检索结果-内蒙古大学图书馆

42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Zhang, Lei Guo, Haotian Dong, Yanjie Wang, Fangxin Cui, Laizhong Leung, Victor C. M. Shenzhen University College of Computer Science and Software Engineering Shenzhen China The Chinese University of HongKong Sse and FNii Shenzhen China Peng Cheng Laboratory Shenzhen China Shenzhen China The University of British Columbia Department of Electrical and Computer Engineering Vancouver Canada

ISBN: (纸本)9798350334142

Tile-based streaming and super resolution are two representative technologies adopted to improve bandwidth efficiency of immersive video steaming. The former allows selective download of contents in the user viewport by splitting the video into multiple independently decodable tiles. The latter leverages client-side computation to reconstruct the received video into higher quality using advanced neural network models. In this work, we propose CASE, a collaborated adaptive streaming and enhancement framework for mobile immersive videos, which integrates super resolution with tile-based streaming to optimize user experience with dynamic bandwidth and limited computing capability. To coordinate the video transmission and reconstruction in CASE, we identify and address several key design issues including unified video quality assessment, computation complexity model for super resolution, and buffer analysis considering the interplay between transmission and reconstruction. We further formulate the quality-of-experience (QoE) maximization problem for mobile immersive video streaming and propose a rate adaptation algorithm to make the best decisions for download and for reconstruction based on the Lyapunov optimization theory. Extensive evaluation results validate the superiority of our proposed approach, which presents stable performance with considerable QoE improvement, while enabling trade-off between playback smoothness and video quality. © 2023 IEEE.

关键词： Video streaming

来源：评论

学校读者我要写书评

暂无评论

Investigating Principle Component Analysis Impact on the Performance of Machine Learning Classifiers: A Health Informatics Application 25

Investigating Principle Component Analysis Impact on the Per...

引用

25th International Arab Conference on Information Technology, ACIT 2024

作者： Banimustafa, Ahmed Almatarneh, Sattam Bulkrock, Olla Alazaidah, Raed Almahasneh, Hossam Samara, Ghassan Higher Colleges of Technology Computer Information Science Dept. Abu Dhabi United Arab Emirates Zarqa University Data Science & Artificial Intelligence Dept. Zarqa Jordan University of Business and Technology College of Engineering Jeddah Saudi Arabia Princess Sumaya University for Technology Software Engineering Dept. Amman Jordan Zarqa University Computer Science Dept. Zarqa Jordan

ISBN: (纸本)9798331540012

Principal Components Analysis (PCA) is a popular dimensionality reduction and feature selection technique. It works by swiping non-informative features while retaining those that are still potentially useful. However, regardless of its wide applications in statistical analysis, the influence of PCA on the performance of classification algorithms has been rarely studied, particularly in the domain of medical image classification. In this paper, we present a thorough analysis of the influence of applying PCA on the classification of medical images. The dataset used in this study consists of thousands of images that represent four types of blood cells. These images are used to train three machine-learning classifier models after transforming images into numerical vectors using a CNN pre-trained embedding algorithm, where each image is encoded using one thousand numerical vectors. The study involves building three classification models using (1) K-nearest Neighbor (KNN), (2) Logistic Regression (LR), and (3) Random Forests (RF). Each model was built twice, once after the application of PCA to reduce the dimensionality of the embedded features and once with the original embedded features. The performance of each model is evaluated using Classification accuracy, F1, AUC, Recall, precision, and specificity metrics. The recorded performance is then compared to drawing a decisive conclusion. © 2024 IEEE.

关键词： Dimensionality reduction

来源：评论

学校读者我要写书评

暂无评论

Public integrity verification for data sharing in cloud with asynchronous revocation

引用

Digital Communications and Networks 2022年第1期8卷 33-43页

作者： Wei Song Yu Wu Yihui Cui Qilie Liu Yuan Shen Zicheng Qiu Jianjun Yao Zhiyong Peng School of Computer Science Wuhan UniversityWuhan430074China b School of Software Engineering Chongqing University of Posts and TelecommunicationsChongqing400054China School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing400054China College of Information Engineering Tarim UniversityAlar CityXinjiang843300China

Cloud data sharing service,which allows a group of people to access and modify the shared data,is one of the most popular and efficient working styles in ***,there is an uprising trend that enterprises tend to move their IT service from local to cloud to ease the management and reduce the *** the new cloud environment,the cloud users require the data integrity verification to inspect the data service at the cloud *** recent studies have focused on this application *** these studies,each user within a group is required to sign a data block created or modified by *** a user is revoked,all the data previously signed by him should be *** the existing research,the resigning process is dependent on the revoked ***,cloud users are *** may exit the system at any time without notifying the system admin and even are revoked due to *** the developers in the cloud-based software development platform,they are voluntary and not strictly controlled by the *** to this feature,cloud users may not always follow the cloud service *** may not participate in generating the resigning key and may even expose their secret keys after being *** the signature is not resigned in time,the subsequent verification will be *** if the secret key is exposed,the shared data will be maliciously modified by the attacker who grasps the ***,forcing a revoked user to participate in the revocation process will lead to efficiency and security *** a result,designing a practical and efficient integrity verification scheme that supports this scenario is highly *** this paper,we identify this challenging problem as the asynchronous revocation,in which the revocation operations(i.e.,re-signing key generation and resigning process)and the user's revocation are *** the revocation operations must be able to be performed without the participation of the revo

关键词： Cloud storage Integrity verification Asynchronous revocation

来源：评论

学校读者我要写书评

暂无评论

Personalized Alarming System for Asthma Management Based on Lung Functionality: Observational Study

Personalized Alarming System for Asthma Management Based on ...

引用

2023 Advances in science and engineering Technology International Conferences, ASET 2023

作者： Alblooshi, Fatima Albadi, Reem Alblooshi, Khawla Ishimirwe, Emma Uwisoneye, Yvettte Alnajjar, Fady Mehiar, Dua'a College of Information Technology United Arab Emirates Universty Al Ain United Arab Emirates College of It United Arab Emirates Universty Department of Computer Science and Software Engineering Al Ain United Arab Emirates

ISBN: (纸本)9781665454742

Asthma is a chronic respiratory disease that can be challenging to manage. To improve asthma management, we designed a personalized alarm system that utilizes lung function data to monitor and alert individuals to potentially harmful air quality. Our pilot observation included seven individuals who were exposed to two different air-quality environments, and we observed significant variations in their lung function responses. Based on these observations, we developed customized alarm systems for each participant that continuously monitored air quality and provided notifications when it reached levels that could potentially exacerbate their asthma symptoms. This personalized approach has the potential to enable individuals to proactively protect their respiratory health and avoid asthma attacks by taking timely and appropriate action based on their own specific needs. © 2023 IEEE.

关键词： Alarm systems

来源：评论

学校读者我要写书评

暂无评论

Enhancing Healthcare Data Security in Cloud Computing Systems through Advanced Homomorphic Encryption Techniques Integrated with Cuckoo Search Optimization Algorithm

Enhancing Healthcare Data Security in Cloud Computing System...

引用

2024 IEEE International Conference on Recent Advances in science and engineering Technology, ICRASET 2024

作者： Sudha, I. Ramesh, P.S. Ponmalar, A. Jagannathan, J. Pandiarajan, Rajkumar Saveetha Institute of Medical and Technical Sciences Simats University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India R.M.K. Engineering College Tamilnadu Chennai India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Department of Software and Systems Engineering Katpadi Vellore India Kalasalingam Academy of Research and Education School of Computing Department of Information and Technology Krishnankoil Virudhunagar India

ISBN: (纸本)9798350388602

The studies in this research are focused on the mix of homomorphic encryption mechanisms and the Cuckoo Search Optimization Algorithm to promote the security of the healthcare data in the cloud computing system. I have observed that cloud solutions are now at the center of the contemporary health care systems, and security of patient's data remains a top priority. Earlier used encryption techniques, though secure if implemented, have problems in the way that data is to be processed first it has to be decrypted and then made ready for use - it is in this phase that data can be easily hacked into. Homomorphic encryption provides solution to this issue since it enables one to perform computations on encrypted data while maintaining its confidentiality. However, it takes a lot of computation which presents a lot of problems even in terms of simple performance. The Cuckoo Search Algorithm, a new nature-inspired metaheuristic, is incorporated into the encryption process to provide further optimization, whilst preserving the security benefits of the algorithm. The use of the proposed methodology takes place employing Python and its deployment at the cloud platform with elaborated dataset containing anonymized records extracted from electronic health records. The outcome proves that there are great enhancements in encryption and decryption time, computational complexity, and capacity, and thereby making the system appropriate for real-world healthcare solutions. This research offers a strong base for protection of healthcare data in cloud and is useful for the enhancement of adaptive, comprehensive and secure cloud computing systems. © 2024 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Generating Targeted Universal Adversarial Perturbation against Automatic Speech Recognition via Phoneme Tailoring

Generating Targeted Universal Adversarial Perturbation again...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zhang, Yujun Chen, Yanqu Wang, Jiakai Hu, Jin Tao, Renshuai Liu, Xianglong State Key Laboratory of Complex & Critical Software Environment Beihang University China School of Computer Science and Engineering Beihang University China College of Computer Science Beijing University of Technology China Zhongguancun Laboratory China School of Computer and Information Technology Beijing Jiaotong University China Institute of Data Space Hefei Comprehensive National Science Center China

ISBN: (纸本)9798350368741

There is a growing concern about adversarial attacks against automatic speech recognition (ASR) systems. Although research into targeted universal adversarial examples (AEs) has progressed, current methods are constrained by inefficient exploitation of audio features, demonstrating insufficient attack ability and robustness in the physical world. To solve this problem, we propose a phoneme-tailored attack (PTA) to improve the quality of the generated AEs. Specifically, to improve attack ability, we propose a Diverse Audio Composition Enrichment method, which enhances the utilization of audio features through phoneme-level slicing and recombination. To adapt AEs to complex environments, we propose a Natural Noise Pattern Guidance method to align AEs with natural noise patterns to improve their robustness. Experiments show that our method achieves an average accuracy of more than 72.34% and 98% with and without a norm constraint, and also demonstrates excellent performance in terms of generalization across datasets and resilience to MP3 compression. © 2025 IEEE.

关键词： Automatic speech recognition natural noise pattern phoneme-level targeted universal adversarial examples

来源：评论

学校读者我要写书评

暂无评论

Advanced Machine Learning Algorithms for 1Predictive Analytics in Healthcare to Enhance Patient Outcomes with Data-Driven Insights

Advanced Machine Learning Algorithms for 1Predictive Analyti...

引用

2024 IEEE International Conference on Recent Advances in science and engineering Technology, ICRASET 2024

作者： Pandiarajan, Rajkumar Jagannathan, J. Ramesh, P.S. Ponmalar, A. Sudha School of Computing Kalasalingam Academy Of Research and Education Department of Information and Technology Krishnankoil Virudhunagar India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Department of Software and Systems Engineering Katpadi Vellore India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India R.M.K. Engineering College Tamilnadu Chennai India Saveetha Institute of Medical and Technical Sciences Simats University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350388602

This research aims to explore the use of modern complex defensive machine learning algorithms in the provision of predictive analytics for health improvement. Incorporating electronic health records, medical image information, and genomic data the work proposes and assesses multiple machine learning models including deep learning, ensemble learning, and reinforcement learning. The main findings shown very high performance in disease prediction, in chronic illness and in the application of efficiency improvements in hospitals as a whole. Overall, such threats as data quality, data privacy, and model interpretability have been discussed in the research and emphasize the importance of the machine learning approach in healthcare. It is highlighted that further development and integration of the interdisciplinary approaches as well as the use of the transparent and interpretable artificial intelligence and machine learning models can be urgent to increase the acceptance among the healthcare staff. This paper enhances the literature on applying machine learning in healthcare systems adding to the repertoire of knowledge for improved patient care. © 2024 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

MVDC : A Multi-view Dental Completion Model Based on Contrastive Learning

MVDC : A Multi-view Dental Completion Model Based on Contras...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Xunyu Yang Qingxin Deng Minghan Huang Landu Jiang Dian Zhang College of Computer Science and Software Engineering Shenzhen University Guangdong China College of Future Technology HKUST(GZ) Guangdong China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Restoring the patient’s occlusal function of broken teeth is a challenging task since tooth texture is very complex, a slight deviation may affect the patient’s chewing function and temporomandibular joint function. Therefore, how to efficiently repair the complete shape and real surface of the crown is a critical problem. Traditional technologies are hard to restore complete shape of the dental crown or lack inlay surface details, due to dataset limitations and complexity of missing parts. In this paper, we propose a multi-view crown restoration framework MVDC based on contrastive learning. Specifically, MVDC contains: 1) a multi-view generator with a specially designed loss measurement by using contrastive learning; 2) a multi-scale discriminator mechanism able to consider relation and consistency between teeth from different scales; 3) an occlusal groove extraction network to extract the occlusal details. We conducted extensive experiments on existing public datasets. The results showcase the superior performance of MVDC.

关键词： Correlation Shape Teeth Contrastive learning Signal processing Maintenance engineering Loss measurement Dentistry Surface texture Speech processing

来源：评论

学校读者我要写书评

暂无评论

A mesh optimization method using machine learning technique and variational mesh adaptation

引用

Chinese Journal of Aeronautics 2022年第3期35卷 27-41页

作者： Tingfan WU Xuejun LIU Wei AN Zenghui HUANG Hongqiang LYU MIITKey Laboratory of Pattern Analysis and Machine Intelligence College of Computer Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjing 211106China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing 210023China College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China

Computational mesh is an important ingredient that affects the accuracy and efficiency of CFD numerical *** light of the introduced large amount of computational costs for many adaptive mesh methods,moving mesh methods keep the number of nodes and topology of a mesh unchanged and do not increase CFD computational *** the state-of-the-art moving mesh method,the variational mesh adaptation approach has been introduced to CFD ***,quickly estimating the flow field on the updated meshes during the iterative algorithm is challenging.A mesh optimization method,which embeds a machine learning regression model into the variational mesh adaptation,is *** regression model captures the mapping between the initial mesh nodes and the flow field,so that the variational method could move mesh nodes iteratively by solving the mesh functional which is built from the estimated flow field on the updated mesh via the regression *** the optimization,the density of the nodes in the high gradient area increases while the density in the low gradient area *** examples are first used to verify the feasibility and effectiveness of the proposed *** then we use the steady subsonic and transonic flows over cylinder and NACA0012 airfoil on unstructured triangular meshes to test our *** show that the proposed method significantly improves the accuracy of the local flow features on the adaptive *** work indicates that the proposed mesh optimization approach is promising for improving the accuracy and efficiency of CFD computation.

关键词： CFD Flow field Machine learning Moving mesh method Regression models Variational mesh adaptation

来源：评论

学校读者我要写书评

暂无评论

AoI Analysis for Automatic Repeat-Request in Vehicular Cooperative Perception Networks

AoI Analysis for Automatic Repeat-Request in Vehicular Coope...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Qinan Huang Jianhua Zeng Chongtao Guo Jing Liu Haoyuan Pan College of Electronics and Information Engineering Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (数字)9798331517786

ISBN: (纸本)9798331517793

Cooperative perception has been shown an effective approach to address the perception limitation problem faced by the individual perception in the era of autonomous driving. Considering a two-source two-hop cooperative perception vehicular network, we investigate the average age of information (AoI) with different automatic repeat-request (ARQ) strategies in this paper. We formulate the packet transmission process as a Markov chain, which allows us to establish linear equations about the first and second moments of all states’ residual waiting time for the destination to receive a new update packet. Then, we derive the average AoI based on the analytical solution to the equations. Furthermore, the analysis is applied to a special case of the single-source two-hop cooperative perception system. Simulation results show that the optimal strategy is neither non-ARQ nor infinite-ARQ, but truncated ARQ, which means that there exists a finite retransmission limit to minimize the average AoI, implying that better cooperative perception can be achieved by optimizing the retransmission limit, especially in the single-source two-hop situation.

关键词： Vehicular and wireless technologies Simulation Performance gain Information age Mathematical models Autonomous vehicles Signal to noise ratio

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：