检索结果-内蒙古大学图书馆

18th IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2024

作者： Sharma, Neha Pandey, Prajjwal Aryan Rathore, Prateek Pandey, Om Jee Indian Institute of Technology BHU Department of Electronics Engineering Varanasi India National Institute of Technology Department of Electronics and Communication Engineering Silchar India The LNM Institute of Information Technology Department of Communication and Computer Engineering Jaipur India

ISBN: (纸本)9798350391725

In the context of 6G IoT networks, distributed computing has become a critical enabler for seamless communication across diverse sectors, such as smart manufacturing, intelligent transportation, healthcare, and defense. Many of these applications involve mobile IoT devices (IoDs) that change locations dynamically, requiring robust and efficient multi-hop data transmission frameworks. Selecting the optimal relay node in distributed 6G IoT networks is essential, as it directly impacts energy efficiency, latency, data interference, and throughput. Additionally, ensuring the availability of the relay node's queue is crucial to prevent data loss. To address these challenges, this work introduces a novel distributed computing framework based on the Request-To-Send (RTS) and Clear-To-Send (CTS) protocols, specifically designed for time-varying 6G IoT networks. The framework incorporates an RTS/CTS mechanism to manage distributed data transfer and employs the Optimal Relay IoD Selection with Q-Learning (OptRISQL) algorithm to determine the optimal relay path dynamically. By distributing computation across nodes, the proposed approach enhances network flexibility, reduces queue sizes, and minimizes memory costs, leading to improved overall network efficiency. Simulation results demonstrate that this distributed computing method effectively reduces interference and enhances throughput, outperforming other current state-of-the-art techniques. Index Terms-6G Internet of Things (IoT), Distributed Computing, Request-To-Send (RTS), Clear-To-Send (CTS), Quality-of-Service (QoS). © 2024 IEEE.

关键词： Smart manufacturing

来源：评论

学校读者我要写书评

暂无评论

Enhancing Drug Repositioning Through Collaborative Metric Learning: A Novel Approach 3

Enhancing Drug Repositioning Through Collaborative Metric Le...

引用

3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Gajendran, Sudhakaran Logeswari, G. Balasubramanian, Kaavin Om Kumar, C.U. Thangaramya, K. Vellore Institute of Technology School of Electronics Engineering Chennai Campus India Vellore Institute of Technology School of Computer Science and Engineering Chennai Campus India Vellore Institute of Technology School of Computer Science and Engineering Vellore India

ISBN: (纸本)9798350372120

Inthe era of big data, leveraging computational approaches for drug repurposing emerges as a promising and efficient method to uncover novel applications for existing medications. This methodology bears significant potential for advancing precision medicine. Deviating from traditional drug development methods, drug repositioning emerges as a costeffective and low-risk strategy. Framed as a top-K recommendation task, the drug repositioning challenge involves aligning medications with the most probable diseases using data related to drugs and diseases. In this work, collaborative metric learning is applied to predict the top diseases that can be recommended to drugs. Firstly, pre-processing of the drugdisease association dataset obtained from CTD database is done, in addition to obtaining drug related data from the same. Secondly, sampling of the dataset is done using SMOTE technique to address the imbalance issue caused due to far lesser number of drug-disease pairs with known associations than the pairs with no known associations in the dataset. Finally, using collaborative metric learning in conjunction with the balanced drug and disease related data, novel drug-disease interaction (DDI) associations are predicted. Latent vectors of drugs and diseases are obtained precisely, and the association probability of drug-disease pairs is then determined using them. According to the experimental analysis, the method works better than the most advanced medication repositioning strategies. © 2024 IEEE.

关键词： Drug interactions

来源：评论

学校读者我要写书评

暂无评论

Rotation-Invariant LiDAR-based Localization Method Based on Feature Pyramid and Vector Neural Network 4

Rotation-Invariant LiDAR-based Localization Method Based on ...

引用

4th International Conference on Neural Networks, Information and Communication engineering, NNICE 2024

作者： Tian, Gengxuan Zhao, Junqiao Tongji University School of Electronics and Information Engineering Department of Computer Science and Technology Shanghai China

ISBN: (纸本)9798350394375

LiDAR-based localization for unmanned vehicle has recently become a highly prominent research area. The LiDAR-based localization task typically involves two crucial tasks: place recognition and pose estimation. However, current research often fails to effectively address issues of place recognition retrieval failures caused by rotations. Some existing methods employ a strategy of coupling the pose estimation task with location recognition, but they often separate these two tasks using two distinct sets of networks to achieve robustness against rotations. Unfortunately, such methods frequently exhibit poor generalization. In this paper, we propose an innovative rotation-invariant LiDAR-based localization method based on feature pyramids and vector neural networks. This approach extracts rotation-invariant global features to accomplish the location recognition task and utilizes rotation-invariant local features for matching corresponding points in point clouds. Employing a coarse-to-fine point matching filtering method to eliminate outliers, and ultimately implementing pose estimation through the RANSAC algorithm, we successfully achieve high-precision and rotation-robust LiDAR-based localization. The experiments indicate that on the Oxford dataset, our method consistently achieves a remarkable 94.7% AR@1% regardless of whether the point cloud undergoes rotation, a performance significantly superior to other methods © 2024 IEEE.

关键词： Rotation

来源：评论

学校读者我要写书评

暂无评论

Enhanced perceptual wavelet packet features for spontaneous Kannada sentence recognition under uncontrolled conditions

引用

International Journal of Speech technology 2025年第1期28卷 153-174页

作者： Shanthamallappa, Mahadevaswamy Pradeep Kumar, B.P. Department of Electronics and Communication Engineering Vidyavardhaka College of Engineering Mysuru Visvesvaraya Technological University Karnataka India Department of Computer Science and Design Atria Institute Of Technology Bengaluru Visvesvaraya Technological University Karnataka India

A Robust Automatic Speech Recognition (ASR) system is proposed through a hybrid combination of Perceptual Wavelet Packet features, Deep Neural Network-Hidden Markov Model (DNN-HMM) acoustic models, and n-gram language models for recognizing Spontaneously spoken Kannada sentences. Two Experiments are performed on own Kannada speech corpus and the widely recognized TIMIT corpus. First one is the experiment on the clean speech datasets and the second one is on the speech degraded by noise data chosen from Noise-US dataset. The proposed system performance is evaluated through the metric Word Error Rate (WER). A comparative study on the performance analysis is presented. The results of the experimental investigations achieved an average reduction in Word Error Rate (WER) of 1.8% over Mel Frequency Cepstral Coefficients (MFCCs) and 2.1% over Perceptual Linear Prediction (PLP) features. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Hidden Markov models

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing technology: The Era of AI-Based 3D-Printed Humanoids 1

Revolutionizing Technology: The Era of AI-Based 3D-Printed H...

引用

1st IEEE Karachi Section Humanitarian technology Conference, Khi-HTC 2024

作者： Hamadullah Irfan, Asim Hadi, Abdul Nawaz, Atif IQRA University Electronics Engineering Karachi Pakistan University of Engineering and Technology Computer Systems Engineering Mehran Jamshoro Pakistan IQRA University Computer Science Karachi Pakistan

ISBN: (纸本)9798350373042

The primary objective of this ground-breaking endeavor is to introduce and highlight the transformative potential of humanoid robotic technology, a domain poised to revolutionize various sectors including automation, healthcare, education, and space exploration. Leveraging advanced artificial intelligence, our humanoid robot emulates human-like capabilities such as speech, comprehension, and multifaceted interactions. This pioneering innovation transcends mere mimicry, harnessing data-driven analytics to facilitate informed decision-making and offer insightful recommendations. Notably, as the nation's inaugural humanoid creation, this project stands as a beacon of promise, inspiring further exploration into novel applications of this technology to significantly benefit society at large. © 2024 IEEE.

关键词： Anthropomorphic robots

来源：评论

学校读者我要写书评

暂无评论

Investigation on compressed air energy storage system for efficient utilisation of renewable power sources

引用

International Journal of Power and Energy Conversion 2024年第3期15卷 281-293页

作者： Karthika, J. Annamalai, T. Kumar, P. Veera Sanjeeva Olana, Firew Dereje Rasu, N. Govindha Department of Electrical and Electronics Engineering Sri Krishna College of Engineering and Technology Kuniamuthur Coimbatore641008 India Department of Electrical and Electronics Engineering Sri Venkateswara College of Engineering Tamil Nadu Sriperumbudur602117 India Department of Mechanical Engineering Annamacharya Institute of Technology and Sciences Andhra Pradesh Rajampet516126 India Department of Electrical and Computer Engineering Mattu University Post-318 Mattu Ethiopia School of Mechanical Engineering Vellore Institute of Technology Vellore India

In recent years, emerging nations have shifted their focus to renewable energy sources for electricity production. This shift has happened in both industrialised and underdeveloped countries. The percentage of electricity produced overall in most developed countries that originates from renewable sources of energy is rising significantly. Currently, the grid is going through a number of modifications to improve its intelligence and stability. These adjustments are becoming more pronounced. Although there are many various types of storage systems available, the CAES system is the most appropriate for large-capacity storage that is ideal for grid integration. However, the overall roundtrip efficiency is less than that of a pumped hydro storage system when it comes to large-scale renewable energy storage. © 2024 Inderscience Enterprises Ltd.

关键词： Compressors

来源：评论

学校读者我要写书评

暂无评论

Leakage Localization of Gas Pipelines Based on Modal Acoustic Emission and Cross-Power Spectrum Peak Optimization

引用

IEEE Sensors Journal 2025年第11期25卷 19982-19992页

作者： Zhang, Wenbiao Gong, Kezheng Cui, Xiwang North China Electric Power University School of Control and Computer Engineering Beijing102206 China Beijing Information Science and Technology University School of Instrument Science and Opto-Electronics Engineering Beijing100192 China

Leakage accidents in natural gas pipelines bring huge property losses and pose serious safety risks. Therefore, faster and more accurate leakage localization is of great significance. In this article, a new method based on modal acoustic emission (MAE) and peak optimization of cross-power spectrum is proposed to enhance the performance of leakage localization. When a pipeline leakage occurs, the sensors installed on the pipelines receive acoustic emission (AE) signals, which have various modes. Instead of extracting a single mode through complex algorithms, the proposed method directly extracts the cross-power spectrum of a specified mode by choosing the appropriate window function and window parameters to locate the leakage with velocity information from dispersion curves. Gaussian, Hamming, and Blackman window functions are compared in the extraction of the cross-power spectrum of L(0, 1) mode, among which the Blackman window function is found to be the most effective. The artificial fish swarm algorithm combined with the iteration criterion for peak optimization is used to obtain suitable window parameters. Finally, the localization error of the above method is less than 5.2%. In addition, the performance of the iteration criterion for peak optimization of cross-power spectrum combined with other intelligent swarm algorithms is investigated. The results show that the maximum errors of other intelligent methods are still less than 9%, demonstrating the great compatibility of the proposed method. © 2001-2012 IEEE.

关键词： Acoustic emissions

来源：评论

学校读者我要写书评

暂无评论

Double-branch fusion network with a parallel attention selection mechanism for camouflaged object detection

引用

Science China(Information Sciences) 2023年第6期66卷 258-266页

作者： Junjiang XIANG Qing PAN Zhengrong ZHANG Songnian FU Yuwen QIN Advanced Institute of Photonics Technology School of Information EngineeringGuangdong University of Technology Guangdong Provincial Key Laboratory of Photonics Information Technology Guangdong University of Technology Guangxi Key Laboratory of Multimedia Communications and Network Technology School of Computer Electronics and InformationGuangxi University

To meet the challenge of camouflaged object detection （COD）,which has a high degree of intrinsic similarity between the object and background,this paper proposes a double-branch fusion network（DBFN）with a parallel attention selection mechanism （PASM）.In detail,a schismatic receptive field block（SRF）combined with an attention mechanism for low-level information is performed to learn texture features in one branch,and an integration of the SRF,a hybrid attention mechanism （HAM）,and a depth feature polymerization module （DFPM）is employed for high-level information to extract detection features in the other ***,both texture features and detection features are input into the PASM to acquire selective expression ***,the final result is obtained after further selective matrix optimization with atrous spatial pyramid pooling （ASPP）and a residual channel attention block （RCAB）being applied *** results on three public datasets verify that our method outperforms the state-of-the-art methods in terms of four evaluation metrics,i.e.,mean absolute error （MAE）,weighted F βmeasure （Fβω）,structural measure （Sα）,and E-measure （Eφ）

关键词： camouflaged object detection attention mechanism feature extraction feature aggregation texture information fuzzy boundary

来源：评论

学校读者我要写书评

暂无评论

Automated Resume Parsing and Ranking using Natural Language Processing 3

Automated Resume Parsing and Ranking using Natural Language ...

引用

3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Thangaramya, K. Logeswari, G. Gajendran, Sudhakaran Deepika Roselind, J. Ahirwar, Neha School of Computer Science and Engineering Vellore Institute of Technology Vellore India School of Computer Science and Engineering Vellore Institute of Technology Chennai Campus India School of Electronics Engineering Vellore Institute of Technology Chennai Campus India

ISBN: (纸本)9798350372120

Advancements in networking and communication have revolutionized the recruitment process, leading to the development of modern resume parsing and ranking systems. With the proliferation of internet-based recruiting, numerous resumes are now stored in recruitment systems. However, traditional methods, such as manual processing and the utilization of unique resume templates, have limitations when dealing with unstructured documents like resumes. Resume parsing is a crucial technique that involves extracting essential details pertaining to applicants to be shortlisted for interview. This paper introduces the 'Resume Parser and Ranker,' an application designed to efficiently and automatically rank resumes, saving considerable time and manpower during the recruitment process. The application is powered by Natural Language Processing (NLP) approach, incorporates heuristic calculations to evaluate the final score of each candidate. The system utilizes Deep Learning (DL) for Named Entity Recognition (NER), achieving an impressive 93% accuracy in information extraction. Notably, this accuracy is close to the level achieved by humans, which typically does not exceed 96%. The high accuracy of the resume parser ensures reliable results, enabling companies to identify the most suitable candidates who can be called for further interview rounds. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Face Attribute Convolutional Neural Network System for Data Security with Improved Crypto Biometrics

引用

computer Systems Science & engineering 2023年第6期45卷 2351-2362页

作者： S.Aanjanadevi S.Aanjankumar K.R.Ramela V.Palanisamy Department of Computer Applications Alagappa UniversityKaraikudi630003TamilnaduIndia Department of Computer Science and Engineering Sri Raaja Raajan College of Engineering and TechnologyAmaravathipudur630301TamilnaduIndia Department of Electrical and Electronics Engineering Ultra College of Engineering and TechnologyMadurai625020TamilnaduIndia

Due to the enormous usage of the internet for transmission of data over a network,security and authenticity become major *** challenges encountered in biometric system are the misuse of enrolled biometric templates stored in database *** describe these issues various algorithms are implemented to deliver better protection to biometric traits such as physical(Face,fingerprint,Ear etc.)and behavioural(Gesture,Voice,tying etc.)by means of matching and verification *** this work,biometric security system with fuzzy extractor and convolutional neural networks using face attribute is proposed which provides different choices for supporting cryptographic processes to the confidential *** proposed system not only offers security but also enhances the system execution by discrepancy conservation of binary *** Face Attribute Convolutional Neural Network(FACNN)is used to generate binary codes from nodal points which act as a key to encrypt and decrypt the entire data for further *** Artificial Intelligence(AI)into the proposed system,automatically upgrades and replaces the previously stored biometric template after certain time period to reduce the risk of ageing difference while *** codes generated from face templates are used not only for cryptographic approach is also used for biometric process of enrolment and *** main face data sets are taken into the evaluation to attain system performance by improving the efficiency of matching performance to verify *** system enhances the system performance by 8%matching and verification and minimizes the False Acceptance Rate(FAR),False Rejection Rate(FRR)and Equal Error Rate(EER)by 6 times and increases the data privacy through the biometric cryptosystem by 98.2%while compared to other work.

关键词： FACNN biometric cryptography AI FAR FRR EER

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：