Efficient Shared Memory Protection Unit on Network-on-Chip 24th

SMP-NoC: A Flexible and Efficient Shared Memory Protection ...

引用

24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Wu, Teng He, Ying Wei, Shengjun Hu, Changzhen School of Cyberspace Science and Technology Beijing Institute of Technology Beijing China Beijing Key Laboratory of Software Security Engineering Technology Beijing Institute of Technology Beijing China

ISBN: (纸本)9789819615445

Network-on-Chip (NoC) is crucial for modern multicore systems, offering high throughput and low latency. However, its shared memory faces threats like illegal access and DDoS attacks. To enhance security, Memory Protection Units (MPUs) with permission tables are used to control access. NoC-MPU architecture uses TLBs and permission tables for request checks and domain isolation via CIDs, but this can cause high latency. To address this, DPU and NSM are combined for dynamic permission updates, though the tables remain static. Our paper introduces a novel Flexible and Efficient Real-Time Memory Protection Unit for NoC, featuring a hardware sandbox and taint-track monitor for pre-testing access requests. It supports dynamic memory region adjustments based on four permissions (RX, RWX, RW, R) and includes an access controller to counter DoS and side channel attacks. The design significantly boosts NoC security with minimal overheads: just 6.2% in throughput, 7.8% in area, and 4.8% in power, outperforming current solutions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： hardware-level sandbox Network-on-Chip(NoC) shared Memory taint-track monitor

来源：评论

学校读者我要写书评

暂无评论

Runtime Verification of Neural-Symbolic Systems 10th

Runtime Verification of Neural-Symbolic Systems

引用

10th International Symposium on Dependable software engineering: Theories, Tools and Applications, SETTA 2024

作者： Deng, Shaojun Liu, Wanwei Zhang, Miaomiao College of Computer Science and Technology National University of Defense Technology Changsha China School of Software Engineering Tongji Uniersity Shanghai China

ISBN: (纸本)9789819606016

Neural-symbolic systems (NSSs), which are typically cyber-physical systems integrated with artificial intelligence modules, have received much attention in both academic and industrial fields. However, thorough verification (such as model checking) of such systems in general leads to prohibitively high costs due to the scale of the state space, and this makes it barely accomplishable within desired time-span. Consequently, light-weight verification techniques are introduced to deal with such cases, e.g., runtime verification (RV, for short). In this paper, we investigate an RV framework for NSSs against signal temporal logic (STL) properties. To guarantee that the on-line monitoring could be accomplished in time, we utilize Euler-prediction to sample the system under scrutiny at discrete time-steps. Our framework supports both qualitative and quantitative on-line monitoring of STL specifications, and thus it terminates whenever a property is satisfied and/or violated by a finite prefix of the trajectory, and it can also provide the bounds of the quantitative satisfaction/violation w.r.t. the remaining execution. Notably, for the so-called piece-wise linear NSSs against affine STL formulas, our approach is exact. On top of it, a prototype tool is implemented, and is experimentally evaluated. The results demonstrate the feasibility of the presented runtime verification approach. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Model checking

来源：评论

学校读者我要写书评

暂无评论

AROhI: An Interactive Toolkit for Estimating ROI of Data Analytics 15

AROhI: An Interactive Toolkit for Estimating ROI of Data Ana...

引用

15th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2025

作者： Zambare, Noopur Idoko, Jacob Acharya, Jagrit Ginde, Gouri Indian Institute of Technology Dept. of Mechanical Engineering Jodhpur India University of Calgary Dept. of Electrical and Software Engineering Canada

ISBN: (纸本)9798331507695

The cost of adopting new technology is rarely analyzed and discussed;however, it is vital for any technological investment because of the cost and effort associated with it. Thus, it is crucial to consider Return On Investment (ROI) when performing data analytics. Decisions on 'How much analytics is needed?' are hard to answer. ROI could guide decision support on the What?, How?, and How Much? Analytics for a given problem. This work details a comprehensive tool that provides conventional and advanced ML approaches for demonstration using software requirements dependency extraction and their ROI analysis as a use case. Utilizing advanced ML techniques such as Active Learning, Transfer Learning and primitive Large language model: BERT (Bidirectional Encoder Representations from Transformers) as its various components for automating dependency extraction, the tool outcomes demonstrate a mechanism to compute the ROI of ML algorithms to present trade-offs between the cost and benefits of a technology investment. © 2025 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Joint classification of hyperspectral and lidar using multi-scale spatial adaptive calibration 6

Joint classification of hyperspectral and lidar using multi-...

引用

6th International Conference on Geoscience and Remote Sensing Mapping, GRSM 2024

作者： Yang, Zhichao Hao, Siyuan Qingdao University of Technology College of information and control engineering Qingdao China Beijing Jiaotong University College of software engineering Beijing China

ISBN: (纸本)9781510688018

In the field of land cover classification, the multimodal fusion of hyperspectral imagery (HSI) and light detection and ranging (LiDAR) data has become a key research direction in remote sensing. Hyperspectral imagery provides rich spectral information, enabling the identification of subtle material differences, while LiDAR data offers high-precision spatial geometric structures. However, the complementarity between these two data modalities faces challenges related to spatial resolution discrepancies and feature inconsistency. To address these challenges, this paper proposes a Multiscale Spatial Adaptive Calibration Network (MSACNet) for joint classification of hyperspectral and LiDAR data. The network extracts multiscale convolutional features and introduces a Spatial Adaptive Calibration Module (SACM) at each scale to adaptively calibrate the fused multimodal features, adjusting for discrepancies between spectral and spatial geometric feature distributions. Experimental results on the Houston2013 dataset demonstrate that the proposed method achieves superior classification performance compared to existing classification models. © 2025 SPIE.

关键词： Image resolution

来源：评论

学校读者我要写书评

暂无评论

LLMaaS: Serving Large-Language Models on Trusted Serverless Computing Platforms

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2025年第2期6卷 405-415页

作者： Cai, Zinuo Ma, Rongbo Fu, Yicheng Zhang, Weishan Ma, Ruhui Guan, Haibing Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China Qingdao Institute of Software College of Computer Science and Technology Qingdao266555 China

In recent years, the emergence of large-language models (LLMs) has profoundly transformed our production and lifestyle. These models have shown tremendous potential in fields, such as natural language processing, speech recognition, and recommendation systems, and are increasingly playing crucial roles in applications such as human-computer interaction and intelligent customer service. Efficient inference solutions for LLMs in data centers have been extensively researched, with a focus on meeting users' quality of service requirements. In this article, we focus on two additional requirements that responsible LLM inference should meet under QoS conditions: security throughout the model execution process and low maintenance requirements for the inference system. Therefore, we propose LLMaaS, a trusted model inference platform based on a serverless computing platform aimed at providing inference as a service for LLMs. First, we design a trusted serverless computing platform based on software guard extension (SGX), which includes distributed identity verification and SGX device plugins to ensure the security and trustworthiness of the inference process. Additionally, to reduce the maintenance requirements of the system, we enhance the SGX-based deep learning computing framework, including replacing PyTorch and using a greedy algorithm for graph partitioning. We conduct tests on four typical large models, and the experimental results demonstrate that, with minimal overhead and user code modifications, we can ensure the security of model execution. © 2020 IEEE.

关键词： Quality of service

来源：评论

学校读者我要写书评

暂无评论

DIEONet:Domain-Invariant Information Extraction and Optimization Network for Visual Place Recognition

引用

Computers, Materials & Continua 2025年第3期82卷 5019-5033页

作者： Shaoqi Hou Zebang Qin Chenyu Wu Guangqiang Yin Xinzhong Wang Zhiguo Wang School of Computer Science and Technology Xinjiang UniversityUrumqi830046China School of Information and Software Engineering University of Electronic Science and Technology ofChinaChengdu611731China Institute of Public Security Kash Institute of Electronics and Information IndustryKashi844000China

Visual Place Recognition(VPR)technology aims to use visual information to judge the location of agents,which plays an irreplaceable role in tasks such as loop closure detection and *** is well known that previous VPR algorithms emphasize the extraction and integration of general image features,while ignoring the mining of salient features that play a key role in the discrimination of VPR *** this end,this paper proposes a Domain-invariant Information Extraction and Optimization Network(DIEONet)for *** core of the algorithm is a newly designed Domain-invariant Information Mining Module(DIMM)and a Multi-sample Joint Triplet Loss(MJT Loss).Specifically,DIMM incorporates the interdependence between different spatial regions of the feature map in the cascaded convolutional unit group,which enhances the model’s attention to the domain-invariant static object *** Loss introduces the“joint processing of multiple samples”mechanism into the original triplet loss,and adds a new distance constraint term for“positive and negative”samples,so that the model can avoid falling into local optimum during *** demonstrate the effectiveness of our algorithm by conducting extensive experiments on several authoritative *** particular,the proposed method achieves the best performance on the TokyoTM dataset with a Recall@1 metric of 92.89%.

关键词： Visual place recognition domain-invariant information mining module multi-sample joint triplet loss

来源：评论

学校读者我要写书评

暂无评论

Intersection of machine learning and mobile crowdsourcing: a systematic topic-driven review

引用

Personal and Ubiquitous Computing 2025年第1期29卷 77-101页

作者： Chen, Weisi Hussain, Walayat Al-Qudah, Islam Al-Naymat, Ghazi Zhang, Xu School of Software Engineering Xiamen University of Technology Fujian Xiamen361024 China Peter Faber Business School Australian Catholic University North SydneyNSW2060 Australia Higher Colleges of Technology Abu Dhabi United Arab Emirates College of Engineering and Information Technology Ajman University Ajman United Arab Emirates

During the past decade of the big data era, mobile crowdsourcing has emerged as a popular research area, leveraging the collective intelligence and engagement of a vast number of individuals using their mobile devices. Another actively evolving area is machine learning, which has recently been augmented by the mobile crowdsourcing approach, especially for data collection and labeling. However, what happens when these two prevailing concepts meet? What topics have been discussed in recent literature? This paper adopts a systematic methodology, leveraging Latent Dirichlet allocation topic modeling for topic discovery from recent publications, to provide a comprehensive and insightful review of the intersection of machine learning and mobile crowdsourcing. Moreover, the paper highlights the emerging federated learning technology that integrates elements from both concepts. Key research questions are answered by examining discovered topics. The paper thoroughly discusses state-of-the-art developments and trends in combining these two concepts and explains the role of one concept in the other. The paper also addresses remaining challenges and outlines a future research agenda, including the potential incorporation of large language models into mobile crowdsourcing systems. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Data Analytics

来源：评论

学校读者我要写书评

暂无评论

Characterizing the app recommendation relationships in the iOS app store: a complex network's perspective

引用

Science China(Information Sciences) 2025年第4期68卷 284-299页

作者： Gang HUANG Fuqi LIN Yun MA Haoyu WANG Qingxiang WANG Gareth TYSON Xuanzhe LIU Key Lab of High Confidence Software Technologies (Peking University) Ministry of Education School of Computer Science Peking University Institute for Artificial Intelligence Peking University School of Cyber Science and Engineering Huazhong University of Science and Technology Alibaba Group Hong Kong University of Science and Technology (Guangzhou)

Mobile apps have become widely adopted in our daily lives. To facilitate app discovery, most app markets provide recommendations for users, which may significantly impact how apps are accessed. However, little has been known about the underlying relationships and how they reflect(or affect) user behaviors. To fill this gap, we characterize the app recommendation relationships in the i OS app store from the perspective of the complex network. We collect a dataset containing over 1.3 million apps and 50 million app recommendations. This dataset enables us to construct a complex network that captures app recommendation relationships. Through this, we explore the recommendation relationships between mobile apps and how these relationships reflect or affect user behavior patterns. The insights gained from our research can be valuable for understanding typical user behaviors and identifying potential policy-violating apps.

关键词： mobile app recommendation complex network user behavior policy-violating app

来源：评论

学校读者我要写书评

暂无评论

From Agile Development Challenges to Agile Digital Readiness Framework in Digital Healthcare: A Review-Driven Approach 3rd

From Agile Development Challenges to Agile Digital Readiness...

引用

3rd International Conference on Advances in Computing Research, ACR 2025

作者： Odeh, Yousra Software Engineering Department Faculty of Science and Information Technology Al-Zaytoonah University of Jordan Amman11733 Jordan

ISBN: (纸本)9783031876462

Following the emergence of the COVID-19 pandemic, the entire healthcare community moved to adopt rapid digital healthcare solutions to avoid and reduce the adverse effects of pandemics. Although launching any digital healthcare solution or tool contributes to resolving or reducing the impact of the dilemma, still the agile development challenges behind this are not well structured or categorized yet. The current agile development of digital healthcare solutions is surrounded by difficulties that must be well-identified and synthesized to overcome and to specify and develop more robust solutions that are digitally ready for transformation. This research proposes a review-driven and expert-validated comprehensive classification for challenges that emerge under the agile development of digital healthcare applications, as the first deliverable in this research. The review covers the years 2020–2024. The classification contributes to deriving another deliverable in this research, that is a digital readiness framework for the agile development of digital healthcare solutions. The digital readiness framework contributes to act as a foundation for sustainable digital transformation and improving healthcare outcomes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Project management

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：