检索结果-内蒙古大学图书馆

3rd IEEE International Conference on Technology, engineering, Management for Societal Impact using Marketing, Entrepreneurship and Talent, TEMSMET 2023

作者： Balekundri, Omkar Tigadi, Raghav Jayakkanavar, Abhilasha Jain College of Engineering and Research Computer Science and Engineering Belgaum India

ISBN: (纸本)9798350397819

The Distributed Ledger Technology (DLT) that underpins various crypto currencies may have a profound impact on the global economy. The Supply Chain Management (SCM) is one of the areas where the DLT is currently being used. By using the Distributed Ledger Technology, blockchain has the potential to vastly enhance different supply chains by facilitating faster and more cost-effective delivery of products. The main benefits of using blockchain in SCM is that it provides an enhancement technique for products traceability, improves coordination among the producer, manufacturer, distributor, retailer and consumer. Also, facilities easier access for funding. In the recent years, the Food Supply Chain (FSC) has been using the blockchain to utilize the benefits of SCM and provide better results for the Food Supply Chain. In this paper, a model is proposed, FARMSUPPLY, which uses blockchain in a Food Supply Chain to provide a better view of farmers, products and retailers. In this model, a Ethereum blockchain method and smart contract for the verification and validation of various attributes at each stage of the food supply chain is presented. © 2023 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

Towards a blockchain-SDN-based secure architecture for cloud computing in smart industrial IoT

引用

Digital Communications and Networks 2023年第2期9卷 411-421页

作者： Anichur Rahman Md Jahidul Islam Shahab S.Band Ghulam Muhammad Kamrul Hasan Prayag Tiwari Department of Computer Science and Engineering National Institute of Textile Engineering and Research(NITER)Constituent Institute of the University of DhakaSavarDhaka1350Bangladesh Department of Computer Science and Engineering Green University of BangladeshDhakaBangladesh Future Technology Research Center College of FutureNational Yunlin University of Science and TechnologyDouliouTaiwanChina Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia Department of Information and Communication Engineering Hankuk University of Foreign StudiesSouth Korea Department of Computer Science Aalto UniversityFinland

Some of the significant new technologies researched in recent studies include BlockChain(BC),Software Defined Networking(SDN),and Smart Industrial Internet of Things(IIoT).All three technologies provide data integrity,confidentiality,and integrity in their respective use cases(especially in industrial fields).Additionally,cloud computing has been in use for several years *** information is exchanged with cloud infrastructure to provide clients with access to distant resources,such as computing and storage activities in the *** are also significant security risks,concerns,and difficulties associated with cloud *** address these challenges,we propose merging BC and SDN into a cloud computing platform for the *** paper introduces“DistB-SDCloud”,an architecture for enhanced cloud security for smart IIoT *** proposed architecture uses a distributed BC method to provide security,secrecy,privacy,and integrity while remaining flexible and *** in the industrial sector benefit from the dispersed or decentralized,and efficient environment of ***,we described an SDN method to improve the durability,stability,and load balancing of cloud *** efficacy of our SDN and BC-based implementation was experimentally tested by using various parameters including throughput,packet analysis,response time,bandwidth,and latency analysis,as well as the monitoring of several attacks on the system itself.

关键词： Smart IIoT Blockchain SDN IoT Security Privacy OpenFlow SDN-Controller Data security Cloud computing Cloud management

来源：评论

学校读者我要写书评

暂无评论

CAML: Cryptographic-Based Cloud Security for Healthcare Data with Machine Learning Technique

引用

Recent Patents on engineering 2025年第2期19卷 26-40页

作者： M.H, Chaithra Vagdevi, S. Department of Computer Science and Engineering REVA University & Research Scholar Affiliated to Visvesvaraya Technological University Karnataka Belagavi India Department of AI & ML City Engineering College Karnataka Bangalore India

Background: The Cloud model is one of the most realistic frameworks with a vast range of social networking interactions. In medical data, security is a major constraint as it incorporates information about the patients. The cloud environment subjected to mobility and openness is exposed to security issues and limits authorization levels for data transmission. Objective: This patent paper aims to propose a security model for attack prevention within the healthcare environment. Methods: The proposed Cryptographic Attribute-based Machine Learning (CAML) scheme incorporates three stages. Initially, the homomorphic encryption escrow is performed for secure data transmission in the cloud. Secondly, the information of the users is evaluated based on the consideration of users' authorization. The authorization process for the users is carried out with the attribute-based ECC technique. Finally, the ML model with the classifier is applied for the detection and classification of attacks in the medical network. Results: The detected attack is computed and processed with the CNN model. Simulation analysis is performed for the proposed CAML with conventional ANN, CNN, and RNN models. The simulation analysis of proposed CAML achieves a higher accuracy of 0.96 while conventional SVM, RF, and DT achieve an accuracy of 0.82, 0.89 and 0.93, respectively. Conclusion: With the analysis, it is concluded that the proposed CAML model achieves higher classification accuracy for attack detection and prevention in the cloud computing environment. © 2025 Bentham science Publishers.

关键词： Cloud security

来源：评论

学校读者我要写书评

暂无评论

IOT-Enabled Smart Crop Recommendation System Using Machine Learning 5

IOT-Enabled Smart Crop Recommendation System Using Machine L...

引用

5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Saranya, S.S. Dharani, A.S. Kavitha, M.N. Selya Dharsnee, M. Pragatheeswari, E. Selya Varsnee, M. Psg Institute of Technology and Applied Research Department of Computer Science and Engineering Coimbatore India Kongu Engineering College Department of Computer Technology - Ug Perundurai India Kongu Engineering College Department of Computer Science and Engineering Perundurai India Kongu Engineering College Department of Computer Technology Perundurai India

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379945

Agriculture, a foundation of India's economy, faces challenges in maximizing yield and resource efficiency. This research presents a machine learning-based system to recommend optimal crops and fertilizers based on soil quality and geographic location. By providing data-driven insights, the proposed system aims to enhance crop productivity, promote sustainable farming practices, and empower farmers to make informed decisions. © 2024 IEEE.

关键词： Smart agriculture

来源：评论

学校读者我要写书评

暂无评论

Target Detection-Oriented RGCN Inference Enhancement Method

引用

computers, Materials & Continua 2025年第4期83卷 1219-1237页

作者： Lijuan Zhang Xiaoyu Wang Songtao Zhang Yutong Jiang Dongming Li Weichen Sun School of Internet of Things Engineering Wuxi UniversityWuxi214105China College of Computer Science and Engineering Changchun University of TechnologyChangchun130012China Computer Science and Technology at Guohao Academy Tongji UniversityShanghai200092China China North Vehicle Research Institute Beijing100072China

In this paper,a reasoning enhancement method based on RGCN(Relational Graph Convolutional Network)is proposed to improve the detection capability of UAV(Unmanned Aerial Vehicle)on fast-moving military targets in urban battlefield *** combining military images with the publicly available VisDrone2019 dataset,a new dataset called VisMilitary was built and multiple YOLO(You Only Look Once)models were tested on *** to the low confidence problem caused by fuzzy targets,the performance of traditional YOLO models on real battlefield images decreases ***,we propose an improved RGCN inference model,which improves the performance of the model in complex environments by optimizing the data processing and graph network *** results show that the proposed method achieves an improvement of 0.4%to 1.7%on mAP@0.50,which proves the effectiveness of the model in military target *** research of this paper provides a new technical path for UAV target detection in urban battlefield,and provides important enlightenment for the application of deep learning in military field.

关键词： RGCN target detection urban battlefield YOLO visual reasoning

来源：评论

学校读者我要写书评

暂无评论

A metadata-aware detection model for fake restaurant reviews based on multimodal fusion

引用

Neural Computing and Applications 2025年第1期37卷 475-498页

作者： Jian, Yifei Chen, Xinyu Wang, Xiaoda Liu, Ying Chen, Xingshu Lan, Xiao Wang, Wenxian Wang, Haizhou School of Cyber Science and Engineering Sichuan University Chengdu China College of Computer Science Sichuan University Chengdu China Cyber Science Research Institute Sichuan University Chengdu China

Nowadays, online reviews have a significant impact on customers who purchase products or evaluate services, as well as merchants who do business. Unfortunately, there are a lot of fake reviews included in them, which badly affect consumers’ decision-making. Fake review detection has been a significant focus of many researchers in the last few years. Existing approaches mostly focus on the review text, the behavior of reviewers, and the relationship between review entities, while ignoring the abundant metadata in reviews. In this research, we construct the first publicly available dataset of fake restaurant review detection with rich metadata. Through detailed analysis of our dataset, we extract 30 metadata features and text features to help improve the detection performance of models, including 10 brand-new features as well as 9 redefined features. Moreover, a novel metadata-aware model for fake restaurant review detection is proposed. In this model, review text is fed to a transformer model and a convolutional neural network based on pre-training strategies, and the extracted features are fed to a multi-layer perceptron with an attention mechanism. Such a structure enables an effective combination of text and rich metadata. Experimental results show that our proposed model has good stability and robustness and achieves an accuracy of 93.12%, outperforming the baselines by 1.73% in generalization ability test. The fake review dataset and innovative framework proposed in this study can provide ideas and solutions for future research. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Extracted features Fake review detection Metadata-aware model Rich metadata

来源：评论

学校读者我要写书评

暂无评论

Relevant Musical Schema-based Human Emotion Controller using Deep Learning Techniques 3

Relevant Musical Schema-based Human Emotion Controller using...

引用

3rd IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Nagaraj, P. Sudar, K. Muthamil Krishna, Gollamandala Vamsi Yeswanth, Grandhi Srinivas Charan, Gurrala Sai Charan, Nidiganti Kalasalingam Academy of Research and Education Krishnankoil Department of Computer Science and Engineering Virudhunagar India Mepco Schlenk Engineering College Department of Computer Science and Engineering Virudhnagar India

ISBN: (纸本)9798350361186

Musical Schema negotiation describes how a user's facial expressions may convey their emotional state or mood. You may see these expressions in the live video from the system camera. Many efforts are being made to teach machines to recognize various human emotions or moods in the field of computer vision and machine learning (ML). There are several techniques available in machine learning to identify human emotions. We propose a system that detects mood in real time and generates a mood-based music player that recommends songs depending on the observed mood. This is now a function that comes pre-installed on the traditional music player applications on our phones. One major benefit of mood detection integration is customer satisfaction. Among this system's objectives are to analyze the user's look, forecast their expression, and suggest music based on how they seem. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

A Deep Learning Approach to Improve Pulmonary Cancer Diagnosis Using CNN 3

A Deep Learning Approach to Improve Pulmonary Cancer Diagnos...

引用

3rd IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Sudar, K. Muthamil Nagaraj, P. Raghavendra, V. Jaashvitha, V. Jayasri, Y. Reddy, Yerva Dasaradha Ramanjaneya Mepco Schlenk Engineering College Department of Computer Science and Engineering Virudhnagar India Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Krishnankoil Virudhunagar India

ISBN: (纸本)9798350361186

It has been proposed that physicians use machine learning-based lung cancer prediction algorithms to treat indeterminate pulmonary nodules that are discovered by accident or during screening. These methods might improve decisionmaking, decrease variability in nodule classification, and decrease the proportion of benign nodules that require unnecessary monitoring or investigation. In this work, we summarise the principal lung cancer prediction methods that have been put out so far and discuss some of the advantages and disadvantages of each. We discuss some of the challenges in creating and verifying such methods and outline the path to clinical acceptance. To ensure the best possible quality of input data for the deep learning models, the preprocessing step involves anatomical area segmentation, noise reduction, and image enhancement. The process of feature extraction involves using convolutional neural networks (CNNs) to extract intricate patterns and features from the lung pictures, which are then utilized to diagnose benign and malignant tumors. Typically, a deep neural network or an ensemble of models is used as the classification network to process this information and determine the final diagnosis. A faster and better outcome for patients may result from the recommended pulmonary cancer detection system's ability to assist medical professionals in accurately identifying malignant tumors in lung imaging. Deep learning is projected to be used in lung cancer detection, which will eventually result in earlier and more effective treatment, hence reducing the burden of this fatal condition. © 2024 IEEE.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

An Empirical Analysis and Overview of a Green 6-G Paradigms and its Various Implementation Applications 4

An Empirical Analysis and Overview of a Green 6-G Paradigms ...

引用

4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Rao, D.T.V. Dharmajee Sharma, Kuldeep Joshi, Sanjeev Kumar Rani, T Sudha Alsalami, Zaid Angadi, Sanjeevkumar Cmr Technical Campus Department of Cse Telangana Hyderabad India Chitkara University Centre of Research Impact and Outreach Punjab Rajpura140401 India Uttaranchal Institute of Technology Uttaranchal University Department of Mechanical Engineering Dehradun248007 India Aditya Engineering College Department of Computer Science and Engineering Surampalem India The Islamic University Najaf Iraq Computer Science and Engineering Nutan College of Engineering and Research Pune Maharashtra Talegaon Dabhade India

ISBN: (纸本)9798350360165

The advent of green 6G technologies holds promise for revolutionary improvements across different areas such as data transmission speed, latency, and traffic volume. Incorporating features like sub-terahertz communication and advanced multiple-input multiple-output (MIMO) technologies, Green 6 G networks aim to surpass the data transmission rates of 5 G while slashing latency to a mere fraction. However, this rapid expansion in network data transfer poses notable hurdles concerning data processing systems and energy usage. Despite strides in energy-efficient computing methods such as green cloud and edge computing, unresolved issues persist, including substantial energy consumption during data migration and idle server power usage. To tackle these challenges, this study proposes a novel strategy called 'In-Network Computing' (INC), which relocates processing tasks from hosts to network devices, leveraging idle resources to alleviate data transmission burdens and mitigate pressure on cloud computing resources. In contrast to edge computing, INC exhibits advantages in the 6 G landscape due to the enhanced computing capabilities and application awareness of network devices. The proposed approach prioritizes energy efficiency by minimizing data centre inputs and integrating host and network node computing environments through virtualization and software-based models. The paper introduces innovative implementations by implementing green 6 g paradigms, focusing on task scheduling and the creation of a prototype system utilizing low-power multicore processors. Experimental validation across diverse application scenarios demonstrates substantial reductions in system energy consumption and network traffic. © 2024 IEEE.

关键词： Data transfer

来源：评论

学校读者我要写书评

暂无评论

Blockchain based prophecy of cardiovascular disease using modified XGBoost

Blockchain based prophecy of cardiovascular disease using mo...

引用

International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Srivastava, Vibha Singh, Ashutosh Kumar Dwivedi, Vijay Kumar Department of Computer Science and Engineering United College of Engineering and Research Uttar Pradesh Naini Prayagraj India

ISBN: (纸本)9781032669663

One of the global and complex disease known as Heart Disease (HD) plays a significant mantle in cardiology and healthcare. In recent times, the blockchain technology is widely used in medical sector for storing the medical records. Still there is a need for enhancing security range and the studies have failed to focus on both the security and HD prediction. Therefore, the proposed study introduced a secured Electronic Health Record (EHR) system over the blockchain environment by implementing encryption and decryption process using Advanced Encryption Standard (AES) algorithm and the HD prediction model is implemented with a Modified Empirical Loss (MEL) Function Extreme Gradient Boosting (XGBoost) classifier. The experimental evaluation is done by using Cleveland Dataset. The efficiency of preferred exemplary is determined with regard to performance metrics namely accuracy, encryption time, precision, decryption time, recall, and F1-score. © 2024 The Author(s).

关键词： Cryptography

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：