检索结果-内蒙古大学图书馆

Quantum search algorithm for continuous domains

Science China(Physics,Mechanics & Astronomy) 2025年第6期Mechanics & Astronomy) .卷 215页

作者： Lvzhou Li Institute of Quantum Computing and Software School of Computer Science and Engineering Sun Yat-sen University

The paper “Fixed-point quantum continuous search algorithm with optimal query complexity’’[1] presents another interesting application of quantum search algorithms by addressing one of the long-standing challenges in quantum computing:how to efficiently perform search over continuous domains. While Grover’s algorithm has been a cornerstone in discrete quantum search with its well-known quadratic speedup [2], many real-world problems—ranging from high-dimensional optimization to spectral analysis of infinite dimensional operators—require searching over continuous, uncountably infinite solution spaces.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Detecting Malicious Migration on Edge to Prevent Running Data Leakage 48

Detecting Malicious Migration on Edge to Prevent Running Dat...

引用

48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Wong, Yuchen Shen, Qingni Li, Cong Liu, Cunzhan Ai, Tianxiang Peking University School of Software and Microelectronics National Engineering Research Center for Software Engineering PKU-OCTA Laboratory for Blockchain and Privacy Computing China

ISBN: (纸本)9781728163277

With the popularity of the Internet of Things (IoT) applications, for instance, smart homes and smart medical, edge servers have become increasingly critical infrastructures. Nevertheless, the loose management puts the edge server under the threat of malicious administrators, which causes the leaking risks of the user's data security. We first give a Data Sniffing Attack that malicious administrators can use live migration to complete without being discovered. To resist the attack, the transparency of live migration to users is the most severe difficulty, where there has not been an effective solution yet. In this paper, we propose a live migration detection model to simulate the migration process, namely observing the indicator values that can obtain without high authorities and calculating the possibility of state transition. Then through many migration experiments, we present the immediate indicators represented by the OS interrupts and the persistent indicators represented by the IO speed, and sort these indicator values into datasets. Next, we train ten frequently-used classifiers and show their accuracy. Eventually, we analyze the advantages and disadvantages of different algorithms in predicting migration and provide the weight recommendation if applied in the detection model. © 2023 IEEE.

关键词： data leakage edge computing Internet of Things live migration malicious administrator

来源：评论

学校读者我要写书评

暂无评论

NCL: Textual Backdoor Defense Using Noise-Augmented Contrastive Learning 48

NCL: Textual Backdoor Defense Using Noise-Augmented Contrast...

引用

48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Zhai, Shengfang Shen, Qingni Chen, Xiaoyi Wang, Weilong Li, Cong Fang, Yuejian Wu, Zhonghai Peking University School of Software and Microelectronics National Engineering Research Center for Software Engineering PKU-OCTA Laboratory for Blockchain and Privacy Computing China

ISBN: (纸本)9781728163277

At present, backdoor attacks attract attention as they do great harm to deep learning models. By poisoning the training data, the adversary makes the model trained based on this dataset being injected with a backdoor. In the field of text, however, existing works do not provide sufficient defense against backdoor attacks. In this paper, we propose a Noise-augmented Contrastive Learning (NCL) framework to defend against textual backdoor attacks when training models with untrustworthy data. With the aim of mitigating the mapping between triggers and the target label, we add appropriate noise perturbing possible backdoor triggers, augment the training dataset, and then pull homology samples in the feature space utilizing contrastive learning objective. Experiments demonstrate the effectiveness of our method in defending three types of textual backdoor attacks, outperforming the prior works. © 2023 IEEE.

关键词： Backdoor defense Contrastive learning Data augmentation Label correction NLP models

来源：评论

学校读者我要写书评

暂无评论

A Color Image Encryption Algorithm Based on Complementary Map and Iterative Convolutional Code 24

A Color Image Encryption Algorithm Based on Complementary Ma...

引用

8th International Conference on Machine Learning and Soft computing, ICMLSC 2024

作者： Xie, Yanlu Zhou, Shihua Lv, Hui Wang, Bin Che, Chao Zhang, Qiang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian China

ISBN: (纸本)9798400716546

Encryption is a valid means to safeguard the safety of images, and for color images, encryption should be performed considering the intrinsic correlation between R, G, and B components. In this paper, we propose an image encryption algorithm based on a complementary map and an iterative convolutional code. Firstly, the plain image is input into the convolutional encoders for iteration to generate the correctional secret key. Secondly, we design a new complementary map. From the test data, the new chaotic map has passed the NIST testing, exhibits a good chaotic characteristic, and has a wider range of chaotic parameters. Thirdly, global scrambling is performed on the color image to disrupt the distribution between R, G, and B. Then, a row-layer and a column-layer are randomly selected to form a set of elements to be encrypted. Finally, performing global diffusion on the image further increases the safety of our scheme. Experimental results show that our algorithm has a preferable encryption effect and elevated safety. © 2024 ACM.

关键词： Convolutional codes

来源：评论

学校读者我要写书评

暂无评论

RGCNU: Recurrent Graph Convolutional Network With Uncertainty Estimation for Remaining Useful Life Prediction

引用

IEEE/CAA Journal of Automatica Sinica 2023年第7期10卷 1640-1642页

作者： Qiwu Zhu Qingyu Xiong Zhengyi Yang Yang Yu School of Big Data&Software Engineering Chongqing UniversityChongqing 400044 Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of EducationChongqing 400044China School of Biology and Engineering Guizhou Medical UniversityGuiyang 550025China

Dear Editor,This letter focuses on the problem of remaining useful life(RUL)prediction of equipment. Existing graph neural network(GCN)-based approaches merely provide the point estimation of RUL. However,the estimated RUL often varies widely due to the model parameters and the noise in data. It is important to know the uncertainty in predictions for reliable risk analysis and maintenance decision *** map the relationship between noisy condition monitoring data and RUL with uncertainty.

关键词： letter estimation prediction

来源：评论

学校读者我要写书评

暂无评论

EnhancedNet Deep Learning Model for Plant Disease Classification 1

EnhancedNet Deep Learning Model for Plant Disease Classifica...

引用

1st International Conference on Logistics, ICL 2024

作者： Umer, Muhammad Javed, Ali Dawood, Hussain University of Engineering and Technology Department of Software Engineering Taxila47050 Pakistan School of Computing Skyline University College Sharjah United Arab Emirates

ISBN: (纸本)9798331518844

Agricultural production vitally contribute to country's economic growth and food needs;however, it depends upon the production and quality of crops. Plants are affected easily due to climate changes and low-quality water. Plants health is examined manually by farmers or pathologists;however, it is not viable to examine each plant regularly due to larger areas of field and limited human resource. If the plant disease gets diagnosed at early stage, the precautionary measures can be taken on time and quality can be improved. There are several solutions available based on modern machine learning and deep learning techniques however, precise prediction and classification is challenging due to the limitations of low light or blurry images. We propose a deep learning-based approach which classifies the healthy and diseases plant using blurry images. Our method addresses the problem using improved layers activation, lesser parameters, using radiant pixels and active neurons. We improved the classification of smaller size and blur images by adding the pooling and dropout layers. Our solution addresses the vanishing gradient and high validation loss problems using a smaller number of parameters as compared to other convolutional neural networks. We evaluated the performance of the proposed method on plant village dataset consisting of a diverse collection of 20600 images. We achieved overall 98.3 % accuracy by minimizing the vanishing gradient, high validation loss and overfitting problem. © 2024 IEEE.

关键词： Plant diseases

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Based Computer Vision Bound Fall Detection for Elderly People 21

Deep Learning Based Computer Vision Bound Fall Detection for...

引用

21st IEEE Student Conference on Research and Development, SCOReD 2023

作者： Abdoul-Halim, Mohamed Abdallah Vengusamy, Sivakumar Asia Pacific University of Technology and Innovation Faculty of Computing Engineering and Technology School of Computing Science and Software Kuala Lumpur Malaysia

ISBN: (纸本)9798350318821

Due to the devastating effects, such as increased mortality and morbidity, falls among the elderly are a significant health issue globally. Supporting the elderly in their daily activities is a significant problem for society because they are the age group with the largest rate of population growth. An automated fall detection system has gained popularity in the healthcare sector due to the social and financial benefits it offers. Vision-based fall detection systems have a great promise now that Smart Homes are a growing trend and there are more cameras in our everyday environments. An autonomous real-time fall detection system based on vision is given in this paper. In this research, we suggested a 3D RGB camera-based method for fall detection. Machine learning algorithms, which were trained on characteristics retrieved by a deep learning-based computer vision algorithm, are used to distinguish between occlusion, falling, and routine everyday activities. Deep learning algorithms are used to identify people in videos. Two datasets - one developed locally and the other made public - were used for the experimental validation of the suggested methodology. Several assessment metrics are computed for evaluation. This analysis demonstrated the efficacy of the suggested solution. Temporal characteristics in a video series are captured using motion history images, and spatial features are then effectively retrieved for classification using a depth-wise convolutional neural network. © 2023 IEEE.

关键词： Fall detection

来源：评论

学校读者我要写书评

暂无评论

Multi-user reinforcement learning based task migration in mobile edge computing

引用

Frontiers of Computer Science 2024年第4期18卷 161-173页

作者： Yuya CUI Degan ZHANG Jie ZHANG Ting ZHANG Lixiang CAO Lu CHEN Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of TechnologyTianjin 300384China School of Internet of Things Engineering Jiangsu Vocational College of Information TechnologyWuxi 214153China School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China School of Sports Economics and Management Tianjin University of SportTianjin 301617China

Mobile Edge computing(MEC)is a promising *** service migration is a key technology in *** order to maintain the continuity of services in a dynamic environment,mobile users need to migrate tasks between multiple servers in real *** to the uncertainty of movement,frequent migration will increase delays and costs and non-migration will lead to service ***,it is very challenging to design an optimal migration *** this paper,we investigate the multi-user task migration problem in a dynamic environment and minimizes the average service delay while meeting the migration *** order to optimize the service delay and migration cost,we propose an adaptive weight deep deterministic policy gradient(AWDDPG)*** distributed execution and centralized training are adopted to solve the high-dimensional *** show that the proposed algorithm can greatly reduce the migration cost and service delay compared with the other related algorithms.

关键词： mobile edge computing mobility service migration deep reinforcement learning deep deterministic policy gradient

来源：评论

学校读者我要写书评

暂无评论

Sustainable Development Goal-17 and Nigeria Data Protection Regulation Adoption among Organizations in Nigeria

Sustainable Development Goal-17 and Nigeria Data Protection ...

引用

2024 International Conference on Science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Babangida-Sabo, Sumayya Avemaria Utulu, Samuel C. Ajibesin, Abel American University of Nigeria Department of Informaton Systems School of Informtaon Technology and Computing Yola Nigeria Amerucan University of Nigeria Department of Software Engineering School of Information Technology and Computing Yola Nigeria

ISBN: (纸本)9798350358155

Adoption of computerized systems by organizations in Nigeria poses some data security challenges to citizens and people from other nations. The challenges require organizations to deploy personal data security that are in line with global standards, hence, Nigeria Data Protection Regulation (NDPR) was introduced. NDPR is to promote ethical personal data security and Nigeria's attainment of the sustainable development goal-17. However, only small number of organizations in Nigeria are able to adopt the NDPR because its adoption is complex and necessitate the implementation of organizational change management (OCM) project. Experience shows that OCM projects usually fails because many OCM frameworks used for OCM projects do not align with both scientifically proven ideas and organizational realities. Our study addresses the benefits of collaborative practice research studies to the production of OCM frameworks that incorporates both theoretical ideas and organizational realities. Our study provides viable solutions to the problem of lack of practice oriented OCM frameworks that organizations in Nigeria can use to drive the adoption the NDPR. © 2024 IEEE.

关键词： Sustainable development goals

来源：评论

学校读者我要写书评

暂无评论

Multi-Sensor Fusion for Fall Detection and Early Warning: Overcoming Camera Blind Spots 24

Multi-Sensor Fusion for Fall Detection and Early Warning: Ov...

引用

8th International Conference on Electronic Information Technology and Computer engineering, EITCE 2024

作者： Zhao, Yehong Deng, Junwen Zhang, Mingyue Liu, Huan Liu, Mingtao Li, Jinmei College of Electrical and Information Engineering Hunan Institute of Traffic Engineering Hunan Hengyang China School of Computing / Software University of South China Hunan Hengyang China

ISBN: (纸本)9798400710094

The aging population has led to an increased need for reliable fall detection systems that can provide timely assistance to individuals who have fallen. This paper presents a multi-sensor fusion system designed to detect falls and issue early warnings, overcoming the limitations of camera-based systems, particularly in areas where camera surveillance is not feasible. We utilize a combination of an MPU6050 six-axis pose sensor and a MAX30102 heart rate and blood oxygen sensor to achieve high accuracy in fall detection. The system is designed to differentiate between falling and normal physical activities, reducing false positives. When a fall is detected, the system triggers an alert and sends real-time health data to a TCP server for monitoring on a mobile terminal. Our approach addresses camera blind spots and provides a comprehensive solution for fall detection in non-visual environments. © 2024 Copyright held by the owner/author(s).

关键词： Fall detection

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：