检索结果-内蒙古大学图书馆

A secure double spectrum auction scheme

Digital communications and Networks 2024年第5期10卷 1415-1427页

作者： Jiaqi Wang Ning Lu Ziyang Gong Wenbo Shi Chang Choi School of Computer Science and Engineering Northeastern UniversityShenyang110004China School of Computer Science and Technology Xidian UniversityXi©anChina Dept.of Computer Engineering Gachon University1342Seongnam-daeroSujeong-guSeongnam-si13120G School of Computer and Communication Engineering Northeastern UniversityQinhuangdao066004China

With the arrival of the 5G era,wireless communication technologies and services are rapidly exhausting the limited spectrum *** auctions came into being,which can effectively utilize spectrum *** of the complexity of the electronic spectrum auction network environment,the security of spectrum auction can not be *** scholars focus on researching the security of the single-sided auctions,while ignoring the practical scenario of a secure double spectrum auction where participants are composed of multiple sellers and *** begin to design the secure double spectrum auction mechanisms,in which two semi-honest agents are introduced to finish the spectrum auction *** these two agents may collude with each other or be bribed by buyers and sellers,which may create security risks,therefore,a secure double spectrum auction is proposed in this *** traditional secure double spectrum auctions,the spectrum auction server with Software Guard Extensions(SGX)component is used in this paper,which is an Ethereum blockchain platform that performs spectrum auctions.A secure double spectrum protocol is also designed,using SGX technology and cryptographic tools such as Paillier cryptosystem,stealth address technology and one-time ring signatures to well protect the private information of spectrum *** addition,the smart contracts provided by the Ethereum blockchain platform are executed to assist offline verification,and to verify important spectrum auction information to ensure the fairness and impartiality of spectrum ***,security analysis and performance evaluation of our protocol are discussed.

关键词： Secure double spectrum auction SGX technology Privacy information Ethereum platform Verification

来源：评论

学校读者我要写书评

暂无评论

Information theory based clustering of cellular network usage data for the identification of representative urban areas

引用

Digital communications and Networks 2024年第6期10卷 1677-1685页

作者： Mihaela I.Chidean Luis Ignacio Jiménez Gil Javier Carmona-Murillo David Cortés-Polo Dept.of Signal Theory and Communication Univ.Rey Juan CarlosFuenlabrada 28942Spain Computer Science University of ValladolidP.de Belén15Valladolid47011Spain Dept.of Computing and Telematics Engineering Univ.de ExtremaduraMérida06800Spain Dept.of Computing and Telematics Engineering Univ.de ExtremaduraCÃceres 10003Spain

The exponential growth of the number of network devices in recent years not only entails the need for automation of management tasks,but also leads to the increase of available network data and metadata.5G and beyond standards already cover those requirements and also include the need to define and use machine learning techniques to take advantage of the data acquired,especially using geolocated Call Detail Record(CDR)data ***,this scenario requires novel cellular network analysis methodologies to exploit all these available data,especially for the network usage pattern in order to ease the management *** this work,a novel method based on information theory metrics like the Kullback-Leibler divergence and data classification algorithms is proposed to identify representative urban areas in terms of the network usage *** validation is performed via computer analysis using the Open Big Data CDR data set in the Milan area for different *** results validate the proposed methodology and also reveal its adaptability in terms of specific scenario *** usage patterns are calculated for each representative area,paving the path to several future research lines in network management,such as network usage prediction based on this methodology and using the comportment time series.

关键词： Clustering 5G Network analysis Multi-feature analysis Kullback-Leibler divergence Cellular networks

来源：评论

学校读者我要写书评

暂无评论

Advancements in Flood Mapping Methodologies: A Comprehensive Review 6

Advancements in Flood Mapping Methodologies: A Comprehensive...

引用

6th IEEE International Conference on Recent Advances in Intelligent Computational Systems, RAICS 2024

作者： Chandran, Divya V Anitha, J. Chandran, Divya V Vijayakumar, Amrutha Raveendran, Anjana Karunya Institute of Technology and Sciences Dept.of Computer Science Engineering Coimbatore India Adi Shankara Institute of Engineering and Technology Dept. of Electronics and Communication Engineering Kalady India

ISBN: (纸本)9798350381689

This review aims to comprehensively assess the recent advancements in flood mapping methodologies and technologies. By analyzing diverse techniques and approaches employed in flood mapping, this review seeks to present an in-depth overview of the current landscape of this field. The primary focus is on evaluating the strengths and limitations inherent in various flood mapping methods. Special attention will be given to exploring the integration of remote sensing technologies and geographic information systems (GIS) in flood mapping. Additionally, the review will delve into the transformative impact of machine learning and artificial intelligence on enhancing the precision and efficiency of flood mapping processes. Recent developments in flood mapping have significantly elevated the accuracy and reliability of the techniques employed. The integration of AI technologies with remote sensing methods has notably contributed to this advancement. Conventional approaches to flood mapping have traditionally relied on multiple methodologies to comprehend potential flood impacts. However, these methods often prove laborious, resource-intensive, and may lack access to real-time data, posing limitations for precise flood mapping and prediction. These identified limitations underscore the critical need for the development of more robust flood mapping techniques. Addressing these challenges is essential for enhancing flood risk assessment, improving management strategies, and ensuring better preparedness for future flood events. © 2024 IEEE.

关键词： Floods

来源：评论

学校读者我要写书评

暂无评论

Non-Invasive Oral Cancer Detection Using Hyperspectral Imaging and Advanced Spectral Unmixing Models

Non-Invasive Oral Cancer Detection Using Hyperspectral Imagi...

引用

2024 IEEE International Conference on Intelligent Computing and Emerging communication Technologies, ICEC 2024

作者： Ayyapa, Valluri Kothamasu, Kesava Sriram Killaru, Priyusha Muddana, Saadhivik Aala, Suresh Gutha, Vamsi Kumar, Mukkara Prasana Chinnadurai, Sunil SRM University Dept.of Electronics and Communication Engineering AP India SRM University Dept. of Computer Science and Engineering AP India SRM University Dept. of Computer Science AP India

ISBN: (纸本)9798331508432

Oral cancer is a significant global health concern, often leading to high mortality rates due to late-stage diagnosis and the lack of effective early detection methods. Despite advances in medical science, the absence of reliable early diagnostic tools remains a critical challenge. Hyperspectral imaging (HSI) has emerged as a powerful noninvasive technology, capturing detailed spectral information across a wide range of wavelengths. This allows for accurate differentiation between cancerous and healthy tissues, improving early detection and enhancing treatment outcomes. In this study, we propose the use of HSI for early oral cancer diagnosis. To address the scarcity of labeled data, we developed a synthetic hyperspectral dataset that includes spectral signatures of both normal and cancerous tissues. The dataset was generated using a bilinear mixing model, with key spectral features extracted through Vertex Component Analysis (VCA) and abundances computed using Non-Negative Least Squares (NNLS). The model's performance was evaluated using Spectral angle distance (SAD) and Root mean square error (RMSE) metrics. Our findings demonstrate that HSI significantly improves the accuracy of early oral cancer detection, outperforming traditional methods. This work highlights the potential of advanced imaging technologies in revolutionizing cancer diagnosis, offering a robust framework for non-invasive detection and showcasing the effectiveness of synthetic datasets in medical imaging research. © 2024 IEEE.

关键词： Deep Learning Hyperspectral Imaging (HSI) Non-Negative Least Squares (NNLS) Oral Cancer Detection Root Mean Square Error (RMSE) Spectral Angle Distance (SAD) Synthetic Dataset Vertex Component Analysis (VCA)

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Flood Detection System Using Semantic Segmentation 7

Deep Learning-Based Flood Detection System Using Semantic Se...

引用

7th International Conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Chandran, Divya V Anitha, J. Anusree, A.R. Nair, Gowri Karunya Institute of Technology and Sciences Dept.of Computer Science Engineering Coimbatore India Adi Shankara Institute of Engineering and Technology Dept. Electronics and Communication Engineering Ernakulam India

ISBN: (纸本)9798350372816

Floods cause immense damage worldwide, resulting in significant financial losses and loss of life. Existing flood detection methods often face limitations, including delays and errors due to manual data interpretation and limited coverage. In this study, we propose a novel flood detection system that leverages deep learning techniques for semantic segmentation. Our system employs a U-Net architecture to analyze aerial and satellite images, identifying flood-affected areas at a pixel level. Trained on a diverse dataset of labeled flood images from various regions, our model is both robust and adaptable. Notably, our system achieves an Intersection over Union (IoU) score of 0.85, surpassing traditional methods in accuracy. This advanced system offers the potential to provide real-time flood information, enhancing disaster response and management. With real-time flood mapping, emergency services can better understand the disaster's scope and plan rescue operations more effectively. Improved emergency response and resource management become possible with timely, precise data on flooded areas, allowing for informed decisions regarding evacuation, relief distribution, and infrastructure maintenance. Future work will focus on integrating additional data sources, such as weather conditions and water flow rates, to further enhance system performance. © 2024 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Privacy-Preserving Deep Learning on Big Data in Cloud

引用

China communications 2023年第11期20卷 176-186页

作者： Yongkai Fan Wanyu Zhang Jianrong Bai Xia Lei Kuanching Li State Key Laboratory of Media Convergence and Communication Communication University of ChinaBeijing 100024China Industrial and Commercial Bank of China Zhuhai Branch Zhuhai 519000China Dept.of Computer Science and Information Engineering Providence UniversityTaichung 43301China

In the analysis of big data,deep learn-ing is a crucial *** data analysis tasks are typically carried out on the cloud since it offers strong computer capabilities and storage ***-ertheless,there is a contradiction between the open nature of the cloud and the demand that data own-ers maintain their *** use cloud resources for privacy-preserving data training,a viable method must be found.A privacy-preserving deep learning model(PPDLM)is suggested in this research to ad-dress this preserving *** preserve data privacy,we first encrypted the data using homomorphic en-cryption(HE)***,the deep learn-ing algorithm’s activation function—the sigmoid func-tion—uses the least-squares method to process non-addition and non-multiplication operations that are not allowed by ***,experimental re-sults show that PPDLM has a significant effect on the protection of data privacy *** with Non-Privacy Preserving Deep Learning Model(NPPDLM),PPDLM has higher computational effi-ciency.

关键词： big data cloud computing deep learning homomorphic encryption privacy-preserving

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Techniques for Speech Emotion Recognition 1

Deep Learning Techniques for Speech Emotion Recognition

引用

1st International Conference on Futuristic Technologies, INCOFT 2022

作者： Bhavani, R. Muni, T Vijay Tata, Ravi Kumar Narasimharao, Jonnadula Murali, K. Kaur, Harpreet Kings Engineering College Dept.of Information Technology Chennai India Koneru Lakshmaiah Education Foundation Dept.of Electrical and Electronics Engineering Vaddeswaram India Koneru Lakshmaiah Education Foundation Dept.of Computer Science and Engineering Vaddeswaram India CMR Technical Campus Medchal Dept.of Computer Science and Engineering Hyderabad India VijayaInstitute of Technology for Women Dept.of Electronics and Communication Engineering Enikepadu India Lovely Professional University Dept.of Computer Science and Engineering Phagwara India

ISBN: (纸本)9781665450461

The identification of feelings sent via one's voice has evolved from a niche field into an essential part of humancomputer interaction (HCI). These systems seek to facilitate more natural interactions between humans and machines by favouring direct voice interaction over the use of conventional input devices in order to comprehend verbal information and to make it simpler for human listeners to respond. A few examples include the use of emotion patterns derived from speech in medical applications, dialogue systems for spoken languages such as those used in cell phone call centres, onboard driving systems in automobiles, and the usage of such patterns in other contexts. In the research that has been done on speech emotion recognition (SER), a variety of methods, many of which are considered to be industry standards in speech analysis and classification, have been applied to the process of extracting emotions from signals. The most crucial stages of the speech emotion recognition (SER) process are the phases that deal with the extraction of features and the categorization of features. For the purpose of speech processing, researchers have developed a variety of features, including prosodic features, vocal traction features, and other hybrid features. The second step involves the categorization of features through the application of deep learning methods. These methods have just lately been put up as a potential replacement for SER's more conventional methods. © 2022 IEEE.

关键词： Speech processing

来源：评论

学校读者我要写书评

暂无评论

Pharmacy Location and Recommendation Services

Pharmacy Location and Recommendation Services

引用

2023 International Conference on System, Computation, Automation and Networking, ICSCAN 2023

作者： Dhanalakshmi, R. Vijayaraghavan, N. Valli, R. Prathiba, Sahaya Beni School of Computer Science and Engineering Vellore Institute of Technology Centre for Cyber Physical Systems Chennai India Kcg College of Technology Dept.of Mathematics Chennai India Manakula Vinayagar Institute of Technology Dept.of Electronics and Communication Puducherry India

ISBN: (纸本)9798350315127

The medical sector has continually advanced in recent years. The integration of medical services with a centralized system, on the other hand, is effective in enhancing people's lives thanks to the technology that is currently available. This system will help people to make out their medicinal requirements in their nearby location. If the exact medicine is not available alternative medicines are recommended based on user searched medicine combination it is achieved by using the rank-based algorithm to find similar medicine. This approach will computerize all pharmacy records so that customers and pharmacists can access them whenever and wherever they choose. The proposed system is to lay out a plan of action to the consumers plus pharmacist and do the representation of web services between them. This system intensifies the engagement of unorganized pharmacies into the computerized system to lift medical assistance. In such a way, the system will become the forthcoming way of e-medicinal services and advances the approach of medicinal assistance that are given to the patients by hospitals and doctors. It also helps to get drug availability in every locality © 2023 IEEE.

关键词： Medicine

来源：评论

学校读者我要写书评

暂无评论

An Efficient Machine Learning Model for Identification of Seagrasses through Morphometrics 2

An Efficient Machine Learning Model for Identification of Se...

引用

2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Dubey, Ashwani Kumar Thanikkal, Jibi G Dilipan, E. Sharma, Puneet Shukla, Manoj Kumar Amity University Uttar Pradesh Aset Dept.of Electronics and Communication Engineering UP Noida India Amity University Uttar Pradesh Aset Dept.of Computer Science and Engineering UP Noida India Saveetha University Center for Marine Omics Saveetha Institute of Medical and Technical Sciences Tamilnadu Chennai77 India Sr University School of Computer Science & Ai Telangana Warangal India

ISBN: (纸本)9798350360523

Seagrasses are marine flowering plants capable of completing their life cycle underwater. Globally, 72 species of seagrasses have been identified, including 15 species from India. Artificial intelligence/ Machine learning techniques are gaining wide use in many fields, and their applications in marine sciences are still in the initial stage. Considering this, a study is attempted to identify seagrass species through Artificial intelligence/ Machine learning techniques. Since the characteristics of seagrass vary depending on location and other environmental factors, identifying seagrass species is regarded as a difficult task. In the present study, a known seagrass species is taken as a reference and its leaf morphological features are considered for shape description and deep learning-based identification. Leaf morphometrics of seagrass species are drawn to develop the databases. Morphological feature extraction algorithm, descriptor generation algorithm, and deep learning-based identification are applied for species identification. Existing artificial intelligence/ machine learning models use image pixels as input to the deep learning model. However, this is the first attempt to recognize seagrasses through their morphological properties. Here, the leaf shape property is utilized for seagrass identification. The proposed machine learning model received 60% accuracy during testing. Additional investigation was possible with the same algorithm for future seagrass species identification. Utilizing Artificial intelligence/ Machine learning algorithms may lead to identifying new seagrass species. © 2024 IEEE.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

An earlier serial lactate determination analysis of cardiac arrest patients using a medical machine learning model

An earlier serial lactate determination analysis of cardiac ...

引用

2023 International Conference on Intelligent Systems for communication, IoT and Security, ICISCoIS 2023

作者： Mohammed, Mehmood Ali Mohammed, Murtuza Ali Mohammed, Vazeer Ali Logeshwaran, J. Jiwani, Nasmin University of the Cumberlands Dept. of Information Technology WilliamsburgKY United States Lewis University Dept.of Computer Information System IL United States Sri Eshwar College of Engineering Dept. of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798350335835

In general, cardiac arrest results in an inability to pump enough blood for the body's needs. Through this, the organs and tissues get enough oxygen and nutrients for their metabolic needs, and excess fluid accumulates. This further increases the severity of the patient's problems. Cardiac arrest is the leading cause of hospitalization in people over 65 and is therefore considered a significant public health problem. It is a pathology linked to an increase in average life expectancy, and its incidence is increasing every year due to the general ageing of the population. In this paper, an earlier serial lactate determination analysis of cardiac arrest patients using a medical machine learning algorithm. It can occur following an episode of cardiac arrest or inadequate treatment of chronic diseases, including diabetes and hypertension. Adopting lifestyle habits that prevent the onset of these conditions is an essential strategy for preventing heart failure. The proposed approach has achieved 91.58% accuracy, 87.96% precision, 84.62% recall, and 85.23% F1-score results compared to other methods. © 2023 IEEE.

关键词： Tissue

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：