检索结果-内蒙古大学图书馆

Air Pollution Monitoring By Integrating Local and Global Information in Self-Adaptive Multiscale Transform Domain

IEEE Transactions on Multimedia 2025年 27卷 3716-3728页

作者： Gu, Ke Liu, Yuchen Liu, Hongyan Liu, Bo Qiao, Junfei Lin, Weisi Zhang, Wenjun Beijing University of Technology School of Information Science and Technology Engineering Research Center of Intelligent Perception and Autonomous Control of Ministry of Education Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute Beijing100124 China Massey University School of Mathematical and Computational Sciences New Zealand Nanyang Technological University College of Computing and Data Science Singapore Shanghai Jiao Tong University Institute of Image Communication and Information Processing Shanghai China

As the deadliest form of pollution, air pollution had a prolonged severe damage to the human health and life safety of nearly 99% of the world's population. Facing to the problem that billions of tons of pollutants discharged into the air per year by industrial activities, this paper proposed a novel image-based air pollution monitor (IAPM) by incorporating local and global information in the self-adaptive multiscale transform domain, so as to achieve the timely and effective leakage detection of typical air pollutants from a single image. To be specific, this paper first developed a screen-shaped module according to two significant findings in visual neuroscience, which include the high sensitivity of human eyes to horizontal and vertical stimuli and the center-surround inhibition, by designing and fusing the square module, horizontal strip module and vertical strip module parallelly for simulating the behaviour of human eyes to extract local features. Second, the learnable weights and proportional mapping were applied to incorporate the screen-shaped module and lightweight vision transformer as backbone, towards more richly exploiting and fusing local and global information just as the way a brain perceives external stimuli. Third, a new self-adaptive multiscale transform domain method was devised based on two motivations from the visual characteristics of multiscale perception and the brain characteristics of self-adaptive domain transform to modify the backbone by using the operations of pooling and pointwise convolution. Extensive experiments implemented on the datasets of carbon particulate matters and ethylene leakage confirmed the superior monitoring performance of the proposed IAPM model beyond the state-of-the-art (SOTA) peers by an accuracy gain of about 4%. Furthermore, the proposed IAPM model only required 0.089 GFLOPs and 0.15 million model parameters, remarkably outperforming SOTA competitors in computational efficiency and storage resources. © 1999-2

关键词： Information leakage

来源：评论

学校读者我要写书评

暂无评论

M3GNAS: Multi-modal Multi-view Graph Neural Architecture Search for Medical Outcome Predictions

M3GNAS: Multi-modal Multi-view Graph Neural Architecture Sea...

引用

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Al-Sabri, Raeed Gao, Jianliang Chen, Jiamin Oloulade, Babatounde Moctard Wu, Zhenpeng Abdullah, Monir Hu, Xiaohua Central South University School of Computer Science and Engineering Changsha China College of Science and Engineering Hamad Bin Khlifa University Division of Information and Computing Technology Doha Qatar College of Computing and Information Technology University of Bisha Saudi Arabia College of Computing & Informatics Drexel University United States

ISBN: (纸本)9798350386226

Multi-modal multi-view graph learning models have achieved significant success in medical outcome prediction, combining various modalities to enhance the performance of various medical tasks. However, current architectures for multi-modal multi-view graph learning (M3GL) models heavily depend on manual design, demanding significant effort and expert experience. Meanwhile, significant advancements have been achieved in the field of graph neural architecture search (GNAS), contributing to the automated design of learning architectures based on graphs. However, GNAS faces challenges in automating multimodal multi-view graph learning (M3GL) models, as existing frameworks cannot handle M3GL architecture topology, and current search spaces do not consider M3GL models. To address the above challenges, we propose, for the first time, a multi-modal multi-view graph neural architecture search (M3GNAS) framework that automates the construction of the optimal M3GL models, enabling the integration of multi-modal features from different views. We also design an effective multi-modal multi-view learning (M3L) search space to develop inner-view and outer-view graph representation learning in the context of graph learning, obtaining a latent graph representation tailored to the specific requirements of downstream tasks. To examine the effectiveness of M3GNAS, it is evaluated on medical outcome prediction tasks. The experimental findings demonstrate our proposed framework's superior performance compared to state-of-the-art models. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Adversarial Machine Learning for Social Good: Reframing the Adversary as an Ally

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4322-4343页

作者： Al-Maliki, Shawqi Qayyum, Adnan Ali, Hassan Abdallah, Mohamed Qadir, Junaid Hoang, Dinh Thai Niyato, Dusit Al-Fuqaha, Ala Division College of Science and Engineering Doha34110 Qatar Information Technology University Lahore54000 Pakistan University of New South Wales Sydney Sydney2052 Australia Qatar University Department of Computer Science and Engineering College of Engineering Doha34110 Qatar University of Technology Sydney School of Electrical and Data Engineering Sydney2052 Australia Nanyang Technological University College of Computing and Data Science 639798 Singapore

Deep neural networks (DNNs) have been the driving force behind many of the recent advances in machine learning. However, research has shown that DNNs are vulnerable to adversarial examples - input samples that have been perturbed to force DNN-based models to make errors. As a result, adversarial machine learning (AdvML) has gained a lot of attention, and researchers have investigated these vulnerabilities in various settings and modalities. In addition, DNNs have also been found to incorporate embedded bias and often produce unexplainable predictions, which can result in antisocial AI applications. The emergence of new AI technologies that leverage large language models (LLMs), such as ChatGPT and GPT-4, increases the risk of producing antisocial applications at scale. AdvML for social good (AdvML4G) is an emerging field that repurposes the AdvML bug to invent prosocial applications. Regulators, practitioners, and researchers should collaborate to encourage the development of prosocial applications and hinder the development of antisocial ones. In this work, we provide the first comprehensive review of the emerging field of AdvML4G. This paper encompasses a taxonomy that highlights the emergence of AdvML4G, a discussion of the differences and similarities between AdvML4G and AdvML, a taxonomy covering social good-related concepts and aspects, an exploration of the motivations behind the emergence of AdvML4G at the intersection of ML4G and AdvML, and an extensive summary of the works that utilize AdvML4G as an auxiliary tool for innovating prosocial applications. Finally, we elaborate upon various challenges and open research issues that require significant attention from the research community. © 2020 IEEE.

关键词： Taxonomies

来源：评论

学校读者我要写书评

暂无评论

Securing 3D Point and Mesh Fog Data Using Novel Chaotic Cat Map

引用

Computers, Materials & Continua 2023年第3期74卷 6703-6717页

作者： K.Priyadarsini Arun Kumar Sivaraman Abdul Quadir Md Areej Malibari Department of Data Science and Business Systems School of ComputingCollege of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathurChennai603203India School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

With the rapid evolution of Internet technology,fog computing has taken a major role in managing large amounts of *** major concerns in this domain are security and ***,attaining a reliable level of confidentiality in the fog computing environment is a pivotal *** different types of data stored in the fog,the 3D point and mesh fog data are increasingly popular in recent days,due to the growth of 3D modelling and 3D printing ***,in this research,we propose a novel scheme for preserving the privacy of 3D point and mesh fog *** Cat mapbased data encryption is a recently trending research area due to its unique properties like pseudo-randomness,deterministic nature,sensitivity to initial conditions,ergodicity,*** boost encryption efficiency significantly,in this work,we propose a novel Chaotic Cat *** sequence generated by this map is used to transform the coordinates of the fog *** improved range of the proposed map is depicted using bifurcation *** quality of the proposed Chaotic Cat map is also analyzed using metrics like Lyapunov exponent and approximate *** also demonstrate the performance of the proposed encryption framework using attacks like brute-force attack and statistical *** experimental results clearly depict that the proposed framework produces the best results compared to the previous works in the literature.

关键词： Chaotic cat map fog computing encryption 3D point fog 3D mesh

来源：评论

学校读者我要写书评

暂无评论

Ruppert's Delaunay Triangulation Refinement Scheme for Optimal RSUs Placement in Vehicle to Infrastructure Communication Network

引用

China Communications 2023年第7期20卷 303-320页

作者： Selvakumari P Chinnasamy A Sree Rathna Lakshmi NVS Sheela D Department of Computer Science and Engineering Tagore Engineering CollegeChennai 600048India Department of Data Science and Business Systems School of ComputingSRMIST kattankulathur CampusChennai 603203India Department of Electronics and Communication Engineering Department of ECE at Agni College of TechnologyChennai 603103India Department of Electronics and Communication Engineering Saveetha School of Engineering SIMATSChennai 600124India

Road Side Units(RSUs)are the essential component of vehicular communication for the objective of improving safety and mobility in the road *** are generally deployed at the roadside and more specifically at the intersections in order to collect traffic information from the vehicles and disseminate alarms and messages in emergency situations to the neighborhood vehicles cooperating with the ***,the development of a predominant RSUs placement algorithm for ensuring competent communication in VANETs is a challenging issue due to the hindrance of obstacles like water bodies,trees and *** this paper,Ruppert’s Delaunay Triangulation Refinement Scheme(RDTRS)for optimal RSUs placement is proposed for accurately estimating the optimal number of RSUs that has the possibility of enhancing the area of coverage during data *** RDTRS is proposed by considering the maximum number of factors such as global coverage,intersection popularity,vehicle density and obstacles present in the map for optimal RSUs placement,which is considered as the core improvement over the existing RSUs optimal placement *** is contributed for deploying requisite RSUs with essential transmission range for maximal coverage in the convex map such that each position of the map could be effectively covered by at least one RSU in the presence of *** simulation experiments of the proposed RDTRS are conducted with complex road traffic *** results of this proposed RDTRS confirmed its predominance in reducing the end-to-end delay by 21.32%,packet loss by 9.38%with improved packet delivery rate of 10.68%,compared to the benchmarked schemes.

关键词： road side units(RSUs) ruppert’s delau-nay triangulation refinement area of global coverage optimal RSUs placement

来源：评论

学校读者我要写书评

暂无评论

Zero Trust Networks: Evolution and Application from Concept to Practice

引用

Computers, Materials & Continua 2025年第2期82卷 1593-1613页

作者： Yongjun Ren Zhiming Wang Pradip Kumar Sharma Fayez Alqahtani Amr Tolba Jin Wang School of Computer Science School of Cyber Science and EngineeringEngineering Research Center of Digital ForensicsMinistry of EducationNanjing University of Information Science and TechnologyNanjing210044China Department of Computing Science University of AberdeenAberdeenAB243FXUK Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Sanya Institute of Hunan University of Science and Technology Sanya572024China

In the context of an increasingly severe cybersecurity landscape and the growing complexity of offensive and defen-sive techniques,Zero Trust Networks(ZTN)have emerged as a widely recognized *** Trust not only addresses the shortcomings of traditional perimeter security models but also consistently follows the fundamental principle of“never trust,always verify.”Initially proposed by John Cortez in 2010 and subsequently promoted by Google,the Zero Trust model has become a key approach to addressing the ever-growing security threats in complex network *** paper systematically compares the current mainstream cybersecurity models,thoroughly explores the advantages and limitations of the Zero Trust model,and provides an in-depth review of its components and key ***,it analyzes the latest research achievements in the application of Zero Trust technology across various fields,including network security,6G networks,the Internet of Things(IoT),and cloud computing,in the context of specific use *** paper also discusses the innovative contributions of the Zero Trust model in these fields,the challenges it faces,and proposes corresponding solutions and future research directions.

关键词： Zero trust cybersecurity software-defined perimeter micro-segmentation internet of things

来源：评论

学校读者我要写书评

暂无评论

Phylogenetic-Informed Generative Adversarial Network for Predicting Mutations in SARS-CoV-2 2

Phylogenetic-Informed Generative Adversarial Network for Pre...

引用

2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Chandar, Vijay Nair, Vishnu G. Rajeswari, D. SRM Institute of Science and Technology School of Computing College of Engineering and Technology Department of Data Science and Business Systems Chennai603203 India

ISBN: (纸本)9798350365269

In the pursuit of developing more effective vaccines against viruses like SARS-CoV-2, understanding their potential mutations is crucial. In order to generate protein sequences, this study presents a unique framework that synergistically blends phylogenetic data with Generative Adversarial Networks (GANs). The proposed method combines the strengths of two models: TEMPO, a transformer-based model proficient in leveraging phylogenetic data for mutation detection in SARS-CoV-2, and MutaGAN, a GAN-based model adept in generating synthetic protein sequences. The phylogenetic data from TEMPO is used in this novel design as the input for the MutaGAN generator, replacing the conventional random noise input used in GANs. The generator may now create synthetic protein sequences that are impacted by the evolutionary past included in the phylogenetic data resulting in the creation of artificial protein sequences that are more biologically significant and lifelike. The discriminator portion of the model, similar to MutaGAN, is still in charge of determining whether or not the input sequences comprise a valid parent-child pair and uses sequences produced by the first GAN as extra negative cases. This prevented the model from going too far off its planned route. Additional investigation into this fascinating confluence of bioinformatics and AI may be possible as a result of this study's conclusions. This approach has tremendous promise in many applications, such as the production of more powerful vaccinations, protein engineering, medication design, and improving our knowledge of biological systems, by forecasting how SARS-CoV-2 could change. A precision of 0.662 and an accuracy of around 0.671, together with a Matthews Correlation Coefficient (MCC) score of 0.313, show that the framework performs very well. These scores show that the framework performs better than a number of cutting-edge baseline techniques. The synthetic protein sequences generated by the framework not only bea

关键词： Coronavirus

来源：评论

学校读者我要写书评

暂无评论

Multi-Verse Optimization for Node Localization in Wireless Sensor Networks 3

Multi-Verse Optimization for Node Localization in Wireless S...

引用

3rd International Conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2024

作者： Pitchaimanickam, B. Muthuvel, P. Rajasekar, R. Srm Institute of Science and Technology School of Computing Department of Computational Intelligence Tamilnadu Kattankulathur603203 India Saveetha Engineering College Saveetha Nagar Department of Ece Chennai Thandalam602117 India School of Computing Kalasalingam Academy of Research and Education Department of Cse Tamilnadu Krishnankoil India

ISBN: (纸本)9798350369083

Wireless Sensor Networks (WSN) are focused on increasing attention to develop their potential applications in healthcare, agriculture, object tracking, and energy management. Sensor nodes are placed in random locations. The information was gathered from the unknown positions of the sensor nodes, and this information may be useless for the applications. The accurate position of the node is required for more sensitive applications of WSN. This work proposes multi-verse optimization as a method for locating unknown nodes. Particle swarm optimization and firefly algorithms are contrasted with the suggested method. The experimental findings demonstrate that, compared to alternative algorithms, the suggested technique yields superior outcomes. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

Enhanced CNN Model for Lettuce Disease Identification in Indoor Aeroponic Vertical Farming Systems 4

Enhanced CNN Model for Lettuce Disease Identification in Ind...

引用

4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Rajendiran, Gowtham Rethnaraj, Jebakumar Malaisamy, Janani Dept. of Computing Technologies School of Computing College of Engineering & Technology Srm Institute of Science & Technology Kattankulathur Tamil Nadu Chengalpattu603203 India

ISBN: (纸本)9798331540364

India, like many other nations, heavily relies on agricultural exports to fund its national budget. Economic losses may occur when crop and plant diseases reduce production quality and quantity. Hence, it is crucial to detect infections early on in crop farming. Commercial crops grown using aeroponic vertical farming techniques include lettuce in particular. To increase the crop yield, the crop should be free from disease-causing agents like viral, bacterial, or fungal. As a response, scientists have utilized deep learning algorithms for the automatic identification of abnormalities in both indoor and outdoor farming crops by capturing leaf images. In this work, fine-tuned convolutional neural networks (CNN) were utilized to identify diseases in the aeroponic lettuce crops in an effective manner. Further, the Convolutional Neural Networks (CNN) were fine-tuned by training them on lettuce images. While testing, a higher accuracy of 95.6258% was achieved. Hence, this research work signifies that the proposed model would be appropriate for lettuce disease classification in controlled environment agriculture. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Design of Area Effcient Multiplier Using High Speed 15-4 Counter 9

Design of Area Effcient Multiplier Using High Speed 15-4 Cou...

引用

9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Vasan, J.K. Shettygari, Sudeshna Hariprasad, S. Maria Dominic Savio, M. Srm Institute of Science and Technology Department of Electronics and Communication Engineering Kattankulathur Chennai India School of Computing Srm Institute of Science and Technology Department of Computational Intelligence Kattankulathur Chennai India

ISBN: (数字)9798350377972

ISBN: (纸本)9798350377972

The high-speed counters are the building blocks to reduce the partial products, increasing the efficiency and speed of the multiplier. This paper presents an innovative approach to designing a 16 × 16 multiplier using a 15-4 counter that utilizes cross-wired 1ogic(CWL) based 3-2 counter instead of traditional full adders. A 15-4 counter is designed by employing a 5-3 counter and a CWL-based 3-2 counter to reduce circuit complexity. Using multiple 5-3 counters instead of conventional full adders reduces the computational effort, strategically integrating these 15-4 counters within specific multiplier columns, achieving greater area efficiency and speed. This method addresses the high computational demands associated with adders, optimizing both performance and area in high-speed multiplier applications. From the simulation result, it can be inferred that the proposed 15-4 counter and cross-wired logic 3-2 counter has excellent efficiency, and the power and delay product(PDP) has reduced by 3.6 % when compared to the existing 15-counter design and 30.27 % decreased in the 3-2 counter design © 2024 IEEE.

关键词： Logic design

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：