检索结果-内蒙古大学图书馆

Advancement in Electronics & Communication engineering (AECE), International Conference on

作者： Ramiz Salama Chadi Altrjman Fadi Al-Turjman Satya Prakash Yadav Satvik Vats Richa Gupta Department of Computer Engineering AI and Robotics Institute Research Center for AI and IoT. Near East University Nicosia TURKIYE Department of Chemical Engineering Waterloo University ON Canada Artificial Intelligence Engineering Dept AI and Robotics Institute Near East University Nicosia Turkey Department of Computer Science and Engineering G.L. Bajaj Institute of Technology and Management(GLBITM) Greater Noida India Department of Computer Science and Engineering Graphic Era Hill University Dehradun India Department of Electronics & Communication Engineering Raj Kumar Goel Institute of technology

Terahertz (THz) (0.1-10 THz) wireless communication is one of the cornerstones of the next 6G wireless networks. THz frequencies have the ability to dramatically increase wireless capacity performance and enable high-resolution environment sensing if applied properly due to the enormous quantity of accessible bandwidth. However, the usage of wireless devices in high-frequency bands like THz is constrained by a very unpredictable and dynamic channel. The ultimate result is essentially unreliable intermittent connections since these channel constraints have a naturally restricted communication range and a high susceptibility to blocking and chemical absorption. Because of this, the THz band's potential for high-rate communications and high-resolution sensing may be hindered. This study thoroughly examines the steps necessary to build up and operate next-generation THz wireless networks that will work together to deliver a variety of communication and sensing services in this environment. We first lay the groundwork for this by defining the THz frequency range's fundamentals. Using these fundamentals as a foundation, we outline and carefully investigate seven specific qualities that characterize THz wireless systems: Some of the subjects discussed include the quasi-opticality of the band, wireless architectures suited for THz, synergy with lower frequency bands, cooperative sensing and communication systems, PHY-layer protocols, spectrum access techniques, and real-time network optimization. These seven distinctive features enable our understanding of how to re-engineer wireless systems as we know them today to fit THz bands and their specific settings. On the one hand, THz systems make use of its quasi-optimality and may turn any sensing opportunity into a communication problem, aiding in the development of a new breed of flexible wireless systems that can do many jobs beyond straightforward communications. THz systems can alternatively use intelligent surfaces, lower

关键词：

来源：评论

学校读者我要写书评

暂无评论

Live Demo: E2P-Events to Polarization Reconstruction from PDAVIS Events

Live Demo: E2P-Events to Polarization Reconstruction from PD...

引用

2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Delbruck, Tobi Wang, Zuowen Mei, Haiyang Haessig, Germain Joubert, Damien Haque, Justin Chen, Yingkai Milde, Moritz B. Gruev, Viktor Univ. of Zurich and ETH Zurich Sensors Group Institute of Neuroinformatics Switzerland Center for Vision Automation & Control High-Performance Vision Systems AIT Austrian Institute of Technology Vienna Austria Western Sydney University Intl. Centre for Neuromorphic Systems The MARCS Institute Sydney Australia University of Illinois at Urbana-Champaign Dept. of Electrical and Computer Engineering UrbanaIL United States

This demonstration shows live operation of of PDAVIS polarization event camera reconstruction by the E2P DNN reported in the main CVPR conference paper Deep Polarization Reconstruction with PDAVIS Events (paper 9149 [... 详细信息

ISBN: (纸本)9798350302493

关键词： Polarization

来源：评论

学校读者我要写书评

暂无评论

Pelican optimized extreme learning machine based prognosis of heart failure using textural patterns in CMR images

Pelican optimized extreme learning machine based prognosis o...

引用

technology & engineering Management Conference - Asia Pacific (TEMSCON-ASPAC), IEEE

作者： M Muthulakshmi K Ashwini R Jansi Batchu Bhanu Sai Mani Kiran Nimmagadda Greeshma Pulimi Keerthi Dept. of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Chennai India Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India Dept. of Electronics And Communication Engineering Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai India Dept. of Computer and Communication Engineering Amrita School Of Engineering Amrita Vishwa Vidyapeetham Chennai India

ISBN: (数字)9798350384659

ISBN: (纸本)9798350384666

One of the abnormal cardiovascular conditions with the greatest rate of increase is heart failure (HF). There is a lot of correlation in the exterior symptoms observed that are typically ignored, particularly when there is progression from one stage to another. Planning an efficient treatment requires grouping patients into different phenotypic categories. In CMR imaging, these conditions show damaged heart muscles. Understanding the classification performance of ELM aided by optimal texture features is the main aim of the proposed work. In this study, Krawtchouk moment and the co-occurrence of neighboring sparse local ternary pattern descriptors are used to extract texture and anatomical information of LV. However, an effective feature selection strategy is required to handle the high dimensionality of the feature vector. The primary benefit of the Pelican optimization algorithm (POA), which takes inspiration from nature, is its capacity to carry out both global and local searches effectively. This paper suggests usage of multi-objective POA to optimize the proportion of extracted features and improve the performance of the ELM classifier. The people with various HF stages have been diagnosed with the maximum accuracy of 95.7 % as a result of this inclusion. The enhanced traits have distinguished moderate and severe HF patients from control participants with significant performance. The proposed work further shows the impact of tissue characterization from CMR image and optimized features-based classification on the HF stage detection.

关键词： Heart Magnetic resonance imaging Myocardium Feature extraction Prediction algorithms Vectors Planning

来源：评论

学校读者我要写书评

暂无评论

Influence of negative Poisson’s ratio on fracture morphologies in CFRP laminates 36

Influence of negative Poisson’s ratio on fracture morpholog...

引用

36th Technical Conference of the American Society for Composites 2021: Composites Ingenuity Taking on Challenges in Environment-Energy-Economy, ASC 2021

作者： Iwasaki, Daiki Nishio, Shuichiro Saito, Hiroshi Manato-Kanesaki Kimpara, Isao Kanazawa Institute of Technology Ishikawa924-0838 Japan Dept. of Computer Science and Systems Engineering Okayama Prefectural University Okayama Japan

ISBN: (纸本)9781713837596

The Poisson's ratio and Young's modulus of CFRP laminates can be varied by changing their stacking sequences. CFRP with the specific stacking sequence can theoretically perform the "negative" Poisson’s ratio, which causes extension in the direction perpendicular to the loading direction, for example. However, the relationship between Poisson's ratio and fracture morphology has not yet been elucidated. In this study, tensile tests were performed for CFRP laminates with negative, zero and positive Poisson’s ratios, and failure morphologies were experimentally investigated. © 2021 36th Technical Conference of the American Society for Composites 2021: Composites Ingenuity Taking on Challenges in Environment-Energy-Economy, ASC 2021. All rights reserved.

关键词： Elastic moduli

来源：评论

学校读者我要写书评

暂无评论

Framework for MR-iFLY Autonomous UAS Navigation and Collision Avoidance

Framework for MR-iFLY Autonomous UAS Navigation and Collisio...

引用

Next Generation Communication & Information Processing (INCIP), International Conference on

作者： B. Santosh Kumar Yagateela Pandu Rangaiah Navdeep Singh Dinesh Kumar Yadav Taqi Mohammed Khattab Al-Rubaye Madhu Palati Department of Computer Science Engineering New Horizon College of Engineering Bangalore India Department of Electronics and Communication Enfineering Institute of Aeronautical Engineering Dundigal Hyderabad India Lovely Professional University Phagwara India Lloyd Institute of Engineering & Technology Greater Noida Uttar Pradesh Department of Medical Laboratory Technology College of Medical Technologies The Islamic University Najaf Iraq Dept. of EEE BMS Institute of Technology and Management Bangalore

ISBN: (数字)9798331528140

ISBN: (纸本)9798331528157

Growing interest in unmanned aerial system (UAS) solutions for 6G communication networks stems from recent advancements in autonomous modules with machine learning computation and embedded graphical processing units GPUs. These technologies significantly improved UAS capabilities, however, providing a robust and operable autonomy module remains a significant challenge. The paper presents and evaluates a novel modular framework for UAS autonomy: MR-iFLY and discusses directions for its extension to enable 6G swarm solutions. We start by presenting the machine learning problem in implementing UAS autonomy on resource-limited devices and provide an in-depth overview of MR-iFLY's new depth estimation and collision avoidance technology. A comprehensive analysis and evaluation of MR-iFL Y's open-source modular framework including several performance indices are also presented. The results show that combining state-of-the-art machine vision components and GPU acceleration leads to a speedup of 15X over baseline models. We provide visualization of the MR-iFLY flight demonstration video obtaining vision-based collision avoidance. The obtained empirical results coupled with the current state of the industry suggest that MR-iFLY is a strong candidate to enable 6G communication swarms by providing autonomous collision avoidance and navigation capabilities while reducing the significant communication overhead.

关键词： 6G mobile communication Visualization Navigation Machine vision depth measurement Graphics processing units Machine learning Real-time systems Communication networks Collision avoidance

来源：评论

学校读者我要写书评

暂无评论

Advancements in Early Detection of Cervical Cancer using Machine Learning and Deep Learning Models for Cervicography Analysis

Advancements in Early Detection of Cervical Cancer using Mac...

引用

Emerging Innovations and Advanced Computing (INNOCOMP), International Conference on

作者： Jagendra Singh Rohit Kumar Kaliyar Roshan Kumari Namita Sharma Manjunath S P. Dharani Prasad School of Computer Science Engineering and Technology Bennett University Greater Noida India Noida Institute of Engineering & Technology Greater Noida India Department of Computer Science Smt. & Sri Y.E.R Government First Grade College Pavagada India Dept. of Pharmacology MB School of Pharmaceutical sciences Mohan Babu University Tirupati India

ISBN: (数字)9798350376470

ISBN: (纸本)9798350376487

This study looks into the efficacy of machine learning (ML) models for early diagnosis of cervical cancer utilizing cervical imaging. They were meticulously built using a dataset of 2322 photos from hospitals and online archives. Following preprocessing and grayscale modification to separate cancer areas, features such as intensity, entropy, cluster shadow, grayscale variance, size, shape, and intensity were retrieved. Three machine learning models (ML) were trained on the retrieved features: Convolutional neural networks (CNN), VGG 16, and Recurrent neural network (RNN). The dataset was separated into 70% testing and 30% training, which produced reliable findings. The CNN model performed the best, with an accuracy of 98.77%, followed by VGG 16 (94.65%) and RNN (87.65%). These models also displayed great sensitivity and specificity, validating their ability to effectively identify malignant and nonmalignant cervical lesions. When trials are compared to existing studies, significant improvements are regularly observed, highlighting the potential of machine learning to revolutionize cervical cancer research beyond what has previously been developed. This work represents a big step forward in the use of computer intelligence for early identification, enabling prompt therapies, and improving outcomes in cervical cancer patients. The findings highlight the impact of ML techniques in increasing changes in diagnostic accuracy and accessibility, and present interesting possibilities for further research and practical application.

关键词： Training Technological innovation Accuracy Recurrent neural networks Shape Sensitivity and specificity Gray-scale

来源：评论

学校读者我要写书评

暂无评论

DynamicVisionCore: A Predictive Object Tracking Framework for Real-Time Robotics Applications 8

DynamicVisionCore: A Predictive Object Tracking Framework fo...

引用

8th International Conference on Trends in Electronics and informatics, ICOEI 2025

作者： Suneel, Sajja Rallan, Reema Jayakarthik, R. Naveenkumar, R. Dubey, Alok Shivaputra Telangana Hyderabad500043 India Lovely Professional University Department of Computer Application Punjab Phagwara India Saveetha College of Liberal Arts and Sciences SIMATS Dept of Computer science India Chandigarh Colleges of Engineering Chandigarh Group of Colleges Department of Computer Science and Engineering Punjab Mohali140307 India College of Dentistry Jazan University Department of Preventive Dental Sciences Jazan Saudi Arabia Dr. Ambedkar Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798331544607

DynamicVisionCore is a novel predictive object tracking framework designed for real-time robotics applications. The system integrates YOLOv8 for object detection and DeepSORT for multi-object tracking, ensuring high accuracy and low latency. The framework achieves an impressive MOTA of 72.5% and MOTP of 80.1% on the MOT17 dataset, outperforming traditional methods such as SORT and ByteTrack. Motion prediction is enhanced using a hybrid Kalman Filter and LSTM-based model, reducing RMSE from 9.7 to 6.3 in occlusion scenarios. Additionally, the system ensures robust performance under challenging conditions, achieving 91.3% accuracy in normal lighting and 85.6% in low-light environments. The implementation is optimized for edge computing platforms like Jetson Xavier, where it achieves real-time processing at 9.7ms per frame. The system's robustness is further validated against varying lighting conditions, occlusions, motion blur, and extreme environments. This research demonstrates the efficacy of DynamicVisionCore in real-time robotic vision applications, ensuring reliable object tracking for autonomous systems. Future work will explore adaptive reinforcement learning strategies and improved sensor fusion techniques to further enhance tracking robustness. © 2025 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Unlocking transcranial FUS-EEG feature fusion for non-invasive sleep staging in next-gen clinical applications

Neuroscience Informatics

引用

Neuroscience informatics 2025年第2期5卷 100209-100209页

作者： Gupta, Suneet Gupta, Praveen Lal, Bechoo Deka, Aniruddha Sarma, Hirakjyoti Gupta, Sheifali School of Computer Science and Engineering Galgotias University Greater Noida India Dept of Computer Science and Engineering KLEF-KL University Vijayawada Campus Andhra Pradesh India Computer Science and Engineering Faculty of Engineering Assam down town University Assam India GUIST Gauhati University Assistant Professor India Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura 140401 India

Accurate and non-invasive sleep staging is essential for evaluating sleep quality and diagnosing neurological and sleep disorders. Addressing the variations in electroencephalogram (EEG) and electrooculogram (EOG) signals across different sleep stages, this study introduces a transcranial focused ultrasound (tFUS) based multimodal feature fusion deep learning model (MFDL) for automated sleep staging. The proposed framework integrates two one-dimensional convolutional neural networks (1D-CNNs) to extract sleep-relevant features from EEG and EOG signals, followed by an adaptive feature fusion module that dynamically assigns weights based on feature significance. By enhancing discriminative features and suppressing irrelevant ones, the model generates a robust multimodal representation of sleep information. Furthermore, a bidirectional long short-term memory (Bi-LSTM) network captures temporal dependencies in sleep stage transitions, improving classification accuracy. The effectiveness of MFDL is validated on the publicly available Sleep-EDF dataset, achieving 94.1% accuracy, 88.2% Kappa coefficient, and 81.9% MF1 score. Notably, the recall rates for the challenging N1 and REM sleep stages are significantly enhanced to 64.6% and 93.5%, respectively. These results highlight the potential of MFDL in enhancing tFUS-based neuromodulation by providing precise, data-driven sleep state monitoring, paving the way for advanced non-invasive brain stimulation technologies in next-gen clinical applications. © 2025 The Authors

关键词： Bi-LSTM Discriminative features EEG Next-gen clinical applications Non-invasive brain signal Sleep staging Transcranial FUS

来源：评论

学校读者我要写书评

暂无评论

Prioritizing TWAS Genetic Biomarkers for Melanoma Metastasis via Gene Expression Profiling*

Prioritizing TWAS Genetic Biomarkers for Melanoma Metastasis...

引用

Data Science and engineering in Healthcare, Medicine and Biology, IEEE EMBS Special Topic Conference on

作者： Mohamed N. Saad Belal Medhat Mohamed Hamed Biomedical Engineering Department Faculty of Engineering Minia University Egypt Institute for Biostatistics and Informatics in Medicine and Ageing Research (IBIMA) Rostock University Medical Center Rostock Germany Computer Science and Engineering Department Faculty of Media Engineering and Technology German University in Cairo Egypt Faculty of Media Engineering and Technology German University in Cairo Egypt

The development of novel therapeutic approaches that target gene alterations in melanoma cells remains an area of active research. This study prioritized ten genes out of 76 genes - associated with melanoma through a transcriptome-wide association study (TWAS). We investigated the potential of the identified ten genes in prognosis of metastasis in melanoma *** Relevance: Our findings have clinical implications for melanoma treatment strategies. Targeted therapies that specifically address the dysregulation of our 10 genes may hold promise in preventing or slowing melanoma metastasis.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Canonical Huffman Coding (CHC) - Discrete Wavelet Transform (DWT) Method for Image Steganography

Canonical Huffman Coding (CHC) - Discrete Wavelet Transform ...

引用

Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： A. Ramesh Babu Ramy Riad Al-Fatlawy K Veeranjaneyulu Divya G Komuravelly Sudheer Kumar Department of Engineering Mathematics Anil Neerukonda Institute of Technology and Sciences Visakhapatnam India The Islamic University Najaf Iraq Dept of IT CVR College of Engineering Telangana India Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengaluru India School of Computer Science and Artificial Intelligence SR University Warangal India

Steganography is a tool that allowed an information to transmit through revealing secret data in enormously growing network. The existing methods has limitations like performance and security problems. In this research, proposed a Canonical Huffman Coding (CHC) - Discrete Wavelet Transform (DWT) for image steganography. The images used in the research are Lena, pepper, barbarra and airplane. The images are pre-processed through image acquisition, filtering and histogram shifting. Then, the images are steganographic by proposed CHC-DWT method. Performance of proposed technique is analysed by performance by Peak Signal-to-Noise Ratio (PSNR), Normalized Coefficient (NC) and Structural Similarity Index Measure (SSIM). Proposed algorithm obtained PSNR 54.09 dB in Lena image, PSNR 53.67 dB in Pepper image, PSNR 54.37 dB in Barbarra image and PSNR 53.72 dB in Airplane image which is effecient than existing algorithms like Quick Response Method (QRM), Ballot Transform (Bat) and hybrid Lempel Ziv Welch (LZW) and Genetic Algorithms (GA)

关键词：

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：