检索结果-内蒙古大学图书馆

9th International Conference on Integrated Circuits and Microsystems, ICICM 2024

作者： Wang, Pengju Zhang, Yuejun Wei, Hongshuai Zhang, Huihong Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China

ISBN: (纸本)9798331509453

The SM4 algorithm is now widely used to ensure the security of data transmission, but its physical implementation is still vulnerable to side channel attack. By studying the structure of SM4 algorithm, this paper proposes a scheme of SM4 algorithm against side-channel attack based on RRAM/CMOS hybrid power balancing. The scheme first studies the dynamic power balancing mechanism under the cooperative operation mode of RRAM cell and CMOS, and designs the complementary output RRAM/CMOS hybrid power balancing cell circuit by utilizing the RRAM programmable resistor states and the efficient control of CMOS logic gates;then, the leakage analysis reveals that there is a vulnerability of SM4 algorithm hardware implementation in the wheel output. To address this issue, the power balancing cell circuit is applied to the wheel output position of SM4 algorithm to decouple the correlation between power consumption and data in the output stage;finally, the power consumption curve is extracted by Spectre simulation under TSMC 65nm process and verified against correlation power analysis (CPA) attack. The experimental results demonstrate that, compared with the traditional implementation, the circuit proposed in this paper can still defend against CPA attack with 1200 power consumption curves, with more than two times higher hardware security than the traditional SM4 implementation. © 2024 IEEE.

关键词： CMOS integrated circuits

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Concrete Characteristics Using Smart Machine Learning Techniques—A Review

Evaluation of Concrete Characteristics Using Smart Machine L...

引用

Proceedings of the Annual Conference of the Canadian Society of Civil engineering 2022

作者： Kapoor, Chinmay Popli, Navneet Kaur Sharma, Ashutosh Gupta, Rishi Faculty of Engineering and Computer Science University of Victoria VictoriaBC Canada

ISBN: (纸本)9783031340260

Concrete is one of the most commonly used materials for a wide range of construction across the world. The heterogeneity of concrete results in wide variation in its properties. How different ingredients are mixed, determines the performance of concrete, especially its compressive strength. Hence, rigorous testing of concrete in the laboratories before it is finally selected to be used for a specific type of construction is required. This process of testing requires large quantities of material, time and money. The advent of machine learning and artificial intelligence appears to be promising and significant work has been done in this field for the development of high-performance concrete. Traditional curve fitting models provide the ability to interpolate data, however, this paper evaluates the efficacy of machine learning models and different types of neural networks that have been specifically utilized to predict in terms of various factors, the compressive strength of concrete. Various algorithms like group method of data handling (GMDH) type neural networks, adaptive neuro-fuzzy inference system (ANFIS), hybrid modified firefly algorithm with artificial neural networks (MFA-ANN) and other hybrid ANN algorithms have been used to perform a comparatively analyzed review. © Canadian Society for Civil engineering 2024.

关键词： High performance concrete

来源：评论

学校读者我要写书评

暂无评论

Deployment of a security solution for cloud 15

Deployment of a security solution for cloud

引用

15th International Conference on Communications, COMM 2024

作者： Chis, Alexandru Balan, Titus-Constantin Cotfas, Petru-Adrian Cotfas, Daniel-Tudor Transylvania University Faculty Electrical Engineering and Computer Science Braov Romania

ISBN: (纸本)9798350355956

Cloud computing offers benefits in the digital world, such as scalability and agility, but securing these environments requires a high level of knowledge and have the potential for misconfiguration. While cloud platforms offer user-friendly interfaces, ensuring robust cloud security requires a balance between user experience and technical expertise to avoid security vulnerabilities that arise from misconfiguration. This paper proposes a fundamental framework for improving the security posture while using the cloud. The framework uses a configurable building block approach to simplify migration and development efforts for cloud-based solutions. The framework focuses on Amazon Web Services (AWS) and automates deployment with infrastructure-as-code (IaC) principles, minimizing the need for deep infrastructure knowledge. This allows users to develop and deploy secure cloud solutions with built-in security tools and monitoring, minimizing the need for extensive infrastructure knowledge on the user's part. This framework aims to provide a hardened environment suited for cloud appropriation. The framework is leveraging security best practices and monitoring tools, harnessing a more secure approach to the use of public cloud environments. © 2024 IEEE.

关键词： Cloud security

来源：评论

学校读者我要写书评

暂无评论

A Deep Learning Approach for Landmines Detection Based on Airborne Magnetometry Imaging and Edge Computing

引用

computer Modeling in engineering & sciences 2024年第5期139卷 2117-2137页

作者： Ahmed Barnawi Krishan Kumar Neeraj Kumar Bander Alzahrani Amal Almansour Faculty of Computing and Information Technology King Abdulaziz UniversityJeddahSaudi Arabia Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyDeemed to be UniversityPatialaIndia

Landmines continue to pose an ongoing threat in various regions around the world,with countless buried landmines affecting numerous human *** detonation of these landmines results in thousands of casualties reported worldwide ***,there is a pressing need to employ diverse landmine detection techniques for their *** effective approach for landmine detection is UAV(Unmanned Aerial Vehicle)based AirborneMagnetometry,which identifies magnetic anomalies in the local terrestrial magnetic *** can generate a contour plot or heat map that visually represents the magnetic field *** the effectiveness of this approach,landmine removal remains a challenging and resource-intensive task,fraughtwith *** computing,on the other hand,can play a crucial role in critical drone monitoring applications like landmine *** processing data locally on a nearby edge server,edge computing can reduce communication latency and bandwidth requirements,allowing real-time analysis of magnetic field *** enables faster decision-making and more efficient landmine detection,potentially saving lives and minimizing the risks involved in the ***,edge computing can provide enhanced security and privacy by keeping sensitive data close to the source,reducing the chances of data exposure during *** paper introduces the MAGnetometry Imaging based Classification System(MAGICS),a fully automated UAV-based system designed for landmine and buried object detection and *** have developed an efficient deep learning-based strategy for automatic image classification using magnetometry dataset *** simulating the proposal in various network scenarios,we have successfully detected landmine signatures present in themagnetometry *** trained models exhibit significant performance improvements,achieving a maximum mean average precision value of 97.8%.

关键词： CNN deep learning landmine detection magnetometer mean average precision UAV

来源：评论

学校读者我要写书评

暂无评论

A Ripple Controller for Single-Inductor Multiple-Output Boost Converters with Non-Cross-Regulation 3

A Ripple Controller for Single-Inductor Multiple-Output Boos...

引用

3rd International Conference on Electronics and Information Technology, EIT 2024

作者： Lei, Jingyu Xia, Yinshui Miao, Xinkai Yan, Deping Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China

ISBN: (纸本)9798350369151

single-inductor multiple-output (SIMO) boost converter faces an issuce of mutual interference and cross-regulation among output voltages. This paper proposes a ripple-based non-cross-regulation controller suitable for SIMO boost converters. The proposed ripple controller effectively resolves the problems of mutual interference and cross-regulation between outputs. © 2024 IEEE.

关键词： Boost converter

来源：评论

学校读者我要写书评

暂无评论

Assessing and prioritizing crucial drivers for CloudIoT-based healthcare adoption: an analytic hierarchy process approach

引用

International Journal of Information Technology (Singapore) 2024年 1-18页

作者： Altawaiha, Iyad Atan, Rodziah Yaakob, Razali Bin Abdullah, Rusli Bin Hj Department of Software Engineering and Information Systems Faculty of Computer Science and Information Technology Universiti Putra Malaysia (UPM) Serdang 43400 Malaysia Department of Computer Science Faculty of Computer Science and Information Technology Universiti Putra Malaysia (UPM) Serdang 43400 Malaysia

The CloudIoT paradigm has profoundly transformed the healthcare industry, providing outstanding innovation and practical applications. However, despite its many advantages, the adoption of this paradigm in healthcare settings remains limited. There is a lack of comprehensive understanding of the factors that ensure successful implementation. To address this issue, we have used the Analytic Hierarchy Process to prioritize 26 factors that could potentially influence the adoption of CloudIoT-based healthcare. These factors were derived from existing literature and categorized into four main groups: personal-specific, technology-specific, environment-specific, and organization-specific factors. Our findings revealed that performance expectancy, trust, facilitating conditions, task complexity, and perceived security are the top five critical factors influencing CloudIoT-based healthcare adoption. Interestingly, our results indicated that environmental factors were less influential than those in the other categories, with personal, technological, and organizational factors dominating the top ten significant factors. The insights from this study can help policymakers, CloudIoT service providers, healthcare providers, designers, and developers better understand the factors contributing to the successful implementation of CloudIoT-based healthcare. This understanding can guide decision-making and inform the development of strategies to promote the broader adoption of this innovative technology. © The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Adoption Analytic hierarchy process CloudIoT Factors Healthcare industry

来源：评论

学校读者我要写书评

暂无评论

Cluster Sampling: A Cluster-Driven Sampling Strategy for Deep Metric Learning 14

Cluster Sampling: A Cluster-Driven Sampling Strategy for Dee...

引用

14th International Conference on computer and Knowledge engineering, ICCKE 2024

作者： Rafiee, Hamideh Abin, Ahmad Ali Majd, Seyed Soroush Faculty of Computer Science and Engineering Shahid Beheshti University Tehran Iran

ISBN: (纸本)9798331511272

Deep metric learning has gained significant attention recently due to its promising performance in image retrieval, face recognition, and clustering tasks. Deep metric learning algorithms map the original data from the initial feature space to a new embedded space by learning a mapping function, where the discriminative power of the samples is increased. Sampling strategies are a critical aspect of deep metric learning algorithms, as they determine the choice of training samples that shape the network’s learning process. This research introduces a novel sampling approach designed to optimize this selection for improved model performance. Given the high dimensionality of embedded spaces, choosing a sampling strategy is critical for enhancing the quality of learned representations and improving model performance. However, existing sampling methods often face significant challenges, such as slow convergence and the tendency to get trapped in suboptimal local minima. To address these challenges, this research proposes a novel sampling approach that leverages the clustering of sample representations within training batches to identify and select the most informative samples for effective training. This approach ensures a more dynamic learning process by clustering data based on shared features and selecting samples both within clusters and between related clusters. The selected samples enable the model to better learn the underlying data structure, thereby enhancing the discriminative power and robustness of the learned metrics. The effectiveness of the proposed approach is validated through empirical evaluations on the cars196 dataset, where it outperforms existing sampling methods. ©2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Efficient Evaluation Methods for Neural Architecture Search: A Survey

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第12期5卷 5990-6011页

作者： Song, Xiaotian Xie, Xiangning Lv, Zeqiong Yen, Gary G. Ding, Weiping Lv, Jiancheng Sun, Yanan Sichuan University College of Computer Science Chengdu610065 China Oklahoma State University School of Electrical and Computer Engineering StillwaterOK74078 United States Nantong University School of Artificial Intelligence and Computer Science Nantong226019 China City University of Macau Faculty of Data Science 999078 China

Neural architecture search (NAS) has received increasing attention because of its exceptional merits in automating the design of deep neural network (DNN) architectures. However, the performance evaluation process, as a key part of NAS, often requires training a large number of DNNs. This inevitably makes NAS computationally expensive. In past years, many efficient evaluation methods (EEMs) have been proposed to address this critical issue. In this article, we comprehensively survey these EEMs published up to date, and provide a detailed analysis to motivate the further development of this research direction. Specifically, we divide the existing EEMs into four categories based on the number of DNNs trained for constructing these EEMs. The categorization can reflect the degree of efficiency in principle, which can in turn help quickly grasp the methodological features. In surveying each category, we further discuss the design principles and analyze the strengths and weaknesses to clarify the landscape of existing EEMs, thus making easily understanding the research trends of EEMs. Furthermore, we also discuss the current challenges and issues to identify future research directions in this emerging topic. In summary, this survey provides a convenient overview of EEM for interested users, and they can easily select the proper EEM method for the tasks at hand. In addition, the researchers in the NAS field could continue exploring the future directions suggested in the article. © 2020 IEEE.

关键词： Network architecture

来源：评论

学校读者我要写书评

暂无评论

A Survey on the Role of Complex Networks in IoT and Brain Communication

引用

computers, Materials & Continua 2023年第9期76卷 2573-2595页

作者： Vijey Thayananthan Aiiad Albeshri Hassan A.Alamri Muhammad Bilal Qureshi Muhammad Shuaib Qureshi Cybersecurity Department Faculty of ComputingEngineering and ScienceUniversity of SouthWalesWalesUK Department of Computer Science Faculty of Computing and Information Technology(FCIT)King Abdulaziz UniversityJeddah21589Saudi Arabia Computer Science Department Umm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Science&IT University of Lakki MarwatLakki Marwat28420KPKPakistan Department of Computer Engineering Chungnam National UniversityDaejeon34134Republic of Korea

Complex networks on the Internet of Things(IoT)and brain communication are the main focus of this *** benefits of complex networks may be applicable in the future research directions of 6G,photonic,IoT,brain,etc.,communication *** data traffic,huge capacity,minimal level of dynamic latency,*** some of the future requirements in 5G+and 6G communication *** emerging communication,technologies such as 5G+/6G-based photonic sensor communication and complex networks play an important role in improving future requirements of IoT and brain *** this paper,the state of the complex system considered as a complex network(the connection between the brain cells,neurons,etc.)needs measurement for analyzing the functions of the neurons during brain ***,we measure the state of the complex system through *** 5G+/6G-based photonic sensor nodes,finding observability influenced by the concept of contraction provides the stability of *** IoT or any sensors fail to measure the state of the connectivity in the 5G+or 6G communication due to external noise and attacks,some information about the sensor nodes during the communication will be ***,neurons considered sing the complex networks concept neuron sensors in the brain lose communication and ***,affected sensor nodes in a contraction are equivalent to compensate for maintaining stability *** this compensation,loss of observability depends on the contraction size which is a key factor for employing a complex *** analyze the observability recovery,we can use a contraction detection algorithm with complex network *** survey paper shows that contraction size will allow us to improve the performance of brain communication,stability of neurons,etc.,through the clustering coefficient considered in the contraction detection *** addition,we discuss the scalability of IoT communication using 5G+/6G

关键词： Complex networks emerging communication IoT based on 6G systems neuroscience photonic technology

来源：评论

学校读者我要写书评

暂无评论

Power Minimization Beamforming Design for Active RIS-Assisted ISAC System 16

Power Minimization Beamforming Design for Active RIS-Assiste...

引用

16th International Conference on Communication Software and Networks, ICCSN 2024

作者： Yin, Lei Jin, Ming Li, Yaming Liu, Yinhong Chen, Chaodi Zhang, Huifang Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China

ISBN: (纸本)9798331506322

This paper investigates the active reconfigurable intelligent surfaces (RIS)-assisted integrated sensing and communication (ISAC) system, in which a dual-functional base station (BS) simultaneously transmits communication information and senses radar targets. Specifically, we consider a challenging practical scenario where the channel state information (CSI) and the radar reflection coefficient are not fully available. Under this limitation, the communication outage probability and target angle estimation failure probability constraints are introduced to describe the robust beamforming design. We aim to minimize the system's total power consumption by jointly optimizing the BS transmit beamformers and the active RIS phase-shifting. To address the non-convex optimization problem, we use the BernsteinType Inequality to safely approximate probability constraints. Then, we use the alternate optimization (AO) algorithm and semidefinite relaxation (SDR) technique to solve subproblems iteratively. Numerical results verify the active RIS-assisted ISAC system can significantly alleviate 'multiplicative fading' and reduce the power consumption compared to benchmark schemes. © 2024 IEEE.

关键词： Convex optimization

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：